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Sun X, Zhao T, Tang G, Bai Y, Kong S, Zhou Y, Hu J, Tan C, Shu Z, Xu J, Ma X. Vertical changes of PM 2.5 driven by meteorology in the atmospheric boundary layer during a heavy air pollution event in central China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 858:159830. [PMID: 36343804 DOI: 10.1016/j.scitotenv.2022.159830] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/05/2022] [Revised: 08/28/2022] [Accepted: 10/26/2022] [Indexed: 06/16/2023]
Abstract
Regional PM2.5 transport is a crucial factor affecting air quality, and the meteorological mechanism in the atmospheric boundary layer (ABL) has not been fully understood over the receptor region in the regional transport of air pollutants. Based on the intensive vertical measurements of air pollutants and meteorology in the ABL during a transport-induced heavy air pollution event in Xiangyang, an urban site over a receptor region in central China, we investigated the meteorological mechanism in vertical PM2.5 changes in the ABL for heavy air pollution over the receptor region. Driven by northerly winds, regional PM2.5 transport was built from upstream northern China to downstream central China, where the observed ABL structures were unstable throughout the air pollution event. We assessed the ABL structures with meteorological and PM2.5 profiles at growth, maintenance, and dissipation stages, and elucidated the mechanism of regional PM2.5 transport inducing air pollution over the receptor region with the contribution of thermal and mechanical factors. The regional PM2.5 transport was concentrated in the upper ABL over the downwind receptor region with high PM2.5 concentrations at altitudes of 600-800 m, where the transported PM2.5 peaks were downwards mixed by vertical wind shear, forming the vertical PM2.5 transport from the upper ABL to near-surface in the growth stage; the weakened winds and less unstable structures in the ABL favored the sustained pollution with slight vertical PM2.5 changes in the maintenance stage, which was dominated by thermal factors with 87 % contribution; the removal of PM2.5 was triggered by increasing winds from the upper ABL, activating the dissipation of heavy PM2.5 pollution with the mechanical effect accounting for 60 % in the dissipation stage. These findings could improve our understanding of ABL's influence on air pollution over the receptor region with implications for the regional transport of air pollutants in environmental changes.
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Affiliation(s)
- Xiaoyun Sun
- Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, PREMIC, Nanjing University of Information Science and 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, PREMIC, Nanjing University of Information Science and Technology, Nanjing 210044, China.
| | - Guiqian Tang
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
| | - Yongqing Bai
- Institute of Heavy Rain, China Meteorological Administration, Wuhan 430205, China
| | - Shaofei Kong
- Department of Atmospheric Sciences, School of Environmental Studies, China University of Geosciences (Wuhan), Wuhan 430074, China
| | - Yue Zhou
- Institute of Heavy Rain, China Meteorological Administration, Wuhan 430205, China
| | - Jun Hu
- Fujian Academy of Environmental Sciences, Fuzhou 350011, China
| | - Chenghao Tan
- State Key Laboratory of Organic Geochemistry, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Zhuozhi Shu
- Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, PREMIC, Nanjing University of Information Science and Technology, Nanjing 210044, China
| | - Jiaping Xu
- Jiangsu Climate Center, Nanjing 210009, China
| | - Xiaodan Ma
- Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, PREMIC, Nanjing University of Information Science and Technology, Nanjing 210044, China
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Wang Y, Jin X, Liu Z, Wang G, Tang G, Lu K, Hu B, Wang S, Li G, An X, Wang C, Hu Q, He L, Zhang F, Zhang Y. Progress in quantitative research on the relationship between atmospheric oxidation and air quality. J Environ Sci (China) 2023; 123:350-366. [PMID: 36521998 DOI: 10.1016/j.jes.2022.06.029] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2021] [Revised: 06/13/2022] [Accepted: 06/22/2022] [Indexed: 06/17/2023]
Abstract
Atmospheric oxidizing capacity (AOC) is an essential driving force of troposphere chemistry and self-cleaning, but the definition of AOC and its quantitative representation remain uncertain. Driven by national demand for air pollution control in recent years, Chinese scholars have carried out studies on theories of atmospheric chemistry and have made considerable progress in AOC research. This paper will give a brief review of these developments. First, AOC indexes were established that represent apparent atmospheric oxidizing ability (AOIe) and potential atmospheric oxidizing ability (AOIp) based on aspects of macrothermodynamics and microdynamics, respectively. A closed study refined the quantitative contributions of heterogeneous chemistry to AOC in Beijing, and these AOC methods were further applied in Beijing-Tianjin-Hebei and key areas across the country. In addition, the detection of ground or vertical profiles for atmospheric OH·, HO2·, NO3· radicals and reservoir molecules can now be obtained with domestic instruments in diverse environments. Moreover, laboratory smoke chamber simulations revealed heterogeneous processes involving reactions of O3 and NO2, which are typical oxidants in the surface/interface atmosphere, and the evolutionary and budgetary implications of atmospheric oxidants reacting under multispecies, multiphase and multi-interface conditions were obtained. Finally, based on the GRAPES-CUACE adjoint model improved by Chinese scholars, simulations of key substances affecting atmospheric oxidation and secondary organic and inorganic aerosol formation have been optimized. Normalized numerical simulations of AOIe and AOIp were performed, and regional coordination of AOC was adjusted. An optimized plan for controlling O3 and PM2.5 was analyzed by scenario simulation.
