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Commuting-Adjusted Short-Term Health Impact Assessment of Airborne Fine Particles with Uncertainty Quantification via Monte Carlo Simulation
Background: Exposure to air pollution is associated with a short-term increase in mortality, and this field has begun to focus on health impact assessment. Objectives: Our aim was to estimate the impact of PM(10) on mortality within 2 days from the exposure in the Italian region of Lombardy for the...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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NLM-Export
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4286278/ https://www.ncbi.nlm.nih.gov/pubmed/25325518 http://dx.doi.org/10.1289/ehp.1408218 |
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author | Baccini, Michela Grisotto, Laura Catelan, Dolores Consonni, Dario Bertazzi, Pier Alberto Biggeri, Annibale |
author_facet | Baccini, Michela Grisotto, Laura Catelan, Dolores Consonni, Dario Bertazzi, Pier Alberto Biggeri, Annibale |
author_sort | Baccini, Michela |
collection | PubMed |
description | Background: Exposure to air pollution is associated with a short-term increase in mortality, and this field has begun to focus on health impact assessment. Objectives: Our aim was to estimate the impact of PM(10) on mortality within 2 days from the exposure in the Italian region of Lombardy for the year 2007, at the municipality level, examining exposure entailed by daily intermunicipality commuting and accounting for uncertainty propagation. Methods: We combined data from different sources to derive probabilistic distributions for all input quantities used to calculate attributable deaths (mortality rates, PM(10) concentrations, estimated PM(10) effects, and commuting flows) and applied a Monte Carlo procedure to propagate uncertainty and sample the distribution of attributable deaths for each municipality. Results: We estimated that annual average PM(10) concentrations above the World Health Organization-recommended threshold of 20 μg/m(3) were responsible for 865 short-term deaths (80% credibility interval: 475, 1,401), 26% of which were attributable to PM(10) above the European Union limit of 40 μg/m(3). Reducing annual average PM(10) concentrations > 20 μg/m(3) by 20% would have reduced the number of attributable deaths by 36%. The largest estimated impacts were along the basin of the Po River and in the largest cities. Commuting contributed to the spatial distribution of the estimated impact. Conclusions: Our estimates, which incorporated uncertainty quantification, indicate that the short-term impact of PM(10) on mortality in Lombardy in 2007 was notable, and that reduction in air pollution would have had a substantial beneficial effect on population health. Using commuting data helped to identify critical areas for prioritizing intervention. Citation: Baccini M, Grisotto L, Catelan D, Consonni D, Bertazzi PA, Biggeri A. 2015. Commuting-adjusted short-term health impact assessment of airborne fine particles with uncertainty quantification via Monte Carlo simulation. Environ Health Perspect 123:27–33; http://dx.doi.org/10.1289/ehp.1408218 |
format | Online Article Text |
id | pubmed-4286278 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | NLM-Export |
record_format | MEDLINE/PubMed |
spelling | pubmed-42862782015-01-13 Commuting-Adjusted Short-Term Health Impact Assessment of Airborne Fine Particles with Uncertainty Quantification via Monte Carlo Simulation Baccini, Michela Grisotto, Laura Catelan, Dolores Consonni, Dario Bertazzi, Pier Alberto Biggeri, Annibale Environ Health Perspect Research Background: Exposure to air pollution is associated with a short-term increase in mortality, and this field has begun to focus on health impact assessment. Objectives: Our aim was to estimate the impact of PM(10) on mortality within 2 days from the exposure in the Italian region of Lombardy for the year 2007, at the municipality level, examining exposure entailed by daily intermunicipality commuting and accounting for uncertainty propagation. Methods: We combined data from different sources to derive probabilistic distributions for all input quantities used to calculate attributable deaths (mortality rates, PM(10) concentrations, estimated PM(10) effects, and commuting flows) and applied a Monte Carlo procedure to propagate uncertainty and sample the distribution of attributable deaths for each municipality. Results: We estimated that annual average PM(10) concentrations above the World Health Organization-recommended threshold of 20 μg/m(3) were responsible for 865 short-term deaths (80% credibility interval: 475, 1,401), 26% of which were attributable to PM(10) above the European Union limit of 40 μg/m(3). Reducing annual average PM(10) concentrations > 20 μg/m(3) by 20% would have reduced the number of attributable deaths by 36%. The largest estimated impacts were along the basin of the Po River and in the largest cities. Commuting contributed to the spatial distribution of the estimated impact. Conclusions: Our estimates, which incorporated uncertainty quantification, indicate that the short-term impact of PM(10) on mortality in Lombardy in 2007 was notable, and that reduction in air pollution would have had a substantial beneficial effect on population health. Using commuting data helped to identify critical areas for prioritizing intervention. Citation: Baccini M, Grisotto L, Catelan D, Consonni D, Bertazzi PA, Biggeri A. 2015. Commuting-adjusted short-term health impact assessment of airborne fine particles with uncertainty quantification via Monte Carlo simulation. Environ Health Perspect 123:27–33; http://dx.doi.org/10.1289/ehp.1408218 NLM-Export 2014-10-17 2015-01 /pmc/articles/PMC4286278/ /pubmed/25325518 http://dx.doi.org/10.1289/ehp.1408218 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 Baccini, Michela Grisotto, Laura Catelan, Dolores Consonni, Dario Bertazzi, Pier Alberto Biggeri, Annibale Commuting-Adjusted Short-Term Health Impact Assessment of Airborne Fine Particles with Uncertainty Quantification via Monte Carlo Simulation |
title | Commuting-Adjusted Short-Term Health Impact Assessment of Airborne Fine Particles with Uncertainty Quantification via Monte Carlo Simulation |
title_full | Commuting-Adjusted Short-Term Health Impact Assessment of Airborne Fine Particles with Uncertainty Quantification via Monte Carlo Simulation |
title_fullStr | Commuting-Adjusted Short-Term Health Impact Assessment of Airborne Fine Particles with Uncertainty Quantification via Monte Carlo Simulation |
title_full_unstemmed | Commuting-Adjusted Short-Term Health Impact Assessment of Airborne Fine Particles with Uncertainty Quantification via Monte Carlo Simulation |
title_short | Commuting-Adjusted Short-Term Health Impact Assessment of Airborne Fine Particles with Uncertainty Quantification via Monte Carlo Simulation |
title_sort | commuting-adjusted short-term health impact assessment of airborne fine particles with uncertainty quantification via monte carlo simulation |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4286278/ https://www.ncbi.nlm.nih.gov/pubmed/25325518 http://dx.doi.org/10.1289/ehp.1408218 |
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