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ASSESSING PAST USE OF TANNERY WASTE SLUDGE AS FARM FIELD FERTILIZER IN NORTHWEST MISSOURI

This study evaluated the past use of tannery waste sludge as farm field fertilizer in Northwest Missouri from 1983 to 2009, addressing concerns over hexavalent chromium contamination. Analyzing data from over 100 locations across four counties, the study focused on exposure pathways, sampling strategies, and risk assessment levels. Through a pilot study involving XRF and CrVI analysis, the project developed a comprehensive field sampling plan to determine the potential risks posed by sludge applications. The analysis of variance illustrated varying levels of total and hexavalent chromium across fields, emphasizing the importance of soil heterogeneity in the study. Using a systematic approach, the study aimed to validate the conceptual site model by reviewing data from sampling efforts, soil conditions, and chromium ratios within the fields. Overall, the project utilized innovative techniques to assess the safety and efficiency of using tannery waste sludge as a farm field fertilizer.

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ASSESSING PAST USE OF TANNERY WASTE SLUDGE AS FARM FIELD FERTILIZER IN NORTHWEST MISSOURI

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  1. ASSESSING PAST USE OF TANNERY WASTE SLUDGE AS FARM FIELD FERTILIZER IN NORTHWEST MISSOURI July 20, 2010 ITRC Meeting Seattle, WA

  2. BACKGROUND • Sludge applied 1983-2009 • 56,000 acres affected • 100+ locations across 4 counties • Concern about risk posed by hexavalent chromium (Cr VI) in sludge.

  3. CSM JACKPOT: TANNERY KEPT LOTS OF DATA ON SLUDGE APPLICATION

  4. STUDY AREA

  5. HERE COMES THE SLUDGE

  6. CONCEPTUAL SITE MODEL • Applications uniform except near buffers, corners, access gates. • Appl. rates frequencies & mechanism known • Runoff concentrates sludge in low areas • High fOC, low pH, & high redox all act to reduce Cr VI to Cr III.

  7. EXPOSURE PATHWAYS • Direct exposure (inh/ingest) to soil by farmer & nearby residents. • Interested in particle fraction <0.25mm • Leaching to groundwater & GW ingestion • Surface water, ecological risk (not assessed)

  8. CrVI SCREENING LEVELS • Represent mean [CrVI] across exposure area that would pose risk to resident child living adjacent. • Farm field = 86 ppm. Based on 80-acre field.

  9. SAMPLING STRATEGY • 56,000 acres affected. Can’t sample it all: Select 15-20 farm field DUs for sampling. • DUs= Exposure Area = 80 acres • SU = 1 acre squares w/in DU • Fields chosen based on CSM (judgemental) – appl. Rate, frequency, time, geography, field type (row crop vs. pasture). • SUs also chosen based on CSM – attempt to select SUs with maximum within-SU and between SU heterogeneity (most conservative).

  10. FARM FIELD DU WITH OVERLAY GRID OF SUs

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

  12. PILOT STUDY • 30 Discrete collected in three FF plots • XRF for total Cr few $/sample. CrVI analysis $160/sample. • Analyzed for total and hex Cr • Variograms showed total and hex Cr vary across fields in similar way & var of Cr >CrVI. • Used worst case observed ratio of CrVI:Cr (~20%) to convert CrVI SL to Cr SL.

  13. = Farm Field DU area = 1-acre SU area = SU increment sample location Farm Field Design 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 SU 72 SU 80 SU 45 SU 28 SU 4

  14. VISUAL SAMPLE PLAN ANALYSIS Our decision error tolerance CrVI AL converted to total Cr AL (using pilot data) From discrete sample XRF data From SU XRF data Number of samples needed within the SU

  15. XRF ANALYSIS

  16. = Farm Field DU area = 1-acre SU area = SU increment sample location Farm Field Design • 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 SU 72 SU 80 Increments combined in one bag Increments combined in oe bag SU 45 DUIS -Split SUIS and combine aliquots to form DUIS (2nd Tier). XRF that. -Send SU & DU IS samples for CrVI analysis SU 28 SU 4 Increments combined in one bag

  17. INCREMENTS/SU & SUs/DU • None of the 60 SUs required more than 10 increments based on VSP analysis (none even >4). • None of the 19 DUs required more than 3 SUs to be sampled. • SDs were low, but key factor was the distance between our estimates of mean [CrVI] & the screening level.

  18. Sample Processing • Air dry discretes, disaggregate, sieve 60 mesh • Create SUIS from discretes • Split SUIS into 3; one to form DUIS, one to lab, one for archive. Split technique was simple mix & pour from bag. • All SUIS and half the DUIS submitted for CrVI analysis • Lab used 2D Japanese slabcake for subsampling

  19. SU IS Replicates Hexavalent Cr, mg/kg Total Cr, mg/kg *SUIS made up of 10 increments collected in systematic (serpentine) pattern

  20. Analytical Subsampling 2D Japanese Slabcake Method Used

  21. Comparison of IS Tiers 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.

  22. Analysis of Relative Uncertainties Data Variability Measured by Width of 1 Side of Uncertainty 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

  23. DATA VALIDATES CSM? • Selection of DUs based on application data captured worst case fields. – Yes, pos. correlation of application rates/frequency to Cr levels. • Our selection of SUs maximized within and between SU variability – Yes, SUs chosen as high variability in field had highest SD, SUs chosen as low variability had lower SD. • Soil redox conditions control ratio of Cr6:Cr in fields. – Yes, fOC highly (negatively) correlated with CrVI

  24. DECISION • Accounting for all sources of variability, and making most conservative assumptions, no 95% UCL was within an order of magnitude of the screening level. • No further investigation planned

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