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Affiliation(s)
- Yuesi Wang
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry (LAPC), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China; College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Xin Jin
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry (LAPC), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China; College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Zirui Liu
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry (LAPC), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China; College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing 100049, China.
| | - Gehui Wang
- Key Lab of Geophysical Information System of the Ministry of Education, School of Geographic Sciences, East China Normal University, Shanghai 200241, China
| | - Guiqian Tang
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry (LAPC), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
| | - Keding Lu
- State Key Joint Laboratory or Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Bo Hu
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry (LAPC), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
| | - Shanshan Wang
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), Department of Environmental Science and Engineering, Fudan University, Shanghai 201203, China
| | - Guohui Li
- Key Lab of Aerosol Chemistry and Physics, State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an 710061, China
| | - Xinqin An
- Institute of Atmospheric Composition and Environmental Meteorology, Chinese Academy of Meteorological Sciences, Beijing 100081, China
| | - Chao Wang
- Institute of Atmospheric Composition and Environmental Meteorology, Chinese Academy of Meteorological Sciences, Beijing 100081, China
| | - Qihou Hu
- Key Lab of Environmental Optics and Technology, Anhui Institute of Optics and Fine Mechanics, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China
| | - Lingyan He
- State Key Joint Laboratory or Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Fenfen Zhang
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
| | - Yuanhang Zhang
- State Key Joint Laboratory or Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China.
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Wang H, Lu K, Tan Z, Chen X, Liu Y, Zhang Y. Formation mechanism and control strategy for particulate nitrate in China. J Environ Sci (China) 2023; 123:476-486. [PMID: 36522007 DOI: 10.1016/j.jes.2022.09.019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2022] [Revised: 09/14/2022] [Accepted: 09/14/2022] [Indexed: 06/17/2023]
Abstract
Over the past decade, fine particulate matter (PM) pollution in China has been abated significantly, benefiting from strict emission control measures, but particulate nitrate continues to rise. Here, we review the progress in particulate nitrate (pNO3-) pollution characterization, nitrate formation mechanisms, and the proposed control strategies in China. The spatial and temporal distributions of pNO3- are summarized. The current status of knowledge on the chemical mechanism is updated, and the significance of its formation pathways is assessed by various approaches such as field observation and modelling of nitrate production rate, as well as isotopic analysis. The factors impacting pNO3- formation and the corresponding pollution regulation strategies are discussed, in which the importance of atmospheric oxidation capacity and ammonia are addressed. Finally, the challenges and open questions in pNO3- pollution control in China are outlined.
