{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,19]],"date-time":"2026-09-19T00:46:41Z","timestamp":1789778801914,"version":"4.0.1"},"reference-count":56,"publisher":"American Chemical Society (ACS)","issue":"11","license":[{"start":{"date-parts":[[2017,12,29]],"date-time":"2017-12-29T00:00:00Z","timestamp":1514505600000},"content-version":"vor","delay-in-days":3790,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2007,11,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Although the dispersion model approach has been used in some epidemiologic studies to examine health effects of traffic-specific air pollution, no study has evaluated the model predictions vigorously.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We evaluated total and traffic-specific particulate matter &amp;lt; 10 and &amp;lt; 2.5 \u03bcm in aero-dynamic diameter (PM10, PM2.5), nitrogren dioxide, and nitrogen oxide concentrations predicted by Gaussian dispersion models against fixed-site measurements at different locations, including traffic-impacted, urban-background, and alpine settings between and across cities. The model predictions were then used to estimate individual subjects\u2019 historical and cumulative exposures with a temporal trend model.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Modeled PM10 and NO2 predicted at least 55% and 72% of the variability of the measured PM10 and NO2, respectively. Traffic-specific pollution estimates correlated with the NOx measurements (R2 \u22650.77) for background sites but not for traffic sites. Regional background PM10 accounted for most PM10 mass in all cities. Whereas traffic PM10 accounted for &amp;lt; 20% of the total PM10, it varied significantly within cities. The modeling error for PM10 was similar within and between cities. Traffic NOx accounted for the majority of NOx mass in urban areas, whereas background NOx accounted for the majority of NOx in rural areas. The within-city NO2 modeling error was larger than that between cities.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>The dispersion model predicted well the total PM10, NOx, and NO2 and traffic-specific pollution at background sites. However, the model underpredicted traffic NOx and NO2 at traffic sites and needs refinement to reflect local conditions. The dispersion model predictions for PM10 are suitable for examining individual exposures and health effects within and between cities.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1289\/ehp.10177","type":"journal-article","created":{"date-parts":[[2007,8,13]],"date-time":"2007-08-13T15:48:12Z","timestamp":1187020092000},"page":"1638-1645","source":"Crossref","is-referenced-by-count":56,"title":["Characterization of Source-Specific Air Pollution Exposure for a Large Population-Based Swiss Cohort (SAPALDIA)"],"prefix":"10.1021","volume":"115","author":[{"given":"L.-J. Sally","family":"Liu","sequence":"first","affiliation":[{"name":"Institute of Social and Preventive Medicine, University of Basel, Basel, Switzerland"},{"name":"Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, Washington, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ivan","family":"Curjuric","sequence":"additional","affiliation":[{"name":"Institute of Social and Preventive Medicine, University of Basel, Basel, Switzerland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dirk","family":"Keidel","sequence":"additional","affiliation":[{"name":"Institute of Social and Preventive Medicine, University of Basel, Basel, Switzerland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"J\u00fcrg","family":"Heldstab","sequence":"additional","affiliation":[{"name":"Infras, Z\u00fcrich, Switzerland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nino","family":"K\u00fcnzli","sequence":"additional","affiliation":[{"name":"ICREA (Instituci\u00f3 Catalana de Recerca i Estudis Avan\u00e7ats) and Center for Research in Environmental Epidemiology (CREAL) at Institut Municipal d\u2019Investigaci\u00f3 M\u00e8dica (IMIM), Barcelona, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lucy","family":"Bayer-Oglesby","sequence":"additional","affiliation":[{"name":"Institute of Social and Preventive Medicine, University of Basel, Basel, Switzerland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ursula","family":"Ackermann-Liebrich","sequence":"additional","affiliation":[{"name":"Institute of Social and Preventive Medicine, University of Basel, Basel, Switzerland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Christian","family":"Schindler","sequence":"additional","affiliation":[{"name":"Institute of Social 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