Year: 2024
Type: article
Abstract: Here, we present modeling evidence of the influences of aerosol feedback on secondary circulations (SCs). The results show that in heavily PM 2.5 polluted Beijing-Tianjin-Hebei (BTH) areas, the aerosol feedback is the primary factor on the occurrence and development of mesoscale SCs in the atmospheric boundary layer. Modeling evidence reveal that the impact of aerosol feedback on SCs is proportional to PM 2.5 concentrations or precursor emissions. During the 2014 Asia-Pacific Economic Cooperation (APEC) with extraordinary emission reduction, the time levels of SCs significantly decreases to ~37.3% of the periods without emission reduction before and after APEC period. The simulated PM 2.5 during APEC are ~47.6% of before and after APEC period, and the measured concentration ratio at 47.7%. The largest variation in SC occurred during the afternoon, which should be related to the stronger solar radiation. We found that the reduction in wind speed caused by aerosol feedback and related convergence and divergence of the air mass play a pivotal role in SCs evolution. Against the background of prevailing westerly winds in BTH, the strengthening and appearance of clockwise SCs caused by aerosol feedback leads to an increase in the frequency of surface easterly U-wind. These phenomena have also been validated in two other emission reduction events and the emission reduction actions in the BTH region in January and July of 2014, 2017, and 2020, respectively. The results of this paper showing substantial impact of aerosol feedback on SCs, which could help promote our understanding of content and level of aerosol feedback to atmospheric changes.
Authors: Jixiang Li, Haipeng Yu, Markku Kulmala, Tom V. Kokkonen, Kai Tang, Jianmin Ma, Zeyong Hu, Siyu Chen, Yuling Hu, Rong Dai, Bofei Zhang, Hongyu Luo, Shu Tao
Language: English
Subfield: Global and Planetary Change
Field: Environmental Science
Domain: Physical Sciences
SDG: Climate action
Open Access status: gold
Estimated APC paid: $3,390
OpenAlex ID: W4405577049
