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The Evaluation of Alternative Exposure Metrics for Traffic-related Air Pollutant Exposure in North Carolina
Citation:
Chang, S., W. Vizuete, V. Isakov, M. Breen, AND S. Arunachalam. The Evaluation of Alternative Exposure Metrics for Traffic-related Air Pollutant Exposure in North Carolina. International Society for Exposure Science (ISES) Annual Conf, Henderson, NV, October 19 - 22, 2015.
Impact/Purpose:
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
Description:
Transportation plays an important role in the modern society but can cause significant health impacts. To quantify the associated health impacts, an appropriate traffic-related air pollution exposure metric is required. In this study, we evaluate the suitability of four exposure metrics for traffic related air pollutants. Metrics including 1) Measurements from central monitoring sites, 2) Indoor concentration combining air exchange rate (AER) and central monitoring sites, 3) Ambient concentration from a hybrid model with dispersion modeling and central monitoring, and 4) Indoor concentration combining the hybrid model in 3) and AER will be evaluated. Hourly traffic-related air pollutant concentration fields will be estimated using the Research LINE source model (R-LINE) and regional background concentration will be estimated with central monitoring data using space-time ordinary kriging (STOK) in three counties (Durham, Orange, and Wake Counties) in the State of North Carolina at Census block level. Hourly central monitoring data are collected from Air Quality System and Chemical Speciation Network. Hourly AER is estimated with the mechanistic Lawrence Berkeley Laboratory (LBL) AER model. We use data from the property assessment records in the three counties for building story height, year built, and floor area; and 2013 American Community Survey (ACS) for fraction of low-income to calculate AER. Using the most sophisticated metric (i.e. Metric 4) as the standard, we will evaluate the feasibility of the four exposure metrics based on the mean and variation of the exposure estimate. Also, we will evaluate the suitability of these metrics with regards to distance from roadways, to evaluate spatial gradients in near-road exposures