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Affiliation(s)
- Haichao Wang
- School of Atmospheric Sciences, Sun Yat-sen University, Guangzhou 510275, China
| | - Keding Lu
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China.
| | - Zhaofeng Tan
- Institute of Energy and Climate Research, IEK-8: Troposphere, Forschungszentrum Jülich GmbH, Jülich 52428, Germany
| | - Xiaorui Chen
- Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Hong Kong 999077, China
| | - Yuhan Liu
- China Institute of Atomic Energy, Beijing 100193, China
| | - Yuanhang Zhang
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
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Xie X, Hu J, Qin M, Guo S, Hu M, Wang H, Lou S, Li J, Sun J, Li X, Sheng L, Zhu J, Chen G, Yin J, Fu W, Huang C, Zhang Y. Modeling particulate nitrate in China: Current findings and future directions. ENVIRONMENT INTERNATIONAL 2022; 166:107369. [PMID: 35772313 DOI: 10.1016/j.envint.2022.107369] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/13/2022] [Revised: 06/07/2022] [Accepted: 06/20/2022] [Indexed: 06/15/2023]
Abstract
Particulate nitrate (pNO3) is now becoming the principal component of PM2.5 during severe winter haze episodes in many cities of China. To gain a comprehensive understanding of the key factors controlling pNO3 formation and driving its trends, we reviewed the recent pNO3 modeling studies which mainly focused on the formation mechanism and recent trends of pNO3 as well as its responses to emission controls in China. The results indicate that although recent chemical transport models (CTMs) can reasonably capture the spatial-temporal variations of pNO3, model-observation biases still exist due to large uncertainties in the parameterization of dinitrogen pentoxide (N2O5) uptake and ammonia (NH3) emissions, insufficient heterogeneous reaction mechanism, and the predicted low sulfate concentrations in current CTMs. The heterogeneous hydrolysis of N2O5 dominates nocturnal pNO3 formation, however, the contribution to total pNO3 varies among studies, ranging from 21.0% to 51.6%. Moreover, the continuously increasing PM2.5 pNO3 fraction in recent years is mainly due to the decreased sulfur dioxide emissions, the enhanced atmospheric oxidation capacity (AOC), and the weakened nitrate deposition. Reducing NH3 emissions is found to be the most effective control strategy for mitigating pNO3 pollution in China. This review suggests that more field measurements are needed to constrain the parameterization of heterogeneous N2O5 and nitrogen dioxide (NO2) uptake. Future studies are also needed to quantify the relationships of pNO3 to AOC, O3, NOx, and volatile organic compounds (VOCs) in different regions of China under different meteorological conditions. Research on multiple-pollutant control strategies involving NH3, NOX, and VOCs is required to mitigate pNO3 pollution, especially during severe winter haze events.
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Affiliation(s)
- Xiaodong Xie
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, School of Environmental Science and Engineering, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Nanjing University of Information Science and Technology, Nanjing 210044, China
| | - Jianlin Hu
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, School of Environmental Science and Engineering, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Nanjing University of Information Science and Technology, Nanjing 210044, China.
| | - Momei Qin
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, School of Environmental Science and Engineering, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Nanjing University of Information Science and Technology, Nanjing 210044, China
| | - Song Guo
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Min Hu
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Hongli Wang
- State Environmental Protection Key Laboratory of Formation and Prevention of Urban Air Pollution Complex, Shanghai Academy of Environmental Sciences, Shanghai 200233, China
| | - Shengrong Lou
- State Environmental Protection Key Laboratory of Formation and Prevention of Urban Air Pollution Complex, Shanghai Academy of Environmental Sciences, Shanghai 200233, China
| | - Jingyi Li
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, School of Environmental Science and Engineering, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Nanjing University of Information Science and Technology, Nanjing 210044, China
| | - Jinjin Sun
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, School of Environmental Science and Engineering, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Nanjing University of Information Science and Technology, Nanjing 210044, China
| | - Xun Li
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, School of Environmental Science and Engineering, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Nanjing University of Information Science and Technology, Nanjing 210044, China
| | - Li Sheng
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, School of Environmental Science and Engineering, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Nanjing University of Information Science and Technology, Nanjing 210044, China
| | - Jianlan Zhu
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, School of Environmental Science and Engineering, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Nanjing University of Information Science and Technology, Nanjing 210044, China
| | - Ganyu Chen
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, School of Environmental Science and Engineering, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Nanjing University of Information Science and Technology, Nanjing 210044, China
| | - Junjie Yin
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, School of Environmental Science and Engineering, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Nanjing University of Information Science and Technology, Nanjing 210044, China
| | - Wenxing Fu
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, School of Environmental Science and Engineering, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Nanjing University of Information Science and Technology, Nanjing 210044, China
| | - Cheng Huang
- State Environmental Protection Key Laboratory of Formation and Prevention of Urban Air Pollution Complex, Shanghai Academy of Environmental Sciences, Shanghai 200233, China
| | - Yuanhang Zhang
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China; CAS Center for Excellence in Regional Atmospheric Environment, Chinese Academy of Science, Xiamen 361021, China.
