1
|
Qu K, Yan Y, Wang X, Jin X, Vrekoussis M, Kanakidou M, Brasseur GP, Lin T, Xiao T, Cai X, Zeng L, Zhang Y. The effect of cross-regional transport on ozone and particulate matter pollution in China: A review of methodology and current knowledge. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 947:174196. [PMID: 38942314 DOI: 10.1016/j.scitotenv.2024.174196] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/31/2024] [Revised: 05/29/2024] [Accepted: 06/20/2024] [Indexed: 06/30/2024]
Abstract
China is currently one of the countries impacted by severe atmospheric ozone (O3) and particulate matter (PM) pollution. Due to their moderately long lifetimes, O3 and PM can be transported over long distances, cross the boundaries of source regions and contribute to air pollution in other regions. The reported contributions of cross-regional transport (CRT) to O3 and fine PM (PM2.5) concentrations often exceed those of local emissions in the major regions of China, highlighting the important role of CRT in regional air pollution. Therefore, further improvement of air quality in China requires more joint efforts among regions to ensure a proper reduction in emissions while accounting for the influence of CRT. This review summarizes the methodologies employed to assess the influence of CRT on O3 and PM pollution as well as current knowledge of CRT influence in China. Quantifying CRT contributions in proportion to O3 and PM levels and studying detailed CRT processes of O3, PM and precursors can be both based on targeted observations and/or model simulations. Reported publications indicate that CRT contributes by 40-80 % to O3 and by 10-70 % to PM2.5 in various regions of China. These contributions exhibit notable spatiotemporal variations, with differences in meteorological conditions and/or emissions often serving as main drivers of such variations. Based on trajectory-based methods, transport pathways contributing to O3 and PM pollution in major regions of China have been revealed. Recent studies also highlighted the important role of horizontal transport in the middle/high atmospheric boundary layer or low free troposphere, of vertical exchange and mixing as well as of interactions between CRT, local meteorology and chemistry in the detailed CRT processes. Drawing on the current knowledge on the influence of CRT, this paper provides recommendations for future studies that aim at supporting ongoing air pollution mitigation strategies in China.
Collapse
Affiliation(s)
- Kun Qu
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China; International Joint Laboratory for Regional Pollution Control, Ministry of Education, Beijing 100816, China; Laboratory for Modeling and Observation of the Earth System (LAMOS), Institute of Environmental Physics (IUP), University of Bremen, Bremen, Germany
| | - Yu Yan
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China; International Joint Laboratory for Regional Pollution Control, Ministry of Education, Beijing 100816, China; Sichuan Academy of Environmental Policy and Planning, Chengdu 610041, China
| | - Xuesong Wang
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China; International Joint Laboratory for Regional Pollution Control, Ministry of Education, Beijing 100816, China.
| | - Xipeng Jin
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China; International Joint Laboratory for Regional Pollution Control, Ministry of Education, Beijing 100816, China; Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, School of Environmental Science and Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, China
| | - Mihalis Vrekoussis
- Laboratory for Modeling and Observation of the Earth System (LAMOS), Institute of Environmental Physics (IUP), University of Bremen, Bremen, Germany; Center of Marine Environmental Sciences (MARUM), University of Bremen, Bremen, Germany; Climate and Atmosphere Research Center (CARE-C), The Cyprus Institute, Nicosia, Cyprus
| | - Maria Kanakidou
- Laboratory for Modeling and Observation of the Earth System (LAMOS), Institute of Environmental Physics (IUP), University of Bremen, Bremen, Germany; Environmental Chemical Processes Laboratory, Department of Chemistry, University of Crete, Heraklion, Greece; Center of Studies of Air quality and Climate Change, Institute for Chemical Engineering Sciences, Foundation for Research and Technology Hellas, Patras, Greece
| | - Guy P Brasseur
- Max Planck Institute for Meteorology, Hamburg, Germany; National Center for Atmospheric Research, Boulder, CO, USA
| | - Tingkun Lin
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China; International Joint Laboratory for Regional Pollution Control, Ministry of Education, Beijing 100816, China
| | - Teng Xiao
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China; International Joint Laboratory for Regional Pollution Control, Ministry of Education, Beijing 100816, China
| | - Xuhui Cai
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China; International Joint Laboratory for Regional Pollution Control, Ministry of Education, Beijing 100816, China
| | - Limin Zeng
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China; International Joint Laboratory for Regional Pollution Control, Ministry of Education, Beijing 100816, China
| | - Yuanhang Zhang
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China; International Joint Laboratory for Regional Pollution Control, Ministry of Education, Beijing 100816, China; Beijing Innovation Center for Engineering Science and Advanced Technology, Peking University, Beijing 100871, China; CAS Center for Excellence in Regional Atmospheric Environment, Chinese Academy of Sciences, Xiamen 361021, China.
| |
Collapse
|
2
|
Chang CY, Wang JL, Chen YC, Chen WN, Wang SH, Chuang MT, Lin NH, Chou CCK, Huang WS, Ke LJ, Pan XX, Ho YJ, Chen YY, Chang CC. Spatiotemporal characterization of PM 2.5, O 3, and trace gases associated with East Asian continental outflows via drone sounding. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 930:172732. [PMID: 38663609 DOI: 10.1016/j.scitotenv.2024.172732] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/26/2024] [Revised: 04/16/2024] [Accepted: 04/22/2024] [Indexed: 05/02/2024]
Abstract
East Asian continental outflows with PM2.5, O3, and other species may determine the baseline conditions and affect the air quality in downwind areas via long-range transport (LRT). To gain insight into the impact and spatiotemporal characteristics of airborne pollutants in East Asian continental outflows, a versatile multicopter drone sounding platform was used to simultaneously observe PM2.5, O3, CO2, and meteorological variables (temperature, specific humidity, pressure, and wind vector) above the northern tip of Taiwan, Cape Fuiguei, which often encounters continental outflows during winter monsoon periods. By coordinating hourly high-spatial-resolution profiles provided by drone soundings, WRF/CMAQ model air quality predictions, HYSPLIT-simulated backward trajectories, and MERRA-2 reanalysis data, we analyzed two prominent phenomena of airborne pollutants in continental outflows to better understand their physical/chemical characteristics. First, we found that pollutants were well mixed within a sounding height of 500 m when continental outflows passed through and completely enveloped Cape Fuiguei. Eddies induced by significant fluctuations in wind speeds coupled with minimal temperature inversion and LRT facilitated vertical mixing, possibly resulting in high homogeneity of pollutants within the outflow layer. Second, the drone soundings indicated exceptionally high O3 concentrations (70-100 ppbv) but relatively low concentrations of PM2.5 (10-20 μg/m3), CO2 (420-425 ppmv), and VOCs in some air masses. The low levels of PM2.5, CO2, and VOCs ruled out photochemistry as the cause of the formation of high-level O3. Further coordination of spatiotemporal data with air mass trajectories and O3 cross sections provided by MERRA-2 suggested that the high O3 concentrations could be attributed to stratospheric intrusion and advection via continental outflows. High-level O3 concentrations persisted in the lower troposphere, even reaching the surface, suggesting that stratospheric intrusion O3 may be involved in the rising trend in O3 concentrations in parts of East Asia in recent years in addition to surface photochemical factors.
Collapse
Affiliation(s)
- Chih-Yuan Chang
- Research Center for Environmental Changes, Academia Sinica, Taipei 11529, Taiwan
| | - Jia-Lin Wang
- Department of Chemistry, National Central University, Chungli 320, Taiwan
| | - Yen-Chen Chen
- Research Center for Environmental Changes, Academia Sinica, Taipei 11529, Taiwan
| | - Wei-Nai Chen
- Research Center for Environmental Changes, Academia Sinica, Taipei 11529, Taiwan
| | - Sheng-Hsiang Wang
- Department of Atmospheric Sciences, National Central University, Taoyuan 32001, Taiwan
| | - Ming-Tung Chuang
- Research Center for Environmental Changes, Academia Sinica, Taipei 11529, Taiwan
| | - Neng-Huei Lin
- Department of Atmospheric Sciences, National Central University, Taoyuan 32001, Taiwan
| | - Charles C-K Chou
- Research Center for Environmental Changes, Academia Sinica, Taipei 11529, Taiwan
| | - Wei-Syun Huang
- Department of Atmospheric Sciences, National Central University, Taoyuan 32001, Taiwan
| | - Li-Jin Ke
- Department of Atmospheric Sciences, National Central University, Taoyuan 32001, Taiwan
| | - Xiang-Xu Pan
- Research Center for Environmental Changes, Academia Sinica, Taipei 11529, Taiwan
| | - Yu-Jui Ho
- Research Center for Environmental Changes, Academia Sinica, Taipei 11529, Taiwan
| | - Yi-Ying Chen
- Research Center for Environmental Changes, Academia Sinica, Taipei 11529, Taiwan
| | - Chih-Chung Chang
- Research Center for Environmental Changes, Academia Sinica, Taipei 11529, Taiwan.
