## 7 Conclusions  
In this study, we have investigated the potential to retrieve aerosol properties and the analysis of sources of retrieval errors, based on numerical experiments using simulated observations in five bands of CAPI on board TanSat. A forward model comprising a linearized Mie code, a trace gas absorption and Rayleigh scattering model, a surface parameterization and a linearized vector radiative transfer model are introduced. In the simulations, we assume a mono-modal aerosol, with a lognormal PSD and a Gaussian-model aerosol profile distribution. The retrieved parameters include five aerosol properties and one surface parameter. The Jacobians of simulated radiances and polarizations with respect to AOD at different observation geometries are discussed. The retrieval sensitivity specified by the DFS and the retrieval errors are analyzed and compared at different viewing geometries, as well as with multi-angle retrieval for four of the main components of the natural mixed aerosol. In the nadir view mode of CAPI, we find that of all of the retrieval parameters, the lowest DFS is obtained for the PSD mode radius (0.55 on average), as well as large posterior error (70%), while the DFS for AOD is always close to 1.0. The range of the total DFS from 3.05-4.83 and the variability of retrieval errors among the different aerosol types confirm the sensitivity of CAPI observations to aerosol microphysical properties. When retrieval is performed with measurements at three along-track viewing angles (\(\pm 16^{\circ}\), nadir), there is additional information for all aerosol properties, with the average increase of the DFS being  
Figure 7: The correlation matrices of retrieval variables for four types of aerosols (four rows): dust (**a**,**b**), soot (**c**,**d**), sea salt (**e**,**f**) and sulfate (**g**,**h**). The left column is in nadir viewing mode, and the right column is in multi-angle mode. 0.31 and the posterior error reduced by a maximum of 23%. By adding another two measurements from other viewing geometries in the retrieval, the aerosol information obtained is improved, and the posterior error can decrease again, from 2%-6%, showing that it is worthwhile to fly CAPI in target mode instead of nadir-only mode. When CAPI works in nadir viewing, the different VZA in the wide FOV of the satellite has little impact on the aerosol information and retrieval error, related to the aerosol phase function. In addition to posterior error, we also analyze the smoothing errors, instrument noise and forward model parameter errors. The results show that the a priori uncertainty is the dominating source of posterior error. Moreover, retrieval errors for sea salt and sulfate are not sensitive to the inaccuracies of aerosol profile distribution, but they result in large errors for dust and soot. Additionally, not only the dependence of surface albedo on wavelength, but also the surface albedo value affects aerosol information content. The error correlation coefficients between the surface parameter and AOD for all aerosols indicate that their different optical properties result in a different strength of correlation between surface reflection and aerosol effects. Multi-angle retrieval can reduce this correlation too some extent for dust. In recent CO\({}_{2}\) retrieval algorithms, an aerosol model has been added to produce a realistic atmosphere, and the performance of imperfect characterization of the aerosol is proven dominative in CO\({}_{2}\) retrieval uncertainties [11]. Thus, aerosol properties synchronously retrieved from CAPI measurements could help to reduce CO\({}_{2}\) retrieval errors for TanSat. It should be noted that the analysis of the retrieval of aerosol properties and error sources in this study is preliminary and accounts only for the impact of different observation geometries and the number of angles for multi-angle observation, as well as a number of pure aerosol types. The effect of aerosols on high precision greenhouse gas retrieval will be considered in future studies.