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Spatiotemporal Assessment of PM(2.5)-Related Economic Losses from Health Impacts during 2014–2016 in China
Background: Particulate air pollution, especially PM(2.5), is highly correlated with various adverse health impacts and, ultimately, economic losses for society, however, few studies have undertaken a spatiotemporal assessment of PM(2.5)-related economic losses from health impacts covering all of th...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6024949/ https://www.ncbi.nlm.nih.gov/pubmed/29914184 http://dx.doi.org/10.3390/ijerph15061278 |
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author | Yang, Yang Luo, Liwen Song, Chao Yin, Hao Yang, Jintao |
author_facet | Yang, Yang Luo, Liwen Song, Chao Yin, Hao Yang, Jintao |
author_sort | Yang, Yang |
collection | PubMed |
description | Background: Particulate air pollution, especially PM(2.5), is highly correlated with various adverse health impacts and, ultimately, economic losses for society, however, few studies have undertaken a spatiotemporal assessment of PM(2.5)-related economic losses from health impacts covering all of the main cities in China. Methods: PM(2.5) concentration data were retrieved for 190 Chinese cities for the period 2014–2016. We used a log-linear exposure–response model and monetary valuation methods, such as value of a statistical life (VSL), amended human capital (AHC), and cost of illness to evaluate PM(2.5)-related economic losses from health impacts at the city level. In addition, Monte Carlo simulation was used to analyze uncertainty. Results: The average economic loss was 0.3% (AHC) to 1% (VSL) of the total gross domestic product (GDP) of 190 Chinese cities from 2014 to 2016. Overall, China experienced a downward trend in total economic losses over the three-year period, but the Beijing–Tianjin–Hebei, Shandong Peninsula, Yangtze River Delta, and Chengdu-Chongqing regions experienced greater annual economic losses. Conclusions: Exploration of spatiotemporal variations in PM(2.5)-related economic losses from long-term health impacts could provide new information for policymakers regarding priority areas for PM(2.5) pollution prevention and control in China. |
format | Online Article Text |
id | pubmed-6024949 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-60249492018-07-16 Spatiotemporal Assessment of PM(2.5)-Related Economic Losses from Health Impacts during 2014–2016 in China Yang, Yang Luo, Liwen Song, Chao Yin, Hao Yang, Jintao Int J Environ Res Public Health Article Background: Particulate air pollution, especially PM(2.5), is highly correlated with various adverse health impacts and, ultimately, economic losses for society, however, few studies have undertaken a spatiotemporal assessment of PM(2.5)-related economic losses from health impacts covering all of the main cities in China. Methods: PM(2.5) concentration data were retrieved for 190 Chinese cities for the period 2014–2016. We used a log-linear exposure–response model and monetary valuation methods, such as value of a statistical life (VSL), amended human capital (AHC), and cost of illness to evaluate PM(2.5)-related economic losses from health impacts at the city level. In addition, Monte Carlo simulation was used to analyze uncertainty. Results: The average economic loss was 0.3% (AHC) to 1% (VSL) of the total gross domestic product (GDP) of 190 Chinese cities from 2014 to 2016. Overall, China experienced a downward trend in total economic losses over the three-year period, but the Beijing–Tianjin–Hebei, Shandong Peninsula, Yangtze River Delta, and Chengdu-Chongqing regions experienced greater annual economic losses. Conclusions: Exploration of spatiotemporal variations in PM(2.5)-related economic losses from long-term health impacts could provide new information for policymakers regarding priority areas for PM(2.5) pollution prevention and control in China. MDPI 2018-06-16 2018-06 /pmc/articles/PMC6024949/ /pubmed/29914184 http://dx.doi.org/10.3390/ijerph15061278 Text en © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Yang, Yang Luo, Liwen Song, Chao Yin, Hao Yang, Jintao Spatiotemporal Assessment of PM(2.5)-Related Economic Losses from Health Impacts during 2014–2016 in China |
title | Spatiotemporal Assessment of PM(2.5)-Related Economic Losses from Health Impacts during 2014–2016 in China |
title_full | Spatiotemporal Assessment of PM(2.5)-Related Economic Losses from Health Impacts during 2014–2016 in China |
title_fullStr | Spatiotemporal Assessment of PM(2.5)-Related Economic Losses from Health Impacts during 2014–2016 in China |
title_full_unstemmed | Spatiotemporal Assessment of PM(2.5)-Related Economic Losses from Health Impacts during 2014–2016 in China |
title_short | Spatiotemporal Assessment of PM(2.5)-Related Economic Losses from Health Impacts during 2014–2016 in China |
title_sort | spatiotemporal assessment of pm(2.5)-related economic losses from health impacts during 2014–2016 in china |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6024949/ https://www.ncbi.nlm.nih.gov/pubmed/29914184 http://dx.doi.org/10.3390/ijerph15061278 |
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