Traffic, which has been steadily increasing over the past two decades, represents an important local source of air pollution, with """"""""local"""""""" most likely encompassing a smaller area (e.g., ~500 m to 1 km neighborhood-scale) than is represented by a typical National Air Quality Network monitoring site. Environmental Protection Agency (EPA) monitoring sites are intended to represent human exposure on an urban-scale (e.g., 4 to 100 km). With the economic pressure to use more efficient fuel (i.e. diesel fuel) levels of traffic-related markers, such as nitrogen dioxide (NO2) and elemental carbon (EC) will likely rise resulting in an increased risk for respiratory effects in sensitive populations. Traffic-related pollutants, including NO2 and EC-containing particle pollution, have been associated with adverse health effects, and NO2 is a criteria pollutant monitored by the EPA. Between 1994 and 2000, over 1,100 children and 2,300 women participated in our prospective cohort studies of respiratory health conducted in Connecticut and central Massachusetts, a region including areas that have been and remain in """"""""non-attainment"""""""" with EPA air quality standards. For analyses of the health effects of air pollution we have had to rely on the high quality, but spatially limited pollutant data measured at EPA air quality monitoring sites. In spite of this limitation, we have demonstrated adverse respiratory health effects with the temporal variability of pollution: e.g., risk of daily symptoms and/or medication use among asthmatic children with increases in daily levels of air pollution. Using Geographic Information Systems (GIS) technology and data from a variety of spatially-related sources, we propose to develop estimates of traffic-generated pollutants with higher spatial and temporal resolution than measurements from EPA monitors can provide. Our goal is to estimate levels of pollution due to traffic within buffers (e.g. a 500 m radius) around a residence within a neighborhood, i.e., residential-scale pollution levels. We plan to capture background pollution levels due to regional sources using estimates of NO2 and EC within larger exposure areas (12x12 km grids - approx. 100 grids in our 14,600 km2 study area) produced by an integrated meteorologic emissions model that includes regional traffic, land use, meteorology, topography, and emissions sources. The primary aim of this study is to use our improved exposure estimates to examine the impact of traffic-generated pollution on respiratory health in the Northeast using our substantial archive of health information. Infants, young children and pregnant asthmatic women, groups represented in our study populations, may be especially sensitive to air pollution. The novelty of our project is the first ever use of pollutant estimates from sophisticated atmospheric models to study the effects short-term exposure to air pollution on respiratory morbidity. The strengths of our proposed research include both improvements in exposure estimation techniques that can be applied to large epidemiological studies, and use of these exposure estimates in the analysis of respiratory health effects.
The exposure assessment techniques developed as a result of this project will advance the field of exposure estimation in epidemiological studies of air pollution and provide an important tool for assessing the public health impact of traffic. Improved health effect estimates should provide important information for how well current air quality standards protect sensitive populations in our region.
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