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. Knowledge of the composition of atmospheric aerosols is importantfor reducing uncertainty in climate assessment. In this study, animproved algorithm is developed for the retrieval of atmospheric columnaraerosol components from optical remote sensing data. This is achieved byusing the complex refractive index (CRI) of a multicomponent liquid systemin the forward model and minimizing the differences with the observations.The aerosol components in this algorithm comprise five species, combiningeight subcomponents including black carbon (BC), water-soluble organic matter (WSOM) andwater-insoluble organic matter (WIOM), ammonium nitrate (AN), sodiumchloride (SC), dust-like content (DU), and aerosol water content in the fine andcoarse modes (AWf and AWc). The calculation of the CRI in themulticomponent liquid system allows for the separation of the water-soluble components(AN, WSOM and AWf) in the fine mode and SC and AWc in thecoarse mode. The uncertainty in the retrieval results is analyzed based onthe simulation of typical models, showing that the complex refractive indexobtained from instantaneous optical–physical inversion compares well withthat obtained from chemical estimation. The algorithm was used to retrievethe columnar aerosol components over China using the ground-based remotesensing measurements from the Sun–sky radiometer Observation NETwork (SONET)in the period from 2010 to 2016. The results were used to analyze theregional distribution and interannual variation. The analysis shows that theatmospheric columnar DU component is dominant in the northern region ofChina, whereas the AW is higher in the southern coastal region. The SCcomponent retrieved over the desert in northwest China originates from apaleomarine source. The AN significantly decreased from 2011 to 2016, by21.9 mg m−2, which is inseparable from China's environmental controlpolicies.

Improved inversion of aerosol components in the atmospheric column from remote sensing data