Advances in science and applications of air pollution ...

2019 ANNUAL AampWMA CRITICAL REVIEW

Advances in science and applications of air pollution monitoring A case studyon oil sands monitoring targeting ecosystem protectionJR Brooka SG Coberb M Freemarkc T Harnerb SM Lib J Liggiob P Makarb and B Paulic

aDalla Lana School of Public Health and Department of Chemical Engineering and Applied Chemistry University of Toronto TorontoOntario Canada bAir Quality Research Division Environment and Climate Change Canada Toronto Ontario Canada cNational WildlifeResearch Centre Environment and Climate Change Ottawa Canada

ABSTRACTThe potential environmental impact of air pollutants emitted from the oil sands industry in AlbertaCanada has received considerable attention The mining and processing of bitumen to producesynthetic crude oil and the waste products associated with this activity lead to significant emissionsof gaseous and particle air pollutants Deposition of pollutants occurs locally (ie near the sources) andalso potentially at distances downwind depending upon each pollutantrsquos chemical and physical proper-ties andmeteorological conditions The Joint Oil SandsMonitoring Program (JOSM)was initiated in 2012by the Government of Canada and the Province of Alberta to enhance or improve monitoring ofpollutants and their potential impacts In support of JOSM Environment and Climate Change Canada(ECCC) undertook a significant research effort via three components the Air Water and Wildlifecomponents which were implemented to better estimate baseline conditions related to levels ofpollutants in the air and water amounts of deposition and exposures experienced by the biota Thecriteria air contaminants (eg nitrogen oxides [NOx] sulfur dioxide [SO2] volatile organic compounds[VOCs] particulate matter with an aerodynamic diameter lt25 μm [PM25]) and their secondary atmo-spheric products were of interest as well as toxic compounds particularly polycyclic aromatic com-pounds (PACs) trace metals and mercury (Hg) This critical review discusses the challenges of assessingecosystem impacts and summarizes themajor results of these efforts through approximately 2018 Focusis on the emissions to the air and the findings from theAir Component of the ECCC research and linkagesto observations of contaminant levels in the surface waters in the region in aquatic species as well as interrestrial andavian species The existing evidenceof impact on these species is briefly discussed as is thepotential for some of them to serve as sentinel species for the ongoing monitoring needed to betterunderstand potential effects their potential causes and to detect future changes Quantification of theatmospheric emissions of multiple pollutants needs to be improved as does an understanding of theprocesses influencing fugitive emissions and local and regional deposition patterns The influence ofmultiple stressors on biota exposure and response from natural bitumen and forest fires to climatechange complicates the current ability to attribute effects to air emissions from the industry Howeverthere is growing evidence of the impact of current levels of PACs on some species pointing to the needto improve the ability to predict PAC exposures and the key emission source involved Although thiscritical review attempts to integrate some of the findings across the components in terms of ECCCactivities increased coordination or integration of air water andwildlife researchwould enhance deeperscientific understanding Improved understanding is needed in order to guide the development of long-term monitoring strategies that could most efficiently inform a future adaptive management approachto oil sands environmental monitoring and prevention of impacts

Implications Quantification of atmospheric emissions for multiple pollutants needs to beimproved and reporting mechanisms and standards could be adapted to facilitate such improve-ments including periodic validation particularly where uncertainties are the largestUnderstanding of baseline conditions in the air water and biota has improved significantlyongoing enhanced monitoring building on this progress will help improve ecosystem protectionmeasures in the oil sands region Sentinel species have been identified that could be used toidentify and characterize potential impacts of wildlife exposure both locally and regionallyPolycyclic aromatic compounds are identified as having an impact on aquatic and terrestrialwildlife at current concentration levels although the significance of these impacts and attributionto emissions from oil sands development requires further assessment Given the improvement inhigh resolution air quality prediction models these should be a valuable tool to future environ-mental assessments and cumulative environment impact assessments

CONTACT JR Brook Jeffbrookutorontoca Dalla Lana School of Public Health and Department of Chemical Engineering and Applied ChemistryUniversity of Toronto 223 College Street Toronto Ontario M5T 1R4 QC CanadaColor versions of one or more of the figures in the paper can be found online at wwwtandfonlinecomuawm

Supplemental data for this paper can be accessed on the publisherrsquos website

JOURNAL OF THE AIR amp WASTE MANAGEMENT ASSOCIATION2019 VOL 69 NO 6 661ndash709httpsdoiorg1010801096224720191607689

copy 2019 The Author(s) Published with license by Taylor amp Francis Group LLCThis is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (httpcreativecommonsorglicensesby-nc-nd40) which permits non-commercial re-use distribution and reproduction in any medium provided the original work is properly cited and is not altered transformed or builtupon in any way

Introduction

The Canadian Oil Sands (OS) are predominantlylocated in the northern half ofAlberta with a small portion in cen-tral-western Saskatchewan In sizethe OS is 142000 km2 and is esti-mated to include approximately 17trillion barrels of oil in the form ofbitumen although the recoverableamount of oil is only about 10 ofthat amount or 1634 billion barrels(Natural Resources Canada Canada

2017) This still makes the OS the third largest known

reserve of oil on earth Once recovered bitumen whichis highly viscous and enriched in sulfur carbon nitro-gen and metals and deficient in hydrogen comparedwith conventional and heavy crude oil requiresupgrading The bitumen extraction separation andupgrading processes that ultimately produce syntheticcrude oil consume energy and resources and producewaste which can pose environmental risks

Two major rivers the Peace River and the AthabascaRiver (AR) both originating from headwaters in the RockyMountains flow through the OS region The glacial-fedAthabasca River is the longest in Alberta its watershedencompasses nearly one quarter of the province From its

Figure 1 Northern Alberta showing the Athabasca River the Peace River the Peace-Athabasca Delta (PAD) and the oil sandsdeposits

JR Brook

662 JR BROOK ET AL

mountainous origins it flows for approximately 1000 kmbefore encountering the large near-surface deposits ofbitumen in the area just north of Fort McMurray thelargest city in the region (population of the RegionalMunicipality of Wood Buffalo which includes the citywas 71589 in 2016) The Athabasca River is a source ofdrinking water for Fort McMurray and the river is anessential source of fresh water for bitumen recovery andprocessing Both rivers empty into Lake Athabasca to thewest of Lake Athabasca they form the Peace-AthabascaDelta (PAD) which is also 200 km downstream fromwhere the Athabasca River flows through the near-surfaceOS deposits The PAD is one of the largest freshwater deltason earth and has been designated as a wetland of interna-tional importance (through the Ramsar Convention) anda United Nations Educational Scientific and CulturalOrganization (UNESCO) World Heritage Site The PADis also partially withinWood Buffalo National Park Figure1 includes a map that provides perspective for the area

There is tremendous biodiversity in the PAD withmillions of migratory birds passing through annuallyThe Lower Athabasca River (LAR) subbasin containsFort McMurray the majority of the OS deposits theMcMurray Formation and the PAD Indigenous inhabi-tants of the region include the Mikisew Cree First Nationand Athabasca Chipewyan First Nation with traditionallands in the region downstream of Fort McMurrayincluding the PAD Others include the Fort McKay FirstNation the Fort McMurray First Nation and MeacutetisLocals who have traditional lands near Fort McMurrayand in and around the active oil sands surface miningregion Oil sands development poses potential risks to theenvironmental health of this part of Canada as well as tothe populations residing there Consequently effectiveenvironmental management of the OS development isan essential responsibility of all stakeholders

The potential value of the OS has been recognized forover a century but economically viable processes torecover this ldquounconventionalrdquo oil from deposits near thesurface became available in the second half of the 1960sAdvances in technology for extraction and in environ-mental protection have been continual since that timeincluding approaches to access what constitutes themajority (approximately 80) of the bitumen that isfarther below the surface using in situ techniques (becauseOS deposits that start deeper than about 70 m are notaccessible through open-pit mining in situ extractionapproaches are required) Collectively through thesetwo processes production in the OS has been yieldingon the order of 27 million barrels of oil per day (NaturalResources Canada Canada 2017) from 045 million cubicmeters (m3) of raw bitumen processed per day (AlbertaEnergy Regulator Canada 2017)

An important driver for technical advance in the OSindustry has been to increase the ratio of bitumen produc-tion to energy input which represents both an economicand an environmental benefit Water consumption hasbeen another key driver with the main options forenhanced environmental performance being reduction inthe amount of freshwater required for bitumen recoveryand processing water recycling which leads to innovationin the clearing in fine suspended tailings in the ponds anduse of more deep saline groundwater in the in situ processCleanup of tailings pond water for reuse and eventualrelease into the watershed so that the land can be reclaimedis another key challengeWith these and other accomplish-ments the current OS industry represents an impressiveengineering achievement for this important economic dri-ver of the Canadian economy

Motivation for the Joint Oil Sands MonitoringProgram (JOSM)

The environmental performance of OS development hasbeen under considerable public scrutiny The prevailingnarrative continually positions their significant contribu-tion to Canadarsquos economy and energy security againstpotential environmental damage and impact to FirstNations communities (Dowdeswell et al 2010)Understanding the extent of the potential environmentaldamage so that its characteristics magnitude and long-term implications can inform public debate and publicpolicy decisions about development is critical Howeverthere has been debate concerning the availability of opentransparent and credible data sources that could be used inmaking sound evidence-based policy and regulatory deci-sions in the OS region The scale and scope of the OSdevelopment means that environmental impact is likelyand some level of management of this impact is required

Given the importance to Canada a Royal Society ofCanada (RSC) panel was tasked with undertakinga comprehensive evidence-based assessment of themajor environmental and health impacts of CanadarsquosOS industry The RSC panel sought to offer Canadiansan independent review assessing the available evidenceand identifying knowledge gaps (The Royal Society ofCanada 2010 Weinhold 2011) The Canadian FederalMinister of the Environment also established a panel(OS Advisory panel) charged with ldquoDocumentingreviewing and assessing the current body of scientificresearch and monitoringrdquo and ldquoIdentifying strengthsand weaknesses in the scientific monitoring and thereasons for themrdquo (Dowdeswell et al 2010) The findingsof these two panels released in 2010 provide context forthe initiation of JOSM (Joint Canada-AlbertaImplementation Plan for Oil Sands Monitoring 2012)

JOURNAL OF THE AIR amp WASTE MANAGEMENT ASSOCIATION 663

Their full reports are available (Dowdeswell et al 2010The Royal Society of Canada 2010) and an overview oftheir findings in the context of this critical review isprovided in Section S11 of the supplemental material

The OS Advisory panelrsquos overarching recommenda-tion was that a shared national vision and managementframework of aligned priorities policies and programsbe developed collaboratively by relevant jurisdictionsand stakeholders based upon four key fundamentalsldquoAn holistic and integrated approach An adaptiveapproach A credible scientific approach andA transparent and accessible approachrdquo The RSC panelrsquosview was that the lack of availability of environmentaldata collected by current developments and operations inthe OS region meant that timely comprehensive assess-ments of the data were not taking place and that con-sistent with the OS Advisory panelrsquos findings providingwider access to monitoring data was a priority forimproving cumulative impact assessment JOSM wasestablished at least partially in response to this priority

The scope of this critical review

This critical review covers the main objectives and find-ings of the (now) Environment and Climate ChangeCanada (ECCC) research and monitoring supportingJOSM with an emphasis on atmospheric emissionsand their potential impacts on air quality and depositionand linkages to water quality and potential impacts onwildlife The conclusions and gaps summarized fromthis ECCC work are generally reflective of reports andpublications up through approximately 2018 In addi-tion to ECCC scientific results some of the existingknowledge and activities prior to the enhanced effortsbrought about by the implementation of JOSM andsome of the non-JOSM work are discussed in this cri-tical review Landscape disruption and habitat loss havelong-term influences on wildlife and ecosystems andattention is being paid to this issue in the OS (AlbertaBiodiversity Monitoring Institute Canada 2019) but arenot discussed in this review Greenhouse gas emissionsare also a critical issue for the OS but are outside thescope of this review Human health effects are alsoa potential concern and were discussed by the RSCpanel but they are also not covered in this review

JOSM is a partnership involving both the Provinceof Alberta and the Government of Canada Given thatthe focus of this review is largely on scientific workundertaken at ECCC in the context of air emissions itdoes not represent a full review of the JOSM science orprogram Nonetheless recognizing that it is helpful totake stock of scientific progress on a regular basis toguide future work it is hoped that this critical review

can play a role in ECCCrsquos integrated planning and mayalso contribute to a future full JOSM science integra-tion and assessment (ie federal and provincial find-ings) ultimately supporting adaptive management ofOS ecosystem impact monitoring

This critical review consists of (1) objectives of JOSMand evidence of impacts (2) challenges of assessing eco-system effects (3) main findings from the AirComponent Air Component applications to the (4)Water and (5) Wildlife Contaminants and ToxicologyComponent and (6) concluding remarks Two ldquointegrat-ing themesrdquo were of interest across components polycyc-lic aromatic compounds (PACs) and mercuryA summary on PAC integration (Harner et al 2018) isreported in this critical review The issue of acid deposi-tion was considered in an integrated manner buildingupon a long monitoring history in this area (ie the AcidRain Program beginning in the 1970s) and results arehighlighted in this critical review (Makar et al 2018)

JOSM objectives

Expanding upon the recommendations of the EC PanelJOSMrsquos main objectives (Joint Canada-AlbertaImplementation Plan for Oil SandsMonitoring 2012) were

(1) Support sound decision-making by govern-ments as well as stakeholders

(2) Ensure transparency through accessible com-parable and quality-assured data

(3) Enhance science-based monitoring forimproved characterization of the state of theenvironment and collect the information neces-sary to understand cumulative effects

(4) Improve analysis of existing monitoring data todevelop a better understanding of historicalbaselines and changes

(5) Reflect the transboundary nature of the issue andpromote collaboration with the governments ofSaskatchewan and the Northwest Territories

At the beginning of JOSM implementation therewas extensive existing monitoring in the OS region(Figure S11) and the starting goals for JOSM were toenhanceimprove these activities In practice multiplefocused monitoring or research projects mainly per-tinent to objectives 3 and 4 were initiated by ECCC tocharacterize general baseline conditions and developmethods useful to detect changes in the environmentin order to make progress on understanding cumula-tive effects

664 JR BROOK ET AL

Evidence of potential impacts

There were at least five lines of evidence that informedJOSM studies

Snowpack measurements Historical cores of lake sediments and peat Air monitoring Samples of the biota (eg lichen or wildlife) Atmospheric modeling results

Kelly et al (Kelly et al 2010 2009) measured PACs andmetals in snow atmultiple locations in theOS developmentarea There was a clear decrease in the amount deposited inthe snowpack in relation to distance from the OS opera-tions The work also demonstrated that pollutants from the

OS activities entering aquatic ecosystems during snowmeltalthough the fate of these pollutants as they traveled fromthe atmosphere to the land and to the local streams tribu-taries and rivers required more study as did the potentialfor impacts on biota Willis et al (2018) revealed a similarpattern for mercury deposition Key questions arising fromthese snowpack studies were the following Do thesedeposition patterns occur every winter What is the spatialpattern of the deposition and how far away from thesources are these pollutants deposited at levels above back-ground Are aquatic species affected when these pollutantsreach aquatic ecosystems

Long-term trends in PAC deposition (Kurek et al2013) provided further evidence that pollutants werebeing transported away from OS operations As shownin Figure 2 dating the layers in sediment cores showed

Figure 2 Long-term trend in PACs in lake sediment cores sampled from the five to six lakes proximate to major oil sands operationsData represented as standardized values (Z scores) Upper graph (A) shows a change in visible reflectance spectroscopy (VRS) ofchlorophyll (indicative of productivity) Middle graph (B) shows the total polycyclic aromatic hydrocarbon (PAH) concentrations andthe bottom graph (C) shows the total dibenzothiophene (DBT) concentrations The lines are from two segmented piecewise linearregression models to identify the timings of breakpoints (from Kurek et al 2013)


that deposition and accumulation of PACs in the envir-onment started to increase around 1970 congruentwith the time that oil sands industrial activity and oilproduction began to increase There has been a cleartrend of increasing PACs since that time

Enhanced air monitoring using passive samplersundertaken by the Wood Buffalo EnvironmentalAssociation (WBEA) found that pollutants related toacid deposition (ie sulfur dioxide [SO2] nitrogen diox-ide [NO2] and nitric acid [HNO3]) were moving fromsource areas to natural ecosystems (Hsu 2013) The RSCreport identified monitoring results even farther down-wind in Saskatchewan and although there was no evi-dence of OS-related SO2 in the available data NO2 waselevated up to 150 km east of the provincial border withAlberta (The Royal Society of Canada 2010) Satelliteproducts derived from multiple years of overpasses(Figure 3) show that NO2 is elevated over a large area intheOS region Comparison of images across time revealedthe magnitude of the increase in NO2 concentrations overthe northern part of the near-surface deposit region andthe size of the area impacted (see also Figure S35)

WBEA was and continues to be responsible forcompliance-oriented monitoring in the region Withsupport from the OS industries WBEA has also estab-lished a range of research programs designed to helpclose the knowledge gaps relevant to studying the fateand impact of OS air pollutant emissions (WoodBuffalo Environmental Association Canada 2018)

Early results of this work are summarized by Percy(2012) Of relevance here are the measurements ofmetals and PACs in lichen collected at multiple loca-tions and distances from the emission sources(Studabaker et al 2012) This early report againdemonstrated that air pollutants were being depositedinto the environment downwind of the OS activities

Atmospheric models have frequently been applied tothe OS area for a variety of purposes (eg Jung and Chang2012) but particularly for air quality management (Davies2012) Although much modeling work was undoubtedlydone to assess the impacts of specific new sources as part ofthe development approvals process larger-scale modelshave provided estimates of the regional transport and fateof emissions from the OS emissions They demonstratethat primary air emissions andor their secondary productscan move and be deposited far downwind During thedevelopment of the ECCC-JOSM Air Component scienceplan deposition estimates were produced from ECCCrsquosmodeling system and compared with the available aquaticand terrestrial critical load maps (Aherne 2011) Theseanalyses suggested that critical loads were potentiallybeing exceeded (Figure S12) especially in the acid-sensitive areas located in northern Saskatchewan

Given clear evidence of the movement of a variety ofair pollutants into the environment ldquobeyond the fencelinesrdquo the critical questions were (and remain) the follow-ing Are effects occurring If yes how significant are theyCan they be attributed to air pollutants from the OS If

Figure 3 Increase in average column nitrogen dioxide (NO2) over the oil sands region between 2005ndash2007 and 2008ndash2010 observedfrom the ldquoOMI satelliterdquo Upper right images show spatial patterns in column NO2 and the lower accompanying images show thegrowth in development between 2005 and 2009 from Landsat The background image is 2005ndash2010 average column NO2 from OMIover northwestern United States and western Canada(adapted from McLinden et al 2012)

666 JR BROOK ET AL

no given the long-term accumulation of deposited pollu-tants in the ecosystems and the expected growth in devel-opments in the OS are significant effects expected in thefuture And finally is the monitoring system in placeadequate for early detection of these effects to ensurethat they can be managed and possibly mitigated Interms of this latter question the perspectives of the ECand RSC panels were that the monitoring system neededimprovement Also an important concept for futuremonitoring as expressed by the EC Panel and recognizedin implementing JOSM was that it needs to be adaptive(eg able to change to address new evidence or monitor-ing needs in a timely manner)

The challenge of measuring ecosystem effects

Although the origin of potentially harmful contaminants inthe ecosystem could be direct release or contaminatedgroundwater seepage to the watershed or possibly spillageonto land areas atmospheric deposition is a well-documented pathway in the OS as discussed aboveHowever once taken up by the biota the original pathwayis difficult to discern and measuring and interpreting theeffects of these exposures represents an ongoing challenge

Given what science is beginning to appreciate aboutlow-dose effects and the effects of combinations ofstressors (Dziedek et al 2016 Gerner et al 2017 Liesset al 2016) it is uncertain whether single-pollutant or -stressor guidelines can be sufficient even if set withprecautionary margins to serve the desired cumulativeeffects management approach Nonetheless applyingsingle-indicator measures requires an evaluation pro-cess (The Royal Society of Canada 2010) For toxics inaquatic ecosystems as an example this generallyinvolves chemical and biological measurements to char-acterize water quality using best available criteria andsetting effects-based objectives in the context of back-ground conditions (eg specific to the LowerAthabasca River) To determine whether there is unac-ceptable risk thresholds or critical effect sizes (CESs)for ecosystem safety are needed Ideally biologicallyrelevant CESs should be defined a priori and shouldconsider the type and magnitude of change that is likelyto be of concern (Munkittrick et al 2009) What istraditionally available in Canada at least are guidelinesset by government agencies such as the CanadianCouncil for Ministers of the Environment (CCME)which has established guidelines for surface water qual-ity (CCME Canada 1999) US EnvironmentalProtection Agency (EPA) guidelines also support eva-luation of the potential level of risk (U S EPA 2019a)

There are numerous aspects of ecosystems that could bemonitored for evidence of potential impacts and that need

to be considered to meet the RSCrsquos recommendationregarding cumulative effects management In general airpollutants that can elicit an ecosystem or biotic responsethrough deposition are classified into the following cate-gories acidifying pollutants eutrophying pollutants traceelements and polycyclic aromatic compounds (PACs)(Wright et al 2018) In order to monitor these and inves-tigate potential impacts and ldquoleading-edgerdquo indicators ofecosystem effects certain indicators or biotic responsemeasures have been examined andor proposed Forinstance some examples of ecosystem effect or healthindicators that may be relevant in the OS include criticalload critical level acid neutralizing capacity ground-levelozone exposure indices (Accumulated Ozone exposureover a Threshold of 40 ppb [AOT40] The sum of hourlyozone concentrations equal to or greater than 60 ppb overthe daylight period 0800 ndash 1959 [SUM60]) eutrophicload nitrogen saturation algae bloom acidity of ombro-trophic bogs biodiversity of plants or animals forest resi-lience toxicity to biota chemical burden in animal tissuesand embryos reproductive success of animals animalstress and death human health arising from multipleexposure routes and human stress (fear of direct pollutanteffects or of food security and food and water safety) Theseexamples largely involve biological (eg biodiversityhealth of animal and vegetation species and humans) andchemical-physical (eg atmospheric deposition amountswater chemistry) indicators and do not reflect potentialsystems-based indicators (eg adaptive capacity resilience)and traditional ecological knowledge (TEK)

In terms of systems-based indicators combinations ofthe indicators in the example list may provide insight intothe state of the whole system a concept that could bedeveloped in the future Monitoring forest health repre-sents a form of a systems-based indicator Thus theTerrestrial Environmental Effects Monitoring (TEEM)program operated by WBEA (Jacques and Legge 2012Percy Maynard and Legge 2012) strives to obtain a widerange of measures at multiple forest plots including atmo-spheric inputs and is a valuable resource for trackingchange over the long term which may then trigger follow-up to identify potential causes TEK must also be includedin an adaptive monitoring program to provide insight onecosystem health As an exampleWBEA has been workingwith local indigenous harvesters to examine concernsregarding the health of local wild berry plants and safetyissues regarding the consumption of wild berriesPerceptions of appearance and taste are being exploredwith data on chemical composition and potential contami-nant load (Wood Buffalo Environmental AssociationCanada 2019)

In terms of the biological and chemical-physical indica-tors clear criteria regarding thresholds of effects are


difficult to determine and may be outdated Chemical-physical indicators exist to provide an easier-to-monitorand early warning approach for tracking biologicalresponse (ie the chemical-physical and biologicalresponse indicators are correlated but are not the biologicalresponse per se) Munkittrick and Arciszewski (2017) con-sidered the case of changes in PACs in sediment cores inthe Cold Lake Alberta area as reported by Korosi et al(2016) They pointed out that as our capacity to detect anychange advances we also require a counterbalance toaccount for ldquotrivialrdquo change Their suggestion was thatthis could be done through an interpretative frameworkbased on contextualization of differences the goal is togenerate meaningful information for environmental mon-itoring programs and potential actions A critical part ofthe proposed framework is data on normal ranges con-sidering site-specific local and regional (distant) levelsDifficulties remain in contextualizing the levels of expo-sure complicated by noisy baselines or small changes thatare or may be well below expected levels for ecologicalimpact (Willis et al 2018 Summers et al 2016) Ideallysuch a framework would be developed and would beroutinely applied to monitoring data to determine whena change has occurred that is considered ldquosignificantrdquo andthat warrants further study (Arciszewski et al 2017a)

Examples of air pollutionndashrelated indicators

A critical load is defined as ldquoa quantitative estimate of anexposure to one ormore pollutants belowwhich significantharmful effects on specified sensitive elements of the envir-onment do not occur according to present knowledgerdquo(Nilsson and Grennfelt 1988) A critical level for vegetationis defined as the ldquoconcentration cumulative exposure orcumulative stomatal flux of atmospheric pollutants abovewhich direct adverse effects on sensitive vegetation mayoccur according to present knowledgerdquo (Convention onLong-Range Transboundary Air Pollution [CLRTAP]2017) Most of the currently specified critical levels identifya threshold meant to protect a certain percentage of speciesat a given confidence level usually set to a level where theimpacts will become discernible (eg 5ndash10 damage)However they are still single-stressor (eg ozone) indica-tors that do not take into account the impact of climate orsoil and plant factors associated with ozone uptake More-detailed calculations that for instance estimate the phyto-toxic ozone dose (POD) above a given threshold are pre-ferred where possible (CLRTAP 2017)

