Report Disclaimer - CEMAlibrary.cemaonline.ca/ckan/dataset/6bcc559c-d5f6-4774-8126-171d96e... ·...

Suite 214, 9914 Morrison Street Fort McMurray, AB T9H 4A4

(780) 799-3947 (Ph)

(780) 714-3081 (Fax)

CUMULATIVE ENVIRONMENTAL MANAGEMENT ASSOCIATION

Report Disclaimer

This report was commissioned by the Cumulative Environmental Management Association (CEMA). This report has been completed in accordance with the Working Group’s terms of reference. The Working Group has closed this project and considers this report final. The Working Group does not fully endorse all of the contents of this report, nor does the report necessarily represent the views or opinions of CEMA or the CEMA Members. The conclusions and recommendations contained within this report are those of the consultant, and have neither been accepted nor rejected by the Working Group. Until such time as CEMA issues correspondence confirming acceptance, rejection, or non-consensus regarding the conclusions and recommendations contained in this report, they should be regarded as information only. For more information please contact CEMA at 780-799-3947.

COPYRIGHT # 1050814: ***All information contained within this report is owned and copyrighted by the Cumulative Environmental Management Association. As a user, you are granted a limited license to display or print the information provided for personal, non-commercial use only, provided the information is not modified and all copyright and other proprietary notices are retained. None of the information may be otherwise reproduced, republished or re-disseminated in any manner or form without the prior written permission of an authorized representative of the Cumulative Environmental Management Association.***

TECHNICAL REPORT

REACH-SPECIFIC WATER QUALITY OBJECTIVES FOR THE

LOWER ATHABASCA RIVER

Submitted to:

Cumulative Environmental Management Association

May 2007 06-1336-009

Golder Associates Ltd. 1000, 940 6th Avenue S.W. Calgary, Alberta, Canada T2P 3T1 Telephone (403) 299-5600 Fax (403) 299-5606

OFFICES ACROSS NORTH AMERICA, SOUTH AMERICA, EUROPE, ASIA AND AUSTRALIA

CEMA - i - Athabasca River Reach Specific May 2007 Water Quality Objectives

Golder Associates R:\Active\_2006\1336-WQ\06-1336-009 Athabasca Criteria\Reporting\Final\CEMA ARIO Interim Memo May 15 FINAL .doc

TABLE OF CONTENTS

SECTION PAGE

1 INTRODUCTION.......................................................................................................1 1.1 OVERVIEW OF APPROACH ..........................................................................................1 1.2 FINAL TERMS OF REFERENCE/SCOPE OF WORK....................................................5 1.3 TERMS & ACRONYMS...................................................................................................8

2 WATER QUALITY CONSTITUENTS.......................................................................12

3 SCREENING METHODS ........................................................................................15 3.1 INTRODUCTION ...........................................................................................................15 3.2 CRITERIA FOR GUIDELINES AND EFFECTS-BASED THRESHOLDS .....................15 3.3 CRITERIA FOR BACKGROUND-BASED BENCHMARKS AND

INVESTIGATION LEVELS ............................................................................................19

4 DEFINITION OF BACKGROUND CONDITIONS.....................................................20 4.1 INTRODUCTION ...........................................................................................................20 4.2 PROCEDURE................................................................................................................20 4.3 RESULTS ......................................................................................................................21

5 EXISTING WATER QUALITY GUIDELINES ...........................................................24 5.1 INTRODUCTION ...........................................................................................................24 5.2 APPROACH...................................................................................................................24 5.3 SUMMARY SCREENING OF EXISTING GUIDELINES...............................................26

6 EFFECTS-BASED OBJECTIVES............................................................................32 6.1 PROCEDURE................................................................................................................32

6.1.1 Interjurisdictional Guidelines ..........................................................................32 6.1.2 Aquatic Life Effects-based Thresholds ..........................................................33 6.1.3 Health Risk-based Thresholds.......................................................................34

6.2 RESULTS ......................................................................................................................35 6.2.1 Interjurisdictional Guidelines ..........................................................................35 6.2.2 Aquatic Life Effects-based Thresholds ..........................................................36 6.2.3 Health Risk-based Thresholds.......................................................................37

6.3 SUMMARY OF EFFECTS-BASED OBJECTIVES........................................................40

7 BACKGROUND-BASED BENCHMARKS................................................................49 7.1 INTRODUCTION ...........................................................................................................49 7.2 PROCEDURE................................................................................................................49 7.3 RESULTS ......................................................................................................................51

8 INVESTIGATIONS LEVELS ....................................................................................56 8.1 INTRODUCTION ...........................................................................................................56 8.2 INVESTIGATION LEVELS INTERFACE MODEL.........................................................57

8.2.1 Source Load Identification and Constituent Ranking Form ...........................57 8.2.2 Single Constituent Investigation Levels Form................................................60

8.3 RESULTS ......................................................................................................................62

CEMA - ii - Athabasca River Reach Specific May 2007 Water Quality Objectives


9 CONCLUSIONS......................................................................................................70 9.1 SUMMARY OF SCREENING RESULTS ......................................................................70 9.2 FINALIZATION OF RSWQOs .......................................................................................71 9.3 POTENTIAL APPLICATION OF INVESTIGATION LEVELS ........................................79

9.3.1 Assessing Attainment with Investigation Levels ............................................79 9.3.2 Management Framework ...............................................................................80

9.4 APPLICATION OF OBJECTIVES FOR OTHER REGIONAL SURFACE WATERS .......................................................................................................................81

9.5 RECOMMENDED FURTHER DEVELOPMENT OF EFFECTS-BASED OBJECTIVES ................................................................................................................82

9.6 RECOMMENDATIONS FOR UPDATES TO ARM AND THE ILIM ..............................82

10 CLOSURE...............................................................................................................83

11 REFERENCES........................................................................................................84

LIST OF TABLES

Table 2.1 Water Quality Constituents ....................................................................................13 Table 2.2 List of the Individual Polycyclic Aromatic Hydrocarbons That Are Included

in PAH Groups 1 to 9 .............................................................................................14 Table 4.1 Background Constituent Concentrations for Lower Athabasca River ...................21 Table 5.1 Screening of Guidelines Relevant to Long-term Average (Median)

Conditions ..............................................................................................................27 Table 5.2 Screening of Guidelines Relevant to Peak (99.91 Percentile) Conditions ............30 Table 6.1 Selected Interjurisdictional Guidelines...................................................................36 Table 6.2 Aquatic Life Effects-based Thresholds ..................................................................37 Table 6.3 Human Health Risk-based Thresholds..................................................................38 Table 6.4 Wildlife Health Risk-based Thresholds..................................................................39 Table 6.5 Screening of Effects-based Objectives Relevant to the Long Term

Average (Median) ..................................................................................................41 Table 6.6 Screening of Effects-based Objectives Relevant to the Peak

Concentration (99.91 Percentile) ...........................................................................44 Table 7.1 Background-based Benchmarks............................................................................52 Table 8.1 Maximum Investigation Levels...............................................................................64 Table 8.2 Summary of Investigation Levels Exceeding Node-specific Background-

based Benchmarks ................................................................................................66 Table 8.3 Comparison of Selected Investigation Levels (those above the BBB) to

Effects-based Objectives .......................................................................................69 Table 9.1 Summary of Final RSWQOs Applicable to Long-term Average Conditions ..........72 Table 9.2 Summary of Final RSWQOs Applicable to Peak Conditions.................................75

CEMA - iii - Athabasca River Reach Specific May 2007 Water Quality Objectives


LIST OF FIGURES

Figure 1.1 Schematic of Steps Used in the Study ....................................................................5 Figure 1.2 Hierarchy of Candidate RSWQOs Considered........................................................8 Figure 3.1 Schematic of the Criteria Used for Screening Existing Guidelines and

Effects-based Thresholds ......................................................................................19 Figure 6.1 Approach for the Development of Effects-based Objectives.................................33 Figure 7.1 Schematic for Screening Background-based Benchmarks ...................................51 Figure 8.1 Source Load Identification Form............................................................................58 Figure 8.2 Constituent Ranking Schematic.............................................................................60 Figure 8.3 Single Constituent Investigation Levels Form .......................................................61 Figure 8.4 Screening Approach for Use of Investigation Levels for Use as

Management-based Objectives .............................................................................63 Figure 9.1 Management Framework for Relating Monitoring and Investigation Levels..........80

LIST OF APPENDICES

Appendix I Scope of Work Appendix II Literature Review Appendix III Development of Chronic Effects Benchmarks Appendix IV Development of Human and Wildlife Health Risk-Based Thresholds Appendix V Athabasca River Model Assumptions and Inputs Appendix VI Water Quality Profile Information Appendix VII Athabasca River Model Results Appendix VIII Constituent Ranking Appendix IX Review of Selected Constituents

CEMA - 1 - Athabasca River Reach Specific May 2007 Water Quality Objectives

Golder Associates

1 INTRODUCTION

Development in the lower Athabasca River (LAR) Watershed includes surface and in-situ oil sands projects, as well as accompanying urban infrastructure. Many of these developments will influence the LAR and its tributaries. Consequently, the Cumulative Environmental Management Association (CEMA) has requested the formulation of reach-specific water quality objectives (RSWQO) that reflect protection of designated water uses. Designated water uses for the LAR, as defined in the request for proposal for the study, are as follows:

• fish and fish habitat;

• suitability of fish for consumption;

• municipal, local domestic and industrial water supply;

• wildlife usage;

• transboundary obligations; and

• Wood Buffalo National Park needs.

1.1 OVERVIEW OF APPROACH

The approach used in this study is based on methods outlined by the Canadian Council of Ministers of the Environment (CCME 2003). These methods fall under two distinct strategies that are commonly used to establish water quality objectives in Canada: an anti-degradation strategy and a use protection strategy. Several of these same methods were selected to develop candidate objectives as follows:

• adoption of generic guidelines (including existing guidelines and interjurisdictional guidelines);

• use of recalculation procedures (to develop effects-based thresholds for aquatic life, human health and wildlife health); and

• use of a background concentrations procedure (to develop background-based benchmarks).

The Athabasca River Model (ARM) was used to define background concentrations and to predict water quality constituent concentrations based on spatial and temporal loadings from existing, approved and planned developments. This component of the work builds on a previous modelling conducted to assist in the development of instream flow needs (IFN) for the LAR (Golder 2006a).


Golder Associates

An investigation levels watershed management method was also used for this study.

Objectives developed using each of these methods were screened for applicability to the LAR. A final selection process was developed based on the results of the screening. Because investigation levels and background based-benchmarks represent non-effects-based management objectives, they have been categorized separately.

The steps taken in implementing this approach are shown in Figure 1.1. A brief description of each of the steps is as follows:

1. Identified water quality constituents

Water quality constituents identified for development of RSWQOs included those examined in recent EIAs as well as those with elevated concentrations in one or more mine waters according to CEMA (2003). The constituents are described in Section 2.

2. Defined method for screening of effects-based objectives, background-based benchmarks and investigation levels

A review of the methods for screening the adequacy of existing guidelines, as proposed by CEMA (2003), is provided in Section 3.2 along with modifications to those methods for screening effects-based objectives for use in this study. The screening method considers the presence or absence of a guideline or effects-based threshold, its applicability to the LAR, and its relationship to background concentrations. The approach used for screening background-based benchmarks and investigation levels is provided in Section 3.3.

3. Defined background conditions

Adequately defined background conditions are critical for use in the screening method. The screening method includes comparing effects-based objectives to background conditions. The development of background-based benchmarks also relies on well-defined background conditions. The Athabasca River Model was used to define background constituent concentrations by taking into account spatial and seasonal variability of these constituent concentrations. Median and 99.91 percentile predictions were used in the characterization of background constituent concentrations. A description of the method is provided in Section 4.2 and the background conditions are provided in Section 4.3.


Golder Associates

4. Defined and screened effects-based objectives, background-based benchmarks and investigation levels

4a. Existing guidelines The sources for existing guidelines are described in Section 5.2. The guidelines and results of the screening are provided in Section 5.3.

4b. Interjurisdictional guidelines and health risk-based thresholds Based on screening the adequacy of the existing guidelines, those available from other jurisdictions were examined. Wherever possible, site-specific information was used to derive aquatic life effects-based thresholds or human and wildlife health risk-based thresholds according to the methods that fall under the recalculation procedure (CCME 2003). The methods applied to develop these guidelines and effects-based thresholds are provided in Section 6.1. The revised guidelines and effects-based thresholds, as well as the results of the screening, are provided in Section 6.2. For the purposes of this report, these guidelines and effects-based thresholds are collectively referred to as effects-based objectives.

4c. Benchmarks based on background concentrations In some cases, effects-based objectives could not be developed or were considered inadequate according to the screening method. In these situations, and as a general strategy for limiting changes to water quality, background-based benchmarks are considered to be appropriate.

Procedures proposed by CCME (2003) were used to develop background-based benchmarks. As explained in Section 7.1, background-based benchmarks are considered to be conservative, non-effects-based management objectives and are categorized separately from effects-based objectives.

Median and 99.91 percentile constituent concentration predictions were used for the development of background-based benchmarks. A description of the method is provided in Section 7.2 and the background-based benchmarks, as well as the results of the screening, are provided in Section 7.3.

4d. Investigation levels An investigation levels watershed management method was proposed for the Muskeg River Watershed (CEMA 2005) and such a method is similarly proposed in conjunction with the development of effects-based objectives and background-based benchmarks identified in this study.


Golder Associates

Investigation levels represent predicted water quality constituent concentrations based on spatial and temporal loadings from existing, approved and planned developments as defined in recent EIAs (Imperial 2005; Suncor 2005; Shell 2005). Investigation levels should only be considered applicable if they are more restrictive than effects-based objectives.

An investigation levels interface model (ILIM) for the LAR also allows for the comparison of investigation levels to background-based benchmarks and to effects-based objectives. The ILIM is described in Section 8.2 and the investigation levels, as well as the results of the screening, are provided in Section 8.3.

5. Finalized objectives

Sections 9.1 and 9.2 provide a review and summary of the effects-based objectives, background-based benchmarks and investigation levels.

The most restrictive effects-based objectives were identified for each constituent, taking into account the appropriate frequency of attainment of the objectives, and excluding effects-based objectives that were identified as inadequate based on the screening criteria.

The potential application of background-based benchmarks and investigation levels, including possible methods for comparing monitoring results to those levels, are provided in Section 9.2. A discussion of the potential application of these types of management objectives for other regional surface waters is provided in Section 9.3.

6. Evaluated potential information gaps

Constituents for which further examination may be required for development of RSWQOs, including those identified for further work under Task C of the request for proposal for the study, are described in Section 9.4. Recommendations for further development of ARM and the ILIM are provided in Section 9.5.


Golder Associates

Figure 1.1 Schematic of Steps Used in the Study

1.2 FINAL TERMS OF REFERENCE/SCOPE OF WORK

Recommended methods for developing effects-based objectives, background-based benchmarks and investigation levels for the LAR were provided in the scope of work for the study (Appendix I). The methods are based on the premise that the values represented by the RSWQOs will enable the integrity of the designated water uses to be maintained. The approaches are supported by the literature (Appendix II) and consider the results of recent oil sands environmental impact assessments.

The final terms of reference/scope of work was based on the original proposal for services along with an addendum; however, additional modifications were made in the final terms of reference/scope of work as represented in the contract and additional minor modifications were included in this report as discussed below:

Task A: Identify methods for establishing RSWQOs and evaluate and recommend methods for the Athabasca River Ai) Review literature This task was addressed in Appendix II, and provides an itemized list of documents reviewed in support of development of effects-based objectives,


Golder Associates

background-based benchmarks and investigation levels for the LAR and a compilation of guidelines developed for other jurisdictions. Methods found that have applicability to the development of effects-based objectives, background-based benchmarks and investigation levels for the LAR were applied in the study and are described throughout the report.

Aii) Verify objectives based on guidelines The scope of work stated that guidelines for human and wildlife health would be verified based on comparison to exposure ratios. This task was modified in the final approach as exposure ratios were used to derive health risk-based thresholds for consideration as effects-based objectives.

Aiii) Evaluate most sensitive water use or objective by type The most limiting candidate effects-based objectives were identified, however, the most limiting candidates were not always recommended as the final RSWQOs. Screening criteria, predicted future concentrations and comparison to background concentrations were also taken into consideration.

Task B: Evaluate Constituents using the approach from Task A Bi) Data collection and compilation Data was collected, compiled and analyzed as required, to develop the effects-based objectives, background-based benchmarks and investigation levels.

Bii) Compilation of guidelines for relevant uses Existing guidelines were compiled and are presented in Section 5. Interjurisdictional guidelines were compiled and are presented in Appendix II.

Biii) Develop chronic effects benchmarks for selected constituents Chronic Effects Benchmarks (CEB) are presented in Section 6. The specific list of CEBs does not directly correspond to the list of CEBs in the final terms of reference/scope of work or on the original proposal for services along the addendum. Additional constituents were included in the final approach and no CEBs were developed for sulphate and TDS because data for completion of species sensitivity distributions were not available as described in the addendum. However, background-based benchmarks and investigation levels were developed for these constituents.

Biv) Develop objectives based on background concentrations for selected constituents Background-based benchmarks were developed for constituents identified under Task B by applying statistical distributions of background concentrations in the LAR as described in Section 4.


Golder Associates

Bv) Apply the Investigation Levels Interface Model The Investigations Level Interface Model (ILIM) developed for the LAR as described in the final terms of reference/scope of work. The following sub-tasks were included:

• defining nodes and snapshots;

• initially scoping candidate constituents;

• identifying source loads (i.e., seepages, muskeg/overburden dewatering, pit lakes and individual tributaries) and their proportional contribution to concentrations at each node;

• applying statistics to distinguish oil sands development contributions from background constituent loading;

• establishing investigation levels that are protective of all water uses and are indicative of developments functioning as proposed in recent EIA applications (Imperial 2005; Shell 2005; Suncor 2005);

• identification of uncertainty; and

• identification of future research needs and data gaps.

Bvi) Evaluate most sensitive water use or objective by type Final RSWQOs were developed after all the effects-based objectives, background-based benchmarks and investigation levels were identified (Section 9). The most sensitive water uses or objective types were identified, but not necessarily chosen as the final RSWQOs.

Bvii) Determine adequacy of objectives to other regional surface water This examination is provided in Section 9.

Task C: Consideration of Additional Constituents Ci) Develop chronic effects benchmarks The additional constituents listed in the scope of work were included in the development of CEBs.

Cii) Develop objectives based on background concentrations The additional constituents listed were included in the development of background-based benchmarks.

Ciii-“Item 3” Further examination of additional constituents “Item 3” under tasks Ci, Cii and Ciii, was also addressed within the study although it was not to be initiated until 2007. Item 3 included further examination of additional constituents to determine whether effects-based


Golder Associates

objectives, background-based benchmarks and investigation levels needed to be developed or whether an alternative approach should be applied. All the constituents listed are addressed in Appendix IX.

1.3 TERMS & ACRONYMS

This section includes definitions of terms and acronyms used in this report. Phrases that are used in a definition and are also defined are italicized. Figure 1.2 provides a categorization hierarchy of the candidate RSWQOs considered.

Figure 1.2 Hierarchy of Candidate RSWQOs Considered


Golder Associates

Background-based Benchmark (BBB): A level calculated using the background concentrations procedure. Background-based benchmarks are considered to be conservative, non-effects-based objectives and are categorized separately from effects-based objectives as management-based objectives.

Background Concentrations Procedure: A procedure described by CCME (2003) for development of reach-specific water quality objectives that is not effects-based, but rather is based on an antidegradation strategy. The procedure involves characterization of background conditions and setting objectives relative to background conditions.

Chronic Effects Benchmark (CEB): A level beyond which detrimental chronic effects to aquatic life may occur. The chronic effects benchmark was calculated from species sensitivity distributions (SSD) where sufficient data were available. Development of CEBs falls under the recalculation procedure for development of site-specific objectives because it is a recalculation of a guideline. This approach is currently being used by the Canadian Council of Ministers of the Environment (CCME) to develop water quality guidelines (CCME 1999).

CEB Effects-based Threshold: An effects-based water quality level above which aquatic ecosystems could begin to experience effects. This is a specific term used in this report to describe the CEB and to clearly identify it as an effects-based threshold and distinguish it from non-effects-based objectives.

Existing Guidelines: Generic guidelines for protection of aquatic life, human health, and wildlife health that apply to the LAR as described in recent oil sands EIAs, as well as U.S. EPA (1992) and Health Canada (2006) aesthetic drinking water guidelines.

Effects-based Objective: An objective derived based on measurable effects relevant to given water use. This type of objective is distinguished from background-based benchmarks or investigation levels which may be based on limiting changes to water quality or existing loading levels. In this study the term is used to refer collectively to existing guidelines, interjurisdictional guidelines, CEB effects-based thresholds and human and wildlife risk-based thresholds.

Effects-based Thresholds: Levels of water quality above which aquatic ecosystems could begin to experience effects.

Guidelines: Protection of aquatic life guidelines are based on effects-based thresholds but will also typically include safety factors. Guidelines are generally


Golder Associates

considered to be conservative values such that compliance with them will afford a high degree of ecosystem protection. Guidelines are typically more stringent than effects-based thresholds.

Interjurisdictional Guidelines: Guidelines from other jurisdictions that are distinct from “existing guidelines”.

Investigation Levels: Water quality levels indicative of developments functioning as proposed in EIA applications, and unique to the locations and time periods for which they occur. Investigation levels represent values beyond which further investigation or mitigation may be triggered.

Recalculation Procedure: A procedure described by CCME (2003) for deriving site-specific water quality objectives that accounts for any real differences between the sensitivity range of the species of aquatic organisms represented in the compete toxicological data set and that of the species that occur at the site under considerations. Strictly, the recalculation procedure applies to objectives for the protection of aquatic life and is implemented by excluding data on species that are not resident at the site under consideration and is calculated using the same methodology employed to derive the generic water quality guideline. In this study, the recalculation procedure is also taken to apply to the development of CEB effects-based thresholds and health risk-based thresholds because in each case, the thresholds are derived using the same methods as the corresponding guidelines.

Reach Specific Water Quality Objective (RSWQO): Synonymous with site-specific water quality objective. In this study the term is used to represent effects-based objectives, background-based benchmarks and investigation levels. Background-based benchmarks and investigation levels are collectively considered to be management-based objectives.

Site-specific Water Quality Objective: Water quality objectives that have been developed based on site-specific information, and taking into account the species and environmental conditions that are relevant to the site.

Long-term Average Concentration: In this report, the long-term average concentration in the LAR was represented by the median concentration for background conditions and investigation levels.

Peak Concentration: The maximum concentration predicted for background concentrations or investigation levels based on a one in three year maximum concentration or the 99.91 percentile (AEP 1995).


Golder Associates

Water Quality Objective: Numerical concentrations or narrative statements that establish the conditions necessary to support and protect the most sensitive designated uses of water at a specified site. Objectives are typically based on generic water quality guidelines, which may be modified to account for local environmental conditions or other factors.


Golder Associates

2 WATER QUALITY CONSTITUENTS

Constituents assessed in recent oil sands EIAs (Imperial 2005; Shell 2005; Suncor 2005) were included in this study based on the following criteria:

• generally thought to be of concern with oil sands mining (e.g., naphthenic acids, ammonia and salts); and

• monitored as part of the Regional Aquatics Monitoring Program (RAMP).

Additional constituents identified as having elevated concentrations in one or more mine waters were also included in this study based on a previous CEMA study (CEMA 2003). These constituents were not assessed in recent oil sands EIAs and could not be addressed following the approach outlined in Section 1, primarily because they were not included in ARM. These were included under “Task C” in the final terms of reference/scope of work. The complete list of constituents is provided in Table 2.1. A total of 58 constituents are included, 13 of which are in the “Task C” group.

Polycyclic aromatic Hydrocarbons (PAHs) were considered as groups rather than as individual species, because:

• toxicity information is limited for some compounds; and

• compounds with similar structures may act additively.

Parent and alkylated PAHs with similar form were combined into nine separate PAH groups (Table 2.2). Carcinogenic PAHs were categorized into three groups based on their toxic equivalency to benzo(a)pyrene. Carcinogenic PAH Group 1 included PAHs with same toxic potency as benzo(a)pyrene. Group 2 included PAHs with a toxic equivalency factor (TEF) of 0.1 (i.e., 10 times less toxic than benzo(a)pyrene) and Group 3 included PAHs with a TEF of 0.01 (i.e., 100 times less toxic than benzo(a)pyrene). The TEF values for the PAHs were determined from U.S. EPA (1993) and OMEE (1997). Non-carcinogenic PAHs were sorted into the remaining six groups, which include substituted versions of the parent compound and/or compounds with similar structure and toxicity. The concentration assigned to each PAH group was developed by summing the concentrations observed for each member of the group.

Dissolved oxygen (DO), and biochemical oxygen (BOD) have also been identified as a constituents of interest in the LAR. Releases from oil sands operations may contain organic constituents that could lead to depressed levels of


Golder Associates

dissolved oxygen, particularly during the winter when the river is covered with ice and no reaeration occurs. The existing guidelines for DO are expected to be applicable to the LAR. Levels of DO can affect the toxicity of other constituents although this relationship is not always well understood. The next phase of this work should consider completing a dissolved oxygen model for the LAR.

While ARM could be configured to represent oxygen dynamics in a simplistic way, a more complex model of oxygen dynamics should be considered as described in Appendix IX.

Table 2.1 Water Quality Constituents

Constituents

Major Ions General Organics PAH Groups calcium naphthenic acids PAH group 1 chloride total phenolics PAH group 2 (including benzo(a)anthracene)

magnesium Total Metals PAH group 3 sodium aluminum PAH group 4 (including acenaphthene and acenaphthylene) sulphate antimony PAH group 5 (including anthracene and phenanthrene) sulphide arsenic PAH group 6 (including biphenyl and alkyl substituted biphenyl)total dissolved solids barium PAH group 7 (including fluorene and fluoranthene) Nutrients beryllium PAH group 8 (including Naphthalene) ammonia boron PAH group 9 (including pyrene)

total nitrogen cadmium “Task C” Constituents total phosphorus chromium dibenzothiophene dissolved organic carbon copper alkyl-substituted dibenzothiophene Whole-effluent Constituents iron di (2-ethylhexyl) phthalate (DEHP) acute toxicity lead methyl isobutyl carbinol (MIBC) chronic toxicity manganese acrylamide fish tainting mercury oil and grease molybdenum total petroleum hydrocarbons nickel toluene selenium xylenes silver dissolved oxygen strontium lithium vanadium fluoride zinc potassium


Golder Associates

Table 2.2 List of the Individual Polycyclic Aromatic Hydrocarbons That Are Included in PAH Groups 1 to 9

Group Constituent Compounds

PAH Group 1 dibenzo(a,h)anthracene

benzo(a)pyrene

methyl benzo(b&k) fluoranthene/methyl benzo(a)pyrene

C2 substituted benzo(b& k) fluoranthene/benzo(a)pyrene

PAH Group 2 benzo(a)anthracene/chrysene

methyl benzo(a)anthracene/chrysene

C2 substituted benzo(a)anthracene/chrysene

benzo(b&k)fluoranthene

indeno(c,d-123)pyrene

PAH Group 3 benzo(g,h,i)perylene

chrysene

carbazole

methyl carbazole

C2 Substituted carbazole

PAH Group 4 acenaphthene

methyl acenaphthene

acenaphthylene

PAH Group 5 anthracene

phenanthrene

methyl phenanthrene/anthracene

C2 substituted phenanthrene/anthracene



1-methyl-7-isopropyl-phenanthrene (retene)

PAH Group 6 biphenyl

methyl biphenyl

C2 substituted biphenyl

C2 substituted biphenyl

PAH Group 7 fluoranthene

fluorene

methyl fluorene

C2 substituted fluorene

PAH Group 8 naphthalene

methyl naphthalenes

C2 substituted naphthalenes



PAH Group 9 methyl fluoranthene/pyrene

pyrene


Golder Associates

3 SCREENING METHODS

3.1 INTRODUCTION

Screening methods were developed to evaluate the potential applicability of effects-based objectives, background-based benchmarks and investigation levels to the LAR. The results of the screening were taken into account in the finalization of objectives.

3.2 CRITERIA FOR GUIDELINES AND EFFECTS-BASED THRESHOLDS

Five criteria were developed for the screening approach used in an earlier CEMA study (CEMA 2003) to evaluate the adequacy of existing guidelines. Some of these criteria, or elements thereof, were used as screening criteria for determining the adequacy of guidelines and effects-based thresholds developed in this study. A schematic of the five criteria is provided in Figure 3.1. The five CEMA screening criteria, along with the modifications used in this study, are:

1) No existing guideline but adverse effect could occur

Constituents that do not have guidelines should not necessarily be considered to be non-toxic. Searches of the ECOTOX database for all constituents that did not have existing chronic guidelines for the protection of aquatic life were performed by CEMA (2003). Where that search showed a constituent could have an adverse effect on a species relevant to the LAR, the constituent was flagged as having an inadequate guideline because the guideline was absent. For other types of guidelines (drinking water, etc.), constituents were flagged as having inadequate guidelines only if there were known adverse effects for the constituent for the particular water use.

Modification For this study, all constituents that did not have an existing guideline for the protection of aquatic life, human or wildlife health, and drinking water were automatically identified for further guideline consideration.

The classification of missing guidelines (or effects-based thresholds) as inadequate based on known adverse effects can be somewhat problematic because any constituent could have adverse effects at some concentration, however, the threshold concentration may be so high that it would never be realized. Therefore absent guidelines were classified under one of the following:


Golder Associates

• Not Relevant (NR) - this category applies when the water use is clearly not related to the constituent.

• Likely Not Relevant (LNR) – this category applies under the following conditions:

− For constiuents considered by CEMA (2003): when the ECOTOX database search did not show that the constituent could have an adverse effect, the potential effect level far exceeds ambient concentrations or when no known adverse effects were identified.

− For other consituents: when potential adverse effects were not identified in the review provided in Appendix IX.

− For constituents indentified under “Task C”: when the consitiuent related to the guidelins was not considered relevant to he LAR based on the review provided in Appendix IX.

• Likely Relevant (LR) – this category applies under the following conditions:

− For constiuents considered by CEMA (2003): when the ECOTOX database search showed that the constituent could have an adverse effect or when known adverse effects were identified.

− For other consituents: where potential adverse effects were identified in the review provided in Appendix IX or where known adverse effects were identified from other sources.

2) Derivation of guideline

The relevance of a guideline to the LAR was confirmed by examining the factors specific to the derivation of the guideline. This included an examination of the endpoints, the organisms or test conditions used in the toxicity assays.

No constituents were found inadequate based on this criterion in the CEMA study (CEMA 2003) although it was noted that the chronic aquatic life guideline for chloride was based primarily on warm water species.

Modification For this study, no modifications were required to this criterion.

3) Guideline lower than background concentration

If a guideline or objective is to be used to evaluate the acceptability of existing or future developments on water quality, then the background concentration of the constituent in the pre-development environment will ideally be below that guideline or objective. It is generally recognized that guideline exceedances, particularly for metals, are common in surface waters unaffected by


Golder Associates

anthropogenic activities (e.g., AEP 1995; AENV 1999; U.S. EPA 2002; CCME 1999). This has been recognized in the oil sands region as well as other regions (e.g., Mackenzie River; MRBB 2003).

The CEMA screening approach stipulated that any guideline that was below the background concentration of the constituent in the LAR more than 50 percent of the time was deemed inadequate. However, this approach may be overly simplistic because it does not take into account the prescribed frequency of attainment for the guidelines. For example, guidelines for the protection of aquatic life should only be exceeded by extreme events (i.e., a one in three year maximum concentration or the 99.91 percentile; AEP 1995), whereas human and wildlife health guidelines should not be exceeded by long term average concentrations (exposures over decades (HC 2002)).

The CEMA screening approach used one site upstream of Fort McMurray and one site at Old Fort for the evaluation of background concentrations relative to existing guidelines. The site upstream of Fort McMurray is also upstream of the confluence with the Clearwater River and therefore is not considered to be completely representative of the water quality in the LAR.

Modification Constituent concentrations in the LAR vary spatially (laterally or longitudinally), or temporally (seasonally). Because of this, a modelling approach that accounted for these gradients was used to represent the background concentrations in the LAR.

Guidelines for the protection of aquatic life were compared to peak 99.91 percentile background constituent concentrations. Human and wildlife health guidelines were compared to median background constituent concentrations. Aesthetic drinking water guidelines (e.g., taste, odour and scaling) were compared to both peak and median constituent concentrations.

4) Guideline does not account for other factors that can contribute to effects

Factors that can contribute to potential adverse effects of some constituents include hardness, suspended material, pH and temperature. The majority of guidelines are based solely on the total concentration of the constituent in water. The toxicity of the constituent to an organism, however, is dependent not only on the total amount of the constituent, but also on the amount available to the organism. Availability of a constituent depends on whether it is highly particle reactive, or easily complexed, factors which are in turn often dependent on hardness, suspended material, pH and temperature.


Golder Associates

Although the definition of this criterion appears to be quite broad, the only constituents identified in the CEMA study (CEMA 2003) under this category were total nitrogen and total phosphorus. The effects of these two constituents are associated with eutrophication and the corresponding guidelines do not reflect the conditions in the LAR. These conditions include wide seasonal variations in nitrogen and phosphorous, limited light availability and the presence of suspended particles.

Many other constituents where the background concentration is above the existing guidelines, particularly metals, likely fall under this category, however evaluation of additional guidelines according to this criteria was beyond the scope of the study.

Modification Although additional constituents likely fall under this category, no modification was made and the only constituents included were total nitrogen and total phosphorus.

5) Guideline greater than median background concentration by factor of 10

This criterion is focused on limiting changes to water quality. Such a concept is not unprecedented in the development of site-specific water quality objectives or as a general policy for water quality management. The Ontario Ministry of the Environment, in its principal guideline and water policy document states as Policy 1: “In areas which have water quality better than the Provincial Objective, water quality shall be maintained at or above (sic) the objectives” (OMEE 1998). Adoption of this “antidegradation” criterion implies that a lowering of the current guideline may be desirable to fit local conditions and management objectives.

Background-based benchmarks and investigation levels are both used to address this criterion.

Modification As with criterion #3, this criterion is based on background constituent concentrations. The criterion was similarly modified by using background concentrations predicted using ARM and by accounting for appropriate attainment frequencies.

Guidelines and effects-based thresholds that fall under criterion #5 are generally protective of water uses and were therefore not identified as inadequate. Guidelines and effects-based thresholds that fall under criterion #5 are not protective of changes in water quality. Investigation levels or background-based benchmarks may be of particular value to limit changes in water quality.


Golder Associates

Figure 3.1 Schematic of the Criteria Used for Screening Existing Guidelines and Effects-based Thresholds

Guideline is inadequate because effects are predictedunder background conditions.

Criterion #3Is the guideline below the

background concentration?Yes

Criterion #5Is the guideline much higher than the background concentration?

Criterion #2 and #4Is the guideline appropriate for

conditions in the LAR?

Is the guideline adequate according to the above criteria?

Guideline is adequate and protective of water uses,

however, objectives that restrict changes may be of particular value.

Guideline is inadequate because effects threshold depends on

local conditions.

Guideline is adequatehowever, effects thresholds based on site-specific conditions may be

more appropriate than the guideline.

Yes

No

Yes

Criterion #1Is the guideline absent?

Yes

Guideline is inadequate.

Guideline was identified as absentand further categorized according to

the likelihood that an effects threshold would be relevant.

3.3 CRITERIA FOR BACKGROUND-BASED BENCHMARKS AND INVESTIGATION LEVELS

The screening criteria described in Section 3.2 were developed for the evaluation of guidelines and effects-based thresholds and, in general, do not apply to background-based benchmarks and investigation levels. Investigation levels and background-based benchmarks were each screened with respect to protection of water uses. Details of the approach are provided in Section 7 for background-based benchmarks and in Section 8 for investigation levels.


Golder Associates

4 DEFINITION OF BACKGROUND CONDITIONS

4.1 INTRODUCTION

The results from the screening methods described in Section 3 are sensitive to the procedures for characterizing background conditions. Constituent concentrations in the LAR vary spatially (laterally or longitudinally), and temporally (seasonally) and water quality data from either one location or one season does not accurately portray background conditions. Additionally, water quality downstream of Fort McMurray is affected by both natural sources (particularly the Clearwater River) and releases from Fort McMurray. Because of this, a modelling approach that accounted for these gradients was used to represent the background conditions in the LAR.

4.2 PROCEDURE

The Athabasca River Model (ARM) was used to predict background concentrations for 45 constituents at five different assessment nodes (Golder 2004a, Appendix V, Figure V-1; Golder 2006a) along the LAR between Fort McMurray and Embarras. The Athabasca River Model is a two-dimensional, vertically-averaged, dispersion model based on analytical solutions to the river dispersion equations, as described by Fischer et al. (1979). The model predicts constituent concentrations along the length of the LAR taking into account the mixing of the Clearwater and Athabasca rivers, while excluding the effects of inputs from Fort McMurray (Golder 2006a). Further details of the assumptions used by the model are described in Appendix V. The water quality profile information including data used to represent background conditions are provided in Appendix VI.

The background concentrations derived from the model exclude the effects of oil sands developments and Fort McMurray, however, they do include releases upstream of Fort McMurray including non-point source releases, pulp mills and sewage treatment plants. The constituents contributed by pulp mills are generally different from those of concern for oil sands operations and include biological oxygen demand, nutrients, resin acids and chlorinated organic constituents (Golder 2004b, Golder 2006a). Although nutrients are included in ARM, oil sands developments do not contribute appreciable levels of nutrients to the LAR (Section 8.3).

The model takes into account seasonal variation in constituent concentrations. Statistical distributions were developed for each season from monitoring data. Statistical distributions were developed for the Athabasca River and for major


Golder Associates

tributaries including the Muskeg and Clearwater rivers. Model inputs were generated by sampling from the appropriate seasonal statistical distributions for each day to develop a 42 year time series. The model was use to predict constituent concentrations for each day in the time series and the output data at each node were used to develop an overall background distribution for each node.

Two background concentrations were defined. A long-term average background concentration was represented by the median background concentration and a peak background concentration was represented by the 99.91 percentile. Background concentrations were calculated for each of the five assessment nodes. The maximum background concentrations among the five assessment nodes were primarily used for the screening conducted in subsequent sections, however background concentrations for individual nodes were also considered.

The screening approach was based on the maximum background concentration among the five assessment nodes.

In some cases, predicted background concentrations were “zero”. This results when all measurements were below detection limits for all inputs in at least one season and all values of the statistical distribution for that season were assumed to be equal to zero. In these cases, predicted concentrations are shown as “<” indicating that they are predicted to be below the relevant detection limit. Subsequently in this report, these predicted concentrations are described as “below detection”.

4.3 RESULTS

The predicted median and 99.91 percentile background constituent concentrations at each node are provided in Appendix VII. The maximum background concentrations among the five assessment nodes are provided Table 4.1.

Table 4.1 Background Constituent Concentrations for Lower Athabasca River

Constituent Units

Maximum (Among Nodes) Long-term Average

Background Concentration(a)

Maximum (Among Nodes) Peak Background Concentration(b)

Major Ions

calcium mg/L 37 77

chloride mg/L 27 97

magnesium mg/L 10 21


Table 4.1 Background Concentrations Derived for the Lower Athabasca River (continued)

Golder Associates

Constituent Units




sodium mg/L 22 74

sulphate mg/L 29 96

sulphide mg/L 0.0040 0.031

total dissolved solids mg/L 200 400 Nutrients

ammonia mg/L 0.038 0.35

total nitrogen mg/L 0.77 4.4

total phosphorus mg/L 0.064 1.5

dissolved organic carbon mg/L 10 43 Whole-effluent Constituents

acute toxicity TUa < <

chronic toxicity TUc < <

fish tainting TPU < < General Organics

naphthenic acids mg/L 0.034 0.63

total phenolics mg/L 0.0038 0.060 Total Metals

aluminum mg/L 0.36 21

antimony mg/L 0.00067 0.0075

arsenic mg/L 0.00079 0.029

barium mg/L 0.082 0.15

beryllium mg/L 0.00027 0.018

boron mg/L 0.039 0.17

cadmium mg/L 0.0005 0.031

chromium mg/L 0.0031 0.035

copper mg/L 0.0028 0.029

iron mg/L 1.0 20

lead mg/L 0.0012 0.0095

manganese mg/L 0.046 0.97

mercury mg/L 0.000036 0.00010

molybdenum mg/L 0.0018 0.013

nickel mg/L 0.0061 0.045

selenium mg/L 0.00018 0.0021

silver mg/L 0.000058 0.00078

strontium mg/L 0.27 1.7


Table 4.1 Background Concentrations Derived for the Lower Athabasca River (continued)

Golder Associates

Constituent Units




vanadium mg/L 0.0022 0.045

zinc mg/L 0.015 0.12 PAH Groups

PAH group 1 µg/L < <

PAH group 2 (including benzo(a)anthracene) µg/L < 0.034

PAH group 3 µg/L < 0.016

PAH group 4 (including acenaphthene and acenaphthylene µg/L < <

PAH group 5 (including anthracene and phenanthrene) µg/L < 0.025

PAH group 6 (including biphenyl and alkyl substituted biphenyl) µg/L < <

PAH group 7 (including fluorene and fluoranthene) µg/L 0.0037 0.94

PAH group 8 (including Naphthalene) µg/L 0.0050 0.90

PAH group 9 (including pyrene) µg/L < 0.012 (a) Concentrations based on the maximum of the median background concentrations among the assessment nodes derived

from the ARM model. (b) Concentrations based on the maximum of the 99.91 percentile background concentrations among the assessment nodes

derived from the ARM model. < Predicted background concentrations are below detection.


Golder Associates

5 EXISTING WATER QUALITY GUIDELINES

5.1 INTRODUCTION

The water quality guidelines applied in the assessment of recent oil sands EIAs were considered to be “existing” guidelines. These existing guidelines included:

• U.S., Canadian, and Albertan guidelines for the protection of aquatic life (U.S. EPA 2002; CCME 1999; AENV 1999);

• U.S. and Canadian human health guidelines (U.S. EPA 1999; U.S. EPA 2002; Health Canada 2006); and

• Canadian livestock guidelines for wildlife health (CCME 1999).

Although aesthetic (e.g., taste, odour or scaling) guidelines were not applied in recent oil sands EIAs, guidelines based on Canadian and U.S. aesthetic drinking water guidelines (HC 2006; U.S. EPA 1992) were considered to be existing guidelines in this study.

5.2 APPROACH

Existing water quality guidelines for the protection of aquatic life used in this study were selected according to the recommended protocol outlined in AENV (1999), which stipulates that:

• the most stringent guideline should be used when multiple guidelines are available for a given substance; and

• the guidelines developed by AENV after 1996 should be given preference over Canadian Council of Ministers of the Environment (CCME) and United States Environmental Protection Agency (U.S. EPA) guidelines.

The recommended selection protocol was applied to all constituents for which guidelines were available, with the following exceptions:

• cadmium

− the U.S. EPA (2002) chronic cadmium guideline was used in place of the lower CCME (1999) chronic guideline, because, as noted by CCME (1999), most ambient waters contain cadmium levels in excess of the recommended CCME chronic cadmium guideline.


Golder Associates

• copper

− the U.S. EPA (2002) acute and CCME (1999) chronic copper guidelines were selected, because the Alberta copper guidelines apply to acid extractable values (as opposed to total values).

Existing water quality guidelines for the protection of human health used in this study were selected using the most stringent value of:

• the U.S. EPA (2002) human health guidelines using a fish consumption rate of 45 g/day (Richardson 1997);

• the U.S. EPA (1999) primary drinking water regulations; or

• the Health Canada (2006) guidelines.

The recommended selection protocol was applied to all constituents for which guidelines were available, with the following exception:

• manganese

− the US EPA human health guideline was not included as this guideline is not based on toxic effects but aesthetic considerations (USEPA 2002).

Existing water quality guidelines for the protection of wildlife health used in this study were taken from the Canadian agricultural livestock use guidelines (CCME 1999).

Existing water quality guidelines for drinking water (aesthetic) used in this study were selected using the most stringent value of either:

• the U.S. EPA (1992) secondary drinking water regulations; or

• the Health Canada (2006) aesthetic guidelines.

The recommended selection protocol was applied to all constituents for which guidelines were available, with the following exception:

• aluminum

− no aluminum guideline was included for this water use as drinking water guidelines for aluminum are based on the use of alum and not on naturally occurring aluminum.


Golder Associates

5.3 SUMMARY SCREENING OF EXISTING GUIDELINES

Tables 5.1 and 5.2 provide a summary of the guideline screening. All of the existing guidelines identified by the screening criteria are bolded. The footnotes indicate the corresponding criteria. Some guidelines could not be completely evaluated as the corresponding predicted background constituent concentrations were below detection (see Section 4.2). “Task C” guidelines could not be completely evaluated because they are not included in ARM and therefore background concentrations were not derived. The guidelines that could not be completely screened are shown in italics.


Golder Associates

Table 5.1 Screening of Guidelines Relevant to Long-term Average (Median) Conditions

Existing Guidelines Guideline Sources

Constituent Units

Maximum (Among Nodes) Long-term

Average Background Concentration(d)

Aesthetic Drinking Water(c)

Human Health(a)

Wildlife Health(b)


Human Health(a)

Wildlife Health(b)

Major Ions calcium mg/L 37 LR LNR 1000 5 - CCME 1999 chloride mg/L 27 250 LNR LNR HC 2006 - - magnesium mg/L 10 LR LNR LNR - - - sodium mg/L 22 200 LNR LNR HC 2006 - - sulphate mg/L 29 500 5 LNR 1000 5 HC 2006 - CCME 1999 sulphide mg/L 0.0040 0.05 5 LNR LNR HC 2006 - - total dissolved solids mg/L 200 500 LNR 3000 5 HC 2006 - CCME 1999 Nutrients ammonia mg/L 0.038 LR LNR LNR - - - total nitrogen mg/L 0.77 LNR LNR LNR - US EPA 1999 CCME 1999 total phosphorus mg/L 0.064 LNR LNR LNR - - - dissolved organic carbon mg/L 10 LNR LNR LNR - - - Whole-effluent Constituents acute toxicity TUa < NR NR NR - - - chronic toxicity TUc < NR NR NR - - - fish tainting TPU < 1(g) NR NR Golder 2004c - - General Organics naphthenic acids mg/L 0.034 LNR LR LR - - - total phenolics mg/L 0.0038 LNR LR 0.002(f) 3 - - CCME 1999 Total Metals aluminum mg/L 0.36 LNR LR 5 5 - - CCME 1999 antimony mg/L 0.00067 LNR 0.0055 LR - US EPA 2002 - arsenic mg/L 0.00079 LNR 0.01 5 0.025 5 - US EPA 1999 CCME 1999 barium mg/L 0.082 LNR 1 5 LR - HC 2006 - beryllium mg/L 0.00027 LNR 0.004 5 0.1 5 - US EPA 1999 CCME 1999 boron mg/L 0.039 LNR 5 5 5 5 - HC 2006 CCME 1999 cadmium mg/L 0.0005 LNR 0.005 0.08 5 - HC 2006 CCME 1999 chromium mg/L 0.0031 LNR 0.05(e) 0.05(e) - HC 2006 CCME 1999


Table 5.1 Screening of Guidelines Relevant to Long-term Average (Median) Conditions (continued)

Golder Associates


Constituent Units




Human Health(a)

Wildlife Health(b)


Human Health(a)

Wildlife Health(b)

copper mg/L 0.0028 1 5 1.3 5 0.5 5 HC 2006 US EPA 2002 CCME 1999 iron mg/L 1.0 0.3 3 0.3 3 LR HC 2006 US EPA 2002 - lead mg/L 0.0012 LNR 0.01 0.1 5 - HC 2006 CCME 1999 manganese mg/L 0.046 0.05 LR LR HC 2006 - - mercury mg/L 0.000036 LNR 0.001 5 0.003 5 - HC 2006 CCME 1999 molybdenum mg/L 0.0018 LNR LR 0.5 5 - - CCME 1999 nickel mg/L 0.0061 LNR 0.34 5 1 5 - US EPA 2002 CCME 1999 selenium mg/L 0.00018 LNR 0.01 5 0.05 5 - HC 2006 CCME 1999 silver mg/L 0.000058 0.1 5 LR LR US EPA 1992 - - strontium mg/L 0.27 LNR LR LR - - - vanadium mg/L 0.0022 LNR LR 0.1 5 - - CCME 1999 zinc mg/L 0.015 5 5 5.1 5 50 5 HC 2006 US EPA 2002 CCME 1999 PAH Groups PAH group 1 µg/L < LNR 0.0029 LR - US EPA 2002 - PAH group 2 (including benzo(a)anthracene) µg/L < LNR 0.0029 LR - US EPA 2002 -

PAH group 3 µg/L < LNR 0.0029 LR - US EPA 2002 - PAH group 4 (including acenaphthene and acenaphthylene µg/L < LNR 330 LR - US EPA 2002 -

PAH group 5 (including anthracene and phenanthrene) µg/L < LNR 6300 LR - US EPA 2002 -

PAH group 6 (including biphenyl and alkyl substituted biphenyl) µg/L < LNR LR LR - - -

PAH group 7 (including fluorene and fluoranthene) µg/L 0.0037 LNR 50 5 LR - US EPA 2002 -

PAH group 8 (including Naphthalene) µg/L 0.0050 LNR LR LR - - - PAH group 9 (including pyrene) µg/L < LNR 630 LR - US EPA 2002 - “Task C” Constituents dibenzothiophene µg/L na LNR LNR LNR - - - alkyl-substituted dibenzothiophene µg/L na LNR LNR LNR - - -


Table 5.1 Screening of Guidelines Relevant to Long-term Average (Median) Conditions (continued)

Golder Associates


Constituent Units




Human Health(a)

Wildlife Health(b)


Human Health(a)

Wildlife Health(b)

di (2-ethylhexyl) phthalate (DEHP) µg/L na LNR 6 LNR - US EPA 2002 - methyl isobutyl carbinol (MIBC) µg/L na LNR LNR LNR - - - acrylamide µg/L na LNR 0 LNR - US EPA 1999 - oil and grease mg/L na LNR LNR LNR - - - total petroleum hydrocarbons mg/L na LNR LNR LNR - - - toluene mg/L na 0.024 1 0.024 HC 2006 US EPA 1999 CCME 1999 xylenes mg/L na 0.3 0.01 LNR HC 2006 US EPA 1999 - dissolved oxygen mg/L na LNR LNR LNR - - - lithium mg/L na LNR LR LR - - - fluoride mg/L na 2 1.5 2 US EPA 1992 HC 2006 CCME 1999 potassium mg/L na LNR LR LR - - -

Note: Bold values fall into one or more of the screening criteria outlined in Section 3.2. Italicized values indicate that no evaluation was possible either because constituent was not modeled or median background concentration was below detection.

1 Guideline is absent. 2 Guideline is inadequate as the method used to determine the guideline is not relevant to the LAR. 3 Guideline is inadequate as the guideline is below the maximum background concentration. 4 Guideline is inadequate as is does not account for other water quality constituents which effect the toxicity. 5 Guideline more than ten times greater than the background concentration. (a) Based on the more conservative guideline of: USEPA (2002) using fish consumption rate of 45 g/d (Richardson 1997), USEPA (1999) primary drinking water objectives and Health Canada (2006) health based drinking water objectives. (b) CCME (1999) livestock watering guidelines. (c) Based on the more conservative of Health Canada (2006) aesthetic objectives and USEPA (1992) secondary drinking water objectives. (d) Concentrations based on the maximum median background concentration among the assessment nodes derived from the ARM model. (e) Chromium III guideline. (f) Guideline for phenols. (g) The fish tainting threshold is aesthetic, but applies to fish tissue quality not drinking water. Guideline from Golder 2004c. NR = Guideline is not relevant, LNR = Guideline is likely not relevant, LR = Guideline is likely relevant. < Predicted background concentrations are below detection. na = not determined as constituent was not in ARM model.


Golder Associates

Table 5.2 Screening of Guidelines Relevant to Peak (99.91 Percentile) Conditions

Existing Guidelines Guidelines Sources

Constituent Units

Maximum (Among Nodes) Peak Background

Concentration(d)

Aquatic Life

Chronic(b,c)

Aesthetic Drinking Water(a)

Aquatic Life Chronic(b,c)


Major Ions calcium mg/L 77 LNR LR - - chloride mg/L 97 230 250 US EPA 2002 HC 2006 magnesium mg/L 21 LNR LR - - sodium mg/L 74 LNR 200 - HC 2006 sulphate mg/L 96 LR 500 - HC 2006 sulphide mg/L 0.031 0.014(e) 3 0.05 US EPA 2002 HC 2006 total dissolved solids mg/L 400 LNR 500 - HC 2006 Nutrients ammonia mg/L 0.35 2.4(e) LR US EPA 2002 - total nitrogen mg/L 4.4 1 3,4 LNR AENV 1999 - total phosphorus mg/L 1.5 0.05 3,4 LNR AENV 1999 - dissolved organic carbon mg/L 43 LNR LNR - - Whole-effluent Constituents acute toxicity TUa < NR NR - - chronic toxicity TUc < 1(k) NR US EPA 1991 - fish tainting TPU < NR 1(j) - Golder 2004cGeneral Organics naphthenic acids mg/L 0.63 LR LNR - - total phenolics mg/L 0.060 0.005(i) 3 LNR AENV 1999 - Total Metals aluminum mg/L 21 0.1 3 LNR CCME 1999 - antimony mg/L 0.0075 LR LNR - - arsenic mg/L 0.029 0.005 3 LNR CCME 1999 - barium mg/L 0.15 LR LNR - - beryllium mg/L 0.018 LR LNR - - boron mg/L 0.17 LR LNR - - cadmium mg/L 0.031 0.00032(f) 3 LNR US EPA 2002 - chromium mg/L 0.035 0.001(g) 3 LNR CCME 1999 - copper mg/L 0.029 0.003(f) 3 1 5 CCME 1999 HC 2006 iron mg/L 20 0.3 3 0.3 3 CCME 1999 HC 2006 lead mg/L 0.0095 0.004(f) 3 LNR CCME 1999 - manganese mg/L 0.97 LR 0.05 3 - HC 2006 mercury(h) mg/L 0.0001 0.000005 3 LNR AENV 1999 - molybdenum mg/L 0.013 0.073 LNR CCME 1999 - nickel mg/L 0.045 0.062(f) LNR US EPA 2002 - selenium mg/L 0.0021 0.001 3 LNR CCME 1999 - silver mg/L 0.00078 0.0001 3 0.1 5 CCME 1999 US EPA 1992strontium mg/L 1.7 LR LNR - - vanadium mg/L 0.045 LR LNR - - zinc mg/L 0.12 0.03 3 5 5 CCME 1999 HC 2006 PAH Groups PAH group 1 µg/L < 0.015 LNR CCME 1999 - PAH group 2 (including benzo(a)anthracene) µg/L 0.034 0.018 3 LNR CCME 1999 -

PAH group 3 µg/L 0.016 LR LNR - -


Table 5.2 Screening of Guidelines Relevant to Peak (99.91 Percentile) Conditions (continued)

Golder Associates

Existing Guidelines Guidelines Sources

Constituent Units


Concentration(d)

Aquatic Life

Chronic(b,c)




PAH group 4 (including acenaphthene and acenaphthylene µg/L < 5.8 LNR CCME 1999 -

PAH group 5 (including anthracene and phenanthrene) µg/L 0.025 0.012 3 LNR CCME 1999 -

PAH group 6 (including biphenyl and alkyl substituted biphenyl) µg/L < LR LNR - -

PAH group 7 (including fluorene and fluoranthene) µg/L 0.94 0.04 3 LNR CCME 1999 -

PAH group 8 (including Naphthalene) µg/L 0.90 1.1 LNR CCME 1999 - PAH group 9 (including pyrene) µg/L 0.012 0.025 LNR CCME 1999 - “Task C” Constituents dibenzothiophene µg/L na LNR LNR - - alkyl-substituted dibenzothiophene µg/L na LNR LNR - - di (2-ethylhexyl) phthalate (DEHP) µg/L na 16 LNR CCME 1999 - methyl isobutyl carbinol (MIBC) µg/L na LNR LNR - - acrylamide µg/L na LNR LNR - - oil and grease mg/L na LNR LNR - - total petroleum hydrocarbons mg/L na LNR LNR - - toluene mg/L na 0.002 0.024 CCME 1999 HC 2006 xylenes mg/L na LNR 0.3 - HC 2006 dissolved oxygen mg/L na 6.5 LNR AENV 1999 - lithium mg/L na LR LNR - - fluoride mg/L na 0.12 2 CCME 1999 US EPA 1992potassium mg/L na LR LNR - - Note: Bold values fall into one or more of the screening criteria outlined in Section 3.2. Italicized values indicate that no evaluation was

possible either because constituent was not modeled or the peak background concentration was below detection. 1 Guideline is absent. 2 Guideline is inadequate as the method used to determine the guideline is not relevant to the LAR. 3 Guideline is inadequate as the guideline is below the maximum background concentration. 4 Guideline is inadequate as is does not account for other water quality constituents which effect the toxicity. 5 Guideline is more than ten times greater than the background concentration. (a) Based on the more conservative of Health Canada (2006) aesthetic objectives and USEPA (1992) secondary drinking water objectives. (b) Based on the more conservative guidelines for the protection of aquatic life of US EPA (2002), CCME (1999) and AENV (1999). (c) 7-day mean. (d) Concentrations based on the maximum 99.91 percentile background concentration among the assessment nodes derived from the ARM

model. (e) Guidelines are pH (acute and chronic) and/or temperature (chronic) dependent; values shown here correspond to a pH of 8 and

temperature of 5 °C, respectively; these guidelines were altered based on site-specific median conditions using methods described in AENV (1999) and U.S.EPA (1999, 2002).

(f) Guidelines are hardness dependent; values shown here are based on a hardness of 125 mg/L; these guidelines were altered based on site-specific hardness levels using the methods described in AENV (1999) and U.S. EPA (2002).

(g) Chromium VI guideline. (h) Alberta chronic mercury guideline for the protection of aquatic life is still draft. (i) Guideline for phenols. (j) The fish tainting threshold is aesthetic, but applies to fish tissue quality not drinking water. Guideline from Golder 2004c. (k) Toxicity guideline taken from US EPA (1991). NR = Guideline is not relevant, LNR = Guideline is likely not relevant, LR = Guideline is likely relevant. < Predicted background concentrations are below detection. na = not determined as constituent was not in ARM model. - = No guideline.


Golder Associates

6 EFFECTS-BASED OBJECTIVES

Many existing guidelines were inadequate based on the screening approach criteria (Tables 5.1 and 5.2).

Where existing guidelines were absent for the LAR, guidelines from other jurisdictions (interjurisdictional water quality guidelines) were evaluated as candidate objectives.

Where appropriate information was available, site-specific effects-based thresholds were developed. Site-specific effects-based thresholds, when developed using standardized techniques, can replace existing water quality guidelines (CCME 2003). Because data specific to the LAR is used in the development of effects-based thresholds, these thresholds are considered to be more accurate than corresponding guidelines (existing and interjurisdictional). These effects-based thresholds were given preference to the corresponding guidelines.

Interjurisdictional guidelines, aquatic life effects-based thresholds and health risk-based thresholds developed in this section are collectively referred to as “effects-based objectives”. Figure 6.1 provides a schematic of the approach for developing new effects-based objectives.

6.1 PROCEDURE

6.1.1 Interjurisdictional Guidelines

In Section 5.3, existing water quality guidelines were evaluated for applicability to the LAR based on the screening methods. Interjurisdictional guidelines were considered as effects-based objectives when there were no existing guidelines as described in Section 5.3. The interjurisdictional guidelines considered for this process were as follows:

• The World Health Organization drinking water guidelines (human health and aesthetic; WHO 2002);

• United Kingdom drinking water guidelines (human health and aesthetic; UKDWI 2002);

• The Ontario Ministry of Environment and Energy Guidelines for the protection of aquatic life (OMEE 2002);

• The British Columbia Ministry of Environment guidelines for the protection of aquatic life (MOEBC 1998); and


Golder Associates

• The Australian National Water Quality Management System Guidelines for the protection of aquatic life and human health (NWQMS 2000).

The guidelines from the above sources are summarized in Appendix II.

Figure 6.1 Approach for the Development of Effects-based Objectives

6.1.2 Aquatic Life Effects-based Thresholds

Chronic Effects Benchmark (CEB) effects-based thresholds were calculated based on Species Sensitivity Distributions (SSD) for EIAs (Imperial 2005; Shell 2005; Suncor 2005). Compiling the necessary toxicological data to develop additional CEB effects-based thresholds was beyond the scope of this study. The CEB effects-based thresholds approach is consistent with the recalculation procedure as defined by CCME (2003) and is based on the same approach used to develop Canadian water quality guidelines (CCME 1999).


Golder Associates

Where sufficient data were available (i.e., toxicity test results for at least five different species), SSDs (Posthuma et al. 2002) were used to derive a CEB, (expressed as a concentration). For constituents where less than five different species were available, the lowest recorded chronic toxicity test result was used to define the CEB. A more detailed description of the methods used to calculate CEB effects-based thresholds is provided in Appendix III.

CEBs were developed for 15 of 20 total metals constituents, 4 of 9 PAH groups and total phenolics (20 of 45 constituents considered under Task B). CEBs were not developed for major ions, nutrients, or naphthenic acids and are not relevant to whole-effluent toxicity parameters.

CEBs were developed using species relevant to conditions in the LAR and are therefore considered to be more accurate effects-based thresholds than existing or interjurisdictional guidelines. These CEBs thus replace all corresponding existing and interjurisdictional guidelines as effects-based objectives.

6.1.3 Health Risk-based Thresholds

Health risk-based thresholds were calculated for human and wildlife health based on the concentration at which no adverse health effects would be expected due to water ingestion. The constituents evaluated were those evaluated for the Kearl EIA (Imperial Oil, 2005), because that EIA contained the most recent health risk assessment.

These health risk-based thresholds were derived assuming that the water quality proportion of the overall exposure ratio (which includes inhalation, dermal, soil, food and water ingestion pathways) would have a maximum value of 0.2 (i.e., equal allocation to each of the pathways). This approach is consistent with the recalculation procedure outlined by CCME (2003) and is based on the protocol used for the derivation of Canadian Environmental Quality Guidelines (CCME 1999). A detailed description of the methods used to calculate health risk-based thresholds is provided in Appendix IV.

Health risk-based thresholds were developed for 19 of 20 total metals constituents, all 9 PAH groups and naphthenic acids (29 of 45 constituents considered under Task B). Health risk-based thresholds were not developed for major ions, nutrients, or total phenolics and are not relevant to whole-effluent toxicity parameters.


Golder Associates

As with aquatic life effects-based thresholds, health risk-based thresholds were developed specifically for conditions in the LAR and are considered to be preferable to existing or interjurisdictional guidelines for human and wildlife health. Therefore these thresholds were given preference over existing and interjurisdictional health guidelines.

6.2 RESULTS

6.2.1 Interjurisdictional Guidelines

Water quality guidelines from other jurisdictions that were considered for this study are compiled in Appendix II. Interjurisdictional guidelines were only considered where there was no existing guideline, as described in Section 3.2.

Table 6.1 provides interjurisdictional guidelines that were considered. The British Columbia chronic guidelines for the protection of aquatic life were considered for sulphate, lithium and potassium and the Australian chronic guideline was considered for xylenes. The guidelines for lithium, potassium and xylenes could not be evaluated against background conditions as these constituents were not included in ARM. The Ontario guideline for xylenes was not considered as it is a provisional guideline.

The British Columbia chronic aquatic life guideline for sulphate is based on three studies that found high toxicity (MOEBC 1998); however, the validity of the guideline is questionable. These studies were replicated by Davies et al. (2003) while controlling for a number of shortcomings of the original experiments. In moderately hard water, no effects were observed at concentrations well over 1,000 mg/L for the three species considered (larval striped bass, the aquatic moss F. antipyretica, and the amphipod H. azteca). In soft water, no observable effects concentrations were detected below 1000 mg/L. This guideline was considered inadequate based on screening criterion #2.

