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Linking Air Land & Water to Examine the Vulnerability of Groundwater Nitrate Contamination from Increased Corn Production
Garcia, V., E. Cooter, B. Hayes, M. Murphy, J. Bash, AND K. Foley. Linking Air Land & Water to Examine the Vulnerability of Groundwater Nitrate Contamination from Increased Corn Production. Presented at AGU Fall Meeting, San Francisco, CA, December 09 - 13, 2013.
The Renewable Fuel Standard (RFS) requires oil refiners to reach a target of 15 billion gallons of corn-based ethanol by 2022. However, there are concerns that the broad-scale use of corn as a source of ethanol may lead to unintended economic and environmental consequences. This study applies the geophysical relationships captured with linked meteorological, air quality and agriculture models to examine the impact of corn production before enactment of the RFS in 2002 and at the height of the RFS targets in 2022. In particular, we investigate the probability of high-levels of nitrate in groundwater resulting from increased corn production and then relate this vulnerability to the potential for infants to acquire Methemoglobinemia, or “Blue Baby Syndrome”. Blue Baby Syndrome (BBS) is a potentially fatal condition that occurs when the hemoglobin (Fe2+) in an infant's red blood cells is oxidized to methemoglobin (Fe3+), preventing the uptake of oxygen from the baby’s blood. Exposure to high levels of nitrate in groundwater occur near the intersection of areas where surface water can more readily leach into shallow aquifers, wells are the main source of drinking water, and high nitrogen inputs exist. We use a coupled meteorological, agricultural and air quality model to identify areas vulnerable to increased nitrate contamination and associated risk to acquiring BBS. We first verify the relationship between predictive variables (e.g., nitrogen deposition and fertilization rates, landcover, soils and aquifer type) and nitrate groundwater levels by applying a regression model to over 800 nitrate measurements taken from wells located throughout the US (Figure 1). We then apply the regression coefficients to the coupled model output to identify areas that are at an increased risk for high nitrate groundwater levels in 2022. Finally, we examine the potential change in risk for acquiring BBS resulting from increased corn production by applying an Oral Reference Dose (RfD) factor from the US EPA Integrated Risk Information System
The National Exposure Research Laboratory (NERL) Atmospheric Modeling and Analysis Division (AMAD) conducts research in support of EPA mission to protect human health and the environment. AMAD research program is engaged in developing and evaluating predictive atmospheric models on all spatial and temporal scales for forecasting the 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.
URLs/Downloads:AGU DEC 2013_REVISED_FINAL.PPTX
Record Details:Record Type: DOCUMENT (PRESENTATION/POSTER)
Organization:U.S. ENVIRONMENTAL PROTECTION AGENCY
OFFICE OF RESEARCH AND DEVELOPMENT
NATIONAL EXPOSURE RESEARCH LAB
ATMOSPHERIC MODELING DIVISION
AIR-SURFACE PROCESSES MODELING BRANCH