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Wang Y, Wang Y, Tang G, Yang Y, Li X, Yao D, Wu S, Kang Y, Wang M, Wang Y. High gaseous carbonyl concentrations in the upper boundary layer in Shijiazhuang, China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2021; 799:149438. [PMID: 34426343 DOI: 10.1016/j.scitotenv.2021.149438] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/04/2021] [Revised: 07/05/2021] [Accepted: 07/30/2021] [Indexed: 06/13/2023]
Abstract
Oxygenated volatile organic compounds (OVOCs) are important precursors of secondary air pollutants. However, knowledge of the vertical characteristics of OVOCs in the lower troposphere is lacking. Pairs of OVOCs samples were simultaneously collected via 2,4-dinitrophenylhydrazine (DNPH) near the ground and in the upper boundary layer (at 500 m in winter and 600 m in summer) with a tethered balloon in Shijiazhuang in January and June 2019. The samples were analyzed via high-performance liquid chromatography (HPLC), and 26 vertical profiles of 13 OVOCs were obtained in this study. In winter, the average concentrations of the total OVOCs (TOVOCs) in the upper boundary layer and near the ground were 7.9 ± 4.1 ppbv and 5.5 ± 2.8 ppbv, respectively; while in summer, the average concentrations were 7.1 ± 3.5 ppbv and 6.5 ± 2.7 ppbv, respectively. Acetone, formaldehyde and acetaldehyde were the three main components accounting for more than 80% of the TOVOCs. Significant vertical differences were observed before sunrise in winter and in the afternoon in summer. The TOVOCs concentration in the residual layer (8.4 ± 3.6 ppbv) was higher than that near the ground (6.0 ± 2.5 ppbv), while in the summer afternoon, the concentration in the upper mixing layer (ML) (9.5 ± 2.2 ppbv) was higher than that near the ground (5.8 ± 3.1 ppbv). OVOCs sources were examined with a positive matrix factorization (PMF) model. In winter, the small-molecule carbonyls (SMCs) in the upper boundary layer are mainly derived from secondary + long-lived species (68.4%) because volatile organic compounds at high concentrations were oxidized into OVOCs. In summer, the SMCs in the upper ML were mainly affected by elevated industrial point source emissions (42.9%). These data indicate that vertical gradient observations of SMCs are an important supplement to advance current air pollution research.
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Affiliation(s)
- Yiming Wang
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry (LAPC), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yinghong Wang
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry (LAPC), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China; University of Chinese Academy of Sciences, Beijing 100049, China.
| | - Guiqian Tang
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry (LAPC), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China; Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; University of Chinese Academy of Sciences, Beijing 100049, China.
| | - Yang Yang
- Weather Modification Office of Hebei Province, Shijiazhuang 050021, China
| | - Xingru Li
- Capital Normal University, Beijing, 100048, China
| | - Dan Yao
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry (LAPC), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China; Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Shuang Wu
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry (LAPC), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
| | - Yanyu Kang
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry (LAPC), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China; Anhui University, Hefei 230601, China
| | - Meng Wang
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry (LAPC), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China; Key Laboratory for Semi-Arid Climate Change of the Ministry of Education, College of Atmospheric Sciences, Lanzhou University, Lanzhou 730000, China
| | - Yuesi Wang
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry (LAPC), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China; Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; University of Chinese Academy of Sciences, Beijing 100049, China
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Variations in Nocturnal Residual Layer Height and Its Effects on Surface PM2.5 over Wuhan, China. REMOTE SENSING 2021. [DOI: 10.3390/rs13224717] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
Abstract
Large amounts of aerosols remain in the residual layer (RL) after sunset, which may be the source of the next day’s pollutants. However, the characteristics of the nocturnal residual layer height (RLH) and its effect on urban environment pollution are unknown. In this study, the characteristics of the RLH and its effect on fine particles with diameters <2.5 μm (PM2.5) were investigated using lidar data from January 2017 to December 2019. The results show that the RLH is highest in summer (1.55 ± 0.55 km), followed by spring (1.40 ± 0.58 km) and autumn (1.26 ± 0.47 km), and is lowest in winter (1.11 ± 0.44 km). The effect of surface meteorological factors on the RLH were also studied. The correlation coefficients (R) between the RLH and the temperature, relative humidity, wind speed, and pressure were 0.38, −0.18, 0.15, and −0.36, respectively. The results indicate that the surface meteorological parameters exhibit a slight correlation with the RLH, but the high relative humidity was accompanied by a low RLH and high PM2.5 concentrations. Finally, the influence of the RLH on PM2.5 was discussed under different aerosol-loading periods. The aerosol optical depth (AOD) was employed to represent the total amount of pollutants. The results show that the RLH has an effect on PM2.5 when the AOD is small but has almost no effect on PM2.5 when the AOD is high. In addition, the R between the nighttime mean RLH and the following daytime PM2.5 at low AOD is −0.49, suggesting that the RLH may affect the following daytime surface PM2.5. The results of this study have a guiding significance for understanding the interaction between aerosols and the boundary layer.
