Measurement And Empirical Analysis On The Economic Loss Of Human Health Caused By PM_2.5 Pollutants

Since the 21st century,China has gradually promoted the process of industrialization and urbanization,and China developed economic construction rapidly.As a result,PM2.5 pollution in cities has become increasingly serious,causing serious negative effects on human health and causing huge economic losses to the society.Severe PM2.5 pollution can lead to a surge in the incidence of various diseases and,and can lead to acute death in sensitive populations.Therefore,in the face of increasingly serious air pollution and public health problems,a comprehensive assessment of human health damage and social economic losses caused by different PM2.5 pollution level has important scientific value and practical significance for not only promoting pollution prevention and control but also maintaining public health in China.In this context,domestic and foreign scholars have adopted a large number of methods to quantify the negative impact of PM2.5 pollution on human health,that is,economic loss of human health caused by air pollution,namely pollution-health economic loss.However,when studying the negative effects of the environment on health by traditional methods,most of them are based on the average pollutant concentration in the study period.Therefore,when quantifying the economic losses caused by negative effects,the results are relatively rough with large random errors.In addition,previous studies only evaluate the economic loss of the overall health caused by pollution.Because different pollution levels will cause varying degrees of damage to human health,these methods may lead to the results that pollution-health economic losses are not evaluated in detail,which leads to poor estimation precision and the evaluation results cannot provide effective reference for future policy.For a more detailed calculation of pollution-health economic losses,this study proposed a novel PM2.5 pollution-health economic loss assessment model,which evaluates PM2.5 pollution-health economic loss based on PM2.5 pollutant concentration data of Beijing,Shanghai,Guangzhou and Shenzhen from 2014 to 2018.Nine distributions(EV distribution,Gamma distribution,Logistic distribution,Loglogistic distribution,Normal distribution,Lognormal distribution,Rayleigh distribution,Rician distribution,and Weibull distribution)and two parameter estimation methods(maximum likelihood estimation method and grasshopper optimization algorithm)are firstly integrated to depict the data characteristics of PM2.5 pollutant concentration.The optimal probability distribution of PM2.5 pollutant concentration in each city from 2014 to 2018 can be selected based on the goodness of fit evaluation index.Then,the optimal distribution was used to measure the characteristics of PM2.5 pollutant concentration,and the distribution of days with different pollution levels in the evaluated period was calculated.Combined with benefit transfer method and the widely used exposure-response function in epidemiological studies,the health damage and economic loss caused by PM2.5 pollution in four cities were evaluated effectively.Unlike traditional health-related economic loss calculation methods,the economic losses caused by PM2.5 pollutants with different pollution levels are measured in this study and combined with GDP to eliminate differences of the unit economic loss in different regions and at different periods so as to compare and analyze PM2.5 pollution-health economic losses reasonably.The proposed novel PM2.5 pollution-health economic loss measurement model provides a new perspective for the accounting of health-related economic loss,which is operable and reliable.This model effectively simulated PM2.5 concentration distribution characteristics of Beijing,Guangzhou,Shanghai,and Shenzhen in 2014-2018 and successfully calculated the corresponding PM2.5 pollution-health economic losses.This study calculates the PM2.5 pollution-health economic loss,analyzes the negative effects of PM2.5 pollution on human health,and improves the existing research system on health-related economic loss.The main conclusions of this study are listed in following:(1)Based on PM2.5 pollutant concentration data of each city and each time period,the parameter estimation performance of intelligent optimization algorithm(Grasshopper optimization algorithm)is better than numerical method(maximum likelihood estimation).The optimal fitting distribution of PM2.5 pollutant concentration data in different cities and different time periods is also different,indicating that the characteristics of PM2.5 pollutant concentration data in different cities and different time periods are different.(2)In most cases,the environmental quality of each city improved from 2014 to 2018,but the values of PM2.5 pollution-health economic loss did not fluctuate significantly.This is because of the continuous improvement of Chinese economic level in the past five years;thus,the unit economic cost of each health terminal rises simultaneously.(3)Based on the annual GDP of each city,it can be found that the Beijing,Shanghai,Guangzhou,and Shenzhen are ranked in order of PM2.5 pollution-health economic loss degree from the largest to the smallest.Besides,over the past five years,the PM2.5 pollution-health economic loss in each city have moderated obviously.This work not only provides a new perspective for PM2.5 pollution-health economic loss assessment,but also provides a reference for the practical application of decision-makers.