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Mogane B, Kachienga LO, Kamika I, Ngobeni-Nyambi R, Momba MNB. Distribution of host-specific Bacteriodales marker genes in water sources of selected rural areas of Vhembe District, South Africa. Sci Rep 2024; 14:19758. [PMID: 39187527 PMCID: PMC11347707 DOI: 10.1038/s41598-024-68771-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2024] [Accepted: 07/29/2024] [Indexed: 08/28/2024] Open
Abstract
Access to safe drinking water sources and appropriate sanitation facilities remains a dream in low and middle-income countries including South Africa. This study identified the origin of faecal pollution by using quantitative polymerase chain reaction (qPCR) targeting host-specific Bacteroidales genetic markers to track the distribution of human-specific (BacHum) and animal-specific (cattle-BacCow, chicken-Cytb, pig-Pig-2-Bac, dog-BacCan) markers in water sources used by rural communities of the Vhembe District Municipality (VDM). Results revealed the prevalence of BacHum, BacCow, and BacCan in all surface water sources in Thulamela Local Municipality (TLM) and Collins Chabane Local Municipality (CLM) during wet (100%) and dry seasons (50-75%). Cytb was not detected in untreated spring water in TLM and CLM, and Pig-2-Bac was not detected in untreated hand-dug well water in TLM during both seasons. Household-level analysis detected Cytb (28.8% wet, 17.5% dry), BacHum (34.4% wet, 25% dry for Pig-2-Bac) in stored untreated spring water in CLM, and Cytb (42.9% wet, 28.5% dry) in untreated hand-dug well water in TLM. Despite differences in detection frequencies of host-specific Bacteroidales, the study highlights the public health concern of faecal pollution in rural VDM households.
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Affiliation(s)
- Barbara Mogane
- Department of Environmental, Water and Earth Sciences, Arcadia Campus, Tshwane University of Technology, 175 Nelson Mandela Avenue, Arcadia, Pretoria, 0001, South Africa
| | - Leonard Owino Kachienga
- Department of Environmental, Water and Earth Sciences, Arcadia Campus, Tshwane University of Technology, 175 Nelson Mandela Avenue, Arcadia, Pretoria, 0001, South Africa
| | - Ilunga Kamika
- Department of Environmental Sciences, School of Environmental Science, College of Agriculture and Environmental Sciences, Faculty of Sciences, Florida Campus, University of South Africa, Florida, Roodepoort, 1710, South Africa
| | - Renay Ngobeni-Nyambi
- Department of Microbiology, Stellenbosch University, Private Bag, X1, Mitieland, 7602, South Africa
| | - Maggy Ndombo Benteke Momba
- Department of Environmental, Water and Earth Sciences, Arcadia Campus, Tshwane University of Technology, 175 Nelson Mandela Avenue, Arcadia, Pretoria, 0001, South Africa.
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Dong Z, Jiang Y, Wang S, Xing J, Ding D, Zheng H, Wang H, Huang C, Yin D, Song Q, Zhao B, Hao J. Spatially and Temporally Differentiated NO x and VOCs Emission Abatement Could Effectively Gain O 3-Related Health Benefits. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2024; 58:9570-9581. [PMID: 38781138 DOI: 10.1021/acs.est.4c01345] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/25/2024]
Abstract
The increasing level of O3 pollution in China significantly exacerbates the long-term O3 health damage, and an optimized health-oriented strategy for NOx and VOCs emission abatement is needed. Here, we developed an integrated evaluation and optimization system for the O3 control strategy by merging a response surface model for the O3-related mortality and an optimization module. Applying this system to the Yangtze River Delta (YRD), we evaluated driving factors for mortality changes from 2013 to 2017, quantified spatial and temporal O3-related mortality responses to precursor emission abatement, and optimized a health-oriented control strategy. Results indicate that insufficient NOx emission abatement combined with deficient VOCs control from 2013 to 2017 aggravated O3-related mortality, particularly during spring and autumn. Northern YRD should promote VOCs control due to higher VOC-limited characteristics, whereas fastening NOx emission abatement is more favorable in southern YRD. Moreover, promotion of NOx mitigation in late spring and summer and facilitating VOCs control in spring and autumn could further reduce O3-related mortality by nearly 10% compared to the control strategy without seasonal differences. These findings highlight that a spatially and temporally differentiated NOx and VOCs emission control strategy could gain more O3-related health benefits, offering valuable insights to regions with severe ozone pollution all over the world.
