Minutes of the July 27, 2010 Exposure Modeling Public Meeting

U.S. Environmental Protection Agency, Office of Pesticide Programs (OPP) One Potomac Yard, S-4370/4380 2777 South Crystal Drive Arlington, VA 22202

Attendees:

Name Association

Uwe Wanner Chemtura Thuang Xiao Dupont Natalia Peranginangin Syngenta
Chris Burnside Toxcel
Russell Jones Bayer Cropsciences
Mark Velleux HydroQual
Catherine Aubee USEPA/EFED Aaron Harding Environmenta l & Turf Services, Inc. Paul Henley Syngenta

LaJan Barnes Environmenta l & Turf Services, Inc.
Mortin Williams Waterborne Stephen Kraemer USEPA/ORD
Kurt Pluntke USEPA/EFED
William Eckel USEPA/EFED
Katherine Carr Monsanto
James Lin USEPA/EFED Donald Brady USEPA/EFED
Brannon Walsh USEPA/AD
David Valcore Valcore Consulting David Healy Stone Environmental
Tom Nolan USGS Isha Khanijo Waterborne Qingli Ma Exponent
Al Barefoot Dupont Andy Newcombe Arcadis Ian Kennedy CAN/PMRA
Stuart Cohen Evnironmenta l & Turf Services, Inc.
Nick Poletika Dow Agrosciences Faruque Kahn USEPA/EFED
Robert Miller USEPA/EFED
Scott Jackson BASF
Iwona Maher USEPA/EFED Chris Koper USEPA/EFED Subijoy Dutta USEPA/EFED Andrew Shelby USEPA/EFEDPaige Doelling NOAA/NMFS
Michael Winchell Stone Environmental Paul Paquin HydroQual Jane Tang Bayer Cropsciences Robert Joseph Syngenta Nathan Snyder Waterborne
John Weeks S.C. Johnson Greg Orrick USEPA/EFED Dirk Young USEPA/EFED
Michael Barrett USEPA/EFED

Yan Donovan USEPA/PRD
Ronald Parker USEPA/EFED
Jim Wolf USEPA/EFED
R. David Jones USEPA/EFED Siros Mostayhimi USEPA/AD Tanja Crk USEPA/EFED
Has Shah American Chemistry

Dial In Participants

Name Association Jeff Giddings Compliance Services James Cooper et al Florida Dept. of Agriculture and Consumer Services
Ann Pitchford USEPA, NERL Bill Mahlburg Nufarm Americas Inc
Richard Allen Bayer Cropsciences Kelly Moran TDC Environmental
Jack Barbash USGS
Frank Voss USGS Vincent Leopold Monsanto
Nick Hart OMB
Monica Ball Dupont Crop Protection
Cecil Dharmasri Syngenta Crop Protection
Eric Weber EPA ORD Tim Negley ARCADIS US, Inc Susan Youngren BERGESON & CAMPBELL, P.C.
Kent Kabler et al Syngenta Crop Protection
Gerhard Goerlitz Bayer Cropsciences
Jim Warren USDA-APHIS
Mark Schocken Schocken Consulting Barbara Pugh AMEC Earth and Environmental Jay Nag Chemtura John Schnupner Cheminova
Joe Zachmann Minnesota Dept of Ag

Ron Struss Minnesota Dept of Ag
Heather Johnson Minnesota Dept of AgJoe Bagdon USDA Greg Malis PMRA

Les Carver Waterborne Joy Honegger Monsanto
John Troiano CDPR
Allan Rose Valent Roy Meyer NJDEP
Kristian Paul DuPont Crop Protection

Welcome and Introductions

The USEPA/OPP/EFED hosts these biannual meetings that are open to the public to provide a forum for exchange of information between EFED and st akeholders with similar technical expertise of

current issues related to pesticide exposure modeling in support of risk assessment. The overarching theme of this meeting was “G round Water Modeling a nd Pesticide Modeling Refinements in Agricultural a nd Urban Environments.” Reuben Baris and Charles Peck (both of USEPA/OPP/EFED) co-chaired the meeting in the capacity of co-chairs of the Water Quality

Technical Team (WQTT).