Internationally recognized procedures for the gen-eration and use of critical level and critical load datahave been set out in the United Nations EconomicCommission for Europersquos (UNECE) Convention onLong-Range Transboundary Air Pollution (CLRTAP

2017) Development of location-specific critical loadsfor sulfur and nitrogen deposition that reflect thepotential for an ecosystem response or a biologicaleffect required years of monitoring and research onacid deposition and eutrophication Through thiswork exposure models were developed to estimate anecosystem-specific critical load based upon terrestrialor aquatic ecosystem parameters For acidifying deposi-tion these include the Simple Mass Balance (SMB)model for terrestrial ecosystems and the Steady-StateWater Chemistry (SSWC) and First-Order AcidityBalance (FAB) models for aquatic ecosystems(CLRTAP 2017) These models are based on the con-cept of determining the charge balance of ions in soilwater (terrestrial ecosystems) or within lakes (aquaticecosystems) exceedances are thus with respect to theextent to which strong anion deposition that canrsquot bebuffered by cations present in andor being depositedto the ecosystem is above an anion threshold whichwill depend on the sensitive plant or animal specieswithin the ecosystem It should be noted that theseUNECE-recommended models for critical loads areldquosteady-staterdquo models they only indicate that ecosystemdamage at a given total deposition level (or calibratedto a specific wet deposition amount) will occur at somepoint from the present time to some point in the futureThey do not provide the time frame to when the effectswill become noticeable (which could potentially be any-where from an immediate impact to years or evencenturies in the future) This is a drawback of themethodology but exceedances of critical loads havenevertheless been considered at least in Europe suffi-cient cause to enact legislation designed to reduce acid-ifying emissions

Dynamic critical load modeling has been attemptedas another approach with the potential to estimate thetime-to-effect for critical load exceedances these mod-els were originally intended as a means to estimate thetime-to-recovery of damaged ecosystems (CLRTAP2017) However the CLRTAP protocols stress thedependence of dynamic models on very accurate localdata and recent work in Canada suggests that dynamicmodels are so poorly constrained by lack of this infor-mation to preclude their use for policy decisions relat-ing to acidifying deposition (Whitfield and Watmough2015) Variations on the CLRTAP (2017) acidifyingdeposition critical load estimating procedures and for-mulae have been constructed usually employing sim-plifying assumptions andor local information Anexample is the protocol agreed upon by the NewEngland GovernorsndashEastern Canadian Premiers (NEG-ECP 2001 Ouimet 2005) that has been used in the pastto create Canada-wide acidifying deposition critical

668 JR BROOK ET AL

load data sets (Aherne and Posch 2013 Carou et al2008 Jeffries et al 2010) These data are used in thecontext of the OS later in this review

Critical loads may also be calculated for the deposi-tion of toxic heavy metals (cadmium lead and mer-cury) (CLRTAP 2017) As for acidifying depositioncritical loads for toxic metals are calculated based onthe receiving ecosystem (terrestrial or aquatic) but arefurther subdivided into the metalsrsquo impact on humanhealth versus ecosystem functioning The human healthimpacts result from uptake of metals into human foodsources and groundwater (metal content in foodfoddercrops grass and animal products the total metal con-tent in soil water below the rooting zone and the metalconcentration in fish) The impacts on ecosystem func-tioning include the free metal ion concentration in soilsolution (impacts on invertebrates plants and soilmicroorganisms) the total metal concentrations in for-est humus (impacts on invertebrates and microorgan-ism impacts) and the total metal concentration infreshwater (impacts on the food chain from algaethrough to top predators) As with acidifying pollu-tants exceedances for metal critical loads only indicatethat at this estimated critical input flux rates harmfuleffects will eventually occur but not when they willoccur Metal critical load calculations have additionalconstraints or limiting factors (1) they may not becalculated for locations where more water is lost thangained (preventing soil leaching and leading to theaccumulation of salts and high pH) and for soils withreducing conditions such as wetlands and (2) they donot include weathering inputs of metals (which areusually of low relevance and are difficult to calculateaccurately but may influence metal levels at locationswhere the geological content of metals is high)Interactions between heavy metals and acidity whetherwhen in the atmosphere (ie on aerosols) or upondeposition are also challenging to consider but maybe important given that acids can convert metals intomore bioavailable forms (eg water soluble)

Even though reasonably well developed thereremain uncertainties and data limitations with criticalloads and levels as highlighted above In terms ofnitrogen deposition before an ecosystem is declaredto be in a state of nitrogen saturation (Earl Valett andWebster 2006 Jung and Chang 2012) that can lead togreater risk of acidification there are increases innutrient load or eutrophic load (Smith Tilman andNekola 1999) Beneficial to some plant and tree spe-cies and not to others shifts in plant success andbiodiversity can occur disrupting the natural state(Kwak Chang and Naeth 2018) which may requirea long period of time to reverse It is difficult to

determine the level of perturbation that is acceptablebecause it is happening over a continuum and theform of the nitrogen (eg reduced oxidized ororganic) and interactions with base cations also hascritical roles such that there is high diversity in thelevel of nitrogen sensitivity among ecosystems(Bobbink et al 2010) Excess nutrients can also havean impact on the allocation of belowground resources(Varma Catherin and Sankaran 2018) such as devel-opment of root systems (Majdi and Kangas 1997)which may increase vulnerability or resilience toother stressors such as frost drought fire and winddamage (Bobbink et al 2010) Thus assessing andprojecting the impacts of nitrogen deposition and set-ting a nutrient nitrogen critical load for the OS regionremains challenging (Murray Whitfield andWatmough 2017) Similarly in regard to fertilization(Mullan-Boudreau et al 2017) or neutralization ofacidity in bogs due to input of basic material (egdust from soil erosion) an acceptable amount ofdecrease in acidity is challenging to determineSetting thresholds for nutrient loads in aquatic eco-systems (eutrophication) is also challenging given thevariability among ecosystems However within certaintypes of environments critical loads have been estab-lished and in some cases an unacceptable point(ldquothresholdrdquo) can be obvious because an undesirableoutcome such as excess algae is highly visible

Challenges in setting thresholds

Although thresholds or critical loads for some heavymetals exist there is less information on toxicitythresholds based upon the levels of chemicals measuredwithin biota and there is variability among species Foroverall ecosystem protection this necessitates identifi-cation of sentinel species which could be a plant oranimal in any ecosystem (Cruz-Martinez and Smits2012) Species selection criteria include feasibilityreproducibility sensitivity ability for laboratory valida-tion capability for long-term monitoring noninvasive-ness or nonlethality ability to setmeasure an effects-based threshold and cost-effectiveness

For a selected sentinel species death (eg the ldquocan-ary in a coal minerdquo concept) is an obvious thresholdbut given the availability of different assessment meth-ods and the sensitivity of modern analytical equipmentit is possible to use measures not based on lethalitynew monitoring methods continue to change what ispossible to measure and observe Although contami-nant load in a range of species has been used exten-sively such as mercury levels in fish or colonialwaterbird eggs (Campbell et al 2013 Evans and


Talbot 2012) andor persistent organic pollutants(POPs) in mammals (Metcalfe 2012) laboratory-basedanalytical measures are becoming more preciseMetabolites in animal blood or tissue gene expressionmeasures (Gagneacute et al 2012 Marentette et al 2017Simmons and Sherry 2016) and epigenetic changes(Brander Biales and Connon 2017) can be measuredand can show evidence of change before the animalrsquoshealth and survival are compromised Other cellularapproaches extending from macroscale measures oforgans (liver gonads thyroid) and immune measures(eg Gagneacute et al 2017) to telomere dynamics (Molleret al 2018) are also available or being explored Thesecellular or molecular markers may also respond ina dose-dependent manner with or without an apparentthreshold

Much like particulate air pollution effects in humanswith no discernible threshold in relation to prematuremortality and an increasing number of preclinical mea-sures the appropriate safe threshold for some indicatorsand most molecular markers of biological effects in nature(ie wild animals) remains unclear This is even morecomplicated in the context of the challenge of chronic low-dose exposure which is an ongoing process occurring inthe OS Precaution regular reassessment and continuousimprovement is the prudent approach Ultimately indica-tors based upon metabolomics proteomics epigenomicsetc may be the preferred approach given that trackingsingle chemicals is not fully reflective of the mixtures thatoccur in reality Bradley et al (2019) recently assessedmultiple indicators of cumulative contaminant effects(hazard) for in-stream biota including in silico approachessuch as ToxCast (EPA 2017) High-throughput methodsfor wildlife based on gene arrays and microarrays are alsobeing developed Bradley et al (2019) point out that giventhe 80000+ parent compounds estimated to be in currentuse globally and the ldquoinestimable chemical-space of poten-tial metabolites and degradatesrdquo from these compoundstoxicity assessment remains a major challenge

The adverse outcome pathway (AOP) is a conceptualframework for organizing existing knowledge concern-ing biologically plausible and empirically supportedlinks between molecular-level perturbation ofa biological system and an adverse outcome at a levelof biological organization of regulatory relevance(Villeneuve et al 2014) This resembles the exposomeconcept (Wild 2012) being explored to improve under-standing of how environmental factors lead to chronicdisease in humans (Rappaport and Smith 2010 Wild2012) To be repeatable and adaptable to multiple typesof ecosystems (or individuals) AOPs must be devel-oped in accordance with a consistent set of core prin-ciples (Villeneuve et al 2014)

Potential of remote sensing

The indicators discussed above require tracking effects ldquoonthe groundrdquo through repeated monitoring The exceptionmight be using atmospheric models to identify areas ofcritical load exceedances and setting new emission regula-tions so that future deposition is deemed acceptably belowexceedance levels However field observations are stillnecessary to verify that the desired outcomes are beingachieved The cost of this tracking or monitoring may beconsiderable especially in remote yet sensitive areas andcould benefit from more efficient approaches Remotesensing is receiving attention in this regard (AndrewWulder and Nelson 2014 De Araujo Barbosa Atkinsonand Dearing 2015 Kerr and Ostrovsky 2003 Knox et al2013 Sioris et al 2018) If satellite observations could beused for early warnings of change then there could be costsavings while also increasing the size of the area possible tohave under surveillance Mapping ecosystem servicesincluding in natural wetlands is one potential possibilityfor this information (Radeva Nedkov andDancheva 2018Zergaw-Ayanu et al 2012) For satellite observations suffi-cient temporal spatial and spectral resolutions are neededAlso for such indices to be sensitive to important charac-teristics of the ecosystems and their functional attributessatellite data need to provide the ability to track phenolo-gical changes and understand interannual variability ofecosystem processes (Paruelo et al 2016) Although satel-lites or other types of remote sensing (eg from aircraft-based aerial surveys) are not capable of providing all that isneeded for cumulative effects monitoring including theneed for strong empirical data allowing early detection ofecological change (Lindenmayera et al 2010) they couldplay a valuable role in remote areas such as the OS

Main findings from the ECCC Air Componentprogram of JOSM

Four overarching questions were posed to guide scien-tific activities toward meeting the Air Componentobjectives

(1) What is being emitted from the oil sandsoperations how much and where

(2) What is the atmospheric fate (transport trans-formation deposition) of oil sands emissions

(3) What are the impacts of oil sands operationson ecosystem and human health

(4) What additional impacts on ecosystem healthand human exposure are predicted as a resultof anticipated future changes in oil sandsdevelopment

670 JR BROOK ET AL

Focused studies involving short- and long-term fieldmeasurements (ground and airborne) were undertakento answer the first two questions and to support waterand wildlife research in answering the third questionIn addition to these monitoring and research activitiesan approach to integrate the information gathered fromthe ambient and emission monitoring using air qualitymodels as well as satellite-based information wasincluded in the Integrated Monitoring Plan(Environment Canada 2011) Information from airquality models provide essential input to ecosystem-and health-based models ultimately providing insightinto the potential human and ecosystem health impactsfrom the OS (fourth question) (Environment Canada2011)

Improving understanding of emissions to theatmosphere

Among the complex open-pit mining and oil extrac-tion processes in the surface mining facilities of theOS pollutants are mainly emitted from five pro-cesses (1) exhaust from off-road vehicles used forremoval of the surface overburden and for excava-tion and transportation of the oil sands ores to anextraction plant (2) ore processing at the extractionand upgrading plants resulting in stack emissions(3) fugitive volatile organic compound (VOC) emis-sions from mine faces tailings ponds and extractionplants and volatilization of fuels used for industrialactivities and vehicles (4) fugitive dust emissionsfrom surface disturbances by the large fleet ofmining and transportation vehicles and (5) wind-blown dust emissions from open surfaces such asmine faces and tailings pond periphery beachesThese emissions are superimposed on other emis-sions such as on-road vehicle exhaust wildfiresresidential wood combustion and other industries(eg cement construction) several of which areengendered by population growth owing to OSemployment

The National Air Pollutant Release Inventory(NPRI) and the complementary Air PollutantEmissions Inventory (APEI) contain annual emissionestimates for the region NPRI (Government ofCanada Canada 2019a) includes data reported byfacilities on releases disposals and recycling of over300 pollutants NPRI collects data from over 9000industrial facilities nationwide including the OSthat meet specified reporting criteria and whoseemissions meet or exceed reporting thresholds forNPRI-listed substances The APEI expands on theofficial annually reported data quantifying emissions

from a range of other important sources (eg motorvehicles agricultural activities natural and opensources etc) for several common air pollutants byprovinceterritory and for all of Canada(Government of Canada Canada 2019b) Accordingto the 2013 NPRI which was the year available at thestart of the Air Component program emissions fromAlbertarsquos OS sector accounted for 61 34 and 14of the provincial total reported VOC SO2 and nitro-gen oxide (NOx) emissions respectively The OS sec-tor was also a large source of particulate matter (PMor total PM [TPM]) and carbon monoxide (CO)emissions in 2013

NPRI specifies reporting thresholds for ldquolisted sub-stancesrdquo that extends beyond the criteria air contami-nants (CACs) and includes range of VOCs such asbenzene toluene ethylbenzene and xylenes (BTEX)and some polycyclic aromatic hydrocarbons (PAHs)(Li et al 2017) Given the complexity of the OS pro-cesses that produce atmospheric emissions of primarypollutants and the potential for secondary formation ofother pollutants it was suspected that otherldquounknownrdquo or ldquounmeasuredrdquo pollutants would be pre-sent in the air over and downwind of the regionTherefore a key part of addressing the first question(ldquoWhat is emittedrdquo) was the need for more detailedambient measurements from the air and the groundThese new data were expected to help determine whatother pollutants might be important to understand inthe context of emission reporting future long-termmonitoring needs and potential for ecosystem andhuman health effects

The NPRI and APEI have traditionally been usedfor the fine-scale air quality monitoring and modelingnecessary to characterize the air emission sources andtheir associated impact on air quality However inthe development of the Air Component program itwas recognized that this inventory did not contain themultipollutant and multiscale air quality informationat the finer spatial and temporal scales necessary tosatisfy the JOSM objectives Therefore a review of 10available national provincial and subprovincial emis-sion inventories in 2012 (Alberta Environment andSustainable Resource Development 2013) was under-taken leading to a new hybrid inventory (JOSMCanada 2016 Zhang et al 2018) The hybrid inven-tory which also included better representation ofspatial and temporal emission patterns was expectedto improve results from the daily air quality modelruns These runs commenced in 2013 for the firstintensive field study in August and September ofthat year and have continued since that time(Figure S33)


Uncertainties in the OS emissionsThe criteria air contaminant (CAC) emissions from theOS (including NOx VOCs SO2 ammonia [NH3] COand PM with aerodynamic diameters lt25 and lt10 μm[PM25 and PM10]) have different degrees of uncertain-ties and conversely reliabilities (Alberta Environmentand Parks 2016) As shown in Figure 4 the most reliableemission data (ie in the hybrid inventory) are for SO2with about 80 of the emissions monitored by contin-uous emission monitoring systems (CEMS) but alsowith significant contributions estimated through theuse of site-specific and generic emission factors (EFs)The latter would have larger uncertainties comparedwith those obtained through CEMS even though theCEMS data may also need external evaluation ForNOx the fraction of emissions monitored by CEMSdrops substantially to ~30 and the majority of theemissions were estimated using site-specific or genericEFs For VOCs there were few actual emission mea-surements application of site-specific EFs accountedfor about 20 of the estimated emissions whereas theremaining emissions were derived from generic EFs orengineering judgment These emission reports werethus expected to have much higher degrees of uncer-tainty compared with those for SO2 The same can besaid about CO and PM emissions from the oil sandssurface mining facilities Current knowledge on PMemissions was reviewed recently by Xing and Du(Xing and Du 2017)

Recognizing the likelihood of emission uncertaintiesthe hybrid emission data were updated through use ofmultiple sources of information (Zhang et al 2018)These included for example new versions of NPRIand APEI measurements from CEMS attached to 17stacks at four OS mining facilities for the 2013 field-study period and daily reports of SO2 emissions during

a 1-week period in August 2013 when the CanadianNatural Resources Ltd (CNRL) Horizon facility experi-enced abnormal operating conditions and the aircraftwas conducting emission evaluation flights Other keylimitations of prior inventories highlighted in Zhanget al (2018) that have been systematically assessed andimproved where possible include (1) the lumping ofall stack emissions under 50 m with surface-level fugi-tive emissions and thus treated as surface releases(Environment Canada Canada 2016) without consid-eration of plume rise (2) the lack of spatial allocationof surface-level fugitive VOC emissions which werereported to NPRI as facility-total emissions withoutdifferentiation between source type (eg mine facestailings ponds and extraction and upgrading plants)(3) out-of-date vegetation fields used for biogenic emis-sions such that much of the area now being mined wasstill being treated as forest (4) failure to treat thetailings ponds present in the mining facilities as water-covered even though by 2013 the tailings ponds in theOS region covered an area of about 180 km2 (5) exclu-sion of some of the available CEMS data (hourly SO2

and NOx emissions and measured stack volume flowrates and exit temperatures) given that such data existfor 100 stacks at 33 facilities with relatively large SO2 orNOx emissions

Despite the initial improvements in the emissionestimates the lack of independent evaluation and emis-sion determination continued to contribute to uncer-tainty Thus a key component of the aircraftmeasurement campaign was validation of the reportedCAC emissions as well as quantification of the emis-sions for a range of other compounds From the aircraftit was possible to obtain a large number of VOC andchemical speciation profiles from each surface miningfacility (Li et al 2017) thereby targeting one of themain uncertainties for one of the major pollutantclasses associated with the OS The instrument packageonboard the aircraft also provided the opportunity toestimate facility-total PM emissions across a large sizerange of particles (06ndash20 μm in diameter) Figure 5shows an example of aircraft observations of PM25

throughout a complete box flight around a facilityThese box flights (Figure S31) were a key part of theaircraft campaign in AugustndashSeptember 2013 becausethey enabled observation-based estimates of short-termemission rates for multiple pollutants

Validation of emissions from aircraft studies

Li et al (2017) used the Top-down Emission RateRetrieval Algorithm (TERRA) (Gordon et al 2015)(see Section S311 of the supplemental material) with

Figure 4 Sources of emission data for criteria air contaminantsfrom the oil sands facilities Results are summarized from theAlberta Environment Sustainable Resource Development(AESRD now part of Alberta Environment and Parks) industrialsurvey on quantification of criteria air contaminant emissionsfrom nonconventional oil and gas sectors (JOSM 2016)

672 JR BROOK ET AL

aircraft-based measurements to estimate facility-totalemissions for several VOCs They found that the valuesof the summed VOC emissions quantified for four ofthe key facilities in the surface mining region SyncrudeMildred Lake (SML) Suncor Millenium and Steepbank(SUN) Canadian Natural Resources Ltd Horizon(CNRL) and Shell Albian Sands and Jackpine (SAJ)mdashnow operated by CNRL were factors of 20 plusmn 0631 plusmn 11 45 plusmn 15 and 41 plusmn 16 higher respectivelywhen scaled to annual totals compared with the datacontained in the NPRI

Figure 6 shows differences in measured (TERRA)versus reported (NPRI) annualized emission estimatesfor 93 separate VOC species included in annual emis-sion reports (totals among the four facilities) groupedby the reporting categories (ie Part 1 Part 5) ofinterest to NPRI Only 11 of the 93 species had aircraft-observed annualized emissions that were similar toreported values whereas 82 species had lower reportedemissions than aircraft-based emission estimates(TERRA) by a factor of 2 to 27800 (Li et al 2017)Looking closely at some specific species the total aro-matic emission rates were 97 plusmn 15 79 plusmn 05 21 plusmn 0315 plusmn 02 053 plusmn 006 and 015 plusmn 002 tons dayminus1 atSML SUN CNRL SAJ Syncrude Aurora (SAU) andImperial Kearl Lake (IKL) respectively These quanti-ties were composed of similar proportions of aromaticsat SML SUN and CNRL but different proportions atSAJ SAU and IKL The higher than previously esti-mated aromatic emission rates coupled with the simi-larities in the aromatic compositions are thought toreflect the naphtha-type solvents used in the bitumen

extraction process at SML SUN and CNRLConversely at SAJ SAU and IKL paraffinic solventsare used (Alberta Environment and Parks [AEP] 2016)and the lower aromatic emission rates detected forthese facilities is consistent with this knowledge Largecontributions from alkanes which peak between C4

and C8 were measured for most of the facilities andthis reflects the use of naphtha and paraffinic solventsused in bitumen-sand-water separation Naphtha sol-vents have higher-carbon alkanes (gtC6) and a higharomatic content whereas paraffinic hydrocarbonscontain carbon numbers around C6 as the effectiveingredients (AEP 2016 Davies 2012) The aircraft andground data were able to detect these differences sug-gesting that VOC ratios may be useful as near-fieldtracers associated with each facility

PM emissions from the facilities originate mainlyfrom four major source categories (1) emissions fromplant stacks (2) tailpipe emissions from the off-roadmining fleet (3) fugitive dust originating from variousmining and transportation activities such as excavationof oil sands ore loading and unloading trucks andwheel abrasion of surfaces by off-road vehicles and(4) wind-blown dust Emission data from plant stacksand fugitive dust source categories are available inNPRI whereas emissions from tailpipe emissions areprovided from other sources (APEI) Although theseemissions are uncertain the most significant uncer-tainty in the PM emission inventories for the OS regionis associated with fugitive dust

TERRA results have been reported for PM25 (Zhanget al 2018) and as shown in Figure 7 the reported

Figure 5 Interpolated observations of PM25 obtained from thebox aircraft flight around the Syncrude Mildred Lake (SML)facility during flight F12 on August 24 2013 The arrows showthe mean wind direction at different flight altitudes corre-sponding to the maximum plume concentrations on the boxwalls Plumes for PM25 can be seen moving northward awayfrom the facility and there appears to be multiple sourcesrelated to the plants and surface mining activities

Figure 6 Comparison of 2013 emission rates for the individualspecies reported to the Canadian National Pollutant ReleaseInventory (NPRI) with the measurement-based emission ratesfor the same species Each dot represents a reported speciesunder either Part 1 or Part 5 of the NPRI reporting require-ments The horizontal bars represent the uncertainty range ofthe measurement-based emission rates (Li et al 2017)


base case PM25 emissions are considerably less than theestimates derived from the aircraft measurements forfive of the six facilities studied Although these discre-pancies are for PM25 Figure S34 shows that 65ndash95 ofPM25 emissions are in PM size bin 8 (diameter rangefrom 128 to 256 μm) implying that the majority of thePM25 mass emissions are from fugitive dust areasources (Eldering and Cass 1996) either from dustkicked up by off-road mining vehicles or from wind-blown dust It is reasonable to expect that this increasein mass toward the larger PM25 sizes continues intolarger sizes which are likely associated with fugitivedust emissions This has implications for acidic deposi-tion given that in these sizes basic material (eg cal-cium [Ca]) is typically present (Wang et al 2015 Zhanget al 2018) Given the presence of petroleum coke(petcoke) stockpiles at the facilities where bitumen isupgraded there is the potential that these large particlesalso contain PACs

In addition to potential differences seen throughdirect comparison (ie Figure 7) there has often beena discrepancy between initial inventory estimates ofprimary PM emissions and the amount of PM actuallydetected in the atmosphere downwind (ie ldquotranspor-table fractionrdquo) This tends to depend on the type ofland cover and indicates that a fraction of the emittedPM is deposited locally and thus does not escape intothe boundary layer or free troposphere for transportdownwind (Pace 2005) The range of uncertainty asso-ciated with the estimate of the transportable fraction ishigh and TERRA estimates in the OS region may helpconstrain the value of this parameter

In terms of PM chemical constituents total blackcarbon (BC) emissions from the OS surface miningfacilities were estimated using the hourly emission rates

(TERRA) to be 707 plusmn 117 tons yrminus1 The total annual BCemissions reported to the UNECE by ECCC (2016) aresimilar to these measurements lending some confidenceto both results However the relative contributions ofoff-road vehicles versus stacks in the UNECE reportdiffer from the TERRA estimates with the latter attri-buting the majority of BC emission to off-road vehiclesversus only 50 for the UNECE report These differ-ences suggest that the UNECE reported total amountwhich is derived using the standard approach (ie fromPM25 mass emission estimates for the oil sands surfacemining facilities in conjunction with the EPA SPECIATEdatabase [EPA 2014] BCPM25 fractions [Cheng et al2019]) is reasonably accurate but differences by sourcecategory suggest a potential need for improvements

