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Liu C, Lu B, Wang Q, Zhang Z, Meng X, Huo J, Herrmann H, Li X. High-level HONO exacerbates double high pollution of O 3 and PM 2.5 in China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 945:174066. [PMID: 38897469 DOI: 10.1016/j.scitotenv.2024.174066] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/21/2024] [Revised: 05/27/2024] [Accepted: 06/15/2024] [Indexed: 06/21/2024]
Abstract
Double high pollution (DHP) of ozone (O3) and fine particulate matter (PM2.5) has frequently been observed in China in recent years. Numerous studies have speculated that DHP might be related to nitrous acid (HONO), but the chemical mechanism involved remains unclear. Field observation results of DHP in Shanghai indicate that the high concentration of HONO produced by nitrogen dioxide (NO2) heterogeneous reactions under conditions of high temperature and high humidity promotes an increase in PM2.5 and O3 concentrations. The box model combined with field observations to reconstruct pollution events indicates that HONO photolysis generates abundant hydroxyl (OH) radicals that rapidly oxidize volatile organic compounds (VOCs), which in turn accelerates the ROx (OH, hydroperoxyl (HO2), and organic peroxy (RO2) radicals) cycle and causes the accumulation of O3. This elevated O3 along with high concentrations of HONO, produces particulate nitrate (pNO3) by encouraging the NO2 + OH reaction. This process strengthens the chemical coupling between O3 and PM2.5, which can exacerbate the DHP of O3 and PM2.5. Sensitivity analysis of pNO3/O3-NOx-VOCs suggests that under nitrogen oxides (NOx = NO + NO2) reduction conditions, simultaneous control of pNO3 and O3 can be expected to be successfully achieved through emission reduction of alkanes and oxygenated VOCs (OVOCs). Therefore, the present research will facilitate the design of appropriate PM2.5 and O3 control strategies for high HONO concentration conditions, and thus alleviate the current stresses of air pollution.
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Affiliation(s)
- Chao Liu
- Department of Environmental Science & Engineering, Fudan University, Shanghai 200438, China
| | - Bingqing Lu
- Department of Environmental Science & Engineering, Fudan University, Shanghai 200438, China
| | - Qian Wang
- Department of Environmental Science & Engineering, Fudan University, Shanghai 200438, China; Shanghai Environmental Monitoring Center, Shanghai 200235, China
| | - Zekun Zhang
- Department of Environmental Science & Engineering, Fudan University, Shanghai 200438, China
| | - Xue Meng
- Department of Environmental Science & Engineering, Fudan University, Shanghai 200438, China
| | - Juntao Huo
- Shanghai Environmental Monitoring Center, Shanghai 200235, China
| | - Hartmut Herrmann
- Leibniz-Institut für Troposphärenforschung (IfT), Permoserstr. 15, 04318 Leipzig, Germany
| | - Xiang Li
- Department of Environmental Science & Engineering, Fudan University, Shanghai 200438, China.
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Xu L, Bao Y, Man H, Zhang Z, Chen J, Shao X, Zhu B, Liu H. Influencing factors on ammonia emissions from gasoline vehicles: A systematic review and meta-analysis. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 923:171467. [PMID: 38447721 DOI: 10.1016/j.scitotenv.2024.171467] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/14/2023] [Revised: 02/18/2024] [Accepted: 03/02/2024] [Indexed: 03/08/2024]
Abstract
Ammonia, a significant precursor for secondary inorganic aerosols, plays a pivotal role in new particle formation. Inventories and source apportionment studies have identified vehicular exhaust as a primary source of atmospheric ammonia in urban regions. Existing research on the factors influencing ammonia emissions from gasoline vehicles exhibits substantial inconsistencies in both test results and analyses. The lack of a uniform pattern in ammonia emissions across different standard vehicles and the significant overlap in test results across diverse operational conditions highlight the complexities in this field of study. While individual results can be interpreted through a mechanistic lens, disparate studies often lack a common explanatory framework. To address this gap, our study leverages the robust and comprehensive approach of meta-analysis to reconcile these inconsistencies and provide a more precise understanding of the factors influencing ammonia emissions from gasoline vehicles. A large number (N = 537) of ammonia emission factors were extracted after screening >1628 publications. The combined ammonia emission factor was 23.57 ± 24.94 mg/km. Emission standards, engine type, ambient temperatures, mileage, vehicle speed, and engine displacement have a significant impact on ammonia emission factors, explaining the ammonia emission factor by up to 50.63 %, with speed being the most significant factor. All these factors are attributed to the interplay of catalyst properties, lambda, and residence time (space velocity). In the current fleet, ammonia emission control is relatively insufficient under low-speed and ultra-high speed, low temperature, and ultra-high mileage conditions. Since ammonia emission factors do not monotonically decrease with the upgrading of motor vehicle emission standards, it is called for the addition of ammonia emission factors indicators in motor vehicle emission standards, and stipulation of targeted testing procedures and testing instruments.