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Affiliation(s)
- Zhaoxin Dong
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
- State Environmental Protection Key Laboratory of Formation and Prevention of the Urban Air Pollution Complex, Shanghai Academy of Environment Sciences, Shanghai 200233, China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
| | - Yueqi Jiang
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
| | - Shuxiao Wang
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
| | - Jia Xing
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
| | - Dian Ding
- Institute for Atmospheric and Earth System Research/Physics, Faculty of Science, University of Helsinki, 00014 Helsinki, Finland
| | - Haotian Zheng
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
| | - Hongli Wang
- State Environmental Protection Key Laboratory of Formation and Prevention of the Urban Air Pollution Complex, Shanghai Academy of Environment Sciences, Shanghai 200233, China
| | - Cheng Huang
- State Environmental Protection Key Laboratory of Formation and Prevention of the Urban Air Pollution Complex, Shanghai Academy of Environment Sciences, Shanghai 200233, China
| | - Dejia Yin
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
| | - Qian Song
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
| | - Bin Zhao
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
| | - Jiming Hao
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
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Wang S, Zhu Y, Jang JC, Jiang M, Yue D, Zhong L, Yuan Y, Zhang M, You Z. Modeling assessment of air pollution control measures and COVID-19 pandemic on air quality improvements over Greater Bay Area of China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 926:171951. [PMID: 38537836 DOI: 10.1016/j.scitotenv.2024.171951] [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: 12/19/2023] [Revised: 03/04/2024] [Accepted: 03/23/2024] [Indexed: 04/17/2024]
Abstract
A remarkable progress has been made toward the air quality improvements over the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) of China from 2017 to 2020. In this study, for the first time, the emission reductions of regional control measures together with the COVID-19 pandemic were considered simultaneously into the development of the GBA's emission inventories for the years of 2017 and 2020. Based on these collective emission inventories, the impacts of control measures, meteorological variations together with temporary COVID-19 lockdowns on the five major air quality index pollutants (SO2, NO2, PM2.5, PM10, and O3, excluding CO) were evaluated using the WRF-CMAQ and SMAT-CE model attainment assessment tool over the GBA region. Our results revealed that control measures in the Pearl River Delta (PRD) region affected significantly the GBA, resulting in pollutant reductions ranging from 48 % to 64 %. In contrast, control measures in Hong Kong and Macao contributed to pollutant reductions up to 10 %. In PRD emission sectors, stationary combustion, on-road, industrial processes and dust sectors stand out as the primary contributors to overall air quality improvements. Moreover, the COVID-19 pandemic during period I (Jan 23-Feb 23) led to a reduction of NO2 concentration by 7.4 %, resulting in a negative contribution (disbenefit) for O3 with an increase by 2.4 %. Our findings highlight the significance of PRD control measures for the air quality improvements over the GBA, emphasizing the necessity of implementing more refined and feasible manageable joint prevention and control policies.
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Affiliation(s)
- Shaoyi Wang
- Guangdong Provincial Key Laboratory of Atmospheric Environment and Pollution Control, College of Environment and Energy, South China University of Technology, Guangzhou Higher Education Mega Center, Guangzhou 510006, China
| | - Yun Zhu
- Guangdong Provincial Key Laboratory of Atmospheric Environment and Pollution Control, College of Environment and Energy, South China University of Technology, Guangzhou Higher Education Mega Center, Guangzhou 510006, China.
| | - Ji-Cheng Jang
- Guangdong Provincial Key Laboratory of Atmospheric Environment and Pollution Control, College of Environment and Energy, South China University of Technology, Guangzhou Higher Education Mega Center, Guangzhou 510006, China
| | - Ming Jiang
- Guangdong Ecological and Environmental Monitoring Center, Guangzhou 510308, China
| | - Dingli Yue
- Guangdong Ecological and Environmental Monitoring Center, Guangzhou 510308, China
| | - Liuju Zhong
- Guangdong Polytechnic of Environmental Protection Engineering, Foshan 528216, China
| | - Yingzhi Yuan
- Guangdong Provincial Key Laboratory of Atmospheric Environment and Pollution Control, College of Environment and Energy, South China University of Technology, Guangzhou Higher Education Mega Center, Guangzhou 510006, China
| | - Mengmeng Zhang
- Guangdong Provincial Key Laboratory of Atmospheric Environment and Pollution Control, College of Environment and Energy, South China University of Technology, Guangzhou Higher Education Mega Center, Guangzhou 510006, China
| | - Zhiqiang You
- Guangdong Provincial Key Laboratory of Atmospheric Environment and Pollution Control, College of Environment and Energy, South China University of Technology, Guangzhou Higher Education Mega Center, Guangzhou 510006, China
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Kusumaningtyas SDA, Tonokura K, Muharsyah R, Gunawan D, Sopaheluwakan A, Iriana W, Lestari P, Permadi DA, Rahmawati R, Samputra NAR. Comprehensive analysis of long-term trends, meteorological influences, and ozone formation sensitivity in the Jakarta Greater Area. Sci Rep 2024; 14:9605. [PMID: 38671080 PMCID: PMC11053138 DOI: 10.1038/s41598-024-60374-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2024] [Accepted: 04/19/2024] [Indexed: 04/28/2024] Open
Abstract
Jakarta Greater Area (JGA) has encountered recurrent challenges of air pollution, notably, high ozone levels. We investigate the trends of surface ozone (O3) changes from the air quality monitoring stations and resolve the contribution of meteorological drivers in urban Jakarta (2010-2019) and rural Bogor sites (2017-2019) using stepwise Multi Linear Regression. During 10 years of measurement, 41% of 1-h O3 concentrations exceeded Indonesia' s national threshold in Jakarta. In Bogor, 0.1% surpassed the threshold during 3 years of available data records. The monthly average of maximum daily 8-h average (MDA8) O3 anomalies exhibited a downward trend at Jakarta sites while increasing at the rural site of Bogor. Meteorological and anthropogenic drivers contribute 30% and 70%, respectively, to the interannual O3 anomalies in Jakarta. Ozone formation sensitivity with satellite demonstrates that a slight decrease in NO2 and an increase in HCHO contributed to declining O3 in Jakarta with 10 years average of HCHO to NO2 ratio (FNR) of 3.7. Conversely, O3 increases in rural areas with a higher FNR of 4.4, likely due to the contribution from the natural emission of O3 precursors and the influence of meteorological factors that magnify the concentration.
