Study On The Correlation Between The MODIS AOD And The Concentration Of PM2.5 In Beijing City

The haze weather that comes frequently in recent years, not only restricts the development of our national economy but also threatens our life and health. Aerosol is the basis and premise that forms the haze, the various pollutants which come from human activities includes the direct aerosol and all kinds of gaseous pollutants, these things can become the haze through the reaction of photochemistry, resulting in the increase of PM2.5 concentration which is harmful to human health. At present the routine method of monitoring atmospheric environment is still through the establishment of ground monitoring station in our country, China has a vast territory, to monitor the condition of the air quality on the large scale and achieve the goal of monitoring the quality of atmosphere regionally and globally, obviously,the number of the existing ground monitoring stations can not meet the demands. The measure of the satellite remote sensing monitoring provides an integrated monitoring system for us, satellite remote sensing has the unique advantages of widely covering, continuity, space and predictability in the monitoring of atmospheric environment, and it also can access the air condition fast, real-time and accurately. The aerosol optical thickness is an important optical characteristic of aerosol colloid, by the inversion of aerosol optical thickness, establishing the relation model between the aerosol optical thickness and PM2.5 concentration, can obtain the concentration of PM2.5 on the surface of the large scale area, which makes up for the lack of the air quality index of the wide region due to the Limited number of the ground monitoring station.In this thesis, choosing Beijing as the study area whose air pollution is serious in the past two years, and the Terra-MODIS satellite remote sensing image data as the sample data that is from 2013 and 2014 shot on sunny days, using the mature dark pixel method, based on ENVI5.0 platform, showing the everyday aerosol optical thickness of Beijing. At the same time to collect PM2.5 instantaneous concentration of the 12 monitoring stations in Beijing which is obtained at the same time with the remote sensing images, and to analysis PM2.5 concentration on spatial and temporal dimensions in Beijing, using the spatial statistical analysis method. Because of using the dark pixels algorithm to retrieve aerosol optical thickness has special application condition, such as the inversion effect in the regions with the high vegetation density is better than the lower vegetation coverage, in spring and summer, the vegetation density is higher than in autumn and winter, so the inversion effect is better. The inversion result sometimes has error in autumn and winter, so to select the better part of the retrieval results. Then extracting the instantaneous aerosol optical thickness value and the PM2.5 concentration according the location of each monitoring station. And doing the correlation analysis and regression analysis of the two values, then establishing linear, quadratic, cubic, exponential, logarithmic and power regression model respectively. Through the comparison of the fit goodness R2 and the model checking accuracy, to select the optimal fitting model.Based on the method of the research above, the results are as follows:(1) Using the dark pixel algorithm to inverse the aerosol optical depth in Beijing,and selecting the inversion results that meet the requirement, and obtaining 6 images in summer, 3 images in spring, 1 image in autumn.(2) Analyzing the change trend of Beijing PM2.5 in time and space dimensions respectively, the PM2.5 value is generally higher in winter, spring is the second, the value is lower in summer and autumn.PM2.5 shows an increasing trend from north to south gradually in spatial change trend.(3) proving the correlation between the aerosol optical thickness and PM2.5. And analyzing the correlation in summer and spring respectively, the Pearson correlation coefficient and the bilateral significant of aerosol optical thickness and PM2.5 are increased obviously, they have the statistical significance and can carry on the regression analysis and build the regression model.(4) By means of the regression analysis, 6 regression models of aerosol optical thickness and PM2.5 have been set up for summer and spring, and selecting three models whose fitting R2 are higher to be verified, they are cubic model, exponential model, and power model, ultimately determining the power model is the best fitted model in spring and summer.