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PresentationsCrop Protection2021

Screening-level pollinator risk assessment for trisiloxane polyether surfactants (Part II): Effects and risk characterization

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ACS 2021, AGRO Division, Zoom Room 03
Session Title: Screening-level pollinator risk assessment for trisiloxane polyether surfactants (Part II): Effects and risk characterization
Thursday, August 26, 2021, 05:25 pm – 05:50 pm USA/Canada – Eastern

The screening-level pollinator risk assessment for three trisiloxane polyether surfactants will expand on the exposure characterization presented in Part I. In this phase, the ecotoxicological effects of three trisiloxane polyether surfactants were evaluated and incorporated with the exposure characterization to evaluate risk. The US EPA model, BeeREX, was used to conduct a Tier I screening-level model assessment to generate risk quotients for comparison against levels of concern. The effects characterization included a review of endpoints from acute and chronic laboratory studies for both larval and adult stage honeybees (Apis mellifera) following published OECD test guidelines. Estimated residue concentrations calculated in Part I were compared to the relevant acute and chronic endpoints (acute 50% lethal dose, LD50 and chronic no-observed-effect dose, NOED) from several GLP toxicology studies to determine the risk quotients (RQs) for this assessment. This presentation will include a comparison of calculated RQs and to defined regulatory levels of concern for pollinator risk assessment, as well as a discussion of the uncertainty analysis.

 

J. Collins (Waterborne). Screening-level pollinator risk assessment for trisiloxane polyether surfactants (Part II): Effects and risk characterization. AGRO, ACS 2021. Virtual Meeting.

PresentationsCrop Protection2021

Screening-level pollinator risk assessment for trisiloxane polyether surfactants (Part I): Challenges and methodologies for estimating exposure of honeybees (Apis mellifera)

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ACS 2021, AGRO Division, Zoom Room 03
Session Title: Screening-level pollinator risk assessment for trisiloxane polyether surfactants (Part I): Challenges and methodologies for estimating exposure of honeybees (Apis mellifera)
Thursday, August 26, 2021, 05:00 pm – 05:25 pm USA/Canada – Eastern

The pollinator risk assessment framework laid out by US EPA, PRMA, and CDPR (2014) is primarily focused on pesticide active ingredients. In recent years, there has been increased interest in the potential impact, if any, to human health and the environment of inert ingredients (i.e., non-pesticidally active components of pesticide products) and chemical substances used as tank mix adjuvants and surfactants. Trisiloxane polyethers represent a class of superspreader surfactants with the unique ability of significantly reducing the surface tension of water to promote a rapid spreading of aqueous solutions on the surfaces of leaves. Since limited data is available regarding routes of exposure to honeybees from trisiloxanes, there are some challenges in the evaluation of exposure characterization. The objective of this presentation is to layout the challenges in the exposure characterization of three trisiloxane polyether surfactants and discuss various methodologies employed to conservatively quantify exposure for use in a screening-level pollinator risk assessment framework for these surfactants. The BeeREX Tier I screening-level risk assessment model uses maximum application rates to estimate worst-case exposure concentrations in various honeybee matrices via model default residue assumptions, for instances where available residue data are not available. The model also provides a refinement option using available residue data. The CDPR Pesticide Use Registry (PUR) database was used to determine reasonable maximum surfactant application rates, which were modeled to determine worst-case exposure rates using default residue assumptions. In addition, refined exposure estimates were determined by incorporating surfactant residues generated in a field residue study.

J. Collins (Waterborne), A. Schmolke (Waterborne)

Screening-level pollinator risk assessment for trisiloxane polyether surfactants (Part I): Challenges and methodologies for estimating exposure of honeybees (Apis mellifera) AGRO, ACS 2021

PresentationsAgriculture and Food, Crop Protection2021

Overview of the chemical degradation kinetics pathway tool and practical considerations for its application for model inputs

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ACS 2021, AGRO Division, Zoom Room 04
Session Title: Overview of the chemical degradation kinetics pathway tool and practical considerations for its application for model inputs
Monday, August 23, 2021, 10:35 am – 11:00 am USA/Canada – Eastern

