4.8 Article

Characterization of Annual Average Traffic-Related Air Pollution Concentrations in the Greater Seattle Area from a Year-Long Mobile Monitoring Campaign

期刊

ENVIRONMENTAL SCIENCE & TECHNOLOGY
卷 56, 期 16, 页码 11460-11472

出版社

AMER CHEMICAL SOC
DOI: 10.1021/acs.est.2c01077

关键词

mobile monitoring; air pollution; particle number count (PNC); ultrafine particles (UFP); black carbon (BC); nitrogen dioxide (NO2); exposure assessment; epidemiology

资金

  1. Adult Changes in Thought-Air Pollution (ACT-AP) Study (National Institute of Environmental Health Sciences [NIEHS], National Institute on Aging) [R01ES026187]
  2. BEBTEH: Biostatistics, Epidemiologic, & Bioinformatic Training in Environmental Health (NIEHS) [T32ES015459]
  3. University of Washington Interdisciplinary Center for Exposure, Disease, Genomics, & Environment (NIEHS) [2P30 ES007033-26]
  4. United States Environmental Protection Agency (EPA) [CR-83998101]

向作者/读者索取更多资源

Growing evidence suggests that traffic-related air pollution (TRAP) has adverse health effects. This study designed an innovative and extensive mobile monitoring campaign to characterize TRAP exposure levels for the Adult Changes in Thought (ACT) study in Seattle. The results showed that the campaign effectively captured the spatial variations of air pollutants, which were explained by land use features related to traffic.
Growing evidence links traffic-related air pollution (TRAP) to adverse health effects. We designed an innovative and extensive mobile monitoring campaign to characterize TRAP exposure levels for the Adult Changes in Thought (ACT) study, a Seattle-based cohort. The campaign measured particle number concentration (PNC) to capture ultrafine particles (UFP), black carbon (BC), nitrogen dioxide (NO2), fine particulate matter (PM2.5), and carbon dioxide (CO2) at 309 roadside sites within a large, 1200 land km(2) (463 mi(2)) area representative of the cohort. We collected about 29 two-minute measurements at each site during all seasons, days of the week, and most times of the day over a 1-year period. Validation showed good agreement between our BC, NO2, and PM2.5 measurements and monitoring agency sites (R-2 = 0.68-0.73). Universal kriging-partial least squares models of annual average pollutant concentrations had cross-validated mean square error-based R-2 (and root mean square error) values of 0.77 (1177 pt/cm(3)) for PNC, 0.60 (102 ng/m(3)) for BC, 0.77 (1.3 ppb) for NO2, 0.70 (0.3 mu g/m(3)) for PM2.5, and 0.51 (4.2 ppm) for CO2. Overall, we found that the design of this extensive campaign captured the spatial pollutant variations well and these were explained by sensible land use features, including those related to traffic.

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