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Characterization of Source-Specific Air Pollution Exposure for a Large Population-Based Swiss Cohort (SAPALDIA)
BACKGROUND: 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. METHODS: We evaluated total and traffic-specific particulate matter < 10 and < 2....
Autores principales: | , , , , , , , |
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Formato: | Texto |
Lenguaje: | English |
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National Institute of Environmental Health Sciences
2007
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2072852/ https://www.ncbi.nlm.nih.gov/pubmed/18007997 http://dx.doi.org/10.1289/ehp.10177 |
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author | Liu, L.-J. Sally Curjuric, Ivan Keidel, Dirk Heldstab, Jürg Künzli, Nino Bayer-Oglesby, Lucy Ackermann-Liebrich, Ursula Schindler, Christian |
author_facet | Liu, L.-J. Sally Curjuric, Ivan Keidel, Dirk Heldstab, Jürg Künzli, Nino Bayer-Oglesby, Lucy Ackermann-Liebrich, Ursula Schindler, Christian |
author_sort | Liu, L.-J. Sally |
collection | PubMed |
description | BACKGROUND: 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. METHODS: We evaluated total and traffic-specific particulate matter < 10 and < 2.5 μm in aero-dynamic diameter (PM(10), PM(2.5)), 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’ historical and cumulative exposures with a temporal trend model. RESULTS: Modeled PM(10) and NO(2) predicted at least 55% and 72% of the variability of the measured PM(10) and NO(2), respectively. Traffic-specific pollution estimates correlated with the NO(x) measurements (R(2) ≥0.77) for background sites but not for traffic sites. Regional background PM(10) accounted for most PM(10) mass in all cities. Whereas traffic PM(10) accounted for < 20% of the total PM(10), it varied significantly within cities. The modeling error for PM(10) was similar within and between cities. Traffic NO(x) accounted for the majority of NO(x) mass in urban areas, whereas background NO(x) accounted for the majority of NO(x) in rural areas. The within-city NO(2) modeling error was larger than that between cities. CONCLUSIONS: The dispersion model predicted well the total PM(10), NO(x), and NO(2) and traffic-specific pollution at background sites. However, the model underpredicted traffic NO(x) and NO(2) at traffic sites and needs refinement to reflect local conditions. The dispersion model predictions for PM(10) are suitable for examining individual exposures and health effects within and between cities. |
format | Text |
id | pubmed-2072852 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2007 |
publisher | National Institute of Environmental Health Sciences |
record_format | MEDLINE/PubMed |
spelling | pubmed-20728522007-11-14 Characterization of Source-Specific Air Pollution Exposure for a Large Population-Based Swiss Cohort (SAPALDIA) Liu, L.-J. Sally Curjuric, Ivan Keidel, Dirk Heldstab, Jürg Künzli, Nino Bayer-Oglesby, Lucy Ackermann-Liebrich, Ursula Schindler, Christian Environ Health Perspect Research BACKGROUND: 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. METHODS: We evaluated total and traffic-specific particulate matter < 10 and < 2.5 μm in aero-dynamic diameter (PM(10), PM(2.5)), 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’ historical and cumulative exposures with a temporal trend model. RESULTS: Modeled PM(10) and NO(2) predicted at least 55% and 72% of the variability of the measured PM(10) and NO(2), respectively. Traffic-specific pollution estimates correlated with the NO(x) measurements (R(2) ≥0.77) for background sites but not for traffic sites. Regional background PM(10) accounted for most PM(10) mass in all cities. Whereas traffic PM(10) accounted for < 20% of the total PM(10), it varied significantly within cities. The modeling error for PM(10) was similar within and between cities. Traffic NO(x) accounted for the majority of NO(x) mass in urban areas, whereas background NO(x) accounted for the majority of NO(x) in rural areas. The within-city NO(2) modeling error was larger than that between cities. CONCLUSIONS: The dispersion model predicted well the total PM(10), NO(x), and NO(2) and traffic-specific pollution at background sites. However, the model underpredicted traffic NO(x) and NO(2) at traffic sites and needs refinement to reflect local conditions. The dispersion model predictions for PM(10) are suitable for examining individual exposures and health effects within and between cities. National Institute of Environmental Health Sciences 2007-11 2007-08-14 /pmc/articles/PMC2072852/ /pubmed/18007997 http://dx.doi.org/10.1289/ehp.10177 Text en http://creativecommons.org/publicdomain/mark/1.0/ Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright. |
spellingShingle | Research Liu, L.-J. Sally Curjuric, Ivan Keidel, Dirk Heldstab, Jürg Künzli, Nino Bayer-Oglesby, Lucy Ackermann-Liebrich, Ursula Schindler, Christian Characterization of Source-Specific Air Pollution Exposure for a Large Population-Based Swiss Cohort (SAPALDIA) |
title | Characterization of Source-Specific Air Pollution Exposure for a Large Population-Based Swiss Cohort (SAPALDIA) |
title_full | Characterization of Source-Specific Air Pollution Exposure for a Large Population-Based Swiss Cohort (SAPALDIA) |
title_fullStr | Characterization of Source-Specific Air Pollution Exposure for a Large Population-Based Swiss Cohort (SAPALDIA) |
title_full_unstemmed | Characterization of Source-Specific Air Pollution Exposure for a Large Population-Based Swiss Cohort (SAPALDIA) |
title_short | Characterization of Source-Specific Air Pollution Exposure for a Large Population-Based Swiss Cohort (SAPALDIA) |
title_sort | characterization of source-specific air pollution exposure for a large population-based swiss cohort (sapaldia) |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2072852/ https://www.ncbi.nlm.nih.gov/pubmed/18007997 http://dx.doi.org/10.1289/ehp.10177 |
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