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Wang J, Dong J, Li R, Zhang X, Xu Q, Song X. Assessing anthropogenic contributions and uncovering inter-regional periodic patterns of ground ozone with high-resolution predictions in 2015-2019 across China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2025; 977:179360. [PMID: 40222250 DOI: 10.1016/j.scitotenv.2025.179360] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/10/2024] [Revised: 03/28/2025] [Accepted: 04/04/2025] [Indexed: 04/15/2025]
Abstract
Owing to the strong spatiotemporal variability of ozone and the complexity of its photochemical reactions, it is urgent but difficult to accurately predict the high-resolution distribution of ozone and quantify the effects of anthropogenic drivers. In this study, we employed a random forest model to predict maximum daily 8-hour average ozone concentrations (MDA8 O₃) at a high resolution of 1 km × 1 km across China from 2015 to 2019. The model's performance was validated using three approaches: sample-based, site-based, and year-based, yielding R-squared values of 0.87, 0.85, and 0.81, respectively, and demonstrating superior accuracy compared to previous studies. Our predictions revealed that Central China experienced the most rapid increase in ozone, with some areas exceeding 6 μg/m3/year, surpassing even the economically developed regions of Eastern China, as identified by Sen's slope and the seasonal Mann-Kendall test. Through high-resolution predictions, we uncovered stable inter-regional periodic patterns of high ozone concentrations across four seasons. By controlling for meteorological variables, we also quantified anthropogenic contributions to the changes in ground-level ozone in 2015-2019, which ranged from -12.18 to 43.71 μg/m3 annually, thereby driving the rapid increase in ozone concentrations over Central China. The high-resolution ozone datasets and the identification of inter-regional periodic patterns offer valuable insights for large-scale ozone studies and provide cost-effective strategies for ozone monitoring and control.
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Affiliation(s)
- Junshun Wang
- College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China; State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
| | - Jin Dong
- Information Center of Ministry of Natural Resources, Beijing 100812, China
| | - Runkui Li
- College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China; State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China.
| | - Xiaoping Zhang
- College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Qun Xu
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing 100005, China; Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing 100005, China
| | - Xianfeng Song
- College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China; State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
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Xie Q, Chen W, Yuan B, Huangfu Y, He X, Wu L, Liu M, You Y, Shao M, Wang X. Significant but Overlooked: The Role of Anthropogenic Monoterpenes in Ozone Formation in a Chinese Megacity. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2025. [PMID: 40226908 DOI: 10.1021/acs.est.5c00001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/15/2025]
Abstract
Recent observations have revealed unexpectedly high concentrations of monoterpenes (MT) in urban areas, frequently surpassing those in forested regions. These findings suggest significant anthropogenic contributions (MTANT), challenging the traditional view that MT emissions are predominantly natural (MTNAT) in current inventories. This oversight likely results in a substantial underestimation of MT's role in urban ozone (O3) production. Therefore, we developed a novel approach to generate a gridded emission inventory (EI) of MTANT, integrating flux measurements of MT and carbon monoxide (CO). Results show that MTANT emission rate in Beijing core areas exceeds MTNAT by a factor of 1.83, with household volatile chemical products (VCPs) contributing 56% of total MTANT emissions. Incorporating MTANT emissions into the Weather Research and Forecasting Model coupled with Chemistry (WRF-Chem) model significantly improved the simulation of diurnal MT variations (correlation coefficient, r = 0.985) and reduced the normalized mean bias (NMB) in surface MT concentration predictions by 53%. Notably, the combined effects of anthropogenic and biogenic MT emissions increased summertime maximum daily 8-h average (MDA8) O3 levels by 12.8 ppb in Beijing core areas, with MT from household VCPs (MTVCP) accounting for 62% of the MTANT-driven O3 increase. This study provides a robust quantitative foundation for assessing the impact of anthropogenic MT emissions on urban air quality and highlights the urgent need for targeted regulatory measures to mitigate their growing contribution to O3 pollution.
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Affiliation(s)
- Qianqian Xie
- College of Environment and Climate, Institute for Environmental and Climate Research, Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Jinan University, Guangzhou 510632, China
| | - Weihua Chen
- College of Environment and Climate, Institute for Environmental and Climate Research, Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Jinan University, Guangzhou 510632, China
| | - Bin Yuan
- College of Environment and Climate, Institute for Environmental and Climate Research, Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Jinan University, Guangzhou 510632, China
| | - Yibo Huangfu
- College of Environment and Climate, Institute for Environmental and Climate Research, Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Jinan University, Guangzhou 510632, China
| | - Xianjun He
- College of Environment and Climate, Institute for Environmental and Climate Research, Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Jinan University, Guangzhou 510632, China
| | - Liqing Wu
- College of Ocean and Meteorology, Guangdong Ocean University, Zhanjiang 524000, China
| | - Mingkai Liu
- State Key Laboratory of Organic Geochemistry, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, China
- Guangdong Provincial Key Laboratory of Environmental Protection and Resources Utilization, Chinese Academy of Science, Guangzhou 510640 China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yingchang You
- College of Environment and Climate, Institute for Environmental and Climate Research, Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Jinan University, Guangzhou 510632, China
| | - Min Shao
- College of Environment and Climate, Institute for Environmental and Climate Research, Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Jinan University, Guangzhou 510632, China
| | - Xuemei Wang
- College of Environment and Climate, Institute for Environmental and Climate Research, Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Jinan University, Guangzhou 510632, China
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Xu L, Wang B, Wang Y, Zhang H, Xu D, Zhao Y, Zhao K. Characterization and Source Apportionment Analysis of PM 2.5 and Ozone Pollution over Fenwei Plain, China: Insights from PM 2.5 Component and VOC Observations. TOXICS 2025; 13:123. [PMID: 39997938 PMCID: PMC11862001 DOI: 10.3390/toxics13020123] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/03/2025] [Revised: 01/30/2025] [Accepted: 01/30/2025] [Indexed: 02/26/2025]
Abstract
PM2.5 and volatile organic compounds (VOCs) have been identified as the primary air pollutants affecting the Fenwei Plain (FWP), necessitating urgent measures to improve its air quality. To gain a deeper understanding of the formation mechanisms of these pollutants, this study employed various methods such as HYSPLIT, PCT, and PMF for analysis. Our results indicate that the FWP is primarily impacted by PM2.5 from the southern Shaanxi air mass and the northwestern air mass during winter. In contrast, during summer, it is mainly influenced by O3 originating from the southern air mass. Specifically, high-pressure fronts are the dominant weather pattern affecting PM2.5 pollution in the FWP, while high-pressure backs predominately O3 pollution. Regarding the sources of PM2.5, secondary nitrates, vehicle exhausts, and secondary sulfates are major contributors. As for volatile organic compounds, liquefied petroleum gas sources, vehicle exhausts, solvent usage, and industrial emissions are the primary sources. This study holds crucial scientific significance in enhancing the regional joint prevention and control mechanism for PM2.5 and O3 pollution, and it provides scientific support for formulating effective strategies for air pollution prevention and control.
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Affiliation(s)
- Litian Xu
- Yunnan Key Laboratory of Meteorological Disasters and Climate Resources in the Greater Mekong Subregion, Yunnan University, Kunming 650091, China
| | - Bo Wang
- Xianyang Environmental Monitoring Station, Xianyang 712000, China
| | - Ying Wang
- Xianyang Meteorological Bureau, Xianyang 712000, China
| | - Huipeng Zhang
- Xianyang Environmental Monitoring Station, Xianyang 712000, China
| | - Danni Xu
- Yunnan Key Laboratory of Meteorological Disasters and Climate Resources in the Greater Mekong Subregion, Yunnan University, Kunming 650091, China
- Xianyang Environmental Monitoring Station, Xianyang 712000, China
- Information School, Yunnan University of Finance and Economics, Kunming 650221, China
| | - Yibing Zhao
- Xianyang Meteorological Bureau, Xianyang 712000, China
| | - Kaihui Zhao
- Yunnan Key Laboratory of Meteorological Disasters and Climate Resources in the Greater Mekong Subregion, Yunnan University, Kunming 650091, China
- Xianyang Environmental Monitoring Station, Xianyang 712000, China
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4
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Liu N, He G, Wang H, He C, Wang H, Liu C, Wang Y, Wang H, Li L, Lu X, Fan S. Rising frequency of ozone-favorable synoptic weather patterns contributes to 2015-2022 ozone increase in Guangzhou. J Environ Sci (China) 2025; 148:502-514. [PMID: 39095184 DOI: 10.1016/j.jes.2023.09.024] [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: 06/29/2023] [Revised: 09/20/2023] [Accepted: 09/20/2023] [Indexed: 08/04/2024]
Abstract
Objective weather classification methods have been extensively applied to identify dominant ozone-favorable synoptic weather patterns (SWPs), however, the consistency of different classification methods is rarely examined. In this study, we apply two widely-used objective methods, the self-organizing map (SOM) and K-means clustering analysis, to derive ozone-favorable SWPs at four Chinese megacities in 2015-2022. We find that the two algorithms are largely consistent in recognizing dominant ozone-favorable SWPs for four Chinese megacities. In the case of classifying six SWPs, the derived circulation fields are highly similar with a spatial correlation of 0.99 between the two methods, and the difference in the mean frequency of each SWP is less than 7%. The six dominant ozone-favorable SWPs in Guangzhou are all characterized by anomaly higher radiation and temperature, lower cloud cover, relative humidity, and wind speed, and stronger subsidence compared to climatology mean. We find that during 2015-2022, the occurrence of ozone-favorable SWPs days increases significantly at a rate of 3.2 day/year, faster than the increases in the ozone exceedance days (3.0 day/year). The interannual variability between the occurrence of ozone-favorable SWPs and ozone exceedance days are generally consistent with a temporal correlation coefficient of 0.6. In particular, the significant increase in ozone-favorable SWPs in 2022, especially the Subtropical High type which typically occurs in September, is consistent with a long-lasting ozone pollution episode in Guangzhou during September 2022. Our results thus reveal that enhanced frequency of ozone-favorable SWPs plays an important role in the observed 2015-2022 ozone increase in Guangzhou.
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Affiliation(s)
- Nanxi Liu
- School of Atmospheric Sciences, Sun Yat-sen University, and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), 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 (Sun Yat-sen University), Ministry of Education, Zhuhai 519082, China
| | - Guowen He
- School of Atmospheric Sciences, Sun Yat-sen University, and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), 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 (Sun Yat-sen University), Ministry of Education, Zhuhai 519082, China
| | - Haolin Wang
- School of Atmospheric Sciences, Sun Yat-sen University, and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), 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 (Sun Yat-sen University), Ministry of Education, Zhuhai 519082, China
| | - Cheng He
- School of Atmospheric Sciences, Sun Yat-sen University, and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), 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 (Sun Yat-sen University), Ministry of Education, Zhuhai 519082, China
| | - Haofan Wang
- School of Atmospheric Sciences, Sun Yat-sen University, and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), 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 (Sun Yat-sen University), Ministry of Education, Zhuhai 519082, China
| | - Chenxi Liu
- School of Atmospheric Sciences, Sun Yat-sen University, and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), 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 (Sun Yat-sen University), Ministry of Education, Zhuhai 519082, China
| | - Yiming Wang
- School of Atmospheric Sciences, Sun Yat-sen University, and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), 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 (Sun Yat-sen University), Ministry of Education, Zhuhai 519082, China
| | - Haichao Wang
- School of Atmospheric Sciences, Sun Yat-sen University, and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), 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 (Sun Yat-sen University), Ministry of Education, Zhuhai 519082, China
| | - Lei Li
- School of Atmospheric Sciences, Sun Yat-sen University, and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), 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 (Sun Yat-sen University), Ministry of Education, Zhuhai 519082, China
| | - Xiao Lu
- School of Atmospheric Sciences, Sun Yat-sen University, and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), 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 (Sun Yat-sen University), Ministry of Education, Zhuhai 519082, China.
| | - Shaojia Fan
- School of Atmospheric Sciences, Sun Yat-sen University, and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), 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 (Sun Yat-sen University), Ministry of Education, Zhuhai 519082, China.
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Banerjee B, Kundu S, Kanchan R, Mohanta A. RETRACTED ARTICLE: Examining the relationship between atmospheric pollutants and meteorological factors in Asansol city, West Bengal, India, using statistical modelling. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2025; 32:6286. [PMID: 38761262 DOI: 10.1007/s11356-024-33608-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/15/2024] [Accepted: 05/04/2024] [Indexed: 05/20/2024]
Affiliation(s)
- Biplab Banerjee
- Department of Geography, Faculty of Science, The MS University Baroda, Vadodara, India, 390002.
| | - Sudipta Kundu
- Department of Geography, Faculty of Science, CSJM University of Kanpur, Kanpur, India
| | - Rolee Kanchan
- Department of Geography, Faculty of Science, The MS University Baroda, Vadodara, India, 390002
| | - Agradeep Mohanta
- Department of Botany, Faculty of Science, The MS University Baroda, Vadodara, 390002, India
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Li M, Yang Y, Wang H, Wang P, Liao H. Unique impacts of strong and westward-extended western Pacific subtropical high on ozone pollution over eastern China. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2024; 358:124515. [PMID: 38996993 DOI: 10.1016/j.envpol.2024.124515] [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: 05/02/2024] [Revised: 06/13/2024] [Accepted: 07/07/2024] [Indexed: 07/14/2024]
Abstract
As a subtropical anticyclonic high-pressure system that typically forms over the northwestern Pacific Ocean in summer, the Western Pacific subtropical high (WPSH) affects meteorological conditions and ozone pollution in China. The relationship between maximum daily 8-h average ozone (MDA8 O3) concentrations and the extremely strong and westward-extended WPSH occurred in 2022 is investigated using observations, reanalysis data and atmospheric chemistry model simulations. During July-August 2022, a significant positive relationship existed between the intensity of the WPSH and MDA8 O3 over southern China, with a correlation coefficient of +0.44, but the correlation is negative (-0.40) in northern China. During the strong WPSH days, MDA8 O3 increased by 16.5 μg m-3 (16.4% relative to July-August average) over southern China and decreased by 19.0 μg m-3 (14.5%) in northern China compared to the weak WPSH days. The unique dipole pattern in the relationship between ozone levels and the WPSH in 2022 exhibited a contrast to that during 2015-2021. The difference is primarily due to the extremely strong WPSH intensity and its unusual westward expansion in 2022. In this case, an anomalous anticyclone at 500 hPa dominates over southern China, which creates conditions conducive for ozone formation and accumulation. The anticyclone weakened horizontal winds and reduced the dispersion of ozone, alongside a high temperature and low relative humidity, which favored the chemical production of ozone. In contrast, abnormal northerly winds enhanced ozone diffusion in northern China and the low temperature reduced ozone chemical production. This study reveals the mechanism for the significant impact of strong and westward-extended WPSH on ozone concentrations over China, emphasizing the role of the WPSH location in modulating meteorology and ozone levels.
