A review of quantification methods for light absorption enhancement of black carbon aerosol

Black carbon (BC) is a distinct type of carbonaceous aerosol that has a significant impact on the environment, human health, and climate. A non-BC material coating on BC can alter the mixing state of the BC particles, which considerably enhances the mass absorption efficiency of BC by directing more energy toward the BC cores (lensing effect). A lot of methods have been reported for quantifying the enhancement factor (Eabs), with diverse results. However, to the best of our knowledge, a comprehensive review specific to the quantification methods for Eabs has not been systematically performed, which is unfavorable for the evaluation of obtained results and subsequent radiative forcing. In this review, quantification methods are divided into two broad categories, direct and indirect, depending on whether experimental removal of the coating layer from an aged carbonaceous particle is required. The direct methods described include thermal peeling, solvent dissolution, and optical virtual exfoliation, while the indirect methods include intercept-linear regression fitting, minimum R squared, numerical simulation, and empirical value. We summarized the principles, procedures, virtues, and limitations of the major Eabs quantification methods and analyzed the current problems in the determination of Eabs. We pointed out what breakthroughs are needed to improve or innovate Eabs quantification methods, particularly regarding the need to avoid the influence of brown carbon, develop a broadband Eabs quantification scheme, quantify the Eabs values for the emissions of low-efficiency combustions, measure the Eabs of particles in a highhumidity environment, design a real-time monitor of Eabs by a proper combination of mature techniques, and make more use of artificial intelligence for better Eabs quantification. This review deepens the understanding of Eabs quantification methods and benefits the estimation of the contribution of BC to radiative forcing using climate models.