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PM2.5 Pollution

Health and Economic Effect Assessment Based on a Recursive Dynamic Computable General Equilibrium Model

Dados Bibliográficos

ID17801015
AutoresKeyao Chen (0000-0003-3781-6946, China Meteorological Administration), Guizhi Wang (0000-0003-1960-2629, Nanjing University of Information Science and Technology, autor correspondente), Lingyan Wu (0000-0002-7910-5213, Nanjing University of Information Science and Technology), Jibo Chen (Nanjing University of Information Science and Technology), Shuai Yuan (0009-0005-7442-9592, Nanjing University of Information Science and Technology), Qi Liu (0000-0001-6077-361X, Shandong Beiming Medical Technology Ltd., Jinan 250000, China), Xiaodong Liu (0000-0002-6115-3049, Edinburgh Napier University)
Ano2019
Volume16
Fascículo24
Páginas5102-5102
Data de publicação2019-12-13
Peer ReviewedSim
Open AccessSim
TipoARTICLE
PeriódicoInternational Journal of Environmental Research and Public Health (JOURNAL)
Identificadores do periódicoISSN: 1661-7827 • E-ISSN: 1660-4601
EditoraMultidisciplinary Digital Publishing Institute (PUBLISHER • CH)
DOI10.3390/ijerph16245102
PMID31847259
OpenAlexW2996099354
IdiomaEN
Referências citadas25

At present particulate matter (PM 2.5 ) pollution represents a serious threat to the public health and the national economic system in China. This paper optimizes the whitening coefficient in a grey Markov model by a genetic algorithm, predicts the concentration of fine particulate matter (PM 2.5 ), and then quantifies the health effects of PM 2.5 pollution by utilizing the predicted concentration, computable general equilibrium (CGE), and a carefully designed exposure-response model. Further, the authors establish a social accounting matrix (SAM), calibrate the parameter values in the CGE model, and construct a recursive dynamic CGE model under closed economy conditions to assess the long-term economic losses incurred by PM 2.5 pollution. Subsequently, an empirical analysis was conducted for the Beijing area: Despite the reduced concentration trend, PM 2.5 pollution continued to cause serious damage to human health and the economic system from 2013 to 2020, as illustrated by various facts, including: (1) the estimated premature deaths and individuals suffering haze pollution-related diseases are 156,588 (95% confidence intervals (CI): 43,335-248,914)) and six million, respectively; and (2) the accumulated labor loss and the medical expenditure negatively impact the regional gross domestic product, with an estimated loss of 3062.63 (95% CI: 1,168.77-4671.13) million RMB. These findings can provide useful information for governmental agencies to formulate relevant environmental policies and for communities to promote prevention and rescue strategies

Beijing · China · Computable general equilibrium · Econometrics · Economic growth · Economics · Geography · Gross domestic product · Macroeconomics · Particulates · Social accounting matrix · Air Quality and Health Impacts · Chemistry · Energy, Environment, Economic Growth · Environmental Science · Urban Transport and Accessibility · Pollution

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