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Affiliation(s)
- Mengyun Li
- Joint International Research Laboratory of Climate and Environment Change, Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, Nanjing, Jiangsu, China
| | - Yang Yang
- Joint International Research Laboratory of Climate and Environment Change, Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, Nanjing, Jiangsu, China.
| | - Hailong Wang
- Atmospheric, Climate, and Earth Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA
| | - Pinya Wang
- Joint International Research Laboratory of Climate and Environment Change, Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, Nanjing, Jiangsu, China
| | - Hong Liao
- Joint International Research Laboratory of Climate and Environment Change, Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, Nanjing, Jiangsu, China
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Ma J, Yan Y, Kong S, Bai Y, Zhou Y, Gu X, Song A, Tong Z. Effectiveness of inter-regional collaborative emission reduction for ozone mitigation under local-dominated and transport-affected synoptic patterns. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2024; 31:51774-51789. [PMID: 39122971 DOI: 10.1007/s11356-024-34656-1] [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: 10/25/2023] [Accepted: 08/03/2024] [Indexed: 08/12/2024]
Abstract
In recent years, the concentrations of ozone and the pollution days with ozone as the primary pollutant have been increasing year by year. The sources of regional ozone mainly depend on local photochemical formation and transboundary transport. The latter is influenced by different weather circulations. How to effectively reduce the inter-regional emission to control ozone pollution under different atmospheric circulation is rarely reported. In this study, we classify the atmospheric circulation of ozone pollution days from 2014 to 2019 over Central China based on the Lamb-Jenkinson method and the global analysis data of the fifth-generation European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis (ERA5) operation. The effectiveness of emission control to alleviate ozone pollution under different atmospheric circulation is simulated by the WRF-Chem model. Among the 26 types of circulation patterns, 9 types of pollution days account for 79.5% of the total pollution days and further classified into 5 types. The local types (A and C type) are characterized by low surface wind speed and stable weather conditions over Central China due to a high-pressure system or a southwest vortex low-pressure system, blocking the diffusion of pollutants. Sensitivity simulations of A-type show that this heavy pollution process is mainly contributed by local emission sources. Removing the anthropogenic emission of pollutants over Central China would reduce the ozone concentration by 39.1%. The other three circulation patterns show pollution of transport characteristics affected by easterly, northerly, or southerly winds (N-EC, EC, S-EC-type). Under the EC-type, removing anthropogenic pollutants of East China would reduce the ozone concentration by 22.7% in Central China.
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Affiliation(s)
- Jing Ma
- Department of Atmospheric Sciences, School of Environmental Studies, China University of Geosciences, Wuhan, 430074, China
| | - Yingying Yan
- Department of Atmospheric Sciences, School of Environmental Studies, China University of Geosciences, Wuhan, 430074, China.
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China.
| | - Shaofei Kong
- Department of Atmospheric Sciences, School of Environmental Studies, China University of Geosciences, Wuhan, 430074, China
- Department of Environmental Science and Engineering, School of Environmental Studies, China University of Geosciences, Wuhan, 430074, China
| | - Yongqing Bai
- Hubei Key Laboratory for Heavy Rain Monitoring and Warning Research, Institute of Heavy Rain, China Meteorological Administration, Wuhan, 430205, China
| | - Yue Zhou
- Hubei Key Laboratory for Heavy Rain Monitoring and Warning Research, Institute of Heavy Rain, China Meteorological Administration, Wuhan, 430205, China
| | - Xihui Gu
- Department of Atmospheric Sciences, School of Environmental Studies, China University of Geosciences, Wuhan, 430074, China
| | - Aili Song
- Department of Atmospheric Sciences, School of Environmental Studies, China University of Geosciences, Wuhan, 430074, China
| | - Zhixuan Tong
- Department of Atmospheric Sciences, School of Environmental Studies, China University of Geosciences, Wuhan, 430074, China
- Key Laboratory of Atmospheric Chemistry, China Meteorological Administration, Beijing, 100081, China
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Zhang X, Sun J, Lin W, Xu W, Zhang G, Wu Y, Dai X, Zhao J, Yu D, Xu X. Long-term variations in surface ozone at the Longfengshan Regional Atmosphere Background Station in Northeast China and related influencing factors. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2024; 348:123748. [PMID: 38460592 DOI: 10.1016/j.envpol.2024.123748] [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: 12/13/2023] [Revised: 02/25/2024] [Accepted: 03/06/2024] [Indexed: 03/11/2024]
Abstract
Surface ozone (O3) is a crucial air pollutant that affects air quality, human health, agricultural production, and climate change. Studies on long-term O3 variations and their influencing factors are essential for understanding O3 pollution and its impact. Here, we conducted an analysis of long-term variations in O3 during 2006-2022 at the Longfengshan Regional Atmosphere Background Station (LFS; 44.44°N, 127.36°E, 330.5 m a.s.l.) situated on the northeastern edge of the Northeast China Plains. The maximum daily 8-h average (MDA8) O3 fluctuated substantially, with the annual MDA8 decreasing significantly during 2006-2015 (-0.62 ppb yr-1, p < 0.05), jumping during 2015-2016 and increasing clearly during 2020-2022. Step multiple linear regression models for MDA8 were obtained using meteorological variables, to decompose anthropogenic and meteorological contributions to O3 variations. Anthropogenic activities acted as the primary drivers of the long-term trends of MDA8 O3, contributing 73% of annual MDA8 O3 variability, whereas meteorology played less important roles (27%). Elevated O3 at LFS were primarily associated with airflows originating from the North China Plain, Northeast China Plain, and coastal areas of North China, primarily occurring during the warm months (May-October). Based on satellite products of NO2 and HCHO columns, the O3 photochemical regimes over LFS revealed NOx-limited throughout the period. NO2 increased first, reaching peak in 2011, followed by substantial decrease; while HCHO exhibited significant increase, contributing to decreasing trend in MDA8 O3 during 2006-2015. The plateauing NO2 and decreasing HCHO may contribute to the increase in MDA8 O3 in 2016. Subsequently, both NO2 and HCHO exhibited notable fluctuations, leading to significant changes in O3. The study results fill the gap in the understanding of long-term O3 trends in high-latitude areas in the Northeast China Plain and offer valuable insights for assessing the impact of O3 on crop yields, forest productivity, and climate change.
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Affiliation(s)
- Xiaoyi Zhang
- State Key Laboratory of Severe Weather, Key Laboratory for Atmospheric Chemistry, Institute of Atmospheric Composition, Chinese Academy of Meteorological Sciences, Beijing, 100081, China; Department of Atmospheric and Oceanic Sciences, Fudan University, Shanghai, 200438, China
| | - Jingmin Sun
- Longfengshan Regional Atmosphere Background Station, China Meteorological Administration (CMA), Heilongjiang, 150200, China
| | - Weili Lin
- Key Laboratory of Ecology and Environment in Minority Areas (Minzu University of China), National Ethnic Affairs Commission, Beijing, 100081, China
| | - Wanyun Xu
- State Key Laboratory of Severe Weather, Key Laboratory for Atmospheric Chemistry, Institute of Atmospheric Composition, Chinese Academy of Meteorological Sciences, Beijing, 100081, China
| | - Gen Zhang
- State Key Laboratory of Severe Weather, Key Laboratory for Atmospheric Chemistry, Institute of Atmospheric Composition, Chinese Academy of Meteorological Sciences, Beijing, 100081, China
| | - Yanling Wu
- Longfengshan Regional Atmosphere Background Station, China Meteorological Administration (CMA), Heilongjiang, 150200, China
| | - Xin Dai
- Longfengshan Regional Atmosphere Background Station, China Meteorological Administration (CMA), Heilongjiang, 150200, China
| | - Jinrong Zhao
- Longfengshan Regional Atmosphere Background Station, China Meteorological Administration (CMA), Heilongjiang, 150200, China
| | - Dajiang Yu
- Longfengshan Regional Atmosphere Background Station, China Meteorological Administration (CMA), Heilongjiang, 150200, China.
| | - Xiaobin Xu
- State Key Laboratory of Severe Weather, Key Laboratory for Atmospheric Chemistry, Institute of Atmospheric Composition, Chinese Academy of Meteorological Sciences, Beijing, 100081, China
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9
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Shen L, Diao Y, Zhao T, Gu X, Shi SS. Meteorological influence on persistent O 3 pollution events in Wuxi in the Yangtze River Delta, China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 917:170484. [PMID: 38296078 DOI: 10.1016/j.scitotenv.2024.170484] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/16/2023] [Revised: 01/03/2024] [Accepted: 01/24/2024] [Indexed: 02/03/2024]
Abstract
The number of O3 pollution days indicates an overall increasing trend over 2014-2021 in Wuxi in the Yangtze River Delta, with the pollution concentrations of MDA8-O3 between 186 and 200 μg·m-3. Specifically, a total of 62 POPEs (persistent O3 pollution events), defined as episodes with 3 or more continuous O3 pollution days, were observed for the 8 years. Using a multi-linear regression model, we find that the meteorology can explain approximately 56.5 % of the O3 variations for the 8 years in Wuxi, with temperature being the most crucial meteorological factor, followed by relative humidity (RH) and wind speeds. High temperature, low RH, low wind speeds and downward airflows significantly correlate with POPE-O3 changes. Three types of synoptic circulations are further identified during the POPEs from 2014 to 2021 by the T-mode (T-PCA) classification method. The primary circulation patterns governing the interannual changes of POPEs are characterized by the largest positive anomalies of temperature and planetary boundary layer (PBL) height; moreover, a distinct vertical mixing process is observed with uplifting airflows in the convective PBL during the afternoon and sinking airflows in the stable PBL at night, which is incredibly conducive to the downward transport of O3 after its upward delivery during daytime and substantially contributes to midnight O3 at the surface. The other two circulation types are associated with uniform descending flows in the PBL; as a result, surface O3 accumulates only near the ground and decreases significantly at night due to the titration effect. This study systematically highlights the influence of critical meteorological factors regulated by different synoptic circulations on the POPE in Wuxi, which provides a scientific basis for pollution control and prediction.
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Affiliation(s)
- Lijuan Shen
- School of Atmosphere and Remote Sensing, Wuxi University, Wuxi 214105, China.
| | - Yiwei Diao
- School of Atmosphere and Remote Sensing, Wuxi University, Wuxi 214105, China
| | - Tianliang Zhao
- Key Laboratory for Aerosol-Cloud-Precipitation of the China Meteorological Administration, Nanjing University of Information Science & Technology, Nanjing 210044, China
| | - Xuesong Gu
- Wuxi Environmental Monitoring Center Station, Wuxi 214023, China
| | - Shuang Shuang Shi
- School of Atmosphere and Remote Sensing, Wuxi University, Wuxi 214105, China
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Mao YH, Shang Y, Liao H, Cao H, Qu Z, Henze DK. Sensitivities of ozone to its precursors during heavy ozone pollution events in the Yangtze River Delta using the adjoint method. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 925:171585. [PMID: 38462008 DOI: 10.1016/j.scitotenv.2024.171585] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/07/2023] [Revised: 03/06/2024] [Accepted: 03/06/2024] [Indexed: 03/12/2024]
Abstract
Although the concentrations of five basic ambient air pollutants in the Yangtze River Delta (YRD) have been reduced since the implementation of the "Air Pollution Prevention and Control Action Plan" in 2013, the ozone concentrations still increase. In order to explore the causes of ozone pollution in YRD, we use the GEOS-Chem and its adjoint model to study the sensitivities of ozone to its precursor emissions from different source regions and emission sectors during heavy ozone pollution events under typical circulation patterns. The Multi-resolution Emission Inventory for China (MEIC) of Tsinghua University and 0.25° × 0.3125° nested grids are adopted in the model. By using the T-mode principal component analysis (T-PCA), the circulation patterns of heavy ozone pollution days (observed MDA8 O3 concentrations ≥160 μg m-3) in Nanjing located in the center area of YRD from 2013 to 2019 are divided into four types, with the main features of Siberian Low, Lake Balkhash High, Northeast China Low, Yellow Sea High, and southeast wind at the surface. The adjoint results show that the contributions of emissions emitted from Jiangsu and Zhejiang are the largest to heavy ozone pollution in Nanjing. The 10 % reduction of anthropogenic NOx and NMVOCs emissions in Jiangsu, Zhejiang and Shanghai could reduce the ozone concentrations in Nanjing by up to 3.40 μg m-3 and 0.96 μg m-3, respectively. However, the reduction of local NMVOCs emissions has little effect on ozone concentrations in Nanjing, and the reduction of local NOx emissions would even increase ozone pollution. For different emissions sectors, industry emissions account for 31 %-74 % of ozone pollution in Nanjing, followed by transportation emissions (18 %-49 %). This study could provide the scientific basis for forecasting ozone pollution events and formulating accurate strategies of emission reduction.