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Affiliation(s)
- Sheila Dewi Ayu Kusumaningtyas
- Agency for Meteorology, Climatology, and Geophysics of the Republic of Indonesia (BMKG), Jl. Angkasa I, No.2, Kemayoran, Jakarta, 10720, Indonesia.
- Department of Environment Systems, Graduate School of Frontier Sciences, The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba, 277-8563, Japan.
| | - Kenichi Tonokura
- Department of Environment Systems, Graduate School of Frontier Sciences, The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba, 277-8563, Japan.
| | - Robi Muharsyah
- Agency for Meteorology, Climatology, and Geophysics of the Republic of Indonesia (BMKG), Jl. Angkasa I, No.2, Kemayoran, Jakarta, 10720, Indonesia
| | - Dodo Gunawan
- School of Meteorology, Climatology, and Geophysics (STMKG), Agency for Meteorology, Climatology, and Geophysics of Republic of Indonesia (BMKG), Pondok Betung, Tangerang Selatan, Indonesia
| | - Ardhasena Sopaheluwakan
- Agency for Meteorology, Climatology, and Geophysics of the Republic of Indonesia (BMKG), Jl. Angkasa I, No.2, Kemayoran, Jakarta, 10720, Indonesia
| | - Windy Iriana
- Department of Environmental Engineering, Faculty of Civil and Environmental Engineering, Bandung Institute of Technology (ITB), Jl. Ganesa No. 10, Bandung, 40132, Indonesia
- Center for Environmental Studies, Bandung Institute of Technology (ITB), Jl. Sangkuriang No.42 A, Bandung, 40135, Indonesia
| | - Puji Lestari
- Department of Environmental Engineering, Faculty of Civil and Environmental Engineering, Bandung Institute of Technology (ITB), Jl. Ganesa No. 10, Bandung, 40132, Indonesia
| | - Didin Agustian Permadi
- Department of Environmental Engineering, Faculty of Civil Engineering and Planning, National Institute of Technology (ITENAS), Jl. PKH. Mustopha No.23, Bandung, 40124, Indonesia
| | - R Rahmawati
- Jakarta Provincial Environmental Agency, Jl. Mandala V No.67, RT.1/RW.2, Cililitan, Jakarta, 13640, Indonesia
| | - Nofi Azzah Rawaani Samputra
- Jakarta Provincial Environmental Agency, Jl. Mandala V No.67, RT.1/RW.2, Cililitan, Jakarta, 13640, Indonesia
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Wang L, Ju T, Li B, Xia X, Huang C, Lv Z, Gu Z. Analysis of human health effects under ozone exposure in the oasis area of Hetao Plain. ENVIRONMENTAL MONITORING AND ASSESSMENT 2024; 196:426. [PMID: 38573396 DOI: 10.1007/s10661-024-12579-1] [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: 11/21/2023] [Accepted: 03/23/2024] [Indexed: 04/05/2024]
Abstract
This article, based on OMI data products, utilizes spatial distribution, ozone-sensitive control areas, Pearson correlation methods, and the Ben-MAP model to study the changes in ozone column concentration from 2018 to 2022, along with the influencing factors and the health of populations exposed to ozone. The findings suggest a spatial variation in the ozone column concentration within the study area, with an increasing trend observed from west to east and from south to north. Over time, the ozone column concentration exhibits an initial increase followed by a subsequent decrease, with the peak concentration observed in 2019 at 37.45 DU and the nadir recorded in 2022 at 33.10 DU. The monthly mean distribution exhibits an inverted V-shaped pattern during the warm season from April to September, with a peak in July (46.71 DU) and a trough in April (35.29 DU). The Hetao Plain Oasis area is primarily a NOx control area in sensitive control areas. The concentrations of O3 and precursor HCHO exhibited significant positive correlations with vegetation index and air temperature, while showing significant negative correlations with wind speed and air pressure. The precursor NO2, in contrast, exhibited a significant negative correlation with both the vegetation index and relative humidity. Based on the ground-based monitoring sites and analysis of human health benefits, the study area witnessed 1944.45 deaths attributed to warm season O3 exposure in 2018, with a subsequent reduction in premature deaths by 149.7, 588.2, and 231.75 for the years 2019 to 2021 respectively when compared to the baseline year. In 2021, the observed decrease in warm-season O3 concentration within that region compared to 2018 resulted in a significant reduction, leading to the prevention of 126 premature deaths.