| |
Collapse
|
3
|
Sun J, Yu X, Ling Z, Fang G, Ming L, Zhao J, Zou S, Guan H, Wang H, Wang X, Wang Z, Gao Y, Tham YJ, Guo H, Zhang Y. Roles of photochemical consumption of VOCs on regional background O 3 concentration and atmospheric reactivity over the pearl river estuary, Southern China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 928:172321. [PMID: 38604373 DOI: 10.1016/j.scitotenv.2024.172321] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/22/2024] [Revised: 04/02/2024] [Accepted: 04/06/2024] [Indexed: 04/13/2024]
Abstract
Understanding of the photochemical ozone (O3) pollution over the Pearl River Estuary (PRE) of southern China remains limited. We performed an in-depth analysis of volatile organic compounds (VOCs) data collected on an island (i.e., the Da Wan Shan Island, DWS) located at the downwind of Pearl River Delta (PRD) from 26 November to 15 December 2021. Abundances of O3 and its precursors were measured when the air masses originated from the inland PRD. We observed that the VOCs levels at the DWS site were lower, while the mixing ratio of O3 was higher, compared to those reported at inland PRD, indicating the occurrence of photochemical consumption of VOCs during the air masses transport, which was further confirmed by the composition and diurnal variations of VOCs, as well as ratios of specific VOCs. The simulation results from a photochemical box model showed that the O3 level in the outflow air masses of inland PRD (O3(out-flow)) was the dominant factor leading to the intensification of O3 pollution and the enhancement of atmospheric radical concentrations (ARC) over PRE, which was mainly contributed by the O3 production via photochemical consumption of VOCs during air masses transport. Overall, our findings provided direct quantitative evidence for the roles of outflow O3 and its precursors from inland PRD on O3 abundance and ARC over the PRE area, highlighting that alleviation of O3 pollution over PRE should focus on the impact of photochemical loss of VOCs in the outflow air masses from inland PRD.
Collapse
Affiliation(s)
- Jiayin Sun
- School of Atmospheric Sciences, Sun Yat-sen University, Key Laboratory of Tropical Atmosphere-Ocean System, Ministry of Education, and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, China
| | - Xiaoyu Yu
- School of Atmospheric Sciences, Sun Yat-sen University, Key Laboratory of Tropical Atmosphere-Ocean System, Ministry of Education, and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, China
| | - Zhenhao Ling
- School of Atmospheric Sciences, Sun Yat-sen University, Key Laboratory of Tropical Atmosphere-Ocean System, Ministry of Education, and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, China.
| | - Guizhen Fang
- School of Marine Sciences, Sun Yat-sen University, and Pearl River Estuary Marine Ecosystem Research Station, Ministry of Education, Zhuhai, China
| | - Lili Ming
- Technical Center of Gongbei Customs District of China, Zhuhai, China
| | - Jun Zhao
- School of Atmospheric Sciences, Sun Yat-sen University, Key Laboratory of Tropical Atmosphere-Ocean System, Ministry of Education, and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, China
| | - Shichun Zou
- School of Marine Sciences, Sun Yat-sen University, and Pearl River Estuary Marine Ecosystem Research Station, Ministry of Education, Zhuhai, China
| | - Huatian Guan
- School of Atmospheric Sciences, Sun Yat-sen University, Key Laboratory of Tropical Atmosphere-Ocean System, Ministry of Education, and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, China
| | - Haichao Wang
- School of Atmospheric Sciences, Sun Yat-sen University, Key Laboratory of Tropical Atmosphere-Ocean System, Ministry of Education, and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, China
| | - Xuemei Wang
- College of Environment and Climate, Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Jinan University, Guangzhou, China
| | - Zhe Wang
- Division of Environment and Sustainability, The Hong Kong University of Science and Technology, Hong Kong, China
| | - Yuan Gao
- Instrumentation and Service Center for Science and Technology, Beijing Normal University, Zhuhai, China
| | - Yee Jun Tham
- School of Marine Sciences, Sun Yat-sen University, and Pearl River Estuary Marine Ecosystem Research Station, Ministry of Education, Zhuhai, China.
| | - Hai Guo
- Department of Civil and Environmental Engineering, Hong Kong Polytechnic University, Hong Kong, China
| | - Yanli Zhang
- Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou, China
| |
Collapse
|
4
|
He Y, Fan S, Wang Y, Liu Y, Lu X, Wang H, He C, Mai C, Du Y. Influence of boundary layer jets on the vertical distribution of ozone in Guangdong, China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 927:171874. [PMID: 38537834 DOI: 10.1016/j.scitotenv.2024.171874] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/25/2024] [Revised: 03/19/2024] [Accepted: 03/20/2024] [Indexed: 04/11/2024]
Abstract
The planetary boundary layer (PBL) characteristics during ozone (O3) episodes in China have been extensively studied; however, knowledge of the impact of boundary layer jets (BLJs) on O3 vertical distribution is limited. This study conducted a field campaign from 1 to 8 December 2020 to examine the vertical structure of the O3 concentration and wind velocity within the boundary layer at two sites (Foshan: FS, Maoming: MM) in Guangdong. Utilising lidar observations and the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem), distinct spatial distribution patterns of O3 over FS and MM influenced by BLJs were identified. The BLJs at both locations exhibited pronounced diurnal variations with a nocturnal maximum exceeding 11 m/s at a height of approximately 500 m. The nocturnal enhancement of BLJs resulted from inertial oscillations coupled with diurnal thermal forcing over sloping terrain. A stronger BLJ at FS induced an evident uplift of O3 and the prevailing northeasterly wind facilitated the transport of O3 in the nocturnal residual layer from FS to MM. After sunrise, surface heating and the development of the PBL caused the air mass with elevated O3 levels in the residual layer to descend to ground level. At MM, calm surface winds, a weaker BLJ at 500 m height, and strong downdrafts collectively contributed to a significant increase in surface O3 concentration in subsequent days. These findings contribute to our understanding of the interactions between BLJs and variations in surface air pollutant concentrations, thereby providing important insights for future regional emissions control measures.
Collapse
Affiliation(s)
- Yuanping He
- Nanhai Branch of Foshan Ecological Environment Bureau, Foshan 528200, China; School of Atmospheric Sciences, Sun Yat-sen University, Zhuhai 519082, China; Guangdong Provincial Observation and Research Station for Climate Environment and Air Quality Change in the Pearl River Estuary, Key Laboratory of Tropical Atmosphere-Ocean System, Ministry of Education, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519082, China
| | - Shaojia Fan
- School of Atmospheric Sciences, Sun Yat-sen University, Zhuhai 519082, China; Guangdong Provincial Observation and Research Station for Climate Environment and Air Quality Change in the Pearl River Estuary, Key Laboratory of Tropical Atmosphere-Ocean System, Ministry of Education, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519082, China.
| | - Yiming Wang
- School of Atmospheric Sciences, Sun Yat-sen University, Zhuhai 519082, China; Guangdong Provincial Observation and Research Station for Climate Environment and Air Quality Change in the Pearl River Estuary, Key Laboratory of Tropical Atmosphere-Ocean System, Ministry of Education, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519082, China
| | - Yiming Liu
- School of Atmospheric Sciences, Sun Yat-sen University, Zhuhai 519082, China; Guangdong Provincial Observation and Research Station for Climate Environment and Air Quality Change in the Pearl River Estuary, Key Laboratory of Tropical Atmosphere-Ocean System, Ministry of Education, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519082, China
| | - Xiao Lu
- School of Atmospheric Sciences, Sun Yat-sen University, Zhuhai 519082, China; Guangdong Provincial Observation and Research Station for Climate Environment and Air Quality Change in the Pearl River Estuary, Key Laboratory of Tropical Atmosphere-Ocean System, Ministry of Education, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519082, China
| | - Haolin Wang
- School of Atmospheric Sciences, Sun Yat-sen University, Zhuhai 519082, China; Guangdong Provincial Observation and Research Station for Climate Environment and Air Quality Change in the Pearl River Estuary, Key Laboratory of Tropical Atmosphere-Ocean System, Ministry of Education, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519082, China
| | - Cheng He
- School of Atmospheric Sciences, Sun Yat-sen University, Zhuhai 519082, China; Guangdong Provincial Observation and Research Station for Climate Environment and Air Quality Change in the Pearl River Estuary, Key Laboratory of Tropical Atmosphere-Ocean System, Ministry of Education, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519082, China
| | - Chuying Mai
- School of Atmospheric Sciences, Sun Yat-sen University, Zhuhai 519082, China; Guangdong Provincial Observation and Research Station for Climate Environment and Air Quality Change in the Pearl River Estuary, Key Laboratory of Tropical Atmosphere-Ocean System, Ministry of Education, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519082, China
| | - Yu Du
- School of Atmospheric Sciences, Sun Yat-sen University, Zhuhai 519082, China; Guangdong Provincial Observation and Research Station for Climate Environment and Air Quality Change in the Pearl River Estuary, Key Laboratory of Tropical Atmosphere-Ocean System, Ministry of Education, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519082, China.
