Assessment of Available Monitoring Data and Modeled EEC Values for an Herbicide (Linuron) in the US and Canada
The purpose of his study was to compile a dataset of monitoring data for an herbicide (linuron) used in North America to create a geospatial illustration of the water monitoring locations and to compare these results to the outputs of standard Tier 2 models. Water quality monitoring records were collected for a 25-year period (1986 – 2015). Over 115,000 sample results were obtained for Canada and the US. Monitoring data for the U.S. was available primarily online. Much of the information for Canada was requested from regulatory agencies and other organizations, and, to a lesser degree, available online. Of the 115,000+ records that were collected 89% are associated with the US and 11% of the monitoring data is for Canada. A majority of the data in both the Canada and the US are for surface water (~60%) and for groundwater (~39%), while results for drinking water are less commonly reported (0.02%). About 1% of the monitoring data indicated that the herbicide was detected. In addition to standard percentile assessments, geo-spatial statistics were applied to identify ranges of sampling density for monitoring and to determine if spatial-temporal trends are present in the data. Monitoring data were compared to standard USEPA and PMRA modeling scenarios. The results indicated that no correlation exists between modeled data and observed data for linuron.
Gerco Hoogeweg*, Isha Khanijo, Stephanie Herbstritt (Waterborne), Kevin Henry, Luis Castro, and Jonathan Akins (TKI). “Assessment of Available Monitoring Data and Modeled EEC Values for an Herbicide (Linuron) in the US and Canada“. Presentation. SETAC NA. 2016.
An Evaluation of Endpoints from Benthic Invertebrate Chronic Toxicity Tests Based On Draft US FIFRA Guidance – Part II
Session: Science of Sediment Toxicity Testing: Method Advances, Interpreting Results and Use of Data in Ecological Risk Assessments
Session Start Time: 8:00AM
Location: Exhibit Hall
Authors: Jennifer Gates*, Mark Cafarella (Waterborne), Theodore Valenti (Syngenta), Kent Kabler (Syngenta), Alan Samel (Dupont), Alan Jones (Dupont), John Green (Dupont), Jane Staveley (Exponent), Bibek Sharma (FMC), Sean McGee (Bayer), Matt McCoole (Bayer), Jiafan Wang (BASF), Maike Habekost (BASF), Hank Krueger (Wildlife International), Susan Thomas (Wildlife International), Michael Bradley (Smithers), Christian Picard (Smithers), Jeff Giddings (CSI), Imad Saab (CropLife)
On October 26, 2007, sediment chronic toxicity testing with benthic aquatic invertebrates became a conditional requirement as part of the Office of Pesticide Program’s ecological effects data requirement contained in 40 CFR Part 158 Subpart G. Studies are now required for any pesticides with soil partition coefficient (Kd) ≥ 50, log Kow ≥ 3, or Koc ≥ 1000. Due to the novelty and complexity of the study designs, it is important to gain a critical understanding of the relative sensitivities of required test endpoints within and among tests. At the 2015 SETAC North America annual meeting, the CropLife America (CLA) Ecotoxicology Work Group Sediment team presented a poster detailing key findings from a sediment toxicity testing database that was compiled by CLA. For the Chironomus dilutus life-cycle tests, larval survival, growth and emergence were the most sensitive parameters, whereas endpoints based on reproduction or adult survival (i.e., number of days to death) were consistently less sensitive. For chronic sediment studies with amiphipods (Hyalella azteca and Leptocheirus plumulosus), survival, growth, and reproduction proved to be important parameters to measure and each parameter yielded the most sensitive endpoint for certain studies. This presentation will provide an update and recommendations for streamlining relevant endpoint selection, as well as more closely consideration of the variability within control responses and subsequent implications.