The minutes and presentation slides for the July 27, 2010 EMPM are posted in the docket (EPAHQ-OPP-2009-0879), which can be accessed at http://www.regulations.gov/ . The docket ID # is reported on the EMPM webpage: http://www.epa.gov/oppefed1/models/water/empm_top.htm

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Brief Updates

None

Presentations

A Look at Prospective Ground-Water Monitoring Studies and their Utility for Developing Pesticide Leaching Models

Ian Kennedy 1 , James Wolf 2 , and Michael Barrett 2

, 1 PMRA, Ottawa, Canada

2 USEPA, Washington, DC

The datasets from prospective groundwater (P GW) monitoring studies, required by EPA for registration of pesticides thought likely to leach to groundwat er are being used by EPA and Health Canada's Pest Management Regulatory Agency (PMRA) to evaluate and develop groundwater exposure models. PMRA and OPP's Envi ronmental Fate and Effects Division (EFED) examined and modeled a number of completed PG W study reports for the utility of the datasets for use in testing leaching models. A number of factors have been identified which commonly limit the use of these data, including:

 Uncertainties in pesticide and degradate fate properties.

 Data censoring, or reporting/det ection limits which are set too high to accurately establish breakthrough patterns with depth fo r the pesticide or degradates. The conducting of studies under conditions where precipitation or irrigation for long periods were insufficient to promote ground water recharge - this is often associated with a high rate of soil-pore water sample collection failure.

 Temporal and spatial variability in the soil matrix is often high and the sampling frequency and sampling locations may be insufficient to track water and solute

movement.

 Study was ended before a complete breakthrough curve was observed.

Presentation Notes: Monitoring data from prospective groundwater (PGW) studies can be used to develop and evaluate exposure models Uncertainties must be identified and addressed to design and implement more relevant and useful
studies Uncertainties in fate studies (Lack of information on site-specific degradation and sorption purposes) Finding the right balance: simplicity v. refinement (can be data intense)
Uncertainties associat ed with temperature Limitations of data censoring • Breakthrough patterns cannot be accurately established • Reporting limits, detection limits set too high Application rate v. water detection limits • Identify fraction of nominal (target) application rate detectable in water samples Issue: Only transformation product has well-defined breakthrough (Must simulate formation of the transformation product) Issue: Insufficient irrigation or precipitation Issue: Studies that end too early Issue: Increased spatial and temporal variability in the soil matrix
Critical elements of effective PGW studies • Complete and accurate weather data
• Detailed soil characterization • Preparation and performance testing

Suction lysimeters have been found useful at many sites, but not always. Success has improved, as shown by the data, but it is a learning process.

Study design could be improved based on chemical- and site -specific leaching predictions.

There is a fair amount of confidence in modeling of extreme leaching situations. Need to balance reasonable objectives of the study, e.g., with chem icals expected to leach very slowly (perhaps many years): One might be able to characterize breakthrough but not detect GW concentrations
within a reasonable timeframe.

Need to know the relationship between physical soil characteristics and chemical degradation. Transformation gets slower with soil depth, and thus [the characterized transformation process?] may not be representative, when the rate of ch ange in transformation rate with soil depth is unknown. Timing is important. ***************************************************************************

Screening Approaches for Predicting Pesticide Concentrations in Groundwater Dazhi Mao, Marty Williams, Mark Chep lick, Amy Ritter, and Robert Morris Waterborne Environmental Inc., Leesburg, VAThe presentation compares three modeling appr oaches for estimating pesticide exposure in groundwater: SCIGROW, an empirical model derived from the results of controlled, field-scale groundwater monitoring studies; 2) PRZM-GW, an adaption of the Pesticide Root Zone Model (PRZM) to estimate pesticide concentrations in shallow ground water; and PRZM-ADAM, the linkage of PRZM to an aquifer dispersion and advection model based on Darcy's law to estimate concentrations in ground water. The methodology and the ability of all three approaches to reproduce the results of pr ospective groundwater monitoring studies are compared.