The WHO human health guidelines were considered for molybdenum and manganese, the United Kingdom aesthetic drinking water guideline was considered for ammonia and the Australian human health guideline was considered for sulphate. The guidelines for molybdenum, ammonium and sulphate were 10 times greater than the corresponding background concentration and therefore, although adequate based on a use protection strategy, fell under criterion #5 as described in Section 3.2.


Golder Associates

Table 6.1 Selected Interjurisdictional Guidelines

Constituent Units Background

Concentration(a) Guideline

Value Guideline Type Source Guidelines Relevant to Peak Conditions sulphate mg/L 96 50 2,3 chronic aquatic life MOEBC 1998 lithium mg/L - 0.096 chronic aquatic life MOEBC 1998 potassium mg/L - 373 chronic aquatic life MOEBC 1998 xylenes mg/L - 0.2 chronic aquatic life NWQMS 2000 Guidelines Relevant to Long-term Average Conditions

manganese mg/L 0.046 0.4 human health drinking water WHO 2002

molybdenum mg/L 0.0018 0.07 5 human health drinking water WHO 2002

ammonia mg/L 0.038 0.5 5 aesthetic drinking water UKDWI 2002

sulphate mg/L 29 500 5 human health drinking water NWQMS 2000

Note: Bold values fall into one or more of the screening criteria outlined in Section 3.2. Values in italics could not be screened as the constituent was not modeled.

1 Guideline is absent. 2 Guideline is inadequate as the method used to determine the guideline is not relevant to the LAR. 3 Guideline is inadequate as the guideline is below the maximum background concentration. 4 Guideline is inadequate as is does not account for other water quality constituents which effect the toxicity. 5 Guideline is more than ten times greater than the background concentration. (a) Background conditions were derived from the ARM model. The 99.91 percentile is shown when comparing to peak

conditions and the median is shown when comparing to long-term average conditions.

6.2.2 Aquatic Life Effects-based Thresholds

CEB effects-based thresholds are shown in Table 6.2.

Aquatic life effects-based thresholds that were developed for aluminum, beryllium, cadmium, chromium, copper, iron, manganese, silver, strontium and total phenolics were lower than the corresponding peak background concentrations in the LAR, and were therefore considered to be inadequate based on screening criterion #3.

Antimony, barium, boron, molybdenum and PAH group 9 all had CEB effects-based thresholds that were 10 times greater than the corresponding background concentration and therefore, although adequate based on a use protection strategy, fell under criterion #5 as described in Section 3.2.

The other CEB effects-based thresholds passed all of the screening criteria.


Golder Associates

Table 6.2 Aquatic Life Effects-based Thresholds

Constituent Units


Concentration(c) Existing Aquatic

Life Guideline CEB Effects-

based Threshold aluminum mg/L 21 0.1 3 0.68(a) 3 antimony mg/L 0.0075 LR 0.51(a) 5 arsenic mg/L 0.029 0.005 3 0.073(a) barium mg/L 0.15 LR 5.8(a) 5 beryllium mg/L 0.018 LR 0.0073(a) 3 boron mg/L 0.171 LR 5.4(a) 5 cadmium mg/L 0.031 0.00032 3 0.00032(a) 3 chromium mg/L 0.035 0.001 3 0.0025(b) 3 copper mg/L 0.029 0.003 3 0.0078(b) 3 iron mg/L 20 0.3 3 0.57(a) 3 manganese mg/L 0.97 LR 0.26(a) 3 molybdenum mg/L 0.0134 0.073 0.73(a) 5 silver mg/L 0.00078 0.0001 3 0.00017(a) 3 strontium mg/L 1.7 LR 0.2(a) 3 vanadium mg/L 0.045 LR 0.16(a) total phenolics mg/L 0.06 0.005 3 0.04(a) 3 PAH group 2 mg/L 0.034 0.018 3 0.18(a) PAH group 5 mg/L 0.025 0.012 3 0.12(a) PAH group 6 mg/L < LR 29(a) PAH group 9 mg/L 0.012 0.025 0.25(a) 5

Note: Bold values fall into one or more of the screening criteria outlined in Section 3.2. Values in italics could not be screened as the background concentration was below detection.

1 Guideline or effects-based threshold is absent. 2 Guideline or effects-based threshold is inadequate as the method used to determine the guideline is not relevant to

the LAR. 3 Guideline or effects-based threshold is inadequate as the guideline is below the maximum background

concentration. 4 Guideline or effects-based threshold is inadequate as is does not account for other water quality constituents which

effect the toxicity. 5 Guideline or effects-based threshold more than ten times greater than the background concentration. (a) Based on Suncor 2005. (b) Based on Imperial 2005. (c) Concentrations based on the maximum 99.91 percentile background concentration among the assessment nodes

derived from the ARM model. LR = Guideline or effects-based threshold is likely relevant. < Predicted background concentrations are below detection.

6.2.3 Health Risk-based Thresholds

Table 6.3 provides the human health risk-based thresholds and Table 6.4 provides the wildlife health risk-based thresholds.


Golder Associates

Table 6.3 Human Health Risk-based Thresholds

Constituent Units

Maximum (Among-Node) Long-term


Existing Human Health Guideline(b)

Human Health Risk-based Threshold(c)

Organics naphthenic acids mg/L 0.034 LR 0.3 Total Metals aluminum mg/L 0.36 LR 11 5 antimony mg/L 0.00067 0.0055 0.0022 arsenic - non-carcinogenic mg/L 0.00079 0.01 5 0.0017 - carcinogenic mg/L 0.00079 0.01 5 0.00026 3 barium mg/L 0.082 1 5 0.088 beryllium mg/L 0.00027 0.004 5 0.011 5 boron mg/L 0.039 5 5 0.06 cadmium mg/L 0.00050 0.005 0.0011 chromium mg/L 0.0031 0.05(e) 8 5 copper mg/L 0.0028 1.3 5 0.17 5 lead mg/L 0.0012 0.01 0.02 5 manganese mg/L 0.046 LR 0.39 mercury mg/L 0.000036 0.001 5 0.0017 5 molybdenum mg/L 0.0018 LR 0.028 5 nickel mg/L 0.0061 0.34 5 0.007 selenium mg/L 0.00018 0.01 5 0.028 5 silver mg/L 0.000058 LR 0.028 5 strontium mg/L 0.27 LR 3.3 5 vanadium mg/L 0.0022 LR 0.017 zinc mg/L 0.015 5.1 5 2 5 PAH Groups PAH group 1 µg/L < 0.0029 0.69 PAH group 2 µg/L < 0.0029 0.069 PAH group 3 µg/L < 0.0029 0.069 PAH group 4 µg/L < 330 330 PAH group 5 µg/L < 6300 1700 PAH group 6 µg/L < LR 280 PAH group 7 µg/L 0.0037 50 5 220 5 PAH group 8 µg/L 0.0050 LR 110 5 PAH group 9 µg/L < 630 165





effect the toxicity. 5 Guideline or effects-based threshold is more than ten times greater than the background concentration. (a) Concentrations based on the maximum median background concentration among the assessment nodes derived

from the ARM model. (b) Based on the more conservative guideline of: USEPA (2002) using fish consumption rate of 45 g/d (Richardson

1997), USEPA (1999) primary drinking water objectives and Health Canada (2006) health based drinking water objectives.

(c) Based on the more conservative of the toddler and adult human health risk-based threshold (Appendix IV). LR = Guideline or effects-based threshold is likely relevant. < Predicted background concentrations are below detection.


Golder Associates

Table 6.4 Wildlife Health Risk-based Thresholds

Constituent Units

Maximum (Among-Node) Long-term


Existing Wildlife Health Guideline(b)

Wildlife Health Risk-based Threshold(c)

Organics naphthenic acids mg/L 0.034 LR 39 5 Total Metals aluminum mg/L 0.36 5 5 11 5 antimony mg/L 0.00067 LR 0.7 5 arsenic mg/L 0.00079 0.025 5 0.71 5 barium mg/L 0.082 LR 34 5 beryllium mg/L 0.00027 0.1 5 4.3 5 boron mg/L 0.039 5 5 180 5 cadmium mg/L 0.0005 0.08 5 6.5 5 chromium mg/L 0.0031 0.05(e) 720 5 copper mg/L 0.0028 0.5 5 4.1 5 lead mg/L 0.0012 0.1 5 52 5 manganese mg/L 0.046 LR 570 5 mercury mg/L 0.000036 0.003 5 7 5 molybdenum mg/L 0.0018 0.5 5 1.5 5 nickel mg/L 0.0061 1 5 260 5 selenium mg/L 0.00018 0.05 5 1.3 5 silver mg/L 0.000058 LR 0.008 5 strontium mg/L 0.27 LR 1700 5 vanadium mg/L 0.0022 0.1 5 1.3 5 zinc mg/L 0.015 50 5 170 5 PAH Groups PAH group 1 µg/L < LR 5600 PAH group 2 µg/L < LR 56000 PAH group 3 µg/L < LR 560000 PAH group 4 µg/L < LR 33000 PAH group 5 µg/L < LR 190000 PAH group 6 µg/L < LR 28000 PAH group 7 µg/L 0.0037 LR 24000 5 PAH group 8 µg/L 0.005 LR 16000 5 PAH group 9 µg/L < LR 14000





effect the toxicity. 5 Guideline or effects-based threshold is more than ten times greater than the background concentration. (a) Concentrations based on the maximum median background concentration among the assessment nodes derived

from the ARM model. (b) CCME (1999) livestock watering guidelines. (c) Based on the more conservative of the mammalian and avian health risk-based threshold (Appendix IV). LR = Guideline or effects-based threshold is likely relevant. < Predicted background concentrations are below detection.


Golder Associates

The only health risk-based threshold that was below the long-term average background concentration in the LAR was the human health risk-based threshold for arsenic. Thus, this threshold was subject to screening criterion #3 and was not adequate. The validity of the arsenic health risk-based threshold is questionable because the oral slope factor may be overly conservative. Therefore, this threshold was also considered inadequate based on screening criterion #2.

Many of the health risk-based thresholds were over ten times greater than the median background concentration in the LAR. This was the case for all of the wildlife health risk-based thresholds. It was also the case for the human health risk-based thresholds for aluminum, beryllium, chromium, copper, lead, mercury, molybdenum, selenium, silver, strontium, zinc and PAH Groups 7 and 8. These constituents, although adequate based on a use protection strategy, fell under criterion #5 as described in Section 3.2.

The wildlife health risk-based thresholds were greater than the human health risk-based thresholds for all constituents evaluated with the exception of aluminum, which had the same threshold for both human and wildlife health, and silver, which had a lower threshold for wildlife health. Therefore, human health risk-based thresholds will be protective of wildlife health for all constituents except silver.

6.3 SUMMARY OF EFFECTS-BASED OBJECTIVES

Effects-based objectives are summarized in Tables 6.5 and 6.6. Existing guidelines are also shown in this table. The adequacy of the effects-based objectives based on the screening approach is provided. Although Table 6.5 contains both guidelines and effects-based thresholds, they are collectively referred to as effects-based objectives, even though it is recognized that guidelines typically include safety factors that make them more conservative and thus less accurate than effects-based thresholds.

Aquatic life effects-based objectives for total dissolved solids, dissolved organic carbon, calcium, magnesium, sodium, sulphate, naphthenic acids and PAH group 3 were not developed although the first five of these were classified as LNR (likely not relevant). Aquatic life effects-based objectives were also not developed for the “Task C” constituents, including dibenzothiophene, alkyl-substituted dibenzothiophene, MIBC, acrylamide, oil and grease, total petroleum hydrocarbons, lithium and potassium.


Golder Associates

Table 6.5 Screening of Effects-based Objectives Relevant to the Long Term Average (Median) Effects-based Objectives (Existing & Interjurisdictional Guidelines, CEB &

Health Risk-based Thresholds) Effects-based Objective Sources

Constituent Units


Average Background

Concentration(d)


Human Health(a)

Wildlife Health(b)


Human Health(a)

Wildlife Health(b)

Major Ions calcium mg/L 37 LR LNR 1000 5 - CCME 1999chloride mg/L 27 250 LNR LNR HC 2006 - - magnesium mg/L 10 LR LNR LNR - - - sodium mg/L 22 200 LNR LNR HC 2006 - - sulphate mg/L 29 500 5 500 5 1000 5 HC 2006 NWQMS 2000 CCME 1999sulphide mg/L 0.004 0.05 5 LNR LNR HC 2006 - - total dissolved solids mg/L 200 500 LNR 3000 5 HC 2006 - CCME 1999Nutrients ammonia mg/L 0.038 0.5 LNR LNR UKDWI 2002 - - total nitrogen mg/L 0.77 LNR LNR LNR - US EPA 1999 CCME 1999total phosphorus mg/L 0.064 LNR LNR LNR - - - dissolved organic carbon mg/L 10 LNR LNR LNR - - - Whole-effluent Constituents acute toxicity TUa < NR NR NR - - - chronic toxicity TUc < NR NR NR - - - fish tainting TPU < 1(g) NR NR Golder 2004c - - General Organics naphthenic acids mg/L 0.03 LNR 0.33 5 39 5 - Appendix IV Appendix IVtotal phenolics mg/L 0.0038 LNR LR 0.002(f) 3 - - CCME 1999Total Metals aluminum mg/L 0.36 LNR 11 5 11 5 - Appendix IV Appendix IVantimony mg/L 0.00067 LNR 0.0022 0.7 5 - Appendix IV Appendix IVarsenic mg/L 0.00079 LNR 0.01 (h) 5 0.71 5 - Appendix IV Appendix IVbarium mg/L 0.082 LNR 0.088 34 5 - Appendix IV Appendix IVberyllium mg/L 0.00027 LNR 0.011 5 4.3 5 - Appendix IV Appendix IVboron mg/L 0.039 LNR 0.055 180 5 - Appendix IV Appendix IVcadmium mg/L 0.0005 LNR 0.0011 6.5 5 - Appendix IV Appendix IVchromium mg/L 0.0031 LNR 8.25 5 720 5 - Appendix IV Appendix IV


Table 6.5 Screening of Effects Thresholds Relevant to the Long Term Average (Median) (continued)

Golder Associates

Effects-based Objectives (Existing & Interjurisdictional Guidelines, CEB &


Constituent Units


Average Background

Concentration(d)


Human Health(a)

Wildlife Health(b)


Human Health(a)

Wildlife Health(b)

copper mg/L 0.0028 1 5 0.165 5 4.1 5 HC 2006 Appendix IV Appendix IViron mg/L 1.0 0.3 3 0.3 3 X HC 2006 US EPA 2002 - lead mg/L 0.0012 LNR 0.02 5 52 5 - Appendix IV Appendix IVmanganese mg/L 0.046 0.05 0.39 570 5 HC 2006 Appendix IV Appendix IVmercury mg/L 0.000036 LNR 0.0017 5 7 5 - Appendix IV Appendix IVmolybdenum mg/L 0.0018 LNR 0.028 5 1.5 5 - Appendix IV Appendix IVnickel mg/L 0.0061 LNR 0.0072 260 5 - Appendix IV Appendix IVselenium mg/L 0.00018 LNR 0.028 5 1.3 5 - Appendix IV Appendix IVsilver mg/L 0.000058 0.1 5 0.028 5 0.008 5 US EPA 1992 Appendix IV Appendix IVstrontium mg/L 0.27 LNR 3.3 5 1700 5 - Appendix IV Appendix IVvanadium mg/L 0.0022 LNR 0.017 1.3 5 - Appendix IV Appendix IVzinc mg/L 0.015 5 5 1.7 5 170 5 HC 2006 Appendix IV Appendix IVPAH Groups PAH group 1 µg/L < LNR 0.69 5600 - Appendix IV Appendix IVPAH group 2 (including benzo(a)anthracene) µg/L < LNR 0.069 56000 - Appendix IV Appendix IV

PAH group 3 µg/L < LNR 0.069 560000 - Appendix IV Appendix IVPAH group 4 (including acenaphthene and acenaphthylene µg/L < LNR 330 33000 - Appendix IV Appendix IV

PAH group 5 (including anthracene and phenanthrene) µg/L < LNR 1700 190000 - Appendix IV Appendix IV

PAH group 6 (including biphenyl and alkyl substituted biphenyl) µg/L < LNR 280 28000 - Appendix IV Appendix IV

PAH group 7 (including fluorene and fluoranthene) µg/L 0.0037 LNR 220 5 24000 5 - Appendix IV Appendix IV

PAH group 8 (including Naphthalene) µg/L 0.0050 LNR 110 5 16000 5 - Appendix IV Appendix IV

PAH group 9 (including pyrene) µg/L < LNR 170 14000 - Appendix IV Appendix IV“Task C” Constituents dibenzothiophene µg/L na LNR LNR LNR - - -


Table 6.5 Screening of Effects Thresholds Relevant to the Long Term Average (Median) (continued)

Golder Associates

Effects-based Objectives (Existing & Interjurisdictional Guidelines, CEB &


Constituent Units


Average Background

Concentration(d)


Human Health(a)

Wildlife Health(b)


Human Health(a)

Wildlife Health(b)

alkyl-substituted dibenzothiophene µg/L na LNR LNR LNR - - - di (2-ethylhexyl) phthalate (DEHP) µg/L na LNR 6 LNR - US EPA 2002 - methyl isobutyl carbinol (MIBC) µg/L na LNR LNR LNR - - - acrylamide µg/L na LNR 0 LNR - US EPA 1999 - oil and grease mg/L na LNR LNR LNR - - - total petroleum hydrocarbons mg/L na LNR LNR LNR - - - toluene mg/L na 0.024 1 0.024 HC 2006 US EPA 1999 CCME 1999xylenes mg/L na 0.3 0.01 LNR HC 2006 US EPA 1999 - dissolved oxygen mg/L na LNR LNR LNR - - - lithium mg/L na LNR LR LR - - - fluoride mg/L na 2 1.5 2 US EPA 1992 HC 2006 CCME 1999potassium mg/L na LNR LR LR - - - Note: Bold values fall into one or more of the screening criteria outlined in Section 3.2. Italicized values indicate that no evaluation was possible either because constituent was not

modeled or median background concentration was below detection. 1 Effects-based objective is absent. 2 Effects-based objective is inadequate as the method used to determine the guideline is not relevant to the LAR. 3 Effects-based objective is inadequate as the guideline is below the maximum background concentration. 4 Effects-based objective is inadequate as is does not account for other water quality constituents which effect the toxicity. 5 Effects-based objective is more than ten times greater than the background concentration. (a) Based on either the health risk-based threshold developed in this study, or the more conservative guideline of: USEPA (2002) using fish consumption rate of 45 g/d (Richardson

1997), USEPA (1999) primary drinking water objectives and Health Canada (2006) health based drinking water objectives. (b) Based on either the health risk-based threshold developed in this study, or CCME (1999) livestock watering guidelines. (c) Based on the more conservative of Health Canada (2006) aesthetic objectives and USEPA (1992) secondary drinking water objectives. (d) Concentrations based on the maximum median background concentration among the assessment nodes derived from the ARM model. (e) Chromium III guideline. (f) Guideline for phenols. (g) The fish tainting threshold is aesthetic, but applies to fish tissue quality not drinking water. Guideline from Golder 2004c. (h) Human health risk-based threshold was developed for arsenic but was not used. < Predicted background concentrations are below detection. na = not determined as constituent is not in ARM model. NR = Effects-based objective is not relevant, LNR = Effects-based objective is likely not relevant, LR = Effects-based objective is likely relevant. - = Either no guideline or no data.


Golder Associates

Table 6.6 Screening of Effects-based Objectives Relevant to the Peak Concentration (99.91 Percentile) Effects-based Objectives (Existing & Interjurisdictional Guidelines, CEB & Health Risk-based Thresholds) Effects-based Objectives Sources

Constituent Units


Concentration(d) Chronic Aquatic

Life (b,c) Aesthetic

Drinking Water(a) Chronic

Aquatic Life(b,c) Aesthetic

Drinking Water(a) Major Ions calcium mg/L 77 LNR LR - chloride mg/L 97 230 250 US EPA 2002 HC 2006 magnesium mg/L 21 LNR LR - - sodium mg/L 74 LNR 200 - HC 2006 sulphate mg/L 96 LR(j) 500 MOEBC 1998 HC 2006 sulphide mg/L 0.031 0.014(h) 3 0.05 US EPA 2002 HC 2006 total dissolved solids mg/L 400 LNR 500 - HC 2006 Nutrients ammonia mg/L 0.35 2.4(e) 0.5 US EPA 2002 UKDWI 2002 total nitrogen mg/L 4.4 1 3 LNR AENV 1999 - total phosphorus mg/L 1.5 0.05 3 LNR AENV 1999 - dissolved organic carbon mg/L 43 LNR LNR - - Whole-effluent Constituents acute toxicity TUa < NR NR - - chronic toxicity TUc < 1(i) NR US EPA 1991 - fish tainting TPU < NR 1(g) - Golder 2004c General Organics naphthenic acids mg/L 0.63 LR LNR - - total phenolics mg/L 0.060 0.005(j) 3 LNR AENV 1999 - Total Metals aluminum mg/L 21 0.68 3 LNR Appendix III - antimony mg/L 0.0075 0.51 5 LNR Appendix III - arsenic mg/L 0.029 0.073 LNR Appendix III - barium mg/L 0.15 5.8 5 LNR Appendix III - beryllium mg/L 0.018 0.0073 3 LNR Appendix III - boron mg/L 0.17 5.4 5 LNR Appendix III - cadmium mg/L 0.031 0.00032(f) 3 LNR Appendix III - chromium mg/L 0.035 0.0025 3 LNR Appendix III - copper mg/L 0.029 0.0078 3 1 5 Appendix III HC 2006 iron mg/L 20 0.57 3 0.3 3 Appendix III HC 2006


Table 6.6 Screening of Effects Thresholds Relevant to the Peak Concentration (99.91 Percentile) (continued)

Golder Associates

Effects-based Objectives (Existing & Interjurisdictional Guidelines, CEB & Health Risk-based Thresholds) Effects-based Objectives Sources

Constituent Units






Drinking Water(a) lead mg/L 0.0095 0.004(f) 3 LNR CCME 1999 - manganese mg/L 0.97 0.26 3 0.05 3 Appendix III HC 2006 mercury mg/L 0.0001 0.000005 3 LNR AENV 1999 - molybdenum mg/L 0.013 0.73 5 LNR Appendix III - nickel mg/L 0.045 0.062(f) LNR US EPA - selenium mg/L 0.0021 0.001 3 LNR CCME 1999 - silver mg/L 0.00078 0.00017 3 0.1 5 Appendix III US EPA 1992 strontium mg/L 1.7 0.2 3 LNR Appendix III - vanadium mg/L 0.045 0.16 LNR Appendix III - zinc mg/L 0.12 0.03 3 5 5 CCME 1999 HC 2006 PAH Groups PAH group 1 µg/L < 0.015 LNR CCME 1999 - PAH group 2 (including benzo(a)anthracene) µg/L 0.034 0.18 LNR Appendix III -

PAH group 3 µg/L 0.016 LR LNR - - PAH group 4 (including acenaphthene and acenaphthylene µg/L < 5.8 LNR CCME 1999 -

PAH group 5 (including anthracene and phenanthrene) µg/L 0.025 0.12 LNR Appendix III -

PAH group 6 (including biphenyl and alkyl substituted biphenyl) µg/L < 29 LNR Appendix III -

PAH group 7 (including fluorene and fluoranthene) µg/L 0.94 0.04 3 LNR CCME 1999 -

PAH group 8 (including Naphthalene) µg/L 0.90 1.1 LNR CCME 1999 - PAH group 9 (including pyrene) µg/L 0.012 0.25 LNR Appendix III - ”Task C” Constituents dibenzothiophene µg/L na LNR LNR - - alkyl-substituted dibenzothiophene µg/L na LNR LNR - - di (2-ethylhexyl) phthalate (DEHP) µg/L na 16 LNR CCME 1999 - methyl isobutyl carbinol (MIBC) µg/L na LNR LNR - - acrylamide µg/L na LNR LNR - -


Table 6.6 Screening of Effects Thresholds Relevant to the Peak Concentration (99.91 Percentile) (continued)

Golder Associates

Effects-based Objectives (Existing & Interjurisdictional Guidelines, CEB & Health Risk-based Thresholds) Effects-based Objectives Sources

Constituent Units






Drinking Water(a) oil and grease mg/L na LNR LNR - - total petroleum hydrocarbons mg/L na LNR LNR - - toluene mg/L na 0.002 0.024 CCME 1999 HC 2006 xylenes mg/L na 0.2 0.3 NWQMS 2000 HC 2006 dissolved oxygen mg/L na 6.5 LNR AENV 1999 - lithium mg/L na 0.096 LNR MOEBC 1998 - fluoride mg/L na 0.12 2 CCME 1999 US EPA 1992 potassium mg/L na 373 LNR MOEBC 1998 -

Note: Bold values fall into one or more of the screening criteria outlined in Section 3.2. Italicized values indicate that no evaluation was possible either because constituent was not modeled or median background concentration was below detection.

1 Effects-based objective is absent. 2 Effects-based objective is inadequate as the method used to determine the guideline is not relevant to the LAR. 3 Effects-based objective is inadequate as the guideline is below the maximum background concentration. 4 Effects-based objective is inadequate as is does not account for other water quality constituents which effect the toxicity. 5 Effects-based objective is more than ten times greater than the background concentration. (a) Based on the more conservative of Health Canada (2006) aesthetic objectives and USEPA (1992) secondary drinking water objectives. (b) Based on the more conservative guidelines for the protection of aquatic life of US EPA (2002), CCME (1999) and AENV (1999). (c) 7-day mean. (d) Concentrations based on the maximum 99.91 percentile background concentration among the assessment nodes derived from the ARM model. (e) Guidelines are pH (acute and chronic) and/or temperature (chronic) dependent; values shown here correspond to a pH of 8 and temperature of 5 °C, respectively; these

guidelines were altered based on site-specific median conditions using methods described in AENV (1999) and U.S.EPA (1999, 2002). (f) Guidelines are hardness dependent; values shown here are based on a hardness of 125 mg/L; these guidelines were altered based on site-specific hardness levels using the

methods described in AENV (1999) and U.S. EPA (2002). (g) Guideline for phenols. (h) The fish tainting threshold is aesthetic, but applies to fish tissue quality not drinking water. Guideline from Golder 2004c. (i) Toxicity guideline taken from US EPA (1991). (j) Interjurisdictional guidelines for sulphate was identified, but was not used. NR = Effects-based objective is not relevant, LNR = Effects-based objective is likely not relevant, LR = Effects-based objective is likely relevant. < Predicted background concentrations are below detection. na = not determined as constituent was not in ARM model. - = No guideline.


Golder Associates

Human health effects-based objectives for dissolved organic carbon, total dissolved solids, calcium, chloride, magnesium, sodium, sulphate, and ammonia were not developed. These constituents were classified as LNR (likely not relevant). Health effects-based objectives were also not developed for the “Task C” constituents including dibenzothiophene, alkyl-substituted dibenzothiophene, MIBC, acrylamide, oil and grease, total petroleum hydrocarbons, toluene, xylenes, lithium and potassium.

Any constituent which did not have and effects-based objective is discussed in Appendix IX. Recommendations for the development of objectives not within the scope of this study are provided in Section 9.4.

The results of the screening analysis for criteria #3 had the potential to be influenced by seasonal dependency. To test the degree of dependency, the screening analysis was also conducted on a seasonal basis (although the results of the analysis are not included in this report). The results of the analysis were similar to the non-seasonally adjusted analysis with the following exceptions:

• the CEB effects-based threshold for aluminum was above the 99.91 percentile background concentration in the winter and therefore would be adequate based on criterion #3 for the winter only;

• the CEB effects-based threshold for beryllium was above the 99.91 percentile background concentration in the spring and fall and therefore would be adequate based on criterion #3 for the spring and fall only;

• the human health risk-based threshold for barium was below the long-term average background concentrations in the winter and therefore would be inadequate based on criterion #3 for the winter only;

• the human health risk-based threshold for nickel was above the long-term average concentration in spring and summer and therefore would be inadequate based on criterion #3 for spring and summer only; and

• the aesthetic guideline for manganese was above the long-term average concentration in spring and summer and therefore would be inadequate based on criterion #3 for spring and summer only.

Therefore, effects-based objectives for these constituents are only intended to be applied during the designated seasons. During other parts of the year background-based benchmarks should be considered as the appropriate management targets to apply to those constituents.

Aquatic life effects-based objectives were below background concentrations (inadequate based on criterion #3) for many metals. The dissolved fraction of metals can be significantly less than the total concentrations as shown in the


Golder Associates

CEMA study (CEMA 2003). In terms of toxicity, the dissolved fraction is more relevant than total metals. CCME and Alberta guidelines for metals are formulated as total metals while US EPA guidelines are formulated as dissolved metals and are converted to total metals. The U.S. EPA is in the process of updating guidelines for metals based on the biotic ligand model (BLM; Niyogi and Wood 2004). The updated copper guideline is currently available (U.S. EPA 2007), but has not been adopted as an effects-based objective at this time because this was not in the scope of study and the basis for this guideline must first be examined for applicability to the LAR. Notwithstanding the need to review any updated BLMs, use of objectives for dissolved metals based on the BLM is appropriate for the LAR.

As described in the notice of availability for the updated copper guideline, the BLM is a metal bioavailability model based on recent information about the chemical behaviour and physiological effects of metals in aquatic environments. Earlier freshwater aquatic life criteria for copper published by the Agency were based on empirical relationships of toxicity to water hardness. That is, a relationship was established linking the criteria concentrations with water hardness. These hardness-dependent criteria, however, represent combined effects of different water quality variables (such as pH and alkalinity) correlated with hardness. Unlike the empirically derived hardness-dependent criteria, the BLM explicitly accounts for individual water quality variables and addresses variables that EPA had not previously factored into the hardness relationship. Where the previous freshwater aquatic life criteria were hardness-dependent, these revised criteria are dependent on a number of water quality parameters (e.g., calcium, magnesium, dissolved organic carbon). BLM-based criteria can be more stringent than the current hardness-based copper criteria and in certain cases the current hardness-based copper criteria may be overly stringent for particular waterbodies.


Golder Associates

7 BACKGROUND-BASED BENCHMARKS

7.1 INTRODUCTION

The background concentration procedure proposed by CCME (2003) was used to develop background-based benchmarks for comparison to effects-based objectives, where available, or for potential use where no adequate effects-based objectives were available.

Benchmarks based on background concentrations differ from effects-based objectives in that they are focused on limiting changes in water quality and therefore, in many cases, they are more conservative than effects-based objectives. The background concentration procedure is considered to be a non-effects-based, conservative approach to development of management objectives and is based on the antidegradation premise that surface water systems with superior water quality (i.e., relative to guidelines) should not be degraded. The approach is directly applicable to waters of national or regional significance. Background-based benchmarks should reflect protection of current designated water uses.

Many of the effects-based objectives provided in Section 6 were inadequate based on screening criterion #3 because they were below the relevant (long-term average or peak) background concentrations. Under these circumstances, it is recommended that background-based benchmarks be used as objectives until or unless appropriate effects-based objectives can be derived.

In other cases, the effects-based objectives were subject to screening criterion #5 because they were greater than 10 times the relevant background concentration in the LAR. Under these circumstances background-based benchmarks can be used as management targets.

Effects-based objectives could not be developed for some constituents within the current scope of work. Under these circumstances, background-based benchmarks can also be used as management targets, until such time as appropriate effects-based objectives can be derived.

7.2 PROCEDURE

Site-specific objectives based on background concentrations can be developed in a number of ways according to CCME (2003). Objectives can be based on the upper limit of background concentrations (e.g., 90th percentile) or on an increment above background concentrations (e.g., 20%).


Golder Associates

For the LAR, background-based benchmarks were established at an incremental increase of 20% above background concentrations. This incremental increase can be applied to any percentile to derive the benchmark for that percentile.

Changes in constituent concentrations less than 20% from background conditions are considered acceptable (MOEBC 1996) because:

• the precision for measurement of low concentration metals in replicate samples is not usually better than 20% under ideal situations in the laboratory; and

• natural variability is often greater than 20%.

Two background-based benchmarks were established, one corresponding to the long-term average background concentration as represented by the median background concentration and a peak background concentration as represented by the 99.91 percentile. In each case, a background-based benchmark was set at 20% above the predicted background concentration. Background concentrations were calculated for each of the five assessment nodes and background-based benchmarks were then set at 20% above these concentrations.

Background-based benchmarks that are below effects-based objectives are considered to be conservatively protective of water uses for the LAR. The background-based benchmarks that exceed effects-based objectives are not explicitly protective of current designated water uses. However, as background-based benchmarks essentially reflect background water quality conditions, compliance with the benchmarks is not expected to result in measurable effects. Thus they should reflect preservation of current designated water uses. Both the median and peak background-based benchmarks must be considered together as it is possible to have an acceptably small shift in median concentrations that result from an unacceptable shift in peak concentrations.

A schematic of the screening approach for background-based benchmarks is provided in Figure 7.1.


Golder Associates

Figure 7.1 Schematic for Screening Background-based Benchmarks

7.3 RESULTS

Background-based benchmarks are unique to each assessment node as are background constituent concentrations. The maximum background-based benchmark among the five assessment nodes was used to represent the overall background-based benchmark. Node-specific benchmarks were used in Section 8 for comparison to investigation levels. The predicted median and 99.91 percentile background concentrations and corresponding background-based benchmarks for each node in the LAR are provided in Appendix VII. The maximum benchmarks for the five nodes are provided in Table 7.1. Benchmarks could not be developed for constituents whose background concentrations were below detection as was the case for both chronic and acute toxicity, fish tainting and PAH groups 1, 2, 3, 4, 5, 6 and 9.


Golder Associates

Table 7.1 Background-based Benchmarks

Background-based Benchmark(a)

Constituent Units

Long-term Average (based

on median)

Peak (based on the 99.91

percentile)

Minimum Health Effects-based

Objective

Chronic Aquatic Life Effects-based

Objective Aesthetic Drinking

Water Guideline

Major Ions

calcium mg/L 44 92 LNR LNR LR

chloride mg/L 32 116 LNR 230 250 magnesium mg/L 12 25 LNR LNR LR

sodium mg/L 26 89 LNR LNR 200 sulphate mg/L 35 115 500 5 LR 500 5 sulphide mg/L 0.0048 0.037 LNR 0.0143 0.05 5 total dissolved solids mg/L 240 480 LNR LNR 500

Nutrients

ammonia mg/L 0.046 0.42 LNR 2.4 0.5 total nitrogen mg/L 0.92 5 LNR 1 3 LNR total phosphorus mg/L 0.077 1.8 LNR 0.05 3 LNR dissolved organic carbon mg/L 12 52 LNR LNR LNR Whole-effluent Constituents

acute toxicity TUa - - NR NR NR chronic toxicity TUc - - NR 1(i) NR fish tainting TPU - - NR NR 1(g)

General Organics

naphthenic acids mg/L 0.041 0.76 0.33 5 LR LNR total phenolics mg/L 0.0046 0.072 0.005(j) 3 0.005(j) 3 LNR Total Metals

aluminum mg/L 0.43 25 11 5 0.68 3 LNR antimony mg/L 0.00080 0.0090 0.0022 0.51 5 LNR arsenic mg/L 0.00095 0.034 0.01 5 0.073 LNR


Table 7.1 Background-based Benchmarks (continued)

Golder Associates


Constituent Units


on median)


percentile)


Objective



Water Guideline

barium mg/L 0.098 0.18 0.088 5.8 5 LNR beryllium mg/L 0.00032 0.021 0.011 5 0.0073 3 LNR boron mg/L 0.047 0.21 0.055 5.4 5 LNR cadmium mg/L 0.00060 0.038 0.0011 0.00032 3 LNR chromium mg/L 0.0037 0.042 8.25 5 0.0025 3 LNR copper mg/L 0.0034 0.035 0.165 5 0.0078 3 1 5 iron mg/L 1.2 24 0.3 3 0.57 3 0.3 3 lead mg/L 0.0014 0.011 0.02 5 0.0043 LNR manganese mg/L 0.055 1.2 0.39 0.26 3 0.05 mercury mg/L 0.000043 0.00012 0.0017 5 0.000005 3 LNR molybdenum mg/L 0.0022 0.016 0.028 5 0.73 5 LNR nickel mg/L 0.0073 0.054 0.0072 0.062 LNR selenium mg/L 0.00022 0.0025 0.028 5 0.001 3 LNR silver mg/L 0.000070 0.00094 0.005 5 0.00017 3 0.1 5 strontium mg/L 0.32 2.0 3.3 5 0.2 3 LNR vanadium mg/L 0.0026 0.054 0.017 0.16 LNR zinc mg/L 0.018 0.15 1.7 5 0.03 3 5 5

PAH Groups

PAH group 1 µg/L - - 0.69 0.015 LNR PAH group 2 µg/L - 0.041 0.069 0.18 LNR PAH group 3 µg/L - 0.019 0.069 LR LNR PAH group 4 µg/L - - 330 5.8 LNR PAH group 5 µg/L - 0.030 1700 0.12 LNR PAH group 6 µg/L - - 280 29 LNR


Table 7.1 Background-based Benchmarks (continued)

Golder Associates


Constituent Units


on median)


percentile)


Objective



Water Guideline

PAH group 7 µg/L 0.0044 1.1 220 5 0.04 3 LNR PAH group 8 µg/L 0.0060 1.1 110 5 1.1 LNR PAH group 9 µg/L - 0.015 170 0.25 LNR Note: Bold values fall into one or more of the screening criteria outlined in Section 3.2. Italicized values indicate that no evaluation was possible because the background

concentration was below detection. Shaded values indicate background-based benchmarks that may be appropriate as RSWQOs because the corresponding effects-based threshold is inadequate based on criterion #3.

1 Effects-based objective is absent. 2 Effects-based objective is inadequate as the method used to determine the guideline is not relevant to the LAR. 3 Effects-based objective is inadequate as the guideline is below the maximum background concentration. 4 Effects-based objective is inadequate as is does not account for other water quality constituents which effect the toxicity. 5 Effects-based objective is more than ten times greater than the background concentration. (a) Benchmarks are set at twenty percent greater than background concentrations. NR = Effects-based objective is not relevant, LNR = Effects-based objective is likely not relevant, LR = Effects-based objective is likely relevant.


Golder Associates

The health effects-based objectives are the relevant objectives for comparison to long-term average background-based benchmarks. Only the health effects-based objectives for iron and total phenolics were below the background concentration (Table 7.1). Thus, these are the only constituents for which the background-based benchmark may be an appropriate surrogate for a health effects-based objective.

The peak background-based benchmarks were compared to the aquatic life effects-based objectives. These background-based benchmarks were higher than the aquatic life effects-based objectives for sulphide, total nitrogen, total phosphorus, total phenolics, aluminum, beryllium, cadmium, copper, iron, lead, manganese, mercury, selenium, silver, strontium, zinc and PAH Group 7.

The peak background-based benchmarks and corresponding background concentrations exceeded the aesthetic drinking water guidelines for iron and manganese.


Golder Associates

8 INVESTIGATIONS LEVELS

8.1 INTRODUCTION

Investigation levels were proposed as management-based objectives for the Muskeg River Watershed (CEMA 2005). These investigation levels represent predicted water quality constituent concentrations for several future time snapshots at several locations in the Muskeg River Watershed based on predicted loadings from existing, approved and planned developments.

Investigation levels are dynamic and unique for each constituent, location, and time period consistent with continually changing operations in a watershed. They are based on model predictions that are indicative of developments functioning as planned in EIAs. Because these levels are consistent with those predicted in recent oil sands EIAs for which acceptability has been assessed, they are considered to be protective of the aquatic ecosystem. Aquatic ecosystem protection was demonstrated in these EIAs through compliance with effects-based thresholds and guidelines. Indeed, as will be demonstrated in this section, these investigation levels are more stringent than most of the other objectives developed in this study. However, they are management- and not effects-based objectives.

There would be a number of benefits to using investigation levels for the LAR:

• Investigation levels specify levels (percentiles) for water quality constituents that are unique for the monitoring location (node) and time period (snapshot) in question. Different stages of development occur at different locations and the sequence of these activities will influence the quantity and quality of the water. Simple compliance with an effects-based threshold will not indicate whether mitigation systems are functioning for that location and time period, and may not guarantee future compliance with that effects-based threshold.

• Because investigation levels must be set below effects-based thresholds, and because the levels are related to staged basin development, investigation levels will enable effective impact prevention by providing adequate time to investigate and respond to monitored results.

• Investigation levels provide a functional basis for determining cause and effect relationships for changes in water quality thus enabling appropriate source control to be implemented if necessary.

• Investigation levels provide a basis for continued focus and refinement in conjunction with new developments, evolving mine plans, and refined modelling assumptions, calibrations and validations.


Golder Associates

The ARM was used to predict concentrations in the LAR for 45 constituents at five assessment nodes from Fort McMurray to Embarras for, existing, approved and planned developments.

8.2 INVESTIGATION LEVELS INTERFACE MODEL

The ARM investigation levels interface model (ILIM) provides a graphical summary of the model output. Model output is generated by selecting the appropriate scenarios (snapshot and node) in the chosen form. Two investigation levels forms are provided.

8.2.1 Source Load Identification and Constituent Ranking Form

The Source Loads Identification and the Constituent Ranking Forms allow the user to examine the source loadings for all constituents simultaneously (Figure 8.1) for a specified node and snapshot. Information is provided through both a stacked bar plot displaying the source constituent concentrations and a table showing the total concentration for each constituent and the fraction of the constituent concentration originating from each of the designated sources. The form also includes a constituent ranking component that shows investigation levels corresponding to user-selected percentiles as well as corresponding background-based benchmarks, guidelines, effects-based objectives, statistical significance and constituent ranking.

To determine the loading contributions from each source, ARM was configured with the various sources sequentially turned on. The following is a list of the different sources considered:

• Athabasca River inflow (background; BG);

• natural tributaries (i.e., tributaries that don’t receive mine related waters; NG);

• sewage inputs direct to the LAR (SEW);

• muskeg overburden/dewatering direct to the LAR (MO/D);

• surface drainage/aquifers direct to the LAR (SD);

• basal seepages direct to the LAR (BS);

• the Muskeg River (MR);

• pit lake inputs direct to the LAR (PL);


Golder Associates

• mine-affected seepages direct to the LAR (MAS); and

• mine-affected tributaries (i.e., tributaries that receive mine related waters; MAT).

Figure 8.1 Source Load Identification Form


Golder Associates

That concentration of the constituent originating from each of the sources can then be calculated as follows:

• C(BG) = 99.91th percentile of background

• C(NT) = 99.91th percentile of NT - C(BG)

• C(SEW) = 99.91th percentile of SEW - C(BG) - C(NT)

• C(MO) = 99.91th percentile of MO - C(BG) - C(PT) - C(SEW)

• and so on until all of the sources categories are included.

Where:

• concentration = C

• background = BG

• natural tributaries = NT

• sewage inputs = SEW

• muskeg/overburden = MO

These concentrations are then used to display the source fractionation of each of the constituent in the interface form.

The statistical difference level provides an alternate comparison between background concentrations and predicted concentrations. The statistical difference level is the ρ-value calculated by applying an equal variance t-test to the log-transformed predicted and background water quality data. This is not a truly valid statistical test because non-independent daily values (15341 days) are used.

The constituent ranking identifies constituents that may be of higher priority for monitoring and/or refinement of effects-based objectives. The ranking scheme is illustrated in Figure 8.2.


Golder Associates

Figure 8.2 Constituent Ranking Schematic

8.2.2 Single Constituent Investigation Levels Form

The Single Constituent Investigation Levels Form provides detailed output for a single constituent and a single node which are both specified by the user (Figure 8.3). The form displays the predicted range of concentrations for each snapshot and compares these values to the effects-based objectives derived in Sections 3 and 4. The form also shows the fraction of the loading originating from the various sources described in Section 8.2.1 for each of the snapshots. If the effects-based objective is based on a water quality guideline then a solid symbol is used whereas effects-based thresholds are displayed using an open symbol.


Golder Associates

Figure 8.3 Single Constituent Investigation Levels Form

Three investigation levels are defined, as follows:

• Long-term average investigation level (50th percentile). Long-term average investigation levels are appropriate for comparison to effects-based objectives for human and wildlife health.

• Instantaneous (Peak) investigation level (user defined percentile but typically the 99.91 percentile), corresponding to a peak concentration. Instantaneous investigation levels are appropriate for comparison to effects-based objectives for the protection of aquatic life.

• Sample average investigation level (user defined percentile but typically the 95th percentile). Sample average investigations levels are appropriate for the evaluation of monitoring data as described in Section 6.2.1.


Golder Associates

The background-based benchmark corresponding to each of the investigation levels is also provided.

8.3 RESULTS

Investigation levels are unique to each time snapshot and assessment node. The maximum investigation level among assessment nodes and time snapshots was used to represent the overall investigation level. In this section, node-specific investigation levels and background-based benchmarks were also examined.

The ARM model was run for each of the snapshots and assessment nodes described in Appendix V. The 99.91 percentile (peak) and median (long-term average) investigation levels (i.e., predicted concentrations) for the model runs are provided in Appendix VII. Investigation levels were evaluated according to the scheme outlined in Figure 8.4 to demonstrate that they were protective of designated water uses. Investigation levels were compared to effects-based objectives only when they were above background-based benchmarks or where background-based benchmarks were absent. Where investigation levels were below background-based benchmarks, the background-based benchmarks or the corresponding investigation levels are both considered to be satisfactory to assess potential effects and are protective of all water uses.

Comparison of Investigation Levels to Background-based Benchmarks

The maximum predicted peak (99.91th percentile) and long-term average (median) investigation levels for each constituent are shown in Table 8.1 along with the maximum (among node) background-based benchmarks. Table 8.2 provides a summary of investigation levels that are above background-based benchmarks at a specific node but are below the maximum (among node) background-based benchmarks. When the investigation level was above the background-based benchmark, it indicated that oil sand developments have an appreciable contribution to predicted constituent concentrations. Likewise, when the investigation level was below the background-based benchmark, contributions from oil sands developments can be considered to be negligible for that constituent.

The maximum (among nodes) peak investigation levels for antimony, boron and molybdenum were above the corresponding maximum (among nodes) background-based benchmarks (Table 8.1). Additionally, the maximum peak investigation levels for ammonia and naphthenic acids were above the node-specific background-based benchmarks for several nodes (Table 8.2), although they were lower than the overall maximum (among node) background-based benchmark.


Golder Associates

The maximum (among nodes) long-term average investigation levels for sulphide, naphthenic acids, boron and molybdenum were above the corresponding maximum (among nodes) median background-based benchmarks (Table 8.2). Additionally, the maximum investigation levels for ammonia, and silver were above the node-specific background-based benchmarks for several nodes (Table 8.2), although they were lower than the overall maximum (among node) background-based benchmark.

Investigation levels for acute and chronic toxicity as well as many of the PAH groups could not be compared to background-based benchmarks because background concentrations were below detection.

If the maximum investigation level for a given constituent is below the corresponding background-based benchmark then no change in water quality is predicted to be associated with that constituent due to planned oil sands developments. For these cases, the background-based benchmarks or the corresponding investigation levels are both satisfactory as management objectives.

Figure 8.4 Screening Approach for Use of Investigation Levels for Use as Management-based Objectives


Golder Associates

Table 8.1 Maximum Investigation Levels

Maximum (Among Nodes)

Investigation Levels(a) Maximum (Among Nodes)

Background-based Benchmarks(b)

Constituent Units

Long--term Average

Concentration(c) Peak

Concentration(d)

Long-term Average


Concentration(d)

Major Ions calcium mg/L 37 77 44 92 chloride mg/L 27 110 32 116 magnesium mg/L 10 21 12 25 sodium mg/L 22 82 26 89 sulphate mg/L 29 96 35 115 sulphide mg/L 0.0050 0.037 0.0048 0.037 total dissolved solids mg/L 200 420 240 480 Nutrients ammonia mg/L 0.042 0.39 0.046 0.42 total nitrogen mg/L 0.77 4.4 0.92 5 total phosphorus mg/L 0.064 1.5 0.077 1.8 dissolved organic carbon mg/L 10 43 12 52 Whole-effluent Constituents acute toxicity TUa 0.0019 0.011 - - chronic toxicity TUc 0.010 0.095 - - fish tainting TPU 0.0101 0.11 - - General Organics naphthenic acids mg/L 0.11 0.65 0.041 0.76 total phenolics mg/L 0.0038 0.060 0.0046 0.072 Total Metals aluminum mg/L 0.36 21 0.43 25 antimony mg/L 0.00067 0.012 0.00080 0.0090 arsenic mg/L 0.00079 0.029 0.00095 0.034 barium mg/L 0.082 0.15 0.098 0.18 beryllium mg/L 0.00027 0.018 0.00032 0.021 boron mg/L 0.061 0.27 0.047 0.21 cadmium mg/L 0.00050 0.031 0.00060 0.038 chromium mg/L 0.0031 0.035 0.0037 0.042 copper mg/L 0.0028 0.029 0.0034 0.035 iron mg/L 1.0 20 1.2 24 lead mg/L 0.0012 0.0095 0.0014 0.011 manganese mg/L 0.055 0.97 0.055 1.2 mercury mg/L 0.000036 0.00010 0.000043 0.00012 molybdenum mg/L 0.0078 0.052 0.0022 0.016 nickel mg/L 0.0061 0.045 0.0073 0.054 selenium mg/L 0.00018 0.0021 0.00022 0.0025 silver mg/L 0.000058 0.00078 0.000070 0.00094 strontium mg/L 0.27 1.7 0.32 2.0


Table 8.1 Maximum Investigation Levels (continued)

Golder Associates


Investigation Levels(a) Maximum (Among Nodes)

Background-based Benchmarks(b)

Constituent Units

Long--term Average


Concentration(d)

Long-term Average


Concentration(d)

vanadium mg/L 0.0025 0.045 0.0026 0.054 zinc mg/L 0.015 0.12 0.018 0.15 PAH Groups PAH group 1 µg/L 0.00018 0.0021 - - PAH group 2 µg/L 0.00072 0.034 - 0.041 PAH group 3 µg/L 0.000057 0.016 - 0.019 PAH group 4 µg/L 0.00020 0.0027 - - PAH group 5 µg/L 0.0024 0.025 - 0.030 PAH group 6 µg/L 0.00014 0.0019 - - PAH group 7 µg/L 0.0039 0.94 0.0044 1.1 PAH group 8 µg/L 0.0053 0.90 0.0060 1.1 PAH group 9 µg/L 0.00079 0.012 - 0.015

Note: Values in bold exceed the corresponding background-based benchmarks. (a) Values based on the maximum ARM results from all nodes and snapshots. (b) Values are ten percent above the maximum ARM background values from the five assessment nodes. (c) Based on the median value. (d) Based on the 99.91 percentile. - = No Data; background is below detection.


Golder Associates

Table 8.2 Summary of Investigation Levels Exceeding Node-specific Background-based Benchmarks

Maximum (Among Nodes) Background-based Benchmarks

Node Specific Background-based Benchmarks

Node-specific Investigation Levels

Constituent Long-term Average

Concentration(a) Peak

Concentration(b)

Node Long-term Average

Concentration(a)Peak

Concentration(b)

Long-term Average

Concentration(a)Peak

Concentration(b)

Node

0.039 0.24 0.035 0.25 3 0.035 0.21 0.037 0.20 4

ammonia 0.046 0.42 1

0.033 0.21 0.034 0.19 5 0.017 0.62 0.090 0.57 2 naphthenic

acids 0.041 0.76 3 (median)

5 (99.91 percentile) 0.017 0.43 0.095 0.65 4

silver 0.00007 0.00094

4 (median) 2 (99.91

percentile)

0.000031 0.0010 0.000033 0.00078 2

Note: Values in bold exceed the corresponding background-based benchmark at the same node. Italicized values also exceed the maximum background-based benchmark. (a) Based on the median value. (b) Based on the 99.91 percentile.


Golder Associates

Comparison of Investigation Levels to Effects-based Objectives

Table 8.3 provides a summary of constituents where the investigation levels were above the corresponding background-based benchmarks. The corresponding effects-based objectives are also provided, where available. In most cases, the investigation levels were well below the effects-based objectives, and therefore the investigation levels were considered to be conservatively protective of water uses. Effects-based objectives were lacking for some constituents, as described in detail in the following paragraphs, and the investigation level was higher than the health effects-based objective for boron.

Cases Where Effects-based Objectives Were Lacking The long-term average investigation levels for ammonia and sulphide were above the corresponding background-based benchmark, but the investigation levels could not be compared to the health effects-based objective because they were not developed for these constituents in this study. The missing health effects-based objective for ammonia and sulphide were classified as LNR. The long-term average investigation levels were also well below the aesthetic drinking water guidelines for these constituents. Ammonia is not generally considered to have health effects at concentrations typically found in drinking water (HC 2006). If health effects were to occur, they would manifest themselves at concentrations greater than the aesthetic drinking water guideline (UKDWI 2002). As the maximum long-term average investigation level was below the aesthetic drinking water guideline, the investigation level can be considered protective of human health. Based on the lines of evidence provided, the long-term average investigation levels for ammonia and sulphide should be considered protective of all water uses. Further evaluation of the health effects-based objective is not required at this time.

The peak investigation level for naphthenic acids was above the corresponding background-based benchmark, but the investigation level could not be compared to an aquatic life effects-based objective because one was not developed in this study. Although the peak investigation levels for naphthenic acids were above the node-specific background-based benchmarks at two nodes, they were below the maximum background-based benchmark and were therefore within the natural range of concentrations in the LAR. However, the ILIM has not been updated to account for a more recent recognition that naphthenic acids derived from process-affected sources are composed of both a toxic, degradable labile portion as well as a refractory non-toxic portion (Golder 2006b). More recent modelling has been incorporating these two fractions with the result that levels of the labile, potentially toxic fraction of naphthenic acids reaching the Athabasca River will be much lower than that heretofore represented by the total levels of that constituent. For the next phase of this study a labile naphthenic acids investigation level should be developed. Developing a background-based


Golder Associates

benchmark for the LAR would be problematic as the assumption would be that background concentration of labile naphthenic acids would be zero. The missing aquatic life effects-based objective for naphthenic acids was classified as LR (likely relevant) because labile naphthenic acids have the potential to be toxic to aquatic life.

Cases Where Investigation Levels Were Above Effects-based Objectives The human health drinking water quality guideline for boron is 5 mg/L whereas the human health risk-based threshold derived in Section 3 is 0.06 mg/L. The drinking water guideline is based on achievable treatment levels rather than on potential effects (HC 2002). Further evaluation of the human health effects-based objective for boron may be warranted.


Golder Associates

Table 8.3 Comparison of Selected Investigation Levels (those above the BBB) to Effects-based Objectives

Investigation Levels

Constituent Units Long-term Average

Concentration(b) Peak

Concentration(c)


Objective

Minimum Aquatic Life Effects-based


Water Guideline Major Ions sulphide mg/L 0.0050 0.037 LNR 0.014 0.05 Nutrients ammonia mg/L 0.037 0.25 LNR 2.4 0.5 Whole-effluent Constituents acute toxicity TUa 0.0019 0.011 NR 0.3 NR chronic toxicity TUc 0.010 0.095 NR 1 NR fish tainting TPU 0.0101 0.11 NR NR 1(a) General Organics naphthenic acids mg/L 0.11 0.65 0.33 LR LNR Total Metals antimony mg/L 0.00067 0.012 0.0022 0.51 LNR boron mg/L 0.061 0.27 0.055 5.4 LNR molybdenum mg/L 0.0078 0.052 0.028 0.73 LNR silver 0.000033 0.00078 0.005 0.00017 0.1 PAH Groups PAH group 1 µg/L 0.00018 0.0021 0.69 0.015 LNR PAH group 2 µg/L 0.00072 0.034 0.069 0.18 LNR PAH group 3 µg/L 0.000057 0.016 0.069 LR LNR PAH group 4 µg/L 0.00020 0.0027 330 5.8 LNR PAH group 5 µg/L 0.0024 0.025 1700 0.12 LNR PAH group 6 µg/L 0.00014 0.0019 280 29 LNR PAH group 9 µg/L 0.00079 0.012 170 0.25 LNR

Note: Values in bold exceed the corresponding background-based benchmark or no background-based benchmark was derived. Italicized values exceed only the background-based benchmark at the same node but not the maximum among nodes. Shaded values exceed the corresponding background-based benchmark and either exceed the relevant effects-based objective or the effects-based objective was not present but identified as likely relevant.

(a) The fish tainting threshold is aesthetic, but applies to fish tissue quality not drinking water. (b) Based on the median value. (c) Based on the 99.91 percentile. NR = Effects-based objective is not relevant, LNR = Effects-based objective is likely not relevant, LR = Effects-based objective is likely relevant. - = no threshold.


Golder Associates

9 CONCLUSIONS

9.1 SUMMARY OF SCREENING RESULTS

The effects-based objectives, background-based benchmarks and investigation levels for the LAR developed in this study should reflect protection of all designated water uses. The investigation levels provided in this study are recommended as a component of a management system for the LAR. They can provide a system for determining whether monitoring results are consistent with development plans. Additionally, as illustrated in Section 8, investigation levels represent values that are protective of water uses.

The background-based benchmarks described in Section 7 reflect negligible changes in water quality and therefore will be reflective of maintaining designated water uses. Attainment of a benchmark suggests that no effects would be expected, but non-attainment of a benchmark in the absence of an effects-based objective suggests that development of an effects-based objective may be important.

The investigation levels described in Section 8 were typically more restrictive than background-based benchmarks. In cases where they were not more restrictive, investigation levels were more restrictive than effects-based objectives (Table 8.3; Section 8.3), with the exception of the long-term average investigation level for boron.

Because of the methods employed in developing health risk-based thresholds, these thresholds are sometimes much lower than corresponding existing guidelines. Typically, these differences would not affect the assessment of releases from oil sands developments, with one exception being boron. The drinking water quality guideline for boron is 5 mg/L and is based on treatment technology, whereas the health risk-based threshold derived in Section 6 is 0.06 mg/L. The health effects-based objective for boron may warrant further refinement.

Effects-based objectives for some constituents have not been developed. Various lines of evidence were considered to determine the likelihood that effects-based objectives were relevant for these constituents. In cases were there was uncertainty in the relevance of the effects-based objectives, background-based benchmarks should be considered protective of water uses.

Investigation levels for major ions and total dissolved solids are considered protective of water uses (Section 8.3) even though human health effects-based


Golder Associates

objectives have not been defined. Effects-based thresholds for human health are higher than aesthetic drinking water guidelines for these constituents (Appendix IX; HC 2002).

The peak investigation level for naphthenic acids was above the corresponding background-based benchmark, but the investigation level could not be compared to an aquatic life effects-based objective because one was not developed in this study. Although the peak investigation levels for naphthenic acids were above the node-specific background-based benchmarks at two nodes, they were below the maximum background-based benchmark and were therefore within the natural range of concentrations in the LAR. It is recommended that a new investigation level for naphthenic acids be developed based on its toxic labile portion as discussed in Section 8. The absence of an aquatic life effects-based objective for labile naphthenic acids was classified as LR (likely relevant) because labile naphthenic acids have the potential to be toxic to aquatic life.

9.2 FINALIZATION OF RSWQOs

All of the RSWQOs considered in this study are shown in Tables 9.1 and 9.2.

RSWQOs Relevant to Long-term Average Conditions

The candidate RSWQOs relevant to long-term average conditions included:

• existing guidelines for human and wildlife health;

• interjurisdictional guidelines for human and wildlife health;

• human and wildlife health risk-based thresholds; and

• existing aesthetic drinking water guidelines.

The most stringent of the candidate RSWQOs relevant to long-term average conditions were identified as final RSWQOs with the following exceptions:

• If a candidate RSWQO was inadequate based on screening criteria #2, #3, or #4 (i.e., was inappropriate for conditions in the LAR or was below background concentrations) it was excluded from consideration. The excluded candidate RSWQOs are shown crossed out in Table 9.1.

• Human and wildlife health risk-based thresholds were given preference over the corresponding guidelines. The excluded guidelines are shown in a light font in Table 9.1.


