基于OMI数据的长三角地区NOx排放清单校验

近年来伴随着我国经济的持续增长，人为源氮氧化物排放居高不下，导致我国区域大气复合污染日趋严重. NO_x排放清单对于大气复合污染研究具有极为重要的意义.为了降低NO_x排放清单的不确定性，基于OMI卫星观测的对流层NO₂柱浓度资料，结合WRF-CMAQ模型系统，对2014年长三角区域NO_x排放清单进行了校验，对于该清单的不确定性进行了初步评估.结果表明，基于长三角地区2014年大气污染物排放清单，利用WRF-CMAQ系统模拟所获得的区域NO₂柱浓度平均值（4.66×1015~10.58×1015 mole/cm2）与OMI卫星数据（3.49×1015~11.47×1015 mole/cm2）较为接近，并且相关性较好（平均R=0.65），归一化平均偏差（NMB）在-7.71%~33.52%之间，平均偏差（Bias）在0.06~0.28之间，可以在一定程度上说明2014年长三角区域NO_x排放总量基本能够反映区域NO₂污染状况.对比分析了OMI卫星遥感资料与CMAQ模型模拟结果，二者NO₂柱浓度空间分布情况总体一致，然而，苏南、上海和浙北等工业较发达地区OMI卫星NO₂柱浓度低于CMAQ模型模拟值，周边经济欠发达地区OMI卫星数据高于CMAQ模型模拟值，表明空间分布仍有进一步优化的空间.利用近地面卫星观测数据与CMAQ模型模拟结果对比，可得近地层观测ρ（NO₂）高于模拟结果，说明仅仅利用地面观测数据验证模型模拟结果存在一定偏差.研究显示，NO_x排放清单模型模拟结果在总量和时间变化方面与OMI卫星资料一致，在空间分配方面存在一定偏差. 

Verification of NOx Emissions in the Yangtze River Delta Region based on OMI Data

In recent years, with the continuous growth of China's economy, anthropogenic emissions of nitrogen oxides remain high, causing regional air pollution. In order to investigate the uncertainty of the NO_x emissions inventory, the NO₂ tropospheric column data from OMI satellite, combined with the WRF-CMAQ modeling system were applied to verify the regional NO_x emissions inventory in the Yangtze River Delta (YRD) region, and the uncertainty of the NO_x emissions inventory was assessed. The results show that, based on the NO_x emissions inventory of the Yangtze River Delta in 2014, the average value of the regional NO₂ column density (4.66×1015-10.58×1015 mole/cm2) obtained from the WRF-CMAQ model and average OM INO₂ tropospheric column density (3.49×1015-11.47×1015 mole/cm2) were close to each other. The correlation was good (average R=0.65), the normalized mean bias (NMB) was from -7.71% to 33.52%, and the bias was between 0.06 and 0.28. Generally, the total amount of NO_x emissions in the YRD region in 2014 could basically reflect the regional NO₂ pollution situation. The study showed that the simulation results of NO_x emissions inventory were consistent with satellite data in total amount and spatial allocation. However, the satellite NO₂ column densities were lower than those simulated from CMAQ in south of Jiangsu, Shanghai, north of Zhejiang and other industrial areas, though in the surrounding economically underdeveloped areas the result was the opposite. This shows that the spatial distributions still need further optimization. By comparing the observed data with the model predicted results, we determined that the NO₂ concentrations of the near ground observation were higher than the model predicted data, which indicates that there would be some deviations in the results if only the ground observation data were used to verify the model results. The results show that the simulation results of NO_x emission inventory are consistent with the satellite data in terms of total amount and time, but there are some deviations in the spatial distribution.