本文评估了直径小于2.5µm的颗粒物(PM2.5)及其组分(黑碳(BC),灰尘,SO4和有机气溶胶(OA))在亚洲,它们来自耦合模型比对项目第六阶段(CMIP6)。此外,表面PM2.5及其成分的未来预测变化,以及他们对人口的接触,还提供了在不同的共享社会经济途径(SSP)方案下的应用。结果表明,表面PM2.5浓度的模拟空间分布与现代研究与应用回顾性分析版本2(MERRA-2)和社会经济数据与应用中心(SEDAC)一致。该模型在气候平均表面PM2.5浓度低/高的地区分布小/大,即,北亚/沙特阿拉伯,伊朗,和中国的新疆。CMIP6的多模式集合再现了亚洲及其次区域的年周期和季节变化的主要特征。在SSP1-2.6,SSP2-4.5和SSP5-8.5的情景下,与1995-2014年的当前时期相比,亚洲的年平均表面PM2.5浓度预计将下降,场景之间存在明显差异。同时,区域范围内变化的幅度和时间有很大不同,下降幅度最大的是南亚(SAS)。在SSP3-7.0下,SAS中表面PM2.5浓度的增加最大,2050年的增加值为8μg/m3;而在SSP370-lowNTCF下,相对于SSP3-7.0,假设空气质量控制措施水平更强,SAS中表面PM2.5浓度降低,东亚(EAS)和东南亚(SEAS)是最大的。季节性趋势的特征与年度趋势的特征一致。表面PM2.5及其组分的浓度趋势相似。预计中亚(CAS)的地表PM2.5浓度的人口加权平均值将下降,EAS,北亚(NAS),还有SEAS,这表明亚洲人口最多的地区的表面PM2.5浓度将下降。在SAS,因为它人口众多,空气污染物对人类健康的影响在未来仍然是灾难性的。总之,亚洲大部分地区的表面PM2.5浓度将下降,这有利于空气质量和人类健康;根据SSP370-lowNTCF,减少短期气候措施(SLCF)将进一步改善空气质量。
This paper evaluates the historical simulated surface concentrations of particulate matter small than 2.5 µm in diameter (PM2.5) and its components (black carbon (BC), dust, SO4, and organic aerosol (OA)) in Asia, which come from Coupled Model Intercomparison Project Phase 6 (CMIP6). In addition, future projected changes of surface PM2.5 and its components, as well as their exposure to population, under the different Shared Socioeconomic Pathway (SSP) scenarios are also provided. Results show that the simulated spatial distribution of surface PM2.5 concentrations is consistent with the Modern-Era Retrospective Analysis for Research and Applications version 2 (MERRA-2) and Socioeconomic Data and Applications Center (SEDAC). The model spreads are small/large over the regions with low/high climatic mean surface PM2.5 concentrations, i.e., Northern Asia/Saudi Arabia, Iran, and Xinjiang Province of China. The multi-model ensemble of CMIP6 reproduces the main features of annual cycles and seasonal variations in Asia and its sub-regions. Under the scenarios of SSP1-2.6, SSP2-4.5, and SSP5-8.5, compared to the present-day period of 1995-2014, annual mean surface PM2.5 concentrations are projected to decrease in Asia, with obvious differences among the scenarios. Meanwhile, the magnitudes and timings of changes at the regional scale are quite different, with the largest decreases in South Asia (SAS). Under SSP3-7.0, the increase of surface PM2.5 concentrations in SAS is the largest, with the increase value of 8 μg/m3 in 2050; while under SSP370-lowNTCF, which assumes stronger levels of air quality control measures relative to the SSP3-7.0, the decreases of surface PM2.5 concentrations in SAS, East Asia (EAS) and Southeast Asia (SEAS) are the largest. The characteristics of seasonal trends are consistent with that of the annual trend. The trends in the concentrations of surface PM2.5 and its components are similar. The population-weighted average values of surface PM2.5 concentrations are projected to decrease in Central Asia (CAS), EAS, North Asia (NAS), and SEAS, and it indicates that the surface PM2.5 concentrations over the most populated area of Asia will decrease. In SAS, because of its large population, the impact of air pollutants on human health is still disastrous in the future. In summary, the surface PM2.5 concentrations over the most area of Asia will decrease, which is beneficial to air quality and human health; under SSP370-lowNTCF, the reduction of short-lived climate forcers (SLCFs) will further improve air quality.