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中国可凝颗粒物对大气有机气溶胶和细颗粒物(PM)的影响。

Impacts of condensable particulate matter on atmospheric organic aerosols and fine particulate matter (PM) in China.

作者信息

Li Mengying, Yu Shaocai, Chen Xue, Li Zhen, Zhang Yibo, Song Zhe, Liu Weiping, Li Pengfei, Zhang Xiaoye, Zhang Meigen, Sun Yele, Liu Zirui, Sun Caiping, Jiang Jingkun, Wang Shuxiao, Murphy Benjamin N, Alapaty Kiran, Mathur Rohit, Rosenfeld Daniel, Seinfeld John H

机构信息

Research Center for Air Pollution and Health, Key Laboratory of Environmental Remediation and Ecological Health, Ministry of Education, College of Environment and Resource Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, PR China.

College of Science and Technology, Hebei Agricultural University, Baoding, Hebei 071000, PR China.

出版信息

Atmos Chem Phys. 2022 Sep 13;22(17):11845-11866. doi: 10.5194/acp-22-11845-2022.

Abstract

Condensable particulate matter (CPM) emitted from stationary combustion and mobile sources exhibits high emissions and a large proportion of organic components. However, CPM is not generally measured when conducting emission surveys of PM in most countries, including China. Consequently, previous emission inventories have not included emission rates for CPM. Here, we construct an emission inventory of CPM in China with a focus on organic aerosols (OAs) based on collected CPM emission information. Results show that OA emissions are enhanced twofold after the inclusion of CPM in a new inventory for China for the years 2014 and 2017. Considering organic CPM emissions and model representations of secondary OA (SOA) formation from CPM, a series of sensitivity cases have been simulated here using the three-dimensional Community Multiscale Air Quality (CMAQ) model to estimate the contributions of CPM emissions to atmospheric OA and fine PM (PM, particulate matter with aerodynamic diameter not exceeding 2.5 μm) concentrations in China. Compared with observations at a Beijing site during a haze episode from 14 October to 14 November 2014, estimates of the temporal average primary OA (POA) and SOA concentrations were greatly improved after including the CPM effects. These scenarios demonstrated the significant contributions of CPM emissions from stationary combustion and mobile sources to the POA (51 %-85 %), SOA (42 %-58 %), and total OA concentrations (45 %-75 %). Furthermore, the contributions of CPM emissions to total OA concentrations were demonstrated over the 2 major cities and 26 other cities of the Beijing-Tianjin-Hebei region (hereafter referred to as the "BTH2 + 26 cities") in December 2018, with average contributions of up to 49 %, 53 %, 54 %, and 50 % for Handan, Shijiazhuang, Xingtai, and Dezhou, respectively. Correspondingly, the inclusion of CPM emissions also narrowed the gap between simulated and observed PM concentrations over the BTH2 + 26 cities. These results improve the simulation performance of atmospheric OA and PM and may also provide important implications for the sources of OA.

摘要

固定燃烧源和移动源排放的可凝结颗粒物(CPM)排放量高,且有机成分占比大。然而,在包括中国在内的大多数国家进行颗粒物排放调查时,通常不会对CPM进行测量。因此,以往的排放清单中并未包含CPM的排放率。在此,我们基于收集到的CPM排放信息,构建了以有机气溶胶(OA)为重点的中国CPM排放清单。结果表明,在2014年和2017年中国新的排放清单中纳入CPM后,OA排放量增加了两倍。考虑到有机CPM排放以及CPM生成二次有机气溶胶(SOA)的模型表示,我们在此使用三维社区多尺度空气质量(CMAQ)模型模拟了一系列敏感性案例,以估算CPM排放在中国对大气OA和细颗粒物(PM,空气动力学直径不超过2.5μm的颗粒物)浓度的贡献。与2014年10月14日至11月14日北京一次霾过程中的观测结果相比,纳入CPM影响后,对一次有机气溶胶(POA)和SOA浓度的时间平均值估算有了显著改善。这些情景表明,固定燃烧源和移动源的CPM排放对POA(51%-85%)、SOA(42%-58%)以及总OA浓度(45%-75%)有显著贡献。此外,2018年12月在京津冀地区的2个主要城市和其他26个城市(以下简称“BTH2+26城市”)展示了CPM排放在总OA浓度中的贡献,邯郸、石家庄、邢台和德州的平均贡献分别高达49%、53%、54%和50%。相应地,纳入CPM排放也缩小了BTH2+26城市模拟和观测的PM浓度之间的差距。这些结果改善了大气OA和PM的模拟性能,也可能为OA的来源提供重要启示。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/765b/11770565/ce779fa09008/nihms-2039780-f0001.jpg

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