Drinking Water Case Studies

Transcription

1 Drinking Water Case Studies CLA Regulatory Conference April 6, 2017 Pat Havens, PhD Principal Research Scientist Dow AgroSciences LLC

2 Introduction Registrants have worked for many years to understand potential impacts to drinking water from product use For both surface water and groundwater Higher-tier studies in lab and field Development of monitoring data sets and advances in their interpretation Advances in model parameterization, scenarios, and algorithms Using all of these to inform and refine modeled concentrations needed for risk assessments 2

3 3 SURFACE WATER

4 Chlorpyrifos - a national scale active ingredient Wide and varied use for over 50 years Data-rich Use Environmental behavior Effects Targeted and general monitoring data Recent revisions in human health endpoint have led to increased concerns from drinking water exposure An ideal surrogate to illustrate concepts for refinement of drinking water exposure First spatially-explicit use intensity

5 Developing and applying PCA at HUC-12 level Immediately dealing with the geospatial distribution Assessment at HUC-12 level (82,857) EPA assessments had identified PCA as an important factor Defined PCAs for 27 labeled crops/groups and aggregated to all labeled crops by HUC-12 5 yrs of CDL (adjusted by NLCD and NASS) & picked worst-case year for all labelled crops In line with corn-soy-cottoncitrus major uses

6 Next potential direct relevance to surface DW Drinking water intake overlay desired, but DWI layer not public Surrogate SDWIS Counties with sources identified as SW and GU (gw under influence of surface water) Extract HUC-12s with EDWC > DWLOC and intersecting SDWIS counties Significant refinement of the extent of areas with potential concern

7 Next steps for modeling Simulations with local-scale information can offer direction on where and when actions may be needed to mitigate exposure PCAs are highly impactful Develop methods to use these at different levels of spatial scale Develop methods to handle small high-intensity use catchments What is the best way to estimate use at a local scale (PCT)? Probabilistic or trends forecasting? Next steps for the modeling tools Local soils/weather Variable use timings, etc. More realistic DW supply water bodies Actual watershed modeling (e.g., SWAT) Revisit direct incorporation of probabilistic modeling results (i.e., daily time series) into human health assessments

8 Monitoring and comparisons to modeling Targeted and general monitoring available Use intensity clearly important Other measures of use (PCT, timing) are also potentially high impact Directed drinking water monitoring has less uncertainty, but Sampling statistics analysis indicates that even nondirected monitoring, in agriculturally-relevant areas, can give useful insight on exposures Bias is less important for long-term averages Further exploration of sampling statistics approaches could be fruitful

9 9 GROUNDWATER

10 Fomesafen changes in GW EEC values EPA used PGW-measured 1 ppb to assess chronic drinking water exposure from groundwater SCI-GROW EDWCs: 11.2 ppb EFED recommended using the ground water monitoring concentration of 1 μg/l as the benchmark concentration for fomesafen in ground water source drinking water because it represents actual use conditions of fomesafen on soybeans on a vulnerable soil. Risk cup not exceeded 2013 EPA used new groundwater model PRZM-GW to revise gw EDWC for fomesafen. Max use rate lb ai/a PRZM-GW EDWCs: acute 51.8 ppb, and chronic 32.3 ppb (>SW EDWCs) Max EDWCs from Florida Citrus - FL Central Ridge Standard scenario Risk cup not exceeded 2016 EPA further revised PRZM-GW EDWCs based on pine seedlings max annual use rate of lb ai/a (special use label for southern states only). PRZM-GW EDWCs: 106 ppb acute, and 88 ppb chronic (>SW EDWCs) Max EDWCs from Wisconsin Corn - WI Central sands Standard scenario EDWC 88 ppb exceeded chronic risk cup

11 Refinement Options Considered Label-relevant scenarios Fomesafen has a geography-dependent use label Gave some additional realism Subsurface fate: degradation under anaerobic soil conditions is rapid (half-life < 20 days) DFOP kinetics to take into account biphasic kinetics behavior PGW (prospective groundwater) and TFD (terrestrial field dissipation) data to inform and validate modeling Temperature- and moisture-dependent degradation Nonlinear (and time-dependent sorption)

