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Using a Coupled Modelling System to Examine the Impacts of Increased Corn Production on Groundwater Quality and Human Health
Citation:
Garcia, V., E. Cooter, J. Bash, M. Murphy, Tim Wade, AND X. Xing. Using a Coupled Modelling System to Examine the Impacts of Increased Corn Production on Groundwater Quality and Human Health. Chapter 18, Air Pollution Modeling and its Application XXIV. Springer International Publishing AG, Cham (ZG), Switzerland, , 113-117, (2016).
Impact/Purpose:
The National Exposure Research Laboratory’s Atmospheric Modeling Division (AMAD) conducts research in support of EPA’s mission to protect human health and the environment. AMAD’s research program is engaged in developing and evaluating predictive atmospheric models on all spatial and temporal scales for forecasting the Nation’s air quality and for assessing changes in air quality and air pollutant exposures, as affected by changes in ecosystem management and regulatory decisions. AMAD is responsible for providing a sound scientific and technical basis for regulatory policies based on air quality models to improve ambient air quality. The models developed by AMAD are being used by EPA, NOAA, and the air pollution community in understanding and forecasting not only the magnitude of the air pollution problem, but also in developing emission control policies and regulations for air quality improvements.
Description:
Attributing nitrogen (N) in the environment to emissions from agricultural management practices is difficult because of the complex and inter-related chemical and biological reactions associated with N and its cascading effects across land, air and water. Such analyses are critical, however, in understanding the benefits and disbenefits associated with environmental management options. Coupled physical models present new opportunities to understand relationships among environmental variables across multiple sources, pathways and scenarios. Because they trace the environmental fate of pollutant concentrations found in the environment through first-principle physical and chemical processes, they shed new light on these complex interactions and how they will respond under various management scenarios. In this study, we use a coupled modeling system to holistically assess the impacts of increased corn production on groundwater and air quality. In particular, we show how the models provide new information on the drivers for contamination in groundwater and air, and then relate pollutant concentration changes attributed to potential changes in corn production between 2002 and 2022 to health and cost outcomes.
