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Wang J, Liu J, Gao L, Xie D, Li C, Xiang L, Xiong H, Xie J, Zhang T, Pan Y. Investigation into enhanced performance of toluene and Hg 0 stimulative abatement over Cr-Mn oxides co-modified columnar activated coke. J Environ Sci (China) 2025; 148:88-106. [PMID: 39095204 DOI: 10.1016/j.jes.2023.09.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2023] [Revised: 09/07/2023] [Accepted: 09/08/2023] [Indexed: 08/04/2024]
Abstract
In this study, a string of Cr-Mn co-modified activated coke catalysts (XCryMn1-y/AC) were prepared to investigate toluene and Hg0 removal performance. Multifarious characterizations including XRD, TEM, SEM, in situ DRIFTS, BET, XPS and H2-TPR showed that 4%Cr0.5Mn0.5/AC had excellent physicochemical properties and exhibited the best toluene and Hg0 removal efficiency at 200℃. By varying the experimental gas components and conditions, it was found that too large weight hourly space velocity would reduce the removal efficiency of toluene and Hg0. Although O2 promoted the abatement of toluene and Hg0, the inhibitory role of H2O and SO2 offset the promoting effect of O2 to some extent. Toluene significantly inhibited Hg0 removal, resulting from that toluene was present at concentrations orders of magnitude greater than mercury's or the catalyst was more prone to adsorb toluene, while Hg0 almost exerted non-existent influence on toluene elimination. The mechanistic analysis showed that the forms of toluene and Hg0 removal included both adsorption and oxidation, where the high-valent metal cations and oxygen vacancy clusters promoted the redox cycle of Cr3+ + Mn3+/Mn4+ ↔ Cr6+ + Mn2+, which facilitated the conversion and replenishment of reactive oxygen species in the oxidation process, and even the CrMn1.5O4 spinel structure could provide a larger catalytic interface, thus enhancing the adsorption/oxidation of toluene and Hg0. Therefore, its excellent physicochemical properties make it a cost-effective potential industrial catalyst with outstanding synergistic toluene and Hg0 removal performance and preeminent resistance to H2O and SO2.
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Affiliation(s)
- Jiajie Wang
- School of Resources Environment and Safety Engineering, University of South China, Hengyang 421001, China; National & Local Joint Engineering Research Center for Airborne Pollutants Control and Radioactivity Protection in Buildings, Hengyang 421001, China; Key Laboratory of Prefabricated Building Energy Saving Technology of Hunan Province, Hengyang 421001, China
| | - Jie Liu
- School of Resources Environment and Safety Engineering, University of South China, Hengyang 421001, China; National & Local Joint Engineering Research Center for Airborne Pollutants Control and Radioactivity Protection in Buildings, Hengyang 421001, China; Key Laboratory of Prefabricated Building Energy Saving Technology of Hunan Province, Hengyang 421001, China
| | - Lei Gao
- School of Resources Environment and Safety Engineering, University of South China, Hengyang 421001, China; National & Local Joint Engineering Research Center for Airborne Pollutants Control and Radioactivity Protection in Buildings, Hengyang 421001, China; Key Laboratory of Prefabricated Building Energy Saving Technology of Hunan Province, Hengyang 421001, China; College of Environmental Science and Engineering, Hunan University, Changsha 410082, China.
| | - Dong Xie
- National & Local Joint Engineering Research Center for Airborne Pollutants Control and Radioactivity Protection in Buildings, Hengyang 421001, China; Key Laboratory of Prefabricated Building Energy Saving Technology of Hunan Province, Hengyang 421001, China
| | - Caiting Li
- College of Environmental Science and Engineering, Hunan University, Changsha 410082, China
| | - Liping Xiang
- National & Local Joint Engineering Research Center for Airborne Pollutants Control and Radioactivity Protection in Buildings, Hengyang 421001, China; Key Laboratory of Prefabricated Building Energy Saving Technology of Hunan Province, Hengyang 421001, China
| | - Huiyu Xiong
- School of Resources Environment and Safety Engineering, University of South China, Hengyang 421001, China; National & Local Joint Engineering Research Center for Airborne Pollutants Control and Radioactivity Protection in Buildings, Hengyang 421001, China; Key Laboratory of Prefabricated Building Energy Saving Technology of Hunan Province, Hengyang 421001, China
| | - Jiaqi Xie
- School of Resources Environment and Safety Engineering, University of South China, Hengyang 421001, China; National & Local Joint Engineering Research Center for Airborne Pollutants Control and Radioactivity Protection in Buildings, Hengyang 421001, China; Key Laboratory of Prefabricated Building Energy Saving Technology of Hunan Province, Hengyang 421001, China
| | - Tianren Zhang
- National & Local Joint Engineering Research Center for Airborne Pollutants Control and Radioactivity Protection in Buildings, Hengyang 421001, China; Key Laboratory of Prefabricated Building Energy Saving Technology of Hunan Province, Hengyang 421001, China
| | - Yueguo Pan
- School of Resources Environment and Safety Engineering, University of South China, Hengyang 421001, China; National & Local Joint Engineering Research Center for Airborne Pollutants Control and Radioactivity Protection in Buildings, Hengyang 421001, China; Key Laboratory of Prefabricated Building Energy Saving Technology of Hunan Province, Hengyang 421001, China
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Man H, Shao X, Cai W, Wang K, Cai Z, Xue M, Liu H. Utilizing a optimized method for evaluating vapor recovery equipment control efficiency and estimating evaporative VOC emissions from urban oil depots via an extensive survey. JOURNAL OF HAZARDOUS MATERIALS 2024; 479:135710. [PMID: 39241364 DOI: 10.1016/j.jhazmat.2024.135710] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/12/2024] [Revised: 08/29/2024] [Accepted: 08/29/2024] [Indexed: 09/09/2024]
Abstract
As an important intermediary between upstream refineries and downstream urban gas stations, volatile organic compound (VOC) emissions from urban oil depots were often disregarded, underestimating their environmental and health implications. An extensive investigation of urban depots' fuel composition and operational dynamics was conducted nationwide. We developed a novel approach that integrates theoretical models with easily measurable operational data from the depots to evaluate the efficiency of post-treatment devices in actual situations. Even in well-managed oil depots, the actual control efficiency of vapor recovery units fluctuates between 63 % and 85 %, depending on the concentration of hydrocarbon vapors in the intake of the device. The national emission factors for gasoline, diesel, and aviation kerosene at a national level were 6.64 ± 1.16, 2.07 ± 0.42, and 6.17 ± 1.05 tons per 10,000 tons, respectively. In 2019, China's urban oil depots emitted 165 thousand tons of VOC. Enhancing control strategies by optimizing the physical and chemical parameters of refined oil, improving storage capacity and turnover efficiency, and upgrading storage tanks had the potential to reduce emissions by more than 60 %. However, a 30 % failure rate in these systems could negate the benefits of these improved strategies.
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Affiliation(s)
- Hanyang Man
- College of Environmental and Resource Sciences, Fujian Key Laboratory of Pollution Control & Resource Reuse, Fujian Normal University, Fuzhou 350007, China.
| | - Xiaohan Shao
- College of Environmental and Resource Sciences, Fujian Key Laboratory of Pollution Control & Resource Reuse, Fujian Normal University, Fuzhou 350007, China
| | - Wenying Cai
- College of Environmental and Resource Sciences, Fujian Key Laboratory of Pollution Control & Resource Reuse, Fujian Normal University, Fuzhou 350007, China
| | - Kai Wang
- China Automotive Technology and Research Center, Beijing 100070, China
| | - Zhitao Cai
- State Key Joint Laboratory of ESPC, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, School of Environment, Tsinghua University, Beijing 100084, China
| | - Ming Xue
- State Key Laboratory of Petroleum Pollution Control, CNPC Research Institute of Safety and Environmental Technology, Beijing 102206, China
| | - Huan Liu
- State Key Joint Laboratory of ESPC, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, School of Environment, Tsinghua University, Beijing 100084, China
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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 F, Zhang C, Ge Y, Zhang Z, Shi G, Feng Y. Multi-scale analysis of the chemical and physical pollution evolution process from pre-co-pollution day to PM 2.5 and O 3 co-pollution day. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 945:173729. [PMID: 38839009 DOI: 10.1016/j.scitotenv.2024.173729] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/24/2024] [Revised: 05/10/2024] [Accepted: 06/01/2024] [Indexed: 06/07/2024]
Abstract
PM2.5 and O3 are two of the main air pollutants that have adverse impacts on climate and human health. The evolution process of PM2.5 and O3 co-pollution are of concern because of the increased frequency of PM2.5 and O3 co-pollution days. Here, we examined the chemical coupling and revealed the driving factors of the PM2.5 and O3 co-pollution evolution process from cleaning day, PM2.5 pollution day, or O3 pollution day, applied by theoretical analysis and model calculation methods. The results demonstrate that PM2.5 and O3 co-pollution day frequently occurred with high concentrations of gaseous precursors and higher sulfur oxidation ratio (SOR) and nitrogen oxidation ratio (NOR), which we attribute to the enhancement of atmospheric oxidation capacity (AOC). The AOC is positively correlated with O3 and weakly correlated with PM2.5. In addition, we found that the correlation coefficients of PM2.5-NO2 (0.62) were higher than that of PM2.5-SO2 (0.32), highlighting the priority of NOx controlling to mitigate PM2.5 pollution. Overall, our discovery can provide scientific evidence to design feasible solutions for the controlling PM2.5 and O3 co-pollution process.
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Affiliation(s)
- Feng Wang
- School of Environmental Science and Safety Engineering, Tianjin University of Technology, Tianjin 300384, China
| | - Chun Zhang
- Shaanxi Province Environmental Monitoring Center, Xi'an 710054, China
| | - Yi Ge
- Shaanxi Province Environmental Monitoring Center, Xi'an 710054, China
| | - Zhang Zhang
- 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; 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
| | - Guoliang Shi
- 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; 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
| | - Yinchang Feng
- 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; 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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Ma Q, Yuan R, Wang S, Sun Y, Zhang Q, Yuan X, Wang Q, Luo C. Indigenized Characterization Factors for Health Damage Due to Ambient PM 2.5 in Life Cycle Impact Assessment in China. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2024; 58:17320-17333. [PMID: 39298624 DOI: 10.1021/acs.est.3c08122] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/22/2024]
Abstract
Life cycle assessment (LCA) is a broadly used method for quantifying environmental impacts, and life cycle impact assessment (LCIA) is an important step as well as a major source of uncertainties in LCA. Characterization factors (CFs) are pivotal elements in LCIA models. In China, the health loss due to ambient PM2.5 is an important aspect of LCIA results, which, however, is generally assessed by adopting CFs developed by global models and there remains a need to integrate localized considerations and the latest information for more precise applications in China. In this study, we developed indigenized CFs for LCIA of health damage due to ambient PM2.5 in China by coupling the atmospheric chemical transport model GEOS-Chem, exposure-response model GEMM containing Chinese cohort studies, and the latest local data. Results show that CFs of four major PM2.5 precursors all exhibit significant interregional variation and monthly differences in China. Our results were generally an order of magnitude higher and show disparate spatial distribution compared to CFs currently in use, suggesting that the health damage due to ambient PM2.5 was underestimated in LCIA in China, and indigenized CFs need to be adopted for more accurate results in LCIA and LCA studies.
