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Cui Y, Liu B, Yang Y, Kang S, Wang F, Xu M, Wang W, Feng Y, Hopke PK. Primary and oxidative source analyses of consumed VOCs in the atmosphere. JOURNAL OF HAZARDOUS MATERIALS 2024; 476:134894. [PMID: 38909463 DOI: 10.1016/j.jhazmat.2024.134894] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/21/2024] [Revised: 05/27/2024] [Accepted: 06/11/2024] [Indexed: 06/25/2024]
Abstract
Consumed VOCs are the compounds that have reacted to form ozone and secondary organic aerosol (SOA) in the atmosphere. An approach that can apportion the contributions of primary sources and reactions to the consumed VOCs was developed in this study and applied to hourly VOCs data from June to August 2022 measured in Shijiazhuang, China. The results showed that petrochemical industries (36.9 % and 51.7 %) and oxidation formation (20.6 % and 35.6 %) provided the largest contributions to consumed VOCs and OVOCs during the study period, whereas natural gas (5.0 % and 7.6 %) and the mixed source of liquefied petroleum gas and solvent use (3.1 % and 4.2 %) had the relatively low contributions. Compared to the non-O3 pollution (NOP) period, the contributions of oxidation formation, petrochemical industries, and the mixed source of gas evaporation and vehicle emissions to the consumed VOCs during the O3 pollution (OP) period increased by 2.8, 3.8, and 9.3 times, respectively. The differences in contributions of liquified petroleum gas and solvent use, natural gas, and combustion sources to consumed VOCs between OP and NOP periods were relatively small. Transport of petrochemical industries emissions from the southeast to the study site was the primary consumed pathway for VOCs emitted from petrochemical industries.
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Affiliation(s)
- Yaqi Cui
- 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.
| | - Yufeng Yang
- 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
| | - Sicong Kang
- Beijing Make Environment Science & Technology Co., Ltd., Beijing 100083, China
| | - Fuquan Wang
- Beijing Make Environment Science & Technology Co., Ltd., Beijing 100083, China
| | - Man Xu
- Shijiazhuang Environmental Prediction Center, Shijiazhuang 050022, China
| | - Wei Wang
- Shijiazhuang Environmental Prediction Center, Shijiazhuang 050022, 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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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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Zhang W, Liu D, Tian H, Pan N, Yang R, Tang W, Yang J, Lu F, Dayananda B, Mei H, Wang S, Shi H. Parsimonious estimation of hourly surface ozone concentration across China during 2015-2020. Sci Data 2024; 11:492. [PMID: 38744849 PMCID: PMC11094007 DOI: 10.1038/s41597-024-03302-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2024] [Accepted: 04/24/2024] [Indexed: 05/16/2024] Open
Abstract
Surface ozone is an important air pollutant detrimental to human health and vegetation productivity, particularly in China. However, high resolution surface ozone concentration data is still lacking, largely hindering accurate assessment of associated environmental impacts. Here, we collected hourly ground ozone observations (over 6 million records), remote sensing products, meteorological data, and social-economic information, and applied recurrent neural networks to map hourly surface ozone data (HrSOD) at a 0.1° × 0.1° resolution across China during 2015-2020. The coefficient of determination (R2) values in sample-based, site-based, and by-year cross-validations were 0.72, 0.65 and 0.71, respectively, with the root mean square error (RMSE) values being 11.71 ppb (mean = 30.89 ppb), 12.81 ppb (mean = 30.96 ppb) and 11.14 ppb (mean = 31.26 ppb). Moreover, it exhibits high spatiotemporal consistency with ground-level observations at different time scales (diurnal, seasonal, annual), and at various spatial levels (individual sites and regional scales). Meanwhile, the HrSOD provides critical information for fine-resolution assessment of surface ozone impacts on environmental and human benefits.
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Affiliation(s)
- Wenxiu Zhang
- State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, 100085, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Di Liu
- State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, 100085, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Hanqin Tian
- Schiller Institute of Integrated Science and Society, Boston College, Chestnut Hill, MA, 02467, USA
| | - Naiqin Pan
- Schiller Institute of Integrated Science and Society, Boston College, Chestnut Hill, MA, 02467, USA
- College of Forestry, Wildlife and Environment, Auburn University, Auburn, AL, 36849, USA
| | - Ruqi Yang
- Department of Forest and Wildlife Ecology, University of Wisconsin-Madison, Madison, WI, 53706, USA
| | - Wenhan Tang
- Department of Atmospheric Sciences, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
| | - Jia Yang
- Natural Resource Ecology & Management, Oklahoma State University, Stillwater, OK, 74078, USA
| | - Fei Lu
- State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, 100085, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Buddhi Dayananda
- School of Agriculture and Food Sciences, The University of Queensland, Brisbane, QLD 4072, Australia
| | - Han Mei
- Division of Environment and Sustainability, The Hong Kong University of Science and Technology, Hong Kong, 999077, China
| | - Siyuan Wang
- State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, 100085, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Hao Shi
- State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, 100085, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
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Ziegler AK, Jensen JK, Jiménez-Gallardo L, Rissler J, Gudmundsson A, Nilsson JÅ, Isaksson C. Dietary fatty acids modulate oxidative stress response to air pollution but not to infection. Front Physiol 2024; 15:1391806. [PMID: 38784118 PMCID: PMC11112072 DOI: 10.3389/fphys.2024.1391806] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2024] [Accepted: 04/17/2024] [Indexed: 05/25/2024] Open
Abstract
Anthropogenic changes to the environment expose wildlife to many pollutants. Among these, tropospheric ozone is of global concern and a highly potent pro-oxidant. In addition, human activities include several other implications for wildlife, e.g., changed food availability and changed distribution of pathogens in cities. These co-occurring habitat changes may interact, thereby modulating the physiological responses and costs related to anthropogenic change. For instance, many food items associated with humans (e.g., food waste and feeders for wild birds) contain relatively more ω6-than ω3-polyunsaturated fatty acids (PUFAs). Metabolites derived from ω6-PUFAs can enhance inflammation and oxidative stress towards a stimulus, whereas the opposite response is linked to ω3-derived metabolites. Hence, we hypothesized that differential intake of ω6-and ω3-PUFAs modulates the oxidative stress state of birds and thereby affects the responses towards pro-oxidants. To test this, we manipulated dietary ω6:ω3 ratios and ozone levels in a full-factorial experiment using captive zebra finches (Taeniopygia guttata). Additionally, we simulated an infection, thereby also triggering the immune system's adaptive pro-oxidant release (i.e., oxidative burst), by injecting lipopolysaccharide. Under normal air conditions, the ω3-diet birds had a lower antioxidant ratio (GSH/GSSG ratio) compared to the ω6-diet birds. When exposed to ozone, however, the diet effect disappeared. Instead, ozone exposure overall reduced the total concentration of the key antioxidant glutathione (tGSH). Moreover, the birds on the ω6-rich diet had an overall higher antioxidant capacity (OXY) compared to birds fed a ω3-rich diet. Interestingly, only the immune challenge increased oxidative damage, suggesting the oxidative burst of the immune system overrides the other pro-oxidative processes, including diet. Taken together, our results show that ozone, dietary PUFAs, and infection all affect the redox-system, but in different ways, suggesting that the underlying responses are decoupled despite that they all increase pro-oxidant exposure or generation. Despite lack of apparent cumulative effect in the independent biomarkers, the combined single effects could together reduce overall cellular functioning and efficiency over time in wild birds exposed to pathogens, ozone, and anthropogenic food sources.
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Affiliation(s)
| | - Johan Kjellberg Jensen
- Department of Biology, Lund University, Lund, Sweden
- Centre for Environmental and Climate Science (CEC), Lund University, Lund, Sweden
| | - Lucía Jiménez-Gallardo
- Department of Biodiversity, Ecology and Evolution, Complutense University of Madrid, Madrid, Spain
| | - Jenny Rissler
- Ergonomics and Aerosol Technology, Department of Design Sciences, Lund University, Lund, Sweden
- Bioeconomy and Health, RISE Research Institutes of Sweden, Lund, Sweden
| | - Anders Gudmundsson
- Ergonomics and Aerosol Technology, Department of Design Sciences, Lund University, Lund, Sweden
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Chen TL, Hsiao TC, Chen AY, Chang KE, Lin TC, Griffith SM, Chou CCK. A traffic-induced shift of ultrafine particle sources under COVID-19 soft lockdown in a subtropical urban area. ENVIRONMENT INTERNATIONAL 2024; 187:108658. [PMID: 38640612 DOI: 10.1016/j.envint.2024.108658] [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: 02/04/2024] [Revised: 04/10/2024] [Accepted: 04/11/2024] [Indexed: 04/21/2024]
Abstract
During the unprecedented COVID-19 city lockdown, a unique opportunity arose to dissect the intricate dynamics of urban air quality, focusing on ultrafine particles (UFPs) and volatile organic compounds (VOCs). This study delves into the nuanced interplay between traffic patterns and UFP emissions in a subtropical urban setting during the spring-summer transition of 2021. Leveraging meticulous roadside measurements near a traffic nexus, our investigation unravels the intricate relationship between particle number size distribution (PNSD), VOCs mixing ratios, and detailed vehicle activity metrics. The soft lockdown era, marked by a 20-27% dip in overall traffic yet a surprising surge in early morning motorcycle activity, presented a natural experiment. We observed a consequential shift in the urban aerosol regime: the decrease in primary emissions from traffic substantially amplified the role of aged particles and secondary aerosols. This shift was particularly pronounced under stagnant atmospheric conditions, where reduced dilution exacerbated the influence of alternative emission sources, notably solvent evaporation, and was further accentuated with the resumption of normal traffic flows. A distinct seasonal trend emerged as warmer months approached, with aromatic VOCs such as toluene, ethylbenzene, and xylene not only increasing but also significantly contributing to more frequent particle growth events. These findings spotlight the criticality of targeted strategies at traffic hotspots, especially during periods susceptible to weak atmospheric dilution, to curb UFP and precursor emissions effectively. As we stand at the cusp of widespread vehicle electrification, this study underscores the imperative of a holistic approach to urban air quality management, embracing the complexities of primary emission reductions and the resultant shifts in atmospheric chemistry.
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Affiliation(s)
- Tse-Lun Chen
- Institute of Environmental Engineering, National Sun Yat-sen University, Kaohsiung, Taiwan; Graduate Institute of Environmental Engineering, National Taiwan University, Taipei, Taiwan
| | - Ta-Chih Hsiao
- Graduate Institute of Environmental Engineering, National Taiwan University, Taipei, Taiwan; Research Center for Environmental Changes, Academia Sinica, Taipei, Taiwan.
| | - Albert Y Chen
- Department of Civil Engineering, National Taiwan University, Taipei, Taiwan
| | - Kuo-En Chang
- Graduate Institute of Environmental Engineering, National Taiwan University, Taipei, Taiwan
| | - Tzu-Chi Lin
- Graduate Institute of Environmental Engineering, National Taiwan University, Taipei, Taiwan
| | - Stephen M Griffith
- Department of Atmospheric Sciences, National Taiwan University, Taipei, Taiwan
| | - Charles C-K Chou
- Research Center for Environmental Changes, Academia Sinica, Taipei, Taiwan
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Mejía C D, Faican G, Zalakeviciute R, Matovelle C, Bonilla S, Sobrino JA. Spatio-temporal evaluation of air pollution using ground-based and satellite data during COVID-19 in Ecuador. Heliyon 2024; 10:e28152. [PMID: 38560184 PMCID: PMC10979269 DOI: 10.1016/j.heliyon.2024.e28152] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2023] [Revised: 02/27/2024] [Accepted: 03/13/2024] [Indexed: 04/04/2024] Open
Abstract
The concentration of gases in the atmosphere is a topic of growing concern due to its effects on health, ecosystems etc. Its monitoring is commonly carried out through ground stations which offer high precision and temporal resolution. However, in countries with few stations, such as Ecuador, these data fail to adequately describe the spatial variability of pollutant concentrations. Remote sensing data have great potential to solve this complication. This study evaluates the spatiotemporal distribution of nitrogen dioxide (NO2) and ozone (O3) concentrations in Quito and Cuenca, using data obtained from ground-based and Sentinel-5 Precursor mission sources during the years 2019 and 2020. Moreover, a Linear Regression Model (LRM) was employed to analyze the correlation between ground-based and satellite datasets, revealing positive associations for O3 (R2 = 0.83, RMSE = 0.18) and NO2 (R2 = 0.83, RMSE = 0.25) in Quito; and O3 (R2 = 0.74, RMSE = 0.23) and NO2, (R2 = 0.73, RMSE = 0.23) for Cuenca. The agreement between ground-based and satellite datasets was analyzed by employing the intra-class correlation coefficient (ICC), reflecting good agreement between them (ICC ≥0.57); and using Bland and Altman coefficients, which showed low bias and that more than 95% of the differences are within the limits of agreement. Furthermore, the study investigated the impact of COVID-19 pandemic-related restrictions, such as social distancing and isolation, on atmospheric conditions. This was categorized into three periods for 2019 and 2020: before (from January 1st to March 15th), during (from March 16th to May 17th), and after (from March 18th to December 31st). A 51% decrease in NO2 concentrations was recorded for Cuenca, while Quito experienced a 14.7% decrease. The tropospheric column decreased by 27.3% in Cuenca and 15.1% in Quito. O3 showed an increasing trend, with tropospheric concentrations rising by 0.42% and 0.11% for Cuenca and Quito respectively, while the concentration in Cuenca decreased by 14.4%. Quito experienced an increase of 10.5%. Finally, the reduction of chemical species in the atmosphere as a consequence of mobility restrictions is highlighted. This study compared satellite and ground station data for NO2 and O3 concentrations. Despite differing units preventing data validation, it verified the Sentinel-5P satellite's effectiveness in anomaly detection. Our research's value lies in its applicability to developing countries, which may lack extensive monitoring networks, demonstrating the potential use of satellite technology in urban planning.
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Affiliation(s)
- Danilo Mejía C
- Grupo CATOx – CEA de la Universidad de Cuenca, Campus Balzay, 010207 Cuenca, Ecuador
- Carrera de Ingeniería Ambiental de la Universidad de Cuenca, Campus Balzay, 010207 Cuenca, Ecuador
| | - Gina Faican
- Grupo CATOx – CEA de la Universidad de Cuenca, Campus Balzay, 010207 Cuenca, Ecuador
| | - Rasa Zalakeviciute
- Grupo de Biodiversidad Medio Ambiente y Salud (BIOMAS), Universidad de Las Americas, Quito - EC 170125, Ecuador
| | - Carlos Matovelle
- Carrera de Ingeniería Ambienta de la Universidad Católica de Cuenca, Ecuador
| | - Santiago Bonilla
- Research Center for the Territory and Sustainable Habitat, Universidad Tecnológica Indoamérica, Machala y Sabanilla, 170301 Quito, Ecuador
| | - José A. Sobrino
- Gobal Change Unit (GCU), Image Processing Laboratory (IPL), University of Valencia, Spain
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Alhajeri NS, Al-Fadhli FM, Aly A, Allen DT. Quantifying the impact of urban road traffic on air quality: activity pre-pandemic and during partial and full lockdowns. ENVIRONMENTAL MONITORING AND ASSESSMENT 2024; 196:418. [PMID: 38570428 DOI: 10.1007/s10661-024-12572-8] [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: 11/26/2023] [Accepted: 03/23/2024] [Indexed: 04/05/2024]
Abstract
The impact of partial and full COVID lockdowns in 2020 on vehicle miles traveled (VMT) in Kuwait was estimated using data extracted from the Directions API of Google Maps and a Python script running as a cronjob. This approach was validated by comparing the predictions based on the app to measuring traffic flows for 1 week across four road segments considered in this study. VMT during lockdown periods were compared to VMT for the same calendar weeks before the pandemic. NOx emissions were estimated based on VMT and were used to simulate the spatial patterns of NOx concentrations using an air quality model (AERMOD). Compared to pre-pandemic periods, VMT was reduced by up to 25.5% and 42.6% during the 2-week partial and full lockdown episodes, respectively. The largest reduction in the traffic flow rate occurred during the middle of these 2-week periods, when the traffic flow rate decreased by 35% and 49% during the partial and full lockdown periods, respectively. The AERMOD simulation results predicted a reduction in the average maximum concentration of emissions directly related to VMT across the region by up to 38%, with the maximum concentration shifting to less populous residential areas as a result of the lockdown.
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Affiliation(s)
- Nawaf S Alhajeri
- Department of Environmental Technology Management, College of Life Sciences, Kuwait University, 13060, Safat, Kuwait.
| | - Fahad M Al-Fadhli
- Department of Chemical Engineering, College of Engineering and Petroleum, Kuwait University, 13060, Safat, Kuwait
| | - Ahmed Aly
- Department of Chemical Engineering, College of Engineering and Petroleum, Kuwait University, 13060, Safat, Kuwait
| | - David T Allen
- Center for Energy and Environmental Resources, The University of Texas at Austin, 10100 Burnet Road, Building 133, M.S. R7100, Austin, TX, 78758, USA
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Shang B, Agathokleous E, Calatayud V, Peng J, Xu Y, Li S, Liu S, Feng Z. Drought mitigates the adverse effects of O 3 on plant photosynthesis rather than growth: A global meta-analysis considering plant functional types. PLANT, CELL & ENVIRONMENT 2024; 47:1269-1284. [PMID: 38185874 DOI: 10.1111/pce.14808] [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: 05/16/2023] [Accepted: 12/21/2023] [Indexed: 01/09/2024]
Abstract
Tropospheric ozone (O3 ) is a phytotoxic air pollutant adversely affecting plant growth. High O3 exposures are often concurrent with summer drought. The effects of both stresses on plants are complex, and their interactions are not yet well understood. Here, we investigate whether drought can mitigate the negative effects of O3 on plant physiology and growth based on a meta-analysis. We found that drought mitigated the negative effects of O3 on plant photosynthesis, but the modification of the O3 effect on the whole-plant biomass by drought was not significant. This is explained by a compensatory response of water-deficient plants that leads to increased metabolic costs. Relative to water control condition, reduced water treatment decreased the effects of O3 on photosynthetic traits, and leaf and root biomass in deciduous broadleaf species, while all traits in evergreen coniferous species showed no significant response. This suggested that the mitigating effects of drought on the negative impacts of O3 on the deciduous broadleaf species were more extensive than on the evergreen coniferous ones. Therefore, to avoid over- or underestimations when assessing the impact of O3 on vegetation growth, soil moisture should be considered. These results contribute to a better understanding of terrestrial ecosystem responses under global change.
