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Han Y, Gu X, Lin C, He M, Wang Y. Effects of COVID-19 on coastal and marine environments: Aggravated microplastic pollution, improved air quality, and future perspective. CHEMOSPHERE 2024; 355:141900. [PMID: 38579953 DOI: 10.1016/j.chemosphere.2024.141900] [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: 02/06/2024] [Revised: 04/01/2024] [Accepted: 04/02/2024] [Indexed: 04/07/2024]
Abstract
The COVID-19 pandemic during 2020-2023 has wrought adverse impacts on coastal and marine environments. This study conducts a comprehensive review of the collateral effects of COVID-19 on these ecosystems through literature review and bibliometric analysis. According to the output and citation analysis of these publications, researchers from the coastal countries in Asia, Europe, and America payed more attentions to this environmental issue than other continents. Specifically, India, China, and USA were the top three countries in the publications, with the proportion of 19.55%, 18.99%, and 12.01%, respectively. The COVID-19 pandemic significantly aggravated the plastic and microplastic pollution in coastal and marine environments by explosive production and unproper management of personal protective equipment (PPE). During the pandemic, the estimated mismanaged PPE waste ranged from 16.50 t/yr in Sweden to 250,371.39 t/yr in Indonesia. In addition, the PPE density ranged from 1.13 × 10-5 item/m2 to 2.79 item/m2 in the coastal regions worldwide, showing significant geographical variations. Besides, the emerging contaminants released from PPE into the coastal and marine environments cannot be neglected. The positive influence was that the COVID-19 lockdown worldwide reduced the release of air pollutants (e.g., fine particulate matter, NO2, CO, and SO2) and improved the air quality. The study also analyzed the relationships between sustainable development goals (SDGs) and the publications and revealed the dynamic changes of SDGs in different periods the COVID-19 pandemic. In conclusion, the air was cleaner due to the lockdown, but the coastal and marine contamination of plastic, microplastic, and emerging contaminants got worse during the COVID-19 pandemic. Last but not least, the study proposed four strategies to deal with the coastal and marine pollution caused by COVID-19, which were regular marine monitoring, performance of risk assessment, effective regulation of plastic wastes, and close international cooperation.
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Affiliation(s)
- Yixuan Han
- State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing, 100875, China
| | - Xiang Gu
- National-Regional Joint Engineering Research Center for Soil Pollution Control and Remediation in South China, Guangdong Key Laboratory of Integrated Agro-environmental Pollution Control and Management, Institute of Eco-environmental and Soil Sciences, Guangdong Academy of Sciences, Guangzhou, 510650, China; School of Environment, Beijing Normal University, Beijing, 100875, China.
| | - Chunye Lin
- School of Environment, Beijing Normal University, Beijing, 100875, China
| | - Mengchang He
- School of Environment, Beijing Normal University, Beijing, 100875, China
| | - Yidi Wang
- Key Laboratory of Water and Sediment Sciences, Ministry of Education, College of Environmental Sciences and Engineering, Peking University, Beijing, 100871, China
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Wu J, Chen X, Li R, Wang A, Huang S, Li Q, Qi H, Liu M, Cheng H, Wang Z. A novel framework for high resolution air quality index prediction with interpretable artificial intelligence and uncertainties estimation. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2024; 357:120785. [PMID: 38583378 DOI: 10.1016/j.jenvman.2024.120785] [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: 09/08/2023] [Revised: 02/02/2024] [Accepted: 03/27/2024] [Indexed: 04/09/2024]
Abstract
Accurate air quality index (AQI) prediction is essential in environmental monitoring and management. Given that previous studies neglect the importance of uncertainty estimation and the necessity of constraining the output during prediction, we proposed a new hybrid model, namely TMSSICX, to forecast the AQI of multiple cities. Firstly, time-varying filtered based empirical mode decomposition (TVFEMD) was adopted to decompose the AQI sequence into multiple internal mode functions (IMF) components. Secondly, multi-scale fuzzy entropy (MFE) was applied to evaluate the complexity of each IMF component and clustered them into high and low-frequency portions. In addition, the high-frequency portion was secondarily decomposed by successive variational mode decomposition (SVMD) to reduce volatility. Then, six air pollutant concentrations, namely CO, SO2, PM2.5, PM10, O3, and NO2, were used as inputs. The secondary decomposition and preliminary portion were employed as the outputs for the bidirectional long short-term memory network optimized by the snake optimization algorithm (SOABiLSTM) and improved Catboost (ICatboost), respectively. Furthermore, extreme gradient boosting (XGBoost) was applied to ensemble each predicted sub-model to acquire the consequence. Ultimately, we introduced adaptive kernel density estimation (AKDE) for interval estimation. The empirical outcome indicated the TMSSICX model achieved the best performance among the other 23 models across all datasets. Moreover, implementing the XGBoost to ensemble each predicted sub-model led to an 8.73%, 8.94%, and 0.19% reduction in RMSE, compared to SVM. Additionally, by utilizing SHapley Additive exPlanations (SHAP) to assess the impact of the six pollutant concentrations on AQI, the results reveal that PM2.5 and PM10 had the most notable positive effects on the long-term trend of AQI. We hope this model can provide guidance for air quality management.