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Affiliation(s)
- Lanzhi Wang
- College of Geography and Environmental Sciences, Northwest Normal University, Lanzhou, 730000, China
- The Key Laboratory of Resource Environment and Sustainable Development of Oasis, Jiayuguan, 730000, Gansu Province, China
- Gansu Province Environmental Science and Engineering Demonstration Laboratory, Lanzhou, 202018, China
| | - Tianzhen Ju
- College of Geography and Environmental Sciences, Northwest Normal University, Lanzhou, 730000, China.
- The Key Laboratory of Resource Environment and Sustainable Development of Oasis, Jiayuguan, 730000, Gansu Province, China.
- Gansu Province Environmental Science and Engineering Demonstration Laboratory, Lanzhou, 202018, China.
| | - Bingnan Li
- Faculty of Atmospheric Remote Sensing, Shaanxi Normal University, Xi'an, 710062, China
| | - Xuhui Xia
- College of Geography and Environmental Sciences, Northwest Normal University, Lanzhou, 730000, China
- The Key Laboratory of Resource Environment and Sustainable Development of Oasis, Jiayuguan, 730000, Gansu Province, China
- Gansu Province Environmental Science and Engineering Demonstration Laboratory, Lanzhou, 202018, China
| | - Cheng Huang
- College of Geography and Environmental Sciences, Northwest Normal University, Lanzhou, 730000, China
- The Key Laboratory of Resource Environment and Sustainable Development of Oasis, Jiayuguan, 730000, Gansu Province, China
- Gansu Province Environmental Science and Engineering Demonstration Laboratory, Lanzhou, 202018, China
| | - Zhichao Lv
- College of Geography and Environmental Sciences, Northwest Normal University, Lanzhou, 730000, China
- The Key Laboratory of Resource Environment and Sustainable Development of Oasis, Jiayuguan, 730000, Gansu Province, China
- Gansu Province Environmental Science and Engineering Demonstration Laboratory, Lanzhou, 202018, China
| | - Zhenrong Gu
- College of Geography and Environmental Sciences, Northwest Normal University, Lanzhou, 730000, China
- The Key Laboratory of Resource Environment and Sustainable Development of Oasis, Jiayuguan, 730000, Gansu Province, China
- Gansu Province Environmental Science and Engineering Demonstration Laboratory, Lanzhou, 202018, China
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Li P, Chen C, Liu D, Lian J, Li W, Fan C, Yan L, Gao Y, Wang M, Liu H, Pan X, Mao J. Characteristics and source apportionment of ambient volatile organic compounds and ozone generation sensitivity in urban Jiaozuo, China. J Environ Sci (China) 2024; 138:607-625. [PMID: 38135424 DOI: 10.1016/j.jes.2023.04.016] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2022] [Revised: 04/15/2023] [Accepted: 04/17/2023] [Indexed: 12/24/2023]
Abstract
In recent years, many cities have taken measures to reduce volatile organic compounds (VOCs), an important precursor of ozone (O3), to alleviate O3 pollution in China. 116 VOC species were measured by online and offline methods in the urban area of Jiaozuo from May to October in 2021 to analyze the compositional characteristics. VOC sources were analyzed by a positive matrix factorization (PMF) model, and the sensitivity of ozone generation was determined by ozone isopleth plotting research (OZIPR) simulation. The results showed that the average volume concentration of total VOCs was 30.54 ppbv and showed a bimodal feature due to the rush-hour traffic in the morning and at nightfall. The most dominant VOC groups were oxygenated VOCs (OVOCs, 29.3%) and alkanes (26.7%), and the most abundant VOC species were acetone and acetylene. However, based on the maximum incremental reactivity (MIR) method, the major VOC groups in terms of ozone formation potential (OFP) contribution were OVOCs (68.09 µg/m3, 31.5%), aromatics (62.90 µg/m3, 29.1%) and alkene/alkynes (54.90 µg/m3, 25.4%). This indicates that the control of OVOCs, aromatics and alkene/alkynes should take priority. Five sources of VOCs were quantified by PMF, including fixed sources of fossil fuel combustion (27.8%), industrial processes (25.9%), vehicle exhaust (19.7%), natural and secondary formation (13.9%) and solvent usage (12.7%). The empirical kinetic modeling approach (EKMA) curve obtained by OZIPR on O3 exceedance days indicated that the O3 sensitivity varied in different months. The results provide theoretical support for O3 pollution prevention and control in Jiaozuo.