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Affiliation(s)
- Qiao Ma
- National Engineering Laboratory for Reducing Emissions from Coal Combustion, Engineering Research Center of Environmental Thermal Technology of Ministry of Education, Shandong Key Laboratory of Energy Carbon Reduction and Resource Utilization, School of Energy and Power Engineering, Shandong University, Jinan 250061, China
- Sustainable Development Research Center, Shandong University, Jinan 250061, China
| | - Renxiao Yuan
- National Engineering Laboratory for Reducing Emissions from Coal Combustion, Engineering Research Center of Environmental Thermal Technology of Ministry of Education, Shandong Key Laboratory of Energy Carbon Reduction and Resource Utilization, School of Energy and Power Engineering, Shandong University, Jinan 250061, China
- Sustainable Development Research Center, Shandong University, Jinan 250061, China
| | - Shan Wang
- National Engineering Laboratory for Reducing Emissions from Coal Combustion, Engineering Research Center of Environmental Thermal Technology of Ministry of Education, Shandong Key Laboratory of Energy Carbon Reduction and Resource Utilization, School of Energy and Power Engineering, Shandong University, Jinan 250061, China
- Sustainable Development Research Center, Shandong University, Jinan 250061, China
| | - Yuchen Sun
- National Engineering Laboratory for Reducing Emissions from Coal Combustion, Engineering Research Center of Environmental Thermal Technology of Ministry of Education, Shandong Key Laboratory of Energy Carbon Reduction and Resource Utilization, School of Energy and Power Engineering, Shandong University, Jinan 250061, China
- Sustainable Development Research Center, Shandong University, Jinan 250061, China
| | - Qianqian Zhang
- National Satellite Meteorological Center, Beijing 100089, China
| | - Xueliang Yuan
- National Engineering Laboratory for Reducing Emissions from Coal Combustion, Engineering Research Center of Environmental Thermal Technology of Ministry of Education, Shandong Key Laboratory of Energy Carbon Reduction and Resource Utilization, School of Energy and Power Engineering, Shandong University, Jinan 250061, China
- Sustainable Development Research Center, Shandong University, Jinan 250061, China
| | - Qingsong Wang
- National Engineering Laboratory for Reducing Emissions from Coal Combustion, Engineering Research Center of Environmental Thermal Technology of Ministry of Education, Shandong Key Laboratory of Energy Carbon Reduction and Resource Utilization, School of Energy and Power Engineering, Shandong University, Jinan 250061, China
- Sustainable Development Research Center, Shandong University, Jinan 250061, China
| | - Congwei Luo
- School of Municipal and Environmental Engineering, Shandong Jianzhu University, Jinan 250101, China
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Ding D, Jiang Y, Wang S, Xing J, Dong Z, Hao J, Paasonen P. Unveiling the health impacts of air pollution transport in China. ENVIRONMENT INTERNATIONAL 2024; 191:108947. [PMID: 39167855 DOI: 10.1016/j.envint.2024.108947] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/01/2024] [Revised: 08/02/2024] [Accepted: 08/12/2024] [Indexed: 08/23/2024]
Abstract
The transport of atmospheric pollutants plays a pivotal role in regional air pollution, highlighting critical concerns over the unequal health outcomes that arise from such transport. While previous researches predominantly focused on key areas in the battle against air pollution, the intensification of control measures necessitates a national perspective to comprehend the health impacts due to pollution transport. Our study establishes an integrated assessment framework that combine an emission-concentration response surface model with a health impact evaluation model to analyse the nationwide health impacts of PM2.5 and O3 pollution transport across China's 31 provinces. We found that, interprovincial transport of PM2.5 and O3 contributed to 747,000 and 110,000 deaths respectively in 2017, which amounts to 38% and 48% of deaths caused by total anthropogenic emissions. North, East, and Central China together contribute 82% and 69% to the health impacts caused by regional PM2.5 and O3 transport respectively, and the transport among these three regions is also significant. The analysis of interprovincial health impact transport shows that, for PM2.5, the top contributors are Hebei, Shandong, Henan, Anhui, and Jiangsu, with the most affected being Henan, Shandong, Jiangsu, Hebei, and Guangdong. Regarding O3, Shandong, Hebei, Henan, Jiangsu, and Anhui contribute the most, while Henan, Shandong, Hebei, Jiangsu, and Anhui are the most affected. This study can shed lights on regional control strategies by prioritizing control areas based on the health impact of air pollution transport in China.
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Affiliation(s)
- Dian Ding
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China; Institute for Atmospheric and Earth System Research/Physics, Faculty of Science, University of Helsinki, 00014 Helsinki, Finland
| | - Yueqi Jiang
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
| | - Shuxiao Wang
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China; State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China.
| | - Jia Xing
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China; State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
| | - Zhaoxin Dong
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
| | - Jiming Hao
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China; State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
| | - Pauli Paasonen
- Institute for Atmospheric and Earth System Research/Physics, Faculty of Science, University of Helsinki, 00014 Helsinki, Finland
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Sun Y, Jiang Y, Xing J, Ou Y, Wang S, Loughlin DH, Yu S, Ren L, Li S, Dong Z, Zheng H, Zhao B, Ding D, Zhang F, Zhang H, Song Q, Liu K, Klimont Z, Woo JH, Lu X, Li S, Hao J. Air Quality, Health, and Equity Benefits of Carbon Neutrality and Clean Air Pathways in China. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2024. [PMID: 39133145 DOI: 10.1021/acs.est.3c10076] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/13/2024]
Abstract
In the pursuit of carbon neutrality, China's 2060 targets have been largely anchored in reducing greenhouse gas emissions, with less emphasis on the consequential benefits for air quality and public health. This study pivots to this critical nexus, exploring how China's carbon neutrality aligns with the World Health Organization's air quality guidelines (WHO AQG) regarding fine particulate matter (PM2.5) exposure. Coupling a technology-rich integrated assessment model, an emission-concentration response surface model, and exposure and health assessment, we find that decarbonization reduces sulfur dioxide (SO2), nitrogen oxides (NOx), and PM2.5 emissions by more than 90%; reduces nonmethane volatile organic compounds (NMVOCs) by more than 50%; and simultaneously reduces the disparities across regions. Critically, our analysis reveals that further targeted reductions in air pollutants, notably NH3 and non-energy-related NMVOCs, could bring most Chinese cities into attainment of WHO AQG for PM2.5 5 to 10 years earlier than the pathway focused solely on carbon neutrality. Thus, the integration of air pollution control measures into carbon neutrality strategies will present a significant opportunity for China to attain health and environmental equality.
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Affiliation(s)
- Yisheng Sun
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, P. R. China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, P. R. China
| | - Yueqi Jiang
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, P. R. China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, P. R. China
| | - Jia Xing
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, P. R. China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, P. R. China
| | - Yang Ou
- College of Environmental Sciences and Engineering, Peking University, Beijing 100871, P. R. China
- Institute of Carbon Neutrality, Peking University, Beijing 100871, P. R. China
| | - Shuxiao Wang
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, P. R. China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, P. R. China
| | - Daniel H Loughlin
- U.S. Environmental Protection Agency, Research Triangle Park, North Carolina 27711, United States
| | - Sha Yu
- Joint Global Change Research Institute, Pacific Northwest National Laboratory, College Park, Maryland 20740, United States
- Center for Global Sustainability, University of Maryland, College Park , Maryland 20742, United States
| | - Lu Ren
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, P. R. China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, P. R. China
| | - Shengyue Li
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, P. R. China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, P. R. China
| | - Zhaoxin Dong
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, P. R. China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, P. R. China
| | - Haotian Zheng
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, P. R. China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, P. R. China
| | - Bin Zhao
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, P. R. China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, P. R. China
| | - Dian Ding
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, P. R. China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, P. R. China
| | - Fenfen Zhang
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, P. R. China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, P. R. China
| | - Haowen Zhang
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, P. R. China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, P. R. China
| | - Qian Song
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, P. R. China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, P. R. China
| | - Kaiyun Liu
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, P. R. China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, P. R. China
| | - Zbigniew Klimont
- International Institute for Applied Systems Analysis (IIASA), Laxenburg 2361, Austria
| | - Jung-Hun Woo
- Department of Civil and Environmental Engineering, Konkuk University, Seoul 05029, Republic of Korea
| | - Xi Lu
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, P. R. China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, P. R. China
| | - Siwei Li
- School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, P. R. China
| | - Jiming Hao
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, P. R. China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, P. R. China
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Dong Z, Li S, Jiang Y, Wang S, Xing J, Ding D, Zheng H, Wang H, Huang C, Yin D, Zhao B, Hao J. Health-Oriented Emission Control Strategy of Energy Utilization and Its Co-CO 2 Benefits: A Case Study of the Yangtze River Delta, China. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2024; 58:12320-12329. [PMID: 38973717 DOI: 10.1021/acs.est.3c10693] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/09/2024]
Abstract
Reducing air pollutants and CO2 emissions from energy utilization is crucial for achieving the dual objectives of clean air and carbon neutrality in China. Thus, an optimized health-oriented strategy is urgently needed. Herein, by coupling a CO2 and air pollutants emission inventory with response surface models for PM2.5-associated mortality, we shed light on the effectiveness of protecting human health and co-CO2 benefit from reducing fuel-related emissions and generate a health-oriented strategy for the Yangtze River Delta (YRD). Results reveal that oil consumption is the primary contributor to fuel-related PM2.5 pollution and premature deaths in the YRD. Significantly, curtailing fuel consumption in transportation is the most effective measure to alleviate the fuel-related PM2.5 health impact, which also has the greatest cobenefits for CO2 emission reduction on a regional scale. Reducing fuel consumption will achieve substantial health improvements especially in eastern YRD, with nonroad vehicle emission reductions being particularly impactful for health protection, while on-road vehicles present the greatest potential for CO2 reductions. Scenario analysis confirms the importance of mitigating oil consumption in the transportation sector in addressing PM2.5 pollution and climate change.
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Affiliation(s)
- Zhaoxin Dong
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
- State Environmental Protection Key Laboratory of Formation and Prevention of the Urban Air Pollution Complex, Shanghai Academy of Environment Sciences, Shanghai 200233, China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
| | - Shengyue Li
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
| | - Yueqi Jiang
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
| | - Shuxiao Wang
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
| | - Jia Xing
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
| | - Dian Ding
- Institute for Atmospheric and Earth System Research/Physics, Faculty of Science, University of Helsinki, 00014 Helsinki, Finland
| | - Haotian Zheng
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
| | - Hongli Wang
- State Environmental Protection Key Laboratory of Formation and Prevention of the Urban Air Pollution Complex, Shanghai Academy of Environment Sciences, Shanghai 200233, China
| | - Cheng Huang
- State Environmental Protection Key Laboratory of Formation and Prevention of the Urban Air Pollution Complex, Shanghai Academy of Environment Sciences, Shanghai 200233, China
| | - Dejia Yin
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
| | - Bin Zhao
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
| | - Jiming Hao
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
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9
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Dong Z, Jiang Y, Wang S, Xing J, Ding D, Zheng H, Wang H, Huang C, Yin D, Song Q, Zhao B, Hao J. Spatially and Temporally Differentiated NO x and VOCs Emission Abatement Could Effectively Gain O 3-Related Health Benefits. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2024; 58:9570-9581. [PMID: 38781138 DOI: 10.1021/acs.est.4c01345] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/25/2024]
Abstract
The increasing level of O3 pollution in China significantly exacerbates the long-term O3 health damage, and an optimized health-oriented strategy for NOx and VOCs emission abatement is needed. Here, we developed an integrated evaluation and optimization system for the O3 control strategy by merging a response surface model for the O3-related mortality and an optimization module. Applying this system to the Yangtze River Delta (YRD), we evaluated driving factors for mortality changes from 2013 to 2017, quantified spatial and temporal O3-related mortality responses to precursor emission abatement, and optimized a health-oriented control strategy. Results indicate that insufficient NOx emission abatement combined with deficient VOCs control from 2013 to 2017 aggravated O3-related mortality, particularly during spring and autumn. Northern YRD should promote VOCs control due to higher VOC-limited characteristics, whereas fastening NOx emission abatement is more favorable in southern YRD. Moreover, promotion of NOx mitigation in late spring and summer and facilitating VOCs control in spring and autumn could further reduce O3-related mortality by nearly 10% compared to the control strategy without seasonal differences. These findings highlight that a spatially and temporally differentiated NOx and VOCs emission control strategy could gain more O3-related health benefits, offering valuable insights to regions with severe ozone pollution all over the world.
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Affiliation(s)
- Zhaoxin Dong
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
- State Environmental Protection Key Laboratory of Formation and Prevention of the Urban Air Pollution Complex, Shanghai Academy of Environment Sciences, Shanghai 200233, China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
| | - Yueqi Jiang
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
| | - Shuxiao Wang
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
| | - Jia Xing
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
| | - Dian Ding
- Institute for Atmospheric and Earth System Research/Physics, Faculty of Science, University of Helsinki, 00014 Helsinki, Finland
| | - Haotian Zheng
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
| | - Hongli Wang
- State Environmental Protection Key Laboratory of Formation and Prevention of the Urban Air Pollution Complex, Shanghai Academy of Environment Sciences, Shanghai 200233, China
| | - Cheng Huang
- State Environmental Protection Key Laboratory of Formation and Prevention of the Urban Air Pollution Complex, Shanghai Academy of Environment Sciences, Shanghai 200233, China
| | - Dejia Yin
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
| | - Qian Song
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
| | - Bin Zhao
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
| | - Jiming Hao
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
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10
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Dai H, Liao H, Wang Y, Qian J. Co-occurrence of ozone and PM 2.5 pollution in urban/non-urban areas in eastern China from 2013 to 2020: Roles of meteorology and anthropogenic emissions. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 924:171687. [PMID: 38485008 DOI: 10.1016/j.scitotenv.2024.171687] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/27/2023] [Revised: 02/25/2024] [Accepted: 03/10/2024] [Indexed: 03/19/2024]
Abstract
We applied a three-dimensional (3-D) global chemical transport model (GEOS-Chem) to evaluate the influences of meteorology and anthropogenic emissions on the co-occurrence of ozone (O3) and fine particulate matter (PM2.5) pollution day (O3-PM2.5PD) in urban and non-urban areas of the Beijing-Tianjin-Hebei (BTH) and Yangtze River Delta (YRD) regions during the warm season (April-October) from 2013 to 2020. The model captured the observed O3-PM2.5PD trends and spatial distributions well. From 2013 to 2020, with changes in both anthropogenic emissions and meteorology, the simulated values of O3-PM2.5PD in the urban (non-urban) areas of the BTH and YRD regions were 424.8 (330.1) and 309.3 (286.9) days, respectively, suggesting that pollution in non-urban areas also warrants attention. The trends in the simulated values of O3-PM2.5PD were -0.14 and -0.15 (+1.18 and +0.81) days yr-1 in the BTH (YRD) urban and non-urban areas, respectively. Sensitivity simulations revealed that changes in anthropogenic emissions decreased the occurrence of O3-PM2.5PD, with trends of -0.99 and -1.23 (-1.47 and -1.92) days yr-1 in the BTH (YRD) urban and non-urban areas, respectively. Conversely, meteorological conditions could exacerbate the frequency of O3-PM2.5PD, especially in the urban YRD areas, but less notably in the urban BTH areas, with trends of +2.11 and +0.30 days yr-1, respectively, owing to changes in meteorology only. The increases in T2m_max and T2m were the main meteorological factors affecting O3-PM2.5PD in most BTH and YRD areas. Furthermore, by conducting sensitivity experiments with different levels of pollutant precursor reductions in 2020, we found that volatile organic compound (VOC) reductions primarily benefited O3-PM2.5PD decreases in urban areas and that NOx reductions more notably influenced those in non-urban areas, especially in the YRD region. Simultaneously, reducing VOC and NOx emissions by 50 % resulted in considerable O3-PM2.5PD decreases (58.8-72.6 %) in the urban and non-urban areas of the BTH and YRD regions. The results of this study have important implications for the control of O3-PM2.5PD in the urban and non-urban areas of the BTH and YRD regions.
