Objective Light-absorbing aerosols have a huge impact on visibility. The atmospheric pollution they cause can pose serious risks to human health. Quantitatively assessing the optical properties and spatiotemporal distribution of light-absorbing aerosols is of vital importance for decision-making in the management and control of complex air pollution. The dynamic changes in the physicochemical properties of light-absorbing aerosols, along with their temporal and spatial heterogeneity, introduce significant uncertainties in simulating their radiative forcing. The challenges arise from difficulties in accurately estimating particle size distribution, chemical composition, and mixed state, impeding precise retrievals through satellite remote sensing, with common model simulations and radiative transfer equations assuming the presence of external mixing for light-absorbing aerosols. However, research indicates that, especially in regions prone to pollution events like East Asia, South Asia, and Southeast Asia, a core-shell mixed state, with black carbon as the core and scattering aerosols like sulfates and nitrates as the shell, best represents the prevailing state of light-absorbing aerosols. Rough assumptions about aerosol states not only introduce significant errors in simulating aerosol number and mass concentrations in the atmosphere but also lead to substantial uncertainties in estimating overall radiative forcing. Methods Data from both satellite and in situ measurements are employed in the present study. First, we employ the AERONET aerosol optical depth (AOD) dataset to identify polluted days at three selected sites, and we match it in space and time with the single scattering albedo (SSA) dataset combined with the TROPOMI ultraviolet (UV) SSA dataset. Second, we utilize the Mie optical model across various combinations of core and shell sizes to establish a preliminary SSA map. Subsequently, we use SSA data from six different wavebands to constrain the SSA output from the Mie model. All calculations are conducted at a daily and grid-level resolution. Upon obtaining probability distributions for core size, shell size, and their corresponding SSA and absorption coefficient (ABS) values, we then apply spatial relationships between the column total absorbing aerosol optical depth (AAOD) from TROPOMI, single-particle absorption, and size distribution. This allows us to assess the column value of black carbon mass concentration and particle number concentration. Results and Discussions Spatial distribution of the mean absorption coefficient obtained from the Mie model simulations during periods of severe pollution shows that the absorption coefficient of the Beijing station is generally higher, with values mainly concentrated between 0. 05 and 0. 07. This indicates a higher presence of light-absorbing aerosols during this period. For the Hong Kong station, most of the absorption coefficients are below 0. 1, with the majority falling below 0. 2 and a low standard deviation of less than 0. 02. Factors related to topography and wind patterns are the primary reasons for the lower values observed in the Hong Kong station (Fig. 3). After applying spatial relationships between the column total AAOD from TROPOMI, the results show that the particle concentrations in the column at the Beijing station generally fall within the range of 3 x 10(19)-5 x 10(19) grid(-1). The number concentrations in Hong Kong are relatively lower than those in Beijing. Except for a few grid points where concentrations reach 2. 5 x 10(19) grid(-1), the overall value range in Hong Kong between 1 x 10(19) and 2 x 10(19) grid(-1). For the Seoul station, particle concentration range is from 1. 5 x 10(19) to 3. 0x 10(19) grid(-1) (Fig. 4). By considering the particle size distribution of black carbon aerosols under the core-shell mixed state simulated by the Mie model, the results of the spatial distribution of black carbon aerosol column mass concentration at each grid point (Fig. 6) shows that over 60% of the area of Beijing have concentrations exceeding 500 kg/grid. In the Hong Kong area, apart from certain regions within the Pearl River Delta urban cluster where black carbon column mass exceeds 500 kg/grid, the values in other areas are below 300 kg/grid. In addition, Seoul has an overall column mass concentration of less than 300 kg/grid.

Absorbing aerosols uniquely impact radiation, aerosol transport, and meteorology. This paper quantifies black carbon core and sulphate shell size and mass using decadal measurements of multi-spectral aerosol optical depth, single scattering albedo, and angstrom exponent from Aerosol Robotic Network stations located throughout East, Southeast, and South Asia, in connection with a MIE model. All sites are uniquely characterized into four types: urban, biomass burning, long-range transport, and clean. Unique size and mass probability distributions of both the core and shell are calculated within each classification. Well known urban, biomass burning, and clean sites are all properly identified. Furthermore, two unique sites previously thought to not have multiple characteristics are identified, with urban and biomass burning significant in Beijing and long-range transport significant in the otherwise clean South China Sea at Taiping Island. It is hoped that these results will allow for advances in attribution and radiative forcing studies. Plain Language Summary Black Carbon strongly absorbs visible radiation, leading to unique impacts on atmospheric radiation, climate, the water cycle, and PM2.5. This work attributes different aerosol source characteristics, and further specifies the size distribution and concentration of aerosol black carbon cores and refractive shells. This work uses measurements of aerosol optical depth, single scatter albedo, and angstrom exponent, across multiple different wavelengths of light, in combination with statistics and a MIE model (physical model of aerosol/radiation interaction) using a Core-Shell approximation. The results show that aerosols observed in East, Southeast, and South Asia can be uniquely classified into four types: urban, biomass burning, long-range transport, and clean. These results are consistent in terms of aerosol size and mass at each site within each type of characterization. Furthermore, two unique sites are identified in which a second characteristic occurs some significant fraction of every year, which otherwise was not known or previously identified in the literature. These results are expected to help enhance the understanding of attribution of aerosols, as well as provide specific size and mass details of the aerosols useful to improve radiative forcing models and aerosol impacts on climate change. Key Points Aerosols are categorized into biomass burning, urban, and long-range types over Asia using decadal long multi-spectral measurements Based on multiple Aerosol Robotic Network Single Scatter Albedo measurements and a MIE model, physical characteristics of different aerosol types are deduced Most aerosols are found to be mixed, with two sites having different characteristics during different times of the year