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Monosodium methanearsonate (MSMA), a sodium salt of monomethylarsonic acid (MMA), is a selective contact herbicide used for the control of a broad spectrum of weeds. In water, MSMA dissociates to ions of sodium (Na+) and monomethylarsonate (MMA-) that is stable and does not transform abiotically. In soils characteristic of MSMA use, several simultaneous processes can occur: (1) microbial methylation of MMA to dimethylarsinic acid (DMA), (2) microbial demethylation of MMA to inorganic arsenic (iAs), (3) methylation of iAs to MMA, and (4) sorption and sequestration of MMA and its metabolites to soil minerals. Sequestered residues are residues that cannot be desorbed from soil in environmental conditions. Sequestration is rapid in the initial several days after MSMA application and continues at a progressively slower rate over time. Once sequestered, MMA and its metabolites are inaccessible to soil microorganisms and cannot be transformed. The rate and extent of the sorption and sequestration as well as the mobility of MMA and its metabolites depend on the local edaphic conditions. In typical MSMA use areas, the variability of the edaphic conditions is constrained. The goal of this research was to estimate the amount of iAs potentially added to drinking water as a result of the use of MSMA, with models and scenarios developed by the US Environmental Protection Agency for pesticide risk assessment. In this project, the estimated drinking water concentrations (EDWCs) for iAs were assessed as the average concentration in the reservoir over a 30-year simulation with annual applications of MSMA at maximum label rates. When the total area of suitable land was assumed to be treated, EDWCs ranged from <0.001 to 0.12 µg/L. When high estimates of actually treated acreage are considered, the EDWCs are below 0.06 µg/L across all scenarios. Integr Environ Assess Manag 2024;00:1-12. © 2024 The Author(s). Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

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Estimating exposure in receiving waterbodies is a key step in the regulatory process to evaluate potential ecological risks posed by the use of agricultural pesticides. The United States Environmental Protection Agency (USEPA) currently uses the Variable Volume Water Model (VVWM) to predict environmental concentrations of pesticides in static waterbodies (ponds) that receive edge-of-field runoff inputs from the Pesticide Root Zone Model (PRZM). This regulatory model, however, does not adequately characterize potential pesticide concentrations in flowing water systems (streams and rivers) drained from watershed areas. This study aims at addressing this gap by coupling the regulatory PRZM model with a watershed-level hydrological model, the Soil and Water Assessment Tool (SWAT), to predict pesticide concentrations in flowing water habitats for aquatic organisms. This coupled PRZM-SWAT model was applied in a test watershed (~HUC12), a headwater watershed of Goodwater Creek in Missouri, and simulation results at the outlet of this watershed were compared to daily and near-daily measured streamflow and atrazine concentration data from a decade-long sampling campaign. Overall, the PRZM-SWAT model captured (1) the general magnitude and temporal trend of daily atrazine concentrations, (2) the observed high-end of exposure levels (>3 ppb) of atrazine concentrations, and (3) the 90th centile annual maximum for various exposure durations (1-, 4-, 7-, 21-, and 60-day rolling average), which are important exposure metrics used in assessing the potential ecological risks posed by the application of pesticides. The PRZM-SWAT model is expected to expand the utility of the field-scale regulatory model to include pesticide exposure prediction capability in flowing waterbodies from agricultural watersheds. Integr Environ Assess Manag 2022;18:1678-1693. © 2022 SETAC.

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Watershed exposure caused by the use of pesticide in farmland has become a major environmental concern. Currently, there are two major approaches to quantify the watershed exposure: monitoring and modeling. Watershed monitoring is expensive, and short-term monitoring is difficult to be used to address potential long-term exposure variability. Model simulation is widely used because not only can it save time and efforts, but it can also simulate the environmental transport process of pesticide over a long time frame to better understand temporal variability. Research on application of commonly used pesticide exposure assessment models such as PRZM, RICEWQ on watershed scale has found that those models need to be coupled together with waterbody models to assess pesticide exposure at the watershed level, and they are applied on a single crop in targeted area within a watershed, failing to consider the diversity of regional and watershed cropping conditions. To address pesticide exposure assessment in different waterbodies after application on multiple crops within a watershed, this study coupled PRZM, RICEWQ, and SWAT models simultaneously in North Tiaoxi watershed. PRZM model and RICEWQ model were used to simulate the exposure of pesticides in dryland and rice paddies separately, and the pesticide masses through runoff, overflow, spray drift, and other routes simulated by the above two models were set as the input of SWAT model which could simulate hydrology and pollutant transport at watershed scale. Pesticide use, cropping, hydrology, and watershed data were collected, and parameterized for exposure modeling of carbaryl in the North Tiaoxi River after uses on orchard, corn, and rice within the watershed. Model predictions showed high degree of agreement between the simulated results and the field monitoring data. The coupled PRZM, RICEWQ, and SWAT model could simulate reasonably well pesticide exposures in waterbodies with applications on multiple crops within a watershed.

