The vertical distribution of distinct aerosol components fundamentally governs atmospheric shortwave heating rates and radiative effects. However, traditional data assimilation (DA) methods typically rely on total aerosol optical thickness (AOT) or extinction, which fails to constrain the specific aerosol composition and often leads to the misallocation of aerosol between scattering and absorbing species. To address this limitation, we develop a component-resolved four-dimensional local ensemble transform Kalman filter (4D-LETKF) system with spatial and observational constraints within the WRF-Chem model. This novel system assimilates CALIOP-MODIS synergistic retrievals of species-specific extinction profiles (dust, sea salt, black carbon, and water-soluble aerosols) to explicitly optimize the three-dimensional distributions of individual components over East Asia. Results demonstrate that this DA system successfully reconstructs the complex vertical layering of multi-component aerosols. Notably, it effectively corrects severe underestimations of elevated black carbon (BC) plumes, capturing persistent free-tropospheric BC layers over South Asia that traditional models typically miss. Independent validations against ground-based AERONET and AD-Net lidar observations confirm significant improvements not only in total AOT and extinction but also in the single scattering albedo (SSA). By independently adjusting the mass of scattering and absorbing species, the system corrects local biases in aerosol optical properties. Consequently, the optimized component-specific profiles profoundly affect the atmospheric shortwave radiative heating. The elevated BC plumes induces a pronounced mid-tropospheric warming accompanied by a reduction in lower-tropospheric heating due to the attenuation of downward solar radiation. This study highlights the importance of component-specific vertical constraints for accurately assessing aerosol-induced atmospheric heating and its vertical structure.