Presentation notes: Mr. Williams compared three models for estimating pesticide exposure in ground water. These models were 1) SCI-GROW, a Tier I screening em pirical model, 2) the Tier II screening model PRZM parameterized for the N-methylcarbamate cumulative risk assessment (PRZM-NMC), and 3) PRZM linked to ADAM, an aquifer dispersion and advection model based on Darcy's law (PRZM-ADAM). Model results were evaluated with soil and vadose zone (5- to 6-foot depth) sampling data from five prospective ground water (PGW) monitoring studies.

Soil concentrations of pesticides and bromide were predicted fairly well with PRZM. However, PRZM tended to flush bromide through the vadose zone too quickly and pesticide concentrations in soil pore water were over-estimated by less than an order of magnitude. Bromide concentrations in ground water were 1) over- estimated with SCI-GROW by approximately twoorders of magnitude, 2) over-estimated by PRZM-NMC by 4X to 8X, and 3) similar to PRZMADAM estimates. Pesticide concentrations in ground water were 1) similar to SCI-GROW estimates, 2) under-estimated by PRZM-NMC, and 3) under-estimated much more by PRZMADAM. Differences between estimates from PRZM-NMC and PRZM-ADAM may have been due to their simulation of different mixing depths (1-m versus 5-m, respectively). Further research may include analysis of additional study data, calibration for bromide timing, and sensitivity analyses. ***************************************************************************

Mechanistic Ground Spray B oom Drift Model Development
David L. Valcore 1 , Harold W. Thistle 2 , P. C. H. Miller 3 , and Clare Butler-Ellis 3

1 Valcore Consulting

2 USDA-USFS

3 Silsoe Applic. Unit, The Arable Group, UK

A number of high quality spray drift datasets ex ist internationally that have provided empirical drift deposition curves for spra y drift risk exposure assessments to sensitive areas. Existing agricultural ground spray drift deposition models ar e empirical. There is a need for more accurate drift predictions to gr eater distances than the typical 30-100 meters or even the 300
meter distance available from th e EPA AgDRIFT model. A multi-phase international effort to develop a robust mechanistic ground boom spray drif t model is underway to address the need to evaluate mitigation options that modify application parameters including spray boom and nozzle type, meteorology and low drift technologies. An updated random walk multi-nozzle spray deposition drift model developed by Silsoe Spray Application Unit, UK was chosen as the basis of current efforts. Initial comparisons of this model with EPA’s accepted Spray Drift Task Force
data have been made and show that the mode l can successfully predict ground deposits up to 200 meters downwind, and potentially beyond. Preliminar y sensitivity analysis of the key parameters in the model algorithms will be discussed. A brief summary of development status, current insights, research and verification plans will also be presented, including benefits expected fordrift risk assessments, drift mitigation options, and support of EPA’s Drift Reduction Technology program.

Presentation Notes: Current Status on Ground Boom Spray Drift Models: deposition based on empirically determined curve fits as a function of drop size distribution; does not account for wi nd speed effects on spray droplets

Current Ground Boom Spray Drift Model Developm ent: Silsoe drift model (UK) which accounts for multiple boom nozzles, sprayer flow, evaporati on/entrainment, and sprayer designs. Model can be run in a probabilistic mode.

