气候变化领域集成服务门户(CCPortal): A novel method of retrieving low visibility during heavily polluted episodes in the North China plain

CCPortal

DOI	10.1016/j.aeaoa.2021.100101
	A novel method of retrieving low visibility during heavily polluted episodes in the North China plain
	Shen, Xiaojing; Sun, Junying; Zhang, Xiaoye; Wang, Hong; Zhou, Chunhong; Zhang, Yangmei; Zhong, Junting; Liu, Zhaodong; Xia, Can; Hu, Xinyao; Zhang, Sinan
通讯作者	Shen, XJ (通讯作者)，Chinese Acad Meteorol Sci, State Key Lab Severe Weather, Beijing 100081, Peoples R China. ; Shen, XJ (通讯作者)，Chinese Acad Meteorol Sci, Key Lab Atmospher Chem CMA, Beijing 100081, Peoples R China.
发表日期	2021
EISSN	2590-1621
卷号	9
英文摘要	The prediction of visibility is an ongoing problem in air quality models, particularly that of low visibility during heavily polluted episodes. In this study, a new method of calculating visibility based on the particle mass concentration of PM2.5 (particles with diameter <= 2.5 mu m) and relative humidity (RH), data for which are generally available in most regions of China, is developed. The method also considers the particle number size distribution (PNSD) and hygroscopic parameter (kappa), and focuses on visibility below 10 km. First, the PNSD was re-constructed under dry condition (PNSDdry,rec) based on the relationship between PM2.5 and the particle volume size distribution modal parameters obtained in a previous study conducted in the North China Plain. Then, the ambient PNSD (PNSDamb,rec) was retrieved based on the PNSDdry,rec and kappa, and the light extinction was calculated by applying the Mie code (sigma(ext,amb)). Finally, the visibility was calculated based on the Koschmieder experimental equation, and denoted as Vis(cal). A parameterization scheme was proposed based on the sigma(ext,amb), PM2.5, and RH to simulate the visibility (Vis(simu)), which is more applicable than the theoretical calculation described above. This method was validated at different locations in different regions in China. The values calculated by the scheme showed agreed well with the observed data in general, especially for low visibility of <= 5 km, associated with severe haze. Although a large bias occurred at some sites, both the hourly and daily averages for almost every event with visibility lower than 5 km were captured. The method reported in this work exhibited smaller bias below 2 km than the other visibility parameterization scheme, and will be available for improving the prediction of visibility in air quality models.
英文关键词	Low visibility prediction; Particle hygroscopicity; Particle number size distribution; Light extinction parameterization
语种	英语
WOS研究方向	Environmental Sciences & Ecology ; Meteorology & Atmospheric Sciences
WOS类目	Environmental Sciences ; Meteorology & Atmospheric Sciences
WOS记录号	WOS:000628672400002
来源期刊	ATMOSPHERIC ENVIRONMENT-X
来源机构	中国科学院西北生态环境资源研究院
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/254690
作者单位	[Shen, Xiaojing; Sun, Junying; Zhang, Xiaoye; Wang, Hong; Zhou, Chunhong; Zhang, Yangmei; Zhong, Junting; Liu, Zhaodong; Xia, Can; Hu, Xinyao; Zhang, Sinan] Chinese Acad Meteorol Sci, State Key Lab Severe Weather, Beijing 100081, Peoples R China; [Shen, Xiaojing; Sun, Junying; Zhang, Xiaoye; Wang, Hong; Zhou, Chunhong; Zhang, Yangmei; Zhong, Junting; Liu, Zhaodong; Xia, Can; Hu, Xinyao; Zhang, Sinan] Chinese Acad Meteorol Sci, Key Lab Atmospher Chem CMA, Beijing 100081, Peoples R China; [Sun, Junying] Chinese Acad Sci, Northwest Inst Ecoenvironm & Resources, State Key Lab Cryospher Sci, Lanzhou 730000, Peoples R China; [Zhong, Junting] Univ Chinese Acad Sci, Beijing 100049, Peoples R China; [Liu, Zhaodong; Xia, Can] Nanjing Univ Informat Sci & Technol, Nanjing 210000, Peoples R China
推荐引用方式 GB/T 7714	Shen, Xiaojing,Sun, Junying,Zhang, Xiaoye,et al. A novel method of retrieving low visibility during heavily polluted episodes in the North China plain[J]. 中国科学院西北生态环境资源研究院,2021,9.
APA	Shen, Xiaojing.,Sun, Junying.,Zhang, Xiaoye.,Wang, Hong.,Zhou, Chunhong.,...&Zhang, Sinan.(2021).A novel method of retrieving low visibility during heavily polluted episodes in the North China plain.ATMOSPHERIC ENVIRONMENT-X,9.
MLA	Shen, Xiaojing,et al."A novel method of retrieving low visibility during heavily polluted episodes in the North China plain".ATMOSPHERIC ENVIRONMENT-X 9(2021).