12 Preliminary refinement results Historical assessments With Refinements PGW-measured 1 ppb SCI-GROW: 6.68 ppb and 11.2 ppb PRZM-GW EDWCs: acute 51.8 ppb, and chronic 32.3 ppb PRZM-GW EDWCs: acute 106 ppb, and chronic 88 ppb Label-relevant PRZM-GW (NC coastal plain) EDWCs: acute: 68.7 ppb, chronic 60.6 ppb Subsurface fate PRZM-GW (NC coastal plain) EDWCs: acute: 19.1 ppb; chronic 14.4 ppb DFOP kinetics PRZM-GW (NC coastal plain) EDWCs: acute: 0.61 ppb; chronic: 0.58 ppb PGW: 1 ppb

13 Concentration (mg/kg) Incorporating refinements into PRZM-GW - synprzm Include DFOP kinetics Include Freundlich sorption isotherms Include temp/moisture rate correction Testing with field data Total soil concentration (0-15 cm) Brimfield, IL Plot 2 Modeled Field_data DAT 13

14 Concentration (ug/l) Concentration (ug/l) And comparison to PGW Preliminary comparison shows significant model improvement at 9 ft and in groundwater Groundwater concentration PGW NC synprzm w/ soil temp and moisture correction+freundlich Field_data Soil pore concentration (9 ft) PGW NC synprzm w/ soil temp and moisture correction+freundlich Field_data DAT DAT

15 Other refinements - building additional PRZM-GW scenarios 15 Current six vulnerable scenarios Represent a small subset of use areas PRZM-GW guidance suggests additional scenarios can be defined as a Tier II step In vulnerable areas, shallow groundwater, w/ high leaching & persistence potential But no specific process outlined

16 Example for US wheat Step 1 - Nationwide screening analysis of all wheat-growing soils 5-year CDL crop footprints for wheat Spatial analysis to ID combinations of soils, weather, and state-dependent crop parameters SSURGO component level Weather SAMSON thiessen polys State-level emergence, maturity, harvest, application dates, GW temperature, evaporation depth, irrigation Standardized chemical inputs, 70 g/ha, Koc 144 ml/g, t ½ 126 d 16

17 Step 2 ID representative scenarios Four winter and spring wheat states selected from the top 5 vulnerable states Specific scenarios selected met: o Post-breakthrough average screening concentrations near 90 th -percentile for the state o In proximity to shallow groundwater wells (corresponding to crop within the same aquifer as the shallowest wells in the state) o In areas of high wheat acreage 17

18 Oklahoma Winter Wheat Representative Scenario Site

19 Comparison to PRZM-GW Standard Scenario Results State Crop concentrations (ppb)* OK Winter Wheat 4.14 TX Winter Wheat 2.55 KS Winter Wheat 1.55 CO Winter Wheat 4.34 ND Spring Wheat 2.04 MT Spring Wheat 2.55 WA Spring Wheat 4.30 TX Spring Wheat 2.98 State PRZM-GW Standard Scenario concentrations (ppb)* FL Citrus 5.92 FL Potato GA Coastal Peanuts 1.94 DELMARVA Sweet Corn 4.54 NC Coastal Cotton 4.41 WI Corn 8.84 *100-year simulation

20 Extensible Methodology Efficient parallel processing using python scripts to run batches of simulations simultaneously, allows national vulnerability assessment while maximizing the number of different environmental conditions evaluated. facilitates extending process to other use patterns and pesticides. New wheat scenarios can be used for modeling other chemicals Represent high post-breakthrough pesticide concentrations, high crop acreage, and shallow groundwater

21 Summing up Crop- and spatially-specific information can add realism to modeled exposures Monitoring and specific-field study results can serve to inform and validate modeling Concepts like these are possible ways forward to a tiered assessment methodology for drinking water