美国加州理工学院
据介绍，气溶胶光吸收已被广泛认为是大城市颗粒物污染恶化的一个促成因素，主要是通过其稳定行星边界层（PBL）的作用。
研究组报告了在冬季雾霾事件中，以吸收为主的气溶胶-辐射相互作用，可以在大范围内降低近地表细颗粒物浓度（PM2.5）。PBL顶部吸收气溶胶的显著升温速率，所产生的“暖泡”效应导致了二次环流，增强了污染（相对清洁）地区的上升运动（向下运动）和辐合（辐散），具有降低近地表PM2.5的净效应。
此外，气溶胶对紫外光的吸收有效地降低了化学物质的光解作用，即气溶胶-光解相互作用，阻碍了臭氧的形成，降低了大气的氧化能力，抑制了气溶胶的二次浓度。他们的模型评估显示，这两种协同效应使近地表PM2.5减少了约7.4%，因此在冬季雾霾事件中，吸光气溶胶的存在可以显著减轻颗粒物污染。
研究人员表示，在天气/气候预测和健康评估模型中，应考虑到这种对气溶胶负荷的负反馈。
附：英文原文
Title: Aerosol light absorption alleviates particulate pollution during wintertime haze events
Author: Wu, Jiarui, Bei, Naifang, Wang, Yuan, Su, Xiaoli, Zhang, Ningning, Wang, Lili, Hu, Bo, Wang, Qiyuan, Jiang, Qian, Zhang, Chenchong, Liu, Yangfan, Wang, Ruonan, Li, Xia, Lu, Yuxuan, Liu, Zirui, Cao, Junji, Tie, Xuexi, Li, Guohui, Seinfeld, John
Issue&Volume: 2024-12-23
Abstract: Aerosol light absorption has been widely considered as a contributing factor to the worsening of particulate pollution in large urban areas, primarily through its role in stabilizing the planetary boundary layer (PBL). Here, we report that absorption-dominated aerosol–radiation interaction can decrease near-surface fine particulate matter concentrations ([PM2.5]) at a large-scale during wintertime haze events. A “warm bubble” effect by the significant heating rate of absorbing aerosols above the PBL top generates a secondary circulation, enhancing the upward motion (downward motion) and the convergence (divergence) in polluted (relatively clean) areas, with a net effect of lowering near-surface [PM2.5]. Furthermore, aerosol absorption of ultraviolet-wave light effectively reduces the photolysis of chemical species, i.e., aerosol–photolysis interaction, hindering ozone formation, reducing atmospheric oxidizing capability, and suppressing secondary aerosol concentrations. Our model assessment reveals that the synergetic two effects decrease near-surface [PM2.5] by around 7.4%, so the presence of light-absorbing aerosols can considerably alleviate particulate pollution during wintertime haze events. Such negative feedbacks to the aerosol loading should be considered in weather/climate prediction and health assessment models.
DOI: 10.1073/pnas.2402281121
Source: https://www.pnas.org/doi/abs/10.1073/pnas.2402281121