气溶胶在气候变化、区域环境和公共健康方面起到重要作用。但由于其空间差异和时间变化特征，当前基于地面站网或极轨卫星的观测方法都不足以全面揭示气溶胶的时空规律。本研究拟利用国产新一代静止卫星风云四号多通道扫描成像辐射计（AGRI）的高时频观测优势，针对中国地区大气污染条件下的气溶胶特性，充分考虑气溶胶参数和观测几何的日变化特征，发展兼具高时空分辨率的静止卫星气溶胶反演算法。内容主要包括：1）基于辐射传输的正演模拟，分析不同散射角度和不同相对湿度条件下气溶胶光学参数敏感性和不确定性；2）结合地面AERONET观测数据，充分利用大气化学模式的气溶胶成分预测信息，优化气溶胶光学参数的动态表达，约束卫星反演的不确定性；3）最终构建基于风云四号AGRI的气溶胶参数日变化特征反演算法，验证反演精度并分析误差来源。研究结果有助于提高国产卫星的气溶胶定量监测能力，可为气候变化研究及大气污染控制提供数据支撑。

Aerosols play an important role in climate change, regional environment and public health. However, because of spatial and temporal variations of aerosol physical and chemical properties, current observation methods based on ground stations or polar orbit satellites, are hard to fully reveal the spatio-temporal variation patterns of aerosols. Taking a full consideration of the diurnal variation of aerosol parameters in the condition of severe air pollution across China, this research attempts to use high time-frequency character of the instrument (the Advanced Geostationary Radiation Imaging) AGRI onboard the new generation geostationary satellite FY-4 to develop a new aerosol retrieval algorithm. The research includes three main aspects: (1) to analyze the sensibility of optical parameters of complex aerosol particles under different scattering angles and relative humidity, based on forward radiation simulation; (2) to optimize the dynamic expression of aerosol’s optical parameters and constrain the uncertainties of the inverse algorithm of satellites, by combining surface AERONET observations and the aerosol composition forecasts of the Chemical Transport Model (CTM); and (3) to develop the aerosol retrieval algorithm that considers diurnal changes of aerosol parameters based on FY-4 AGRI, and to validate the retrievals and analyze sources of errors. The results of this research may help enhance the aerosol spatial mapping ability of domestic satellites, as well as provide essential data to support the researches on air pollution control methodology and the interaction of aerosols with climate change.