Study On Temporal And Spatial Evolution And Influencing Factors Of PM_2.5 Population Exposure Risk In Anhui Province

With the rapid development of economy,air pollution has become one of the important factors affecting people’s health.The severe haze weather makes PM_2.5pollution the most concerned.As the government has stepped up its efforts to prevent and control PM_2.5pollution,the concentration of PM_2.5has been decreasing as a whole,and the pollution has been effectively controlled.However,at present,PM_2.5is still the primary pollutant,and the concentration of PM_2.5in Anhui Province has not yet reached The secondary standard of ambient air quality has adverse effects on the health of the population in Anhui Province.Human exposure to high concentrations of PM_2.5may lead to an increase in the risk of disease and mortality.Therefore,it is necessary to study the exposure risk of PM_2.5population in Anhui Province.In this study,the PM_2.5population exposure risk assessment method was used to assess the PM_2.5population exposure risk in Anhui Province,and its influencing factors were analyzed.The main conclusions of the study are as follows:（1）The temporal and spatial distribution characteristics of PM_2.5concentration in Anhui Province were analyzed by the arithmetic mean method.The results showed that the highest monthly average concentration in Anhui Province appeared in January or February,and the lowest value appeared in July or August.The pattern of winter>spring>autumn>summer,the average annual concentration in 2017 was higher than that in 2016,and it continued to decline in 2018 and 2019.In terms of space,the overall pattern is North Anhui>Central Anhui>South Anhui.In addition,the overall population density also showed the largest in northern Anhui and the smallest in southern Anhui,and the overall population density showed an increasing trend.Among them,some areas of Wuhu,Hefei and other cities showed a very significant growth trend.（2）Through spatial autocorrelation analysis,the results show that the spatialcorrelation of PM_2.5in Anhui Province is relatively significant,tending to spatial aggregation.The Mean Absolute Error（MAE）,Root Mean Square Error（RMSE）and Mean Relative Error（MRE）were used to verify the accuracy of the three interpolation methods,and finally kriging interpolation was selected for interpolation analysis.Based on PM_2.5population exposure risk based on PM_2.5concentration,PM_2.5population exposure risk based on population density,and PM_2.5population exposure risk based on population weighting,in terms of time,the average annual exposure risk values were higher in 2017 than in 2016,and then decreased for two consecutive years,and both were the highest in winter and lowest in summer;in terms of space,they all showed a pattern of northern Anhui>central Anhui>southern Anhui Among them,the overall exposure risks of cities in northern Anhui are relatively high,Chuzhou and Hefei in central Anhui are relatively high,and Huangshan,Xuancheng and Chizhou in southern Anhui are relatively low,based on the population density PM_2.5population exposure risk There is also a law that the central urban area weakens towards the periphery,and half of the urban central area is a high-value area.In terms of changing trends,the overall annual mean value of PM_2.5population exposure risk based on PM_2.5concentration and the annual mean value of PM_2.5population exposure risk based on population density showed a decreasing trend as a whole,but there were also increasing trends in some areas,with the average value in different seasons.A small part of the area showed an increasing trend to varying degrees,and the situation in winter was the most serious.Cities where the annual mean value of PM_2.5population exposure risk based on population weighting did not increase,cities did not show an increasing trend in spring,summer and autumn,and only Lu’an in winter showed an increasing trend.（3）A total of 19 index factors were selected from the three index layers of society and economy,air pollutants and meteorological conditions to analyze the PM_2.5population exposure risk based on PM_2.5concentration and the PM_2.5population exposure risk under population weighting Influencing factors,both exposure risks were significantly correlated with the number of permanent residents,green coverage,car ownership,SO₂,NO₂,PM₁₀,CO,O₃,rainfall,air pressure,air temperature,wind speed,and relative humidity.