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Affiliation(s)
- Yu-Hao Mao
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control/Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science and Technology (NUIST), Nanjing 210044, China; Key Laboratory of Meteorological Disaster, Ministry of Education(KLME)/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD)/International Joint Research Laboratory on Climate and Environment Change (ILCEC), NUIST, Nanjing 210044, China.
| | - Yongjie Shang
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control/Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science and Technology (NUIST), Nanjing 210044, China
| | - Hong Liao
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control/Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science and Technology (NUIST), Nanjing 210044, China; Key Laboratory of Meteorological Disaster, Ministry of Education(KLME)/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD)/International Joint Research Laboratory on Climate and Environment Change (ILCEC), NUIST, Nanjing 210044, China
| | - Hansen Cao
- Department of Mechanical Engineering, University of Colorado, Boulder, CO 80309, USA
| | - Zhen Qu
- Department of Mechanical Engineering, University of Colorado, Boulder, CO 80309, USA
| | - Daven K Henze
- Department of Mechanical Engineering, University of Colorado, Boulder, CO 80309, USA
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Zheng Y, Jiang F, Feng S, Shen Y, Liu H, Guo H, Lyu X, Jia M, Lou C. Large-scale land-sea interactions extend ozone pollution duration in coastal cities along northern China. ENVIRONMENTAL SCIENCE AND ECOTECHNOLOGY 2024; 18:100322. [PMID: 37860828 PMCID: PMC10582397 DOI: 10.1016/j.ese.2023.100322] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/15/2022] [Revised: 09/21/2023] [Accepted: 09/23/2023] [Indexed: 10/21/2023]
Abstract
Land-sea atmosphere interaction (LSAI) is one of the important processes affecting ozone (O3) pollution in coastal areas. The effects of small-scale LSAIs like sea-land breezes have been widely studied. However, it is not fully clear how and to what extent the large-scale LSAIs affect O3 pollution. Here we explored an O3 episode to illuminate the role of large-scale LSAIs in O3 pollution over the Bohai-Yellow Seas and adjacent areas through observations and model simulations. The results show that the northern Bohai Sea's coastal region, influenced by the Mongolian High, initially experienced a typical unimodal diurnal O3 variation for three days, when O3 precursors from Beijing-Tianjin-Hebei, Shandong, and Northeast China were transported to the Bohai-Yellow Seas. Photochemical reactions generated O3 within marine air masses, causing higher O3 levels over the seas than coastal regions. As the Mongolian High shifted eastward and expanded, southerly winds on its western edge transported O3-rich marine air masses toward the coast, prolonging pollution for an additional three days and weakening diurnal variations. Subsequently, emissions from the Korean Peninsula and marine shipping significantly affected O3 levels in the northern Bohai Sea (10.7% and 13.7%, respectively). Notably, Shandong's emissions played a substantial role in both phases (27.5% and 26.1%, respectively). These findings underscore the substantial impact of large-scale LSAIs driven by the Mongolian High on O3 formation and pollution duration in coastal cities. This insight helps understand and manage O3 pollution in northern Bohai Sea cities and broadly applies to temperate coastal cities worldwide.
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Affiliation(s)
- Yanhua Zheng
- Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, International Institute for Earth System Science, Nanjing University, Nanjing, 210023, China
| | - Fei Jiang
- Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, International Institute for Earth System Science, Nanjing University, Nanjing, 210023, China
- Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing, 210023, China
- Frontiers Science Center for Critical Earth Material Cycling, Nanjing University, Nanjing, 210023, China
| | - Shuzhuang Feng
- Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, International Institute for Earth System Science, Nanjing University, Nanjing, 210023, China
| | - Yang Shen
- Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, International Institute for Earth System Science, Nanjing University, Nanjing, 210023, China
| | - Huan Liu
- School of Environment, Tsinghua University, Beijing, 100084, China
| | - Hai Guo
- Air Quality Studies, Department of Civil and Environmental Engineering, Hong Kong Polytechnic University, Hong Kong, China
| | - Xiaopu Lyu
- Air Quality Studies, Department of Civil and Environmental Engineering, Hong Kong Polytechnic University, Hong Kong, China
| | - Mengwei Jia
- Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, International Institute for Earth System Science, Nanjing University, Nanjing, 210023, China
| | - Chenxi Lou
- Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, International Institute for Earth System Science, Nanjing University, Nanjing, 210023, China
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12
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Ji X, Chen G, Chen J, Xu L, Lin Z, Zhang K, Fan X, Li M, Zhang F, Wang H, Huang Z, Hong Y. Meteorological impacts on the unexpected ozone pollution in coastal cities of China during the unprecedented hot summer of 2022. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 914:170035. [PMID: 38218482 DOI: 10.1016/j.scitotenv.2024.170035] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/21/2023] [Revised: 01/04/2024] [Accepted: 01/07/2024] [Indexed: 01/15/2024]
Abstract
Surface ozone pollution under climate warming has become a serious environmental issue. In the summer of 2022, abnormal warming spread over most of the Northern Hemisphere and resulted in the abnormal increase in O3 concentrations. In this study, we focused on the coastal cities in China and investigated the O3 trends in July during 2015 to 2022. Four regions with different locations and emission levels were selected for comparison. A significant increase of O3 concentration in July 2022 were observed in the southern coastal cities (16.7-22.8 μg m-3) while the opposite characteristics were found in the northern coastal cities (decrease of 0.26-2.18 μg m-3). The results indicated various distribution patterns of the O3 concentrations responded to heat wave across China. The weakening of East Asian summer monsoon, extension of the western Pacific subtropical high, significant warming, stronger solar radiation, lower relative humidity, less rainfall and sinking motion of atmosphere in 2022 were beneficial for O3 generation and accumulation in the southern coastal areas. Meteorological changes in July 2022 could lead to an increase of 15.6 % in O3 concentrations in southern coastal cities compared to that in 2015-2021, based on the analysis of machine learning. Air temperature was the main contributor to high O3 concentrations in the coast of Fujian province, while other coastal cities depended on relative humidity. This study indicated the challenge of O3 pollution control in coastal areas under global warming, especially in extreme heat wave events.
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Affiliation(s)
- Xiaoting Ji
- Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; Fujian Key Laboratory of Atmospheric Ozone Pollution Prevention, Chinese Academy of Sciences, Xiamen 361021, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Gaojie Chen
- Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; Fujian Key Laboratory of Atmospheric Ozone Pollution Prevention, Chinese Academy of Sciences, Xiamen 361021, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Jinsheng Chen
- Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; Fujian Key Laboratory of Atmospheric Ozone Pollution Prevention, Chinese Academy of Sciences, Xiamen 361021, China.
| | - Lingling Xu
- Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; Fujian Key Laboratory of Atmospheric Ozone Pollution Prevention, Chinese Academy of Sciences, Xiamen 361021, China
| | - Ziyi Lin
- Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; Fujian Key Laboratory of Atmospheric Ozone Pollution Prevention, Chinese Academy of Sciences, Xiamen 361021, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Keran Zhang
- Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; Fujian Key Laboratory of Atmospheric Ozone Pollution Prevention, Chinese Academy of Sciences, Xiamen 361021, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Xiaolong Fan
- Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; Fujian Key Laboratory of Atmospheric Ozone Pollution Prevention, Chinese Academy of Sciences, Xiamen 361021, China
| | - Mengren Li
- Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; Fujian Key Laboratory of Atmospheric Ozone Pollution Prevention, Chinese Academy of Sciences, Xiamen 361021, China
| | - Fuwang Zhang
- Environmental Monitoring Center of Fujian, Fuzhou 350003, China
| | - Hong Wang
- Fujian Key Laboratory of Severe Weather, Key Laboratory of Straits Severe Weather China Meteorological Administration, Fuzhou 350007, China
| | - Zhi Huang
- Xiamen Institute of Environmental Science, Xiamen, China
| | - Youwei Hong
- Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; Fujian Key Laboratory of Atmospheric Ozone Pollution Prevention, Chinese Academy of Sciences, Xiamen 361021, China; University of Chinese Academy of Sciences, Beijing 100049, China.
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La Colla NS, Salvador P, Botté SE, Artíñano B. Air quality and characterization of synoptic circulation weather patterns in a South American city from Argentina. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2024; 351:119722. [PMID: 38061092 DOI: 10.1016/j.jenvman.2023.119722] [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: 06/22/2023] [Revised: 11/21/2023] [Accepted: 11/25/2023] [Indexed: 01/14/2024]
Abstract
The potential cause-effect relationship between synoptic meteorological conditions and levels of criteria air pollutants, including CO, NO2, O3, PM10, PM2.5 and SO2, in Bahia Blanca, Argentina, was assessed for the period of 2018-2019. Daily back-trajectories and global meteorological data fields were employed to characterize the primary transport paths of air masses reaching the study site, and to identify the synoptic meteorological patterns responsible for these atmospheric circulations. Time series of surface-level meteorological parameters and midday mixing layer height were collected to examine the impact of the synoptic meteorological patterns on local meteorology. Furthermore, the NAAPS global aerosol model was utilized to identify days when contributions from long-range transport processes, such as dust and/or biomass burning smoke, impacted air quality. By applying this methodology, it was determined that the air masses coming from the N, NW and W regions significantly contributed to increased mean concentrations of coarse particles in this area through long-range transport events involving dust and smoke. Indeed, the high average levels of PM10 recorded in 2018-2019 (annual mean values of 47 and 52 μg/m3, respectively) represent the main air quality concern in Bahía Blanca. Moreover, PM10, PM2.5 and NO2 emissions should be reduced in order to meet recommended air quality guidelines. On the other hand, the results from this study suggest that the sources and meteorological processes leading to the increase in the concentrations of CO and SO2 have a local-regional origin, although these air pollutants did not reach high values probably as a consequence of the strong wind speed registered in this region during any synoptic meteorological pattern.
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Affiliation(s)
- Noelia S La Colla
- Instituto Argentino de Oceanografía (IADO - CONICET/UNS), Bahía Blanca, 8000, Argentina; Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Buenos Aires, 1425, Argentina; Departamento de Biología, Bioquímica y Farmacia, Universidad Nacional del Sur (UNS), Bahía Blanca, 8000, Argentina.
| | - Pedro Salvador
- Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas (CIEMAT), Av. Complutense 40, 28040, Madrid, Spain
| | - Sandra E Botté
- Instituto Argentino de Oceanografía (IADO - CONICET/UNS), Bahía Blanca, 8000, Argentina; Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Buenos Aires, 1425, Argentina; Departamento de Biología, Bioquímica y Farmacia, Universidad Nacional del Sur (UNS), Bahía Blanca, 8000, Argentina
| | - Begoña Artíñano
- Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas (CIEMAT), Av. Complutense 40, 28040, Madrid, Spain
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Yan R, Wang H, Huang C, An J, Bai H, Wang Q, Gao Y, Jing S, Wang Y, Su H. Impact of spatial scales of control measures on the effectiveness of ozone pollution mitigation in eastern China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 906:167521. [PMID: 37793456 DOI: 10.1016/j.scitotenv.2023.167521] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/03/2023] [Revised: 09/23/2023] [Accepted: 09/29/2023] [Indexed: 10/06/2023]
Abstract
Ozone (O3) pollution is becoming the primary air pollution issue with the large decrease in fine particulate concentrations in eastern China. The development of widely recognized policies for controlling O3 pollution episodes is urgent. This study aims to provide actionable and comprehensive suggestions for O3 control policy development, with an emphasis on the precursor emission reductions. Here, we compared the impacts of different spatial scale reductions on a widespread O3 pollution episode in eastern China by a state-of-the-art regional air quality model. We find that region-scale joint control (in >30 cities) is much more effective than city-scale sporadic reduction in reducing O3 concentration. Sporadic controls only reduce the maximum daily 8-h average (MDA8) O3 by ∼1 μg/m3 in the controlled city, whereas regional controls lead to a MDA8 O3 decrease of ∼8 μg/m3 in the controlled region. In addition, the emission reduction effectiveness increased by 2.6 times from <5 cities to >30 cities. Continuous reductions have a cumulative effect on the decrease of MDA8 O3, showing the strongest effects within 24 h and diminishing after 48 h, which underscores the importance of reducing emissions 24 h prior to an episode. Moreover, the effect of control measures on MDA8 O3 varies spatially depending on the ratio of volatile organic compounds (VOCs) to nitrogen oxides (NOx) (VOCs/NOx). Both the reductions of VOC and NOx emissions have a positive effect on the decrease of MDA8 O3 in summer, but the effects of VOC reductions are 1.2 to 1.7 times higher than those of NOx reductions. The residential sector, due to its high VOCs/NOx emission ratio, exhibits the highest efficiency in the reduction of O3 concentrations. Our results highlight the importance of regional joint control and synergistic reduction of VOCs and NOx in eastern China.
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Affiliation(s)
- Rusha Yan
- School of Environmental Science and Engineering, Nanjing University of Information Science & Technology, Nanjing, China; State Environmental Protection Key Laboratory of Formation and Prevention of Urban Air Pollution Complex, Shanghai Academy of Environmental Sciences, Shanghai, China
| | - Hongli Wang
- State Environmental Protection Key Laboratory of Formation and Prevention of Urban Air Pollution Complex, Shanghai Academy of Environmental Sciences, Shanghai, China.
| | - Cheng Huang
- State Environmental Protection Key Laboratory of Formation and Prevention of Urban Air Pollution Complex, Shanghai Academy of Environmental Sciences, Shanghai, China
| | - Jingyu An
- State Environmental Protection Key Laboratory of Formation and Prevention of Urban Air Pollution Complex, Shanghai Academy of Environmental Sciences, Shanghai, China
| | - Heming Bai
- Research Center for Intelligent Information Technology, Nantong University, Nantong, China
| | - Qian Wang
- State Environmental Protection Key Laboratory of Formation and Prevention of Urban Air Pollution Complex, Shanghai Academy of Environmental Sciences, Shanghai, China
| | - Yaqin Gao
- State Environmental Protection Key Laboratory of Formation and Prevention of Urban Air Pollution Complex, Shanghai Academy of Environmental Sciences, Shanghai, China
| | - Shengao Jing
- State Environmental Protection Key Laboratory of Formation and Prevention of Urban Air Pollution Complex, Shanghai Academy of Environmental Sciences, Shanghai, China
| | - Yanyu Wang
- State Environmental Protection Key Laboratory of Formation and Prevention of Urban Air Pollution Complex, Shanghai Academy of Environmental Sciences, Shanghai, China
| | - Hang Su
- State Environmental Protection Key Laboratory of Formation and Prevention of Urban Air Pollution Complex, Shanghai Academy of Environmental Sciences, Shanghai, China; Multiphase Chemistry Department, Max Planck Institute for Chemistry, Mainz, Germany.