Golder Associates

Table 9.1 Summary of Final RSWQOs Applicable to Long-term Average Conditions

Reach Specific Water Quality Objectives

Candidate Effects-based Objectives Final Effects-based

Objectives Management-based Objectives Existing Guidelines Other Effects-based Objectives

Constituent Units

Maximum (Among Nodes) Long-Term Average

Background Concentration(d)


Human Health(a)

Wildlife Health(b)

Inter-jurisdictional Guidelines

Human Health Risk-Based Thresholds

Wildlife Health Risk-Based Thresholds Value Source

Long-term Average

Investigation Level(c)

Long-term Average Background-based

Benchmark(c)

Major Ions

calcium mg/L 37 LNR LNR 1000 5 - LNR LNR 1000 CCME 1999 37 44

chloride mg/L 27 250 LNR LNR - LNR LNR 250 HC 2006 27 32

magnesium mg/L 10 LNR LNR LNR - LNR LNR LNR - 10 12

sodium mg/L 22 200 LNR LNR - LNR LNR 200 HC 2006 22 26

sulphate mg/L 29 500 5 LNR 1000 5 500 5 (i) LNR LNR 500 HC 2006 29 35

sulphide mg/L 0.0040 0.05 5 LNR LNR - LNR LNR 0.05 HC 2006 0.0050 0.0048

total dissolved solids mg/L 200 500 LNR 3000 5 - LNR LNR 500 HC 2006 200 240

Nutrients

ammonia mg/L 0.038 LNR LNR LNR 0.5 5 (j) LNR LNR 0.5 UKDWI 2002 0.042 0.046

total nitrogen mg/L 0.77 LNR LNR LNR - LNR LNR LNR - 0.77 0.92

total phosphorus mg/L 0.064 LNR LNR LNR - LNR LNR LNR - 0.064 0.077

dissolved organic carbon mg/L 10 LNR LNR LNR - LNR LNR LNR - 10 12

Toxicity

acute toxicity TUa - NR NR NR - LNR LNR NR - 0.0019 -

chronic toxicity TUc - NR NR NR - LNR LNR NR - 0.010 -

fish tainting TPU - 1(g) NR NR - LNR LNR 1 Golder 2004c 0.0101 -

General Organics

naphthenic acids mg/L 0.034 LNR X X - 0.33 5 39 5 0.33 RBT 0.11 0.041

total phenolics mg/L 0.0038 LNR X 0.002(f) 3 - LR LR LR - 0.0038 0.0046

Total Metals

aluminum mg/L 0.36 LNR LR 5 5 - 11 5 11 5 11 RBT 0.36 0.43

antimony mg/L 0.00067 LNR 0.0055 LR - 0.0022 0.7 5 0.0022 RBT 0.00067 0.00080

arsenic mg/L 0.00079 LNR 0.01 5 0.025 5 - 0.00026 (k) 2,3 0.71 5 0.01 HC 2006 0.00079 0.00095

barium mg/L 0.082 LNR 1 5 LR - 0.088(l) 34 5 0.088 RBT 0.082 0.098

beryllium mg/L 0.00027 LNR 0.004 5 0.1 5 - 0.011 5 4.3 5 0.011 RBT 0.00027 0.00032

boron mg/L 0.039 LNR 5 5 5 5 - 0.055 180 5 0.055 RBT 0.061 0.047

cadmium mg/L 0.0005 LNR 0.005 0.08 5 - 0.0011 6.5 5 0.0011 RBT 0.00050 0.00060

chromium mg/L 0.0031 LNR 0.05(e) 0.05(e) - 8.3 5 720 5 8.3 RBT 0.0031 0.0037

copper mg/L 0.0028 1 5 1.3 5 0.5 5 - 0.17 5 4.1 5 0.17 RBT 0.0028 0.0034

iron mg/L 1.0 0.3 3 0.3 3 LR - LR LR LR - 1.0 1.2

lead mg/L 0.0012 LNR 0.01 0.1 5 - 0.02 5 52 5 0.02 RBT 0.0012 0.0014

manganese mg/L 0.046 0.05(n) LR LR 0.4(h) 0.39 570 5 0.05 HC 2006 0.055 0.055

mercury mg/L 0.000036 LNR 0.001 5 0.003 5 - 0.0017 5 7 5 0.0017 RBT 0.000036 0.000043


Table 9.1 Summary of Final RSWQOs, Background-based Benchmarks and Investigation Levels Applicable to Long-term Average Conditions (continued)

Golder Associates




Constituent Units




Human Health(a)

Wildlife Health(b)




Long-term Average



Benchmark(c)

molybdenum mg/L 0.0018 LNR LR 0.5 5 0.07 5 (h) 0.028 5 1.5 5 0.028 RBT 0.0078 0.0022

nickel mg/L 0.0061 LNR 0.34 5 1 5 - 0.0072(m) 260 5 0.0072 RBT 0.0061 0.0073

selenium mg/L 0.00018 LNR 0.01 5 0.05 5 - 0.028 5 1.3 5 0.028 RBT 0.00018 0.00022

silver mg/L 0.000058 0.1 5 LR LR - 0.028 5 0.008 5 0.008 RBT 0.000058 0.000070

strontium mg/L 0.27 LNR LR LR - 3.3 5 1700 5 3.3 RBT 0.27 0.32

vanadium mg/L 0.0022 LNR LR 0.1 5 - 0.017 1.3 5 0.017 RBT 0.0025 0.0026

zinc mg/L 0.015 5 5 5.1 5 50 5 - 1.7 5 170 5 1.7 RBT 0.015 0.018

PAH Groups

PAH group 1 µg/L - LNR 0.0029 LNR - 0.69 5600 0.69 RBT 0.00018 -

PAH group 2 (including benzo(a)anthracene) µg/L - LNR 0.0029 LNR - 0.069 56000 0.069 RBT 0.00072 -

PAH group 3 µg/L - LNR 0.0029 LNR - 0.069 560000 0.069 RBT 0.000057 -

PAH group 4 (including acenaphthene and acenaphthylene

µg/L - LNR 330 LNR - 330 33000 330 RBT 0.00020 -

PAH group 5 (including anthracene and phenanthrene)

µg/L - LNR 6300 LNR - 1700 190000 1700 RBT 0.0024 -

PAH group 6 (including biphenyl and alkyl substituted biphenyl)

µg/L - LNR LR* LNR - 280 28000 280 RBT 0.00014 -

PAH group 7 (including fluorene and fluoranthene) µg/L 0.0037 LNR 50 5 LNR - 220 5 24000 5 220 RBT 0.0039 0.0044

PAH group 8 (including Naphthalene) µg/L 0.0050 LNR LR* LNR - 110 5 16000 5 110 RBT 0.0053 0.0060

PAH group 9 (including pyrene) µg/L - LNR 630 LNR - 170 14000 170 RBT 0.00079 -

“Task C” Constituents

dibenzothiophene µg/L - LNR LNR LNR LNR LNR LNR - - - -

alkyl-substituted dibenzothiophene µg/L - LNR LNR LNR LNR LNR LNR - - - -

di (2-ethylhexyl) phthalate (DEHP) µg/L - LNR 6 LNR LNR LNR LNR - - - -

methyl isobutyl carbinol (MIBC) µg/L - LNR LNR LNR LNR LNR LNR - - - -

acrylamide µg/L - LNR 0 LNR LNR LNR LNR - - - -

oil and grease mg/L - LNR LNR LNR LNR LNR LNR - - - -

total petroleum hydrocarbons mg/L - LNR LNR LNR LNR LNR LNR - - - -

toluene mg/L - 0.024 1 0.024 LNR LNR LNR - - - -


Table 9.1 Summary of Final RSWQOs, Background-based Benchmarks and Investigation Levels Applicable to Long-term Average Conditions (continued)

Golder Associates




Constituent Units




Human Health(a)

Wildlife Health(b)




Long-term Average



Benchmark(c)

xylenes mg/L - 0.3 0.01 X LNR LNR LNR - - - -

dissolved oxygen mg/L - LNR LNR LNR LNR LNR LNR - - - -

lithium mg/L - LR LR LR LR LR LR - - - -

fluoride mg/L - 2 1.5 2 LNR LNR LNR - - - -

potassium mg/L - LR LR LR LR LR LR - - - -

Note: Bold values indicates that the effects-based objective is inadequate based on the screening approach. Bolded background-based benchmarks indicate that these can be used as surrogates for effects-based objective. Italicized values indicate that no evaluation was possible either because constituent was not modeled or median background concentration was zero.

1 Effects-based objective is absent. 2 Effects-based objective is inadequate as the method used to determine the guideline is not relevant to the LAR. 3 Effects-based objective is inadequate as the guideline is below the maximum background concentration. 4 Effects-based objective is inadequate as is does not account for other water quality constituents which effect the toxicity. 5 Effects-based objective is more than ten times greater than the background concentration. (a) Based on the more conservative guideline of: USEPA (2002) using fish consumption rate of 45 g/d (Richardson 1997), USEPA (1999) primary drinking water objectives and Health Canada (2006) health based drinking water objectives. (b) CCME (1999) livestock watering guidelines. (c) Based on the more conservative of Health Canada (2006) aesthetic objectives and USEPA (1992) secondary drinking water objectives. (d) Concentrations based on the maximum median background concentration among the assessment nodes derived from the ARM model. (e) Chromium III guideline. (f) Guideline for phenols. (g) The fish tainting threshold is aesthetic, but applies to fish tissue quality not drinking water. Guideline from Golder 2004c. (h) WHO (2002) drinking water guideline for human health. (i) Australian human health drinking water guideline (NWQMS 2000). (j) UK aesthetic drinking water guideline. (k) The background-based benchmark for arsenic was not considered as a surrogate because the health risk-based threshold was inadequate based on criterion #2 and was not considered further. (l) The human health risk-based threshold for barium is applicable for the fall and winter only. Based on the overall long-term average background concentration, the health risk-based threshold was adequate based on criterion #3. (m) The human health risk-based threshold for nickel is applicable for the fall and winter only. Based on the overall long-term average background concentration, the health risk-based threshold was adequate based on criterion #3. (n) The aesthetic guideline for manganese is applicable for the fall and winter only. Based on the overall long-term average background concentration, the guideline was adequate based on criterion #3. NR = Effects-based objective is not relevant, LNR = Effects-based objective is likely not relevant, LR = Effects-based objective threshold is likely relevant. - = Either no guideline or no data.


Golder Associates

Table 9.2 Summary of Final RSWQOs Applicable to Peak Conditions




Constituent Units


Peak Background Concentration(d)



Inter-Jurisdictional

Guidelines CEB Effects-based

Thresholds Value Source Peak Investigation

Level(c) Peak Background-based

Benchmark(c)

Major Ions

calcium mg/L 77 LNR LNR - LNR LNR - 77 92

chloride mg/L 97 230 250 - LR 230 US EPA 2002 110 116

magnesium mg/L 21 LNR LNR - LNR LNR - 21 25

sodium mg/L 74 LNR 200 - LNR 200 HC 2006 82 89

sulphate mg/L 96 LR 500 50 (l) (n) 2,3 LR 500 HC 2006 96 115

sulphide mg/L 0.031 0.014(e) 3 0.05 - LR LR - 0.037 0.037

total dissolved solids mg/L 400 LNR 500 - LNR 500 HC 2006 420 480

Nutrients

ammonia mg/L 0.35 2.4(e) LNR - LR* 2.4 US EPA 2002 0.39 0.42

total nitrogen mg/L 4.4 1 3,4 LNR - LNR LR - 4.4 5

total phosphorus mg/L 1.5 0.05 3,4 LNR - LNR LR - 1.5 1.8

dissolved organic carbon mg/L 43 LNR LNR - LNR LNR - 43 52

Toxicity

acute toxicity TUa - NR NR - NR NR 0.011 -

chronic toxicity TUc - 1(k) NR - NR 1 US EPA 1991 0.095 -

fish tainting TPU - NR 1(j) - NR 1 Golder 2004c 0.11 -

General Organics

naphthenic acids mg/L 0.63 LR LNR - LR LR - 0.65 0.76

total phenolics mg/L 0.060 0.005(i) 3 LNR - 0.04 3 LR - 0.060 0.072

Total Metals

aluminum mg/L 21 0.1 3 LNR - 0.68 3(o) LR - 21 25

antimony mg/L 0.0075 X LNR - 0.51 5 0.51 CEB 0.012 0.0090

arsenic mg/L 0.029 0.005 3 LNR - 0.073 0.073 CEB 0.029 0.034

barium mg/L 0.15 X LNR - 5.8 5 5.8 CEB 0.15 0.18

beryllium mg/L 0.018 X LNR - 0.0073 3(p) LR - 0.018 0.021

boron mg/L 0.17 X LNR - 5.4 5 5.4 CEB 0.27 0.21

cadmium mg/L 0.031 0.00032(f) 3 LNR - 0.00032(f) 3 LR - 0.031 0.038

chromium mg/L 0.035 0.001(g) 3 LNR - 0.0025 3 LR - 0.035 0.042

copper mg/L 0.029 0.003(f) 3 1 5 - 0.0078 3 LR - 0.029 0.035

iron mg/L 20 0.3 3 0.3 3 - 0.57 3 LR - 20 24

lead mg/L 0.0095 0.004(f) 3 LNR - - LR - 0.010 0.011


Table 9.2 Summary of Final Candidate RSWQOs, Background-based Benchmarks and Investigation Levels Applicable to Peak Conditions (continued)

Golder Associates




Constituent Units









Benchmark(c)

manganese mg/L 0.97 X 0.05 3 - 0.26 3 LR - 1.0 1.2

mercury(h) mg/L 0.0001 0.000005 3 LNR - LR LR - 0.00010 0.00012

molybdenum mg/L 0.013 0.073 LNR - 0.73 5 0.73 CEB 0.052 0.016

nickel mg/L 0.045 0.062(f) LNR - LR 0.062 US EPA 2002 0.045 0.054

selenium mg/L 0.0021 0.001 3 LNR - LR LR - 0.0021 0.0025

silver mg/L 0.00078 0.0001 3 0.1 5 - 0.00017 3 LR - 0.00078 0.00094

strontium mg/L 1.7 X LNR - 0.2 3 LR - 1.7 2.0

vanadium mg/L 0.045 X LNR - 0.16 LR - 0.045 0.054

zinc mg/L 0.12 0.03 3 5 5 - LR LR - 0.12 0.15

PAH Groups

PAH group 1 µg/L - 0.015 LNR - LR 0.015 CCME 1999 0.0021 -

PAH group 2 (including benzo(a)anthracene) µg/L 0.034 0.018 3 LNR - 0.18 0.18 CEB 0.034 0.041

PAH group 3 µg/L 0.016 X LNR - LR LR - 0.016 0.019

PAH group 4 (including acenaphthene and acenaphthylene µg/L - 5.8 LNR - LR 5.8 CCME 1999 0.003 -

PAH group 5 (including anthracene and phenanthrene) µg/L 0.025 0.012 3 LNR - 0.12 0.12 CEB 0.025 0.030

PAH group 6 (including biphenyl and alkyl substituted biphenyl) µg/L - X LNR - 29 29 CEB 0.002 -

PAH group 7 (including fluorene and fluoranthene) µg/L 0.94 0.04 3 LNR - LR 1.0 BBB 0.94 1.1

PAH group 8 (including Naphthalene) µg/L 0.90 1.1 LNR - LR 1.1 CCME 1999 0.90 1.1

PAH group 9 (including pyrene) µg/L 0.012 0.025 LNR - 0.25 0.250 CEB 0.012 0.015

“Task C” Constituents

dibenzothiophene µg/L - LNR LNR - LNR - - - -

alkyl-substituted dibenzothiophene µg/L - LNR LNR - LNR - - - -

di (2-ethylhexyl) phthalate (DEHP) µg/L - 16 LNR - LNR - - - -

methyl isobutyl carbinol (MIBC) µg/L - LNR LNR - LNR - - - -

acrylamide µg/L - LNR LNR - LNR - - - -

oil and grease mg/L - LNR LNR - LNR - - - -

total petroleum hydrocarbons mg/L - LNR LNR - LNR - - - -

toluene mg/L - 0.002 0.024 - LNR - - - -

xylenes mg/L - LNR 0.3 0.2(m) LNR - - - -

dissolved oxygen mg/L - 6.5 LNR - LNR - - - -

lithium mg/L - LR LNR 0.096(l) LR - - - -


Table 9.2 Summary of Final Candidate RSWQOs, Background-based Benchmarks and Investigation Levels Applicable to Peak Conditions (continued)

Golder Associates




Constituent Units









Benchmark(c)

fluoride mg/L - 0.12 2 - LNR - - - -

potassium mg/L - LR LNR 373(l) LR - - - -

Note: Bold values indicates that the effects-based objective s inadequate based on the screening approach. Bolded background-based benchmarks indicate that these can be used as surrogates for effects-based objectives. Italicized values indicate that no evaluation was possible either because constituent was not modeled or median background concentration was zero.

1 Effects-based objective is absent. 2 Effects-based objective is inadequate as the method used to determine the guideline is not relevant to the LAR. 3 Effects-based objective is inadequate as the guideline is below the maximum background concentration. 4 Effects-based objective is inadequate as is does not account for other water quality constituents which effect the toxicity. 5 Effects-based objective is more than ten times greater than the background concentration. (a) Based on the more conservative of Health Canada (2006) aesthetic objectives and USEPA (1992) secondary drinking water objectives. (b) Based on the more conservative guidelines for the protection of aquatic life of US EPA (2002), CCME (1999) and AENV (1999). (c) 7-day mean. (d) Concentrations based on the maximum 99.91 percentile background concentration among the assessment nodes derived from the ARM model. (e) Guidelines are pH (acute and chronic) and/or temperature (chronic) dependent; values shown here correspond to a pH of 8 and temperature of 5 °C, respectively; these guidelines were altered based on site-

specific median conditions using methods described in AENV (1999) and U.S.EPA (1999, 2002). (f) Guidelines are hardness dependent; values shown here are based on a hardness of 125 mg/L; these guidelines were altered based on site-specific hardness levels using the methods described in AENV (1999) and U.S. EPA (2002). (g) Chromium VI guideline. (h) Alberta chronic mercury guideline for the protection of aquatic life is still draft. (i) Guideline for phenols. (j) The fish tainting threshold is aesthetic, but applies to fish tissue quality not drinking water. Guideline from Golder 2004c. (k) Toxicity guideline taken from US EPA (1991). (l) BC Chronic aquatic life guideline (MOEBC 1998). (m) Australian Chronic aquatic life guideline (NWQMS 2000). (n) The background-based benchmark for sulphate was not considered as a surrogate because the interjurisdictional guideline was inadequate based on criterion #2 and was not considered further. (o) The CEB effects-based threshold for aluminum is applicable in the fall only. Based on the overall peak concentration the CEB effects-based threshold was inadequate based on criterion #3. (p) The CEB effects-based threshold for beryllium is applicable in the fall only. Based on the overall peak concentration the CEB effects-based threshold was inadequate based on criterion #3. NR = Effects-based objective is not relevant, LNR = Effects-based objective is likely not relevant, LR = Effects-based objective is likely relevant. - = No guideline.


Golder Associates

Background-based benchmarks were identified for use as management-based objectives where no final effects-based objective could be identified (i.e., they were inadequate based on criterion #3 or they were absent but classified as likely relevant).

The final RSWQOs relevant to long-term average conditions are shown in Table 9.1 along with the source.

RSWQOs Relevant to Peak Conditions

The candidate RSWQOs relevant to peak conditions included:

• existing guidelines for protection of aquatic life;

• interjurisdictional guidelines for aquatic life;

• CEB effects-based thresholds;

• existing aesthetic drinking water guidelines; and

• background-based benchmarks for constituents where background concentrations were greater than one or more of the candidate effects-based objectives (i.e., they were inadequate based on criterion #3).

The most stringent of the candidate RSWQOs relevant to peak conditions were identified as the final RSWQOs with the following exceptions:

• If a candidate RSWQO was inadequate based on screening criteria #2, #3, or #4 (i.e., was inappropriate for conditions in the LAR or was below background concentrations) it was excluded from consideration. The excluded candidate RSWQOs are shown crossed out in Table 9.2.

• CEB effects-based thresholds were given preference over the corresponding guidelines. The excluded guidelines are shown in a light font in Table 9.2.

Background-based benchmarks were identified as management-based objectives where no final effects-based objectives could be identified (i.e., they were inadequate based on criterion #3 or they were absent but classified as likely relevant).

The final RSWQOs relevant to peak conditions are shown in Table 9.2 along with the source.


Golder Associates

9.3 POTENTIAL APPLICATION OF INVESTIGATION LEVELS

9.3.1 Assessing Attainment with Investigation Levels

Water quality investigation levels were established based on percentiles of constituent concentrations and can be compared to measurements from single sampling events or averaged monitoring results. For example, a 99.91 percentile concentration (i.e., an instantaneous or peak investigation level) could be compared to a single monitored result. A 99.91th percentile concentration is equivalent to a one in 3-year exceedance probability and is supported as an acceptable frequency of exceedance of water quality guidelines by AEP (1995). A 95th percentile (the default sample average investigation level) or some other user-defined percentile could be compared to the average of monitored results. The 95th percentile probability level is often used by AENV as an average monthly substance release limit based on an average of the results from 4 samples collected per month.

A more refined sample average investigation level percentile can be developed based on the relationship between the mean of the results from a specified number of samples, the predicted long term average, and the variability of the predictions. Equations for this relationship are defined in AEP (1995). The ILIM has been configured so that the user can generate whatever percentile is deemed most appropriate for the constituent and investigation level of interest.

ARM produces stochastic predictions, that is, it calculates a range of possible values for all possible stream flows for the year. Judgement must be used in interpreting monitoring results if for example the flows are high and the observed constituent levels are also high. In spite of this qualification, investigation levels at 99.91th percentile are considered conservative predictions, irrespective of the flow.

Aside from the absolute value of the investigation level, the ILIM provides additional information to assist the manager in decision making. The following information is also provided:

• effect-based objectives described in Section 6;

• identification of loading sources and their contribution to the total loading of the substance; and

• the range of the modelled predictions (box and whisker plots with mean, median, minimum, maximum and percentiles).


Golder Associates

9.3.2 Management Framework

Investigation levels can be a valuable component of an effective management system for the LAR. They provide a measure for determining if monitoring results are consistent with conditions predicted in the EIAs. Additionally, as illustrated in Section 8, they represent objectives that are protective of water uses. Predictions and monitoring findings must be closely related to establish cause and effect linkages and, if necessary, to enable effective mitigation responses.

A flow diagram that proposes how monitoring and investigation levels would be related in a management framework is provided in Figure 9.1.

Figure 9.1 Management Framework for Relating Monitoring and Investigation Levels

Monitor

Mitigate

Investigation Level and/orModel Refinement

Investigation LevelCompliance?No YesInvestigate

A management protocol developed for using investigation levels should include underlying assumptions such as:

• investigation levels should be compared against monitoring data generated from company specific monitoring programs and regional programs such as RAMP;


Golder Associates

• investigation levels are not intended to replace the use of effects-based objectives and background-based benchmarks for monitoring and compliance but to complement their use;

• investigation levels should be unique for the location and time period to ensure that managers are able to identify constituent levels that are not appropriate for the timeframe and location for which they are predicted;

• water quality investigation levels should provide constituent source load predictions so that the manager is able to investigate the potential source of constituents in a directed manner;

• water quality investigation levels should be considered within the context of both streamflow predictions and observed streamflows for the appropriate location and time period because predicted constituent concentrations are related to streamflows;

• investigation levels should provide uncertainty estimates in constituent concentrations so that levels being investigated and follow-up actions can be considered within that context;

• continued refinement of ARM must be sought to improve prediction accuracy, particularly in the area of metals, sulphides and the attenuation of trace organics; and

• investigation levels should be refined on a regular basis consistent with mine plan changes, EIA model updates, and refinements discussed above, so that the accuracy of impact predictions will improve and reflect inevitable mine plan changes.

9.4 APPLICATION OF OBJECTIVES FOR OTHER REGIONAL SURFACE WATERS

The effects-based objectives developed in Section 6 would be relevant to other surface waters in the oil sands region, including pit lakes. The investigation levels approach could also be applied to other surface waters; however, investigation levels, background-based benchmarks and constituent rankings would be unique to any give watercourse or waterbody.

Development of background-based benchmarks for pit lakes would require special consideration. Background-based benchmarks could be based on models of pit lakes, excluding mine affected waters, or alternatively they could be based on data collected from reference lakes in the region. Both of these approaches are consisted with the methods outlined by the Canadian Council of Ministers of the Environment (CCME 2003).


Golder Associates

9.5 RECOMMENDED FURTHER DEVELOPMENT OF EFFECTS-BASED OBJECTIVES

For the majority of constituents, investigation levels provide a conservative management-based objective that is protective of water uses. Therefore, in most cases, development of additional effects-based objectives is generally not required (Section 8.3), with the only exception possibly being boron. A detailed review of constituents not fully addressed in this study is provided Appendix IX.

No effects-based objectives for naphthenic acids were identified. The investigation levels at specific nodes were above the corresponding node-specific background based benchmark. However, a new investigation level for labile naphthenic acids is being proposed for the next phase of related work. Notwithstanding, naphthenic acids are considered important for development of effects-based objectives.

Aquatic life effects-based objectives were below background concentrations (inadequate based on criterion #3) for many metals. The dissolved faction of metals can be significantly less than the total concentrations as shown in the CEMA study (CEMA 2003). In terms of toxicity, the dissolved fraction is more relevant than total metals. CCME and Alberta guidelines for metals were formulated as total metals while U.S. EPA guidelines were formulated as dissolved metals and were converted to total metals. U.S. EPA is in the process of updating guidelines for metals based on the biotic ligand model (Niyogi and Wood 2004). Use of objectives for dissolved metals based on the biotic ligand model are appropriate for the LAR.

9.6 RECOMMENDATIONS FOR UPDATES TO ARM AND THE ILIM

Several constituents could be considered for inclusion in ARM including potassium, lithium, fluoride, oil and grease, total petroleum hydrocarbons, toluene and xylene. The rationale for consideration for inclusion is provided in Appendix IX.

Investigation levels should be considered within the context of both streamflow predictions and observed streamflows for the appropriate location and time period because predicted constituent concentrations are related to streamflows and seasons. Although investigation levels at 99.91th percentile are considered to be conservative predictions, irrespective of the flow, ARM could be configured represent the correspondence between streamflow and constituent concentrations. As an alternative, the ARM ILIM could be configured to produce season-specific investigation levels.


Golder Associates

10 CLOSURE

We trust the above meets your present requirements. If you have any questions or require additional details, please contact the undersigned.

GOLDER ASSOCIATES LTD.

Report prepared by: Report reviewed by: Dennis Kramer, M.Sc. Andrews Takyi, Ph.D., P.Eng. Water Quality Specialist Senior Environmental Engineer Tammy Rosner, M.Sc. Kenneth Froese, PhD Water Quality Specialist Senior Risk Assessment Specialist Ian Mackenzie, M.Sc., Principal, Oil Sands Director


Golder Associates

11 REFERENCES

AENV (Alberta Environment). 1999. Surface Water Quality Guidelines for Use in Alberta. Environmental Service, Environmental Sciences Division. Edmonton, AB.

AEP (Alberta Environmental Protection). 1995. Water Quality Based Effluent Limits Procedures Manual. Environmental Protection. Edmonton, AB.

CCME (Canadian Council of Ministers of the Environment). 1999. Canadian Environmental Quality Guidelines. Winnipeg, MB.

CCME (Canadian Council of Ministers of the Environment). 2003. Guidance on the Site-specific Application of Water Quality Guidelines in Canada: Procedures for Deriving Numerical Water Quality Objectives.

CEMA (Cumulative Environmental Management Association and Western Resource Solutions). 2003. Development of Reach Specific Water Quality Guidelines for Variables of Concern in the Lower Athabasca River: Identification of Variables of Concern and Assessment of the Adequacy of the current Guidelines. Final report prepared for Cumulative Environmental Management Association (CEMA) by Western Resource Solutions (WRS).

CEMA (Cumulative Environmental Management Association). 2005. Muskeg River Watershed Integrity Investigation Levels. Prepared by Golder Associates Ltd. Submitted to CEMA August, 2005.

Davies, T.D., J.S. Pickard and K.J. Hall. 2003. Sulphate toxicity to freshwater organisms and molybdenum toxicity to rainbow trout embryos/alevins by Mine Reclamation Symposium Proceedings 1977 - 2002 On CD-ROM, published by BC TRCR

Fischer, H.B., E.J. List, R.C.Y. Koh, J. Imberger and N.H. Brooks. 1979. Mixing in Inland and Coastal Waters. Academic Press, Inc. San Diego, California.

Geckler, J.R., W.B. Horning, T.M. Neiheisel, Q.H. Pickering, E.L. Robinson, and C.E. Stephan. 1976. Validity of Laboratory Tests for Predicting Copper Toxicity in Streams. U.S.EPA, Duluth, MN: 208 p.

Golder (Golder Associates Limited.). 2004a. Athabasca River Model Update and Reach Segmentation. March 2004. Calgary, Alberta.


Golder Associates

Golder. 2004b. Weldwood of Canada’s EEM Cycle 3 and Provincial Approval Monitoring Programs. Submitted to Alberta Environment, Edmonton, Alberta on behalf of Weldwood of Canada Limited, Hinton Division, Hinton, Alberta.

Golder. 2004c. Fish Tainting Literature and Modeling Review. September 2004. Calgary, Alberta.

Golder 2006a. Athabasca River Model Interface for Instream Flow Needs Assessment. Submitted to Alberta Environment.

Golder 2006b. Summary of Naphthenic Acids Predictions for the Oil Sands Region. Submitted to Canadian Oil Sands Network for Research and Development. Wetlands and Aquatics Working Group.

HC (Health Canada). 2002. Guidelines for Canadian Drinking Water Quality. Health Canada, Ottawa, ON.

Imperial Oil (Imperial Oil Resources Ventures Limited). 2005. Kearl Oil Sands Project - Mine Development. Volume 1 to 9. Submitted to Alberta Energy and Utilities Board and Alberta Environment. Prepared by Imperial Oil Resources Ventures Limited in association with Golder Associates Ltd., AXYS Environmental Consulting Ltd., Komex International Inc. and Nichols Applied Management. Calgary, AB. Submitted July, 2005.

MOEBC (Ministry of Environment British Columbia). 1996. Developing Water Quality Objectives in British Columbia: A Users Guide, British Columbia Water, Air and Climate change Branch.

MOEBC. 1998. British Columbia Approved Water Quality Guidelines (Criteria), British Columbia Ministry of Water, Land and Air Protection. pp 65.

MRRB (Mackenzie River Basin Board). 2003. Highlights of the Mackenzie River Basin State of the Aquatic Ecosystem Report 2003.

Niyogo, S. and Wood, C.M. 2004. Biotic Ligand Model, a Flexible Tool for Developing Site-Specific Water Quality Guidelines for Metals. Enivron. Sci. Technol., 38.


Golder Associates

NWQMS (National Water Quality Management Strategy). 2000. Environment Australia. Inland Waters. Water Quality Guidelines. HTML version. OMEE. 1998. Policies Guidelines Provincial Water Quality Objectives of the Ministry of Environment and Energy. pp 34.

OMEE (Ontario Ministry of Energy and the Environment). 1997. Scientific Criteria Document for Multimedia Standards Development Polycyclic Aromatic Hydrocarbons (PAH). Part 1: Hazard Identification and Dose-Response Assessment.

OMEE. 1998. Water Management Policies and Guidelines: Provincial Water Quality Objectives of the Ministry of Environment and Energy.

Posthuma, L., G.W. Suter II and T.P. Traas. 2002. Species Sensitivity Distributions in Ecotoxicology. Lewis Publishers, Boca Raton.

Richardson, G.M. 1997. Compendium of Canadian human exposure factors to risk assessment. O’Connor Associates Environmental Inc. Ottawa, Ontario.

Shell (Shell Canada Limited). 2005. Muskeg River Mine Expansion Project Application and Environmental Impact Assessment. Submitted to Alberta Energy and Utilities Board and Alberta Environment. Prepared by Golder Associates Ltd. and Nichols Applied Management. Volume 1, 2, 3 and 4. Fort McMurray, AB. Submitted April, 2005.

Suncor (Suncor Energy Inc.). 2005. Voyageur Project Application and Environmental Impact Assessment. Submitted to Alberta Energy and Utilities Board and Alberta Environment. Volumes 1A, 1B, 2, 3, 4, 5 and 6. Fort McMurray, AB. Submitted March, 2005.

UKDWI (UK Drinking Water Inspectorate). 2002. Drinking Water Regulations Schedule 1 and 2. UK Drinking Water Inspectorate. http:/www.dwi.gov.uk/regs/si3184/3184.htm.

U.S. EPA. (U.S Environmental Protection Agency). 1991. Technical Support Document For Water Quality-based Toxics Control. Office of Water, EPA/505/2-90-001.

U.S. EPA. 1992. Secondary Drinking Water Regulations: Guidance for Nuisance Chemicals. Office of Water, July 1992. US EPA 817-K-92-001.


Golder Associates

U.S. EPA. 1993. Provisional Guidance for Quantitative Risk Assessment of Polycyclic Aromatic Hydrocarbons. EPA/600/R-93/089.

U.S. EPA. 1999. Primary Drinking Water Regulations: Office of Water.

U.S. EPA. 2002. National Recommended Water Quality Criteria. Office of Water. November 2002. U.S. EPA 822–R–02–047.

U.S. EPA. 2007. Aquatic Life Ambient Freshwater Quality Criteria--Copper 2007 Revision EPA-HQ-OW-2003-0079

WHO (World Health Organization). 2002. Guidelines for Drinking Water Quality – Substances and Parameters. www.who.int/water_sanitation_health/GDWQ/Summary_tables/Tab5.htm.

APPENDIX I

SCOPE OF WORK

CEMA - i - Athabasca River Reach Specific May 2007 Water Quality Objectives

Golder Associates

TABLE OF CONTENTS

SECTION PAGE

1 FINAL TERMS OF REFERENCE/SCOPE OF WORK...............................................1

2 METHODS AND STUDY TASKS FROM ORIGINAL PROPOSAL...........................15 2.1 TASK A – IDENTIFY METHODS FOR ESTABLISHING RSWQO, EVALUATE

AND RECOMMEND METHODS FOR THE ATHABASCA RIVER ...............................15 2.1.1 Review and Summarize Literature.................................................................15 2.1.2 Recommend Methods for Developing RSWQOs...........................................16

2.2 TASK B – EVALUATE VOCS WITH THE APPROVED METHOD ...............................19 2.2.1 Data Collection and Compilation....................................................................19 2.2.2 Compile Guidelines for Relevant Uses ..........................................................19 2.2.3 Develop Chronic Effects Benchmarks for Selected Substances ................20 2.2.4 Develop Objectives Based on Background Concentrations for

Selected Substances .....................................................................................20 2.2.5 Apply the Investigations Level Interface Model to the Athabasca

River...............................................................................................................20 2.2.6 Evaluate Most Sensitive Water Use or Objective Type .................................22 2.2.7 Determine Adequacy of Objectives to Other Regional Surface

Waters............................................................................................................22 2.3 TASK C – EVALUATE REMAINING VOCS ..................................................................23

3 REVISED METHODS AND STUDY TASKS FROM THE ADDENDUM ...................24 3.1 TASK A – IDENTIFY METHODS FOR ESTABLISHING RSWQO, EVALUATE

AND RECOMMEND METHODS FOR THE ATHABASCA RIVER ...............................24 3.1.1 Review and Summarize Literature.................................................................24 3.1.2 Recommend Methods for Developing RSWQOs...........................................24

3.2 TASK B – EVALUATE VOCS WITH THE APPROVED METHOD ...............................24 3.3 TASK C – EVALUATE REMAINING VOCS ..................................................................25

3.3.1 Develop Chronic Effects Benchmarks ...........................................................26 3.3.2 Development of Objectives Based on Background Concentrations ..............27 3.3.3 Apply the Investigations Level Interface Model to the Athabasca

River...............................................................................................................27 3.3.4 Summary of Approach ...................................................................................28

4 REFERENCES........................................................................................................29

LIST OF TABLES

Table 1 Summary of Approach for VOCs and Other Parameters ......................................11 Table 2 Sources and Approaches for Establishing Water Quality Objectives....................15

LIST OF FIGURES

Figure 1 Investigation Levels Sample Interface...................................................................21

CEMA I-1 Athabasca River Reach Specific May 2007 Water Quality Objectives

Golder Associates

1 FINAL TERMS OF REFERENCE/SCOPE OF WORK

The original Proposal for Services along with the addendum to the original proposal is enclosed in Attachment 2.

BACKGROUND

The Cumulative Environmental Management Association (CEMA) is a forum for regional stakeholders to facilitate discussions and make consensus-based decisions forming the basis for action by members, and recommendations to Alberta Environment’s Regional Sustainable Development Strategy (RSDS) as appropriate, on managing the region’s cumulative environmental effects. CEMA accomplishes its work through technical working groups.

One such technical working group is the Surface Water Working Group (SWWG), established as a direct response to stakeholders and regulators concerns about cumulative environmental impacts to water resources in the oil sands area. The Water Quality Task Group (WQTG) is a part of the SWWG and was formed to develop and recommend reach specific quality objectives for the lower Athabasca River (LAR).

The WQTG (WQTG) is undertaking a comprehensive program to investigate water quality objectives for the LAR, based on science with the goal of no negative change in water quality that impairs the aquatic ecosystem. Societal and economic / technological aspects for achieving no negative change in water quality will be included as necessary.

In general, reach specific objectives will be developed for parameters where there is an existing baseline exceedance of the existing Alberta or CCME – PAL guidelines, where current guidelines have been determined to be inadequate or where guidelines do not exist.

The reach specific objectives are to be protective of the following uses:

• Fish and fish habitat (supporting existing fisheries; protection of aquatic life) Suitability of fish for consumption (fish tainting)

• Recreation and aesthetics • Municipal water supply (to a treatment system) • Local domestic use, by residents and visitors along the river and in the Delta • Industrial water supply (e.g., cooling and process water) • Wildlife usage • Transboundary obligations (e.g. Mackenzie River Basin Agreement) • Wood Buffalo National Park needs

Work completed to date by the WQTG, includes:

• Selection of potential variables of concern (VOCNs) based on a review of relevant oil sands wastewaters


Golder Associates

• An assessment of the adequacy of current guidelines for each VOCN to protect specific water uses identified above and preparation of a list of VOCNs which require some type of guideline development

• A dye mixing study to determine the lateral mixing coefficient of the Athabasca River; • An update of the existing Athabasca River Model to allow for reach specific modeling

of VOCNs • In addition, Alberta Environment supported work to model some parameters

pertinent to instream flow needs thus extending the ARM model update to reach specific modeling for select parameters

A table summarizing VOCNs for which reach specific objectives were recommended by a previous WQTG report (WRS 2002), can be found in Appendix II. The WQTG have added chronic and acute toxicity to this list. It is recognized that the level of effort required to develop reach specific parameters may vary depending on the type of parameter, its characteristics and available information.

It is also recognized that the consultant may apply their knowledge to prioritize and further refine the list of VOCNs, adding or removing variables as appropriate provided detailed justification in the completion of this contract.

SCOPE OF WORK

The project purpose is to develop reach specific water quality objectives (RSWQO) to protect designated water uses. The WQTG has identified three tasks necessary for the incremental development of the RSWQOs, they are as follows:

Task A) Identify methods for establishing RSWQO, evaluate and recommend methods for the Athabasca River via:

Aii.) Review and summarize literature

The literature review will include an itemized list of documents reviewed and a description of any methods found that may have applicability to development of reach specific water quality objectives (RSWQO) in the LAR. The review will also include a compilation of guidelines developed for other jurisdictions that may be applicable to the LAR.

As much work on the establishment of benchmarks has occurred as a result of the EIA process. Methods for determining RSWQO are well established and fall within one of the categories below. The consultant will use one or a combination of these to achieve contract deliverables.

Guidelines will be used as default objectives except where deemed inappropriate due to guidelines being exceeded by background concentrations or where guidelines are considered too high relative to background concentrations. Thus alternative objectives will be developed when guidelines are lacking or have been identified as being insufficient in some way. The consultant will evaluate the current list of VOCNs and identify where guidelines may be insufficient.


Golder Associates

Guidelines could be a mixture of existing numbers but priority is usually given to Alberta Ambient Water Quality Guidelines, CCME and USEPA guidelines where appropriate or others if rationalized in the context of the lower Athabasca River.

Methods considered for developing RSWQOs as a component of the literature review will be based on available information and will not include additional site – specific data collection. The method proposed for each VOCN will depend on the reason the parameter was identified as a VOCN (CEMA – WRS, 2003). The approach for each group of parameters may include one or more of the following, as identified in the proposal (Appendix IV): water quality guidelines (WQC), chronic effect benchmarks, background concentrations procedure (BCP), investigations level (IL) approach.

The rationale for use of these methods will be based on characteristics of the VOCN’s under consideration. As per proposal (Appendix IV) the approaches for categorization of each category of VOC’s include:

1) where guidelines are absent and there are known adverse affects on one or more water uses;

2) where endpoints, organisms or test conditions used in the derivation of guidelines were not relevant to the conditions of the LAR;

3) where guidelines are exceeded more then 50% of the time under natural condition in the LAR;

4) where guidelines do not take into account other water quality parameters that can affect toxicity, speciation, bioavailability or any other adverse effect s on the other water uses;

5) where a guideline is greater then the median concentration of the VOC in the LAR by a factor of 10; or

6) where other criteria cannot be strictly applied to parameters.

Aii) verify objectives based on guidelines

The guidelines, in particular those for human and wildlife health, will be subject to verification based on results of recent Environmental Impact Assessments (EIA). Proximity of predicted concentrations to identify thresholds will be compared to the magnitude of the exposure ratios (ER’s) identified in the human and wildlife health risk assessments.

Aiii) evaluate most sensitive water use or objective type

Where objectives are directly linked to specific water uses, parameters will be ranked according to their sensitivity of water uses and objectives types, to determine the most limiting objective. This will be applied as the RSWQO.

Task B) Evaluate VOCs with the approach from Task A

The WQTG has identified the VOCs where RSWQO would be most easily achieved given current available information or are specifically important (e.g. Polycyclic aromatic hydrocarbons - PAHs). These parameters include the following:


Golder Associates

• chronic toxicity; • total dissolved solids; • sulphate; • sodium; • iron; • aluminum; • boron; • ammonia (excluding eutrophication effects); • molybdenum; • chloride; • PAH group 1 (dibenzo(a,h)anthracene, benzo(a)pyrene, methyl benzo(b&k)

fluoranthene/benzo(a)pyrene, c2substituted benzo(b&k)fluoranthene/benzo(a)pyrene);

• PAH group 2 (benzo(a)anthracene/chrysene, methyl benzo(a)anthracene/chrysene, c2 substituted benzo(a)anthracene/chrysene, benzo(b&k)fluoranthene, indeno(c,d-123)pyrene);

• PAH group 3 (benzo(g,h,i)perylene, chrysene, carbazole, methyl carbazole, methyl carbazole, c2 substituted carbazole; excluding development of CEB);

• PAH group 4 (acenaphthene, methyl acenaphthene, acenaphthylene); • PAH group 5 (anthracene, phenanthrene, methyl phenanthrene/anthracene, c2

substituted phenanthrene/anthracene, c3 substituted phenanthrene/anthracene, c4 substituted phenanthrene/anthracene, 1-methyl-7-isopropyl-phenanthrene (Retene);

• PAH group 6 (biphenyl, methyl biphenyl, c2 substituted biphenyl); • PAH group 7 (fluoranthene, fluorene, methyl fluorene, c2 substituted fluorene); • PAH group 8 (naphthalene, methyl naphthalene, c2 substituted naphthalene,

c3substituted naphthalene, c4 substituted naphthalene); and • PAH group 9 (methyl fluoranthene/pyrene, pyrene).

(Note that the PAH groups described above include 5 of the 37 VOCs described in the request for proposal (RFP) as follows: fluorene, naphthalene, alkyl-substituted PAHs, biphenyl and alkyl substituted biphenyl. )

B.i.) Data collection and compilation

Data will be collected, compiled and analyzed as required, to develop the RSWQOs. Data acquisition should include toxicity (acute and chronic), applicable water quality limits / guidelines / threshold values, LAR quality and flow data and mine water quality and flow data All data compilation and calculations will include quality control procedures.

B.ii) Compilation of guidelines for relevant use

The single approach recommended for use in the LAR from Task A, will be applied to the parameters listed on page 12, for the Lower Athabasca River. The RSWQO are to apply to the entire river from Ft. McMurray to Lake Athabasca as a first priority. The adequacy or applicability of the RSWQO for the LAR to regional tributaries, pit lakes (at the time of the proposed discharge) and Lake Athabasca, will also be discussed.


Golder Associates

Appropriate guidelines for the various uses will be compiled. The primary sources for guidelines are as follows:

• U.S. EPA, CCME and Alberta guidelines for the protection of aquatic life • U.S. EPA guidelines for the protection of human health will be used as the basis

for human health thresholds • Canadian drinking water guidelines will be used as the basis for municipal and

domestic water supply thresholds • Canadian agriculture guidelines will be used as the basis for wildlife thresholds.

B.iii) Develop chronic effects benchmarking for selected substances

• Chronic effects benchmarking (CEB) will be assessed to develop chronic guidelines fro the protection of aquatic life, using species distributions previously used in recent EIAs. Potential parameters are identified as: aluminum, boron, iron, molybdenum, sulphate, PAHs (groups 2 and 6) and TDS (based on the approach described in Section 5.1.2. of proposal – Appendix IV) Development of a CEB for sodium however is included under Task C.

B.iv) Develop objectives based on background concentrations for selected substances

Objectives based on background concentrations for selected substances will be developed. Distribution of background concentrations for the LAR as identified in recent EIAs will be used to calculate objectives based on background concentrations.

B.v) Apply the Investigation Level Interface Model to the Lower Athabasca River

The investigations level (IL) interface model, will be applied to the Lower Athabasca River, as was applied for CEMA to the Muskeg River (CEMA 2005). Tasks that comprise this work item include:

• defining nodes and snapshots; • initially scoping candidate substances; • identifying source loads (i.e., seepages, muskeg/overburden dewatering, pit

lakes and individual tributaries) and their proportional contribution to concentrations at each node;

• applying statistics to distinguish oil sands development contributions from background substance loading;

• establishing investigation levels that are protective of all water uses and are indicative of developments functioning as proposed in recent EIA applications (Imperial 2005; Shell 2005; Suncor 2005);

• identification of uncertainty; and • identification of future research needs and data gaps.

The IL approach will be applied to the candidate substances specified in Appendix II as well as other parameters that are currently included in the information obtained for the LAR instream flow needs assessment (AENV, 2005) model described below. Modelling


Golder Associates

of the extended parameter list will be used to prioritize the substances addressed under Task C. The tools developed for the Muskeg River IL model will be modified for the Athabasca River to show ILs, RSWQOs and contributions of loading sources (e.g., seepages, point source discharges, tributaries and background).

The IL assessment will be undertaken by developing an interface model. The model will allow the user to display graphical output of relevant objectives and predicted substance concentrations for selected nodes and snapshots. The IL assessment will include additional parameters beyond the 12 identified for consideration in Task B. The additional information will be used to prioritize substances for consideration in Task C.

B.vi) Evaluate most sensitive water use or objectives type.

Final overall RSWQO will be developed once the guidelines have been compiled and objectives calculated for the CEB, background concentrations and IL approaches.

B.vii) Determine adequacy of objectives to other regional surface water.

A secondary objective will be to examine the suitability of this approach for assigning RSWQOs to regional tributaries, pit lakes and Lake Athabasca. Factors that may indicate that an alternate approach may be required will be identified. These factors will include the potential water uses, significance of the watercourses and waterbodies, background water quality and approved and potential developments within the corresponding watersheds.

Task C) Evaluate remaining VOCs

Items 2 and 3 for this workplan task are not included within this contract however may be included at a later date. Although related to Task A and Task B, items 2 and 3 for Task C will be initiated in 2007, subject to the 2007 WQTG budget. Items 1 and 4 for Task C are doable within the current specified contract and budget.

The remaining VOCs identified for analysis under Task C are as follows:

• total nitrogen; • total phosphorus; • ammonia (eutrophication effects); • potassium; • antimony; • cadmium; • chromium; • lithium; • nickel; • strontium; • vanadium; • naphthenic acids; • toluene; • xylenes;


Golder Associates

• acenaphthene; • acenaphthylene; • dibenzothiophene; • alkyl-substituted dibenzothiophene; • di (2-ethylhexyl) phthalate (DEHP); • methyl isobutyl carbinol (MIBC); • acrylamide; • fish tainting; • oil and grease; and • total petroleum hydrocarbons.

The approach proposed for Task B can also be applied for the remaining VOCs, which include: developing chronic effects benchmarks, developing objectives based on background concentrations and application of the IL model. Variations to these components for Task C include:

C.i) Develop chronic effects benchmarks (CEB)

Item 1

CEBs to be developed for antimony, cadmium, chromium, strontium and vanadium, based on .species sensitivity distributions completed as components of previous Environment Impact Assessments (EIAs) for oil sands. This work is to be conducted along with Tasks A and B.

Item 2

A detailed literature review along with species sensitivity distribution database would be required to develop CEBs for naphthenic acids, total dissolved solids, sulphate, sodium, potassium, lithium, PAH group 3, acenaphthylene, dibenzothiophene, alkyl substituted dibenzothiophene, methyl isobutyl carbinol, acrylamide, oil and grease, and total petroleum hydrocarbons because a. Development of CEBs for these parameters, may be beyond the financial limitations of this study. Additionally, it may not be desirable or feasible to develop CEBs for some of these parameters. The following Item 3 is therefore proposed as an alternative.

Item 3

Further examination of the parameters listed under Item 2 will be undertaken to determine whether a CEB need be developed or whether there is an alternative approach to identify an objective for the protection of aquatic life.

Item 4

Objectives based on CEBs will be developed for beryllium, copper, manganese, silver, sulphide, total phenolics and zinc (note these parameters were not identified as VOCs in the RFP). This work is to be conducted along with Tasks A and B.


Golder Associates

C.ii) Development of Objectives Based on Background Concentrations

Based on a preliminary review of the parameters included in Task C, the proposed approach may require objectives based on background concentrations for total nitrogen, total phosphorus, ammonia, cadmium, chromium, nickel, toluene, acenaphthene and di (2 ethylhexyl) phthalate.

Item 1

Objectives based on background concentrations will be developed for total nitrogen, total phosphorus, ammonia, cadmium, chromium and nickel, because the data has been compiled as a component of previous oil sands EIAs.

Item 2

Developing objectives based on background concentrations for toluene, acenaphthene and di (2ethylhexyl) phthalate would require a greater level of effort because these parameters were not included in the assessment for previous oil sands EIAs. Therefore this item is no longer included in the work plan.

Item 3

Further examination of the parameters listed under Item 2 will be undertaken to determine whether an objective based on background concentrations need be developed.

Item 4

Objectives based on background concentrations will be developed for arsenic, barium, beryllium, calcium, copper, DOC, lead, magnesium, manganese, mercury, selenium, silver, sulphide, total phenols and zinc. These parameters were not identified as VOCs in RFP, however, the development of objectives based on background concentrations would provide additional information on the ranking of parameters that have been used in previous assessments.

C.iii) Apply the Investigations Level Interface Model to the Athabasca River

Item 1

ILIM will be applied for total nitrogen, total phosphorus, cadmium, chromium, nickel, potassium, antimony, naphthenic acids and fish tainting.

Item 2

Applying ILIM for lithium, toluene, xylene, acenaphthene, acenaphthylene, dibenzothiophene, alkyl-substituted dibenzothiophene, di (2ethylhexyl) phthalate, methyl isobutyl carbinol, acrylamide, oil and grease, and total petroleum hydrocarbons would require a greater level of effort because these parameters were not included in the


Golder Associates

assessment for previous oil sands EIAs. Therefore this item is no longer included in the work plan.

Item 3

Further examination of the parameters listed under Item 2 could be undertake to determine whether an objective based on ILIM need be developed.

Item 4

ILIM could be applied, at minimal cost, for arsenic, barium, beryllium, calcium, copper, DOC, lead, magnesium, manganese, mercury, selenium, silver, sulphide, total phenols and zinc. These parameters were not identified as VOCs in the RFP, however, the ILIM approach would provide additional information on the ranking of parameters that have been used in previous assessments.

C.iv) Summary of Approach

Each item under each task is associated with a different group of parameters. Parameters under Item 1 include VOCs that may be able to be included within Task B using the corresponding approach to objective development. Parameters included under Item 4 may also be included under Task B. Parameters under Items 2 and 3 are unusual parameters as they have either not been assessed in recent oil sands EIAs or have been assessed using an alternative approach. Applying the approach described in Task B to these parameters would likely be expensive and may not be appropriate therefore, it has been recommended to use the approach described under Item 3 as an alternative to the approach identified under Item 2. These parameters would need to be further researched to determine whether they should be included in the ILIM and / or whether CEB should be developed for them. A summary table of all the VOCs, as well as the additional parameters identified under Item 4 is provided in Appendix III.

CEMMa

A I-10 Athabasca River Reach Specific y 2007 Water Quality Objectives

Golder Associates

APPENDIX II

Summary of Variables of Concern as per Identified within Development of Reach Specific Water Quality Objectives for Variables of Concern on the Lower

Athabasca River: Identification of Variables of Concern and Assessment of the Adequacy of Available Guidelines (CEMA – WRS, 2003)

Summary of VOCNs (CEMA, WRS 2003)

Ammonia Total Nitrogen Total Phosphorus Sulphate Sodium Potassium Chloride Aluminum Antimony Boron

Cadmium Chromium Lithium Molybdenum Nickel

Strontium Vanadium Naphthenic Acids Toluene Xylenes

Acenaphthene Acenaphthylene Fluorene Naphthalene Alkyl substituted PAHs

Dibenzothiophene Alkylsubstituted Dibenzothiophenes

Biphenyl Alkyl substituted Biphenyl

Di(2ethylhexyl) phthalate (DEHP)

Methyl isobutyl Carbinol (MIBC)

Acrylamide Fish Tainting Oil & Grease Total

Petroleum Hydrocarbons

Chronic Toxicity Acute Toxicity Total Dissolved Solids Iron


Golder Associates

APPENDIX III

Summary of Approach for VOC’s and Other Parameters

Table 1 Summary of Approach for VOCs and Other Parameters

Item 1 Item 2 (Not Recommended) Item 3 (Recommended) Item 4

Parameter Develop CEB

Develop Objectives Based on

Background Concentrations

Apply ILIM

Develop CEB

Develop Objective based on


Apply ILIM

Evaluate Parameter

for Development

of CEB or other effect threshold

Evaluate Parameter for

Development of Objective Based on Background Concentration

Evaluate Parameter

for Application

of ILIM

Develop CEB



Apply ILIM

VOCs identified in RFP

acute toxicity na na x

chronic toxicity na na x

total dissolved solids x x x x

sulphate x x x x

sodium x x x x

iron x x x

aluminum x x x

boron x x x

ammonia (excluding eutrophication effects) na x x

molybdenum x x x

chloride x x

PAH group 1 (dibenzo(a,h)anthracene, benzo(a)pyrene, methyl benzo(b&k) fluoranthene/ benzo(a)pyrene, c2 substituted benzo(b&k)fluoranthene/benzo(a)pyrene)

na x x `


Golder Associates





Apply ILIM

Develop CEB



Apply ILIM

Evaluate Parameter

for Development




Evaluate Parameter

for Application

of ILIM

Develop CEB



Apply ILIM

PAH group 2 (benzo(a)anthracene/chrysene, methyl benzo(a)anthracene/chrysene, c2 substituted benzo(a)anthracene/chrysene, benzo(b&k)fluoranthene, indeno(c,d-123)pyrene)

x x x

PAH group 3 (benzo(g,h,i)perylene, chrysene, carbazole, methyl carbazole, methyl carbazole, c2 substituted carbazole; excluding development of CEB)

x x x x

PAH group 4 (acenaphthene, methyl acenaphthene, acenaphthylene) na x x

PAH group 5 (anthracene, phenanthrene, methyl phenanthrene/anthracene, c2 substituted phenanthrene/anthracene, c3 substituted phenanthrene/anthracene, c4 substituted phenanthrene/anthracene, 1-methyl-7-isopropyl-phenanthrene (Retene))

na x x

PAH group 6 (biphenyl, methyl biphenyl, c2 substituted biphenyl) x x x

PAH group 7 (fluoranthene, fluorene, methyl fluorene, c2 substituted fluorene) na x x

PAH group 8 (naphthalene, methyl naphthalene, c2 substituted naphthalene, c3 substituted naphthalene, c4 substituted naphthalene)

na x x

PAH group 9 (methyl fluoranthene/pyrene, pyrene) na x x

total nitrogen x x x x

total phosphorus x x x x


Golder Associates





Apply ILIM

Develop CEB



Apply ILIM

Evaluate Parameter

for Development




Evaluate Parameter

for Application

of ILIM

Develop CEB



Apply ILIM

ammonia (eutrophication effects) x x x x

potassium x x x x

antimony x x x

cadmium x x x

chromium x x x

lithium x x x x x x

nickel x x x x

strontium x x x

vanadium x x x

naphthenic acids x x x x

fish tainting na x x

toluene x x x x x x

xylenes x x x x x x

acenaphthene x x x x x x

acenaphthylene x x x x x x

dibenzothiophene x x x x x x

alkyl-substituted dibenzothiophene x x x x x x

di (2-ethylhexyl) phthalate (DEHP) x x x x x x

methyl isobutyl carbinol (MIBC) x x x x x x

acrylamide x x x x x x

oil and grease x x x x x x

total petroleum hydrocarbons x x x x x x

A I-14 Athabasca River Reach Specific y 2007 Water Quality Objectives

Golder Associates





Apply ILIM

Develop CEB



Apply ILIM

Evaluate Parameter

for Development




Evaluate Parameter

for Application

of ILIM

Develop CEB



Apply ILIM

Additional Parameters

arsenic x x

barium x x

beryllium x x x

calcium x x

copper x x x

DOC x x

lead x x

magnesium x x

manganese x x x

mercury x x

selenium x x x

silver x x x

sulphide x x x

total phenols x x x

zinc x x x

CEMMa


Golder Associates

2 METHODS AND STUDY TASKS FROM ORIGINAL PROPOSAL

2.1 TASK A – IDENTIFY METHODS FOR ESTABLISHING RSWQO, EVALUATE AND RECOMMEND METHODS FOR THE ATHABASCA RIVER

2.1.1 Review and Summarize Literature

Identification of the most appropriate approach for assigning RSQWO will involve a literature review of methods applied by agencies in other jurisdictions. A brief summary of this literature is listed in Table 2.

The literature review will include a summary of the methods used by each agency to derive guidelines or objectives, a summary of the applicable guidelines and a discussion of the suitability of each method for developing objectives for the LAR.

Table 2 Sources and Approaches for Establishing Water Quality Objectives

Source Driving Force Approach

Alberta Environment General guidelines for freshwater protection and development of RSWQOs

Develops general guidelines to form basis of RSWQOs

Task force comprised of local stakeholders and government

Intensifying urban development along with agriculture in the Elbow River watershed, Alberta

Derives consensus-based warning and advisory levels that consider end-use thresholds

Canadian Council of Ministers of the Environment

General protection of Canada’s freshwater Develops conservative protective measures based on toxicological data

British Columbia Ministry of the Environment

Developing RSWQOs for British Columbia and Yukon

Applies several methods for assigning RSWQOs to toxicants that are non-persistent and do not demonstrate cumulative effects

Ontario Ministry of Environment and Energy

Protection of aquatic life, recreational water uses and aesthetics

Sets general objectives with site-specific objectives where more stringent measures are required

U.S. EPA Defining the goals for a waterbody by designating its uses, setting criteria to protect those uses and protecting waterbodies from pollutants

Sets national water quality standards and approves site-specific objectives set by states

World Health Organization Development of water quality guidelines for drinking, bathing and recreation

Sets “health-based targets” for microbial and chemical parameters

Australian and New Zealand Environment and Conservation Council

Protection and management of the environmental values supported by water resources

Sets general guidelines and site-specific objectives based on cost-benefit analysis programs involving input from stakeholders or local jurisdictions

Golder Associates for Industry Members

Environmental Impact Assessments in Athabasca River watershed

Derives benchmark concentrations for various parameters included in EIA predictions

Golder Associates for CEMA

Planned oil sands developments in the Muskeg River Watershed

Develops investigation levels for several nodes and snapshots based on EIA predictions


Golder Associates

2.1.2 Recommend Methods for Developing RSWQOs

Although the RFP requests that an approach be recommended as part of the project work, with subsequent application of that method to VOCs, this work plan assumes a specific method has already been selected for developing objectives for the 12 VOCs specified under Task B in the RFP. The rationale for presupposing a specific method is:

• the level of effort can only be accurately defined based on a specific method for developing RSWQOs (as they vary widely and the budget is pre-determined for this job)

• we are already familiar with most of the methods described in the literature and believe that many may not be appropriate for application to the LAR because they require collection of toxicity data or would otherwise be prohibitively expensive.

Should the literature review indicate that there are more appropriate methods consistent with the current budget, we will, at that time, propose these alternative method(s) to CEMA.

The budget provided assumes that the approach described in this section will be followed. However, the final method employed will depend on the outcome of Task A as well as feedback from CEMA. Given that the final approach used could be subject to an iterative process of feedback and approval from CEMA, appreciable deviations from the approach described in this proposal may be subject to a corresponding change in budget.

Step 1 - Evaluate Proposed Method Based on Literature Review The suitability of the proposed method and alternative methods will be evaluated based on information from the literature review.

Step 2 – Define Objectives for Relevant Water Uses Guidelines for various uses will be used as default objectives. Alternative objectives will be developed only when guidelines are lacking or have been identified as being insufficient in some way. Guidelines considered will be based on those described in Attachment 2 of the RFP. Note that no guidelines or thresholds have been identified for industrial water supply, transboundary obligations or Wood Buffalo National Park needs; therefore, these uses will not be considered.

A number of methods will be considered for developing objectives as a component of the literature review. Data requirements of each of these methods and data availability will be key for selecting the most appropriate method(s). For example, the water-effects ratio approach is one of the most conventional methods for developing site-specific objectives; however, the approach requires site-specific toxicity data (i.e., toxicity data using dilution water from the site), which is not available or limited for the LAR. Collection of site-specific data is beyond the scope and budget of the study. Consequently, the following alternate methods of developing objectives have been identified.


Golder Associates

The method proposed for each VOC will depend on the reason the parameter was identified as a VOC, as described in Attachment 2 of the RFP. The approach for each group of parameters may include one or more of the following techniques:

Water Quality Guidelines (WQG) for identified water uses applicable to the LAR. Guidelines, where available and relevant to the LAR can be used as objectives.

Chronic Effect Benchmarks (CEBs) based on available toxicity data as used in recent EIAs (Imperial 2005; Shell 2005; Suncor 2005). Chronic effects benchmarks can be used as objectives for the protection of aquatic life, which will often be the most sensitive water use. The approach for developing CEBs is provided in Attachment III.

Background Concentrations Procedure (BCP) as outlined by CCME (CCME 2003). The natural background concentrations of a substance in water are determined and these levels are used to define acceptable water quality conditions at the site under consideration.

Investigation Levels (IL) Approach as described in the Muskeg River Watershed Integrity Investigation Levels Study (CEMA 2005). Investigation Levels are instream substance concentrations that are dynamic and unique for each location and time period, reflective of continually changing operations. However, these levels must be protective of the aquatic ecosystems. RSWQOs could be set relative to the IL identified.

The rationale for use of the methods described above will be based on characteristics of the VOCs under consideration. The approach for each category of VOCs is described below. Note that there are some discrepancies in Attachment 2 of the RFP and the parameters identified under the categories below are based on our general interpretation of the information provided in the attachment.

1) Guidelines are absent and there are known adverse affects on one or more water uses

Of the 12 VOCs identified for consideration in Task B, boron, sodium, sulphate, TDS and some PAHs fall under this category based on protection of aquatic life. For parameters where guidelines for the protection of aquatic life are lacking, CEBs will be developed and applied as objectives for the protection of aquatic life.

For the 12 VOCs identified for consideration in Task B, guidelines were available for all uses where potential effects were known for the VOC. Therefore, none of the parameters were classified under this category due to non-aquatic life uses.

2) Endpoints, organisms or test conditions used in the derivation of guidelines were not relevant to the conditions of the LAR

The approach for this category is the same as the approach for the first category. CEBs can be calculated using only toxicity data that is relevant to the site. Of the


Golder Associates

12 VOCs identified for consideration in Task B, aluminum falls under this category.

3) Guidelines are exceeded more than 50% of the time under natural conditions in the LAR

Of the 12 VOCs identified for Task B, aluminum and iron fall under this category (although iron was not addressed in Attachment 2 of the RFP).

For parameters where it can be shown that natural concentrations in the river exceed the guidelines more that 50% of the time, objective development will be based on the background concentrations procedure and the IL approach. CEBs will also be calculated for these parameters as effects thresholds may be higher than observed background concentrations. Objectives derived based on the three approaches will be compared and evaluated in Step 4.

4) Guideline does not take into account other water quality parameters that can affect toxicity, speciation, bioavailability or any other adverse effects on other water uses

This category applies primarily to nutrients, which may have indirect effects on aquatic life that are not associated with direct toxic effects. Of the 12 VOCs identified for consideration in Task B, ammonia falls under this category because the guideline may be insufficient to protect against stimulating effects on algal growth.

Eutrophication effects must be evaluated taking into account other nitrogen species as well as phosphorus and therefore ammonia will be considered as a component of Task C.

5) Guideline is greater than the median concentration of the VOC in the LAR by a factor of 10

Of the 12 VOCs identified for Task B:

• existing guidelines for the protection of aquatic life are greater than the median concentration of the VOC in the river by a factor of 10 for chloride, molybdenum and acute and chronic toxicity

• existing drinking water guidelines are greater than the median concentration of the VOC in the river by a factor of 10 for boron, chloride and sodium.

For the parameters where existing guidelines are greater than the median concentration of the VOC in the river by a factor of 10, a lower objective required to protect water uses may not be warranted. Setting objectives much lower than guidelines must be based on a management strategy such as the IL approach, or alternatively, on the background concentrations procedure, rather than on effects thresholds. Therefore RSWQOs for these parameters will be based on the background concentrations procedure and the IL approach. Objectives derived based on the two approaches will be compared and evaluated in Step 4.


Golder Associates

6) Parameters where the other criteria cannot be strictly applied Some organics could fall under this category because concentrations in the LAR are non-detectable while significant levels can be measured in some wastewaters. None of the 12 VOCs identified for Task B are included in this category. Organic parameters considered under Task C may require modified approaches to develop RSWQOs.

Step 3 – Verify Objectives Based on Guidelines The guidelines considered, particularly those for human and wildlife health, will be subject to verification based on the results of recent EIAs. Proximity of predicted concentrations to identified thresholds will be compared to the magnitude of the exposure ratios (ERs) identified in the human and wildlife health risk assessments. ERs are based on multiple pathways and, although methods exist for translating ERs into objectives, those methods cannot be used due to the budget restraints of the project. However, ERs can be used to verify that effects ratios and guidelines can provide similar conclusions regarding human and wildlife health effects.

Step 4 – Evaluate Most Sensitive Water Use or Objective Type In some cases, such as the background concentrations method or IL approach, objectives are not directly linked to specific water uses. In other cases, guidelines or CEBs may be linked to a specific water use. The sensitivity of water uses and objective types will be ranked for each parameter to identify the most limiting objective, which will be applied as the RSWQO.