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Affiliation(s)
- Junhao Wu
- State Key Laboratory of Estuarine and Coastal Research, East China Normal University, Shanghai, 200062, China
| | - Xi Chen
- School of Geographic Sciences, East China Normal University, Shanghai, 200241, China; Key Laboratory of Geographic Information Science, Ministry of Education, East China Normal University, Shanghai, 200241, China; Key Laboratory of Spatial-Temporal Big Data Analysis and Application of Natural Resources in Megacities, Ministry of Natural Resources, Shanghai, 200241, China.
| | - Rui Li
- School of Geographic Sciences, East China Normal University, Shanghai, 200241, China
| | - Anqi Wang
- Department of Mathematics, The University of Manchester, Manchester, M13 9PL, UK
| | - Shutong Huang
- School of Geographic Sciences, East China Normal University, Shanghai, 200241, China
| | - Qingli Li
- Shanghai Key Laboratory of Multidimensional Information Processing, East China Normal University, Shanghai, 200241, China
| | - Honggang Qi
- School of Computer Science and Technology, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Min Liu
- School of Geographic Sciences, East China Normal University, Shanghai, 200241, China; Key Laboratory of Geographic Information Science, Ministry of Education, East China Normal University, Shanghai, 200241, China
| | - Heqin Cheng
- State Key Laboratory of Estuarine and Coastal Research, East China Normal University, Shanghai, 200062, China.
| | - Zhaocai Wang
- College of Information, Shanghai Ocean University, Shanghai, 201306, China.
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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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Zoran M, Savastru R, Savastru D, Tautan M, Tenciu D. Linkage between Airborne Particulate Matter and Viral Pandemic COVID-19 in Bucharest. Microorganisms 2023; 11:2531. [PMID: 37894189 PMCID: PMC10609195 DOI: 10.3390/microorganisms11102531] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2023] [Revised: 09/21/2023] [Accepted: 09/25/2023] [Indexed: 10/29/2023] Open
Abstract
The long-distance spreading and transport of airborne particulate matter (PM) of biogenic or chemical compounds, which are thought to be possible carriers of SARS-CoV-2 virions, can have a negative impact on the incidence and severity of COVID-19 viral disease. Considering the total Aerosol Optical Depth at 550 nm (AOD) as an atmospheric aerosol loading variable, inhalable fine PM with a diameter ≤2.5 µm (PM2.5) or coarse PM with a diameter ≤10 µm (PM10) during 26 February 2020-31 March 2022, and COVID-19's five waves in Romania, the current study investigates the impact of outdoor PM on the COVID-19 pandemic in Bucharest city. Through descriptive statistics analysis applied to average daily time series in situ and satellite data of PM2.5, PM10, and climate parameters, this study found decreased trends of PM2.5 and PM10 concentrations of 24.58% and 18.9%, respectively compared to the pre-pandemic period (2015-2019). Exposure to high levels of PM2.5 and PM10 particles was positively correlated with COVID-19 incidence and mortality. The derived average PM2.5/PM10 ratios during the entire pandemic period are relatively low (<0.44), indicating a dominance of coarse traffic-related particles' fraction. Significant reductions of the averaged AOD levels over Bucharest were recorded during the first and third waves of COVID-19 pandemic and their associated lockdowns (~28.2% and ~16.4%, respectively) compared to pre-pandemic period (2015-2019) average AOD levels. The findings of this research are important for decision-makers implementing COVID-19 safety controls and health measures during viral infections.