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Affiliation(s)
- Huibin Dai
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, China
| | - Hong Liao
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, China.
| | - Ye Wang
- Key Laboratory of Meteorological Disaster, Ministry of Education (KLME)/Joint International Research Laboratory of Climate and Environment Change (ILCEC)/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Nanjing University of Information Science and Technology, Nanjing 210044, China
| | - Jing Qian
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, China
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11
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Zhang Z, Man H, Zhao J, Huang W, Huang C, Jing S, Luo Z, Zhao X, Chen D, He K, Liu H. VOC and IVOC emission features and inventory of motorcycles in China. JOURNAL OF HAZARDOUS MATERIALS 2024; 469:133928. [PMID: 38447368 DOI: 10.1016/j.jhazmat.2024.133928] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/04/2023] [Revised: 02/09/2024] [Accepted: 02/28/2024] [Indexed: 03/08/2024]
Abstract
How did the motorcycle emissions evolve during the economic development in China? To address data gaps, this study firstly measured the volatile organic compound (VOC) and intermediate-volatility organic compound (IVOC) emissions from motorcycles. The results confirmed that the emission control of motorcycles, especially small-displacement motorcycles, significantly lagged behind other gasoline-powered vehicles. For the China IV motorcycles, the average VOC and IVOC emission factors (EFs) were 2.74 and 7.78 times higher than the China V-VI light-duty gasoline vehicles, respectively. The notable high IVOC emissions were attributed to a dual influence from gasoline and lubricating oil. Furthermore, based on the complete EF dataset and economy-related activity data, a county-level emission inventory was developed in China. Motorcycle VOC and IVOC emissions changed from 2536.48 Gg and 197.19 Gg in 2006 to 594.21 Gg and 12.66 Gg in 2020, respectively. The absence of motorcycle IVOC emissions in the existed vehicular inventories led to an underestimation of up to 20%. Across the 15 years, the motorcycle VOC and IVOC emission hotspots were concentrated in the undeveloped regions, with the rural emissions reaching 5.81-10.14 times those of the urban emissions. This study provides the first-hand and close-to-realistic data to support motorcycle emission management and accurate air quality simulations.
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Affiliation(s)
- Zhining Zhang
- State Key Joint Laboratory of ESPC, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, School of Environment, Tsinghua University, Beijing 100084, China
| | - Hanyang Man
- Fujian Key Laboratory of Pollution Control & Resource Reuse, College of Environmental and Resource Sciences, Fujian Normal University, Fuzhou, 350007, China
| | - Junchao Zhao
- State Key Joint Laboratory of ESPC, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, School of Environment, Tsinghua University, Beijing 100084, China
| | - Wendong Huang
- Shanghai Motor Vehicle Inspection Certification & Tech Innovation Center Co., Ltd, Shanghai 201805, China
| | - Cheng Huang
- State Environmental Protection Key Laboratory of Formation and Prevention of Urban Air Pollution Complex, Shanghai Academy of Environmental Sciences, Shanghai 200233, China
| | - Shengao Jing
- State Environmental Protection Key Laboratory of Formation and Prevention of Urban Air Pollution Complex, Shanghai Academy of Environmental Sciences, Shanghai 200233, China
| | - Zhenyu Luo
- State Key Joint Laboratory of ESPC, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, School of Environment, Tsinghua University, Beijing 100084, China
| | - Xinyue Zhao
- State Key Joint Laboratory of ESPC, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, School of Environment, Tsinghua University, Beijing 100084, China
| | - Dawei Chen
- State Environmental Protection Key Laboratory of Vehicle Emission Control and Simulation, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Kebin He
- State Key Joint Laboratory of ESPC, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, School of Environment, Tsinghua University, Beijing 100084, China
| | - Huan Liu
- State Key Joint Laboratory of ESPC, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, School of Environment, Tsinghua University, Beijing 100084, China.
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12
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Wang F, Chen A, Lan T, Chen X, Wang M, Hu X, Wang P, Cheng D, Zhang D. Synergistic catalytic removal of NO x and chlorinated organics through the cooperation of different active sites. JOURNAL OF HAZARDOUS MATERIALS 2024; 468:133722. [PMID: 38367433 DOI: 10.1016/j.jhazmat.2024.133722] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/06/2023] [Revised: 01/26/2024] [Accepted: 02/03/2024] [Indexed: 02/19/2024]
Abstract
The synergistic removal of NOx and chlorinated volatile organic compounds (CVOCs) has become the hot topic in the field of environmental catalysis. However, due to the trade-off effects between catalytic reduction of NOx and catalytic oxidation of CVOCs, it is indispensable to achieve well-matched redox property and acidity. Herein, synergistic catalytic removal of NOx and chlorobenzene (CB, as the model of CVOCs) has been originally demonstrated over a Co-doped SmMn2O5 mullite catalyst. Two kinds of Mn-Mn sites existed in Mn-O-Mn-Mn and Co-O-Mn-Mn sites were constructed, which owned gradient redox ability. It has been demonstrated that the cooperation of different active sites can achieve the balanced redox and acidic property of the SmMn2O5 catalyst. It is interesting that the d band center of Mn-Mn sites in two different sites was decreased by the introduction of Co, which inhibited the nitrate species deposition and significantly improved the N2 selectivity. The Co-O-Mn-Mn sites were beneficial to the oxidation of CB and it cooperates with Mn-O-Mn-Mn to promote the synergistic catalytic performance. This work paves the way for synergistic removal of NOx and CVOCs over cooperative active sites in catalysts.
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Affiliation(s)
- Fuli Wang
- School of Environmental and Chemical Engineering, State Key Laboratory of Advanced Special Steel, Innovation Institute of Carbon Neutrality, College of Sciences, Shanghai University, Shanghai 200444, China
| | - Aling Chen
- School of Environmental and Chemical Engineering, State Key Laboratory of Advanced Special Steel, Innovation Institute of Carbon Neutrality, College of Sciences, Shanghai University, Shanghai 200444, China
| | - Tianwei Lan
- School of Environmental and Chemical Engineering, State Key Laboratory of Advanced Special Steel, Innovation Institute of Carbon Neutrality, College of Sciences, Shanghai University, Shanghai 200444, China
| | - Xin Chen
- School of Environmental and Chemical Engineering, State Key Laboratory of Advanced Special Steel, Innovation Institute of Carbon Neutrality, College of Sciences, Shanghai University, Shanghai 200444, China
| | - Mengxue Wang
- School of Environmental and Chemical Engineering, State Key Laboratory of Advanced Special Steel, Innovation Institute of Carbon Neutrality, College of Sciences, Shanghai University, Shanghai 200444, China
| | - Xiaonan Hu
- School of Environmental and Chemical Engineering, State Key Laboratory of Advanced Special Steel, Innovation Institute of Carbon Neutrality, College of Sciences, Shanghai University, Shanghai 200444, China
| | - Penglu Wang
- School of Environmental and Chemical Engineering, State Key Laboratory of Advanced Special Steel, Innovation Institute of Carbon Neutrality, College of Sciences, Shanghai University, Shanghai 200444, China
| | - Danhong Cheng
- School of Environmental and Chemical Engineering, State Key Laboratory of Advanced Special Steel, Innovation Institute of Carbon Neutrality, College of Sciences, Shanghai University, Shanghai 200444, China.
| | - Dengsong Zhang
- School of Environmental and Chemical Engineering, State Key Laboratory of Advanced Special Steel, Innovation Institute of Carbon Neutrality, College of Sciences, Shanghai University, Shanghai 200444, China.
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13
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Dong Z, Zhang D, Wang T, Song X, Hao Y, Wang S, Wang S. Sources and environmental impacts of volatile organic components in a street canyon: Implication for vehicle emission. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 917:170569. [PMID: 38296102 DOI: 10.1016/j.scitotenv.2024.170569] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/13/2023] [Revised: 01/28/2024] [Accepted: 01/28/2024] [Indexed: 02/03/2024]
Abstract
Street canyons serve as a representative environment that directly reflects the impact of vehicular emissions. Volatile organic compounds (VOCs) sampling during an O3 pollution event and a PM2.5 pollution episode was conducted at an urban site and a street canyon in Zhengzhou, China. It has been determined that street canyons suffer from more severe particle and NOx pollution than the urban site. Additionally, O3 has been identified as a significant or emerging pollutant in street canyon environments. In terms of VOCs, the street canyon exhibits 1.4 and 1.1 times higher total VOC concentrations compared to the urban site during the O3 and PM2.5 pollution episodes, respectively. In the street canyon location, there was a slight increase in the proportion of alkanes and aromatics, while the proportions of oxygenated VOCs and halogenated hydrocarbons decreased. Source apportionment analysis reveals that street canyons were more susceptible to the accumulation of VOCs from coating solvent, liquid petroleum gas (LPG), and gasoline additives. Consequently, the environmental impacts of VOCs originating from coating solvent and LPG were more pronounced in the street canyon location compared to the urban site. The trends of NOx concentration indicate that future continuously stricter vehicle emission standards and control policies can further reduce vehicle exhaust emissions and more attention needs to be focused on the reduction of non-exhaust emissions (i.e., coating solvent) and LPG vehicles.
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Affiliation(s)
- Zhangsen Dong
- College of Chemistry, Zhengzhou University, Zhengzhou 450001, China; Research Institute of Environmental Sciences, Zhengzhou University, Zhengzhou 450000, China
| | - Dong Zhang
- College of Chemistry, Zhengzhou University, Zhengzhou 450001, China; Research Institute of Environmental Sciences, Zhengzhou University, Zhengzhou 450000, China
| | - Tiantian Wang
- Research Institute of Environmental Sciences, Zhengzhou University, Zhengzhou 450000, China; School of Ecology and Environment, Zhengzhou University, Zhengzhou 450000, China
| | - Xinshuai Song
- Research Institute of Environmental Sciences, Zhengzhou University, Zhengzhou 450000, China; School of Ecology and Environment, Zhengzhou University, Zhengzhou 450000, China
| | - Yanyan Hao
- Research Institute of Environmental Sciences, Zhengzhou University, Zhengzhou 450000, China; School of Ecology and Environment, Zhengzhou University, Zhengzhou 450000, China
| | - Shanshan Wang
- Research Institute of Environmental Sciences, Zhengzhou University, Zhengzhou 450000, China; School of Ecology and Environment, Zhengzhou University, Zhengzhou 450000, China
| | - Shenbo Wang
- Research Institute of Environmental Sciences, Zhengzhou University, Zhengzhou 450000, China; School of Ecology and Environment, Zhengzhou University, Zhengzhou 450000, China.
