期刊
ENVIRONMENTAL RESEARCH COMMUNICATIONS
卷 3, 期 7, 页码 -出版社
IOP Publishing Ltd
DOI: 10.1088/2515-7620/ac0e0b
关键词
cloud condensation nuclei; aerosol; supersaturation; hygroscopicity; closure analysis
资金
- NASA
- U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research, Climate and Environmental Sciences Division
The study reveals that properties and source regions of aerosols can impact CCN concentrations. Particle size is identified as the most critical factor influencing aerosol activation ability.
The activation ability of aerosols as cloud condensation nuclei (CCN) is crucial in climate and hydrological cycle studies, but their properties are not well known. We investigated the long-term measurements of atmospheric aerosol properties, CCN concentrations (N-CCN) at supersaturation (SS = 0.1%-1.0%), and hygroscopicity at the Department of Energy's Southern Great Plains (SGP) site to illustrate the dependence of N-CCN on aerosol properties and transport pathways. Cluster analysis was applied to the back trajectories of air masses to investigate their respective source regions. The results showed that aged biomass burning aerosols from Central America were characterized by higher accumulation mode particles (N-accu; median value 805 cm(-3)) and relatively high aerosol hygroscopicity (kappa; median value similar to 0.25) values that result in the higher CCN activation and relatively high N-CCN (median value 258-1578 cm(-3) at a SS of 0.1%-1.0%). Aerosols from the Gulf of Mexico were characterized by higher N-accu (similar to 35%), and N-CCN (230-1721 cm(-3) at a SS of 0.1%-1.0%) with the lowest kappa (similar to 0.17). In contrast, relatively high nucleation mode particles (N-nucl; similar to 20%) and low N-CCN (128-1553 cm(-3) at a SS of 0.1%-1.0%) with higher kappa (similar to 0.30) values were observed on the aerosols associated with a westerly wind. The results indicate particle size as the most critical factor influencing the ability of aerosols to activate, whereas the effect of chemical composition was secondary. Our CCN closure analysis suggests that chemical composition and mixing state information are more crucial at lower SS, whereas at higher SS, most particles become activated regardless of their chemical composition and size. This study affirms that soluble organic fraction information is required at higher SS for better N-CCN prediction, but both the soluble organics fraction and mixing state are vital to reduce the N-CCN prediction uncertainty at lower SS.
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