基于卫星遥感的大气污染物和温室气体排放反演

Satellite-based emission inversion for air pollutants and greenhouse gases

中文关键词:  排放反演, 大气污染物, 温室气体, 卫星遥感

英文关键词:emission inversion, atmospheric pollutants, greenhouse gases, satellite observation

中文摘要:

      基于卫星遥感的大气污染物和温室气体排放反演研究，为全面认识这些关键大气成分来源、精准实施减排措施提供了不可或缺的信息和数据基础。国内外相关研究在过去二十年中有了长足的发展，其中我国学者为领域发展做出了重要贡献，同时也对我国环境保护和碳中和事业提供了重要的科学支撑。在中国气象学会成立100周年之际，文中系统梳理我国学者近二十年来在星基排放反演方面的研究进展。首先，对常用排放反演方法进行简要总结，包括资料同化、局地质量平衡、高斯模型、二维模型、机器学习等。在此基础上，展示我国学者在氮氧化物（NOx）、氨气（NH3）、甲醛（HCHO）、乙二醛（CHOCHO）、二氧化硫（SO2）和一氧化碳（CO）等大气污染物，以及二氧化碳（CO2）和甲烷（CH4）等温室气体排放（和碳汇）反演的研究成果。最后，探讨反演方法和反演物种的历史演化进程、当前所面临的主要挑战和未来可能的发展方向，以期进一步推动大气污染物和温室气体排放的准确定量。

英文摘要:

      Satellite-based emission inversions of atmospheric pollutants and greenhouse gases provide indispensable information and data foundation for a comprehensive understanding of the sources of these key atmospheric compositions and for the precise implementation of emission reduction measures. Great advances have been made in the field of emission inversion over the past two decades, with Chinese domestic scholars making substantial contributions, which have provided important scientific support for environmental protection and carbon neutrality in China. In celebrating the 100th anniversary of the Chinese Meteorological Society, this paper systematically reviews the research progress of Chinese scholars in satellite-based emission inversion in the past two decades. Several widely used inversion methods, including data assimilation, local mass balance, Gaussian models, two-dimensional models and machine learning, are briefly summarized. Emission inversion studies of atmospheric pollutants, including nitrogen oxides (NOx), ammonia (NH3), formaldehyde (HCHO), glyoxal (CHOCHO), sulfur dioxide (SO2) and carbon monoxide (CO), as well as greenhouse gases, including carbon dioxide (CO2) and methane (CH4) performed by Chinese scholars are then presented. Finally, the historical evolution of inversion methods and target species, challenges in current satellite-based emission inversion and future research directions are discussed to promote more accurate quantification of atmospheric pollutants and greenhouse gas emissions.