2.2 TASK B – EVALUATE VOCS WITH THE APPROVED METHOD

2.2.1 Data Collection and Compilation

Data will be collected, compiled and analyzed, as required, to develop the RSWQOs. Data acquisition may include toxicity data, applicable water quality limits/guidelines/threshold values, LAR quality and flow data and mine water quality and flow data. Flow and water quality data for the LAR and mine waters will be based on the data used in recent EIAs (Imperial 2005; Shell 2005; Suncor 2005). All data compilation and calculations will include quality control procedures.

2.2.2 Compile Guidelines for Relevant Uses

Appropriate guidelines for the various uses will be compiled. The primary sources for guidelines are as follows:

• U.S. EPA, CCME and Alberta guidelines for the protection of aquatic life • U.S. EPA guidelines for the protection of human health will be used as the

basis for human health thresholds • Canadian drinking water guidelines will be used as the basis for municipal

and domestic water supply thresholds


Golder Associates

• Canadian agriculture guidelines will be used as the basis for wildlife thresholds.

2.2.3 Develop Chronic Effects Benchmarks for Selected Substances

Previous species sensitivity distributions completed as parts of Environmental Impact Assessments (EIAs) for oil sands (Imperial 2005; Shell 2005; Suncor 2005) can be used to develop CEBs, which function as chronic guidelines for the protection of aquatic life.

We propose development of chronic effects benchmarks for aluminum, boron, iron, molybdenum, sulphate, PAHs (groups 2 and 6) and TDS based on the approach described in Section 5.1.2. Development of a CEB for sodium will be deferred to Task C.

2.2.4 Develop Objectives Based on Background Concentrations for Selected Substances

Site-specific objectives based on background concentrations can be developed in a number of ways (CCME 2003). Objectives can be based on the upper limit of the background concentrations (for example the 90th percentile or alternative statistic) or on an increment above background such as 10%. Distributions developed for the LAR as a component of recent EIAs will be used to calculated objectives based on background concentrations.

2.2.5 Apply the Investigations Level Interface Model to the Athabasca River

The Investigations Level Interface Model (ILIM) has been applied to the Muskeg River (CEMA 2005) by members of the proposed study team, and a similar approach is proposed for the LAR. The following sub-tasks will be included in applying the investigation levels approach to the LAR:

• defining nodes and snapshots • initially scoping candidate substances • identifying source loads (i.e., seepages, muskeg/overburden dewatering, pit

lakes and individual tributaries) and their proportional contribution to concentrations at each node

• applying statistics to distinguish oil sands development contributions from background substance loading

• establishing investigation levels that are protective of all water uses and are indicative of developments functioning as proposed in recent EIA applications (Imperial 2005; Shell 2005; Suncor 2005)

• identification of uncertainty • identification of future research needs and data gaps.


Golder Associates

Nodes and snapshots have already been defined as a component of the instream flow needs assessment for the LAR and an interface has been developed that could form a basis for the ILIM interface although it did not include contributing loadings from seepages, points sources tributaries and background (Golder 2006). The IL approach will be applied to the candidate substances specified in the RFP as well as other parameters that are currently included in the model described below. Modelling of the extended parameter list will be used prioritize the substances addressed under Task C. The tools developed for the Muskeg River will be modified for the Athabasca River to show ILs, RSWQOs and contributions of loading sources (e.g., seepages, point source discharges, tributaries and background).

The IL assessment will be undertaken by developing an interface model. The model will allow the user to display graphical output of relevant objectives and predicted substance concentrations for selected nodes and snapshots. A sample of the graphical interface is shown in Figure 1.

The IL assessment will include additional parameters beyond the 12 identified for consideration in Task B. The additional information will be used to prioritize substances for consideration in Task C.

Figure 1 Investigation Levels Sample Interface

The ILIM will be based on predictions from the Athabasca River Model (ARM). ARM is an Excel-based program used to simulate water quality in the Athabasca


Golder Associates

River from downstream of Fort McMurray to the Athabasca River Delta. It is a 2-dimensional model that can predict how substance concentrations vary across the width and length of the Athabasca River, between Fort McMurray and the Athabasca River Delta. The Athabasca River Model is an analytical model that works by solving the river dispersion equations described by Fischer et al. (1979). It includes point source discharges, tributary inflows and seepage flows, as well as inputs from the Fort McMurray Wastewater Treatment Plant. It also accounts for water withdrawals, and makes the assumption that once a substance enters the river it remains in the water column. In other words, decay, settling, partitioning and other removal mechanisms are ignored. The Athabasca River Model will be used to assess how existing, approved and planned developments, may affect water quality in the Athabasca River, from Fort McMurray to the Athabasca River Delta. For this project, the model will be run dynamically to produce daily estimates of in-stream concentrations over several decades. Predicted concentrations at regulatory mixing zone boundaries (AEP 1995) will then be compared to baseline levels, background concentrations and applicable water quality guidelines. A far-field mixing zone boundary will be established across the width of the Athabasca River just upstream of the Embarras River.

The Athabasca River Model was initially calibrated using the results of dye tracer studies completed in 1995 (e.g., Golder 1995). The model calibration was then updated using the information collected from a CEMA-sponsored dye study completed in 2003 (Trillium and Hydrographics 2003, Golder 2004). During its initial development in the mid-1990s, the model was validated by comparing predicted results to those generated by the National Water Research Institute, who had also developed a model for the lower Athabasca River watershed [as described in Booty et al. (1996)]. More recently, the conclusions drawn from the model predictions have been validated through the Regional Aquatics Monitoring Program (RAMP 2006).

Water withdrawal rates by oil sands operators will be estimated using the information presented in the recent CEMA report entitled “A Compilation of Information and Data of Water Supply and Demand in the Lower Athabasca River Reach” (Golder 2003).

Golder is prepared to provide the model and input files to AENV.

2.2.6 Evaluate Most Sensitive Water Use or Objective Type

Once the guidelines have been compiled and objectives calculated for the CEB, background concentrations and IL approaches, this information will be used to develop a final overall RSWQO.

2.2.7 Determine Adequacy of Objectives to Other Regional Surface Waters

A secondary objective will be to examine the suitability of this approach for assigning RSWQOs to regional tributaries, pit lakes and Lake Athabasca. Factors that may indicate that an alternate approach may be required will be identified. These factors will include the potential water uses, significance of the


Golder Associates

watercourses and waterbodies, background water quality and approved and potential developments within the corresponding watersheds.

2.3 TASK C – EVALUATE REMAINING VOCS

After completion of the literature review, a work plan will be developed outlining the proposed approach for setting objectives for the remaining VOCs included in the RFP. The approach proposed for Task B can also be applied for the remaining VOC, however, special consideration may be needed for some VOCs including organic constituents, fish tainting and nutrients. It is anticipated that the approach will involve compilation of toxicity data and calculation of CEBs for sodium, potassium, lithium antimony, cadmium, chromium, nickel, strontium, vanadium and possibly additional organic parameters. It will also include grouping and objective development for organic constituents.


Golder Associates

3 REVISED METHODS AND STUDY TASKS FROM THE ADDENDUM

3.1 TASK A – IDENTIFY METHODS FOR ESTABLISHING RSWQO, EVALUATE AND RECOMMEND METHODS FOR THE ATHABASCA RIVER

3.1.1 Review and Summarize Literature

The literature review will include an itemized list of documents reviewed and a description of any methods found that may have applicability to development of reach specific water quality objectives (RSWQO) in the LAR. The review will also include a compilation of guidelines developed for other jurisdictions that may be applicable to the LAR.

The literature review will not include a summary of the methods used by each agency to derive guidelines or objectives or a discussion of the suitability of each method for developing objectives for the Lower Athabasca River (LAR).

3.1.2 Recommend Methods for Developing RSWQOs

Any new potentially applicable approaches identified as a component of the literature review will be described; however, detailed consideration of the feasibility of the approaches will not be undertaken.

No recommendation on approach will be provided. The revised scope assumes that the approach described in the proposal will be approved based on the information that has already been provided. The approach is consistent with approaches that have been used in the past to evaluate the potential effects to surface waters in the region.

3.2 TASK B – EVALUATE VOCS WITH THE APPROVED METHOD

No revision of the scope of Task B is proposed. Parameters identified as variables of concern (VOCs) included under Task B are as follows:

• acute toxicity; • chronic toxicity; • total dissolved solids; • sulphate; • sodium; • iron; • aluminum; • boron;


Golder Associates

• ammonia (excluding eutrophication effects); • molybdenum; • chloride; • PAH group 1 (dibenzo(a,h)anthracene, benzo(a)pyrene, methyl benzo(b&k)

fluoranthene/ benzo(a)pyrene, c2 substituted benzo(b&k)fluoranthene/benzo(a)pyrene);

• PAH group 2 (benzo(a)anthracene/chrysene, methyl benzo(a)anthracene/chrysene, c2 substituted benzo(a)anthracene/chrysene, benzo(b&k)fluoranthene, indeno(c,d-123)pyrene);

• PAH group 3 (benzo(g,h,i)perylene, chrysene, carbazole, methyl carbazole, methyl carbazole, c2 substituted carbazole; excluding development of CEB);

• PAH group 4 (acenaphthene, methyl acenaphthene, acenaphthylene); • PAH group 5 (anthracene, phenanthrene, methyl phenanthrene/

anthracene, c2 substituted phenanthrene/anthracene, c3 substituted phenanthrene/anthracene, c4 substituted phenanthrene/anthracene, 1-methyl-7-isopropyl-phenanthrene (Retene);

• PAH group 6 (biphenyl, methyl biphenyl, c2 substituted biphenyl); • PAH group 7 (fluoranthene, fluorene, methyl fluorene, c2 substituted

fluorene); • PAH group 8 (naphthalene, methyl naphthalene, c2 substituted

naphthalene, c3 substituted naphthalene, c4 substituted naphthalene); and • PAH group 9 (methyl fluoranthene/pyrene, pyrene).

Note that the PAH groups described above include 5 of the 37 VOCs described in the request for proposal (RFP) as follows: fluorene, naphthalene, alkyl-substituted PAHs, biphenyl and alkyl substituted biphenyl.

3.3 TASK C – EVALUATE REMAINING VOCS

The remaining VOCs identified for analysis under Task C are as follows:

• total nitrogen; • total phosphorus; • ammonia (eutrophication effects); • potassium; • antimony; • cadmium; • chromium; • lithium; • nickel; • strontium; • vanadium; • naphthenic acids; • toluene;


Golder Associates

• xylenes; • acenaphthene; • acenaphthylene; • dibenzothiophene; • alkyl-substituted dibenzothiophene; • di (2-ethylhexyl) phthalate (DEHP); • methyl isobutyl carbinol (MIBC); • acrylamide; • fish tainting; • oil and grease; and • total petroleum hydrocarbons.

This addendum describes a number of optional tasks that could be undertaken to support development of RSWQOs for the VOCs considered in Task C or to further evaluate the need for development of RSWQOs for those parameters.

3.3.1 Develop Chronic Effects Benchmarks

Based on a preliminary review of the parameters included in Task C, the proposed approach may require development of CEBs for naphthenic acids, sodium, potassium, lithium, antimony, cadmium, chromium, nickel, strontium, vanadium, PAH group 3, xylenes, acenaphthylene, dibenzothiophene, alkyl substituted dibenzothiophene, methyl isobutyl carbinol and acrylamide. The following alternative approach is now proposed:

Item 1 Species sensitivity distributions completed as a parts of previous Environment Impact Assessments (EIAs) for oil sands can be used to develop CEBs for antimony, cadmium, chromium, strontium and vanadium.

Item 2 There would be an additional level of effort required to develop CEBs for naphthenic acids, total dissolved solids, sulphate, sodium, potassium, lithium, PAH group 3, acenaphthylene, dibenzothiophene, alkyl substituted dibenzothiophene, methyl isobutyl carbinol, acrylamide, oil and grease, and total petroleum hydrocarbons because a detailed literature review would have to be completed and a database and species sensitivity distribution developed. Development of CEBs for these parameters, may be beyond the financial limitations of this study. Additionally, it may not be desirable or feasible to develop CEBs for some of these parameters. The following Item 3 is therefore proposed as an alternative.

Item 3 Further examination of the parameters listed under Item 2 will be undertaken to determine whether a CEB need be developed or whether there is an alternative approach to identify an objective for the protection of aquatic life.


Golder Associates

Item 4 Objectives based on CEBs will be developed for beryllium, copper, manganese, silver, sulphide, total phenolics and zinc (note these parameters were not identified as VOCs in the RFP).

3.3.2 Development of Objectives Based on Background Concentrations

Based on a preliminary review of the parameters included in Task C, the proposed approach may require objectives based on background concentrations for total nitrogen, total phosphorus, ammonia, cadmium, chromium, nickel, toluene, acenaphthene and di (2 ethylhexyl) phthalate.

Item 1 Objectives based on background concentrations will be developed for total nitrogen, total phosphorus, ammonia, cadmium, chromium and nickel, because the data has been compiled as a component of previous oil sands EIAs.

Item 2 Developing objectives based on background concentrations for toluene, acenaphthene and di (2ethylhexyl) phthalate would require a greater level of effort because these parameters were not included in the assessment for previous oil sands EIAs. Therefore this item is no longer included in the work plan.

Item 3 Further examination of the parameters listed under Item 2 will be undertaken to determine whether an objective based on background concentrations need be developed.

Item 4 Objectives based on background concentrations will be developed for arsenic, barium, beryllium, calcium, copper, DOC, lead, magnesium, manganese, mercury, selenium, silver, sulphide, total phenols and zinc. These parameters were not identified as VOCs in RFP, however, the development of objectives based on background concentrations would provide additional information on the ranking of parameters that have been used in previous assessments.

3.3.3 Apply the Investigations Level Interface Model to the Athabasca River

Item 1 ILIM will be applied for total nitrogen, total phosphorus, cadmium, chromium, nickel, potassium, antimony, naphthenic acids and fish tainting.


Golder Associates

Item 2 Applying ILIM for lithium, toluene, xylene, acenaphthene, acenaphthylene, dibenzothiophene, alkyl-substituted dibenzothiophene, di (2ethylhexyl) phthalate, methyl isobutyl carbinol, acrylamide, oil and grease, and total petroleum hydrocarbons would require a greater level of effort because these parameters were not included in the assessment for previous oil sands EIAs. Therefore this item is no longer included in the work plan.

Item 3 Further examination of the parameters listed under Item 2 could be undertake to determine whether an objective based on ILIM need be developed.

Item 4 ILIM could be applied, at minimal cost, for arsenic, barium, beryllium, calcium, copper, DOC, lead, magnesium, manganese, mercury, selenium, silver, sulphide, total phenols and zinc. These parameters were not identified as VOCs in the RFP, however, the ILIM approach would provide additional information on the ranking of parameters that have been used in previous assessments.

3.3.4 Summary of Approach

Each item under each task is associated with a different group of parameters. Parameters under Item 1 include VOCs that could readily be included under Task B using the corresponding approach to objective development. Parameters included under Item 4 could also readily be included under Task B, but were not identified as VOCs in the RFP. Parameters under Items 2 and 3 are unusual parameters as they have either not been assessed in recent oil sands EIAs or have been assessed using an alternative approach. Applying the approach described in Task B to these parameters would be expensive and may not be appropriate. For example, for fish tainting parameters it may be advisable to defer development of objectives until completion of the fish tainting research program that is currently underway. Therefore, we recommend the approach described under Item 3 as an alternative to the approach identified under Item 2. These parameters would be further researched to determine whether they should be included in the ILIM and/or whether CEB should be developed for them. A summary table of all the VOCs, as well as the additional parameters identified under Item 4 is provided in Table 1.


Golder Associates

4 REFERENCES


Booty, W.G., B.G. Brownlee, G.A. MacInnis and O. Resler. A Two-Dimensional Contaminant Fate and Transport Model for the Lower Athabasca. National Water Research Institute. NWRI Contribution No. 96-202

CCME (Canadian Council of Ministers of the Environment). 2003. Guidance on the Site-Specific Application of Water Quality Guidelines in Canada: Procedures for Deriving Numerical Water Quality Objectives.


De Beers. 2002. Snap Lake Diamond Project Environmental Assessment Report. Appendix IX.8 Site Specific Water Quality Benchmarks and Mine Water Discharge Toxicity Testing. Prepared by Golder Associates Ltd., Submitted to the Mackenzie Valley Environmental Impact Review Board February 2002.

Fischer, H.B., E.J. List, R.C.Y. Koh, J. Imberger and N. Brooks. 1979. Mixing in Inland and Coastal Waters. Academic Press, Inc. NY.

Golder (Golder Associates Ltd.). 1995. Mixing Characteristics of the Suncor Effluent Discharge to the Athabasca River. Prepared for Suncor Energy Inc.

Golder. 2003. Athabasca River Operational Discharges (Phase I). Submitted to CONRAD Environmental Research Group, Fort McMurray.

Golder. 2004. Athabasca River Model Update and Reach Segmentation. March 2004. Calgary, Alberta.

Golder. 2003b. A Compilation of Information and Data of Water Supply and Demand in the Lower Athabasca River Reach. Prepared for the CEMA Surface Water Working Group (SWWG).

Golder. 2006. Athabasca River Model Interface for Instream Flow Needs Assessment. Submitted to Alberta Environment.

Golder and Cantox (Golder Associates Ltd. and Cantox Environmental Inc.). 2002. Surface Water Quality and Human, Aquatic Biota and Wildlife Health for Jackpine Mine - Phase 1. Prepared for Shell Canada Limited. June 2002. 215 pp. + Appendices.

Imperial (Imperial Oil Resources Ventures Limited). 2005. Kearl Oil Sands Project. Mine Development. Volume 1 to 9. Submitted to Alberta Energy and Utilities Board and Alberta Environment. Prepared by Imperial Oil Resources Ventures Limited in Association with Golder Associates Ltd. Axys Environmental Consulting Ltd. Komex International Inc. and Nichols Applied Management. July 2005. Calgary, Alberta.

RAMP (RAMP Implementation Team). 2006. Regional Aquatics Monitoring Program (RAMP) 2005 Technical Report. Prepared for the RAMP Steering Committee. April 2006.


Golder Associates

Shell (Shell Canada Limited). 1997. Application for the Approval of Muskeg River Mine Project. Volumes 1, 2, 3 and 5. Submitted to Alberta Energy and Utilities Board and Alberta Environment. Prepared by Shell Canada Limited, Golder Associates Ltd., Komex International Inc., Conor Pacific Environmental Technologies Inc. and Nichols Applied Management. Calgary, AB. December 1997.

Shell. 2005. Muskeg River Mine Expansion Project Application and Environmental Impact Assessment. Volume 1,2, 3 and 4. Submitted to Alberta Energy and Utilities Board and Alberta Environment. Prepared by Shell Canada Limited in Association with Golder Associates Ltd. And Nichols Applied Management. April 2005. Fort McMurray, AB.

Suncor (Suncor Energy Inc.). 2005. Voyageur Project Application and Environmental Impact Assessment. Volumes 1A, 1B, 2, 3, 4, 5 and 6. Submitted to Alberta Energy and Utilities Board and Alberta Environment. Prepared by Suncor Energy Inc. Oil Sands in Association with Golder Associates Ltd. And Nichols Applied Management. March 2005. Fort McMurray, AB.

Trillium and Hydrographics (Trillium Engineering & Hydrographics Inc.). 2003. Measurement of Transverse Mixing Coefficients in the lower Athabasca River. Prepared for the CEMA Surface Water Working Group (SWWG).

TrueNorth (TrueNorth Energy L.P.). 2001. Fort Hills Oil Sands Project. Volume 3. Environmental Impact Assessment. Prepared by Golder Associates Ltd. Submitted to Alberta Energy and Utilities Board and Alberta Environmental Protection.

APPENDIX II

LITERATURE REVIEW

CEMA II-i Athabasca River Reach Specific May 2007 Water Quality Objectives

Golder Associates

TABLE OF CONTENTS

SECTION PAGE

II-1 INTRODUCTION ...................................................................................................1

II-2 APPROACHES FOR DEVELOPING REACH SPECIFIC WATER QUALITY OBJECTIVES ........................................................................................................2

II-3 GUIDELINES FROM OTHER JURISTICTIONS.....................................................3

II-4 REFERENCES ......................................................................................................6

LIST OF TABLES

Table II-1 Literature Sources for Approaches for Developing Reach Specific Water Quality Objectives ....................................................................................................2

Table II-2 Compilation of Guidelines from Other Jurisdictions.................................................4

CEMA II-1 Athabasca River Reach Specific May 2007 Water Quality Objectives

Golder Associates

II-1 INTRODUCTION

The literature review includes the following:

• Section II-2 provides a review of approaches to the development of reach-specific water quality objectives (RSWQO).

• Section II-3 provides a review and compilation of interjurisdictional guidelines that are not normally applied to the Lower Athabasca River (LAR) but may be applicable.


Golder Associates

II-2 APPROACHES FOR DEVELOPING REACH SPECIFIC WATER QUALITY OBJECTIVES

A review was undertaken to support the approaches described in the scope of work (Appendix I) and the study approach (Section 1). The documents reviewed are summarized in Table II-1.

Table II-1 Literature Sources for Approaches for Developing Reach Specific Water Quality Objectives

Source Relevant Information

Protocol to Develop Alberta Water Quality Guidelines for Protection of Freshwater Aquatic Life (AEP 1996)

Defines approach for developing guidelines based on toxicity data.

Report of the Upper Elbow River Instream Objectives Working Group (AENV 1999)

Derives consensus-based warning and advisory levels that consider end-use thresholds.

Guidance on the Site-specific Application of Water Quality Guidelines in Canada: Procedures for Deriving Numerical Water Quality Objectives (CCME 2003)

Defines procedures for deriving site-specific water quality objectives including the background concentration, recalculation, water effect ratio, and resident species procedures. Defines conditions when these procedures can be used.

A Protocol for Deriving Water Quality Guidelines for the Protection of Aquatic Life (CCME 1999)

Defines approach for developing guidelines based on toxicity data.

Methods for Deriving Site-Specific Water Quality Objectives in British Columbia and Yukon (MOEBC 1997)

Applies several methods for assigning reach specific water quality objectives to toxicants that are non-persistent and do not demonstrate cumulative effects. Methods are based on those outlined by CCME 2003.

Developing Water Quality Objectives in British Columbia: A Users Guide (MOEBC 1996)

Describes situations where site-specific water quality objects can replace water quality criteria.

Water Management Policies and Guidelines: Provincial Water Quality Objectives of the Ministry of Environment and Energy. (OMEE 1999)

Describes the process of replacement of general objectives with site-specific objectives where more stringent measures are required.

The Biotic Ligand Model, a Flexible Tool for Developing Site-Specific Water Quality Guidelines for Metals (Niyogi and Wood, 2004)

Presents a site specific approach to deriving water quality objectives for metals, recognizing the importance of metal complexation by abiotic ligands (dissolved organic matter, carbonate, sulphide etc.) to metal toxicity.

Guidance on Human Health Preliminary Quantitative Risk Assessment (HC 2004)

Defines approach for developing risk-based human and wildlife health thresholds.

Development and Adoption of Nutrient Criteria into Water Quality Standards (U.S. EPA 2001)

Explains national water quality standards and approval process for site-specific nutrient objectives set by states.

Guidelines for Drinking Water Quality (WHO 2002) Describes methods for developing health based targets for drinking water.

Muskeg River Watershed Integrity Investigation Levels (CEMA 2005)

Provides an example of how investigation levels can be used to set site-specific water quality management targets.

Water Quality Guidelines (NWQMS 2000) Sets general guidelines and site-specific objectives based on cost-benefit analysis programs involving input from stakeholders or local jurisdictions.

CEMMa

A II-3 Athabasca River Reach Specific y 2007 Water Quality Objectives

Golder Associates

II-3 GUIDELINES FROM OTHER JURISDICTIONS

A detailed list of interjurisdictional guidelines that may be applicable to the LAR is provided in Table II-2. Guidelines sources are:

• The World Health Organization drinking water guidelines (human health and aesthetic; WHO 2002);

• United Kingdom drinking water guidelines (human health and aesthetic; UKDWI 2002);

• The Ontario Ministry of Environment and Energy Guidelines for the protection of aquatic life (OMEE 2002);

• The British Columbia Ministry of Environment guidelines for the protection of aquatic life, drinking water (human health and aesthetic) and wildlife (MOEBC 1998); and

• The Australian National Water Quality Management System Guidelines for the protection of aquatic life and human health (NWQMS 2000).


Table II-2 Compilation of Guidelines from Other Jurisdictions

WHO Drinking Water Guidelines(d)

United Kingdom Drinking Water Guidelines(e) BC Water Quality Guidelines(f)

Ontario Guidelines(g) Australian Guidelines(h)

Protection of Aquatic Life Constituent Units

Health Based Aesthetic Health Based Aesthetic Instantaneous 30 day mean

Drinking Water

Wildlife Health

Protection of Aquatic Life


Drinking Water

Major Ions calcium mg/L - - - - - - - - - - - chloride mg/L - 250 - 250 600 150 250(b) 600 - - 250(b)

magnesium mg/L - - - - - - - - - - - sodium mg/L - 200 - 200 - - - - - - 180(b)

sulphate mg/L - 250 - 250 100 50 500(b) - - - 500 sulphide mg/L - - - - - - - - - 0.0005 0.05(b)

total dissolved solids mg/L - 1000 - - - - - - - - 500(b)

Nutrients ammonia mg/L - 1.5 - 0.5 - - - - 2.44 0.32 0.5(b)

total nitrogen(c) mg/L 11.3 - 50 - 200 40 10 10 - - - total phosphorus mg/L - - - - - - - - - - - dissolved organic carbon mg/L - - - - - - - - - - - Toxicity acute toxicity Tua - - - - - - - - - - - chronic toxicity Tuc - - - - - - - - - - - fish tainting TPU - - - - - - - - - - - General Organics naphthenic acids mg/L - - - - - - - - - - - total phenolics mg/L - - - - - - - - 0.001(a) - - Total Metals aluminum mg/L - 0.2 - 0.2 0.1 0.05 0.2 5 0.075 0.027 0.2(b)

antimony mg/L 0.02 - 0.005 - - - - - - - 0.003 arsenic mg/L 0.01 - 0.01 - - 0.005 0.025 0.025 0.005(a) 0.001 0.007 barium mg/L 0.7 - - - - - - - - - - beryllium mg/L - - - - - - - - 1.1 - - boron mg/L 0.05 - 1 - - 1.2 5 5 0.2(a) 0.09 0.3 cadmium mg/L 0.003 - 0.005 - - - - - 0.0002 0.00006 0.002 chromium mg/L 0.05 - 0.05 - - - - - 0.001 0.00001 0.05 copper mg/L 2 - 2 - 0.002 18.45 0.5 0.3 0.005 - - iron mg/L - - - 0.2 - - - - 0.3 - - lead mg/L 0.01 - 0.025 - - - 0.05 0.1 0.025 0.001 0.01 manganese mg/L 0.4 - - 0.05 2.2 1.3 - - - 1.2 0.05 mercury mg/L 0.001 - 0.001 - - - 0.001 - 0.002 0.00006 0.001 molybdenum mg/L 0.07 - - - 2 1 0.25 0.05 0.04(a) - 0.05 nickel mg/L 0.02 - 0.02 - - - - - 0.025 0.008 0.02 selenium mg/L 0.01 - 0.01 - - 0.002 0.01 0.004 0.1 0.005 0.01 silver mg/L - - - - 0.003 0.0015 - - 0.0001 - - strontium mg/L - - - - - - - - - - - vanadium mg/L - - - - - - - - 0.006(a) - - zinc mg/L - 3 - - 0.8 0.2 5 - 0.02(a) 0.0024 3(b)

A II-5 Athabasca River Reach SpecMay 2007 Water Quality Objectiv

ific es

Table II-2 Compilation of Guidelines from Other Jurisdictions (continued)

Golder Associates

WHO Drinking Water Guidelines(d)

United Kingdom Drinking Water Guidelines(e) BC Water Quality Guidelines(f)

Ontario Guidelines(g) Australian Guidelines(h)

Protection of Aquatic Life Constituent Units

Health Based Aesthetic Health Based Aesthetic Instantaneous 30 day mean

Drinking Water

Wildlife Health



Drinking Water

PAH Groups PAH group 1 µg/L 0.7 - 0.01 - - 0.01 0.01 - - - - PAH group 2 (including benzo(a)anthracene) µg/L - - 0.1 - - 0.1 - - 0.0004(a) - -

PAH group 3 µg/L - - 0.1 - - - - - - - - PAH group 4 (including acenaphthene and acenaphthylene µg/L - - 0.1 - - 6 - - - - -

PAH group 5 (including anthracene and phenanthrene) µg/L - - 0.1 - - 0.3 - - 0.0008(a) - -

PAH group 6 (including biphenyl and alkyl substituted biphenyl) µg/L - - 0.1 - - - - - 0.2(a) - -

PAH group 7 (including fluorene and fluoranthene) µg/L - - 0.1 - - 4 - - 0.0008(a) - -

PAH group 8 (including Naphthalene) µg/L - - 0.1 - - 1 - - 7(a) 0.0025 - PAH group 9 (including pyrene) µg/L - - 0.1 - - - - - - - - Additional Parameters Considered by WRS dibenzothiophene µg/L - - - - - - - - - - - alkyl-substituted dibenzothiophene µg/L - - - - - - - - - - - di (2-ethylhexyl) phthalate (DEHP) µg/L 0.008 - - - - - - - 0.6 - 10 methyl isobutyl carbinol (MIBC) µg/L - - - - - - - - - - - acrylamide µg/L 0.5 - 0.1 - - - - - - - 0.2 oil and grease mg/L - - - - - - - - - - - total petroleum hydrocarbons mg/L - - - - - - - - - - - toluene mg/L - 0.7 - - - 0.039 0.024 - 0.0008(a) - - xylenes mg/L - 0.5 - - - - - - 0.002(a) 0.2 - dissolved oxygen mg/L - - - - - - - - - - - lithium mg/L - - - - - - - - - - - fluoride mg/L 1.5 - 1.5 - - 0.3 1.5 1.5 - - 1.5 potassium mg/L - - - - - - - - - - -

(h) Guidelines from NWQMS 2000.

(g) Guidelines from MOEBC 1998.

(e) Guidelines from UKDWI 2002. (f) Guidelines from OMEE 2002.

(d) Guidelines from WHO 2002.

(a) Interim guideline only.

(c) Guidelines for nitrate.

(b) Aesthetic guideline.

CEM


Golder Associates

II-4 REFERENCES

AENV (Alberta Environment). 1999. Report of the Upper Elbow River Instream Objectives Working Group. October 1999.

AEP (Alberta Environmental Protection). 1996. Protocol to Develop Alberta Water Quality Guidelines for Protection of Aquatic Life. Environmental Protection. Edmonton, AB.

CCME (Canadian Council of Ministers of the Environment). 1999. A Protocol for Deriving Water Quality Guidelines for the Protection of Aquatic Life.

CCME (Canadian Council of Ministers of the Environment). 2003. Guidance on the Site-specific Application of Water Quality Guidelines in Canada: Procedures for Deriving Numerical Water Quality Objectives.


HC (Health Canada). 2004. Guidance on Human Health Preliminary Quantitative Risk Assessment. Health Canada, Ottawa, ON.

MOEBC (Ministry of Environment British Columbia). 1996. Developing Water Quality Objectives in British Columbia: A Users Guide, British Columbia Water, Air and Climate change Branch.

MOEBC (Ministry of Environment British Columbia). 1997. Methods for Deriving Site-Specific Water Quality Objectives in British Columbia and Yukon. Water Air and Climate Chande Branch. Prepared by MacDonald Environmental Services.

MOEBC (Ministry of Environment British Columbia). 1998. British Columbia Approved Water Quality Guidelines (Criteria), British Columbia Ministry of Water, Land and Air Protection.

NWQMS (National Water Quality Management Strategy). 2000. Environment Australia. Inland Waters. Water Quality Guidelines. HTML version.


Golder Associates

Niyogo, S. and Wood, C.M. 2004. Biotic Ligand Model, a Flexible Tool for Developing Site-Specific Water Quality Guidelines for Metals. Enivron. Sci. Technol., 38.

OMEE (Ontario Ministry of Environment and Energy). 1998. Water Management Policies and Guidelines: Provincial Water Quality Objectives of the Ministry of Environment and Energy.

UKDWI. 2002. Drinking Water Regulations Schedule 1 and 2. UK Drinking Water Inspectorate. http:/www.dwi.gov.uk/regs/si3184/3184.htm.

U.S. EPA. 2001. Development and Adoption of Nutrient Criteria into Water Quality Standards. USEPA memorandum WQSP-01-01.

WHO. 2002. Guidelines for Drinking Water Quality – Substances and Parameters. www.who.int/water_sanitation_health/GDWQ/Summary_tables/Tab5.htm.

APPENDIX III

DEVELOPMENT OF CHRONIC EFFECTS BENCHMARKS

CEMA III-i Athabasca River Reach Specific May 2007 Water Quality Objectives

Golder Associates

TABLE OF CONTENTS

SECTION PAGE

III-1 INTRODUCTION ...................................................................................................1

III-2 METHODS.............................................................................................................2 GENERAL APPROACH....................................................................................................2 STEP 1 - CREATING A TOXICOLOGICAL DATABASE .................................................3 STEP 2 - STATISTICAL ANALYSIS OF AVAILABLE DATA............................................4 STEP 3 - IDENTIFICATION OF CHRONIC EFFECTS BENCHMARK ............................6 SPECIFIC APPROACHES FOR SELECTED CONSTITUENTS .....................................6

III-3 RESULTS ..............................................................................................................8

III-4 SUMMARY OF SELECTED CHRONIC EFFECTS BENCHMARKS.....................20

III-5 REFERENCES ....................................................................................................21

LIST OF TABLES

Table III-1 Summary of Available Aquatic Toxicity Data for Antimony......................................5 Table III-2 List of the Individual Polycyclic Aromatic Hydrocarbons That Are Included

in PAH Groups 2, 5 and 9........................................................................................7 Table III-3 Summary of Chronic Effects Benchmarks.............................................................20

LIST OF FIGURES

Figure III-1 Outline of the Process Used to Identify Chronic Effects Benchmarks.....................3 Figure III-2 Species Sensitivity Distribution for Antimony ..........................................................9 Figure III-3 Species Sensitivity Distribution for Arsenic as As (III) ...........................................10 Figure III-4 Species Sensitivity Distribution for Boron..............................................................12 Figure III-5 Species Sensitivity Distribution for Hexavalent Chromium....................................14 Figure III-6 Species Sensitivity Distribution for Copper............................................................15 Figure III-7 Species Sensitivity Distribution for Manganese.....................................................16

LIST OF ATTACHMENTS

Attachment III-A Summary of Available Chronic Toxicity Data for Substances of Potential Concern

CEMA III-1 Athabasca River Reach Specific May 2007 Water Quality Objectives

Golder Associates

III-1 INTRODUCTION

Chronic effects benchmarks were developed for the following constituents:

• aluminum

• antimony

• arsenic

• barium

• beryllium

• boron

• cadmium

• chromium

• copper

• iron

• manganese

• molybdenum

• silver

• sulphide

• strontium

• vanadium

• total phenolics

• PAH Group 2 (benzo(a)anthracene)

• PAH Group 5 (anthracene)

• PAH Group 6 (biphenyl)

• PAH Group 9 (pyrene)

Toxicological data compiled in recent environmental impact assessments (Imperial 2005; Shell 2005; Suncor 2005). Chronic benchmarks were developed based on this compiled data to evaluate the impact changes in water quality may have on aquatic health. Where sufficient data were available (i.e., toxicity test results for at least five different species), Species Sensitivity Distributions (SSDs) (Posthuma et al. 2002) were used to derive a chronic effects benchmark, which is expressed as a concentration. The term “chronic effects benchmark” is used herein to define a level beyond which detrimental effects to aquatic health may occur.

For constituents where less data were available, the lowest recorded chronic toxicity test result was used to define the chronic effects benchmark. A more detailed description of the methodology used to identify the chronic effects benchmarks for the constituents listed above is provided in Section III-2. The results of the identification process are outlined in Section III-3. A summary of the selected chronic effects benchmarks is provided in Section III-4.


Golder Associates

III-2 METHODS

General Approach

Chronic effects benchmarks were developed based on a review of current toxicological literature. Where toxicity test results for at least five different species were available, the SSD approach (Posthuma et al. 2002) was used to derive the chronic effects benchmark. For constituents where less data were available, the lowest recorded chronic toxicity test result for aquatic species relevant to Alberta was used to define the chronic effects benchmark.

The SSD approach was selected for use in acknowledgement that there are biological differences amongst species and the variation amongst species sensitivities can be described by a statistical distribution function to yield a species sensitivity distribution. The distribution can then be used to define an environmental quality criterion, expressed as a concentration, that is expected to be safe to most species (Posthuma et al. 2002). The most commonly used criterion is referred to as the HC5 value, which stands for hazardous concentration to 5% of species. Conversely, the HC5 value can also be thought of the concentration at which 95% of the species would be fully protected (i.e., unaffected). A comparison of chronic, single species and experimental ecosystem data for metals, pesticides, surfactants and other organic and inorganic compounds, has shown that the HC5 is conservative threshold of effects to aquatic ecosystems (Versteeg et al. 1999).

The SSD approach has been used to derive most of the current U.S. EPA water quality criteria for protection of aquatic life and is considered by this regulatory agency to be the recommended approach for developing in-stream criteria (Stephan et al. 1985). It has also been used by several European nations for deriving water quality criteria and has been recommended as a standard ecological risk assessment technique by Suter and Barnthouse (1993), the Aquatic Risk Assessment and Mitigation Dialog Group (Baker et al. 1994) and the Water Environmental Research Foundation (Parkhurst et al. 1996). The SSD approach is now being used by the Canadian Council of Ministers of the Environment (CCME) to develop water quality guidelines and is the preferred method for deriving sediment quality criteria.

The application of the SSD approach to the Lower Athabasca River followed a three step process outlined in Figure III-1. This included creating a toxicological database for each constituent, analyzing the available data and deriving an HC5 value or, where insufficient data were available, using the lowest reported chronic toxicity test results. Each step in this process is discussed in more detail below.


Golder Associates

Figure III-1 Outline of the Process Used to Identify Chronic Effects Benchmarks

1. Creation of a Toxicological Database

2. Statistical Analysis of Toxicity Data

3. Identification of Chronic Effects Benchmark

1a. Assemble available data1b. Inclusion / exclusion of available data

2a. Development of species mean values

Quality check

2b. Determination of percent affected

2c. Generate species sensistivity distribution (SSD)

3a. Use HC5

concentration from SSD

3b. Use lowest reported chronic value

Data available for more than 4 species?

Yes

No

Step 1 - Creating a Toxicological Database Step 1a - Assemble Available Toxicity Data

Available chronic toxicological data for each constituent were summarized, with a focus on data for both invertebrates and fish. The initial groundwork for the development of each toxicity database began with the inclusion of all primary chronic toxicity data used to derive relevant Canadian Water Quality Guidelines (CCME 1999) and U.S. Ambient Water Quality Criteria (U.S. EPA 2002). The toxicity database was expanded by querying the AQUIRE and ECOTOX databases and by searching for other available scientific literature. The resulting database contained data with consistent test endpoints, such as mortality, reduced survival, growth or reproduction, derived from chronic studies. All chronic studies included in the toxicity database were either early life-stage or life-cycle tests. Although the database does not include all available data, it consists of the


Golder Associates

primary data that meet both the requirements of the U.S. EPA and CCME guideline development protocol (e.g., Stephan et al. 1985).

Step 1b - Inclusion or Exclusion of Selected Data

Once the available data were assembled, test species were screened for inclusion or exclusion based specifically on the relevance of the test species to a northern waterbody (e.g., was it a resident species to northern Alberta). To complete the screening, the general rules for developing site-specific water quality objectives (MacDonald et al. 2002) were followed. The applicable rules are summarized below:

• toxicity data on species that are known to occur or may occur at the site can not be excluded;

• toxicity data on species that are known not to occur or are not likely to occur at the site can be excluded;

• if a member of a family of freshwater fish may occur at the site, then toxicity data from any fish species within that family is maintained in the database; and

• if a member of a class of freshwater invertebrates may occur at the site, then toxicity data from that invertebrate class is retained in the toxicity database.

End points based on no observed effects concentrations (i.e., NOEC values) were excluded, since they do not represent thresholds beyond which effects would be expected to occur. For the same reason, end points based on the geometric mean of lowest observed effects concentration (i.e., LOEC) and NOEC were also excluded.

The resulting toxicity databases are summarized in Tables IIIA-1 to IIIA-13 included in Attachment IIIA for all constituents except cadmium, total phenolics, sulphide, selenium and PAH Groups 2, 5 and 9. A slightly different approach was adopted to derive chronic effects benchmarks for these seven constituents, as outlined in Section 2.2.

Step 2 - Statistical Analysis of Available Data Following the compilation of the toxicological databases, a statistical analysis of the assembled data points was completed if data were available for five or more species. The statistical analysis consisted of:

• developing species mean values; • ranking the species mean value to determine percent affected; and • fitting of a statistical distribution to the available data set, if appropriate.


Golder Associates

Species means were calculated by taking the geometric mean of the individual test results. The geometric mean, as oppose to the arithmetic mean, was used to minimize the bias of high test results, and to ensure adherence to the protocol recommended by Posthuma et al. (2002). Species mean values were then ranked from lowest to highest, and the percent of species affected was calculated based on dividing the rank assigned to each species mean by the total number of species. An example of this process is illustrated in Table III-1 using toxicity data for antimony.

Table III-1 Summary of Available Aquatic Toxicity Data for Antimony

Species Name Common Name Chronic Value (μg/L)

Species Average (μg/L) Rank Percent

Affected (%)

Oncorhynchus mykiss rainbow trout 580 3,046 1 16.7 Oncorhynchus mykiss rainbow trout 16,000 Daphnia magna cladoceran 1,600 3,916 2 33.3 Daphnia magna cladoceran 2,700 Daphnia magna cladoceran 4,500 Daphnia magna cladoceran 12,100 Pimephales promelas fathead minnow 2,300 4,870 3 50 Pimephales promelas fathead minnow 5,400 Pimephales promelas fathead minnow 9,300 Caenorabditis elegans nematode 20,000 20,000 4 66.7 Gammarus pseudolimnaeus amphipod 25,700 25,700 5 83.3

Tubifex tubifex worm 678,000 678,000 6 100

Once the species mean values were ranked and the “percent of species affected” was calculated, the data were plotted, and a best-fit curve identified using SigmaPlot 8.02 (SPSS Inc. 2002). Since SSDs typically follow a sigmoidal pattern, the data were first assessed using a logistic function. If the logistic function proved to be a poor fit, other relationships were evaluated (e.g., logarithmic). As previously stated, SSDs were only developed for substances with chronic results available for five or more species. Although a higher species cutoff is generally used by the U.S. EPA (Stephan et al. 1985) and other organizations (e.g., minimum of nine species), a cutoff of five species was adopted taking into consideration that the test species were relevant to the study area and included what are typically the most sensitive species (i.e., cladocerans and salmonids). We acknowledge that SSDs developed with more than five species are likely more robust. However, for the purposes of this study, we feel that the five species cutoff was appropriate.


Golder Associates

Step 3 - Identification of Chronic Effects Benchmark Step 3a - Derivation of the HC5 Concentration

Following the development of an appropriate regression model, the concentration that would affect 5% of the species in the aquatic community (i.e., the HC5 value) was calculated in an iterative fashion using the model equation and subsequently used as the chronic effects benchmark for the constituent in question.

Generally, logistic regression models provided the best-fit to the observed data for each of the SOPCs for which SSD were developed. Logistic regression models produce sigmoidal curves, which tend to deviate from the observed data at the tails of the distribution. This deviation results in HC5 values that are more conservative than would have been generated by manually fitting to the available data.

Step 3b - Selection of the Lowest Reported Chronic Value

For most SOPCs, toxicity data were available for fewer than 5 species. Exceptions included antimony, arsenic, boron and manganese. As a result, SSD were only developed for only four of the 20 SOPCs listed in Section 1. Chronic effects benchmarks for the remaining substances were based on the lowest chronic toxicity result present in the constituent-specific toxicity databases.

Specific Approaches for Selected Constituents Total Phenolics

Total phenolics is a measure of the total mass of individual phenolic compounds present within a given sample. The focus of most toxicological testing has been on individual phenolic compounds, rather than looking at them in combination. Mono- and dihydric forms tend to be the most common, and phenol tends to be the most toxic among them (CCME 1999). The chronic effects benchmark was, therefore, set to the lowest chronic test result reported for phenol by CCME (1999).

Sulphide

The U.S. EPA criteria for sulphide was developed in 1978, prior to the adoption of the SSD approach for guideline development (U.S. EPA 1978). It is based on a rather limited set of toxicological data. However, no relevant additional information, beyond that considered in the formation of the guideline, was obtained. The U.S. EPA criteria does not include a safety factor like those developed by the CCME. As such, it likely represents a threshold beyond which detrimental effects to aquatic health could occur. The criteria was adopted as the chronic effects benchmark.


Golder Associates

Cadmium

The U.S. EPA revised their recommended criteria for cadmium in 2001 (U.S. EPA 2001). The revised criteria was developed using the SSD approach and was based on an extensive review of the available toxicological literature. It was deemed to be ineffective to repeat this work, since little additional information has been developed since the release of the revised criteria. The criteria was adopted as the chronic effects benchmark for cadmium.

PAH Groups 2, 5 and 9

PAH Groups 2, 5 and 9 consist of parent and alkylated PAHs that have similar form. A complete list of the individual PAHs included in each group is provided in Table III-2. Canadian water quality guidelines have been established for one or more of the individual PAHs included in each group (CCME 1999). Little information beyond that reported in CCME (1999) was obtained. Chronic effects benchmarks for each group were, therefore, developed by selecting the most restrictive guideline applicable to each group and reducing the safety factor used in its development. The safety factor was not completely eliminated, because most of these guidelines are based on acute toxicity test results. Instead, the safety factor was reduced to reflect an acute to chronic ratio of 1:10, such that the selected chronic benchmark was equal to the acute value used to derive the guideline multiplied by a factor of 0.1.

Table III-2 List of the Individual Polycyclic Aromatic Hydrocarbons That Are Included in PAH Groups 2, 5 and 9

Group Constituent Compounds

PAH Group 2 Benzo (a) anthracene/chrysene methyl benzo (a) anthracene/chrysene C2 substituted benzo (a) anthracene/chrysene Benzo (b&k) fluoranthene Indeno (c,d-123) pyrene PAH Group 5 Anthracene Phenanthrene methyl phenanthrene/anthracene C2 substituted phenanthrene/anthracene C3 substituted phenanthrene/anthracene C4 substituted phenanthrene/anthracene 1-methyl-7-isopropyl-phenanthrene (retene) PAH Group 9 methyl fluoranthene/pyrene Pyrene


Golder Associates

III-3 RESULTS

Aluminum Aluminum toxicity and speciation varies with pH changes in the environment. The aluminum ion, Al3+, is toxic and is normally bound as various Al(OH)n compounds at pH values between 6 and 9. As such, aluminum toxicity is normally observed in low pH environments, where more elemental ion (Al3+) is available. In the Oil Sands Region, pH levels in surface waterbodies are typically greater than 7 (Golder 2003); therefore, aluminum toxicity from Al3+ is expected to be low.

Most of the available chronic toxicity data for aluminum originate from low pH studies that are not applicable to the Oil Sands Region and were, therefore, excluded (Table IIIA-1). As a result, insufficient data were available to develop a SSD. The lowest reported toxicity value of 0.68 mg/L was, therefore, selected for use as the chronic effects benchmark for aluminum. This value is based on an EC50 test result using Daphnia magna. The Canadian water quality guideline for aluminum is 0.1 mg/L (CCME 1999).

Antimony Two forms of antimony exist can exist in the dissolved phase (ATSDR 1997); however, most antimony released into waterways is associated with particulate matter. Dissolved antimony (III) occurs under moderately oxidizing conditions, whereas dissolved antimony (V) predominates in highly oxidizing environments (NWQMS 2000). Most toxicological studies focus on antimony (III).

Surface waters in the Oil Sands Regions tend to contain high levels of dissolved oxygen, although periodic anoxia has been observed (Golder 2003). Dissolved antimony would be expected to exist predominantly as antimony (V). As such, development of an antimony benchmark based on toxicity testing using antimony (III) is a conservative approach.

There were sufficient toxicity data available for antimony to develop a SSD, with a logistic regression model providing a good fit to the observed data (i.e., r2 = 0.934) (Figure III-2). The logistic model took the following form:

0931.1

5262.71

9768.99−

⎟⎠⎞

⎜⎝⎛

+

=x

y

where: y = percent of aquatic community affected; and

x = antimony concentration (mg/L).


Golder Associates

Based on the logistic regression model, the HC5 for antimony was estimated to be 0.51 mg/L. The data used to generate the SSD for antimony are summarized in Table IIIA-2.

Arsenic

Arsenic can exist in four oxidation states: -3, 0, +3, and +5. In aquatic systems, inorganic arsenic occurs primarily in two oxidation states: As(V) and As(III). Both forms generally exist together, although As(V) predominates under oxidizing conditions and As(III) predominates under reducing conditions. The oxidation state of arsenic is the major factor affecting toxicity. Inorganic As(III) is the more toxic form (ATSDR 1997).

Figure III-2 Species Sensitivity Distribution for Antimony

0

10

20

30

40

50

60

70

80

90

100

0.1 1 10 100 1000

Concentration (mg/L)

Perc

ent a

ffect

ed

HC5 = 0.51 mg/L

As previously noted, surface waters in the Oil Sands Regions tend to contain high levels of dissolved oxygen, although periodic anoxia has been observed (Golder 2003). Inorganic arsenic would be expected to exist predominantly as As (V). However, limited chronic toxicity data were available for As (V).

There were sufficient toxicity data available for arsenic, in the form of As (III), to develop a SSD, with a logistic regression model providing a good fit to the observed data (i.e., r2 = 0.965) (Figure III-3). The logistic model took the following form:


Golder Associates

8758.0

8538.21

3715.129−

⎟⎠⎞

⎜⎝⎛

+

=x

y


x = arsenic [As(III)] concentration (mg/L).

Based on the logistic regression model, the HC5 for arsenic, in the form of As(III), was estimated to be 0.073 mg/L. Since As(V) is expected to be the dominant form of arsenic present in the Oil Sands Region and As(III) is the more toxic form, the chronic effects benchmark of 0.073 mg/L is considered to be conservative. The data used to generate the SSD for arsenic are summarized in Table IIIA-3.

Figure III-3 Species Sensitivity Distribution for Arsenic as As (III)

0

10

20

30

40

50

60

70

80

90

100

0.01 0.1 1 10 100


Perc

ent a

ffect

ed

HC5 = 0.073 mg/L

Barium

The acetate, nitrate and halide salts of barium are soluble in water, but the carbonate, chromate, fluoride, oxalate, phosphate and sulphate salts are quite insoluble. The aqueous solubility of barium compounds increases as the pH decreases. Organometallic barium compounds are ionic and are hydrolyzed in water. The concentration of barium ions in natural aquatic systems will be limited by naturally occurring anions, such as sulphates and carbonates, and by the possible adsorption of barium ions onto metal oxides and hydroxides. In the Oil Sands Region, barium tends to exist primarily in dissolved form.


Golder Associates

Insufficient data were available to develop a SSD for barium (Table IIIA-4). The lowest reported toxicity value of 5.8 mg/L was, therefore, selected for use as the chronic effects benchmark for barium. This value is based on an EC16 test result generated using Daphnia magna.

Beryllium

Beryllium can exist in two common oxidation states: Be(O) and Be(+2). In aquatic systems, beryllium exhibits only the +2 oxidation state. Between a pH range 6 to 8, the speciation of beryllium is controlled by the formation solid beryllium hydroxide, Be(OH)2 , which has a very low solubility (ATSDR 1997). Beryllium concentrations in the Oil Sands Region tend to be below detection limits.

Insufficient data were available to develop a SSD for beryllium (Table IIIA-5). The lowest reported toxicity value of 7.3 μg/L was, therefore, selected for use as the chronic effects benchmark for beryllium. This value is based on a LOEC test result generated using Daphnia magna.

Boron

In the environment, boron combines with oxygen and other elements to form borates. Borates are widely found in nature, and are present in oceans, sedimentary rocks, coal, shale and some soils. There are several commercially important borates, including borax, boric acid, sodium perborate and the minerals ulexite and colemanite. Borates dissolved in the water can adsorb onto, and desorb from, many different surfaces that can be found in rivers and streams. In the Oil Sands Region, boron is largely present in its dissolved form.

There were sufficient toxicity data available for boron to develop a SSD, with a logistic regression model providing a good fit to the observed data (i.e., r2 = 0.965) (Figure III-4). The logistic model took the following form:

4157.1

4749.511

8188.127−

⎟⎠⎞

⎜⎝⎛

+

=x

y


x = boron concentration (mg/L).

Based on the logistic regression model, the HC5 for boron was estimated to be 5.4 mg/L. The data used to generate the SSD for boron are summarized in Table IIIA-6.

http://www.greenfacts.org/glossary/def/elements.htm

http://www.greenfacts.org/glossary/pqrs/sedimentary-rock.htm

http://www.greenfacts.org/glossary/tuv/ulexite.htm

http://www.greenfacts.org/glossary/abc/borate.htm

http://www.greenfacts.org/glossary/abc/adsorb-adsorbtion-desorb.htm

http://www.greenfacts.org/glossary/abc/adsorb-adsorbtion-desorb.htm


Golder Associates

Cadmium

Cadmium is usually found as a mineral combined with other elements, such as oxygen (cadmium oxide), chlorine (cadmium chloride) or sulfur (cadmium sulfate, cadmium sulfide). It may exist in water as a hydrated ion, as inorganic complexes (such as carbonates, hydroxides, chlorides or sulphates) or as organic complexes with humic acids (OECD 1994). Cadmium may enter aquatic systems through weathering and erosion of soils and bedrock, atmospheric deposition, direct discharge from industrial operations, leakage from landfalls and contaminated sites and the dispersive use of sludge and fertilizers in agriculture.

Figure III-4 Species Sensitivity Distribution for Boron

0

10

20

30

40

50

60

70

80

90

100

1 10 100 1000


Perc

ent a

ffect

ed

HC5 = 5.4 mg/L

The predominant dissolved form of cadmium in freshwater is the cadmium ion (Cd 2+), which is the form that is most bioavailable to aquatic biota (Wright and Welbourn 1994). Upon entry to the aquatic ecosystem, cadmium tends to partition to particulate matter and dissolved organic matter, reducing concentrations of the free ion in the water column, thereby lowering its bioavailability (Jonnalagadda and Rao 1993).

Modifying factors, such as hardness, salinity, pH and dissolved oxygen levels, can have a profound effect on cadmium toxicity to aquatic plants and animals. Ions, such as hydrogen and calcium, may compete with cadmium, resulting in reduced cadmium uptake and toxicity (Wright and Welbourn 1994). The toxicity of cadmium to fish is strongly affected by hardness, mainly due to competition for anionic binding sites at the gills between cadmium ions and ions responsible for hardness (i.e., calcium and magnesium) (Parametrix 1995).

http://www.cadmium.org/env_ref.html#o


Golder Associates

The U.S. EPA revised their recommended criteria for cadmium in 2001 (U.S. EPA 2001). The revised criteria was developed using the SSD approach and was based on an extensive review of the available toxicological literature. The revised criteria also includes a hardness correction factor. It was deemed to be ineffective to repeat this work, since little additional information has been developed since the release of the revised criteria. The criteria was adopted as the chronic effects benchmark for cadmium.

Chromium

Chromium can exist in different oxidation states from -II to +VI. Chromium (III) is the most stable oxidation state, while chromium (VI) compounds are strongly oxidizing. Chromium (VI) is the main species found in surface waters and aerobic soils; chromium (III) dominates in mildly reducing environments, such as sediments and wetlands. Hexavalent chromium forms several stable oxyacids and anions including HCrO4

- (hydrochromate), Cr2O72-(dichromate), and CrO4

2- (chromate) (CCME 1999). Most chromium (VI) salts are soluble and very mobile, with a long residence time in surface and groundwater (CCME 1999). The high oxidizing potential, high solubility and ease of permeation of biological membranes make chromium (VI) generally more toxic than chromium (III) (CCME 1999). Hexavalent chromium can be reduced to the trivalent state by S2-, Fe(II), fulvic acid, low molecular weight organic compounds, and proteins inside organic cells (CCME 1999).

Sufficient toxicity data was available to develop an SSD for hexavalent chromium, with a logistic regression model providing a good fit to the observed data (i.e., r2 = 0.976) (see Figure III-5). The logistic model took the following form:

7054.0

2895.1641

215.101−

⎟⎠⎞

⎜⎝⎛

+

=x

y

where: y = percent of aquatic community affected

x = chromium concentration (μg/L)

Based on the logistic regression model, the HC5 for hexavalent chromium was estimated to be 2.48 μg/L or 0.00248 mg/L. The data used to generate the SSD for chromium is summarized (see Table IIIA-7).


Golder Associates

Figure III-5 Species Sensitivity Distribution for Hexavalent Chromium

Copper

In natural waters, copper occurs primarily as the divalent cupric ion in free and complex forms (Callahan et al. 1979). The cupric ion (Cu2+) is the most readily available (Suedel et al. 1996) and toxic inorganic species of copper (Campbell and Stokes 1985). It is very reactive, forming complexes and precipitates with organic and inorganic substances and suspended solids in the water column (U.S. EPA 1985b). Copper can be toxic to aquatic life, but at low concentrations it is a minor nutrient for both aquatic plants and animals (U.S. EPA 1985b).

Water quality can also affect the toxicity and bioavailability of copper to aquatic life. Generally, as water hardness increases, toxicity decreases. Water hardness in natural waters is controlled by the presence of calcium (Ca2+) and magnesium (Mg2+), which compete with metal cations for binding sites on the gills of aquatic organisms (ICME 1995).

In freshwater organisms, studies have shown that the gills are the principal sites of metal toxicity (Evans 1987; Wood 1992). Copper acts as a surface active toxicant to freshwater fish, exerting damage by binding to anionic sites on the gills. Therefore, uptake of Na+ by the gills is blocked and the fish are at risk of lethal decreases in plasma Na+ concentrations (hyponatremia).

Sufficient toxicity data was available to develop an SSD for copper, with a logistic regression model providing a good fit to the observed data (i.e., r2 = 0.988) (see Figure III-6). The logistic model took the following form:

0 10

20

30

40

50

60

70

80

90

100

1 10 100 1000 10000

Concentration (µg/L)

Perc

ent a

ffect

ed

HC5 = 2.48 mg/L


Golder Associates

5778.1

9778.471

4222.92−

⎟⎠⎞

⎜⎝⎛

+

=x

y

where: y = percent of aquatic community affected

x = chromium concentration (μg/L)

Based on the logistic regression model, the HC5 for copper was estimated to be 7.83 μg/L or 0.0078 mg/L. The data used to generate the SSD for chromium is summarized (see Table IIIA-8).

Figure III-6 Species Sensitivity Distribution for Copper

Iron

Iron exists in two forms: soluble ferrous (Fe2+) iron and insoluble ferric (Fe3+) iron. Oxidation-reduction reactions determine the chemical behaviour of iron in the aquatic environment. In aerobic systems, the vast majority of iron is present in water as insoluble ferric ion, which is largely non-toxic. Under anaerobic conditions, soluble ferrous iron can form. Although periodic anoxia has been observed in the Oil Sands Region, dissolved oxygen levels tend to be high, and iron exists predominantly as insoluble ferric iron.

0

10

20

30

40

50

60

70

80

90

100

1 10 100 1000 10000 100000Concentration (µg/L)

Perc

ent a

ffec

ted

HC 5 = 7.83 mg/L


Golder Associates

Insufficient data were available to develop a SSD for iron (Table IIIA-9). The lowest reported toxicity value of 0.57 mg/L was, therefore, selected for use as the chronic effects benchmark for iron. This value is based on a maximum allowable toxicant concentration (MATC) end point developed using fathead minnows.

Manganese

Manganese is an essential trace element and is present in almost all organisms. It exists in oxidation states ranging from -3 to +7, of which divalent and trivalent manganese are the more important forms in aquatic systems (CCREM 1987). Manganese decreases in availability at pH values above 7.3, which is generally reflective of conditions in the Oil Sands Region (Golder 2003).

There were sufficient toxicity data available for manganese to develop a SSD, with a logistic regression model providing a good fit to the observed data (i.e., r2 = 0.922) (Figure III-7). The logistic model took the following form:

2263.1

0033.31

8414.106−

⎟⎠⎞

⎜⎝⎛

+

=x

y


x = manganese concentration (mg/L).

Based on the logistic regression model, the HC5 for manganese was estimated to be 0.26 mg/L. The data used to generate the SSD for manganese are summarized in Table IIIA-10.

Figure III-7 Species Sensitivity Distribution for Manganese

0

10

20

30

40

50

60

70

80

90

100

0.1 1 10 100


Perc

ent a

ffect

ed

HC5 = 0.26 mg/L


Golder Associates

Molybdenum

Molybdenum can exist in the valence states +2 to +6 and readily forms organometallic complexes in aquatic systems (CCME 1999), although it will remain in solution at pH values greater than 5. Molybdenum is an essential trace element and is found in aquatic organisms. Insufficient data were available to develop a SSD for molybdenum (Table IIIA-11). The lowest reported toxicity value of 0.73 mg/L was, therefore, selected for use as the chronic effects benchmark for molybdenum. This value is based on a 28-day LC50 value derived using rainbow trout. It is the same test result used by the CCME to derive the current Canadian water quality guideline for molybdenum.

Silver

Silver exists in the aquatic environment primarily in the univalent state Ag(I). It has been shown in laboratory experiments to be one of the most toxic metals to aquatic life (i.e., effects begin to occur at very low concentrations). However, in the natural environment, silver is often bound to chloride, dissolved organic carbon or sulfur-containing ligands, which reduce its bioavailability. Laboratory data may, therefore, overestimate the toxicity of silver (NWQMS 2000). In the Oil Sands Region, silver concentrations in surface waterbodies tend to be low or non-detectable.

Insufficient data were available to develop a SSD for silver (Table IIIA-12). The lowest reported toxicity value of 0.00017 mg/L was, therefore, selected for use as the chronic effects benchmark for silver. This value is based on a LOEC concentration derived using rainbow trout.

Sulphide

The toxicity of sulphide is associated with its un-dissociated form (H2S) and is dependent on temperature, pH and dissolved oxygen concentrations. At lower pH levels, the amount of un-dissociated sulphide increases. At a pH of 8.0 and a temperature range of 10 to 30οC, only 7 to 15% of the sulphide in solution will exist as H2S. When temperatures are low, fish exhibit a greater tolerance for H2S. The presence of dissolved oxygen levels promotes conversion of H2S to sulfates, thereby reducing toxicity.

The U.S. EPA criteria for sulphide was developed in 1978, prior to the adoption of the SSD approach for guideline development (U.S. EPA 1978). It is based on a rather limited set of toxicological data. However, no relevant additional information, beyond that considered in the formation of the guideline, was obtained. The U.S. EPA criteria does not include a safety factor like those developed by the CCME. As such, it likely to represent a threshold beyond which detrimental effects to aquatic health could occur. The criteria, which is


Golder Associates

0.002 mg/L un-dissociated hydrogen sulphide, was adopted as the chronic effects benchmark.

Strontium

Strontium can exist in two oxidation states: 0 and +2. Under normal environmental conditions, only the +2 oxidation state is stable enough to be of practical importance, since it readily reacts with both water and oxygen (Cotton and Wilkinson 1980; Hibbins 1997). There are 26 isotopes of strontium, four of which occur naturally. Naturally occurring strontium is not radioactive and is either referred to as stable strontium or strontium.