| |
Collapse
|
5
|
Li P, Chen C, Liu D, Lian J, Li W, Fan C, Yan L, Gao Y, Wang M, Liu H, Pan X, Mao J. Characteristics and source apportionment of ambient volatile organic compounds and ozone generation sensitivity in urban Jiaozuo, China. J Environ Sci (China) 2024; 138:607-625. [PMID: 38135424 DOI: 10.1016/j.jes.2023.04.016] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2022] [Revised: 04/15/2023] [Accepted: 04/17/2023] [Indexed: 12/24/2023]
Abstract
In recent years, many cities have taken measures to reduce volatile organic compounds (VOCs), an important precursor of ozone (O3), to alleviate O3 pollution in China. 116 VOC species were measured by online and offline methods in the urban area of Jiaozuo from May to October in 2021 to analyze the compositional characteristics. VOC sources were analyzed by a positive matrix factorization (PMF) model, and the sensitivity of ozone generation was determined by ozone isopleth plotting research (OZIPR) simulation. The results showed that the average volume concentration of total VOCs was 30.54 ppbv and showed a bimodal feature due to the rush-hour traffic in the morning and at nightfall. The most dominant VOC groups were oxygenated VOCs (OVOCs, 29.3%) and alkanes (26.7%), and the most abundant VOC species were acetone and acetylene. However, based on the maximum incremental reactivity (MIR) method, the major VOC groups in terms of ozone formation potential (OFP) contribution were OVOCs (68.09 µg/m3, 31.5%), aromatics (62.90 µg/m3, 29.1%) and alkene/alkynes (54.90 µg/m3, 25.4%). This indicates that the control of OVOCs, aromatics and alkene/alkynes should take priority. Five sources of VOCs were quantified by PMF, including fixed sources of fossil fuel combustion (27.8%), industrial processes (25.9%), vehicle exhaust (19.7%), natural and secondary formation (13.9%) and solvent usage (12.7%). The empirical kinetic modeling approach (EKMA) curve obtained by OZIPR on O3 exceedance days indicated that the O3 sensitivity varied in different months. The results provide theoretical support for O3 pollution prevention and control in Jiaozuo.
Collapse
Affiliation(s)
- Pengzhao Li
- State Centre for International Cooperation on Designer Low-Carbon and Environmental Materials, School of Materials Science and Engineering, Zhengzhou University, Zhengzhou 450001, China
| | - Chun Chen
- State Centre for International Cooperation on Designer Low-Carbon and Environmental Materials, School of Materials Science and Engineering, Zhengzhou University, Zhengzhou 450001, China; Henan Key Laboratory of Environmental Monitoring Technology, Henan Ecological Environment Monitoring and Safety Center, Zhengzhou 450046, China
| | - Dan Liu
- Henan Key Laboratory of Environmental Monitoring Technology, Henan Ecological Environment Monitoring and Safety Center, Zhengzhou 450046, China
| | - Jie Lian
- Jiaozuo Ecological Environment Monitoring Center of Henan Province, Jiaozuo 454003, China
| | - Wei Li
- Jiaozuo Ecological Environment Monitoring Center of Henan Province, Jiaozuo 454003, China
| | - Chuanyi Fan
- Jiaozuo Ecological Environment Monitoring Center of Henan Province, Jiaozuo 454003, China
| | - Liangyu Yan
- State Centre for International Cooperation on Designer Low-Carbon and Environmental Materials, School of Materials Science and Engineering, Zhengzhou University, Zhengzhou 450001, China
| | - Yue Gao
- State Centre for International Cooperation on Designer Low-Carbon and Environmental Materials, School of Materials Science and Engineering, Zhengzhou University, Zhengzhou 450001, China
| | - Miao Wang
- State Centre for International Cooperation on Designer Low-Carbon and Environmental Materials, School of Materials Science and Engineering, Zhengzhou University, Zhengzhou 450001, China
| | - Hang Liu
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
| | - Xiaole Pan
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China.
| | - Jing Mao
- State Centre for International Cooperation on Designer Low-Carbon and Environmental Materials, School of Materials Science and Engineering, Zhengzhou University, Zhengzhou 450001, China.
| |
Collapse
|
6
|
Hu Q, Ji X, Hong Q, Li J, Li Q, Ou J, Liu H, Xing C, Tan W, Chen J, Chang B, Liu C. Vertical Evolution of Ozone Formation Sensitivity Based on Synchronous Vertical Observations of Ozone and Proxies for Its Precursors: Implications for Ozone Pollution Prevention Strategies. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2024; 58:4291-4301. [PMID: 38385161 PMCID: PMC10919071 DOI: 10.1021/acs.est.4c00637] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/18/2024] [Revised: 02/03/2024] [Accepted: 02/05/2024] [Indexed: 02/23/2024]
Abstract
Photochemical ozone (O3) formation in the atmospheric boundary layer occurs at both the surface and elevated altitudes. Therefore, the O3 formation sensitivity is needed to be evaluated at different altitudes before formulating an effective O3 pollution prevention and control strategy. Herein, we explore the vertical evolution of O3 formation sensitivity via synchronous observations of the vertical profiles of O3 and proxies for its precursors, formaldehyde (HCHO) and nitrogen dioxide (NO2), using multi-axis differential optical absorption spectroscopy (MAX-DOAS) in urban areas of the Beijing-Tianjin-Hebei (BTH), Yangtze River Delta (YRD), and Pearl River Delta (PRD) regions in China. The sensitivity thresholds indicated by the HCHO/NO2 ratio (FNR) varied with altitude. The VOC-limited regime dominated at the ground level, whereas the contribution of the NOx-limited regime increased with altitude, particularly on heavily polluted days. The NOx-limited and transition regimes played more important roles throughout the entire boundary layer than at the surface. The feasibility of extreme NOx reduction to mitigate the extent of the O3 pollution was evaluated using the FNR-O3 curve. Based on the surface sensitivity, the critical NOx reduction percentage for the transition from a VOC-limited to a NOx-limited regime is 45-72%, which will decrease to 27-61% when vertical evolution is considered. With the combined effects of clean air action and carbon neutrality, O3 pollution in the YRD and PRD regions will transition to the NOx-limited regime before 2030 and be mitigated with further NOx reduction.
Collapse
Affiliation(s)
- Qihou Hu
- Key
Laboratory of Environmental Optics and Technology, Anhui Institute
of Optics and Fine Mechanics, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China
| | - Xiangguang Ji
- Information
Materials and Intelligent Sensing Laboratory of Anhui Province, Anhui University, Hefei 230601, China
| | - Qianqian Hong
- School
of Environment and Civil Engineering, Jiangnan
University, Wuxi 214122, China
| | - Jinhui Li
- Institute
of Physical Science and Information Technology, Anhui University, Hefei 230601, China
| | - Qihua Li
- Institute
of Physical Science and Information Technology, Anhui University, Hefei 230601, China
| | - Jinping Ou
- The
Department of Health Promotion and Behavioral Sciences, School of
Public Health, Anhui Medical University, Hefei 230032, China
| | - Haoran Liu
- Institute
of Physical Science and Information Technology, Anhui University, Hefei 230601, China
| | - Chengzhi Xing
- Key
Laboratory of Environmental Optics and Technology, Anhui Institute
of Optics and Fine Mechanics, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China
| | - Wei Tan
- Key
Laboratory of Environmental Optics and Technology, Anhui Institute
of Optics and Fine Mechanics, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China
| | - Jian Chen
- Department
of Environmental Science and Engineering, University of Science and Technology of China, Hefei 230026, China
| | - Bowen Chang
- Institute
of Physical Science and Information Technology, Anhui University, Hefei 230601, China
| | - Cheng Liu
- Key
Laboratory of Environmental Optics and Technology, Anhui Institute
of Optics and Fine Mechanics, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China
- Department
of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, Hefei 230026, China
- Center
for Excellence in Regional Atmospheric Environment, Institute of Urban
Environment, Chinese Academy of Sciences, Xiamen 361021, China
- Key
Laboratory of Precision Scientific Instrumentation of Anhui Higher
Education Institutes, University of Science
and Technology of China, Hefei 230026, China
| |
Collapse
|
7
|
You Y, Wang X, Wu Y, Chen W, Chen B, Chang M. Quantified the influence of different synoptic weather patterns on the transport and local production processes of O 3 events in Pearl River Delta, China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 912:169066. [PMID: 38070576 DOI: 10.1016/j.scitotenv.2023.169066] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/25/2023] [Revised: 11/10/2023] [Accepted: 12/01/2023] [Indexed: 01/18/2024]
Abstract
Regional ozone (O3) pollution in the Pearl River Delta (PRD) region has become a topic of discussion in recent years. The occurrence of regional O3 pollution are influenced by local emissions and cross-regional transportation. In this study, we identified the predominant synoptic patterns that were associated with regional O3 pollution from August to November in 2015-2021 using the Lamb-Jenkinson classification technique. All synoptic types were divided into four major categories of NE-type, C-type, S-type and A-type, which accounted for 42 %, 25 %, 18 % and 15 % of the total number of regional O3 pollution days, respectively. The weather conditions for each synoptic pattern were described by using MERRA-2 datasets. Then a rapidly method was established to quantify the contribution of cross-regional processes to high O3 concentration in different synoptic patterns over the PRD through the WRF-Flexpart model. The NE-type weather condition was characterized by a relatively large wind speed with a significant cross-regional transport contribution of 35.8 %. The A-type weather condition had moderate surface wind speed with the stable weather condition, resulting in a lower cross-region transport contribution of 27.7 %. Under controlled by C-type, the stagnant weather condition caused by low-pressure systems on its periphery, would suppress diffusion of O3. As a result, the regional O3 pollution in the PRD were mostly attributed to locally (87.9 %) with minimal cross-regional transport (12.1 %). The S-type weather condition was mainly associated with the West Pacific Subtropical High and the surface equalization pressure field, accompanied by low wind speed. Therefore, the considerable (minor) contribution of local production (cross-regional transport) of 83.3 % (16.7 %) to O3 pollution in the PRD is a consequence of the stagnation weather condition.