Low-molecular-weight organic acids (LMWOAs)and isocyanic acid (HNCO) had never been reportedfor the OS or for most other sources in Canada orglobally They are both products of secondary forma-tion in the atmosphere but are also directly emittedThe transportation sector is an important source ofHNCO (Brady et al 2014 Wentzell et al 2013 Wrenet al 2018) and emission rates were estimated from theaircraft measurements to be 22 plusmn 08 kg hrminus1 fromSUN followed by that from the SML facility of15 plusmn 05 kg hrminus1 Figures S32a and S32b show thatby tracking a specific integrated plume downwindincreases in HNCO and LMWOAs can be observed(Liggio et al 2017) Additionally for HNCO there isalignment of the plume emanating from SML and thelocation of active open-pit mining which is consistentwith the expectation of the source being the off-roadheavy-duty diesel fleet Isocyanates of which HNCO isthe simplest stable and volatile species have recentlybeen classified as being in the highest inhalation

-

500

1000

1500

2000

2500

3000

3500

4000

Tonnes

Base Case (Annual Total) Aircraft (Aug amp Sept)

Figure 7 Comparison of PM25 emissions between base case annual emissions obtained from all available bottom-up emissioninventory information and the aircraft-observation-based (top-down) estimates for the two summer months (August andSeptember 2013) for the six oil sands mining facilities (Zhang et al 2018)

674 JR BROOK ET AL

toxicological potency class in an assessment of 296inhalable species of concern (Schuumluumlrmann et al 2016)

LMWOA emissions (Figure S32a) for the SUNSML SAU SAJ CNRL and IKL facilities were esti-mated to be 162 plusmn 22 108 plusmn 15 45 plusmn 6 56 plusmn 8 60 plusmn 8and 19 plusmn 3 kg hrminus1 respectively or approximately 12tons dayminus1 of primary LMWOAs (Liggio et al 2017)From the atmospheric chemical process perspectiveLMWOAs could be contributors to precipitation acid-ity and ionic balance particularly in remote areas(Khare et al 1999 Stavrakou et al 2012) Althoughimportant in their own right their relative contributionto acidic deposition could become more important ifanthropogenic NOx and SOx emissions decreaseLMWOAs are also key participants in the aqueous-phase chemistry of clouds and contribute to secondaryorganic aerosol formation through various reactionswithin the aqueous portion of the particle phase(Carlton et al 2007 Ervens et al 2004 Lim et al2010) Furthermore since organic acids are also formedin photochemical reactions their measurements serveas indicators of atmospheric transformation processesThus measurements of LMWOAs can help evaluate theGlobal Environmental MultiscalendashModeling Air-qualityand Chemistry model (GEM-MACH) specifically thechemical mechanisms within the model From anenvironmental health perspective deposition ofLMWOAs may have ecosystem impacts as they havebeen shown to be toxic to various marine invertebrates(Staples et al 2000 Sverdrup et al 2001) phytotoxic(Himanen et al 2012 Lynch 1977) and interfere withthe uptake and mobilization of heavy metals by micro-bial communities in soils (Menezes-Blackburn et al2016 Song et al 2016) However studies on thehuman toxicity of LMWOAs are sparse and the resultsunclear (Azuma et al 2016 Rydzynski 1997)

It is important to note some of the limitations in thecurrent emission validation findings derived from thetop-down approach Because of limitations in the mini-mum aircraft flying altitude there is larger uncertaintyin the emission estimates associated with surfacesources 20 versus elevated stack emissions at about10 (Gordon et al 2015) However these uncertaintylevels are small compared with those expected for bot-tom-up inventory estimates from large and complexarea sources such as OS facilities

The largest uncertainty regarding comparison of thetop-down results and the reported inventory is poten-tially due to the limited number of flights around eachfacility These were also limited in time (ie AugustndashSeptember 2013) thus the top-down estimates in gen-eral needed to be temporally extrapolated for compar-ison with data in the NPRI and APEI databases These

extrapolations were done with caution taking into con-sideration potential uncertainties and with notedcaveats (Li et al 2017) Another limitation is thatalthough TERRA can theoretically be applied to anysize volume (ie could isolate a single stack) aircraftflights become logistically challenging to capture smal-ler elements within the OS facilities Thus the emissiondata reported thus far are for mainly whole facilitiesrecognizing that there is heterogeneity in the emissionsacross these relatively large areas and that more-resolved measurement would be desirable

Ground-based measurements have also been analyzedto assess consistency with known emissions For exampleParajulee and Wania (Parajulee and Wania 2014) sug-gested that a significant amount of PAH emissions fromtailings ponds would be necessary to explain their model-ing results The Galarneau et al (2014) study of tailingspond water supported this finding demonstrating thatgiven known water concentrations there is a potential forPAHs to partition into the air Harner et al (2018) alsohighlighted that potential in order for the inverse model-ing of Parajulee andWania (2014) to explain the observedambient concentrations of phenanthrene pyrene andbenzo[a]pyrene in 2009 their emissions would need tobe 2ndash3 orders of magnitude higher than those reported inthe NPRI and APEI databases More recent emissionestimates also based on inverse modeling but fora larger amount of ambient monitoring data (Schusteret al 2015) also concluded that PAH emissions areunderestimated (Qiu et al 2018) This work foundthat benzothiophene emissions needed to be morethan an order of magnitude higher than the currentlyavailable estimates in order to explain the observationsQiu et al (2018) also estimated what the emissions ofalkylated PAHs (alk-PAHs) which are not required tobe reported needed to be to fit the observations 160 tonsyrminus1 for C1-naphthalenes 130 tons yrminus1 for C2-naphthalenes 52 tons yrminus1 for C3-naphthalenes 19 tonsyrminus1 for C1-fluorenes and 35 tons yrminus1 for C1-phenanthraceneanthracenes

Remote sensing observations are being used exten-sively to monitor air pollutants over the OS regionSO2 NO2 CO NH3 methanol (CH3OH) and formicacid (HCOOH) have been observed from 2004 onwardon the Aura satellite Figure 3 shows how the amountof NO2 increased over the northern parts of the surfaceminable region in the late 2000s The ECCC satelliteresearch has led to improved methods to derive emis-sions and for retrievals of SO2 (Fioletov et al 20172015) and ammonia (Shephard et al 2015) McLindenet al (2012) examined the annual trends from 2005 to2011 and showed that there is good agreement betweenthe trend derived from satellite (vertical column density


and area-integrated NO2 mass) and ground NO2 obser-vations and bitumen production (Figure S35) suggest-ing that such analyses could provide anotherindependent validation of the reported emissionsCurrently 3-yr running average annual SO2 emissionsfrom the OS region for 2006ndash2017 are being analyzedfor trends for comparison with the NPRI reports forthe same time period (McLinden personal communi-cation 2019)

Greenhouse gases (GHG) are generally not a pollutantof interest in regard to long-term ecosystem effects due todepositionexposure (ie the topic of this paper) as is thecase for the other pollutants discussed in this sectionHowever they will contribute to climate change effectsLiggio et al (2019) report that the aircraft-derived carbondioxide (CO2) emissions intensities are at times largerthan what would be derived using publicly available datain the Greenhouse Gas Reporting Program (GHGRP)The difference in calculation results translates intoa potential gap in CO2 emissions of approximately 17Mt annually which could correspond to a 64 increaserelative to reported emissions for the four major surfacemining operations in the OS Similarly methane (CH4)annual emissions estimated using aircraft hourly emissionrates from the five major facilities in the surface miningregion was found to be 48 plusmn 8 higher than that extractedfor 2013 from the GHGRP (Baray et al 2018) Theseestimates were based upon examination of emissionsfrom mine faces and tailings ponds which are the majorsources of CH4 on the facilities Clearly the discrepanciesbetween the aircraft-based (top-down) emission estimatesand the methods used to estimate emissions reported tothe GHGRP indicate a need for reconciliation betweenthe bottom-up (used to report to inventories) and top-down estimates

How do the emissions transform in theatmospheremdashAssessment of changes in pollutantsduring atmospheric transport

Given the large emissions of volatile organic com-pounds (VOCs) and other pollutants (eg NOx) fromOS sources it was anticipated that as they are trans-ported away from the source area they would trans-form into both gaseous- and particle-phase oxygenatedproducts Thus four of the 2013 aircraft flights exam-ined the formation rates of andor total quantities ofsecondary organic aerosols (SOAs) particle organicnitrates (pONs) gas-phase low-molecular-weightorganic acids (LMWOAs) and isocyanic acid(HNCO) downwind of the OS In general ozone levelsnear and downwind of the OS region are relatively low

(ie hourly maxima typically less than 60 ppbv) andthus were not a focus of these transformation studies

SOA formation was hypothesized to be importantgiven that bitumen is composed of lower-volatility hydro-carbons and open-pit extraction and subsequent proces-sing could release a disproportionately large fraction ofSOA precursors (semivolatile organic compounds andintermediate volatility organic compounds [SVOCsIVOCs]) into the atmosphere Should even a smallamount of the bitumen volatilize during productionthere would be a strong potential for SOA formationdownwind of the region However although oil and gasproduction and processing including OS productionwere known to be a significant source of VOC emissions(Simpson et al 2010) SVOCIVOC emissions were onlysuspected Liggio et al (2016) reported large amounts ofSOAs forming downwind (Figure 8) suggestive of suchemissions from the OS activities After correcting fordispersion of the plume as it spread downwind a 6-foldrelative increase in organic aerosol mass (as SOAs) wasobserved over 4 hr of transport away from the OS facil-ities In terms of the amount of SOAs formed they foundthat during the summer season of the aircraft flightsformation was on the order of 55ndash101 tons dayminus1 andlikely higher given that SOA formation beyond the lastflight screens and at night were not considered Thesequantities are comparable to what has been observedforming downwind of major cities (Liggio et al 2016)

Based upon laboratory experiments the characteris-tics of the newly formed SOAs were found to be similarto the hydroxyl (OH) oxidation products of bitumenvapors (Liggio et al 2016) To determine how much

S

A

C

B

D

Figure 8 Organic aerosol (OM) observations at varying dis-tances and times downwind from the main oil sands surfacemining region (S) The aircraft flew at multiple heights perpen-dicular to the wind direction to capture the complete plume asit dispersed and transformed Clear increases in OM after thefirst transect (A) can be seen by more red yellow and greencolors in B C and D The yellow text indicates estimates of theamount of secondary organic aerosol (SOA) formed betweenthe separate transects (Liggio et al 2016)

676 JR BROOK ET AL

SVOCsIVOCs would need to be present to explain theobserved SOAs a Lagrangian box model was set up forthe OS conditions This initially only considered theknown VOC emissions along with the other primaryemissions (eg NOx) However oxidation products ofthe speciated alkanes alkenes and aromatic hydrocar-bons could only explain lt6 of the observed SOAsand adding isoprene and monoterpenes only explainedan additional 9 or less However by adding into thebox at the start of the run 3ndash45 ppbv of bitumenSVOCsIVOCs the chemical mechanism and aerosolformation scheme using realistic physical propertiesdetermined in the laboratory (Liggio et al 2016) wasable to simulate the aircraft SOA measurements After3 hr this scheme contributed ~86 of the observedSOAs Even though 3ndash45 ppbv of IVOCsSVOCs issmall compared with the ~70 ppbv of VOCs observedduring the flight at the first pass through the OS plumethe IVOCSVOC species are the dominant contributorto SOA formation The existence of significant amountsof IVOCsSVOCs in the air in the OS region was alsoverified through ground measurements taken just northof SML (Tokarek et al 2018) These results highlightthe need for additional data on IVOCSVOC emissionsfor the OS in order to accurately predict the amount ofSOAs and PM25 traveling downwind and potentiallyaccumulating in sensitive ecosystems

Large amounts of LMWOAs (eg formic and aceticacids) were also found to form as the OS emissionsmoved downwind (Figure S32a) (Liggio et al 2017)Secondary formation rates within 1 photochemical dayof the OS were in excess of 180 tons dayminus1 and theamounts observed were more than an order of magni-tude greater than the knownexpected primary emis-sions (Liggio et al 2017) Based upon the knownprecursor VOC emissions Liggio et al (2017) deter-mined that that amount of LMWOAs formed wouldrequire that 50 of the carbon emitted was trans-formed to organic acids within 1 photochemical dayThis is an unusually high effective yield suggesting thepresence of unknownunmeasured hydrocarbons cap-able of producing LMWOAs upon oxidation with sig-nificant yields However current photochemicalmechanisms are not able to reproduce the LMWOAobservations suggesting that similar to SOAs there isa ldquomissingrdquo precursor This unknown source wouldneed to account for 54ndash77 of the observedLMWOAs and is not expected to be related to theoxidation of biogenic species As for SOAs IVOCs aresuspected to be this source although through reactionsthat induce fragmentation of these relatively large car-bon molecules (Lambe et al 2012) In terms of ecosys-tem impacts it is presently not clear the extent to which

weak acid deposition from LMWOAs to sensitive eco-systems could contribute to critical load exceedances

Secondary formation of HNCO is known to occur inthe atmosphere (Roberts et al 2014 Wentzell et al2013 Woodward-Massey et al 2014 Zhao et al2014a) Laboratory experiments have demonstratedthat HNCO is formed photochemically from the OHoxidation of off-road heavy-duty diesel exhaust vapors(Link et al 2016) Analysis of downwind observationsin the OS region (Figure S32b) provided two separateestimates of the HNCO formation rate 116 plusmn 25 kghrminus1 in one flight and 186 plusmn 38 kg hrminus1 in the otherRelative to the primary emission amount these second-ary amounts formed after 4 hr were from a factor of 2to asymp20 greater than what is estimated to be emittedalthough it should be noted that this enhancement inHNCO due to secondary formation in the OS region isbased upon conditions in AugustndashSeptember 2013Atmospheric HNCO production during other seasonsis unknown However these summertime proportionsare much higher than laboratory studies using dieselexhaust (Kang et al 2007 Link et al 2016) and thereasons for this large discrepancy are not clearSomething unique with the emissions from the off-road heavy-duty diesel in the OS or the fuels used orthe levels of NOx or underestimates in the laboratoryexperiments due to wall losses of later-generation VOCoxidation products (Lambe et al 2011) are possibleexplanations In terms of implications current modelestimates indicate that potential exposures in closeproximity to the facilities (eg work camps FortMcKay) are below the 1000 ppt threshold for potentialhealth effects (Roberts et al 2011) However given thatHNCO levels are expected to be proportional to OSproduction because of their link to heavy-duty dieselemissions (Cheng et al 2018 Liggio et al 2017) furtherincreases in OS production via surface mining wouldlikely increase HNCO exposures in Fort McMurray andother nearby communities

As PACs are a diverse class of compounds theirdistribution is likely to undergo considerable changeas they move from their specific source locations onthe OS facilities to downwind areas Quinones andnitrated compounds are believed to be the dominantend products from these reactions (Arey et al 1992Keyte Harrison and Lammel 2013 Lundstedt et al2007) and these compounds were measured at severalground sites within the surface-mineable region(Harner et al 2018) Separate measurements of theambient gas- and particle-phase concentrations ofseven unsubstituted PAHs and 19 corresponding qui-nones at the WBEA site south of Fort McKay Alberta(AMS13) showed that the unsubstituted PAHs were


predominantly found in the gas phase In contrastquinones were more abundant in the particle phase(Wnorowski 2017 Wnorowski and Charland 2017)The average 24-hr concentrations were greatest for 2-and 3-ring quinones average 53 plusmn 7 8 ng mndash3 (rangeof 01ndash325 ng mndash3) average for 4- and 5-ring species of04 plusmn 06 ng mndash3 (range of 01ndash26 ng mndash3) and lowestfor 6-ring quinines average 01 plusmn 01 ng mndash3 (range of001ndash03 ng mndash3) These concentrations are of the sameorder of magnitude as reported elsewhere for industrialsites (Harner et al 2018) Diurnal measurementsshowed a higher abundance of quinones during day-time than nighttime indicating that some PAH sourcesare linked to daytime local activity and favorable photo-chemical conditions for the oxidative transformationsof quinone precursors Correlations of quinone andPAH concentrations with colocated primary pollutantmeasurements (eg NOx) suggested that unsubstitutedPAHs originate from primary emission sources asso-ciated with OS activities (Wnorowski 2017 Wnorowskiand Charland 2017) In contrast the temperature-dependent formation of the quinones corresponded toa decrease in PAH and NO2 levels suggesting gas-phase oxidation of quinone precursors by free radicals(Wnorowski 2017 Wnorowski and Charland 2017)

Given their semivolatile nature many PACs in theregion can be expected to cycle between gas and parti-cle phases depending upon temperature and otheratmospheric conditions This can happen over short(ie diurnal) and long (ie seasonal) timescales Hsuet al (2015) presented evidence of evaporation of PAHsfrom Lake Gregoire which may be sufficiently large asto control local atmospheric concentrations in summerwith peak levels occurring in May They suggest thatPAHs that were atmospherically deposited during thewinter months may have run off to the lakersquos surfacewaters during snow melt from which evaporationoccurred when temperatures increased in springThese partitioning processes could have a significantinfluence on where some PACs accumulate in theenvironment in what chemical form and their atmo-spheric processing However these processes have yetto be explored in a systematic manner in the OS regionA modeling study examining the fate of PAHs relativeto trace metals (ie inert tracer) around the Sudbury(Ontario Canada) smelter provides some insight intothe impact of these processes (Thuens et al 2014) Astheory would predict lower-molecular-weight PAHswere observed to have shorter lifetimes than the higher-molecular-weight PAHs Travel distances in colderwinters were more than twice those in the hotter sum-mers indicative of the longer travel distances possiblefor particles Overall travel distances of up to 500 km

were found for the trace metals whereas they wereshorter for the semivolatile PAHs

Model evaluation and improvementmdashTowardbetter tools for integration of information toestimate impacts of OS emissions

The Global Environmental MultiscalendashModeling Air-quality and Chemistry model (GEM-MACH) has beenused extensively for applications in the OS region (seeSection S312 of the supplemental material) GEM-MACH (Makar et al 2015b 2015a Moran et al 2010)stems from a longer history of prediction model develop-ment involving the Acid Deposition and Oxidants Model(ADOM) which has its roots in the acid deposition era(Venkatram and Karamchandani 1986) followed byA Unified Regional Atmospheric Modeling System(AURAMS) which was initially developed to incorporateparticulate matter in the ECCCrsquos modeling tools (Brookand Moran 2000 Gong et al 2006) In parallel to dailyGEM-MACH runs based upon the grid and domainshown in Figure S33 a number of components in themodel have been modified including emissions andtested against observations from the aircraft and groundto determine whether they lead to improved predictionsThis iterative process of model evaluation improvementand testing is critical given the ongoing role of GEM-MACH in identifying areas of potential concern (egabove critical loads) and in a range of other applicationsin the region (eg emission reduction scenarios air qual-ity forecasting)

Incorporation of observed emission rates fromaircraft dataTo determine whether GEM-MACH predictionsimprove through incorporation of the aircraft-basedemission estimates (Li et al 2017) new VOC and size-resolved PM emissions files were created and modelsensitivity analyses were conducted (Zhang et al2018) In addition to speciating VOCs and PM andadjusting their emission rates to reflect the aircraftobservations spatial allocation of the facility-totalemissions to specific locations within the facilities(eg stacks tailings ponds mine faces) was improved(Figure S36) Stroud et al (2018) found that with theaircraft-based VOC and organic PM emission esti-mates changes in the model predictions for theAugustndashSeptember 2013 period was sometimes con-siderable particularly based on a comparison of 99thpercentiles of aircraft-observed and modeled VOCand organic aerosols (Figure 9) This statistic isa quantitative estimate of whether the model capturesthe plume maxima mixing ratios whereas the model

678 JR BROOK ET AL

median value is more representative of the regionalbackground concentrations The modeled ditrisubsti-tuted aromatics (AROM) median and 99 percentilemixing ratios were both closer to the aircraft observa-tions The statistical analysis with the monosubstitutedaromatic (TOLU) species showed comparable results(ie similar performance with the original and revisedemissions)

For the C4+ alkanes (ALKA) which are emitted inlarge quantities given their use in bitumen processing(Li et al 2017) the mean bias and median value werefound to be higher with the revised emissionsHowever the 99th percentile was closer to the observedvalue with the revised emissions In terms of SOAformation the modeled PM1 organic aerosol meanbias and root mean square error improved significantlywith the revised emissions although the organic aerosolmean bias still remained negative One likely cause ofthe continued underestimate of organic aerosols isinsufficient organic aerosol enhancement from second-ary formation in the modeled plumes particularly dueto missing contributions from IVOCsSVOCs (Liggioet al 2016) Overall Stroud et al (2018) concluded thatthe use of the aircraft estimates of emission ratesresulted in comparable or higher and potentiallyimproved results compared with predictions based

upon the original inventory (ie bottom-up inventory)in GEM-MACH

Increasing resolution in the PM size distributionTwo-bin (size cuts of 001 256 and 1024 μm dia-meter) and 12-bin (size cuts of 001 002 004 008016 032 064 128 256 512 1024 2048 and 4096μm diameter) particle schemes were implemented inGEM-MACH and the predicted PM concentrationswere compared with surface PM25 observations The12-bin version led to improvements with the mean biasdecreasing from minus26 to minus17 μg mminus3 and the fraction ofobservations within a factor of 2 increased from 039 to045 (Akingunola et al 2018) These observations sug-gest that a sizeable fraction of particulate underpredic-tions in 2-bin simulations may be due to poorrepresentation of particle microphysics despite the sub-binning used in some of the algorithms simulatingmicrophysics processes Figure 10 which providesinformation on the PM25 in the region during theAugustndashSeptember 2013 study period compares themodeled PM25 with the surface observations The 12-bin scheme did improve predictions although negativebiases for the frequency of low concentration eventsand positive biases for the frequency of high concen-tration events were still evident

Figure 9 Comparison of the observed and model histograms of VOC categories simulated by the GEM-MACH model The firstcolumn is from aircraft observations obtained from flights during two summer months (August and September 2013) The secondcolumn is from GEM-MACH using the available bottom-up emission inventory information for VOCs and organic aerosol The thirdcolumn is model estimates using revised VOC emissions obtained from the aircraft-observation-based (top-down) emission estimates(Li et al 2017) The 99th percentile values for the different VOC groups and total organic aerosol are displayed in each graph (Stroudet al 2018)


Impact of meteorology on local-scale motionsmdashVertical and horizontal placement of plumesGEM-MACH and most comparable models continue touse empirical plume rise formulae based on observationscollected between 1969 and 1985 (Briggs 1969 19751984 1985) Comparisons between model predictions ofthe height of SO2 plumes and the aircraft observationsindicated that GEM-MACH had a tendency to under-predict the height of buoyant plumes and overestimatethe frequency and intensity of surface fumigation eventsTo understand possible reasons for this discrepancy andto improve the model meteorological observations wereused to ldquodriverdquo the standard Briggs plume rise algorithmsand then these and alternative formulations (Gordon et al2018) were evaluated using aircraft observations of SO2

plumes This confirmed that the plume rise algorithmsunderestimate plume rise with 50 or more of the pre-dicted plume heights falling below half of the observedvalues in the OS region In addition computations ofplume rise using different sources of meteorological data(aircraft two tall meteorological towers and surface-based remote sensing) sometimes resulted in differentestimates of plume height suggesting that plume riseestimates can be influenced by the high degree of spatialheterogeneity in meteorology in the OS regionMeteorological observations close to or at the stacksmight therefore be required for observation-basedimprovements to estimates of plume rise which can ulti-mately influence where the emissions are deposited

Akingunola et al (2018) compared results from theplume rise algorithms using inputs from GEM-MACH(ie as opposed to from meteorological observations)to the aircraft observations These simulations revealedthat the predicted temperature profiles and planetary

boundary layer (PBL) heights (key determining factorsin plume rise) were different between the locationscontaining the meteorological observations and thelocations of the stacks That is the model also revealedthe potential for spatial heterogeneity in conditionsbetween meteorological observation locations againimplying that at-stack meteorological observations areneeded to obtain optimal results from the plume risealgorithms Akingunola et al (2018) also found thatonce these meteorological differences were taken intoaccount using model predictions at the actual stacklocations a new plume rise estimation methodologythat makes use of successive residual buoyancy calcula-tions gave significantly improved results for both plumeheight and SO2 concentrations in plumes Howeverexcessive fumigation relative to observations stilloccurred at times This appeared to be related to themeteorological model tending to systematically under-predict the temperatures in the lowest 2 km of theatmosphere resulting in an overestimation of the tem-perature gradient and excessive fumigation