Evaluation of Silsoe drift model – comparison to Spray Drift Task Force field data and sensitivity analysis conducted (e.g. nozzle porosity paramete rs, humidity, volatilization, boom height, wind speed, entrained air velocity, and droplet size distribution)

Results

 Model tended to over-predict for short distances from sprayer

 Most important environmental parameters to deposition – boom height, wind speed,

evaporation rate, and minimum droplet size

 Most important nozzle-specific parameters to deposition – droplet size distribution and

entrainment

Future Work

 Refine model to address air induction nozzles

 Further investigate multiple nozzles

 Perform more studies to retrieve more input data

 Improve computational fluid dynamics model

Discussion

 Investigation on impact of adjuvants needed

 Largest reductions in hot, dry environments with tank mixes using non-volatile oils

 Drop sizes may be most modified in the upper portions of spectra > 100μm

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Using Modern Watershed and Cropping Data as a Basis for Estimating Percentage Crop

Treatment Nathan J. Snyder 1 , Joshua J. Amos 1 , Peggy S. Lee 1 , and Aldos C. Barefoot 2

1 Waterborne Environmental Inc. Leesburg, VA

2 DuPont Crop Protection, Newark, DE

Distributing pesticide use data or determining percent of crop treatment is dependent on estimates of cropping information. If an attempt is made to distribute sales or use data to a geographic area smaller than the collection resolution (i.e. CRD/c ounty/zipcode data distributed to a small watershed), spatially accurate croppi ng estimates are require d. The use of modern watershed and cropping information (and a comparis on to traditional county level data) will be presented through a case study. Examples of im provement to the traditional regional PCA values currently being used for drinking water modeling will be discussed. Two areas of the USEPA regional PCA methodology will be evaluated 1) Regional default PCAs developed fromlarge watersheds (8-digit Hydrologi c Unit Codes), and 2) concerns with scale and uncertainty of crop distribution within waters heds. Regional PCAs were an interim step in moving from national PCAs to PCAs developed from actual dr inking watersheds. In the 10-years since the 1999 SAP review and seven years since the development of regional PCAs, updates to watersheds and crop coverages have become availa ble. Concerns with limitations in PCAs for individual crops for development of protective residue values fo r drinking water assessments can be addressed through the recently available data. It is appropriate to move beyond an interim step and improve drinking water estimates us ing cropping and pesticide use data distributed through PCA adjusted EECs in actual drinking watersheds.

Presentation Notes: Presentation on the use of percent cropped ar ea (PCA) estimates to refine drinking water assessments. Review of EPA’s development of PCA values and their current approach to implementing PCAs. Discussion of the current limitations to EPA’s method: PCAs too coarse for use with minor crops, so EPA uses default PCA PCA for multiple crops based on single watershed w/ highest percent of crops being
modeled HUC-8s may not provide reasonable estimates for smaller watersheds Assumes uniform and homogeneous distribution of crops

Need for development of Tier 3 approach that combines local knowledge of drinking water supplies, actual watersheds, and spatial distribution of crops with regional scenarios and weather. Use of GIS with SDWIS, NHDPlus, and DWMA to delineate water intakes and watersheds. Use of NASS Crop Data Layers to delineate spatia l crop areas. Good agreement between CDL data and Ag Census data.

Development of a Tier 3 assessment and PCAs is feasible, will help identify vulnerable monitoring locations, will help identify areas requi ring possible stewardship activities, and protect important use areas that fall outside poten tially vulnerable drinking water supplies.

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Design and Testing of a Process-Based Gro undwater Vulnerability Assessment (P-GWAVA) System for Predicting the Concentrations of Agrichemicals in Ground Water Across the Conterminous United States Using Data from the National Water-Quality Assessment (NAWQA) Program
Jack E. Barbash and Frank D. Voss U.S. Geological Survey, Tacoma, WA

Over the past two decades, many tools have been employed to predict th e likelihood of detecting surface-derived contaminants in ground water. St atistical relations have been used at large spatial scales to predict contaminant occurrence from various site-based parameters. At such scales, however, process-based simulations of the transport and fate of the compounds of interest have been relatively uncommon. This presentati on will describe an approach that (1) employs a geographic information system to provide spatia lly-structured data i nput to a process-based vadose-zone model (PRZM or RZWQM) for any lo cation in the conterminous United States, (2) simulates the transport and fate of pesticides, pestic ide transformation products and nitrate to
estimate their concentrations in the vadose zone beneath each selected lo cation, and (3) compares
the simulated concentrations w ith those measured in shallow ground water sampled from over1,900 wells across the Nation between 1992 and 2007 by the U.S. Geological Survey’s National Water-Quality Assessment (NAWQA) program.

