期刊
ATMOSPHERIC ENVIRONMENT
卷 41, 期 35, 页码 7500-7511出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.atmosenv.2007.05.039
关键词
long term; exposure; air pollution; geographic information system; traffic; land-use regression modeling; spatial variability
Traffic is a major source of air pollutants in urban environments, and exposure to these pollutants may be associated with adverse health effects. However, inconsistencies in observational epidemiological studies may be caused by differential measurement errors in various approaches in assessing exposure. We aimed to evaluate a simple method for assessing outdoor air pollutant concentrations in Oslo, Norway, through a land-use regression method. Samples of nitrogen oxides (NOx) were collected in two different weeks using Ogawa passive diffusion samplers simultaneously at 80 locations across Oslo. Independent variables used in subsequent regression models as predictors of the pollutants were derived using the Arc 9 geographic information system (GIS) software. indicators of land use, traffic, population density, and physical geography were tested. The final regression model yielded an adjusted coefficient of determination (R-2) of 0.77 for nitrogen dioxide (NO2), 0.66 for nitric oxide (NO), and 0.73 for NOx. The results suggest that a good predictive exposure model can be derived from this approach, which can be used to estimate long-term small-area variation in concentrations for individual exposure assessment in epidemiological studies in a highly cost-effective way. These small-area variations in traffic pollution are important since they may have associations with health effects. (C) 2007 Elsevier Ltd. All rights reserved.
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