Jennifer Gates, Mark Cafarella (Waterborne Environmental), Theodore Valenti (Syngenta), Kent Kabler (Syngenta), Alan Samel (Dupont), Alan Jones (Dupont), John Green (Dupont), Jane Staveley (Exponent), Bibek Sharma (FMC), Sean McGee (Bayer), Matt McCoole (Bayer), Jiafan Wang (BASF), Maike Habekost (BASF), Hank Krueger (Wildlife International), Susan Thomas (Wildlife International), Michael Bradley (Smithers), Christian Picard (Smithers), Jeff Giddings (CSI), Imad Saab (CropLife). “An Evaluation of Endpoints from Benthic Invertebrate Chronic Toxicity Tests Based On Draft US FIFRA Guidance – Part II“. Poster. SETAC NA. 2016.
A Spatially-Distributed Modeling Framework to Integrate Effects of Agricultural Best Management Practices: A Midwest Case Study
The federal pesticide risk assessment framework does not currently quantitatively account for off-field transport and exposure effects of best management practices (BMPs). Within the agricultural landscapes of the U.S., numerous structural and cultural BMPs are currently in place, mostly developed from NRCS programs to address agrichemical and soil loss reduction, natural resource conservation, and yield increase. In this work, a Midwest watershed was used as a case study for development of a spatially-distributed modeling approach to quantitatively evaluate potential impact of pesticide reduction (load and/or concentration) from multiple BMPs at multiple scales. This framework included a hydrologic and chemical transport model that was paired with stream flow and routing components to represent upland hydrologic processes, land management practices, and a flowing, receiving water body. Within the upland model, specific sub-areas were modeled separately to represent various structural BMPs, based on their physical location. Furthermore, cultural BMPs were also incorporated into the upland model to different degrees to evaluate model sensitivity. A baseline scenario was developed and used to define comparative difference between addition (adoption) and elimination of BMPs in a step-wise fashion. As part of the baseline scenario, relevant literature values and publically-available environmental data were used to inform model parameterization. This modeling framework can be used to explore how BMPs may be considered in a regulatory framework, addressing issues such as: BMP adoption rate and viability, weather-dependent behavior, and frequency and extent of BMP efficacy.
Dan Perkins, Rohith Gali, Matt Gloe, Brian Jacobson (Waterborne), Clint Truman (Syngenta). ” A Spatially-Distributed Modeling Framework to Integrate Effects of Agricultural Best Management Practices: A Midwest Case Study.” Poster. SETAC NA. 2016.
Advances in the Refined National-Scale Drinking Water Assessment Framework: Case Study Chlorpyrifos
In the US pesticide regulatory scheme for human dietary exposure, estimates of the surface-derived drinking water contribution are assessed with simple scenario-based modeling techniques. Such estimates can be a useful and conservative approach in a tiered risk assessment to systematically eliminate potential concern; however, the limited conclusions that can be reached are often not adequate to address the true extent of potential exposures. The current work focuses on advances in national-scale drinking water concentration estimation techniques, using chlorpyrifos as a case study. The method incorporates spatially-distributed environmental and management information in a risk framework at the watershed (HUC12) scale. Concepts of standard scenarios to create conservative, regionally representative (at an extent wider than HUC12) estimates of exposure patterns were applied and then were distributed at the HUC12 watershed scale by matching them with HUC12-specific cropping patterns derived from five years of cropland data layer (CDL) data. As a conservative first approximation, it was assumed that a drinking water source co-occurs within every HUC12 where applications were made to labeled crops. In this way, HUC12-specific exposure estimates were derived for all chlorpyrifos-labeled crops. Then, county-level community water system (CWS) locations were included to eliminate risk concern from HUC12 watersheds that did not co-occur with a CWS. Results from this first approximation eliminated concern in 83% of HUC12 watersheds with labeled crop(s). The impact of refinements and assumptions on the remaining 17% of HUC12 watersheds was further explored. Potential refinements included higher-resolution rainfall, soils, runoff and erosion data inputs, more realistic environmental fate, application timing and application type information, and percent crop treated. Significant impact was observed from the inclusion of these refinements, with at least 92% of the remaining HUC12 watersheds yielding a conclusion of no concern. Characterization of potential risk in a spatially-distributed fashion increases risk characterization accuracy/certainty because of the inclusion of best-available data to inform estimates of exposure and co-occurrence. In conclusion, it was discovered that spatially-distributed environmental and management factors must be considered to increase certainty and characterize potential risk, rather than relying solely on a scenario-based approach.