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15
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Li R, Gao Y, Han Y, Zhang Y, Zhang B, Fu H, Wang G. Elucidating the mechanisms of rapid O 3 increase in North China Plain during COVID-19 lockdown period. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 906:167622. [PMID: 37806584 DOI: 10.1016/j.scitotenv.2023.167622] [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: 06/20/2023] [Revised: 10/02/2023] [Accepted: 10/04/2023] [Indexed: 10/10/2023]
Abstract
Ozone (O3) levels in North China Plain (NCP) suffered from rapid increases during the COVID-19 period. Many previous studies have confirmed more rapid NOx reduction compared with VOCs might be responsible for the O3 increase during this period, while the comprehensive impacts of each VOC species and NOx on ambient O3 and their interactions with meteorology were not revealed clearly. To clarify the detailed reasons for the O3 increase, a continuous campaign was performed in a typical industrial city of NCP. Meanwhile, the machine-learning technique and the box model were employed to reveal the mechanisms of O3 increase from the perspective of meteorology and photochemical process, respectively. The result suggested that the ambient O3 level in Tangshan increased from 18.7 ± 4.63 to 45.6 ± 8.52 μg/m3 (143%) during COVID-19 lockdown, and the emission reduction and meteorology contributed to 54 % and 46 % of this increment, respectively. The lower wind speed (WS) coupled with regional transport played a significant role on O3 increase (30.8 kg/s). The O3 sensitivity verified that O3 production was highly volatile organic compounds (VOC)-sensitive (Relative incremental reactivity (RIR): 0.75), while the NOx showed the negative impact on O3 production in Tangshan (RIR: -0.59). It suggested that the control of VOCs rather than NOx might be more effective in reducing O3 level in Tangshan because it was located on the VOC-limited regime. Besides, both of ozone formation potential (OFP) analysis and observation-based model (OBM) demonstrated that the alkenes (36.3 ppb) and anthropogenic oxygenated volatile organic compounds (OVOCs) (15.2 ppb) showed the higher OFP compared with other species, and their reactions released a large number of HO2 and RO2 radicals. Moreover, the concentrations of these species did not experience marked decreases during COVID-19 lockdown, which were major contributors to O3 increase during this period. This study also underlined the necessity of priority controlling alkenes and OVOCs across the NCP.
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Affiliation(s)
- Rui Li
- Key Laboratory of Geographic Information Science of the Ministry of Education, School of Geographic Sciences, East China Normal University, Shanghai 200241, PR China.
| | - Yining Gao
- Key Laboratory of Geographic Information Science of the Ministry of Education, School of Geographic Sciences, East China Normal University, Shanghai 200241, PR China
| | - Yu Han
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention, Department of Environmental Science & Engineering, Institute of Atmospheric Sciences, Fudan University, Shanghai 200433, PR China
| | - Yi Zhang
- Tangshan Ecological Environment Publicity and Education Center, Tangshan 063000, Hebei, PR China
| | - Baojun Zhang
- Tangshan Ecological Environment Publicity and Education Center, Tangshan 063000, Hebei, PR China
| | - Hongbo Fu
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention, Department of Environmental Science & Engineering, Institute of Atmospheric Sciences, Fudan University, Shanghai 200433, PR China
| | - Gehui Wang
- Key Laboratory of Geographic Information Science of the Ministry of Education, School of Geographic Sciences, East China Normal University, Shanghai 200241, PR China.
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Ma X, Yin Z, Cao B, Wang H. Meteorological influences on co-occurrence of O 3 and PM 2.5 pollution and implication for emission reductions in Beijing-Tianjin-Hebei. SCIENCE CHINA. EARTH SCIENCES 2023; 66:1-10. [PMID: 37359777 PMCID: PMC10205161 DOI: 10.1007/s11430-022-1070-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/27/2022] [Revised: 01/17/2023] [Accepted: 01/30/2023] [Indexed: 06/28/2023]
Abstract
Co-occurrence of surface ozone (O3) and fine particulate matter (PM2.5) pollution (CP) was frequently observed in Beijing-Tianjin-Hebei (BTH). More than 50% of CP days occurred during April-May in BTH, and the CP days reached up to 11 in two months of 2018. The PM2.5 or O3 concentration associated with CP was lower than but close to that in O3 and PM2.5 pollution, indicating compound harms during CP days with double-high concentrations of PM2.5 and O3. CP days were significantly facilitated by joint effects of the Rossby wave train that consisted of two centers associated with the Scandinavia pattern and one center over North China as well as a hot, wet, and stagnant environmental condition in BTH. After 2018, the number of CP days decreased sharply while the meteorological conditions did not change significantly. Therefore, changes in meteorological conditions did not really contribute to the decline of CP days in 2019 and 2020. This implies that the reduction of PM2.5 emission has resulted in a reduction of CP days (about 11 days in 2019 and 2020). The differences in atmospheric conditions revealed here were helpful to forecast the types of air pollution on a daily to weekly time scale. The reduction in PM2.5 emission was the main driving factor behind the absence of CP days in 2020, but the control of surface O3 must be stricter and deeper. Electronic Supplementary Material Supplementary material is available in the online version of this article at 10.1007/s11430-022-1070-y.
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Affiliation(s)
- Xiaoqing Ma
- Key Laboratory of Meteorological Disaster, Ministry of Education/Joint International Research Laboratory of Climate and Environment Change (ILCEC)/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Nanjing University of Information Science & Technology, Nanjing, 210044 China
| | - Zhicong Yin
- Key Laboratory of Meteorological Disaster, Ministry of Education/Joint International Research Laboratory of Climate and Environment Change (ILCEC)/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Nanjing University of Information Science & Technology, Nanjing, 210044 China
- Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, 519080 China
- Nansen-Zhu International Research Centre, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029 China
| | - Bufan Cao
- Key Laboratory of Meteorological Disaster, Ministry of Education/Joint International Research Laboratory of Climate and Environment Change (ILCEC)/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Nanjing University of Information Science & Technology, Nanjing, 210044 China
| | - Huijun Wang
- Key Laboratory of Meteorological Disaster, Ministry of Education/Joint International Research Laboratory of Climate and Environment Change (ILCEC)/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Nanjing University of Information Science & Technology, Nanjing, 210044 China
- Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, 519080 China
- Nansen-Zhu International Research Centre, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029 China
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17
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Yan Y, Wang X, Huang Z, Qu K, Shi W, Peng Z, Zeng L, Xie S, Zhang Y. Impacts of synoptic circulation on surface ozone pollution in a coastal eco-city in Southeastern China during 2014-2019. J Environ Sci (China) 2023; 127:143-157. [PMID: 36522048 DOI: 10.1016/j.jes.2022.01.026] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2021] [Revised: 01/10/2022] [Accepted: 01/11/2022] [Indexed: 06/17/2023]
Abstract
The coastal eco-city of Fuzhou in Southeastern China has experienced severe ozone (O3) episodes at times in recent years. In this study, three typical synoptic circulations types (CTs) that influenced more than 80% of O3 polluted days in Fuzhou during 2014-2019 were identified using a subjective approach. The characteristics of meteorological conditions linked to photochemical formation and transport of O3 under the three CTs were summarized. Comprehensive Air Quality Model with extensions was applied to simulate O3 episodes and to quantify O3 sources from different regions in Fuzhou. When Fuzhou was located to the west of a high-pressure system (classified as "East-ridge"), more warm southwesterly currents flowed to Fuzhou, and the effects of cross-regional transport from Guangdong province and high local production promoted the occurrence of O3 episodes. Under a uniform pressure field with a low-pressure system occurring to the east of Fuzhou (defined as "East-low"), stagnant weather conditions caused the strongest local production of O3 in the atmospheric boundary layer. Controlled by high-pressure systems over the mainland (categorized as "Inland-high"), northerly airflows enhanced the contribution of cross-regional transport to O3 in Fuzhou. The abnormal increases of the "East-ridge" and "Inland-high" were closely related to O3 pollution in Fuzhou in April and May 2018, resulting in the annual maximum number of O3 polluted days during recent years. Furthermore, the rising number of autumn O3 episodes in 2017-2019 was mainly related to the "Inland-high", indicating the aggravation of cross-regional transport and highlighting the necessity of enhanced regional collaboration and efforts in combating O3 pollution.
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Affiliation(s)
- 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
| | - 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.
| | - Zhengchao Huang
- Center for Environmental Education and Communications of Ministry of Ecology and Environment, Beijing 100020, China
| | - 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
| | - Wenbin Shi
- 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
| | - Zimu Peng
- 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
| | - Shaodong Xie
- 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.
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Ding J, Dai Q, Fan W, Lu M, Zhang Y, Han S, Feng Y. Impacts of meteorology and precursor emission change on O 3 variation in Tianjin, China from 2015 to 2021. J Environ Sci (China) 2023; 126:506-516. [PMID: 36503777 DOI: 10.1016/j.jes.2022.03.010] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2021] [Revised: 02/05/2022] [Accepted: 03/03/2022] [Indexed: 06/17/2023]
Abstract
Deterioration of surface ozone (O3) pollution in Northern China over the past few years received much attention. For many cities, it is still under debate whether the trend of surface O3 variation is driven by meteorology or the change in precursors emissions. In this work, a time series decomposition method (Seasonal-Trend decomposition procedure based on Loess (STL)) and random forest (RF) algorithm were utilized to quantify the meteorological impacts on the recorded O3 trend and identify the key meteorological factors affecting O3 pollution in Tianjin, the biggest coastal port city in Northern China. After "removing" the meteorological fluctuations from the observed O3 time series, we found that variation of O3 in Tianjin was largely driven by the changes in precursors emissions. The meteorology was unfavorable for O3 pollution in period of 2015-2016, and turned out to be favorable during 2017-2021. Specifically, meteorology contributed 9.3 µg/m3 O3 (13%) in 2019, together with the increase in precursors emissions, making 2019 to be the worst year of O3 pollution since 2015. Since then, the favorable effects of meteorology on O3 pollution tended to be weaker. Temperature was the most important factor affecting O3 level, followed by air humidity in O3 pollution season. In the midday of summer days, O3 pollution frequently exceeded the standard level (>160 µg/m3) at a combined condition with relative humidity in 40%-50% and temperature > 31°C. Both the temperature and the dryness of the atmosphere need to be subtly considered for summer O3 forecasting.
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Affiliation(s)
- Jing Ding
- Tianjin Environmental Meteorological Center, Qi xiangtai road, Tianjin 300074, China; CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health Research, Tianjin 300074, China
| | - Qili Dai
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China; CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health Research, Tianjin 300074, China.
| | - Wenyan Fan
- Tianjin Environmental Meteorological Center, Qi xiangtai road, Tianjin 300074, China; CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health Research, Tianjin 300074, China
| | - Miaomiao Lu
- Tianjin Environmental Meteorological Center, Qi xiangtai road, Tianjin 300074, China; CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health Research, Tianjin 300074, China
| | - Yufen Zhang
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China; CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health Research, Tianjin 300074, China
| | - Suqin Han
- Tianjin Environmental Meteorological Center, Qi xiangtai road, Tianjin 300074, China; CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health Research, Tianjin 300074, China.
| | - Yinchang Feng
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China; CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health Research, Tianjin 300074, China
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Chen B, Wang Y, Huang J, Zhao L, Chen R, Song Z, Hu J. Estimation of near-surface ozone concentration and analysis of main weather situation in China based on machine learning model and Himawari-8 TOAR data. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 864:160928. [PMID: 36539084 DOI: 10.1016/j.scitotenv.2022.160928] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/22/2022] [Revised: 11/21/2022] [Accepted: 12/10/2022] [Indexed: 06/17/2023]
Abstract
Ozone (O3) is an important greenhouse gas in the atmosphere. Stratospheric ozone protects human beings, but high near-surface ozone concentrations threaten environment and human health. Owing to the uneven distribution of ground-monitoring stations and the low time resolution of polar orbiting satellites, it is difficult to accurately evaluate the refinement and synergistic pollution of near-surface ozone in China. Besides, atmospheric circulation patterns also affect ozone concentrations greatly. In this study, a new generation of geostationary satellite is used to estimate the hourly near-surface ozone concentration with a spatial resolution of 0.05°. First, the Pearson correlation coefficient and maximum information coefficient were used to study the correlation between the top of atmospheric radiation (TOAR) of Himawari-8 satellite and O3 concentration; seven TOAR channels were selected. Second, based on an interpretable deep learning model, the hourly ozone concentration in China from September 2015 to August 2021 was obtained using the TOAR-O3 model. Finally, the self-organizing map method was used to determine six major summer weather circulation patterns in China. The results showed that (1) the near-surface O3 concentration can be accurately estimated; the R2 (RMSE: μg/m3) values of the daily, monthly, and annual tenfold cross validation results were 0.91 (12.74), 0.97 (5.64), and 0.98 (1.75), respectively. The feature importance of the model showed that the temperature, TOAR, and boundary layer height contributed 38 %, 22 %, and 13 %, respectively. (2) The O3 concentration showed obvious spatiotemporal difference and gradually increased from 10:00 to 15:00 (Beijing time) every day. In most areas of China, O3 concentration had increased significantly. (3) The O3 concentration in northern China was the highest under the circulation pattern of the Meiyu front over the Yangtze River Delta, while in southern China, it was the highest under the circulation pattern of the northeast cold vortex controlling most of China.