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14
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Meng F, Ronda R, Strokal M, Kroeze C, Ma L, Krol M, de Graaf I, Zhao Y, Wang Y, Du X, Liu X, Xu W, Zhang F, Wang M. Setting goals for agricultural nitrogen emission reduction to ensure safe air and groundwater quality: A case study of Quzhou, the North China Plain. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2024; 351:119737. [PMID: 38064983 DOI: 10.1016/j.jenvman.2023.119737] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/19/2023] [Revised: 11/21/2023] [Accepted: 11/27/2023] [Indexed: 01/14/2024]
Abstract
Setting nitrogen (N) emission targets for agricultural systems is crucial to prevent to air and groundwater pollution, yet such targets are rarely defined at the county level. In this study, we employed a forecasting-and-back casting approach to establish human health-based nitrogen targets for air and groundwater quality in Quzhou county, located in the North China Plain. By adopting the World Health Organization (WHO) phase I standard for PM2.5 concentration (35 μg m-3) and a standard of 11.3 mg NO3--N L-1 for nitrate in drinking water, we found that ammonia (NH3) emissions from the entire county must be reduced by at least 3.2 kilotons year-1 in 2050 to meet the WHO's PM2.5 phase I standard. Additionally, controlling other pollutants such as sulfur dioxide (SO2) and nitrogen oxides (NOx) is necessary, with required reductions ranging from 16% to 64% during 2017-2050. Furthermore, to meet the groundwater quality standard, nitrate nitrogen (NO3--N) leaching to groundwater should not exceed 0.8 kilotons year-1 by 2050. Achieving this target would require a 50% reduction in NH3 emissions and a 21% reduction in NO3--N leaching from agriculture in Quzhou in 2050 compared to their respective levels in 2017 (5.0 and 2.1 kilotons, respectively). Our developed method and the resulting N emission targets can support the development of environmentally-friendly agriculture by facilitating the design of control strategies to minimize agricultural N losses.
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Affiliation(s)
- Fanlei Meng
- State Key Laboratory of Nutrient Use and Management, College of Resources and Environmental Sciences, National Academy of Agriculture Green Development, National Observation and Research Station of Agriculture Green Development (Quzhou, Hebei), China Agricultural University, Beijing, China; Water Systems and Global Change Group, Wageningen University & Research, P.O. Box 47, 6700, AA, Wageningen, the Netherlands
| | - Reinder Ronda
- Meteorology and Air Quality Group, Wageningen University & Research, P.O. Box 47, 6700, AA, Wageningen, the Netherlands; Royal Netherlands Meteorological Institute (KNMI), Utrechtseweg 297, 3731, GA, De Bilt, the Netherlands
| | - Maryna Strokal
- Water Systems and Global Change Group, Wageningen University & Research, P.O. Box 47, 6700, AA, Wageningen, the Netherlands
| | - Carolien Kroeze
- Water Systems and Global Change Group, Wageningen University & Research, P.O. Box 47, 6700, AA, Wageningen, the Netherlands; Environmental Systems Analysis Group, Wageningen University & Research, Wageningen, 6708, PB, the Netherlands
| | - Lin Ma
- Key Laboratory of Agricultural Water Resources, Hebei Key Laboratory of Soil Ecology, Center for Agricultural Resources Research, Institute of Genetic and Developmental Biology, The Chinese Academy of Sciences, 286 Huaizhong Road, Shijiazhuang, 050021, Hebei, China
| | - Maarten Krol
- Meteorology and Air Quality Group, Wageningen University & Research, P.O. Box 47, 6700, AA, Wageningen, the Netherlands
| | - Inge de Graaf
- Water Systems and Global Change Group, Wageningen University & Research, P.O. Box 47, 6700, AA, Wageningen, the Netherlands
| | - Yuanhong Zhao
- College of Oceanic and Atmospheric Sciences, Ocean University of China, Qingdao, 266100, China
| | - Yutong Wang
- State Key Laboratory of Pollution Control and Resource Reuse and School of the Environment, Nanjing University, 163 Xianlin Ave., Nanjing, Jiangsu, 210023, China
| | - Xiaohui Du
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China
| | - Xuejun Liu
- State Key Laboratory of Nutrient Use and Management, College of Resources and Environmental Sciences, National Academy of Agriculture Green Development, National Observation and Research Station of Agriculture Green Development (Quzhou, Hebei), China Agricultural University, Beijing, China
| | - Wen Xu
- State Key Laboratory of Nutrient Use and Management, College of Resources and Environmental Sciences, National Academy of Agriculture Green Development, National Observation and Research Station of Agriculture Green Development (Quzhou, Hebei), China Agricultural University, Beijing, China.
| | - Fusuo Zhang
- State Key Laboratory of Nutrient Use and Management, College of Resources and Environmental Sciences, National Academy of Agriculture Green Development, National Observation and Research Station of Agriculture Green Development (Quzhou, Hebei), China Agricultural University, Beijing, China
| | - Mengru Wang
- Water Systems and Global Change Group, Wageningen University & Research, P.O. Box 47, 6700, AA, Wageningen, the Netherlands; Environmental Systems Analysis Group, Wageningen University & Research, Wageningen, 6708, PB, the Netherlands
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15
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Yan R, Wang H, Huang C, An J, Bai H, Wang Q, Gao Y, Jing S, Wang Y, Su H. Impact of spatial scales of control measures on the effectiveness of ozone pollution mitigation in eastern China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 906:167521. [PMID: 37793456 DOI: 10.1016/j.scitotenv.2023.167521] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/03/2023] [Revised: 09/23/2023] [Accepted: 09/29/2023] [Indexed: 10/06/2023]
Abstract
Ozone (O3) pollution is becoming the primary air pollution issue with the large decrease in fine particulate concentrations in eastern China. The development of widely recognized policies for controlling O3 pollution episodes is urgent. This study aims to provide actionable and comprehensive suggestions for O3 control policy development, with an emphasis on the precursor emission reductions. Here, we compared the impacts of different spatial scale reductions on a widespread O3 pollution episode in eastern China by a state-of-the-art regional air quality model. We find that region-scale joint control (in >30 cities) is much more effective than city-scale sporadic reduction in reducing O3 concentration. Sporadic controls only reduce the maximum daily 8-h average (MDA8) O3 by ∼1 μg/m3 in the controlled city, whereas regional controls lead to a MDA8 O3 decrease of ∼8 μg/m3 in the controlled region. In addition, the emission reduction effectiveness increased by 2.6 times from <5 cities to >30 cities. Continuous reductions have a cumulative effect on the decrease of MDA8 O3, showing the strongest effects within 24 h and diminishing after 48 h, which underscores the importance of reducing emissions 24 h prior to an episode. Moreover, the effect of control measures on MDA8 O3 varies spatially depending on the ratio of volatile organic compounds (VOCs) to nitrogen oxides (NOx) (VOCs/NOx). Both the reductions of VOC and NOx emissions have a positive effect on the decrease of MDA8 O3 in summer, but the effects of VOC reductions are 1.2 to 1.7 times higher than those of NOx reductions. The residential sector, due to its high VOCs/NOx emission ratio, exhibits the highest efficiency in the reduction of O3 concentrations. Our results highlight the importance of regional joint control and synergistic reduction of VOCs and NOx in eastern China.
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Affiliation(s)
- Rusha Yan
- School of Environmental Science and Engineering, Nanjing University of Information Science & Technology, Nanjing, China; State Environmental Protection Key Laboratory of Formation and Prevention of Urban Air Pollution Complex, Shanghai Academy of Environmental Sciences, Shanghai, China
| | - Hongli Wang
- State Environmental Protection Key Laboratory of Formation and Prevention of Urban Air Pollution Complex, Shanghai Academy of Environmental Sciences, Shanghai, China.
| | - Cheng Huang
- State Environmental Protection Key Laboratory of Formation and Prevention of Urban Air Pollution Complex, Shanghai Academy of Environmental Sciences, Shanghai, China
| | - Jingyu An
- State Environmental Protection Key Laboratory of Formation and Prevention of Urban Air Pollution Complex, Shanghai Academy of Environmental Sciences, Shanghai, China
| | - Heming Bai
- Research Center for Intelligent Information Technology, Nantong University, Nantong, China
| | - Qian Wang
- State Environmental Protection Key Laboratory of Formation and Prevention of Urban Air Pollution Complex, Shanghai Academy of Environmental Sciences, Shanghai, China
| | - Yaqin Gao
- State Environmental Protection Key Laboratory of Formation and Prevention of Urban Air Pollution Complex, Shanghai Academy of Environmental Sciences, Shanghai, China
| | - Shengao Jing
- State Environmental Protection Key Laboratory of Formation and Prevention of Urban Air Pollution Complex, Shanghai Academy of Environmental Sciences, Shanghai, China
| | - Yanyu Wang
- State Environmental Protection Key Laboratory of Formation and Prevention of Urban Air Pollution Complex, Shanghai Academy of Environmental Sciences, Shanghai, China
| | - Hang Su
- State Environmental Protection Key Laboratory of Formation and Prevention of Urban Air Pollution Complex, Shanghai Academy of Environmental Sciences, Shanghai, China; Multiphase Chemistry Department, Max Planck Institute for Chemistry, Mainz, Germany.
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16
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Wang C, Duan W, Cheng S, Jiang K. Emission inventory and air quality impact of non-road construction equipment in different emission stages. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 906:167416. [PMID: 37774875 DOI: 10.1016/j.scitotenv.2023.167416] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/15/2023] [Revised: 09/05/2023] [Accepted: 09/25/2023] [Indexed: 10/01/2023]
Abstract
Non-road construction equipment (NRCE) is an important source of air pollution, and it is crucial to fully understand the impact of NRCE on atmospheric PM2.5 and O3 pollution. However, systematic assessment of the impact of NRCE emissions on the atmosphere is lacking, especially with the latest implementation of the Stage IV Standard, and current research progress is insufficient for the development of effective control measures. This study estimated NRCE emission inventories at different emission standard stages and their impact on the atmosphere, using the "2 + 26" cities as the case study area. The results showed that the total NRCE emissions of CO, NOx, VOC, and PM2.5 were 387, 418, 82, and 24 kt in 2015 and 319, 262, 62, and 15 kt in 2020 and are predicted to be 270, 226, 48, and 10 kt in 2025, respectively. Simulation results showed that the contributions of NRCE to NO3-, NO2, PM2.5, and O3 were 16.7 %, 18.9 %, 7.7 %, and 8.2 % in 2015 to 13.6 %, 18.4 %, 6.5 %, and 6.7 % in 2020, respectively. In both 2015 and 2020, NRCE emissions in southern cities showed greater impacts on the average concentrations in the "2 + 26" cities than those in northern cities. The contributions of local NRCE emissions to local PM2.5 and O3 concentrations in the 28 cities ranged from 30 %-59 % and 13 %-39 %, respectively. The O3 sensitivity estimated by the HDDM illustrated that nonlinear characteristics highlighted the importance of coordinated control of NOx and VOC and can inspire development of post-processing technology and electricity substitution. The belt-like area connecting Zhengzhou to Beijing showed higher exposure concentrations of PM2.5 and O3, and the concentration exposure in urban areas was much higher than that in the rural and other areas. The environmental impact assessment of NRCE emissions can provide guidance for its management and development.
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Affiliation(s)
- Chuanda Wang
- Key Laboratory of Beijing on Regional Air Pollution Control, Faculty of Environment and Life, Beijing University of Technology, Beijing 100124, China
| | - Wenjiao Duan
- Key Laboratory of Beijing on Regional Air Pollution Control, Faculty of Environment and Life, Beijing University of Technology, Beijing 100124, China.
| | - Shuiyuan Cheng
- Key Laboratory of Beijing on Regional Air Pollution Control, Faculty of Environment and Life, Beijing University of Technology, Beijing 100124, China
| | - Kai Jiang
- Key Laboratory of Beijing on Regional Air Pollution Control, Faculty of Environment and Life, Beijing University of Technology, Beijing 100124, China
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17
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Zhao H, Meng P, Gao S, Wang Y, Sun P, Wu Z. Recent advances in simultaneous removal of NOx and VOCs over bifunctional catalysts via SCR and oxidation reaction. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 906:167553. [PMID: 37802335 DOI: 10.1016/j.scitotenv.2023.167553] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/24/2023] [Revised: 09/26/2023] [Accepted: 09/30/2023] [Indexed: 10/08/2023]
Abstract
NOx and volatile organic compounds (VOCs) are two major pollutants commonly found in industrial flue gas emissions. They play a significant role as precursors in the formation of ozone and fine particulate matter (PM2.5). The simultaneous removal of NOx and VOCs is crucial in addressing ozone and PM2.5 pollution. In terms of investment costs and space requirements, the development of bifunctional catalysts for the simultaneous selective catalytic reduction (SCR) of NOx and catalytic oxidation of VOCs emerges as a viable technology that has garnered considerable attention. This review provides a summary of recent advances in catalysts for the simultaneous removal of NOx and VOCs. It discusses the reaction mechanisms and interactions involved in NH3-SCR and VOCs catalytic oxidation, the effects of catalyst acidity and redox properties. The insufficiency of bifunctional catalysts was pointed out, including issues related to catalytic activity, product selectivity, catalyst deactivation, and environmental concerns. Subsequently, potential solutions are presented to enhance catalyst performance, such as optimizing the redox properties and acidity, enhancing resistance to poisoning, substituting environment friendly metals and introducing hydrocarbon selective catalytic reduction (HC-SCR) reaction. Finally, some suggestions are given for future research directions in catalyst development are prospected.