Dan Perkins*, Nathan Snyder, Josh Amos, Kendall Jones (Waterborne), Patrick Havens (Dow AgroSciences), Nick Poletika (Risk Analysis Solutions). “Advances in the Refined National-Scale Drinking Water Assessment Framework: Case Study Chlorpyrifos.” Poster. SETAC NA. 2016.
Exposure Assessment Modelling Approach to Non-Target Plants Through Runoff from Agricultural Fields
The U.S. EPA uses the screening model, TerrPlant, to estimate exposure to non-target terrestrial plants from a single application of pesticide. Audrey III is a higher tier exposure model that has been developed by U.S. EPA to estimate exposure to plants in a Plant Exposure Zone (PEZ). The objective of this study was to investigate the magnitude and likelihood of exposure of non-target plants to pesticide residues through runoff from agricultural field to an adjacent PEZ. TerrPlant and AUDREYIII will be compared to two vegetative filter models: PRZM-Buffer and VFSMOD. PRZM-Buffer is a modified version of the Pesticide Root Zone Model (PRZM), a rainfall-runoff simulation model, to simulate pesticide fate and transport in a PEZ. VFSMOD is a vegetative filter strip (VFS) model designed to simulate VFS processes to remove sediment and pesticides from field runoff/erosion. Current EPA Tier II scenarios for PRZM were used to represent main field simulations. Movement of pesticide through the PEZ and the concentrations for the segments were modeled with the PRZM-Buffer model and VFSMOD. Results from these two models will be compared to each other and to U.S. EPA models TerrPlant and AUDREYIII. Multiple widths of buffers were assessed to determine distance required for soil concentrations to drop below level of concern for non-target crop.
Amy Ritter, Mark Cheplick, Dean Desmarteau, Nathan Snyder (Waterborne Environmental). “Exposure Assessment Modelling Approach to Non-Target Plants Through Runoff from Agricultural Fields.” Poster. SETAC NA. 2016.
PresentationsHome and Personal Care Products2016
A Framework for Dynamic Estimation of Environmental Concentrations of Microplastics in WWTP Effluents and Receiving Waters at a National Scale
Down-the-drain exposure models provide a valuable screening-level tool for estimating environmental exposure to product ingredients which are treated and discharged at municipal wastewater treatment plants. Microplastics, plastic particles smaller than 5 mm diameter, enter wastewater treatment plants (WWTP) due to a variety of sources. Exposure modeling was performed using the iSTREEM® model, a publicly-available web-based model supported by the American Cleaning Institute (www.istreem.org) which estimates spatially-explicit concentrations of chemicals in effluent and receiving waters across the U.S. WWTP influent loadings of microbeads were estimated using per-capita usage derived from market manufacture survey (Gouin et al 2015) combined with individual facility population served and flow estimates within the iSTREEM® model. The analysis used multiple values for removal during treatment based on total suspended solid removal data and a wide range of in-stream decay rates, resulting in a variety of potential environmental exposure estimates. The removal and decay rates have a non-linear effect across the varying facilities & stream segments in the US landscape. Therefore, we developed an approach which leverages the advantages of the iSTREEM® model (national scope, individual facilities, and distributions of output) with the ability to screen for potential concern based on uncertain (and dynamic) removal and decay rates. This allows for flexibility in modeling the environmental concentration of microbeads regardless of size, weight, or physicochemical properties. We developed a 2-dimensional matrix with removal rate and decay rate as the primary axes. The individual cells within the array will then correspond to a reasonable worst-case Predicted Environmental Concentration (PEC) (e.g. 95th percentile) based on the national iSTREEM® results. These concentrations are based on a proxy quantity of microbeads which can be easily scaled. Therefore, with the matrix it is possible to supply an approximate removal and decay rate for the microplastic of interest and assess the estimated exposure by scaling the matrix value using the relationship between the substance quantity of interest and the proxy. This matrix framework can be used to help inform environmental exposure assessments by readily providing concentrations based on varying model inputs on WWTP removal and in-stream decay rates for microplastics, which continues to evolve as more research is conducted.