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The use of Nitrogen (N) fertilizer boosted crop production to accommodate 7 billion people on Earth in the 20th century but with the consequence of exacerbating N losses from agricultural landscapes. Land management practices that can prevent high N load are constantly being sought for mitigation and conservation purposes. This study was aimed at evaluating the impacts of different land management practices under projected climate scenarios on surface runoff linked N load at the field scale level. A framework to analyze changes in N load at a high spatiotemporal resolution under high greenhouse emission climate projections was developed using the Pesticide Root Zone Model (PRZM) for the Willow Creek Watershed in the Fort Cobb Experimental Watershed in Oklahoma. Specifically, 12 combinations of land management and climate scenarios were evaluated based on their N load via surface runoff from 2020 to 2070. Results showed that crop rotation practices lowered both the N load and the probability of high N load events. Spring application reduced the negative effects in summer and fall from other land management practices but at the risk of increased probability of generating high N load in April and May. The fertilizer application rate was found to be the most critical factor that affected the amount and the probability of high N load events. By adopting a target application management approach, the monthly maximum N can be decreased by 13% while the annual mean N load by 6%. The model framework and analysis method developed in this research can be used to analyze tradeoffs between environmental welfare and economic benefits of N fertilizer at the field scale level.

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Wheat crops and the major wheat-growing regions of the United States are not included in the 6 crop- and region-specific scenarios developed by the US Environmental Protection Agency (USEPA) for exposure modeling with the Pesticide Root Zone Model conceptualized for groundwater (PRZM-GW). The present work augments the current scenarios by defining appropriately vulnerable PRZM-GW scenarios for high-producing spring and winter wheat-growing regions that are appropriate for use in refined pesticide exposure assessments. Initial screening-level modeling was conducted for all wheat areas across the conterminous United States as defined by multiple years of the Cropland Data Layer land-use data set. Soil, weather, groundwater temperature, evaporation depth, and crop growth and management practices were characterized for each wheat area from publicly and nationally available data sets and converted to input parameters for PRZM. Approximately 150 000 unique combinations of weather, soil, and input parameters were simulated with PRZM for an herbicide applied for postemergence weed control in wheat. The resulting postbreakthrough average herbicide concentrations in a theoretical shallow aquifer were ranked to identify states with the largest regions of relatively vulnerable wheat areas. For these states, input parameters resulting in near 90th percentile postbreakthrough average concentrations corresponding to significant wheat areas with shallow depth to groundwater formed the basis for 4 new spring wheat scenarios and 4 new winter wheat scenarios to be used in PRZM-GW simulations. Spring wheat scenarios were identified in North Dakota, Montana, Washington, and Texas. Winter wheat scenarios were identified in Oklahoma, Texas, Kansas, and Colorado. Compared to the USEPA's original 6 scenarios, postbreakthrough average herbicide concentrations in the new scenarios were lower than all but Florida Potato and Georgia Coastal Peanuts of the original scenarios and better represented regions dominated by wheat crops. Integr Environ Assess Manag 2017;13:992-1006. © 2017 The Authors. Integrated Environmental Assessment and Management Published by Wiley Periodicals, Inc. on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

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Within the European Union the exposure of aquatic organisms to pesticides is assessed by simulations with the so-called FOCUS Surface Water Scenarios. Runoff plays an important role in these scenarios. As little is known about the effect of runoff size on the exposure, we investigated the effect of runoff size on the concentration in the runoff water and in streams simulated with the PRZM and TOXSWA models for two FOCUS runoff scenarios. For weakly sorbing pesticides (KF,oc<100Lkg-1) the pesticide concentration in the runoff water decreased exponentially with increasing daily runoff size. The runoff size hardly affected the pesticide concentration in the runoff water of strongly sorbing pesticides (KF,oc≥1000Lkg-1). For weakly sorbing pesticides the concentration in the FOCUS stream reached a maximum at runoff sizes of about 0.3 to 1mm. The concentration increased rapidly when the runoff size increased from 0 to 0.1mm and gradually decreased when runoff exceeded 1mm. For strongly sorbing pesticides the occurrence of the maximum concentration in the stream is clearly less pronounced and lies approximately between 1 and 20mm runoff. So, this work indicates that preventing small runoff events (e.g. by vegetated buffer strips) reduces exposure concentrations strongly for weakly sorbing pesticides. A simple metamodel was developed for the ratio between the concentrations in the stream and in the runoff water. This model predicted the ratios simulated by TOXSWA very well and it demonstrated that (in addition to runoff size and concentration in runoff) the size of the pesticide-free base flow and pesticide treatment ratio of the catchment determine the stream concentration to a large extent.

