Changes in wintertime visibility across China over 2013-2019 and the drivers: A comprehensive assessment using machine learning method
文献类型：期刊论文
| 作者 | Chen, Lu2,6; Zhang, Fang6; Ren, Jingye1; Li, Zhigang2; Xu, Weiqi3; Sun, Yele3; Liu, Lingling4; Wang, Xinming5 |
| 刊名 | SCIENCE OF THE TOTAL ENVIRONMENT
 |
| 出版日期 | 2024-02-20 |
| 卷号 | 912页码:11 |
| 关键词 | Visibility PM2.5 Meteorology Aerosol hygroscopic growth China |
| ISSN号 | 0048-9697 |
| DOI | 10.1016/j.scitotenv.2023.169516 |
| 英文摘要 | Effective emission reduction measures have largely lowered the particulate concentration in China, but low -visibility events still occur frequently, greatly affecting people's daily life, travel, and health. In the context of carbon neutrality strategy and climate change, the mechanisms governing visibility changes may be undergoing a transformation. To address this critical issue, we have undertaken a comprehensive assessment by employing a novel approach that combines site observations, model-derived datasets, and machine learning techniques. Our analysis of the dataset shows varying degrees of improvement in wintertime visibility in regions such as North China, South China, and the Fenwei Plain over 2013-2019, but an unexpected deterioration (approximately 1 km yr(-1)) in central and southern China (CSC). We further elucidate key roles of PM2.5 reduction in these regions with visibility improvement; whereas the unsatisfactory visibility trend in CSC was caused by combined effect of relative humidity (RH) increase (47 %), aerosol hygroscopicity (kappa) enhancement (9 %), and boundary layer (BLH) reduction (8 %), which greatly overwhelms the effect of PM2.5 reduction recently. Moreover, the study reveals a growing influence of RH on the wintertime visibility, reaching 40 % +/- 24 % to the total contribution in 2019, while that of PM2.5 declined to 18 % +/- 19 % and is expected to further diminish with emission reduction. Note those often-neglected factors-temperature, wind speed, BLH, and kappa, account for over 40 % of the total contribution. Though the importance of aerosol hygroscopic growth to visibility was found decreasing recently, it retains non-negligible impacts on driving inter-annual visibility trends. This study yields innovative insights for air pollution control, underscoring the imperative of region-specific strategies to mitigate low-visibility events. |
| WOS研究方向 | Environmental Sciences & Ecology |
| 语种 | 英语 |
| WOS记录号 | WOS:001165426100001 |
| 源URL | [http://ir.gig.ac.cn/handle/344008/77339]  |
| 专题 | 有机地球化学国家重点实验室 |
| 通讯作者 | Zhang, Fang; Wang, Xinming |
| 作者单位 | 1.Xian Inst Innovat Earth Environm Res, Xian 710061, Peoples R China 2.Beijing Normal Univ, Fac Geog Sci, Beijing 100875, Peoples R China 3.Chinese Acad Sci, Inst Atmospher Phys, State Key Lab Atmospher Boundary Layer Phys & Atmo, Beijing, Peoples R China 4.Beijing Normal Univ, Coll Life Sci, Beijing 100875, Peoples R China 5.Chinese Acad Sci, State Key Lab Organ Geochem, Guangzhou Inst Geochem, Guangzhou 510640, Peoples R China 6.Harbin Inst Technol Shenzhen, Sch Civil & Environm Engn, Shenzhen 518055, Peoples R China |
| 推荐引用方式 GB/T 7714 | Chen, Lu,Zhang, Fang,Ren, Jingye,et al. Changes in wintertime visibility across China over 2013-2019 and the drivers: A comprehensive assessment using machine learning method[J]. SCIENCE OF THE TOTAL ENVIRONMENT,2024,912:11. |
| APA | Chen, Lu.,Zhang, Fang.,Ren, Jingye.,Li, Zhigang.,Xu, Weiqi.,...&Wang, Xinming.(2024).Changes in wintertime visibility across China over 2013-2019 and the drivers: A comprehensive assessment using machine learning method.SCIENCE OF THE TOTAL ENVIRONMENT,912,11. |
| MLA | Chen, Lu,et al."Changes in wintertime visibility across China over 2013-2019 and the drivers: A comprehensive assessment using machine learning method".SCIENCE OF THE TOTAL ENVIRONMENT 912(2024):11. |
入库方式： OAI收割
来源：广州地球化学研究所
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。