ASSESSING PAST USE OF ASSESSING PAST USE OF TANNERY WASTE SLUDGE TANNERY WASTE SLUDGE

AS FARM FIELD FERTILIZER AS FARM FIELD FERTILIZER IN NORTHWEST MISSOURIIN NORTHWEST MISSOURI

July 20, 2010ITRC MeetingSeattle, WA

BACKGROUNDBACKGROUND

Sludge applied 1983-2009Sludge applied 1983-2009 56,000 acres affected56,000 acres affected 100+ locations across 4 counties100+ locations across 4 counties Concern about risk posed by hexavalent Concern about risk posed by hexavalent

chromium (Cr VI) in sludge.chromium (Cr VI) in sludge.

CSM JACKPOT: TANNERY KEPT LOTS OF DATA ON CSM JACKPOT: TANNERY KEPT LOTS OF DATA ON SLUDGE APPLICATIONSLUDGE APPLICATION

STUDY AREASTUDY AREA

HERE COMES THE SLUDGE

CONCEPTUAL SITE MODELCONCEPTUAL SITE MODEL

Applications uniform except near buffers, Applications uniform except near buffers, corners, access gates.corners, access gates.

Appl. rates frequencies & mechanism Appl. rates frequencies & mechanism knownknown

Runoff concentrates sludge in low areasRunoff concentrates sludge in low areas High fOC, low pH, & high redox all act to High fOC, low pH, & high redox all act to

reduce Cr VI to Cr III.reduce Cr VI to Cr III.

EXPOSURE PATHWAYSEXPOSURE PATHWAYS

Direct exposure (Direct exposure (inhinh/ingest) to soil by /ingest) to soil by farmer & nearby residents.farmer & nearby residents.

Interested in particle fraction <0.25mmInterested in particle fraction <0.25mm Leaching to groundwater & GW ingestionLeaching to groundwater & GW ingestion Surface water, ecological risk (not Surface water, ecological risk (not

assessed)assessed)

CrVI SCREENING LEVELSCrVI SCREENING LEVELS

Represent mean [CrVI] across exposure Represent mean [CrVI] across exposure area that would pose risk to resident child area that would pose risk to resident child living adjacent.living adjacent.

Farm field = 86 ppm. Based on 80-acre Farm field = 86 ppm. Based on 80-acre field. field.

SAMPLING STRATEGYSAMPLING STRATEGY

56,000 acres affected. Can’t sample it all: 56,000 acres affected. Can’t sample it all: Select 15-20 farm field DUs for sampling.Select 15-20 farm field DUs for sampling.

DUsDUs= = Exposure Area = 80 acresExposure Area = 80 acres SU = 1 acre squares w/in DUSU = 1 acre squares w/in DU Fields chosen based on CSM (judgemental) – Fields chosen based on CSM (judgemental) –

appl. Rate, frequency, time, appl. Rate, frequency, time, geographygeography, field , field type (row crop vs. pasture). type (row crop vs. pasture).

SUs also chosen based on CSM – attempt to SUs also chosen based on CSM – attempt to select SUs with maximum within-SU and select SUs with maximum within-SU and between SU heterogeneity (most conservative). between SU heterogeneity (most conservative).

FARM FIELD DU WITH OVERLAY FARM FIELD DU WITH OVERLAY GRID OF SUsGRID OF SUs

DECISION RULEDECISION RULE

If 95% UCL on [CrVI] (measured using If 95% UCL on [CrVI] (measured using SUIS) in SUIS) in anyany farm field DU exceeds the farm field DU exceeds the screening level, investigation will be screening level, investigation will be expanded; otherwise conclude that expanded; otherwise conclude that sludge applications do not pose risk - sludge applications do not pose risk - NFA. NFA.

PILOT STUDYPILOT STUDY

30 Discrete collected in three FF plots30 Discrete collected in three FF plots XRF for total Cr few $/sample. CrVI analysis XRF for total Cr few $/sample. CrVI analysis

$160/sample.$160/sample. Analyzed for total and hex CrAnalyzed for total and hex Cr Variograms showed total and hex Cr vary Variograms showed total and hex Cr vary

across fields in similar way & var of Cr >CrVI. across fields in similar way & var of Cr >CrVI. Used worst case observed ratio of CrVI:Cr Used worst case observed ratio of CrVI:Cr

(~20%) to convert CrVI SL to Cr SL.(~20%) to convert CrVI SL to Cr SL.

Farm Field DesignFarm Field Design= Farm Field DU area= 1-acre SU area= SU increment sample location

SU 80

SU 4

SU 72

SU 45

SU 28

Start with 3 SUs and 10 discretes (increments)

Analyze each increment 4x by XRF

-Provides measure of within bag heterogeneity

-Use mean, SD, AL in VSP to determine # incr. needed in SU

-If >10 increments needed, collect them.

REPEAT FOR OTHER 2 SUs

VISUAL SAMPLE PLAN ANALYSISVISUAL SAMPLE PLAN ANALYSIS

Our decision error tolerance

From SU XRF data

CrVI AL converted to total Cr AL

(using pilot data)

Number of samples needed

within the SU

From discrete sample XRF

data

XRF ANALYSISXRF ANALYSIS

Farm Field DesignFarm Field Design= Farm Field DU area= 1-acre SU area= SU increment sample location

SU 80

SU 4

SU 72

SU 45

SU 28

DUIS

Increments combined

in oe bag

Increments combined

in one bag

Increments combined

in one bag

-Split SUIS and combine aliquots to form DUIS (2nd Tier). XRF that.-Send SU & DU IS samples for CrVI analysis

Combine SU increments together to form SUIS & XRF 4x

-Use mean, SD, AL of the 3 SUIS in VSP to determine number of SUs needed for the DU.

