ACS Fall 2023

Join Waterborne Environmental at the upcoming ACS Fall 2023: Harnessing the Power of Data conference from August 13th-17th, 2023 in San Francisco, CA! We're sending a cotillion of experts who will present short courses and papers (abstracts below), and meet with colleagues within the industry. For information about scheduling a meeting during the event, please contact Andy Jacobson.

Upcoming Events
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Waterborne Talks

Sunday, August 13, 2023, 8:55-9:20AM, Room 3022, West Bldg. (Moscone Center)

Title: Machine learning to integrate environmental mechanistic modeling and water quality monitoring for pesticides. Zechariah Stone, Presenter; Yaoxing WuDavid DreierLula GhebremichaelNick GeitnerAndy Jacobson; Wenlin Chen

Abstract: Environmental mechanistic modeling and water quality monitoring both play a critical role in pesticide regulatory assessments. Standard scenario-based mechanistic models such as the U.S. Environmental Protection Agency (EPA) Pesticide Water Calculators (PWC) are almost exclusively used for ecological and drinking water exposure assessments. Surface water monitoring data when satisfying certain data quality criteria can be used in the new EPA pesticide drinking water assessment paradigm through a time-series regression (SEAWAVE-QEX). These two approaches (i.e., scenario-based PWC and monitoring-based SEAWAVE-QEX) are implemented in tiers, but little attempt has been made to connect them, resulting in limited opportunity for pesticides and watersheds without or with less abundant monitoring data for high tier refinements. In this paper, we propose and show how the data-driven Machine Learning (ML) model can aid connecting a mechanistic model PWC with water monitoring data and bring in real watershed scale drivers into the refinement of water exposure predictions. We used the high-quality, high-frequency water monitoring data collected in the U.S. that meets the SEAWAVE-QEX criteria during 2001-2019 to train and test the ML model. Daily (or interpolated) monitoring observations were used to calculate average exposure at various intervals between 1 day, 4 days, 21 days, 60 days or one year for each monitoring year, which served as target variable in ML modeling. Environmental predictions of scenario-based models (PWC) were incorporated into the ML datasets as proxy feature variables which reflect the insight of the mechanistic processes of chemical fate and transport and other variables including physico-chemical properties and label-prescribed use patterns. Scenario-based models, however, may or may not accurately represent the specific watershed scale fate and transport processes. This gap between standard PWC environmental scenarios and watershed-specific features, such as weather profiles, county-level annual pesticide application rate, land use, soil characteristics, and stream flow rate, are bridged through ML modeling. Model performance is evaluated by cross validation and statistical criteria. Examples of mapping national-level atrazine concentration in surface water are provided and compared with results of U.S.EPA Watershed Regressions for Pesticides (WARP) model.

Sunday, August 13, 2023, 2:05-2:30PM, Room 3016, West Bldg. (Moscone Center)

Title: Novel remote sensing approach for estimating field-scale crop planting and pesticide application timing. Nick Guth, Presenter; Andy JacobsonZechariah StoneRichard Brain

Abstract: Pesticide modeling plays a key role to characterize pesticide exposures in surface waters; however, the performance of such models can be limited by the uncertainty of their data inputs. One source of uncertainty is knowledge of the application timing of pesticide use since exact application timing is often unavailable. Due to recent improvements in satellite imagery, both in resolution and re-visit period, we propose to estimate crop planting dates as a proxy to pesticide application timing for pre-emergent and early post emergent corn herbicides using the Sentinel-2 satellite imagery driven normalized difference vegetation index (NDVI) and the relationship between Growing Degree Days (GDD) and corn growth stages. To evaluate the performance of this framework, field data on corn planting dates were collected from several Midwestern U.S. corn fields during the crop growth seasons from 2018 to 2022. Using this field data as ground truth data, the accuracy of the remote sensing approach for estimating field-scale crop planting and pesticide application timing will be evaluated.