Presentation Notes: This presentation described the design and testing of the Process-Based Groundwater Vulnerability Assessment (P-GWAVA) System. The principal objective of P-GWAVA is to make the most informed predictions possible of agrichemical concentrations in ground water, anywhere in the lower 48 states. To make informed predictions P-GWAVA: • incorporates as much process understanding as possible • uses only on data sources covering all areas of the lower 48 states • employs only public domain models

P-GWAVA is designed to simulated concentratio ns of agrichemicals in the vadose zone as indicator concentrations in shallow groundwater. Since there are more monitoring data on atrazine and its degradates, deethyl atrazine (DEA) and nitr ate, these compounds were used exclusively in development of the model. During the development of P-GWAVA predicted concentrations in the vadose zone were compared with concentrations measured in shallow groundwater by NAWQA. Since atrazine is most commonly used on corn, use on corn is simulated at all sites.

The PRZM (Pesticide Root Zone Model) and RZ WQM (Root Zone Water Quality Model) models were employed.

The P-GWAVA system was designed for running unsaturated zone simulations at multiple sites.

CLIGEN and SSURGO Data were used for RZWQM Inputs.

For Phase 1 (PRZM) of the system development study, 42 areas (1254 well sites) were selected relative to where atrazine use was employed in an agricultural setting throughout the country. For phase 2 (RZWQM), 435 wells were selected relative to where atrazine was used in an agricultural setting within the Corn Belt. In PRZM, soil column data is presented in uniform composition to a depth of one meter. For PRZM, the soils data taken from STATSGO, weighted by depth and area. For RZWQM all soil layers are represented to a depth of 3 meters. Soil Data for RZWQM was
data taken from SSURGO.

Only 7% of the mass balance of the compound wa s detected in soil after seven years of annual atrazine applications (2 kg/ha/yr) in southwestern Indiana. Only 0.26% of DEA was found in the soil. This was mainly due to plant uptake and mineralization.

P-GWAVA was also used to predic t nitrate concentrations in the same area of southwest Indians. Nitrate concentrations of 0.08 mg/L were predicted in the vadose zone.

Observed atrazine, DEA, and nitrate groundwater concentrations were higher than those predicted in the RZWQM vadose zone. Observed DEA and nitrate concentrations were higher than predicted vadose zone concentrations from PRZM. The statistical correlation between predicted and observed solute concentrations in both the Corn Belt and nationwide had low R squares. ***************************************************************************Comparison of Models for Estimating the Remova l of Pesticides by Vegetative Buffer Strips

Michael Winchell 1 , Russell Jones 2 , and Tammara Estes 1

1 Stone Environmental, Montpelier, VT

2 Bayer CropScience, Stilwell, KS

Vegetated buffer areas established between agricu ltural fields and receiving waters have long been recommended as a best management practi ce to reduce the amount of sediment, nutrients, and pesticides entering water bodies and recently intensively manage d vegetated filter strips have been mandated as label requirements for plant pr otection products in both Europe and North America. Also recently, models have been develo ped to predict the amount of active ingredients
and their metabolites removed from runoff flow ing through these strips. This presentation
reviews the features of five models (APEX, PRZM, REMM, SWAT, and VFSMOD-WQ) which can be used to predict the re duction in pesticide loss in runo ff passing through a vegetative buffer strip. The predictions from four of these models are compared using three common data sets, one from Europe and the other two from the Un ited States. The conditions modeled include a range of soils properties, slopes, rainfall events, and pesticide so rption characteristics. All four models predicted significant reducti ons of pesticides in the buffe r consistent with the observed reductions, providing strong support for the use of these models as tools for estimating buffer effectiveness. A sensitivity analysis was conducted with the four models to determine the effects of input parameter uncertainty on the predic tions of pesticide reduction in the buffer.