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Affiliation(s)
- Pengzhao Li
- State Centre for International Cooperation on Designer Low-Carbon and Environmental Materials, School of Materials Science and Engineering, Zhengzhou University, Zhengzhou 450001, China
| | - Chun Chen
- State Centre for International Cooperation on Designer Low-Carbon and Environmental Materials, School of Materials Science and Engineering, Zhengzhou University, Zhengzhou 450001, China; Henan Key Laboratory of Environmental Monitoring Technology, Henan Ecological Environment Monitoring and Safety Center, Zhengzhou 450046, China
| | - Dan Liu
- Henan Key Laboratory of Environmental Monitoring Technology, Henan Ecological Environment Monitoring and Safety Center, Zhengzhou 450046, China
| | - Jie Lian
- Jiaozuo Ecological Environment Monitoring Center of Henan Province, Jiaozuo 454003, China
| | - Wei Li
- Jiaozuo Ecological Environment Monitoring Center of Henan Province, Jiaozuo 454003, China
| | - Chuanyi Fan
- Jiaozuo Ecological Environment Monitoring Center of Henan Province, Jiaozuo 454003, China
| | - Liangyu Yan
- State Centre for International Cooperation on Designer Low-Carbon and Environmental Materials, School of Materials Science and Engineering, Zhengzhou University, Zhengzhou 450001, China
| | - Yue Gao
- State Centre for International Cooperation on Designer Low-Carbon and Environmental Materials, School of Materials Science and Engineering, Zhengzhou University, Zhengzhou 450001, China
| | - Miao Wang
- State Centre for International Cooperation on Designer Low-Carbon and Environmental Materials, School of Materials Science and Engineering, Zhengzhou University, Zhengzhou 450001, China
| | - Hang Liu
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
| | - Xiaole Pan
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China.
| | - Jing Mao
- State Centre for International Cooperation on Designer Low-Carbon and Environmental Materials, School of Materials Science and Engineering, Zhengzhou University, Zhengzhou 450001, China.
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Qi H, Duan W, Cheng S, Huang Z, Hou X. Research on regional ozone prevention and control strategies in eastern China based on pollutant transport network and FNR. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 918:170486. [PMID: 38311077 DOI: 10.1016/j.scitotenv.2024.170486] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/14/2023] [Revised: 01/08/2024] [Accepted: 01/24/2024] [Indexed: 02/06/2024]
Abstract
O3 pollution in China has worsened sharply in recent years, and O3 formation sensitivity (OFS) in many regions have gradually changed, with eastern China as the most typical region. This study constructed the transport networks of O3 and NO2 in different seasons from 2017 to 2020. The transport trends and the clustering formation patterns were summarized by analyzing the topological characteristics of the transport networks, and the patterns of OFS changes were diagnosed by analyzing the satellite remote sensing data. Based on that, the main clusters that each province or city belongs to in different pollutant transport networks were summarized and proposals for the inter-regional joint prevention and control were put forward. As the results showed, O3 transport activity was most active in spring and summer and least active in winter, while NO2 transport activity was most active in autumn and winter and least active in summer. OFS in summer mainly consisted of transitional regimes and NOx-limited regimes, while that in other seasons was mainly VOC-limited regimes. Notably, there was a significant upward trend in the proportion of transitional regimes and NOx-limited regimes in spring, autumn, and winter. For regions showing NOx-limited regime, areas with higher out-weighted degrees in the NO2 transport network should focus on controlling local NOx emissions, such as central regions in summer. For regions showing VOC-limited regime, areas with higher out-weighted degrees in the O3 transport network should focus on controlling local VOCs emissions, such as central and south-central regions in summer. For regions that belong to the same cluster and present the same OFS in each specific season, regional cooperative emission reduction strategies should be established to block important transmission paths and weaken regional pollution consistency.
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Affiliation(s)
- Haoyun Qi
- Key Laboratory of Beijing on Regional Air Pollution Control, Faculty of Environment and Life, Beijing University of Technology, Beijing 100124, China
| | - Wenjiao Duan
- Sino-Japan Friendship Center for Environmental Protection, Beijing 100029, China.
| | - Shuiyuan Cheng
- Key Laboratory of Beijing on Regional Air Pollution Control, Faculty of Environment and Life, Beijing University of Technology, Beijing 100124, China
| | - Zijian Huang
- Key Laboratory of Beijing on Regional Air Pollution Control, Faculty of Environment and Life, Beijing University of Technology, Beijing 100124, China
| | - Xiaosong Hou
- Key Laboratory of Beijing on Regional Air Pollution Control, Faculty of Environment and Life, Beijing University of Technology, Beijing 100124, China
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8
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Tan Y, Han S, Chen Y, Wu Z, Lee SC. Long-term variation and evaluation of air quality across Hong Kong. J Environ Sci (China) 2023; 127:284-294. [PMID: 36522060 DOI: 10.1016/j.jes.2022.05.009] [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: 02/15/2022] [Revised: 05/06/2022] [Accepted: 05/06/2022] [Indexed: 06/17/2023]
Abstract
Study of Air Quality Objectives (AQOs) and long-term changes of air pollution plays a decisive role in formulating and refining pollution control strategies. In this study, 10-year variations of six major air pollutants were analyzed at seven monitoring sites in Hong Kong. The continuous decrease of annual averaged concentrations of NO2, SO2, CO, PM2.5 and PM10 and numbers of days with severe pollution conditions validated the efficiency of the series of air pollution control schemes implemented by the Hong Kong government. However, there is still a big gap to meet the ultimate targets described by the World Health Organization. Besides, the concentration of O3 at roadside and urban stations increased by 135% ± 25% and 37% ± 18% from 2011 to 2020, respectively, meanwhile the highest 8 hr averaged O3 concentration was observed as 294 µg/m3 at background station in 2020, which pointed out the increasing ozone pollution in Hong Kong. There was a great decrease in the annual times of air quality health index (AQHI) laying in "high", "very high" and "serious" categories from 2011 to 2020 with the decrease rate of 89.70%, 91.30% and 89.74% at roadside stations, and 79.03%, 95.98% and 72.73% at urban stations, respectively. Nevertheless, the number of days categorized as "high" or above at roadside station was twice more than that in the urban station during the past ten years. Thus, more policies and attentions should be given to the roadside air quality and its adverse health effect to pedestrians on street.