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Affiliation(s)
- Bin Chen
- Key Laboratory for Semi-Arid Climate Change of the Ministry of Education, College of Atmospheric Sciences, Lanzhou University, Lanzhou 730000, China; Collaborative Innovation Center for Western Ecological Safety, Lanzhou 730000, China.
| | - Yixuan Wang
- Key Laboratory for Semi-Arid Climate Change of the Ministry of Education, College of Atmospheric Sciences, Lanzhou University, Lanzhou 730000, China; Collaborative Innovation Center for Western Ecological Safety, Lanzhou 730000, China
| | - Jianping Huang
- Key Laboratory for Semi-Arid Climate Change of the Ministry of Education, College of Atmospheric Sciences, Lanzhou University, Lanzhou 730000, China; Collaborative Innovation Center for Western Ecological Safety, Lanzhou 730000, China
| | - Lin Zhao
- Key Laboratory for Semi-Arid Climate Change of the Ministry of Education, College of Atmospheric Sciences, Lanzhou University, Lanzhou 730000, China; Collaborative Innovation Center for Western Ecological Safety, Lanzhou 730000, China
| | - Ruming Chen
- Key Laboratory for Semi-Arid Climate Change of the Ministry of Education, College of Atmospheric Sciences, Lanzhou University, Lanzhou 730000, China; Collaborative Innovation Center for Western Ecological Safety, Lanzhou 730000, China
| | - Zhihao Song
- Key Laboratory for Semi-Arid Climate Change of the Ministry of Education, College of Atmospheric Sciences, Lanzhou University, Lanzhou 730000, China; Collaborative Innovation Center for Western Ecological Safety, Lanzhou 730000, China
| | - Jiashun Hu
- Key Laboratory for Semi-Arid Climate Change of the Ministry of Education, College of Atmospheric Sciences, Lanzhou University, Lanzhou 730000, China; Collaborative Innovation Center for Western Ecological Safety, Lanzhou 730000, China
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Zhang X, Xu W, Zhang G, Lin W, Zhao H, Ren S, Zhou G, Chen J, Xu X. First long-term surface ozone variations at an agricultural site in the North China Plain: Evolution under changing meteorology and emissions. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 860:160520. [PMID: 36442628 DOI: 10.1016/j.scitotenv.2022.160520] [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: 10/01/2022] [Revised: 11/10/2022] [Accepted: 11/22/2022] [Indexed: 06/16/2023]
Abstract
Significant upward trends in surface ozone (O3) have been widely reported in China during recent years, especially during warm seasons in the North China Plain (NCP), exerting adverse environmental effects on human health and agriculture. Quantifying long-term O3 variations and their attributions helps to understand the causes of regional O3 pollution and to formulate according control strategy. In this study, we present long-term trends of O3 in the warm seasons (April-September) during 2006-2019 at an agricultural site in the NCP and investigate the relative contributions of meteorological and anthropogenic factors. Overall, the maximum daily 8-h average (MDA8) O3 exhibited a weak decreasing trend with large interannual variability. < 6 % of the observed trend could be explained by changes in meteorological conditions, while the remaining 94 % was attributed to anthropogenic impacts. However, the interannual variability of warm season MDA8 O3 was driven by both meteorology (36 ± 28 %) and anthropogenic factors (64 ± 27 %). Daily maximum temperature was the most essential factor affecting O3 variations, followed by ultraviolet radiation b (UVB) and boundary layer height (BLH), with rising temperature trends inducing O3 inclines throughout April to August, while UVB mainly influenced O3 during summer months. Under changes in emissions and air quality, warm season O3 production regime gradually shifted from dominantly VOCs-limited during 2006-2015 to NOx-limited afterwards. Relatively steady HCHO and remarkably rising NOx levels resulted in the fast decreasing MDA8 O3 (-2.87 ppb yr-1) during 2006-2012. Rapidly decreasing NOx, flat or slightly increasing HCHO promoted O3 increases during 2012-2015 (9.76 ppb yr-1). While afterwards, slow increases in HCHO and downwards fluctuating NOx led to decreases in MDA8 O3 (-4.97 ppb yr-1). Additionally, continuous warming trends might promote natural emissions of O3 precursors and magnify their impacts on agricultural O3 by inducing high variability, which would require even more anthropogenic reduction to compensate for.
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Affiliation(s)
- Xiaoyi Zhang
- Department of Atmospheric and Oceanic Sciences, Fudan University, Shanghai 200433, China; State Key Laboratory of Severe Weather, Key Laboratory for Atmospheric Chemistry, Institute of Atmospheric Composition, Chinese Academy of Meteorological Sciences, Beijing 100081, China
| | - Wanyun Xu
- State Key Laboratory of Severe Weather, Key Laboratory for Atmospheric Chemistry, Institute of Atmospheric Composition, Chinese Academy of Meteorological Sciences, Beijing 100081, China.
| | - Gen Zhang
- State Key Laboratory of Severe Weather, Key Laboratory for Atmospheric Chemistry, Institute of Atmospheric Composition, Chinese Academy of Meteorological Sciences, Beijing 100081, China
| | - Weili Lin
- College of Life and Environmental Sciences, Minzu University of China, Beijing 100081, China
| | - Huarong Zhao
- State Key Laboratory of Severe Weather, Institute of Agricultural Meteorology, Chinese Academy of Meteorological Sciences, Beijing 100081, China
| | - Sanxue Ren
- State Key Laboratory of Severe Weather, Institute of Agricultural Meteorology, Chinese Academy of Meteorological Sciences, Beijing 100081, China
| | - Guangsheng Zhou
- State Key Laboratory of Severe Weather, Institute of Agricultural Meteorology, Chinese Academy of Meteorological Sciences, Beijing 100081, China; Hebei Gucheng Agricultural Meteorology National Observation and Research Station, Baoding 072656, China
| | - Jianmin Chen
- Department of Atmospheric and Oceanic Sciences, Fudan University, Shanghai 200433, China
| | - Xiaobin Xu
- State Key Laboratory of Severe Weather, Key Laboratory for Atmospheric Chemistry, Institute of Atmospheric Composition, Chinese Academy of Meteorological Sciences, Beijing 100081, China.
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21
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Chen J, Guo L, Liu H, Jin L, Meng W, Fang J, Zhao L, Zeng XW, Yang BY, Wang Q, Guo X, Deng F, Dong GH, Shang X, Wu S. Modification effects of ambient temperature on associations of ambient ozone exposure before and during pregnancy with adverse birth outcomes: A multicity study in China. ENVIRONMENT INTERNATIONAL 2023; 172:107791. [PMID: 36739855 DOI: 10.1016/j.envint.2023.107791] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/24/2022] [Revised: 01/12/2023] [Accepted: 01/28/2023] [Indexed: 06/18/2023]
Abstract
BACKGROUND Epidemiological studies suggest that both ambient ozone (O3) and temperature were associated with increased risks of adverse birth outcomes. However, very few studies explored their interaction effects, especially for small for gestational age (SGA) and large for gestational age (LGA). OBJECTIVES To estimate the modification effects of ambient temperature on associations of ambient O3 exposure before and during pregnancy with preterm birth (PTB), low birth weight (LBW), SGA and LGA based on multicity birth cohorts. METHODS A total of 56,905 singleton pregnant women from three birth cohorts conducted in Tianjin, Beijing and Maoming, China, were included in the study. Maximum daily 8-h average O3 concentrations of each pregnant woman from the preconception period to delivery for every day were estimated by matching their home addresses with the Tracking Air Pollution in China (TAP) datasets. We first applied the Cox proportional-hazards regression model to evaluate the city-specific effects of O3 exposure before and during pregnancy on adverse birth outcomes at different temperature levels with adjustment for potential confounders, and then a meta-analysis across three birth cohorts was conducted to calculate the pooled associations. RESULTS In pooled analysis, significant modification effects of ambient temperature on associations of ambient O3 with PTB, LBW and LGA were observed (Pinteraction < 0.05). For a 10 μg/m3 increase in ambient O3 exposure at high temperature level (> 75th percentile), the risk of LBW increased by 28 % (HR: 1.28, 95% CI: 1.13-1.46) during the second trimester and the risk of LGA increased by 116% (HR: 2.16, 95%CI: 1.16-4.00) during the entire pregnancy, while the null or weaker association was observed at corresponding low (≤ 25th percentile) and medium (> 25th and ≤ 75th percentile) temperature levels. CONCLUSION This multicity study added new evidence that ambient high temperature may enhance the potential effects of ambient O3 on adverse birth outcomes.
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Affiliation(s)
- Juan Chen
- Institute of Disaster and Emergency Medicine, Tianjin University, Tianjin, China; Tianjin Key Laboratory of Disaster Medicine Technology, Tianjin, China; Wenzhou Safety (Emergency) Institute, Tianjin University, Wenzhou, China; Department of Occupational and Environmental Health, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, China
| | - Liqiong Guo
- Institute of Disaster and Emergency Medicine, Tianjin University, Tianjin, China; Tianjin Key Laboratory of Disaster Medicine Technology, Tianjin, China; Wenzhou Safety (Emergency) Institute, Tianjin University, Wenzhou, China
| | - Huimeng Liu
- Department of Occupational and Environmental Health, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, China
| | - Lei Jin
- Institute of Reproductive and Child Health, National Health Commission Key Laboratory of Reproductive Health, Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Wenying Meng
- Tongzhou Maternal and Child Health Care Hospital, Beijing, China
| | - Junkai Fang
- Tianjin Healthcare Affair Center, Tianjin, China
| | - Lei Zhao
- Institute of Disaster and Emergency Medicine, Tianjin University, Tianjin, China; Tianjin Key Laboratory of Disaster Medicine Technology, Tianjin, China; Wenzhou Safety (Emergency) Institute, Tianjin University, Wenzhou, China
| | - Xiao-Wen Zeng
- Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Bo-Yi Yang
- Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Qi Wang
- Department of Toxicology, School of Public Health, Peking University, Beijing, China
| | - Xinbiao Guo
- Department of Occupational and Environmental Health Sciences, School of Public Health, Peking University, Beijing, China
| | - Furong Deng
- Department of Occupational and Environmental Health Sciences, School of Public Health, Peking University, Beijing, China
| | - Guang-Hui Dong
- Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Xuejun Shang
- Department of Andrology, Jinling Hospital, School of Medicine, Nanjing University, Nanjing, China.
| | - Shaowei Wu
- Department of Occupational and Environmental Health, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, China; Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Xi'an, Shaanxi, China; Key Laboratory of Trace Elements and Endemic Diseases in Ministry of Health, Xi'an, Shaanxi, China.
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Pan W, Gong S, Lu K, Zhang L, Xie S, Liu Y, Ke H, Zhang X, Zhang Y. Multi-scale analysis of the impacts of meteorology and emissions on PM 2.5 and O 3 trends at various regions in China from 2013 to 2020 3. Mechanism assessment of O 3 trends by a model. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 857:159592. [PMID: 36272478 DOI: 10.1016/j.scitotenv.2022.159592] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/23/2022] [Revised: 10/14/2022] [Accepted: 10/16/2022] [Indexed: 06/16/2023]
Abstract
A multiscale analysis of meteorological trends was carried out to investigate the impacts of the large-scale circulation types as well as the local-scale key weather elements on the complex air pollutants, i.e., PM2.5 and O3 in China. Following accompanying papers on synoptic circulation impact and key weather elements and emission contributions (Gong et al., 2022a; Gong et al., 2022b), an emission-driven Observation-based Box Model (e-OBM) was developed to study the impact mechanisms on O3 trend and quantitatively assess the effects of variation in the emissions control over 2013-2020 for Beijing, Chengdu, Guangzhou and Shanghai. Compared with the original OBM, the e-OBM not only improves the performance to simulate the hourly O3 peak concentration in daytime, but also reasonably reproduces the maximum daily 8-hour average (MDA8) O3 concentrations in the four cities. Based upon the sensitivity experiments, it is found that the meteorology is the dominant driver for the MDA8 O3 trend, contributing from about 32 % to 139 % to the variations. From the mechanistic point of view, the variations of meteorology lead to the enhancement of atmospheric oxidation capacity and the acceleration of O3 production. Further evaluation to the emission changes in four cities shows that the O3-precursors relationships of the four cities have been changed from the VOC-limited regime in 2013 to the transition regime or near-transition regime in 2020. Though the NOx/VOCs ratios have been obviously decreased, the emission reductions up to 2020 were still not enough to mitigate O3 pollution in these cities. It is emphasized in this study that the strengthened control measures with maintaining a certain ratio of NOx and VOCs should be implemented to further curb the increasing trend of O3 in urban areas.
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Affiliation(s)
- Weijun Pan
- State Key Laboratory of Severe Weather & Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing 100081, China
| | - Sunling Gong
- State Key Laboratory of Severe Weather & Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing 100081, China; National Observation and Research Station of Coastal Ecological Environments in Macao, Macao Environmental Research Institute, Macau University of Science and Technology, 999078, Macao.
| | - Keding Lu
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China.
| | - Lei Zhang
- State Key Laboratory of Severe Weather & Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing 100081, China
| | - Shaodong Xie
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Yuhan Liu
- Department of Nuclear Safety, China Institute of Atomic Energy, Beijing 102413, China
| | - Huabing Ke
- State Key Laboratory of Severe Weather & Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing 100081, China
| | - Xiaoling Zhang
- Plateau Atmosphere and Environment Key Laboratory of Sichuan Province, School of Atmospheric Sciences, Chengdu University of Information Technology, Chengdu 610225, 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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23
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He C, Wu Q, Li B, Liu J, Gong X, Zhang L. Surface ozone pollution in China: Trends, exposure risks, and drivers. Front Public Health 2023; 11:1131753. [PMID: 37026118 PMCID: PMC10071862 DOI: 10.3389/fpubh.2023.1131753] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2022] [Accepted: 03/03/2023] [Indexed: 04/08/2023] Open
Abstract
Introduction Within the context of the yearly improvement of particulate matter (PM) pollution in Chinese cities, Surface ozone (O3) concentrations are increasing instead of decreasing and are becoming the second most important air pollutant after PM. Long-term exposure to high concentrations of O3 can have adverse effects on human health. In-depth investigation of the spatiotemporal patterns, exposure risks, and drivers of O3 is relevant for assessing the future health burden of O3 pollution and implementing air pollution control policies in China. Methods Based on high-resolution O3 concentration reanalysis data, we investigated the spatial and temporal patterns, population exposure risks, and dominant drivers of O3 pollution in China from 2013 to 2018 utilizing trend analysis methods, spatial clustering models, exposure-response functions, and multi-scale geographically weighted regression models (MGWR). Results The results show that the annual average O3 concentration in China increased significantly at a rate of 1.84 μg/m3/year from 2013 to 2018 (160 μg/m3) in China increased from 1.2% in 2013 to 28.9% in 2018, and over 20,000 people suffered premature death from respiratory diseases attributed to O3 exposure each year. Thus, the sustained increase in O3 concentrations in China is an important factor contributing to the increasing threat to human health. Furthermore, the results of spatial regression models indicate that population, the share of secondary industry in GDP, NOx emissions, temperature, average wind speed, and relative humidity are important determinants of O3 concentration variation and significant spatial differences are observed. Discussion The spatial differences of drivers result in the spatial heterogeneity of O3 concentration and exposure risks in China. Therefore, the O3 control policies adapted to various regions should be formulated in the future O3 regulation process in China.
