A Study Of Combined Air Pollution Transport In Beijing-Tianjin-Hebei Region Based On Multivariate Detrended Cross-correlation Analysis And Complex Network

In recent years,the regional combined air pollution characterized by fine particulate matter(PM_2.5)and ozone（O₃）has become increasingly severe,seriously affecting human life and mental health.Beijing-Tianjin-Hebei is the economic,political and cultural center of China.The cross-correlation between PM_2.5 and O₃ is complex at different time scales,so the cross-correlation relationship of secondary pollution is complex with obviously complex network structure in Beijing-Tianjin-Hebei air pollution transportation channels cities（"2+26"cities）.Therefore,the study of the complex cross-correlation between PM_2.5 and O₃in the region is helpful to provide scientific basis for the policy formulation of regional air pollution control.Firstly,the complex cross-correlation between secondary pollutants is revealed based on the multifractal method.Then,a new multifractal parameter index is constructed to evaluate the PM_2.5and O₃coordinated control capability of different cities.Further study the cross-correlation between cities,and on this basis,build a new complex network model of air composite pollution transportation to explore the transport characteristics of PM_2.5and O₃ in different time scales.In order to provide scientific basis for the control of secondary pollutants in Beijing-Tianjin-Hebei,this study is studied.（1）Based on Multifractal Detrended ross-correlation analysis（MFDCCA）method,the complex cross-correlation between PM_2.5 and O₃ at different time scales is deeply understood,and a new multifractal parameter index^ηis established to evaluate the PM_2.5 and O₃ coordinated control capability of four cites in China（Beijing,Shanghai,Guangzhou and Chengdu）.Combined with the sliding window method,the high temporal scale resolution ofηvalue of each city is analyzed in order to determine the time evolution of^ηvalue.Then,the monthly variation ofηvalue in four cities is studied.The results show that the PM_2.5 and O₃coordinated control capability is the best in summer,the relationship between inderηand meteorological conditions is further discussed.Finally,the long-term evolution trend ofηvalue is studied by Mann-Kendall test method.The results show that theηvalue of Beijing has increasing trend after 2017.Beijing has the weakest coordinated control capability of PM_2.5 and O₃.This may be caused by the combinated of environmental governance,meteorological conditions and external regional transportation in Beijing.（2）Based on the hourly PM_2.5 and O₃ concentrations in"2+26"cities from1January 2017 to 31 December 2020,the complex nonlinear cross-correlation between PM_2.5 and O₃between cities is revealed by using the multivariate detrended cross-correlation analysis（MV-DCCA）method.The results show that there is a significant cross-correlation between PM_2.5 and O₃ among cities at multiple time scales.This cross-correlation has the characteristics of long-term sustainability.This means that the emission of PM_2.5 and O₃ from one city in the past moment will have a long-term impact on the pollution of PM_2.5 and O₃ from another city in the future.Furthermore,it discusses the influence of pollution transportation time and the distance between cities onρ_MV-DCCA.Then,by comparing the concentration evolution of PM_2.5 and O₃with the collapse of sand pile,it is result that the evolution of PM_2.5 and O₃ in the atmosphere has the basic characteristics of self-organized criticality complex system.Therefore,the change rule of multi-time scale correlation between PM_2.5 and O₃ in different cities is similar every year.In addition,by comparing the cross-correlation coefficientρ_MV-DCCAvalue of cities in different seasons,it is found that the PM_2.5 and O₃cross-correlation between cities is stronger in the 24-hour time scale in summer.In winter,the PM_2.5 and O₃ cross-correlation between cities increases with the increase of time scale,which must be paid attention to in the atmospheric management of"2+26"cities.（3）Based on the ρ_MV-DCCA of different cities,it is used as the criterion for judging edge connection.And taking"2+26"cities as nodes,a new network model of combined air pollution is constructed.To explore the multi-time scale characteristics of combined air pollution,in order to reveal the transportation mode of secondary pollution between cities in the region.The results show that the cross-correlation between PM_2.5 and O₃pollution among"2+26"cities is complicated,and there is no isolated city node.Small-world effect exists in the networks of regional combined air pollution at multiple time scales.With the increase of time scale,the small world effect of the network will be significantly enhanced.The network of air composite pollution will be more closely connected,and the transportation relationship between regional PM_2.5 and O₃ pollution will be more complicated.On the basis,the importance of nodes is evaluated based on their network characteristics.Furthermore,the annual variation characteristics of regional combined air pollution network are discussed.The characteristics of regional air composite pollution network under epidemic situation truly reflect the objective law of air composite pollution transportation.On the 8-hour and 24-hour time scales,the relationship between PM_2.5 and O₃ transportation between cities in summer is more complicated.In winter,the difference of regional air composite pollution transport network characteristics decreases,and the relationship between PM_2.5 and O₃ transport among cities in winter is more complicated.In this study,based on the nonlinear cross-correlation between PM_2.5 and O₃among cities in the region,the complex network model of air compound pollution is organically integrated with the complex network,which can effectively reflect the multi-time scale characteristics of regional secondary pollution transportation mode.This also provides a new way of thinking for the study of regional atmospheric composite pollution transport.