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Affiliation(s)
- Yan Tan
- School of Environmental and Municipal Engineering, Qingdao University of Technology, Qingdao 266520, China
| | - Shuwen Han
- Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Hong Kong SAR 999077, China
| | - Yi Chen
- Division of Environment and Sustainability, The Hong Kong University of Science and Technology, Hong Kong SAR 999077, China
| | - Zhongbiao Wu
- Key Laboratory of Environment Remediation and Ecological Health, Ministry of Education, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China
| | - Shun-Cheng Lee
- Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Hong Kong SAR 999077, China.
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Chen Y, Wang M, Yao Y, Zeng C, Zhang W, Yan H, Gao P, Fan L, Ye D. Research on the ozone formation sensitivity indicator of four urban agglomerations of China using Ozone Monitoring Instrument (OMI) satellite data and ground-based measurements. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 869:161679. [PMID: 36682570 DOI: 10.1016/j.scitotenv.2023.161679] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/02/2022] [Revised: 01/12/2023] [Accepted: 01/14/2023] [Indexed: 06/17/2023]
Abstract
Near surface ozone is a typical secondary pollutant, and is mostly generated by a series of complex photochemical reactions of volatile organic compounds (VOCs) and nitrogen oxides (NOx) in the air under sunlight. At present, a large number of studies have applied FNR (a ratio of formaldehyde (HCHO) to nitrogen dioxide (NO2) retrieved by satellite) indicator to study the ozone formation sensitivity (OFS). OFS analysis is critical for taking targeted ozone pollution prevention and control measures. Regional OFS can be more accurately diagnosed by utilizing localized FNR threshold. In this study, localized FNR thresholds were established for four severe ozone polluted urban agglomerations in China (Beijing-Tianjin-Hebei (BTH) region, Yangtze River Delta (YRD) region, Pearl River Delta (PRD) region, and Chengdu-Chongqing (CY) region), based on the statistical analysis between FNR (obtained from OMI observation, with daily transit time of approximately 13:45 local standard time) and ΔO3/ΔNO2 (the ratio of ozone change to nitrogen dioxide change between two consecutive months, obtained from ground measurements) from 2014 to 2016. And these thresholds were verified by the statistical analysis between FNR and ΔO3/O3 (ozone change rate between two consecutive months), and between FNR and O3 concentration during the OFS significant shift months. Furthermore, the results were also compared and verified with the method proposed by previous studies. The results indicate that there are significant regional dependences in the FNR threshold, and the lower-upper limits for the four urban agglomerations are as follows: 0.65-1.21 for BTH, 0.64-1.48 for the YRD, 1.25-2.39 for the PRD, and 1.44-3.69 for CY (FNR < lower limit indicates VOCs-limited regime; lower limit < FNR < upper limit indicates transitional regime; FNR > upper limit indicates NOx-limited regime). This method eliminates the problems associated with the undifferentiated use of FNR thresholds in different regions and significantly reduces the deviations for OFS.
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Affiliation(s)
- Yuping Chen
- School of Environment and Energy, South China University of Technology, Guangzhou 510006, China
| | - Meiyuan Wang
- School of Environment and Energy, South China University of Technology, Guangzhou 510006, China
| | - Yijuan Yao
- School of Environment and Energy, South China University of Technology, Guangzhou 510006, China
| | - Chunling Zeng
- School of Environment and Energy, South China University of Technology, Guangzhou 510006, China
| | - Wei Zhang
- School of Environment and Energy, South China University of Technology, Guangzhou 510006, China
| | - Hui Yan
- School of Environment and Energy, South China University of Technology, Guangzhou 510006, China
| | - Ping Gao
- School of Environment and Energy, South China University of Technology, Guangzhou 510006, China
| | - Liya Fan
- School of Environment and Energy, South China University of Technology, Guangzhou 510006, China; National Engineering Laboratory for Volatile Organic Compounds Pollution Control Technology and Equipment, Guangzhou 510006, China; Guangdong Provincial Key Laboratory of Atmospheric Environment and Pollution Control, Guangzhou 510006, China; Guangdong Provincial Engineering and Technology Research Centre for Environmental Risk Prevention and Emergency Disposal, Guangzhou 510006, China.