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Affiliation(s)
- Chao He
- College of Resources and Environment, Yangtze University, Wuhan, China
| | - Qian Wu
- School of Resource and Environmental Sciences, Wuhan University, Wuhan, China
| | - Bin Li
- College of Resources and Environment, Yangtze University, Wuhan, China
| | - Jianhua Liu
- College of Resources and Environment, Yangtze University, Wuhan, China
| | - Xi Gong
- School of Low Carbon Economics, Hubei University of Economics, Wuhan, China
- Collaborative Innovation Center for Emissions Trading System Co-constructed by the Province and Ministry, Wuhan, China
- *Correspondence: Xi Gong
| | - Lu Zhang
- State Key Laboratory of Freshwater Ecology and Biotechnology, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan, China
- Lu Zhang
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Gao J, Li Y, Xie Z, Wang L, Hu B, Bao F. Which aerosol type dominate the impact of aerosols on ozone via changing photolysis rates? THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 854:158580. [PMID: 36075440 DOI: 10.1016/j.scitotenv.2022.158580] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/06/2022] [Revised: 09/01/2022] [Accepted: 09/03/2022] [Indexed: 06/15/2023]
Abstract
The impact of aerosols on ozone via influencing photolysis rates is a combined effect of absorbing aerosols (AA) and scattering aerosols (SA). However, AA and SA show different optical properties and influence photolysis rates differently, which then cause different impacts on ozone. Till now, the dominate factor is disconfirmed, which is largely due to the impact of SA on ozone not reaching to a consistent conclusion. In this study, the WRF-Chem model was implemented to simulate the air pollutants over the North China Plain (NCP). The impacts of AA and SA on ozone via influencing photolysis rates were quantitatively isolated and analyzed. Our results also demonstrated the decreasing effect of AA on ozone within planet boundary layer (PBL) which is consistent with the conclusions of previous studies. But for SA, it decreased the ozone chemical contribution (CHEM) near surface but increased which in the upper layers of PBL, that enlarge the ozone vertical gradients. In this case, more vertical exchanges of ozone would occur with the effect of vertical mixing motion of atmosphere, then the opposite CHEM variations were counteracted with each other and finally led to very slight changes in ozone within PBL. Thus, it can be summarized that AA dominate this impact of aerosols on ozone. Reducing AA could cause a general increase in ozone (ΔO3) over the NCP. Based on the aerosol levels of this case, ΔO3 would be seen over 86 % of the areas in the NCP when reducing AA by 3/4 and ΔO3 was more significant in the megacities. Our study highlights the different relationships between ozone and aerosol types, which suggests that more attentions should be paid on aerosol types, especially AA, when making the synergetic control strategy of aerosols and ozone in China.
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Affiliation(s)
- Jinhui Gao
- Plateau Atmosphere and Environment Key Laboratory of Sichuan Province, School of Atmospheric Sciences, Chengdu University of Information Technology, Chengdu, China; Department of Ocean Science and Engineering, Southern University of Science and Technology, Shenzhen, China; Center for the Oceanic and Atmospheric Science at SUSTech (COAST), Southern University of Science and Technology, Shenzhen, China
| | - Ying Li
- Department of Ocean Science and Engineering, Southern University of Science and Technology, Shenzhen, China; Center for the Oceanic and Atmospheric Science at SUSTech (COAST), Southern University of Science and Technology, Shenzhen, China.
| | - Zhouqing Xie
- Department of Environmental Science and Engineering, University of Science and Technology of China, Hefei, China
| | - Lili Wang
- State Key Laboratory of Atmosphere Boundary Layer Physics and Atmospheric Chemistry (LAPC), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
| | - Bo Hu
- State Key Laboratory of Atmosphere Boundary Layer Physics and Atmospheric Chemistry (LAPC), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
| | - Fangwen Bao
- Department of Ocean Science and Engineering, Southern University of Science and Technology, Shenzhen, China; Center for the Oceanic and Atmospheric Science at SUSTech (COAST), Southern University of Science and Technology, Shenzhen, China
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25
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Chen Y, Li H, Karimian H, Li M, Fan Q, Xu Z. Spatio-temporal variation of ozone pollution risk and its influencing factors in China based on Geodetector and Geospatial models. CHEMOSPHERE 2022; 302:134843. [PMID: 35533939 DOI: 10.1016/j.chemosphere.2022.134843] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/14/2022] [Revised: 04/14/2022] [Accepted: 05/01/2022] [Indexed: 05/17/2023]
Abstract
Ozone (O3) has become the primary pollutant in many cities, and high concentrations of O3 cause significant harm to the ecological environment and human health. This study investigated the spatiotemporal distribution of surface concentrations of ozone over entire China and analyzed the influencing factors based on the geographical detector technique. Moreover, the Pearson correlation analysis was used to analyze the influence of various meteorological factors on ozone concentrations. The results showed that, on the national scale, the daily average O3 concentration in the cities of China in 2019 was 92.441 μg/m3 and the nonattainment rate of daily average ozone was 7.98%. However, the ozone nonattainment rate was 33.33% in heavily polluted regions. The highest O3 concentration was observed in summer, and the lowest was observed in spring. The O3 concentrations in cities across the country showed significant spatial distribution characteristics. Among the five pollutants, the highest correlation was observed between O3 and PM2.5 and the lowest was observed between O3 and SO2. Among the metrological factors, wind speed and solar radiation are the most influencing factors, and showed positive correlation. Moreover, the annual precipitation is negatively correlated with O3-8h concentrations. The methods and findings of this paper can be used as an aid for air pollution control programs in different regions for diminishing the risk of exposure to various air pollutants.
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Affiliation(s)
- Youliang Chen
- School of Civil and Surveying & Mapping Engineering, Jiangxi University of Science and Technology, Ganzhou, 341000, China; School of Geosciences and Info Physics, Central South University, Changsha, 410000, China
| | - Hongchong Li
- School of Civil and Surveying & Mapping Engineering, Jiangxi University of Science and Technology, Ganzhou, 341000, China
| | - Hamed Karimian
- School of Civil and Surveying & Mapping Engineering, Jiangxi University of Science and Technology, Ganzhou, 341000, China.
| | - Meimei Li
- School of Civil and Surveying & Mapping Engineering, Jiangxi University of Science and Technology, Ganzhou, 341000, China; School of Artificial Intelligence, Jiangxi University of Applied Science, Nanchang, 330100, China
| | - Qin Fan
- School of Civil and Surveying & Mapping Engineering, Jiangxi University of Science and Technology, Ganzhou, 341000, China
| | - Zhigang Xu
- School of Resource Engineering, Longyan University, Longyan, 361000, China
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26
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Zhang W, Li W, An X, Zhao Y, Sheng L, Hai S, Li X, Wang F, Zi Z, Chu M. Numerical study of the amplification effects of cold-front passage on air pollution over the North China Plain. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 833:155231. [PMID: 35427612 DOI: 10.1016/j.scitotenv.2022.155231] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/27/2022] [Revised: 04/06/2022] [Accepted: 04/08/2022] [Indexed: 06/14/2023]
Abstract
Cold-front systems provide scavenging mechanisms for air pollution in the North China Plain (NCP), but the transport of pollutants with cold fronts aggravates air quality downstream. The impact of cold fronts on PM2.5 concentrations over the NCP during 8-14 December 2019 was studied using the WRF-Chem model. Results indicate that cold fronts directly influence PM2.5 concentration through regional transport of pollutants and adjustment of meteorological systems, and they indirectly affect air quality by influencing aerosol-radiation interaction. Pollutants affecting downstream areas may be transported to altitudes of ~3 km along the frontal surface, with near-surface PM2.5 concentrations increasing temporarily at up to 15 μg·m-3·h-1 behind the surface frontal line owing to the inversion layer triggered by the oblique frontal surface. The transport process plays an essential role in affecting air pollution levels, more than vertical mixing and chemical reaction processes. Changes in the meteorological system (eastward shift of the high-pressure center) occurring with the passage of cold fronts facilitate the accumulation and transport of pollutants in the NCP, reducing air quality in the western and northern NCP. Cold fronts may also indirectly exacerbate near-surface pollutant diffusion conditions by affecting solar radiation incidence, with a reduction of the 2-m temperature by as much as 1 °C, increasing near-surface (<1 and 0.5 km agl on the pre- and post-frontal sides, respectively) PM2.5 concentrations by up to 40 μg·m-3, while reducing upper-layer concentrations by up to 30 μg·m-3. This study emphasizes the amplification effect of cold fronts on air pollution, with inter-regional cooperation being essential in improving air quality in the NCP region.
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Affiliation(s)
- Weihang Zhang
- College of Oceanic and Atmospheric Sciences, Ocean University of China, Qingdao 266100, China
| | - Wenshuai Li
- College of Oceanic and Atmospheric Sciences, Ocean University of China, Qingdao 266100, China
| | - Xiadong An
- College of Oceanic and Atmospheric Sciences, Ocean University of China, Qingdao 266100, China
| | - Yuanhong Zhao
- College of Oceanic and Atmospheric Sciences, Ocean University of China, Qingdao 266100, China
| | - Lifang Sheng
- College of Oceanic and Atmospheric Sciences, Ocean University of China, Qingdao 266100, China; Key Laboratory of Physical Oceanography, Ocean University of China, Qingdao 266100, China.
| | - Shangfei Hai
- College of Oceanic and Atmospheric Sciences, Ocean University of China, Qingdao 266100, China
| | - Xiaodong Li
- College of Oceanic and Atmospheric Sciences, Ocean University of China, Qingdao 266100, China
| | - Fei Wang
- College of Oceanic and Atmospheric Sciences, Ocean University of China, Qingdao 266100, China
| | - Zhifei Zi
- College of Oceanic and Atmospheric Sciences, Ocean University of China, Qingdao 266100, China
| | - Ming Chu
- College of Environmental Science and Engineering, Ocean University of China, Qingdao 266100, China
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27
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Zhou M, Li Y, Zhang F. Spatiotemporal Variation in Ground Level Ozone and Its Driving Factors: A Comparative Study of Coastal and Inland Cities in Eastern China. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:ijerph19159687. [PMID: 35955043 PMCID: PMC9367812 DOI: 10.3390/ijerph19159687] [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: 07/06/2022] [Revised: 07/29/2022] [Accepted: 08/03/2022] [Indexed: 05/24/2023]
Abstract
Variations in marine and terrestrial geographical environments can cause considerable differences in meteorological conditions, economic features, and population density (PD) levels between coastal and inland cities, which in turn can affect the urban air quality. In this study, a five-year (2016-2020) dataset encompassing air monitoring (from the China National Environmental Monitoring Centre), socioeconomic statistical (from the Shandong Province Bureau of Statistics) and meteorological data (from the U.S. National Centers for Environmental Information, National Oceanic and Atmospheric Administration) was employed to investigate the spatiotemporal distribution characteristics and underlying drivers of urban ozone (O3) in Shandong Province, a region with both land and sea environments in eastern China. The main research methods included the multiscale geographically weighted regression (MGWR) model and wavelet analysis. From 2016 to 2019, the O3 concentration increased year by year in most cities, but in 2020, the O3 concentration in all cities decreased. O3 concentration exhibited obvious regional differences, with higher levels in inland areas and lower levels in eastern coastal areas. The MGWR analysis results indicated the relationship between PD, urbanization rate (UR), and O3 was greater in coastal cities than that in the inland cities. Furthermore, the wavelet coherence (WTC) analysis results indicated that the daily maximum temperature was the most important factor influencing the O3 concentration. Compared with NO, NO2, and NOx (NOx ≡ NO + NO2), the ratio of NO2/NO was more coherent with O3. In addition, the temperature, the wind speed, nitrogen oxides, and fine particulate matter (PM2.5) exerted a greater impact on O3 in coastal cities than that in inland cities. In summary, the effects of the various abovementioned factors on O3 differed between coastal cities and inland cities. The present study could provide a scientific basis for targeted O3 pollution control in coastal and inland cities.