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Affiliation(s)
- Huaiyuan Zhao
- Department of Environmental Engineering, Zhejiang University, Hangzhou 310058, China; Zhejiang Tianlan Environmental Protection Technology Co., Ltd., Hangzhou 311202, China; Zhejiang Provincial Engineering Research Center of Industrial Boiler & Furnace Flue Gas Pollution Control, 866 Yuhangtang Road, Hangzhou 310058, China
| | - Pu Meng
- Zhejiang Tianlan Environmental Protection Technology Co., Ltd., Hangzhou 311202, China; Zhejiang Provincial Engineering Research Center of Industrial Boiler & Furnace Flue Gas Pollution Control, 866 Yuhangtang Road, Hangzhou 310058, China
| | - Shan Gao
- Zhejiang Tianlan Environmental Protection Technology Co., Ltd., Hangzhou 311202, China; Zhejiang Provincial Engineering Research Center of Industrial Boiler & Furnace Flue Gas Pollution Control, 866 Yuhangtang Road, Hangzhou 310058, China.
| | - Yuejun Wang
- Zhejiang Tianlan Environmental Protection Technology Co., Ltd., Hangzhou 311202, China; Zhejiang Provincial Engineering Research Center of Industrial Boiler & Furnace Flue Gas Pollution Control, 866 Yuhangtang Road, Hangzhou 310058, China
| | - Pengfei Sun
- Department of Chemistry, Key Laboratory of Surface & Interface Science of Polymer Materials of Zhejiang Province, Zhejiang Sci-Tech University, Hangzhou 310018, China
| | - Zhongbiao Wu
- Department of Environmental Engineering, Zhejiang University, Hangzhou 310058, China; Zhejiang Provincial Engineering Research Center of Industrial Boiler & Furnace Flue Gas Pollution Control, 866 Yuhangtang Road, Hangzhou 310058, China
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18
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Wang M, Chen X, Jiang Z, He TL, Jones D, Liu J, Shen Y. Meteorological and anthropogenic drivers of surface ozone change in the North China Plain in 2015-2021. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 906:167763. [PMID: 37832678 DOI: 10.1016/j.scitotenv.2023.167763] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Revised: 09/16/2023] [Accepted: 10/10/2023] [Indexed: 10/15/2023]
Abstract
Surface ozone (O3) concentrations in China have increased largely in the past decade. An accurate understanding of O3 pollution evolution is critical for making effective regulatory policies. Here we integrate data- and process-based models to explore the drivers of the observed summertime surface O3 change in the North China Plain (NCP) over 2015-2021. The data-based model by the deep learning (DL) suggests the reverse of meteorological contributions to the observed O3 change, i.e., 0.14 ppb/y in 2015-2019 and -1.74 ppb/y in 2019-2021. This is mainly resulted from the reversed changes in meteorological variables in surface air temperature and relative humidity. The simulations from a global chemical transport model, GEOS-Chem, also support those results, i.e., the meteorological contribution to O3 changes are 0.26 ppb/y in 2015-2019 and -0.74 ppb/y in 2019-2021. Furthermore, our analysis exhibits possible weakened anthropogenic contributions to surface O3 rise, for example, 1.53 and 0.54 ppb/y by DL in 2015-2019 and 2019-2021, respectively. Similarly, GEOS-Chem simulations suggest an accelerated decrease in surface O3 concentrations driven by the decline in nitrogen dioxide (NO2) concentrations, i.e., approximately 0.4 and 1.2 ppb in 2015-2019 and 2019-2021, respectively. The combined effects of meteorological and anthropogenic contributions led to a significant decrease in surface O3 concentrations by -1.20 ppb/y in 2019-2021. The findings in this work offer valuable insights to mitigate O3 pollution in China.
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Affiliation(s)
- Min Wang
- School of Earth and Space Sciences, University of Science and Technology of China, Hefei, Anhui 230026, China
| | - Xiaokang Chen
- School of Earth and Space Sciences, University of Science and Technology of China, Hefei, Anhui 230026, China
| | - Zhe Jiang
- School of Earth and Space Sciences, University of Science and Technology of China, Hefei, Anhui 230026, China.
| | - Tai-Long He
- Department of Physics, University of Toronto, Toronto, ON M5S 1A7, Canada; Department of Atmospheric Sciences, University of Washington, Seattle, WA 98195, USA.
| | - Dylan Jones
- Department of Physics, University of Toronto, Toronto, ON M5S 1A7, Canada
| | - Jane Liu
- School of Geographical Sciences, Fujian Normal University, Fuzhou, Fujian 350007, China; Department of Geography and Planning, University of Toronto, Toronto, ON M5S 3G3, Canada
| | - Yanan Shen
- School of Earth and Space Sciences, University of Science and Technology of China, Hefei, Anhui 230026, China
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19
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Wang T, Wang Y, Zhang Z, Liang C, Shan M, Sun Y. A regional cooperative reduction game model for air pollution control in North China. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2023; 346:118949. [PMID: 37717391 DOI: 10.1016/j.jenvman.2023.118949] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/23/2023] [Revised: 08/12/2023] [Accepted: 09/06/2023] [Indexed: 09/19/2023]
Abstract
Due to variations in economic scale, economic structure, and technological advancement across different Chinese provinces and cities, the cost of air pollution reduction differs significantly. Therefore, the total reduction cost can be decreased by capitalizing on these regional discrepancies in reduction cost to carry out cooperative emission reduction. In this paper, taking NOx reduction in North China as an example, a regional cooperative reduction game (CRG) model was constructed to minimize the total cost of emission reduction while achieving future emission reduction targets. The fair allocation of benefits from cooperation plays a crucial role in motivating regions to participate into the cooperation. A comprehensive mechanism of benefits allocation was proposed to achieve fair transferred compensation. The mechanism combines the consumption responsibility principle based on input-output theory and the Shapley value method based on game theory. Compared to the cost before the optimized collaboration, the CRG model will save 20.36% and 13.71% of the total reduction cost in North China, respectively, under the target of 17.68% NOx reduction by 2025 and 66.44% NOx reduction by 2035 relative to 2020. This method can be employed in other regions to achieve targets for air pollution reduction at minimum cost, and to motivate inter-regional cooperation with this practical and fair way of transferred compensation.
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Affiliation(s)
- Tingyu Wang
- School of Environmental Science and Engineering, Tianjin University, Tianjin, 300350, China
| | - Yuan Wang
- School of Environmental Science and Engineering, Tianjin University, Tianjin, 300350, China.
| | - Zengkai Zhang
- State Key Laboratory of Marine Environmental Science, College of the Environment and Ecology, Xiamen University, Xiamen, Fujian, 361102, China.
| | - Chen Liang
- School of Environmental Science and Engineering, Tianjin University, Tianjin, 300350, China
| | - Mei Shan
- School of Environmental Science and Engineering, Tianjin University, Tianjin, 300350, China
| | - Yun Sun
- School of Environmental Science and Engineering, Tianjin University, Tianjin, 300350, China
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20
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Chen D, Khetan A, Lei H, Rizzotto V, Yang JY, Jiang J, Sun Q, Peng B, Chen P, Palkovits R, Ye D, Simon U. Copper Site Motion Promotes Catalytic NO x Reduction under Zeolite Confinement. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2023; 57:16121-16130. [PMID: 37842921 DOI: 10.1021/acs.est.3c03422] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/17/2023]
Abstract
Ammonia-mediated selective catalytic reduction (NH3-SCR) is currently the key approach to abate nitrogen oxides (NOx) emitted from heavy-duty lean-burn vehicles. The state-of-art NH3-SCR catalysts, namely, copper ion-exchanged chabazite (Cu-CHA) zeolites, perform rather poorly at low temperatures (below 200 °C) and are thus incapable of eliminating effectively NOx emissions under cold-start conditions. Here, we demonstrate a significant promotion of low-temperature NOx reduction by reinforcing the dynamic motion of zeolite-confined Cu sites during NH3-SCR. Combining complex impedance-based in situ spectroscopy (IS) and extended density-functional tight-binding molecular dynamics simulation, we revealed an environment- and temperature-dependent nature of the dynamic Cu motion within the zeolite lattice. Further coupling in situ IS with infrared spectroscopy allows us to unravel the critical role of monovalent Cu in the overall Cu mobility at a molecular level. Based on these mechanistic understandings, we elicit a boost of NOx reduction below 200 °C by reinforcing the dynamic Cu motion in various Cu-zeolites (Cu-CHA, Cu-ZSM-5, Cu-Beta, etc.) via facile postsynthesis treatments, either in a reductive mixture at low temperatures (below 250 °C) or in a nonoxidative atmosphere at high temperatures (above 450 °C).
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Affiliation(s)
- Dongdong Chen
- National Engineering Laboratory for VOCs Pollution Control Technology and Equipment, Guangdong Provincial Key Laboratory of Atmospheric Environment and Pollution Control, School of Environment and Energy, South China University of Technology, 510006 Guangzhou, China
| | - Abhishek Khetan
- Multiscale Modelling of Heterogeneous Catalysis in Energy Systems, RWTH Aachen University, Schinkelstrasse 8, 52062 Aachen, Germany
| | - Huarong Lei
- National Engineering Laboratory for VOCs Pollution Control Technology and Equipment, Guangdong Provincial Key Laboratory of Atmospheric Environment and Pollution Control, School of Environment and Energy, South China University of Technology, 510006 Guangzhou, China
- Institute of Inorganic Chemistry, RWTH Aachen University, Landoltweg 1a, 52074 Aachen Germany
| | - Valentina Rizzotto
- Institute of Inorganic Chemistry, RWTH Aachen University, Landoltweg 1a, 52074 Aachen Germany
| | - Jia-Yue Yang
- Optics & Thermal Radiation Research Center, Shandong University, 266237 Qingdao, China
| | - Jiuxing Jiang
- MOE Key Laboratory of Bioinorganic and Synthetic Chemistry, School of Chemistry, Sun Yat-Sen University, 510275 Guangzhou, China
| | - Qiming Sun
- Innovation Center for Chemical Sciences, College of Chemistry, Chemical Engineering and Materials Science, Soochow University, 215123 Suzhou, China
| | - Baoxiang Peng
- Laboratory of Industrial Chemistry, Ruhr University Bochum, 44780 Bochum, Germany
| | - Peirong Chen
- National Engineering Laboratory for VOCs Pollution Control Technology and Equipment, Guangdong Provincial Key Laboratory of Atmospheric Environment and Pollution Control, School of Environment and Energy, South China University of Technology, 510006 Guangzhou, China
| | - Regina Palkovits
- Chair of Heterogeneous Catalysis and Chemical Technology, RWTH Aachen University, Worringerweg 2, 52074 Aachen, Germany
| | - Daiqi Ye
- National Engineering Laboratory for VOCs Pollution Control Technology and Equipment, Guangdong Provincial Key Laboratory of Atmospheric Environment and Pollution Control, School of Environment and Energy, South China University of Technology, 510006 Guangzhou, China
| | - Ulrich Simon
- Institute of Inorganic Chemistry, RWTH Aachen University, Landoltweg 1a, 52074 Aachen Germany
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21
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Wang Q, Sheng D, Wu C, Zhao J, Li F, Yao S, Ou X, Li W, Chen J. Exploring ozone formation rules and concentration response to the change of precursors based on artificial neural network simulation in a typical industrial park. Heliyon 2023; 9:e20125. [PMID: 37810165 PMCID: PMC10559865 DOI: 10.1016/j.heliyon.2023.e20125] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2023] [Revised: 09/12/2023] [Accepted: 09/12/2023] [Indexed: 10/10/2023] Open
Abstract
Industrial parks have more complex O3 formation mechanisms due to a higher concentration and more dense emission of precursors. This study establishes an artificial neural network (ANN) model with good performance by expanding the moment and concentration changes of pollutants into general variables of meteorological factors and concentrations of pollutants. Finally, the O3 formation rules and concentration response to the changes of volatile organic compounds (VOCs) and nitrogen oxides (NOx) was explored. The results showed that the studied area belonged to the NOx-sensitive regime and the sensitivity was strongly affected by relative humidity (RH) and pressure (P). The concentration of O3 tends to decrease with a higher P, lower temperature (Temp), and medium to low RH when nitric oxide (NO) is added. Conversely, at medium P, high Temp, and high RH, the addition of nitrogen dioxide (NO2) leads to a larger decrease capacity in O3 concentration. More importantly, there is a local reachable maximum incremental reactivity (MIRL) at each certain VOCs concentration level which linearly increased with VOCs. The general maximum incremental reactivity (MIR) may lead to a significant overestimation of the attainable O3 concentration in NOx-sensitive regimes. The results can significantly support the local management strategies for O3 and the precursors control.
