| Aerosol satellite remote sensing has important advantages in large-scale and continuous spatial observation of air quality.However,due to the differences in the physical and chemical properties of Aerosol Optical Depth?AOD?and PM2.5 itself,coupled with the influence of different time scales and regional geography features,the estimation of PM2.5 concentration in large-scale areas through AOD alone is proposed.The accuracy is not stable.Based on this,this paper selects Sichuan Province as the research area,combines the geographical features of AOD and PM2.5concentrations,studies and compares the linear fitting Pearson correlation coefficient?difference between AOD and PM2.5 concentrations in the global and local areas.In2015 and 2017,the correlation coefficient between AOD and PM2.5 concentrations in the subtropical monsoon climate zone,Sichuan Basin,Chengdu-Chongqing urban agglomeration and Sichuan Province has little difference?the difference between?is less than 0.3?,and the AOD in plateau climate,plateau mountains,and Sanzhou area.Although the correlation coefficient with the concentration of PM2.5 is very high,the overall difference with Sichuan Province is obvious,the PM2.5 monitoring stations are sparsely distributed and the analysis results are not representative.Taken together,the overall land use regression model?LUR model?of Sichuan Province in 2015 and2017 was finally constructed in combination with AOD and other types of feature elements,and the distribution map of PM2.5 pollution in 2015 and 2017 was obtained.By analyzing the spatial and temporal distribution pattern of PM2.5 pollution in 2015and 2017,we compared the progress of atmospheric pollution control in Sichuan Province in the past three years and the pollution changes in the original key prevention and control regions,in order to reasonably implement the macro-control of the pollution prevention and control policy in Sichuan Province.Investigate key areas and policies for the prevention and control of scientific air pollution in the new era.The main work and conclusions of this thesis are as follows:?1?Using the MODIS Combined AOD data from 2015,2017 and the PM2.5concentration data from the ground air pollution monitoring station in Sichuan Province,the seasonal average and annual average AOD-PM2.5 site concentration maps of Sichuan Province in 2015 and 2017 were produced.The results show that the AOD value in Sichuan Province is similar to the overall distribution of PM2.5concentration in the site,the high AOD coverage area and the high PM2.5concentration are in the spring and winter seasons;the high AOD coverage area in the summer and autumn is small.PM2.5 site concentration is low.Affected by factors such as topography,rainfall,temperature,and atmospheric circulation in Sichuan Province,the trend of the concentration distribution of the PM2.5 site and the high value of the AOD in the summer and autumn of 2015 is opposite.According to the climate,altitude and socioeconomic level of Sichuan Province,it was found that the high concentrations of AOD and site PM2.5 were generally concentrated in the subtropical monsoon climate zone,the Sichuan Basin,and Chengdu-Chongqing urban agglomeration.The low values were concentrated in the plateau climate and plateau.Mountain and Sanzhou areas.It shows that the temporal and spatial distribution characteristics of AOD value and site PM2.5 concentration in Sichuan Province,although there are differences in individual seasonal trends,the overall changes are the same,showing a certain correlation.?2?Combining the geographic characteristics of AOD and PM2.5 concentrations,Sichuan Province was zoned according to climate,elevation terrain and socio-economic level.The spatial and temporal correlations between AOD and PM2.5concentrations in Sichuan Province during 2015 and 2017 were analyzed..The results show that:from the perspective of the overall situation in Sichuan Province,AOD and site PM2.5 concentrations have a certain spatial and temporal correlation,and the correlation between the spring and winter seasons is relatively high,in the summer and autumn,the correlation of AOD and site PM2.5 concentrations is not stable.In terms of local subdivision,the correlations between the subtropical monsoon climate,Sichuan Basin,Chengyu urban agglomeration,and site PM2.5concentrations over time scales are similar to the changes in Sichuan's global correlation;In plateau climate,plateau mountains,and three states,the correlation between AOD and PM2.5 concentration in the area is extremely high,with little change over time,and there is a large difference in overall correlation with Sichuan Province.This aspect is related to the scarcity or lack of data on the ground monitoring site of PM2.5 in the west of Sichuan Province.It shows that the correlation coefficient between plateau climate,plateau mountains,AOD and site PM2.5 in Sanzhou area is high,but it is not representative.On the other hand,it also shows that compared with the number of sites,Sichuan Province has a relatively small scope as a research area and cannot reflect the differences between PM2.5concentration and AOD in global and local sub-districts.Therefore,Sichuan Province is to conduct partial zoning modeling.The effect and significance of the re-coupling into a global AOD-PM2.5 fitting model was not significant.Finally,AOD and other various feature elements were selected to construct the global seasonal average and annual average LUR regression model of Sichuan Province.?3?From the combined AOD data and multi-source geographical feature elements,the predictor which the most significant correlation with the site PM2.5concentration is selected as a model.After removing the strong collinearity feature variables,the seasonal average and annual average global LUR model of Sichuan Province in 2015 and 2017 was constructed.A 10-fold cross validation method was used to verify the accuracy of the model by determining the coefficient?R2?and adjusted judgment coefficient(R2adj),relative error???,and root mean squared error?RMSE?indicators.Using the constructed LUR model,spatial and temporal distribution maps of PM2.5 concentrations in Sichuan Province in 2015 and 2017were obtained.From the simulation results of PM2.5 concentration distribution,it can be known that the change of PM2.5 concentration over time scale in Sichuan province from 2015 to 2017 is the highest in winter,followed by spring and autumn,and lowest in summer;the spatial distribution pattern remains unchanged from east to west and low.However,the overall PM2.5 concentration has decreased,indicating that the prevention and control of air pollution in Sichuan Province has achieved preliminary results.At the same time,along with the gradual changes in the high and low value areas of the polluted land,they provide suggestions for the joint prevention and control methods and policy adjustment of the PM2.5 pollution in Sichuan Province. |
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