The Distribution And Variation Of AOD Over China Based On MODIS Remote Sensing DT And DB Data Set

As a major factor measuring aerosol concentrations, Aerosol Optical Depth (AOD) is applied to characterize atmospheric turbidity. The temporal and spatial distribution of AOD is affected by both sources (including natural and anthropogenic emissions) and meteorological conditions. By using data from the Moderate Resolution Imaging Spectrometer (MODIS) on board NASA’s EOS satellites and the Aerosol Robotic Network (AERONET), the distribution and variation of aerosols over China and other11countries in recent10years are discussed.In data processing, the DT (Dark Target) algorithm retrieved dataset (C005) are combined with DB (Deep Blue) algorithm retrieved dataset (C005) from July2002to March2013. In this way, two datasets are merged with the DT dataset being given precedence.Comparison of AOD between the two MODIS datasets and AERONET observations from27sites over China and other11emerging economies has been made. It shows the relatively good correlations of MODIS datasets and AERONET observations in various countries, especially in America, which indicates that the merging data can be utilized in the study of AOD.Based on the dataset, the annual, seasonal and monthly distribution and variation of AOD are investigated over China. A further analysis is also made over Western and Eastern China divided by the "Hu Line" in geography. Applying World Development Indicator from1960to2012released by World Bank, the impacts of population, GDP and energy consumption have on the distribution of AOD are also discussed. The findings are as follows:(1) Distribution of AOD varies significantly over China. The densely populated and developed regions, including Beijing-Tianjin-Hebei region, the Pearl River Delta, the middle and upper reaches of Yangtze River and Yangtze River Delta, and the Sichuan Basin show high values over western regions. High values can also be found in Tarim Basin and Qaidam Basin over western areas. The relative lower value are mainly distributed in Northern Inner Mongolia, some parts of Heilongjiang province, northwestern of the Yunnan-Guizhou Plateau, the Western Sichuan Plateau and southeastern parts of Qinghai-Tibet Plateau.(2) The temporal variation of AOD is also remarkable. An obvious variation is presented over south parts of Northeastern China, Beijng-Tianjin-Tangshan area, the middle and lower reaches of Yangtze River, Pearl River Delta, Taklimakan Desert, and Northwestern parts of Tibet Plateau. The highest AOD appears in spring, being lower in summer and winter, and the minimum in autumn. As for the monthly variation, April hits the highest AOD, while AOD in June and December is lower, and November show the lowest mean AOD. (3)A relative high AOD can be seen on the east of the Hu Line, being0.42to0.49, while AOD is0.23-0.28on the west of the Hu Line. Difference in the mean value between the east and the west is about0.2. Both sides show a tendency of increasing and the rate is higher in the eastern region.(4)The highest AOD occurs in spring when it reaches0.55in the east and0.35in the west, whereas it shows the lowest value in autumn, being0.38in the east and0.17in the west. In the eastern region, AOD increases gradually from January to June and then reaches the highest value. Later it decreases and reaches the lowest value in November. In western region, AOD increases from January to April and then decreases slightly until August. However, it decreases significantly and also tends to be the lowest in November.(5) A linear regression between population density and AOD has been accomplished. Analysis shows that correlation coefficient between AOD and population density of the country, eastern region and western region are0.32,0.35and0.23respectively, which indicates that more anthropogenic aerosols leads to higher AOD in eastern region. A positive correlation of0.4is represented between GDP and AOD, which means the growth of GDP could result in the increase of AOD. A positive correlation of0.49is also found between energy consumption and AOD, which is considered as the most effected factors.In the last parts, distribution and variation of AOD are analyzed in those densely populated area including India, Pakistan, Thailand, Vietnam, Bangladesh, Indonesia in Asia, Mexico, Brazil, Argentina in America, and Niger, Congo in Africa, according to the converged dataset. We find that:(1) Annual mean AOD shows a value higher than0.5in1country, between0.4to0.5in3countries, between0.3to0.4in3countries, between0.2to0.3in1country, and lower than0.2in3American countries, respectively. According to the analysis, AOD in these countries are ranked as:Bangladesh, Pakistan, Niger, India, China, Congo, Vietnam, Thailand, Indonesia, Mexico, Brazil and Argentina. China ranked fifth among these12countries, which suggest that AOD in China is not the highest over the world.(2)AOD shows a tendency of increasing in most of the countries except for Niger, Brazil, Pakistan and Indonesia. The increasing rates are ranked as follows:Bengal, India, Argentina, Thailand, Vietnam, Mexico and Congo. The believability of increasing rate in Bangladesh and India is more than99%, but fail to reach the value in other5countries.