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Affiliation(s)
- Bo Shang
- Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Nanjing University of Information Science and Technology, Nanjing, Jiangsu, China
- Key Laboratory of Ecosystem Carbon Source and Sink, China Meteorological Administration (ECSS-CMA), School of Ecology and Applied Meteorology, Nanjing University of Information Science and Technology, Nanjing, Jiangsu, China
| | - Evgenios Agathokleous
- Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Nanjing University of Information Science and Technology, Nanjing, Jiangsu, China
- Key Laboratory of Ecosystem Carbon Source and Sink, China Meteorological Administration (ECSS-CMA), School of Ecology and Applied Meteorology, Nanjing University of Information Science and Technology, Nanjing, Jiangsu, China
| | - Vicent Calatayud
- Fundación CEAM, c/Charles R. Darwin 14, Parque Tecnológico, Paterna, Valencia, Spain
| | - Jinlong Peng
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
| | - Yansen Xu
- Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Nanjing University of Information Science and Technology, Nanjing, Jiangsu, China
- Key Laboratory of Ecosystem Carbon Source and Sink, China Meteorological Administration (ECSS-CMA), School of Ecology and Applied Meteorology, Nanjing University of Information Science and Technology, Nanjing, Jiangsu, China
| | - Shuangjiang Li
- Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Nanjing University of Information Science and Technology, Nanjing, Jiangsu, China
- Key Laboratory of Ecosystem Carbon Source and Sink, China Meteorological Administration (ECSS-CMA), School of Ecology and Applied Meteorology, Nanjing University of Information Science and Technology, Nanjing, Jiangsu, China
| | - Shuo Liu
- Zhejiang Carbon Neutral Innovation Institute, Zhejiang University of Technology, Hangzhou, Zhejiang, China
| | - Zhaozhong Feng
- Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Nanjing University of Information Science and Technology, Nanjing, Jiangsu, China
- Key Laboratory of Ecosystem Carbon Source and Sink, China Meteorological Administration (ECSS-CMA), School of Ecology and Applied Meteorology, Nanjing University of Information Science and Technology, Nanjing, Jiangsu, China
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Lyu Y, Gao Y, Pang X, Sun S, Luo P, Cai D, Qin K, Wu Z, Wang B. Elucidating contributions of volatile organic compounds to ozone formation using random forest during COVID-19 pandemic: A case study in China. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2024; 346:123532. [PMID: 38365075 DOI: 10.1016/j.envpol.2024.123532] [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: 09/05/2023] [Revised: 11/10/2023] [Accepted: 02/07/2024] [Indexed: 02/18/2024]
Abstract
Ozone has been reported to increase despite nitrogen oxides reductions during the COVID-19 pandemic, and ozone formation needs to be revisited using volatile organic compounds (VOCs), which are rarely measured during the pandemic. Here, a total of 98 VOCs species were monitored in an economy-active city in China from January 2021 to August 2022 to assess contributions to ozone formation during the pandemic. Total VOCs concentrations were 35.55 ± 21.47 ppb during the entire period, among which alkanes account for the largest fraction (13.78 ppb, 38.0%), followed by aromatics (6.16 ppb, 16.8%) and oxygenated VOCs (OVOCs, 5.69 ppb, 15.7%). Most VOCs groups (e.g., alkenes, OVOCs) and individual species (e.g., isoprene, methyl vinyl ketone) display obvious seasonal and diurnal variations, which are related to their sources and reactivities. No weekend effects of VOCs suggest limited influences from traffic emissions during pandemic. Aromatics and alkenes are the major contributors (39% and 33%) to ozone formation potential, largely driven by o/m/p-xylene (21%), ethylene (15%), toluene (9%). Secondary organic aerosol formation potential is dominated by toluene (>50%) despite its low proportion (5%). Further inclusion of VOCs and meteorology in the Random Forest model shows good ozone prediction performance (R2 = 0.77-0.86, RMSE = 11.95-19.91 μg/m3, MAE = 8.89-14.58 μg/m3). VOCs and NO2 contribute >50% of total importance with the largest difference in importance ratio of VOCs/NO2 in the summer and winter, implying ozone formation regime may vary. No seasonal variations in importance of meteorology are observed, while importance of other variables (e.g., PM2.5) is highest in the summer. This work identifies critical VOCs groups and species for ozone formation during the pandemic, and demonstrates the feasibility of machine learning algorithms in elucidation of ozone formation mechanisms.
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Affiliation(s)
- Yan Lyu
- College of Environment, Zhejiang University of Technology, Hangzhou, 310014, China; School of Environment and Spatial Informatics, China University of Mining and Technology, Xuzhou, 221116, China; Shaoxing Research Institute, Zhejiang University of Technology, Shaoxing, 312077, China
| | - Yibu Gao
- College of Environment, Zhejiang University of Technology, Hangzhou, 310014, China
| | - Xiaobing Pang
- College of Environment, Zhejiang University of Technology, Hangzhou, 310014, China; Shaoxing Research Institute, Zhejiang University of Technology, Shaoxing, 312077, China.
| | - Songhua Sun
- Shaoxing Ecological and Environmental Monitoring Center of Zhejiang Province, Shaoxing, 312000, China
| | - Peisong Luo
- Shaoxing Ecological and Environmental Monitoring Center of Zhejiang Province, Shaoxing, 312000, China
| | - Dongmei Cai
- Department of Environment Sciences and Engineering, Fudan University, Shanghai, 200433, China
| | - Kai Qin
- School of Environment and Spatial Informatics, China University of Mining and Technology, Xuzhou, 221116, China
| | - Zhentao Wu
- College of Environment, Zhejiang University of Technology, Hangzhou, 310014, China
| | - Baozhen Wang
- Green Intelligence Environmental School, Yangtze Normal University, Chongqing, 408100, China
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10
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Zhang Y, Feng W. Impact of the coronavirus disease 2019 pandemic on the diversity of notifiable infectious diseases: a case study in Shanghai, China. PeerJ 2024; 12:e17124. [PMID: 38495754 PMCID: PMC10941765 DOI: 10.7717/peerj.17124] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2023] [Accepted: 02/26/2024] [Indexed: 03/19/2024] Open
Abstract
The outbreak of coronavirus disease 2019 (COVID-19) has not only posed significant challenges to public health but has also impacted every aspect of society and the environment. In this study, we propose an index of notifiable disease outbreaks (NDOI) to assess the impact of COVID-19 on other notifiable diseases in Shanghai, China. Additionally, we identify the critical factors influencing these diseases using multivariate statistical analysis. We collected monthly data on 34 notifiable infectious diseases (NIDs) and corresponding environmental and socioeconomic factors (17 indicators) from January 2017 to December 2020. The results revealed that the total number of cases and NDOI of all notifiable diseases decreased by 47.1% and 52.6%, respectively, compared to the period before the COVID-19 pandemic. Moreover, the COVID-19 pandemic has led to improved air quality as well as impacted the social economy and human life. Redundancy analysis (RDA) showed that population mobility, particulate matter (PM2.5), atmospheric pressure, and temperature were the primary factors influencing the spread of notifiable diseases. The NDOI is beneficial in establishing an early warning system for infectious disease epidemics at different scales. Furthermore, our findings also provide insight into the response mechanisms of notifiable diseases influenced by social and environmental factors.
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Affiliation(s)
- Yongfang Zhang
- School of Chemistry and Chemical Engineering, Zhoukou Normal University, Zhoukou, China
| | - Wenli Feng
- School of Chemistry and Chemical Engineering, Zhoukou Normal University, Zhoukou, China
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11
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Pan J, Li X, Zhu S. High-resolution estimation of near-surface ozone concentration and population exposure risk in China. ENVIRONMENTAL MONITORING AND ASSESSMENT 2024; 196:249. [PMID: 38340249 DOI: 10.1007/s10661-024-12416-5] [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: 10/14/2023] [Accepted: 01/29/2024] [Indexed: 02/12/2024]
Abstract
Considering the spatial and temporal effects of atmospheric pollutants, using the geographically and temporally weighted regression and geo-intelligent random forest (GTWR-GeoiRF) model and Sentinel-5P satellite remote sensing data, combined with meteorological, emission inventory, site observation, population, elevation, and other data, the high-precision ozone concentration and its spatiotemporal distribution near the ground in China from March 2020 to February 2021 were estimated. On this basis, the pollution status, near-surface ozone concentration, and population exposure risk were analyzed. The findings demonstrate that the estimation outcomes of the GTWR-GeoiRF model have high precision, and the precision of the estimation results is higher compared with that of the non-hybrid model. The downscaling method enhances estimation results to some extent while addressing the issue of limited spatial resolution in some data. China's near-surface ozone concentration distribution in space shows obvious regional and seasonal characteristics. The eastern region has the highest ozone concentrations and the lowest in the northeastern region, and the wintertime low is higher than the summertime high. There are significant differences in ozone population exposure risks, with the highest exposure risks being found in China's eastern region, with population exposure risks mostly ranging from 0.8 to 5.
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Affiliation(s)
- Jinghu Pan
- College of Geography and Environmental Science, Northwest Normal University, No. 967 Anning East Road, Lanzhou, Gansu Province, People's Republic of China.
| | - Xuexia Li
- College of Geography and Environmental Science, Northwest Normal University, No. 967 Anning East Road, Lanzhou, Gansu Province, People's Republic of China
| | - Shixin Zhu
- College of Geography and Environmental Science, Northwest Normal University, No. 967 Anning East Road, Lanzhou, Gansu Province, People's Republic of China
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12
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Navaratnam AMD, Williams H, Sharp SJ, Woodcock J, Khreis H. Systematic review and meta-analysis on the impact of COVID-19 related restrictions on air quality in low- and middle-income countries. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 908:168110. [PMID: 37884141 DOI: 10.1016/j.scitotenv.2023.168110] [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: 08/09/2023] [Revised: 10/19/2023] [Accepted: 10/23/2023] [Indexed: 10/28/2023]
Abstract
BACKGROUND Low- and middle-income countries (LMIC) are disproportionately affected by air pollution and its health burden, representing a global inequity. The COVID-19 pandemic provided a unique opportunity to investigate the impact of unprecedented lockdown measures on air pollutant concentrations globally. We aim to quantify air pollutant concentration changes across LMIC settings as a result of COVID-19 restrictions. METHODS Searches for this systematic review and meta-analysis were carried out across five databases on 30th March 2022; MEDLINE, Embase, Web of Science, Scopus and Transport Research Information Documentation. Modelling and observational studies were included, as long as the estimates reflected city or town level data and were taken exclusively in pre-lockdown and lockdown periods. Mean percentage changes per pollutant were calculated and meta-analyses were carried out to calculate mean difference in measured ground-level observed concentrations for each pollutant (PROSPERO CRD42022326924). FINDINGS Of the 2982 manuscripts from initial searches, 256 manuscripts were included providing 3818 percentage changes of all pollutants. No studies included any countries from Sub-Saharan Africa and 34 % and 39.4 % of studies were from China and India, respectively. There was a mean percentage change of -37.4 %, -21.7 %, -54.6 %, -39.1 %, -48.9 %, 16.9 %, -34.9 %, -30.6 % and - 14.7 % for black carbon (BC), carbon monoxide (CO), nitric oxide (NO), nitrogen dioxide (NO2), oxides of nitrogen (NOx), ozone (O3), particulate matter 10 (PM10) and 2.5 (PM2.5) and sulphur dioxide (SO2), respectively. Meta-analysis included 100 manuscripts, providing 908 mean concentration differences, which showed significant reduction in mean concentration in all study settings for BC (-0.46 μg/m3, PI -0.85; -0.08), CO (-0.25 mg/m3, PI -0.44; -0.03), NO2 (-19.41 μg/m3, PI -31.14; -7.68) and NOx (-22.32 μg/m3, PI -40.94; -3.70). INTERPRETATION The findings of this systematic review and meta-analysis quantify and confirm the trends reported across the globe in air pollutant concentration, including increases in O3. Despite the majority of global urban growth occurring in LMIC, there are distinct geographical gaps in air pollution data and, where it is available, differing approaches to analysis and reporting.
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Affiliation(s)
| | - Harry Williams
- Institute of Applied Health Research, University of Birmingham, Birmingham, UK
| | - Stephen J Sharp
- MRC Epidemiology Unit, University of Cambridge, Cambridge, UK
| | - James Woodcock
- MRC Epidemiology Unit, University of Cambridge, Cambridge, UK
| | - Haneen Khreis
- MRC Epidemiology Unit, University of Cambridge, Cambridge, UK.
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13
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Bhattarai H, Tai APK, Val Martin M, Yung DHY. Impacts of changes in climate, land use, and emissions on global ozone air quality by mid-21st century following selected Shared Socioeconomic Pathways. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 906:167759. [PMID: 37832689 DOI: 10.1016/j.scitotenv.2023.167759] [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: 05/22/2023] [Revised: 09/12/2023] [Accepted: 10/10/2023] [Indexed: 10/15/2023]
Abstract
Surface ozone (O3) is a major air pollutant and greenhouse gas with significant risks to human health, vegetation, and climate. Uncertainties around the impacts of various critical factors on O3 is crucial to understand. We used the Community Earth System Model to investigate the impacts of land use and land cover change (LULCC), climate, and emissions on global O3 air quality under selected Shared Socioeconomic Pathways (SSPs). Our findings show that increasing forest cover by 20 % under SSP1 in East China, Europe, and the eastern US leads to higher isoprene emissions leading 2-5 ppb increase in summer O3 levels. Climate-induced meteorological changes, like rising temperatures, further enhance BVOC emissions and increase O3 levels by 10-20 ppb in urban areas with high NOx levels. However, higher BVOC emissions can reduce O3 levels by 5-10 ppb in remote environments. Future NOx emissions control reduces O3 levels by 5-20 ppb in the US and Europe in all SSPs, but reductions in NOx and changes in oxidant titration increase O3 in southeast China in SSP5. Increased NOx emissions in southern Africa and India significantly elevate O3 levels up to 15 ppb under different SSPs. Climate change is equally important as emissions changes, sometimes countering the benefits of emissions control. The combined effects of emissions, climate, and land cover result in worse O3 air quality in northern India (+40 %) and East China (+20 %) under SSP3 due to anthropogenic NOx and climate-induced BVOC emissions. Over the northern hemisphere, surface O3 decreases due to reduced NOx emissions, although climate and land use changes can increase O3 levels regionally. By 2050, O3 levels in most Asian regions exceed the World Health Organization safety limit for over 150 days per year. Our study emphasizes the need to consider complex interactions for effective air pollution control and management in the future.
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Affiliation(s)
- Hemraj Bhattarai
- Earth and Environmental Sciences Programme and Graduate Division of Earth and Atmospheric Sciences, Faculty of Science, The Chinese University of Hong Kong, Hong Kong, China
| | - Amos P K Tai
- Earth and Environmental Sciences Programme and Graduate Division of Earth and Atmospheric Sciences, Faculty of Science, The Chinese University of Hong Kong, Hong Kong, China; State Key Laboratory of Agrobiotechnology and Institute of Environment, Energy and Sustainability, The Chinese University of Hong Kong, Hong Kong, China.
| | - Maria Val Martin
- Leverhulme Centre for Climate Change Mitigation, School of Biosciences, University of Sheffield, Sheffield, UK.
| | - David H Y Yung
- Earth and Environmental Sciences Programme and Graduate Division of Earth and Atmospheric Sciences, Faculty of Science, The Chinese University of Hong Kong, Hong Kong, China
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14
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Anbari K, Sicard P, Omidi Khaniabadi Y, Raja Naqvi H, Rashidi R. Assessing the effect of COVID-19 pandemic on air quality change and human health outcomes in a capital city, southwestern Iran. INTERNATIONAL JOURNAL OF ENVIRONMENTAL HEALTH RESEARCH 2023; 33:1716-1727. [PMID: 36099327 DOI: 10.1080/09603123.2022.2120967] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/24/2022] [Accepted: 08/30/2022] [Indexed: 06/15/2023]
Abstract
The aimsof this study were to assess the spatial variation of PM2.5, NO2, and O3 between 2019 (before) and 2020 (during COVID-19 pandemic); and calculation the health outcomes of exposure to these pollutants. The daily PM2.5, NO2, and O3 concentrations were applied to assess health effects by relative risk, and baseline incidence. The annual PM2.5 and NO2 mean concentrations exceeded the WHO guideline values, while O3 did not exceed. The restrictive measures associated to COVID-19 led to reduction at the annual means of PM2.5 and NO2 by -25.5% and -23.1%, respectively, while the annual mean of O3 increased by +7.9%. The number of M-CVD and M-RD (-25.6%, -26.1%) related to PM2.5 exposure, and HA-COPD and HA-RD >65 years old (-21% and -3.84%) related to NO2 exposure were reduced in 2020, and O3 exposure-related M-CVD (+30.1%) and HA-RD >65 years old (+23.4%) increased compared to the previous year 2019.