Presentation Notes: In this study, four different models were evaluated (APEX, PRZM-BUFF, REMM, and VFSMOD) using three case studies. Vegetative filter strips have long been recognized as successful at reducing runoff concentrations to receiving streams and recently have been mandated in many cases. A qualitative way of evaluating filter strips has be come necessary. This can be done through either field work (looking at so il, weather, topography, climate, etc.) or by using mechanistic
models that can account for different levels and balances of the pr evious listed inputs. The 3 objectives of this presentation were to:
1. Evaluate the four models 2. Understand the sensitivity of the 4 models 3. Analyze the models for use

APEX o This model is mostly used for agricultural non-point source and nutrient evaluation. o The study area is divided into subareas, with the subareas having the possibility of being different (for example, overland flow versus channel flow).

PRZM-BUFF o This model is used in pesticide exposure and for other non-point source issues
o It is divided into a main treated field run and a second run that in volves the outflow from the main treated field through the vegetation in the buffer

REMM o Used for nutrient management, multi-zone uses mostly with pesticides o There is no field component (only buffer) o Has 3 parts to the buffer. 1 Vegetative filter strip 2 Managed strip (for example, woody vegetation) 3 Unmanaged (for example, stream bank)

VFSMOD o Sub-daily time step model used for non-point source o Flow and sediment loads are input into the model in a time series o Equations are used to estimate infiltration and sediment depositiono Pesticide reduction is a function of infiltra tion, deposition, chemical characteristics, and soil clay

Discussion 1) In PRZM-BUFF, the Curve No (CN) was made artificially high because it was designed for daily sensitivity, not hourly. 2) Differences in parameterizations could have been why there was more error in some models (REMM) over others. However, evaluators only looked at inputs and outputs parameterized for REMM as one grass filter strip divided into the three parts. ***************************************************************************

Advances in Modeling Urban/Residential Pesticide Runoff Marty Williams, Amy Ritter, Me gan White, and Mark Cheplick Waterborne Environmental Inc., Leesburg, VA

The U.S. Environmental Protection Agency's (USEPA's) Storm Water Management Model (SWMM) is widely used for urban water manage ment and water quality analysis. The model is limited in its ability to simulate pesticides be cause of a general lack of knowledge of washoff
coefficients values for hard surface runoff and the inability to specify discrete pesticide applications. USEPA's Pesticide Root Zone Mode l (PRZM) was developed to simulate pesticide runoff and leaching in agricultural environments a nd is limited in its ability to urban drainage
features. Recent enhancements have been to both models to overcome these deficiencies. Pesticide and water runoff predictions from both models are compared.

Presentation Notes: In 2006, a model evaluation compared the St ormwater Management Model (SWMM) and the Pesticide Root Zone Model (PRZM). The objective was to present r ecent advances in modeling pesticide runoff urban/residential landscapes. Model pesticide applications and pe sticide washoff from hard surfaces w ith SWMM. Model runoff and pesticide washoff from hard surfaces with PRZM. Within SWMM, pesticide application is added as a continuous buildup; whereas within PRZM, the pesticide can be added at a distinct interval. Simulation of Storm Water Runoff with SWMM and PRZM showed comparable results.
Enhancements within both models allow for refined runoff concentrations. SWMM (beta) now has the ability to simulate discrete applications of chemicals. PRZM (WinPRZMwdv) now has the ability to simulate hard surface runoff of chemicals SWMM and PRZM reasonably simulated hydrologic response of UK roadway and an Oregon
residential area SWMM and PRZM reasonably simulated atrazine and glyphosate from a UK roadway Data is becoming available to develop washoff coefficients for hard surfaces (pesticide properties/formulations vs. surface conditions)

Discussion: It was unclear as to whether the weather data pr esented in Oregon dataset was representative of a
national scenario.