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He G, Deng T, Wu D, Wu C, Huang X, Li Z, Yin C, Zou Y, Song L, Ouyang S, Tao L, Zhang X. Characteristics of boundary layer ozone and its effect on surface ozone concentration in Shenzhen, China: A case study. THE SCIENCE OF THE TOTAL ENVIRONMENT 2021; 791:148044. [PMID: 34118664 DOI: 10.1016/j.scitotenv.2021.148044] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/12/2021] [Revised: 05/09/2021] [Accepted: 05/21/2021] [Indexed: 06/12/2023]
Abstract
In late September 2019, the longest and most extensive ozone (O3) pollution process occurred at Pearl River Delta. Base on the observational data, surface-level O3, vertical distribution characteristics boundary layer O3 as well as its effect on surface-level O3 are thoroughly analyzed. The O3 lidar results showed similar vertical O3 profiles both in pollution episodes and clean periods, from which a high O3 concentration layer between 300 and 500 m and a sub-high O3 concentration layer between 1300 and 1700 m (near the top of the mixing layer) can be found. Besides, the downward O3 transport paths from the high/sub-high O3 concentration layers could be observed along with the boundary layer evolution: At nighttime, large amounts of O3 were effectively stored into the residual layer (RL). Due to the upward development of Mixing layer (ML) in early morning, atmospheric vertical mixing carried the O3 inside the RL down to the surface, which led to a rapid increase in the surface-level O3. The sub-high O3 layer began the downward mixing at noon, and became well-mixed after the boundary layer was fully developed in the afternoon, by which the near surface O3 pollution deteriorated again. Further analysis of the heavy O3 pollution episodes show that, the high O3 concentration inside the RL contributed 54% ± 6% of the surface-level O3 at 9:00 LT and the average contribution of O3 in the sub-high concentration layer to the surface-level O3 at 14:00 LT was 26% ± 9%. Based on the quantitative analysis of the observational data, this paper focus to reveal the importance of the contribution of O3 inside the RL and near the top of the ML to the surface O3.
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Affiliation(s)
- Guowen He
- Guangdong Engineering Research Center for Online Atmospheric Pollution Source Appointment Mass Spectrometry System, Institute of Mass Spectrometer and Atmospheric Environment, Jinan University, Guangzhou 510632, 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
- Guangdong Engineering Research Center for Online Atmospheric Pollution Source Appointment Mass Spectrometry System, Institute of Mass Spectrometer and Atmospheric Environment, Jinan University, Guangzhou 510632, China; Institute of Tropical and Marine Meteorology/Guangdong Provincial Key Laboratory of Regional Numerical Weather Prediction, China Meteorological Administration, Guangzhou 510640, China.