Reliable chemical degradation tools for modeling kinetic pathways are imperative to conducting accurate human health and environmental risk assessments. While the EU FOCUS organization has extensive guidance for conducting the analysis and software tools have been developed in many iterations (CAKE, KinGUII, Model Maker, etc), the USEPA has not formally released tools or guidance for pathway modeling. In 2020, the USEPA included a kinetics software tool, Deg Kinetics v 2.8.2, for kinetic evaluation of chemical degradation data for applications in drinking water assessments with several evaluations. This Excel based solver serves as a useful tool for modeling single first order chemical pathways and evaluation of degradation within the pathway as an input into the typical exposure models used by USEPA, PMRA, and state agencies. This presentation will utilize the Deg Kinetics v 2.8.2 tool in the context of real-world application of the tool as a comparison of its setup, inputs, and parameter selection to that of other FOCUS typical kinetics tools. Finally, this presentation will provide an overview of methods for combining data from multiple datasets as inputs into the model framework – specifically regarding considerations with rapidly degrading parent to daughter and granddaughter compounds and the impact on model predictions.

P. Paulausky (Waterborne), A. Ritter (Waterborne), N. Snyder (Waterborne). Overview of the chemical degradation kinetics pathway tool and practical considerations for its application for model inputs. AGRO, ACS 2021, Virtual Meeting

PresentationsAgriculture and Food, Crop Protection2021

Collection of water monitoring data: Working in the spirit of GLPs

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ACS 2021, AGRO Division, Zoom Room 04
Session Title: Collection of water monitoring data: Working in the spirit of GLPs
Monday, August 23, 2021, 07:25 pm – 07:45 pm USA/Canada – Eastern

Over time the accessibility and processes used for the collection of water monitoring data has changed. The days of transcription from laboratory reports are becoming minimal and electronic data files from comprehensive databases are becoming more commonplace, which requires new approaches for data reproducibility and documentation. Over the past decade, water monitoring data have been collected under the “spirit of the GLPs” in its documentation, reproducibility, and archival. While all aspects of the GLP program are not required, critical steps throughout the data collection and processing follow the underlying principles of the GLPs. As more electronic data were collected from a variety of sources, the process of how to standardize these data increased in complexity. Challenges such as data transformation, traceability, and connections to historic data needed to be addressed to ensure data quality and to answer questions from regulators. In addition, we have continued to enhance our data processing protocols to ensure consistency in data handling, analysis, and documentation of uncertainty. For studies in which GLPs are not necessarily required by a sponsor, we explore an approach of operating under the “spirit of the GLPs” to ensure that monitoring data processes and summarization are repeatable, traceable and provide confidence around electronic data processing and archival similar to those electronic data collected under GLP programs.

J. Trask (Waterborne), L. Johnson (Waterborne), J. Crider (Waterborne)

Collection of water monitoring data: Working in the spirit of GLPs. AGRO, ACS 2021, Virtual Meeting

PresentationsAgriculture and Food, Crop Protection2021

Using GIS overlay methods to determine vulnerable agricultural areas in the Ukraine

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ACS 2021, AGRO Division, Zoom Room 02
Session Title: Using GIS overlay methods to determine vulnerable agricultural areas in the Ukraine
Monday, August 23, 2021, 05:50 pm – 06:15 pm USA/Canada – Eastern

