Seasonal And Trend Characteristics Of PM2.5 In Large And Medium Cities In China

In recent years,China’s high-quality economic development and accelerated urbanization process have also brought serious environmental problems.PM2.5 has become China’s most important air pollutant.How to accurately describe the characteristics of PM2.5 has always been an important subject.In view of this,this paper uses the structural time series adjustment method based on the state space model to decompose the seasonal and trend components of PM2.5 in 74 large and medium cities in China,and then uses Kruskal-Wallis test to explore the stability of seasonal components.Mann-Kendall test combined with Sen’s slope is used to describe the direction and size of the change in the trend component.Finally,the coefficient of variation and spatial statistical methods are used to explore the convergence characteristics of trend components.The main research conclusions of this paper are:(1)The seasonal composition of PM2.5 in all cities is a unity of unity and difference.The unity is reflected in the U-shaped characteristics of "high in winter,low in summer,and middle in spring and autumn" in all cities,which has obvious periodicity.The difference refers to the fact that the seasonal composition of each city isdifferent due to its own geographical conditions,meteorological conditions and economic and social factors.(2)PM2.5 seasonal composition was relatively stable in all cities in spring and autumn,PM2.5 Seasonal components in Shenyang,Hohhot,Urumqi,Yinchuan,Lhasa,and Chongqing are unstable in summer,and PM2.5 seasonal components in Xining,Yangzhou,and Nanchang are unstable in winter.(3)From 2014 to 2018,only PM2.5 time series in Urumqi has no obvious downward trend,PM2.5 pollution control in other cities has achieved some significant effects.However,there are still few cities that are falling faster.(4)Considering the convergence characteristics of the PM2.5 trend,first,there is sigma convergence in the whole country and type I region("rapid decline" type)and type II region("wave fluctuation" type),but there is no sigma convergence in the type III region("smooth change" type).The sigma convergence rate of the type II region("wave fluctuation" type)is significantly faster than the type I region("rapid decline" type).There is a clear "catching up" situation;Second,the PM2.5 trend shows significant agglomeration characteristics and monthly differences,but this spatial correlation is decreasing year by year.The trend of PM2.5 in the evolution process from 2014 to 2018 showed a regional concentration and continuity phenomenon,without very obvious spatial changes;Third,there is absolute beta convergence in the PM2.5 trend components of the entire country and the three major regions.The type III region("smooth change" type)has the fastest convergence rate,followed by the type II region("wave fluctuation" type),and the type I region("rapid decline" type)has the slowest convergence rate.Based on the above conclusions,this article puts forward relevant policy recommendations for the management of PM2.5 in 74 urban areas in China,and provides scientific decision support for the promotion of China’s air pollution control.