Nikki Maples-Reynolds, Chris M. Holmes, Raghu Vamshi (Waterborne), Iain A. Davies, Beth A. Lange (Personal Care Products Council), Scott Dyer (The Procter & Gamble Company). “A Framework for Dynamic Estimation of Environmental Concentrations of Microplastics in WWTP Effluents and Receiving Waters at a National Scale.” Presentation. SETAC NA. 2016.
Application of a Population Model for a Threatened Plant Species in Herbicide Risk Assessment
Extrapolating from organism-level endpoints, as generated from standard pesticide toxicity tests, to populations is an important step in threatened and endangered species risk assessments. Population modeling approaches can be used as tools to estimate potential risk from pesticides to sensitive populations by integrating multiple sub-lethal and lethal effects simultaneously and by accounting for differences in species’ life histories.
We apply a population model for a threatened herbaceous plant species, Boltonia decurrens, to estimate the potential population-level impacts of different herbicides. We combine conservative in-habitat exposure scenarios with dose-response curves for growth and survival of standard test species, and apply those in the species-specific model. In the model, a yearly herbicide exposure from drift is linked to dose-response curves derived from vegetative vigor tests and affects established plants. Dose-response curves derived from seedling emergence tests are applied to model the effects of exposure from herbicides transported via runoff to emerging seedlings. Exposures are distributed across the simulated habitat applying the RegDISP model for spray drift, and a combination of the Pesticide Root Zone Model (PRZM) and the Vegetative Filter Strip Model (VFSMOD) for runoff. The distributed exposure modeling approach makes it possible to assess potential effects of herbicides on plant populations growing in habitats that border chemical use areas/fields and can be used to assess the effectiveness of mitigation measures such as in-field spray buffer zones.
We show that responses of organism-level endpoints are not proportional to modeled population-level effects of pesticides. Specifically, comparison of dose-response curves from standard toxicity test species with the output of the population model demonstrates that the most sensitive organism-level endpoint is not predictive of population-level impacts. In addition, the model results suggest that in-field spray buffer zones can considerably reduce potential effects on populations of B. decurrens growing at the edge of a field. Our case study presents how species-specific population models can be applied in pesticide risk assessment bringing organism-level endpoints, exposure assumptions and species characteristics together in an ecologically relevant context.
Amelie Schmolke, Dan Perkins, Amy Ritter, Dean Desmarteau (Waterborne), Richard Brain (Syngenta), Pernille Thorbek (Syngenta), Valery E. Forbes (University of Minnesota). “Application of a Population Model for a Threatened Plant Species in Herbicide Risk Assessment.” Presentation. SETAC NA. 2016.
Papers & ReportsCrop Protection2016
Population Modeling for Pesticide Risk Assessment of Threatened Species – A Case Study of a Terrestrial Plant, Boltonia decurrens
Although population models are recognized as necessary tools in the ecological risk assessment of pesticides, particularly for species listed under the Endangered Species Act, their application in this context is currently limited to very few cases. The authors developed a detailed individual-based population model for a threatened plant species, the decurrent false aster (Boltonia decurrens), for application in pesticide risk assessment. Floods and competition with other plant species are known factors that drive the species’ population dynamics and were included in the model approach. The authors use the model to compare the population-level effects of five toxicity surrogates applied to B. decurrens under varying environmental conditions. The model results suggest that the environmental conditions under which herbicide applications occur may have a higher impact on populations than organism-level sensitivities to an herbicide within a realistic range. Indirect effects may be as important as the direct effects of herbicide applications by shifting competition strength if competing species have different sensitivities to the herbicide. The model approach provides a case study for population-level risk assessments of listed species. Population-level effects of herbicides can be assessed in a realistic and species-specific context, and uncertainties can be addressed explicitly. The authors discuss how our approach can inform the future development and application of modeling for population-level risk assessments of listed species, and ecological risk assessment in general. This article is protected by copyright.