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Affiliation(s)
- Lizhong Xu
- College of Environmental and Resource Sciences, Fujian Key Laboratory of Pollution Control & Resource Reuse, Fujian Normal University, Fuzhou 350007, China; Digital Fujian Internet-of-things Laboratory of Environmental Monitoring, Fuzhou 350007, China
| | - Yumeng Bao
- College of Environmental and Resource Sciences, Fujian Key Laboratory of Pollution Control & Resource Reuse, Fujian Normal University, Fuzhou 350007, China
| | - Hanyang Man
- College of Environmental and Resource Sciences, Fujian Key Laboratory of Pollution Control & Resource Reuse, Fujian Normal University, Fuzhou 350007, China; Digital Fujian Internet-of-things Laboratory of Environmental Monitoring, Fuzhou 350007, China.
| | - 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
| | - Jiawei Chen
- 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
| | - Bo Zhu
- College of Environmental and Resource Sciences, Fujian Key Laboratory of Pollution Control & Resource Reuse, Fujian Normal University, Fuzhou 350007, China; Digital Fujian Internet-of-things Laboratory of Environmental Monitoring, Fuzhou 350007, 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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Xu B, Jin J, Fang L, Pang M, Xia J, Li B, Liao H. A decadal atmospheric ammonia reanalysis product in China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 912:169053. [PMID: 38097067 DOI: 10.1016/j.scitotenv.2023.169053] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/16/2023] [Revised: 11/30/2023] [Accepted: 11/30/2023] [Indexed: 12/17/2023]
Abstract
Atmospheric ammonia has great environmental implications due to its important role in ecosystem and nitrogen cycle, as well as contribution to formation of secondary particles. China is recognized as a hotspot of NH3 pollution owing to agricultural and livestock intensification. In the quest to achieve a comprehensive understanding of atmospheric ammonia load and to quantify its environmental impacts in China, relying solely either on existing measurements or on model simulations falls short. Their limitations, either in spatial coverage and integrity or in data quality, fails to meet the needs. Available reanalysis products exhibit a marked deficiency in ammonia data. We therefore aim to propose an integrated ammonia reanalysis product in China, adeptly melding satellite observations from the Infrared Atmospheric Sounding Interferometer (IASI) NH3 retrievals with chemical transport model simulation, capitalizing on the robust Ensemble Kalman Filter (EnKF) data assimilation methodology. The product is validated in high quality via the comparison against independent measurements from ground monitoring stations. Spanning a decade from 2013 to 2022, our reanalysis uncovers not just the spatial intricacies of NH3 concentrations but also their temporal dynamics. Our findings pinpointed the spatial disparities in atmospheric ammonia intensities, highlighting regional hotspots in the NCP, SCB, and Northeast China, and identified annual and seasonal patterns. Our research provides crucial insights for shaping future NH3 pollution prevention and control strategies in China.
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Affiliation(s)
- Bufan Xu
- Joint International Research Laboratory of Climate and Environment Change, 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 and Technology, Nanjing, Jiangsu, China
| | - Jianbing Jin
- Joint International Research Laboratory of Climate and Environment Change, 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 and Technology, Nanjing, Jiangsu, China.
| | - Li Fang
- Joint International Research Laboratory of Climate and Environment Change, 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 and Technology, Nanjing, Jiangsu, China
| | - Mijie Pang
- Joint International Research Laboratory of Climate and Environment Change, 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 and Technology, Nanjing, Jiangsu, China
| | - Ji Xia
- Joint International Research Laboratory of Climate and Environment Change, 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 and Technology, Nanjing, Jiangsu, China
| | - Baojie Li
- Joint International Research Laboratory of Climate and Environment Change, 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 and Technology, Nanjing, Jiangsu, China
| | - Hong Liao
- Joint International Research Laboratory of Climate and Environment Change, 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 and Technology, Nanjing, Jiangsu, China.
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