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Long-term exposure and health risk assessment from air pollution: impact of regional scale mobility

BACKGROUND: The negative effect of air pollution on human health is widely reported in recent literature. It typically involves urbanized areas where the population is concentrated and where most primary air pollutants are produced. A comprehensive health risk assessment is therefore of strategic im...

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Autores principales: Gilardi, Lorenza, Marconcini, Mattia, Metz-Marconcini, Annekatrin, Esch, Thomas, Erbertseder, Thilo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10196305/
https://www.ncbi.nlm.nih.gov/pubmed/37208713
http://dx.doi.org/10.1186/s12942-023-00333-8
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author Gilardi, Lorenza
Marconcini, Mattia
Metz-Marconcini, Annekatrin
Esch, Thomas
Erbertseder, Thilo
author_facet Gilardi, Lorenza
Marconcini, Mattia
Metz-Marconcini, Annekatrin
Esch, Thomas
Erbertseder, Thilo
author_sort Gilardi, Lorenza
collection PubMed
description BACKGROUND: The negative effect of air pollution on human health is widely reported in recent literature. It typically involves urbanized areas where the population is concentrated and where most primary air pollutants are produced. A comprehensive health risk assessment is therefore of strategic importance for health authorities. METHODS: In this study we propose a methodology to perform an indirect and retrospective health risk assessment of all-cause mortality associated with long-term exposure to particulate matter less than 2.5 microns (PM(2.5)), nitrogen dioxide (NO(2)) and ozone (O(3)) in a typical Monday to Friday working week. A combination of satellite-based settlement data, model-based air pollution data, land use, demographics and regional scale mobility, allowed to examine the effect of population mobility and pollutants daily variations on the health risk. A Health Risk Increase (HRI) metric was derived on the basis of three components: hazard, exposure and vulnerability, utilizing the relative risk values from the World Health Organization. An additional metric, the Health Burden (HB) was formulated, which accounts for the total number of people exposed to a certain risk level. RESULTS: The effect of regional mobility patterns on the HRI metric was assessed, resulting in an increased HRI associated with all three stressors when considering a dynamic population compared to a static one. The effect of diurnal variation of pollutants was only observed for NO(2) and O(3). For both, the HRI metric resulted in significantly higher values during night. Concerning the HB parameter, we identified the commuting flows of the population as the main driver in the resulting metric. CONCLUSIONS: This indirect exposure assessment methodology provides tools to support policy makers and health authorities in planning intervention and mitigation measures. The study was carried out in Lombardy, Italy, one of the most polluted regions in Europe, but the incorporation of satellite data makes our approach valuable for studying global health. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12942-023-00333-8.
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spelling pubmed-101963052023-05-20 Long-term exposure and health risk assessment from air pollution: impact of regional scale mobility Gilardi, Lorenza Marconcini, Mattia Metz-Marconcini, Annekatrin Esch, Thomas Erbertseder, Thilo Int J Health Geogr Research BACKGROUND: The negative effect of air pollution on human health is widely reported in recent literature. It typically involves urbanized areas where the population is concentrated and where most primary air pollutants are produced. A comprehensive health risk assessment is therefore of strategic importance for health authorities. METHODS: In this study we propose a methodology to perform an indirect and retrospective health risk assessment of all-cause mortality associated with long-term exposure to particulate matter less than 2.5 microns (PM(2.5)), nitrogen dioxide (NO(2)) and ozone (O(3)) in a typical Monday to Friday working week. A combination of satellite-based settlement data, model-based air pollution data, land use, demographics and regional scale mobility, allowed to examine the effect of population mobility and pollutants daily variations on the health risk. A Health Risk Increase (HRI) metric was derived on the basis of three components: hazard, exposure and vulnerability, utilizing the relative risk values from the World Health Organization. An additional metric, the Health Burden (HB) was formulated, which accounts for the total number of people exposed to a certain risk level. RESULTS: The effect of regional mobility patterns on the HRI metric was assessed, resulting in an increased HRI associated with all three stressors when considering a dynamic population compared to a static one. The effect of diurnal variation of pollutants was only observed for NO(2) and O(3). For both, the HRI metric resulted in significantly higher values during night. Concerning the HB parameter, we identified the commuting flows of the population as the main driver in the resulting metric. CONCLUSIONS: This indirect exposure assessment methodology provides tools to support policy makers and health authorities in planning intervention and mitigation measures. The study was carried out in Lombardy, Italy, one of the most polluted regions in Europe, but the incorporation of satellite data makes our approach valuable for studying global health. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12942-023-00333-8. BioMed Central 2023-05-19 /pmc/articles/PMC10196305/ /pubmed/37208713 http://dx.doi.org/10.1186/s12942-023-00333-8 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Gilardi, Lorenza
Marconcini, Mattia
Metz-Marconcini, Annekatrin
Esch, Thomas
Erbertseder, Thilo
Long-term exposure and health risk assessment from air pollution: impact of regional scale mobility
title Long-term exposure and health risk assessment from air pollution: impact of regional scale mobility
title_full Long-term exposure and health risk assessment from air pollution: impact of regional scale mobility
title_fullStr Long-term exposure and health risk assessment from air pollution: impact of regional scale mobility
title_full_unstemmed Long-term exposure and health risk assessment from air pollution: impact of regional scale mobility
title_short Long-term exposure and health risk assessment from air pollution: impact of regional scale mobility
title_sort long-term exposure and health risk assessment from air pollution: impact of regional scale mobility
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10196305/
https://www.ncbi.nlm.nih.gov/pubmed/37208713
http://dx.doi.org/10.1186/s12942-023-00333-8
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