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Affiliation(s)
- Mengge Zhou
- Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yonghua Li
- Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
| | - Fengying Zhang
- China National Environmental Monitoring Centre, Beijing 100012, China
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28
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Du Y, Zhao K, Yuan Z, Luo H, Ma W, Liu X, Wang L, Liao C, Zhang Y. Identification of close relationship between large-scale circulation patterns and ozone-precursor sensitivity in the Pearl River Delta, China. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2022; 312:114915. [PMID: 35313148 DOI: 10.1016/j.jenvman.2022.114915] [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: 08/12/2021] [Revised: 03/07/2022] [Accepted: 03/14/2022] [Indexed: 06/14/2023]
Abstract
To curb the continuous deterioration of ozone (O3) pollution in China, identifying the O3-precursor sensitivity (OPS) and its driving factors is a prerequisite for formulating effective O3 pollution control measures. Traditional OPS identification methods have limitations in terms of spatiotemporal representation and timeliness; therefore, they are not appropriate for making OPS forecasts for O3 contingency control. OPS is not only influenced by local precursor emissions but is also closely related to meteorological conditions governed by large-scale circulation (LSC). In this study, a localized three-dimensional numerical modeling system was used to investigate the relationship between LSC and OPS in the Pearl River Delta (PRD) of China during September 2017, a month with continuous O3 pollution. Our results highlighted that there was a close relationship between LSC and OPS over the PRD, and the four dominant LSC patterns corresponded well to the NOx-limited, NOx-limited, VOC-limited, and transitional regimes, respectively. The clear linkage between LSC and OPS was mainly driven by the spatial heterogeneity of NOx and VOC emissions within and beyond the PRD along the prevailing winds under different LSC patterns. A conceptual model was developed to highlight the intrinsic causality between the LSC and OPS. Because current technology can accurately forecast LSC 48-72 h in advance, the LSC-based OPS forecast method provided us with a novel approach to guide contingency control and management measures to reduce peak O3 at a regional scale.
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Affiliation(s)
- Yi Du
- School of Environment and Energy, South China University of Technology, Guangzhou, 510006, China
| | - Kaihui Zhao
- School of Environment and Energy, South China University of Technology, Guangzhou, 510006, China.
| | - Zibing Yuan
- School of Environment and Energy, South China University of Technology, Guangzhou, 510006, China.
| | - Huihong Luo
- School of Environment and Energy, South China University of Technology, Guangzhou, 510006, China
| | - Wei Ma
- School of Environment and Energy, South China University of Technology, Guangzhou, 510006, China
| | - Xuehui Liu
- School of Environment and Energy, South China University of Technology, Guangzhou, 510006, China
| | - Long Wang
- Guangdong Provincial Academy of Environmental Science, Guangzhou, 510045, China
| | - Chenghao Liao
- Guangdong Provincial Academy of Environmental Science, Guangzhou, 510045, China
| | - Yongbo Zhang
- Guangdong Provincial Academy of Environmental Science, Guangzhou, 510045, China
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29
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Cao J, Qiu X, Liu Y, Yan X, Gao J, Peng L. Identifying the dominant driver of elevated surface ozone concentration in North China plain during summertime 2012-2017. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2022; 300:118912. [PMID: 35092729 DOI: 10.1016/j.envpol.2022.118912] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/28/2021] [Revised: 01/21/2022] [Accepted: 01/25/2022] [Indexed: 06/14/2023]
Abstract
The increasingly serious surface ozone (O3) pollution in North China Plain (NCP) has received wide attention. However, the contribution of the changes for each emission source to the elevated O3 concentration, as well as the direct and indirect effect of meteorological condition variation on increased O3 level have not been comprehensively analyzed. This study applied the Community Multiscale Air Quality (CMAQ) model coupled with the integrated source apportionment method (ISAM) to quantify changes in daily maximum 8-h average O3 concentration (MDA8 O3) under different air pollutants emissions and meteorological conditions during summertime 2012-2017. The results showed that incoordinate NOx/VOC emission control sustainably increased MDA8 O3 by 2.2-36.2 μg/m3 in the NCP, of which emission changes from industrial and transportation sectors were the predominant contributors (-0.6-19.5 μg/m3 for industrial sector and 1.2-18.1 μg/m3 for transportation, respectively). In contrast, MDA8 O3 decreased by 2.5-9.2 μg/m3 for the power plants. The effect of changes in meteorological condition on MDA8 O3 exhibited significantly spatial and temporal variation and unfavorable meteorological fields were shown in 2014, 2016, and 2017, which enhanced MDA8 O3 by -2.5-23.1, -5.3-20.7, and -7.2-25.8 μg/m3, respectively. In addition, the changed meteorological factors indirectly affected the biogenic emission thus prompting the increases of MDA8 O3 by -3.9-4.9 μg/m3 in the NCP during 2012-2017. The sensitive simulations suggested that more aggressive control measures about VOC reduction in industrial and transportation sectors should be implemented to further mitigate the O3 pollution under unfavorable meteorological condition.
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Affiliation(s)
- Jingyuan Cao
- College of Environmental Sciences and Engineering, North China Electric Power University, Beijing, 102206, China; Key Laboratory of Resources and Environmental Systems Optimization, Ministry of Education, College of Environmental Science and Engineering, North China Electric Power University, Beijing 102206, China
| | - Xionghui Qiu
- College of Environmental Sciences and Engineering, North China Electric Power University, Beijing, 102206, China; Key Laboratory of Resources and Environmental Systems Optimization, Ministry of Education, College of Environmental Science and Engineering, North China Electric Power University, Beijing 102206, China.
| | - Yang Liu
- College of Environmental Sciences and Engineering, North China Electric Power University, Beijing, 102206, China; Key Laboratory of Resources and Environmental Systems Optimization, Ministry of Education, College of Environmental Science and Engineering, North China Electric Power University, Beijing 102206, China
| | - Xiao Yan
- Beijing Municipal Research Institute of Environmental Protection, Beijing 100037, China
| | - Jian Gao
- Chinese Research Academy of Environmental Sciences, Beijing, 100012, China
| | - Lin Peng
- College of Environmental Sciences and Engineering, North China Electric Power University, Beijing, 102206, China; Key Laboratory of Resources and Environmental Systems Optimization, Ministry of Education, College of Environmental Science and Engineering, North China Electric Power University, Beijing 102206, China
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30
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Analysis of the Characteristics of Ozone Pollution in the North China Plain from 2016 to 2020. ATMOSPHERE 2022. [DOI: 10.3390/atmos13050715] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
As a major gaseous pollutant, ozone (O3) adversely affects human health and ecosystems. In recent years, ozone pollution in China has gradually become a prominent issue, especially in the North China Plain (NCP). To study the long-term spatio-temporal variation patterns of O3 in the NCP, this study selected 230 monitoring stations in the NCP from 2016 to 2020 as research objects, used the Kriging interpolation method and global Moran’s index to discuss the spatial-temporal distribution of O3, combining meteorological and social statistical data to analyze the causes underlying regional differences. The temporal analysis demonstrated that the O3-8h average concentrations increased annually from 2016 to 2018 and decreased from 2019 to 2020. The O3 concentrations were higher in spring and summer (117.89–154.20 μg/m3) and lower in autumn and winter (53.81–92.95 μg/m3). The spatial analysis revealed that O3 concentrations were low in the north and south of the NCP but high in the central area. The spatial distribution of O3 exhibited considerable cross-seasonal variability. Both meteorological conditions of high temperature and low pressure increased O3 concentrations. The spatial distribution of O3 varied depending on the period. However, the central and western regions of the Shandong Province were constantly characterized by high O3 concentrations. This pattern has been likely formed by heavy industry in the Shandong Province, as large-scale industrial production and frequent traffic flows produce a large amount of precursors, thereby exacerbating regional O3 pollution. These characteristics were attributed to emission reduction policies, meteorological conditions, the emission intensity of anthropogenic sources, and regional transport in the NCP. Overall, for cities with heavy industrial facilities in the central NCP, a timely adjustment of the energy and industrial structure, effectively controlling the emission of precursors, promoting new clean energy, and strengthening regional joint prevention and control are effective ways to alleviate O3 pollution.
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31
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Prediction of the Impact of Meteorological Conditions on Air Quality during the 2022 Beijing Winter Olympics. SUSTAINABILITY 2022. [DOI: 10.3390/su14084574] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
The issue of air pollution has attracted more and more attention. Understanding how to predict air quality based on weather conditions has strong practical significance. For the first time, this paper combines weather circulation with climate prediction models to explore long-term air quality predictions. Using the T-mode (time realizations in columns) objective circulation classification method, we classified the weather circulation affecting Beijing, China, according to nine categories of predominant weather conditions. PM2.5, NO2, SO2, and CO concentration distributions for these nine circulation patterns were also determined. When the Beijing area was controlled by northwestern low pressure, a high-pressure rear, or a weak pressure field, the PM2.5 concentrations were higher, while high-pressure systems and a high-pressure rear were mostly associated with relatively high NO2, SO2, and CO concentrations. The concentrations of these pollutants under high-pressure fronts and northwestern high-pressure settings were low. Using the FLEXPART-WRF model to simulate the 48 h backward trajectory of the highest PM2.5 concentration under the nine circulation patterns from 2015 to 2021, we obtained the trap time of pollutants per unit concentration (imprint analysis) and determined the particle trap area under each circulation pattern. When using the EC-Earth climate prediction model, the daily circulation field during the Beijing Winter Olympics was forecasted, and the nine circulation patterns were compared. The corresponding circulation pattern in Beijing during the 2022 Winter Olympics should be conducive to the diffusion of pollutants and, therefore, the air quality is expected to be good.
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32
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Gong S, Liu Y, He J, Zhang L, Lu S, Zhang X. Multi-scale analysis of the impacts of meteorology and emissions on PM 2.5 and O 3 trends at various regions in China from 2013 to 2020 1: Synoptic circulation patterns and pollution. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 815:152770. [PMID: 34990661 DOI: 10.1016/j.scitotenv.2021.152770] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/20/2021] [Revised: 12/20/2021] [Accepted: 12/25/2021] [Indexed: 06/14/2023]
Abstract
A multiscale analysis of meteorological trends was carried out to investigate the impacts of the large-scale circulation types as well as the local-scale key weather elements on the complex air pollutants, i.e. PM2.5 and O3 in China. As the first paper in the series, the relationship between synoptic circulation patterns and pollution was investigated. Six types of circulation patterns are defined and clustered to correlate with the observed pollutant levels, resulting in the identification of the impact similarity and difference of circulations on PM2.5 and O3 for three regions in China, i.e., the BTH (Beijing, Tianjin and Hebei), YRD (Yangtze River Delta) and PRD (Peral River Delta), from 2013 to 2020. It is found that the six clustered circulation patterns were able to classify the circulation patterns that influence the pollutants and yield significant correlations with O3 and PM2.5 in three regions. The major circulation patterns governing the heavy PM2.5 and O3 were identified separately for each region and found to show inter-annual variabilities. Composite analysis indicated that there were some circulation patterns that caused the dual-highs of PM2.5 and O3 with about 13%, 8% and 3% occurrences during the period of 2013 to 2020 in Beijing, Shanghai and Guangzhou, respectively. The key weather elements for each type of circulation pattern were also identified. A detailed study of the impacts of key weather elements and emissions on the PM2.5 and O3 trends will accompany this paper (Gong et al., 2022).
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Affiliation(s)
- Sunling Gong
- State Key Laboratory of Severe Weather, Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing 100081, China.
| | - Yilin Liu
- Zigong Meteorological Bureau, No.126, Xiyuan Street, Ziliujing District, Zigong, Sichuan Province 643000, China
| | - Jianjun He
- State Key Laboratory of Severe Weather, Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing 100081, China.
| | - Lei Zhang
- State Key Laboratory of Severe Weather, Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing 100081, China
| | - Shuhua Lu
- State Key Laboratory of Severe Weather, Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing 100081, China
| | - Xiaoye Zhang
- State Key Laboratory of Severe Weather, Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing 100081, China
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33
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Zhao K, Wu Y, Yuan Z, Huang J, Liu X, Ma W, Xu D, Jiang R, Duan Y, Fu Q, Xu W. Understanding the underlying mechanisms governing the linkage between atmospheric oxidative capacity and ozone precursor sensitivity in the Yangtze River Delta, China: A multi-tool ensemble analysis. ENVIRONMENT INTERNATIONAL 2022; 160:107060. [PMID: 34952358 DOI: 10.1016/j.envint.2021.107060] [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: 10/06/2021] [Revised: 12/19/2021] [Accepted: 12/20/2021] [Indexed: 06/14/2023]
Abstract
Continued exacerbation of ozone (O3) pollution in China has driven the urgent need for an emission control strategy that efficiently reduces O3 levels. Determining O3 precursor sensitivity (OPS) and its driving factors is a prerequisite for formulating effective O3 control strategies. In this study, we proposed an atmospheric oxidative capacity-based indicator, HO2/OH, and demonstrated its effectiveness in indicating OPS over the Yangtze River Delta (YRD) of China by applying a localized comprehensive air quality model with extensions (CAMx) coupled with the Weather Research and Forecasting (WRF) model. A strong correlation was discovered between HO2/OH and OPS, and HO2/OH showed the best performance in separating NOx- and VOC-limited regimes in comparison with other commonly used indicators. A comprehensive analysis with ensemble diagnostic tools revealed the spatial heterogeneity of NOx and VOC emissions and the impact of regional transport controlling the relationship between OPS variations and the HO2/OH indicator over the YRD. The process analysis results show that days with higher contributions from horizontal advection favored OPS transitions in Shanghai, Nanjing, Hefei, Suzhou, and Wuhu, while vertical advection caused OPS transitions in Hangzhou and Ningbo. O3 source apportionment technology analysis indicated that the regional contributions from Zhejiang and Jiangsu/Anhui corresponded well to the NOx-limited and VOC-limited regimes, respectively. Our results provide a better understanding of the underlying mechanisms of the relationship between OPS and the HO2/OH indicator and can help guide contingency control measures for O3 despiking over the YRD and other photochemically active regions worldwide.