Collapse
Affiliation(s)
- Yingchang You
- Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Institute for Environmental and Climate Research, Jinan University, Guangzhou, China; Institute for Environmental and Climate Research, Jinan University, Guangzhou, China
| | - Xuemei Wang
- Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Institute for Environmental and Climate Research, Jinan University, Guangzhou, China; Institute for Environmental and Climate Research, Jinan University, Guangzhou, China.
| | - Yongkang Wu
- Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Institute for Environmental and Climate Research, Jinan University, Guangzhou, China; Institute for Environmental and Climate Research, Jinan University, Guangzhou, China
| | - Weihua Chen
- Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Institute for Environmental and Climate Research, Jinan University, Guangzhou, China; Institute for Environmental and Climate Research, Jinan University, Guangzhou, China
| | - Bingyin Chen
- Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Institute for Environmental and Climate Research, Jinan University, Guangzhou, China; Institute for Environmental and Climate Research, Jinan University, Guangzhou, China
| | - Ming Chang
- Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Institute for Environmental and Climate Research, Jinan University, Guangzhou, China; Institute for Environmental and Climate Research, Jinan University, Guangzhou, China
| |
Collapse
|
8
|
Guan Y, Shen Y, Wu T, Su W, Li D, Ni S, Zhang T, Han J, Duan E. Urban canopy height ozone distribution in a Chinese inland city: Effects of anthropogenic NO emissions. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 905:167448. [PMID: 37777121 DOI: 10.1016/j.scitotenv.2023.167448] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/10/2023] [Revised: 09/17/2023] [Accepted: 09/27/2023] [Indexed: 10/02/2023]
Abstract
With the increase of urban building height, people pay more and more attention to the characteristics of pollutants in urban canopy height. This study combined the generalized additive model (GAM) and the observation-based model (OBM) to explore the vertical characteristics and drivers of ozone (O3) based on meteorology tower (200 m) data to quantify the effects of factors and photochemical reactions on O3 formation at different heights. The F values of GAM reflect the importance of each factor, indicating that NO (F is 33.99 in the peak season, 36.72 in the non-peak season) was the dominant driver of O3 and was more important in the lower layer (20-116 m). Temperature (F is 35.42) was the main contributor to O3 pollution in the peak season, especially for O3 in the upper layer (116-200 m). The net O3 production rate in the peak season was 1.47 times that in the non-peak season due to strong photochemical reactions and meteorological conditions. And the net O3 production rate decreased sharply with increasing height in the two seasons. Less net O3 production in the upper layer was accompanied by a higher O3 mixing ratio, which indicated that there was more background O3 in the upper layer. OBM model results showed that the reaction between hydroperoxyl radical (HO2) and NO was the primary contribution pathway, accounting for 54.00 % and 57.50 % in the peak and non-peak seasons, respectively. O3 formation was highly sensitive to VOCs, while NOx reduction could have positive or negative effects on O3 depending on the levels of hydroxyl radical (OH). The understanding of the formation mechanism of O3 and the influence of NO on O3 provides insights into the importance of anthropogenic activities at urban canopy heights in shaping the vertical structure of O3.
Collapse
Affiliation(s)
- Yanan Guan
- School of Environmental Science and Engineering, Hebei University of Science and Technology, Shijiazhuang 050018, China; National Joint Local Engineering Research Center for Volatile Organic Compounds and Odorous Pollution Control, Shijiazhuang 050018, China
| | - Ying Shen
- School of Environmental Science and Engineering, Hebei University of Science and Technology, Shijiazhuang 050018, China
| | - Tianyuan Wu
- School of Environmental Science and Engineering, Hebei University of Science and Technology, Shijiazhuang 050018, China
| | - Wenkang Su
- HeBei Provincial Academy of Ecological Environmental Science, Shijiazhuang 050018, China
| | - Dong Li
- Shijiazhuang City Environmental Prediction and Forecast Center, Shijiazhuang 050018, China
| | - Shuangying Ni
- HeBei Provincial Academy of Ecological Environmental Science, Shijiazhuang 050018, China
| | - Tao Zhang
- Shijiazhuang Environmental Monitoring Center, Shijiazhuang 050021, China
| | - Jing Han
- School of Environmental Science and Engineering, Hebei University of Science and Technology, Shijiazhuang 050018, China; National Joint Local Engineering Research Center for Volatile Organic Compounds and Odorous Pollution Control, Shijiazhuang 050018, China
| | - Erhong Duan
- School of Environmental Science and Engineering, Hebei University of Science and Technology, Shijiazhuang 050018, China; National Joint Local Engineering Research Center for Volatile Organic Compounds and Odorous Pollution Control, Shijiazhuang 050018, China.
| |
Collapse
|
9
|
Shu Z, Zhao T, Chen Y, Liu Y, Yang F, Jiang Y, He G, Yang Q, Zhang Y. Terrain effect on atmospheric process in seasonal ozone variation over the Sichuan Basin, Southwest China. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2023; 338:122622. [PMID: 37783418 DOI: 10.1016/j.envpol.2023.122622] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/02/2023] [Revised: 09/14/2023] [Accepted: 09/25/2023] [Indexed: 10/04/2023]
Abstract
Terrain effect is challenging for understanding atmospheric environment changes under complex topography. This study targets the Sichuan Basin (SCB), a deep basin isolated by plateaus and mountains in Southwest China, by employing WRF-Chem with integrated process rates (IPR) analysis to characterize the terrain-driven seasonal variations of tropospheric ozone (O3) with atmospheric physical and chemical processes. Results show that the basin terrain exerts reversed impacts on regional air quality changes by aggravating summertime and alleviating wintertime near-surface O3 with the relative contributions oscillating seasonally between -40% and 40% in SCB. Similarly, a seasonal shift of vertical O3 structures is dominated by summertime positive and wintertime negative changes in the lower troposphere induced by basin terrain. The key contributions of atmospheric process to near-surface O3 are identified with vertical and horizontal transport, which is dominated by basin terrain with intensifying seasonal and diurnal variations. With the existence of basin, the daytime O3 productions at the near-surface layer are elevated in months of warm seasons (April and July) but inhibited in the cold seasons (October and January), presenting a seasonal transition of primary factor from meteorology to aerosol-radiation forcing on photochemical reactions. Driven by plateau-basin thermodynamic forcing, horizontal O3 transport between the SCB and eastern TP is enhanced by mountain-plains solenoid (MPS), and even nocturnal O3-rich layers contribute to the impacts of vertical exchange on near-surface O3 levels. The terrain effects of deep basin under the interaction of Asian monsoons and westerlies could jointly change atmospheric physical and chemical processes to construct the seasonal and diurnal O3 evolution patterns over the SCB region.
Collapse
Affiliation(s)
- Zhuozhi Shu
- Sichuan Academy of Environmental Sciences, Chengdu 610041, China; Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, Nanjing University of Information Science &Technology, Nanjing, 210044, China
| | - Tianliang Zhao
- Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, Nanjing University of Information Science &Technology, Nanjing, 210044, China.
| | - Yongsheng Chen
- Centre for Research in Earth and Space Science, Lassonde School of Engineering, York University, Toronto, M3J 1P3, Canada
| | - Yubao Liu
- Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, Nanjing University of Information Science &Technology, Nanjing, 210044, China
| | - Fumo Yang
- School of Carbon Neutrality Future Technology, National Engineering Research Center on Flue Gas Desulfurization, Sichuan University, Chengdu, 610065, China
| | - Yongcheng Jiang
- Xiamen Key Laboratory of Straits Meteorology, Xiamen Meteorological Bureau, Xiamen, 361013, China
| | - Guoqing He
- School of Atmospheric Sciences, Nanjing University of Information Science &Technology, Nanjing, 210044, China
| | - Qingjian Yang
- Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, Nanjing University of Information Science &Technology, Nanjing, 210044, China
| | - Yuqing Zhang
- Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, Nanjing University of Information Science &Technology, Nanjing, 210044, China
| |
Collapse
|
10
|
Zhang X, Deng T, Wu D, Chen L, He G, Yang H, Zou Y, Pei C, Yue D, Tao L, Ouyang S, Wang Q, Zhang Z. The influence of lightning activity on NO x and O 3 in the Pearl River Delta region. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 902:166001. [PMID: 37536585 DOI: 10.1016/j.scitotenv.2023.166001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/17/2023] [Revised: 07/30/2023] [Accepted: 07/31/2023] [Indexed: 08/05/2023]
Abstract
Extremely high-temperature lightning generates NOx by electrolyzing nitrogen and oxygen molecules, regulating ozone concentration. The Pearl River Delta (PRD) is located in the world's high-value area of lightning density, and lightning-generated NOx (LNOx) cannot be ignored. Using the flash data from Guangdong-Hong Kong-Macao Lightning Location System and multi-site atmospheric composition data, we estimate the NOx variations in lightning activity and its impact on O3 across the PRD region. The cloud-to-groud (CG) frequency from 2013 to 2021 shows a decreasing trend driven by urban regions. We observe that the lightning density is steadily decreasing from the south-central part of Guangzhou City to the surrounding area. A comparison of the different sites with lightning days and non-lightning days shows that a significant amount (13. 84-20. 47 %) of ground-level NOx concentration at urban stations can be attributed to lightning NOx emissions. A lower lightning frequency and low background concentration observed at suburban sites indicated a limited contribution of LNOx. The average decrease in O3 concentration at urban stations (15.92-25.06 %) was significantly higher than that at suburban stations (5.34-8.95 %) due to the influence of titration and lower actinic radiation. There was a greater fluctuation in NOx and O3 concentrations during the cases, and the surface NOx concentration displayed the most significant responsiveness to LNOx under direct lightning striking in the tall tower. This phenomenon has not been reported, however, it is consistent with the laboratory-based observations suggesting the amount of LNO increases with peak current. LNOx significantly impacts air quality in the PRD during the high convective season. Further in situ and vertical distribution observations are necessary to explore the ground-level impact of LNOx.