Sunday, August 13, 2023, 2:30-2:55PM, Room 3016, West Bldg. (Moscone Center)

Title: PWC-PREP Tool: A user-friendly tool to facilitate preparation of label-compliant Pesticide in Water Calculator (PWC) batch input files. Logan Insinga, Presenter; Steve KayDean Desmarteau

Abstract:The USEPA’s Pesticide in Water Calculator (PWC) simulates pesticide applications to land surfaces and subsequent transport to and fate in waterbodies. When using PWC, one significant issue is accurately modeling pesticides as they typically have diverse uses and restrictions that vary based on the use site, region, and time of year. These uses and restrictions are codified in the product label and can be highly interrelated with many permutations of potential applications. Therefore, defining conservative yet label-compliant use-patterns can be difficult and time consuming. Failure to account for all labeled agronomic restrictions including total pesticide amount applied and number of application limitations on an annual and interval specific (e.g., pre-emergence or post-emergence) basis, as well as multiple application rates with rate-specific limitations (i.e., number of applications and temporal windows), minimum reapplication intervals, and pre-harvest intervals can lead to modeling of non-label-compliant or unrealistic application use patterns. In addition, efforts to ensure modeling is conservative (e.g., simulation of applications during wettest months of the year or maximizing total amount applied in a year) can significantly complicate application date assignment logic. To address these difficulties, the Generic Endangered Species Task Force (GESTF) has developed the PWC-PREP Tool to facilitate batch file preparation for PWC modeling. Specifically, the PWC-PREP Tool features a robust algorithm that generates label-compliant application dates and rates for a wide variety of use sites, regions, and chemicals. Leveraging a graphical user interface, the tool is highly configurable and allows the user to control modeling parameters related to application methods, drift factors, agronomic restrictions, and date-assignment. The PWC-PREP Tool to has been successfully used to efficiently parameterize a national set of PWC runs (n > 30,000) that follow label instructions in a manner that is transparent and can be repeated.

Monday, August 14, 2023, 9:50 - 10:15AM, Room 3016, West Bldg. (Moscone Center)

Title: What is the appropriate sampling frequency necessary for pesticide monitoring programs in flowing surface waters? An analysis using SEAWAVE-QEX. Andy Jacobson, Presenter; Zechariah StoneBrenna KentRichard Brain

Abstract: Surface water monitoring data can be invaluable for regulatory exposure assessments of pesticides as it provides context/comparison for modeled/predicted exposures. In 2019, the United States Environmental Protection Agency (USEPA) published a white paper which presented tools to quantitatively assess water monitoring data for pesticide risk assessment. Among these was the Seasonal Wave with Streamflow Adjustment with Extended Capability (SEAWAVE-QEX) model, which is a time-series model developed by the United States Geological Survey (USGS) to simulate daily pesticide concentrations in surface water using existing, non-daily monitoring data, seasonal patterns, and daily streamflow. Due to the considerable monetary costs and logistical challenges of water quality monitoring programs, including sample collection and analytical chemistry, an analysis was conducted to determine the appropriate sampling frequency, utilized in-conjunction with SEAWAVE-QEX, to accurately estimate pesticide exposures in flowing surface water. To conduct this analysis, daily monitoring data collected from watersheds in the Atrazine Ecological Monitoring Program (AEMP) were subsampled at various intervals (4-day, 7-day, 14-day, and 30-day) to evaluate the predictive performance of utilizing monitoring data collected at each sample frequency interval. The primary objective of this work is to determine the appropriate sampling frequency of pesticide monitoring data to accurately estimate exposures in flowing surface waters and ultimately inform monitoring program design and reduce the associated costs of future programs, including the continuation of the AEMP. Another objective is to demonstrate that monitoring data collected at less frequent sampling intervals is still more accurate than the USEPA’s Pesticide Water Calculator (PWC) at estimating pesticide exposures, and therefore should be utilized in national pesticide exposure assessments when available and appropriate.

