Char and soot represent distinct types of elemental carbon (EC) with varying sources and physicochemical properties. However, quantitative studies in sources, atmospheric processes and light-absorbing capabilities between them remain scarce, greatly limiting the understanding of EC's climatic and environmental impacts. For in-depth analysis, concentrations, mass absorption efficiency (MAE) and stable carbon isotope were analyzed based on hourly samples collected during winter 2021 in Nanjing, China. Combining measurements, atmospheric transport model and radiative transfer model were employed to quantify the discrepancies between char-EC and soot-EC. The mass concentration ratio of char-EC to soot-EC (R-C/S) was 1.4 +/- 0.6 (mean +/- standard deviation), showing significant dependence on both source types and atmospheric processes. Case studies revealed that lower R-C/S may indicate enhanced fossil fuel contributions, and/or considerable proportions from long-range transport. Char-EC exhibited a stronger light-absorbing capability than soot-EC, as MAE(char) (7.8 +/- 6.7 m(2)g(-1)) was significantly higher than MAE(soot) (5.4 +/- 3.4 m(2)g(-1))(p < 0.001). Notably, MAE(char) was three times higher than MAE(soot) in fossil fuel emissions, while both were comparable in biomass burning emissions. Furthermore, MAE(soot) increased with aging processes, whereas MAE(char) exhibited a more complex trend due to combined effects of changes in coatings and morphology. Simulations of direct radiative forcing (DRF) for five sites indicated that neglecting the char-EC/soot-EC differentiation could cause a 10 % underestimation of EC's DRF, which further limit accurate assessments of regional air pollution and climate effects. This study underscores the necessity for separate parameterization of two types of EC for pollution mitigation and climate change evaluation.

Atmospheric black carbon (BC) is the most important aerosol contributor to global warming. However, there is a lack of understanding about the climate impact of BC aerosols because of systematic discrepancies between model and observation estimates of light absorption enhancements (Eabs) in atmospheric processes after emissions, and such discrepancies are transferred directly into large uncertainties of aerosol radiative forcing assessments. In this study, we quantify Eabs of atmospheric BC aerosols with diverse particle morphology distributions using a multi-dimensional aerosol model. We show that current widely used Mie method may overestimate BC Eabs by similar to 50% because variations in particle morphology are not considered. Although absorption calculation can be improved by including complex particle morphology and heterogeneity in composition, we find that neglect of the diverse particle morphology distributions in modeling may lead to 15% similar to 30% relative deviations on Eabs estimations of BC aerosol ensembles. The results thus imply that particle morphology distribution should be included in models to accurately represent the radiative effects of BC aerosols.