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Affiliation(s)
- Khatereh Anbari
- Social Determinants of Health Research Center, School of Medicine, Lorestan University of Medical Sciences, Khorramabad, Iran
| | | | - Yusef Omidi Khaniabadi
- Occupational and Environmental Health Research Center, Petroleum Industry Health Organization (PIHO), Ahvaz, Iran
| | - Hasan Raja Naqvi
- Department of Geography, Faculty of Natural Sciences, Jamia Millia Islamia, New Delhi, India
| | - Rajab Rashidi
- Department of Occupational Health, Nutritional Health Research Center, School of Health and Nutrition, Lorestan University of Medical Sciences, Khorramabad, Iran
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15
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Liu Z, Wang B, Wang C, Sun Y, Zhu C, Sun L, Yang N, Fan G, Sun X, Xia Z, Pan G, Zhu C, Gai Y, Wang X, Xiao Y, Yan G, Xu C. Characterization of photochemical losses of volatile organic compounds and their implications for ozone formation potential and source apportionment during summer in suburban Jinan, China. ENVIRONMENTAL RESEARCH 2023; 238:117158. [PMID: 37726031 DOI: 10.1016/j.envres.2023.117158] [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: 06/05/2023] [Revised: 08/30/2023] [Accepted: 09/14/2023] [Indexed: 09/21/2023]
Abstract
Volatile organic compounds (VOCs) undergo substantial photochemical losses during their transport from emission sources to receptor sites, resulting in serious implications for their source apportionment and ozone (O3) formation. Based on the continuous measurements of VOCs in suburban Jinan in August 2022, the effects of photochemical losses on VOC source contributions and O3 formation were evaluated in this study. The observed and initial concentrations of total VOCs (TVOC) were 12.0 ± 5.1 and 16.0 ± 7.4 ppbv, respectively. Throughout the observation period, alkenes had the most prominent photochemical losses (58.2%), followed by aromatic hydrocarbons (23.1%), accounting for 80.6% and 6.9% of the total losses, respectively. During high O3 episodes, the photochemical loss of VOCs was 6.9 times higher than that during the cleaning period. Alkene losses (exceeding 67.3%), specifically losses of isoprene, propylene, ethylene, and n-butene, dominated the total losses of VOCs during the O3 increase period. Eight sources of VOCs were identified by positive matrix factorization (PMF) based on the observed and initial concentration data (OC-PMF and IC-PMF, respectively). Concentrations of all emission sources in the OC-PMF were underestimated by 2.4%-57.1%. Moreover, the contribution of each emission source was over- or underestimated compared with that in case of the IC-PMF. The contributions of biogenic and motor vehicle exhaust emissions were underestimated by 5.3 and 2.8 percentage points, respectively, which was associated with substantial oxidation of the emitted high-reactive species. The contributions of coal/biomass burning and natural gas were overestimated by 2.4 and 3.9 percentage points, respectively, which were related to the emission of low-reactive species (acetylene, ethane, and propane). Based on our results, the photochemical losses of VOCs grossly affect their source apportionment and O3 formation. Thus, photochemical losses of VOCs must be thoroughly accounted to establish a precise scientific foundation for air-pollution control strategies.
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Affiliation(s)
- Zhenguo Liu
- School of Environmental Science and Engineering, Qilu University of Technology (Shandong Academy of Sciences), Jinan, 250353, China
| | - Baolin Wang
- School of Environmental Science and Engineering, Qilu University of Technology (Shandong Academy of Sciences), Jinan, 250353, China.
| | - Chen Wang
- School of Environmental Science and Engineering, Qilu University of Technology (Shandong Academy of Sciences), Jinan, 250353, China.
| | - Yuchun Sun
- School of Environmental Science and Engineering, Qilu University of Technology (Shandong Academy of Sciences), Jinan, 250353, China
| | - Chuanyong Zhu
- School of Environmental Science and Engineering, Qilu University of Technology (Shandong Academy of Sciences), Jinan, 250353, China
| | - Lei Sun
- School of Environmental Science and Engineering, Qilu University of Technology (Shandong Academy of Sciences), Jinan, 250353, China
| | - Na Yang
- School of Environmental Science and Engineering, Qilu University of Technology (Shandong Academy of Sciences), Jinan, 250353, China
| | - Guolan Fan
- Jinan Eco-environmental Monitoring Center of Shandong Province, Jinan, 250101, China
| | - Xiaoyan Sun
- Jinan Eco-environmental Monitoring Center of Shandong Province, Jinan, 250101, China
| | - Zhiyong Xia
- Jinan Eco-environmental Monitoring Center of Shandong Province, Jinan, 250101, China
| | - Guang Pan
- Jinan Eco-environmental Monitoring Center of Shandong Province, Jinan, 250101, China
| | - Changtong Zhu
- School of Environmental Science and Engineering, Qilu University of Technology (Shandong Academy of Sciences), Jinan, 250353, China
| | - Yichao Gai
- School of Environmental Science and Engineering, Qilu University of Technology (Shandong Academy of Sciences), Jinan, 250353, China
| | - Xiaoyu Wang
- School of Environmental Science and Engineering, Qilu University of Technology (Shandong Academy of Sciences), Jinan, 250353, China
| | - Yang Xiao
- Zibo Eco-environmental Monitoring Center of Shandong Province, Zibo, 255000, China
| | - Guihuan Yan
- Ecology Institute of Shandong Academy of Sciences, Qilu University of Technology (Shandong Academy of Sciences), Jinan, 250103, China
| | - Chongqing Xu
- School of Environmental Science and Engineering, Qilu University of Technology (Shandong Academy of Sciences), Jinan, 250353, China; Ecology Institute of Shandong Academy of Sciences, Qilu University of Technology (Shandong Academy of Sciences), Jinan, 250103, China
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16
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Zhao H, Wang Y, Zhang Z. Increased ground-level O 3 during the COVID-19 pandemic in China aggravates human health risks but has little effect on winter wheat yield. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2023; 338:122713. [PMID: 37813142 DOI: 10.1016/j.envpol.2023.122713] [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: 07/19/2023] [Revised: 10/01/2023] [Accepted: 10/07/2023] [Indexed: 10/11/2023]
Abstract
In January 2020, the novel coronavirus (COVID-19) outbreak emerged in China, prompting the enforcement of stringent lockdown measures nationwide to contain its spread. Multiple studies have demonstrated that these measures successfully reduced the levels of air pollutants except for ozone (O3). However, the potential risks of nationwide O3 changes during this period remain uncertain. To address this gap, we evaluated the ecological and health effects of O3 using hourly O3 data from 1 January to 17 June in both 2020 and 2019. Our results indicated that all health and ecological indicators, except SUM06 (sum of all hourly O3 over 60 ppb), during the COVID-19 pandemic in 2020 increased most obviously in Stages 2 and 3 with the strictest control measures, compared to the same period in 2019. The national premature deaths due to short-term O3 exposure during Stages 2-3 in 2020 totaled 146,558 (95% CI: 79,386-213,730) for all non-accidental causes and 82,408 (95% CI: 30,522-134,295) for cardiovascular diseases, increasing by 18.78% and 18.76% in 2019, respectively. The most significant increase in health risks occurred in Hubei, followed by Jiangxi, Zhejiang, Hunan, and Shaanxi. In addition, the estimated national winter wheat production losses (WWPL) attributable to O3 amounted to 50.6 and 51.1 million metric tons for 2019 and 2020, respectively. Among the major winter wheat-producing provinces, Anhui and Jiangsu experienced a larger increase in WWPL, while Shandong and Hebei suffered a greater decrease in 2020 compared to 2019, resulting in little overall change in WWPL between the two years. These findings provided direct evidence of the harmful effects of O3 during the COVID-19 pandemic and serve as a valuable reference for future air pollution control.
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Affiliation(s)
- Hui Zhao
- School of Resources and Environmental Engineering, Jiangsu University of Technology, Changzhou, 213001, China; Department of Environmental Science and Engineering, Fudan University, Shanghai, 200438, China; Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control (AEMPC), Nanjing University of Information Science & Technology, Nanjing, 210044, China.
| | - Yiyi Wang
- Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control (AEMPC), Nanjing University of Information Science & Technology, Nanjing, 210044, China; State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing, 210023, China
| | - Zhen Zhang
- Shaanxi Meteorological Service Center of Agricultural Remote Sensing and Economic Crops, Xi'an, 710014, China
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17
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Tavella RA, El Koury Santos J, de Moura FR, da Silva Júnior FMR. Better understanding the behavior of air pollutants at shutdown times - results of a short full lockdown. INTERNATIONAL JOURNAL OF ENVIRONMENTAL HEALTH RESEARCH 2023; 33:1525-1532. [PMID: 35917492 DOI: 10.1080/09603123.2022.2105310] [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: 04/21/2022] [Accepted: 07/19/2022] [Indexed: 06/15/2023]
Abstract
Numerous studies have evaluated the effects of lockdowns during the COVID-19 pandemic, but most of them have concerned large cities and regions. This study aimed to evaluate the dynamics of air pollutants during and after the implementation of a short lockdown in the medium-sized city of Pelotas, Brazil, using hourly measurements of pollutants. The evaluation period included in this study was between August 9th and 12th, 2020. A machine learning model was used to investigate the expected behavior against what was observed during the study period. All pollutants presented a gradual reduction until a dynamic plateau established 48 hours after the start of the lockdown: NO2 (↓4%), O3 (↓34%), SO2 (↓24%), CO (↓48%), PM10 (↓82%) and PM2.5 (↓82%). At the end of the restriction measures, the PM10 and PM2.5 levels continued to decline beyond expectations. Our findings show that these measures can positively affect the air quality in medium-sized cities.
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Affiliation(s)
- Ronan Adler Tavella
- Universidade Federal do Rio Grande - FURG, Av. Itália km 8 Bairro Carreiros, Rio Grande, RS, Brazil
| | - Jéssica El Koury Santos
- Programa de Pós Graduação em Ciências Ambientais, Centro de Engenharias, Universidade Federal de Pelotas, Pelotas, RS, Brazil
| | - Fernando Rafael de Moura
- Universidade Federal do Rio Grande - FURG, Av. Itália km 8 Bairro Carreiros, Rio Grande, RS, Brazil
| | - Flávio Manoel Rodrigues da Silva Júnior
- Universidade Federal do Rio Grande - FURG, Av. Itália km 8 Bairro Carreiros, Rio Grande, RS, Brazil
- Programa de Pós Graduação em Ciências Ambientais, Centro de Engenharias, Universidade Federal de Pelotas, Pelotas, RS, Brazil
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18
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Yilmaz S, Menteş Y, Angin SN, Qaid A. Impact of the COVID-19 outbreak on urban air, Land surface temperature and air pollution in cold climate zones. ENVIRONMENTAL RESEARCH 2023; 237:116887. [PMID: 37611782 DOI: 10.1016/j.envres.2023.116887] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/05/2022] [Revised: 07/16/2023] [Accepted: 08/12/2023] [Indexed: 08/25/2023]
Abstract
The objective of this study was to analyze air pollution and thermal environment in Turkey's cold region before, during, and after COVID-19 in 2019, 2020 and 2021. The CO, NO2, O3, PM10 and SO2 data from the state air quality stations, as well as ground air temperature data from six weather stations, and land satellite images from the USGS website using ArcGIS 10.4.1 software were collected in January, March, April and August of 2019, 2020 an 2021. In order to evaluate the impact of COVID-19 measures and restrictions on cold region cities, air pollution indicators, land surface temperature and air temperature as well as statistical data were analyzed. The results indicated that the CO, NO2, PM10 and SO2 emissions decreased by 14.9%, 14.3%, 47.1% and 28.5%, but O3 increased by 16.9%, respectively, during the COVID-19 lockdown in 2020 as compared to these of the pre-COVID-19 levels in 2019. A positive correlation between air temperature and O3 in 2019 (r2 = 0.80), and in 2020 and 2021 (r2 = 0.64) was obtained. Air temperature in 2020 and 2021 decreased due to lockdowns and quarantine measures that led to lower O3 emissions as compared to 2019. Negative correlations were also found between air temperature and NO2 (r2 = 0.60) and SO2 (r2 = 0.5). There was no correlation between air temperature and PM10. During the COVID-19 lockdown and intense restrictions in April 2020, the average LST and air temperature values dropped by 14.7 °C and 1.6 °C respectively, compared to April 2019. These findings may be beneficial for future urban planning, particularly in cold regions.
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Affiliation(s)
- Sevgi Yilmaz
- Atatürk University, Faculty of Architecture and Design, Department of Landscape Architecture, 25240 Erzurum, Turkey.
| | - Yaşar Menteş
- Ministry of Agriculture and Forestry, Elazığ Provincial Directorate of Agriculture and Forestry, Elazığ - PhD Candidate, Atatürk University, Faculty of Architecture and Design Department of Landscape Architecture Affiliation, Erzurum, Turkey
| | - Sena Nur Angin
- , Atatürk University, Faculty of Architecture and Design, Department of Landscape Architecture, 25240 Erzurum, Turkey
| | - Adeb Qaid
- Department of Architecture Engineering, Kingdom University, Riffa, Bahrain.
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19
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Gao Y, Wang S, Zhang C, Xing C, Tan W, Wu H, Niu X, Liu C. Assessing the impact of urban form and urbanization process on tropospheric nitrogen dioxide pollution in the Yangtze River Delta, China. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2023; 336:122436. [PMID: 37640224 DOI: 10.1016/j.envpol.2023.122436] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/23/2023] [Revised: 07/31/2023] [Accepted: 08/21/2023] [Indexed: 08/31/2023]
Abstract
Optimizing urban form through urban planning and management policies can improve air quality and transition to demand-side control. Nitrogen dioxide (NO2) in the urban atmosphere, mainly emitted by anthropogenic sources such as industry and vehicles, is a key precursor of fine particles and ozone pollution. Both NO2 and its secondary pollutants pose health risks for humans. Here we assess the interactions between urban forms and airborne NO2 pollution in different cities with various stages of urbanization in the Yangtze River Delta (YRD) in China, by using the machine learning and geographical regression model. The results reveal a strong correlation between urban fragmentation and tropospheric NO2 vertical column density (TVCD) in YRD cities in 2020, particularly those with lower or higher levels of urbanization. The correlation coefficients (R2) between NO2 TVCD and the largest patch index (a metric of urban fragmentation) in different cities are greater than 0.8. For cities at other urbanization stages, population and road density are strongly correlated with NO2 TVCD, with an R2 larger than 0.61. This study highlights the interdependence among urbanization, urban forms, and air pollution, emphasizing the importance of customized urban landscape management strategies for mitigating urban air pollution.
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Affiliation(s)
- Yuanyun Gao
- Key Laboratory of Environmental Optics & Technology, Anhui Institute of Optics and Fine Mechanics, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China; Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, Hefei 230026, China; Nanjing Institute of Environmental Sciences, Ministry of Ecology and Environment of China, 8 Jiang Wang Miao St., Nanjing 210042, China
| | - Shuntian Wang
- Department of Civil, Environmental and Geomatic Engineering, Institute of Environmental Engineering, Ecological Systems Design, Swiss Federal Institute of Technology, ETH Zurich, 8093 Zurich, Switzerland; Department of Humanities, Social, And Political Sciences, Institute of Science, Technology, And Policy (ISTP), Swiss Federal Institute of Technology, ETH Zurich, 8092 Zurich, Switzerland
| | - Chengxin Zhang
- Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, Hefei 230026, China.
| | - Chengzhi Xing
- Key Laboratory of Environmental Optics & Technology, Anhui Institute of Optics and Fine Mechanics, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China
| | - Wei Tan
- Key Laboratory of Environmental Optics & Technology, Anhui Institute of Optics and Fine Mechanics, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China
| | - Hongyu Wu
- School of Environmental Science and Optoelectronic Technology, University of Science and Technology of China, Hefei 230026, China
| | - Xinhan Niu
- Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, Hefei 230026, China
| | - Cheng Liu
- Key Laboratory of Environmental Optics & Technology, Anhui Institute of Optics and Fine Mechanics, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China; Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, Hefei 230026, China
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20
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Garsa K, Khan AA, Jindal P, Middey A, Luqman N, Mohanty H, Tiwari S. Assessment of meteorological parameters on air pollution variability over Delhi. ENVIRONMENTAL MONITORING AND ASSESSMENT 2023; 195:1315. [PMID: 37831195 DOI: 10.1007/s10661-023-11922-2] [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: 07/16/2023] [Accepted: 09/30/2023] [Indexed: 10/14/2023]
Abstract
In this study, the relationships between meteorological parameters (relative humidity, wind speed, temperature, planetary boundary layer, and rainfall) and air pollutants (particulate matter and gaseous pollutants) have been evaluated during a 3-year period from 2019 to 2021. Diffusion and dispersion of air contaminants were significantly influenced by meteorology over the capital city. The results of correlation matrix and principal component analysis (PCA) suggest a season's specific influence of meteorological parameters on atmospheric pollutants' concentration. Temperature has the strongest negative impact on pollutants' concentration, and all the other studied meteorological parameters negatively (reduced) as well as positively (increased) impacted the air pollutants' concentration. A two-way process was involved during the interaction of pollutants with relative humidity and wind speed. Due to enhanced moisture-holding capacity during non-monsoon summers, particles get larger and settle down on the ground via dry deposition processes. Winter's decreased moisture-holding capacity causes water vapour coupled with air contaminants to remain suspended and further deteriorate the quality of the air. High wind speed helps in the dispersion and dilution but a high wind speed associated with dust particles may increase the pollutants' level downwind side. The PM2.5/PM10 variation revealed that the accumulation effect of relative humidity on PM2.5 was more intense than PM10. Daily average location-specific rainfall data revealed that moderate to high rainfall has a potential wet scavenging impact on both particulate matters and gaseous pollutants.