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Affiliation(s)
- Qiaoli Wang
- College of Environment, Zhejiang University of Technology, Hangzhou, 310032, China
| | - Dongping Sheng
- College of Environment, Zhejiang University of Technology, Hangzhou, 310032, China
| | - Chengzhi Wu
- Trinity Consultants, Inc. (China Office), Hangzhou, 310012, China
| | - Jingkai Zhao
- College of Environment, Zhejiang University of Technology, Hangzhou, 310032, China
| | - Feili Li
- College of Environment, Zhejiang University of Technology, Hangzhou, 310032, China
| | - Shengdong Yao
- College of Environment, Zhejiang University of Technology, Hangzhou, 310032, China
| | - Xiaojie Ou
- College of Environment, Zhejiang University of Technology, Hangzhou, 310032, China
| | - Wei Li
- Key Laboratory of Biomass Chemical Engineering of the Ministry of Education, Institute of Industrial Ecology and Environment, College of Chemical and Biological Engineering, Zhejiang University (Zijingang Campus), Hangzhou, 310030, China
| | - Jianmeng Chen
- College of Environment, Zhejiang University of Technology, Hangzhou, 310032, China
- Zhejiang University of Science & Technology, Hangzhou, 310023, China
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22
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Tian X, Xiong Y, Mi Z, Zhang Q, Tian K, Zhao B, Dong Z, Wang S, Ding D, Xing J, Zhu Y, Long S, Zhang P. Mismatched Social Welfare Allocation and PM 2.5-Related Health Damage along Value Chains within China. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2023; 57:12689-12700. [PMID: 37587658 DOI: 10.1021/acs.est.3c00181] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/18/2023]
Abstract
Value chains have played a critical part in the growth. However, the fairness of the social welfare allocation along the value chain is largely underinvestigated, especially when considering the harmful environmental and health effects associated with the production processes. We used fine-scale profiling to analyze the social welfare allocation along China's domestic value chain within the context of environmental and health effects and investigated the underlying mechanisms. Our results suggested that the top 10% regions in the value chain obtained 2.9 times more social income and 2.1 times more job opportunities than the average, with much lower health damage. Further inspection showed a significant contribution of the "siphon effect"─major resource providers suffer the most in terms of localized health damage along with insufficient social welfare for compensation. We found that inter-region atmosphere transport results in redistribution for 53% health damages, which decreases the welfare-damage mismatch at "suffering" regions but also causes serious health damage to more than half of regions and populations in total. Specifically, around 10% of regions have lower social welfare and also experienced a significant increase in health damage caused by atmospheric transport. These results highlighted the necessity of a value chain-oriented, quantitative compensation-driven policy.
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Affiliation(s)
- Xin Tian
- School of Environment, Beijing Normal University, Beijing 100875, China
- State Key Laboratory of Water Environment Simulation, Beijing Normal University, Beijing 100875, China
| | - Yiling Xiong
- School of Environment, Beijing Normal University, Beijing 100875, China
| | - Zhifu Mi
- The Bartlett School of Sustainable Construction, University College London, London WC1E 7HB, U.K
| | - Qianzhi Zhang
- School of Environment, Beijing Normal University, Beijing 100875, China
| | - Kailan Tian
- Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190, China
| | - Bin Zhao
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
| | - Zhaoxin Dong
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
| | - Shuxiao Wang
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
| | - Dian Ding
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
| | - Jia Xing
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
| | - Yun Zhu
- Guangdong Provincial Key Laboratory of Atmospheric Environment and Pollution Control, College of Environment and Energy, South China University of Technology, Guangzhou Higher Education Mega Center, Guangzhou 510006, China
| | - Shicheng Long
- Guangdong Provincial Key Laboratory of Atmospheric Environment and Pollution Control, College of Environment and Energy, South China University of Technology, Guangzhou Higher Education Mega Center, Guangzhou 510006, China
| | - Pingdan Zhang
- Business School, Beijing Normal University, Beijing 100875, China
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23
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Ren Y, Guan X, Zhang Q, Li L, Tao C, Ren S, Wang Q, Wang W. A machine learning-based study on the impact of COVID-19 on three kinds of pollution in Beijing-Tianjin-Hebei region. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 884:163190. [PMID: 37061051 PMCID: PMC10102532 DOI: 10.1016/j.scitotenv.2023.163190] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/19/2023] [Revised: 03/25/2023] [Accepted: 03/27/2023] [Indexed: 05/07/2023]
Abstract
Large-scale restrictions on anthropogenic activities in China in 2020 due to the Corona Virus Disease 2019 (COVID-19) indirectly led to improvements in air quality. Previous studies have paid little attention to the changes in nitrogen dioxide (NO2), fine particulate matter (PM2.5) and ozone (O3) concentrations at different levels of anthropogenic activity limitation and their interactions. In this study, machine learning models were used to simulate the concentrations of three pollutants during periods of different levels of lockdown, and compare them with observations during the same period. The results show that the difference between the simulated and observed values of NO2 concentrations varies at different stages of the lockdown. Variation between simulated and observed O3 and PM2.5 concentrations were less distinct at different stages of lockdowns. During the most severe period of the lockdowns, NO2 concentrations decreased significantly with a maximum decrease of 65.28 %, and O3 concentrations increased with a maximum increase of 75.69 %. During the first two weeks of the lockdown, the titration reaction in the atmosphere was disrupted due to the rapid decrease in NO2 concentrations, leading to the redistribution of Ox (NO2 + O3) in the atmosphere and eventually to the production of O3 and secondary PM2.5. The effect of traffic restrictions on the reduction of NO2 concentrations is significant. However, it is also important to consider the increase in O3 due to the constant volatile organic compounds (VOCs) and the decrease in NOx (NO+NO2). Traffic restrictions had a limited effect on improving PM2.5 pollution, so other beneficial measures were needed to sustainably reduce particulate matter pollution. Research on COVID-19 could provide new insights into future clean air action.
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Affiliation(s)
- Yuchao Ren
- Big Data Research Center for Ecology and Environment, Environment Research Institute, Shandong University, Qingdao 266003, PR China
| | - Xu Guan
- Shandong Academy for Environmental Planning, Jinan 250101, PR China.
| | - Qingzhu Zhang
- Big Data Research Center for Ecology and Environment, Environment Research Institute, Shandong University, Qingdao 266003, PR China.
| | - Lei Li
- Big Data Research Center for Ecology and Environment, Environment Research Institute, Shandong University, Qingdao 266003, PR China
| | - Chenliang Tao
- Big Data Research Center for Ecology and Environment, Environment Research Institute, Shandong University, Qingdao 266003, PR China
| | - Shilong Ren
- Big Data Research Center for Ecology and Environment, Environment Research Institute, Shandong University, Qingdao 266003, PR China
| | - Qiao Wang
- Big Data Research Center for Ecology and Environment, Environment Research Institute, Shandong University, Qingdao 266003, PR China
| | - Wenxing Wang
- Big Data Research Center for Ecology and Environment, Environment Research Institute, Shandong University, Qingdao 266003, PR China
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24
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Zhang B, Qiao L, Han H, Xie W, Li L. Variations in VOCs Emissions and Their O 3 and SOA Formation Potential among Different Ages of Plant Foliage. TOXICS 2023; 11:645. [PMID: 37624151 PMCID: PMC10458546 DOI: 10.3390/toxics11080645] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/21/2023] [Revised: 07/21/2023] [Accepted: 07/22/2023] [Indexed: 08/26/2023]
Abstract
Volatile organic compounds (VOCs) emitted by plant foliage play an important role in ozone (O3) and secondary organic aerosol (SOA) formation. Their emissions can be influenced by the leaf age. We explored the VOCs emissions and their effects on the formation of O3 and SOA from plant foliage in different ages. VOCs emissions from the young, mature, and senescent leaves of Ginkgo biloba, Ligustrum lucidum, and Forsythia suspensa were measured using the dynamic enclosure system and the TD-GC-MS technique. Based on the emission rates of quantified compounds, their potential to form O3 and SOA was estimated. Results showed that there were significant differences in the VOCs emission rate and their composition among leaves in different ages. The emission rate of the total VOCs by young leaves was the highest, while the lowest by senescent leaves. Monoterpenes were the dominant VOCs category, and isoprene emission had the lowest contribution for the leaves at each age. With increasing leaf age, the proportion of monoterpenes emission increased, and the proportion of sesquiterpenes decreased. The variations of isoprene and other VOCs were different. The potentials of total VOCs, isoprene, monoterpenes, sesquiterpenes, and other VOCs to form O3 (OFP) and SOA (SOAP) varied significantly among leaves at different ages. The total OFP and SOAP were the highest by young leaves, while the lowest by senescent leaves. With increasing leaf age, the contribution of monoterpenes to OFP and SOAP also increased, while that of sesquiterpenes decreased. Our study will provide support for the more accurate parameterization of the emission model and help to understand the VOCs emissions and study the precise prevention and control of complex air pollution at different times.
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Affiliation(s)
| | | | | | - Wenxia Xie
- College of Environmental Sciences and Engineering, Carbon Neutrality and Eco-Environmental Technology Innovation Center of Qingdao, Qingdao University, Qingdao 266071, China; (B.Z.); (L.Q.); (H.H.)
| | - Lingyu Li
- College of Environmental Sciences and Engineering, Carbon Neutrality and Eco-Environmental Technology Innovation Center of Qingdao, Qingdao University, Qingdao 266071, China; (B.Z.); (L.Q.); (H.H.)
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25
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Zheng H, Chang X, Wang S, Li S, Zhao B, Dong Z, Ding D, Jiang Y, Huang G, Huang C, An J, Zhou M, Qiao L, Xing J. Sources of Organic Aerosol in China from 2005 to 2019: A Modeling Analysis. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2023; 57:5957-5966. [PMID: 36994990 DOI: 10.1021/acs.est.2c08315] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/19/2023]
Abstract
Organic aerosol (OA) is a key component of fine particulate matter (PM2.5) and affects the human health and leads to climate change. With strict control measures for air pollutants during the last decade, the OA concentration in China declined slowly, while its sources remain unclear. In this study, we simulate the primary OA (POA) and secondary OA (SOA) concentrations from 2005 to 2019 with a state-of-the-art air quality model, Community Multiscale Air Quality (CMAQ, version 5.3.2) coupled with a Two-Dimensional Volatility Basis Set (2D-VBS) module, and a long-term emission inventory of full-volatility organic compounds in China and conduct source apportionment and sensitivity analysis. The simulation results show that, from 2005 to 2019, the OA concentration in China decreased from 24.0 to 12.8 μg/m3 with most of the reduction from POA. The OA pollution from residential biomass burning declined 75% from 2005 to 2019, while it is still the major OA source in China. OA pollution from VCP increased by more than 2-fold and became the largest SOA source in China. From 2014 to 2019, the NOx control in China slightly offset the decrease of SOA concentration due to elevated oxidation capacity.
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Affiliation(s)
- Haotian Zheng
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
- State Environmental Protection Key Laboratory of the Formation and Prevention of the Urban Air Pollution Complex, Shanghai Academy of Environmental Sciences, Shanghai 200233, China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
| | - Xing Chang
- Transport Planning and Research Institute, Ministry of Transport, Laboratory of Transport Pollution Control and Monitoring Technology, Beijing 100028, China
| | - Shuxiao Wang
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
| | - Shengyue Li
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
| | - Bin Zhao
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
| | - Zhaoxin Dong
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
| | - Dian Ding
- Institute for Atmospheric and Earth System Research/Physics, Faculty of Science, University of Helsinki, 00014 Helsinki, Finland
| | - Yueqi Jiang
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
| | - Guanghan Huang
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
| | - Cheng Huang
- State Environmental Protection Key Laboratory of the Formation and Prevention of the Urban Air Pollution Complex, Shanghai Academy of Environmental Sciences, Shanghai 200233, China
| | - Jingyu An
- State Environmental Protection Key Laboratory of the Formation and Prevention of the Urban Air Pollution Complex, Shanghai Academy of Environmental Sciences, Shanghai 200233, China
| | - Min Zhou
- State Environmental Protection Key Laboratory of the Formation and Prevention of the Urban Air Pollution Complex, Shanghai Academy of Environmental Sciences, Shanghai 200233, China
| | - Liping Qiao
- State Environmental Protection Key Laboratory of the Formation and Prevention of the Urban Air Pollution Complex, Shanghai Academy of Environmental Sciences, Shanghai 200233, China
| | - Jia Xing
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
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26
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Jiang Y, Ding D, Dong Z, Liu S, Chang X, Zheng H, Xing J, Wang S. Extreme Emission Reduction Requirements for China to Achieve World Health Organization Global Air Quality Guidelines. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2023; 57:4424-4433. [PMID: 36898019 DOI: 10.1021/acs.est.2c09164] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/18/2023]
Abstract
A big gap exists between current air quality in China and the World Health Organization (WHO) global air quality guidelines (AQG) released in 2021. Previous studies on air pollution control have focused on emission reduction demand in China but ignored the influence of transboundary pollution, which has been proven to have a significant impact on air quality in China. Here, we develop an emission-concentration response surface model coupled with transboundary pollution to quantify the emission reduction demand for China to achieve WHO AQG. China cannot achieve WHO AQG by its own emission reduction for high transboundary pollution of both PM2.5 and O3. Reducing transboundary pollution will loosen the reduction demand for NH3 and VOCs emissions in China. However, to meet 10 μg·m-3 for PM2.5 and 60 μg·m-3 for peak season O3, China still needs to reduce its emissions of SO2, NOx, NH3, VOCs, and primary PM2.5 by more than 95, 95, 76, 62, and 96% respectively, on the basis of 2015. We highlight that both extreme emission reduction in China and great efforts in addressing transboundary air pollution are crucial to reach WHO AQG.
