Assessment of the impacts of aromatic VOC emissions and yields of SOA on SOA concentrations with the air quality model RAMS-CMAQ

被引:36
|
作者
Li, Jialin [1 ,2 ]
Zhang, Meigen [1 ,2 ,3 ]
Wu, Fangkun [1 ]
Sun, Yele [1 ,2 ]
Tang, Guigian [1 ]
机构
[1] Chinese Acad Sci, IAP, State Key Lab Atmospher Boundary Layer Phys & Atm, Beijing 100029, Peoples R China
[2] Univ Chinese Acad Sci, Beijing, Peoples R China
[3] Chinese Acad Sci, Inst Urban Environm, Ctr Excellence Urban Atmospher Environm, Xiamen, Peoples R China
基金
中国国家自然科学基金;
关键词
Secondary organic aerosol; Volatile organic compounds; RAMS-CMAQ; Fine particles; China; SECONDARY ORGANIC AEROSOL; CHEMICAL-TRANSPORT MODEL; BASIS-SET APPROACH; CARBONACEOUS AEROSOL; SOURCE APPORTIONMENT; BIOGENIC EMISSIONS; SICHUAN BASIN; CHINA; URBAN; GAS;
D O I
10.1016/j.atmosenv.2017.03.035
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The secondary organic aerosol (SOA) concentration is generally underestimated by models. Recent studies suggest that the underprediction is related to underestimations of aromatic volatile organic compound (VOC) emissions and SOA yields in current models. Here, the impacts of these two factors in China were investigated with the regional air quality modeling system RAMS-CMAQ referring to field observations during the episode from October 14 to November 14, 2014. Comparisons between the observed and modeled SOA of four sensitivity simulation cases indicated the significant impacts of the two underestimated factors on the SOA output. By considering these two aspects, the simulated mean SOA concentrations significantly increased by nearly 4 times with a good representation of the intensively temporal variations of concentrations, which were largely controlled by photochemical processes rather than meteorological conditions. The improvement in SOA compensated for the underestimations by approximately 23.5% and contributed to the mean fraction of SOA to organic aerosol (OA) by increasing the fraction from less than 7% to more than 25%, which was closer to the observed result. These results suggested a more reasonable and more realistic representation of SOA formation in the model after allowing for the two factors. Due to the better simulation of SOA, predictions of OA were correspondingly improved when the correlation coefficient increased from 0.57 to 0.73 and other bias parameters were reduced, which indicated the improved ability of our model to trace the temporal variations of OA. Based on the improved simulation throughout the episode, the mean SOA concentration was obviously higher in eastern China than in the west. The highest concentration appeared in the Sichuan Basin and Pearl River Delta (PRD) areas, with values of 6-11 mu g/m(3) and 8-17 mu g/m(3), respectively. Over the wide regions of central and eastern China, the dominant component in SOA was formed from anthropogenic sources (ASOA), generally accounting for more than 60%. (C) 2017 Elsevier Ltd. All rights reserved.
引用
收藏
页码:105 / 115
页数:11
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