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Affiliation(s)
- Kalpana Garsa
- Amity Centre for Air Pollution Control (ACAPC) & Amity Centre for Ocean-Atmospheric Science and Technology (ACOAST), Amity University Haryana, Gurugram, 122413, India
| | - Abul Amir Khan
- Amity Centre for Air Pollution Control (ACAPC) & Amity Centre for Ocean-Atmospheric Science and Technology (ACOAST), Amity University Haryana, Gurugram, 122413, India.
| | - Prakhar Jindal
- Space System Engineering, Delft University of Technology, Kluyverweg 1, 2629, HS, Delft, The Netherlands
| | - Anirban Middey
- CSIR-National Environmental Engineering Research Institute (NEERI), Kolkata Zonal Centre, Kolkata, West Bengal, 700107, India
| | - Nadeem Luqman
- Amity Institute of Behavioural and Allied Sciences (AIBAS), Amity University Haryana, Gurugram, 122413, India
| | - Hitankshi Mohanty
- Amity Centre for Air Pollution Control (ACAPC) & Amity Centre for Ocean-Atmospheric Science and Technology (ACOAST), Amity University Haryana, Gurugram, 122413, India
| | - Shubhansh Tiwari
- Amity Centre for Air Pollution Control (ACAPC) & Amity Centre for Ocean-Atmospheric Science and Technology (ACOAST), Amity University Haryana, Gurugram, 122413, India
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21
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Mu X, Wang S, Jiang P, Wu Y. Estimation of surface ozone concentration over Jiangsu province using a high-performance deep learning model. J Environ Sci (China) 2023; 132:122-133. [PMID: 37336603 DOI: 10.1016/j.jes.2022.09.032] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/25/2021] [Revised: 09/22/2022] [Accepted: 09/26/2022] [Indexed: 06/21/2023]
Abstract
Recently, the global background concentration of ozone (O3) has demonstrated a rising trend. Among various methods, groun-based monitoring of O3 concentrations is highly reliable for research analysis. To obtain information on the spatial characteristics of O3 concentrations, it is necessary that the ground monitoring sites be constructed in sufficient density. In recent years, many researchers have used machine learning models to estimate surface O3 concentrations, which cannot fully provide the spatial and temporal information contained in a sample dataset. To solve this problem, the current study utilized a deep learning model called the Residual connection Convolutional Long Short-Term Memory network (R-ConvLSTM) to estimate daily maximum 8-hr average (MDA8) O3 over Jiangsu province, China during 2020. In this research, the R-ConvLSTM model not only provides the spatiotemporal information of MDA8 O3, but also involves residual connection to avoid the problem of gradient explosion and gradient disappearance with the deepening of network layers. We utilized the TROPOMI total O3 column retrieved from Sentinel-5 Precursor, ERA5 reanalysis meteorological data, and other supplementary data to build a pre-trained dataset. The R-ConvLSTM model achieved an overall sample-base cross-validation (CV) R2 of 0.955 with root mean square error (RMSE) of 9.372 µg/m3. Model estimation also showed a city-based CV R2 of 0.896 with RMSE of 14.029 µg/m3, the highest MDA8 O3 in spring being 122.60 ± 31.60 µg/m3 and the lowest in winter being 69.93 ± 18.48 µg/m3.
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Affiliation(s)
- Xi Mu
- School of Resources and Environmental Engineering, Anhui University, Hefei 230601, China
| | - Sichen Wang
- School of Resources and Environmental Engineering, Anhui University, Hefei 230601, China
| | - Peng Jiang
- School of Resources and Environmental Engineering, Anhui University, Hefei 230601, China; Information Materials and Intelligent Sensing Laboratory of Anhui Province, Hefei 230601, China; Anhui Province Engineering Laboratory for Mine Ecological Remediation, Anhui University, Hefei 230601, China.
| | - Yanlan Wu
- School of Resources and Environmental Engineering, Anhui University, Hefei 230601, China; Information Materials and Intelligent Sensing Laboratory of Anhui Province, Hefei 230601, China
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22
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Amiri F, Jamali AA, Gharibvand LK. Tracing air pollution changes (CO, NO2, SO2, and HCHO) using GEE and Sentinel 5P images in Ahvaz, Iran. ENVIRONMENTAL MONITORING AND ASSESSMENT 2023; 195:1259. [PMID: 37777996 DOI: 10.1007/s10661-023-11885-4] [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: 08/31/2022] [Accepted: 09/14/2023] [Indexed: 10/03/2023]
Abstract
The first case of COVID-19 in Iran was reported on February 25, 2020, leading in the implementation of a government-mandated lockdown as the virus gradually spread to different cities. The objective of this study was to evaluate the impact of the COVID-19 pandemic on air quality in Ahvaz city by utilizing Sentinel 5 images and the Google Earth Engine (GEE) platform. Specifically, the concentrations of air pollutants, including CO, NO2, SO2, and HCHO, during the COVID-19 pandemic from May 10 to June 01, 2021, were examined. Also, they were compared to the same period in 2019. Additionally, the influence of meteorological parameters, such as wind speed and precipitation, on pollutant concentrations during the pandemic and in the pre-pandemic year of 2019 were investigated. The results revealed a significant decrease in the concentrations of NO2 (13.7%), CO (6.1%), SO2 (28%), and HCHO (9.5%) in Ahvaz during the study period in 2021 compared to the same period in 2019. Statistical analyses indicated no significant changes in wind speed and precipitation between the COVID-19 pandemic and the pre-pandemic period in 2019. Therefore, the impact of these parameters on the observed changes in pollutant concentrations can be disregarded. It is clear that the COVID-19 epidemic and the subsequent lockdown measures, including traffic restrictions and business closures, played a crucial role in significantly reducing air pollutant concentrations in Ahvaz.
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Affiliation(s)
- Fatemeh Amiri
- Department of Petroleum Engineering, Masjed-Soleiman Branch, Islamic Azad University, Masjed-Soleiman, Iran
| | - Ali Akbar Jamali
- Department of GIS-RS and Watershed Management, Meybod Branch, Islamic Azad University, Meybod, Yazd, Iran.
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23
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Lu B, Zhang Z, Jiang J, Meng X, Liu C, Herrmann H, Chen J, Xue L, Li X. Unraveling the O 3-NO X-VOCs relationships induced by anomalous ozone in industrial regions during COVID-19 in Shanghai. ATMOSPHERIC ENVIRONMENT (OXFORD, ENGLAND : 1994) 2023; 308:119864. [PMID: 37250918 PMCID: PMC10204281 DOI: 10.1016/j.atmosenv.2023.119864] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/24/2022] [Revised: 04/24/2023] [Accepted: 05/22/2023] [Indexed: 05/31/2023]
Abstract
The COVID-19 pandemic promoted strict restrictions to human activities in China, which led to an unexpected increase in ozone (O3) regarding to nitrogen oxides (NOx) and volatile organic compounds (VOCs) co-abatement in urban China. However, providing a quantitative assessment of the photochemistry that leads to O3 increase is still challenging. Here, we evaluated changes in O3 arising from photochemical production with precursors (NOX and VOCS) in industrial regions in Shanghai during the COVID-19 lockdowns by using machine learning models and box models. The changes of air pollutants (O3, NOX, VOCs) during the COVID-19 lockdowns were analyzed by deweathering and detrending machine learning models with regard to meteorological and emission effects. After accounting for effects of meteorological variability, we find increase in O3 concentration (49.5%). Except for meteorological effects, model results of detrending the business-as-usual changes indicate much smaller reduction (-0.6%), highlighting the O3 increase attributable to complex photochemistry mechanism and the upward trends of O3 due to clear air policy in Shanghai. We then used box models to assess the photochemistry mechanism and identify key factors that control O3 production during lockdowns. It was found that empirical evidence for a link between efficient radical propagation and the optimized O3 production efficiency of NOX under the VOC-limited conditions. Simulations with box models also indicate that priority should be given to controlling industrial emissions and vehicle exhaust while the VOCs and NOX should be managed at a proper ratio in order to control O3 in winter. While lockdown is not a condition that could ever be continued indefinitely, findings of this study offer theoretical support for formulating refined O3 management in industrial regions in Shanghai, especially in winter.
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Affiliation(s)
- Bingqing Lu
- Department of Environmental Science & Engineering, Fudan University, Shanghai, 200438, China
| | - Zekun Zhang
- Department of Environmental Science & Engineering, Fudan University, Shanghai, 200438, China
| | - Jiakui Jiang
- Department of Environmental Science & Engineering, Fudan University, Shanghai, 200438, China
| | - Xue Meng
- Department of Environmental Science & Engineering, Fudan University, Shanghai, 200438, China
| | - Chao Liu
- Department of Environmental Science & Engineering, Fudan University, Shanghai, 200438, China
| | - Hartmut Herrmann
- Leibniz-Institut für Troposphärenforschung (IfT), Permoserstr. 15, 04318, Leipzig, Germany
| | - Jianmin Chen
- Department of Environmental Science & Engineering, Fudan University, Shanghai, 200438, China
| | - Likun Xue
- Environment Research Institute, Shandong University, Qingdao, Shandong, 266237, China
| | - Xiang Li
- Department of Environmental Science & Engineering, Fudan University, Shanghai, 200438, China
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24
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Mihăilă D, Lazurca LG, Bistricean IP, Horodnic VD, Mihăilă EV, Emandi EM, Prisacariu A, Nistor A, Nistor B, Roșu C. Air quality changes in NE Romania during the first Covid 19 pandemic wave. Heliyon 2023; 9:e18918. [PMID: 37636459 PMCID: PMC10447937 DOI: 10.1016/j.heliyon.2023.e18918] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2022] [Revised: 08/01/2023] [Accepted: 08/02/2023] [Indexed: 08/29/2023] Open
Abstract
This study analyzes for the first time uniformly and causally the level of pollution and air quality for the NE-Romania Region, one of the poorest region in the European Union. Knowing the level of pollution and air quality in this region, which can be taken as a benchmark due to its positional and economic-geographical attributes, responds to current scientific and practical needs. The study uses an hourly database (for five pollutants and five climate elements), from 2009 to 2020, from 19 air quality monitoring stations in northeastern Romania. Pollutant levels were statistically and graphically/cartographically modeled for the entire 2009-2020 interval on the distributive-spatial and regime, temporal component. Inter-station differences and similarities were analyzed causally. Taking advantage of the emergency measures between March 16 and May 14, 2020, we observed the impact of the event on the regional air quality in northeastern Romania. During the emergency period, the metropolitan area of Suceava (with over 100,000 inhabitants) was quarantined, which allowed us to analyze the impact of the quarantine period on the local air quality. We found that, in this region, air quality falls into class I (for NO2, SO2 and CO), II for O3 and III for PM10. During the lockdown periods NO2 and SO2 decreased for the entire region by 8.6 and 14.3%, respectively, and in Suceava by 13.9 and 40.1%, respectively. The causes of the reduction were anthropogenic in nature.
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Affiliation(s)
- Dumitru Mihăilă
- Department of Geography, Stefan Cel Mare University, Suceava, Romania
- Applied Geography Research Center - GEA, Department of Geography, Stefan Cel Mare University, Suceava, Romania
| | - Liliana Gina Lazurca
- Department of Geography, Stefan Cel Mare University, Suceava, Romania
- Applied Geography Research Center - GEA, Department of Geography, Stefan Cel Mare University, Suceava, Romania
| | - Ionel-Petruț Bistricean
- Department of Geography, Stefan Cel Mare University, Suceava, Romania
- Applied Geography Research Center - GEA, Department of Geography, Stefan Cel Mare University, Suceava, Romania
| | - Vasilică-Dănuț Horodnic
- Department of Geography, Stefan Cel Mare University, Suceava, Romania
- Applied Geography Research Center - GEA, Department of Geography, Stefan Cel Mare University, Suceava, Romania
| | | | - Elena-Maria Emandi
- Department of Geography, Stefan Cel Mare University, Suceava, Romania
- Applied Geography Research Center - GEA, Department of Geography, Stefan Cel Mare University, Suceava, Romania
| | - Alin Prisacariu
- Department of Geography, Stefan Cel Mare University, Suceava, Romania
- Applied Geography Research Center - GEA, Department of Geography, Stefan Cel Mare University, Suceava, Romania
| | - Alina Nistor
- Department of Geography, Stefan Cel Mare University, Suceava, Romania
- Applied Geography Research Center - GEA, Department of Geography, Stefan Cel Mare University, Suceava, Romania
| | | | - Constantin Roșu
- Department of Geography, Stefan Cel Mare University, Suceava, Romania
- Applied Geography Research Center - GEA, Department of Geography, Stefan Cel Mare University, Suceava, Romania
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25
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Li Y, Li R. A hybrid model for daily air quality index prediction and its performance in the face of impact effect of COVID-19 lockdown. PROCESS SAFETY AND ENVIRONMENTAL PROTECTION : TRANSACTIONS OF THE INSTITUTION OF CHEMICAL ENGINEERS, PART B 2023; 176:673-684. [PMID: 37350802 PMCID: PMC10264166 DOI: 10.1016/j.psep.2023.06.021] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/04/2022] [Revised: 05/22/2023] [Accepted: 06/06/2023] [Indexed: 06/24/2023]
Abstract
Accurate and dependable air quality forecasting is critical to environmental and human health. However, most methods usually aim to improve overall prediction accuracy but neglect the accuracy for unexpected incidents. In this study, a hybrid model was developed for air quality index (AQI) forecasting, and its performance during COVID-19 lockdown was analyzed. Specifically, the variational mode decomposition (VMD) was employed to decompose the original AQI sequence into some subsequences with the parameters optimized by the Whale optimization algorithm (WOA), and the residual sequence was further decomposed by the complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN). On this basis, a deep learning method bidirectional long short-term memory coupled with added time filter layer and attention mechanism (TFA-BiLSTM) was employed to explore the latent dynamic characteristics of each subsequence. This WOA-VMD-CEEMDAN-TFA-BiLSTM hybrid model was used to forecast AQI values for four cities in China, and results verified that the accuracy of the hybrid model outperformed other proposed models, achieving R2 values of 0.96-0.97. In addition, the improvement in MAE (34.71-49.65%) and RMSE (32.82-48.07%) were observed over single decomposition-based model. Notably, during the epidemic lockdown period, the hybrid model had significant superiority over other proposed models for AQI prediction.
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Affiliation(s)
- Yuting Li
- School of Environmental Science and Engineering, Tianjin University, Tianjin 300350, PR China
| | - Ruying Li
- School of Environmental Science and Engineering, Tianjin University, Tianjin 300350, PR China
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26
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Meng X, Lu B, Liu C, Zhang Z, Chen J, Herrmann H, Li X. Abrupt exacerbation in air quality over Europe after the outbreak of Russia-Ukraine war. ENVIRONMENT INTERNATIONAL 2023; 178:108120. [PMID: 37527587 DOI: 10.1016/j.envint.2023.108120] [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: 05/15/2023] [Revised: 07/16/2023] [Accepted: 07/26/2023] [Indexed: 08/03/2023]
Abstract
Much attention has been paid to the world economy and social situations in response to the outbreak of war between Russia and Ukraine in the context of COVID-19. However, much less attention has been paid to the detrimental effect of war on the atmospheric environment. Here, we used an extended deweathered-detrended technique to quantitatively evaluate changes in ambient NO2, O3, and PM2.5 AQI levels arising from emission changes (due to pandemic-driven lockdowns and war-related activities) in European cities. Results show pandemic-induced lockdowns mitigated regional air pollution in Europe, but the war activities led to an average increase of approximately 9.78% in PM2.5 and 10.07% in NO2, along with an average decrease of about 7.93% in O3 levels in cities near the war zones. Moreover, the regional air pollution exacerbated by the war activities has offset the improvements in air quality observed during the COVID-19 pandemic. The potential mechanism analysis show that the increase in atmospheric pollutant emissions driven by the war activities led to the complexity of chemical reactions in the mixed atmospheric system, which posed a huge challenge to the alleviation of air pollution in the region. This study highlights the urgent need for a ceasefire from an environmental perspective.
