Abstract

Many studies have reported that air pollution, especially fine particulate matter (PM2.5), has a significant impact on health and causes economic loss. Gansu Province is in the northwest of China, which is a typical economically underdeveloped area. However, few studies have evaluated the economic loss of PM2.5 related to health effects in this province. In this study, a log-linear exposure-response function was used to estimate the health impact of PM2.5 in 14 cities in Gansu Province from 2015 to 2017, and the amended human capital (AHC) and cost of illness (COI) method were used to evaluate the related economic loss caused by the health impact from PM2.5. The results show that the estimated total number of health endpoints attributed to PM2.5 pollution were 1,644,870 (95%CI: 978,484–2,215,921), 1,551,447 (95%CI: 917,025–2,099,182) and 1,531,372 (95%CI: 899,769–2,077,772) in Gansu Province from 2015 to 2017, respectively. Correspondingly, the economic losses related to health damage caused by PM2.5 pollution were 42,699 (95%CI: 32,380–50,768) million Chinese Yuan (CNY), 43,982 (95%CI: 33,305–52,386) million CNY and 44,261 (95%CI: 33,306–52,954) million CNY, which were equivalent to 6.45% (95%CI: 4.89%–7.67%), 6.28% (95%CI: 4.75%–7.48%), and 5.93% (95%CI: 4.64%–7.10%) of the region Gross Domestic Product (GDP) from 2015 to 2017, respectively. It could be seen that the proportions of health economic loss to GDP were generally high, although the proportion had a slight downward trend. The economic loss from chronic bronchitis and all-cause mortality accounted for more than 94% of the total economic loss. The health impact, economic loss and per capita economic loss in Lanzhou, the provincial capital city of Gansu, were obviously higher than other cities from the same province. The economic loss in Linxia accounted for the highest proportion of GDP. The health impacts in the Hexi region, including the cities of Jiuquan, Jiayuguan, Zhangye, Jinchang and Wuwei, were generally lower, but the economic loss and per capita economic loss were still higher. We also found that urbanization and industrialization were highly correlated with health economic loss caused by PM2.5 pollution. In conclusion, the PM2.5-related health economic burden in Gansu Province was serious. As an economically underdeveloped region, it was very important to further adopt rigid and effective pollution control policies.

Highlights

  • Air pollution is the world’s largest environmental health risk, and is ranked as the fourth among all factors [1,2]

  • We found that urbanization and industrialization were highly correlated with health economic loss caused by PM2.5 pollution

  • (Cpi + GDPp × TIi ) × Ni i=1 where DC2 is the economic loss from outpatient visits, hospitalizations and asthma attributed to PM2.5, Cpi represents the direct medical cost per case of health endpoint i, GDPp is the daily per capita Gross Domestic Product (GDP) of the study city, TIi is the working time loss due to health endpoint I, Ni is the number of cases of health endpoint i caused by PM2.5 pollution, i is the type of health endpoint, and m represents the number of health endpoint

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Summary

Introduction

Air pollution is the world’s largest environmental health risk, and is ranked as the fourth among all factors [1,2]. Among all kinds of air pollutants, PM2.5 is considered to be more toxic and harmful to human health [12], and is most closely related to various health effect endpoints [13] It can penetrate deep into the lungs and trigger systemic effects, and increase the risk of disease by increasing oxidative stress [14,15]. These adverse effects on human health have caused significant economic and social costs [16,17,18], bringing great pressure to environmental managers and decision makers. There is still a serious lack of research on the assessment of health economic loss attributed to PM2.5 -related air pollution in less developed regions, such as Northwest China.

Methods
Data Collection
Exposure–Response Coefficients
Health Information
Estimating Health Effects
Economic Loss Evaluation of Health Effects
Pollution
Correlation Analysis with Social Economic Development
Policy Implications
Uncertainty Analysis
Conclusions
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