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Assessment of population exposure to PM10 for respiratory disease in Lanzhou (China) and its health-related economic costs based on GIS

BACKGROUND: Evaluation of the adverse health effects of PM(10) pollution (particulate matter less than 10 microns in diameter) is very important for protecting human health and establishing pollution control policy. Population exposure estimation is the first step in formulating exposure data for qu...

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Autores principales: Sun, Zhaobin, An, Xingqin, Tao, Yan, Hou, Qing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3852930/
https://www.ncbi.nlm.nih.gov/pubmed/24069906
http://dx.doi.org/10.1186/1471-2458-13-891
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author Sun, Zhaobin
An, Xingqin
Tao, Yan
Hou, Qing
author_facet Sun, Zhaobin
An, Xingqin
Tao, Yan
Hou, Qing
author_sort Sun, Zhaobin
collection PubMed
description BACKGROUND: Evaluation of the adverse health effects of PM(10) pollution (particulate matter less than 10 microns in diameter) is very important for protecting human health and establishing pollution control policy. Population exposure estimation is the first step in formulating exposure data for quantitative assessment of harmful PM(10) pollution. METHODS: In this paper, we estimate PM(10) concentration using a spatial interpolation method on a grid with a spatial resolution 0.01° × 0.01°. PM(10) concentration data from monitoring stations are spatially interpolated, based on accurate population data in 2000 using a geographic information system. Then, an interpolated population layer is overlaid with an interpolated PM(10) concentration layer, and population exposure levels are calculated. Combined with the exposure-response function between PM(10) and health endpoints, economic costs of the adverse health effects of PM(10) pollution are analyzed. RESULTS: The results indicate that the population in Lanzhou urban areas is distributed in a narrow and long belt, and there are relatively large population spatial gradients in the XiGu, ChengGuan and QiLiHe districts. We select threshold concentration C(0) at: 0 μg m(-3) (no harmful health effects), 20 μg m(-3) (recommended by the World Health Organization), and 50 μg m(-3) (national first class standard in China) to calculate excess morbidity cases. For these three scenarios, proportions of the economic cost of PM(10) pollution-related adverse health effects relative to GDP are 0.206%, 0.194% and 0.175%, respectively. The impact of meteorological factors on PM(10) concentrations in 2000 is also analyzed. Sandstorm weather in spring, inversion layers in winter, and precipitation in summer are important factors associated with change in PM(10) concentration. CONCLUSIONS: The population distribution by exposure level shows that the majority of people live in polluted areas. With the improvement of evaluation criteria, economic damage of respiratory disease caused by PM(10) is much bigger. The health effects of Lanzhou urban residents should not be ignored. The government needs to find a better way to balance the health of residents and economy development. And balance the pros and cons before making a final policy.
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spelling pubmed-38529302013-12-16 Assessment of population exposure to PM10 for respiratory disease in Lanzhou (China) and its health-related economic costs based on GIS Sun, Zhaobin An, Xingqin Tao, Yan Hou, Qing BMC Public Health Research Article BACKGROUND: Evaluation of the adverse health effects of PM(10) pollution (particulate matter less than 10 microns in diameter) is very important for protecting human health and establishing pollution control policy. Population exposure estimation is the first step in formulating exposure data for quantitative assessment of harmful PM(10) pollution. METHODS: In this paper, we estimate PM(10) concentration using a spatial interpolation method on a grid with a spatial resolution 0.01° × 0.01°. PM(10) concentration data from monitoring stations are spatially interpolated, based on accurate population data in 2000 using a geographic information system. Then, an interpolated population layer is overlaid with an interpolated PM(10) concentration layer, and population exposure levels are calculated. Combined with the exposure-response function between PM(10) and health endpoints, economic costs of the adverse health effects of PM(10) pollution are analyzed. RESULTS: The results indicate that the population in Lanzhou urban areas is distributed in a narrow and long belt, and there are relatively large population spatial gradients in the XiGu, ChengGuan and QiLiHe districts. We select threshold concentration C(0) at: 0 μg m(-3) (no harmful health effects), 20 μg m(-3) (recommended by the World Health Organization), and 50 μg m(-3) (national first class standard in China) to calculate excess morbidity cases. For these three scenarios, proportions of the economic cost of PM(10) pollution-related adverse health effects relative to GDP are 0.206%, 0.194% and 0.175%, respectively. The impact of meteorological factors on PM(10) concentrations in 2000 is also analyzed. Sandstorm weather in spring, inversion layers in winter, and precipitation in summer are important factors associated with change in PM(10) concentration. CONCLUSIONS: The population distribution by exposure level shows that the majority of people live in polluted areas. With the improvement of evaluation criteria, economic damage of respiratory disease caused by PM(10) is much bigger. The health effects of Lanzhou urban residents should not be ignored. The government needs to find a better way to balance the health of residents and economy development. And balance the pros and cons before making a final policy. BioMed Central 2013-09-27 /pmc/articles/PMC3852930/ /pubmed/24069906 http://dx.doi.org/10.1186/1471-2458-13-891 Text en Copyright © 2013 Sun et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Sun, Zhaobin
An, Xingqin
Tao, Yan
Hou, Qing
Assessment of population exposure to PM10 for respiratory disease in Lanzhou (China) and its health-related economic costs based on GIS
title Assessment of population exposure to PM10 for respiratory disease in Lanzhou (China) and its health-related economic costs based on GIS
title_full Assessment of population exposure to PM10 for respiratory disease in Lanzhou (China) and its health-related economic costs based on GIS
title_fullStr Assessment of population exposure to PM10 for respiratory disease in Lanzhou (China) and its health-related economic costs based on GIS
title_full_unstemmed Assessment of population exposure to PM10 for respiratory disease in Lanzhou (China) and its health-related economic costs based on GIS
title_short Assessment of population exposure to PM10 for respiratory disease in Lanzhou (China) and its health-related economic costs based on GIS
title_sort assessment of population exposure to pm10 for respiratory disease in lanzhou (china) and its health-related economic costs based on gis
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3852930/
https://www.ncbi.nlm.nih.gov/pubmed/24069906
http://dx.doi.org/10.1186/1471-2458-13-891
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