Insufficient data were available to develop a SSD for strontium (Table IIIA-13). The lowest reported toxicity value of 0.2 mg/L was, therefore, selected for use as the chronic effects benchmark for strontium. This value is based on a 28-day LC50 result generating using rainbow trout.

Vanadium

The transport and partitioning of vanadium in water is influenced by pH, redox potential, and the presence of particulate. In fresh water, vanadium generally exists in solution as the vanadyl ion (V4+) under reducing conditions and the vanadate ion (V5+) under oxidizing conditions, or as an integral part of, or adsorbed onto, particulate matter (Wehrli and Stumm 1989). The partitioning of vanadium between water and sediment is strongly influenced by the presence of particulate in the water. Both vanadate and vanadyl species are known to bind strongly to mineral or biogenic surfaces by adsorption or complexing (Wehrli and Stumm 1989). It has been estimated that only 13% of the total vanadium present in the water column is in dissolved form (WHO 1988).

Insufficient data were available to develop a SSD for vanadium (Table IIIA-14). The lowest reported toxicity value of 0.16 mg/L was, therefore, selected for use as the chronic effects benchmark for this constituent. This value is based on a 28-day LC50 test result generated using rainbow trout.

Total Phenolics

Phenols and phenolic substances are aromatic, organic compounds with one or more hydroxyl groups attached to a benzene ring. They include such substances as cresol, catechol, quinol, eylenol, guaiacol, hydroquinone (4-hydroxyphenol) and resorcinol (3-hydroxyphenol) (CCME 1999). Total phenolics is a measure of the total mass of individual phenolic compounds present within a given sample. The focus of most toxicological testing has been on individual phenolic compounds, rather than looking at them in combination. Mono- and dihydric


Golder Associates

forms tend to be the most common, and phenol tends to be the most toxic among them (CCME 1999). The chronic effects benchmark was, therefore, set to the lowest chronic test result reported for phenol by CCME (1999), which was a 9-day LC50 value of 0.04 mg/L derived using leopard frogs (Rana pipiens).

Polycyclic Aromatic Hydrocarbons

The SOPCs identified in water quality Section 4.6.3 and 4.6.4 included four of the nine PAH groups considered in the aquatic resources assessment (i.e., PAH Group 2, 5, 6 and 9). As previously noted, each PAH group consists of parent and alkylated PAHs that have similar form. The individual PAHs included in Groups 2, 5 and 9 are summarized in Table 2. Constituents to PAH Group 6 were limited to biphenyl, methyl biphenyl and C2 substituted biphenyl.

Canadian water quality guidelines have been established for one or more of the individual PAHs included in PAH Groups 2, 5 and 9 (CCME 1999). Little information beyond that reported in CCME (1999) was obtained. Chronic effects benchmarks for each group were, therefore, developed by selecting the most restrictive guideline applicable to each group and reducing the safety factor used in its development. The safety factor was not completely eliminated, because most of these guidelines are based on acute toxicity test results. Instead, the safety factor was reduced to reflect an acute to chronic ratio of 1:10, such that the selected chronic benchmark was equal to the acute value used to derive the guideline multiplied by a factor of 0.1.

For PAH Group 2, the benzo(a)anthracene guideline of 0.018 μg/L was used. The resulting chronic effects benchmark was set at 0.18 μg/L, which was derived by dividing the acute value used to derive the guideline by a chronic to acute ratio of 10. The same approach was used for PAH Group 5, whereby the anthracene guideline of 0.012 μg/L was used and the resulting chronic effects benchmark was set at 0.12 μg/L. Similarly, for PAH Group 9, the pyrene guideline of 0.025 μg/L was used, and the resulting chronic effects benchmark was set at 0.25 μg/L, which was derived by dividing the acute value used to derive the guideline by a chronic to acute ratio of 10.

For PAH Group 6, available toxicity data for biphenyl were summarized. There were insufficient data available to develop a SSD (Table IIIA-15). The lowest reported toxicity value of 29 μg/L was, therefore, selected for use as the chronic effects benchmark for this constituent. This value is based on a 30-day LC50 value derived using fathead minnows.


Golder Associates

III-4 SUMMARY OF SELECTED CHRONIC EFFECTS BENCHMARKS

The chronic effects benchmarks identified for each of the constituents listed in Section 1 are summarized in Table III-3.

Table III-3 Summary of Chronic Effects Benchmarks

Constituent Chronic Effects Benchmark (mg/L)

aluminum 0.68 antimony 0.51 arsenic 0.073 barium 5.8 beryllium 0.0073 boron 5.4 cadmium 0.00042(a) chromium 0.00248 copper 0.0078 iron 0.57 manganese 0.26 molybdenum 0.73 silver 0.00017 sulphide 0.002(b) strontium 0.2 vanadium 0.16 total phenolics 0.04 PAH Group 2 0.00018 PAH Group 5 0.00012 PAH Group 6 0.029 PAH Group 9 0.00025

(a) Based on a hardness of 180 mg/L. (b) Un-dissociated hydrogen sulphide.


Golder Associates

III-5 REFERENCES

Allin, C.J. and R.W. Wilson. 1999. Behavioural and Metabolic Effects of Chronic Exposure to Sublethal Aluminum in Acidic Soft Water in Juvenile Rainbow Trout (Oncorhynchus mykiss). Can. J. Fish. Aquat. Sci. 56: 670-678.

Amelung, M. 1981. Auswirkungen gelöster Eisenverbindungen auf die Ei- und Larvalentwicklung von Salmo gairdneri (Richardson). Arch. Fisch Wiss. 32: 77–87.

ANZECC (Australia and New Zealand Environment and Conservation Council). 1999. National Water Quality Management Strategy. Draft Australian and New Zealand Guidelines for Fresh and Marine Water Quality. Prepared under the auspices of Australia and New Zealand Environment and Conservation Council and Agriculture and Resource Management Council of Australia and New Zealand.

Arthur, J.W., and E.N. Leonard. 1970. Effects of Copper on Gammarus pseudolimnaeus, Physa integra, and Campeloma decisum in Soft Water. J.Fish.Res.Board Can. 27(7):1277-1283.

Atland, A. and B.T. Barlaup. 1996. Avoidance of Toxic Mixing Zones by Atlantic Salmon (Salmo salar L.) and Brown Trout (Salmo trutta L.) in the Limed River Audna, Southern Norway. Environmental Pollution 90 (2): 203-208.

ATSDR (Agency for Toxic Substances and Disease Registry). 1997. Toxicological Profiles on CD-ROM. U.S. Public Health Service. CRC Press, Inc.

Bailey, H.C., and D.H.W. Liu. 1980. Lumbriculus variegatus, a Benthic Oligochaete, as a Bioassay Organism. In: J.C. Eaton, P.R. Parrish, and A.C. Hendricks (Eds.), Aquatic Toxicology and Hazard Assessment, 3rd Symposium, ASTM STP 707, Philadelphia, PA :205-215.

Baker, J.L., A.C. Barefoot, L.E. Beasley, L. Burns, P. Caukins, J. Clark, R.L. Feulner, J.P. Giesy, R.L. Graney, R. Griggs, H. Jacoby, D. Laskowski, A. Maciorowski, E. Mihaich, H. Nelson, R. Parrish, R.E. Siefert, K.R. Solomon and W. van der Schalie. 1994. Final Report: Aquatic Risk Assessment and Mitigation Dialog Group. SETAC Press, Pensacola, FL, USA.

Baker, J.P. and C.L. Schofield. 1982. Aluminum Toxicity to Fish in Acidic Waters. Water, Air, and Soil Pollution 18: 289-309.


Golder Associates

BCMELP (British Columbia Ministry of Environment, Lands and Parks). 1996. Water Quality Criteria for Molybdenum. Ministry of Environment and Parks. Province of British Columbia. 6p. Beckman, R.J. and R.D. Cook. 1983. Outliers. Technometrics, 25: 119-149.

Benoit, DA. 1976. Toxic effects of hexavalent chromium on brook trout (Salvelinus fontinalis) and rainbow trout (Salmo gairdneri). Water Res. 10(6): 497-500.

Biesinger, K.E. and G.M. Christensen. 1972. Effects of Various Metals on Survival, Growth, Reproduction, and Metabolism of Daphnia magna. J. Fish. Res Board Can 29: 1,691-1,700.

Birge, W.J. 1978. Aquatic Toxicology of Trace Elements of Coal and Fly Ash. In: J.H. Thorp and J.W. Gibbons (eds.). Energy and Environmental Stress in Aquatic Ecosystems. CONF-771114. National Technical Information Service, Springfield, Virginia. p. 219.

Birge, W.J. and J.A. Black. 1977. Sensitivity of Vertebrate Embryos to Boron Compounds.

Birge, W.J. and J.A. Black. 1981. Toxicity of Boron to Embryonic and Larval Stages of Largemouth Bass (Micropterus salmoides) and Rainbow Trout (Salmo gairdneri). Completion report prepared for Proctor & Gamble.

Birge, W.J., J.A. Black and A.G. Westerman. 1979. Evaluation of Aquatic Pollutants Using Fish and Amphibian Eggs as Bioassay Organisms. In: Nielsen, S.W., G. Migaki and D.G. Scarpelli (eds.). Symp. Animals Monitors Environ. Pollut., 1977, Storrs, CT. 12: 108-118.

Birge, W.J., J.A. Black, A.G. Westerman and J.E. Hudson. 1980. Aquatic Toxicity Tests on Inorganic Elements Occurring in Oil Shale. In: C. Gale (ed.). 1979. EPA-600/9-80-022, Oil Shale Symposium: Sampling, Analysis and Quality Assurance. March 1979. U.S.EPA, Cincinnati, OH: 519-534.

Birge, W.J., R.D. Hoyt, J.A. Black, M.D. Kercher and W.A. Robison. 1993. Effects of Chemical Stresses on Behavior of Larval and Juvenile Fishes and Amphibians. Water Quality and the Early Life Stages of Fishes., American Fisheries Society Symposium 14: 55-65.


Golder Associates

Birge, W.J., J.A. Black, A.G. Westerman, T.M. Short, S.B. Taylor, D.M. Bruser and E.D. Wallingford. 1985. Recommendations on Numerical Values for Regulating Iron and Chloride Concentrations for the Purpose of Protecting Warmwater Species of Aquatic Life in the Commonwealth of Kentucky. University of Kentucky, Lexington, KY. 73 p.

Birge, W.J., J.E. Hudson, J.A. Black and A.G. Westerman. 1978. Embryo-Larval Bioassays on Inorganic Coal Elements and in Situ Biomonitoring of Coal-Waste Effluents. In: Symp.U.S.Fish Wildl.Serv., Surface Mining Fish Wildl. Needs in Eastern U.S., W.VA.: 97-104 pp.

Black, J.A. and W.J. Birge. 1980. An Avoidance Response Bioassay for Aquatic Pollutants. Res. Report No.123, Water Resour. Res. Inst., University of Kentucky, Lexington, Kentucky Y: 34-180490.

Black, J.A. J.B. Barnum and W.J. Birge. 1993. An Integrated Assessment of the Effects of Boron to the Rainbow Trout. Chemosphere 26: 1,383-1,413.

Borgmann, U., Cove, R., and Loveridge, C. 1980. Effect of metals on the biomass kinetics of freshwater copepods. Can. J. Fish. Aquat. Sci. 37(4): 567-575.

Boutet, C. and C. Chaisemartin. 1973. Specific Toxic Properties of Metallic Salts in Austropotamobius pallipes pallipes and Orconectes limosus. C. R. Soc. Biol.(Paris) 167(12): 1,933-1,938.

Brooke L.T., D.J. Call, S.H. Poirier, T.P. Markee, C.A. Lindberg, D.J. McCauley and P.G. Simonson. 1986. Acute Toxicity and Chronic Effects of Bis(tributyltin)oxide to Several Species of Freshwater Organisms. Centre for Lake Superior Environmental Studies, University of Wisconsin-Superior, Wisconsin.

Butterwick, L., N. De Oude and K. Raymond. 1989. Safety Assessment of Boron in Aquatic and Terrestrial Environments. Ecotoxicology and Environmental Safety. 17: 339- 371.

Cabejszek, I. and M. Stasiak. 1960. Investigation on the Influence of some Metals on the Biocoenosis of Water with the use of Daphnia magna as an Indicator (Part I). Roczyn. Zabl. Hig. Warsaw 11: 303-312 (POL) (ENG ABS).


Golder Associates

Call, D.J., L.T. Brook, N. Ahmad and J.E. Richter. 1983. Toxicity and Metabolism Studies with EPA Priority Pollutants and Related Chemicals in Freshwater Organisms. EPA-600/3-83-095. U.S. Environmental Protection Agency, Duluth, MN.

Call, D.J., C.N. Polkinghorne, T.P. Markee, L.T. Brooke, D.L. Geiger, J.W. Gorsuch and K.R. Robillard. 1999. Silver Toxicity to Chironomus tentans in Two Freshwater Sediments. Environ. Toxicol. Chem. 18(1): 30-39.

Callahan, M., Slimak, M., Gabel, N., May, I., Fowler, C., Freed, R., Jennings, P., Durfee, R., Whitmore, F., Maestri, B., Mabay, W., Holt, B., and Gould, C. 1979. Water-related environmental fate of 129 priority pollutants. EPA-440/4-70-029a, U.S. Environmental Protection Agency, Office of Water Planning and Standards, Washington, D.C.

Campbell, P.G.C. and Stokes P.M. 1985. Acidification and Toxicity of Metals to Aquatic Biota. Canadian Journal of Fisheries and Aquatic Sciences 42 (12): 2034-2049.

Canivet, V., Chambon, P., and Gibert, J. 2001. Toxicity and Bioaccumulation of Arsenic and Chromium in Epigean and Hypogean Freshwater Macroinvertebrates. Arch. Environ. Contam. Toxicol. 40(3): 345-354.

Cardwell, R.D., D.G. Forman, T.R. Payne and D.J. Wilbur. 1976. Acute Toxicity of Selected Toxicants to Six Species of Fish. Ecol reserve PA USEPA. Mar 1976. 600/3-76-008. 117 pp.

CCME (Canadian Council of Ministers of the Environment). 1999. (with updates to 2003). Canadian Environmental Quality Guidelines. Winnipeg, MN. Chaikowsky, C.L.A. 2000. Analysis of Alberta Temperature Observations and Estimates by Global Climate Models. Report for Science and Technology Branch, Environmental Sciences Division, Alberta Environment, October 2000, Pub. No: T/562.

CCREM (Canadian Council of Resource and Environment Ministers). 1987. Canadian Water Quality Guidelines of the Canadian Council of Resource and Environment Ministers. March 1987.

Chaisuksant, Y., Q. Yu and D. Connell. 1997. Internal Lethal Concentrations of Halobenzenes with Fish (Gambusia affinis). Ecotoxicol. Environ. Saf. 37: 66-75.


Golder Associates

Chakoumakos, C., R.C. Russo, and R.V. Thurston. 1979. Toxicity of Copper to Cutthroat Trout (Salmo clarki) Under Different Conditions of Alkalinity, pH, and Hardness. Environ.Sci.Technol. 13(2):213-219.

Chapman, G.A. 1978. Toxicities of Cadmium, Copper, and Zinc to Four Juvenile Stages of Chinook Salmon and Steelhead. Trans. Am. Fish. Soc. 107(6): 841-847.

Cleveland, L., D.R. Buckler and W.G. Brumbaugh. 1991. Residue Dynamics and Effects of Aluminum on Growth and Mortality in Brook Trout. Environ. Toxicol. Chem. 10(2): 243-248.

Cotton, F.A. and G. Wilkinson (eds). 1980. Beryllium and the Group II Elements: Mg, Ca, Sr, Ba, Ra. In: Advanced Inorganic Chemistry: A Comprehensive Text. New York, NY: John Wiley & Sons.

Dave, G. 1984. Effects of Waterborne Iron on Growth, Reproduction, Survival and Haemoglobin in Daphnia magna. Comp. Biochem. Physiol. 78C: 433-438.

Davies, T. 2002. Sulphate Toxicity to the Freshwater Organisms and Molybdenum Toxicity to Rainbow Trout (Oncorhynchus mykiss). Masters Thesis, Department of Resource Management and Environmental Studies, University of British Columbia, BC.

Davies, P.H., J.P. Goettl, Jr. and J.R. Sinley. 1978. Toxicity of Silver to Rainbow Trout (Salmo gairdneri). Water Res. 12: 113–117.

Davis, J.C. and B.J. Mason. 1973. Toxicity of Boron to Pacific Salmon, and Boron Uptake Experiments with Pacific Salmon and Oysters. Appendix III. In: Zinc and Boron Pollution in Coastal Waters of British Columbia by Effluents from the Pulp and Paper Industry. 1973. Environment Canada, Pacific Region, Vancouver, B.C.

Davis, J.C., and I.G. Shand. 1978. Acute and Sublethal Copper Sensitivity, Growth and Saltwater Survival in Young Babine Lake Sockeye Salmon. Can.Fish.Mar.Serv.Tech.Rep.No. 847:1-55.

De Foe, D.L. 1982. Arsenic (V) Test Results. U.S.EPA, Duluth, MN. Memo to R.L. Spehar. U.S.EPA, Duluth, MN.


Golder Associates

Diamond, J.M., D.G. Mackler, M. Collins and D. Gruber. 1990. Derivation of a Freshwater Silver Criteria for the New River, Virginia, Using Representative Species. Environ. Toxicol. Chem. 9(11): 1,425-1,434.

Dill, D.C., M.A. Mayes, C.G. Mendoza, G.U. Boggs and J.A. Emmitte. 1982. Comparison of the Toxicities of Biphenyl, Monochlorobiphenyl, and 2,2',4,4'-Tetrachlorobiphenyl to Fish and Daphnids. In: Pearson, J.G., R.B. Foster and W.E. Bishop (eds.). Aquatic Toxicology and Hazard Assessment, 5th Conference, ASTM STP 766. Philadelphia, PA. 245-256.

Dixon, D.G. and J.B. Sprague. 1981. Acclimation-Induced Changes in Toxicity of Arsenic and Cyanide to Rainbow Trout, Salmo gairdneri Richardson. J. Fish Biol. 18(5): 579-589.

Doe, K.G., W.R. Parker, S.J. Ponsford and J.D.A. Vaughan. 1987. The Acute and Chronic Toxicity of Antimony to Daphnia magna and Rainbow Trout. Environmental Protection Service. Conservation and Protection, Environment Canada.

Dowden, B.F. and H.J. Bennett. 1965. Toxicity of Selected Chemicals to Certain Animals. J. Water Pollut. Control Fed. 37(9): 1,308-1,316.

Elnabarawy, M.T., A.N. Welter and R.R. Robideau. 1986. Relative Sensitivity of Three Daphnid Species to Selected Organic and Inorganic Chemicals. Environ. Toxicol. Chem. 5(4): 393-398.

Finlayson, B.J., and K.M. Verrue. 1982.: Toxicities of Copper, Zinc, and Cadmium Mixtures to Juvenile Chinook Salmon. Trans.Am.Fish.Soc. 111(5):645-650.

Evans, D.H. 1987. The Fish Gill - Site of Action and Model For Toxic Effects of Environmental-Pollutants. Environmental Health Perspectives 71: 47-58.

Fromm, P.O. and R.M. Stokes. 1962. Assimilation and Metabolism of Chromium by Trout. J.Water Pollut.Control Fed. 34(11): 1151-1155.

Geckler, J.R., W.B. Horning, T.M. Neiheisel, Q.H. Pickering, E.L. Robinson, and C.E. Stephan. 1976. Validity of Laboratory Tests for Predicting Copper Toxicity in Streams. EPA-600/3-76-116. National Technical Information Service, Springfield, VA.


Golder Associates

Gersich, F.M. 1984. Evaluation of a Static Renewal Chronic Toxicity Test Method for Daphnia magna Straus using Boric Acid. Environmental Toxicology and Chemistry 3(1): 89-94.

Gersich, F.M., E.A. Bartlett, P.G. Murphy and D.P. Milazzo. 1989. Chronic Toxicity of Biphenyl to Daphnia magna Straus. Bull. Environ. Contam. Toxicol. 43(3): 355-362 (OECDG Data File).

Goettl, J.P.Jr., P.H. Davies and J.R. Sinley. 1976. Water Pollution Studies. In: D.B. Cope (Ed.), Colorado Fish.Res.Rev.1972-1975, DOW-R-R-F72-75, Colorado Div. of Wildl., Boulder, CO.: 68-75.

Golder. 2003. Oil Sands Regional Aquatics Monitoring Program (RAMP) - 2002. Submitted to the RAMP Steering Committee. Calgary, AB. 825 pp.

Hibbins, S.G. 1997. Strontium and Strontium Compounds. In: Kroschwitz, J.I. and M. Howe-Grant (eds.). Kirk-Othmer Encyclopedia of Chemical Technology. New York, NY: John Wiley & Sons, Vol. 22 947-955.

Hogstrand, C., F. Galvez and C.M. Wood. 1996. Toxicity, Silver Accumulation and Metallothionein Induction in Freshwater Rainbow Trout During Exposure to Different Silver Salts. Environ. Toxicol. Chem. 15(7): 1,102-1,108.

Holdway, D.A. and J.B. Sprague. 1979. Chronic Toxicity of Vanadium to Flagfish. Water Res. 13(9): 905-910.

ICME (International Council on Metals and the Environment) 1995. Persistence, Bioaccumulation and Toxicity of Metals and Metal Compounds. Prepared by Parametrix, Inc. Ottawa, ON.

Imperial Oil (Imperial Oil Resources Ventures Limited). 2005. Kearl Oil Sands Project - Mine Development. Volume 1 to 9. Submitted to Alberta Energy and Utilities Board and Alberta Environment. Prepared by Imperial Oil Resources Ventures Limited in association with Golder Associates Ltd., AXYS Environmental Consulting Ltd., Komex International Inc. and Nichols Applied Management. Calgary, AB. Submitted July, 2005.

Jana, S. and S.S. Sahana. 1989. Sensitivity of the Freshwater Fishes Clarias batrachus and Anabas testudineus to Heavy Metals. Environment and Ecology 7(2): 265-270.


Golder Associates

Jonnalagadda, S.B. and P.V. Rao. 1993. Toxicity, Bioavailability and Metal Speciation. Compar Biochem Physiol Ser C Compar Pharmacol Toxicol 106(3): 585-595.

Khangarot, B.S. 1991. Toxicity of Metals to a Freshwater Tubificid Worm, Tubifex tubifex (Muller). Bulletin of Environmental Contamination and Toxicology 46(6): 906-912.

Kimball, G. 1978. The Effects of Lesser Known Metals and One Organic to Fathead Minnows (Pimephales promelas) and Daphnia magna. Dept. of Entomology, Fisheries and Wildlife, University of Minnesota, Minneapolis, MN: 88.

Kimball, G. (undated). The Effects of Lesser Known Metals and One Organic to Fathead Minnows (Pimephales promelas) and Daphnia magna. Department of Entomology, Fisheries and Wildlife, University of Minnesota.

Klaine, S.J., T.W. La Point, G.P. Cobb, B.L. Forsythe II, T.P. Bills, M.D. Wenholz and R.D. Jeffers. 1996. Influence of Water Quality Constituents on Silver Toxicity: Preliminary Result Reference Source. In: Andren, A.W. and T.W. Bober (eds.). 3rd Int.Conf.Proc.Transport, Fate and Effects of Silver in the Environment, Aug. 6-9, 1995, Washington, D.C. 65-77 pp.

Knudtson, B.K. 1979. Acute Toxicity of Vanadium to Two Species of Freshwater Fish. Bull. Environ. Contam. Toxicol. 23(1/2): 95-99.

Koponen, K., P. Lindstrom-Seppa and J.V.K. Kukkonen. 2000. Accumulation Pattern and Biotransformation Enzyme Induction in Rainbow Trout Embryos Exposed to Sublethal Aqueous Concentrations of 3,3',4,4'-Tetrachlorobiphenyl. Chemosphere 40(3): 245-253.

Kuhn, R. 1988. Schadstoffwirkungen von Umweltchemikalien im Daphnien-Reproduktions-Test als Grundlage fr die Bewertung der Umweltgefhrlichkeit in Aquatischen Sys. Forschungsbericht 10603052, Mrz (OECDG Data File).

Kuhn, R., M. Pattard, K. Pernak and A. Winter. 1989. Results of the Harmful Effects of Water Pollutants to Daphnia magna in the 21 Day Reproduction Test. Water Res. 23(4): 501-510 (OECDG Data File).


Golder Associates

Lappivaara, J., A. Kiviniemi and A. Oikari. 1999. Bioaccumulation and Subchronic Physiological Effects of Waterborne Iron Overload on Whitefish Exposed in Humic and Nonhumic Water. Arch. Environ. Contam. Toxicol. 37(2): 196-204.

LeBlanc, G.A. and J.W. Dean. 1984. Antimony and Thallium Toxicity to Embryos and Larvae of Fathead Minnows (Pimephales promelas). Bull. Environ. Contam. Toxicol. 32(5): 565-569.

Leino, R.L. and J.H. McCormick. 1993. Histopathological Effects of Experimental Acidification on Largemouth Bass, Rock Bass, and Yellow Perch from Little Rock Lake, Wisconsin. In: Proceedings of the Nineteenth Annual Aquatic Toxicity Workshop: October 4-7, 1992. Edmonton, Alberta. Canadian Technical Report of Fisheries and Aquatic Sciences. 1942: 201-223.

Lewis, M.A. and L.C. Valentine. 1981. Acute and Chronic Toxicities of Boric Acid to Daphnia magna Straus. Bulletin of Environmental Contamination and Toxicology 27(3): 309-315.

Lima, A.R., C. Curtis, D.E. Hammermeister, T.P. Markee, C.E. Northcott and L.T. Brooke. 1984. Acute and Chronic Toxicities of Arsenic (III) to Fathead Minnows, Flagfish, Daphnids, and an Amphipod. Archives of Environmental Contamination and Toxicology. 13 (5): 595-601.

Lin, H.C. and P.P. Hwang. 1998. Acute and Chronic Effects of Antimony Chloride (SbCl3) on Tilapia (Oreochromis mossambicus) Larvae. Bull. Environ. Contam. Toxicol. 61(1): 129-134.

MacDonald, D.D., J.B. Kemper, D.E. Smorong and D.A. Levy. 2002 (Draft). Guidance on the Site-specific Application of Water Quality Guidelines in Canada: Procedures for Deriving Numerical Water Quality Objectives. Prepared for Canadian Council of Ministers of the Environment and Environment Canada.

McDevitt, C.A., J. Pickard, K. Andersen and C. Eickoff. 1999. Toxicity of Molybdenum to Early Life Stages of Rainbow Trout in On Site Bioassays. Proceedings of the 1999 Workshop on Molybdenum Issues in Reclamation. Price, W.A., Hart, B., and Howell, C. (eds.) Bitech Publishers Ltd., Richmond, B.C. 120-129 pp.


Golder Associates

McKim, J.M., and D.A. Benoit. 1971. Effects of Long-Term Exposures to Copper on Survival, Growth, and Reproduction of Brook Trout (Salvelinus fontinalis). J.Fish.Res.Board Can. 28:655-662.

McKim, J.M., Eaton, J.G., and G.W. Holcombe. 1978. Metal Toxicity to Embryos and Larvae of 8 Species of Freshwater Fish .2. Copper. Bulletin of Environmental Contamination and Toxicology 19 (5): 608-616 1978.

Meador, J.P. 1991. The Interaction of pH, Dissolved Organic Carbon, and Total Copper in the Determination of Ionic Copper and Toxicity. Aquat.Toxicol. 19(1):13-31.

Merrett, W.J., G.P. Rutt, N.S. Weatherley, S.P. Thomas and S.J. Ormerod. 1991. The Response of Macroinvertebrates to Low pH and Increased Aluminum Concentrations in Welsh Streams: Multiple Episodes and Chronic Exposure. Arch. Hydrobiol. 121(1): 115-125.

Mount, D. I. 1982. Memorandum to Charles E. Spehar. U.S. Environmental Protection Agency, Duluth, Minn. June 7.

Mount, D.I., and T.J. Norberg. 1984. A Seven-Day Life-Cycle Cladoceran Toxicity Test. Environ.Toxicol.Chem. 3(3):425-434.

Mowbray, D.L. 1988. Assessment of the Biological Impact of Ok Tedi Mine Tailings, Cyanide and Heavy Metals. In: Pernetta, J.C. (ed.). Potential Impacts of Mining on the Fly River, UNEP, Athens, Greece, Reg. Seas Rep. Stud. No. 99: 45-74.

Munzinger, A., and F. Monicelli. 1992. Heavy Metal Co-Tolerance in a Chromium Tolerant Strain of Daphnia magna. Aquat. Toxicol. 23(3/4): 203-216.

Naddy, R.B., T.W. La Point and S.J. Klaine. 1995. Toxicity of Arsenic, Molybdenum and Selenium Combinations to Ceriodaphnia dubia. Environ. Toxicol. Chem. 14: 329-336.

Nebeker, A.V., C.K. McAuliffe, R. Mshar and D.G. Stevens. 1983. Toxicity of Silver to Steelhead and Rainbow Trout, Fathead Minnows and Daphnia magna. Environ. Toxicol. Chem. 2: 95-104.


Golder Associates

Nebeker, A.V., M.A. Cairns, and C.M. Wise. 1984. Relative Sensitivity of Chironomus tentans Life Stages to Copper. Environ.Toxicol.Chem. 3(1):151-158.

Nichols, J.W., G.A. Wedemeyer, F.L. Mayer, W.W. Dickhoff, S.V. Gregory, W.T. Yasutake and S.D. Smith. 1984. Effects of Freshwater Exposure to Arsenic Trioxide on the Parr-smolt Transformation of Coho Salmon (Oncorhynchus kisutch). Environ. Toxicol. Chem. 3(1): 143-149.

NRCC (National Research Council of Canada). 1978. Associated Committee on Scientific Criteria for Environmental Quality Subcommittee on Heavy Metals and Other Compounds. Effects of Arsenic in the Canadian Environment. NRCC, Ottawa, 349 pp.

NWQMS (National Water Quality Management Strategy). 2000. Australian and New Zealand Guidelines for Fresh and Marine Water Quality. Prepared by Australia and New Zealand Environment and Conservation Council (ANZECC) and Agriculture and Resource Management Council of Australia and New Zealand (ARMCANZ).

OECD (Organisation for Economic Co-operation and Development). 1994. Risk Reduction Monograph No. 5: Cadmium. OECD Environment Directorate. Paris, France.

Parametrix. 1995. Persistence Bioaccumulation and Toxicity of Metal Compounds. A Publication by the International Council on Metals and the Environment. Prepared by: Parametrix Inc. Washington DC.

Parkhurst, B.R., W. Warren-Hicks, R.D. Cardwell, J. Volosin, T. Etchison, J.B. Butcher and S.M. Covington. 1996. Methodology for Aquatic Ecological Risk Assessment. RP91-AER-1. Water Environment Research Foundation, Alexandria, VA, USA.

Paulson, P.C., J.R. Pratt, and J. Cairns Jr. 1983. Relationship of Alkaline Stress and Acute Copper Toxicity in the Snail Goniobasis livescens (Menke). Bull.Environ.Contam.Toxicol. 31(6):719-726.

Peuranen, S., P.J. Vuorinen, M. Vuorinen and H. Tuurala. 1993. Effects of Acidity and Aluminium on Fish Gills in Laboratory Experiments and in the Field. Sci. Total Envir. Suppl. 979-988 pp.


Golder Associates

Pickard, J., McKee, P. and Stroiazzo, J. 1999. Site specific multi-species toxicity testing of sulphate and molybdenum spiked mining effluent and receiving water. Proceedings of the 1999 Workshop on Molybdenum Issues in Reclamation. Price, W.A., Hart, B., and Howell, C. (eds). Bitech Publishers Ltd., Richmond, B.C. 86-95 pp.

Pickering, Q.H. 1988. Evaluation and Comparison of Two Short-Term Fathead Minnow Tests for Estimating Chronic Toxicity. Water Res. 22(7): 883-893.

Posthuma, L., G.W. Suter II and T.P. Traas. 2002. Species Sensitivity Distributions in Ecotoxicology. Lewis Publishers, Boca Raton.

Reader, J., T. Dalziel and R. Morris. 1988. Growth, Mineral Uptake and Skeletal Calcium Deposition in Brown Trout, Salmo trutta, L., Yolk Sac Fry Exposed to Aluminum and Manganese in Soft Acid Water. J. Fish. Biol. 32: 607-624.

Rehwoldt, R., L. Lasko, C. Shaw, and E. Wirhowski. 1973. The Acute Toxicity of Some Heavy Metal Ions Toward Benthic Organisms. Bull.Environ.Contam.Toxicol. 10(5):291-294.

Rodgers Jr., J.H., E. Deaver and P.L. Rogers. 1994. Evaluations of the Bioavailability and Toxicity of Silver in Sediment. Proceedings, 2nd Argentum International Conference on the Transport, Fate, and Effects of Silver in the Environment, Madison, WI, USA, September 11-14, 131-138 pp.

Rodgers, J.H.J., E. Deaver, B.C. Suedel and P.L. Rogers. 1997. Comparative Aqueous Toxicity of Silver Compounds: Laboratory Studies with Freshwater Species. Bull. Environ. Contam. Toxicol. 58: 851-858.

Sample, B.E., G.W. Suter II, M.B. Sheaffer, D.S. Jones and R.A. Efroymson. 1997. Ecotoxicological Profiles for Selected Metals and Other Inorganic Chemicals. Risk Assessment Program, Oak Ridge National Laboratory, Oak Ridge, Tennessee.

Sanborn, N.H. 1945. The Lethal Effect of Certain Chemicals on Fresh Water Fish. The Canning Trade 16(27): 13-15.


Golder Associates

Sauter, S., K. S. Buxton, K. J. Macek, and S. R. Petrocelli. 1976. Effects exposure to heavy metals on selected freshwater fish. EPA-600/3-76-105. U.S. Environmental Protection Agency, Duluth, Minn.

Schumaker, R.J., W.H. Funk and B.C. Moore. 1993. Zooplankton Responses to Aluminum Sulfate Treatment of Newman Lake, Washington. Journal of Freshwater Ecology., Vol. 8, No. 4, 375-387 pp.

Shell (Shell Canada Limited). 2005. Muskeg River Mine Expansion Project Application and Environmental Impact Assessment. Submitted to Alberta Energy and Utilities Board and Alberta Environment. Prepared by Golder Associates Ltd. and Nichols Applied Management. Volume 1,2, 3 and 4. Fort McMurray, AB. Submitted April, 2005.

Sorensen, E.M.B. 1976. Toxicity and Accumulation of Arsenic in Green Sunfish, Lepomis cyanellus, Exposed to Arsenate in Water. Bull. Environ. Contam. Toxicol. 15(6): 756 761.

Sorensen, E.M.B. and N.K.R. Smith. 1981. Hemosiderin Granules: Cytotoxic Response to Arsenic Exposure in Channel Catfish. Bulletin of Environmental Contamination and Toxicology 27(5): 645-653.

Spehar, R.L. and J.T. Fiandt. 1986. Acute and Chronic Effects of Water Quality Criteria-Based Metal Mixtures on Three Aquatic Species. Environ. Toxicol. Chem. 5(10): 917-931.

Spehar, R.L., J.T. Fiandt, R.L. Anderson and D.L. De Foe. 1980. Comparative Toxicity of Arsenic Compounds and Their Accumulation in Invertebrates and Fish. Arch. Environ. Contam. Toxicol. 9(1): 53-63.

SPSS Inc. 2002. SigmaPlot 8.0. Chicago, Illinois.

Stephan, C.E., D.I. Mount, D.J. Hansen, J.H. Gentile, G.A. Chapman and W.A. Brungs. 1985. Guidelines for Deriving Numerical National Water Quality Criteria for the Protection of Aquatic Organisms and Their Uses. PB85-227049. National Technical Information Services, Springfield, VA.

Stephenson, R.R. 1983. Effects of Water Hardness, Water Temperature, and Size of the Test Organism on the Susceptibility of the Fresh-Water Shrimp, Gammarus-Pulex (L), to Toxicants. Bulletin of Environmental Contamination and Toxicology 31 (4): 459-466.


Golder Associates

Sprague, J.B., and B.A. Ramsay. 1965. Lethal Levels Mixed Copper-Zinc Solutions for Juvenile Salmon. Journal of the Fisheries Research Board of Canada 22 (2): 425-& 1965.

Suedel, B.C., E. Deaver, and J.H. Rodgers Jr. 1996. Experimental Factors that may Affect Toxicity of Aqueous and Sediment-Bound Copper to Freshwater Organisms. Arch.Environ.Contam.Toxicol. 30(1):40-46.

Suncor. 2005. Voyageur Project Application and Environmental Impact Assessment. Volumes 1A, 1B, 2, 3, 4, 5 and 6. Submitted to Alberta Energy and Utilities Board and Alberta Environment. Prepared by Suncor Energy Inc. Oil Sands in Association with Golder Associates Ltd. And Nichols Applied Management. March 2005. Fort McMurray, AB.

Surber, E.W. and O.L. Meehean. 1931. Lethal Concentrations of Arsenic for Certain Aquatic Organisms. Trans. Am. Fish. Soc. 61: 225-239.

Suter, G. II and L. Barnthouse. 1993. Chapter 2: Assessment Concepts. In: Ecological Risk Assessment. G.W. Suter II (editor). Lewis Publishers, Chelsea, MI.

Suter, G.W. II and C. Tsao. 1996. Toxicological Benchmarks for Screening of Potential Contaminants of Concern for Effects on Aquatic Biota: 1996 Revision. ES/ER/TM-96/RI. Oak Ridge National Laboratory, Oak Ridge, Tennessee.

Thompson, J.A.J., J.C. Davis and R.E. Drew. 1976. Toxicity, Uptake and Survey Studies of Boron in the Marine Environment. Water Res. 10: 869-875.

Trabalka, J.R. and C.W. Gehrs, 1977. An Observation on the Toxicity of Hexavalent Chromium to Daphnia magna, Toxicol. Lett., 1: 131-134.

U.S. EPA (United States Environmental Protection Agency). 1978. Quality Criteria for Water (Red Book). Washington, DC. PB-263 943.

U.S. EPA. 1980a. Ambient Water Quality Criteria for Beryllium. EPA 440/5-80-024. U.S. Environmental Protection Agency, Washington, D.C.

U.S. EPA. 1980b. Ambient Water Quality Criteria for Silver. EPA 440/5-80-071. U.S. Environmental Protection Agency, Washington, D.C.


Golder Associates

U.S. EPA. 1984. Ambient Water Quality Criteria for Cadmium - 1984. EPA 440/5-84-032. U.S. Environmental Protection Agency, Washington, D.C.

U.S. EPA. 1985a. Ambient Water Quality Criteria for Arsenic - 1984. EPA 440/5-84-033. U.S. Environmental Protection Agency, Washington, D.C.

U.S. EPA. 1985b. Ambient Water Quality Criteria for Copper - 1984. U.S. Department of Commerce, National Technical Information Service (NTIS). EPA 440/5-84-031.

U.S. EPA. 2001. Update of Ambient Water Quality Criteria for Cadmium. EPA-822-R-01-001. National Technical Information Service, Springfield, VA.

U.S. EPA. 2002. National Recommended Water Quality Criteria: 2002. Office of Water 4304T. United States Environmental Protection Agency. EPA 822-R-02-047.

Versteeg, D.J., S.E. Belanger and G.J. Carr. 1999. Understanding Single Species and Model Ecosystem Sensitivity: Data-based Comparison. Environ. Toxicol. Chem. 18(6): 1,329-1,346.

Vuorinen, P.J., M. Rask, M. Vuorinen, S. Peuranen and J. Raitaniemi. 1994. The Sensitivity to Acidification of Pike (Esox lucius), Whitefish (Coregonus lavaretus) and Roach (Rutilus rutilus): Comparison of Field and Reference Source. In: R. Muller and R. Lloyd (eds.). Sublethal and Chronic Effects of Pollutants on Freshwater Fish. Chapter 25. Fishing News Books, London : 283-293.

Walker, M.K. and R.E. Peterson. 1991. Potencies of Polychlorinated Dibenzo-p-Dioxin, Dibenzofuran, and Biphenyl Congeners, Relative to 2,3,7,8-Tetrachlorodibenzo-p-Dioxin, for Producing Early Life Stage Mortality in Rainbow Trout (Oncorhynchus mykiss). Aquat. Toxicol. 21: 219-238.

Warnick, S.L., and H.L. Bell. 1969. The Acute Toxicity of Some Heavy Metals to Different Species of Aquatic Insects. J.Water Pollut.Control Fed. 41(2 Pt.1):280-284.

Wehrli, B. and Stumm, W. 1989. Vanadyl in Natural-Waters - Adsorption and Hydrolysis Promote Oxygenation. Geochimica et Cosmochimica Acta 53 (1): 69-77.


Golder Associates

Williams, P.L. and D.B. Dusenbery. 1990. Aquatic Toxicity Testing Using the Nematode, Caenorhabditis elegans. Environmental Toxicology and Chemistry 9(10): 1,285-1,290.

Wood, C.M. 1992. Flux Measurements as Indexes of H+ and Metal Effects on Fresh-Water Fish. Aquatic Toxicology 22 (4): 239-264.

WHO (World Health Organization). 1988. Vanadium. Environmental Health Criteria 81. World Health Organization, Geneva, Switzerland.

Wright, D.A. and P.M. Welbourn. 1994. Cadmium in the Aquatic Environment: A Review of Ecological, Physiological, and Toxicological Effects on Biota.

Wurtz, C.B., and C.H. Bridges. 1961. Preliminary Results From Macro-Invertebrate Bioassays. Proc.Pa.Acad.Sci. 35:51-56.

Zabel, E.W., P.M. Cook and R.E. Peterson. 1995. Toxic Equivalency Factors of Polychlorinated Dibenzo-p-Dioxin, Dibenzofuran and Biphenyl Congeners Based on Early Life Stage Mortality in Rainbow Trout. Aquat. Toxicol. 31(4): 315-328.

ATTACHMENT III-A

SUMMARY OF AVAILABLE CHRONIC TOXICITY DATA FOR SUBSTANCES OF POTENTIAL CONCERN

CEMA A-1 Athabasca River Reach Specific May 2007 Water Quality Objectives

Golder Associates

Table IIIA-1 Summary of Chronic Toxicity Data Available of Aluminum

Metal Speciation Species Name Common Name Chronic

value (ug/L)

Hardness (ug/L) pH Temp

(oC) End-point Source Included/Excluded

aluminum chloride Daphnia magna Water flea 680 EC50 Biesinger and Christensen 1972 Included

Sulfuric acid, Aluminum salt (3:2) Rotifera Rotifer phylum 1000 Population Schumaker et al. 1993 Included

Sulfuric acid, Aluminum salt (3:2) Daphnia magna Water flea 2840 211000 8.3 19.9 MATC (Reproduction) Kimball 1978 Included

Sulfuric acid, Aluminum salt (3:2) Daphnia magna Water flea 4260 211000 8.3 19.9 LOEC (Reproduction) Kimball 1978 Included

Sulfuric acid, Aluminum salt (3:2) Pimephales promelas Fathead minnow 5800 233000 7.27 24.8 MATC (weight) Kimball 1978 Included

Sulfuric acid, Aluminum salt (3:2) Pimephales promelas Fathead minnow 5800 233000 7.27 24.8 MATC (length) Kimball 1978 Included

Sulfuric acid, Aluminum salt (3:2) Pimephales promelas Fathead minnow 7100 233000 7.27 24.8 LOEC (weight) Kimball 1978 Included

Sulfuric acid, Aluminum salt (3:2) Pimephales promelas Fathead minnow 7100 233000 7.27 24.8 LOEC (length) Kimball 1978 Included

Sulfuric acid, Aluminum salt (3:2) Pimephales promelas Fathead minnow 9200 233000 7.27 24.8 MATC (% survival) Kimball 1978 Included

Sulfuric acid, Aluminum salt (3:2) Pimephales promelas Fathead minnow 11900 233000 7.27 24.8 LOEC (% survival) Kimball 1978 Included

aluminum chloride Carassius auratus Goldfish 150 195000 7.4 22 LC50 Birge 1978 Excluded (non resident species)

aluminum Carassius auratus Goldfish 150 LC50 Birge et al. 1979 Excluded (non resident species)

aluminum chloride Oncorhynchus mykiss Rainbow trout 29 5.3 15 Behaviour Allin and Wilson 1999 Excluded (Low pH)

aluminum Micropterus salmoides Largemouth bass 29.2 cellular changes Leino and McCormick 1993 Excluded (Low pH)

aluminum chloride Salmo salar Atlantic salmon 70 5 13 Behaviour Atland and Barlaup 1996 Excluded (Low pH)

aluminum chloride Catostomus commersoni White sucker 70 growth Baker and Schofield 1982 Excluded (Low pH)

aluminum chloride Salvelinus fontinalis Brook trout 70 growth Baker and Schofield 1982 Excluded (Low pH)

aluminum fluoride Esox lucius Northern pike 100 EC50 Vuorinen et al. 1994 Excluded (Low pH)

Sulfuric acid, Aluminum salt (3:2) Coregonus lavaretus Pollan, whitefish 100 EC50 Vuorinen et al. 1994 Excluded (Low pH)


aluminum Coregonus lavaretus Pollan whitefish 176 physiological changes Peuranen et al. 1993 Excluded (Low pH)


Table IIIA-1 Summary of Chronic Toxicity Data Available of Aluminum (continued)

Golder Associates

Metal Speciation Species Name Common Name Chronic

value (ug/L)

Hardness (ug/L) pH Temp

(oC) End-point Source Included/Excluded


Sulfuric acid, Aluminum salt (3:2) Amphinemura Sulcicollis Stonefly 360 4.8-7 Population Merret et al. 1991 Excluded (Low pH)

Sulfuric acid, Aluminum salt (3:2) Rhithrogena semicolorata Mayfly 360 4.8-7 Population Merret et al. 1991 Excluded (Low pH)

Sulfuric acid, Aluminum salt (3:2) Hydropsyche instabilis Caddisfly 360 4.8-7 Population Merret et al. 1991 Excluded (Low pH)


aluminum Salvelinus fontinalis Brook trout 268 growth Cleveland et al. 1991 Excluded (endpoint)

Sulfuric acid, Aluminum salt (3:2) Daphnia magna Water flea 1890 211000 8.3 19.9 NOEC (Reproduction) Kimball 1978 Excluded (endpoint)

Sulfuric acid, Aluminum salt (3:2) Pimephales promelas Fathead minnow 3288 CV Suter and Tsao 1996 Excluded (endpoint)


Golder Associates

Table IIIA-2 Summary of Chronic Toxicity Data Available of Antimony Metal Speciation Species Name Common Name Chronic Value (ug/L) End-point Source Included/Excluded

antimony trichloride Oncorhynchus mykiss rainbow trout 580 LC50 (embryo/larva) Birge 1978 Included

antimony trichloride Daphnia magna Cladoceran 1600 28-d life-cycle test Suter and Tsao 1996 Included

antimony trichloride Pimephales promelas Fathead minnow 2300 LOEC (growth) Kimball n.d. Included

antimony trichloride Daphnia magna Cladoceran 2700 LC50 Doe et al. 1987 Included

antimony trichloride Daphnia magna Cladoceran 4500 LC50 Kimball n.d. Included

antimony trichloride Pimephales promelas Fathead minnow 5400 embryo/larval Suter and Tsao 1996 Included

antimony trichloride Pimephales promelas Fathead minnow 9300 LOEC (lethality) Kimball n.d. Included

antimony trichloride Daphnia magna Cladoceran 12100 LC50 Doe et al. 1987 Included

antimony trichloride Oncorhynchus mykiss rainbow trout 16000 LC50 Doe et al. 1987 Included

antimony Caenorabditis elegans Nematode 20000 LC50 Williams and Dusenbery 1990 Included

antimony trichloride Gammarus pseudolimnaeus amphipod 25700 LC50 Brooke et al. 1986 Included

antimony trichloride Tubifex tubifex Worm 678000 EC50 Khangarot 1991 Included

antimony trichloride Hydra 500 EC50 Brooke et al. 1986 Excluded (non resident species)

antimony trichloride Carassius auratus Goldfish 11300 LC50 Birge 1978 Excluded (non resident species)

antimony trichloride Oreochromis mossambicus Tilapia 15000 LOEC Lin and Hwang 1998 Excluded (non resident species)

Antimony trioxide Pimephales promelas Fathead minnow 7.5 NOEC (embryo/larval) Leblanc and Dean 1984 Excluded (end point)

antimony trichloride Oncorhynchus mykiss rainbow trout 28.6 LC1 (embryo/larva) Birge 1978 Excluded (end point)

antimony trichloride Carassius auratus Goldfish 111 LC1 Birge 1978 Excluded (end point)

antimony trichloride Daphnia magna Cladoceran 800 NOEC (growth) Doe et al. 1987 Excluded (end point)

antimony trichloride Daphnia magna Cladoceran 1700 NOEC Doe et al. 1987 Excluded (end point)

antimony trichloride Lumbriculus variegatus annelid 25700 NOEC Brooke et al. 1986 Excluded (end point)

antimony trichloride Pycnopsyche sp. caddisfly 25700 NOEC Brooke et al. 1986 Excluded (end point)


Golder Associates

Table IIIA-3 Summary of Chronic Toxicity Data Available of Arsenic

Metal Speciation Species Name Common Name Chronic Value (µg/L) End-point Source Include/Exclude

Arsenic Daphnia magna Cladoceran 520 EC16 Biesinger and Christensen 1972 Included

As(III) - AsNaO2 Oncorhynchus mykiss rainbow trout 134 EC10 U.S. EPA 1984 Included

As(III) - AsNaO2 Oncorhynchus kisutch Coho salmon 300 Physiological alteration Nichols et al. 1984 Included

As(III) C.vernalis Copepod 320 EC20 Borgmann et al. 1980 Included

As(III) - AsNaO2 Oncorhynchus mykiss rainbow trout 540 LC50 (Chronic) Birge 1978 Included

As(III) - AsNaO2 Oncorhynchus mykiss rainbow trout 550 EC50 Birge and Black 1981 Included

As(III) Gammarus pseudolimnaeus Amphipod 960 80% mortality Spehar et al. 1980 Included

As(III) C. dubia Cladoceran 1000 LOEC Spehar and Fiant 1986 Included

As(III) Oncorhynchus mykiss rainbow trout 1000 decrease in fat weight gain U.S. EPA 1984 Included

As(III) Daphnia magna Cladoceran 1320 LOEC (% Survival) Lima et al. 1984 Included

As(III) Daphnia magna Cladoceran 1320 LOEC (production of young) Lima et al. 1984 Included

As(III) Daphnia magna Cladoceran 1320 LOEC (length) Lima et al. 1984 Included

As(III) Daphnia magna Cladoceran 1400 50% reproductive impairment Biesinger and Christensen 1972 Included

As(III) Caenis diminuta Mayfly nymph 2234 25% mort Surber and Meehean 1931 Included

As(III) Daphnia magna Cladoceran 2850 LC50 Biesinger and Christensen 1972 Included

As(III) Pimephales promelas Fathead minnow 4300 LOEC (length) Lima et al. 1984 Included

As(III) Pimephales promelas Fathead minnow 4300 LOEC (weight) Lima et al. 1984 Included

As(III) Callibaetus sp. Mayfly 4469 94% mortality Surber and Meehean 1931 Included

As(III) Hyalella knickerbockeri Amphipod 4469 70% mortality Surber and Meehean 1931 Included

As(III) Caenis diminuta Mayfly nymph 5958 62% mort Surber and Meehean 1931 Included

As(III) - AsNaO2 Salvelinus fontinalis Brook trout 10440 LC50 (262 h) Cardwell et al. 1976 Included

As(III) - AsNaO2 Pimephales promelas Fathead minnow 10556 LC50(336 h) Cardwell et al. 1976 Included

As(III) Oncorhynchus mykiss rainbow trout 13300 LC50 Dixon and Sprague 1981 Included

As(III) Pimephales promelas Fathead minnow 16500 LOEC (% Survival) Lima et al. 1984 Included

As(V) Daphnia magna Cladoceran 450 Life cycle tests U.S. EPA 1985a Included

As(V) Pimephales promelas Fathead minnow 892 EC20 De Foe 1982 Included

CEMA A-5 Athabasca River Reach Specific May 2007 Water Quality Objectives Table IIIA-3 Summary of Chronic Toxicity Data Available of Arsenic (continued)

Golder Associates


Arsenic A. testudineus climbing perch 500 LOEC Jana and Sahana 1989 Excluded (non resident species)

Arsenic A. testudineus climbing perch 970 LOEC Jana and Sahana 1989 Excluded (non resident species)

Arsenic Clarias batrachus catfish 970 LOEC Jana and Sahana 1989 Excluded (non resident species)

Arsenic acid, Sodium salt Lepomis cyanellus Green sunfish 30000 LT50 Sorensen 1976 Excluded (non resident species)





As(III) Jordinella floridae Flagfish 2960 CV Lima et al. 1984 Excluded (non resident species)

As(V) Carassius auratus goldfish 24600-41600 LC50 NRCC 1978 Excluded (non resident species)

AsNaO2 Carassius auratus goldfish 490 LC50 (Chronic) Birge 1978 Excluded (non resident species)

AsNaO2 Ictalurus punctatus channel catfish 15000 ultrastructural changes in liver Sorensen and Smith 1981 Excluded (non

resident species)

AsNaO2 Lepomis macrochirus Bluegill sunfish 18328 LC50 (336 h) Cardwell et al. 1976 Excluded (non resident species)

AsNaO2 Carassius auratus goldfish 18618 LC50 (336 h) Cardwell et al. 1976 Excluded (non resident species)

AsNaO2 Micropterus salmoides largemouth bass 42100 EC50 Birge 1978 Excluded (non resident species)

As(III) Pimephales promelas Fathead minnow 2962 CEV Call et al. 1983 Excluded (end-point)


Golder Associates

Table IIIA-4 Summary of Chronic Toxicity Data Available of Barium Metal Speciation Species Name Common Name Chronic Value (µg/L) End-point Source Include/Exclude

Barium chloride Daphnia magna Crustacean 5800 EC16 (Rep) Biesinger and Christensen 1972 Included

Barium chloride Daphnia magna Crustacean 8900 EC50 (21-d) Biesinger and Christensen 1972 Included

Barium chloride Daphnia magna Crustacean 13500 EC50 (21-d) Biesinger and Christensen 1972 Included

Barium chloride Daphnia magna Crustacean 14500 LC50 (48h) Biesinger and Christensen 1972 Included

Barium chloride Oncorhynchus mykiss Rainbow trout 42700 LC50(28-d) Birge et al. 1980 Included

Barium chloride Orconectes limosus Crayfish 59000 LC50 Boutet and Chaisemartin 1973 Included

Barium chloride Orconectes limosus Crayfish 61000 LC50 Boutet and Chaisemartin 1973 Included

Barium chloride Austropotamobius pallipes pall Crayfish 39000 LC50 Boutet and Chaisemartin 1973 Excluded (non resident species)

Barium chloride Austropotamobius pallipes pall Crayfish 43000 LC50 Boutet and Chaisemartin 1973 Excluded (non resident species)

Table IIIA-5 Summary of Chronic Toxicity Data Available of Beryllium Metal Speciation Species Name Common Name Chronic Value (µg/L) End-point Source Include/Exclude Beryllium sulphate Daphnia magna Cladoceran 7.3 LOEC Kimball 1978 Included Beryllium Pimephales promelas Fathead minnow 148 EC20 U.S. EPA 1980a Included

Beryllium sulphate Carassius auratus Goldfish 38400 LC50 (Mort. 240 H) Cardwell et al. 1976 Excluded (non resident species)





Beryllium Daphnid spp. 3.8 EC20 Suter and Tsao 1996 Excluded (end point) Beryllium Daphnia magna Cladoceran 5 CV Sample et al. 1997 Excluded (end point) Beryllium Daphnia magna Cladoceran 5.3 CV Suter and Tsao 1996 Excluded (end point) Beryllium Pimephales promelas Fathead minnow 57 CV U.S. EPA 1980a Excluded (end point)


Golder Associates

Table IIIA-6 Summary of Chronic Toxicity Data Available of Boron Metal Speciation Species Name Common Name Chronic Value (µg/L) End-point Source Include/Exclude

Boric acid O. Mykiss rainbow trout 100 LOEC Black et al. 1993 Included

Boric acid O. Mykiss rainbow trout 100 LOEC (mort) ANZECC 1999 Included

Boric acid O. Mykiss rainbow trout 1000 LOEC (36 D) Butterwick et al. 1989 Included

Boric acid Daphnia magna Cladoceran 9300 MATC ANZECC 1999 Included

Borax O. Mykiss rainbow trout 9700 LOEC Birge and Black 1977 Included

Boric acid O. Mykiss rainbow trout 12170 LOEC Birge and Black 1981 Included

Boric acid Daphnia magna Cladoceran 13000 LOEC (21 D) Lewis and Valentine 1981 Included

Boric acid Daphnia magna Cladoceran 13100 LOEC BCMELP 1996 Included

Boric acid Daphnia magna Cladoceran 13600 LC50 (21 D) Gersich 1984 Included

Boric acid O. Mykiss rainbow trout >17000 LOEC (60 D) Butterwick et al. 1989 Included

Boric acid Pimephales promelas Fathead minnow 24000 LOEC (growth) Butterwick et al. 1989 Included

Boric acid Daphnia magna Cladoceran 25400 LOEC (21 D) BCMELP 1996 Included

Boric acid Daphnia magna Cladoceran 26400 LOEC (21 D) BCMELP 1996 Included

Borax O. Mykiss rainbow trout 27000 LC50 (28D) Birge and Black 1977 Included

Borax O. Mykiss rainbow trout 49700 LOEC Birge and Black 1977 Included

Boric acid Daphnia magna Cladoceran 52200 LC50 (21 D) Gersich 1984 Included

Boric acid Daphnia magna Cladoceran 53200 LC50 (21 D) Lewis and Valentine 1981 Included

Borax O. Mykiss rainbow trout 54000 LC50 (28 D) Birge and Black 1977 Included

Boric acid O. Mykiss rainbow trout 79000 LC50 (28 D) Birge and Black 1977 Included

Boric acid Pimephales promelas Fathead minnow 88000 LOEC (survival) Butterwick et al. 1989 Included

Boric acid Micropterus salmoides largemouth bass 92000 LC50 (11 D) Birge et al. 1993 Included

sodium metaborate O. kisutch coho salmon 93000 LC50 Davis and Mason 1973 Included


sodium metaborate O. kisutch coho salmon 113000 LC50 Thompson et al. 1976 Included

Boric acid O. Mykiss rainbow trout 138000 LC50 (28 D) Black et al. 1993 Included


Boric acid Daphnia magna Cladoceran 266000 LC50 ANZECC 1999 Included

Boric acid O. Mykiss rainbow trout 969000 EC50 (7D) BCMELP 1996 Included

Boric acid Ictalurus punctatus channel catfish 22000 LC50 (28 D) Birge and Black 1977 Excluded (non resident species)

CEMA A-8 Athabasca River Reach Specific May 2007 Water Quality Objectives Table IIIA-6 Summary of Chronic Toxicity Data Available of Boron (continued)

Golder Associates


Boric acid Carassius auratus goldfish 46000 LC50 (28 D) Birge and Black 1977 Excluded (non resident species)

Borax Carassius auratus goldfish 59000 LC50 (28 D) Birge and Black 1977 Excluded (non resident species)

Borax Carassius auratus goldfish 65000 LC50 (28 D) Birge and Black 1977 Excluded (non resident species)

Borax Ictalurus punctatus channel catfish 71000 LC50 (28 D) Birge and Black 1977 Excluded (non resident species)

Boric acid Carassius auratus goldfish 75000 LC50 (28 D) Birge and Black 1977 Excluded (non resident species)






Boric acid Daphnia magna Cladoceran 8830 CV Sample et al. 1997 Excluded (end-point)

Boric acid Daphnia magna Cladoceran 9330 CV Sample et al. 1997 Excluded (end-point)


Golder Associates

Table IIIA-7 Summary of Chronic Toxicity Data Available for Hexavalent Chromium (VI)

Metal species Species Common

Name

Measured Chronic Value

(µg/L) End-Point Source Site-Specific

Screening

Chromium (VI) Asellus aquatics Isopod 510 LC50 (240-h) Canivet et al. 2001 Included

Chromium (VI) Ceriodaphnia reticulata Cladoceran 40 LC50 (>96-h) Mount 1982 Included

Chromium (VI) Daphnia pulex Cladoceran 6.132 LC50 (>96-h) Mount 1982 Included

Chromium (VI) Daphnia magna Water flea 480 LC50 (120-h) Cabejszek and Stasiak 1960 Included

Chromium (VI) Daphnia magna Water flea 5 100% mort. Munzinger and Monicelli 1992 Included

Chromium (VI) Daphnia magna Water flea 2,000 EC50 (21-d) Biesinger and Christensen 1972 Included

Chromium (VI) Daphnia magna Water flea 600 EC50 (21-d) Biesinger and Christensen 1972 Included

Chromium (VI) Daphnia magna Water flea 10 LC50 (>96-h) Trabalka and Gahrs 1997 Included

Chromium (VI) Daphnia magna Water flea 2.5 LC50 (>96-h) Mount 1982 Included

Chromium (VI) Gammarus fossarum Amphipod 190 LC50 (240-h) Canivet et al. 2001 Included

Chromium (VI) Heptagenia sulphurea Mayfly 220 LC50 (240-h) Canivet et al. 2001 Included

Chromium (VI) Hydropsiche pellucidula Caddisfly 4,800 LC50 (240-h) Canivet et al. 2001 Included

Chromium (VI) Niphargus rhenorhodanensis Amphipod 230 LC50 (240-h) Canivet et al. 2001 Included

Chromium (VI) Oncorhynchus mykiss Rainbow trout 180 LC50 (28-d) Birge 1978 Included

Chromium (VI) Oncorhynchus mykiss Rainbow trout 180 LC50 (28-d) Birge et al. 1978 Included

Chromium (VI) Oncorhynchus mykiss Rainbow trout 190 LC50 (28-d) Birge et al. 1980 Included

Chromium (VI) Oncorhynchus mykiss Rainbow trout 10 100% survival Fromm and Stokes 1962 Included

Chromium (VI) Oncorhynchus mykiss Rainbow trout 264.6 LC50 (>96-h) Benoit 1976 Included

Chromium (VI) Oncorhynchus mykiss Rainbow trout 73.18 LC50 (>96-h) Sauter et al. 1976 Included

Chromium (VI) Orconectes limosus Crayfish 1,800 LC50 (30-d) Boutet and Chaisemartin 1973 Included


Table IIIA-7 Summary of Chronic Toxicity Data Available for Hexavalent Chromium (continued)

Golder Associates

Metal species Species Common

Name

Measured Chronic Value

(µg/L) End-Point Source Site-Specific

Screening

Chromium (VI) Orconectes limosus Crayfish 3,100 LC50 (30-d) Boutet and Chaisemartin 1973 Included

Chromium (VI) Physa fontinalis Snail 4,200 LC50 (240-h) Canivet et al. 2001 Included

Chromium (VI) Pimephales promelas Fathead minnow 6,000 LOEC (7-d) Pickering 1988 Included

Chromium (VI) Pimephales promelas Fathead minnow 2,400 LOEC (7-d) Pickering 1988 Included

Chromium (VI) Salvelinus fontinalis Brook trout 264.6 LC50 (>96-h) Benoit 1976 Included

Chromium (VI) Simocephalus serrulatus Cladoceran 19.9 LC50 (>96-h) Mount 1982 Included

Chromium (VI) Simocephalus vetulus Cladoceran 6.132 LC50 (>96-h) Mount 1982 Included


Golder Associates

Table IIIA-8 Summary of Chronic Toxicity Data Available for Copper

Metal Species Species Name Common

Name

Selected Chronic Value at 180

mg/L Hardness End point Source Original Source

Excluded/ Included

Copper Ceriodaphnia dubia Cladoceran 10.47 LC50 or EC50 U.S. EPA Suedel et al. 1996 Included

