首页 | 本学科首页   官方微博 | 高级检索  
     检索      


Machine learning and theoretical analysis release the non-linear relationship among ozone, secondary organic aerosol and volatile organic compounds
Authors:Feng Wang  Zhongcheng Zhang  Gen Wang  Zhenyu Wang  Mei Li  Weiqing Liang  Jie Gao  Wei Wang  Da Chen  Yinchang Feng  Guoliang Shi
Institution:1. State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China;2. CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health Research (CLAER), College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China;3. State Key Laboratory on Odor Pollution Control, Tianjin Academy of Environmental Sciences, Tianjin 300191, China;4. Guangdong Provincial Engineering Research Center for On-line Source Apportionment System of Air Pollution Jinan University, Institute of Mass Spectrometry and Atmospheric Environment, Guangzhou 510632, China;5. Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Guangzhou 510632, China;6. Trusted AI System Laboratory, College of Computer Science, Nankai University, Tianjin 300350, China;7. Key Laboratory of Civil Aviation Thermal Hazards Prevention and Emergency Response, Civil Aviation University of China, Tianjin 300300, China
Abstract:
Keywords:Corresponding authors    VOCs  Machine learning  Photochemical consumption  Ozone formation potential  Secondary organic aerosol formation potential
点击此处可从《环境科学学报(英文版)》浏览原始摘要信息
点击此处可从《环境科学学报(英文版)》下载免费的PDF全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号