| | - Daiqi Ye
- School of Environment and Energy, South China University of Technology, Guangzhou 510006, China; National Engineering Laboratory for Volatile Organic Compounds Pollution Control Technology and Equipment, Guangzhou 510006, China; Guangdong Provincial Key Laboratory of Atmospheric Environment and Pollution Control, Guangzhou 510006, China; Guangdong Provincial Engineering and Technology Research Centre for Environmental Risk Prevention and Emergency Disposal, Guangzhou 510006, China
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10
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Yang G, Liu Y, Li W, Zhou Z. Association analysis between socioeconomic factors and urban ozone pollution in China. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023; 30:17597-17611. [PMID: 36197615 DOI: 10.1007/s11356-022-23298-w] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/18/2022] [Accepted: 09/23/2022] [Indexed: 06/16/2023]
Abstract
Ozone pollution in China has gradually increased, attracting extensive attention. Existing studies on ozone pollution typically take environmental and chemical perspectives. As air pollution is closely related to social and economic activities, it is also important to study ozone pollution from a socioeconomic perspective. Using the association rule mining technique, we uncovered hidden patterns between ozone variance and socioeconomic factors in macro-, meso-, and micro-scenarios in 297 Chinese cities. We found that the acceleration of urbanization and industrialization has indeed aggravated urban ozone pollution. The supply of water and power resources may be a significant factor influencing urban ozone pollution. Transportation hub cities with more developed economies and industries are more likely to suffer from ozone pollution in summer and autumn. Human behavior is a critical factor influencing the weekly variance in ozone concentration during weekdays and weekends. The influence of plant-derived VOC emissions on the formation of ozone cannot be overlooked. Our results deepen the understanding of ozone pollution in Chinese cities, and we provide corresponding policy recommendations to alleviate ozone pollution and improve air quality.
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Affiliation(s)
- Guangfei Yang
- Institute of Systems Engineering, Dalian University of Technology, No. 2 Linggong Road, Ganjingzi District, Dalian City, 116024, Liaoning Province, China
| | - Yuhong Liu
- Institute of Systems Engineering, Dalian University of Technology, No. 2 Linggong Road, Ganjingzi District, Dalian City, 116024, Liaoning Province, China
| | - Wenli Li
- Institute of Systems Engineering, Dalian University of Technology, No. 2 Linggong Road, Ganjingzi District, Dalian City, 116024, Liaoning Province, China
| | - Ziyao Zhou
- Institute of Systems Engineering, Dalian University of Technology, No. 2 Linggong Road, Ganjingzi District, Dalian City, 116024, Liaoning Province, China.
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11
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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: 0.5] [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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12
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Mao J, Yan F, Zheng L, You Y, Wang W, Jia S, Liao W, Wang X, Chen W. Ozone control strategies for local formation- and regional transport-dominant scenarios in a manufacturing city in southern China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 813:151883. [PMID: 34826481 DOI: 10.1016/j.scitotenv.2021.151883] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/14/2021] [Revised: 10/23/2021] [Accepted: 11/18/2021] [Indexed: 06/13/2023]
Abstract
Given the leveling off of fine particulate matter (PM2.5), ground-level ozone (O3) pollution has become one of the most significant atmospheric pollution issues in the Pearl River Delta (PRD) region in China, especially in the manufacturing city of Dongguan, which faces more severe O3 pollution. The development of strategies to control O3 precursor emissions, including volatile organic compounds (VOCs) and nitrogen oxide (NOx), depends to a large extent on the source region of the O3 pollution. In this study, by combining the Weather Research and Forecasting model coupled with chemistry (WRF-Chem), the Empirical Kinetic Modeling Approach (EKMA), and the Flexible Particle model (FLEXPART), more effective strategies of controlling O3 precursor emissions were identified under two typical types of O3 pollution episodes: local formation (LF)-dominant (8-12 September 2019) and regional transport (RT)-dominant (23-27 October 2017) episodes, distinguished by the WRF-FLEXPART model. During the LF-dominant episode, the EKMA revealed that the O3 formation in Dongguan was in a transitional regime, and the abatement of solvent use-VOCs emissions in the key area of Dongguan was more effective in reducing O3 levels, with an emission reduction benefit 1.7 times that of total VOCs emission sources throughout Dongguan. With respect to the RT-dominant episode, the reduction in VOCs emissions in the local region did not effectively curb O3 pollution, although the photochemical regime of the O3 formation in Dongguan was VOCs-limited. A 50% reduction in NOx emissions in the upwind regions (parts of Guangzhou and Huizhou) effectively decreased the O3 concentration in Dongguan by 17%. The results of this study emphasize the importance of the source region of O3 pollution in the implementation of effective O3 control strategies and provide valuable insights for region-specific precursor emission policy formulation, not only in Dongguan, but also in other regions facing severe O3 pollution.
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Affiliation(s)
- Jingying Mao
- Guangdong-Hong Kong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Institute for Environmental and Climate Research, Jinan University, Guangzhou 510632, PR China
| | - Fenghua Yan
- Guangdong-Hong Kong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Institute for Environmental and Climate Research, Jinan University, Guangzhou 510632, PR China
| | - Lianming Zheng
- Guangdong-Hong Kong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Institute for Environmental and Climate Research, Jinan University, Guangzhou 510632, PR China
| | - Yingchang You
- Guangdong-Hong Kong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Institute for Environmental and Climate Research, Jinan University, Guangzhou 510632, PR China
| | - Weiwen Wang
- Guangdong-Hong Kong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Institute for Environmental and Climate Research, Jinan University, Guangzhou 510632, PR 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
| | - Wenhui Liao
- Guangdong University of Finance, Guangzhou 510521, PR China
| | - Xuemei Wang
- Guangdong-Hong Kong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Institute for Environmental and Climate Research, Jinan University, Guangzhou 510632, PR China
| | - Weihua Chen
- Guangdong-Hong Kong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Institute for Environmental and Climate Research, Jinan University, Guangzhou 510632, PR China.
