The Research Of PM2.5 Atmospheric Concentration Uncertainty Based On Information Entropy

With the rapid development of urbanization and industrialization in recent years,the air pollution in cities has become a key problem that restricts the construction of ecological civilization and sustainable development.Fine particulate matter(PM2.5)is one of the main bottlenecks to improve the urban air quality in China,which can affect human health and climate change,and reduce the visibility of the atmosphere.Regional PM2.5 transport will cause air pollution in the larger spatial and temporal scales.Therefore,the research on the uncertainty of each district in the city of PM2.5 concentration and mutual transfer process has important practical significance.Related studies have indicated that PM2.5 concentration is closely related to the urban population,natural conditions,regional traffic road conditions and meteorological factors,and has significant regional pollution characteristics.Because of the complex formation of PM2.5,such as time,space and other factors,it is difficult to select the distribution of PM2.5 concentration.In this paper,PM2.5 concentration uncertainty in urban area and its transfer process are investigated by using the information entropy as the theoretical tool:PM2.5 concentration uncertainty is measured by the difference entropy.Two kinds of difference entropy is defined,which is used to describe the uncertainty of PM2.5 daily average concentration and time average concentration.Then,Two kinds of differentialentropy is proved that it is poorer than original entropy with the principle of maximum entropy and according to probability approaches information entropy,which can explain the two errors tend to zero.Therefore,PM2.5 concentration entropy uncertainty is measured.Finally,according to the real-time concentration data of PM2.5,the maximum entropy principle is used to evaluate data uncertainty.Aim at each district in the city of PM2.5 concentration uncertainty mutual transfer process,combine PM2.5 spatial position with information entropy.The information transfer rate of PM2.5 monitoring stations is derived,which is used to measure the PM2.5 monitoring stations in the east-west and north-south direction reducing information.And the regression method is used to simulate the information transfer function,which explains the PM2.5 concentration uncertainty changes in the east-west and north-south direction.Make an empirical analysis for Wuhan autumn and winter PM2.5 concentration uncertainty and its transfer process for empirical analysis.The results show that: in the season,PM2.5 concentrations in Wuhan city is associated with latitude and has no obvious linear relationship with longitude;the distribution of PM2.5 concentrations in the city from the south to the north has great randomness,and in the north to the south shows obvious increasing law,indicating that the PM2.5 from the north to the south has obvious characteristics of the diffusion.