Collapse
Affiliation(s)
- Xue Zhang
- Institute of Mass Spectrometry and Atmospheric Environment, Jinan University, Guangzhou 511443, China; Institute of Tropical and Marine Meteorology, Guangdong Provincial Key Laboratory of Regional Numerical Weather Prediction, China Meteorological Administration, Guangzhou 510640, China
| | - Tao Deng
- Institute of Tropical and Marine Meteorology, Guangdong Provincial Key Laboratory of Regional Numerical Weather Prediction, China Meteorological Administration, Guangzhou 510640, China.
| | - Dui Wu
- Institute of Mass Spectrometry and Atmospheric Environment, Jinan University, Guangzhou 511443, China; Institute of Tropical and Marine Meteorology, Guangdong Provincial Key Laboratory of Regional Numerical Weather Prediction, China Meteorological Administration, Guangzhou 510640, China.
| | - Lüwen Chen
- Institute of Tropical and Marine Meteorology, Guangdong Provincial Key Laboratory of Regional Numerical Weather Prediction, China Meteorological Administration, Guangzhou 510640, China
| | - Guowen He
- Institute of Tropical and Marine Meteorology, Guangdong Provincial Key Laboratory of Regional Numerical Weather Prediction, China Meteorological Administration, Guangzhou 510640, China; School of Atmospheric Science, Sun Yat-sen University, Zhuhai 519082, China
| | - Honglong Yang
- Shenzhen National Climate Observatory, Meteorological Bureau of Shenzhen Municipality, Shenzhen 518040, China
| | - Yu Zou
- Institute of Tropical and Marine Meteorology, Guangdong Provincial Key Laboratory of Regional Numerical Weather Prediction, China Meteorological Administration, Guangzhou 510640, China
| | - Chenglei Pei
- Guangzhou Environmental Monitoring Center Station, Guangzhou 511443, China
| | - Dingli Yue
- Guangdong Provincial Environmental Monitoring Center, Guangzhou 511443, China
| | - Liping Tao
- Institute of Mass Spectrometry and Atmospheric Environment, Jinan University, Guangzhou 511443, China; Institute of Tropical and Marine Meteorology, Guangdong Provincial Key Laboratory of Regional Numerical Weather Prediction, China Meteorological Administration, Guangzhou 510640, China
| | - Shanshan Ouyang
- Institute of Tropical and Marine Meteorology, Guangdong Provincial Key Laboratory of Regional Numerical Weather Prediction, China Meteorological Administration, Guangzhou 510640, China; Institute of Environmental and Climate Research, Jinan University, Guangzhou 511443, China
| | - Qing Wang
- Institute of Mass Spectrometry and Atmospheric Environment, Jinan University, Guangzhou 511443, China; Institute of Tropical and Marine Meteorology, Guangdong Provincial Key Laboratory of Regional Numerical Weather Prediction, China Meteorological Administration, Guangzhou 510640, China
| | - Zebiao Zhang
- Institute of Mass Spectrometry and Atmospheric Environment, Jinan University, Guangzhou 511443, China; Institute of Tropical and Marine Meteorology, Guangdong Provincial Key Laboratory of Regional Numerical Weather Prediction, China Meteorological Administration, Guangzhou 510640, China
| |
Collapse
|
11
|
Yuan Z, Pei CL, Li HX, Lin L, Hou R, Liu S, Zhang K, Cai MG, Xu XR. Vertical distribution and transport of microplastics in the urban atmosphere: New insights from field observations. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 895:165190. [PMID: 37385506 DOI: 10.1016/j.scitotenv.2023.165190] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/25/2023] [Revised: 06/19/2023] [Accepted: 06/26/2023] [Indexed: 07/01/2023]
Abstract
The distribution and transport of atmospheric microplastics (AMPs) have raised concerns regarding their potential effects on the environment and human health. Although previous studies have reported the presence of AMPs at ground level, there is a lack of comprehensive understanding of their vertical distribution in urban environments. To gain insight into the vertical profile of AMPs, field observations were conducted at four different heights (ground level, 118 m, 168 m and 488 m) of the Canton Tower in Guangzhou, China. Results showed that the profiles of AMPs and other air pollutants had similar layer distribution patterns, although their concentrations differed. The majority of AMPs were composed of polyethylene terephthalate and rayon fibers ranging from 30 to 50 μm. As a result of atmospheric thermodynamics, AMPs generated at ground level were only partially transported upward, leading to a decrease in their abundance with increasing altitude. The study found that the stable atmospheric stability and lower wind speed between 118 m and 168 m resulted in the formation of a fine layer where AMPs tended to accumulate instead of being transported upward. This study for the first time delineated the vertical profile of AMPs within the atmospheric boundary layer, providing valuable data for understanding the environmental fate of AMPs.
Collapse
Affiliation(s)
- Zhen Yuan
- Key Laboratory of Tropical Marine Bio-resources and Ecology, Guangdong Provincial Key Laboratory of Applied Marine Biology, South China Sea Institute of Oceanology, Chinese Academy of Sciences, Guangzhou 510301, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Cheng-Lei Pei
- Guangzhou Sub-branch of Guangdong Ecological and Environmental Monitoring Center, Guangzhou 510006, China
| | - Heng-Xiang Li
- Key Laboratory of Tropical Marine Bio-resources and Ecology, Guangdong Provincial Key Laboratory of Applied Marine Biology, South China Sea Institute of Oceanology, Chinese Academy of Sciences, Guangzhou 510301, China; Sanya Institute of Ocean Eco-Environmental Engineering, Sanya 572100, China
| | - Lang Lin
- Key Laboratory of Tropical Marine Bio-resources and Ecology, Guangdong Provincial Key Laboratory of Applied Marine Biology, South China Sea Institute of Oceanology, Chinese Academy of Sciences, Guangzhou 510301, China; Sanya Institute of Ocean Eco-Environmental Engineering, Sanya 572100, China
| | - Rui Hou
- Key Laboratory of Tropical Marine Bio-resources and Ecology, Guangdong Provincial Key Laboratory of Applied Marine Biology, South China Sea Institute of Oceanology, Chinese Academy of Sciences, Guangzhou 510301, China; Sanya Institute of Ocean Eco-Environmental Engineering, Sanya 572100, China
| | - Shan Liu
- Key Laboratory of Tropical Marine Bio-resources and Ecology, Guangdong Provincial Key Laboratory of Applied Marine Biology, South China Sea Institute of Oceanology, Chinese Academy of Sciences, Guangzhou 510301, China; Sanya Institute of Ocean Eco-Environmental Engineering, Sanya 572100, China
| | - Kai Zhang
- National Observation and Research Station of Coastal Ecological Environments in Macao, Macao Environmental Research Institute, Macau University of Science and Technology, Macao SAR, China
| | - Ming-Gang Cai
- State Key Laboratory of Marine Environmental Science, Xiamen University, Xiamen 361102, China
| | - Xiang-Rong Xu
- Key Laboratory of Tropical Marine Bio-resources and Ecology, Guangdong Provincial Key Laboratory of Applied Marine Biology, South China Sea Institute of Oceanology, Chinese Academy of Sciences, Guangzhou 510301, China; Sanya Institute of Ocean Eco-Environmental Engineering, Sanya 572100, China.
| |
Collapse
|
12
|
Liu X, Yi G, Zhou X, Zhang T, Bie X, Li J, Tan H. Spatio-temporal variations of PM 2.5 and O 3 in China during 2013-2021: Impact factor analysis. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2023; 334:122189. [PMID: 37451585 DOI: 10.1016/j.envpol.2023.122189] [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: 01/05/2023] [Revised: 06/13/2023] [Accepted: 07/11/2023] [Indexed: 07/18/2023]
Abstract
Fine particulate matter (PM2.5) and ozone (O3) pollution are regarded as significant secondary air pollutants. The PM2.5 in most regions in China declined, and the decreasing rate in January was lower than the annual average. However, O3 concentration showed a steady increasing trend in most regions, and the increasing rate in July was slightly higher than the annual average. In particular, the annual average PM2.5 concentration and excess rate showed an increasing trend on the northern slope of the Tianshan Mountains. Conversely, O3 concentrations had shown a consistent increasing trend, exceeding the annual average limit of 100 μg/m3. Surface pressure exhibited positive correlations with PM2.5 in winter and O3 in summer across urban agglomerations. Moreover, soil temperature at different depths explained over 30% of the variations in PM2.5 and O3 in the Chengdu-Chongqing, Beijing-Tianjin-Hebei, and Lanzhou-Xining urban agglomerations. In winter, relative humidity demonstrated a positive correlation with urban agglomerations in northeast and northwest China, regions characterized by dry climates. During the COVID-19 period, the impacts of meteorological factors and soil temperature on PM2.5 and O3 differed significantly compared to preceding and subsequent periods. Notably, during the winter of 2020, the Harbin-Changchuan urban agglomeration exhibited a notable transition, as O3 and PM2.5 concentrations shifted from a strong negative correlation to a robust positive correlation. This remarkable shift, with deviations explained up to 60%, represents a unique phenomenon worth emphasizing in the study's findings.