***************************************************************************Spray Drift Exposure Refinements for Salmonid Off-Channel Habitat

Nick Poletika 1 , Rick Reiss 2 , Steve Cryer 1 , and Stever Cramer 3

1 Dow AgroSciences LLC

2 Exponent, Inc

3 Cramer Fish Sciences

Off-channel stream habitat is vi ewed by the National Marine Fisher ies Service as the habitat type in which Pacific Coast threatened/endangered sa lmonids are most vulnera ble to adverse impacts from spray drift residues resulting from applicatio ns of agricultural pesticides. Data describing the water body characteristics of off-channel habi tat associated with agricultural landscapes were
collected and used to conduct refined spray drift and aquati c dissipation modeling. Flowing water was found to be a key characteristic infl uencing exposure magnitude and duration in offchannel stream features relevant to agricultura l settings. Based on advanced technical modeling approaches and representative, best availa ble measurement data, time-varying exposure assessments for the three main types of important off-channel habitat (side channels, alcoves, and backwater pools) were completed for durations consistent with acute toxicity testing. The exposure assessments were compared to screen ing-level exposure predictions assuming typical off-channel habitat is represented by shallow static water bodies.

Presentation Notes: The impetus of the spray drift exposure modeling work relating to salmonid off-channel habitats stems from the first NMFS biological opinion (BiOp) of Nov. 18, 2008. Several off-channel habitats were proposed in the BiOp but not all were deemed necessary (at least for this presentation) for modeling. Off-channel areas consid ered in the presentation include side channels, alcoves, and backwater pools. Relatively high shade % values were also considered, as they would be indicative of quality salmon habitat as well as ri parian habitat (and thus spray drift interception zones). All three off-channel areas have charact eristic flows: channel flow, hyporheic flow & mixing with main channel, and eddy current mass exchange, respectively. A different model
construct is used for each off-channel habitat to generate time-weighted average concentrations (i.e., a change in concentration over time) that are consistent with acute toxicity test times (24-96 hours): Stream Assessment Tool (SAT) in AgDrift 2.0.05, AgDrift 2.0.05 & dye study measurements, and AgDrift 2.0.05 & channel flow data & fluid dynamic modeling, respectively. Representative locations (in OR, CA) for data needs were based on NLCD 2001 land cover data (open water 11, pasture/hay 81, and cultivated crops 82) that indicated whether the site of interest was representative of agricultural areas. Several model assumptions were considered conservative. The worst-case results for both aerial and gro und scenarios for each habitat (1-day averages) indicate that the greater the distance between app lication site and water the lower the chemical concentration in water. However, the backwater habitat appears to have the greatest chemical concentrations of the three habitat types.

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Spatially-Distributed Watershed Model for Chemical Exposure Assessment: Case Study of Antimicrobial Copper Uses in Urbanized Areas

Mark Velleux, Paul Paquin, Aar on Redman, and Robert Santore HydroQual, Inc.

Copper is used as an antimicrobi al agent in building materials su ch as algae-resistant shingles and treated wood. In urbanized areas, copper-co ntaining building materials may be present inroofs, wood decks, wood fences, and utility poles installed in densely clustered and widely dispersed locations across the landscape. Releases from these materials may pose risks to aquatic and terrestrial organisms. The TREX (T wo-dimensional R unoff E rosion and Ex port) watershed model was used to simulate spatially-distributed copper releases, runoff, and estimated exposure concentrations in surface water, soil, and sediment for an urba nized setting. Setting design was based on typical housing densitie s and upper-end copper use pattern s in building materials to provide a representative “worst-cas e” scenario with respect to spat ial distributions and variability of copper sources at the watershed scale. Coppe r release rates from building materials were
defined as functions of surface area and rainfall using measurements from manufacturers or other field study results. The model requires data to define watershed boundaries, the stream network, land surface elevations, soils, land use, physical processes that control runoff and soil and sediment transport, as well as rainfall. Data we re obtained from standard sources including the U.S. Geological Survey, Natural Resource Conser vation Service, National Weather Service, and
Census Bureau. The watershed area was 21.4 km 2 . The model grid was defined at a 90 meter resolution and includes 2,558 cells. Simulations were performed for a 10-year period with 772 storms defined using 15-minute rainfall data. Resu lts were analyzed in terms of the frequency with which modeled exposure conc entrations exceeded benchmarks for water, sediment or soil.
Surface water benchmarks were determined with the biotic ligand model (BLM) for copper. Simulated copper exposures from algae-resistant sh ingles were relatively low and did not result in exceedances in any media. Simulated exposures from treated wood were larger than those for shingles and resulted in two water quality be nchmark exceedances (i.e. 2 days in 10 years).