Slight errors in the horizontal direction of advectionwhich will displace the location of plumes can result inlarge errors when predictions and observations are com-pared This can be accentuated in more spatially resolvedmodels such that the advantages of the finer resolutionwhich can be significant for simulating a range of pro-cesses may be difficult to quantify in model diagnosticevaluation (Fox 1981 1984 Hanha 1988) Russell et al(2018) presented a new approach to account for this mis-alignment in their analysis of the potential benefits ofa more spatially resolved model (ie 10 vs 25 km resolu-tion) They accounted for the fact that when the modelresolution is relatively low the plumes spread over a largercross-sectional distance and wind direction errors havea smaller impact than when model resolution is high andplumes are less spatially distributed (Landers et al 2010)These techniques have the potential to help evaluatewhether improvements to the model ultimately to predictlong-term conditions and undertake emission scenariowork are having the intended benefits However for airquality forecasting to provide advanced short-term warn-ings (ie for location populations) misalignment errorsremain problematic highlighting the ongoing need formore accurate simulations of meteorology Incorporationof meteorological observations into model forecasts viadata assimilation may ultimately be needed to improveair quality forecasting in the OS region

Two-way air-surface exchange processesmdashAircraftand satellite evidence for ammonia bidirectional fluxConcentrations of ammonia (NH3) measured from theaircraft along with satellite data showed that background

Figure 10 Histogram of surface PM25 using Wood BuffaloEnvironmental Association (WBEA) surface monitoring data(blue) and the 2-bin (red) and 12-bin (purple) configurationsof the GEM-MACH model (Akingunola et al 2018)

680 JR BROOK ET AL

NH3 concentrations in the region were approximately 06ppbv throughout the boundary layer and into the lowertroposphere (Shephard et al 2015) However initialGEM-MACH simulations underpredicted backgroundNH3 relative to these observations Bidirectional fluxes ofNH3 in which natural emissions as well as deposited NH3

stored within vegetated surfaces is released once concen-trations drop below a vegetation-dependent ldquocompensa-tion pointrdquo concentration were tested in GEM-MACHand found to be capable of accounting for the deficit withobservations (Whaley et al 2018b) Bidirectional fluxesmay have an impact on net nitrogen deposition and two-way exchange processes will likely be necessary to bettersimulate the movement of PACs in the OS region

Integration of Air Component findingsmdashTwoexamples

Acid deposition and the potential for critical loadexceedancesThe most up-to-date estimates of total S andN deposition and critical load exceedances overAlberta and Saskatchewan were provided by Makaret al (2018) These were derived through an annualrun (August 1 2013ndashJuly 31 2014) of the 2-bin 25 kmresolution version of GEM-MACHv2 combined withavailable wet deposition observations and revised fugi-tive dust emissions derived through application of thelocal 12-bin version of GEM-MACH25 and informedby the aircraft observations Relative to the first set ofmodel estimates (ie GEM-MACH25 runs initiated at

the start of JOSM) these new model-measurementfusion corrections (Figures S37ndashS39) resulted inincreased base cation and decreased anion depositionrespectively These new deposition estimates were com-pared with the estimated critical loads (ie an updateto Figure S12) Areas potentially experiencing criticalload exceedances implying potential future ecosystemdamage assuming continuation of emissions at thelevels used in the air quality model can be seen inFigures 11 and 12 for terrestrial and aquatic ecosys-tems respectively

Two different approaches the simplified NEG-ECP(2001) protocol and the CLRTAP (2017) approach(see ldquoExamples of air pollutionndashrelated indicatorsrdquo)were considered in the determination of critical loadsThe estimated terrestrial critical load exceedances(NEG-ECP protocol) cover an area of120 times 104 km2 In contrast the total area estimatedto be in exceedance using the CLRTAP (2017) criticalloads is more than 5 times higher 699 times 104 km2encompassing about 16 of the region for which datawere available within the Province of Alberta Theselatter critical load exceedance values include data onprovince-specific vegetation and soil updates and theuse of a more rigorous protocol (see ldquoExamples of airpollutionndashrelated indicatorsrdquo) The inclusion of theobservation-corrected base cation deposition esti-mates derived from the aircraft measurements led toestimates of predictions of more neutralization in thevicinity of the oil sands (circled regions in Figures 11and 12) relative to initial model estimates (Makar

Figure 11 Predicted terrestrial ecosystem critical load exceedances with respect to Sdep + Ndep (deposition) using (a) NEG-ECP(2001) and (b) CLRTAP (2017) methodologies (eq haminus1 yrminus1) (from Makar et al 2018) Lower left of each panel percentage of theentire critical load data area which is in exceedance and the total area in exceedance in km2 Circled region 140 km radius circlearound the Athabasca oil sands


et al 2018) This is hypothesized to better reflect thedust emissions from the oil sands activities (Makaret al 2018) However although this enhanced basecation deposition which may be interpreted as pro-tective for acidification it may occur simultaneouslywith dust deposition of toxics (ie PACs and metals)which can also originate from area sources associatedwith OS development

Assessment of the current knowledge on PACsGiven the snowpack and lake sediment observations(Kelly et al 2009 Willis et al 2018) their known andor potential toxicity and presence in air water and thebiota an integrated program was undertaken for PACsMonitoring conducted within the ECCC WaterComponent of JOSM indicated that the amount ofPACs and other toxics (eg naphthenic acid metals)seeping from tailings ponds into the watershed is smallrelative to other sources (Bickerton et al 2018) sug-gesting the need to focus on atmospheric pathwaysbetween the OS industry and the surrounding environ-ment Harner et al (2018) assessed the current knowl-edge on PACs (before ~2017) in regard to theiremissions and transformation concentrations in airwet and dry deposition and insights from source attri-bution and modeling studies Three main categories ofPACs have been the focus of monitoring in the OSregion polycyclic aromatic hydrocarbons (PAHs) alky-lated PAHs (alk-PAHs) and dibenzothiophenes (DBTsand alk-DBTs) These are defined in Section S32 of thesupplemental material

Due to the complexity of the transport transforma-tion and deposition processes (eg particle depositiondeposition with snow rain etc) and lack of knowledgea comprehensive model to assess local to regionaltransport of PACs and their by-products and to predicttheir net influence on ecological systems as has beendone for acidifying pollutants is not available for theOS region However simplified modeling approacheshave been applied in the OS region to gain insight intoemissions of PACs (Parajulee and Wania 2014 Qiuet al 2018) These indicate that fugitive emissions ofPAHs and alk-PAHs represent the major source to theatmosphere These include resuspended dust frommine faces unpaved roads and petroleum coke storagepiles as well as volatilization from tailings ponds(Figure 13)

Schuster et al (2019) documented the long-termconcentrations of the three PAC classes across 15 sitesin the OS region covering the period 2010ndash2016 Thesepassive data serve as a key baseline for assessing theimpact of future and expanded mining projects in theregion on ambient levels of PACs They have helpedevaluate the contribution of forest fire combustionemissions to the PAH levels in air as well as the con-tribution from revolatilization (during forest fires) ofambient PAHs which were previously taken up byforests (Rauert Kananathalingham and Harner 2017)Forest fire emissions currently play an important rolein the PAC levels in the region one that could increasedue to climate change However beyond the parentPAHs there is a lack of information on wood

Figure 12 (a) Predicted lake ecosystem critical load excee-dances with respect to Sdep GEM-MACH Sdep scaled usingprecipitation deposition observations and NEG-ECP (2001)methodology (eq haminus1 yrminus1) (b) Predicted aquatic ecosystemcritical load exceedances with respect to Sdep corrected tomatch precipitation observations CLRTAP (2017) methodology(eq haminus1 yrminus1) (c) Predicted aquatic ecosystem critical loadexceedances with respect to Sdep +Ndep corrected to matchprecipitation observations (eq haminus1 yrminus1) (Makar et al 2018)

682 JR BROOK ET AL

combustion emission factors for alk-PAHs and theDBTs complicating assessment of the contributionfrom the OS industry to their levels in water sedimentand biological compartments (Schuster et al 2019)

Although forest fires are important the spatial pat-terns in PACs observed in the passive sampling net-work (sites shown Figure S310) demonstrate that PACsin air are largely attributed to OS production opera-tions although levels in different mining-type regionshave not been assessed (ie PACs arising from in situversus open-pit mining extraction) The alk-PAHs arethe dominant group in the air and they are attributedto petrogenic sources (ie geological sources asopposed to combustion or pyrogenic sources)Observations have shown that other PAC classes suchas DBTs quinones transformation products (egnitro- and oxy-PAHs) and a wide range of otherPACs (eg heterocyclic aromatics) also contribute tothe PAC levels in air (Wnorowski 2017)

Consistent with the spatial pattern in air concentra-tions (Schuster et al 2019) deposition occurs ona gradient with higher deposition near oil sands pro-duction activity Spatial patterns of PAC depositionhave been explored using a variety of methods includ-ing snow (Manzano et al 2016) bulk deposition

collectors (Bari Kindzierski and Cho 2014) lichen(Graney et al 2017 Landis et al 2019) moss sampling(Zhang et al 2016) and a passive dry deposition sam-pler (Jariyasopit et al 2018) However quantitativelinkage between concentrations in air andor precipita-tion and the levels in these different forms of collectionmedia is difficult to assess (Zhang et al 2016)Precipitation samples using wet-only collectors havealso been deployed in the OS region (Muir et al2012) Three ldquonear-fieldrdquo sites have been operatedwith monthly collection since 2010 The highest load-ings or atmospheric wet deposition fluxes (microg mminus2) ofPACs were observed in the winter months (JanuaryndashMarch) in 2011 and 2012 at the two sites closest to theOS operations whereas loadings at the third sitealthough only ~10 km north of SML were 4- to6-fold lower in winter but similar from May toOctober 2012 PAHs (17 unsubstituted) in precipitationat these two close sites were lower than the total annualwinter snow fluxes observed at the sites on theAthabasca River which were within 5 km of theselocations (next paragraph) This is likely due to con-tributions from other sources such as petcoke andhaul-road dust in the snow relative to the wet-onlysamplers

UTM easting (m)

ab

c

UTM

north

ing

(m)

Figure 13 (a) Emission sources to air for PAHs in the oil sands region derived from the JOSM emission database (Qiu et al 2018) (b)Inset map of western Canada showing the Athabasca oil sands region (c) Zoomed-in map of emissions over the surface-mineablearea Line sources include transportation emissions Area sources include tailings pond mine face mine fleet community heatingairport and traffic emissions Note oil sands region boundaries are based on 2009 data (Harner et al 2018)


Multiyear JOSM snowpack observations based upona systematic sampling strategy affirm the pattern shownby Kelly et al (2009) and also extend the data to greaterdistances and show that there is considerable year-to-year variability in the magnitude and location of thehighest deposition amounts (Manzano et al 2016Figure S311) Figure 14 shows that there is a rapiddrop-off in PAC deposition (accumulated in snow)with distance from a reference site close to the surfacemining (AR6 in Kelly et al (2009)) Beyond 10 km thedeposition appears to be uniform and the shape of thepattern (Figure S311) implies that there may be limiteddirectional dependence on deposition amountHowever a more detailed analysis of the decrease indeposition with direction using a Lagrangian trajectorymodel suggested that regional wind patterns and theintensity of PAC emissions play a role (Cho et al 2014)Although dependent upon sampling design Figure 15suggests that PACs could be spreading further towardthe north and south compared with the east and west(Cho et al 2014) Although the greater spread to thenorth would be in the direction of the PAD all mea-surements of PACs that far north (150ndash200 km) findthat PAC loadings in the PAD are in the same range asfound at remote sites in western US national parks(Landers et al 2010)

The long-term temporal trends of PAC depositionfirst shown for lakes relatively close to the more-activesurface mining areas (Figure 3) have now been studiedamong a larger number of lakes including those fartheraway such as in the PAD (Muir et al 2018) Results

from peat cores (Zhang et al 2016) are also availableand largely confirm the temporal and spatial patternsseen from the lake sediments increases in alk-PAHsDBTs and alk-DBTs correspond to the period of OSdevelopment and expansion

Harner et al (2018) highlighted results of isotopicanalysis (Bosch et al 2015) of sediment cores froma small lake in the PAD (Jautzy et al 2015) In thatwork combined use of 13C 2H and 14C provided evi-dence of the contribution of petcoke from the OS to thephenanthrene in lake sediments in the PAD thus provid-ing an example of the promise of such approaches forsource attribution Petcoke has been of interest given itsopen storage at the facilities with on-site upgrading andthe toxics it contains Petcoke has been identified in snow(Zhang et al 2016) passive air samplers (Jariyasopit et al2018) moss (Zhang et al 2016) and lichen (Landis et al2019) Quantitative estimates of petcokersquos and othersourcesrsquo contributions to PAHs in moss using chemicalmass balance (CMB) have been shown to be feasible(Zhang et al 2016) Zhang et al (2016) found that closerto the open piles of coke the median amount of the PAHsin moss attributable to (delayed) petcoke was 29whereas farther away the median dropped to 9Among the moss samples examined the average petcokecontribution was 26 Emissions from upgrading wereestimated to be of similar importance with an averagecontribution of 22 In contrast there was little evidencethat PACs directly from resuspended bitumen wasmigrating to the locations of moss collection Althoughthere are ongoing uncertainties associated with source

2012

0

10

20

30

2014

0

10

20

30

0 5 10 15 20 25

2013

0

10

20

30

0 5 10 15 20 25

2011

0

5

10

15

Distance from AR6 (km)

PAC

dep

ositi

on (m

gm

)2

Figure 14 Winter 2011 2012 2013 and 2014 snowpack total PAC loadings (mgm2) versus distance (0ndash25 km) from site AR6located on the Athabasca River near the Suncor and Syncrude upgraders and roughly in the centre of the major oil sands industrialarea (Manzano et al 2016)

684 JR BROOK ET AL

apportionment as more profiles across a larger range ofPACs become available and understanding improves ofhow profiles change in the atmosphere andor afterdeposition better constraints on the solutions can beexpected Section S321 of the supplemental materialprovides a brief overview of some of the other receptormodeling or source apportionment work relevant to theOS region

Potential impacts of air pollutant deposition onwater quality and aquatic effects

The Water Component of JOSM conducted by ECCCfocused on seven priority themes related to water qual-ity and quantity modeling and benthic and fish healthwithin the LAR and receiving water bodies (Bickertonet al 2018 Chambers et al 2018 Culp et al 2018bDroppo et al 2018a Glozier et al 2018 Kirk et al 2018McMaster et al 2018) These main activities are sum-marized in the supplemental material (see SectionsS41 S42 S43) and this section focuses on resultsrelated to atmospheric deposition and understandingthe fate and impacts of this deposition on water qualityand aquatic species

Atmospheric deposition patterns of mercury andtrace metals

Paleosediment cores from a wide spatial distribution oflakes across the oil sands region indicated that PACs

and inorganic contaminants (eg vanadium) increasedsince the OS development began (1960s) with impactsmost pronounced in lakes lt50 km from the majordevelopment area (Kirk et al 2018) In addition toPACs (Figure S311) mercury and a suite of tracemetals were measured in the late winter snow samplescollected at a large number of locations (Kirk et al2014) Consistent with previous work (Kelly et al2010 2009) the peak deposition was observed close tothe most active surface mining and upgrading areas anddropped off with distance Figure 16 shows the patternfor total and methyl mercury (THg MeHg) reported byKirk et al (2014) Seventy to eighty percent of specieswere bound to particulates gt045 μm in size whichhelps explain the higher loadings closer to the sourcesgiven gravitational settling Comparing the valuesbetween the maps shows that the percent MeHg wasquite low (average 25 plusmn 17 in 2012)

Deposition at the most distant sites studied whichwere in the PAD were found to be consistent with thebaseline deposition approximated as the amount at thefar reaches of the ~20000 km2 zone measured andmapped in Figure 16 Spatial patterns in V Zn andNi which are emitted from OS operations were highlycorrelated with the THg and MeHg concentrations(r = 073minus086 P lt 001) suggesting that mercuryincluding MeHg has similar source locationsFurthermore the strength of the correlations implythat MeHg is emitted directly from some OS activitiesAn alternate explanation for the high correlationbetween THg and MeHg could be that the latter is

1000

800

600

400

200

00 10 20 30 40 50 60

West and East Transect SitesNorth and South Transect SitesAll Transect Sites

Distance (km)

Tota

l Mas

s D

epos

ited

(kg)

Figure 15 Total mass of the sum of PAHs deposited with distance from the oil sands operations Case 1 (dotted line) uses the datafrom only the north and south transect sites case 2 (dashed line) uses data from only the west and east transect sites and case 3(solid line) used data from all transect sites (Cho et al 2014 Harner et al 2018)


formed from THg in the snowpack However Williset al (2018) found that this in situ production is unli-kely to be an important net source of MeHg in thesnowpack

Crustal elements and total suspended solids deposi-tion closely followed the mercury spatial patternwhereas spatial correlations with dissolved organic car-bon (DOC) and sulfate were lower indicating differentsources or transport pathways for these species Byintegrating the total amount of THg deposited within50 km of a central point in Figure 16 (referred to asAR6 in Kelly et al [2009]) Kirk et al (2014) estimatedthat a total of lt19 and 005 kg of THg and MeHgrespectively were deposited to the landscape during thelt4-month period of snow accumulation (ie betweenthe first major snowfall and sampling in the spring)This is less than the 17 kg of THg they estimated wasemitted during that time period by assuming thatannual atmospheric emissions in NPRI did not varygreatly from month to month Thus the results fromthe snowpack are much less than the emissionsreported suggesting that the emissions may be over-estimated in the NPRI or a large percentage of what isemitted is not captured by the snow sampling or istransported further than 50 km or that a portion ofthe mercury deposited within 50 km is lost postdeposition and so is not detected in the snow THgand MeHg can undergo postdepositional processing insnowpacks likely by photoreduction and photo-demethylation However understanding of the pro-cesses controlling Hg in the surrounding environmentremains poor which was also demonstrated from

observations of the behavior of mercury observed inlichen (Blum et al 2012) In contrast through the sameestimation procedure Kirk et al (2014) found that theamounts of V and Ni in the snowpack within 50 kmwere about double the reported emissions whereas theamount of Zn deposited was more than 8 times theamount reported to NPRI

There is little understanding of how the contami-nants deposited on land as indicated by the snowsamples may be transformed biogeochemically as theymove through the sediment continuum from hill slopeto aquatic depositional areas (Droppo et al 2018b)There are also multiple ecological processes controllingrates of contaminant bioaccumulation and biomagnifi-cation through food webs during and after this trans-port into the tributaries and the LAR Comparisons ofPAH assemblages in snow and spring melt surfacewaters reveal considerable differences (Birks et al2017)

Toxicological assessment of the potential impact ofcontaminants deposited to the snowpackToxicological assessments have focused on laboratorystudies using fathead minnow larvae These chronicexposure studies (ie ge3 weeks) using melted snowfrom sites near the mines and industrial stacks demon-strated that there is decreased larval fish survival(McMaster et al 2018 Parrott et al 2018) Howeverexposure to freshet water (ie spring meltwater) didnot impact survival suggesting that the dilution occur-ring in the region is sufficient to limit impacts to fishSpecies such as walleye and white sucker have

Figure 16 Deposition of THg (left) and MeHg (right) to the Athabasca oil sands region in winter 2012 Contours of THg and MeHgloads (ng m-2) were produced through Kriging of the measured values shown by the colored circles (Kirk et al 2014)

686 JR BROOK ET AL

embryonic developmental periods of 18ndash20 days and somay be more sensitive than fathead minnow to thecontaminants in snow and spring meltwaters (Parrottet al 2018)

The apparent elimination of toxicity from snow meltto spring run off in the tributaries likely due to dilutionof the contaminant exposure was further explored bycomparing the sum of PAHs + alk-PAHs in snow andspring meltwater Parrott et al (2018) reported that thetotal concentration of PAHs + alk-PAHs in springmeltwater collected near the largest amount of deposi-tion (see Figure S311) was about 50 ng Lminus1 whereasthe concentrations in snow near this location (AR6)ranged from 23815 to 273140 ng Lminus1 Evaluation ofwhich of the deposited contaminants in the snow weremost responsible for the fish toxicity observed from themelted snow suggested that PACs were the likely cause(Lee et al 2015 Parrott et al 2018) Metals were notdeemed to be responsible for the observed effects giventheir snow concentrations relative to water guidelinesonly 13 of the 45 metals measured have a water qualityguideline (CCME Canada 1999) Similarly effects werealso not suspected to be due to naphthenic acids insnow close to industrial operations (Parrott et al 2018)However it is possible that other PACs containingN and S heteroatoms which were also characterizedby Manzano et al (2016) could be associated with theobserved effects (Parrott et al 2018)

Comparisons of the toxicity of snow samples usingthe laboratory techniques revealed that there were dif-ferences between years with 2012 snow being the mosttoxic and having the highest PAHs and 2013 being theleast toxic These differences were consistent with PACloading estimates in snow samples collected over thesame period (Manzano et al 2016) Differences in toxi-city or potency over shorter timescales such as atdifferent times in spring melt could also occur in theOS region However Parrot et al (2018) did not collectmultiple spring meltwater samples over time (withina year) to assess potential differences in contaminantconcentrations and effects on fish The toxicity of snowvaried among sampling locations However the effectswere not necessarily linked to the quantity of alk-PAHs(Parrott et al 2018) The reasons for this behaviorcould be due to the form of the PACs in the snow asit appeared that the less potent but higher-alk-PAHsnow contained particulate dust from the piles of pet-coke nearby This lower potency could be indicativethat PACs associated with petcoke particles may belargely unavailable to larval fish In contrast snowfrom a different location in the OS region that wasless impacted by petcoke dust (evidenced by particlesthat were brown and finer-grained compared with the

petcoke-impacted site) had considerable potency butlower alk-PAH concentrations implying that in thesesnow samples the particle-bound contaminants mayhave been more bioavailable to the fish

Monitoring water quality in the Athabasca Rivertributaries

Tributary monitoring occurred on 15 tributaries (10 onthe west side and 5 on the east side of the AthabascaRiver) in addition to the Clearwater River and severalof its tributaries from April 2012 to March 2015Sampling locations are shown in Chambers et al(2018) (see Figure 1 and Section S441 of the supple-mental material) The highest concentrations of thetarget parameters were observed during snowmelt per-iods or rain events suggesting a link to atmosphericdeposition although enhanced erosion was also likelyinvolved This uncertainty masks our knowledge of therelative contributions of atmospheric particulate mate-rial within the rivers versus that derived from naturalaquatic and terrestrial erosion There was a slight var-iation to the general pattern of snowmelt or rain eventpeaks for MeHg which showed increasing concentra-tions with increasing flow during spring However thegreatest concentration of MeHg occurred during themid- to late-summer months when MeHg productionis principally controlled by microbial pathways Themajority of inorganic and organic contaminants didnot exceed the Guidelines for the Protection ofAquatic Life (CCME Canada 1999) Where excee-dances did occur they were mostly associated withthe spring freshet and large rain events when sus-pended sediment and loadings are typically high Onlypyrene from the PACs showed occasional exceedancesfor established guidelines (Chambers et al 2018)

Analysis of historical tributary water quality data(1972ndash2010) showed no discernible change in concen-trations and loads of total V dissolved Se (diss Se) anddissolved As (diss As) prior to OS development whensampled above versus below the McMurray formation(Alexander and Chambers 2016) These observationswere thus used to represent reference chemical condi-tions (ie water chemistry associated with predevelop-ment conditions) Following increases in OSdevelopment concentrations and loads were oftengreater downstream of development compared withmeasurements from (unimpacted) reference sites(Figure 17) This historical analysis is suggestive ofa possible influence of OS development on total Vdiss Se and diss As concentrations and loads In addi-tion concentrations tended to be highest during the


land-clearing phase of development (Alexander andChambers 2016 Chambers et al 2018)

A case study focusing on the Muskeg River(1972ndash2009 data) provided insight into the impacts ofdevelopment and land disturbance (Alexander andChambers 2016) on tributary water quality Data fromsites on the river were grouped into three categoriesupstream of development (MU7) just downstream ofdevelopment (MU4) and downstream of development(MU1) as well as downstream of incisement of theMcMurray Formation (Figure 18) Reference condi-tions were estimated by pooling concentrations fromall upstream sites and the downstream sites sampledprior to development (Figure 18 Alexander andChambers 2016) Concentrations of diss As diss Seand total V were greatest during the early stage ofmine development at MU4 the site situated closest toactive development (13ndash35 greater than reference)Kelly et al (2010) also observed that concentrations ofmetals such as cadmium and zinc were correlated with

the extent of land disturbance in the watershedConcentrations of diss Se were also elevated duringthe subsequent development phase at the furthestdownstream site (21 greater than reference) Duringthe early phase of mine development diss As diss Seand total V loads were 34ndash126 greater immediatelydownstream of development and 47ndash148 greater atthe furthest downstream site compared with referenceloads (Figure 18) (Alexander and Chambers 2016Chambers et al 2018)

Analysis of more recent data for the Muskeg River(ie data collected during JOSM) found that annualloads of diss As diss Se and total V were gt200greater downstream compared with upstream of devel-opment (Figure 18) However differences in upstreamversus downstream loads varied seasonally differenceswere greatest during snowmelt for diss As (1299 plusmn 815vs 300 plusmn 146kg yearminus1 for downstream versusupstream respectively P = 003) but greatest duringthe open-water period for diss Se and total V (both gt4timesgreater P = 004 and P lt 001 for diss Se and total Vrespectively)