Collapse
Affiliation(s)
- Xian Liu
- College of Earth Science, Chengdu University of Technology, Chengdu, 610059, China
| | - Guihua Yi
- College of Tourism and Urban-Rural Planning, Chengdu University of Technology, Chengdu, 610059, China.
| | - Xiaobing Zhou
- Geological Engineering Department, Montana Technological University, Butte, MT, 59701, USA
| | - Tingbin Zhang
- College of Earth Science, Chengdu University of Technology, Chengdu, 610059, China; State Environmental Protection Key Laboratory of Synergetic Control and Joint Remediation for Soil & Water Pollution, Chengdu University of Technology, Chengdu, 610059, China
| | - Xiaojuan Bie
- College of Tourism and Urban-Rural Planning, Chengdu University of Technology, Chengdu, 610059, China
| | - Jingji Li
- State Environmental Protection Key Laboratory of Synergetic Control and Joint Remediation for Soil & Water Pollution, Chengdu University of Technology, Chengdu, 610059, China; College of Ecological Environment, Chengdu University of Technology, Chengdu, 610059, China
| | - Huizhi Tan
- College of Earth Science, Chengdu University of Technology, Chengdu, 610059, China
| |
Collapse
|
13
|
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.
Collapse
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
| |
Collapse
|
14
|
Yao Y, Ma K, He C, Zhang Y, Lin Y, Fang F, Li S, He H. Urban Surface Ozone Concentration in Mainland China during 2015-2020: Spatial Clustering and Temporal Dynamics. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2023; 20:3810. [PMID: 36900822 PMCID: PMC10001023 DOI: 10.3390/ijerph20053810] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/22/2022] [Revised: 02/15/2023] [Accepted: 02/17/2023] [Indexed: 06/18/2023]
Abstract
Urban ozone (O3) pollution in the atmosphere has become increasingly prominent on a national scale in mainland China, although the atmospheric particulate matter pollution has been significantly reduced in recent years. The clustering and dynamic variation characteristics of the O3 concentrations in cities across the country, however, have not been accurately explored at relevant spatiotemporal scales. In this study, a standard deviational ellipse analysis and multiscale geographically weighted regression models were applied to explore the migration process and influencing factors of O3 pollution based on measured data from urban monitoring sites in mainland China. The results suggested that the urban O3 concentration in mainland China reached its peak in 2018, and the annual O3 concentration reached 157 ± 27 μg/m3 from 2015 to 2020. On the scale of the whole Chinese mainland, the distribution of O3 exhibited spatial dependence and aggregation. On the regional scale, the areas of high O3 concentrations were mainly concentrated in Beijing-Tianjin-Hebei, Shandong, Jiangsu, Henan, and other regions. In addition, the standard deviation ellipse of the urban O3 concentration covered the entire eastern part of mainland China. Overall, the geographic center of ozone pollution has a tendency to move to the south with the time variation. The interaction between sunshine hours and other factors (precipitation, NO2, DEM, SO2, PM2.5) significantly affected the variation of urban O3 concentration. In Southwest China, Northwest China, and Central China, the suppression effect of vegetation on local O3 was more obvious than that in other regions. Therefore, this study clarified for the first time the migration path of the gravity center of the urban O3 pollution and identified the key areas for the prevention and control of O3 pollution in mainland China.
Collapse
Affiliation(s)
- Youru Yao
- Key Laboratory of Earth Surface Processes and Regional Response in the Yangtze-Huaihe River Basin, School of Geography and Tourism, Anhui Normal University, Wuhu 241002, China
| | - Kang Ma
- Key Laboratory of Earth Surface Processes and Regional Response in the Yangtze-Huaihe River Basin, School of Geography and Tourism, Anhui Normal University, Wuhu 241002, China
| | - Cheng He
- Helmholtz Zentrum München–German Research Center for Environmental Health (GmbH), Institute of Epidemiology, 85764 Neuherberg, Germany
| | - Yong Zhang
- Department of Geological Sciences, University of Alabama, Tuscaloosa, AL 35487, USA
| | - Yuesheng Lin
- Key Laboratory of Earth Surface Processes and Regional Response in the Yangtze-Huaihe River Basin, School of Geography and Tourism, Anhui Normal University, Wuhu 241002, China
| | - Fengman Fang
- Key Laboratory of Earth Surface Processes and Regional Response in the Yangtze-Huaihe River Basin, School of Geography and Tourism, Anhui Normal University, Wuhu 241002, China
| | - Shiyin Li
- School of Environment, Nanjing Normal University, Nanjing 210023, China
| | - Huan He
- School of Environment, Nanjing Normal University, Nanjing 210023, China
| |
Collapse
|
15
|
Liang Y, Wu C, Wu D, Liu B, Li YJ, Sun J, Yang H, Mao X, Tan J, Xia R, Deng T, Li M, Zhou Z. Vertical distributions of atmospheric black carbon in dry and wet seasons observed at a 356-m meteorological tower in Shenzhen, South China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 853:158657. [PMID: 36096219 DOI: 10.1016/j.scitotenv.2022.158657] [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: 06/27/2022] [Revised: 08/28/2022] [Accepted: 09/06/2022] [Indexed: 06/15/2023]
Abstract
Black carbon (BC) is a vital climate forcer in the atmosphere, but measurements of BC vertical profiles near the surface remain limited. This study investigates time-resolved vertical profiling of BC in both dry (December 2017) and wet (August 2018) seasons in Shenzhen, China, at a 356-m meteorological tower. In the dry season, five micro-aethalometers were deployed at different heights (2, 50, 100, 200, and 350 m), while four heights (2, 100, 200, and 350 m) were measured in the wet season. The concentrations of equivalent BC (eBC) showed a decreasing trend with altitude in the dry season, while a weaker vertical gradient was observed in the wet season. The diurnal variability of eBC in the dry season is also more significant than in the wet season. Correlation analysis between eBC concentrations at the ground and those at the upper levels suggest a better vertical mixing of eBC in the wet season than in the dry season. In the wet season when south wind prevailed, eBC concentration at ground level was likely reduced by the large amount of vegetation cover south to the sampling site. In the dry season, eBC concentrations at 350 m show little dependence on wind speed, implying that local emissions have a limited effect on eBC concentrations at 350 m. In the wet season when brown carbon influence was weak, higher wind speed leads to a higher Ångström exponent (AAE) at 350 m, likely associated with more aged BC particles. Cluster analysis of backward trajectories suggests that high eBC concentration was associated with air masses from Central China in both seasons. This study provides a better understanding on the influencing factors that affect the vertical distributions of BC in the lower part of the boundary layer.
Collapse
Affiliation(s)
- Yue Liang
- Institute of Mass Spectrometry and Atmospheric Environment, Guangdong Provincial Engineering Research Center for on-line source apportionment system of air pollution, Jinan University, Guangzhou 510632, China; Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Guangzhou 510632, China; Department of Civil and Environmental Engineering, Faculty of Science and Technology, University of Macau, Taipa, Macau
| | - Cheng Wu
- Institute of Mass Spectrometry and Atmospheric Environment, Guangdong Provincial Engineering Research Center for on-line source apportionment system of air pollution, Jinan University, Guangzhou 510632, China; Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Guangzhou 510632, China.