GIS overlay methods such as vulnerability index methods are frequently used to assess the relative vulnerability of groundwater or surface water to contaminants. The application of these methods is driven in large part by data availability, and assessor expertise and familiarity. This may result in a bias in the models as certain criteria are over- or underemphasized; for example, pesticide behavior is often ignored in commonly used index methods, where environmental factors such as pH and organic carbon have been shown to affect the local vulnerability of groundwater and surface water. Furthermore, vulnerability index methods may feature subjective weights and rankings, which increases the likelihood of bias. Two new index methods using a standardized approach are introduced and applied to determine groundwater and surface water vulnerability for corn production areas in the Ukraine. For groundwater, the following parameters were included: average annual rainfall, topsoil sand content, topsoil organic carbon content, topsoil pH, drainage class and depth to groundwater. For surface water, key variables included slope, days with more than 25.4 mm of rainfall, topsoil available water capacity, topsoil organic carbon content, topsoil pH and drainage class. A weighting schema was developed for each of the variables. Weights ranged from 1 to 6, with 1 being the lowest weight and 6 being the highest weight and were based on six percentile classes. This has the advantage that the distribution of variables is accounted for and are unbiased, and that the method can be easily applied to other regions to provide a systematic and transparent assessment approach. Using this approach, the maximum vulnerability score is 36 and the results show the relative vulnerability for both groundwater and surface water. For groundwater, 12.7% of the total agricultural areas fall in the upper percentile class (>83.3%) of vulnerability and have scores 26 – 33. For surface water 13.2% of the total agricultural areas falling into the upper percentile class and have scores 26 – 35. The maximum attainable vulnerable score of 36 was not achieved in either assessment.

 

C. Hoogeweg (Waterborne), N. Peranginangin (Syngenta), R. Krueger (Waterborne), A. Ritter (Waterborne)

Using GIS overlay methods to determine vulnerable surface water areas in the Ukraine. AGRO, ACS 2021, Virtual Meeting

PresentationsAgriculture and Food, Crop Protection2021

Using GIS overlay methods to determine vulnerable surface water areas in Brazil

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ACS 2021, AGRO Division, Zoom Room 02
Session Title: Using GIS overlay methods to determine vulnerable surface water areas in Brazil
Monday, August 23, 2021 05:25 pm – 05:50 pm USA/Canada – Eastern

Brazil’s diverse agricultural landscape poses challenges to assess the impact of agricultural chemicals due to the differences in climate, unique soils, and agricultural management practices across the country. The aim of this project was to determine areas in Brazil that are currently under soybean production and potentially vulnerable to surface water runoff. Potential vulnerable areas were determined by conducting a GIS overlay of soils, climate, and topography data within likely soybean production areas. Potential vulnerable areas were defined as areas having soils with high levels of clay and rainfall with steep slopes, soils low in water holding capacity, and/or poor drainage. The results from this assessment can be used to select potential vulnerable areas for detailed exposure modeling using regulatory accepted environmental fate models. The municipalities with the highest soybean production are located in Mato Grosso (Central Brazil), Paraná, Santa Catarina and Rio Grande Do Sul in southern Brazil. The lowest runoff index was calculated to be 11 and the highest 35. Areas with lower runoff potential are found throughout Brazil and are more prevalent than high runoff potential areas. When the runoff index dataset is filtered to the soybean production areas, regions in Santa Catarina, Paraná and Goiás all have areas with a high (>27) runoff index. This indicates that compared to other soybean producing regions, these areas are more likely to be vulnerable to runoff. Only 9.24% of the soybean regions fall in the highest runoff vulnerability class, having an index of 27 or greater. The majority, 70.66%, of the areas fall within the median range of vulnerability (index 16 – 26). The frequency distribution chart of runoff vulnerability indices shows a bi-modal distribution. The theoretical highest vulnerability value of 42 was never reached in this assessment.

C. Hoogeweg (Waterborne), M. Urban (Syngenta), J. Schulze-Aurich (Syngenta), W. Phelps (Syngenta), A. Cione (Syngenta), A. Ritter (Waterborne). Using GIS overlay methods to determine vulnerable surface water areas in Brazil. AGRO, ACS 2021. Virtual Meeting

PresentationsCrop Protection2021

Modelling Ecosystems in Mesocosms: A Ring Study Approach With Four Aquatic Systems Models

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Session: Effect Modelling for Regulatory Environmental Risk Assessment of Chemicals: Where Are We and What Comes Next?

