Literature DB >> 27063584

Economic Impacts from PM2.5 Pollution-Related Health Effects in China: A Provincial-Level Analysis.

Yang Xie1,2, Hancheng Dai2, Huijuan Dong2, Tatsuya Hanaoka2, Toshihiko Masui2.   

Abstract

This study evaluates the PM2.5 pollution-related health impacts on the national and provincial economy of China using a computable general equilibrium (CGE) model and the latest nonlinear exposure-response functions. Results show that the health and economic impacts may be substantial in provinces with a high PM2.5 concentration. In the WoPol scenario without PM2.5 pollution control policy, we estimate that China experiences a 2.00% GDP loss and 25.2 billion USD in health expenditure from PM2.5 pollution in 2030. In contrast, with control policy in the WPol scenario, a control investment of 101.8 billion USD (0.79% of GDP) and a gain of 1.17% of China's GDP from improving PM2.5 pollution are projected. At the provincial level, GDP loss in 2030 in the WoPol scenario is high in Tianjin (3.08%), Shanghai (2.98%), Henan (2.32%), Beijing (2.75%), and Hebei (2.60%) and the top five provinces with the highest additional health expenditure are Henan, Sichuan, Shandong, Hebei, and Jiangsu. Controlling PM2.5 pollution could bring positive benefits in two-thirds of provinces. Tianjin, Shanghai, Beijing, Henan, Jiangsu, and Hebei experience most benefits from PM2.5 pollution control as a result of a higher PM2.5 pollution and dense population distribution. Conversely, the control investment is higher than GDP gain in some underdeveloped provinces, such as Ningxia, Guizhou, Shanxi, Gansu, and Yunnan.

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Year:  2016        PMID: 27063584     DOI: 10.1021/acs.est.5b05576

Source DB:  PubMed          Journal:  Environ Sci Technol        ISSN: 0013-936X            Impact factor:   9.028


  38 in total

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2.  The Relationships between PM2.5 and Meteorological Factors in China: Seasonal and Regional Variations.

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Journal:  Int J Environ Res Public Health       Date:  2017-12-05       Impact factor: 3.390

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4.  Developing a model to predict air pollution (case study: Tehran City).

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Journal:  J Environ Health Sci Eng       Date:  2021-01-07

5.  Spatial and Temporal Characteristics of Environmental Air Quality and Its Relationship with Seasonal Climatic Conditions in Eastern China during 2015-2018.

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Journal:  Int J Environ Res Public Health       Date:  2021-04-24       Impact factor: 3.390

6.  Spatiotemporal Variability of Remotely Sensed PM2.5 Concentrations in China from 1998 to 2014 Based on a Bayesian Hierarchy Model.

Authors:  Junming Li; Meijun Jin; Zheng Xu
Journal:  Int J Environ Res Public Health       Date:  2016-08-01       Impact factor: 3.390

7.  Spatiotemporal Patterns of Ground Monitored PM2.5 Concentrations in China in Recent Years.

Authors:  Junming Li; Xiulan Han; Xiao Li; Jianping Yang; Xuejiao Li
Journal:  Int J Environ Res Public Health       Date:  2018-01-11       Impact factor: 3.390

8.  Control Models and Spatiotemporal Characteristics of Air Pollution in the Rapidly Developing Urban Agglomerations.

Authors:  Longwu Liang; Zhenbo Wang
Journal:  Int J Environ Res Public Health       Date:  2021-06-07       Impact factor: 3.390

9.  Characterization of Fine Particulate Matter and Associated Health Burden in Nanjing.

Authors:  Dongyang Nie; Mindong Chen; Yun Wu; Xinlei Ge; Jianlin Hu; Kai Zhang; Pengxiang Ge
Journal:  Int J Environ Res Public Health       Date:  2018-03-27       Impact factor: 3.390

10.  Health and related economic benefits associated with reduction in air pollution during COVID-19 outbreak in 367 cities in China.

Authors:  Tingting Ye; Suying Guo; Yang Xie; Zhaoyue Chen; Michael J Abramson; Jane Heyworth; Simon Hales; Alistair Woodward; Michelle Bell; Yuming Guo; Shanshan Li
Journal:  Ecotoxicol Environ Saf       Date:  2021-06-30       Impact factor: 6.291

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