Copper Daphnia pulicaria Cladoceran 10.64 LC50 or EC50 U.S. EPA Lind et al. manuscript Included

Copper Ceriodaphnia reticulata Cladoceran 11.35 LC50 or EC50 U.S. EPA Included

Copper Oncorhynchus kisutch (smolt) Coho salmon 12.68 LC50 or EC50 U.S. EPA Chapman 1978 Included

Copper Oncorhynchus tshawytscha

Chinook salmon 16.19 LC50 or EC50 U.S. EPA

Finleyson and Verrue 1982 Included

Copper sulphate Gammarus pseudolimnaeus Amphipod 20.03 LC50 or EC50 U.S. EPA Arthur and Leonard 1970 Included

Copper Moina dubia Cladoceran 22.06 LC50 or EC50 U.S. EPA Included

Copper Daphnia magna Cladoceran 24.98 LC50 or EC50 U.S. EPA Meador 1991 Included

Copper chloride Salmo clarki Cutthroat trout 25.38 LC50 or EC50 U.S. EPA Chakoumakos et al. 1979 Included

Copper chloride Gammarus pulex Amphipod 26.07 LC50 or EC50 U.S. EPA Stephenson 1983 Included

Copper Daphnia ambigua Cladoceran 28.50 LC50 or EC50 U.S. EPA Included

Copper Daphnia pulex Cladoceran 29.22 LC50 or EC50 U.S. EPA Mount and Norberg 1984 Included

Copper sulphate Physa heterostropha Snail 29.80 LC50 or EC50 U.S. EPA Wurtz and Bridges 1961 Included

Copper Daphnia parvula Cladoceran 30.34 LC50 or EC50 U.S. EPA Included

Copper sulphate Semotilus atromaculatus Creek chub 32.18 LC50 or EC50 U.S. EPA Geckler et al. 1976 Included

Copper sulphate Campeloma decisum Snail 35.56 LC50 or EC50 U.S. EPA Arthur and Leonard 1970 Included

Copper sulphate Physa integra Snail 35.56 LC50 or EC50 U.S. EPA Arthur and Leonard 1970 Included

Copper sulphate Salvelinus fontinalis Brook trout 42.13 LC50 or EC50 U.S. EPA McKim and Benoit 1971 Included

Copper sulphate Gyraulus circumstriatus Snail 46.65 LC50 or EC50 U.S. EPA Wurtz and Bridges, 1961 Included

Copper sulphate Limnodrilus hoffmeisteri Worm 48.06 LC50 or EC50 U.S. EPA Wurtz and Bridges, 1961 Included

Copper Clisttornia magnifica Caddisfly 54.38 LC50 or EC50 U.S. EPA Included

Copper sulphate Salmo gardneri Rainbow trout 61.55 LC50 or EC50 U.S. EPA McKim et al. 1978 Included

Copper sulphate Catostomus commersoni White sucker 67.82 LC50 or EC50 U.S. EPA McKim et al. 1978 Included


Table IIIA-8 Summary of Chronic Toxicity Data Available for Copper (continued)

Golder Associates

Metal Species Species Name Common

Name

Selected Chronic Value at 180

mg/L Hardness End point Source Original Source

Excluded/ Included

Copper Echinogammarus berilloni Amphipod 68.54 LC50 or EC50 U.S. EPA Included

Copper Salmo salar Atlantic salmon 75.31 LC50 or EC50 U.S. EPA

Sprague and Ramsey 1965 Included

Copper Daphnia rosea Cladoceran 79.29 LC50 or EC50 U.S. EPA Included

Copper Nais sp. Worm 81.49 LC50 or EC50 U.S. EPA Rehwoldt et al. 1973 Included

Copper chloride Oncorhynchus nerka (fingerling)

Sockeye salmon 89.55 LC50 or EC50 U.S. EPA Davis and Shand 1978 Included

Copper sulphate Salvelinus namaycush Lake trout 98.90 LC50 or EC50 U.S. EPA McKim et al. 1978 Included

Copper sulphate Salmo trutta Brown trout 108.46 LC50 or EC50 U.S. EPA McKim et al. 1978 Included

Copper sulphate Goniobasis livenscens Snail 137.94 LC50 or EC50 U.S. EPA Paulson et al. 1983 Included

Copper sulphate Esox lucius Northern pike 195.70 LC50 or EC50 U.S. EPA McKim et al. 1978 Included

Copper sulphate Lumbriculus variegatus Worm 219.77 LC50 or EC50 U.S. EPA Bailey and Liu 1980 Included

Copper Chironomus riparius Midge 223.73 LC50 or EC50 U.S. EPA Included

Copper Alona Afinis Cladoceran 443.93 LC50 or EC50 U.S. EPA Included

Copper Amnicola sp.(adult) Snail 746.97 LC50 or EC50 U.S. EPA Rehwoldt et al. 1973 Included

Copper Chironomus decorus Midge 754.75 LC50 or EC50 U.S. EPA Included

Copper Crangonyx pseudogracilis Amphipod 1167.98 LC50 or EC50 U.S. EPA Included

Copper Chironomus tentans Midge 1394.75 LC50 or EC50 U.S. EPA Nebeker et al. 1984 Included

Copper Unidentified Damselfly 4164.90 LC50 or EC50 U.S. EPA Rehwoldt et al. 1973 Included

Copper sulphate Acroneuria lycorias Stonefly 9273.24 LC50 or EC50 U.S. EPA Warnick and Bell 1969 Included


Golder Associates

Table IIIA-9 Summary of Chronic Toxicity Data Available of Iron Metal Speciation Species Name Common Name Chronic Value (µg/L) End-point Source Included/Excluded

Iron Chloride Pimephales promelas Fathead minnow 570 MATC Birge et al. 1985 Included

Iron Chloride Pimephales promelas Fathead minnow 1010 LOEC (21-D) Birge et al. 1985 Included

Iron Chloride Daphnia magna Water flea 5200 EC50 (21-d; reprod) Biesinger and Christensen 1972 Included

Iron Chloride Daphnia magna Water flea 5900 EC50 (21-d; immobilization) Biesinger and Christensen 1972 Included

Iron Chloride Daphnia magna Water flea 15000 LC50 (4.2-d mort) Dowden and Bennett 1965 Included

Iron Chloride Orconectes limosus Crayfish 21000 LC50 (30-d) Boutet and Chaisemartin 1973 Included

Iron Chloride Orconectes limosus Crayfish 22000 LC50 (30-d) Boutet and Chaisemartin 1973 Included

Iron Chloride Daphnia magna Water flea 65000 LC50(120h-mort) Cabejszek and Stasiak 1960 Included

Sulfuric acid, Iron (2+) salt (1:1) Osteichthyes Bony fish

superclass 100000 0 % Mortality Sanborn 1945 Included

Iron Coregonus lavaretus Pollan, whitefish 630 0 % Mortality Lappivaara et al. 1999 Excluded (non resident species)



Iron Chloride Austropotamobius pallipes pall Crayfish 13200 LC50 (30-d) Boutet and Chaisemartin 1973 Excluded (non resident species)



Sulfuric acid, Iron (2+) salt (1:1) Gambusia affinis Western

mosquitofish 20000 LC50 (4-d) Mowbray 1988 Excluded (non resident species)

Sulfuric acid, Iron (2+) salt (1:1) Gambusia affinis Western

mosquitofish 34000 LC50 (4-d) Mowbray 1988 Excluded (non resident species)

Sulfuric acid, Iron (2+) salt (1:1) Carassius auratus Goldfish 100000 0 % Mortality Sanborn 1945 Excluded (non resident

species)

Iron Chloride Daphnia magna Water flea 128 ET50 (immobilization) Dave 1984 Excluded (high hardness)


Table IIIA-9 Summary of Chronic Toxicity Data Available of Iron (continued)

Golder Associates

Metal Speciation Species Name Common Name Chronic Value (µg/L) End-point Source Included/Excluded






Iron Chloride Daphnia magna Water flea 158 CV Dave 1984 Excluded (end point)

Iron Chloride Pimephales promelas Fathead minnow 320 NOEC Birge et al. 1985 Excluded (end point)

Iron Chloride Oncorhynchus mykiss rainbow trout 1300 CV Amelung 1981 Excluded (end point)


Golder Associates

Table IIIA-10 Summary of Chronic Toxicity Data Available of Manganese


Manganese Salmo trutta Brown trout 360 (30-d) decrease in body calcium concentrations

Reader et al. 1988 Included

Manganese Salmo trutta Brown trout 1080 (30-d) impaired development Reader et al. 1988 Included

MnSO4 - H2O Daphnia magna Cladoceran 1100 LOEC ( 28-d reproduction) Kimball 1978 Included

MnSO4 - H2O Pimephales promelas Fathead minnow 2480 LOEC (length 28-d) Kimball 1978 Included

MnSO4 - H2O Pimephales promelas Fathead minnow 2480 LOEC (weight 28-d) Kimball 1978 Included

Manganese(II)chloride (1:2) Oncorhynchus mykiss rainbow trout 2910 LC50 Birge 1978 Included

Manganese(II)chloride (1:2) Daphnia magna Cladoceran 4100 EC16 (reproduction) Biesinger and Christensen 1972 Included

Manganese(II)chloride (1:2) Daphnia magna Cladoceran 5200 EC50 (reproduction) Biesinger and Christensen 1972 Included

MnSO4 - H2O Daphnia magna Cladoceran 7700 LOEC (7-d reproduction) Kimball 1978 Included

MnSO4 - H2O Pimephales promelas Fathead minnow 19690 LOEC (% survival 28-d) Kimball 1978 Included

Manganese Orconectes limosus Crayfish 34000 LC50 (30 D; mort) Boutet and Chaisemartin 1973 Included

Manganese Orconectes limosus Crayfish 36000 LC50 (30 D; mort) Boutet and Chaisemartin 1973 Included

Manganese Austropotamobius pallipes pall Crayfish 17000 LC50 (30 D;mort) Boutet and Chaisemartin 1973 Excluded (non

resident species)

Manganese Austropotamobius pallipes pall Crayfish 18000 LC50 (30 D; mort) Boutet and Chaisemartin 1973 Excluded (non

resident species)


Golder Associates

Table IIIA-11 Summary of Chronic Toxicity Data Available of Molybdenum


Na2MoO4 Oncorhynchus mykiss rainbow trout 730 LC50 28D Birge 1978 Included

Na2MoO4 Oncorhynchus mykiss rainbow trout 790 LC50 28D Birge et al. 1979 Included

MoO3 Daphnia magna Cladoceran 930 LC50 28D Kimball n.d Included

MoO3 Daphnia magna Cladoceran 1150 LOEC 28D Kimball n.d Included

MoO3 Daphnia magna Cladoceran 4500 LOEC 7D Kimball n.d Included

Molybdenum Oncorhynchus mykiss rainbow trout >30000 LOEC McDevitt et al. 1999 Included

Sodium molybdate Ceriodaphnia dubia Cladoceran 34000 8d-IC12.5 (#of young after 3 broods) Naddy et al. 1995 Included



Molybdenum Oncorhynchus clarki cutthroat trout >90000 LC50 30D Pickard et al. 1998 Included

Na2MoO4 Oncorhynchus mykiss rainbow trout 400000 LOEC (32-d % survival) Davies 2002 Included

Na2MoO4 Oncorhynchus mykiss rainbow trout 1000000 LOEC (32-d % survival) Davies 2002 Included


Golder Associates

Table IIIA-12 Summary of Chronic Toxicity Data Available of Silver


Nitric acid, silver (1+) salt Oncorhynchus mykiss Rainbow trout 0.17 LOEC

(18 month Mort) Davies et al. 1978 Included

Nitric acid, silver (1+) salt Oncorhynchus mykiss Rainbow trout 0.17 LOEC

(18 month Mort) Goettl et al. 1976 Included

Nitric acid, silver (1+) salt Daphnia magna Cladoceran 1.06 LC50

(10-d mort) Rodgers et al. 1997 Included

Nitric acid, silver (1+) salt Daphnia magna Cladoceran 1.22 LOEC

(10-d reprod) Rodgers et al. 1997 Included

Nitric acid, silver (1+) salt Daphnia magna Cladoceran 2.2 EC50

(14-d reprod) Elnabarawy et al. 1986 Included

Nitric acid, silver (1+) salt Daphnia magna Cladoceran 2.6 MATC

(21-d mort) Nebeker et al. 1983 Included


(21-d reprod) Nebeker et al. 1983 Included

AgNO3 Daphnia magna Cladoceran 2.6 life cycle test U.S. EPA 1980b Included

AgNO3 Daphnia magna Cladoceran 2.9 EC50 (21-d reproduction) Nebeker et al. 1983 Included

AgNO3 Daphnia magna Cladoceran 3.2 life cycle test U.S. EPA 1980b Included Nitric acid, silver (1+) salt Daphnia magna Cladoceran 3.6 EC50

(7-d mort) Elnabarawy et al. 1986 Included



Nitric acid, silver (1+) salt Oncorhynchus mykiss Rainbow trout 4.8 LC50

(144 hr-mort) Diamond et al. 1990 Included

Silver Pimephales promelas Fathead minnow 5.1 LC50 (100 hr mort) Klaine et al. 1996 Included





Silver Daphnia magna Cladoceran 5.2 life cycle test U.S. EPA 1980b Included



Nitric acid, silver (1+) salt Oncorhynchus mykiss Rainbow trout 9.1 LC50

(168 hr-mort) Hogstrand et al. 1996 Included

Silver Oncorhynchus mykiss Rainbow trout 10 LC50 (28-d mort) Birge et al. 1979 Included

Nitric acid, silver (1+) salt Oncorhynchus mykiss Rainbow trout 10 LC50

(28-d mort) Birge 1978 Included


Table IIIA-12 Summary of Chronic Toxicity Data Available of Silver (continued)

Golder Associates


Nitric acid, silver (1+) salt Oncorhynchus mykiss Rainbow trout 10 LC50

(28-d mort) Birge et al. 1979 Included

AgNO3 Oncorhynchus mykiss Rainbow trout 12 early life cycle test U.S. EPA 1980b Included

AgNO3 Daphnia magna Cladoceran 13 life cycle test U.S. EPA 1980b Included Nitric acid, silver (1+) salt Daphnia magna Cladoceran 13.1 MATC




AgNO3 Daphnia magna Cladoceran 15 life cycle test U.S. EPA 1980b Included AgNO3 Daphnia magna Cladoceran 29 life cycle test U.S. EPA 1980b Included

AgNO3 Chironomus tetanus midge 57 10-d LC50 (dry weight) Call et al 1999 Included

AgNO3 Chironomus tetanus midge 66 LOEC (dry weight) Call et al 1999 Included

AgNO3 Chironomus tetanus midge 127 LOEC (dry weight) Call et al 1999 Included

AgNO3 Chironomus tetanus midge 500 LOEC (dry weight& total biomass)

Call et al 1999 Included

AgNO3 Chironomus tetanus midge 1170 10-d LC50 (dry weight &total biomass)

Call et al 1999 Included

AgNO3 Chironomus tetanus midge 2200 LOEC (total biomass) Call et al 1999 Included

AgNO3 Chironomus tetanus midge 2750 10-d LC50 (total biomass) Call et al 1999 Included

AgNO3 Chironomus tetanus midge 15100 10-d LC50 (dry weight) Call et al 1999 Included

AgNO3 Chironomus tetanus midge 259000 EC50 (10-d emergence) Rodgers et al. 1994 Included

Nitric acid, silver (1+) salt Oncorhynchus mykiss Rainbow trout <0.1 MATC

(60-d growth) Nebeker et al. 1983 Included

Ag2S Notonecta sp. >1000 LC50 (58-d) Rodgers et al. 1994 Included Silver chloride Daphnia magna Cladoceran >12000 LC50 (mort) Rodgers et al. 1997 Included Thiosulfuric acid, Disilver (1+)salt Daphnia magna Cladoceran >12000 LC50 (mort) Rodgers et al. 1997 Included

Nitric acid, silver (1+) salt Oncorhynchus mykiss Rainbow trout >6.7 LOEC

(7-d growth) Diamond et al. 1990 Included

Nitric acid, silver (1+) salt Oncorhynchus mykiss Rainbow trout >6.7 LOEC

(7-d mort) Diamond et al. 1990 Included

Nitric acid, silver (1+) salt Carassius auratus Goldfish 30 LC50 (7-d mort) Birge 1978 Excluded (non resident

species)


Table IIIA-12 Summary of Chronic Toxicity Data Available of Silver (continued)

Golder Associates


Nitric acid, silver (1+) salt Carassius auratus Goldfish 30 LC50 (7-d mort) Birge et al. 1979 Excluded (non resident

species)

Table IIIA-13 Summary of Chronic Toxicity Data Available of Strontium


Strontium chloride Oncorhynchus mykiss rainbow trout 200 LC50 (28 D) Birge 1978 Included

Strontium chloride Daphnia magna Cladoceran 42000 EC16 Biesinger and Christensen 1972 Included

Strontium chloride Daphnia magna Cladoceran 60000 EC20 Biesinger and Christensen 1972 Included

Strontium chloride Daphnia magna Cladoceran 86000 LC50 Biesinger and Christensen 1972 Included

Strontium chloride Orconectes limosus Crayfish 720000 LC50 Boutet and Chaisemartin 1973 Included

Strontium chloride Orconectes limosus Crayfish 860000 LC50 Boutet and Chaisemartin 1973 Included

Strontium chloride Carassius auratus Goldfish 8580 LC50 (7 D) Birge 1978 Excluded (non resident species)

Strontium chloride Austropotamobius pallipes pall Crayfish 320000 LC50 Boutet and Chaisemartin 1973 Excluded (non resident

species)

Strontium chloride Austropotamobius pallipes pall Crayfish 390000 LC50 Boutet and Chaisemartin 1973 Excluded (non resident

species)


Golder Associates

Table IIIA-14 Summary of Chronic Toxicity Data Available of Vanadium


Vanadium pentoxide Oncorhynchus mykiss rainbow trout 160 LC50(28-d) Birge 1978 Included

Vanadium pentoxide Pimephales promelas Fathead minnow 170 MATC (length) Kimball 1978 Included

Vanadium pentoxide Pimephales promelas Fathead minnow 240 LOEC (LENGTH) Kimball 1978 Included

Vanadium pentoxide Pimephales promelas Fathead minnow 340 MATC (weight) Kimball 1978 Included

Vanadium pentoxide Pimephales promelas Fathead minnow 480 LOEC (weight) Kimball 1978 Included

Vanadium pentoxide Pimephales promelas Fathead minnow 480 MATC (%survival) Kimball 1978 Included

Vanadium pentoxide Daphnia magna Cladoceran 940000 MATC (reproduction) Kimball 1978 Included

Vanadium pentoxide Carassius auratus Goldfish 1020 LC50 Knudtson 1979 Excluded (non resident species)

Vanadium pentoxide Carassius auratus Goldfish 4520 LC50 Knudtson 1979 Excluded (non resident species)

Vanadium pentoxide Carassius auratus Goldfish 4600 LC50 Birge 1978 Excluded (non resident species)

Vanadium pentoxide fish spp. 20 cv Suter and Tsao 1996 Excluded (end point)

Vanadium pentoxide Jordinella floridae Flagfish 80 cv Holdway and Sprague 1979 Excluded (end point)

Vanadium pentoxide Daphnia Magna Cladoceran 1900 cv Kimball, n.d Excluded (end point)


Golder Associates

Table IIIA-15 Summary of Chronic Toxicity Data Available of PAH Group 6 (biphenyl)

Compound Species Name Common Name Chronic Value (µg/L) End-point Source Included/Excluded

2,2',4,4'-Tetrachloro-1,1-biphenyl Pimephales promelas Fathead minnow 29 LC50 (30-d mort) Dill et al. 1982 Included

3,3',4,4',5-Pentachloro-1,1'-biphenyl Oncorhynchus mykiss Rainbow trout 74 LC50 (7-d, mort) Walker and Peterson 1991 Included

2,2',4,4'-Tetrachloro-1,1-biphenyl Pimephales promelas Fathead minnow 97 LC50 (12-d mort) Dill et al. 1982 Included

1,1'-Biphenyl Daphnia magna Water flea 230 MATC (21-d mort) Gersich et al. 1989 Included

1,1'-Biphenyl Daphnia magna Water flea 230 MATC (21-d reprod) Gersich et al. 1989 Included

3,3',4,4'-Tetrachloro-1,1'-biphenyl Oncorhynchus mykiss Rainbow trout 500 LOEC (7-d, mort) Koponen et al. 2000 Included

3,4,4',5-Tetrachloro-1,1'-biphenyl Oncorhynchus mykiss Rainbow trout 549 LD50(mort; ~30-d) Zabel et al. 1995 Included

2-Chlorobiphenyl Pimephales promelas Fathead minnow 820 LC50 (30-d mort) Dill et al. 1982 Included


3,3',4,4'-Tetrachloro-1,1'-biphenyl Oncorhynchus mykiss Rainbow trout 1348 LD50(mort; ~7-d) Walker and Peterson 1991 Included


3,3',4,4',5,5'-Hexachloro-1,1'-biphenyl

Oncorhynchus mykiss Rainbow trout 7110 LD50(mort; ~30-d) Zabel et al. 1995 Included

2,3,3',4,4'-Pentachloro-1,1'-biphenyl Oncorhynchus mykiss Rainbow trout >6970 LD50(mort; ~7-d) Walker and Peterson 1991 Included

2,3,3',4,4'-Pentachloro-1,1'-biphenyl Oncorhynchus mykiss Rainbow trout >6970 LD50(mort; ~7-d) Walker and Peterson 1991 Included

1,1'-Biphenyl, Chloro derivs. Gambusia affinis Western

mosquitofish 103 LT50 (633 hr, mort) Chaisuksant et al. 1997 Excluded (non resident species)


mosquitofish 148 LT50 (255.3 hr, mort) Chaisuksant et al. 1997 Excluded (non resident species)






Table IIIA-15 Summary of Chronic Toxicity Data Available of PAH Group 6 (biphenyl) (continued)

Golder Associates

Compound Species Name Common Name Chronic Value (µg/L) End-point Source Included/Excluded




mosquitofish 305 LC50 (97 hr mort) Chaisuksant et al. 1997 Excluded (non resident species)





3,3',4,4'-Tetrachloro-1,1'-biphenyl Oncorhynchus mykiss Rainbow trout 100 NOEC(7-d, mort) Koponen et al. 2000 Excluded (end point)

3,3'-Dimethyl-[1,1'-biphenyl]-4,4'-diamine Daphnia magna Water flea 160 NOEC (21-d reprod.) Kuhn et al. 1989 Excluded (end point)

3,3'-Dimethyl-[1,1'-biphenyl]-4,4'-diamine Daphnia magna Water flea 16000 NOEC (21-d behav.) Kuhn 1988 Excluded (end point)

APPENDIX IV

DEVELOPMENT OF HUMAN AND WILDLIFE HEALTH RISK-BASED THRESHOLDS

CEMA IV-i Athabasca River Reach Specific May 2007 Water Quality Objectives

Golder Associates

TABLE OF CONTENTS

SECTION PAGE

IV-1 INTRODUCTION ...................................................................................................1 IV-1.1 METHODS...................................................................................................................1

IV-2 RESULTS ..............................................................................................................4

IV-3 REFERENCES ......................................................................................................6

LIST OF TABLES

Table IV-1 Risk-based Effects Thresholds for Human Receptors............................................4 Table IV-2 Risk-based Effects Thresholds for Wildlife Receptors............................................5

CEMA IV-1 Athabasca River Reach Specific May 2007 Water Quality Objectives

Golder Associates

IV-1 INTRODUCTION

This appendix provides the methods and results to determine risk-based water concentrations protective for human and wildlife receptors (or health risk-based). A health risk-based threshold is defined as the concentration of a chemical in a specified medium (e.g., water) that would not result in an unacceptable risk to people or wildlife if they were exposed to that concentration over a chronic period of time. Risk-based health effects ratios incorporate both toxicity information and exposure parameters (e.g., consumption rates, body weights, and exposure times). The risk-based water concentrations were used to check that the criteria derived by aquatics resources are also protective of human and wildlife health.

IV-1.1 METHODS

Risk-based effects thresholds were calculated for human and wildlife health to determine the concentration at which no adverse health effects would be expected due to water ingestion. The parameters of interest were those that were assessed in the EIA completed for the Kearl Oil Sands Project (Imperial Oil, 2005). Conventional parameters, major ions, nutrients, and aquatic toxicity parameters were not evaluated in this assessment because they are not considered to be of significant risk to human or wildlife receptors. This was the same approach as presented in the Environmental Health component of the Kearl EIA (Volume 8).

Human Health

The risk-based approach, exposure parameters and toxicity values used to calculate the RBCs were all the same as used in the Kearl Project EIA (Volume 8, Appendix 3A, Sections 3A.1.2.2.2 and 3A.1.2.2.3, respectively; Imperial Oil 2005). The only exception was that it was assumed that people would obtain 100% of their drinking water all year rather than for six months per year, which was the assumption used in the Kearl EIA. Toxicity reference values (TRV) and slope factors (SF) are taken directly from the Kearl Project EIA (Volume 8, Appendix 3A, Table 3A-26 and Table 3A-27, respectively; Imperial Oil 2005).

Since this assessment focused on the water ingestion pathway only, an allocation factor of 20% was applied in the calculation. This approach is consistent with that of the protocol used for the derivation of Canadian Environmental Quality Guidelines (CCME 1999). The assumption is that a person is exposed via five


Golder Associates

media, water, air, soil, food and consumer products, with each medium composing 20% of the total exposure.

The equation used to calculate non-carcinogenic RBCs is as follows:

RBC = TRV x 0.2 x BW

IR x Time

Where:

• TRV = parameter specific toxicity reference value (mg/kg-day)

• BW = body weight of human (kg)

• IR = water IR for adult or toddler (L/day)

• Time = exposure time, assumed 100%

For carcinogenic chemicals, only adult receptors are evaluated, which is consistent with the approach used by CCME (1999) in the derivation of environmental quality guidelines. Due to the length of the adult life phase, it is considered to be representative of lifetime exposure for carcinogenic assessments.

The equation used to calculate carcinogenic RBCs is as follows:

RBC = SF x 0.00001 x 0.2 x BW x (56/75)

IR x (56/75)

Where:

• SF = parameter-specific slope factor (mg/kg-day)-1

• BW = body weight for adult (kg)

• IR = adult water IR (L/ day)

An acceptable cancer risk has been defined by Health Canada (2004) as an incremental increase in cancer incidence of 1 in 100,000. Therefore, a factor of 0.00001 was included in the calculation. A factor of 56/75 was also included to account for the adult portion of a lifetime.


Golder Associates

Wildlife Health

A similar approach was used to calculate health risk-based thresholds for wildlife receptors. For the purposes of this assessment, the most sensitive mammalian and avian species were identified based on the Kearl Project EIA (Volume 8, Appendix 3A, Section 3A.1.6.1.2). In other words, health risk-based thresholds were calculated for all receptors, and the mammalian and avian receptor that had the lowest RBC were used for the assessment (i.e., meadow vole and ruffed grouse). RBCs were based on the No-Observed-Adverse-Effect-Level (NOAEL) from toxicity studies using laboratory animals. If a NOAEL was not available, the Lowest-Observed-Adverse-Effect-Level (LOAEL) was used. When a LOAEL was used, a factor of 10 was applied to the RBC to account for the unavailability of a NOAEL.

The toxicity values and exposure parameters were the same as used in the Kearl Project EIA (Volume 8, Appendix 3A, Section 3A.1.6.3). The equation used to calculate RBCs is as follows:

RBC = (NOAEL x BW)

WIR

Where:

• NOAEL = NOAEL for the receptor (vole and grouse) (mg/kg-day)

• BW = body weight of receptor (vole and grouse) (kg)

• WIR = water ingestion rate for receptor (vole and grouse) (mg/L)


Golder Associates

IV-2 RESULTS

The resulting risk-based health effects for human and wildlife receptors are presented in Tables IV-1 and IV-2 below.

Table IV-1 Risk-based Effects Thresholds for Human Receptors

Human Health Risk-based Effects Thresholds (mg/L)

Constituent Adult Toddler Metals aluminum 18.9 11.0 antimony 0.004 0.002 arsenic - non-carcinogenic 0.003 0.002 arsenic - carcinogenic 0.0003 N/A barium 0.2 0.09 beryllium 0.02 0.01 boron 0.09 0.06 cadmium 0.002 0.001 chromium 14.1 8.3 copper 0.3 0.2 lead 0.03 0.02 manganese 0.7 0.4 mercury 0.003 0.002 molybdenum 0.05 0.03 nickel 0.01 0.007 selenium 0.05 0.03 silver 0.047 0.028 strontium 5.6 3.3 vanadium 0.03 0.02 zinc 2.8 1.6 Organics naphthenic acids 0.6 0.3 PAH Groups PAH group 1 - carcinogenic 0.0007 N/A PAH group 2 - carcinogenic 0.00007 N/A PAH group 3 - carcinogenic 0.00007 N/A PAH group 4 - acenaphthenes 0.6 0.3 PAH group 5 - anthracenes 2.8 1.6 PAH group 6 - biphenyls 0.5 0.3 PAH group 7 - fluoranthene 0.4 0.2 PAH group 8 - naphthalenes 0.2 0.1 PAH group 9 - pyrenes 0.3 0.2

Notes: N/A = not applicable since carcinogenic RBCs are not calculated for toddlers.


Golder Associates

Table IV-2 Risk-based Effects Thresholds for Wildlife Receptors

Wildlife Health Risk-based Effects Thresholds (mg/L)

Constituent Mammalian Avian Metals aluminum 10.8 2,157 antimony 0.7 1.9 arsenic 0.7 69.6 barium 33.6 430 beryllium 4.3 9.9 boron 182 390 cadmium 6.5 19.1 chromium 17,814 722 copper 105 4.1 lead 52.1 88.7 manganese 573 22,395 mercury 7 8.9 molybdenum 1.5 3.2 nickel 260 1101 selenium 1.3 6.8 silver 0.008 34.2 strontium 1,711 2,648 vanadium 1.3 150 zinc 1041 172 Organics naphthenic acids 39.1 90 PAH Groups PAH group 1 - carcinogenic 5.6 15 PAH group 2 - carcinogenic 56.2 150 PAH group 3 - carcinogenic 562 1,500 PAH group 4 - acenaphthenes 32.6 305 PAH group 5 - anthracenes 187 305 PAH group 6 - biphenyls 28.1 75 PAH group 7 - fluoranthene 23.6 63 PAH group 8 - naphthalenes 15.6 36 PAH group 9 - pyrenes 14 37.5


Golder Associates

IV-3 REFERENCES

Canadian Council of Ministers of the Environment (CCME). 1999. Updated 2005. Canadian Environmental Quality Guidelines. CCME, Winnipeg, MB.

Health Canada. 2004. Guidance on Human Health Preliminary Quantitative Risk Assessment. Health Canada, Ottawa, ON.

Imperial Oil. 2005. Kearl Oil Sands Project – Mine Development. Volume 8: Environmental Health. Submitted to AENV July 2005.

APPENDIX V

ATHABASCA RIVER MODEL ASSUMPTIONS AND INPUTS

CEMA V-i Athabasca River Reach Specific May 2007 Water Quality Objectives

Golder Associates

TABLE OF CONTENTS

SECTION PAGE

V-1 INTRODUCTION ...................................................................................................1

V-2 MODEL DESCRIPTION.........................................................................................2

V-3 MODEL CALIBRATION AND VALIDATION...........................................................7

V-4 BACKGROUND FLOWS........................................................................................7

V-5 BACKGROUND WATER QUALITY .......................................................................8

V-6 FORT MCMURRAY SEWAGE TREATMENT PLANT............................................9

V-7 OIL SANDS RELATED SOURCE WATER QUALITY AND FLOWS.....................10

V-8 ASSESSMENT NODES.......................................................................................16

V-9 SNAPSHOTS.......................................................................................................16

V-10 REFERENCES ....................................................................................................18

LIST OF TABLES

Table V-1 Long-Term Population Estimates for the Town of Fort McMurray .......................10 Table V-2 Flow Information Used in the Athabasca River Model .........................................11 Table V-3 Assessment Nodes...............................................................................................16

LIST OF FIGURES

Figure V-1 Water Quality Modelling Nodes for the Athabasca River Model ..........................17

CEMA V-1 Athabasca River Reach Specific May 2007 Water Quality Objectives

Golder Associates

V-1 INTRODUCTION

Athabasca River water quality was predicted using a two-dimensional (vertically-averaged), dispersion model, which is based on analytical solutions to river dispersion equations developed by Fischer et al. (1979). The Athabasca River Model (ARM) has recently been updated to include reach specific transverse-mixing coefficients and water withdrawals (Golder 2004). The model was also run stochastically for this report. Stochastic modelling allowed for the simulation of average daily in-stream water quality throughout the available 42 year flow record (i.e., 1960 to 2001; Environment Canada 2003).

The model has the capability of handling both point-source discharges (e.g., stream discharge or mine effluents) and non-point source discharges (e.g., groundwater seepage). To accommodate multiple sources, the model was set-up to include a number of discharge points distributed along the length of the river between Fort McMurray and just upstream of the Embarras River. Each potential water release from existing or approved projects and tributary flows was routed through one of these discharge nodes. The characteristics of each node were then selected to reflect the type of flow passing through that node. Tributary inflows and direct surface discharges were considered point sources discharging from the appropriate river bank. Seepages were treated as exponential line sources stretching from the appropriate river bank to half the river width.

The ARM incorporates the following key assumptions:

• vertical mixing is complete, instantaneous;

• longitudinal dispersion is negligible;

• mass reaching the river banks is reflected back into the river;

• dispersion coefficients are constant across the width of the river;

• different flow-dependent transverse dispersion coefficients apply to each of the five reaches of the river defined by Trillium and Hydrographics (2003); and

• substances released into the Athabasca River remain in the water column (i.e., precipitation, chemical or biological decay, settling and sediment partitioning not assumed to occur).


Golder Associates

V-2 MODEL DESCRIPTION

For a single hypothetical point-source load with negligible flow, the following equation describes the concentration at any location downstream of the source (Fischer et al. 1979):

( ) ( ) ( )∑=

−=

−−

⎪⎭

⎪⎬⎫

⎪⎩

⎪⎨⎧

⎥⎥⎦

⎤

⎢⎢⎣

⎡ +−−+

⎥⎥⎦

⎤

⎢⎢⎣

⎡ −−−+=

Nrj

Nrj

uxxk

BKjj

udWMeCxC

i

2

20

2

20

0

/)( 2exp

2exp,

ξηη

ξηη

πξη (V-1)

where:

C(x,η) = concentration in Athabasca River (mg/L)

CBK = background concentrations in Athabasca River, upstream of Fort McMurray (mg/L)

M = load of constituent from the source release (kg/d)

k = decay rate of constituent (s-1)

x = longitudinal distance downstream from the upstream boundary of the reach (m)

xi = longitudinal distance of source downstream from the upstream boundary of the reach (m)

u = velocity of Athabasca River at the upstream boundary of the reach, Equation (V-3) (m/s)

d = depth of Athabasca River at the upstream boundary of the reach, Equation (V-4) (m)

W0 = river width at the upstream boundary of the modelled reach, Equation (V-3) (m)

ξ = the normalized transverse mixing coefficient (dimensionless),

J = the j’th reflection

Nr = the number of river bank reflections depends on the rate of transverse mixing across the river and the distance downstream, x, in the calculation; an Nr=2 was applied.

η = the normalized location across the river (normalized by fraction of river flow) (dimensionless)

ηo = the normalized location across the river of the centre of the source (normalized by fraction of river flow) (dimensionless)


Golder Associates

The normalized transverse mixing coefficient (ξ ) is:

)0(

2Q

xuEd t=ξ (V-2)

where:

Et = transverse mixing coefficient of the reach (m2/s)

Q(0) = river flow at the upstream boundary of each reach (m3/s)

The width, velocity and depth of the river can be determined from Q(0) using the following Leopold-Maddock relationships:

(V-3) wbwQaW )0(0 =

(V-4) Qa =u ub u )0(

(V-5) Q a = d db d )0(

where:

aw, au, ad, bw, bu, and bd are empirical constants that were determined using measured data. They are related as follows:

1=×× dbu aaa

1=++ uwd bbb

Thus, for any given river flow, river depth, velocity as well as dispersion coefficient can be determined, and constituent concentrations at locations downstream of the discharge point can be predicted using the above equations.

The ARM contains adjustments to the basic Fischer equations to accurately approximate the effects of small source flows. Each of the sources is considered to be a line source. The width of the line for source i (wi [dimensionless]) can be user defined but has a minimum width (wmin i [dimensionless]) given by:

(V-6) ( )xsii QQw /min =


Golder Associates

where:

Qsi = Flow rate of source i (m3/s)

Q(x) = Flow in Athabasca River of the point being modelled (m3/s)

Line sources with greater width than the minimum width may be specified, for example, when a release has a multi-port diffuser. A line-source release can be treated as an infinite number of point sources along a distance across the river equal to the line source’s width. An equation for calculating river concentrations downstream of a line source can therefore be derived by integrating the point-source equation over the width of the line source and accounting for the finite width of a river by reflecting the plume at both river bank boundaries. A line source with different flows along the line, such as a zone of influent groundwater seepage, can be represented as a series of line sources with differing flows. The general equation describing the concentration downstream of several sources is:

( )

( )( ) ( )( )

( )( ) ( )( )∑ ∑∑= −=

−−

=

⎥⎥⎥⎥⎥

⎦

⎤

⎢⎢⎢⎢⎢

⎣

⎡

⎟⎟⎠

⎞⎜⎜⎝

⎛ −−−+⎟⎟⎠

⎞⎜⎜⎝

⎛ −−++

⎟⎟⎠

⎞⎜⎜⎝

⎛ +−−+⎟⎟⎠

⎞⎜⎜⎝

⎛ +−+

+=s r

r

itiN

i

N

Nj

i

hihi

i

hihi

i

hihi

i

hihi

uxxkN

h

ohiBK jrjr

jrjrC

CxC1

/

1 2erf

2erf

2erf

2erf

e2

),(

ξηη

ξηη

ξηη

ξηη

η (V-7)

where:

Ns = the number of sources upstream of the modelled location

Nti = number of line segments for the i’th source

i = the i’th source

h = the h’th segment in a series of line sources

Cohi = initial concentration of h’th section of the i’th source, fully vertically mixed over the line source segment river flow fraction. Equation (V-8) (mg/L)

rhi = half width of the line source segment (whi) normalized by fraction of river flow, i.e., rhi= whi/2 (dimensionless)

ηhi = the normalized location across the river of the centre of the h’th source (dimensionless)

ξi = the normalized transverse mixing coefficient for a line source. Equation (V-10) (dimensionless)

The above line source equation has been normalized by the fraction of river flow (i.e., the lateral distance is represented by the fraction of total river flow). The


Golder Associates

initial concentration for a line source is calculated by mixing the line source flow with the river flow over the width of the line source:

( )xhi

sishiohi Cr2

CqC

'= (V-8)

where:

qshi = the line source flow rate (m3/s) (see next section)

'C si = the line source concentration adjusted to background concentration. Equation (V-9) (mg/L)

The concentration of the source is adjusted for the background concentration in the Athabasca River:

(V-9) BKsisi CCC −='

where:

Csi = the line source concentration which is assumed to be the same for each line source segment, although it need not be (mg/L)

The normalized transverse mixing coefficient is given by:

six

ti QQ

xuEd−

=)(

2ξ (V-10)

The value of d, and u are determined from Q(0) as outlined above in Equation (V-2) to Equation (V-4).

To account for changes in seepage rate with distance from shore, a series of line sources are used with varying initial concentrations. The initial concentrations are determined by an exponential function and are distributed in such a way that the total seepage mass of constituent is conserved. The seepage rate from the bank to the centre of the river was, therefore, assumed to follow the following form of decay (Shaw and Prepas 1990):

(V-11) ηQksisi eKQq −= 1'


Golder Associates

where:

qsi’ = line source segment seepage per unit η (dimensionless)

K1 = a scaling constant (dimensionless)

kQ = exponential decay constant (dimensionless)

Integrating this functional form for the seepage rate over the half width of the river and normalizing by the total seepage, the seepage flow fractions between ηa and ηb (i.e., lateral locations of the seepage segment) can be expressed as:

Q

bQaQ

k

kk

si

ab

Qq

5.0e1ee

−

−−

−−

=ηη

(V-12)

where:

qab = line source segment seepage between river flow fraction ηa and ηb (m3/s)

Qsi = total seepage to river (m3/s), and

The seepage for each segment can then be expressed in terms of the line source segment centre, ηhi and its half width, rhi:

Q

hihiQhihiQ

k

rkrk

si

shi

Qq

5.0

)()(

e1ee

−

+−−−

−−

=ηη

(V-13)

The following steps were required to solve the river mixing equations:

• Obtain appropriate time-series of background data for Athabasca River (flows and concentrations).

• Specify release locations along the river and source type (point, line or exponential line). Some outfalls receive more than one release and in such cases, the discharges are grouped together and flow-weighted concentrations and the total flow of the release are input to the model at the release location.

• Estimate the velocity and depth of the river from Equation (V-4) and Equation (V-5).

• Compute mixing coefficient using Equation (V-10).

• Estimate the exponential decay constant, kQ, in Equation (V-13) which describes the distribution of groundwater seepage flow to the river. The


Golder Associates

exponential distribution of flow is described in Shaw and Prepas (1990). Values for kQ are site specific, but a value of kQ =0.1 provides a reasonable estimate.

• Specify locations in the river for which modelled concentrations are desired. The river models described by Equation (V-7) provide estimates of river concentrations at specific locations downstream the reference point. Therefore, both a distance downstream, x, and a lateral location across the river width (which is expressed as a fraction of the total river flow), η, are specified. The calculation can be performed using a matrix of x and η values so that river concentrations are can be plotted or contour-plotted.

V-3 MODEL CALIBRATION AND VALIDATION

Lateral mixing in the Athabasca River has been calibrated to field dye dispersion measurements (Trillium and Hydrographics 2003; Golder 2004). The calibration involved adjusting model parameters until predicted concentrations mimicked measured dye concentrations. The adjusted parameters for each reach were lateral dispersion coefficient and the Leopold Maddock coefficients that relate river flow to river velocity, water depth and river width. The accuracy of model predictions is high since the hydraulic parameters in the model are strongly related to headwater flow, which is continuously measured at Fort McMurray.

V-4 BACKGROUND FLOWS

Although background flows in the Athabasca, Clearwater, MacKay, Ells and Firebag rivers were obtained from measured flow records, daily information was not available for the entire 42 year simulation period. Therefore, a new method for generating hydrologic stochastic time series was developed to “in-fill” any missing data. The algorithm was designed to preserve the statistical distribution of the existing daily data for each station, as well as the regional cross-correlations between nearby stations. Stochastic hydrologic time series at multiple sites were generated. Instead of first generating the annual series and then subjecting it to some form of disaggregation, the algorithm built the series from the bottom up. A matrix of daily series (each day being placed in a single matrix column) was first generated independently for each site and each week using the appropriate distribution functions (typically kernel-based empirical functions). The matrix columns contained the daily data, while rows designated individual years. A desired auto-regressive lag and cross-site correlation structure was then imposed by systematically re-ordering the sequence of previously generated data in each column, such that the statistical properties of the generated and historical flow series were similar. Consistent with this


Golder Associates

approach, rows of the matrix were re-ordered for the annual statistics, thus preserving the annual auto-correlation as well as the auto-correlation between the start and end days of two subsequent years.

The main disadvantage of other methods is that they rely exclusively on the use of correlation, so the original distribution properties are lost. This is because a high proportion of the data are generated based on correlation, which tends to slant the distribution. Therefore, an advantage of this procedure is that it allows historical data to be merged with generated data. This feature was completed during the re-ordering phase, where random sampling of the data can be occasionally substituted by historical data. As a result, the statistical properties of the available historical series (i.e., mean, standard deviation and distribution type) were preserved once the “in-filling” was accomplished.

V-5 BACKGROUND WATER QUALITY

Background water quality was defined using in-stream monitoring data collected from the Athabasca River just upstream of Fort McMurray and from the mouth of the Clearwater River. The contribution of upstream pulp mills and municipalities were thus accounted for in the background data. The Athabasca River model boundary was set downstream of Fort McMurray. However, AENV’s long-term water quality monitoring site is situated upstream of Fort McMurray, and does not account for inflow from the Clearwater River. The following data was used in the calculation of water quality and flow in the Athabasca River downstream of Fort McMurray:

• concentrations in the in the Athabasca River upstream of Fort McMurray (WDS stations AB07CC0020/0030/DA1470 (AENV 2004);

• flow in the Athabasca River downstream of Fort McMurray (HYDAT station 07DA001 (Environment Canada 2003) [m3/s];

• concentration in the Clearwater River ((Golder 2002, 2003a; RAMP 2004) and WDS stations: AB07CD0100/0210 (AENV 2004)); and

• flow in the Clearwater River (HYDAT station 07CD001).

The process for deriving water quality profiles for the Clearwater and Athabasca rivers was consistent with the approach presented in Appendix VI. Distributions were randomly sampled on a daily basis to provide a continuous concentration time-series for the 42-year flow record.

To account for the delayed mixing that occurs between the Athabasca and Clearwater rivers, the upstream boundary was divided into ten lateral segments.


Golder Associates

Five to nine segments were assigned Athabasca River water quality depending on the relative flows of the two rivers, one segment was assumed to be a transitional area where the Athabasca and Clearwater rivers begin to mix, and the remaining segments were assigned Clearwater River water quality. The concentration in the transitional segment was calculated to ensure that the average concentration across all segments was equal to the concentration calculated assuming the two rivers were fully mixed.

Potential water releases from existing, approved and planned developments and tributary flows were routed through relevant discharge nodes. Model input was derived directly from the dynamic model time-series inputs from recent oil sands EIAs (Shell 2005; Suncor 2005; Imperial 2005).

Seasonal background water quality distributions were also generated for other major tributaries to the Athabasca River, including the Ells, Firebag and MacKay rivers, using the method outlined in Appendix VI. Contributions from small tributaries such as McLean, Poplar and Fort creeks were not included in the Athabasca River model, since they make up such a small portion of the Athabasca River watershed. Mine waters discharged to these streams were, as previously stated, added directly to the Athabasca River as point sources.

V-6 FORT MCMURRAY SEWAGE TREATMENT PLANT

The potential influence of the Fort McMurray domestic wastewater treatment plant was also accounted for in the model by adding a point source release at the upstream boundary of the model. A relationship between sewage flow and population size was derived using 1996 and 2001 sewage flow information from the Regional Municipality of Wood Buffalo and population projection for Fort McMurray during the same period. An approximate per capita generation rate of 300L/person/day was developed. The estimates of population growth in Fort McMurray that were used were developed for the Planned Development cases in recent EIAs (Shell 2005; Suncor 2005; Imperial 2005), and are summarized in Table V-1. The chemical profile assumed for this model is presented in Appendix VI.


Golder Associates

Table V-1 Long-Term Population Estimates for the Town of Fort McMurray

Year Population(a)

Current Conditions 49,340

2008 73,638

2040 94,477

Far Future 94,477 (a) Source: NAM (2005).

V-7 OIL SANDS RELATED SOURCE WATER QUALITY AND FLOWS

ARM includes direct and indirect seepage flows to the Athabasca River as shown in Table V-2.

Each direct seepage inflow into the Athabasca River was assigned an appropriate water quality profile using the approach outlined in Appendix VI. Flow used for each inflow were derived from previous EIAs:

• Suncor Millennium (Suncor 1998);

• TrueNorth Fort Hills (TrueNorth 2001);

• Shell Jackpine (including updated flows for the Aurora North and South Projects) (Golder and Cantox 2002);

• CNRL Horizon (CNRL 2002);

• Suncor South Tailings Pond (Suncor 2003);

• Shell Muskeg River Mine Expansion (Shell 2005);

• Suncor Voyager Project (Suncor 2005); and

• Imperial Kearl (Imperial 2005).

For indirect inflows (i.e., those entering via tributaries) daily concentrations were derived as part of previous EIAs:

• Tar River and the Horizon diversion channel in CNRL 2002;

• McLean Creek in Suncor 2003;

• Muskeg River, Isador’s Lake and ETDA wetlands for Shell 2005; and

• Steepbank River for Suncor 2005.


Golder Associates

For TrueNorth 2001, time series for indirect releases were not available so mine related water were included as direct releases ignoring tributary flows.

The model includes pit lake outflows from the Fort Hills and Aurora North projects. TrueNorth pit lake water quality was assigned average concentrations as reported in the EIA (TrueNorth 2001) whereas Aurora North pit lake water quality was assigned to Jackpine pit lake water quality.

Table V-2 Flow Information Used in the Athabasca River Model Flow (m3/s)

Node Source Flow Type Assigned

Water Chemistry

Water Chemistry Reference Background 2008 2040 Far Future

N1 Fort McMurray Sewage

Fort McMurray sewage

Ft. Mc. sewage

Appendix Table I-31 0.242 0.261 0.334 0.334

N2 McLean Creek

surface discharge

McLean Creek

Suncor (2003a) time series(a) time

series(a)time

series(a) time series(a)

N3 MacKay River

surface discharge

Mackay River

Appendix Tables I-23 & I-24

time series(b) time series(b)

time series(b) time series(b)

N4 Shipyard Lake (via)

Suncor basal seepage

basal aquifer (Suncor)

Appendix Table I-26 0 0 0.0038 0.0038

muskeg dewatering

muskeg dewatering

Appendix Table I-35 0 0.048 0 0

surficial aquifer surficial aquifer (Suncor)


N5a Millennium seepage direct discharge

surficial aquifer (Suncor)

Appendix Table I-25 0 0.0056 0.0015 0.0015

sand seepage process affected seepage

Appendix Table I-29 0 0 0.01 0

CT seepage process affected seepage

Appendix Table I-29 0 0.0018 0.0018 0.0018

N6

Suncor Lease 86/17 - South Mine Drainage

Basin #1 runoff Suncor site drainage


Ponds 4&5 Suncor site drainage

Appendix Table I-33 0 0 0 0

Pond 5 Suncor site drainage

Appendix Table I-33 0 0 0.04 0.04

Pond 1 & 2/3 Suncor site drainage


Flue Gas Desulfurization Pond

process affected seepage



Table V-2 Flow Information Used in the Athabasca River Model (continued)

Golder Associates

Flow (m3/s) Node Source Flow Type

Assigned Water

Chemistry


N6a

Suncor Lease 86/17 - South Mine Drainage (seepage)

Pond 2/3 process affected seepage

Appendix Table I-29 0 0.015 0.0057 0.0057

Pond 5 Flue Gas Desulfurization Pond


Appendix Table I-29 0 0 0.00008 0.00008

N7

Suncor Lease 86/17 - Tar Island Dyke Seepage

Pond 1 process affected seepage


N8 Wastewater Discharge Point

wastewater system

Suncor wastewater

Appendix Table I-36 0 0.285 0.285 0

cooling pond effluent

cooling pond effluent


south terrace Suncor site drainage

Appendix Table I-33 0 0 0.0098 0.0098

river side Suncor site drainage


N8a

Wastewater Discharge Point-seepage

river side drainage

Suncor site drainage




river side seepage





riverside CT process affected seepage

Appendix Table I-29 0 0 0.0118 0.0118

Pond 2/3 CT process affected seepage


N9 Steepbank River

surface discharge

Steepbank River

Suncor (2005) time series(c) time

series(c)time

series(c) time series(c)

N9a Steepbank River Seepage

seepage process affected seepage

Appendix Table I-29 0 0.0009 0.0011 0.0013

N10

Mid-Plant Drainage Discharge Point

mid-plant drainage


Appendix Table I-33 0 0.00034 0.00034 0

sewage Suncor sewage effluent




Golder Associates


Assigned Water

Chemistry


N11 Pond 4 Seepage Pond 4


Appendix Table I-29 0 0.001 0.001 0.001

N12 Pond 5 Seepage Pond 5


Appendix Table I-29 0 0.0035 0.0047 0.0047

N13

North Mine Drainage Discharge Point

north terrace Suncor site drainage


N13a

North Mine Drainage Discharge Point (seepage)

north mine drainage


Appendix Table I-33 0 0.00351 0.0038 0.0038

north terrace Flue Gas Desulphurization


Appendix Table I-29 0 0 0.0186 0.0186

north terrace CT



N14 Pond 6 Drainage drainage Suncor site

drainage Appendix Table I-29 0 0 0.03 0.03

N14a Pond 6 Drainage (seepage)

Pond 5 CT process affected seepage

Appendix Table I-29 0 0 0.0008 0.0008

N15 Pond 6 Seepage

Pond 6 seepage


Appendix Table I-29 0 0 0.0036 0.0036

N16 Muskeg River surface discharge

Muskeg River

Shell (2005)(d) time series(d) time

series(d)time

series(d) time series(d)

N17 Shell Seepage

tailings pond seepage

muskeg dewatering (2008)




N17a Deep Seepage

Jackpine CT seepage

basal aquifer (Shell)

Appendix Table I-39 0 0 0 0.003

MRM sand seepage



Aurora sand seepage



Jackpine sand seepage





Golder Associates


Assigned Water

Chemistry


N18 Isadore's Lake

surface discharge

Isadore's Lake

Shell (2005)(d) time series(d) time

series(d)time


CT seepage process affected seepage


sand seepage process affected seepage


wetlands wetlands Shell (2005)(d) time series(d) time

series(d)time


N19 Syncrude Pit Lake Discharge

Syncrude overburden dewatering

muskeg dewatering


Syncrude Pit Lake discharge

Jackpine Pit Lake

Golder and Cantox (2002)

0 0 0.154 0.154

Syncrude sand seepage



N19a Syncrude Seepage

Syncrude basal aquifer seepage



Syncrude CT seepage



N21 Fort Creek Aurora muskeg drainage

muskeg dewatering


Aurora CT seepage



N22 Fort Creek 2 South Pit Lake (Area 7) - 2024

Fort Hills South Pit Lake

TrueNorth (2001a) 0 0 0.132 0.13

N22a Fort Creek 2 Seepage

thickened tailings seepage



N23 Fort Creek 3 overburden dewatering

muskeg dewatering


N23a Fort Creek 3 Seepage



Appendix Table I-29 0 0 0.0088 0.0088

N24 Fort Creek 4 (via)

muskeg drainage

muskeg dewatering


tailings management area seepage



N25a Susan Lake 1 Seepage




N26 Susan Lake 2 North Pit Lake (Area 8) - Far (2140)

Fort Hills North Pit Lake

TrueNorth (2001a) 0 0 0 0.17



Golder Associates


Assigned Water

Chemistry


N27 Ells River surface discharge Ells River

Appendix Tables I-17 to I-20

time series(e) time series(e)

time series(e) time series(e)

N28 Tar River surface discharge Tar River CNRL

(2002) time series(f) time series(f)

time series(f) time series(f)

N28a CNRL seepage

CNRL basal seepage 1

basal aquifer (CNRL)



muskeg dewatering





N28b CNRL Seepage

CNRL seepage from in pit tails


Appendix Table I-29 0 0 0.00063 0

N29b Calumet River Seepage





muskeg dewatering





N31 Firebag River surface discharge

Firebag River

Appendix Tables I-21 & I-22

time series(g) time series(g)

time series(g) time series(g)

N32

CNRL Muskeg/Overburden Dewatering

muskeg/overburden dewatering

muskeg dewatering


N33 CNRL Diversion Channel

time series Diversion Channel

CNRL (2002) time series(f) time

series(f)time

series(f) time series(f)

N33a

CNRL Diversion Channel Seepage





muskeg dewatering





(a) Model input water chemistry distributions are included in Appendix 3-8. (b) Flows were included as presented in Suncor (2003). (b) Based on monitored flow data from Station 07DB001 (Environment Canada 2003). (c) Flows were included as presented in Suncor (2005). (d) Flows were included as presented in Shell (2005). (e) Based on monitored flow data from Station 07DA017 (Environment Canada 2003). (f) Flows were included as presented in CNRL (2002). (g) Based on monitored flow data from Station 07DC001 (Environment Canada 2003). (h) CNRL basal seepage is distributed along and 20 km length of the Athabasca River.


Golder Associates

V-8 ASSESSMENT NODES

The nodes used in this study are same nodes that have been used in previous modeling studies (Golder 2006). The locations of these nodes were selected taking into account IFN study segments (RL&L 2003). Table V-3 provides the locations and descriptions of each of the assessment nodes. Figure V-1 also shows the input nodes and assessment nodes.

Table V-3 Assessment Nodes

Node Distance Downstream of Fort McMurray (km) Description

Node 1 10.1 just upstream of the confluence with McLean Creek and within the IFN Segment 5 study site

Node 2 49.9 2000 m downstream from the confluence with the Muskeg River in the IFN Study Segment 4

Node 3 82.2 2000 m downstream of the IFN Segment 4 study site to capture loading from all sources within the study site

Node 4 145.2 10 km downstream of the confluence with the Firebag River in the IFN Segment 3 study site

Node 5 179. 5 10 km upstream of the confluence with the Embarras River in the IFN Segment 2 study site

V-9 SNAPSHOTS

Time snapshots were based on recent oil sands EIAs (Shell 2005; Suncor 2005; Imperial 2005). Time snapshots used were background, 2008, 2040 and far-future.

FortMcKay

N2

N3

N4

N5a

N6

N7N8a

N9N9aN10N11

N12N13N13a

N14N14a

N16N17N17a

N18N18a

N19 N19a

N21

N22N22a

N23N23a

N24

N25aN25

N26

N27

N28aN28 N28b

N29b

N32

N33aN33

Fort McKay

N1

N31

LEGEND

REFERENCE

WATER QUALITY MODELLINGAND ASSESSMENT NODES

FIGURE: 1


Golder Associates

V-10 REFERENCES

AENV. 2004. Data obtained from AENV Water Data System. Environmental Service, Environmental Sciences Division, Edmonton, AB.

CNRL (Canadian Natural Resources Limited). 2002. Horizon Oil Sands Project – Application for Approval. Volume 1 Prepared by Canadian Natural Resources Limited. Volumes 2, 3, 4, 5, 6, 7 and 8 Prepared by Golder Associates Ltd. for Canadian Natural Resources Limited. Submitted to Alberta Energy and Utilities Board and Alberta Environment. June 2002. Calgary, AB.

Environment Canada. 2003. Hydrological Database (HYDAT) Version 2000-2001. Station 07DA001 (Athabasca River below Fort McMurray).

Fischer, H.B., E.J. List, R.C.Y Koh, J. Imberger and N.H. Brooks. 1979. Mixing in Inland and Coastal Waters. Academic Press, Inc. San Diego, CA.

Golder (Golder Associates Ltd.). 2002. Oil Sands Regional Aquatics Monitoring Program (RAMP) 2001. Volume I: Chemical and Biological Monitoring. Volume II: Climatic and Hydrologic Monitoring. Submitted to RAMP Steering Committee. April 2002.

Golder. 2003. Oil Sands Regional Aquatics Monitoring Program (RAMP) 2002. Submitted to the RAMP Steering Committee. March 2003.

Golder. 2004. Athabasca River Model Update and Reach Segmentation. March 2004. Calgary AB.

Golder. 2005. Water Quality Modelling Report for the Suncor Voyageur Project. Prepared for Suncor Energy Inc. March 2005. Calgary, AB.

Golder. 2006. Athabasca River Model Interface for Instream Flow Needs Assessment. Submitted to Alberta Environment.

Golder and Cantox (Golder Associates Ltd. and Cantox Environmental Inc.). 2002. Surface Water Quality and Human, Aquatic Biota and Wildlife Health for Jackpine Mine - Phase 1. Prepared for Shell Canada Limited. June 2002.


Golder Associates

Imperial (Imperial Oil Resources Ventures Limited). 2005. Kearl Oil Sands Project. Mine Development. Volume 1 to 9. Submitted to Alberta Energy and Utilities Board and Alberta Environment. Prepared by Imperial Oil Resources Ventures Limited in Association with Golder Associates Ltd. Axys Environmental Consulting Ltd. Komex International Inc. and Nichols Applied Management. July 2005. Calgary, Alberta.

NAM (Nichols Applied Management). 2005. Urban Population Model Update. Submitted to the Regional Issues Working Group.

RAMP (RAMP 2003 Implementation Team). 2004. Regional Aquatics Monitoring Program (RAMP) 2003 Annual Report. Prepared for: RAMP Steering Committee. Submitted by the RAMP 2003 Implementation Team consisting of: Hatfield Consultants Ltd., Jacques Whitford Environment Ltd., Mack, Slack & Associates Inc., and Western Resource Solution. March 2004.

RL&L (RL&L Environmental Services Ltd. / Golder Associates Ltd.) 2003. Fish Overwintering Use of the Lower Athabasca River 2001 to 2003. Submitted to CEMA Water Working Group. October 2003. Fort McMurray, Alberta.

Shaw, R.D. and E.E. Prepas. 1990. Groundwater-Lake Interactions, 2: Nearshore Seepage Pattern and the Contribution of Groundwater to Lakes in Central Alberta. J. Hydrol. 119:121- 139.

Shell (Shell Canada Limited). 1997. Muskeg River Mine Project EIA. Volumes 2, 3 and 5. Prepared by Golder Associates Ltd.

Shell. 2005. Muskeg River Mine Expansion Project Application and Environmental Impact Assessment. Volume 1,2, 3 and 4. Submitted to Alberta Energy and Utilities Board and Alberta Environment. Prepared by Shell Canada Limited in Association with Golder Associates Ltd. And Nichols Applied Management. April 2005. Fort McMurray, AB.

Suncor (Suncor Energy Inc.). 1998. Project Millennium Application. Volumes 1 and 2. Prepared by Golder Associates Ltd., Calgary AB.

Suncor. 2003. Suncor South Tailings Pond Project. Volumes 1 and 2. Prepared by Suncor Energy Inc., Oil Sands in association with Golder Associates Ltd., Nichols Applied Management and Millennium EMS Solutions. December 19, 2003. Fort McMurray, AB.


Golder Associates

Suncor. 2005. Voyageur Project Application and Environmental Impact Assessment. Volumes 1A, 1B, 2, 3, 4, 5 and 6. Submitted to Alberta Energy and Utilities Board and Alberta Environment. Prepared by Suncor Energy Inc. Oil Sands in Association with Golder Associates Ltd. And Nichols Applied Management. March 2005. Fort McMurray, AB.

Trillium and Hydrographics (Trillium Engineering & Hydrographics Inc.). 2003. Measurement of Transverse Mixing Coefficients in the lower Athabasca River. In Preparation for CEMA Surface Water Working Group (SWWG).

TrueNorth (TrueNorth Energy L.P.). 2001. Fort Hills Oil Sands Project. Volume 3. Environmental Impact Assessment. Prepared by Golder Associates Ltd. Submitted to Alberta Energy and Utilities Board and Alberta Environmental Protection.