Tributary water composition has also been studiedin the context of acidity given that OS operations emitpotentially acidifying pollutants to the air and largetracks of northeastern Alberta are acid sensitiveAnalyses assessing 83 snowmelt events on fiveAthabasca River tributaries between 1989 and 2014found that 32 of the snow melts studied (39) exhib-ited acidification (pH lt 7) episodes (AlexanderChambers and Jeffries 2017) The 2012ndash2014 datashowed that snowmelt concentrations of 11 prioritypollutants and Al were always higher during low pHepisodes (Alexander Chambers and Jeffries 2017) Thisfinding is consistent with reports from Dickson(Dickson 1978) and Lawrence (Lawrence 2002) thatacidification episodes are often associated with highstream flows and can cause mobilization and transportof contaminants such as metals from the land base toadjacent water courses

Monitoring water quality in the Athabasca Riverand the PAD

Similar to the tributaries guideline exceedances werefew and generally occurred during spring freshetwhen suspended solids and contaminant loads arehigh Section S442 of the supplemental material dis-cusses the LAR monitoring implemented in JOSMTotal iron aluminum and copper had very highexceedances which is not uncommon for earth ele-ments Overall dissolved parameters often showed aninverse relationship to the hydrograph whereas those

Figure 17 Mean annual (2012ndash2014) concentrations of dis-solved arsenic (diss As) dissolved selenium (diss Se) and totalvanadium (total V) at upstream (U) and downstream (D) siteson three Athabasca River tributaries (Ells Muskeg Steepbank)Significant differences (P lt 005) are identified () betweenupstream and downstream sites on the same river (EllsMuskeg or Steepbank) or the three rivers overall (Chamberset al 2018)

688 JR BROOK ET AL

contaminants associated with the particulate phaseincreased with flow For the parameters assessed todate which included total phosphate (TP) dissolvedorganic carbon (DOC) THg MeHg and metals (AsSe V and B) there was an increase in concentrationfrom above Fort McMurray to below but thereafterthese parameters exhibited relatively constant concen-trations to the PAD This increase is suspected to be

due to the sewage treatment plant and influence fromthe Clearwater River (Glozier et al 2018)Concentration ranges for both THg and MeHg over-lapped throughout the entire study area and long-itudinal patterns were similar for both of these formsof mercury

Variations in mercury levels in the PAD tributariesthat were sampled were complex and the reasons are

Figure 18 Muskeg River watershed showing (a) the three aggregate study sites MU7 situated up stream of development MU4situated just downstream of development and MU1 (near the river mouth) situated downstream of development as well asincisement of the McMurray formation (b) concentrations of dissolved As dissolved Se and total V at the upstream site (MU7) andtwo downstream sites sampled prior to development (c) average daily loads (kbday) of dissolved As dissolved Se and total V at thedownstream site (MU1) with the stage of mining operations identified for the period of record (d) annual loads (2012-14) only) ofdissolved As dissolved Se and total V at upstream (MU7) and downstream (MU1) sites (Chambers et al 2018)


not well understood This highlights the challenge asso-ciated with studying water quality in the PAD andlinking observations to possible sources such as theOS development either from transport down the LARor in the atmosphere For example samples in down-stream reaches of the LAR Peace River and SlaveRiver as well as the Birch and McIvor rivers frequentlyexceeded the CCME guideline for THg for the protec-tion of aquatic life (CCME Canada 2003) Mean med-ian and ranges of THg and MeHg concentrations weregreatest in the two westernmost tributaries the Birchand McIvor rivers Also as with major ions and nutri-ents the total and dissolved metals measured in thetributaries of the PAD showed a large range and varia-bility and distinct patterns among sites depending onthe parameter However understanding the reasons forthis large ldquowithin-PADrdquo variability will need to improvebefore the impact of ldquoexternal inputsrdquo (eg atmo-spheric deposition from the OS flow down the AR)can be quantified

In addition to examining PAC concentrations andvariations in space and time with grab samples alongthe LAR semipermeable membrane devices (SPMDs)were deployed to passively sample multiple speciesparticularly PACs from the river water Yang et al(2011) identified a typical PAC profile for bitumenfrom the OS region Bituminous samples are domi-nated by alkylated naphthalenes fluorenes

phenantherenesanthracenes fluoranthenespyrenesand dibenzothiophenes When Yang et al (2011)combined SPMD data from the LAR and rivers ofthe PAD from 2013 to 2015 the typical bitumen PACprofile was evident However this profile was onlyevident in SPMD samples collected from sites withinand downstream of the bituminous area of theAthabasca main stem Typical of bitumen within theOS region concentrations of alk-PAHs in the SPMDsamples obtained within and downstream of the bitu-minous area were higher than those of unsubstitutedparent compounds which were dominated bynaphthalenes fluorenes phenanthrenesanthracenesfluoranthenespyrenes and dibenzothiophenes Therewere also measurable concentrations of PACs withfive and six benzenoid rings (eg benzofluoranthenesbenzopyrenes dibenz[ah]anthracene perylene benzo[ghi]perylene and indeno[123-cd]pyrene) whichare among the compounds identified as PriorityPollutants (PPs) by the EPA (2019b) and recognizedas carcinogenic by the CCME Collectively the SPMDresults suggest that natural erosion of bitumen playsa role in the LAR water chemistry but atmosphericdeposition is also contributor

Most PACs measured using the SPMDs exhibitedsimilar spatial and temporal concentration changes(Glozier et al 2018) This is illustrated in Figure 19 bythe pattern of C4-phenanthrenesanthracenes which

Figure 19 Concentration of C4-phenanthrenesanthracenes (ngL) from 2013 to 2015 at seven Athabasca River main stem sites (M0through M9) tributaries and wetlands in the Peace-Athabasca Delta (PAD) and the Peace and Slave Rivers (Glozier et al 2018)

690 JR BROOK ET AL

had the highest average concentrations (Glozier et al2018) concentrations were lowest outside the OS areain the Peace and Slave rivers and in two PAD wetlandsHigher concentrations were recorded at sites locatedwithin the bituminous watershed of the AR notablyimmediately downstream of the Clearwater River andnear the Muskeg River Concentrations within the LARdownstream of the bituminous area were slightly lowerand retained the Athabasca oil sands chemical signa-ture Tributaries within the PAD (Richardson QuatreFourches and Birch rivers) also contained measurableconcentrations of PACs

Seasonally concentrations of PACs were notably lowerduring the under-ice period than during the open-waterseason (Figure 19) This pattern in PAC concentrationsdiffered for the more volatile PACs and some of the bitu-men-specific compounds Volatile PACs were nearlyabsent upstream of the OS peaked in the OS miningarea and decreased in concentration with distance down-stream of the OS mining area (ie Slave and Peace riversPAD tributaries) This suggests evaporation into the air asone mechanism for the downstream decrease in the con-centrations of these species OS dibenzothiophenes weregreatly reduced in concentration far downstream of theOS mining area (ie in the Slave River) compared withfurther upstream likely due to the dilutive effect of thePeace River upon confluence with the LAR Other PACssuch as indeno[123-cd]pyrene were also absent fromsamples collected upstream of the OS region and moreremote areas such as the PAD Although indeno[123-cd]pyrene has been associated by other studies with oilproduction and refinery effluent discharges (HarmanFarmen and Tollefsen 2010 Parrott et al 1999) themonitoring in the LAR suggests that Fort McMurraymay be contributing For example on the east side ofthe river it was present at its highest concentrationsimmediately downstream of the Clearwater River (andFort McMurray) (Glozier et al 2018)

Methods developed for the investigation of thebiologicalecological condition of aquaticecosystems

To evaluate the efficacy of monitoring designs toanswer bioassessment questions that can potentiallydetect impacts from the OS development studies ofbenthos caged mussels and fish in the LAR mainstem tributaries deltaic and extended geographic eco-systems were undertaken (Culp et al 2018b) In theLAR main stem the benthic assemblages largely exhib-ited good ecological condition with intolerant taxafound in large abundances at all sampling sitesHowever Culp et al (2018b) demonstrated some shifts

in diversity depending upon location This suggests thatstudies of benthic assemblages can be sensitive indica-tors of impact but at present the main shift observed isdifficult to attribute to the OS development The mid-dle reaches of their study area exposed to municipalsewage effluent from Fort McMurray (includes nutri-ents) and OS development showed increased relativeabundance of tolerant taxa (Culp et al 2018b)However at sites considerably downstream of thedevelopment the community distribution shifted backtoward reference conditions upstream of the distur-bance (Culp et al 2018b) Although the observed dif-ference in middle-reach benthic communities wasassociated with trends of high algal biomass definitivelinkage of environmental drivers to this ecologicalchange will require direct examination of associationsbetween the longitudinal benthic pattern and key sup-porting variables (eg nutrients PACs V) throughadditional field experiments

Similar to the LAR main stem benthic assemblages inthe tributaries generally exhibited good ecological condi-tion with high abundance of intolerant Ephemeroptera(mayfly) Plecoptera (stonefly) and Trichoptera (caddis-fly) (EPT) taxa among the sites Biological conditions atreference sites located outside of the OS region but withinthe natural deposit were found to be similar (Culp et al2018b) However benthic assemblages in areas with anincreased OS impact were divergent from these referencesites Further investigation is required to determinewhether there is a causal relationship between exposureto environmental stressors associated with OS develop-ment and this altered assemblage composition as thebiological change was confounded between natural pro-cesses (eg erosion) and development

The PAD wetland monitoring sites represented twopotential distinct exposure pathways (1) surface flowand associated sediment deposition from the LAR and(2) atmospheric transport and deposition of emissionsin the form of snow rain andor dust particlesDespite potential contributions from these exposureroutes PAD macroinvertebrate assemblages appearedto be in a healthy state exhibiting high biodiversity aswell as strong seasonal and spatial variability of rich-ness and composition (Culp et al 2018b) Thus todate there is no evidence of cumulative effects (onbenthos species) in these deltaic ecosystems arisingfrom OS activities

Mussels exposed to middle-reach waters were lessable to cope with stress tests and compared withreference sites mussel condition was lower at sitesdownstream of the OS development area (Piloteet al 2018) These longitudinal patterns may indicatemild environmental stress related to the combined


effects of nutrient (sewage treatment effluent) andcontaminant stressor (ie natural or emitted OS con-taminants) exposure

Monitoring of fish health in OS region was builtupon the methods developed for CanadarsquosEnvironmental Effects Monitoring program (egMcMaster Hewitt and Parrott 2006) To assess theability of these methods to identify potential impactssampling locations encompassed reference sites insideand outside the OS deposit that were both upstreamas well as downstream of development White suckerswere used to assess changes because in previous work(Arciszewski et al 2017b) they were found to besensitive indicators of fish health in relation to sam-pling downstream and within the OS depositHowever similar to the main stem benthic resultsthe pattern observed thus far is indicative of nutrientenrichment as white sucker were older longer andheavier than reference fish thus exhibiting increasedcondition and increased levels of internal fat storesWhite suckers within the deposit also exhibited expo-sure to PACs as their livers had significantlyincreased enzyme activity (ie induced biomolecularchanges Arciszewski et al 2017b)

Fish health research in the tributaries conducted bythe JOSM Water Component developed health base-lines for sentinel species primarily the slimy sculpinand used this information to determine the potentialfor OS development to affect overall fish health (Parrottet al 2018) Slimy sculpin were found to be sensitivebiological indicators as shown by consistent changes infish health between reference and exposure sites withinthe OS deposit The recorded end point changesincluded increases in liver size with corresponding bio-molecular changes (ie induction of ethoxyresorufin-O-deethylase [EROD] activity) for fish collected atexposure sites as well as reductions in energy investedin reproductive development as represented by lowergonadal development These downstream responses areindicative of exposure to inducing compounds asEROD activity followed a similar pattern to PACbody burden the latter of which is shown in Figure20 Moreover assessment of sediment toxicity sug-gested that sediments were the source of the elevatedPACs in the water column (McMaster et al 2018)Controlled exposures of fathead minnows to naturaloil sands sediment from two river sites (SteepbankRiver and Ells River lower sites) demonstrateddecreased embryolarval fish survival (Parrott et al2018) However continuous exposure of resident fishto sediment within the oil sands deposit appears to berequired for the increased expression of EROD activity

at these sites (McMaster et al 2018) Similar to thetributaries sculpin in the LAR within the OS depositarea also appeared to be exposed to compounds thatinduce biomolecular changes (inducing compounds)Furthermore there is evidence that exposure to thesecompounds is higher downstream of development(McMaster et al 2018)

Establishing a methodology for causal assessmentof ecological effects

Attribution to the OS development activities andrelated atmospheric deposition remains uncertaingiven other stressors (eg Fort McMurray sewagetreatment plant releases to the AR) and inputs fromnatural bitumen erosion The impact of human activ-ities in aquatic ecosystems is most often the result ofmultiple stressors associated with different sources ofstressors (Norton Cormier and Suter 2015) Becauseof this it is challenging to link ecological effects toindividual stressors or the combined interactiveeffects of multiple stressor threats An effectiveapproach for analyzing a large body of evidence of

Figure 20 Polycyclic aromatic compounds (PACs) levels infemale slimy sculpin collected from the Steepbank River duringthe fall of 2012ndash2013 Sites represent the Steepbank lower site(lower and RAMP lower same site) Steepbank mid site (MCMid) Steepbank upper site (MC Upper) and a site furtherupstream (RAMP Upper) Values represent the mean plusmn SEParent PAHs pink alkylated PAHs green total PAHs blue(Reproduced from Culp et al 2018b)

692 JR BROOK ET AL

stressor effects on ecological components of aquaticecosystems is the use of weight-of-evidenceapproaches such as the ecological casual assessmentmethod proposed by Norton Cormier and Suter(2015) This approach which can assess data fromdifferent sources such as of pollutants from naturalerosive processes or atmospheric deposition is beingimplemented to evaluate its utility to collectivelyassess their relative potential to cause ecological effectsin the context of the OS (Culp et al 2018a) Resultsare suggestive that this weight-of-evidence approachcan enable the linkage of ecological effects and candi-date causes and forward plausible support as to theimportance of these pathways (Culp et al 2018a)

Causal pathways suggest that the observed LAR eco-logical trends were associated mostly with nutrientenrichment from treated municipal sewage effluentfrom Fort McMurray However the combined con-taminant exposure from sewage effluent industrialoperations (atmospheric deposition) and natural expo-sure to bitumen may also be contributing to theseecological trends (Culp et al 2018a)

Potential impacts of air pollutantconcentrations and deposition on wildlife

The Wildlife Contaminants and Toxicology Componentrsquosmain objective was to assess the health of wildlife speciesthat are potentially exposed toOS-generated contaminantsIn terms of direct wildlife impacts the key chemicals ofconcern were PACs Hg and MeHg trace metals andnaphthenic acids Each has the potential to cause toxicityand some can bioaccumulate and biomagnify in biota andmay persist in the environment (Achten and Andersson2015 Clarkson 1993 Clemente and Fedorak 2005)A sentinel species (see Section S53 of the supplementalmaterial) approach was adopted to gain a better under-standing of exposure routes impacts and the biologicalmechanisms involved potentially enabling development ofa long-term wildlife contaminant and toxicology monitor-ing program As such in-depth monitoring and researchprojects were carried out with multiple species to assess thepresence and effects of contaminants in plant commu-nities in terrestrial and wetland species and in down-stream receiving environments

The main sentinel species used in the WildlifeContaminants and Toxicology Component projectsare listed in Table 1 ecological surveys and samplingstrategies varied among the species listed For amphi-bians migratory birds and plant communities andsemiaquatic furbearer species all of which stay withinlocalized areas during the key periods of interestexposed (ie near to the OS operations) and control

or baseline locations were studied and comparedMultiple representative sites for each of these condi-tions were identified and sampling was largely carriedout in 2012ndash2014 with some continuing to 2018 Forcolonial waterbirds the PAD was of interest given thepotential for accumulation of contaminants of concern(COCs) from atmospheric deposition and transportdown the LAR

The wildlife species listed in Table 1 were able toprovide information on contaminant burdens and spa-tial and temporal trends of COCs in the region andwere used to assess toxicological responses to COCexposure Thus these species were used to provide theinsight needed for evaluating the health of native spe-cies and generate information on overall ecosystemhealth (Cruz-Martinez and Smits 2012) In additionstudying some of these species provided informationrelated to food safety and food security concerns forlocal indigenous land-users andor were also poten-tially important species (ie valued ecosystem compo-nents) as a result of their cultural and traditional valuesor their importance for local economic livelihood SeeSection S552 of the supplemental material

Plant health and community composition

Using on-site vegetation surveys (see Section S553 ofthe supplemental material) and observations from the

Table 1 JOSM Wildlife Contaminants and ToxicologyComponent sentinel speciesSpecies group Sentinel species Contaminants

Mammals Muskrat (Ondatrazibethicus)

Heavy metalsPACs trace metals

Beaver (Castorcanadensis)American marten(Martes americana)Mink (Neovison vison)River otter (Lontracanadensis)Fisher (Martespennanti)

Colonial waterbirds Caspian tern(Hydroprogne caspia)

As Hg PACs

Common tern (Sternahirundeo)Ring-billed gull (Larusdelawarensis)California gull (Laruscalifornicus)Herring gull (Larusargentatus)

Amphibians Wood frog (Lithobatessylvaticus)

Hg PACs

Plant health andcommunitycomposition

Wetlanduplandvegetation communities

Trace metals PACs

Migratory birds Tree swallow(Tachycineta bicolor)

PACs

See Section S552 of the supplemental material


corresponding seed bank germinated in the laboratory(from soil samples) it was found that OS sites hadgreater species richness compared with the east andwest reference sites although this difference was onlysignificant for OS versus east sites However overalldiversity was high across the sites with 290 herbaceousand woody plant species identified in the region ofwhich over 85 were perennial species (Boutin andCarpenter 2017) The added richness at the OS siteswas mainly composed of non-native or introduced spe-cies compared with reference sites that were almostexclusively native perennials

OS sites also had greater levels of PACs in soil andvegetation (above- and belowground plant parts) com-pared with the reference sites Although the relativeproportion of alk-PAHs and parent PAHs were notsignificantly different among sites (soil and vegetation)with alk-PAHs being more prevalent there were differ-ences in the distribution among PAC species (soil)among some sites (Boutin and Carpenter 2017) Soilguidelines (Ontario andor EPA) were exceeded forseveral of the parent PAHs at some of the OS sitesThere was a significant negative correlation betweensite minimum distance to an upgrading facility andthe total concentration of parent PAH compoundsand a weaker nonsignificant correlation with alk-PAHs Distance to the nearest upgrader facility wasalso significantly correlated to trace metal concentra-tion for 13 of the 28 metals measured with elevatedlevels at OS sites (Boutin and Carpenter 2017) Therewere guideline exceedances for 14 out of 28 metalsmeasured predominantly at the OS sites (Boutin andCarpenter 2017) Further investigation is required todetermine how specific contaminants affect plant spe-cies and to understand potential contaminant burdensin the food web

Amphibians

Boreal wetlands closer to the OS facilities receivespring melt containing significant amounts of atmo-spheric contaminants that were deposited and accu-mulated in the snow over winter As discussed abovethe link between these contaminants and their levelsin tributaries and the LAR is complex but localwetlands may be more directly impacted and arethus an important ecosystem to monitor As thespring melt coincides with the wood frog breedingseason wood frog early life stages may be exposed topotentially high COC levels during early stages ofdevelopment In particular amphibians may beexposed to detrimentally high levels of PACs duringembryo development which is a particularly

sensitive point in their life cycle (Mundy et al2018) Amphibians have shown to be sensitive indi-cators of wetland quality during previous studies onwetlands containing OS processed water (HersikornCiborowski and Smits 2010 Pollet and Bendell-Young 2000)

Under the Amphibian and Wetland Health programsamples were collected from wetlands close to and moredistant from OS industrial facilities to measure concentra-tions of the COCs in amphibian breeding habitatMeasurements were obtained in wood frog tadpoles andin addition PAC concentrations were measured usingsemipermeable membrane devices (SPMDs) TheseSPMDs were deployed at the same wetlands for

Figure 21 (A) sumPACs detected in SPMDs (ng SPMDminus1) deployed inthe Athabasca oil sands region (AOSR) Field blank corrected Barsrepresent the mean with error bars representing the standard errorof the mean from duplicate (Gateway 2014 Hat-S5) and triplicateSPMD deployments Wetlands study sites are arranged on the x-axisfrom nearest to furthest from oil sands upgraders (B) sumPACs accu-mulated in SPMDs (ng SPMDminus1) deployed in 2013 and 2014 asa negative exponential relationship with distance from oil sandsindustrial development (r2 = 089) PAC values are field blankcorrected error bars represent the standard error of the mean ofdetected PAC analytes Note Gateway wetland was not included inthis analysis because it is adjacent to a reclaimed overburden pile(C) sumPACs accumulated in SPMDs represented as Cfree (pg Lminus1)deployed in 2013 and 2014 as a negative exponential relationshipwith distance to upgraders (r2 = 066) As noted above Gatewaywetland is not included in this analysis (Mundy et al 2018)

694 JR BROOK ET AL

5ndash6 weeks close to the locations of wood frog egg massesThe PAC profiles found in the wood frog tadpoles and theSPMDs were dominated by C1ndashC4 alk-PACs indicatingpetrogenic sources (Mundy et al 2018) Although the totalPACs in wood frog tadpole tissue did not differ signifi-cantly between wetland sites SPMDs deployed withina 25 km radius of surface mining activity measured thehighest concentrations of PACs showing a significantexponential relationship between PAC accumulation anddistance to OS mining activities (Figure 21) consistentwith the snow deposition studies discussed above Thesite closest to the OS upgrading facilities which wasalong the north-south highway adjacent to SUN andSML had SPMD PAC levels that were approximately 10-fold and 3-fold higher than the other wetland sites in 2013and 2014 respectively (Mundy et al 2018) In the woodfrog tadpoles total PACs were 25 higher at this closestlocation however there were no statistically significantdifferences among the locations for parent PAHs or thealk-PAHs overall Mercury and MeHg and trace metalswere also measured in wood frogs and their habitat levelswere generally low and did not reveal a spatial pattern inrelation to distance to air pollution emission sourcesalthough levels infrequently surpassed the CCME guidelinelevels for the protection of freshwater aquatic life (CCMECanada 1999)

Discrepancies among SPMD accumulation of PACsand invertebrate tissues have been observed in otherstudies as described in Mundy et al (2018)) Thuslaboratory studies were conducted to improve under-standing of the wood frog tadpole exposure routes andmetabolism of alkyl and parent PACs using sedimentcollected from the McKay River in the OS region(Bilodeau et al 2019) The wood frog tadpoles exposedto PAC-laden sediment and water were found torapidly accumulate and commence elimination ofmost PACs within 12ndash24 hr of exposure (Bilodeauet al 2019) and reach an equilibrium within 12ndash48 hrMultiple linear regression analyses showed that PACconcentrations in the sediment were a better predictorof PAC concentrations in the wood frog tadpoles thanthe water concentration during combined exposureexperiments The wood frog tadpoles accumulatedmore total alk-PACs than parent PACs as well ashigher concentrations of the alkylated compoundscompared with their respective parent compoundsThere was also a clear petrogenic PAC profile observedin the wood frog tadpoles this closely resembled theprofile of the McKay River sediment to which they wereexposed (Bilodeau et al 2019) Overall both parent andalkyl-substituted PACs had low bioaccumulationpotential with anthracene fluoranthene retene andC1-benzofluoranthenesbenzopyrenes having the

highest potential and only C4-naphthalenes persistingin wood frog tadpoles after 48 hr of depuration Thusthe results of the laboratory experiments suggested thatthe wood frog tadpoles seem to be efficient at metabo-lizing and eliminating most parent and alkyl-substituted PACs (Bilodeau et al 2019)

Despite the complicated exposure pathways andbioaccumulation behaviors of PACs in wood frog tad-poles the results to date suggest that it might be pos-sible to use SPMDs to monitor PACs in naturalwetlands in the OS region and possibly to replacesampling of wood frog tadpoles with SPMD deploy-ment in an effort to replace invasive and lethal animalsampling with the use of passive samplers Howeverthere is a need for further validation of SPMDs assurrogates for wood frog tadpoles considerationsaround water chemistry interactions and PAC uptakeby wood frog larvae and tadpole PAC metabolism inrelation to SPMD accumulation need to be addressed(Weinhold 2011) Nevertheless use of SPMDs as pas-sive environmental samplers shows promise for theassessment of the potential exposure of resident wet-land species to PACs and with further investigationthis approach might be used to monitor model andassess the risk for potential toxicological impacts overspace and time

Migratory birds

In the OS region PACs can accumulate in sedimentsand aquatic insects resulting in a high exposure poten-tial to PACs for nesting tree swallows that primarilyconsume aquatic insects (Fernie et al 2018a) In thepast biological responses of tree swallows breeding onreclaimed wetlands in the OS region have been studied(Cruz-Martinez et al 2015 Gentes et al 2007 GodwinBarclay and Smits 2019 Harms et al 2010) DuringJOSM colonies of nest boxes for breeding tree swallowswere established adjacent to water bodies (Figure S51)at four study sites in 2012 and 2013 (Fernie et al2018a) Two colonies were located in the surfacemining area of the Fort McMurray region within5 km of active mining extraction and processing (OSsites) Two other colonies were established at referencesites one in 2012 and the other in 2013 more than100 km from regional OS operations (Fernie et al2018a)

At the sites samples of blood pectoral muscle dor-sal feathers and feces were collected from the treeswallow nestlings along with passive air samples (mea-surements including SO2 NOx hydrogen sulfide [H2S]and VOCs) and grab samples of water Twenty-oneanalyzed parent PAHs all 13 alk-PAHs and 4 of 5