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Two categories of pesticide soil models now exist. Government regulatory agencies use pesticide fate and transport hydrology models, including versions of PRZM.gw. They have good descriptions of pesticide transport by water flow. Their descriptions of chemical mechanisms are unrealistic, having been postulated using the universally accepted but incorrect pesticide soil science. The objective of this work is to report experimental tests of a pesticide soil model in use by regulatory agencies and to suggest possible improvements. Tests with experimentally based data explain why PRZM.gw predictions can be wrong by orders of magnitude. Predictive spreadsheet models are the other category. They are experimentally based, with chemical stoichiometry applied to integral kinetic rate laws for sorption, desorption, intra-particle diffusion, and chemical reactions. They do not account for pesticide transport through soils. Each category of models therefore lacks what the other could provide. They need to be either harmonized or replaced. Some preliminary tests indicate that an experimental mismatch between the categories of models will have to be resolved. Reports of pesticides in the environment and the medical problems that overlap geographically indicate that government regulatory practice needs to account for chemical kinetics and mechanisms. Questions about possible cause and effect links could then be investigated.

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Pesticide transport by surface runoff depends on climate, agricultural practices, topography, soil characteristics, crop type, and pest phenology. To accurately assess the impact of climate change, these factors must be accounted for in a single framework by integrating their interaction and uncertainty. This article presents the development and application of a framework to assess the impact of climate change on pesticide transport by surface runoff in southern Québec (Canada) for the 1981-2040 period. The crop enemies investigated were: weeds for corn (Zea mays); and for apple orchard (Malus pumila), 3 insect pests (codling moth [Cydia pomonella], plum curculio [Conotrachelus nenuphar], and apple maggot [Rhagoletis pomonella]), 2 diseases (apple scab [Venturia inaequalis], and fire blight [Erwinia amylovora]). A total of 23 climate simulations, 19 sites, and 11 active ingredients were considered. The relationship between climate and phenology was accounted for by bioclimatic models of the Computer Centre for Agricultural Pest Forecasting (CIPRA) software. Exported loads of pesticides were evaluated at the edge-of-field scale using the Pesticide Root Zone Model (PRZM), simulating both hydrology and chemical transport. A stochastic model was developed to account for PRZM parameter uncertainty. Results of this study indicate that for the 2011-2040 period, application dates would be advanced from 3 to 7 days on average with respect to the 1981-2010 period. However, the impact of climate change on maximum daily rainfall during the application window is not statistically significant, mainly due to the high variability of extreme rainfall events. Hence, for the studied sites and crop enemies considered, climate change impact on pesticide transported in surface runoff is not statistically significant throughout the 2011-2040 period. Integr Environ Assess Managem 2016;12:559-571. © Her Majesty the Queen in Right of Canada 2015; Published 2015 SETAC.

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The performance of the pesticide fate model PRZM to predict the fate of two fungicides, penconazole and metalaxyl, and the major metabolite of metalaxyl (CGA-62826), in amended and unamended vineyard soils was tested from undisturbed soils columns experiments. Three different treatments were tested in two soils: control soil (unamended), and soil amended with fresh or composted spent mushroom substrates, which correspond to common agricultural practices in Spain. Leaching experiments were performed under non-saturated flow conditions. The model was parameterized with laboratory and literature data, and using pedotransfer functions. It was first calibrated for water flow against chloride breakthrough curves. The key parameter was the hydrodynamic dispersion coefficient (DISP). No leaching of penconazole, the most hydrophobic fungicide, was observed. It remained in the top 0-8 cm of the column. In any case, simulations were highly correlated to the experimental results. On the contrary, metalaxyl and its metabolite were consistently found in the leachates. A calibration step of the Kd of metalaxyl and CGA-62826 and of DISP for CGA-62826 was necessary to obtain good prediction of the leaching of both compounds. PRZM generally simulated acceptable metalaxyl vertical distribution in the soil profiles although results were overestimated for its metabolite. Nevertheless, PRZM can be reasonably used to assess the leaching (through breakthrough curves) and vertical distribution of fungicides in amended soils, knowing their DISP values.

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