APPENDIX VI

WATER QUALITY PROFILE INFORMATION

CEMA VI-i Athabasca River Reach Specific May 2007 Water Quality Objectives

Golder Associates

TABLE OF CONTENTS

SECTION PAGE

VI-1 DERIVATION OF WATER QUALITY INPUT..........................................................1 VI-1.1 Outlier Detection ...................................................................................................... 1 VI-1.2 Distribution Fitting and Goodness of Fit................................................................... 4 VI-1.3 Special Cases .......................................................................................................... 5 VI-1.4 Bounding the Distribution ......................................................................................... 5

VI-2 WATER QUALITY PROFILE INFORMATION........................................................6

VI-3 REFERENCES ....................................................................................................87

LIST OF TABLES

Table VI-1 Background Water Quality in the Steepbank River (Winter) ..................................7 Table VI-2 Background Water Quality in the Steepbank River (Spring) ..................................9 Table VI-3 Background Water Quality in the Steepbank River (Summer).............................11 Table VI-4 Background Water Quality in the Steepbank River (Fall).....................................13 Table VI-5 Background Water Quality in the Unnamed Creek (Fall and Winter) ..................15 Table VI-6 Background Water Quality in the Unnamed Creek (Spring and Summer)...........17 Table VI-7 Water Quality in the Unnamed Creek (Annual) ....................................................19 Table VI-8 Water Quality in the Athabasca River, Upstream of Fort McMurray

(Winter) .................................................................................................................21 Table VI-9 Water Quality in the Athabasca River, Upstream of Fort McMurray

(Spring) .................................................................................................................23 Table VI-10 Water Quality in the Athabasca River, Upstream of Fort McMurray

(Summer)..............................................................................................................25 Table VI-11 Water Quality in the Athabasca River, Upstream of Fort McMurray (Fall) ...........27 Table VI-12 Water Quality in the Athabasca River, Upstream of the Steepbank River

(Annual) ................................................................................................................29 Table VI-13 Water Quality in the Clearwater River (Winter) ....................................................31 Table VI-14 Water Quality in the Clearwater River (Spring) ....................................................33 Table VI-15 Water Quality in the Clearwater River (Summer).................................................35 Table VI-16 Water Quality in the Clearwater River (Fall).........................................................37 Table VI-17 Water Quality in the Ells River (Winter)................................................................39 Table VI-18 Water Quality in the Ells River (Spring)................................................................41 Table VI-19 Water Quality in the Ells River (Summer).............................................................43 Table VI-20 Water Quality in the Ells River (Fall) ....................................................................45 Table VI-21 Water Quality in the Firebag River (Ice Cover) ....................................................47 Table VI-22 Water Quality in the Firebag River (Open Water) ................................................49 Table VI-23 Water Quality in the Mackay River (Ice Cover) ....................................................51 Table VI-24 Water Quality in the Mackay River (Open Water) ................................................53 Table VI-25 Suncor Surficial Aquifer Water Quality .................................................................55 Table VI-26 Suncor Basal Water Quality .................................................................................57 Table VI-27 Tailings Pond Water Quality .................................................................................59 Table VI-28 Process Affected Water Quality ...........................................................................61 Table VI-29 Process Affected Seepage Quality.......................................................................63 Table VI-30 Mature Fine Tailings Seepage Quality .................................................................65 Table VI-31 Mature Fine Tailings Flux Water Quality ..............................................................67

CEMA VI-ii Athabasca River Reach Specific May 2007 Water Quality Objectives

Golder Associates

LIST OF TABLES

Table VI-32 Fort McMurray Sewage Effluent Water Quality ....................................................69 Table VI-33 Suncor Site Drainage Water Quality ....................................................................71 Table VI-34 Suncor Cooling Water Quality ..............................................................................73 Table VI-35 Suncor Sewage Water Quality .............................................................................75 Table VI-36 Suncor Wastewater Quality ..................................................................................77 Table VI-37 Muskeg and Overburden Dewatering Water Quality - Muskeg River Mine .........79 Table VI-38 CNRL Basal Water Quality ...................................................................................81 Table VI-39 Shell Basal Water Quality.....................................................................................83 Table VI-40 TrueNorth Basal Water Quality ............................................................................85

LIST OF FIGURES

Figure VI-1 Process for Deriving Water Quality Profiles ...........................................................2

CEMA VI-1 Athabasca River Reach Specific May 2007 Water Quality Objectives

Golder Associates

VI-1 DERIVATION OF WATER QUALITY INPUT

For every type of mine-related source water, unique probability distributions were assigned to each water quality constituent modelled. Available water quality data were compiled and used to characterize the source waters. The following standardized screening process was used to develop a probability distribution for each constituent:

• Step 1 - remove outliers from the measured data;

• Step 2 - fit suitable probability distributions to the remaining data;

• Step 3 - assess the goodness of fit for all applicable distributions to determine the most appropriate distribution type;

• Step 4 - process any special cases (e.g., datasets with less than 10 values); and

• Step 5 - determine the minimum and maximum bounds to define a reasonable range for the chosen distribution.

A conceptual representation of the process used to assign water quality distributions is presented in Figure VI-1. The figure illustrates the chronological order of events necessary for the selection of a distribution for each modelled water quality constituent.

VI-1.1 OUTLIER DETECTION

“Outlier” is a collective term that refers to either a contaminant or discordant observation (Beckman and Cook 1983). A discordant observation appears surprising or discrepant, but the origin of the result is unknown. A contaminant is an observation that may induce bias to the fitted probability distribution, and the reason for its characteristics can be explained.

If a measurement was identified as an outlier, the origin of the result was investigated to validate the results of outlier detection tests (WMO 1985) performed on the dataset. Outliers of explainable origins (i.e., there was a reason for the anomalous result) were considered contaminants and were removed from the dataset without further consideration. Outliers of unknown origin were considered discordant observations and were retained in the dataset for further investigation.


Golder Associates

Figure VI-1 Process for Deriving Water Quality Profiles


Golder Associates

Three statistical tests were used to identify outliers. These included the three times standard deviation (3σ) rule, the Hampel identifier and the combined Rosner - Dixon test, descriptions of which are presented below. An observation was considered an outlier only if it was flagged by all three outlier tests. By using multiple tests, the possibility of misdiagnoses was reduced (Jain 1981; Beckman and Cook 1983; WMO 1985; Pearson 2001; Kottegoda 1984). Misdiagnosis is often referred to as (1) swamping or Type I error, when a normal datum is falsely identified as an outlier, or (2) masking or Type VI error, when an outlier is falsely identified as a normal datum (Jain 1981; Beckman and Cook 1983).

The three statistical tests commonly identify an observation “x” as an outlier if “x” meets the following criterion:

kSLx +> (21)

where, L is a location parameter (i.e., a reference in the sample domain), S is a scale or dispersion parameter, and k is a parameter that indicates a tolerance level to dispersion. The three outlier tests differ in their definition of L, S and k. To use the outlier tests, the observations must be independent of one another and follow a normal distribution. Thus, lognormal data must be log transformed prior to the application of the tests.

The 3σ rule is the most common of the outlier tests, because it is simple to implement and uses well known statistical properties, namely mean and standard deviation to represent L and S (Pearson 2001). The 3σ rule test is a single-outlier detection test, so consecutive testing for many-outlier detection was required (Beckman and Cook 1983). The mean and standard deviation were calculated for the dataset being analyzed. If the maximum value was identified as an outlier, it was removed from the dataset. A new mean and standard deviation were then calculated for the remaining data, and the maximum observed value was again tested. This iterative process continued until no outlier was detected.

The Hampel identifier is a more recent test, and was developed to address some of the masking issues that can affect the 3σ rule (Pearson 2001). Hampel (1985) first proposed this test, and it was evaluated further by Davies and Gather (1993) and Pearson (2001). In this test, L is the median and S is a dispersion coefficient. Although this test has not yet been used systematically on water quality data, its resemblance with the 3σ rule makes it suitable for that purpose. The Hampel identifier can be considered as a many-outlier detection test, so an iterative process was not needed.

The Rosner test was specifically designed to reduce the masking effect encountered in other outlier detection tests (Rosner 1975, 1983). The Rosner test


Golder Associates

is considered a suitable test for outliers in water quality data (Gilbert 1987; Jain 1981), but is only applicable when the sample size is greater or equal to 25. An evaluation performed by Jain (1981) validated the efficiency of the test. However, Jain noted the importance of carefully selecting the number of outliers expected in the dataset, since the test will only analyze as many outliers as specified by the user. The number of outliers was set at 30% of the sample size for this analysis, since it was unlikely that more than 30% of the dataset were outlier values. In this test, L is the mean and S is standard deviation of a subset of the data that does not include suspected outliers.

When the sample size was less than 25, the Dixon test was used in place of the Rosner test (Dixon 1950, 1951, 1953; Sokal and Rohlf 1981; Gilbert 1987). Because it is a single-outlier detection test, it is recommended that consecutive testing be performed to account for the possible presence of multiple outliers, as described for the 3σ rule. The variables L and S do not apply to this test.

VI-1.2 DISTRIBUTION FITTING AND GOODNESS OF FIT

The probability distributions considered for the water quality data were normal, lognormal and delta-lognormal. These three types of distributions can generally be used to characterize water quality information in any receiving waterbody (AEP 1995; U.S. EPA 1991). To identify which distribution best described a water quality constituent, all three distributions were initially fitted to the available measured data for the constituent. Statistical goodness of fit tests, consisting of the Chi-square test, the Kolmogorov-Smirnov test and the squared correlation coefficient (Sokal and Rohlf 1981) were used to determine which distribution type was most appropriate.

The Chi-square test at a 5% statistical significance level was employed only to provide support in selecting the most appropriate distributions. The test can be difficult to apply to water quality data. Datasets may often be too small, or contain too many replicates for the test to provide useful results. Consequently, the Kolmogorov-Smirnov test was used as a decision criterion. It was required that the probability distribution pass this test at the 5% statistical significance level to be selected as a candidate for the best distribution for a given dataset. However, if none of the available distributions passed this test, the final criterion for selecting the most appropriate distribution was the squared correlation coefficient.

The squared correlation coefficient is a standard statistical measure (Stedinger et al. 1993), which allows the available probability distributions to be ranked in terms of goodness of fit. In general, the probability distribution with the highest squared correlation coefficient was considered the most appropriate for the


Golder Associates

dataset. The statistical significance level of the squared correlation was also evaluated to ensure that the relationship was not obtained by chance or random fluctuations (Walpole and Myers 1978).

VI-1.3 SPECIAL CASES

Three special cases may occur during the probability distribution fitting process. These include 1) datasets with less than ten observations; 2) datasets with all observations at a single, constant value or below the analytical detection limit; and 3) no data are available for the water quality constituent. When there were less than ten observations in the datatset, and less than 50% of the observations were reported as less than the analytical detection limit, a lognormal distribution was selected. Otherwise, a delta-lognormal distribution was selected. Both distributions were characterized using a coefficient of variation equal to 0.6, consistent with Alberta Environment guidelines (AEP 1995). When the dataset consisted of many observations of the same value, expert judgment was used to assign a distribution. In some cases, a surrogate was probability distribution was derived from the fitted distribution of another related water quality constituent or the distribution of the constituent for another source water type. In other cases, the selected distribution was a constant value (a Dirac function), or a uniform distribution with assigned minimum and maximum bounds. For cases in which no observed data exists for a given water quality constituent, professional judgement was used to derive distributions that will provide conservative predictions.

VI-1.4 BOUNDING THE DISTRIBUTION

If left unbounded, distributions can produce exceptionally high concentrations that are not realistic to the aquatic system. Therefore, each distribution was assigned a minimum and maximum value. The minimum value of the distribution was set to zero for the normal distribution, a value very close to zero (e.g., 0.00000001) for the lognormal distribution, or half the detection limit for the delta-lognormal distribution. The maximum bound was most often set to either three standard deviations from the mean or the maximum value observed, whichever was the largest. In some cases, the maximum observed value was an outlier, but the value corresponding to three standard deviations from the mean was too high to be reasonable. If appropriate, the extreme value produced by the distribution was replaced with the maximum observed value multiplied by a weighting factor that ranges from 1 to 3. The larger the weighting factor was applied to datasets with smaller number of data points and larger standard deviation.


Golder Associates

VI-2 WATER QUALITY PROFILE INFORMATION

Water quality profiles have been defined for:

• Steepbank River (Tables VVI-1 to VVI-4);

• Unnamed Creek (Tables VVI-5 to VVI-8);

• Athabasca River (Tables VVI-8 to VVI-12);

• Clearwater River (Tables VVI-13 to VVI-16);

• Ells River (Tables VVI-17 to VVI-20);

• Firebag River (Tables VVI-21 and VVI-22);

• Mackay River (Tables VVI-23 and VVI-24);

• Natural groundwater:

− surficial aquifer (Table VVI-25);

− basal aquifer (Table VVI-26);

• Mine waters (note that process affected seepage is the only mine water released directly to the Athabasca River):

− tailings pond water (Table VVI-27);

− process affected water (Table VVI-28);

− process affected seepage (Table VVI-29);

− MFT seepage (Table VVI-30);

− MFT flux waters (Table VVI-31);

• Fort McMurray sewage effluent (Table VVI-32);

• Suncor Lease 86/17 waters:

− site drainage (Table VVI-33);

− cooling water effluent (Table VVI-34);

− sewage effluent (Table VVI-35);

− wastewater (Table VI-36);

• Muskeg and overburden at other facilities (Table VI-37);

• Basal aquifer waters from other operators:

− CNRL basal aquifer (Table VI-38);

− Shell basal aquifer (Table VI-39);

− TrueNorth basal aquifer (Table VI-40).


Golder Associates

Table VI-1 Background Water Quality in the Steepbank River (Winter) Sample Size

Constituent Units Selected

Distribution Average StandardDeviation 95th Percentile Delta(a) D(b) All

Non-Detects

Number of Outliers

Conventional Constituents

dissolved organic carbon mg/L lognormal 13 4 21 - - 30 0 0

total dissolved solids mg/L normal 343 63 448 - - 27 0 0

Major Ions

calcium mg/L normal 63 11 82 - - 29 0 0

chloride mg/L normal 6 2 10 - - 31 0 0

magnesium mg/L normal 20 3 26 - - 29 0 0

sodium mg/L lognormal 40 12 63 - - 31 0 0

sulphate mg/L lognormal 12 4 19 - - 31 0 0

sulphide mg/L lognormal 0.006 0.008 0.021 - - 19 17 0

Nutrients

nitrogen - ammonia mg/L lognormal 0.04 0.03 0.10 - - 12 4 0

nitrogen, total mg/L lognormal 0.8 0.3 1.4 - - 27 0 0

phosphorus, total mg/L normal 0.06 0.03 0.1 - - 26 0 1

Toxicity

toxicity - acute TUa none(c) 0 0 0 - - 0 0 -

toxicity - chronic TUc none(c) 0 0 0 - - 1 1 -

General Organics

naphthenic acids mg/L lognormal 0.8 0.4 1.7 - - 6 4 0

total phenolics mg/L delta lognormal 0.0015 0.0024 0.0067 0.71 0.0005 24 17 0

Metals (Total)

aluminum (AL) mg/L lognormal 0.07 0.04 0.16 - - 10 0 0

antimony (SB) mg/L lognormal 0.0008 0.0005 0.0017 - - 4 0 0

arsenic (AS) mg/L normal 0.0003 0.0002 0.0006 - - 11 6 0

barium (Ba) mg/L lognormal 0.08 0.01 0.11 - - 11 0 0

beryllium (Be) mg/L none(d) 0 0 0 - - 8 8 -

boron (B) mg/L lognormal 0.28 0.16 0.60 - - 8 0 0

cadmium (Cd) mg/L lognormal 0.0003 0.0004 0.0011 - - 11 8 0

chromium (Cr) mg/L lognormal 0.002 0.001 0.004 - - 9 4 0

copper (Cu) mg/L lognormal 0.002 0.001 0.004 - - 9 1 0

iron (Fe) mg/L normal 0.86 0.36 1.48 - - 11 0 0

lead (Pb) mg/L lognormal 0.00051 0.00081 0.0019 - - 10 3 0

manganese (Mn) mg/L normal 0.02 0.01 0.04 - - 11 1 0

mercury (Hg) mg/L normal 0.000038 0.000018 0.000069 - - 23 21 0

molybdenum (Mo) mg/L lognormal 0.0006 0.0004 0.0013 - - 6 0 0

nickel (Ni) mg/L lognormal 0.0049 0.0116 0.0253 - - 11 6 0

selenium (Se) mg/L lognormal 0.0004 0.0005 0.0013 - - 11 9 0

silver (Ag) mg/L delta lognormal 0.00002 0.00002 0.00006 0.83 0.00002 6 5 0

strontium (Sr) mg/L lognormal 0.29 0.17 0.62 - - 8 1 0

vanadium (V) mg/L lognormal 0.001 0.001 0.002 - - 26 19 0


Table VI-1 Background Water Quality in the Steepbank River (Winter) (continued)

Golder Associates

Sample Size


Distribution Average StandardDeviation 95th Percentile Delta(a) D(b) All

Non-Detects

Number of Outliers

zinc (Zn) mg/L lognormal 0.02 0.01 0.04 - - 8 0 0

Target PAHs and Alkylated PAHs

PAH Group 1 µg/L none(d) 0 0 0 - - 2 2 -









Tainting Potential

tainting potential TPU none(c) 0 0 0 - - - - - (a) Proportion of data that were reported as less than the method detection limit (MDL). (b) Average of all MDL values; reported as half the MDL. (c) Background was assumed to be non-toxic and free of tainting compounds. (d) The distribution was set to zero if all values were reported as less than the MDL. Source: Based on information from Golder (1996a, 2003, 2005a), RAMP (2004) and from Alberta Environment WDS stations:

AB07DA1000\2710\2720\0260 (AENV 2004b).


Golder Associates

Table VI-2 Background Water Quality in the Steepbank River (Spring) Sample Size


Distribution Average Standard Deviation

95th Percentile Delta(a) D(b) All

Non-Detects

Number of

Outliers



total dissolved solids mg/L lognormal 143 91 320 - - 26 0 0

Major Ions

calcium mg/L lognormal 26 14 54 - - 25 0 0

chloride mg/L lognormal 2 2 5 - - 29 0 1

magnesium mg/L lognormal 8 5 18 - - 25 0 0




Nutrients

nitrogen - ammonia mg/L delta

lognormal 0.02 0.01 0.04 0.67 0.02 6 4 0


phosphorus, total mg/L lognormal 0.08 0.05 0.17 - - 12 0 0

Toxicity



General Organics

naphthenic acids mg/L lognormal 1 0.6 2.1 - - 6 3 0


Metals (Total)

aluminum (Al) mg/L lognormal 0.51 0.29 1.08 - - 6 1 0

antimony (Sb) mg/L delta lognormal 0.0003 0.0003 0.001 0.5 0.00017 6 3 0

arsenic (As) mg/L lognormal 0.0004 0.0003 0.001 - - 6 2 0


beryllium (Be) mg/L delta lognormal 0.0004 0.0004 0.0013 0.83 0.0005 6 5 0


cadmium (Cd) mg/L delta lognormal 0.0006 0.0012 0.0033 0.83 0.00038 6 5 0


copper (Cu) mg/L delta lognormal 0.001 0.001 0.003 0.5 0.0005 6 3 0

iron (Fe) mg/L lognormal 0.95 0.55 2.03 - - 7 0 0


manganese (Mn) mg/L lognormal 0.03 0.02 0.07 - - 6 0 0

mercury (Hg) mg/L delta lognormal 0.000027 0.000026 0.000082 0.67 0.000026 6 4 0




Table VI-2 Background Water Quality in the Steepbank River (Spring) (continued)

Golder Associates

Sample Size




Non-Detects

Number of

Outliers

selenium (Se) mg/L delta lognormal 0.0001 0.0002 0.0005 0.83 0.00018 6 5 0

silver (Ag) mg/L lognormal 0.00001 0.00001 0.00003 - - 2 0 0














Tainting Potential

tainting potential TPU none(c) 0 0 0 - - - - - (a) Proportion of data that were reported as less than the method detection limit (MDL). (b) Average of all MDL values; reported as half the MDL. (c) No information available, so assumed to be zero in natural surface waters. (d) The distribution was set to zero if all values were reported as less than the MDL. Source: Based on information from Golder (1996b, 2003, 2005a), RAMP (2004) and from Alberta Environment WDS stations:

AB07DA1000\2710\2720\0260 (AENV 2004b). .


Golder Associates

Table VI-3 Background Water Quality in the Steepbank River (Summer) Sample Size




Non-Detects

Number of Outliers


dissolved organic carbon mg/L normal 21 4 28 - - 18 0 0


Major ions


chloride mg/L delta lognormal 2 2 7 0.19 0.35 26 5 0


sodium mg/L delta lognormal 10 5 19 0.04 0.5 26 1 0



Nutrients


nitrogen, total mg/L normal 0.9 0.4 1.6 - - 18 0 0


toxicity



General Organics


total phenolics mg/L lognormal 0.0024 0.0036 0.0084 - - 24 14 0

Metals (Total)

aluminum (Al) mg/L normal 0.16 0.09 0.32 - - 10 0 0

antimony (Sb) mg/L lognormal 0.0004 0.0002 0.0008 - - 5 1 0


barium (Ba) mg/L normal 0.03 0.01 0.05 - - 10 0 0

beryllium (Be) mg/L lognormal 0.0011 0.0009 0.0028 - - 10 6 0






lead (Pb) mg/L delta lognormal 0.0011 0.0014 0.0039 0.55 0.00013 11 6 0







Table VI-3 Background Water Quality in the Steepbank River (Summer) (continued)

Golder Associates

Sample Size




Non-Detects

Number of Outliers

silver (Ag) mg/L none(d) 0 0 0 - - 6 6 -

strontium (Sr) mg/L normal 0.091 0.044 0.17 - - 10 0 0













Tainting Potential

tainting potential TPU none(c) 0 0 0 - - - - -

(a) Proportion of data that were reported as less than the method detection limit (MDL). (b) Average of all MDL values; reported as half the MDL. (c) No information available, so assumed to be zero in natural surface waters. (d) The distribution was set to zero if all values were reported as less than the MDL. Source: Based on information from Golder (1996b, 2003, 2005a), RAMP (2004) and from Alberta Environment WDS stations:

AB07DA1000\2710\2720\0260 (AENV 2004b).


Golder Associates

Table VI-4 Background Water Quality in the Steepbank River (Fall) Sample Size




Non-Detects

Number of

Outliers




Major Ions





sulphate mg/L normal 5 3 10 - - 20 1 0


Nutrients


nitrogen, total mg/L normal 1 0.6 2.1 - - 17 1 0


Toxicity



General Organics



Metals (Total)



arsenic (As) mg/L normal 0.0005 0.0003 0.0009 - - 14 4 2





chromium (Cr) mg/L normal 0.004 0.003 0.009 - - 13 1 0

copper (Cu) mg/L normal 0.002 0.001 0.004 - - 11 1 0




mercury (Hg) mg/L none(d) 0 0 0 - - 11 11 -


nickel (Ni) mg/L normal 0.0023 0.0017 0.0054 - - 13 4 0





Table VI-4 Background Water Quality in the Steepbank River (Fall) (continued)

Golder Associates

Sample Size




Non-Detects

Number of

Outliers

vanadium (V) mg/L normal 0.001 0.001 0.002 - - 18 8 1












Tainting Potential

tainting potential TPU none(c) 0 0 0 - - - - - (a) Proportion of data that were reported as less than the method detection limit (MDL). (b) Average of all MDL values; reported as half the MDL. (c) No information available, so assumed to be zero in natural surface waters. (d) The distribution was set to zero if all values were reported as less than the MDL. Source: Based on information from Golder (1996b, 2003, 2005a), RAMP (2004) and from Alberta Environment WDS stations:

AB07DA1000\2710\2720\0260 (AENV 2004b).


Golder Associates

Table VI-5 Background Water Quality in the Unnamed Creek (Fall and Winter) Sample Size




Non-Detects

Number of

Outliers




Major Ions






Sulphide mg/L lognormal 0.006 0.003 0.012 - - 8 3 0

Nutrients




Toxicity


toxicity - chronic TUc none(d) 0 0 0 - - 2 2 -

General Organics


total phenolics mg/L normal 0.001 0.0006 0.002 - - 11 8 0

Metals (Total)

aluminum (Al) mg/L normal 1 0.64 2.2 - - 11 1 0




beryllium (Be) mg/L normal 0.0004 0.0001 0.0007 - - 11 10 0











selenium (Se) mg/L normal 0.0003 0.0002 0.0006 - - 11 10 0




zinc (Zn) mg/L normal 0.02 0.01 0.03 - - 11 2 0


Table VI-5 Background Water Quality in the Unnamed Creek (Fall and Winter) (continued)

Golder Associates

Sample Size




Non-Detects

Number of

Outliers











Tainting Potential

tainting potential TPU none(c) 0 0 0 - - - - - (a) Proportion of data that were reported as less than the method detection limit (MDL). (b) Average of all MDL values; reported as half the MDL. (c) No information available, so assumed to be zero in natural surface waters. (d) The distribution was set to zero if all values were reported as less than the MDL.

Source: based on information from field samples collected in 2001, 2002, and 2004 (Golder 2005a), also includes information from nearby small creeks, including Wood, Leggett and McLean Creeks (Golder 1996b, 1999a, 2000a, 2001a, 2002a, 2003) and RAMP (2004).


Golder Associates

Table VI-6 Background Water Quality in the Unnamed Creek (Spring and Summer)

Sample Size


Distribution Average Standard Deviation 95th Percentile Delta(a) D(b) All

Non-Detects

Number of

Outliers




Major Ions






sulphide mg/L delta lognormal 0.002 0.003 0.007 0.67 0.0015 3 2 0

Nutrients


lognormal 0.02 0.02 0.06 0.5 0.016 8 4 0



Toxicity



General Organics

naphthenic acids mg/L delta

lognormal 0.7 0.9 2.7 0.75 0.5 8 6 0


Metals (Total)








chromium (Cr) mg/L delta lognormal 0.002 0.002 0.007 0.75 0.0008 8 6 0





Table VI-6 Background Water Quality in the Unnamed Creek (Spring and Summer) (continued)

Golder Associates

Sample Size


Distribution Average Standard Deviation 95th Percentile Delta(a) D(b) All

Non-Detects

Number of

Outliers




nickel (Ni) mg/L delta lognormal 0.0019 0.0015 0.0049 0.63 0.002 8 5 0







PAH Group 1 µg/L none(c) 0 0 0 - - 0 0 -









Tainting Potential


(a) Proportion of data that were reported as less than the method detection limit (MDL). (b) Average of all MDL values; reported as half the MDL. (c) No information available, so assumed to be zero in natural surface waters. Source: based on information from field samples collected in 2001, 2002, and 2004 (Golder 2005a), also includes information from

nearby small creeks, including Wood, Leggett and McLean Creeks (Golder 1996b, 1999a, 2000a, 2001a, 2002a, 2003) and RAMP (2004).


Golder Associates

Table VI-7 Water Quality in the Unnamed Creek (Annual) Sample Size




Non-Detects

Number of Outliers




Major Ions







Nutrients

nitrogen - ammonia mg/L normal 0.03 0.01 0.05 - - 18 13 1



Toxicity



General Organics



Metals (Total)

aluminum (Al) mg/L delta lognormal 0.66 1.26 2.55 0.05 0.01 19 1 0









iron (Fe) mg/L lognormal 1.14 0.96 3 - - 18 0 0



mercury (Hg) mg/L lognormal 0.000033 0.00011 0.00014 - - 14 12 0








Table VI-7 Water Quality in the Unnamed Creek (Annual) (continued)

Golder Associates

Sample Size




Non-Detects

Number of Outliers

zinc (Zn) mg/L delta lognormal 0.02 0.02 0.07 0.11 0.002 19 2 0











Tainting Potential

tainting potential TPU none(c) 0 0 0 - - - - - (a) Proportion of data that were reported as less than the method detection limit (MDL). (b) Average of all MDL values; reported as half the MDL. (c) No information available, so assumed to be zero in natural surface waters. (d) The distribution was set to zero if all values were reported as less than the MDL. Source: based on information from field samples collected in 2001, 2002, and 2004 (Golder 2005a), also includes information from nearby small

creeks, including Wood, Leggett and McLean Creeks (Golder 1996b, 1999a, 2000a, 2001a, 2002a, 2003) and RAMP (2004).


Golder Associates

Table VI-8 Water Quality in the Athabasca River, Upstream of Fort McMurray (Winter)

Sample Size Constituent Units

Selected Distribution Average

Standard Deviation

95th Percentile Delta(a) D(b) All Non-Detects

Number of Outliers




Major Ions







Nutrients


lognormal 0.03 0.03 0.08 0.2 0.005 35 7 0


phosphorus, total mg/L delta lognormal 0.03 0.01 0.05 0.02 0.0015 59 1 2

Toxicity



General Organics

naphthenic acids mg/L none(c) 0 0 0 - - 0 0 -


Metals (Total)









copper (C) mg/L lognormal 0.002 0.003 0.008 - - 33 9 0


lead (Pb) mg/L normal 0.001 0.00053 0.0019 - - 14 8 1







Table VI-8 Water Quality in the Athabasca River, Upstream of Fort McMurray (Winter) (continued)

Golder Associates



Standard Deviation


Number of Outliers



vanadium (V) mg/L delta lognormal 0.002 0.003 0.007 0.63 0.0005 43 27 0









PAH Group 7 µg/L normal 0.41 0.18 0.72 - - 4 3 0



Tainting Potential

tainting potential TPU none(c) 0 0 0 - - - - - (a) Proportion of data that were reported as less than the method detection limit (MDL). (b) Average of all MDL values; reported as half the MDL. (c) No information available, so assumed to be zero in natural surface waters. (d) The distribution was set to zero if all values were reported as less than the MDL. Source: based on information from Alberta Environment WDS stations: AB07CC0030/DA1470 (AENV 2004b).


Golder Associates

Table VI-9 Water Quality in the Athabasca River, Upstream of Fort McMurray (Spring)

Sample Size




Non-detects

Number of Outliers




Major Ions






sulphide mg/L none(c) 0 0 0 - - 7 7 -

Nutrients




Toxicity

toxicity - acute TUa none(d) 0 0 0 - - 0 0 -


General Organics

naphthenic acids mg/L none(d) 0 0 0 - - 0 0 -


Metals (Total)




















Table VI-9 Water Quality in the Athabasca River, Upstream of Fort McMurray (Spring) (continued)

Golder Associates

Sample Size




Non-detects

Number of Outliers













Tainting Potential

tainting potential TPU none(d) 0 0 0 - - - - - (a) Proportion of data that were reported as less than the method detection limit (MDL). (b) Average of all MDL values; reported as half the MDL. (c) The distribution was set to zero if all values were reported as less than the MDL. (d) No information available, so assumed to be zero in natural surface waters. Source: based on information from Alberta Environment WDS stations: AB07CC0030/DA1470 (AENV 2004b).


Golder Associates

Table VI-10 Water Quality in the Athabasca River, Upstream of Fort McMurray (Summer)

Sample Size




Number of

Outliers


dissolved organic carbon

mg/L lognormal 9 6 21 - - 42 0 0


Major Ions




sodium mg/L normal 6 2 9 - - 63 0 0


sulphide mg/L normal 0.004 0.002 0.007 - - 16 15 0

Nutrients




Toxicity



General Organics



Metals (Total)

















Table VI-10 Water Quality in the Athabasca River, Upstream of Fort McMurray (Summer) (continued)

Golder Associates

Sample Size




Number of

Outliers





Zinc (Zn) mg/L normal 0.02 0.01 0.04 - - 22 0 0



PAH Group 2 µg/L delta lognormal 0.0058 0.006 0.018 0.67 0.005 3 2 0



PAH Group 5 µg/L lognormal 0.0065 0.0038 0.014 - - 3 1 0





Tainting Potential


(a) Proportion of data that were reported as less than the method detection limit (MDL). (b) Average of all MDL values; reported as half the MDL. (c) No information available, so assumed to be zero in natural surface waters. (d) The distribution was set to zero if all values were reported as less than the MDL. Source: based on information from Alberta Environment WDS stations: AB07CC0020/CC0030/DA1470 (AENV 2004b).


Golder Associates

Table VI-11 Water Quality in the Athabasca River, Upstream of Fort McMurray (Fall)

Sample Size




Non-Detects

Number of

Outliers




Major Ions







Nutrients




Toxicity



General Organics



Metals (Total)










iron (Fe) mg/L lognormal 0.96 0.56 2 - - 9 0 0









Table VI-11 Water Quality in the Athabasca River, Upstream of Fort McMurray (Fall) (continued)

Golder Associates

Sample Size




Non-Detects

Number of

Outliers














Tainting Potential

tainting potential TPU none(c) 0 0 0 - - - - - (a) Proportion of data that were reported as less than the method detection limit (MDL). (b) Average of all MDL values; reported as half the MDL. (c) No information available, so assumed to be zero in natural surface waters. (d) The distribution was set to zero if all values were reported as less than the MDL. Source: based on information from Alberta Environment WDS stations: AB07CC0030/DA1470 (AENV 2004b).


Golder Associates

Table VI-12 Water Quality in the Athabasca River, Upstream of the Steepbank River (Annual)

Sample Size




Non-Detects

Number of

Outliers




Major Ions


chloride mg/L delta lognormal 12 12 35 0.01 1 155 2 0



sulphate mg/L delta lognormal 25 12 48 0.01 5.4 142 2 0


Nutrients




Toxicity



General Organics



Metals (Total)

















Table VI-12 Water Quality in the Athabasca River, Upstream of the Steepbank River (Annual) (continued)

Golder Associates

Sample Size




Non-Detects

Number of

Outliers
















Tainting Potential

tainting potential TPU none(c) 0 0 0 - - - - - (a) Proportion of data that were reported as less than the method detection limit (MDL). (b) Average of all MDL values; reported as half the MDL. (c) No information available, so assumed to be zero in natural surface waters. (d) The distribution was set to zero if all values were reported as less than the MDL. Source: based on information from Golder (1996b, 1998, 2001a, 2002a, 2003), RAMP (2004) and from Alberta Environment WDS

stations: AB07DA0090\0100\0140\0150\0155\0160\0170\0180\0190\1500 (AENV 2004b).


Golder Associates

Table VI-13 Water Quality in the Clearwater River (Winter) Sample Size




Non-Detects

Number ofOutliers




Major Ions







Nutrients

nitrogen - ammonia mg/L delta lognormal 0.07 0.02 0.10 0.07 0.005 15 1 0

nitrogen, total mg/L lognormal 0.6 0.2 1 - - 29 0 0


Toxicity



General Organics



Metals (Total)


















Table VI-13 Water Quality in the Clearwater River (Winter) (continued)

Golder Associates

Sample Size




Non-Detects

Number ofOutliers















Tainting Potential


(a) Proportion of data that were reported as less than the method detection limit (MDL). (b) Average of all MDL values; reported as half the MDL. (c) No information available, so assumed to be zero in natural surface waters.

(d) The distribution was set to zero if all values were reported as less than the MDL. Source: based on information from Golder (2002a, 2003), RAMP (2004) and from Alberta Environment WDS stations:

AB07CD0100/0210(AENV 2004b).


Golder Associates

Table VI-14 Water Quality in the Clearwater River (Spring) Sample Size




Number of Outliers

Conventional Constituents dissolved organic carbon mg/L normal 9 2 12 - - 12 0 0


Major Ions







Nutrients

nitrogen - ammonia mg/L none(c) 0.0 0.0 0.0 - - 3 3 -

nitrogen, total mg/L lognormal 1 0.9 2.7 - - 10 0 0


Toxicity



General Organics



Metals (Total)


















Table VI-14 Water Quality in the Clearwater River (Spring) (continued)

Golder Associates



Standard Deviation


Number of Outliers















Tainting Potential

tainting potential TPU none(d) 0 0 0 - - - - - (a) Proportion of data that were reported as less than the method detection limit (MDL). (b) Average of all MDL values; reported as half the MDL. (c) The distribution was set to zero if all values were reported as less than the MDL. (d) No information available, so assumed to be zero in natural surface waters. Source: based on information from Golder (2002a, 2003), RAMP (2004) and from Alberta Environment WDS stations:

AB07CD0100/0210(AENV 2004b).


Golder Associates

Table VI-15 Water Quality in the Clearwater River (Summer) Sample Size




Non-detects

Number of

Outliers




Major Ions







Nutrients


lognormal 0.02 0.02 0.05 0.6 0.022 5 3 0

nitrogen, total mg/L normal 0.7 0.2 1 - - 24 0 3


Toxicity



General Organics



Metals (Total)



















Table VI-15 Water Quality in the Clearwater River (Summer) (continued)

Golder Associates

Sample Size




Non-detects

Number of

Outliers














Tainting Potential

tainting potential TPU none(c) 0 0 0 - - - - - (a) Proportion of data that were reported as less than the method detection limit (MDL). (b) Average of all MDL values; reported as half the MDL. (c) No information available, so assumed to be zero in natural surface waters. (d) The distribution was set to zero if all values were reported as less than the MDL. Source: based on information from Golder (2002a, 2003), RAMP (2004) and from Alberta Environment WDS stations:

AB07CD0100/0210(AENV 2004b).


Golder Associates

Table VI-16 Water Quality in the Clearwater River (Fall) Sample Size




Non-Detects

Number of

Outliers




major ions







Nutrients

nitrogen - ammonia mg/L none(c) 0 0 0 - - 4 4 -

nitrogen, total mg/L delta lognormal 0.6 0.2 1 0.06 0.1 18 1 0


Toxicity



General Organics



Metals (Total)







cadmium (Cd) mg/L none(c) 0 0 0 - - 8 8 -



iron (Fe) mg/L lognormal 1 0.59 2.17 - - 4 0 0




molybdenum (Mo) mg/L delta lognormal 0.0003 0.0003 0.0009 0.57 0.0003 7 4 0




Table VI-16 Water Quality in the Clearwater River (Fall) (continued)

Golder Associates

Sample Size




Non-Detects

Number of

Outliers

silver (Ag) mg/L none(c) 0 0 0 - - 4 4 -














Tainting Potential


AB07CD0100/0210(AENV 2004b).


Golder Associates

Table VI-17 Water Quality in the Ells River (Winter) Sample Size




Non-Detects

Number Of

Outliers




Major Ions







Nutrients


nitrogen, total mg/L lognormal 0.7 0.2 1 - - 14 0 0


Toxicity



General Organics



Metals (Total)



















Table VI-17 Water Quality in the Ells River (Winter) (continued)

Golder Associates

Sample Size




Non-Detects

Number Of

Outliers














Tainting Potential

tainting potential TPU none(c) 0 0 0 - - - - - (a) Proportion of data that were reported as less than the method detection limit (MDL). (b) Average of all MDL values; reported as half the MDL. (c) No information available, so assumed to be zero in natural surface waters. (d) The distribution was set to zero if all values were reported as less than the MDL. Source: based on information from RAMP (2004) and from Alberta Environment WDS stations: AB07DA1240/1250/0750 (AENV 2004).


Golder Associates

Table VI-18 Water Quality in the Ells River (Spring) Sample Size


Distribution Average StandardDeviation


Non-Detects

Number of

Outliers




Major Ions







Nutrients




Toxicity



General Organics

naphthenic acids mg/L delta lognormal 0.5 0.5 1.5 0.75 0.5 4 3 0


Metals (Total)
















selenium (Se) mg/L none(c) 0 0 0 - - 4 4 -




Table VI-18 Water Quality in the Ells River (Spring) (continued)

Golder Associates

Sample Size




Non-Detects

Number of

Outliers













Tainting Potential

tainting potential TPU none(d) 0 0 0 - - - - - (a) Proportion of data that were reported as less than the method detection limit (MDL). (b) Average of all MDL values; reported as half the MDL. (c) The distribution was set to zero, if all values were reported as less than the MDL. (d) No information available, so assumed to be zero in natural surface waters. Source: based on information from Golder (1999b, 2002a, 2003), RAMP 2004 and from Alberta Environment WDS stations:

AB07DA1240 (AENV 2004b).


Golder Associates

Table VI-19 Water Quality in the Ells River (Summer) Sample Size




Non-Detects

Number ofOutliers




Major Ions







Nutrients




Toxicity



General Organics



Metals (Total)













mercury (Hg) mg/L none(c) 0 0 0 - - 9 9 -




Table VI-19 Water Quality in the Ells River (Summer) (continued)

Golder Associates

Sample Size




Non-Detects

Number ofOutliers
















Tainting Potential


AB07DA1240/0750 (AENV 2004b).


Golder Associates

Table VI-20 Water Quality in the Ells River (Fall) Sample Size




Non-Detects

Number ofOutliers




major ions







Nutrients




Toxicity



General Organics



Metals (Total)



arsenic (As) mg/L delta lognormal 0.0005 0.0004 0.0013 0.6 0.0005 5 3 0


beryllium (Be) mg/L none(c) 0 0 0 - - 4 4 -















Table VI-20 Water Quality in the Ells River (Fall) (continued)

Golder Associates

Sample Size




Non-Detects

Number ofOutliers













Tainting Potential

tainting potential TPU none(d) 0 0 0 - - - - - (a) Proportion of data that were reported as less than the method detection limit (MDL). (b) Average of all MDL values; reported as half the MDL. (c) The distribution was set to zero if all values were reported as less than the MDL. (d) No information available, so assumed to be zero in natural surface waters. Source: based on information from Golder (1999a, 2002a, 2003), RAMP 2004 and from Alberta Environment WDS stations:

AB07DA1240/0750 (AENV 2004b).


Golder Associates

Table VI-21 Water Quality in the Firebag River (Ice Cover) Sample Size




Non-Detects

Number ofOutliers




major ions


chloride mg/L normal 2.4 0.4 3.0 - - 29 0 2





Nutrients




Toxicity



General Organics



Metals (Total)


















Table VI-21 Water Quality in the Firebag River (Ice Cover) (continued)

Golder Associates

Sample Size




Non-Detects

Number ofOutliers

Silver (Ag) mg/L delta lognormal 0.0006 0.0008 0.002 0.5 0.00002 6 3 0














Tainting Potential

tainting potential TPU none(c) 0 0 0 - - - - - (a) Proportion of data that were reported as less than the method detection limit (MDL). (b) Average of all MDL values; reported as half the MDL. (c) No information available, so assumed to be zero in natural surface waters. (d) The distribution was set to zero if all values were reported as less than the MDL. Source: based on information from Golder (1999a, 2003), RAMP 2004 and from Alberta Environment WDS stations:

AB07DC0060/0090/0100/0110 (AENV 2004b).


Golder Associates

Table VI-22 Water Quality in the Firebag River (Open Water) Sample Size




Non-Detects

Number of

Outliers




Major Ions







Nutrients




Toxicity



General Organics



Metals (Total)




















Table VI-22 Water Quality in the Firebag River (Open Water) (continued)

Golder Associates

Sample Size




Non-Detects

Number of

Outliers













Tainting Potential

tainting potential TPU none(c) 0 0 0 - - - - - (a) Proportion of data that were reported as less than the method detection limit (MDL). (b) Average of all MDL values; reported as half the MDL. (c) No information available, so assumed to be zero in natural surface waters. Source: based on information from Golder (1999a, 2003), RAMP (2004) and from Alberta Environment WDS stations:

AB07DC0100/0110 (AENV 2004b).


Golder Associates

Table VI-23 Water Quality in the Mackay River (Ice Cover) Sample Size




Non-Detects

Number of

Outliers




major ions







Nutrients




Toxicity



General Organics



Metals (Total)


antimony (Sb) mg/L none(d) 0 0 0 - - 1 1 -











mercury (Hg) mg/L none (d) 0 0 0 - - 14 14 -



selenium (Se) mg/L none(d) 0 0 0 - - 3 3 -




Table VI-23 Water Quality in the Mackay River (Ice Cover) (continued)

Golder Associates

Sample Size




Non-Detects

Number of

Outliers













Tainting Potential

tainting potential TPU none(c) 0 0 0 - - - - - (a) Proportion of data that were reported as less than the method detection limit (MDL). (b) Average of all MDL values; reported as half the MDL. (c) No information available, so assumed to be zero in natural surface waters. (d) The distribution was set to zero if all values were reported as less than the MDL. Source: based on information from Golder (2003) and from Alberta Environment WDS stations: AB07DB0060/0070 (AENV 2004b).


Golder Associates

Table VI-24 Water Quality in the Mackay River (Open Water) Sample Size




Non-Detects

Number ofOutliers




major ions







Nutrients


lognormal 0.03 0.03 0.09 0.5 0.026 8 4 0



Toxicity


toxicity - chronic TUc none(d) 0 0 0 - - 1 0 0

General Organics



Metals (Total)







cadmium (Cd) mg/L none(c) 0 0 0 - - 8 8 -











Table VI-24 Water Quality in the Mackay River (Open Water) (continued)

Golder Associates

Sample Size




Non-Detects

Number ofOutliers











PAH Group 6 µg/L none(e) 0 0 0 - - 0 0 0




Tainting Potential

tainting potential TPU none(e) 0 0 0 - - - - - (a) Proportion of data that were reported as less than the method detection limit (MDL). (b) Average of all MDL values; reported as half the MDL. (c) The distribution was set to zero if all values were reported as less than the MDL. (d) Assumed that observed toxicity was related to humic or other similar materials that are not released or influenced by mine operations. (e) No information available, so assumed to be zero in natural surface waters. Source: based on information from Golder (1999a, 2001a, 2002a, 2003), RAMP (2004) and from Alberta Environment WDS stations:

AB07DB0060/0300 (AENV 2004b).


Golder Associates

Table VI-25 Suncor Surficial Aquifer Water Quality Sample Size




Non-Detects

Number ofOutliers




Major Ions


chloride mg/L delta lognormal 6 10 24 0.22 0.17 46 10 0





Nutrients

nitrogen - ammonia mg/L none(c) 0.0 0.0 0.0 - - 0 0 -

nitrogen, total mg/L none(c) 0 0 0 - - 0 0 -

phosphorus, total mg/L delta lognormal 0.35 0.71 1.55 0.45 0.05 33 15 0

Toxicity



General Organics


total phenolics mg/L none(d) 0 0 0 - - 7 7 -

Metals (Total)






boron (B) mg/L normal 0.42 0.18 0.73 - - 22 0 0














Table VI-25 Suncor Surficial Aquifer Water Quality (continued)

Golder Associates

Sample Size




Non-Detects

Number ofOutliers













Tainting Potential

tainting potential TPU none(c) 0 0 0 - - - - - (a) Proportion of data that were reported as less than the method detection limit (MDL). (b) Average of all MDL values; reported as half the MDL. (c) No information available then the distribution was assumed to be zero. (d) The distribution was set to zero if all values were reported as less than the MDL. Source: based on information from Klohn-Crippen (1996, 1998a) and Golder (2005b).


Golder Associates

Table VI-26 Suncor Basal Water Quality Sample Size




Non-Detects

Number of

Outliers




Major Ions







Nutrients




Toxicity



General Organics

naphthenic acids mg/L lognormal 18.3 8.1 34 - - 18 0 0


Metals (Total)










iron (Fe) mg/L delta lognormal 1.19 2.41 6.42 0.33 0.0049 42 14 0







Table VI-26 Suncor Basal Water Quality (continued)

Golder Associates

Sample Size




Non-Detects

Number of

Outliers
















Tainting Potential

tainting potential TPU none(c) 0 0 0 - - - - - (a) Proportion of data that were reported as less than the method detection limit (MDL). (b) Average of all MDL values; reported as half the MDL. (c) No information available then the distribution was assumed to be zero. Source: based on information from Klohn-Crippen (1996, 1998a) and Golder (2005b).


Golder Associates

Table VI-27 Tailings Pond Water Quality

Sample Size




Non-Detects

Number of

Outliers




Major Ions







Nutrients




Toxicity

toxicity - acute TUa normal 13.5 7.1 25.8 - - 19 0 0

toxicity - chronic(c) TUc normal 28.3 12.0 48.5 - - 0 0 -

General Organics

naphthenic acids mg/L uniform 100 11.5 80-120(d) - - 2 0 -


Metals (Total)





beryllium (Be) mg/L lognormal 0.0013 0.0016 0.0045 - - 11 11 -










Table VI-27 Tailings Pond Water Quality (continued)

Golder Associates

Sample Size




Non-Detects

Number of

Outliers

molybdenum (Mo) mg/L normal 0.69 0.36 1.32 - - 74 2 0



silver (Ag) mg/L delta lognormal 0.00011 0.00012 0.00035 0.42 0.000095 17 17 -





PAH Group 1 µg/L lognormal 0 0 0 - - 2 2 -


PAH Group 3 µg/L none(e) 0 0 0 - - 2 2 -


PAH Group 5 µg/L normal 0 0 0 - - 2 2 -



PAH Group 8 µg/L delta lognormal 0 0 0 0.39 0.042 2 2 -


Tainting Potential

tainting potential TPU uniform 46 85 173 - - - - -

(a) Proportion of data that were reported as less than the method detection limit (MDL). (b) Average of all MDL values; reported as half the MDL. (c) The average was calculated from the acute toxicity:chronic toxicity ratio observed in the process-affected waters; standard deviation

was calculated based on the coefficient of variation observed in process-affected waters. (d) reported as the range of the uniform distribution (i.e., minimum - maximum). (e) The distribution was set to zero if all values were reported as less than the MDL. Source: based on information from EVS (1989, 1990, 1992, 1993), Nix (1982, 1983), Noton (1980), Nelson et al. (1993), FTFC

(1995), MacKinnon (1981), MacKinnon et al. (1982), MacKinnon and Benson (1985) and Zenon (1986).


Golder Associates

Table VI-28 Process Affected Water Quality Sample Size




Non-Detects

Number ofOutliers




Major Ions







Nutrients




Toxicity


toxicity - chronic TUc normal 4.6 1.9 7.8 - - 18 0 1

General Organics

naphthenic acids mg/L normal 68.3 15.5 93.9 - - 60 0 0


Metals (Total)


antimony (Sb) mg/L normal 0.0054 0.0036 0.012 - - 10 4 0








iron (Fe) mg/L delta lognormal 0.51 0.85 2 0.33 0.018 40 13 0











Table VI-28 Process Affected Water Quality (continued)

Golder Associates

Sample Size




Non-Detects

Number ofOutliers









PAH Group 7 µg/L lognormal 0.25 0.49 1 - - 23 13 0



Tainting Potential

tainting potential TPU uniform 46 85 173 - - - - - (a) Proportion of data that were reported as less than the method detection limit (MDL). (b) Average of all MDL values; reported as half the MDL. (c) The distribution was set to zero if all values were reported as less than the MDL. Source: based on information from Golder (1996a, 1997a, 1997b, 1999b, 2000b, 2001b, 2001c, 2002b, 2005c), Klohn-Crippen

(1998b), Cooper (2004), HydroQual (1996), BOVAR (1996), Suncor (1995), Albian (1999) and NAQUADAT stations 20AL07DA1003/1004/1011.


Golder Associates

Table VI-29 Process Affected Seepage Quality Sample Size




Non-Detects

Number ofOutliers




Major Ions







Nutrients




Toxicity


toxicity - chronic TUc normal 4.6 1.9 7.8 - - 18 0 1

General Organics

naphthenic acids mg/L normal 68.3 15.5 93.9 - - 60 0 0


Metals (Total)


















Table VI-29 Process Affected Seepage Quality (continued)

Golder Associates

Sample Size




Non-Detects

Number ofOutliers















Tainting Potential

tainting potential TPU uniform 46 85 173 - - - - - (a) Proportion of data that were reported as less than the method detection limit (MDL). (b) Average of all MDL values; reported as half the MDL. (c) The distribution was set to zero if all values were reported as less than the MDL. Source: based on information from Golder (1996a, 1997a, 1997b, 1999b, 2000b, 2001b, 2001c, 2002b, 2005c), Klohn-Crippen (1998b),

Cooper (2004), HydroQual (1996), BOVAR (1996), Suncor (1995), Albian (1999) and NAQUADAT stations 20AL07DA1003/1004/1011.


Golder Associates

Table VI-30 Mature Fine Tailings Seepage Quality Sample Size




Non-Detects

Number of

Outliers

Conventional Constituents(c)



Major Ions(c)







Nutrients

nitrogen - ammonia(c) mg/L lognormal 8.4 8.1 23.8 - - 70 0 0

nitrogen, total(c) mg/L normal 13.2 5.7 22.9 - - 13 0 0

phosphorus, total(d) mg/L lognormal 0.13 0.2 0.46 - - 51 5 0

Toxicity

toxicity - acute(c) TUa normal 13.5 7.1 25.8 - - 19 0 0

toxicity - chronic(e) TUc normal 28.3 12.0 48.5 - - 0 0 -

General Organics(c)

naphthenic acids mg/L uniform 100 11.5 80-120(c) - - 2 0 -


Metals (Total)(d)


















Table VI-30 Mature Fine Tailings Seepage Quality (continued)

Golder Associates

Sample Size




Non-Detects

Number of

Outliers





Target PAHs and Alkylated PAHs(f)



PAH Group 3 µg/L none 0 0 0 - - 24 24 -







Tainting Potential

tainting potential TPU uniform 46 85 173 - - - - - (a) Proportion of data that were reported as less than the method detection limit (MDL). (b) Average of all MDL values; reported as half the MDL. (c) Statistics were assumed to be equal to the tailings pond water dataset. (d) Statistics were assumed to be equal to process-affected seepage dataset. (e) The average was calculated from the acute toxicity:chronic toxicity ratio observed in the process-affected waters; standard deviation

was calculated based on the coefficient of variation observed in process-affected waters. (f) Statistics were assumed to be process-affected water dataset.


Golder Associates

Table VI-31 Mature Fine Tailings Flux Water Quality Sample Size




Non-Detects

Number ofOutliers

Conventional Constituents(c)



Major Ions(c)







Nutrients

nitrogen - ammonia(c) mg/L lognormal 8.4 8.1 23.8 - - 70 0 0

nitrogen, total(c) mg/L normal 13.2 5.7 22.9 - - 13 0 0

phosphorus, total(d) mg/L lognormal 0.13 0.2 0.46 - - 48 15 0

Toxicity

toxicity - acute(c) TUa normal 13.5 7.1 25.8 - - 19 0 0

toxicity - chronic(e) TUc 28.3 12.0 48.5 - - 0 0 - -

General Organics(c)

naphthenic acids mg/L uniform 100 11.5 80-120(c) - - 2 0 -


Metals (Total)(d)


antimony (Sb) mg/L normal 0.0054 0.0036 0.012 - - 10 4 0








iron (Fe) mg/L delta lognormal 0.51 0.85 2 0.33 0.018 40 13 0











Table VI-31 Mature Fine Tailings Flux Water Quality (continued)

Golder Associates

Sample Size




Non-Detects

Number ofOutliers


Target PAHs and Alkylated PAHs(d)










Tainting Potential

tainting potential TPU uniform(d) 46 85 173 - - - - - (a) Proportion of data that were reported as less than the method detection limit (MDL). (b) Average of all MDL values; reported as half the MDL. (c) Statistics were assumed to be equal to the tailings pond water dataset. (d) Statistics were assumed to be equal to process-affected water dataset. (e) The average was calculated from the acute toxicity:chronic toxicity ratio observed in the process-affected waters; standard deviation

was calculated based on the coefficient of variation observed in process-affected waters.


Golder Associates

Table VI-32 Fort McMurray Sewage Effluent Water Quality Sample Size




Non-Detects

Number of

Outliers




Major Ions







Nutrients

nitrogen - ammonia mg/L lognormal(d) 5 5 16 - - 9 0 -

nitrogen, total mg/L lognormal(d) 13.7 5.3 25 - - 18 0 -

phosphorus, total mg/L lognormal(d) 0.9 0.8 2.5 - - 17 0 -

Toxicity



General Organics



Metals (Total)


antimony (Sb) mg/L none(c) 0 0 0 - - 0 0 -



beryllium (Be) mg/L none(e) 0 0 0 - - 1 1 -

boron (B) mg/L none(c) 0 0 0 - - 0 0 -












strontium (Sr) mg/L none(c) 0 0 0 - - 0 0 -


Table VI-32 Fort McMurray Sewage Effluent Water Quality (continued)

Golder Associates

Sample Size




Non-Detects

Number of

Outliers













Tainting Potential

tainting potential TPU none(c) 0 0 0 - - - - - (a) Proportion of data that were reported as less than the method detection limit (MDL). (b) Average of all MDL values; reported as half the MDL. (c) No information available, so the distribution was assumed to be zero. (d) Distributions defined using monitoring data collected from the Gold Bar Waste Water Treatment Plant between 1994 and 2003 (J.

Heise, City of Edmonton, personal communication). (e) The distribution was set to zero, if all values were reported as less than the MDL. Source: based on information from Alberta Environment WDS stations: AB07DA2660/2670 (AENV 2004b).


Golder Associates

Table VI-33 Suncor Site Drainage Water Quality Sample Size




Non-Detects

Number ofOutliers




Major Ions







Nutrients




Toxicity


toxicity - chronic TUc delta

lognormal 1.92 2.15 6.29 0.57 1 7 4 0

general organics

naphthenic acids mg/L lognormal 5.4 3 11.1 - - 13 0 0


Metals (Total)







cadmium (Cd) mg/L normal 0.0017 0.0008 0.003 - - 16 12 0





manganese (Mn) mg/L lognormal 0.25 0.5 1 - - 16 0 0





Table VI-33 Suncor Site Drainage Water Quality (continued)

Golder Associates

Sample Size




Non-Detects

Number ofOutliers
















Tainting Potential

tainting potential TPU none(d) 0 0 0 - - - - -

(a) Proportion of data that were reported as less than the method detection limit (MDL). (b) Average of all MDL values; reported as half the MDL. (c) The distribution was set to zero, if all values were reported as less than the MDL. (d) No information available, so the distribution was assumed to be zero. Source: based on information from Golder (1996a).


Golder Associates

Table VI-34 Suncor Cooling Water Quality Sample Size




Non-Detects

Number ofOutliers




Major Ions







Nutrients


lognormal 0.05 0.04 0.13 0.08 0.01 13 1 0



Toxicity


toxicity - chronic TUc lognormal 1.61 0.93 3.43 - - 4 0 0

General Organics



Metals (Total)











lead (Pb) mg/L none(d) 0 0 0 - - 3 3 -






Table VI-34 Suncor Cooling Water Quality (continued)

Golder Associates

Sample Size




Non-Detects

Number ofOutliers
















Tainting Potential


(a) Proportion of data that were reported as less than the method detection limit (MDL). (b) Average of all MDL values; reported as half the MDL. (c) No information available, so the distribution was assumed to be zero. (d) The distribution was set to zero, if all values were reported as less than the MDL. Source: based on information from Golder (1996a) and NAQUADAT station 20AL07DA1013.


Golder Associates

Table VI-35 Suncor Sewage Water Quality Sample Size




Non-Detects

Number of

Outliers




Major Ions







Nutrients




Toxicity

toxicity - acute TUa lognormal 1.24 0.72 2.62 - - 1 0 0


General Organics



Metals (Total)


















Table VI-35 Suncor Sewage Water Quality (continued)

Golder Associates

Sample Size




Non-Detects

Number of

Outliers















Tainting Potential


(a) Proportion of data that were reported as less than the method detection limit (MDL). (b) Average of all MDL values; reported as half the MDL. (c) No information available, so the distribution was assumed to be zero. (d) The distribution was set to zero if all values were reported as less than the MDL. Source: based on information from Golder (1996a) and NAQUADAT station 20AL07DA1005.


Golder Associates

Table VI-36 Suncor Wastewater Quality Sample Size




Non-Detects

Number ofOutliers




Major Ions







Nutrients




Toxicity



General Organics



Metals (Total)





beryllium (Be) mg/L normal 0.0011 0.0005 0.002 - - 43 41 0









molybdenum (Mo) mg/L delta

lognormal 0.17 0.15 0.49 0.02 0.00625 89 2 0


Table VI-36 Suncor Wastewater Quality (continued)

Golder Associates

Sample Size




Non-Detects

Number ofOutliers

















Tainting Potential


(a) Proportion of data that were reported as less than the method detection limit (MDL). (b) Average of all MDL values; reported as half the MDL. (c) No information available, so the distribution was assumed to be zero. (d) The distribution was set to zero if all values were reported as less than the MDL. Source: based on information from Golder (1996a), HydroQual (1996), NAQUADAT stations 20AL07DA1000/1001 and Suncor (2003).


Golder Associates

Table VI-37 Muskeg and Overburden Dewatering Water Quality - Muskeg River Mine

Sample Size




Non-Detects

Number ofOutliers




Major Ions







Nutrients




Toxicity

toxicity - acute TUa none(c) 0 0 0 - - 48 5 0

toxicity - chronic TUc none(c) 0 0 0 - - 14 9 0

General Organics



Metals (Total)










iron (Fe) mg/L delta lognormal 1.0 2.6 4.8 0.15 0.005 79 12 0


manganese (Mn) mg/L delta lognormal 0.35 0.55 1.53 0.11 0.002 79 9 0



Table VI-37 Muskeg and Overburden Dewatering Water Quality - Muskeg River Mine (continued)

Golder Associates

Sample Size




Non-Detects

Number ofOutliers











PAH Group 3 µg/L none 0 0 0 - - 20 20 -







Tainting Potential

tainting potential TPU none(d) 0 0 - - - - - (a) Proportion of data that were reported as less than the method detection limit (MDL). (b) Average of all MDL values; reported as half the MDL. (c) The distribution was set to zero, if all values were reported as less than the MDL. (d) No information available, so the distribution was assumed to be zero. Source: based on information from Albian (2002), Suncor (2003) and Syncrude (1998).


Golder Associates

Table VI-38 CNRL Basal Water Quality Sample Size



95th Percentile Delta(a) D(b)

All Non-

detects Number of

Outliers



total dissolved solids mg/L normal 83,276 55,963 188,049 - - 11 0 0

Major Ions


chloride mg/L normal 51,278 34,459 11,6338 - - 11 0 0


sodium mg/L normal 30,440 20,292 68,589 - - 11 0 0

sulphate mg/L normal 1,428 981 3,287 - - 11 1 0

sulphide mg/L lognormal 25 14 52 - - 1 0 0

Nutrients




Toxicity



General Organics


total phenolics mg/L none 0 0 0 - - 0 0 -

Metals (Total)






















Table VI-38 CNRL Basal Water Quality (continued)

Golder Associates

Sample Size



95th Percentile Delta(a) D(b)

All Non-

detects Number of

Outliers











Tainting Potential


(a) Proportion of data that were reported as less than the method detection limit (MDL). (b) Average of all MDL values; reported as half the MDL. (c) No information available, so the distribution was assumed to be zero. (d) The distribution was set to zero, if all values were reported as less than the MDL. Source: based on information from CNRL (2002).


Golder Associates

Table VI-39 Shell Basal Water Quality Sample Size




Number of

Outliers



mg/L lognormal 8 8 23 - - 23 0 0

total dissolved solids

mg/L normal 3,283 1,538 5,915 - - 95 0 0

Major Ions


chloride mg/L lognormal 842 1,042 3268 - - 101 0 0


sodium mg/L lognormal 888 1,160 3,255 - - 41 0 0


sulphide mg/L delta lognormal 5 10 27 0.03 0.0025 35 1 0

Nutrients




Toxicity

toxicity - acute TUa delta

lognormal 1.4 1.7 5 0.67 1 6 4 0

toxicity - chronic TUc lognormal 8.3 4.8 17.6 3 0 0

General Organics



Metals (Total)





beryllium (Be) mg/L none 0 0 0 - - 8 8 -


cadmium (Cd) mg/L none(d) 0 0 0 - - 23 23 -







Table VI-39 Shell Basal Water Quality (continued)

Golder Associates

Sample Size




Number of

Outliers



lognormal 0.0076 0.013 0.037 0.75 0.0025 8 6 0



silver (Ag) mg/L normal 0.0070 0.0037 0.013 - - 29 17 0














Tainting Potential


(a) Proportion of data that were reported as less than the method detection limit (MDL). (b) Average of all MDL values; reported as half the MDL. (c) No information available, so the distribution was assumed to be zero. (d) The distribution was set to zero, if all values were reported as less than the MDL. Source: based on information from Komex (2002, 2005) and Imperial (2005).