DBTs were found in nestling (muscle and feces) airand water samples and for most PACs levels werehigher at OS sites compared with reference sites(Figure 22) These data enabled PAC tissue concentra-tions of tree swallows to be described in relation toconcentrations in the air and water Compared withreference sites tree swallow nestlings developing nearactive mining sites located in the OS region accumu-lated higher concentrations of PACs and exposureroute importance was dependent on the specificcompound

Two main interrelated outcomes were studied in thetree swallows thyroid morphology and hormones(Fernie et al 2019) and reproductive success and devel-opmental changes (Cruz-Martinez et al 2015 Fernieet al 2018) As described above the nestlings wereexposed to a combination of stressors Thus althoughit is difficult to tease out cause of the effects observed

these studies were able to use statistical models toidentify which of the measured stressors contributedto the changes observed in the tree swallowsHowever results suggest that the greatest influenceson avian thyroid function in the OS region especiallythe thyroid gland came from the nestlingsrsquo accumula-tion and tissue burdens (ie PAC levels in muscle)more so than their short-term exposure (ie PAC levelsin feces) to PACs particularly to C2-naphthalenesTheir consumption of aquatic emerging insects withhigher PAC burdens than terrestrial insects likely alsoplayed a role in the changes observed in thyroid func-tion of the nestlings Colder (minimum) temperaturesduring nestling development and air pollutants espe-cially SO2 during the nestling period further contrib-uted to alterations in thyroid function Although thecombined effects of these multistressor impacts arecomplex and all were identified as contributing to the

Figure 22 The concentrations of the six major PAHs measured in nestling tree swallows (ngg wet weight) Concentrations weresimilar between the reference birds (REF1 REF2) and significantly higher (P le 005) in the birds from the oil sands miningndashrelatedsites (OS1 OS2) in the Athabasca oil sands region (Fernie et al 2018a)

696 JR BROOK ET AL

impacts on thyroid morphology and hormones theseresponses were most notable in the birds having thehighest PAC burdens (OS site) therefore suggestinga clear role of the PACs However multivariate analysesalso revealed consistent relationships between SO2 andthyroid activity substantiating initial hypotheses (egFernie et al 2016) In addition although similar repro-ductive success was observed among sites in 2012reproductive success at OS site 2 was significantlylower than other sites during 2013 there the nestlingsrsquobeing significantly lighter and in poorer body conditionwas related in part to the exposure andor accumula-tion of specific PACs The results to date suggest thatalthough tree swallows were likely able to compensatefor their air pollution PAC exposure a combination ofhatching timing diet weather and contaminant expo-sure and accumulation likely all affected reproductivesuccess and nestling development (Fernie et al 2018)Further study is needed however given the addedcomplexity of the timing of these combined stressorswhich was found to potentially be important (Fernieet al 2018) Overall different factors likely influencenestling body mass at different ages diet and PACsmay have more influence on younger nestlings whereassex hatch date and the extent of rainfall but poten-tially not exposure to PACs may influence the growthof older nestlings (Fernie et al 2018)

Colonial waterbirds

In the PAD as elsewhere colonial waterbirds are high-tropic-level species and therefore can accumulate highlevels of biomagnifying contaminants such as Hg(Dolgova et al 2018b) Colonial waterbird eggs fromgull and tern colonies in downstream receiving envir-onments of the LAR were therefore used to assess

spatial and temporal trends in Hg arsenic (As) andPACs in eggs (Campbell et al 2013 HebertNordstrom and Shutt 2010 Hebert et al 2011) A keymethodological development enabled this assessmentnamely the ability to standardize concentrations acrossspace and species through the use of compound-specific amino acid stable isotope analyses (Dolgovaet al 2018a 2018b) This approach can account fordifferent embryonic developmental stages across differ-ent colonial waterbird species at different trophic posi-tions Although As and PAC levels were low analysishas shown that Hg levels increased in gull and tern eggscollected from sites in LAR receiving waters over theJOSM period whereas Hg concentrations in Californiagull eggs at Alberta sites south of this region havedeclined over time (Campbell et al 2013 Hebert et al2011) Compared with reference sites to the south andnorth Figure 23 shows that Hg concentrations in gulleggs were found to be greatest at sites in downstreamreceiving waters of the LAR Levels have exceededtoxicity thresholds for embryotoxicity in Caspian terneggs (Campbell et al 2013 Hebert et al 2011) Inaddition Hg concentrations in gull and tern eggs aresufficiently high in northern Alberta to require anadvisory restricting their consumption by indigenousharvesters and traditional land-users (My WildAlberta2017) Although higher Hg levels in gull and tern eggshave been found in receiving environments down-stream of the OS region (Dolgova et al 2018a) andpotential mechanisms and Hg transport pathways existthat could help explain these higher Hg levels down-stream (Hebert 2019) additional research is required tounderstand the role of the LAR in transporting Hg todownstream environments and more research invol-ving Hg in air in aquatic and terrestrial systems and inbiota in the region is necessary to assess the relative

Figure 23 Geometric mean (plusmn 95 confidence intervals) total mercury (THg) concentrations in gull eggs collected from threeregions south (lt58degN sites 1ndash5) downstream of the Athabasca River (589degNndash594degN sites 6ndash8) and north (gt59degN sites 9ndash12) Sitenumbers are shown in Figure 1B (a) Regional means based on non-normalized THg data (b) Regional means based on THg datanormalized for trophic position (δ15NBulkPhe) and species Letters above means indicate statistical differences (means with the sameletter are not different) Phe = phenylalanine (Dolgova et al 2018b)


contribution of the OS industrial operations to theoverall Hg budget of the LAR and downstreamenvironments

Sentinel species

For a sentinel species to be useful it needs to besensitive to exposure to the contaminant of interestso that a measurable biological effect occurs inresponse to exposure (Cruz-Martinez and Smits2012) Sensitive and measurable (and robust andrepeatable the measures must be easily distinguishedfrom the ldquonoiserdquo in the system) biological effects areimportant for early detection of contaminant concen-tration changes in the ecosystem and for providingpotential ldquomarkersrdquo or thresholds for regulatoryaction (Cruz-Martinez and Smits 2012) Soundknowledge of the sentinel speciesrsquo biology is alsorequired so that causation of effects can be investi-gated Given that contaminants can be transportedthroughout the ecosystem exposure routes will varydepending on the species Species of higher trophicpositions within an ecosystem are valuable as sentinelspecies as they have the potential to bioaccumulateand biomagnify certain contaminants and can there-fore provide insight to ecosystem effects (Cruz-Martinez and Smits 2012)

Feasibility of cost of sample collection and analysesis another important consideration when selectinga sentinel species not only for practicality but alsofor cost efficiency (Cruz-Martinez and Smits 2012) Inaddition species that have widespread distribution buta restricted home range ensure exposure to local con-taminants while allowing site selection to occur to allowoptimization of study design (Cruz-Martinez and Smits2012) It is also important that samples can be easilyobtained and that the species is tolerant to interferenceif the study involves noninvasive or nonlethal sampling(Cruz-Martinez and Smits 2012)

Tree swallows have been used to monitor contami-nants in the OS region since the late 1990s with aneven longer history of use in examining effects onecosystems of environmental contaminants Table 2lists the criteria used in the comprehensive evaluationframework for assessing a speciesrsquo potential asa sentinel species and summarizes expert judgmentfor the tree swallow as a case study This builds uponexisting knowledge including recent experience gainedduring the JOSM Many of the tree swallow attributesbased on the criteria in Table 2 support a conclusionthat they are a robust sentinel species for long-termambient monitoring of the potential impacts of airpollution in the OS region

Concluding remarks

This critical review attempts to describe the extent ofthe ECCC science advances in air pollution under-standing and links to potential ecosystem responsespertaining to OS development in Alberta CanadaThis work was in support of JOSM a major multi-stakeholder effort Recognizing that the extent of themonitoring and research that has been conducted dur-ing JOSM and by other researchers is greater than whathas been covered in this critical review it is not appro-priate to base overall conclusions about OS impactsonly on the portion of the work presented hereFurthermore JOSM (now referred to as OSM) is anongoing program and ECCC results reviewed hererepresent relatively early steps in the research giventhe long time frame required to advance understandingof the complex scientific questions affecting the OSregion

Important improvements have been made in base-line information across air water and wildlife and asa result future monitoring can be expected to be moresensitive and responsive to environmental changesassociated with OS development Monitoring and eva-luation of potential sentinel species relevant to air pol-lutant emissions that have been undertaken haveidentified approaches for continued monitoring in theOS region Contaminant exposures have been docu-mented in the aquatic and terrestrial species studiedand biological responses have also been observedHowever attribution of these effects to OS air pollutantemissions in light of other sources and stressors isa significant challenge and knowledge is incomplete

Table 2 Criteria supporting use of the tree swallow as anindicator of OS air pollution impacts

Tree swallow rank

Criterion Low Medium High

Robust and reproducible response Research feasibilitytractability Response sensitivity Link to OS Link to air pollution Link to OS air pollution Cost-efficient ldquoHealth-basedrdquo measurements possible Laboratory validation Noninvasive or nonlethal possible Regulatory relevance ldquoThresholdrdquo measurements Long-term monitoring capability Power analysis for sample size possible Human health linkage Risk assessmentmapping possible Indigenous knowledge incorporation possible

Notes The ldquovaluerdquo or ability of the tree swallow to fulfill the requirements ofthe individual criteria is ranked based upon expert judgment Table S51(Section S53 of the supplemental material) provides rationale and sup-porting citations for these rankings

698 JR BROOK ET AL

Understanding the significance or implications of theseeffects also requires further research In particular link-ing water quality throughout the region to OS develop-ment and the associated atmospheric emissions whileaccounting for natural levels of contaminants such asPACs due to erosion of bitumen remains a challenge

Ongoing research related to the OS region will beable to improve quantification of emissions and atmo-spheric processes so that areas of potential concern (iewhere contaminants are being detected in the ecosys-tem or are projected to be occurring at or near criticalloads) can be more reliably characterized and priori-tized for enhanced monitoring This could also includeambient monitoring of pollutants previously not stu-died such as intermediate volatility organic species(IVOCs) organic nitrates organic acids isocyanicacid secondary organic aerosols and large particle(dust) composition

Increasing the extent that ambient concentrationand deposition monitoring of pollutants is activelylinked to research undertaken by the other compo-nents (ie water and wildlife) will be needed to gaina better understanding of the specific role(s) of airemissions in ecological effects Greater integrationwill also be necessary to improve understanding ofhow the elevated amounts of deposition of acidifyingand neutralizing compounds mercury trace metalsand PACs that have been identified within 25ndash50 kmof the main surface mining region move from thepoints of deposition into the watershed and biotaSimilarly more-integrated studies are needed inorder to better understand the origins of the higherlevels of mercury in gull eggs in the PAD and thereasons for the observed variability in mercurymetals and PACs among sampling points across thePAD In the future these integrated studies wouldideally lead to a much improved understanding ofthe relationships among the emissions of these pollu-tants of concern and ecosystem exposures (ie deposi-tion transformation and uptake) and biologicalresponses However atmospheric and multimediamodels capable of representing these processes (forPACs and metals) have yet to be applied and testedin the OS region Acquiring this capacity (eg physi-cally based models of PAC emission transformationand deposition) will require more research and devel-opment and the importance or priority of obtainingsuch capacity requires assessment including new mea-surement studies that test current knowledge

To obtain the holistic understanding desired fromair emissions to impacts many knowledge gaps willneed to be filled Many of these gaps are not uniqueto the OS but represent ongoing gaps in scientific

understanding of relevance to most environmentalissues pertaining to pollutant releases to the air (egdry deposition and atmospheric scavenging processesbiological effects of chemical mixtures and of multiplestressors including effects of low-dose chronic expo-sures multimedia measurement and source attributionof chemical exposures)

The weight of evidence based upon multiple mea-surements and data analyses indicates that atmosphericemissions from complex industrial sources are not wellknown and are likely being underestimated This per-tains to key toxics generally emitted in small quantitiessuch as PACs and metals for which emissions aredifficult to determine particularly from fugitivesources to compounds previously not formally consid-ered such as low-molecular-weight organic acids andintermediate and semivolatile organic compounds andto important criteria air contaminants such as VOCsGiven the critical role of accurate knowledge of what isbeing emitted to scientific understanding of effects(eg estimating inputs into ecosystems) and environ-mental management addressing the gap in emissionknowledge is important

A scientifically sound sentinel species approach towildlife monitoring is emerging and becoming viableHowever identification of the appropriate thresholdsfor meaningful effects (eg critical effect sizes) includ-ing in aquatic species that can be sufficiently attributedto OS development activities and air pollutant emis-sions and that can be used to predict more seriouseffects (and additionally in the context of overall cumu-lative effects) represents an ongoing challenge Signs ofearly stress through monitoring are desired howeverthresholds at which adaptive OS management woulddictate a response requires attention As mentionedabove more-integrated studies are needed to poten-tially advance understanding

Some of the priorities for ongoing and enhancedmonitoring to advance scientific understanding andpotentially inform adaptive management include multi-media multistressor monitoring of conditions andchanges and their sources in the PAD deposition andecosystem changes in areas where current best esti-mates are that critical loads for acidic deposition arebeing exceeded tracking of changes in contaminantlevels in plant and animal tissues particularly thoseconsumed by humans where some levels have led toconsumption advisories and improved tracking andindependent validation of atmospheric emissions ofa wide range of compounds from multiple sourcesincluding key fugitive sources that contribute to thelarge burden of chemically complex dust in the near-field region and VOCs (IVOCs) and PACs


Glossary of terms

ALKA C4+ alkanesalk-DBTs alkylated dibenzothiophenesalk-PAHs alkylated PAHsAPEI Air Pollutant Emissions InventoryAOP adverse outcome pathwayAR Athabasca RiverAROM ditrisubstituted aromaticsAURAMS A Unified Regional Air-quality

Modeling SystemBTEX benzene toluene ethylbenzene and

xylenesCACs criteria air contaminantsCCME Canadian Council for Ministers of the

EnvironmentCEMA Cumulative Environmental

Management AssociationCES critical effect sizesCLRTAP Convention on Long-Range

Transboundary Air PollutionCNRL Natural Resources Limited Horizon

FacilityCOCs contaminants of concernDBTs dibenzothiophenesDOC dissolved organic carbonECCC Environment and Climate Change

CanadaEFs emission factorsEPA US Environmental Protection AgencyEPT Ephemeroptera (mayfly) Plecoptera

(stonefly) and Trichoptera (caddisfly)(EPT)

EROD ethoxyresorufin-O-deethylaseFA HCOOHformic acidFAB First-Order Acidity BalanceGEM Global Environmental MultiscaleGEM-MACH Global Environmental Multiscalendash

Modeling Air-quality and CHemistrymodel

GHGs green house gasesGHGRP Greenhouse Gas Reporting ProgramHNCO isocyanic acidIJC International Joint CommissionIKL Imperial Kearl Oil Sands MineIVOCs intermediate volatile organic

compoundsJOSM Joint Oil Sands Monitoring (Canadamdash

Alberta)LAR Lower Athabasca RiverLMWOAs low-molecular-weight organic acidsMeHg methyl mercuryNEG-ECP New England GovernorsndashEastern

Canadian PremiersNPRI National Pollutant Release InventoryOMI ozone monitoring instrumentON organonitratesOS oil sandsPACs polycyclic aromatic compoundsPAD Peace-Athabasca DeltaPAHs polycyclic aromatic hydrocarbonsPM or TPM particulate matter

POD phytotoxic ozone dosepON particulate organonitrate compoundsPOPs persistent organic pollutantsRamsar Convention The Convention on Wetlands of

International ImportanceRSC Royal Society of CanadaSAJ Shell Albian Sands and Jackpine MinesSAU Syncrude Aurora Facilitydiss As dissolved Asdiss Se dissolved SeSLCPs short-lived climate pollutantsSMB Simple Mass BalanceSML Syncrude Mildred Lake FacilitySOA secondary organic aerosolSPMD semipermeable membrane deviceSSWC Steady-State Water ChemistrySVOCs semivolatile organic compoundsSUN Suncor Millenium and SteepbankTEEM Terrestrial Environmental Effects

MonitoringTEK traditional ecological knowledgeTERRA Top-down Emission Rate Retrieval

AlgorithmTES tropospheric emission spectrometerTHg total mercuryTOLU monosubstituted aromaticTP total phosphateUNECE LRTAP United Nations Economic

Commission for Europe Long-RangeTransboundary Air Pollution

UNESCO United Nations Educational Scientificand Cultural Organization

UNFCCC United Nations FrameworkConvention on Climate Change

VOC volatile organic compoundsWBEA Wood Buffalo Environmental

AssociationWMO-UNEP World Meteorological Organisationndash

United Nations EnvironmentalProtection

Acknowledgment

The authors thank Stoyka Netcheva Sean Rowe AndreaDarlington Julie Narayan Mark Shepard and ChrisMcLinden from the Air Quality Research Division ofEnvironment and Climate Change Canada Kim FernieCatherine Soos Craig Hebert Phil Thomas Lukas MundyCeacuteline Boutin David Carpenter and Julie Bilodeau from theWildlife and Landscape Science Directorate and Joseph Culpand Ian Droppo from the Water Science and TechnologyDirectorate of Environment and Climate Change Canadafor their contributions

Funding

The monitoring reviewed in this paper was funded under theOil Sands Monitoring Program and through the Environmentand Climate Change Canada Air Pollution program

700 JR BROOK ET AL

About the author

Dr JR Brook recently joined the faculty at the University ofToronto after a 27 career as a scientist in the Air QualityResearch Division of Environment and Climate ChangeCanada

References

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Akingunola A P A Makar J Zhang A Darlington S-M Li M Gordon M D Moran and Q Zheng 2018A chemical transport model study of plume rise and par-ticle size distribution for the Athabasca oil sands AtmosChem Phys 188667ndash88 doi105194acp-18-8667-2018

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Alexander A C P A Chambers and D S Jeffries 2017Episodic acidification of 5 rivers in Canadalsquos oil sandsduring snowmelt A 25-year record Sci Total Environ599-600739ndash49 doi101016jscitotenv201704207

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Arciszewski T J K R Munkittrick B W KilgourH M Keith J E Linehan and M E McMaster 2017bIncreased size and relative abundance of migratory fishesobserved near the Athabasca oil sands Facets 2833ndash58doi101139facets-2017-0028

Arciszewski T J K R Munkittrick G J ScrimgeourM G Dubeacute F J Wrona and R R Hazewinkel 2017aUsing adaptive processes and adverse outcome pathwaysto develop meaningful robust and actionable environ-mental monitoring programs Integr Environ AssessManag 13 (5)877ndash91 doi101002ieam1938

Arey J W P Harger D Helmig and R Atkinson 1992Bioassay-directed fractionation of mutagenic PAH atmo-spheric photooxidation products and ambient particulateextracts Mutat Res Lett 281 (1)67ndash76 doi1010160165-7992(92)90038-J

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Baray S A Darlington M Gordon K L HaydenA Leithead S-M Li P S K Liu R L MittermeierS G Moussa J OlsquoBrien et al 2018 Quantification ofmethane sources in the Athabasca Oil Sands Region ofAlberta by aircraft mass balance Atmos Chem Phys187361ndash78 doi105194acp-18-7361-2018

Bari M W Kindzierski and S Cho 2014 A wintertimeinvestigation of atmospheric deposition of metals andpolycyclic aromatic hydrocarbons in the Athabasca OilSands region Canada Sci Total Environ 485ndash486180ndash92doi101016jscitotenv201403088

Bickerton G J W Roy R A Frank J SpoelstraG Langston L Grapentine and L M Hewitt 2018Assessments of groundwater influence on select river sys-tems in the oil sands region of Alberta Oil SandsMonitoring Program Technical Report Series No 15 32ISBN 978-1-4601-4029-1

Bilodeau J C J M Gutierrez-Villagomez L E KimpeP J Thomas B D Pauli V L Trudeau and J M Blais2019 Toxicokinetics and bioaccumulation of polycyclic aro-matic compounds in wood frog tadpoles (Lithobates sylvati-cus) exposed to Athabasca oil sands sediment AquatToxicol 207217ndash22 doi101016jaquatox201811006

Birks S J S Cho E Taylor Y Yi and J J Gibson 2017Characterizing the PAHs in surface waters and snow in theAthabasca region Implications for identifying hydrologicalpathways of atmospheric deposition Sci Total Environ603ndash604570ndash83 doi101016jscitotenv201706051

Blum J D M W Johnson J D Gleason J D DemersM S Landis and S Krupa 2012 Mercury concentrationand isotopic composition of epiphytic tree lichens in theAthabasca Oil Sands Region In Alberta Oil Sands EnergyIndustry and the Environment ed K E Percy 373ndash90Oxford UK Elsevier

Bobbink R K Hicks J Galloway T Spranger R AlkemadeM Ashmore M Bustamante S Cinderby E DavidsonF Dentener et al 2010 Global assessment of nitrogendeposition effects on terrestrial plant diversity Asynthesis Ecol Appl 20 (1)30ndash59 doi10189008-11401

Bosch C A Andersson M Krusa C Bandh I HovorkovaJ Klanova T Knowles R D Pancost R P Evershed andO Gustafsson 2015 Source apportionment of polycyclicaromatic hydrocarbons in central European soils withcompound-specific triple isotopes (_13C _14C and_2H) Environ Sci Technol 49 (13)7657ndash65doi101021acsest5b01190


Boutin C and D J Carpenter 2017 Assessment of wetlandupland vegetation communities and evaluation ofsoil-plant contamination by polycyclic aromatic hydrocar-bons and trace metals in regions near oil sands mining inAlberta Sci Total Environ 576829ndash39 doi101016jscitotenv201610062

Bradley P M C A Journey J P Berninger D T ButtonJ M Clark S R Corsi L A DeCicco K G HopkinsB J Huffman N Nakagaki et al 2019 Mixed-chemicalexposure and predicted effects potential in wadeablesoutheastern USA streams Sci Total Environ 65570ndash83doi101016jscitotenv201811186

Brady J M T A Crisp S Collier T KuwayamaS D Forestieri V Perraud Q Zhang M J KleemanC D Cappa and T H Bertram 2014 Real-time emissionfactor measurements of isocyanic acid from light dutygasoline vehicles Environ Sci Technol 48 (19)11405ndash12doi101021es504354p

Brander S M A D Biales and R E Connon 2017 Therole of epigenomics in aquatic toxicology Environ ToxicolChem 36 (10)2565ndash73 doi101002etc3930

Briggs G A 1985 Analytical parameterizations of diffusionThe convective boundary layer J Clim Appl Meteorol 24(11)1167ndash86 doi1011751520-0450(1985)024le1167APODTCge20CO2

Briggs G A 1969 Plume rise Springfield Virginia US AtomicEnergy Commission Division of Technical Information

Briggs G A 1975 Plume rise predictions In Lectures on airPollution and environmental impact analyses edD Haugen 59ndash111 Boston University of Chicago Press

Briggs G A 1984 Plume rise and buoyancy effects atmo-spheric sciences and power production Oak Ridge USATechnical Information Center US Dept of Energy

Brook J R and M D Moran 2000 International workshopon techniques and problems in modelling size-distributedaerosol formation and composition Atmos Environ341153ndash54

Campbell H E D R Kindopp S MacMillan P MartinE Neugebauer L Patterson and J Shatford 2013Mercury trends in colonial waterbird eggs downstream ofthe oil sands region of Alberta Canada Environ SciTechnol 47 (20)11785ndash92 doi101021es402542w

Carlton A G B J Turpin K E Altieri S SeitzingerA Reff H J Lim and B Ervens 2007 Atmospheric oxalicacid and SOA production from glyoxal Results of aqueousphotooxidation experiments Atmos Environ 41(35)7588ndash602 doi101016jatmosenv200705035

Carou S I Dennis J Aherne R Ouimet P A ArpS A Watmough I DeMerchant M Shaw B VetV Bouchet et al 2008 A national picture of acid deposi-tion critical loads for forest soils in Canada CanadianCouncil of Ministers of the Environment PN 1412 6

CCME Canada 1999 Canadian sediment quality guidelinesfor the protection of aquatic life Accessed January 9 2019httpceqg-rcqeccmecadownloaden312

CCME Canada 2003 Canadian sediment quality guidelinesfor the protection of aquatic life Accessed March 22 2019httpceqg-rcqeccmecadownloaden221

Chambers P A A Alexander Trusiak J Kirk C ManzanoD Muir C Cooke and R Hazewinkel 2018 Surface waterquality of lower athabasca river tributaries Oil Sands

Monitoring Program Technical Report Series No 13 34ISBN 978-1-4601-4027-7

Cheng Y S-M Li M Gordon and P Liu 2018 Sizedistribution and coating thickness of black carbon fromthe Canadian oil sands operations Atmos Chem Phys182653ndash67 doi105194acp-18-2653-2018

Cheng Y S-M Li J Liggio M Gordon A DarlingtonQ Zheng P Liu and M Wolde 2019 Top down deter-mination of black carbon emission from oil sands facilitiesin Alberta Canada using aircraft measurements EnvironScie Technol