Abstract:  Aquatic systems models (ASMs) represent food-web interactions in an aquatic community and interactions with environmental conditions. Ecological models, including ASMs, are valuable tools in pesticide risk assessments because they can be applied to a range of biotic and abiotic conditions, as well as to a variety of exposure scenarios which would be impractical to test empirically. Four ASMs (Streambugs, AQUATOX, CASM, and StoLam with STREAMcom) that have been developed, published and applied in pesticide risk assessments and other contexts are the subjects of this ring study. Model inputs and outputs are compared among the ASMs, using mesocosm data generated and provided by MESOCOSM GmbH. The ASM ring study includes: a) analysis and preparation of mesocosm control and treatment data, b) definition of the food web represented across ASMs, c) parameterization of the ASMs, d) calibration of the ASMs to mesocosm control data, e) validation of the calibrated ASMs against mesocosm control data not used in the calibration, f) calibration of the ASMs to mesocosm treatment data. All steps are documented in detail, following the recommendations of the good modeling practice. We will present methods and results of the steps a) – d). We outline an approach for defining a mesocosm food web that can be represented by multiple ASMs, and the parameterization and calibration of the ASMs to the available mesocosm data. The approach provides important insights into the strengths and limitations of different ASMs for this particular modelling exercise through comparison of the model outputs with each other and with empirical data. In the next steps of the ring study, we will evaluate the ASMs using independent mesocosm data from the same test site, and simulate treatment effects for an example pesticide.

Authors: Amelie Schmolke (Waterborne), Nika Galic (Syngenta), Steven Bartell (Cardno), Isabel O’Connor (EBP), Simon Spycher (EBP), Nele Schuwirth (EAWAG), Tido Strauss (Gaiac), Damian Preziosi (Integral), Robert Pastorok (Integral), Peter Ebke (Mesocosm GmbH), Jürgen Schmidt (Mesocosm GmbH), Farah Abi-Akar (Waterborne), Jennifer Collins (Waterborne), Roman Ashauer (Syngenta).  SETAC Europe 2021.

PresentationsCrop Protection2020

An Overview of Key Features of Population Models and Their Relevance for Ecological Risk Assessment

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Session Title: 5.06 – Environmental Effects Modeling: Advances in Development and Application of Effects Models in Environmental Risk Assessment
SciCon2 5.06.01

Abstract:

The last two decades have seen substantial advances in the development of population models for the ecological risk assessment (ERA) of chemicals. These include guidance on systematic and consistent model creation and documentation, model evaluation and testing, and choosing models of appropriate complexity to address different types of risk assessment questions. A growing collection of case studies has clearly demonstrated how such models can inform risk assessment and risk management decisions, and slowly but surely there are indications that the acceptance of population models for ERA will continue to increase. Nevertheless, there remain misconceptions about population models for ERA, including confusion regarding differences among types of model formalization (e.g., differential equation, matrix or agent-based models), uncertainty surrounding the implications of including or ignoring different aspects of reality in the models, as well as a lack of consensus on the role that the models should play in the ERA process. We provide an overview of the key features that may be included in population models to inform ERAs. They include density dependence, spatial variability, external drivers, stochasticity, life history, behavior, energetics and how exposure and effects are integrated in the models. We consider why these features are relevant for ERA and how they can be incorporated into three broadly defined population model categories: unstructured, structured, and agent-based. We show that nearly all features can be included in all model categories, but some features are more or less easily incorporated in certain model types. Using a previously published database of population models, we assessed the frequency with which each of the key features has been included so far in the different model categories. We show that some features have been more strongly associated with a certain model category. The aims of the overview are to help model developers and model evaluators assess the extent to which a model and its features are fit for purpose and to increase the consistency and transparency of population models used for ERA.

C. Accolla (University of Minnesota), M. Vaugeois (University of Minnesota), V. Grimm (Helmholtz Centre for Environmental Research – UFZ), A. Schmolke (Waterborne), A. Moore (University of Minnesota), P. Rueda-Cediel  (University of Minnesota), V. Forbes (University of Minnesota)

An Overview of Key Features of Population Models and Their Relevance for Ecological Risk Assessment. SciCon2 5.06.01, SETAC 2020 Virtual Meeting.