| | - Dui Wu
- Institute of Mass Spectrometry and Atmospheric Environment, Guangdong Provincial Engineering Research Center for on-line source apportionment system of air pollution, Jinan University, Guangzhou 510632, China; Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Guangzhou 510632, China
| | - Ben Liu
- Department of Civil and Environmental Engineering, Faculty of Science and Technology, University of Macau, Taipa, Macau
| | - Yong Jie Li
- Department of Civil and Environmental Engineering, Faculty of Science and Technology, University of Macau, Taipa, Macau
| | - Jiayin Sun
- Institute of Mass Spectrometry and Atmospheric Environment, Guangdong Provincial Engineering Research Center for on-line source apportionment system of air pollution, Jinan University, Guangzhou 510632, China; Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Guangzhou 510632, China
| | - Honglong Yang
- Shenzhen Meteorological Bureau, CMA, Shenzhen 518040, China
| | - Xia Mao
- Shenzhen Meteorological Bureau, CMA, Shenzhen 518040, China
| | - Jian Tan
- Institute of Mass Spectrometry and Atmospheric Environment, Guangdong Provincial Engineering Research Center for on-line source apportionment system of air pollution, Jinan University, Guangzhou 510632, China; Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Guangzhou 510632, China
| | - Rui Xia
- Institute of Mass Spectrometry and Atmospheric Environment, Guangdong Provincial Engineering Research Center for on-line source apportionment system of air pollution, Jinan University, Guangzhou 510632, China; Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Guangzhou 510632, China
| | - Tao Deng
- Institute of Tropical and Marine Meteorology, CMA, Guangzhou 510080, China
| | - Mei Li
- Institute of Mass Spectrometry and Atmospheric Environment, Guangdong Provincial Engineering Research Center for on-line source apportionment system of air pollution, Jinan University, Guangzhou 510632, China; Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Guangzhou 510632, China
| | - Zhen Zhou
- Institute of Mass Spectrometry and Atmospheric Environment, Guangdong Provincial Engineering Research Center for on-line source apportionment system of air pollution, Jinan University, Guangzhou 510632, China; Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Guangzhou 510632, China
| |
Collapse
|
16
|
Chen L, Pang X, Li J, Xing B, An T, Yuan K, Dai S, Wu Z, Wang S, Wang Q, Mao Y, Chen J. Vertical profiles of O 3, NO 2 and PM in a major fine chemical industry park in the Yangtze River Delta of China detected by a sensor package on an unmanned aerial vehicle. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 845:157113. [PMID: 35787910 DOI: 10.1016/j.scitotenv.2022.157113] [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: 05/09/2022] [Revised: 06/27/2022] [Accepted: 06/28/2022] [Indexed: 06/15/2023]
Abstract
The vertical profiles and diurnal variations of air pollutants at different heights in the fine chemical industry park (FCIP) were systematically studied in this study. Air pollutants in a major FCIP in the Yangtze River Delta of China within 500 m above ground level (AGL) detected by a sensor package on an unmanned aerial vehicle (UAV). The air pollutants including ozone (O3), nitrogen dioxide (NO2), particulate matter (PM), total volatile organic compounds (TVOCs) and carbon monoxide (CO), respectively, had been measured through more than one hundred times of vertical flights from Aug. 2020 to Jul. 2021. The concentrations of NO2 and CO generally decreased with the height while the concentrations of O3 increased with the height within 500 m AGL. The photochemical reaction resulted in a strong inverse relationship between the vertical profiles of O3 and that of NO2. The concentrations of PM2.5 and TVOCs generally decreased with the height below 100 m AGL and were fully mixed above 100 m AGL. The vertical profiles of different particle sizes were well consistent with the R2 value of 0.97 between PM1 and PM2.5 and 0.93 between PM2.5 and PM10. The NO2 and PM2.5 concentrations sometimes increased with height maybe due to the influence of temperature inversion layer or long-distance transportation from northern China. The diurnal variations of NO2, O3, TVOCs and CO concentrations at different heights within 500 m AGL were basically consistent. The diurnal variations range of PM2.5 concentrations below 100 m AGL was large and different from other heights, which should be greatly influenced by the local emissions. The unstable atmospheric stability was accompanied by strong photochemical reactions and convective activities, resulting in low concentrations of NO2 and PM2.5, while high concentrations of O3.
Collapse
Affiliation(s)
- Lang Chen
- College of Environment, Zhejiang University of Technology, Hangzhou 310000, China
| | - Xiaobing Pang
- College of Environment, Zhejiang University of Technology, Hangzhou 310000, China.
| | - Jingjing Li
- Shaoxing Ecological and Environmental Monitoring Center of Zhejiang Province, Shaoxing 312000, China.
| | - Bo Xing
- Shaoxing Ecological and Environmental Monitoring Center of Zhejiang Province, Shaoxing 312000, China
| | - Taicheng An
- Guangdong Key Laboratory of Environmental Catalysis and Health Risk Control, Guangzhou Key Laboratory of Environmental Catalysis and Pollution Control, School of Environmental Science and Engineering, Institute of Environmental Health and Pollution Control, Guangdong University of Technology, Guangzhou 510006, China
| | - Kaibin Yuan
- College of Environment, Zhejiang University of Technology, Hangzhou 310000, China
| | - Shang Dai
- College of Environment, Zhejiang University of Technology, Hangzhou 310000, China
| | - Zhentao Wu
- College of Environment, Zhejiang University of Technology, Hangzhou 310000, China
| | - Shuaiqi Wang
- College of Environment, Zhejiang University of Technology, Hangzhou 310000, China
| | - Qiang Wang
- College of Environment, Zhejiang University of Technology, Hangzhou 310000, China
| | - Yiping Mao
- College of Environment, Zhejiang University of Technology, Hangzhou 310000, China
| | - Jianmeng Chen
- College of Environment, Zhejiang University of Technology, Hangzhou 310000, China.
| |
Collapse
|
17
|
Zhang X, Jian X, Zhao Y, Liu X, Chen K, Wang L, Tao S, Liu J, Huang T, Gao H, Liu Y, Zhugu R, Ma J. Tropospheric Ozone Perturbations Induced by Urban Land Expansion in China from 1980 to 2017. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2022; 56:6978-6987. [PMID: 35271270 DOI: 10.1021/acs.est.1c06664] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Urbanization perturbs air pollutants from a dynamic and thermodynamic perspective, which has inspired extensive investigations in China due to rapid urban land expansion in the past four decades. However, knowledge gaps remain in the long-term and nationwide responses to air pollutants to urbanization. The evolution of tropospheric ozone associated with urban land expansion across China was assessed from 1980 to 2017 using a coupled WRF-Chem model based on a recently updated land use change (LUC) data set. The results revealed that urban-land expansion drove growing ozone trends for this period and contributed about 3-9% to its summer maximum concentrations during the 2010s in major urban agglomerations across China. The association between a long-term change in summer O3 concentrations and LUC after excluding the effect of precursor emissions and meteorological conditions and causes of interannual (short-term) variations in O3 concentrations induced by urban-land expansion were also explored by examining the relationships between ozone fluctuations and meteorological variables.
Collapse
Affiliation(s)
- Xiaodong Zhang
- Laboratory for Earth Surface Processes, College of Urban and Environmental Sciences, Peking University, Beijing 100871, P.R. China
| | - Xiaohu Jian
- Laboratory for Earth Surface Processes, College of Urban and Environmental Sciences, Peking University, Beijing 100871, P.R. China
| | - Yuan Zhao
- Key Laboratory for Environmental Pollution Prediction and Control, College of Earth and Environmental Sciences, Lanzhou University, Lanzhou 730000, P.R. China
| | - Xinrui Liu
- Laboratory for Earth Surface Processes, College of Urban and Environmental Sciences, Peking University, Beijing 100871, P.R. China
| | - Kaijie Chen
- Laboratory for Earth Surface Processes, College of Urban and Environmental Sciences, Peking University, Beijing 100871, P.R. China
| | - Linfei Wang
- Laboratory for Earth Surface Processes, College of Urban and Environmental Sciences, Peking University, Beijing 100871, P.R. China
| | - Shu Tao
- Laboratory for Earth Surface Processes, College of Urban and Environmental Sciences, Peking University, Beijing 100871, P.R. China
| | - Junfeng Liu
- Laboratory for Earth Surface Processes, College of Urban and Environmental Sciences, Peking University, Beijing 100871, P.R. China
| | - Tao Huang
- Key Laboratory for Environmental Pollution Prediction and Control, College of Earth and Environmental Sciences, Lanzhou University, Lanzhou 730000, P.R. China
| | - Hong Gao
- Key Laboratory for Environmental Pollution Prediction and Control, College of Earth and Environmental Sciences, Lanzhou University, Lanzhou 730000, P.R. China
| | - Yijie Liu
- Laboratory for Earth Surface Processes, College of Urban and Environmental Sciences, Peking University, Beijing 100871, P.R. China
| | - Ruiru Zhugu
- Laboratory for Earth Surface Processes, College of Urban and Environmental Sciences, Peking University, Beijing 100871, P.R. China
| | - Jianmin Ma
- Laboratory for Earth Surface Processes, College of Urban and Environmental Sciences, Peking University, Beijing 100871, P.R. China
- Key Laboratory for Environmental Pollution Prediction and Control, College of Earth and Environmental Sciences, Lanzhou University, Lanzhou 730000, P.R. China
| |
Collapse
|
18
|
Sbai SE, Bentayeb F, Yin H. Atmospheric pollutants response to the emission reduction and meteorology during the COVID-19 lockdown in the north of Africa (Morocco). STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT : RESEARCH JOURNAL 2022; 36:3769-3784. [PMID: 35498271 PMCID: PMC9033931 DOI: 10.1007/s00477-022-02224-z] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Accepted: 03/25/2022] [Indexed: 06/14/2023]
Abstract
UNLABELLED Climate and air quality change due to COVID-19 lockdown (LCD) are extremely concerned subjects of several research recently. The contribution of meteorological factors and emission reduction to air pollution change over the north of Morocco has been investigated in this study using the framework generalized additive models, that have been proved to be a robust technique for the environmental data sets, focusing on main atmospheric pollutants in the region including ozone (O3), nitrogen dioxide (NO2), sulfur dioxide (SO2), particulate matter (PM2.5 and PM10), secondary inorganic aerosols (SIA), nom-methane volatile organic compounds and carbon monoxide (CO) from the regional air pollution dataset of the Copernicus Atmosphere Monitoring Service. Our results, indicate that secondary air pollutants (PM2.5, PM10 and O3) are more influenced by metrological factors and the other air pollutants reported by this study (NO2 and SO2). We show a negative effect for PBHL, total precipitation and NW10M on PM (PM2.5 and PM10 ), this meteorological parameters contribute to decrease in PM2.5 by 9, 2 and 9% respectively, before LCD and 8, 1 and 5% respectively during LCD. However, a positive marginal effect was found for SAT, Irradiance and RH that contribute to increase PM2.5 by 9, 12 and 18% respectively, before LCD and 17, 54 and 34% respectively during LCD. We found also that meteorological factors contribute to O3, PM2.5, PM10 and SIA average mass concentration by 22, 5, 3 and 34% before LCD and by 28, 19, 5 and 42% during LCD respectively. The increase in meteorological factors marginal effect during LCD shows the contribution of photochemical oxidation to air pollution due to increase in atmospheric oxidant (O3 and OH radical) during LCD, which can explain the response of PM to emission reduction. This study indicates that PM (PM2.5, PM10) has more controlled by SO2 due to the formation of sulfate particles especially under high oxidants level. The positive correlation between westward wind at 10 m (WW10M), Northward Wind at 10 m (NW10M) and PM indicates the implication of sea salt particles transported from Mediterranean Sea and Atlantic Ocean. The Ozone mass concentration shows a positive trend with Irradiance, Total and SAT during LCD; because temperature and irradiance enhance tropospheric ozone formation via photochemical reaction.This study shows the contribution of atmospheric oxidation capacity to air pollution change. SUPPLEMENTARY INFORMATION The online version contains supplementary material available at 10.1007/s00477-022-02224-z.