Cho S K Sharma B Brassard and R Hazewinkel 2014Polycyclic aromatic hydrocarbon deposition in the snow-pack of the Athabasca oil sands region of Alberta CanadaWater Air Soil Pollut 225 (5)1910 doi101007s11270-014-1910-4

Clarkson T W 1993 Mercury Major issues in environmen-tal health Environ Health Perspect 10031ndash38doi101289ehp9310031

Clemente J S and P M Fedorak 2005 A review of theoccurrence analyses toxicity and biodegradation ofnaphthenic acids Chemosphere 60 (5)585ndash600doi101016jchemosphere200502065

CLRTAP 2017 Manual on methodologies and criteria formodelling and mapping critical loads and levels and airpollution effects risks and trends Accessed March 222019 httpicpmappingorg

Cooke C A J L Kirk D C G Muir J A WiklundX Wang A Gleason and M S Evans 2017 Spatial andtemporal patterns in trace element deposition to lakes inthe Athabasca oil sands region (Alberta Canada) EnvironRes Lett 12124001

Cruz-Martinez L K J Fernie C Soos T HarnerF Getachew and J Smits 2015 Detoxification endocrineand immune responses of tree swallow nestlings naturallyexposed to air contaminants from the Alberta oil sandsSci Total Environ 5028ndash15 doi101016jscitotenv201409008

Cruz-Martinez L and J Smits 2012 Potential to use ani-mals as monitors of ecosystem health in the Oil SandsRegion Environment doi107939R31C4G

Culp J M I G Droppo P Di Cenzo A Alexander-TrusiakD J Baird S Beltaos B Bickerton B Bonsal B RbP A Chambers et al 2018a Synthesis report for thewater component Canada-Alberta joint oil sands monitor-ing Key findings and recommendations Oil SandsMonitoring Program Technical Report Series No 11 46ISBN 978-1-4601-4025-3

Culp J M N E Glozier D J Baird F J Wrona R B BruaA L Ritcey D L Peters R Casey C B ChoungC J Curry et al 2018b Assessing ecosystem health inbenthic macroinvertebrate assemblages of the athabascariver main stem tributaries and peace-athabasca deltaOil Sands Monitoring Technical Report Series No 1782 ISBN 978-1-4601-4155-7

Davies M J E 2012 Air quality modelling in the AthabascaOil Sands Region In Alberta Oil Sands Energy industryand the environment ed K E Percy 267ndash309 OxfordUK Elsevier

De Araujo Barbosa C C P M Atkinson and J A Dearing2015 Remote sensing of ecosystem services A systematic

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review Ecol Indic 52430ndash43 doi101016jecolind201501007

Dickson W 1978 Some effects of acidification on Swedishlakes Verh Internat Verein Limnol 20851ndash56

Dolgova S D Crump E Porter K Williams andC E Hebert 2018a Stage of development affects dryweight mercury concentrations in bird eggs Laboratoryevidence and adjustment method Environ ToxicolChem 37 (4)1168ndash74 doi101002etc4066

Dolgova S B N Popp K Courtoreille R H M EspieB Maclean J R Straka G R Tetreault S Wilkie andC E Herbert 2018b Spatial trends in a biomagnifyingcontaminant Application of amino acid compoundndashSpecific stable nitrogen isotope analysis to the interpreta-tion of bird mercury levels Environ Toxicol Chem 37(5)1466ndash75 doi101002etc4113

Dowdeswell L P Dillon S Ghoshal A Miall J Rasmussenand J P Smol 2010 A foundation for the future Buildingan environmental monitoring system for the system for theOil Sands Gatineau Environment Canada

Droppo I G P Di Cenzo J Power C Jaskot P ChambersA C Alexander J Kirk and D Muir 2018b Temporaland spatial trends in riverine suspended sediment andassociated polycyclic aromatic compounds (PAC) withinthe Athabasca Oil Sands Region Sci Total Environ6261382ndash93 doi101016jscitotenv201801105

Droppo I G T Prowse B Bonsal Y Dibike S BeltaosB Krishnappan H-L Eum S Kashyap A Sakibaeiniaand A Gupta 2018a Regional Hydro-climatic andSediment Modelling for the Lower Athabasca River OilSands Region Oil Sands Monitoring Program TechnicalReport Series No 16 89 ISBN 978-1-4601-4030-7

Dziedek C W Haumlrdtle G von Oheimb and A Fichtner2016 Nitrogen addition enhances drought sensitivity ofyoung deciduous tree species Front Plant Sci 77doi103389fpls201601100

Earl S R H M Valett and J R Webster 2006 Nitrogensaturation in stream ecosystems Ecology 87 (12)3140ndash51

ECCC Environment and Climate Change Canada 2016Canadarsquos Black carbon inventory 2016 edition AccessedApril 5 2019 httpsecgccaair3F796B41-0B87-4C14-B76D-899D23CD0295Black20Carbon202016-EN-Finalpdf

Eldering A and G R Cass 1996 Source-oriented model forair pollutant effects on visibility J Geophys Res Atmos1011 (14)19343ndash70 doi10102995JD02928

Environment Canada 2011 Eds FJ Wrona P di Cenzoand K Schaefer Integrated monitoring plan for the oilsands ndash Expanded geographic extent for water qualityand quantity aquatic biodiversity and effects and acidsensitive lake component httppublicationsgccacollectionscollection_2011ecEn14-49-2011-engpdf

Environment Canada Canada 2016 Environment and cli-mate change Canada amp Alberta environment and parks)Joint oil sands monitoring program emissions inventorycompilation Accessed April 5 2019 httpsopenalbertacapublications9781460125658

Ervens B G Feingold G J Frost and S M Kreidenweis2004 A modeling of study of aqueous production ofdicarboxylic acids 1 Chemical pathways and speciatedorganic mass production J Geophys Res Atmos 109(15)15201ndash20 doi1010292003JD004387

Evans M S and A Talbot 2012 Investigations of mercuryconcentrations in walleye and other fish in the AthabascaRiver ecosystem with increasing oil sands developmentsEnviron Monit Assess 14 (7)1989ndash2003 doi101039c2em30132f

Fernie K J L Cruz-Martinez L Peters V PalaceAndand J Smits 2016 Inhaling benzene toluene nitrogendioxide and sulfur dioxide disrupts thyroid function incaptive American kestrels (Falco sparverius) EnvironSci Technol 50 (20)11311ndash18 doi101021acsest6b03026

Fernie K J S C Marteinson D Chen A Eng T HarnerJ Smits and C Soos 2018a Elevated exposure uptake andaccumulation of polycyclic aromatic hydrocarbons by nest-ling tree swallows (Tachycineta bicolor) through multipleexposure routes in active mining-related areas of theAthabasca oil sands region Sci Total Environ624250ndash61 doi101016jscitotenv201712123

Fernie K J S C Marteinson D Chen L Peters V Palaceand J Smits 2019 Changes in thyroid function of nestlingtree swallows (Tachycineta bicolor) in relation to polycyc-lic aromatic compounds and other stressors in theAthabasca Oil Sands Environ Res 169464ndash75doi101016jenvres201811031

Fernie K J S C Martienson C Soos D Chen L Cruz-Martinez and J Smits 2018 Reproductive and develop-mental changes in tree swallows (Tachycineta bicolor)are influenced by multiple stressors including polycyclicaromatic compounds in the Athabasca Oil SandsEnviron Pollut 238931ndash41 doi101016jenvpol201803074

Fioletov V E C Mclinden N Krotkov and C Li 2015Lifetimes and emissions of SO2 from point sources esti-mated from OMI Geophys Res Lett 426 doi1010022015GL063148

Fioletov V E C A McLinden S K KharolN A Krotkov C Li J Joiner M D Moran R VetA J H Visschedijk and H A C Denier van der Gon2017 Multi-source SO2 emission retrievals and consis-tency of satellite and surface measurements withreported emissions Atmos Chem Phys 1712597ndash616doi105194acp-17-12597-2017

Fox D G 1981 Judging air quality model performance -summary of the AMS Workshop on Dispersion ModelPerformance Woods Hole Mass 8-11 September 1980Bull Am Met Soc 62599ndash609 doi1011751520-0477-(1981)062lt0599JAQMPgt20CO2

Fox D G 1984 Uncertainty in air quality modelling ndashA summary of the AMS Workshop on Quantifying andCommunicating Model Uncertainty Woods Hole MassSeptember 1982 Bull Am Met Soc 6527ndash36 doi1011751520-0477(1984)065lt00273AUIAQMgt20CO3B2

Gagneacute F A Bruneau P Turcotte C Gagnon andE Lacaze 2017 An investigation of the immunotoxicityof oil sands processed water and leachates in troutleukocytes Ecotoxicol Environ Saf 14143ndash51doi101016ecoenv201703012

Gagneacute F M Douville C Andreacute T Debenest A TalbotJ Sherry L M Hewitt R A Frank M E McMasterJ Parrot et al 2012 Differential changes in gene expres-sion in rainbow trout hepatocytes exposed to extracts of oilsands process-affected water and the Athabasca River


Comp Biochem Physiol C 155 (4)551ndash59 doi101016jcbpc201201004

Galarneau E B P Hollebone Z Yang and J Schuster2014 Preliminary measurement-based estimates of PAHemissions from oil sands tailings ponds Atmos Environ97332ndash35 doi101016jatmosenv201408038

Gentes M L A McNabb C Waldner and J Smits 2007Increased thyroid hormone levels in tree swallows(Tachycineta bicolor) on reclaimed wetlands of theAthabasca oil sands Arch Environ Contam Toxicol 53(2)287ndash92 doi101007s00244-006-0070-y

Gerner N V M Koneacute M S Ross A Pereira A C UlrichJ W Martin and M Liess 2017 Stream invertebratecommunity structure at Canadian Oil Sands developmentis linked to concentration of bitumen-derivedcontaminants Sci Total Environ 5751005ndash13doi101016jscitotenv201609169

Glozier N E K Pippy L Levesque A Ritcey B ArmstrongO Tobin C A Cooke M Conly L Dirk C Epp et al 2018Surface water quality of the athabasca peace and slave riversand riverine waterbodies within the Peace-Athabasca DeltaOil Sands Monitoring Program Technical Report Series No14 64 ISBN 978-1-4601-4152-6

Godwin C M R M Barclay and J E G Smits 2019 Treeswallow (Tachycineta bicolor) nest success and nestlinggrowth near oilsands mining operations in NortheasternAlberta Can J Zool 1ndash41 doi101139cjz-2018-0247

Gong W A P Dastoor V S Bouchet S GongP A Makar M D Moran B Pabla S Menard L-P Crevier S Cousineau et al 2006 Cloud processing ofgases and aerosols in a regional air quality model(AURAMS) Atmos Res 82 (1ndash2)248ndash75 doi101016jatmosres200510012

Gordon M S-M Li R Staebler A Darlington K HaydenJ OlsquoBrien and M Wolde 2015 Determining air pollutantemission rates based onmass balance using airborne measure-ment data over the Alberta oil sands operations Atmos MeasTech 8 (3745ndash3765)2015 doi105194amt-8-3745-2015

Gordon M P Makar R Staebler J Zhang A AkingunolaW Gong and S-M Li 2018 A comparison of plume risealgorithms to stack plume measurements in the AthabascaOil Sands Atmos Chem Phys 1814695ndash714 doi105194acp-18-14695-2018

Government of Canada Canada 2019a National pollutantrelease inventory Accessed March 22 2019 httpswwwcanadacaenservicesenvironmentpollution-waste-managementnational-pollutant-release-inventoryhtml

Government of Canada Canada 2019b Canadarsquos air pollu-tant emissions inventory Accessed March 22 2019httpsopencanadacadataendatasetfa1c88a8-bf78-4fcb-9c1e-2a5534b92131

Graney J R M S Landis K J Puckett W B StudabakerE S Edgerton A H Legge and K E Percy 2017Differential accumulation of PAHs elements and Pb iso-topes by five lichen species from the Athabasca Oil SandsRegion in Alberta Canada Chemosphere 184700ndash10doi101016jchemosphere201706036

Hanha S R 1988 Air quality model evaluation anduncertainty J Air Poll Cont Assoc 38 (4)406ndash12doi10108008940630198810466390

Harman C E Farmen and K E Tollefsen 2010Monitoring North Sea oil production discharges using

passive sampling devices coupled with in vitro bioassaytechniques J Environ Monit 12 (9)1699ndash708doi101039C0EM00147C

Harms N J G D Fairhurst G R Bortolotti andJ E G Smits 2010 Variation in immune function bodycondition and feather corticosterone in nestling TreeSwallows (Tachycineta bicolor) on reclaimed wetlands inthe Athabasca oil sands Alberta Canada Environ Pollut158 (3)841ndash48 doi101016jenvpol200909025

Harner T C Rauert D Muir J Schuster Y-M HsuL Zhang G Marson J G Watson J Ahad S Choet al 2018 Air synthesis review on polycyclic aromaticcompounds in the Oil Sands Region Environ Rev 26(4)430ndash68 doi101139er-2018-0039

Hebert C 2019 The river runs through it The AthabascaRiver delivers mercury to aquatic birds breeding fardownstream PLoS ONE 14 (4)e0206192 doi101371jour-nalpone0206192

Hebert C W Nordstrom and L Shutt 2010 Colonialwaterbirds nesting on Egg Island Lake athabasca 2009Can Field-Naturalist 12449ndash53 doi1022621cfnv124i11029

Hebert C E D V C Weseloh S Macmillan D Campbelland W Nordstrom 2011 Metals and polycyclic aromatichydrocarbons in colonial waterbird eggs from LakeAthabasca and the Peace-Athabasca Delta CanadaEnviron Toxicol Chem 30 (5)1178ndash83 doi101002etc489

Hersikorn B D J J H Ciborowski and J Smits 2010 Theeffects of oil sands wetlands on wood frogs (Ranasylvatica) Toxicol Environ Chem 92 (8)1513ndash27doi10108002772240903471245

Himanen M P Prochazka K Haumlnninen and A Oikari 2012Phytotoxicity of low-weight carboxylic acids Chemosphere88 (4)426ndash31 doi101016jchemosphere201202058

Hsu Y M 2013 Trends in passively-measured ozone nitro-gen dioxide and sulfur dioxide concentrations in theAthabasca Oil Sands Region of Alberta Canada AerosolAir Qual Res 131448ndash63 doi104209aaqr2012080224

Hsu Y-M T Harner H Li and P Fellin 2015 PAHmeasurements in air in the Athabasca oil sands regionEnviron Sci Technol 49 (9)5584ndash92 doi101021acsest5b00178

Jacques D R and A H Legge 2012 Ecological analoguesfor biomonitoring industrial sulfur emissions in theAthabasca Oil Sands Region Alberta Canada Chapter10 In Alberta Oil Sands Energy industry and the environ-ment ed K E Percy 219ndash41 Oxford UK Elsevier

Jariyasopit N Y Zhang J W Martin and T Harner 2018Comparison of polycyclic aromatic compounds in air mea-sured by conventional passive air samplers and passive drydeposition samplers and contributions from petcoke andoil sands ore Atmos Chem Phys 189161ndash71 doi105194acp-18-9161-2018

Jautzy J J J M Ahad C Gobeil A Smirnoff B D Barstand M M Savard 2015 Isotopic evidence for oil sandspetroleum coke in the PeacendashAthabasca Delta Environ SciTechnol 49 (20)12062ndash70 doi101021acsest5b03232

Jeffries D S R G Semkin J J Gibson and I Wong 2010Recently surveyed lakes in northern Manitoba andSaskatchewan Canada Characteristics and critical loadsof acidity J Limnol 69 (Suppl 1)45ndash55 doi104081jlim-nol2010s145

704 JR BROOK ET AL

Joint Canada-Alberta Implementation Plan for Oil SandsMonitoring 2012 Accessed April 5 2019 httpwwwecg c c a S c i t e c h D 0AF 1 4 2 3 - 3 5 1C - 4CBC -A9 9 0 -4ADA543E7181COM1519_Final20OS20Plan_02pdf

JOSM Canada 2016 Joint oil sands monitoring programemissions inventory report Accessed January 9 2019httpswwwcanadacaenenvironment-climate-changeservicesscience-technologypublicationsjoint-oil-sands-monitoring-emissions-reporthtml

Jung K and S X Chang 2012 Four years of simulatedN and S depositions did not cause N saturation ina mixedwood boreal forest ecosystem in the Oil SandsRegion in Northern Alberta Canada For Ecol Manag28062ndash70 doi101016jforeco201206002

Kang E M J Root D W Toohey and W H Brune 2007Introducing the concept of Potential Aerosol Mass (PAM)Atmos Chem Phys 75727ndash44 doi105194acp-7-5727-2007

Kelly E N D W Schindler P V Hodson J W ShortR Radmanovich and C C Nielsen 2010 Oil Sands devel-opment contributes elements toxic at low concentrationsto the Athabasca River and its tributaries Proc Natl AcadSci USA 10716178ndash83 doi101073pnas1008754107

Kelly E N J W Short D W Schindler P V HodsonM Ma A K Kwan and B L Fortin 2009 Oil Sandsdevelopment contributes polycyclic aromatic compoundsto the Athabasca River and its tributaries Proc Natl AcadSci USA 106 (52)22346ndash51 doi101073pnas0912050106

Kerr J T and M Ostrovsky 2003 From space to speciesEcological applications for remote sensing Trends EcolEvol 18 (6)299ndash305 doi101016S0169-5347(03)00071-5

Keyte I J R M Harrison and G Lammel 2013 Chemicalreactivity and long-range transport potential of polycyclicaromatic hydrocarbons - a review Chem Soc Rev 42(24)9333ndash91 doi101039c3cs60147a

Khare P N Kumar K M Kumari and S S Srivastava1999 Atmospheric formic and acetic acids An overviewRev Geophys 37 (2)227ndash48 doi1010291998RG900005

Kirk J D Muir C Manzano C Cooke J WiklundA Gleason J Summers J Smol and J Kurek 2018Atmospheric deposition to the Athabasca Oil SandsRegion using snowpack measurements and dated lakesediment cores Oil Sands Monitoring Program TechnicalReport Series No 12 43 ISBN 978-1-4601-4026-0

Kirk J L D C G Muir A Gleason X Wang G LawsonR A Frank I Lehnherr and F Wrona 2014 Atmosphericdeposition of mercury and methylmercury to landscapesand waterbodies of the Athabasca Oil Sands RegionEnviron Sci Technol 48 (13)7374ndash83 doi101021es500986r

Knox A N Mykhaylova G J Evans C J Lee B Kamey andJ R Brook 2013 The expanding scope of air pollution mon-itoring can facilitate sustainable development Sci TotalEnviron 448189ndash96 doi101016jscitotenv201207096

Korosi J B C A Cooke D C Eickmeyer L E Kimpe andJ M Blais 2016 In-situ bitumen extraction associatedwith increased petrogenic polycyclic aromatic compoundsin lake sediments from the Cold Lake heavy oil fields(Alberta Canada) Environ Pollut 218915ndash22doi101016jenvpol201608032

Kurek J J L Kirk D C G Muir X Wang M S Evans andJ P Smol 2013 Legacy of a half century of Athabasca OilSands development recorded by lake ecosystems ProcNatl Acad Sci USA 110 (5)1761ndash66 doi101073pnas1217675110

Kwak J H S X Chang and M A Naeth 2018 Eleven yearsof simulated deposition of nitrogen but not sulfur changedspecies composition and diversity in the herb stratum ina boreal forest in western Canada For Ecol Manag4121ndash8 doi101016jforeco201801049

Lambe A T A T Ahern L R Williams J G SlowikJ P S Wong J P D Abbatt W H Brune N L NgJ P Wright D R Croasdale et al 2011 Characterizationof aerosol photooxidation flow reactors Heterogeneousoxidation secondary organic aerosol formation and cloudcondensation nuclei activity measurements Atmos MeasTech 4445ndash61 doi105194amt-4-445-2011

Lambe A T T B Onasch D R Croasdale J P WrightA T Martin J P Franklin P Massoli J H KrollM R Canagaratna W H Brune et al 2012 Transitionsfrom functionalization to fragmentation reactions oflaboratory Secondary Organic Aerosol (SOA) generatedfrom the OH oxidation of alkane precursors EnvironSci Technol 46 (10)5430ndash37 doi101021es300274t

Landers D H S M Simonich D Jaffe L GeiserD H Campbell A Schwindt C Schreck M KentW Hafner H E Taylor et al 2010 The WesternAirborne Contaminant Assessment Project (WACAP)An interdisciplinary evaluation of the impacts of airbornecontaminants in western US national parks Environ SciTechnol 44 (3)855ndash59 doi101021es901866e

Landis M S W B Studabaker J P Pancras J R GraneyK Puckett E M White and E S Edgerton 2019 Sourceapportionment of an epiphytic lichen biomonitor to eluci-date the sources and spatial distribution of polycyclic aro-matic hydrocarbons in the Athabasca Oil Sands RegionAlberta Canada Sci Total Environ 6541241ndash57doi101016jscitotenv201811131

Lawrence G B 2002 Persistent episodic acidification ofstreams linked to acid rain effects on soil Atmos Environ36 (10)1589ndash98 doi101016S1352-2310(02)00081-X

Lee K M Boufadel B Chen J Foght P HodsonS Swanson and A Venosa 2015 Expert panel report onthe behaviour and environmental impacts of crude oilreleased into aqueous environments Ottawa ON RoyalSociety of Canada ISBN 978-1-928140-02-3

Li S-H A Leithead S G Moussa J Liggio M D MoranD Wang K Hayden A Darlington M GordonR Staebler et al 2017 Differences between measuredand reported volatile organic compound emissions fromoil sands facilities in Alberta Canada Proc Natl Acad SciUSA 114 (19)E3756ndashE3765 doi101073pnas1617862114

Liess M K Foit S Knillmann R B Schaumlfer andH D Liess 2016 Predicting the synergy of multiple stresseffects Sci Rep 632965 doi101038srep32965

Liggio J S-M Li K Hayden Y M Taha C StroudA Darlington B D Drollette M Gordon P Lee P Liuet al 2016 Oil sands operations as a large source ofsecondary organic aerosols Nature 534 (7605)91ndash94doi101038nature17646


Liggio J S-M Li R Staebler K Hayden A DarlingtonR L Mittermeier J OrsquoBrien R McLaren M WoldeD Worthy et al 2019 Measurements indicate that CO2emissions from Canadian Oil Sands are higher than esti-mates made using internationally recommended methodNat Commun 10 (1)1863

Liggio J C Stroud J J B Wentzell J Zhang J SommersA Darlington P Liu S G Moussa A LeitheadK Hayden et al 2017 Quantifying the primary emissionsand photochemical formation of isocyanic acid (HNCO)downwind of oil sands operations Environ Sci Technol51 (24)14462ndash71 doi101021acsest7b04346

Lim Y B Y Tan M J Perri S P Seitzinger and B J Turpin2010 Aqueous chemistry and its role in secondary organicaerosol (SOA) formation Atmos Chem Phys 10(6)10521ndash39 doi105194acp-10-10521-2010

Lindenmayera B G E Likens C J Krebs and R J Hobbs2010 Improved probability of detection of ecological ldquosur-prisesrdquo Proc Natl Acad Sci USA 107 (51)21957ndash62doi101073pnas1015696107

Link M F B Friedman R Fulgham P Brophy A GalangS H Jathar P Veres J M Roberts and D K Farmer2016 Photochemical processing of diesel fuel emissions asa large secondary source of isocyanic acid (HNCO)Geophys Res Lett 43 (8)4033ndash41 doi1010022016GL068207

Lundstedt S P A White C L Lemieux K D LynesI B Lambert L Oberg P Haglund and M Tysklind2007 Sources fate and toxic hazards of oxygenated poly-cyclic aromatic hydrocarbons (PAHs) atPAH-contaminated sites Ambio 36 (6)475ndash85doi10157900447447(2007)36[475SFATHO]20CO2

Lynch J M 1977 Phytotoxicity of acetic acid produced inthe anaerobic decomposition of wheat straw J ApplBacteriol 42 (1)81ndash87

Majdi H and P Kangas 1997 Demography of fine roots inresponse to nutrient applications in a Norway spruce standin southwestern Sweden Ecoscience 4 (2)199ndash205doi10108011956860199711682396

Makar P A A Akingunola J Aherne A S Cole Y-A Aklilu J Zhang I Wong K Hayden S-M LiJ Kirk et al 2018 Estimates of exceedances of criticalloads for acidifying deposition in Alberta andSaskatchewan Atmos Chem Phys 189897ndash927doi105194acp-18-9897-2018

Makar P A W Gong C Hogrefe Y Zhang G CurciR Zabkar J Milbrandt U Im A Balzarini R Baroet al 2015b Feedbacks between air pollution and weatherpart 2 Effects on chemistry Atmos Environ 115499ndash526doi101016jatmosenv201410021

Makar P A W Gong J Milbrandt C Hogrefe Y ZhangG Curci R Zabkar U Im A Balzarini R Baro et al2015a Feedbacks between air pollution and weather part1 Effects on weather Atmos Environ 115442ndash69doi101016jatmosenv201412003

Manzano C A D Muir J Kirk C Teixeira M SiuX Wang J P Charland D Schindler and E Kelly2016 Temporal variation in the deposition of polycyclicaromatic compounds in snow in the Athabasca Oil Sandsarea of Alberta Environ Monit Assess 188 (9)542doi101007s10661-016-5500-3