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Affiliation(s)
- Xue Meng
- Department of Environmental Science & Engineering, Fudan University, Shanghai, 200032, China
| | - Bingqing Lu
- Department of Environmental Science & Engineering, Fudan University, Shanghai, 200032, China
| | - Chao Liu
- Department of Environmental Science & Engineering, Fudan University, Shanghai, 200032, China
| | - Zekun Zhang
- Department of Environmental Science & Engineering, Fudan University, Shanghai, 200032, China
| | - Jianmin Chen
- Department of Environmental Science & Engineering, Fudan University, Shanghai, 200032, China
| | - Hartmut Herrmann
- Leibniz-Institut für Troposphärenforschung (IfT), Permoserstr. 15, Leipzig, 04318, Germany
| | - Xiang Li
- Department of Environmental Science & Engineering, Fudan University, Shanghai, 200032, China
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27
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Zhang K, Chen R, Cai Z, Hou L, Li X, Xu X, Sun Y, Lu X, Jiang Q. The effect of ozone short-term exposure on flow-mediated dilation: Using data before and after COVID-19 lockdown in Shanghai. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 881:163485. [PMID: 37068686 PMCID: PMC10105378 DOI: 10.1016/j.scitotenv.2023.163485] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/23/2023] [Revised: 04/02/2023] [Accepted: 04/09/2023] [Indexed: 06/01/2023]
Abstract
BACKGROUND Short-term ambient ozone exposure has been shown to have an adverse impact on endothelial function, contributing to major cardiovascular diseases and premature death. However, only limited studies have focused on the impact of short-term ozone exposure on Flow-mediated Dilation (FMD), and their results have been inconsistent. The current study aims to explore the relationship between short-term ambient ozone exposure and FMD. In addition, the study aims to investigate how lockdown measures for COVID-19 may influence ozone concentration in the atmosphere. METHODS Participants were recruited from a hospital in Shanghai from December 2020 to August 2022. Individuals' ozone exposure was determined using residential addresses. A distributed lag nonlinear model was adopted to assess the exposure-response relationship between short-term ozone exposure and FMD. A comparison was made between ambient ozone concentration and FMD data collected before and after Shanghai's lockdown in 2022. RESULTS When ozone concentration was between 150 and 200 μg/m3, there was a significant reduction in FMD with a 2-day lag. Elderly individuals (age ≥ 65), females, non-drinkers, and non-smokers were found to be more susceptible to high concentrations of ozone exposure. The lockdown did elevate ambient ozone concentration compared to the same period previously. INTERPRETATION This study proposes that an ambient ozone concentration of 150-200 μg/m3 is harmful to endothelial function, and that a reduction in human activity during lockdown increased the concentration, which in turn reduced FMD. However, the underlying mechanism requires further research.
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Affiliation(s)
- Kai Zhang
- Tongren Hospital, Shanghai Jiao Tong University School of Medicine, China
| | - Rukun Chen
- Tongren Hospital, Shanghai Jiao Tong University School of Medicine, China; Faculty of Medicine, University of Southampton, United Kingdom of Great Britain and Northern Ireland
| | - Zhenzhen Cai
- Shanghai Fourth People's Hospital, School of Medicine, Tongji University, China
| | - Lei Hou
- Tongren Hospital, Shanghai Jiao Tong University School of Medicine, China
| | - Xiaoguang Li
- Shanghai Fourth People's Hospital, School of Medicine, Tongji University, China
| | - Xin Xu
- Tongren Hospital, Shanghai Jiao Tong University School of Medicine, China
| | - Yishuai Sun
- Tongren Hospital, Shanghai Jiao Tong University School of Medicine, China
| | - Xiaotong Lu
- Tongren Hospital, Shanghai Jiao Tong University School of Medicine, China
| | - Qixia Jiang
- Tongren Hospital, Shanghai Jiao Tong University School of Medicine, China.
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28
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Calatayud V, Diéguez JJ, Agathokleous E, Sicard P. Machine learning model to predict vehicle electrification impacts on urban air quality and related human health effects. ENVIRONMENTAL RESEARCH 2023; 228:115835. [PMID: 37019297 DOI: 10.1016/j.envres.2023.115835] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/06/2023] [Revised: 03/31/2023] [Accepted: 04/01/2023] [Indexed: 05/16/2023]
Abstract
Air pollution is a prevailing environmental problem in cities worldwide. The future vehicle electrification (VE), which in Europe will be importantly fostered by the ban of thermal engines from 2035, is expected to have an important effect on urban air quality. Machine learning models represent an optimal tool for predicting changes in air pollutants concentrations in the context of future VE. For the city of Valencia (Spain), a XGBoost (eXtreme Gradient Boosting package) model was used in combination with SHAP (SHapley Additive exPlanations) analysis, both to investigate the importance of different factors explaining air pollution concentrations and predicting the effect of different levels of VE. The model was trained with 5 years of data including the COVID-19 lockdown period in 2020, in which mobility was strongly reduced resulting in unprecedent changes in air pollution concentrations. The interannual meteorological variability of 10 years was also considered in the analyses. For a 70% VE, the model predicted: 1) improvements in nitrogen dioxide pollution (-34% to -55% change in annual mean concentrations, for the different air quality stations), 2) a very limited effect on particulate matter concentrations (-1 to -4% change in annual means of PM2.5 and PM10), 3) heterogeneous responses in ground-level ozone concentrations (-2% to +12% change in the annual means of the daily maximum 8-h average concentrations). Even at a high VE increase of 70%, the 2021 World Health Organization Air Quality Guidelines will be exceeded for all pollutants in some stations. VE has a potentially important impact in terms of reducing NO2-associated premature mortality, but complementary strategies for reducing traffic and controlling all different air pollution sources should also be implemented to protect human health.
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Affiliation(s)
- V Calatayud
- Fundación CEAM, Parque Tecnológico, C/Charles R. Darwin, 14, Paterna, Spain.
| | - J J Diéguez
- Fundación CEAM, Parque Tecnológico, C/Charles R. Darwin, 14, Paterna, Spain
| | - E Agathokleous
- Institute of Ecology, Key Laboratory of Agrometeorology of Jiangsu Province, School of Applied Meteorology, Nanjing University of Information Science & Technology, Nanjing, 210044, China
| | - P Sicard
- ARGANS, 260 Route Du Pin Montard, Biot, France
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Mishra M, Chen PH, Bisquera W, Lin GY, Le TC, Dejchanchaiwong R, Tekasakul P, Jhang CW, Wu CJ, Tsai CJ. Source-apportionment and spatial distribution analysis of VOCs and their role in ozone formation using machine learning in central-west Taiwan. ENVIRONMENTAL RESEARCH 2023:116329. [PMID: 37276975 DOI: 10.1016/j.envres.2023.116329] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/24/2023] [Revised: 05/24/2023] [Accepted: 06/02/2023] [Indexed: 06/07/2023]
Abstract
This study assessed the machine learning based sensitivity analysis coupled with source-apportionment of volatile organic carbons (VOCs) to look into new insights of O3 pollution in Yunlin County located in central-west region of Taiwan. One-year (Jan 1 to Dec 31, 2021) hourly mass concentrations data of 54 VOCs, NOX, and O3 from 10 photochemical assessment monitoring stations (PAMs) in and around the Yunlin County were analyzed. The novelty of the study lies in the utilization of artificial neural network (ANN) to evaluate the contribution of VOCs sources in O3 pollution in the region. Firstly, the station specific source-apportionment of VOCs were carried out using positive matrix factorization (PMF)-resolving six sources viz. AAM: aged air mass, CM: chemical manufacturing, IC: Industrial combustion, PP: petrochemical plants, SU: solvent use and VE: vehicular emissions. AAM, SU, and VE constituted cumulatively more than 65% of the total emission of VOCs across all 10 PAMs. Diurnal and spatial variability of source-segregated VOCs showed large variations across 10 PAMs, suggesting for distinctly different impact of contributing sources, photo-chemical reactivity, and/or dispersion due to land-sea breezes at the monitoring stations. Secondly, to understand the contribution of controllable factors governing the O3 pollution, the output of VOCs source-contributions from PMF model along with mass concentrations of NOX were standardized and first time used as input variables to ANN, a supervised machine learning algorithm. ANN analysis revealed following order of sensitivity in factors governing the O3 pollution: VOCs from IC > AAM > VE ≈ CM ≈ SU > PP ≈ NOX. The results indicated that VOCs associated with IC (VOCs-IC) being the most sensitive factor which need to be regulated more efficiently to quickly mitigate the O3 pollution across the Yunlin County.
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Affiliation(s)
- Manisha Mishra
- Institute of Environmental Engineering, National Yang Ming Chiao Tung University, Hsinchu, 30010, Taiwan.
| | - Pin-Hsin Chen
- Institute of Environmental Engineering, National Yang Ming Chiao Tung University, Hsinchu, 30010, Taiwan
| | - Wilfredo Bisquera
- Institute of Environmental Engineering, National Yang Ming Chiao Tung University, Hsinchu, 30010, Taiwan
| | - Guan-Yu Lin
- Department of Environmental Science and Engineering, Tunghai University, Taichung, 407302, Taiwan.
| | - Thi-Cuc Le
- Institute of Environmental Engineering, National Yang Ming Chiao Tung University, Hsinchu, 30010, Taiwan
| | - Racha Dejchanchaiwong
- Air Pollution and Health Effect Research Center, And Department of Chemical Engineering, Prince of Songkla University, Songkhla, 90100, Thailand
| | - Perapong Tekasakul
- Air Pollution and Health Effect Research Center, And Department of Mechanical and Mechatronics Engineering, Prince of Songkla University, Songkhla, 90100, Thailand
| | | | - Ci-Jhen Wu
- Environmental Protection Bureau, Yunlin County, Taiwan
| | - Chuen-Jinn Tsai
- Institute of Environmental Engineering, National Yang Ming Chiao Tung University, Hsinchu, 30010, Taiwan
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Aboagye EM, Effah NAA, Effah KO. A bibliometric analysis of the impact of COVID-19 social lockdowns on air quality: research trends and future directions. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023:10.1007/s11356-023-27699-3. [PMID: 37219782 DOI: 10.1007/s11356-023-27699-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Received: 10/26/2022] [Accepted: 05/12/2023] [Indexed: 05/24/2023]
Abstract
Social lockdowns improved air quality during the COVID-19 pandemic. Governments had previously spent a lot of money addressing air pollution without success. This bibliometric study measured the influence of COVID-19 social lockdowns on air pollution, identified emerging issues, and discussed future perspectives. The researchers examined the contributions of countries, authors, and most productive journals to COVID-19 and air pollution research from January 1, 2020, to September 12, 2022, from the Web of Sciences Core Collection (WoS). The results showed that (a) publications on the COVID-19 pandemic and air pollution were 504 (research articles) with 7495 citations, (b) China ranked first in the number of publications (n = 151; 29.96% of the global output) and was the main country in international cooperation network, followed by India (n = 101; 20.04% of the total articles) and the USA (n = 41; 8.13% of the global output). Air pollution plagues China, India, and the USA, calling for many studies. After a high spike in 2020, research published in 2021 declined in 2022. The author's keywords have focused on "COVID-19," "air pollution," "lockdown," and "PM25." These keywords suggest that research in this area is focused on understanding the health impacts of air pollution, developing policies to address air pollution, and improving air quality monitoring. The COVID-19 social lockdown served as a specified procedure to reduce air pollution in these countries. However, this paper provides practical recommendations for future research and a model for environmental and health scientists to examine the likely impact of COVID-19 social lockdowns on urban air pollution.
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Affiliation(s)
| | | | - Kwaku Obeng Effah
- Law School, Zhongnan University of Economics and Law, Wuhan, China
- Department Political Science, University of Ghana, Legon, Accra, Ghana
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Halder B, Ahmadianfar I, Heddam S, Mussa ZH, Goliatt L, Tan ML, Sa'adi Z, Al-Khafaji Z, Al-Ansari N, Jawad AH, Yaseen ZM. Machine learning-based country-level annual air pollutants exploration using Sentinel-5P and Google Earth Engine. Sci Rep 2023; 13:7968. [PMID: 37198391 DOI: 10.1038/s41598-023-34774-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2022] [Accepted: 05/08/2023] [Indexed: 05/19/2023] Open
Abstract
Climatic condition is triggering human health emergencies and earth's surface changes. Anthropogenic activities, such as built-up expansion, transportation development, industrial works, and some extreme phases, are the main reason for climate change and global warming. Air pollutants are increased gradually due to anthropogenic activities and triggering the earth's health. Nitrogen Dioxide (NO2), Carbon Monoxide (CO), and Aerosol Optical Depth (AOD) are truthfully important for air quality measurement because those air pollutants are more harmful to the environment and human's health. Earth observational Sentinel-5P is applied for monitoring the air pollutant and chemical conditions in the atmosphere from 2018 to 2021. The cloud computing-based Google Earth Engine (GEE) platform is applied for monitoring those air pollutants and chemical components in the atmosphere. The NO2 variation indicates high during the time because of the anthropogenic activities. Carbon Monoxide (CO) is also located high between two 1-month different maps. The 2020 and 2021 results indicate AQI change is high where 2018 and 2019 indicates low AQI throughout the year. The Kolkata have seven AQI monitoring station where high nitrogen dioxide recorded 102 (2018), 48 (2019), 26 (2020) and 98 (2021), where Delhi AQI stations recorded 99 (2018), 49 (2019), 37 (2020), and 107 (2021). Delhi, Kolkata, Mumbai, Pune, and Chennai recorded huge fluctuations of air pollutants during the study periods, where ~ 50-60% NO2 was recorded as high in the recent time. The AOD was noticed high in Uttar Pradesh in 2020. These results indicate that air pollutant investigation is much necessary for future planning and management otherwise; our planet earth is mostly affected by the anthropogenic and climatic conditions where maybe life does not exist.
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Affiliation(s)
- Bijay Halder
- Department of Remote Sensing and GIS, Vidyasagar University, Midnapore, 721102, India
- New Era and Development in Civil Engineering Research Group, Scientific Research Center, Al-Ayen University, Nasiriyah, Thi-Qar, 64001, Iraq
| | - Iman Ahmadianfar
- Department of Civil Engineering, Behbahan Khatam Alanbia University of Technology, Behbahan, Iran
| | - Salim Heddam
- Agronomy Department, Faculty of Science, University, 20 Août 1955 Skikda, Route El Hadaik, BP 26, Skikda, Algeria
| | | | - Leonardo Goliatt
- Computational Modeling Program, Federal University of Juiz de Fora, Juiz de Fora, MG, Brazil
| | - Mou Leong Tan
- GeoInformatic Unit, Geography Section, School of Humanities, Universiti Sains Malaysia, 11800, Penang, Malaysia
- School of Geographical Sciences, Nanjing Normal University, Nanjing, 210023, China
| | - Zulfaqar Sa'adi
- Centre for Environmental Sustainability and Water Security, Research Institute for Sustainable Environment, Universiti Teknologi Malaysia (UTM), 81310, Sekudai, Johor, Malaysia
| | - Zainab Al-Khafaji
- Department of Building and Construction Technologies Engineering, AL-Mustaqbal University College, Hillah, 51001, Iraq
| | - Nadhir Al-Ansari
- Civil, Environmental and Natural Resources Engineering, Lulea University of Technology, 97187, Lulea, Sweden.
| | - Ali H Jawad
- Faculty of Applied Sciences, Universiti Teknologi MARA, 40450, Shah Alam, Selangor, Malaysia
| | - Zaher Mundher Yaseen
- Civil and Environmental Engineering Department, King Fahd University of Petroleum and Minerals, Dhahran, 31261, Saudi Arabia.
- Interdisciplinary Research Center for Membranes and Water Security, King Fahd University of Petroleum and Minerals (KFUPM), Dhahran, Saudi Arabia.
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Yang J, Ji Q, Pu H, Dong X, Yang Q. How does COVID-19 lockdown affect air quality: Evidence from Lanzhou, a large city in Northwest China. URBAN CLIMATE 2023; 49:101533. [PMID: 37122825 PMCID: PMC10121109 DOI: 10.1016/j.uclim.2023.101533] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/09/2022] [Revised: 03/04/2023] [Accepted: 04/14/2023] [Indexed: 05/03/2023]
Abstract
Coronavirus disease (COVID-19) has disrupted health, economy, and society globally. Thus, many countries, including China, have adopted lockdowns to prevent the epidemic, which has limited human activities while affecting air quality. These affects have received attention from academics, but very few studies have focused on western China, with a lack of comparative studies across lockdown periods. Accordingly, this study examines the effects of lockdowns on air quality and pollution, using the hourly and daily air monitoring data collected from Lanzhou, a large city in Northwest China. The results indicate an overall improvement in air quality during the three lockdowns compared to the average air quality in the recent years, as well as reduced PM2.5, PM10, SO2, NO2, and CO concentrations with different rates and increased O3 concentration. During lockdowns, Lanzhou's "morning peak" of air pollution was alleviated, while the spatial characteristics remained unchanged. Further, ordered multi-classification logistic regression models to explore the mechanisms by which socioeconomic backgrounds and epidemic circumstances influence air quality revealed that the increment in population density significantly aggravated air pollution, while the presence of new cases in Lanzhou, and medium- and high-risk areas in the given district or county both increase the likelihood of air quality improvement in different degrees. These findings contribute to the understanding of the impact of lockdown on air quality, and propose policy suggestions to control air pollution and achieve green development in the post-epidemic era.