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Affiliation(s)
- Yueqi Jiang
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
| | - Dian Ding
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
- Institute for Atmospheric and Earth System Research/Physics, Faculty of Science, University of Helsinki, 00014 Helsinki, Finland
| | - Zhaoxin Dong
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
| | - Shuchang Liu
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
- Institute for Atmospheric and Climate Science, ETH Zurich, CH-8092 Zurich, Switzerland
| | - Xing Chang
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
- Transport Planning and Research Institute, Ministry of Transport, Laboratory of Transport Pollution Control and Monitoring Technology, Beijing 100028, China
| | - Haotian Zheng
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
| | - Jia Xing
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
| | - Shuxiao Wang
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
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27
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Ke L, Feng G, Zhang Y, Ma X, Zhao B, Sun Y, Dong Z, Xing J, Wang S, Di Q. Causal effects of prenatal and chronic PM 2.5 exposures on cognitive function. ENVIRONMENTAL RESEARCH 2023; 219:115138. [PMID: 36565844 DOI: 10.1016/j.envres.2022.115138] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/12/2022] [Revised: 11/08/2022] [Accepted: 12/20/2022] [Indexed: 06/17/2023]
Abstract
Growing evidence indicated an association between PM2.5 exposure and cognitive function, but the causal effect and the cognitive effect of prenatal PM2.5 exposure remain elusive. We obtained 15,099 subjects from a nationally representative sample of China and measured their cognitive performance. We ascertained subjects' prenatal PM2.5 exposure and chronic PM2.5 exposure of the recent two years. Using this national sample, we found that PM2.5 exposure during the mid- to late-pregnancy was significantly associated with declined cognition and income; chronic PM2.5 exposure was also independently associated with cognition and income measured at adulthood with greater magnitude. Negative effect modification was observed between prenatal and chronic PM2.5 exposure. Instrumental variable approach and difference-in-difference study verified causal effects: every 1 μg/m3 increase in prenatal and chronic PM2.5 exposures were causally associated with -0.22% (-0.38%, -0.06%) and -0.17% (-0.31%, -0.03%) changes in cognitive function, respectively. People with low cognition and low income were more vulnerable to PM2.5 exposure with greater cognitive and income decline. In the future, although China's improved air quality continues to benefit people and reduce cognitive decline induced by chronic PM2.5 exposure, high prenatal PM2.5 exposure will continue to hurt the overall cognition of Chinese population, since in total 360 million people were born during the 2000-2020 polluted era. Prenatal PM2.5-induced cognitive decline would remain largely unchanged before 2050 and gradually reduce after 2065, regardless of environmental policy scenarios. The long-lasting cognitive impact of PM2.5 is worth considering while enacting environmental policies.
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Affiliation(s)
- Limei Ke
- School of Medicine, Tsinghua University, Beijing, 100084, China.
| | - Guoqing Feng
- School of Medicine, Tsinghua University, Beijing, 100084, China.
| | - Yao Zhang
- Soochow College, Soochow University, Suzhou, 215006, China; Division of Sports Science & Physical Education, Tsinghua University, Beijing, 100084, China.
| | - Xindong Ma
- Division of Sports Science & Physical Education, Tsinghua University, Beijing, 100084, China; IDG/McGovern Institute for Brain Research, Tsinghua University, Beijing, 100084, China.
| | - Bin Zhao
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of environment, Tsinghua University, Beijing, 100084, China; State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing, 100084, China.
| | - Yisheng Sun
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of environment, Tsinghua University, Beijing, 100084, China.
| | - Zhaoxin Dong
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of environment, Tsinghua University, Beijing, 100084, China.
| | - Jia Xing
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of environment, Tsinghua University, Beijing, 100084, China; State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing, 100084, China.
| | - Shuxiao Wang
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of environment, Tsinghua University, Beijing, 100084, China; State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing, 100084, China.
| | - Qian Di
- Vanke School of Public Health, Tsinghua University, Beijing, 100084, China; Institute for Healthy China, Tsinghua University, Beijing, 100084, China.
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28
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Guo J, Zhang X, Gao Y, Wang Z, Zhang M, Xue W, Herrmann H, Brasseur GP, Wang T, Wang Z. Evolution of Ozone Pollution in China: What Track Will It Follow? ENVIRONMENTAL SCIENCE & TECHNOLOGY 2023; 57:109-117. [PMID: 36577015 PMCID: PMC9835882 DOI: 10.1021/acs.est.2c08205] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/03/2022] [Revised: 12/16/2022] [Accepted: 12/16/2022] [Indexed: 06/17/2023]
Abstract
Increasing surface ozone (O3) concentrations has emerged as a key air pollution problem in many urban regions worldwide in the last decade. A longstanding major issue in tackling ozone pollution is the identification of the O3 formation regime and its sensitivity to precursor emissions. In this work, we propose a new transformed empirical kinetic modeling approach (EKMA) to diagnose the O3 formation regime using regulatory O3 and NO2 observation datasets, which are easily accessible. We demonstrate that mapping of monitored O3 and NO2 data on the modeled regional O3-NO2 relationship diagram can illustrate the ozone formation regime and historical evolution of O3 precursors of the region. By applying this new approach, we show that for most urban regions of China, the O3 formation is currently associated with a volatile organic compound (VOC)-limited regime, which is located within the zone of daytime-produced O3 (DPO3) to an 8h-NO2 concentration ratio below 8.3 ([DPO3]/[8h-NO2] ≤ 8.3). The ozone production and controlling effects of VOCs and NOx in different cities of China were compared according to their historical O3-NO2 evolution routes. The approach developed herein may have broad application potential for evaluating the efficiency of precursor controls and further mitigating O3 pollution, in particular, for regions where comprehensive photochemical studies are unavailable.
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Affiliation(s)
- Jia Guo
- Key
Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental
Sciences, Chinese Academy of Sciences, Beijing 100085, China
- University
of Chinese Academy of Sciences, Beijing 100049, China
| | - Xiaoshan Zhang
- Key
Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental
Sciences, Chinese Academy of Sciences, Beijing 100085, China
- University
of Chinese Academy of Sciences, Beijing 100049, China
| | - Yi Gao
- University
of Chinese Academy of Sciences, Beijing 100049, China
- State
Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric
Chemistry (LAPC), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
| | - Zhangwei Wang
- Key
Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental
Sciences, Chinese Academy of Sciences, Beijing 100085, China
- University
of Chinese Academy of Sciences, Beijing 100049, China
| | - Meigen Zhang
- University
of Chinese Academy of Sciences, Beijing 100049, China
- State
Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric
Chemistry (LAPC), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
| | - Wenbo Xue
- Center
of Air Quality Simulation and System Analysis, Chinese Academy of Environmental Planning, Beijing 100012, China
| | - Hartmut Herrmann
- Atmospheric
Chemistry Department (ACD), Leibniz Institute
for Tropospheric Research (TROPOS), Permoserstraße 15, Leipzig 04318, Germany
| | - Guy Pierre Brasseur
- Department
of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Kowloon 999077, Hong Kong SAR, China
- Environmental
Modeling Group, Max Planck Institute for
Meteorology, Hamburg 20146, Germany
- Atmospheric
Chemistry Observations and Modeling Laboratory, National Center for Atmospheric Research, Boulder, Colorado 80307, United States
| | - Tao Wang
- Department
of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Kowloon 999077, Hong Kong SAR, China
| | - Zhe Wang
- Division
of Environment and Sustainability, The Hong
Kong University of Science and Technology, Kowloon 999077, Hong Kong, China
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29
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Cheng Y, Huang XF, Peng Y, Tang MX, Zhu B, Xia SY, He LY. A novel machine learning method for evaluating the impact of emission sources on ozone formation. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2023; 316:120685. [PMID: 36400136 DOI: 10.1016/j.envpol.2022.120685] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/28/2022] [Revised: 11/06/2022] [Accepted: 11/14/2022] [Indexed: 06/16/2023]
Abstract
Ambient ozone air pollution is one of the most important environmental challenges in China today, and it is particularly significant to identify pollution sources and formulate control strategies. In present study, we proposed a novel method of positive matrix factorization-SHapley Additive explanation (PMF-SHAP) for evaluating the impact of emission sources on ozone formation, which can quantify the main emission sources of ozone pollution. In this method, we first used the PMF model to identify the source of volatile organic compounds (VOCs), and then quantified various emission sources using a combination of machine learning (ML) models and the SHAP algorithm. The R2 of the optimal ML model in this method was as high as 0.96, indicating that the prediction performance was excellent. Furthermore, we explored the impact of different emission sources on ozone formation, and found that ozone formation in Shenzhen was more affected by VOCs, of which vehicle emission sources may have the greatest impact. Our results suggest that the appropriate combination of traditional models with ML models can well address environmental pollution problems. Moreover, the conclusions obtained based on the PMF-SHAP method were different from the traditional ozone formation potential (OFP) results, providing valuable clues for related mechanism studies.
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Affiliation(s)
- Yong Cheng
- Laboratory of Atmospheric Observation Supersite, School of Environment and Energy, Peking University Shenzhen Graduate School, Shenzhen, 518055, China
| | - Xiao-Feng Huang
- Laboratory of Atmospheric Observation Supersite, School of Environment and Energy, Peking University Shenzhen Graduate School, Shenzhen, 518055, China.
| | - Yan Peng
- Laboratory of Atmospheric Observation Supersite, School of Environment and Energy, Peking University Shenzhen Graduate School, Shenzhen, 518055, China
| | - Meng-Xue Tang
- Laboratory of Atmospheric Observation Supersite, School of Environment and Energy, Peking University Shenzhen Graduate School, Shenzhen, 518055, China
| | - Bo Zhu
- Laboratory of Atmospheric Observation Supersite, School of Environment and Energy, Peking University Shenzhen Graduate School, Shenzhen, 518055, China
| | - Shi-Yong Xia
- Laboratory of Atmospheric Observation Supersite, School of Environment and Energy, Peking University Shenzhen Graduate School, Shenzhen, 518055, China
| | - Ling-Yan He
- Laboratory of Atmospheric Observation Supersite, School of Environment and Energy, Peking University Shenzhen Graduate School, Shenzhen, 518055, China
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30
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Bai X, Liu W, Wu B, Liu S, Liu X, Hao Y, Liang W, Lin S, Luo L, Zhao S, Zhu C, Hao J, Tian H. Emission characteristics and inventory of volatile organic compounds from the Chinese cement industry based on field measurements. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2023; 316:120600. [PMID: 36347407 DOI: 10.1016/j.envpol.2022.120600] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/06/2022] [Revised: 10/08/2022] [Accepted: 11/02/2022] [Indexed: 06/16/2023]
Abstract
Volatile organic compounds (VOCs) are major precursors of ozone (O3) and secondary organic aerosols (SOA), which degrade air quality and pose a serious risk to human health and ecological systems. Previous studies on the emission characteristics of VOCs have predominantly focused on petrochemical and solvent-using sources, while localized studies on the cement industry are scarce in China. Field measurements for four cement plants were carried out in this study to investigate the emission levels, source profiles, and secondary pollutant generation potential of 98 VOCs species emitted from rotary and shaft kilns in China. Furthermore, a species-differentiated VOCs emission inventory was compiled for the Chinese cement industry in 2019. The results demonstrated that the mass concentration of VOCs emitted from shaft kiln was more than 20-fold higher than that emitted from rotary kilns, and the alkanes was the dominant species (56%) in shaft kilns, while oxygenated VOCs (OVOCs) and halocarbons were the main species in rotary kilns. Moreover, alkenes & alkyne were the dominant contributors to ozone formation potential (OFP) in shaft kilns, whereas alkenes & alkyne and OVOCs were comparable and prominent contributors in rotary kilns. In contrast, secondary organic aerosol potential (SOAP) for the two types of kilns was dominated by aromatics. In 2019, approximately 18.18 kt VOCs were emitted from cement production and were found to be largely concentrated in the southeast and central provinces of China. Considering the influence on environmental conditions, high OFP-contributing species in cement kilns are suggested to be a priority in the pollution mitigation of O3. This study provides a new, comprehensive, and reasonable cognition of the current VOCs emissions from both rotary and shaft kilns in China, which will aid in a better understanding of VOCs emission characteristics and guide future policy-making.