| | - Cheng Wu
- Guangdong Engineering Research Center for Online Atmospheric Pollution Source Appointment Mass Spectrometry System, Institute of Mass Spectrometer and Atmospheric Environment, Jinan University, Guangzhou 510632, China
| | - Xiaofeng Huang
- Key Laboratory for Urban Habitat Environmental Science and Technology, School of Environment and Energy, Peking University Shenzhen Graduate School, Shenzhen 518055, China
| | - Zhenning Li
- Institute of Environment, Energy and Sustainability, The Chinese University of Hong Kong, Hong Kong 999077, China
| | - Changqin Yin
- Institute of Tropical and Marine Meteorology/Guangdong Provincial Key Laboratory of Regional Numerical Weather Prediction, China Meteorological Administration, Guangzhou 510640, China
| | - Yu Zou
- Institute of Tropical and Marine Meteorology/Guangdong Provincial Key Laboratory of Regional Numerical Weather Prediction, China Meteorological Administration, Guangzhou 510640, China
| | - Lang Song
- Guangdong Provincial Academy of Environmental Science, Guangzhou 510045, China
| | - Shanshan Ouyang
- Institute for Environmental and Climate Research, Jinan University, Guangzhou 511443, China
| | - Liping Tao
- Guangdong Engineering Research Center for Online Atmospheric Pollution Source Appointment Mass Spectrometry System, Institute of Mass Spectrometer and Atmospheric Environment, Jinan University, Guangzhou 510632, China
| | - Xue Zhang
- Guangdong Engineering Research Center for Online Atmospheric Pollution Source Appointment Mass Spectrometry System, Institute of Mass Spectrometer and Atmospheric Environment, Jinan University, Guangzhou 510632, China
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8
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Tang G, Liu Y, Huang X, Wang Y, Hu B, Zhang Y, Song T, Li X, Wu S, Li Q, Kang Y, Zhu Z, Wang M, Wang Y, Li T, Li X, Wang Y. Aggravated ozone pollution in the strong free convection boundary layer. THE SCIENCE OF THE TOTAL ENVIRONMENT 2021; 788:147740. [PMID: 34134376 DOI: 10.1016/j.scitotenv.2021.147740] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/22/2021] [Revised: 05/05/2021] [Accepted: 05/09/2021] [Indexed: 06/12/2023]
Abstract
Clarifying the relationship between meteorological factors and ozone can provide scientific support for ozone pollution prediction, but the effects of boundary layer meteorology, especially boundary layer height and turbulence, on ozone pollution are rarely studied. Here, ozone and its related meteorological factors were observed in summer in Shijiazhuang, a city with the most serious ozone pollution on the North China Plain. The forced and free convection boundary layers were classified using ground remote observations. After eliminating the forced convection condition, strong free convection conditions, exhibiting a high boundary layer height, high wind speed, strong turbulence and large-scale free convection velocity, were found to be beneficial for the aggravation of ozone pollution. Combined with the ozone profile detected by a tethered balloon, the ozone chemical budget was calculated using the differences in the column ozone concentrations between the morning and afternoon, and the results confirmed the impact of free convection intensity on ozone pollution. The change in ozone sensitivity from VOCs sensitivity to NOx sensitivity driven by strong free convection was the main reason for the deterioration of ozone pollution. This study clarified the impact of boundary layer meteorology on ozone and its sensitivity and has important practical significance for ozone pollution prevention and early warning.
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Affiliation(s)
- Guiqian Tang
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China; Center for Excellence in Urban Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yuting Liu
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Xiao Huang
- HuiHua College of Hebei Normal University, Shijiazhuang 050091, China
| | - Yinghong Wang
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China.
| | - Bo Hu
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
| | - Yucui Zhang
- Key Laboratory of Agricultural Water Resources, Center for Agricultural Resources Research, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Shijiazhuang 050021, China
| | - Tao Song
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
| | - Xiaolan Li
- Institute of Atmospheric Environment, China Meteorological Administration, Shenyang, Liaoning 110166, China
| | - Shuang Wu
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
| | - Qihua Li
- Institutes of Physical Science and Information Technology, Anhui University, Hefei 230601, China
| | - Yanyu Kang
- Institutes of Physical Science and Information Technology, Anhui University, Hefei 230601, China
| | - Zhenyu Zhu
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
| | - Meng Wang
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
| | - Yiming Wang
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Tingting Li
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
| | - Xin Li
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
| | - Yuesi Wang
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China; Center for Excellence in Urban Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; University of Chinese Academy of Sciences, Beijing 100049, China.
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