PM2.5 Pollution: Health and Economic Effect Assessment Based on a Recursive Dynamic Computable General Equilibrium Model

Chen, Keyao; Wang, Guizhi; Wu, Lingyan; Chen, Jibo; Yuan, Shuai; Liu, Qi; Liu, Xiaodong

Abstract

At present particulate matter (PM₂.₅) 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 (PM₂.₅), and then quantifies the health effects of PM₂.₅ 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 PM₂.₅ pollution. Subsequently, an empirical analysis was conducted for the Beijing area: Despite the reduced concentration trend, PM₂.₅ 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.

Citation

Chen, K., Wang, G., Wu, L., Chen, J., Yuan, S., Liu, Q., & Liu, X. (2019). PM2.5 Pollution: Health and Economic Effect Assessment Based on a Recursive Dynamic Computable General Equilibrium Model. International Journal of Environmental Research and Public Health, 16(24), Article 5102. https://doi.org/10.3390/ijerph16245102

• Journal Article Type: Article
• Acceptance Date: Dec 12, 2019
• Online Publication Date: Dec 13, 2019
• Publication Date: Dec 13, 2019
• Deposit Date: Feb 21, 2020
• Publicly Available Date: Feb 24, 2020
• Journal: International Journal of Environmental Research and Public Health
• Electronic ISSN: 1660-4601
• Publisher: MDPI
• Peer Reviewed: Peer Reviewed
• Volume: 16
• Issue: 24
• Article Number: 5102
• DOI: https://doi.org/10.3390/ijerph16245102
• Keywords: haze pollution; genetic algorithm; exposure-response model; computable general equilibrium model; health effects
• Public URL: http://researchrepository.napier.ac.uk/Output/2578165