-If >3 SUs needed, collect them

INCREMENTS/SU & SUs/DUINCREMENTS/SU & SUs/DU

None of the 60 SUs required more than None of the 60 SUs required more than 10 increments based on VSP analysis 10 increments based on VSP analysis (none even >4).(none even >4).

None of the 19 DUs required more than 3 None of the 19 DUs required more than 3 SUs to be sampled.SUs to be sampled.

SDs were low, but key factor was the SDs were low, but key factor was the distance between our estimates of mean distance between our estimates of mean [CrVI] & the screening level.[CrVI] & the screening level.

Sample ProcessingSample Processing

Air dry discretes, disaggregate, sieve 60 meshAir dry discretes, disaggregate, sieve 60 mesh Create SUIS from discretesCreate SUIS from discretes Split SUIS into 3; one to form DUIS, one to lab, Split SUIS into 3; one to form DUIS, one to lab,

one for archive. Split technique was simple mix one for archive. Split technique was simple mix & pour from bag.& pour from bag.

All SUIS and half the DUIS submitted for CrVI All SUIS and half the DUIS submitted for CrVI analysisanalysis

Lab used 2D Japanese slabcake for Lab used 2D Japanese slabcake for subsamplingsubsampling

SU IS ReplicatesSU IS Replicates

SU Repl1 Repl2 Repl3 RSD

205-88 1.02 0.652 0.779 22.9

214-37 1.13 0.715 0.674 30.0

221-162 4.07 3.45 4.57 13.9

*SUIS made up of 10 increments collected in systematic (serpentine) pattern

Hexavalent Cr, mg/kg

SU Repl1 Repl2 Repl3 RSD

205-88 105 149 159 20.9

214-37 264 289 267 5.0

221-162 97 115 105 8.5

Total Cr, mg/kg

Analytical SubsamplingAnalytical Subsampling

DU-SU CrVICr VI Lab

dup RPD

201 0.06 0.063 4.9

209-96 1.05 0.942 10.8

205-88 1.110 0.938 16.8

212-53 0.605 0.750 21.4

213-44 0.833 0.788 5.6

214-25 1.610 1.620 0.6

215-55 0.069 0.080 14.8

217-103 0.793 0.775 2.3

221-162 4.38 3.76 15.2

2D Japanese Slabcake Method Used

Comparison of IS TiersComparison of IS Tiers

ID Ave of SUIS DU-IS Result %RPD

DU 202 135 131 3

DU 203 68 67 1

DU 204 133 126 5

DU 205 146 141 3

DU 209 52 48 7

DU 210 61 61 0

DU 212 227 251 10

DU 213 244 254 4

DU 214 285 225 23

DU 215 263 282 7

DU 216 109 116 7

DU 217 268 264 2

DU 218 197 204 3

DU 219 60 63 5

DU 221 104 96 8

DU 222 118 108 9

DU 223 78 80 3

DU 224 44 39 11

DU 225 103 97 6

ID Ave of SUISDU-IS

Result %RPD

DU 212 0.75 0.49 42

DU 213 1.04 0.703 38

DU 214 0.77 0.35 75

DU 215 0.62 1.73 95

DU 217 1.05 1.16 10

DU 221 2.59 1.64 45

DU 225 1.38 1.48 7

Total Cr, mg/kg (XRF) Hexavalent Cr, mg/kg

Micro scale heterogeneity of total Cr in matrix controlled well by sample splitting technique. Less well for CrVI.

Analysis of Relative UncertaintiesAnalysis of Relative UncertaintiesData Variability Measured by Width of 1 Side of Uncertainty Data Variability Measured by Width of 1 Side of Uncertainty Interval Normalized to the Mean (i.e., interval width/mean)Interval Normalized to the Mean (i.e., interval width/mean)

General trends:-Higher variability in CrVI vs. total Cr-Variability incr. with scale from within sample to within SU to between SU. But,-For some DUs, micro-scale variability within sample dominates.

*only portion of DU data shown

DATA VALIDATES CSM?DATA VALIDATES CSM?

Selection of DUs based on application data Selection of DUs based on application data captured worst case fields. – Yes, pos. captured worst case fields. – Yes, pos. correlation of application rates/frequency to Cr correlation of application rates/frequency to Cr levels.levels.

Our selection of SUs maximized within and Our selection of SUs maximized within and between SU variability – Yes, SUs chosen as between SU variability – Yes, SUs chosen as high variability in field had highest SD, SUs high variability in field had highest SD, SUs chosen as low variability had lower SD.chosen as low variability had lower SD.

Soil redox conditions control ratio of Cr6:Cr in Soil redox conditions control ratio of Cr6:Cr in fields. – Yes, fOC highly (negatively) correlated fields. – Yes, fOC highly (negatively) correlated with CrVIwith CrVI

DECISIONDECISION

Accounting for all sources of variability, Accounting for all sources of variability, and making most conservative and making most conservative assumptions, no 95% UCL was within an assumptions, no 95% UCL was within an order of magnitude of the screening level.order of magnitude of the screening level.

No further investigation plannedNo further investigation planned