Collapse
Affiliation(s)
- Salah Eddine Sbai
- Department of Physics, Laboratoires de Physique des Hauts Energies Modélisation et Simulation, Mohammed V University in Rabat, Rabat, Morocco
| | - Farida Bentayeb
- Department of Physics, Laboratoires de Physique des Hauts Energies Modélisation et Simulation, Mohammed V University in Rabat, Rabat, Morocco
| | - Hao Yin
- Key Laboratory of Environmental Optics and Technology, Anhui Institute of Optics and Fine Mechanics, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, 230031 China
- University of Science and Technology of China, Hefei, 230026 China
| |
Collapse
|
19
|
Spatiotemporal Patterns and Regional Transport of Ground-Level Ozone in Major Urban Agglomerations in China. ATMOSPHERE 2022. [DOI: 10.3390/atmos13020301] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Ground-level ozone (O3) pollution has become a serious environmental issue in major urban agglomerations in China. To investigate the spatiotemporal patterns and regional transports of O3 in Beijing–Tianjin–Hebei (BTH-UA), the Yangtze River Delta (YRD-UA), the Triangle of Central China (TC-UA), Chengdu–Chongqing (CY-UA), and the Pearl River Delta urban agglomeration (PRD-UA), multiple transdisciplinary methods were employed to analyze the O3-concentration data that were collected from national air quality monitoring networks operated by the China National Environmental Monitoring Center (CNEMC). It was found that although ozone concentrations have decreased in recent years, ozone pollution is still a serious issue in China. O3 exhibited different spatiotemporal patterns in the five urban agglomerations. In terms of monthly variations, O3 had a unimodal structure in BTH-UA but a bimodal structure in the other urban agglomerations. The maximum O3 concentration was in autumn in PRD-UA, but in summer in the other urban agglomerations. In spatial distribution, the main distribution of O3 concentration was aligned in northeast–southwest direction for BTH-UA and CY-UA, but in northwest–southeast direction for YRD-UA, TC-UA, and PRD-UA. O3 concentrations exhibited positive spatial autocorrelations in BTH-UA, YRD-UA, and TC-UA, but negative spatial autocorrelations in CY-UA and PRD-UA. Variations in O3 concentration were more affected by weather fluctuations in coastal cities while the variations were more affected by seasonal changes in inland cities. O3 transport in the center cities of the five urban agglomerations was examined by backward trajectory and potential source analyses. Local areas mainly contributed to the O3 concentrations in the five cities, but regional transport also played a significant role. Our findings suggest joint efforts across cities and regions will be necessary to reduce O3 pollution in major urban agglomerations in China.
Collapse
|
20
|
Wu C, Liu B, Wu D, Yang H, Mao X, Tan J, Liang Y, Sun JY, Xia R, Sun J, He G, Li M, Deng T, Zhou Z, Li YJ. Vertical profiling of black carbon and ozone using a multicopter unmanned aerial vehicle (UAV) in urban Shenzhen of South China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2021; 801:149689. [PMID: 34425446 DOI: 10.1016/j.scitotenv.2021.149689] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/23/2021] [Revised: 08/11/2021] [Accepted: 08/11/2021] [Indexed: 06/13/2023]
Abstract
Existing studies on vertical profiling of black carbon (BC) and ozone (O3) were mainly conducted in the rural areas, leading to limited knowledge of their vertical distributions in the urban area. To fill this knowledge gap, vertical profiling (0-500 m and 0-900 m, AGL) of BC and O3 was conducted in a highly urbanized area of Shenzhen in subtropical South China using a multicopter unmanned aerial vehicle (UAV) platform. In total 32 flights were conducted from the 10th to 15th, December 2017 (winter campaign) and 42 flights from the 19th to 28th, August 2018 (summer campaign) with 4 time slots per day, including morning, afternoon, evening, and midnight. In general, equivalent BC (eBC) concentration decreased as the height increased with an overall slope of -0.13 μg m-3 per 100 m in the winter campaign and -0.08 μg m-3 per 100 m in the summer campaign. On the contrary, an increase of O3 level with altitude was observed (7.8 ppb per 100 m). Absorption Ångström exponent (AAE) exhibits a slightly increasing trend with height. Seasonality of eBC vertical profiles was observed in morning, afternoon and midnight flights, but not for evening flights. The analysis showed the shape of vertical profiles of eBC and O3 can be affected by planetary boundary layer height (PBLH) and air mass origin. Calculated heating rates due to BC show distinct seasonal variability for morning but not for afternoon, because of the counteracting effects by solar irradiance in the subtropical afternoon and eBC concentration in urban South China influenced by the monsoon climate.
Collapse
Affiliation(s)
- Cheng Wu
- Institute of Mass Spectrometry and Atmospheric Environment, Guangdong Provincial Engineering Research Center for On-line Source Apportionment System of Air Pollution, Jinan University, Guangzhou 510632, China; Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Guangzhou 510632, China.
| | - Ben Liu
- Department of Civil and Environmental Engineering and Centre for Regional Oceans, Faculty of Science and Technology, University of Macau, Taipa, Macau
| | - Dui Wu
- Institute of Mass Spectrometry and Atmospheric Environment, Guangdong Provincial Engineering Research Center for On-line Source Apportionment System of Air Pollution, Jinan University, Guangzhou 510632, China; Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Guangzhou 510632, China; Institute of Tropical and Marine Meteorology, CMA, Guangzhou 510080, China
| | - Honglong Yang
- Shenzhen Meteorological Bureau, CMA, Shenzhen 518040, China
| | - Xia Mao
- Shenzhen Meteorological Bureau, CMA, Shenzhen 518040, China
| | - Jian Tan
- Institute of Mass Spectrometry and Atmospheric Environment, Guangdong Provincial Engineering Research Center for On-line Source Apportionment System of Air Pollution, Jinan University, Guangzhou 510632, China; Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Guangzhou 510632, China
| | - Yue Liang
- Institute of Mass Spectrometry and Atmospheric Environment, Guangdong Provincial Engineering Research Center for On-line Source Apportionment System of Air Pollution, Jinan University, Guangzhou 510632, China; Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Guangzhou 510632, China
| | - Jia Yin Sun
- Institute of Mass Spectrometry and Atmospheric Environment, Guangdong Provincial Engineering Research Center for On-line Source Apportionment System of Air Pollution, Jinan University, Guangzhou 510632, China; Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Guangzhou 510632, China
| | - Rui Xia
- Institute of Mass Spectrometry and Atmospheric Environment, Guangdong Provincial Engineering Research Center for On-line Source Apportionment System of Air Pollution, Jinan University, Guangzhou 510632, China; Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Guangzhou 510632, China
| | - Jiaren Sun
- Key Laboratory of urban ecological Environmental Simulation and protection, South China Institute of Environmental Sciences, the Ministry of Ecology and Environment of PRC, Guangzhou 510530, China
| | - Guowen He
- Institute of Mass Spectrometry and Atmospheric Environment, Guangdong Provincial Engineering Research Center for On-line Source Apportionment System of Air Pollution, Jinan University, Guangzhou 510632, China; Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Guangzhou 510632, China
| | - Mei Li
- Institute of Mass Spectrometry and Atmospheric Environment, Guangdong Provincial Engineering Research Center for On-line Source Apportionment System of Air Pollution, Jinan University, Guangzhou 510632, China; Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Guangzhou 510632, China
| | - Tao Deng
- Institute of Tropical and Marine Meteorology, CMA, Guangzhou 510080, China
| | - Zhen Zhou
- Institute of Mass Spectrometry and Atmospheric Environment, Guangdong Provincial Engineering Research Center for On-line Source Apportionment System of Air Pollution, Jinan University, Guangzhou 510632, China; Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Guangzhou 510632, China
| | - Yong Jie Li
- Department of Civil and Environmental Engineering and Centre for Regional Oceans, Faculty of Science and Technology, University of Macau, Taipa, Macau.
| |
Collapse
|