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Community-Based Decision-Making: Application of Web-Based Near-Road Modeling System to Newport News, Virginia
Citation:
Barzyk, T., J. Essoka, T. Blount, E. Holloman, A. Harris, B. Naess, K. Crawford, AND G. Besa. Community-Based Decision-Making: Application of Web-Based Near-Road Modeling System to Newport News, Virginia. ISES Annual Meeting, Henderson, NV, Henderson, NV, October 18 - 23, 2015.
Impact/Purpose:
The National Exposure Research Laboratory (NERL) Human Exposure and Atmospheric Sciences Division (HEASD) conducts research in support of EPA mission to protect human health and the environment. HEASD research program supports Goal 1 (Clean Air) and Goal 4 (Healthy People) of EPA strategic plan. More specifically, our division conducts research to characterize the movement of pollutants from the source to contact with humans. Our multidisciplinary research program produces Methods, Measurements, and Models to identify relationships between and characterize processes that link source emissions, environmental concentrations, human exposures, and target-tissue dose. The impact of these tools is improved regulatory programs and policies for EPA.
Description:
Living, working, and going to school near roadways has been associated with a number of adverse health effects, including asthma exacerbation, cardiovascular impairment, and respiratory symptoms. In the United States, 30% - 45% of urban populations live or work in the near-road environment, with a greater percentage of minority and low-income residents living in areas with highly- trafficked roadways. Near-road studies typically use surrogates of exposure to evaluate potential causality of health effects, including proximity, traffic counts, or total length of roads within a given radius. In contrast, simplified models provide an opportunity to examine how changes in input parameters, such as vehicle counts or speeds, can affect air quality. Simplified or reduced-form models typically retain the same or similar algorithms most responsible for characterizing uncertainty in more sophisticated models. The Community Line Source modeling system (C-LINE) allows users to explore what-if scenarios such as increases in diesel trucks or total traffic; examine hot spot conditions and areas for further study; determine ideal monitor placement locations; or evaluate air quality changes due to traffic re-routing. This presentation describes the input parameters, analytical procedures, visualization routines, and software considerations for C-LINE, and an example application for Newport News, Virginia. Results include scenarios related to port development and resulting traffic changes. Areas and populations with potentially high impacts are identified, and differences in air toxics concentrations for the what-if scenarios are examined. These outputs are being used to identify potential risk reduction options for the neighboring communities, and to evaluate near-road impacts in the context of multiple other environmental health stressors, such as port emissions and coal ash.