Golder Associates

Table VI-40 TrueNorth Basal Water Quality Sample Size




Non-Detects

Number of

Outliers



mg/L lognormal 13 8 28 - - 2 0 0

total dissolved solids mg/L lognormal 52,425 5,113 61,223 - - 27 0 0

Major Ions

calcium mg/L normal 1,098 280 1559 - - 28 0 0

chloride mg/L normal 28,849 3,200 34,170 - - 25 0 0


sodium mg/L normal 18,213 2,032 21,550 - - 28 0 0

sulphate mg/L normal 3,238 651 4,307 - - 28 0 0


Nutrients



phosphorus, total mg/L none(d) 0 0 0 - - 0 0 -

toxicity

toxicity - acute TUa none(e) 0 0 0 4 1 -

toxicity - chronic TUc delta

lognormal 12.8 9.8 31.7 0.5 11 4 2 0

general organics



Metals (Total)





beryllium (Be) mg/L none(c) 0 0 0 - - 29 29 -










Table VI-40 TrueNorth Basal Water Quality (continued)

Golder Associates

Sample Size




Non-Detects

Number of

Outliers


lognormal 0.022 0.059 0.11 0.62 0.0025 29 18 0



silver (Ag) mg/L none 0 0 0 - - 29 29 -














Tainting Potential

tainting potential TPU none(d) 0 0 0 - - - - -

(a) Proportion of data that were reported as less than the method detection limit (MDL). (b) Average of all MDL values; reported as half the MDL. (c) The distribution was set to zero, if all values were reported as less than the MDL. (d) No information available, so the distribution was assumed to be zero. (e) The distribution was set to zero, because the acute toxicity was primarily associated with sulphide, which will be removed through treatment. Source: based on information from Clifton (2001) and TrueNorth (2001).


Golder Associates

VI-3 REFERENCES

AENV. 2004a. Final Terms of Reference Environmental Impact Assessment (EIA) Report for the Suncor Energy Voyageur Project. Issued by Alberta Environment. December, 2004.

AENV. 2004b. Data obtained from AENV Water Data System. Environmental Service, Environmental Sciences Division, Edmonton, AB.


Albian (Albian Sands Energy Inc.). 1999. Unpublished Data Used in the Shell Jackpine – Phase 1 EIA.

Albian. 2002. Unpublished data collected in support of EPEA Approval #20809-00-01.

Beckman, R.J., and R.D. Cook. 1983. Outliers. Technometrics, 25: 119-149.

BOVAR (Bovar Environmental Ltd.). 1996. Environmental impact assessment for the Syncrude Canada Limited Aurora Mine. Report prepared for Syncrude Canada Limited.

Clifton (Clifton Associates Ltd.). 2001. Technical Supporting Document. Hydrogeology Baseline Study. Fort Hills Oil Sands Project. Prepared for TrueNorth Energy. Calgary, AB.

Cooper, N.J. 2004. Vegetation Community Development of Reclaimed Oil Sands Wetlands. MSc. Thesis, University of Alberta, Edmonton, AB.

Davies, L. and U. Gather. 1993. The Identification of Multiple Outliers. Journal of the American Statistical Association, 88: 782-801.

Dixon, W.J. 1950. Analysis of Extreme Values. Annals of Mathematical Statistics, 22: 488-506.

Dixon, W.J. 1951. Ratios Involving Extreme Values. Annals of Mathematical Statistics, 22: 68-78.


Golder Associates

Dixon, W.J. 1953. Processing Data for Outliers. Biometrics, 9: 74-89.

EVS (EVS Consultants Ltd.). 1989. Tailing Pond Water and Sludge: Disposal and Reclamation. Summary Report.

EVS. 1990. Water Quality Inventory of Tailings Ponds and Assessment of In-situ Experiment Tanks. Proj. No. 3/144-07.

EVS. 1992. Chemical and Toxicological Characteristics of Interstitial Water and Fine Tails. Final Report.

EVS. 1993. Natural Wetlands for the Treatment of Leachate From Oil Sands Tailings Ponds. Technical Report #1.

FTFC (Fine Tailings Fundamentals Consortium). 1995. Advances in oils sands tailings research, Volume VI: Fine tails and process water reclamation. Alberta Department of Energy Oil Sands and Research Division.

Gilbert, R.O. 1987. Statistical Methods for Environmental Pollution Monitoring. John Wiley & Sons, New York.

Golder (Golder Associates Ltd.) 1996a. Athabasca River water releases impact assessment. Prepared for Suncor Oil Sands Group. For McMurray, AB.

Golder. 1996b. Aquatic baseline report for the Athabasca, Steepbank and Muskeg Rivers in the vicinity of the Steepbank and Aurora Mines. Prepared for: Suncor Inc., Oil Sands Group and Syncrude Canada Ltd. Calgary, AB.

Golder. 1997a. Synthesis of Environmental Information on Consolidate/ Composite Tailings (CT). Prepared for Suncor Energy Inc. Fort McMurray, AB.

Golder. 1997b. A limnological survey of Suncor’s Pond 5 East. Prepared for Suncor Energy Inc., Calgary, AB.

Golder. 1998. Oil Sands Regional Aquatics Monitoring Program (RAMP). 1997 Report. Prepared for Suncor Energy Inc., Shell Canada Limited and Syncrude Canada Ltd. Fort McMurray, AB.

Golder. 1999a. Oil Sands Regional Aquatics Monitoring Program (RAMP): Field Technical Procedures. Final Report for the RAMP Steering Committee.


Golder Associates

Golder. 1999b. The Effects of Consolidated Tailings Release Water and Deposits on Terrestrial and Wetlands Ecosystems. Prepared for Suncor Inc., Oil Sands Group. Golder Project Report No. 982-2243. Calgary, AB.

Golder. 2000a. Oil Sands Regional Aquatics Monitoring Program (RAMP) 1999. Final Report for the RAMP Steering Committee.

Golder. 2000b. Assessment of Trophic Level and Fish Health Effects of Oil Sands CT Water. Submitted to Suncor Energy Inc., Oil Sands, Syncrude Canada Ltd., Albian Sands Energy Inc., Mobil Oil Canada Properties Ltd., Koch Canada Ltd.

Golder. 2001a. Oil Sands Regional Aquatics Monitoring Program (RAMP) 2000. Volume VI: Climate and Hydrologic Monitoring. Prepared for the RAMP Steering Committee, Fort McMurray, AB.

Golder. 2001b. Consolidation Tailings (CT) Integrated Reclamation Landscape Demonstration Project: Technical Report #1 - Year 2000 : Summary Report. Prepared for Suncor Inc. Golder Project Report No. 002-2249. Calgary, AB.

Golder. 2001c. Base Mine Lake Water Quality Modelling Study. Report Submitted to Syncrude Canada Ltd., Fort McMurray, AB.

Golder. 2002a. Oil Sands Regional Aquatics Monitoring Program (RAMP) 2001. Volume I: Chemical and Biological Monitoring. Volume VI: Climatic and Hydrologic Monitoring. Submitted to RAMP Steering Committee. April 2002.

Golder. 2002b. Consolidation Tailings (CT) Integrated Reclamation Landscape Demonstration Project: Technical Report #2 - Year 2001 : Final. Prepared for Suncor Inc. Golder Project Report No. 012-2226. Calgary, AB.

Golder. 2003. Oil Sands Regional Aquatics Monitoring Program (RAMP) 2002. Submitted to the RAMP Steering Committee. March 2003.

Golder. 2005a. Water Quality Environmental Setting Report for the Suncor Voyageur Project. Prepared for Suncor Energy Inc. March 2005. Calgary, AB.


Golder Associates

Golder. 2005b. Hydrogeology Environmental Setting Report for the Suncor Voyageur Project. Prepared for Suncor Energy Inc. March 2005. Calgary, AB.

Golder. 2005c. Consolidated Tailings (CT) Integrated Reclamation Landscape Demonstration Project: Technical Report # 5-Year 2005. Final Report prepared for Suncor Energy., Oil Sands. Fort McMurray, Alberta.

Hampel, F. R. 1985. The Breakdown Points of the Mean Combined with some Rejection Rules. Technometrics, 27: 95-107.

HydroQual. 1996. Laboratory Studies on Trophic Level Effects and Fish Health Effects of Suncor Tar Island Dyke Wastewater. Report for Suncor Inc., Oil Sands Group. Calgary, AB.

Imperial (Imperial Oil Resources Ventures Limited). 2005. Groundwater Baseline Report for the Kearl Oil Sands Project. In preparation.

Jain, R.B. 1981. Percentage Points of Many-Outlier Detection Procedures. Technometrics, 23: 71-75.

Klohn-Crippen (Klohn-Crippen Consultants Ltd.). 1996. Hydrogeology Baseline for the Steepbank Oil Sands Mine.

Klohn-Crippen. 1998a. Hydrogeology Baseline for Project Millennium. Ref. # PA 2839. Prepared for Suncor Energy Inc.

Klohn-Crippen. 1998b. Pond 2/3 Seepage Assessment Program. Prepared for Suncor Inc., Oil Sands Group. Calgary, AB.

Komex. (Komex International Ltd.). 2002. Hydrogeology Environmental Setting Jackpine Mine – Phase 1. Prepared for Shell Canada Limited. Prepared by Komex International Ltd. May 2002.

Komex. 2005. Hydrogeology Environmental Setting Report for the Muskeg River Mine Expansion. Prepared for Shell Canada Limited. April 2005. E35770112

Kottegoda, N.T. 1984. Investigation of Outliers in Annual Maximum Flow Series. Journal of Hydrology, 72: 105-137.


Golder Associates

MacKinnon, M. 1981. A Study of the Chemical and Physical Properties of Syncrude's Tailings Pond. Mildred Lake.

MacKinnon, M. and W. Benson. 1985. Chemical Treatment of Tailings Pond Water: Clarification and Detoxification. Syncrude Canada Ltd. Edmonton, AB.

MacKinnon, M. and W. Benson and J. Doyle. 1982. Properties of the Tailing Pond at Syncrude’s Mildred Lake Oil Sands Plant, 1981.

Nelson, R., M.D. MacKinnon and J. Gulley. 1993. Application of Toxicity Testing in the Evaluation of Reclamation Options for Oil Sands Fine Tails. Prepared for AOSTRA, Suncor Energy Inc. and Syncrude Canada Ltd.

Nix, P.G. 1982. Characteristics of Suncor Tailings Ponds Top Water and Detoxification In-situ or in Biological Waste Treatment Systems. Chemical and Geological Laboratories Ltd.

Nix, P.G. 1983. Detoxification of Tailings Pond Top Water. Chemical and Geological Laboratories Ltd.

Noton, L. 1980. Limnological Sampling of Suncor Pond 1A. Chemical and Geological Laboratories Ltd. Fort McMurray, AB. September 1980.

Pearson, R.K. 2001. Exploring Process Data. Journal of Process Control, 11: 179-194.

RAMP (RAMP 2003 Implementation Team). 2004. Regional Aquatics Monitoring Program (RAMP) 2003 Annual Report. Prepared for: RAMP Steering Committee. Submitted by the RAMP 2003 Implementation Team consisting of: Hatfield Consultants Ltd., Jacques Whitford Environment Ltd., Mack, Slack & Associates Inc., and Western Resource Solution. March 2004.

Rosner, B. 1975. On the Detection of Many Outliers. Technometrics, 17: 221-227.

Rosner, B. 1983. Percentage Points for a Generalized ESD Many-Outlier Procedure. Technometrics, 25: 165-172.


Golder Associates

Sokal, R.R. and F.J. Rohlf. 1981. Biometry – The Principles and Practice of Statistics in Biological Research, 2nd Edition. W.H. Freeman and Company, New York, 859 pages plus statistical tables.

Stedinger, J.R., R.M. Vogel and E. Foufoula-Georgiou. 1993. Frequency Analysis of Extreme Events. In: Maidment, D.R. (ed), Handbook of Hydrology, McGraw-Hill, New York, Chapter 18.

Suncor (Suncor Energy Inc.). 1995. Unpublished Consolidated Tailings Data Used in the Project Millennium EIA

Suncor. 2003. Unpublished Data Collected in Support of EPEA Approval number #94-01-21.

Syncrude. 1998. Unpublished Muskeg and Overburden Dewatering Chemistry.

TrueNorth. 2001. Unpublished Basal Aquifer Data Collected to Address Supplemental Information Requirements.

U.S. EPA. (United States Environmental Protection Agency) 1991. Technical Support Document for Water Quality-Based Toxics Control. Office of Water Enforcement and Permits, Office of Water Regulations and Standards, US Environmental Protection Agency, Washington, DC, Appendix E.

Walpole, R.E. and R.H. Myers. 1978. Probability and Statistics for Engineers and Scientist, 2nd Edition. Macmillan Publishing, New York.

WMO (World Meteorological Organization). 1985. Guidelines for Computerized Data Processing in Operational Hydrology and Land and Water Management. Joint FAO/WMO Publication, WMO Report No. 634, Geneva, Switzerland, Part 2.

Zenon (Zenon Environmental Inc.). 1986. Novel Methods for Characterization and Treatment of Toxic Oil Sands Wastewater. Phase VI-Step 1. Burlington, ON.

Personal Communications

J. Heise, City of Edmonton, personal communication.

APPENDIX VII

ATHABASCA RIVER MODEL RESULTS

CEMAMay 2007

Table VII-1Model Results for the Athabasca River Model – Node 1 – Upstream of McLean Creek

Page 1 of 2

Athabasca River Reach SpecificWater Quality Objectives

Background ConcentrationsBackground-Based

Benchmarks 2008 Snapshot 2040 Snapshot Far Future SnapshotLong-Term Average a) Peak(b)

Long-Term Average(a) Peak(b)




Major Ionscalcium mg/L 37 77 44 92 37 77 37 77 37 77chloride mg/L 27 97 32 116 27 97 27 97 27 97magnesium mg/L 10 21 12 25 10 21 10 21 10 21sodium mg/L 22 74 26 89 22 74 22 74 22 74sulphate mg/L 29 96 35 115 29 96 29 96 29 96sulphide mg/L 0.004 0.031 0.005 0.037 0.004 0.031 0.004 0.031 0.004 0.031total dissolved solids mg/L 200 400 240 480 200 400 200 400 200 400Nutrientsammonia mg/L 0.038 0.35 0.046 0.42 0.038 0.35 0.039 0.39 0.039 0.39total nitrogen mg/L 0.77 4.4 0.92 5.3 0.77 4.4 0.77 4.4 0.77 4.4total phosphorus mg/L 0.06 1.5 0.07 1.8 0.06 1.5 0.06 1.5 0.06 1.5dissolved organic carbon mg/L 10 43 12 52 10 43 10 43 10 43Whole-effluent constituentacute toxicity TUa 0 0 0 0 0 0 0 0 0 0chronic toxicity TUc 0 0 0 0 0 0 0 0 0 0fish tainting TPU 0 0 0 0 0 0 0 0 0 0General Organicsnaphthenic acids mg/L 0 0 0 0 0 0 0 0 0 0total phenolics mg/L 0.0038 0.060 0.0046 0.072 0.0038 0.060 0.0038 0.060 0.0038 0.060Total Metalsaluminum mg/L 0.4 21 0.5 25 0.4 21 0.4 21 0.4 21antimony mg/L 0.0007 0.0075 0.0008 0.0090 0.0007 0.0075 0.0007 0.008 0.0007 0.0075arsenic mg/L 0.0008 0.029 0.0010 0.034 0.0008 0.029 0.0008 0.029 0.0008 0.029barium mg/L 0.082 0.15 0.098 0.18 0.082 0.15 0.082 0.15 0.082 0.15beryllium mg/L 0.0003 0.018 0.0004 0.021 0.0003 0.018 0.0003 0.018 0.0003 0.018boron mg/L 0.038 0.16 0.046 0.19 0.038 0.16 0.038 0.16 0.038 0.16cadmium mg/L 0.0005 0.031 0.0006 0.038 0.0005 0.031 0.0005 0.031 0.0005 0.031chromium mg/L 0.0031 0.035 0.0037 0.042 0.0031 0.035 0.0031 0.035 0.0031 0.035copper mg/L 0.0028 0.029 0.0034 0.035 0.0028 0.029 0.0028 0.029 0.0028 0.029iron mg/L 1 20 1 24 1 20 1 20.1 1 20lead mg/L 0.0012 0.0095 0.0014 0.011 0.0012 0.0095 0.0012 0.0095 0.0012 0.0095manganese mg/L 0.045 0.39 0.054 0.47 0.045 0.39 0.045 0.39 0.045 0.39mercury mg/L 0.00004 0.0001 0.00005 0.00012 0.00004 0.0001 0.00004 0.0001 0.00004 0.0001molybdenum mg/L 0.0018 0.013 0.0022 0.016 0.0018 0.013 0.0018 0.013 0.0018 0.013nickel mg/L 0.006 0.045 0.007 0.054 0.006 0.045 0.006 0.045 0.006 0.045selenium mg/L 0.0002 0.0021 0.0002 0.0025 0.0002 0.0021 0.0002 0.0021 0.0002 0.0021silver mg/L 0.00002 0.00031 0.00002 0.00037 0.00002 0.00031 0.00002 0.00031 0.00002 0.00031strontium mg/L 0.27 1.7 0.32 2 0.27 1.7 0.27 1.7 0.27 1.7vanadium mg/L 0.0022 0.045 0.0026 0.054 0.0022 0.0448 0.0022 0.0448 0.0022 0.0448zinc mg/L 0.015 0.122 0.0180 0.146 0.015 0.122 0.015 0.122 0.015 0.122PAH GroupsPAH group 1 µg/L 0 0 0 0 0 0 0 0 0 0PAH group 2 µg/L 0 0.034 0 0.041 0 0.034 0 0.034 0 0.034PAH group 3 µg/L 0 0.016 0 0.019 0 0.016 0 0.016 0 0.016PAH group 4 µg/L 0 0 0 0 0 0 0 0 0 0PAH group 5 µg/L 0 0.025 0 0.030 0 0.025 0 0.025 0 0.025

Constituent Units

Golder Associates

CEMAMay 2007

Table VII-1Model Results for the Athabasca River Model – Node 1 – Upstream of McLean Creek

Page 2 of 2



Benchmarks 2008 Snapshot 2040 Snapshot Far Future SnapshotLong-Term Average a) Peak(b)




Long-Term Average(a) Peak(b)Constituent Units

PAH group 6 µg/L 0 0 0 0 0 0 0 0 0 0PAH group 7 µg/L 0.0037 0.94 0.0044 1.1 0.0037 0.94 0.0037 0.94 0.0037 0.94PAH group 8 µg/L 0.0050 0.90 0.0060 1.1 0.005 0.90 0.005 0.90 0.005 0.90PAH group 9 µg/L 0 0.012 0 0.015 0 0.012 0 0.012 0 0.012

(a) based on the median concentration of model results for 15000 days(a) based on the 99.91 percentile

Golder Associates

CEMAMay 2007

Table VII-2Model Results for the Athabasca River Model – Node 2 – Downstream of Muskeg River

Page 1 of 2



Benchmarks 2008 Snapshot 2040 Snapshot Far Future SnapshotLong-Term Average(a) Peak(b)





Major Ionscalcium mg/L 36 74 43 89 36 74 36 74 36 74chloride mg/L 17 68 20 82 17 67 17 67 17 67magnesium mg/L 9 20 11 24 9 20 9 20 9 20sodium mg/L 18 56 22 67 18 56 22 64 20 60sulphate mg/L 28 90 34 108 28 90 29 90 28 90sulphide mg/L 0.0035 0.021 0.004 0.025 0.0036 0.021 0.0034 0.020 0.0043 0.038total dissolved solids mg/L 190 380 228 456 200 390 200 380 200 380Nutrientsammonia mg/L 0.032 0.24 0.038 0.29 0.042 0.31 0.037 0.30 0.034 0.22total nitrogen mg/L 0.69 3.5 0.83 4.2 0.7 3.5 0.75 3.5 0.72 3.5total phosphorus mg/L 0.05 1.5 0.06 1.7 0.06 1.5 0.06 1.4 0.05 1.5dissolved organic carbon mg/L 9 42 11 50 10 42 10 42 10 42Whole-effluent constituentacute toxicity TUa 0 0 0 0 0.0009 0.0066 0.0019 0.011 0.0014 0.0086chronic toxicity TUc 0 0 0 0 0.009 0.087 0.01 0.095 0.004 0.037fish tainting TPU 0 0 0 0 0.001 0.0852 0.0051 0.1138 0.0037 0.1137General Organicsnaphthenic acids mg/L 0.01 0.47 0 1 0.08 0.57 0.09 0.45 0.08 0.38total phenolics mg/L 0.0033 0.039 0.0040 0.047 0.0033 0.037 0.0032 0.038 0.0032 0.038Total Metalsaluminum mg/L 0.3 20 0.4 24 0.3 20 0.3 20 0.3 20antimony mg/L 0.0004 0.0052 0.0005 0.0062 0.0004 0.0052 0.0005 0.0052 0.0005 0.0052arsenic mg/L 0.0007 0.028 0.0008 0.034 0.0007 0.028 0.0008 0.028 0.0007 0.028barium mg/L 0.079 0.15 0.095 0.18 0.079 0.15 0.079 0.15 0.079 0.147beryllium mg/L 0.0002 0.017 0.0002 0.020 0.0002 0.017 0.0003 0.017 0.0003 0.017boron mg/L 0.035 0.17 0.042 0.21 0.039 0.15 0.062 0.27 0.05 0.18cadmium mg/L 0.0004 0.028 0.0005 0.033 0.0004 0.028 0.0004 0.027 0.0004 0.028chromium mg/L 0.0028 0.034 0.0034 0.041 0.0028 0.034 0.0028 0.034 0.0028 0.034copper mg/L 0.0025 0.025 0.0030 0.030 0.0025 0.025 0.0025 0.025 0.0025 0.025iron mg/L 0.9 19 1 23 0.9 19 0.9 19 0.9 19lead mg/L 0.0011 0.0094 0.0013 0.011 0.0011 0.0094 0.0011 0.0093 0.0011 0.0093manganese mg/L 0.046 0.97 0.055 1.2 0.055 0.81 0.046 0.41 0.044 0.41mercury mg/L 0.00003 0.00009 0.00004 0.00011 0.00003 0.00009 0.00003 0.00009 0.00003 0.00009molybdenum mg/L 0.0017 0.010 0.0020 0.012 0.0027 0.011 0.0078 0.052 0.0047 0.017nickel mg/L 0.005 0.042 0.006 0.050 0.005 0.042 0.005 0.042 0.005 0.042selenium mg/L 0.0002 0.0015 0.0002 0.0018 0.0002 0.0014 0.0002 0.0015 0.0002 0.0015silver mg/L 0.00002 0.00078 0.00002 0.00094 0.00002 0.00062 0.00003 0.00029 0.00003 0.00028strontium mg/L 0.26 1.6 0.31 2 0.26 1.6 0.26 1.6 0.26 1.6vanadium mg/L 0.0018 0.044 0.0022 0.053 0.0024 0.0444 0.0025 0.0443 0.0019 0.0439zinc mg/L 0.013 0.102 0.0156 0.122 0.013 0.101 0.013 0.096 0.013 0.097PAH GroupsPAH group 1 µg/L 0 0 0 0 0.0002 0.0021 0.0002 0.0021 0 0.001PAH group 2 µg/L 0 0.033 0 0.040 0.001 0.033 0.001 0.033 0.0002 0.033PAH group 3 µg/L 0 0.015 0 0.018 0.0001 0.015 0.0001 0.015 0 0.015

Constituent Units

Golder Associates

CEMAMay 2007

Table VII-2Model Results for the Athabasca River Model – Node 2 – Downstream of Muskeg River

Page 2 of 2








Constituent UnitsPAH group 4 µg/L 0 0 0 0 0.0001 0.0015 0.0001 0.0019 0.0001 0.0019PAH group 5 µg/L 0 0.024 0 0.029 0.0023 0.025 0.0024 0.025 0.0003 0.024PAH group 6 µg/L 0 0 0 0 0.0001 0.0016 0.0001 0.0019 0.0001 0.0017PAH group 7 µg/L 0.0036 0.88 0.0043 1.1 0.0039 0.87 0.0039 0.87 0.0037 0.88PAH group 8 µg/L 0.0049 0.84 0.0059 1.0 0.0052 0.84 0.0053 0.84 0.0051 0.84PAH group 9 µg/L 0 0.012 0 0.014 0.0008 0.012 0.0008 0.012 0.0001 0.012


Golder Associates

CEMAMay 2007

Table VII-3Model Results for the Athabasca River Model – Node 3 – Downstream of Beaver Creek

Page 1 of 2








Major Ionscalcium mg/L 35 70 42 84 35 70 35 70 35 70chloride mg/L 14 61 17 73 14 61 17 74 16 66magnesium mg/L 9 19 11 23 9 19 9 19 9 19sodium mg/L 17 53 20 64 18 53 20 64 19 59sulphate mg/L 27 84 32 101 27 84 27 84 27 84sulphide mg/L 0.0036 0.022 0.004 0.027 0.0036 0.022 0.0041 0.023 0.0047 0.036total dissolved solids mg/L 190 360 228 432 190 360 200 380 190 370Nutrientsammonia mg/L 0.03 0.18 0.036 0.22 0.034 0.23 0.035 0.24 0.033 0.19total nitrogen mg/L 0.7 3.2 0.84 3.9 0.71 3.2 0.73 3.2 0.72 3.2total phosphorus mg/L 0.05 1.4 0.06 1.7 0.06 1.4 0.05 1.4 0.05 1.4dissolved organic carbon mg/L 10 40 12 48 10 40 10 40 10 40Whole-effluent constituentacute toxicity TUa 0 0 0 0 0.0006 0.0044 0.0016 0.0085 0.0014 0.011chronic toxicity TUc 0 0 0 0 0.006 0.058 0.007 0.065 0.005 0.041fish tainting TPU 0 0 0 0 0.0006 0.055 0.010 0.11 0.0044 0.10General Organicsnaphthenic acids mg/L 0.02 0.63 0 1 0.08 0.63 0.1 0.64 0.11 0.63total phenolics mg/L 0.003 0.0336 0.0036 0.040 0.0031 0.033 0.003 0.033 0.003 0.033Total Metalsaluminum mg/L 0.3 19 0.4 23 0.3 19 0.3 19 0.3 19antimony mg/L 0.0004 0.0046 0.0005 0.0055 0.0004 0.0045 0.0005 0.0045 0.0005 0.0045arsenic mg/L 0.0007 0.0265 0.0008 0.032 0.0007 0.026 0.0007 0.026 0.0007 0.026barium mg/L 0.076 0.143 0.091 0.17 0.076 0.14 0.076 0.14 0.076 0.14beryllium mg/L 0.0003 0.0156 0.0004 0.019 0.0003 0.016 0.0003 0.016 0.0003 0.016boron mg/L 0.039 0.149 0.047 0.18 0.042 0.14 0.052 0.16 0.048 0.15cadmium mg/L 0.0004 0.0248 0.0005 0.030 0.0004 0.025 0.0004 0.024 0.0004 0.025chromium mg/L 0.0027 0.0317 0.0032 0.038 0.0027 0.032 0.0027 0.032 0.0027 0.032copper mg/L 0.0024 0.0227 0.0029 0.027 0.0025 0.023 0.0025 0.022 0.0025 0.023iron mg/L 1 17.2 1 21 1 17 1 17 1 17lead mg/L 0.0012 0.0089 0.0014 0.0107 0.0012 0.0089 0.0012 0.0089 0.0012 0.0089manganese mg/L 0.04 0.423 0.048 0.51 0.045 0.39 0.04 0.36 0.039 0.36mercury mg/L 0.00002 0.00008 0.00002 0.00010 0.00002 0.00008 0.00003 0.00008 0.00003 0.00008molybdenum mg/L 0.0016 0.0093 0.0019 0.011 0.0023 0.0098 0.0045 0.023 0.0032 0.011nickel mg/L 0.005 0.039 0.006 0.047 0.005 0.039 0.005 0.039 0.005 0.039selenium mg/L 0.0002 0.0013 0.0002 0.0016 0.0002 0.0013 0.0002 0.0013 0.0002 0.0013silver mg/L 0.00002 0.00033 0.00002 0.00040 0.00002 0.00027 0.00003 0.00022 0.00003 0.00022strontium mg/L 0.25 1.42 0.30 2 0.25 1.4 0.25 1.4 0.25 1.4vanadium mg/L 0.0017 0.0413 0.0020 0.050 0.0022 0.0413 0.0022 0.0413 0.0018 0.0412zinc mg/L 0.012 0.086 0.0144 0.103 0.013 0.085 0.013 0.085 0.013 0.085PAH GroupsPAH group 1 µg/L 0 0 0 0 0.0001 0.0014 0.0002 0.0015 0.0001 0.001PAH group 2 µg/L 0 0.032 0 0.039 0.001 0.032 0.001 0.032 0.0002 0.032PAH group 3 µg/L 0 0.015 0 0.018 0 0.015 0 0.015 0 0.015

Constituent Units

Golder Associates

CEMAMay 2007

Table VII-3Model Results for the Athabasca River Model – Node 3 – Downstream of Beaver Creek

Page 2 of 2








Constituent UnitsPAH group 4 µg/L 0 0 0 0 0.0002 0.0027 0.0001 0.0014 0.0001 0.0016PAH group 5 µg/L 0 0.024 0 0.028 0.0016 0.024 0.0017 0.024 0.0003 0.024PAH group 6 µg/L 0 0 0 0 0.0001 0.0011 0.0001 0.0014 0.0001 0.0015PAH group 7 µg/L 0.0036 0.83 0.0043 1.00 0.0037 0.83 0.0037 0.83 0.0036 0.83PAH group 8 µg/L 0.0047 0.80 0.006 0.96 0.0049 0.79 0.005 0.79 0.0048 0.80PAH group 9 µg/L 0 0.012 0 0.014 0.0005 0.012 0.0005 0.012 0.0001 0.012


Golder Associates

CEMAMay 2007

Table VII-4Model Results for the Athabasca River Model – Node 4 – Downstream of the Firebag River

Page 1 of 2








Major Ionscalcium mg/L 33 66 40 79 33 66 33 66 33 66chloride mg/L 17 61 20 73 11 44 18 112 16 76magnesium mg/L 9 18 11 22 9 18 9 18 9 18sodium mg/L 16 47 19 56 15 43 20 82 18 63sulphate mg/L 25 79 30 95 25 79 26 79 26 79sulphide mg/L 0.0036 0.019 0.004 0.022 0.0037 0.019 0.005 0.021 0.0045 0.030total dissolved solids mg/L 180 350 216 420 190 350 200 420 190 370Nutrientsammonia mg/L 0.026 0.17 0.031 0.20 0.035 0.19 0.037 0.20 0.029 0.18total nitrogen mg/L 0.65 3.0 0.78 3.5 0.68 2.9 0.69 2.9 0.67 2.9total phosphorus mg/L 0.05 1.3 0.06 1.6 0.05 1.3 0.05 1.3 0.05 1.3dissolved organic carbon mg/L 9 39 11 47 9 39 9 39 9 39Whole-effluent constituentacute toxicity TUa 0 0 0 0 0.0004 0.003 0.001 0.0078 0.001 0.0096chronic toxicity TUc 0 0 0 0 0.004 0.038 0.005 0.048 0.004 0.031fish tainting TPU 0 0 0 0 0.0004 0.038 0.0043 0.064 0.006 0.082General Organicsnaphthenic acids mg/L 0.01 0.32 0 0 0.07 0.65 0.09 0.65 0.07 0.35total phenolics mg/L 0.0027 0.030 0.0032 0.036 0.0028 0.030 0.0028 0.030 0.0027 0.030Total Metalsaluminum mg/L 0.3 18 0.4 22 0.3 18 0.3 18 0.3 18antimony mg/L 0.0003 0.0037 0.0004 0.0044 0.0004 0.012 0.0004 0.012 0.0004 0.0037arsenic mg/L 0.0007 0.026 0.0008 0.031 0.0007 0.026 0.0007 0.026 0.0007 0.026barium mg/L 0.07 0.14 0.084 0.16 0.07 0.14 0.071 0.14 0.071 0.14beryllium mg/L 0.0002 0.015 0.0002 0.018 0.0002 0.015 0.0002 0.015 0.0002 0.015boron mg/L 0.035 0.13 0.042 0.15 0.036 0.13 0.042 0.13 0.041 0.13cadmium mg/L 0.0004 0.022 0.0005 0.027 0.0004 0.022 0.0004 0.022 0.0004 0.022chromium mg/L 0.0025 0.031 0.0030 0.037 0.0025 0.031 0.0025 0.031 0.0025 0.031copper mg/L 0.0023 0.021 0.0028 0.025 0.0023 0.021 0.0024 0.021 0.0023 0.021iron mg/L 0.9 16 1 19 0.9 16 0.9 16 0.9 16lead mg/L 0.0011 0.0085 0.0013 0.0102 0.0011 0.0085 0.0011 0.0084 0.0011 0.0084manganese mg/L 0.033 0.34 0.040 0.41 0.042 0.34 0.039 0.34 0.033 0.34mercury mg/L 0.00002 0.00008 0.00002 0.00010 0.00002 0.00008 0.00002 0.00008 0.00002 0.00008molybdenum mg/L 0.0015 0.0083 0.0018 0.0100 0.002 0.0086 0.0033 0.014 0.003 0.016nickel mg/L 0.005 0.036 0.006 0.043 0.005 0.042 0.005 0.042 0.005 0.036selenium mg/L 0.0002 0.0012 0.0002 0.0014 0.0002 0.0012 0.0002 0.0012 0.0002 0.0012silver mg/L 0.00006 0.00055 0.00007 0.00066 0.00006 0.00055 0.00006 0.00055 0.00002 0.00021strontium mg/L 0.24 1.3 0.29 2 0.24 1.3 0.24 1.3 0.24 1.3vanadium mg/L 0.0015 0.04 0.0018 0.048 0.0019 0.04 0.0019 0.04 0.0016 0.0397zinc mg/L 0.011 0.081 0.0132 0.097 0.012 0.080 0.012 0.080 0.012 0.080PAH GroupsPAH group 1 µg/L 0 0 0 0 0.0001 0.0009 0.0001 0.001 0.0001 0.0007PAH group 2 µg/L 0 0.030 0 0.036 0.0003 0.030 0.0004 0.030 0.0001 0.030PAH group 3 µg/L 0 0.014 0 0.017 0 0.014 0 0.014 0 0.014

Constituent Units

Golder Associates

CEMAMay 2007

Table VII-4Model Results for the Athabasca River Model – Node 4 – Downstream of the Firebag River

Page 2 of 2








Constituent UnitsPAH group 4 µg/L 0 0 0 0 0.0001 0.001 0 0.0009 0.0001 0.0011PAH group 5 µg/L 0 0.022 0 0.027 0.0011 0.022 0.0011 0.022 0.0002 0.022PAH group 6 µg/L 0 0 0 0 0 0.0007 0.0001 0.0009 0 0.001PAH group 7 µg/L 0.0034 0.76 0.0041 0.91 0.0034 0.76 0.0034 0.75 0.0034 0.76PAH group 8 µg/L 0.0045 0.73 0.005 0.87 0.0046 0.72 0.0046 0.72 0.0046 0.72PAH group 9 µg/L 0 0.011 0 0.013 0.0004 0.011 0.0004 0.011 0.0001 0.011


Golder Associates

CEMAMay 2007

Table VII-5Model Results for the Athabasca River Model – Node 5 – Upstream of Embarras River

Page 1 of 2








Major Ionscalcium mg/L 33 65 40 78 33 65 33 65 33 65chloride mg/L 16 60 19 72 11 42 18 111 15 74magnesium mg/L 9 18 11 22 9 18 9 18 9 18sodium mg/L 15 46 18 55 15 41 19 82 18 62sulphate mg/L 25 78 30 94 25 78 25 78 25 78sulphide mg/L 0.0034 0.015 0.004 0.018 0.0034 0.015 0.0048 0.019 0.0044 0.028total dissolved solids mg/L 180 350 216 420 180 350 200 410 190 370Nutrientsammonia mg/L 0.026 0.16 0.031 0.20 0.032 0.18 0.034 0.19 0.028 0.17total nitrogen mg/L 0.65 2.9 0.78 3.5 0.66 2.9 0.67 2.9 0.66 2.9total phosphorus mg/L 0.05 1.3 0.06 1.6 0.05 1.3 0.05 1.3 0.05 1.3dissolved organic carbon mg/L 9 38 11 46 9 38 9 38 9 38Whole-effluent constituentacute toxicity TUa 0 0 0 0 0.0003 0.0027 0.001 0.0077 0.001 0.0091chronic toxicity TUc 0 0 0 0 0.004 0.035 0.005 0.045 0.004 0.03fish tainting TPU 0 0 0 0 0.0004 0.035 0.0039 0.062 0.0053 0.078General Organicsnaphthenic acids mg/L 0.03 0.44 0 1 0.06 0.46 0.08 0.47 0.06 0.31total phenolics mg/L 0.0026 0.029 0.0031 0.035 0.0027 0.029 0.0027 0.029 0.0026 0.029Total Metalsaluminum mg/L 0.3 18 0.4 22 0.3 18 0.3 18 0.3 18antimony mg/L 0.0003 0.0035 0.0004 0.0042 0.0004 0.0075 0.0004 0.0075 0.0004 0.0035arsenic mg/L 0.0007 0.025 0.0008 0.030 0.0007 0.025 0.0007 0.025 0.0007 0.025barium mg/L 0.069 0.14 0.083 0.16 0.069 0.14 0.069 0.13 0.069 0.14beryllium mg/L 0.0002 0.014 0.0002 0.017 0.0002 0.014 0.0002 0.014 0.0002 0.014boron mg/L 0.034 0.12 0.041 0.15 0.036 0.12 0.042 0.13 0.04 0.13cadmium mg/L 0.0004 0.022 0.0005 0.026 0.0004 0.021 0.0004 0.021 0.0004 0.021chromium mg/L 0.0024 0.030 0.0029 0.036 0.0024 0.030 0.0025 0.030 0.0025 0.030copper mg/L 0.0023 0.020 0.0028 0.024 0.0023 0.020 0.0024 0.020 0.0023 0.020iron mg/L 0.9 16 1 19 0.9 15 0.9 15 0.9 16lead mg/L 0.001 0.0083 0.0012 0.0100 0.001 0.0083 0.0011 0.0083 0.0011 0.0083manganese mg/L 0.031 0.34 0.037 0.41 0.038 0.34 0.036 0.34 0.031 0.34mercury mg/L 0.00002 0.00008 0.00002 0.00010 0.00002 0.00008 0.00002 0.00008 0.00002 0.00008molybdenum mg/L 0.0015 0.0081 0.0018 0.0097 0.002 0.0083 0.0032 0.013 0.0028 0.011nickel mg/L 0.005 0.035 0.006 0.042 0.005 0.037 0.005 0.037 0.005 0.035selenium mg/L 0.0002 0.0012 0.0002 0.0014 0.0002 0.0012 0.0002 0.0012 0.0002 0.0012silver mg/L 0.00005 0.00036 0.00006 0.00043 0.00005 0.00036 0.00005 0.00036 0.00002 0.00021strontium mg/L 0.23 1.3 0.28 2 0.23 1.3 0.23 1.3 0.23 1.3vanadium mg/L 0.0015 0.040 0.0018 0.047 0.0018 0.0393 0.0018 0.0393 0.0016 0.0393zinc mg/L 0.011 0.079 0.0132 0.095 0.011 0.077 0.012 0.077 0.011 0.078PAH GroupsPAH group 1 µg/L 0 0 0 0 0.0001 0.0008 0.0001 0.0009 0.0001 0.0007PAH group 2 µg/L 0 0.029 0 0.035 0.0003 0.029 0.0003 0.029 0.0001 0.029PAH group 3 µg/L 0 0.014 0 0.017 0 0.014 0 0.014 0 0.014

Constituent Units

Golder Associates

CEMAMay 2007

Table VII-5Model Results for the Athabasca River Model – Node 5 – Upstream of Embarras River

Page 2 of 2








Constituent UnitsPAH group 4 µg/L 0 0 0 0 0.0001 0.0009 0 0.0009 0 0.0011PAH group 5 µg/L 0 0.022 0 0.026 0.001 0.022 0.001 0.022 0.0002 0.022PAH group 6 µg/L 0 0 0 0 0 0.0007 0.0001 0.0009 0 0.001PAH group 7 µg/L 0.0033 0.74 0.0040 0.89 0.0034 0.74 0.0034 0.74 0.0033 0.74PAH group 8 µg/L 0.0044 0.72 0.005 0.86 0.0045 0.71 0.0045 0.71 0.0045 0.71PAH group 9 µg/L 0 0.011 0 0.013 0.0003 0.011 0.0003 0.011 0.0001 0.011


Golder Associates

APPENDIX VIII

CONSTITUENT RANKING

CEMA VIII-1 Athabasca River Reach Specific May 2007 Water Quality Objectives

Golder Associates

Introduction

A constituent ranking scheme was developed to identify constituents that may be of higher priority for monitoring and/or refinement of effects-based objectives. The scheme is set up such that constituents which exceed background-based benchmarks and effects-based objectives will be easily identified. The ranking scheme is illustrated in Figure VIII-1. Constituents were ranked based on both median and peak substance concentrations. The ranking of median concentrations was based on human health effects-based objectives, whereas the ranking of peak substance concentrations was based on aquatic life effects-based objectives.

Figure VIII-1 Constituent Ranking Schematic

Is the investigation level more restrictive than

effects-based RSWQOs?

Rank 2Investigation level protects

water use if it is more restrictive thaneffects-based RSWQO. Further examination

of effects thresholds is not required. Constituent may be a

candidate for monitoring to confirmEIA predictions.

No

Yes Yes

Is there an adequate effects-based RSWQO?

Is the investigation level more restrictive than

effects-based RSWQOs?

Rank 1Development of effects-based RSWQO could be considered.

No

Yes Yes

Is the investigation level more restrictive than the

background-based benchmark?

Yes

No

Oil sands contributions forthis constituent are small and arenot a likely candidate for effects

monitoring or refinement ofeffects-based RSWQOs.

No

Rank 0

No

Is there an adequate effects-based RSWQO?

Rank 3Further examination of

effects threshold required for development of effects-based RSWQOs. Constituent is

a candidate for monitoring to confirmEIA predictions.


Golder Associates

Results

Table VIII-1 provides the ranking for all of the constituents included in ARM for both median and peak substance concentrations. Constituents in Table VIII-1 are sorted according to the maximum rank for each constituent. The maximum rank among the various snapshots and assessment nodes is shown.

Table VIII-1 Constituent Ranking Table

Constituent Rank based on Median(c)

Rank Based on Peak(b)

sodium 3 3 sulphide 3 3 ammonia 3 2 boron 3 2 naphthenic acids 2 3 antimony 2 2 molybdenum 2 2 manganese 2 1 silver 2 1 vanadium 2 1 chloride 0 2 fish tainting 2(a) 2(a)

acute toxicity 2(a) 2(a)

chronic toxicity 2(a) 2(a)

PAH Group 1 2(a) 2(a)



PAH Group 3 2(a) 1 PAH Group 2 2(a) 0 PAH Group 5 2(a) 0 PAH Group 9 2(a) 0 dissolved organic carbon 1 1 iron 1 1 magnesium 1 1 total nitrogen 1 1 total phenolics 1 1 total phosphorus 1 1 aluminum 0 1 beryllium 0 1 cadmium 0 1 calcium 0 1


Table VIII-1 Constituent Ranking Table (continued)

Golder Associates

Constituent Rank based on Median(c)

Rank Based on Peak(b)

chromium 0 1 copper 0 1 lead 0 1 mercury 0 1 selenium 0 1 strontium 0 1 zinc 0 1 arsenic 0 0 barium 0 0 nickel 0 0 sulphate 0 0 total dissolved solids 0 0 PAH Group 7 0 0 PAH Group 8 0 0

(a) Background concentration was zero, and therefore the background-based benchmarks could not be calculated.

(b) Ranking was based on aquatic life effects-based objective. (c) Ranking was based on the human health effects-based objective.

APPENDIX IX

REVIEW OF SELECTED CONSTITUENTS

CEMA IX-i Athabasca River Reach Specific May 2007 Water Quality Objectives

Golder Associates

TABLE OF CONTENTS

SECTION PAGE

IX-1 INTRODUCTION ...................................................................................................1

IX-2 REVIEW OF CONSTITUENTS ..............................................................................1 IX-2.1 NUTRIENTS..............................................................................................................1 IX-2.2 AMMONIA (HUMAN AND WILDLIFE HEALTH EFFECTS) .....................................1 IX-2.3 MAJOR IONS............................................................................................................2 IX-2.4 NAPHTHENIC ACIDS...............................................................................................3 IX-2.5 PAH GROUP 3..........................................................................................................4 IX-2.6 METHYL ISOBUTYL CARBINOL (MIBC).................................................................4 IX-2.7 DI (2-ETHYLHEXYL) PHTHALATE (DEHP).............................................................5 IX-2.8 ACRYLAMIDE...........................................................................................................5 IX-2.9 GENERAL HYDROCARBON CONSTITUENTS ......................................................6 IX-2.10 TOLUENE AND XYLENE .........................................................................................6 IX-2.11 TAINTING COMPOUNDS.........................................................................................7 IX-2.12 OXYGEN RELATED CONSTITUENTS ....................................................................7 IX-2.13 LITHIUM....................................................................................................................9

IX-3 REFERENCES ......................................................................................................9

CEMA IX-1 Athabasca River Reach Specific May 2007 Water Quality Objectives

Golder Associates

IX-1 INTRODUCTION

This section provides a review of constituents that could not be fully addressed for at least one of the following reasons:

• They were not included in ARM;

• Information for the development of CEB effects-based or health risk-based thresholds was not readily available;

• There was limited data for mine affected waters and/or the LAR; and/or

• Potential effects to aquatic life or humans were not toxicity based.

Many of the constituents were identified for consideration under Task C. The following sections provided a more detailed review of these constituents including recommendations on further study requirements.

IX-2 REVIEW OF CONSTITUENTS

IX-2.1 NUTRIENTS

Nutrients that were included as potential variables of concern (VOCN) by CEMA (2003) are nitrogen and phosphorus. Guidelines for total nitrogen and total phosphorus were considered inadequate because current guidelines for the protection of aquatic life were thought not to represent conditions in the LAR. The ammonia guideline was considered inadequate because the toxicity-based guideline has the potential to be above the threshold for eutrophication effects.

Investigation levels and background-based benchmarks were developed as a component of this study. Investigation levels were lower than background-based benchmarks for total nitrogen and total phosphorus. The background-based benchmarks are considered protective of designated uses (Section 4.1). Therefore, no further development of effects-based objective for eutrophication is recommended for total nitrogen and total phosphorus at this time.

IX-2.2 AMMONIA (HUMAN AND WILDLIFE HEALTH EFFECTS)

The long-term average investigation level of ammonia was above the corresponding background-based benchmark. The investigation level could not be compared to a health risk-based objective as one was not developed in this study. Ammonia is considered not to have health effects at concentrations


Golder Associates

generally found in drinking water (HC 2002). If health effects do occur it is at concentrations greater than the aesthetic drinking water guideline (UKDWI 2002). As the maximum long-term average investigation level was below the aesthetic drinking water guideline, the investigation level can be considered protective of human health. Based on the lines of evidence provided, the long-term average investigation level for ammonia should be considered protective of human health. Further evaluation of the health risk-based objective is not required.

IX-2.3 MAJOR IONS

Major ions that were included as VOCNs by CEMA (2003) are chloride, magnesium, sodium, potassium, fluoride and sulphate. Calcium is also a major ion and was included in the constituent list as was total dissolved solids (TDS), which represents the total of all major ions.

With the exception of chloride and fluoride, major ions and TDS did not have guidelines for the protection of aquatic life for the LAR and data for development of CEBs was not included in recent EIAs. Information for development of a risk-based objective for human and wildlife health was also not available.

Investigation levels and background-based benchmarks were developed as a component of this study for calcium, chloride, magnesium, sodium, sulphate and TDS.

Human health risk-based objectives were absent for major ions but were classified as LNR (likely not relevant). Potential human health effects were identified by CEMA (2003) for sodium and chloride only and these effects are associated with hypertension. The Canadian drinking water guidelines technical documentation (HC 2002) identify human health thresholds well above aesthetic guidelines. No human health drinking water guidelines are provided by Health Canada because effects thresholds are well above concentrations normally found in drinking water. The long-term average investigation levels for major ions were all well below the aesthetic drinking water guidelines and were protective of designated water uses as described in Section 8. Further development of effects thresholds is not required.

Aquatic life effects-based objectives were absent for calcium, magnesium, sodium, sulphate and total dissolved solids. The search of toxicity literature conducted by CEMA (2003) did not turn up any evidence of toxicity data for these constituents with the exception of sulphate and investigation levels were well below aesthetic guidelines. The peak investigation level for sulphate was


Golder Associates

below the background based threshold for sulphate, and therefore the investigation level is considered protective of aquatic life. Based on the lines of evidence provided, the peak investigation levels for all major ions should be considered protective of water uses. Further development of effects-based objectives is not required.

Potassium and fluoride are not currently included in ARM. They were identified as having elevated concentrations in mine waters by CEMA (2003) and should be considered for inclusion in ARM. After investigation levels and background-based benchmarks have been determined, priority for development of additional effects thresholds can be determined.

IX-2.4 NAPHTHENIC ACIDS

There was no chronic aquatic life guideline available for naphthenic acids and data for the development of a CEB effects-based threshold was not included in recent EIAs. This is because there is a lack of sufficient chronic toxicity data for aquatic biota (Imperial 2005, Volume 8).

Naphthenic acids act as surfactants, interfering with normal gas exchange across gill membranes. They also produce narcosis. As a result, sublethal toxicity endpoints (e.g., reduced growth or reproduction) can be reached and surpassed quickly, leading to acute toxicity (i.e., reduced survival). Naphthenic acids have been identified as the agent responsible for the majority of the acute toxicity observed in tailings water and other process-affected waters (MacKinnon and Boerger 1986; Verbeek et al. 1993).

Results of testing with commercial mixtures of naphthenic acids and different oil sands waters indicate that acute toxicity values for naphthenic acids can range from 1.4 to 75 mg/L depending on the individual compounds tested and the age of the sample. Age is an important consideration, since naphthenic acids readily degrade (Herman et al. 1994; MacKinnon and Boerger 1986; Holowenko et al. 2002). The degradation of naphthenic acids results in lower toxicity, as shown by studies on fresh versus aged tailing pond water (Holowenko et al. 2002).

The peak investigation levels for naphthenic acids were above the corresponding node-specific background-based benchmark at two nodes, although all of the peak investigation levels were not below the maximum background-based benchmark and were therefore within the natural range of concentrations in the LAR. The lack of an aquatic life effects-based objective was classified as LR (likely relevant) because naphthenic acids have the potential to be toxic to aquatic life. Study of the aquatic toxicity of naphthenic acids is ongoing.


Golder Associates

The ARM ILIM has not been updated to account for a more recent recognition that naphthenic acids derived from process-affected sources are composed of both a toxic, degradable labile portion as well as a refractory non-toxic portion (Golder 2006). More recent modelling has been incorporating these two fractions with the result that levels of the labile, potentially toxic fraction of naphthenic acids reaching the Athabasca River will be much lower than that heretofore represented by the total levels of that constituent. For the next phase of this study a labile naphthenic acids investigation level should be developed. Developing a background-based benchmark for the LAR would be problematic as the assumption would be that background concentration of labile naphthenic acids would be zero.

IX-2.5 PAH GROUP 3

There was no guideline available for PAH group 3 and data for the development of a CEB effects-based threshold was not included in recent EIAs. None of the constituents in PAH group 3 were included in the list of VOCNs developed by CEMA (2003), however this group is included in ARM and was considered in the study.

Investigation levels and background-based benchmarks (for peak values only) were developed as a component of this study for PAH group 3, which allowed the group to be ranked according to the scheme (Section 5.2.2). Investigation levels were lower than the background-based benchmarks for this group. The background-based benchmarks are considered protective of designated uses (Section 4.1). Therefore, no further development of effects-based thresholds for PAH group 3 is recommended at this time. However, a CEB effects-based threshold for this constituent group will likely be developed as a component of upcoming EIAs and this threshold can be included in the ARM ILIM in future updates.

IX-2.6 METHYL ISOBUTYL CARBINOL (MIBC)

MIBC is used as a frothing agent used in the extraction process by some operators. Levels of this compound in the tailings water and in the LAR are unknown. This compound was listed as a VOCN by CEMA (2003) because of its known toxic properties (NIOSH 2002).

MIBC is a largely hydrophobic, alkylated alcohol with a solubility of 17 g/L (BOVAR 1996). The acute toxicity threshold of MIBC is estimated to be in the order of 300 to 400 mg/L (BOVAR 1996). The concentration of MIBC in tailings should be between 1 and 50 mg/L and it is expected to rapidly


Golder Associates

biodegrade with a half-life of 2 to 15 days. Therefore, MIBC is not expected to be found in mine waters.

It is recommended that mine water seepage be analyzed for MIBC prior to any further consideration for the development of objectives for the LAR.

IX-2.7 DI (2-ETHYLHEXYL) PHTHALATE (DEHP)

DEHP is used in the plastics industry for the production of PVC plastics. Based on a very limited data set, this constituent was identified as a VOCN in the CEMA Study. The guideline was found to be inadequate because it was more than 10 times greater than the concentration in the river. The single measurement of concentration in mine water was below all available water quality guidelines and this compound is not associated with the oil sands industry. It is not included in ARM. No further study of this constituent is recommended.

IX-2.8 ACRYLAMIDE

Polyacrylamides are high molecular weight polymers used to bind particles to fine tailings to form heavier aggregates (thickened tails). There are few measurements of polyacrylamide or acrylamide (the monomer resulting from the breakdown of polyacrylamide) in the various wastewaters and no measurements in the Athabasca River. Acrylamide was listed as a VOCN by CEMA (2003) because of its known toxicity (Kindzierski 2001).

Polyacrylamides consist of subunits of acrylamide monomer, and contain free residual acrylamide units that may be released to surface waters. Acrylamide monomer is a suspected neurotoxin and carcinogen. However, acrylamide levels in polyacrylamide products are considered environmentally safe (Sojka and Surapeneni 2001), and residual acrylamide is readily metabolized by micro-organisms in surface waters (Larcombe 1999).

Probable NOEC have been developed for acrylamide (UKEA 2000). Long-term NOECs for acrylamide are reported for fish, aquatic invertebrates and freshwater algae, and short term concentrations lethal to 50% of the organisms (LC50) are reported for fish, aquatic invertebrates, algae and micro-organisms. The lowest reported LC50 is 33.85 mg/L for algae. The lowest reported long-term NOEC is 2.04 mg/L, for Mysidopsis bahai. Applying appropriate assessment factors to the long-term NOEC reported threshold results in a probable NOEC of 20.4 μg/L for the long term (chronic threshold) and 33.8 μg/L for the short-term (acute threshold). U.S. EPA drinking water regulations require that polyacrylamide


Golder Associates

product usage in water treatment be limited such that the maximum acrylamide level does not exceed 0.5 µg/L (U.S. EPA 2002).

Although polyacrylamide and acrylamide have been included in earlier versions of ARM, they were not included in the most recent EIAs. These constituents were modelled in smaller tributaries as a component of the Horizon EIA (CNRL 2002). Predicted concentrations in the tributaries were very low and no appreciable levels would be expected in the LAR.

IX-2.9 GENERAL HYDROCARBON CONSTITUENTS

Oil and grease and total petroleum hydrocarbons were identified as VOCNs with inadequate guidelines by CEMA (2003). Oil and grease is one of the key constituents for EPEA discharge limits for sedimentation ponds. No numeric criteria for these constituents are included in the current guidelines and they are not included in ARM. These constituents are not good candidates for development of numerical effects thresholds for human and wildlife health or aquatic life because of their non-specific nature. Specific organic constituents related to oil sands developments are included in the constituent list. Therefore, general hydrocarbon constituents are not recommended for further development of effects thresholds. However, these constituents could readily be included in ARM and background-based benchmarks and investigation levels developed.

IX-2.10 TOLUENE AND XYLENE

Toluene and xylene were identified as VOCNs with inadequate guidelines by CEMA (2003). Toluene and xylene have the potential to have toxic effects to humans and aquatic life as well as to affect taste and odour of drinking water and fish flesh. Toluene is considered to be non-persistent in the aquatic environment and it is removed by volatization and biodegradation.

Guidelines for these constituents reviewed by CEMA (2003) were variable and in many cases much higher than concentrations in the LAR.

Toluene and xylene are not currently included in ARM. They were identified as having elevated concentrations in mine waters (i.e., concentrations greater than 10 times the background concentration) by CEMA (2003) and should be considered for inclusion in ARM. After investigation levels and background-based benchmarks have been determined, priority for development of effects-based objectives can be determined. Because these constituents are considered non-persistent, decay rates should be derived and included in ARM.


Golder Associates

IX-2.11 TAINTING COMPOUNDS

Tainting compounds identified as VOCNs with inadequate guidelines in the CEMA study include dibenzothiophene, alkyl-substituted dibenzothiophene, phenols, toluene and xylenes. These constituents are not currently included in ARM.

Fish tainting is currently assess based on whole-effluent tests that are similar to toxicity testing. A whole-effluent tainting constituent is include in ARM. Thresholds developed for individual compounds may not be applicable to the LAR as fish tainting may be caused by additive effects of many chemicals.

The CONRAD Wetlands and Aquatics Working Group is currently undertaking a research program on fish tainting. Development of reach specific objectives for tainting compounds should be based on recommendations from the working group.

IX-2.12 OXYGEN RELATED CONSTITUENTS

Biochemical oxygen demand (BOD) and dissolved oxygen (DO) were identified as VOCNs with adequate guidelines by CEMA (2003). Releases from oil sands operations may contain organic constituents that could lead to depressed levels of dissolved oxygen, particularly during the winter when the river is covered with ice and no reaeration occurs.

Oxygen is not currently included in ARM. A dynamic model such as WASP would be appropriate to model oxygen dynamics. WASP includes key physical, chemical and biological processes which govern the dynamic variation of DO in the Athabasca River, and to apply the developed model to simulate DO under different release and flow management scenarios for the Athabasca River.

Proposed Approach

The Water Quality Analysis Simulation Program (WASP) is proposed to be applied for modelling the DO dynamics in the Athabasca River. The WASP model is public-domain software developed and supported by the U.S. Environmental Protection Agency (U.S. EPA). The model has established a well-recognized reputation as an effective and practical water quality modelling tool for simulating DO and other water quality constituents in almost all types of waterbodies.


Golder Associates

The WASP model would be set up and configured as a 2-dimensional grid system to represent the variation of DO along both the longitudinal and lateral direction of the Athabasca River. All the boundary flows, including upstream inflow, the tributaries, and withdraw flows, will be incorporated into the model. The internal kinematic wave function in the WASP model would be applied to calculate the advective transport of all the boundary flows.

The major processes that govern the dynamic variation of DO in the Athabasca River include the replenishment of DO through reaeration, the consumption of DO due to oxidation of organic matter and ammonia in the water column and oxygen demand from the sediment, and the inhibition of reaeration via ice-cover during winter. Accordingly, the WASP model would be used to predict these kinetic processes and the selected water quality constituents, including DO, carbonaceous biochemical oxygen demand (CBOD), and ammonia. Water temperature would also be simulated as it regulates the rates of many kinetic processes in the model, such as the CBOD oxidation, or the reaeration.

The WASP model could be set up to run between 1990 and 2005, so as to evaluate the DO levels under different wet or dry conditions. The developed DO model, after calibrated and validated against measured data, could be applied to assess the DO profiles under various water release and flow management scenarios.

Data Requirements

The required information for modelling DO in the Athabasca River is listed below:

• Geometric data for the reaches along the river, including lengths, widths, depths, bed slopes and roughness;

• Lateral mixing coefficients for the reaches along the river;

• Boundary flow rate time series for inflows from upstream water, major tributaries, or major non-point surface runoff waters;

• Withdrawals flow time series;

• Measured temperature and concentrations of CBOD, ammonia, and DO in the Athabasca River, the major tributaries, and non-point runoffs;

• Loading rate time-series of CBOD, ammonia and DO from sewage treatment plants, mine water seepages, or other point/non-point sources;

• Percentage of surface covered by ice during winter period; and


Golder Associates

• Local meteorological data, including hourly air temperature, dew point temperature, cloud cover, wind speed, and solar radiation.

IX-2.13 LITHIUM

Lithium was identified as a VOCN with an inadequate guideline by CEMA (2003). Lithium did not have a current guideline for the protection of aquatic life for the LAR and data for development of CEBs was not included in recent EIAs, however CEMA (2003) found that lithium has the potential to be toxic to aquatic life and guidelines from other jurisdictions were obtained for use in this study. Lithium is also not currently included in ARM. Lithium was identified as having elevated concentrations in mine waters by CEMA (2003) and should be considered for inclusion in ARM. After investigation levels and background-based benchmarks have been determined, priority for development of additional effects-based objectives can be determined.

IX-3 REFERENCES

BOVAR Environmental Ltd. (BOVAR). 1996. Environmental Impact Assessment for the Syncrude Canada Ltd. Aurora Mine. Report prepared for Syncrude Canada Ltd.

CEMA (Cumulative Environmental Management Association and Western Resource Solutions). 2003. Development of Reach Specific Water Quality Guidelines for Variables of Concern in the Lower Athabasca River: Identification of Variables of Concern and Assessment of the Adequacy of the current Guidelines. Final report prepared for Cumulative Environmental Management Association (CEMA) by Western Resource Solutions (WRS).

CNRL (Canadian Natural Resources Limited). 2002. Horizon Oil Sands Project – Application for Approval. Volume 1 Prepared by Canadian Natural Resources Limited. Volumes 2, 3, 4, 5, 6, 7 and 8 Prepared by Golder Associates Ltd. for Canadian Natural Resources Limited. Calgary, AB. June 2002.

HC (Health Canada). 2002. Guidelines for Canadian Drinking Water Quality. Health Canada, Ottawa, ON.

Herman, D.C., P.M. Fedorak, M.D. MacKinnon and J.W. Costeron. 1994. Biodegradation of Naphthenic Acids by Microbial Populations Indigenous to Oil Sands Tailings. Canadian Journal of Microbiology. 40: 467-477.


Golder Associates

Holowenko, F.M., M.D. MacKinnon and P.M. Fedorak. 2002. Characterization of Naphthenic Acids in Oil Sands Wastewaters by Gas Chromatography – Mass Spectrometry. Water Research. 36: 2,843-2,855.

Kindziersky, W.B. 2001. Screening Evaluation and Risk Assessment Of Acrylamide Impacts. From Polymer-Amended Thickened Tailings Deposits. Report to Albian Sands Energy Inc.

Larcombe, M.F. 1999. Technical publication on chemical removal of sediment from earthworks stormwater. Draft Auckland Regional Council Technical Publication, September 1999.

MacKinnon, M.D. and H. Boeger. 1986. Description of Two Treatment Methods for Detoxifying Oil Sands Tailings Pond Water. Water Pollution Research Journal of Canada. 21: 496-512.

NIOSH (2002) NIOSH Pocket Guide to Chemical Hazards. Internet edition. http://www.cdc.gov/niosh/npg/npg.html

Sojka, R.E. and A. Surapaneni. 2001. Potential use of polyacrylamide (PAM) in Australian agriculture to improve off- and on-site environmental impacts and infiltration management.

UKDWI. 2002. Drinking Water Regulations Schedule 1 and 2. UK Drinking Water Inspectorate. http:/www.dwi.gov.uk/regs/si3184/3184.htm

UKEA (United Kingdom Environment Agency). 2000. Risk of acrylamide (draft report). United Kingdom Environmental Agency, Ecotoxicology & Hazardous Substances National Centre, Wallingford, Oxfordshire. CAS No. 79-06-1.

U.S. EPA. 2002. Treatment techniques for acrylamide and epichlorohydrin. Code of Federal Regulations. 40CFR141.111.

Verbeek, R.C., W. MacKay and M. MacKinnon. 1993. Isolation and Characterization of the Acutely Toxic Compounds in Oil Sands Process Water from Syncrude and Suncor. In: Oil Sands: Our Petroleum Future Conference, Edmonton, Alberta. April 4-7, 1993. Alberta Oil Sands Technology and Research Authority, Edmonton, Alberta Paper No. F-12.

http://www.cdc.gov/niosh/npg/npg.html

Report Disclaimer - CEMAlibrary.cemaonline.ca/ckan/dataset/6bcc559c-d5f6-4774-8126-171d96e... ·...

Documents

Transcript of Report Disclaimer - CEMAlibrary.cemaonline.ca/ckan/dataset/6bcc559c-d5f6-4774-8126-171d96e... ·...