Marentette J R K Sarty A M Cowie R A FrankL M Hewitt J L Parrot and C J Martyniuk 2017Molecular responses of Walleye (Sander vitreus) embryosto naphthenic acid fraction components extracted fromfresh oil sands process-affected water Aquat Toxicol18211ndash19 doi101016jaquatox201611003

McLinden 2019 personal communicationMcLinden C A V E Fioletov K F Boersma

N A A Krotkov C Sioris P Veefkind and K Yang2012 Air quality over the Canadian oil sands A firstassessment using satellite observations Geophys Res Lett39 (4)4804 doi1010292011GL050273

McMaster M J Parrott A Bartlett F Gagne M EvansG Tetreault H Keith and J Gee 2018 Aquatic ecosystemhealth assessment of the Athabasca River mainstream andtributaries using fish health and fish and invertebrate tox-icological testing Oil Sands Monitoring Program TechnicalReport Series No 18 76 ISBN 978-1-4601-4032-1

McMaster M E L M Hewitt and J L Parrott 2006A decade of research on the environmental impacts ofpulp and paper mill effluents in Canada Field studiesand mechanistic research J Toxicol Environ HealthB Crit Rev 9319ndash39 doi10108015287390500195752

Menezes-Blackburn D C Paredes H Zhang C D GilesT Darch M Stutter T S George C Shand D LumsdonP Cooper et al 2016 Organic Acids Regulation ofChemical-Microbial Phosphorus Transformations inSoils Environ Sci Technol 50 (21)11521ndash31doi101021acsest6b03017

Metcalfe C 2012 Persistent organic pollutants in the marinefood chain UNUedu February 23 Accessed March 222019 httpsunuedupublicationsarticlespersistent-organic-pollutants-in-the-marine-food-chainhtml

Moller P R S Wils D M Jensen M H G Andersen andM Roursgaard 2018 Telomere dynamics and cellularsenescence An emerging field in environmental and occu-pational toxicology Crit Rev Toxicol 48 (9)761ndash88doi1010801040844420181538201

Moran M D S Meacutenard D Talbot P Huang P A MakarW Gong H Landry S Gravel S Gong L-P Crevieret al 2010 Particulate-matter forecasting with GEM-MACH15 a new Canadian air-quality forecast model InAir pollution modelling and its application xx edD G Steyn and S T Rao 289ndash92 Dordrecht Springer

Muir D X Wang J Kirk A Gleason C Teixeira S BackusL Bradley C Mihele and G Poole 2012 Depositionalpatterns of inorganics and polyaromatic compounds inprecipitation in the Athabasca Oil Sands area of AlbertaCanada Proceedings of 33rd Annual SETAC MeetingLong Beach California November 11ndash15

Mullan-Boudreau G L J Davies K Devito D G FroeseT Noernberg R Pelletier and W Shotyk 2017Reconstructing Past Rates of Atmospheric DustDeposition in the Athabasca Bituminous Sands RegionUsing Peat Cores from Bogs Land Degrad Dev 288doi101002ldr2782

Mundy L J J C Bilodeau D M Schock P J ThomasJ M Blais and B D Pauli 2018 Using wood frog(Lithobates sylvaticus) tadpoles and semipermeable mem-brane devices to monitor polycyclic aromatic compoundsin boreal wetlands in the oil sands region of northern

706 JR BROOK ET AL

Alberta Canada Chemosphere 214148ndash57 doi101016jchemosphere201809034

Munkittrick K M C J Arens R B Lowell andG P Kaminski 2009 A review of potential methods ofdetermining critical effects size for designing environmen-tal monitoring programs Environ Toxicol Chem 28(7)1361ndash71 doi10189708-3761

Munkittrick K R and T J Arciszewski 2017 Using normalranges for interpreting results of monitoring and tiering toguide future work A case study of increasing polycyclicaromatic compounds in lake sediments from the ColdLake oil sands (Alberta Canada) described in Korosiet al (2016) Environ Pollut 231 (Pt 1)1215ndash22doi101016jenvpol201707070

Murray C A C J Whitfield and S A Watmough 2017Uncertainty-based terrestrial critical loads of nutrientnitrogen in northern Saskatchewan Canada BorealEnviron Res 22231ndash44

My WildAlberta 2017 Gull and tern egg consumptionadvisory Accessed April 5 2019 httpsmywildalbertacahuntingsafety-proceduresgull-and-tern-egg-consumption-advisoryaspx

Natural Resources Canada Canada 2017 Crude oil factsAccessed March 22 2019 httpswwwnrcangccaenergyfactscrude-oil20064

NEG-ECP 2001 Critical load of sulphur and nitrogen assess-ment and mapping protocol for upland forests HalifaxCanada New England Governors and eastern CanadianPremiers Environment Task Group Acid Rain ActionPlan

Nilsson J and P Grennfelt 1988 Critical loads for sulphurand nitrogen Report from a workshop held at SkoklosterSweden March 19ndash24

Norton S B S M Cormier and G W Suter 2015Ecological causal assessment Boca Raton Florida USACRC Press

Ouimet R 2005 Cartographie des Charges CritiquesdrsquoAciditeacute des Forecircts Deuxiegraveme ApproximationGouvernement du Queacutebec Ministegravere des Ressources nat-urelles et de la Faune Direction de la recherche forestiegravereRapport interne ndeg 487 48

Pace T G 2005 Methodology to estimate the transportablefraction (TF) of fugitive dust emissions for regional andurban scale air quality analyses Accessed March 15 2019httpswwwnrcgovdocsML1321ML13213A386pdf

Parajulee A and F Wania 2014 Evaluating officiallyreported polycyclic aromatic hydrocarbon emissions inthe Athabasca oil sands region with a multimedia fatemodel Proc Natl Acad Sci USA 111 (9)3344ndash49doi101037pnas1319780111

Parrott J L S M Backus A I Borgmann and M Swyripa1999 The use of semipermeable membrane devices toconcentrate chemicals in oil refinery effluent on theMackenzie River Arctic 52125ndash38 doi1014430arctic917

Parrott J L J R Marentette L M Hewitt M E McMasterP L Gillis W P Norwood J L Kirk K M PeruJ V Headley Z Wang et al 2018 Meltwater from snowcontaminated by oil sands emissions is toxic to larval fishbut not spring river water Sci Tot Environ 625264ndash74doi101016jscitotenv201712284

Paruelo J M M Texeira L Staiano M MastraacutengeloL Amdan and F Gallego 2016 An integrative index of

Ecosystem Services provision based on remotely senseddata Ecol Indic 71145ndash54 doi101016jecolind201606054

Percy K E 2012 Alberta oil sands Energy industry and theenvironment Oxford UK Elsevier

Percy K E D G Maynard and A H Legge 2012 Applyingthe forest health approach to monitoring boreal ecosys-tems in the Athabasca Oil Sands Region In Alberta OilSands Energy industry and the environment edK E Percy 193ndash218 Oxford UK Elsevier

Pilote M C Andreacute P Turcotte F Gagneacute and C Gagnon 2018Metal bioaccumulation and biomarkers of effects in cagedmussels exposed in the Athabasca oil sands area Sci TotalEnviron 610-611377ndash90 doi101016jscitotenv201708023

Pollet I and L I Bendell-Young 2000 Amphibians asindicators of wetland quality in wetlands formed from oilsands effluent Environ Toxicol Chem 19 (10)2589ndash97doi101002etc5620191027

Qiu X I Cheng F Yang E Horb L Zhang and T Harner2018 Emissions databases for polycyclic aromatic com-pounds in the Canadian Athabasca Oil Sands Region ndashDevelopment using current knowledge and evaluationwith passive sampling and air dispersion modelling dataAtmos Chem Phys 183457ndash67 doi105194acp-18-3457-2018

Radeva K R Nedkov and A Dancheva 2018 Applicationof remote sensing data for a wetland ecosystem servicesassessment in the area of Negovan village Paper presentedat SPIE Remote Sensing Conference Berlin GermanySeptember 21ndash24

Rappaport S M and M T Smith 2010 Environment anddisease risks Science 330 (6003)460ndash61 doi101126science1192603

Rauert C A Kananathalingham and T Harner 2017Characterization and modeling of polycyclic aromaticcompound uptake into spruce tree wood Environ SciTechnol 51 (9)5287ndash95 doi101021acsest7b01297

Roberts J M P R Veres A K Cochran C WarnekeI R Burling R J Yokelson B Lerner J B GilmanW C Kuster R Fall et al 2011 Isocyanic acid in theatmosphere and its possible link to smoke-related healtheffects Proc Natl Acad Sci USA 108 (22)8966ndash71doi101073pnas1103352108

Roberts J M P R Veres T C Vandenboer C WarnekeM Graus E J Williams B Lefer C A BrockR Bahreini F Oumlztuumlrk et al 2014 New insights intoatmospheric sources and sinks of isocyanic acid HNCOfrom recent urban and regional observations J GeophysRes 1191060ndash72 doi1010022013JD019931

The Royal Society of Canada 2010 Environmental andhealth impacts of Canadarsquos Oil Sands industry AccessedMarch 22 2019 httpsrscsrccasitesdefaultfilesRSC20Oil20Sands20Panel20Main20Report20Oct202012pdf

Russell M A Hakami P A Makar A Akingunola J ZhangM D Moran and Q Zheng 2018 An EVALUATION OFTHE EFfiCACY OF VERY HIGH RESOLUTION AIR-QUALITY MODELLING OVER THE Athabasca OilSands Region Alberta Canada Atmos Chem Phys 18 inreview doi105194acp-2018-967

Rydzynski K World Health Organization amp InternationalProgramme for Chemical Safety 1997 Acrylic acid


World Health Organization httpwwwwhointirishandle1066541955

Schuster J K T Harner K Su C Mihele and A Eng 2015First results from the oil sands passive air monitoringnetwork for polycyclic aromatic compounds Environ SciTechnol 49 (5)2991ndash98 doi101021es505684e

Schuster J K K Su A Eng T Harner A Wnorowski andJ-P Charland 2019 Temporal and spatial trends of poly-cyclic aromatic compounds in air across the Athabasca oilsands region reflect inputs from open pit mining andforest fires Environ Sci Technol 6 (3)178ndash83doi101021acsestlett9b00010

Schuumluumlrmann G R U Ebert I Tluczkiewicz S E Escherand R Kuumlhne 2016 Inhalation threshold of toxicologicalconcern (TTC) - Structural alerts discriminate high fromlow repeated-dose inhalation toxicity Environ Int88123ndash32 doi101016jenvint201512005

Shephard M W C A McLinden K E Cady-Pereira M LuoS G Moussa A Leithead J Liggio R M StaeblerA Akingunola P Makar et al 2015 Tropospheric EmissionSpectrometer (TES) satellite observations of ammonia metha-nol formic acid and carbon monoxide over the Canadian oilsands Validation and model evaluation Atmos Meas Tech85189ndash211 doi105194amt-8-5189-2015

Simmons D B D and J P Sherry 2016 Plasma proteomeprofiles of White Sucker (Catostomus commersonii) from theAthabasca River within the oil sands deposit Comp BiochemPhysiol D 19181ndash89 doi101016jcbd201603003

Simpson I J N J Blake B Barletta G S Diskin H E FuelbergK Gorham L G Huey S Meinardi F S Rowland S A Vayet al 2010 Characterization of trace gases measured overalberta oil sands mining operations 76 speciated C2-C10volatile organic compounds (VOCs) CO2 CH4 CO NONO2 NOy O3 and SO2 Atmos Chem Phys 1011931ndash54doi105194acp-10-11931-2010

Sioris C C McLinden J Dawson B Brisco L Fu andT Nunifu 2018 AEP-ECCC workshop on current andemerging methods for satellite monitoring of the oilsands Oil Sands Monitoring Program Technical ReportSeries No 4 19 ISBN 978-1-4601-4195-3

Smith V H G D Tilman and J C Nekola 1999Eutrophication Impacts of excess nutrient inputs on fresh-water marine and terrestrial ecosystems Environ Pollut100 (1ndash3)179ndash96 doi101016S0269-7491(99)00091-3

Song Y W H R Wang Y X Cao F Li C H Cui andL X Zhou 2016 Inhibition of low molecular organic acidson the activity of acidithiobacillus species and its effect onthe removal of heavy metals from contaminated soilHuanjing KexueEnviron Sci 37 (5)1960ndash67doi1013227jhjkx201605046

Staples C A S R Murphy J E McLaughlin H W LeungT C Cascieri and C H Farr 2000 Determination ofselected fate and aquatic toxicity characteristics of acrylicacid and a series of acrylic esters Chemosphere 40(1)29ndash38 doi101016S0045-6535(99)00228-3

Stavrakou T J F Muumlller J Peeters A Razavi L ClarisseC Clerbaux P F Coheur D Hurtmans M De MaziegravereC Vigouroux et al 2012 Satellite evidence for a largesource of formic acid from boreal and tropical forestsNat Geosci 5 (1)26ndash30 doi101038ngeo1354

Stroud C A P A Makar J Zhang M D MoranA Akingunola S-M Li A Leithead K Hayden and M Siu

2018 Improving air quality model predictions of organicspecies using measurement-derived organic gaseous and par-ticle emissions in a petrochemical-dominated region AtmosChem Phys 1813531ndash45 doi105194acp-18-13531-2018

Studabaker W B S Krupa R K M Jayanty and J HRaymer 2012 Measurement of polynuclear aromatichydrocarbons (PAHs) in epiphytic lichens for receptormodeling I the Athabasca oil sands region (AOSR) Apilot study In Alberta Oil Sands Energy industry andthe environment ed K E Percy 391ndash426 Oxford UKElsevier

Summers J C J Kurek J L Kirk D C Muir X WangJ A Wiklund C A Cooke M S Evans and S P Smol2016 Recent warming rather than industrial emissions ofbioavailable nutrients is the dominant driver of lake pri-mary production shifts across the Athabasca Oil SandsRegion PLoS ONE 11 (5)e0153987 doi101371journalpone0153987

Sverdrup L E T Kaumlllqvist A E Kelley C S Fuumlrst andS B Hagen 2001 Comparative toxicity of acrylic acid tomarine and freshwater microalgae and the significance forenvironmental effects assessments Chemosphere 45 (4ndash-5)653ndash58 doi101016S0045-6535(01)00044-3

Thuens S C Blodau F Wania and M Radke 2014Comparison of atmospheric travel distances of severalPAHs calculated by two fate and transport models (thetool and ELPOS) with experimental values derived froma peat bog transect Atmosphere 5 (2)324ndash41 doi103390atmos5020324

Tokarek T W C A Odame-Ankrah J A Huo R McLarenA K Y Lee M G Adam M D Willis J P D AbbattC Mihele A Darlington et al 2018 Principal componentanalysis of summertime ground site measurements in theAthabasca oil sands Sources of IVOCs Atmos Chem Phys1817819ndash1784 doi105194acp-18-17819-2018

United States Environmental Protection Agency USA 2014SPECIATE data browser Accessed March 22 2019httpscfpubepagovspeciate

United States Environmental Protection Agency USA2017 Toxicity forecasting Accessed March 25 2019httpswwwepagovchemical-researchtoxicity-forecasting

United States Environmental Protection Agency USA2019a National recommended water quality criteria ndashAquatic life criteria table Accessed January 9 2019httpswwwepagovwqcnational-recommended-water-quality-criteria-aquatic-life-criteria-table

United States Environmental Protection Agency USA2019b Toxic and priority pollutants under the cleanwater act Accessed April 5 2019 httpswwwepagovegtoxic-and-priority-pollutants-under-clean-water-act

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Venkatram A and P Karamchandani 1986 Source-receptor relationships a look at acid depositionmodeling Environ Sci Technol 20 (11)1084ndash91doi101021es00153a002

Villeneuve D L D Crump N Garcia-Reyero M HeckerT H Hutchinson C A LaLone B Landesmann

708 JR BROOK ET AL

T Lettieri S Munn M Nepelska et al 2014 Adverseoutcome pathway (AOP) development I Strategies andprinciples Toxicol Sci 142 (2)312ndash20 doi101093toxscikfu199

Wang X J C Chow S D Kohl K E Percy A H Leggeand J G Watson 2015 Characterization of PM25 andPM10 fugitive dust source profiles in the Athabasca OilSands Region J Air Waste Manag Assoc 65 (12)1421ndash33doi1010801096224720151100693

Weinhold B 2011 Albertarsquos Oil Sands Hard evidence miss-ing data new promises Environ Health Perspect 119 (3)A126ndashA131 doi101289ehp119-a126

Wentzell J J B J Liggio S M Li A Vlasenko R StaeblerG Lu M J Poitras T Chan and J R Brook 2013Measurements of gas phase acids in diesel exhaustA relevant source of HNCO Environ Sci Technol 47(14)7663ndash71 doi101021es401127j

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Whitfield C J and S A Watmough 2015 Acid depositionin the Athabasca Oil Sands Region A policy perspectiveEnviron Monit Assess 187 (12)771 doi101007s10661-015-4979-3

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Yang C Z Wang Z Yang B Hollebone C E BrownM Landriault and B Fieldhouse 2011 Chemical finger-prints of Alberta oil sands related petroleum productsEnviron Forensics 12173ndash88 doi101080152759222011574312

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Zhang J M D Moran Q Zheng P A MakarP Baratzadeh G Marson P Liu and S-M Li 2018Emissions preparation and analysis for multiscale air qual-ity modelling over the athabasca oil sands region ofAlberta Canada Atmos Chem Phys 1810459ndash81doi105194acp-2017-1215

Zhang Y W Shotyk C Zaccone T Noernberg R PelletierB Bicalho D G Froese L Davies and J W Martin 2016Airborne petcoke dust is a major source of polycyclic aromatichydrocarbons in the Athabasca Oil Sands Region Environ SciTechnol 50 (4)1711ndash20 doi101021acsest5b05092

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Introduction

The Canadian Oil Sands (OS) are predominantlylocated in the northern half ofAlberta with a small portion in cen-tral-western Saskatchewan In sizethe OS is 142000 km2 and is esti-mated to include approximately 17trillion barrels of oil in the form ofbitumen although the recoverableamount of oil is only about 10 ofthat amount or 1634 billion barrels(Natural Resources Canada Canada

2017) This still makes the OS the third largest known

reserve of oil on earth Once recovered bitumen whichis highly viscous and enriched in sulfur carbon nitro-gen and metals and deficient in hydrogen comparedwith conventional and heavy crude oil requiresupgrading The bitumen extraction separation andupgrading processes that ultimately produce syntheticcrude oil consume energy and resources and producewaste which can pose environmental risks

Two major rivers the Peace River and the AthabascaRiver (AR) both originating from headwaters in the RockyMountains flow through the OS region The glacial-fedAthabasca River is the longest in Alberta its watershedencompasses nearly one quarter of the province From its

Figure 1 Northern Alberta showing the Athabasca River the Peace River the Peace-Athabasca Delta (PAD) and the oil sandsdeposits

JR Brook

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JOSM objectives








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-

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UTM easting (m)

ab

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UTM

north

ing

(m)







2012

0

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ited

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688 JR BROOK ET AL











690 JR BROOK ET AL

















692 JR BROOK ET AL















As Hg PACs



Hg PACs



Trace metals PACs


PACs





Amphibians





694 JR BROOK ET AL





Migratory birds








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Colonial waterbirds






Sentinel species




Concluding remarks




Tree swallow rank




698 JR BROOK ET AL










Glossary of terms


























Acknowledgment


Funding


700 JR BROOK ET AL

About the author


References























































702 JR BROOK ET AL























































704 JR BROOK ET AL


















































706 JR BROOK ET AL

























































708 JR BROOK ET AL






































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668 JR BROOK ET AL




















670 JR BROOK ET AL


















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-

500

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Tonnes



674 JR BROOK ET AL
















S

A

C

B

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678 JR BROOK ET AL














680 JR BROOK ET AL














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UTM easting (m)

ab

c

UTM

north

ing

(m)







2012

0

10

20

30

2014

0

10

20

30

0 5 10 15 20 25

2013

0

10

20

30

0 5 10 15 20 25

2011

0

5

10

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PAC

dep

ositi

on (m

gm

)2


684 JR BROOK ET AL








1000

800

600

400

200

00 10 20 30 40 50 60


Distance (km)

Tota

l Mas

s D

epos

ited

(kg)









686 JR BROOK ET AL

















688 JR BROOK ET AL











690 JR BROOK ET AL

















692 JR BROOK ET AL















As Hg PACs



Hg PACs



Trace metals PACs


PACs





Amphibians





694 JR BROOK ET AL





Migratory birds








696 JR BROOK ET AL


Colonial waterbirds






Sentinel species




Concluding remarks




Tree swallow rank




698 JR BROOK ET AL










Glossary of terms


























Acknowledgment


Funding


700 JR BROOK ET AL

About the author


References























































702 JR BROOK ET AL























































704 JR BROOK ET AL


















































706 JR BROOK ET AL

























































708 JR BROOK ET AL






































666 JR BROOK ET AL
















668 JR BROOK ET AL




















670 JR BROOK ET AL


















672 JR BROOK ET AL















-

500

1000

1500

2000

2500

3000

3500

4000

Tonnes



674 JR BROOK ET AL
















S

A

C

B

D


676 JR BROOK ET AL













678 JR BROOK ET AL














680 JR BROOK ET AL














682 JR BROOK ET AL





UTM easting (m)

ab

c

UTM

north

ing

(m)







2012

0

10

20

30

2014

0

10

20

30

0 5 10 15 20 25

2013

0

10

20

30

0 5 10 15 20 25

2011

0

5

10

15


PAC

dep

ositi

on (m

gm

)2


684 JR BROOK ET AL








1000

800

600

400

200

00 10 20 30 40 50 60


Distance (km)

Tota

l Mas

s D

epos

ited

(kg)









686 JR BROOK ET AL

















688 JR BROOK ET AL











690 JR BROOK ET AL

















692 JR BROOK ET AL















As Hg PACs



Hg PACs



Trace metals PACs


PACs





Amphibians





694 JR BROOK ET AL





Migratory birds








696 JR BROOK ET AL


Colonial waterbirds






Sentinel species




Concluding remarks




Tree swallow rank




698 JR BROOK ET AL










Glossary of terms


























Acknowledgment


Funding


700 JR BROOK ET AL

About the author


References























































702 JR BROOK ET AL























































704 JR BROOK ET AL


















































706 JR BROOK ET AL

























































708 JR BROOK ET AL






































668 JR BROOK ET AL




















670 JR BROOK ET AL


















672 JR BROOK ET AL















-

500

1000

1500

2000

2500

3000

3500

4000

Tonnes



674 JR BROOK ET AL
















S

A

C

B

D


676 JR BROOK ET AL













678 JR BROOK ET AL














680 JR BROOK ET AL














682 JR BROOK ET AL





UTM easting (m)

ab

c

UTM

north

ing

(m)







2012

0

10

20

30

2014

0

10

20

30

0 5 10 15 20 25

2013

0

10

20

30

0 5 10 15 20 25

2011

0

5

10

15


PAC

dep

ositi

on (m

gm

)2


684 JR BROOK ET AL








1000

800

600

400

200

00 10 20 30 40 50 60


Distance (km)

Tota

l Mas

s D

epos

ited

(kg)









686 JR BROOK ET AL

















688 JR BROOK ET AL











690 JR BROOK ET AL

















692 JR BROOK ET AL















As Hg PACs



Hg PACs



Trace metals PACs


PACs





Amphibians





694 JR BROOK ET AL





Migratory birds








696 JR BROOK ET AL


Colonial waterbirds






Sentinel species




Concluding remarks




Tree swallow rank




698 JR BROOK ET AL










Glossary of terms


























Acknowledgment


Funding


700 JR BROOK ET AL

About the author


References























































702 JR BROOK ET AL























































704 JR BROOK ET AL


















































706 JR BROOK ET AL

























































708 JR BROOK ET AL










































670 JR BROOK ET AL


















672 JR BROOK ET AL















-

500

1000

1500

2000

2500

3000

3500

4000

Tonnes



674 JR BROOK ET AL
















S

A

C

B

D


676 JR BROOK ET AL













678 JR BROOK ET AL














680 JR BROOK ET AL














682 JR BROOK ET AL





UTM easting (m)

ab

c

UTM

north

ing

(m)







2012

0

10

20

30

2014

0

10

20

30

0 5 10 15 20 25

2013

0

10

20

30

0 5 10 15 20 25

2011

0

5

10

15


PAC

dep

ositi

on (m

gm

)2


684 JR BROOK ET AL








1000

800

600

400

200

00 10 20 30 40 50 60


Distance (km)

Tota

l Mas

s D

epos

ited

(kg)









686 JR BROOK ET AL

















688 JR BROOK ET AL











690 JR BROOK ET AL

















692 JR BROOK ET AL















As Hg PACs



Hg PACs



Trace metals PACs


PACs





Amphibians





694 JR BROOK ET AL





Migratory birds








696 JR BROOK ET AL


Colonial waterbirds






Sentinel species




Concluding remarks




Tree swallow rank




698 JR BROOK ET AL










Glossary of terms


























Acknowledgment


Funding


700 JR BROOK ET AL

About the author


References























































702 JR BROOK ET AL























































704 JR BROOK ET AL


















































706 JR BROOK ET AL

























































708 JR BROOK ET AL























Advances in science and applications of air pollution ...

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