Schmolke, A., Brain, R., Thorbek, P., Perkins, D. and Forbes, V. (2016), Population modeling for pesticide risk assessment of threatened species – A case study of a terrestrial plant, Boltonia decurrens. Environ Toxicol Chem. Accepted Author
Monitoring Approaches to Provide Temporal and Spatial Context to Residential Pesticide Occurrence in the American River
- Session title: Environmental Fate & Modeling of Agriculturally-Related Chemicals
- Presentation type: Poster
- Presentation room: Regency Ballroom B on display from 1:00PM – 5:00PM
- Presentation date: Monday, August 22, 2016
- Presenting Author: Greg Goodwin
Extensive urban stream and river monitoring for residential use pyrethroids has been conducted in California over the last few years and detectable residues of potential concern have been measured in some samples. Unfortunately, most of these monitoring programs have been based on simple grab sampling and have reported whole water residues; as a result, the temporal and spatial context of biologically relevant pyrethroid residues remains unknown. Consequently, a program was designed to address these questions by employing a spatially robust monitoring design at 8 locations down the length of the lower American River. The design specified multiple replicate sample collection across a variety of time scales (hourly to multi-day) during several dry weather and rainfall driven monitoring events over a 3-year period. Both discrete and depth-integrated water column samples were collected at each location with associated measurements of flow rate, depth and suspended solids concentrations. Both cross-sectional and Lagrangian sampling techniques were utilized, providing spatial characterization both within a river cross-section as well as longitudinally up and down a river reach. Analyses quantified pyrethroid residues and TOC co-occurrence. This rich long-term monitoring dataset, combined with GIS approaches allows a detailed analysis of residential pesticide residue occurrence in space and time and provides context for the program results which show that while higher pyrethroid residues do occasionally occur during storm events they are spatially confined, transient (on a time-scale of a few hours), rapidly diluted and heavily modified by the presence of dissolved and particulate organic matter. This work also allows data from other monitoring programs and publications to be put into context.
Greg Goodwin (Waterborne Environmental), Stephen Clark (Pacific EcoRisk), Gary Mitchell (FMC), Scott Jackson (BASF Corporation), Chris Harbourt (Agrible), Paul Hendley (Phasera Ltd.). “Monitoring Approaches to Provide Temporal and Spatial Context to Residential Pesticide Occurrence in the American River”. Poster. ACS 2016.
Predicting Pesticide Biphasic Soil Concentration Decline Under Field Conditions: Model-Data Comparison
- Session title: Subsurface Fate of Pesticides
- Presentation type: Presentation
- Presentation room: Commonwealth Hall A2 at 9:45AM
- Presentation date: Thursday, August 25, 2016
- Presenting Author: Dazhi Mao
As part of the NAFTA degradation kinetics calculation process, the Double First-Order in Parallel (DFOP) model is considered along with the Single First Order (SFO) and the Intermediate Order Rate Equation (IORE). However, only SFO kinetics are represented in pesticide fate regulatory modeling tools like the Pesticide Root Zone Model (PRZM), thus hindering the model’s capability of simulating chemicals with biphasic degradation characteristics. We have recently incorporated DFOP into synPRZM, a PRZM-based environmental fate model as an additional option to the sorption kinetics developed by Syngenta and Waterborne for predicting field soil residue declines. The model codes in synPRZM treat the chemical under simulation as two separate fractions which are determined by the DFOP degradation kinetics, with each fraction having a distinct degradation rate constant. Both fractions are simulated simultaneously each day, and the sum of their results is output as a whole for the chemical. Using DFOP parameters independently measured in laboratory soil metabolism studies, synPRZM was able to predict a number of field soil residue data sets reasonably well without elaborated calibration. Predicted soil pore water concentrations from synPRZM are compared with measured data from field lysimeters. The robust performance of synPRZM demonstrates the model’s predictive capability as a useful and pragmatic option to handle biphasic degradation behavior frequently observed in pesticide field studies.
Dazhi Mao* (Waterborne Environmental), Wenlin Chen (Syngenta Crop Protection), Mark Cheplick (Waterborne Environmental). “Predicting Pesticide Biphasic Soil Concentration Decline Under Field Conditions: Model-Data Comparison”. Presentation. ACS 2016.