利用OMI遥感数据研究中国区域大气NO_2

利用臭氧观测仪（Ozone Monitoring Instrument,OMI）卫星遥感反演的NO2柱浓度数据,分析了自2004年以来中国地区对流层NO2柱浓度（TroNO2）和总NO2柱浓度（TotNO2）的时空特征及其影响的原因.中国区域平均TroNO2和TotNO2呈现上升的趋势,年平均分别增长了4.67%和2....

Characteristics of atmospheric NO2 over China using OMI remote sensing data

The temporal-spatial characteristics of the tropospheric column NO₂ (TroNO₂) and total column NO₂ (TotNO₂) over China is analyzed using remote sensing data derived from OMI sensor. In general, the regional mean values of TroNO₂ and TotNO₂ have an increasing trend over China. The annual increasing rates are 4.67% and 2.21%, respectively. In addition, the TroNO₂ and TotNO₂ present annual variability. During the summer time, the TotNO₂ has the largest value, while the TroNO₂ has the smallest value. In contrast, TroNO₂ has the largest value and the TotNO₂ has a sub-peak value in the winter time. As the TroNO₂ mainly comes from the troposphere in which human activity plays a dominant role, it indicates that the anthropogenic emission NO_x is the main source of atmospheric NO₂ in winter. The large values appear over northern China, Yangtze River Delta and Pearl River Delta regions, which is closely associated with urbanization and economic development. The variability of TroNO₂ and TotNO₂ as well as the ratio of TroNO₂ and TotNO₂ reflects the anthropogenic emission impact. For the change trend, the atmospheric NO₂ is increasing over northern China and Yangtze River Delta regions, and is decreasing over Pearl River Delta region. Our results show that, the TroNO₂ over northern China and Yangtze River Delta region were increased 23.78% and 25.73%, respectively, and the Pearl River Delta region was decreased 34.65% from late 2000 to late 2009. Over the Tibetan Plateau region, the TroNO₂, TotNO₂ and their ratio show a stable annual variability and a parabolic curve. The largest often appears in summertime, implying the pattern of natural emission. In Sichuan Basin, the NO₂ shows another pattern, which is affected by more complex factors. TroNO₂ and TotNO₂ present close correlation, especially in the eastern industrial regions with larger correlation coefficients (correlation coefficients higher than 0.9 and ratios larger than 0.7).