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Wang F, Zhang C, Ge Y, Zhang R, Huang B, Shi G, Wang X, Feng Y. Atmospheric reactive nitrogen conversion kicks off the co-directional and contra-directional effects on PM 2.5-O 3 pollution. JOURNAL OF HAZARDOUS MATERIALS 2024; 478:135558. [PMID: 39159579 DOI: 10.1016/j.jhazmat.2024.135558] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/14/2024] [Revised: 08/15/2024] [Accepted: 08/15/2024] [Indexed: 08/21/2024]
Abstract
As the two important ambient air pollutants, particulate matter (PM2.5) and ozone (O3) can both originate from gas nitrogen oxides. In this study, applied by theoretical analysis and machine learning method, we examined the effects of atmospheric reactive nitrogen on PM2.5-O3 pollution, in which nitric oxide (NO), nitrogen dioxide (NO2), gaseous nitric acid (HNO3) and particle nitrate (pNO3-) conversion process has the co-directional and contra-directional effects on PM2.5-O3 pollution. Of which, HNO3 and SO2 are the co-directional driving factors resulting in PM2.5 and O3 growing or decreasing simultaneously; while NO, NO2, and temperature represent the contra-directional factors, which can promote the growth of one pollutant and reduce another one. Our findings suggest that designing the suitable co-controlling strategies for PM2.5-O3 sustainable reduction should target at driving factors by considering the contra-directional and co-directional effects under suitable sensitivity regions. For co-directional driving factors, the design of suitable mitigation strategies will jointly achieve effective reduction in PM2.5 and O3; while for contra-directional driving factors, it should be more patient, otherwise, it is possible to reduce one item but increase another one at the same time.
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Affiliation(s)
- Feng Wang
- School of Environmental Science and Safety Engineering, Tianjin University of Technology, Tianjin 300384, China; The State Environmental Protection Key Laboratory of Urban Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China; China Meteorological Administration-Nankai University (CMA-NKU) Cooperative Laboratory for Atmospheric Environment-Health Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China
| | - Chun Zhang
- Shaanxi Province Environmental Monitoring Center, Xi'an 710054, China
| | - Yi Ge
- Shaanxi Province Environmental Monitoring Center, Xi'an 710054, China
| | - Ruiling Zhang
- School of Environmental Science and Safety Engineering, Tianjin University of Technology, Tianjin 300384, China
| | - Bijie Huang
- Hubei Key Laboratory of Industrial Fume and Dust Pollution Control, Jianghan University, Wuhan 430056, China
| | - Guoliang Shi
- The State Environmental Protection Key Laboratory of Urban Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China; China Meteorological Administration-Nankai University (CMA-NKU) Cooperative Laboratory for Atmospheric Environment-Health Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China
| | - Xiaoli Wang
- School of Environmental Science and Safety Engineering, Tianjin University of Technology, Tianjin 300384, China.
| | - Yinchang Feng
- The State Environmental Protection Key Laboratory of Urban Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China; China Meteorological Administration-Nankai University (CMA-NKU) Cooperative Laboratory for Atmospheric Environment-Health Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China.
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Wang X, Fu G, Ren NQ. Artificial intelligence is transforming the research paradigm of environmental science and engineering. ENVIRONMENTAL SCIENCE AND ECOTECHNOLOGY 2024; 19:100346. [PMID: 38058954 PMCID: PMC10696158 DOI: 10.1016/j.ese.2023.100346] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/08/2023]
Affiliation(s)
- Xu Wang
- State Key Laboratory of Urban Water Resource and Environment, School of Civil and Environmental Engineering, Harbin Institute of Technology, Shenzhen, Shenzhen, 518055, China
| | - Guangtao Fu
- Centre for Water Systems, College of Engineering, Mathematics and Physical Sciences, University of Exeter, Exeter, EX4 4QF, United Kingdom
| | - Nan-Qi Ren
- State Key Laboratory of Urban Water Resource and Environment, School of Civil and Environmental Engineering, Harbin Institute of Technology, Shenzhen, Shenzhen, 518055, China
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