Effective identification of aerosol type is the basis of accurate quantification of aerosol -climate and aerosolenvironment interactions. However, there are different aerosol category settings and identifying parameter selections among different aerosol identification methods, which causes incoherence in data comparisons and uncertainty in quantifying thier climate and environment effects. To bridge the gap, this study establishes spatial correlations and aerosol type conversion relationships among four commonly -used aerosol identification methods, which includes AOD-AE, AE -SSA, FMF-SSA, and SAE-AAE. Aerosol optical properties observed at 37 typical AERONET sites are selected as the testbed, including marine, desert dust, clean continent, urban industry, and biomass burning sites. Results show that marine and desert dust aerosols are the most effectively identified types, while urban industry and biomass burning aerosols overlap much in the identification spaces since they contain similar chemical components. Dust and marine aerosol generally have the best agreement among the four identification methods, because desert dust and marine particles have distinctive chemical components from other kinds, thus the category setting from the perspective of emission source, light absorbing ability, or chemical components has less influence on the identification results. Spatial correlation between the four commonly -used aerosol identification methods futher refines the correspondence of aerosol category, light absorption capacity, and chemical components. And we find that uncertain aerosols defined in FMF-SSA are mostly marine aerosols.