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Affiliation(s)
- Jianping Yang
- State Key Laboratory of Cryospheric Science, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, Gansu 730000, China
| | - Qin Ji
- State Key Laboratory of Cryospheric Science, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, Gansu 730000, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Hongzheng Pu
- School of Management, Chongqing University of Technology, Chongqing 400054, China
| | - Xinyang Dong
- State Key Joint Laboratory of Environment Simulation and Pollution Control (SKLESPC), School of Environment, Tsinghua University, Beijing 100084, China
| | - Qin Yang
- State Key Laboratory of Cryospheric Science, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, Gansu 730000, China
- University of Chinese Academy of Sciences, Beijing, China
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Rudke AP, Martins JA, Hallak R, Martins LD, de Almeida DS, Beal A, Freitas ED, Andrade MF, Koutrakis P, Albuquerque TTA. Evaluating TROPOMI and MODIS performance to capture the dynamic of air pollution in São Paulo state: A case study during the COVID-19 outbreak. REMOTE SENSING OF ENVIRONMENT 2023; 289:113514. [PMID: 36846486 PMCID: PMC9941323 DOI: 10.1016/j.rse.2023.113514] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/27/2022] [Revised: 01/11/2023] [Accepted: 02/17/2023] [Indexed: 06/18/2023]
Abstract
Atmospheric pollutant data retrieved through satellite sensors are continually used to assess changes in air quality in the lower atmosphere. During the COVID-19 pandemic, several studies started to use satellite measurements to evaluate changes in air quality in many different regions worldwide. However, although satellite data is continuously validated, it is known that its accuracy may vary between monitored areas, requiring regionalized quality assessments. Thus, this study aimed to evaluate whether satellites could measure changes in the air quality of the state of São Paulo, Brazil, during the COVID-19 outbreak; and to verify the relationship between satellite-based data [Tropospheric NO2 column density and Aerosol Optical Depth (AOD)] and ground-based concentrations [NO2 and particulate material (PM; coarse: PM10 and fine: PM2.5)]. For this purpose, tropospheric NO2 obtained from the TROPOMI sensor and AOD retrieved from MODIS sensor data by using the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm were compared with concentrations obtained from 50 automatic ground monitoring stations. The results showed low correlations between PM and AOD. For PM10, most stations showed correlations lower than 0.2, which were not significant. The results for PM2.5 were similar, but some stations showed good correlations for specific periods (before or during the COVID-19 outbreak). Satellite-based Tropospheric NO2 proved to be a good predictor for NO2 concentrations at ground level. Considering all stations with NO2 measurements, correlations >0.6 were observed, reaching 0.8 for specific stations and periods. In general, it was observed that regions with a more industrialized profile had the best correlations, in contrast with rural areas. In addition, it was observed about 57% reductions in tropospheric NO2 throughout the state of São Paulo during the COVID-19 outbreak. Variations in air pollutants were linked to the region economic vocation, since there were reductions in industrialized areas (at least 50% of the industrialized areas showed >20% decrease in NO2) and increases in areas with farming and livestock characteristics (about 70% of those areas showed increase in NO2). Our results demonstrate that Tropospheric NO2 column densities can serve as good predictors of NO2 concentrations at ground level. For MAIAC-AOD, a weak relationship was observed, requiring the evaluation of other possible predictors to describe the relationship with PM. Thus, it is concluded that regionalized assessment of satellite data accuracy is essential for assertive estimates on a regional/local level. Good quality information retrieved at specific polluted areas does not assure a worldwide use of remote sensor data.
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Affiliation(s)
- A P Rudke
- Department of Sanitary and Environmental Engineering, Federal University of Minas Gerais, Av. Pres. Antônio Carlos, 6627, 31270-901 Belo Horizonte, Brazil
- Federal University of Technology - Paraná, Av. Dos Pioneiros, 3131, 86036-370 Londrina, Brazil
| | - J A Martins
- Federal University of Technology - Paraná, Av. Dos Pioneiros, 3131, 86036-370 Londrina, Brazil
| | - R Hallak
- Instituto de Astronomia, Geofísica e Ciências Atmosféricas, Universidade de São Paulo, Rua do Matão, 1226, Cidade Universitária, 05508-090, São Paulo, Brazil
| | - L D Martins
- Federal University of Technology - Paraná, Av. Dos Pioneiros, 3131, 86036-370 Londrina, Brazil
| | - D S de Almeida
- Federal University of Technology - Paraná, Av. Dos Pioneiros, 3131, 86036-370 Londrina, Brazil
- Federal University of São Carlos, Rod. Washington Luiz, Km 235, SP310, 13565-905, São Carlos, Brazil
| | - A Beal
- Federal University of Technology - Paraná, Av. Dos Pioneiros, 3131, 86036-370 Londrina, Brazil
| | - E D Freitas
- Instituto de Astronomia, Geofísica e Ciências Atmosféricas, Universidade de São Paulo, Rua do Matão, 1226, Cidade Universitária, 05508-090, São Paulo, Brazil
| | - M F Andrade
- Instituto de Astronomia, Geofísica e Ciências Atmosféricas, Universidade de São Paulo, Rua do Matão, 1226, Cidade Universitária, 05508-090, São Paulo, Brazil
| | - P Koutrakis
- Department of Environmental Health, Harvard T. H. Chan School of Public Health, Boston, MA 02114, USA
| | - T T A Albuquerque
- Department of Sanitary and Environmental Engineering, Federal University of Minas Gerais, Av. Pres. Antônio Carlos, 6627, 31270-901 Belo Horizonte, Brazil
- Post Graduation Program on Environmental Engineering - Federal University of Espírito Santo, Av. Fernando Ferrari, 514, 29075-910 Vitória, Brazil
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Yao H, Wang L, Liu Y, Zhou J, Lu J. Impact of the COVID-19 lockdown on typical ambient air pollutants: Cyclical response to anthropogenic emission reduction. Heliyon 2023; 9:e15799. [PMID: 37153417 PMCID: PMC10152760 DOI: 10.1016/j.heliyon.2023.e15799] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2022] [Revised: 04/21/2023] [Accepted: 04/21/2023] [Indexed: 05/09/2023] Open
Abstract
Preliminary studies have confirmed that ambient air pollutant concentrations are significantly influenced by the COVID-19 lockdown measures, but little attention focus on the long term impacts of human countermeasures in cities all over the world during the period. Still, fewer have addressed their other essential properties, especially the cyclical response to concentration reduction. This paper aims to fill the gaps with combined methods of abrupt change test and wavelet analysis, research areas were made of five cities, Wuhan, Changchun, Shanghai, Shenzhen and Chengdu, in China. Abrupt changes in contaminant concentrations commonly occurred in the year prior to the outbreak. The lockdown has almost no effect on the short cycle below 30 d (days) for both pollutants, and a negligible impact on the cycle above 30 d. PM2.5 (fine particulate matter) has a stable short-cycle nature, which is greatly influenced by anthropogenic emissions. The analysis revealed that the sensitivity of PM2.5 to climate is increased along with the concentrations of PM2.5 were decreasing by the times when above the threshold (30-50 μg m-3), and which could lead to PM2.5 advancement relative to the ozone phase over a period of 60 d after the epidemic. These results suggest that the epidemic may have had an impact earlier than when it was known. And significant reductions in anthropogenic emissions have little impact on the cyclic nature of pollutants, but may alter the inter-pollutant phase differences during the study period.
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Affiliation(s)
- Heng Yao
- Department of Environmental Science and Engineering, School of Information and Safety Engineering, Zhongnan University of Economics and Law, Wuhan 430073, China
| | - Lingchen Wang
- Department of Environmental Science and Engineering, School of Information and Safety Engineering, Zhongnan University of Economics and Law, Wuhan 430073, China
| | - Yalin Liu
- Department of Environmental Science and Engineering, School of Information and Safety Engineering, Zhongnan University of Economics and Law, Wuhan 430073, China
| | - Jingcheng Zhou
- Department of Environmental Science and Engineering, School of Information and Safety Engineering, Zhongnan University of Economics and Law, Wuhan 430073, China
- Institute of Environmental Management and Policy, Zhongnan University of Economics and Law, Wuhan 430073, China
| | - Jiawei Lu
- South China Institute of Environmental Sciences, Ministry of Ecology and Environment, Guangzhou 510655, China
- Guangdong Province Engineering Laboratory for Solid Waste Incineration Technology and Equipment, Guangzhou 510330, China
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Chang X, Zheng H, Zhao B, Yan C, Jiang Y, Hu R, Song S, Dong Z, Li S, Li Z, Zhu Y, Shi H, Jiang Z, Xing J, Wang S. Drivers of High Concentrations of Secondary Organic Aerosols in Northern China during the COVID-19 Lockdowns. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2023; 57:5521-5531. [PMID: 36999996 DOI: 10.1021/acs.est.2c06914] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/19/2023]
Abstract
During the COVID-19 lockdown in early 2020, observations in Beijing indicate that secondary organic aerosol (SOA) concentrations increased despite substantial emission reduction, but the reasons are not fully explained. Here, we integrate the two-dimensional volatility basis set into a state-of-the-art chemical transport model, which unprecedentedly reproduces organic aerosol (OA) components resolved by the positive matrix factorization based on aerosol mass spectrometer observations. The model shows that, for Beijing, the emission reduction during the lockdown lowered primary organic aerosol (POA)/SOA concentrations by 50%/18%, while deteriorated meteorological conditions increased them by 30%/119%, resulting in a net decrease in the POA concentration and a net increase in the SOA concentration. Emission reduction and meteorological changes both led to an increased OH concentration, which accounts for their distinct effects on POA and SOA. SOA from anthropogenic volatile organic compounds and organics with lower volatility contributed 28 and 62%, respectively, to the net SOA increase. Different from Beijing, the SOA concentration decreased in southern Hebei during the lockdown because of more favorable meteorology. Our findings confirm the effectiveness of organic emission reductions and meanwhile reveal the challenge in controlling SOA pollution that calls for large organic precursor emission reductions to rival the adverse impact of OH increase.
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Affiliation(s)
- Xing Chang
- 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
- Transport Planning and Research Institute, Ministry of Transport, Laboratory of Transport Pollution Control and Monitoring Technology, Beijing 100028, China
| | - 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
| | - 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
| | - Chao Yan
- Joint International Research Laboratory of Atmospheric and Earth System Research, School of Atmospheric Sciences, Nanjing University, Nanjing 210023, China
- Institute for Atmospheric and Earth System Research/Physics, Faculty of Science, University of Helsinki, Helsinki 00560, Finland
| | - 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
| | - Ruolan Hu
- 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
| | - Shaojie Song
- 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
| | - 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 Sources and Control of Air Pollution Complex, Beijing 100084, China
| | - Shengyue Li
- 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
| | - Zeqi Li
- 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
| | - Yun Zhu
- Guangdong Provincial Key Laboratory of Atmospheric Environment and Pollution Control, College of Environment and Energy, Guangzhou Higher Education Mega Center, South China University of Technology, Guangzhou 510006, China
| | - Hongrong Shi
- Key Laboratory of Middle Atmosphere and Global Environment Observation, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100045, China
| | - Zhe Jiang
- Key Laboratory of Middle Atmosphere and Global Environment Observation, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100045, 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
| | - 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
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Yen YC, Ku CH, Hsiao TC, Chi KH, Peng CY, Chen YC. Impacts of COVID-19's restriction measures on personal exposure to VOCs and aldehydes in Taipei City. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 880:163275. [PMID: 37028680 PMCID: PMC10074730 DOI: 10.1016/j.scitotenv.2023.163275] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/12/2022] [Revised: 02/21/2023] [Accepted: 03/31/2023] [Indexed: 05/23/2023]
Abstract
The Coronavirus Disease 2019 (COVID-19) pandemic provided an unprecedented natural experiment, that allowed us to investigate the impacts of different restrictive measures on personal exposure to specific volatile organic compounds (VOCs) and aldehydes and resulting health risks in the city. Ambient concentrations of the criteria air pollutants were also evaluated. Passive sampling for VOCs and aldehydes was conducted for graduate students and ambient air in Taipei, Taiwan, during the Level 3 warning (strict control measures) and Level 2 alert (loosened control measures) of the COVID-19 pandemic in 2021-2022. Information on the daily activities of participants and on-road vehicle counts nearby the stationary sampling site during the sampling campaigns were recorded. Generalized estimating equations (GEE) with adjusted meteorological and seasonal variables were used to estimate the effects of control measures on average personal exposures to the selected air pollutants. Our results showed that ambient CO and NO2 concentrations in relation to on-road transportation emissions were significantly reduced, which led to an increase in ambient O3 concentrations. Exposure to specific VOCs (benzene, methyl tert-butyl ether (MTBE), xylene, ethylbenzene, and 1,3-butadiene) associated with automobile emissions were remarkably decreased by ~40-80 % during the Level 3 warning, resulting in 42 % and 50 % reductions of total incremental lifetime cancer risk (ILCR) and hazard index (HI), respectively, compared with the Level 2 alert. In contrast, the exposure concentration and calculated health risks in the selected population for formaldehyde increased by ~25 % on average during the Level 3 warning. Our study improves knowledge of the influence of a series of anti-COVID-19 measures on personal exposure to specific VOCs and aldehydes and its mitigations.
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Affiliation(s)
- Yu-Chuan Yen
- National Institute of Environmental Health Sciences, National Health Research Institutes, 35 Keyan Road, Zhunan Town, Miaoli, Taiwan
| | - Chun-Hung Ku
- National Institute of Environmental Health Sciences, National Health Research Institutes, 35 Keyan Road, Zhunan Town, Miaoli, Taiwan
| | - Ta-Chih Hsiao
- Graduate Institute of Environmental Engineering, National Taiwan University, Taiwan
| | - Kai Hsien Chi
- Institute of Environmental and Occupational Health Sciences, National Yang Ming Chiao Tung University, Taipei 112, Taiwan
| | - Chiung-Yu Peng
- Department of Public Health, Kaohsiung Medical University, Kaohsiung 80708, Taiwan
| | - Yu-Cheng Chen
- National Institute of Environmental Health Sciences, National Health Research Institutes, 35 Keyan Road, Zhunan Town, Miaoli, Taiwan; Department of Occupational Safety and Health, China Medical University, 91 Hsueh-Shih Road, Taichung, Taiwan; Department of Safety, Health and Environmental Engineering, National United University, No. 2, Lienda, Miaoli 360302, Taiwan; Research Center for Environmental Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan.
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Raza T, Shehzad M, Abbas M, Eash NS, Jatav HS, Sillanpaa M, Flynn T. Impact assessment of COVID-19 global pandemic on water, environment, and humans. ENVIRONMENTAL ADVANCES 2023; 11:100328. [PMID: 36532331 PMCID: PMC9741497 DOI: 10.1016/j.envadv.2022.100328] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/16/2022] [Revised: 11/15/2022] [Accepted: 12/04/2022] [Indexed: 06/17/2023]
Abstract
One of the most significant threats to global health since the Second World War is the COVID-19 pandemic. Due to COVID-19 widespread social, environmental, economic, and health concerns. Other unfavourable factors also emerged, including increased trash brought on by high consumption of packaged foods, takeout meals, packaging from online shopping, and the one-time use of plastic products. Due to labour shortages and residents staying at home during mandatory lockdowns, city municipal administrations' collection and recycling capacities have decreased, frequently damaging the environment (air, water, and soil) and ecological and human systems. The COVID-19 challenges are more pronounced in unofficial settlements of developing nations, particularly for developing nations of the world, as their fundamental necessities, such as air quality, water quality, trash collection, sanitation, and home security, are either non-existent or difficult to obtain. According to reports, during the pandemic's peak days (20 August 2021 (741 K cases), 8 million tonnes of plastic garbage were created globally, and 25 thousand tonnes of this waste found its way into the ocean. This thorough analysis attempts to assess the indirect effects of COVID-19 on the environment, human systems, and water quality that pose dangers to people and potential remedies. Strong national initiatives could facilitate international efforts to attain environmental sustainability goals. Significant policies should be formulated like good quality air, pollution reduction, waste management, better sanitation system, and personal hygiene. This review paper also elaborated that further investigations are needed to investigate the magnitude of impact and other related factors for enhancement of human understanding of ecosystem to manage the water, environment and human encounter problems during epidemics/pandemics in near future.
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Affiliation(s)
- Taqi Raza
- Department of Biosystems Engineering & Soil Science, University of Tennessee, USA
| | | | - Mazahir Abbas
- Department of Bioscience, University of Wah Cantt, Quaid Avenue, Wah Cantt 47040, Pakistan
| | - Neal S Eash
- Department of Biosystems Engineering & Soil Science, University of Tennessee, USA
| | - Hanuman Singh Jatav
- Department of Soil Science and Agricultural Chemistry, Sri Karan Narendra Agriculture University, Rajasthan 303329, India
- Department of Soil Science and Agricultural Chemistry, Institute of Agricultural Sciences, Banaras Hindu University, Varanasi 221005, India
| | - Mika Sillanpaa
- Department of Chemical Engineering, School of Mining, Metallurgy and Chemical Engineering, University of Johannesburg, P.O. Box 17011, Doornfontein 2028, South Africa
| | - Trevan Flynn
- Department of Horticulture and Natural Resources, University of Bonn, Germany
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38
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Li D, Lasenby J. Investigating impacts of COVID-19 on urban mobility and emissions. CITIES (LONDON, ENGLAND) 2023; 135:104246. [PMID: 36811025 PMCID: PMC9935275 DOI: 10.1016/j.cities.2023.104246] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/12/2022] [Revised: 02/12/2023] [Accepted: 02/12/2023] [Indexed: 05/03/2023]
Abstract
The COVID-19 pandemic has severely impacted human activities in a way never documented in modern history. The prevention policies and measures have abruptly changed well-established urban mobility patterns. In this context, we exploit different sources of urban mobility data to gain insights into the effects of restrictive policies on the daily mobility and exhaust emissions in pandemic and post-pandemic periods. Manhattan, the most densely populated borough in New York City, is chosen as the study area. We collect data generated by taxis, sharing bikes, and road detectors between 2019 and 2021, and estimate exhaust emissions using the COPERT (Computer Programme to calculate Emissions from Road Transport) model. A comparative analysis is conducted to identify important changes in urban mobility and emission patterns, with a particular focus on the lockdown period in 2020 and its counterparts in 2019 and 2021. The results of the paper fuel the discussion on urban resilience and policy-making in a post pandemic world.
