High-resolution modeling of residential outdoor particulate levels in Sweden

Large-scale exposure assessments that include both between- and within-city differences in air pollution levels are lacking. The objective of this study was to model long-term particle exposure for the whole of Sweden, separating long-range transport from local sources, which were further separated into combustion and road dust. Annual regional, urban and local traffic PM exposure contributions were modeled for 26,000 addresses from a national survey, using a European scale model, an urban model and a local traffic model. Total PM10 was overall dominated by the regional contribution, ranging from 3.5 mu g/m(3) (northernmost) to 13.5 mu g/m(3) (southernmost). Local traffic and urban sources contributed nationally on average to 16% of total PM10, but for urban populations this contribution was larger (for Stockholm around 30%). Generalized to the Swedish adult population, the average residential exposure contributions from regional, urban and local traffic PM10 were 10.2, 1.3 and 0.2 mu g/m(3), respectively. Corresponding exposure to PM, was 5.1, 0.5 and 0.03 mu g/m(3), respectively. Long-range transport dominates average Swedish residential PM1 and PM10 levels, but for urban populations the contributions from urban and local traffic sources are important and may even dominate for residences close to heavily trafficked roads. The study shows the importance of considering both national and city-scale gradients. The approach to exposure modeling at home addresses of a Swedish cohort includes both the regional scale and the urban and local traffic contributions to total PM exposure. With this we can resolve both between- and within-city gradients in national exposure assessments. The within-city exposure is further divided into a submicron (combustion) and a supermicron (road dust generated by studded tires) part. This gives new possibilities to study health impacts of different particles generated in Scandinavian cities. Journal of Exposure Science and Environmental Epidemiology (2013) 23, 306-314; doi:10.1038/jes.2012.122; published online 23 January 2013