Presentation Notes: The main focus of the presentation was on antimi crobial pesticides. It is well documented in EPA websites and elsewhere that determining human and ecological risks from exposure to antimicrobial pesticides requires different types of measurements and models than those needed for pesticides largely applied to crops and other plants. Specific applications could be any variants of the following: Antifoulants, biocides wood preservatives, etc. Antimicrobial copper use in building products...

Different field settings were considered such as – Agricultural Use:
Farm fields Uniform application Building Products:
Urbanized areas Spatially variable! biocide mass released not equal to mass installed Address variability with watershed approach

TREX Watershed Model: Two-Dimensional Runoff, Erosion & Export This model is available to anyone and can be downloaded from: http://www.engr.colostate.edu/~pierre/ce_ o ld/Projects/TREX%20Web%20Pages/TREXHome.html

This chemical transport model followed EPA’s WASP model to some extent. The following diagram provides an overall view of the major input components in the model.

Major Inputs for the TREX Model include: • Topography (DEM)• Soil characteristics
• Land cover
• Stream and sediment characteristics
• Rainfall • Chemical application and release rates • Chemical partitioning and fate parameters

A few Case Studies were presented – Antimicrobial Copper – Examined two separate copper uses using 90m x 90m boxes: Algae-resistant (AR) Shingles and
Treated Wood

Uses and setting differ from agricultural case. The case studies were undertaken in – 1. Urban setting with spatially-variable landscape conditions; rainfall-driven releases from roofs, decks, fences, and poles... 2. Lake setting with marina and inputs from upstream Simulated copper transport and fate to calcu late estimated environmental concentrations (EECs).

The setting was based on real watershed

The information was used to calibrate the model for these parameters. Information on Slide Fences – treated wood fences, Toledo, OH were used to represent the urban setting. Copper sources in urban setting were a combination treated wood decks and fences Overall summary Cu Release rate – 20% CCA, 80% non-CCA, overall 14.1 mg/m2 /day.

The Environmental Benchmarks for Cu in Surface Water, Soil, and Sediment were checked and compared with the release rates. Results for Algae-Resistant Shin gles for over 10 years indicated that Cu releases driven by Rainfall. Sediment – stream segment – 9% of Cu deposits ends up in stream beds. EECs and Benchmarks indicated monthly change and time variable change. Simulated Cu Mass Fate – over 10 years didn’t see much leaching. In treated wood there were two Benchmark exceedances in 10-year period fo r the average concentrations. Results are expected to be conservative. According to the author/presenter’s interpretation – both urban and aquatic setting EECs are not expected to exceed the benchmarks.

Discussion: 1. GIS mapping of the study area was used to estimate the total drainage and copper source from the urban setting; it was unclear as to how any erro rs associated with this data were corrected. 2. The accuracy of the concentrations of Cu in water measured and whether there were any special measurements for hot-spots woul d be presented in follow-on material. 3. At the time of the evaluation, there were no considerations given or a study undertaken to estimate possible high concentrations of Cu in the surface water from AR Shingles in areas with
acid rain and from treated woods in acidic waters. If there is a primary application in such environments, assessors would evaluate this in future work would assess.

Wrap Up

The Next EMPM will be held on December 7, 2010. The meeting theme will be announced through the “empm listserve” foru m on the LYRIS list serve at: https://lists.epa.gov/re ad/? forum=empmlist

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