PresentationsCrop Protection2020

Assessing the Risks of Pesticides to Terrestrial Threatened and Endangered Species: Opportunities to Refine Risk Assessments for Listed Terrestrial Plants

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Session Title: 5.04 – Endangered Species Assessments for Pesticides
SciCon2 5.04.14

Abstract:

There is a continuing need to develop improved procedures and tools for assessing pesticide risks to threatened and endangered (i.e., listed) species in the United States. As part of meeting this challenge, the TERrestrial Endangered Species Assessment (TERESA) model was developed following a tiered approach to efficiently evaluate potential pesticide exposures and risks to listed terrestrial species. The terrestrial plant version of TERESA includes the ability to evaluate risks to listed plant species based on direct effects or potential indirect pathways (e.g., effects to insect pollinators or obligate symbionts). For species that are not screened out in the first tiers of the analysis in TERESA, various refinements can be conducted to better characterize risk using information about the species and relevant product use patterns. We conducted refined case studies for a subset of listed terrestrial plant species potentially exposed to a representative insecticide. Multiple lines of evidence were evaluated including refined spatial exposure estimates based on product use information and species life history and characteristics that may influence exposure potential. Factors considered in these analyses include local use conditions, application rates and methods, temporal relationships between species and application timing and species habitat associations. Given the low direct toxicity of this pesticide to terrestrial plants, the focus is on illustrating an approach to evaluate risk to biological features upon which the listed plant species depends. The case studies highlight the importance of bringing together the most reliable and relevant information to reduce uncertainty and improve our understanding of pesticide risk to listed species.

M. Kern (Balance EcoSolutions LLC), N. Green (Waterborne), N. Snyder (Waterborne), D. Moore (Intrinsik), S. Teed (Intrinsik), C. Priest (Intrinsik), H. Rathjens (Stone Environmental), M. Winchell (Stone Environmental), T. Blickley (Eurofins EAG Agroscience Services LLC)

Assessing the Risks of Pesticides to Terrestrial Threatened and Endangered Species: Opportunities to Refine Risk Assessments for Listed Terrestrial Plants. SciCon2 5.04.14, SETAC 2020 Virtual Meeting.

PresentationsCrop Protection2020

A Tiered Approach to Efficient Refinement of Aquatic Exposure Assessments for Endangered Species

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Session Title: 5.04 – Endangered Species Assessments for Pesticides
SciCon2 5.04.08

Abstract:

Quantitative pesticide exposure and risk modeling is a powerful tool to effectively and efficiently make the important distinction between threatened and endangered species that are likely to be and not likely to be adversely affected (LAA and NLAA, respectively) as a resulted of a pesticideís labeled uses. To achieve efficiency and transparency in such assessment for aquatic species, progressive steps in exposure modeling are needed that employ the best available datasets and scientific approaches to introduce meaningful and substantial refinements. We have developed a multi-tiered approach for aquatic exposure modeling designed to meet these requirements for national scale endangered species risk assessments. The approach begins with Tier 1 which is highly conservative and represents potential high-end exposure for all species. Tier 1 accounts for a wide range of potential use patterns, cropping scenarios, application dates, and weather conditions. At Tier 2, much greater relevance of the exposure estimates for each species is achieved by accounting for the spatial overlap between pesticide exposure scenarios and species ranges and critical habitats. In Tier 2, two additional refinement steps are incorporated into the exposure modeling. The first refinement accounts for potential pesticide use sites, or percent cropped area (PCA), in estimating exposure concentrations in multiple static and flowing aquatic habitat types. PCA for large numbers of relevant water bodies within a species range are analyzed using GIS datasets and processing techniques. The second refinement step in Tier 2 is based on best available pesticide usage data. Usage data are analyzed probabilistically to generate an ensemble of pesticide usage scenarios across the US and overlaid with species ranges. This pesticide usage data refinement step results in quantitative pesticide exposure probability distributions that are then incorporated into risk assessment decisions. The two-tier methodology developed is an efficient, effective, and transparent process using best available data and scientific analysis methods that helps guide a risk assessor to making NLAA/LAA decisions in national endangered species risk assessments.

M. Winchell (Stone Environmental), H. Rathjens (Stone Environmental), S. Castro-Tanzi (Stone Environmental), J. Dunne (Stone Environmental), N. Snyder (Waterborne), P. Havens (Corteva Agriscience)

A Tiered Approach to Efficient Refinement of Aquatic Exposure Assessments for Endangered Species. SciCon2 5.04.08, SETAC 2020 Virtual Meeting.