Monday, August 14, 2023, 4:40-5:05PM, Room 3014, West Bldg. (Moscone Center)

Title: Inventory and review of existing agricultural best management practices for pesticides in the USA. Andy Jacobson, PresenterNick Guth; Zechariah StoneDean DesmarteauRichard Brain

Abstract: As part of the U.S. Environmental Protection Agency’s (EPA) updated 2022 Endangered Species Act (ESA) workplan, Federal Insecticide, Fungicide, and Rodenticide Act (FIFRA) Interim Ecological Mitigation, the Agency has proposed a picklist approach of runoff mitigation measures to protect listed species identified as potentially at risk from predicted pesticide exposure based on a screening-level risk assessment approach. However, it is unclear how effective the proposed mitigations are, how feasibly they can be implemented, and/or how likely they are to be adopted. A screening level risk assessment is insufficient to inform on the necessity for mitigation, and incomplete knowledge of picklist implications introduces uncertainty regarding their effectiveness to ameliorate potential risks identified under this paradigm. Moreover, this proposed process adds considerable uncertainty for growers.

To evaluate the potential ramifications of picklist mitigation measures proposed by the EPA, a database was developed to inventory existing, implemented agricultural Best Management Practices (BMPs) for pesticide runoff in the contiguous US. Sources of this database encompass management practices funded by both federal and state government agencies, including departments of agriculture and conservation. In addition, the feasibility and viability of picklist mitigation measures, which may vary due to underlying environmental conditions such as soil type, slope, land use, geographical region, and other characteristics, were evaluated. A webtool was also created to allow users to query the BMP database and map query results in relation to relevant spatial layers for endangered species’ ranges and critical habitats. Ultimately, the objectives of this work are to support refinement of the endangered species assessment process for pesticides by inventorying the existing agricultural BMPs, evaluating the potential ramifications of picklist mitigation measures proposed by the EPA, and to provide feasible BMP recommendations to farmers to support compliance with the ESA.

Monday, August 14, 2023, 4:05-5:30PM, Room 3022, West Bldg. (Moscone Center)

Title: Climate change and agriculture: AGRO’s role in ensuring sustainable agriculture. Heidi Irrig, Presenter; Pamela RiceAmy Ritter

Abstract:The chemists and scientists who comprise the American Chemical Society (ACS), Agrochemical Division (AGRO), are consciously addressing issues facing our world and its climate. In 2015 the United Nations (UN) established 17 Sustainable Development Goals (SDG) to protect the planet and improve the lives of everyone around the planet. SDG 13: “Take urgent action to combat climate change and its impacts”, will be reviewed and the current role AGRO has in addressing this goal. The evolution of AGRO meeting topics and leadership collaboration with other ACS Division will be assessed in the context of this goal. AGRO has brought complex science topics to the forefront for discussion and consideration amongst a wide variety of industry, academic and government experts for assessment. Addressing the development and use of agricultural products and technologies to ensure agricultural productivity and sustainability amongst potential climate change is a particularly relevant topic for consideration. AGRO provides a neutral forum for the various agricultural and chemical sections to evaluate the current situation and develop plans to have a positive impact on the changing world climate.

Waterborne Co-chairing Technical Symposia

Monday, August 14, 2023, 2:00 - 6:00PM, Room 3022, West Bldg. (Moscone Center)

Title: Adapting Agricultural Chemistry and Practices to a Changing Climate Authors: Patricia Engel, Organizer; Nnemeka Ihegwuagu, Organizer; Heidi Irrig, Organizer; Pamela Rice, Organizer; Amy Ritter, OrganizerFrederick Salzman, Organizer, Presider

Monday, August 14, 2023, 2:00 - 5:35PM, Room 3014, West Bldg. (Moscone Center)

Title: Pesticide Runoff Mitigation: Characterization, Quantification, and Implementation Authors: Huajin Chen, Organizer, Presider; Patrick Havens, Organizer, Presider; Philip Janney, Organizer; Amy Ritter, Organizer, Presider

Division/Committee: [AGRO] Division of Agrochemicals

This symposium will discuss advances in approaches to quantify the effectiveness of mitigation measures for pesticide runoff, characterization of mitigation measures that are currently implemented, field studies on effectiveness of runoff mitigation measures, research on new mitigation practices, and strategies to incorporate mitigations in risk assessments and management of pesticide.

Monday, August 14, 2023, 2:00 - 5:35PM, Room 3016, West Bldg. (Moscone Center)

Title: Transitioning from the Laboratory to the Landscape Challenges and Opportunities Authors: Jennifer Collins, Organizer, Presider; John Purdy, Organizer, Presider; Tom Steeger, Organizer, Presider; Katrina White, Organizer