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Affiliation(s)
- Xiaoxuan Bai
- State Key Joint Laboratory of Environmental Simulation & Pollution Control, School of Environment, Beijing Normal University, Beijing, 100875, China; Center for Atmospheric Environmental Studies, Beijing Normal University, Beijing, 100875, China
| | - Wei Liu
- State Key Joint Laboratory of Environmental Simulation & Pollution Control, School of Environment, Beijing Normal University, Beijing, 100875, China; Center for Atmospheric Environmental Studies, Beijing Normal University, Beijing, 100875, China
| | - Bobo Wu
- State Key Joint Laboratory of Environmental Simulation & Pollution Control, School of Environment, Beijing Normal University, Beijing, 100875, China; Center for Atmospheric Environmental Studies, Beijing Normal University, Beijing, 100875, China; School of Ecology and Environment, Beijing Technology and Business University, Beijing, 100048, China
| | - Shuhan Liu
- State Key Joint Laboratory of Environmental Simulation & Pollution Control, School of Environment, Beijing Normal University, Beijing, 100875, China; Center for Atmospheric Environmental Studies, Beijing Normal University, Beijing, 100875, China
| | - Xiangyang Liu
- State Key Joint Laboratory of Environmental Simulation & Pollution Control, School of Environment, Beijing Normal University, Beijing, 100875, China; Center for Atmospheric Environmental Studies, Beijing Normal University, Beijing, 100875, China
| | - Yan Hao
- State Key Joint Laboratory of Environmental Simulation & Pollution Control, School of Environment, Beijing Normal University, Beijing, 100875, China
| | - Weizhao Liang
- Center for Atmospheric Environmental Studies, Beijing Normal University, Beijing, 100875, China
| | - Shumin Lin
- State Key Joint Laboratory of Environmental Simulation & Pollution Control, School of Environment, Beijing Normal University, Beijing, 100875, China; Center for Atmospheric Environmental Studies, Beijing Normal University, Beijing, 100875, China
| | - Lining Luo
- State Key Joint Laboratory of Environmental Simulation & Pollution Control, School of Environment, Beijing Normal University, Beijing, 100875, China; Center for Atmospheric Environmental Studies, Beijing Normal University, Beijing, 100875, China
| | - Shuang Zhao
- State Key Joint Laboratory of Environmental Simulation & Pollution Control, School of Environment, Beijing Normal University, Beijing, 100875, China; Center for Atmospheric Environmental Studies, Beijing Normal University, Beijing, 100875, China
| | - Chuanyong Zhu
- Center for Atmospheric Environmental Studies, Beijing Normal University, Beijing, 100875, China; School of Environmental Science and Engineering, Qilu University of Technology, Jinan, 250353, China
| | - Jiming Hao
- School of Environment, Tsinghua University, Beijing, 100084, China
| | - Hezhong Tian
- State Key Joint Laboratory of Environmental Simulation & Pollution Control, School of Environment, Beijing Normal University, Beijing, 100875, China; Center for Atmospheric Environmental Studies, Beijing Normal University, Beijing, 100875, China.
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31
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Zhang Z, Jiang J, Lu B, Meng X, Herrmann H, Chen J, Li X. Attributing Increases in Ozone to Accelerated Oxidation of Volatile Organic Compounds at Reduced Nitrogen Oxides Concentrations. PNAS NEXUS 2022; 1:pgac266. [PMID: 36712335 PMCID: PMC9802302 DOI: 10.1093/pnasnexus/pgac266] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/10/2022] [Revised: 08/26/2022] [Accepted: 11/15/2022] [Indexed: 11/19/2022]
Abstract
Surface ozone (O3) is an important secondary pollutant affecting climate change and air quality in the atmosphere. Observations during the COVID-19 lockdown in urban China show that the co-abatement of nitrogen oxides (NOx) and volatile organic compounds (VOCs) caused winter ground-level O3 increases, but the chemical mechanisms involved are unclear. Here we report field observations in the Shanghai lockdown that reveals increasing photochemical formation of O3 from VOC oxidation with decreasing NOx. Analyses of the VOC profiles and NO/NO2 indicate that the O3 increases by the NOx reduction counteracted the O3 decreases through the VOC emission reduction in the VOC-limited region, and this may have been the main mechanism for this net O3 increase. The mechanism may have involved accelerated OH-HO2-RO2 radical cycling. The NOx reductions for increasing O3 production could explain why O3 increased from 2014 to 2020 in response to NOx emission reduction even as VOC emissions have essentially remained unchanged. Model simulations suggest that aggressive VOC abatement, particularly for alkenes and aromatics, should help reverse the long-term O3 increase under current NOx abatement conditions.
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Affiliation(s)
- Zekun Zhang
- Department of Environmental Science & Engineering, Fudan University, Shanghai 200032, China
| | - Jiakui Jiang
- Department of Environmental Science & Engineering, Fudan University, Shanghai 200032, China
| | - Bingqing Lu
- Department of Environmental Science & Engineering, Fudan University, Shanghai 200032, China
| | - Xue Meng
- Department of Environmental Science & Engineering, Fudan University, Shanghai 200032, China
| | - Hartmut Herrmann
- Leibniz-Institut für Troposphärenforschung (IfT), Permoserstr. 15, 04318 Leipzig, Germany
| | - Jianmin Chen
- Department of Environmental Science & Engineering, Fudan University, Shanghai 200032, China
| | - Xiang Li
- Department of Environmental Science & Engineering, Fudan University, Shanghai 200032, China
- Institute of Eco-Chongming (IEC), Shanghai, China
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32
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Chen T, Zhang P, Ma Q, Chu B, Liu J, Ge Y, He H. Smog Chamber Study on the Role of NO x in SOA and O 3 Formation from Aromatic Hydrocarbons. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2022; 56:13654-13663. [PMID: 36136046 DOI: 10.1021/acs.est.2c04022] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
China is facing dual pressures to reduce both PM2.5 and O3 pollution, the crucial precursors of which are NOx and VOCs. In our study, the role of NOx in both secondary organic aerosol (SOA, the important constituent of PM2.5) and O3 formation was examined in our 30 m3 indoor smog chamber. As revealed in the present study, the NOx level can obviously affect the OH concentration and volatility distribution of gas-phase oxidation products and thus O3 and SOA formation. Reducing the NOx concentration to the NOx-sensitive regime can inhibit O3 formation (by 42%), resulting in the reduction of oxidation capacity, which suppresses the SOA formation (by 45%) by inhibiting the formation of O- and N-containing gas-phase oxidation products with low volatility. The contribution of these oxidation products to the formation of SOA was also estimated, and the results could substantially support the trend of SOA yield with NOx at different VOC levels. The atmospheric implications of NOx in the coordinated control of PM2.5 and O3 are also discussed.
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Affiliation(s)
- Tianzeng Chen
- State Key Joint Laboratory of Environment Simulation and Pollution Control, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
| | - Peng Zhang
- State Key Joint Laboratory of Environment Simulation and Pollution Control, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Qingxin Ma
- State Key Joint Laboratory of Environment Simulation and Pollution Control, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
- Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Biwu Chu
- State Key Joint Laboratory of Environment Simulation and Pollution Control, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
- Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Jun Liu
- State Key Joint Laboratory of Environment Simulation and Pollution Control, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yanli Ge
- State Key Joint Laboratory of Environment Simulation and Pollution Control, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Hong He
- State Key Joint Laboratory of Environment Simulation and Pollution Control, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
- Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China
- University of Chinese Academy of Sciences, Beijing 100049, China
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Yuan R, Ma Q, Zhang Q, Yuan X, Wang Q, Luo C. Coordinated effects of energy transition on air pollution mitigation and CO 2 emission control in China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 841:156482. [PMID: 35671858 DOI: 10.1016/j.scitotenv.2022.156482] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/27/2022] [Revised: 05/22/2022] [Accepted: 05/31/2022] [Indexed: 06/15/2023]
Abstract
China has made progress in energy transition to improve air quality, but still confronts challenges including further ambient PM2.5 reduction, O3 pollution mitigation, and CO2 emission control. To explore the coordinated effects of energy transition on air quality and carbon emission in the near term in China, we designed 4 scenarios in 2025 based on different projections of energy transition progress with varying end-of-pipe control level, in each of which we calculated emissions of major air pollutants and CO2, and simulated ambient PM2.5 and O3 concentrations. Results show that energy transition has disparate effects on emission reduction of different air pollutants and sectors, which largely depends on their current end-of-pipe control levels. The different effects on emission reduction may result in opposite variation tendencies of ambient PM2.5 and O3 concentration in a future scenario with aggressive energy transition policies and end-of-pipe control level in 2018. With the end-of-pipe control level strengthened in 2025, PM2.5 and O3 concentration could both reduce on the national scale, but the reduction of ambient O3 lags behind PM2.5, indicating the difficulty of O3 pollution control. As to CO2, national emission would go up in 2025 either implementing current or aggressive energy transition policies due to growing needs of electricity and on-road transportation, but emissions in most provinces could decline to below the 2018 level with aggressive energy transition policies because of substitution of clean energy in industrial, residential and off-road transportation sectors. The study results suggest strictly implementing restrictive end-of-pipe control measures along with energy transition to simultaneously reduce ambient PM2.5 and O3 concentration, and accelerating substitution of renewable energy in power sectors where electricity generation grows rapidly to synergistically control air pollution and CO2 emissions. Furthermore, the projection of CO2 emissions could provide references for short-term emission control targets from the perspective of air quality improvement.
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Affiliation(s)
- Renxiao Yuan
- National Engineering Laboratory for Reducing Emissions from Coal Combustion, Engineering Research Center of Environmental Thermal Technology of Ministry of Education, Shandong Key Laboratory of Energy Carbon Reduction and Resource Utilization, School of Energy and Power Engineering, Shandong University, Jinan 250061, China
| | - Qiao Ma
- National Engineering Laboratory for Reducing Emissions from Coal Combustion, Engineering Research Center of Environmental Thermal Technology of Ministry of Education, Shandong Key Laboratory of Energy Carbon Reduction and Resource Utilization, School of Energy and Power Engineering, Shandong University, Jinan 250061, China.
| | - Qianqian Zhang
- National Satellite Meteorological Center, Beijing 100089, China
| | - Xueliang Yuan
- National Engineering Laboratory for Reducing Emissions from Coal Combustion, Engineering Research Center of Environmental Thermal Technology of Ministry of Education, Shandong Key Laboratory of Energy Carbon Reduction and Resource Utilization, School of Energy and Power Engineering, Shandong University, Jinan 250061, China
| | - Qingsong Wang
- National Engineering Laboratory for Reducing Emissions from Coal Combustion, Engineering Research Center of Environmental Thermal Technology of Ministry of Education, Shandong Key Laboratory of Energy Carbon Reduction and Resource Utilization, School of Energy and Power Engineering, Shandong University, Jinan 250061, China
| | - Congwei Luo
- School of Municipal and Environmental Engineering, Shandong Jianzhu University, Jinan 250101, China
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Wang P, Zhu S, Vrekoussis M, Brasseur GP, Wang S, Zhang H. Is atmospheric oxidation capacity better in indicating tropospheric O 3 formation? FRONTIERS OF ENVIRONMENTAL SCIENCE & ENGINEERING 2022; 16:65. [PMID: 35693985 PMCID: PMC9170499 DOI: 10.1007/s11783-022-1544-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/22/2022] [Revised: 04/08/2022] [Accepted: 04/10/2022] [Indexed: 06/15/2023]
Abstract
Tropospheric ozone (O3) concentration is increasing in China along with dramatic changes in precursor emissions and meteorological conditions, adversely affecting human health and ecosystems. O3 is formed from the complex nonlinear photochemical reactions from nitrogen oxides (NO x = NO + NO2) and volatile organic compounds (VOCs). Although the mechanism of O3 formation is rather clear, describing and analyzing its changes and formation potential at fine spatial and temporal resolution is still a challenge today. In this study, we briefly summarized and evaluated different approaches that indicate O3 formation regimes. We identify that atmospheric oxidation capacity (AOC) is a better indicator of photochemical reactions leading to the formation of O3 and other secondary pollutants. Results show that AOC has a prominent positive relationship to O3 in the major city clusters in China, with a goodness of fit (R 2) up to 0.6. This outcome provides a novel perspective in characterizing O3 formation and has significant implications for formulating control strategies of secondary pollutants.
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Affiliation(s)
- Peng Wang
- Department of Atmospheric and Oceanic Sciences, Fudan University, Shanghai, 200438 China
- IRDR ICoE on Risk Interconnectivity and Governance on Weather/Climate Extremes Impact and Public Health, Fudan University, Shanghai, 200438 China
| | - Shengqiang Zhu
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention, Department of Environmental Science & Engineering, Fudan University, Shanghai, 200438 China
| | - Mihalis Vrekoussis
- Institute of Environmental Physics, University of Bremen, Bremen, D-28359 Germany
- Climate and Atmosphere Research Center (CARE-C), the Cyprus Institute, Nicosia, 27456 Cyprus
| | - Guy P. Brasseur
- Max Planck Institute for Meteorology, Hamburg, 20146 Germany
- National Center for Atmospheric Research, Boulder, CO 80307 USA
| | - Shuxiao Wang
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084 China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing, 100084 China
| | - Hongliang Zhang
- IRDR ICoE on Risk Interconnectivity and Governance on Weather/Climate Extremes Impact and Public Health, Fudan University, Shanghai, 200438 China
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention, Department of Environmental Science & Engineering, Fudan University, Shanghai, 200438 China
- Institute of Eco-Chongming (IEC), Shanghai, 202162 China
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