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13
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Li C, Liu Y, Cheng B, Zhang Y, Liu X, Qu Y, An J, Kong L, Zhang Y, Zhang C, Tan Q, Feng M. A comprehensive investigation on volatile organic compounds (VOCs) in 2018 in Beijing, China: Characteristics, sources and behaviours in response to O 3 formation. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 806:150247. [PMID: 34562762 DOI: 10.1016/j.scitotenv.2021.150247] [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: 06/12/2021] [Revised: 08/22/2021] [Accepted: 09/05/2021] [Indexed: 06/13/2023]
Abstract
Observations of volatile organic compounds (VOCs) are a prerequisite for evaluating the effectiveness of government efforts targeting VOC pollution. Here, based on the one-year online VOC measurement in 2018 in Beijing, systematic analyses and model simulation were conducted to illuminate VOC characteristics, emission sources, regional hotspots and behaviours in response to O3 formation. The observed mean VOC concentration in 2018 was 29.12 ± 17.64 ppbv declined distinctly compared to that in 2015 and 2016. Vehicle exhaust (39.95%), natural gas/liquefied petroleum gas (22.04%) and industrial sources (20.64%) were the main contributors to VOCs in Beijing. Regional transport, mainly from the south-south-east (SSE) and south-south-west (SSW), quantitatively contributed 36.65%-55.06% to VOCs based on our developed method. O3 sensitivity tended to be in the transition regime in summer identified by ground-based and satellite observations. Strong solar radiation along with high temperature and low humidity aggravated O3 pollution that was further intensified by regional transport from southern polluted regions. The model simulation determined that turning off CH3CHO related reactions brought about the most predominantly short-term and long-run O3 reduction, indicating that control policies in VOC species should be tailored, instead of one-size-fits-all. Overall, region-collaborated and active VOC-species-focused strategies on VOC controls are imperative.
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Affiliation(s)
- Chenlu Li
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, China
| | - Yafei Liu
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, China
| | - Bingfen Cheng
- Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Yuepeng Zhang
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, China
| | - Xingang Liu
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, China.
| | - Yu Qu
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China.
| | - Junling An
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
| | - Liuwei Kong
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, China
| | - Yingying Zhang
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, China
| | - Chen Zhang
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, China
| | - Qinwen Tan
- Chengdu Academy of Environmental Sciences, Chengdu 610072, China
| | - Miao Feng
- Chengdu Academy of Environmental Sciences, Chengdu 610072, China
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14
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Liu C, Shi K. A review on methodology in O 3-NOx-VOC sensitivity study. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2021; 291:118249. [PMID: 34600066 DOI: 10.1016/j.envpol.2021.118249] [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: 06/15/2021] [Revised: 08/26/2021] [Accepted: 09/26/2021] [Indexed: 06/13/2023]
Abstract
Gaining insight into the response of surface ozone (O3) formation to its precursors plays an important role in the policy-making of O3 pollution control. However, the real atmosphere is an open and dissipative system, and its complexity poses a great challenge to the study of nonlinear relations between O3 and its precursors. At present, model-based methods based on reductionism try to restore the real atmospheric photochemical system, by coupling meteorological model and chemical transport model in temporal and spatial resolution completely. Nevertheless, large inconsistencies between predictions and true values still exist, due to the great uncertainty originated from emission inventory, photochemical reaction mechanism and meteorological factors. Recently, based on field observations, some nonlinear methods have successfully revealed the complex emergent properties (long-term persistence, multi-fractal, etc) in coupling correlation between O3 and its precursors at different time scales. The emergent properties are closely associated with the intrinsic dynamics of atmospheric photochemical system. Taking them into account when building O3 prediction model, is helpful to reduce the uncertainty in the results. Nonlinear methods (fractal, chaos, etc) based on holism can give new insights into the nonlinear relations between O3 and its precursors. Changes of thinking models in methodology are expected to improve the precision of forecasting O3 concentration. This paper has reviewed the advances of different methods for studying the sensitivity of O3 formation to its precursors during the past few decades. This review highlights that it is necessary to incorporate the emergent properties obtained by nonlinear methods into the modern models, for assessing O3 formation under combined air pollution environment more accurately. Moreover, the scaling property of coupling correlation detected in the real observations of O3 and its precursors could be used to test and improve the simulation performance of modern models.
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Affiliation(s)
- Chunqiong Liu
- College of Environmental Sciences and Engineering, China West Normal University, Nanchong, Sichuan, China; College of Biology and Environmental Sciences, Jishou University, Jishou, Hunan, China
| | - Kai Shi
- College of Environmental Sciences and Engineering, China West Normal University, Nanchong, Sichuan, China; College of Biology and Environmental Sciences, Jishou University, Jishou, Hunan, China.
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