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Affiliation(s)
- Duo Li
- Department of Engineering, University of Cambridge, Cambridge CB2 1PZ, UK
- Department of Engineering, Nottingham Trent University, Nottingham NG1 4FQ, UK
| | - Joan Lasenby
- Department of Engineering, University of Cambridge, Cambridge CB2 1PZ, UK
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Xu H, Xiao K, Pan J, Fu Q, Wei X, Zhou J, Yu Y, Hu X, Ren H, Cheng J, Peng S, Hong N, Ye Y, Su N, He Z, Hu T. Evidence of aircraft activity impact on local air quality: A study in the context of uncommon airport operation. J Environ Sci (China) 2023; 125:603-615. [PMID: 36375942 PMCID: PMC8900605 DOI: 10.1016/j.jes.2022.02.039] [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: 05/26/2021] [Revised: 10/15/2021] [Accepted: 02/22/2022] [Indexed: 06/15/2023]
Abstract
Wuhan Tianhe International Airport (WUH) was suspended to contain the spread of COVID-19, while Shanghai Hongqiao International Airport (SHA) saw a tremendous flight reduction. Closure of a major international airport is extremely rare and thus represents a unique opportunity to straightforwardly observe the impact of airport emissions on local air quality. In this study, a series of statistical tools were applied to analyze the variations in air pollutant levels in the vicinity of WUH and SHA. The results of bivariate polar plots show that airport SHA and WUH are a major source of nitrogen oxides. NOx, NO2 and NO diminished by 55.8%, 44.1%, 76.9%, and 40.4%, 33.3% and 59.4% during the COVID-19 lockdown compared to those in the same period of 2018 and 2019, under a reduction in aircraft activities by 58.6% and 61.4%. The concentration of NO2, SO2 and PM2.5 decreased by 77.3%, 8.2%, 29.5%, right after the closure of airport WUH on 23 January 2020. The average concentrations of NO, NO2 and NOx scatter plots at downwind of SHA after the lockdown were 78.0%, 47.9%, 57.4% and 62.3%, 34.8%, 41.8% lower than those during the same period in 2018 and 2019. However, a significant increase in O3 levels by 50.0% and 25.9% at WUH and SHA was observed, respectively. These results evidently show decreased nitrogen oxides concentrations in the airport vicinity due to reduced aircraft activities, while amplified O3 pollution due to a lower titration by NO under strong reduction in NOx emissions.
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Affiliation(s)
- Hao Xu
- School of Environmental Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240, China; Tianjin Research Institute for Water Transport Engineering, Ministry of Transport, Tianjin 300456, China
| | - Kai Xiao
- Wuhan Environmental Protection Science Academy, Wuhan 430015, China
| | - Jun Pan
- Shanghai Environmental Monitoring Center, Shanghai 200233, China
| | - Qingyan Fu
- Shanghai Environmental Monitoring Center, Shanghai 200233, China
| | - Xiaodong Wei
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, China; East China Air Traffic Management Bureau CAAC, Shanghai 200335, China
| | - Junrui Zhou
- Wuhan Environmental Protection Science Academy, Wuhan 430015, China
| | - Yamei Yu
- Shanghai Environmental Monitoring Center, Shanghai 200233, China
| | - Xue Hu
- School of Environmental Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240, China; China-UK Low Carbon College, Shanghai 201306, China
| | - Huarui Ren
- School of Environmental Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Jinping Cheng
- School of Environmental Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240, China.
| | - Shitao Peng
- Tianjin Research Institute for Water Transport Engineering, Ministry of Transport, Tianjin 300456, China
| | - Ningning Hong
- Tianjin Research Institute for Water Transport Engineering, Ministry of Transport, Tianjin 300456, China
| | - Yin Ye
- Tianjin Research Institute for Water Transport Engineering, Ministry of Transport, Tianjin 300456, China
| | - Ning Su
- Tianjin Research Institute for Water Transport Engineering, Ministry of Transport, Tianjin 300456, China
| | - Zehui He
- Tianjin Research Institute for Water Transport Engineering, Ministry of Transport, Tianjin 300456, China
| | - Tao Hu
- Tianjin Research Institute for Water Transport Engineering, Ministry of Transport, Tianjin 300456, China
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Wang Y, Ge Q. The positive impact of the Omicron pandemic lockdown on air quality and human health in cities around Shanghai. ENVIRONMENT, DEVELOPMENT AND SUSTAINABILITY 2023:1-26. [PMID: 37362999 PMCID: PMC9975847 DOI: 10.1007/s10668-023-03071-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/23/2022] [Accepted: 02/21/2023] [Indexed: 06/28/2023]
Abstract
The Omicron pandemic broke out in Shanghai in March 2022, and some infected people spread to some cities in the Yangtze River Delta (YRD) region. To achieve the dynamic zero-COVID target as soon as possible, Shanghai and nine cities that were heavily affected by Shanghai implemented the lockdown measures. This paper aims to quantify the impact of the lockdown on air quality and human health. A difference-in-difference (DID) model was first used to measure the impact of the lockdown on air quality in these ten cities. Based on the results of the DID model, we estimated the PM2.5-related health and economic benefits using the concentration-response function and the value of statistical life method. Results showed that the lockdown has reduced the concentrations of PM2.5, PM10, SO2, NO2, and CO by 9.87 μg/m3, 17.31 μg/m3, 0.75 μg/m3, 9.03 μg/m3, and 0.07 mg/m3, respectively. The number of avoided premature deaths due to PM2.5 reduction was estimated to be 35,342. The resulting economic benefits totaled 18.86 billion US dollars. We investigated the reasons for the air quality improvement in these ten cities and found the "3 + 11" policy has had a great impact on air quality. Compared with the first COVID-19 lockdown in early 2020, the effect of the lockdown in 2022 was smaller. These findings demonstrated that reductions in anthropogenic emissions would achieve substantial air quality improvement and health benefits. This paper re-emphasized continuous efforts to improve air quality are essential to protect public health.
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Affiliation(s)
- Yu Wang
- Business School, University of Shanghai for Science and Technology, 334 Jungong Rd, Shanghai, 200093 People’s Republic of China
| | - Qingqing Ge
- College of Business, Yancheng Teachers University, 2 South Hope Avenue, Yancheng, 224051 People’s Republic of China
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Wang W, He BJ. Co-occurrence of urban heat and the COVID-19: Impacts, drivers, methods, and implications for the post-pandemic era. SUSTAINABLE CITIES AND SOCIETY 2023; 90:104387. [PMID: 36597490 PMCID: PMC9801697 DOI: 10.1016/j.scs.2022.104387] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/28/2022] [Revised: 12/28/2022] [Accepted: 12/29/2022] [Indexed: 05/05/2023]
Abstract
Cities, the main place of human settlements, are under various mega challenges such as climate change, population increase, economic growth, urbanization, and pandemic diseases, and such challenges are mostly interlinked. Urban heat, due to heatwaves and heat islands, is the combined effect of climate change and urbanization. The COVID-19 is found to be a critical intervention of urban heat. However, the interrelationship between COVID-19 and urban heat has not been fully understood, constraining urban planning and design actions for improving the resilience to the dual impacts of heat and the pandemic. To close this research gap, this paper conducted a review on the co-occurrence of urban heat and the COVID-19 pandemic for a better understanding of their synergies, conflicts or trade-offs. The research involves a systematic review of urban temperature anomalies, variations in air pollutant concentrations, unbalanced energy development, and thermal health risks during the pandemic lockdown. In addition, this paper further explored data sources and analytical methods adopted to screen and identify the interventions of COVID-19 to urban heat. Overall, this paper is of significance for understanding the impact of COVID-19 on urban heat and provides a reference for coping with urban heat and the pandemic simultaneously. The world is witnessing the co-existence of heat and the pandemic, even in the post-pandemic era. This study can enlighten city managers, planners, the public, and researchers to collaborate for constructing a robust and resilient urban system for dealing with more than one challenges.
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Affiliation(s)
- Wei Wang
- Centre for Climate-Resilient and Low-Carbon Cities, School of Architecture and Urban Planning, Chongqing University, Chongqing, 400045, China
- Institute for Smart City of Chongqing University in Liyang, Chongqing University, Liyang, 213300, Jiangsu, China
| | - Bao-Jie He
- Centre for Climate-Resilient and Low-Carbon Cities, School of Architecture and Urban Planning, Chongqing University, Chongqing, 400045, China
- Institute for Smart City of Chongqing University in Liyang, Chongqing University, Liyang, 213300, Jiangsu, China
- Key Laboratory of New Technology for Construction of Cities in Mountain Area, Ministry of Education, Chongqing University, Chongqing, 400045, China
- State Key Laboratory of Subtropical Building Science, South China University of Technology, Guangzhou, 510641, China
- Network for Education and Research on Peace and Sustainability (NERPS), Hiroshima University, Hiroshima, 739-8530, Japan
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42
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Volke MI, Abarca-Del-Rio R, Ulloa-Tesser C. Impact of mobility restrictions on NO 2 concentrations in key Latin American cities during the first wave of the COVID-19 pandemic. URBAN CLIMATE 2023; 48:101412. [PMID: 36627949 PMCID: PMC9816081 DOI: 10.1016/j.uclim.2023.101412] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/17/2021] [Revised: 12/13/2022] [Accepted: 01/03/2023] [Indexed: 06/17/2023]
Abstract
Between March and June 2020, activity in the major cities of Latin America declined due to containment efforts implemented by local governments to avoid the rapid spread of COVID-19. Our study compared 2020 with the previous year and demonstrated a considerable drop in tropospheric NO2 levels obtained by the SENTINEL 5P satellite in major Latin American cities. Lima (47.5%), Santiago (36.1%), São Paulo (27%), Rio de Janeiro (23%), Quito (18.6%), Bogota (17.5%), Buenos Aires (16.6%), Guayaquil (15.3%), Medellin (14.2%), La Paz (9.5%), Belo Horizonte (7.8%), Mexico (7.6%) and Brasilia (5.9%) registered statistically significant decreases in NO2 concentrations during the study period. In addition, we analyzed mobility data from Google and Apple reports as well as meteorological information from atmospheric reanalysis data along with satellite fields between 2011 and 2020, and performed a refined multivariate analysis (non-negative matrix approximation) to show that this decrease was associated with a reduction in population mobility rather than meteorological factors. Our findings corroborate the argument that confinement scenarios may indicate how air pollutant concentrations can be effectively reduced and managed.
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Affiliation(s)
- Matias I Volke
- Energy Doctoral Program, Faculty of Engineering, Universidad de Concepción, Concepción 4030000, Chile
| | - Rodrigo Abarca-Del-Rio
- Department of Geophysics, Faculty of Physical and Mathematical Sciences, University of Concepcion, Concepcion, Chile
| | - Claudia Ulloa-Tesser
- Environmental Engineering Department, Faculty of Environmental Science and EULA Center, Universidad de Concepción, Chile
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43
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R L, Bano S, More D, Ambulkar R, Mondal T, Maurya P, Bs M. On the transition of major pollutant and O 3 production regime during Covid-19 lockdowns. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2023; 328:116907. [PMID: 36508979 DOI: 10.1016/j.jenvman.2022.116907] [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: 08/15/2021] [Revised: 11/02/2022] [Accepted: 11/26/2022] [Indexed: 06/17/2023]
Abstract
Lockdowns enforced amid the pandemic facilitated the evaluation of the impact of emission reductions on air quality and the production regime of O3 under NOx reduction. Analysis of space-time variation of various pollutants (PM10, PM2.5, NOx, CO, O3 and VOC or TNMHC) through the lockdown phases at eight typical stations (Urban/Metro, Rural/high vegetation and coastal) is carried out. It reveals how the major pollutant (PM10 or PM2.5 or O3, or CO) differs from station to station as lockdowns progress depending on geography, land-use pattern and efficacy of lockdown implementation. Among the stations analyzed, Delhi (Chandnichowk), the most polluted (PM10 = 203 μgm-3; O3 = 17.4 ppbv) in pre-lockdown, experienced maximum reduction during the first phase of lockdown in PM2.5 (-47%), NO2 (-40%), CO (-37%) while O3 remained almost the same (2% reduction) to pre-lockdown levels. The least polluted Mahabaleshwar (PM10 = 45 μgm-3; O3 = 54 ppbv) witnessed relatively less reduction in PM2.5 (-2.9%), NO2 (-4.7%), CO (-49%) while O3 increased by 36% to pre-lockdown levels. In rural stations with lots of greenery, O3 is the major pollutant attributed to biogenic VOC emissions from vegetation besides lower NO levels. In other stations, PM2.5 or PM10 is the primary pollutant. At Chennai, Jabalpur, Mahabaleshwar and Goa, the deciding factor of Air Quality Index (AQI) remained unchanged, with reduced values. Particulate matter, PM10 decided AQI for three stations (dust as control component), and PM2.5 decided the same for two but within acceptable limits for stations. Improvement of AQI through control of dust would prove beneficial for Chennai and Patiala; anthropogenic emission control would work for Chandani chowk, Goa and Patiala; emission control of CO is required for Mahabaleshwar and Thiruvanathapuram. Under low VOC/NOx ratio conditions, O3 varies with the ratio, NO/NO2, with a negative (positive) slope indicating VOC-sensitive (NOx-sensitive) regime. Peak O3 isopleths as a function of NOx and VOC depicting distinct patterns suggest that O3 variation is entirely non-linear for a given NOx or VOC.
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Affiliation(s)
- Latha R
- Indian Institute of Tropical Meteorology, Pune, India
| | - Shahana Bano
- Indian Institute of Tropical Meteorology, Pune, India
| | - Dolly More
- Indian Institute of Tropical Meteorology, Pune, India
| | | | | | | | - Murthy Bs
- Indian Institute of Tropical Meteorology, Pune, India.
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44
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Liu B, Yang Y, Yang T, Dai Q, Zhang Y, Feng Y, Hopke PK. Effect of photochemical losses of ambient volatile organic compounds on their source apportionment. ENVIRONMENT INTERNATIONAL 2023; 172:107766. [PMID: 36706584 DOI: 10.1016/j.envint.2023.107766] [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: 10/14/2022] [Revised: 12/19/2022] [Accepted: 01/17/2023] [Indexed: 06/18/2023]
Abstract
Photochemical losses of ambient volatile organic compounds (VOCs) substantially affect source apportionment analysis. Hourly speciated VOC data measured from April to August 2020 in Tianjin, China were used to analyze the photochemical losses of VOC species and assess the impacts of photochemical losses on source apportionment by comparing the positive matrix factorization (PMF) results based on observed and initial concentration data (OC-PMF and IC-PMF). The initial concentrations of the VOC species were estimated using a photochemical age-based parameterization method. The results suggest that the average photochemical loss of total VOCs (TVOCs) during the ozone pollution period was 2.4 times higher than that during the non-ozone pollution period. The photochemical loss of alkenes was more significant than that of the other VOC species. Temperature has an important effect on photochemical losses, and different VOC species have different sensitivities to temperature; high photochemical losses mainly occurred at temperatures between 25 °C and 35 °C. Photochemical losses reduced the concentrations of highly reactive species in the OC-PMF factor profile. Compared with the IC-PMF results, the OC-PMF contributions of biogenic emissions and polymer production-related industrial sources were underestimated by 73 % and 50 %, respectively, likely due to the oxidation of isoprene and propene, respectively. The contribution of diesel and gasoline evaporation was underestimated by 39 %, which was likely due to the loss of m,p-xylene. Additionally, the contributions of liquefied petroleum gas, vehicle emissions, natural gas, and oil refinery were underestimated by 31 %, 29 %, 23 %, and 13 %, respectively. When the O3 concentrations were higher than 140 μg m-3 or the temperatures were higher than 30 °C, the photochemical losses from most sources increased substantially. Additionally, solar radiation produced different photochemical losses for different source types.
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Affiliation(s)
- 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
| | - Yang Yang
- 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
| | - Tao Yang
- 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.
| | - 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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Khreis H, Sanchez KA, Foster M, Burns J, Nieuwenhuijsen MJ, Jaikumar R, Ramani T, Zietsman J. Urban policy interventions to reduce traffic-related emissions and air pollution: A systematic evidence map. ENVIRONMENT INTERNATIONAL 2023; 172:107805. [PMID: 36780750 DOI: 10.1016/j.envint.2023.107805] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Revised: 02/03/2023] [Accepted: 02/04/2023] [Indexed: 06/18/2023]
Abstract
BACKGROUND Urban areas are hot spots for human exposure to air pollution, which originates in large part from traffic. As the urban population continues to grow, a greater number of people risk exposure to traffic-related air pollution (TRAP) and its adverse, costly health effects. In many cities, there is a need and scope for air quality improvements through targeted policy interventions, which continue to grow including rapidly changing technologies. OBJECTIVE This systematic evidence map (SEM) examines and characterizes peer-reviewed evidence on urban-level policy interventions aimed at reducing traffic emissions and/or TRAP from on-road mobile sources, thus potentially reducing human exposures and adverse health effects and producing various co-benefits. METHODS This SEM follows a previously peer-reviewed and published protocol with minor deviations, explicitly outlined here. Articles indexed in Public Affairs Index, TRID, Medline and Embase were searched, limited to English, published between January 1, 2000, and June 1, 2020. Covidence was used to screen articles based on previously developed eligibility criteria. Data for included articles was extracted and manually documented into an Excel database. Data visualizations were created in Tableau. RESULTS We identified 7528 unique articles from database searches and included 376 unique articles in the final SEM. There were 58 unique policy interventions, and a total of 1,139 unique policy scenarios, comprising these interventions and different combinations thereof. The policy interventions fell under 6 overarching policy categories: 1) pricing, 2) land use, 3) infrastructure, 4) behavioral, 5) technology, and 6) management, standards, and services, with the latter being the most studied. For geographic location, 463 policy scenarios were studied in Europe, followed by 355 in Asia, 206 in North America, 57 in South America, 10 in Africa, and 7 in Australia. Alternative fuel technology was the most frequently studied intervention (271 times), followed by vehicle emission regulation (134 times). The least frequently studied interventions were vehicle ownership taxes, and studded tire regulations, studied once each. A mere 3 % of studies addressed all elements of the full-chain-traffic emissions, TRAP, exposures, and health. The evidence recorded for each unique policy scenario is hosted in an open-access, query-able Excel database, and a complementary interactive visualization tool. We showcase how users can find more about the effectiveness of the 1,139 included policy scenarios in reducing, increasing, having mixed or no effect on traffic emissions and/or TRAP. CONCLUSION This is the first peer-reviewed SEM to compile international evidence on urban-level policy interventions to reduce traffic emissions and/or TRAP in the context of human exposure and health effects. We also documented reported enablers, barriers, and co-benefits. The open-access Excel database and interactive visualization tool can be valuable resources for practitioners, policymakers, and researchers. Future updates to this work are recommended. PROTOCOL REGISTRATION Sanchez, K.A., Foster, M., Nieuwenhuijsen, M.J., May, A.D., Ramani, T., Zietsman, J. and Khreis, H., 2020. Urban policy interventions to reduce traffic emissions and traffic-related air pollution: Protocol for a systematic evidence map. Environment international, 142, p.105826.
