Air Quality Modeling in Support of the Near-Road Exposures and Effects of Urban Air Pollutants Study (NEXUS)

International Journal of Environmental Research and Public Health

Vlad Isakov¹  Saravanan Arunachalam²  Stuart Batterman³  Sarah Bereznicki¹  Janet Burke¹  Kathie Dionisio¹  Val Garcia¹  David Heist¹  Steve Perry¹  Michelle Snyder² 

[1] National Exposure Research Laboratory, United States Environmental Protection Agency, 109 T.W. Alexander Drive, Research Triangle Park, NC 27711 USA; E-Mails:;Institute for the Environment, University of North Carolina at Chapel Hill, 100 Europa Drive, Chapel Hill, NC 27517, USA; E-Mails:;Department of Environmental Health Sciences, School of Public Health, University of Michigan, Room 6075 SPH2, 1420 Washington Heights, Ann Arbor, MI 48109-2029 USA; E-Mail:

关键词: dispersion modeling;    air pollution;    exposure;    traffic;   

DOI  :  10.3390/ijerph110908777

来源: mdpi

【 摘 要 】

A major challenge in traffic-related air pollution exposure studies is the lack of information regarding pollutant exposure characterization. Air quality modeling can provide spatially and temporally varying exposure estimates for examining relationships between traffic-related air pollutants and adverse health outcomes. A hybrid air quality modeling approach was used to estimate exposure to traffic-related air pollutants in support of the Near-Road Exposures and Effects of Urban Air Pollutants Study (NEXUS) conducted in Detroit (Michigan, USA). Model-based exposure metrics, associated with local variations of emissions and meteorology, were estimated using a combination of the American Meteorological Society/Environmental Protection Agency Regulatory Model (AERMOD) and Research LINE-source dispersion model for near-surface releases (RLINE) dispersion models, local emission source information from the National Emissions Inventory, detailed road network locations and traffic activity, and meteorological data from the Detroit City Airport. The regional background contribution was estimated using a combination of the Community Multi-scale Air Quality (CMAQ) and the Space-Time Ordinary Kriging (STOK) models. To capture the near-road pollutant gradients, refined “mini-grids” of model receptors were placed around participant homes. Exposure metrics for CO, NO_x, PM_2.5 and its components (elemental and organic carbon) were predicted at each home location for multiple time periods including daily and rush hours. The exposure metrics were evaluated for their ability to characterize the spatial and temporal variations of multiple ambient air pollutants compared to measurements across the study area.

【 授权许可】

CC BY   
© 2014 by the authors; licensee MDPI, Basel, Switzerland.