Locating the missing absorption enhancement due to multi‒core black carbon aerosols
Xiyao Chen, Joseph Ching, Feng Wu, Hitoshi Matsui, Mark Z. Jacobson, Fan Zhang, Yuanyuan Wang, Zexuan Zhang, Dantong Liu, Shupeng Zhu, Yinon Rudich, Zongbo Shi, Hanjin Yoo, Ki‐Joon Jeon, Weijun Li
Abstract
Black carbon (BC) aerosols, with their strong light-absorbing ability, are major drivers of the global climate. In existing models, BC aerosols are simplified as a single core when determining radiative effects. Here, we found that 21% of BC aerosols contain multiple cores during a wildfire smoke observation. By considering dynamic effective medium approximation (DEMA) with Mie theory and assuming randomly distributed multi‒core BC, the light absorption was 1.81 times greater than that under the single‒core assumption for particles with overall diameters >400 nm and core diameters >200 nm. A machine learning emulator was developed for DEMA-based absorption enhancements and incorporated into a global atmospheric model. For global aerosol absorption, multi‒core BC particles lead to a 19% increase, especially in wildfire-affected regions. This study emphasizes the critical role of multi‒core BC particles in amplifying radiative forcing and the necessity to revise models for the simulation of BC climate impact. Wildfire observations reveal that 21% of black carbon aerosols contain multiple cores, and accounting for this morphology increases global absorption by 19%, highlighting a missing source of radiative forcing in current models.