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

As the society continues along the road of the economic development, more and more population accumulated in the city. With the excessive industrial gases, the heavy traffic and a large number of coal combustion, the air pollution is becoming a more serious problem that nobody can ignore. At present, the PM 2.5(the particle whose diameter is less than 2.5μm) has become the primary pollutant in the air. And because of the factor such as small diameter, high absorptivity and high diffusivity, the PM2.5 threaten people’s health and living environment. As the capital of China, Beijing, one of the international metropolis, is the window of the China, which draws attention from everywhere of the world. However, the severe haze that occurs in Beijing in 2013 does harm to the image of the capital, bringing about a wide range of discussion from all scientists and civil citizens. The effective and efficient supervision to air quality is the main goal of the control of the air pollution.The supervision to air pollutant is the first step to study the air pollution. At present, the main approaches of supervision are two ways, including ground-supervision and remote-sensing-supervision. The advantages of the ground-supervision are high precision and real time monitoring while the disadvantages are expensive maintenance and difficulty of setting up monitor equipment in mountains, rivers and deserts. By comparison, the edges of remote-sensing technology are the wide monitor range, real time and the low cost. With the development of the satellite technology and the launch of satellites, the remote-sensing supervision will play an important role in the supervision of the environment pollution. Therefore, the significance of the combination of data from ground monitor equipment and data from the remote sense satellites is considerable for the supervision to the air quality and for drawing the reasonable and effective plan to control the air pollutant.In this paper, I use the MODIS remote sensing data to calculate the Aerosol optical thickness based on the 6S Atmospheric transmission model, and subsequently combine with the PM2.5 data from ground monitor to establish the model of regression analysis. I evaluate the PM2.5 concentration based on the best fitting model, hoping to find out the relationship between the AOD and the concentration. The main content as follows:1) Use remote sensing data from TERRA and AQUA satellites to reversal AOD of Beijing in different date. Compare with data from the AERONET monitor site to show that the correlation coefficient is 0.73(TERRA) and 0.76(AQUA) respectively, suggesting that using remote sensing data to reversal AOD is feasible.2) Combine the data from 12 monitoring sites with the reversal AOD and analyze the feature of Beijing air pollution. The result shows that the concentration of PM2.5 in suburb such as Changping and Yanqing is smaller than the downtown of Beijing, the same as the AOD results; the max concentration of PM2.5 in winter is more severe than that in summer while the AOT is opposite, suggesting that there should be a correction according to the different season and weather.3) Correct the reversal AOD data by adding vertical correction and humidity correction. Combine with data from 12 monitoring sites to establish 5 kinds of regression analysis model. The quadratic and exponential models show the best result respectively, and the correlation coefficients are 0.691(TERRA) and 0.718(AQUA).4) Respectively establish four seasons fitting model. The result shows that the coefficient in summer is the highest(TERRA is 0.81 and AQUA is 0.83); the winter is the lowest(TERRA is 0.51 and AQUA is 0.57). Compare the data of predicted by AODand measured values from monitoring sites. The result suggests that most results of this approach are good in spite of the low precision in bad weather, which imply that in bad weather, we should consider more factors and corrections.