Assessing the Public Health Economic Loss from PM2.5 Pollution in ‘2 + 26’ Cities
Abstract
:1. Introduction
1.1. Background
1.2. Significance
1.3. Literature Review and Research Gap
1.4. The Main Work and the Innovations
2. Study Area
2.1. Background
2.2. Existing Problems
2.2.1. High Pollution Intensity
2.2.2. Difficulty in Controlling PM2.5 Pollution
2.2.3. Air Pollution Control System Needs to Be Improved
3. Methods and Data
3.1. The Exposure-Response Model
3.2. Health Effect Loss Model
3.3. Willingness to Pay Method
4. Results
4.1. Unit Economic Value of Each Health Effect Terminal
4.2. Health Effect Loss in ‘2 + 26’ Cities
4.3. Total Health Effect Economic Loss in‘2 + 26’ Cities
4.3.1. The Economic Loss of Three Kinds of Health Terminals
4.3.2. Total Economic Loss
5. Conclusions
5.1. Health Effect Loss Cannot Be Neglected
5.2. The Economic Loss of Public Health Effect Presents Regional Differences
6. Policies
6.1. Continue to Implement Coal Consumption Control to Reduce Health Effect Loss
6.2. Control the Level of Urbanization and Optimize the Arrangement of the Core Area
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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---|---|---|---|
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3 | Xie et al. | 2014 [13] | Used the Poisson Regression model and the estimating method of environmental value to evaluate the risk of acute health damage to high-concentration PM2.5 exposure in Beijing’s residents. |
4 | Etchie et al. | 2017 [14] | Assessed the health and economic loss of Nagpur region. The study utilized a life-table approach to calculate the number of premature deaths and disability-adjusted life years associated with the five health effect terminals associated with PM2.5 exposure. |
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6 | Zeng et al. | 2019 [16] | Used spatial interpolation and Ben-map tools to figure out the health loss in China from air pollution, especially PM2.5 in 2017, which spatially analyzed the health economic loss at a city scale. |
7 | Yao et al. | 2020 [17] | Calculated the health loss from PM2.5 with the log-linear model along with the exposure-response function. |
8 | Zhang and Cao | 2022 [18] | Evaluated the policy effects of air pollution control using a double-difference model (DID). |
Healthy Terminal | β (%) | E Value (‰) | |
---|---|---|---|
Death | Total mortality | 0.40 (0.19, 0.62) | 0.0161644 |
Respiratory disease mortality | 1.43 (0.85, 2.01) | 0.0017025 | |
Cardiovascular mortality | 0.53 (0.15, 0.9) | 0.007523 | |
Hospitalization | Respiratory diseases | 1.09 (0, 2.21) | 0.0350411 |
Cardiovascular diseases | 0.68 (0.43, 0.93) | 0.0270904 | |
Outpatient | Pediatrics (0–14 years old) | 0.56 (0.2, 0.9) | 0.4191781 |
Internal medicine (at least 15 years old) | 0.49 (0.27, 0.7) | 1.1261644 | |
Sick | Acute bronchi | 7.90 (2.7, 13) | 0.1041096 |
Asthma | 2.10 (1.45, 2.74) | 0.1536986 |
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Wang, Y.; Sun, K.; Li, L.; Lei, Y.; Wu, S.; Jiang, Y.; Xi, Y.; Wang, F.; Cui, Y. Assessing the Public Health Economic Loss from PM2.5 Pollution in ‘2 + 26’ Cities. Int. J. Environ. Res. Public Health 2022, 19, 10647. https://doi.org/10.3390/ijerph191710647
Wang Y, Sun K, Li L, Lei Y, Wu S, Jiang Y, Xi Y, Wang F, Cui Y. Assessing the Public Health Economic Loss from PM2.5 Pollution in ‘2 + 26’ Cities. International Journal of Environmental Research and Public Health. 2022; 19(17):10647. https://doi.org/10.3390/ijerph191710647
Chicago/Turabian StyleWang, Yifeng, Ken Sun, Li Li, Yalin Lei, Sanmang Wu, Yong Jiang, Yanling Xi, Fang Wang, and Yanfang Cui. 2022. "Assessing the Public Health Economic Loss from PM2.5 Pollution in ‘2 + 26’ Cities" International Journal of Environmental Research and Public Health 19, no. 17: 10647. https://doi.org/10.3390/ijerph191710647