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Affiliation(s)
- Kaihui Zhao
- School of Environment and Energy, South China University of Technology, Guangzhou 510006, China
| | - Yonghua Wu
- The City College of New York (CCNY), New York, NY 10031, USA; NOAA-Cooperative Science Center for Earth System Sciences and Remote Sensing Technologies, New York, NY 10031, USA
| | - Zibing Yuan
- School of Environment and Energy, South China University of Technology, Guangzhou 510006, China.
| | - Jianping Huang
- NOAA-NCEP Environmental Modeling Center and IM System Group Inc., College Park, MD 720740, USA; Yale-NUIST Center on Atmospheric Environment, Nanjing University of Information Science & Technology, Nanjing 210044, China
| | - Xuehui Liu
- School of Environment and Energy, South China University of Technology, Guangzhou 510006, China
| | - Wei Ma
- School of Environment and Energy, South China University of Technology, Guangzhou 510006, China
| | - Danni Xu
- School of Environment and Energy, South China University of Technology, Guangzhou 510006, China
| | - Rongsheng Jiang
- Jiangsu Meteorological Service Center, Nanjing 210008, China
| | - Yusen Duan
- Shanghai Environmental Monitoring Center, Shanghai 200235, China
| | - Qingyan Fu
- Shanghai Environmental Monitoring Center, Shanghai 200235, China
| | - Wei Xu
- Xianyang Meteorological Bureau, Xianyang 712000, China
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34
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Chen W, Wang W, Jia S, Mao J, Yan F, Zheng L, Wu Y, Zhang X, Dong Y, Kong L, Zhong B, Chang M, Shao M, Wang X. A New Index Developed for Fast Diagnosis of Meteorological Roles in Ground-Level Ozone Variations. ADVANCES IN ATMOSPHERIC SCIENCES 2022; 39:403-414. [PMID: 35079193 PMCID: PMC8773386 DOI: 10.1007/s00376-021-1257-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/06/2021] [Revised: 09/08/2021] [Accepted: 10/08/2021] [Indexed: 05/09/2023]
Abstract
China experienced worsening ground-level ozone (O3) pollution from 2013 to 2019. In this study, meteorological parameters, including surface temperature (T 2 ), solar radiation (SW), and wind speed (WS), were classified into two aspects, (1) Photochemical Reaction Condition (PRC = T 2 × SW) and (2) Physical Dispersion Capacity (PDC = WS). In this way, a Meteorology Synthetic Index (MSI = PRC/PDC) was developed for the quantification of meteorology-induced ground-level O3 pollution. The positive linear relationship between the 90th percentile of MDA8 (maximum daily 8-h average) O3 concentration and MSI determined that the contribution of meteorological changes to ground-level O-3 varied on a latitudinal gradient, decreasing from ∼40% in southern China to 10%-20% in northern China. Favorable photochemical reaction conditions were more important for ground-level O3 pollution. This study proposes a universally applicable index for fast diagnosis of meteorological roles in ground-level O3 variability, which enables the assessment of the observed effects of precursor emissions reductions that can be used for designing future control policies. ELECTRONIC SUPPLEMENTARY MATERIAL Supplementary material is available in the online version of this article at 10.1007/s00376-021-1257-x.
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Affiliation(s)
- Weihua Chen
- Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Institute for Environmental and Climate Research, Jinan University, Guangzhou, 510632 China
| | - Weiwen Wang
- Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Institute for Environmental and Climate Research, Jinan University, Guangzhou, 510632 China
| | - Shiguo Jia
- School of Atmospheric Sciences, Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies, Sun Yat-sen University, Guangzhou, 510275 China
| | - Jingying Mao
- Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Institute for Environmental and Climate Research, Jinan University, Guangzhou, 510632 China
| | - Fenghua Yan
- Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Institute for Environmental and Climate Research, Jinan University, Guangzhou, 510632 China
| | - Lianming Zheng
- Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Institute for Environmental and Climate Research, Jinan University, Guangzhou, 510632 China
| | - Yongkang Wu
- Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Institute for Environmental and Climate Research, Jinan University, Guangzhou, 510632 China
| | - Xingteng Zhang
- Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Institute for Environmental and Climate Research, Jinan University, Guangzhou, 510632 China
| | - Yutong Dong
- Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Institute for Environmental and Climate Research, Jinan University, Guangzhou, 510632 China
| | - Lingbin Kong
- Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Institute for Environmental and Climate Research, Jinan University, Guangzhou, 510632 China
| | - Buqing Zhong
- Key Laboratory of Vegetation Restoration and Management of Degraded Ecosystems, South China Botanical Garden, Chinese Academy of Sciences, Guangzhou, 510650 China
| | - Ming Chang
- Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Institute for Environmental and Climate Research, Jinan University, Guangzhou, 510632 China
| | - Min Shao
- Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Institute for Environmental and Climate Research, Jinan University, Guangzhou, 510632 China
| | - Xuemei Wang
- Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Institute for Environmental and Climate Research, Jinan University, Guangzhou, 510632 China
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Gu Y, Liu B, Dai Q, Zhang Y, Zhou M, Feng Y, Hopke PK. Multiply improved positive matrix factorization for source apportionment of volatile organic compounds during the COVID-19 shutdown in Tianjin, China. ENVIRONMENT INTERNATIONAL 2022; 158:106979. [PMID: 34991244 DOI: 10.1016/j.envint.2021.106979] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/10/2021] [Revised: 10/13/2021] [Accepted: 11/10/2021] [Indexed: 06/14/2023]
Abstract
Ambient concentrations of volatile organic compounds (VOCs) vary with emission rates, meteorology, and chemistry. Conventional positive matrix factorization (PMF) loses information because of dilution variations and chemical losses. Multiply improved PMF incorporates the ventilation coefficient, and total solar radiation or oxidants to reduce the effects of dispersion and chemical loss. These methods were applied to hourly speciated VOC data from November 2019 to March 2020 including during the COVID-19 shutdown. Various comparisons were made to assess the influences of these fluctuation drivers by time of day. Dispersion normalized PMF (DN-PMF) reduced the dispersion variations. Dispersion-radiation normalized PMF (DRN-PMF) reduced the impact of chemical loss, especially at night, which was better than Dispersion-Ox normalized PMF (DON-PMF). The conditional bivariate probability function (CBPF) plots of DRN-PMF results were consist with actual source locations. The DN-PMF, DRN-PMF, and DON-PMF results were consistent between 10:00 and 15:00, suggesting dispersion was significantly more influential than photochemical reactions during these times. The DRN-PMF results indicated that the highest VOC contributors during the COVID-19 shutdown were liquefied petroleum gas (LPG) (28.8%), natural gas (25.2%), and pulverized coal boilers emissions (19.6%). Except for petrochemical-related enterprises and LPG, the contribution concentrations of all other sources decreased substantially during the COVID-19 shutdown, by 94.7%, 90.6%, and 86.8% for vehicle emissions, gasoline evaporation, and the mixed source of diesel evaporation and solvent use, respectively. Controlling the use of motor vehicles and related volatilization of diesel fuel and gasoline can be effective in controlling VOCs in the future.
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Affiliation(s)
- Yao Gu
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control & Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China; CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health Research, Tianjin 300350, China
| | - Baoshuang Liu
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control & Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China; CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health Research, Tianjin 300350, China.
| | - Qili Dai
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control & Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China; CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health Research, Tianjin 300350, China
| | - Yufen Zhang
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control & Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China; CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health Research, Tianjin 300350, China
| | - Ming Zhou
- State Key Joint Laboratory of Environment Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Yinchang Feng
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control & Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China; CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health Research, Tianjin 300350, China
| | - Philip K Hopke
- Department of Public Health Sciences, University of Rochester School of Medicine and Dentistry, Rochester, NY 14642, USA; Institute for a Sustainable Environment, Clarkson University, Potsdam, NY 13699, USA
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Zhao Z, Zhou Z, Russo A, Du H, Xiang J, Zhang J, Zhou C. Impact of meteorological conditions at multiple scales on ozone concentration in the Yangtze River Delta. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2021; 28:62991-63007. [PMID: 34218370 DOI: 10.1007/s11356-021-15160-2] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/21/2020] [Accepted: 06/23/2021] [Indexed: 05/16/2023]
Abstract
Tropospheric ozone is known to have adverse effects on human health. Ozone pollution events are often associated with specific atmospheric circulation conditions. Therefore, studying the relationship between atmospheric circulation and ozone is particularly important for early warning and forecasting of ozone pollution events. Focusing on the Yangtze River Delta region, particularly in four important large industrial cities (Xuzhou, Nanjing, Shanghai, and Hangzhou) in the Yangtze River Delta, the T-mode objective classification method was applied to classify the weather circulation that mainly affects the Yangtze River Delta region into nine types. Local wind fields for the four industrial cities were classified according to their propensity for ventilation, stagnation, and recirculation based on the Allwine and Whiteman method. Based on the analysis of large-scale atmospheric circulation, we concluded that certain circulation patterns correspond to excessive ozone concentrations, while other circulation patterns correspond to good air quality. Moreover, ozone pollution was not closely related to local regional transmission. The importance of high temperatures in potentiating ozone pollution was also identified in the study area, whereas the effect of relative humidity was negligible. Finally, the importance of the different scale atmospheric motions was analyzed by studying two specific ozone pollution events in Xuzhou area (March, 2019) and Nanjing area (July-August, 2017). This analysis was complemented by HYSPLIT model's outputs to simulate the pollutant diffusion path. Regarding the first episode, ozone concentration is often closely related to the slowly approaching thermal high-pressure system. In the second episode, local transmission had little effect on the generation and spread of ozone pollution. Furthermore, and comparing the circulation conditions with local meteorological factors, it was found that the increase in ozone concentration was often accompanied by higher temperature, and the response to humidity was not clear.
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Affiliation(s)
- Zezheng Zhao
- National University of Defense Technology, College of Meteorology and Oceanology, Nanjing, 211101, China
| | - Zeming Zhou
- National University of Defense Technology, College of Meteorology and Oceanology, Nanjing, 211101, China
| | - Ana Russo
- Instituto Dom Luíz, Faculdade de Ciências da Universidade de Lisboa, Campo Grande, Edifício C1, Piso 1, 1749-016, Lisboa, Portugal
| | - Huadong Du
- National University of Defense Technology, College of Meteorology and Oceanology, Nanjing, 211101, China
| | - Jie Xiang
- National University of Defense Technology, College of Meteorology and Oceanology, Nanjing, 211101, China
| | - Jiping Zhang
- Department of Atmospheric and Oceanic Sciences, School of Physics, Peking University, Beijing, 100871, China
| | - Chengjun Zhou
- National University of Defense Technology, College of Meteorology and Oceanology, Nanjing, 211101, China.
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Ma M, Yao G, Guo J, Bai K. Distinct spatiotemporal variation patterns of surface ozone in China due to diverse influential factors. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2021; 288:112368. [PMID: 33773209 DOI: 10.1016/j.jenvman.2021.112368] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/01/2020] [Revised: 02/28/2021] [Accepted: 03/10/2021] [Indexed: 06/12/2023]
Abstract
A better knowledge of surface ozone variations and the relevant influential factors is of great significance for controlling frequent ozone pollution events. In this study, we first examined the primary variation patterns of surface ozone in space and time across China via a clustering analysis on the basis of daily maximum 8h average surface ozone (MDA8) between 2015 and 2018. Statistical models were then established between MDA8 and a set of influential factors to pinpoint dominant factors contributing to regional MDA8 variations. The clustering results revealed four typical variation patterns of MDA8 in China given distinct pollution levels, seasonality, and long-term trends. Statistical modeling results indicated that the seasonal variability of MDA8 was closely associated with UV radiation and meteorological factors like boundary layer height, temperature and relative humidity. In contrast, the long-term trends of MDA8 were largely linked to ozone precursors and meteorological variables including temperature, relative humidity, and total cloud cover. Moreover, the phenomenal increasing trends of MDA8 in North China were found to be statistically associated with the depletion of nitrogen dioxide (NO2) and carbon monoxide (CO). Specifically, substantial increases in volatile organic compounds (VOCs) along with depletions in NO2 and CO significantly boosted the photochemical ozone formation chain process in a VOC-limited regime like the North China plain. Overall, the inferred linkage in this study provides evidence and clues to help control increasing ozone pollution events in North China.
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Affiliation(s)
- Mingliang Ma
- School of Surveying and Geo-Informatics, Shandong Jianzhu University, Jinan, 250101, China
| | - Guobiao Yao
- School of Surveying and Geo-Informatics, Shandong Jianzhu University, Jinan, 250101, China
| | - Jianping Guo
- State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing, 100081, China
| | - Kaixu Bai
- Key Laboratory of Geographic Information Science (Ministry of Education), East China Normal University, Shanghai, 200241, China; School of Geographic Sciences, East China Normal University, Shanghai, 200241, China.
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Briz-Redón Á, Belenguer-Sapiña C, Serrano-Aroca Á. Changes in air pollution during COVID-19 lockdown in Spain: A multi-city study. J Environ Sci (China) 2021; 101:16-26. [PMID: 33334512 PMCID: PMC7402215 DOI: 10.1016/j.jes.2020.07.029] [Citation(s) in RCA: 101] [Impact Index Per Article: 25.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2020] [Revised: 07/29/2020] [Accepted: 07/31/2020] [Indexed: 05/08/2023]
Abstract
The COVID-19 pandemic has escalated into one of the largest crises of the 21st Century. The new SARS-CoV-2 coronavirus, responsible for COVID-19, has spread rapidly all around the world. The Spanish Government was forced to declare a nationwide lockdown in view of the rapidly spreading virus and high mortality rate in the nation. This study investigated the impact of short-term lockdown during the period from March 15th to April 12th 2020 on the atmospheric levels of CO, SO2, PM10, O3, and NO2 over 11 representative Spanish cities. The possible influence of several meteorological factors (temperature, precipitation, wind, sunlight hours, minimum and maximum pressure) on the pollutants' levels were also considered. The results obtained show that the 4-week lockdown had significant impact on reducing the atmospheric levels of NO2 in all cities except for the small city of Santander as well as CO, SO2, and PM10 in some cities, but resulted in increase of O3 level.
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Affiliation(s)
- Álvaro Briz-Redón
- Statistics Office, City Council of Valencia, c/Arquebisbe Mayoral, 2, 46002 Valencia, Valencia, Spain
| | - Carolina Belenguer-Sapiña
- Department of Analytical Chemistry, Faculty of Chemistry, University of Valencia, c/Doctor Moliner 50, 46100 Burjassot, Valencia, Spain
| | - Ángel Serrano-Aroca
- Centro de Investigación Traslacional San Alberto Magno, Universidad Católica de Valencia San Vicente Mártir, c/Guillem de Castro 94, 46001 Valencia, Valencia, Spain.
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