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Affiliation(s)
- Haneen Khreis
- MRC Epidemiology Unit, School of Clinical Medicine, University of Cambridge, Box 285 Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge CB2 0QQ, United Kingdom.
| | - Kristen A Sanchez
- Center for Advancing Research in Transportation Emissions, Energy, and Health (CARTEEH), Texas A&M Transportation Institute (TTI), TX, USA; Texas A&M School of Public Health, TX, USA.
| | - Margaret Foster
- Texas A&M University, Center for Systematic Reviews and Research Syntheses, College Station, TX, USA.
| | - Jacob Burns
- Institute for Medical Information Processing, Biometry and Epidemiology, Ludwig Maximilian University of Munich, Munich, Germany.
| | - Mark J Nieuwenhuijsen
- Barcelona Institute for Global Health (ISGlobal), Barcelona, Spain; Universitat Pompeu Fabra (UPF), Barcelona, Spain; CIBER Epidemiologia y Salud Publica (CIBERESP), Madrid, Spain.
| | - Rohit Jaikumar
- Center for Advancing Research in Transportation Emissions, Energy, and Health (CARTEEH), Texas A&M Transportation Institute (TTI), TX, USA.
| | - Tara Ramani
- Center for Advancing Research in Transportation Emissions, Energy, and Health (CARTEEH), Texas A&M Transportation Institute (TTI), TX, USA.
| | - Josias Zietsman
- Center for Advancing Research in Transportation Emissions, Energy, and Health (CARTEEH), Texas A&M Transportation Institute (TTI), TX, USA.
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Xu T, Zhang C, Liu C, Hu Q. Variability of PM 2.5 and O 3 concentrations and their driving forces over Chinese megacities during 2018-2020. J Environ Sci (China) 2023; 124:1-10. [PMID: 36182119 DOI: 10.1016/j.jes.2021.10.014] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2021] [Revised: 09/19/2021] [Accepted: 10/11/2021] [Indexed: 06/16/2023]
Abstract
Recently, air pollution especially fine particulate matters (PM2.5) and ozone (O3) has become a severe issue in China. In this study, we first characterized the temporal trends of PM2.5 and O3 for Beijing, Guangzhou, Shanghai, and Wuhan respectively during 2018-2020. The annual mean PM2.5 has decreased by 7.82%-33.92%, while O3 concentration showed insignificant variations by -6.77%-4.65% during 2018-2020. The generalized additive models (GAMs) were implemented to quantify the contribution of individual meteorological factors and their gas precursors on PM2.5 and O3. On a short-term perspective, GAMs modeling shows that the daily variability of PM2.5 concentration is largely related to the variation of precursor gases (R = 0.67-0.90), while meteorological conditions mainly affect the daily variability of O3 concentration (R = 0.65-0.80) during 2018-2020. The impact of COVID-19 lockdown on PM2.5 and O3 concentrations were also quantified by using GAMs. During the 2020 lockdown, PM2.5 decreased significantly for these megacities, yet the ozone concentration showed an increasing trend compared to 2019. The GAMs analysis indicated that the contribution of precursor gases to PM2.5 and O3 changes is 3-8 times higher than that of meteorological factors. In general, GAMs modeling on air quality is helpful to the understanding and control of PM2.5 and O3 pollution in China.
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Affiliation(s)
- Tianyi Xu
- School of Environmental Science and Optoelectronic Technology, University of Science and Technology of China, Hefei 230026, China; Key Laboratory of Environmental Optics and Technology, Anhui Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Hefei 230031, China
| | - Chengxin Zhang
- Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, Hefei 230026, China.
| | - Cheng Liu
- Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, Hefei 230026, China; Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; Key Laboratory of Environmental Optics and Technology, Anhui Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Hefei 230031, China; Key Laboratory of Precision Scientific Instrumentation of Anhui Higher Education Institutes, University of Science and Technology of China, Hefei 230026, China.
| | - Qihou Hu
- Key Laboratory of Environmental Optics and Technology, Anhui Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Hefei 230031, China
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Guan Y, Shen Y, Liu X, Liu X, Chen J, Li D, Xu M, Wang L, Duan E, Hou L, Han J. Important revelations of different degrees of COVID-19 lockdown on improving regional air quality: a case study of Shijiazhuang, China. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023; 30:21313-21325. [PMID: 36269475 PMCID: PMC9589624 DOI: 10.1007/s11356-022-23715-0] [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: 09/05/2022] [Accepted: 10/14/2022] [Indexed: 05/06/2023]
Abstract
To control the spread of COVID-19, Shijiazhuang implemented two lockdowns of different magnitudes in 2020 (lockdown I) and 2021 (lockdown II). We analyzed the changes in air quality index (AQI), PM2.5, O3, and VOCs during the two lockdowns and the same period in 2019 and quantified the effects of anthropogenic sources during the lockdowns. The results show that AQI decreased by 13.2% and 32.4%, and PM2.5 concentrations decreased by 12.9% and 42.4% during lockdown I and lockdown II, respectively, due to the decrease in urban traffic mobility and industrial activity levels. However, the sudden and unreasonable emission reductions led to an increase in O3 concentrations by 160.6% and 108.4%, respectively, during the lockdown period. To explore the causes of the O3 surge, the major precursors NOx and VOCs were studied separately, and the main VOCs species affecting ozone formation during the lockdown period and the source variation of VOCs were identified, and it is important to note that the relationship between diurnal variation characteristics of VOCs and cooking became apparent during the lockdown period. These findings suggest that regional air quality can be improved by limiting production, but attention should be paid to the surge of O3 caused by unreasonable emission reductions, clarifying the control priorities for urban O3 management.
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Affiliation(s)
- Yanan Guan
- School of Environmental Science and Engineering, Hebei University of Science and Technology, Shijiazhuang, 050018, China
- National Joint Local Engineering Research Center for Volatile Organic Compounds and Odorous Pollution Control, Shijiazhuang, 050018, China
| | - Ying Shen
- School of Environmental Science and Engineering, Hebei University of Science and Technology, Shijiazhuang, 050018, China
| | - Xinyue Liu
- School of Environmental Science and Engineering, Hebei University of Science and Technology, Shijiazhuang, 050018, China
| | - Xuejiao Liu
- School of Environmental Science and Engineering, Hebei University of Science and Technology, Shijiazhuang, 050018, China
| | - Jing Chen
- Shijiazhuang City Environmental Meteorological Center, Shijiazhuang, 050018, China
| | - Dong Li
- Shijiazhuang City Environmental Prediction and Forecast Center, Shijiazhuang, 050018, China
| | - Man Xu
- Shijiazhuang City Environmental Prediction and Forecast Center, Shijiazhuang, 050018, China
| | - Litao Wang
- School of Environmental Science and Engineering, Hebei University of Science and Technology, Shijiazhuang, 050018, China
- National Joint Local Engineering Research Center for Volatile Organic Compounds and Odorous Pollution Control, Shijiazhuang, 050018, China
| | - Erhong Duan
- School of Environmental Science and Engineering, Hebei University of Science and Technology, Shijiazhuang, 050018, China
- National Joint Local Engineering Research Center for Volatile Organic Compounds and Odorous Pollution Control, Shijiazhuang, 050018, China
| | - Li'an Hou
- Xi'an High-Tech Institute, Xi'an, 710025, Shaanxi, China
| | - Jing Han
- School of Environmental Science and Engineering, Hebei University of Science and Technology, Shijiazhuang, 050018, China.
- National Joint Local Engineering Research Center for Volatile Organic Compounds and Odorous Pollution Control, Shijiazhuang, 050018, China.
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Tavella RA, Galeao da Rosa Moraes N, Maciel Aick CD, Ramires PF, Pereira N, Soares AG, da Silva Júnior FMR. Weekend effect of air pollutants in small and medium-sized cities: The role of policies stringency to COVID-19 containment. ATMOSPHERIC POLLUTION RESEARCH 2023; 14:101662. [PMID: 36686558 PMCID: PMC9842451 DOI: 10.1016/j.apr.2023.101662] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/28/2022] [Revised: 01/14/2023] [Accepted: 01/14/2023] [Indexed: 06/17/2023]
Abstract
Although the pattern of air pollutants has been extensively studied during the COVID-19 pandemic, the weekend effect has been rarely investigated. In order to understand the impact of policies stringency as well as the interruption-recovery pattern, the aim of the study was to investigate the levels of air pollutants (O3, NO2, SO2, PM2.5, PM10) and PM2.5/PM10 ratio before and after the COVID-19 pandemic in four cities in the state of Rio Grande do Sul, Brazil, evaluating the weekend effect at these two scenarios and also identifying how the restriction measures applied locally had an impact on this effect. For this, daily data from two years of monitoring of air pollutants were collected and the weekend effect was calculated based on the levels from Monday to Friday (weekday) and Saturday and Sunday (weekend). There was a positive weekend effect for almost all criteria air pollutants in the four cities, and an intrinsic relation between the weekend effect and the restriction measures adopted. A negative weekend effect was observed in the scenario characterized by less restrictive and more permissive policies for daily and occupational activities. Conversely, when more stringent measures were implemented, this trend was reversed and higher intensities of positive weekend effect were observed as restrictions increased. In conclusion, the COVID-19 perturbation to air quality changed as regions tighten and loosen restrictions on human mobility. These insights that can guide responsible authorities about future strategies and policies for air quality control.
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Affiliation(s)
- Ronan Adler Tavella
- Programa de Pós-graduação Em Ciências da Saúde, Faculdade de Medicina, Universidade Federal Do Rio Grande, Campus Carreiros, 96200-400, Rio Grande - RS, Brazil
- Universidade Federal Do Rio Grande - FURG, Av. Itália, Km 8, Campus Carreiros, CEP, 96203-900, Rio Grande - RS, Brazil
| | - Niely Galeao da Rosa Moraes
- Universidade Federal Do Rio Grande - FURG, Av. Itália, Km 8, Campus Carreiros, CEP, 96203-900, Rio Grande - RS, Brazil
| | - Carlos Daniel Maciel Aick
- Programa de Pós-graduação Em Ciências Ambientais, Centro de Engenharias, Universidade Federal de Pelotas, Praça Domingos Rodrigues, Centro, 96010-450, Pelotas, RS, Brazil
| | - Paula Florencio Ramires
- Programa de Pós-graduação Em Ciências da Saúde, Faculdade de Medicina, Universidade Federal Do Rio Grande, Campus Carreiros, 96200-400, Rio Grande - RS, Brazil
- Universidade Federal Do Rio Grande - FURG, Av. Itália, Km 8, Campus Carreiros, CEP, 96203-900, Rio Grande - RS, Brazil
| | - Natália Pereira
- Programa de Pós-graduação Em Ciências da Saúde, Faculdade de Medicina, Universidade Federal Do Rio Grande, Campus Carreiros, 96200-400, Rio Grande - RS, Brazil
- Universidade Federal Do Rio Grande - FURG, Av. Itália, Km 8, Campus Carreiros, CEP, 96203-900, Rio Grande - RS, Brazil
| | - Ana Gonçalves Soares
- Bristol Medical School, University of Bristol, Barley House, Oakfield Grove, Bristol, BS8 2BN, UK
| | - Flavio Manoel Rodrigues da Silva Júnior
- Programa de Pós-graduação Em Ciências da Saúde, Faculdade de Medicina, Universidade Federal Do Rio Grande, Campus Carreiros, 96200-400, Rio Grande - RS, Brazil
- Universidade Federal Do Rio Grande - FURG, Av. Itália, Km 8, Campus Carreiros, CEP, 96203-900, Rio Grande - RS, Brazil
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Hui K, Yuan Y, Xi B, Tan W. A review of the factors affecting the emission of the ozone chemical precursors VOCs and NO x from the soil. ENVIRONMENT INTERNATIONAL 2023; 172:107799. [PMID: 36758299 DOI: 10.1016/j.envint.2023.107799] [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: 11/12/2022] [Revised: 01/28/2023] [Accepted: 02/01/2023] [Indexed: 06/18/2023]
Abstract
The soil environment is one of the main places for the generation, emission, and absorption of various atmospheric pollutants, including nitrogen oxides (NOx) and volatile organic compounds (VOCs), which are the main chemical precursors for the formation of ground-level ozone. Ground-level ozone pollution has become a concerning environmental problem because of the harm it poses to human health and the surrounding ecological environment. However, current studies on chemical precursors of ozone mainly focus on emissions from industrial sources, forest vegetation, and urban vehicle exhaust; by contrast, few studies have examined the role of the soil environment on NOx and VOCs emissions. In addition, the soil environment is complex and heterogeneous. Agricultural activities (fertilization) and atmospheric deposition provide nutrients for the soil environment, with a significant effect on NOx and VOCs emissions. There is thus a need to study the environmental factors related to the release of NOx and VOCs in the soil to enhance our understanding of emission fluxes and the types of NOx and VOCs in the soil environment and aid efforts to control ground-level ozone pollution through appropriate measures such as management of agricultural activities. This paper reviews the generation of NOx and VOCs in the soil environment and the effects of various environmental factors on this process. Some suggestions are provided for future research on the regulation of NOx and VOCs emissions in the soil environment and the ability of the soil environment to contribute to ground-level ozone pollution.
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Affiliation(s)
- Kunlong Hui
- State Key Laboratory of Environmental Criteria and Risk Assessment, and State Environmental Protection Key Laboratory of Simulation and Control of Groundwater Pollution, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Ying Yuan
- State Key Laboratory of Environmental Criteria and Risk Assessment, and State Environmental Protection Key Laboratory of Simulation and Control of Groundwater Pollution, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Beidou Xi
- State Key Laboratory of Environmental Criteria and Risk Assessment, and State Environmental Protection Key Laboratory of Simulation and Control of Groundwater Pollution, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Wenbing Tan
- State Key Laboratory of Environmental Criteria and Risk Assessment, and State Environmental Protection Key Laboratory of Simulation and Control of Groundwater Pollution, Chinese Research Academy of Environmental Sciences, Beijing 100012, China.
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Sicard P, Agathokleous E, Anenberg SC, De Marco A, Paoletti E, Calatayud V. Trends in urban air pollution over the last two decades: A global perspective. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 858:160064. [PMID: 36356738 DOI: 10.1016/j.scitotenv.2022.160064] [Citation(s) in RCA: 46] [Impact Index Per Article: 46.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/20/2022] [Revised: 11/03/2022] [Accepted: 11/04/2022] [Indexed: 06/16/2023]
Abstract
Ground-level ozone (O3), fine particles (PM2.5), and nitrogen dioxide (NO2) are the most harmful urban air pollutants regarding human health effects. Here, we aimed at assessing trends in concurrent exposure of global urban population to O3, PM2.5, and NO2 between 2000 and 2019. PM2.5, NO2, and O3 mean concentrations and summertime mean of the daily maximum 8-h values (O3 MDA8) were analyzed (Mann-Kendall test) using data from a global reanalysis, covering 13,160 urban areas, and a ground-based monitoring network (Tropospheric Ozone Assessment Report), collating surface O3 observations at nearly 10,000 stations worldwide. At global scale, PM2.5 exposures declined slightly from 2000 to 2019 (on average, - 0.2 % year-1), with 65 % of cities showing rising levels. Improvements were observed in the Eastern US, Europe, Southeast China, and Japan, while the Middle East, sub-Saharan Africa, and South Asia experienced increases. The annual NO2 mean concentrations increased globally at 71 % of cities (on average, +0.4 % year-1), with improvements in North America and Europe, and increases in exposures in sub-Saharan Africa, Middle East, and South Asia regions, in line with socioeconomic development. Global exposure of urban population to O3 increased (on average, +0.8 % year-1 at 89 % of stations), due to lower O3 titration by NO. The summertime O3 MDA8 rose at 74 % of cities worldwide (on average, +0.6 % year-1), while a decline was observed in North America, Northern Europe, and Southeast China, due to the reduction in precursor emissions. The highest O3 MDA8 increases (>3 % year-1) occurred in Equatorial Africa, South Korea, and India. To reach air quality standards and mitigate outdoor air pollution effects, actions are urgently needed at all governance levels. More air quality monitors should be installed in cities, particularly in Africa, for improving risk and exposure assessments, concurrently with implementation of effective emission control policies that will consider regional socioeconomic imbalances.
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Affiliation(s)
| | | | - Susan C Anenberg
- George Washington University, Milken Institute School of Public Health, United States
| | | | | | - Vicent Calatayud
- Fundación CEAM, Parque Tecnológico, C/Charles R. Darwin, 14, Paterna, Spain
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