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Affiliation(s)
- Maria Zoran
- C Department, National Institute of R&D for Optoelectronics, 409 Atomistilor Street, MG5, 077125 Magurele, Romania; (R.S.); (D.S.); (M.T.); (D.T.)
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Tao J, Yan J, Su H, Huang C, Tong S, Ho HC, Xia Q, Zhu C, Zheng H, Hossain MZ, Cheng J. Impacts of PM 2.5 before and after COVID-19 outbreak on emergency mental disorders: A population-based quasi-experimental and case-crossover study. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2023; 334:122175. [PMID: 37437758 DOI: 10.1016/j.envpol.2023.122175] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/29/2022] [Revised: 06/04/2023] [Accepted: 07/09/2023] [Indexed: 07/14/2023]
Abstract
The ongoing COVID-19 pandemic is a great challenge to mental health, but fine particulate matter (PM2.5), an increasingly reported risk factor for mental disorders, has been greatly alleviated during the pandemic in many countries. It remains unknown whether COVID-19 outbreak can affect the association between PM2.5 exposure and the risk of mental disorders. This study aimed to investigate the associations of total and cause-specific mental disorders with PM2.5 exposure before and after the COVID-19 outbreak in China. Data on daily emergency department visits (EDVs) and hospitalizations of mental disorders from 2016 to 2021 were obtained from Anhui Mental Health Center for Hefei city. An interrupted time series analysis was used to quantify the impact of COVID-19 outbreak on EDVs and hospitalizations of mental disorders. A time-stratified case-crossover analysis was employed to evaluate the association of mental disorders with PM2.5 exposure before and after the COVID-19 outbreak, especially in the three months following the COVID-19 outbreak. After COVID-19 outbreak, there was an immediate and significant decrease in total mental disorders, including a reduction of 15% (95% CI: 3%-26%) in EDVs and 44% (95% CI: 36%-51%) in hospitalizations. PM2.5 exposure was associated with increased risk of EDVs and hospitalizations for total and cause-specific mental disorders (schizophrenia, schizotypal and delusional disorders; neurotic, stress-related, and somatoform disorders) before COVID-19 outbreak, but this PM2.5-related risk elevation significantly decreased after COVID-19 outbreak, with greater risk reduction at the first month after the outbreak. However, young people (0-45 years) were still vulnerable to PM2.5 exposure after the COVID-19 outbreak. This study first reveals that the risk of PM2.5-related emergency mental disorders decreased after the COVID-19 outbreak in China. The low concentration of PM2.5 might benefit mental health and greater efforts are required to mitigate air pollution in the post-COVID-19 era.
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Affiliation(s)
- Junwen Tao
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, China; Anhui Province Key Laboratory of Major Autoimmune Disease, Hefei, China
| | - Junwei Yan
- Affiliated Psychological Hospital of Anhui Medical University, Hefei, China; Anhui Mental Health Center, Hefei, China; Hefei Fourth People's Hospital, Hefei, China; Anhui Clinical Research Center for Mental Disorders, Hefei, China
| | - Hong Su
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, China; Anhui Province Key Laboratory of Major Autoimmune Disease, Hefei, China
| | - Cunrui Huang
- Vanke School of Public Health, Tsinghua University, Beijing, China
| | - Shilu Tong
- National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China; School of Public Health, Institute of Environment and Population Health, Anhui Medical University, Hefei, China; Centre of Global Health, School of Public Health, Nanjing Medical University, Nanjing, China; School of Public Health and Social Work, Queensland University of Technology, Brisbane, Australia
| | - Hung Chak Ho
- Department of Public and International Affairs, City University of Hong Kong, Hong Kong, China
| | - Qingrong Xia
- Affiliated Psychological Hospital of Anhui Medical University, Hefei, China; Anhui Mental Health Center, Hefei, China; Hefei Fourth People's Hospital, Hefei, China; Anhui Clinical Research Center for Mental Disorders, Hefei, China
| | - Cuizhen Zhu
- Affiliated Psychological Hospital of Anhui Medical University, Hefei, China; Anhui Mental Health Center, Hefei, China; Hefei Fourth People's Hospital, Hefei, China; Anhui Clinical Research Center for Mental Disorders, Hefei, China
| | - Hao Zheng
- Department of Environmental Health, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, China
| | - Mohammad Zahid Hossain
- International Centre for Diarrhoeal Disease Research, Bangladesh (icddr,b), Dhaka, Bangladesh
| | - Jian Cheng
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, China; Anhui Province Key Laboratory of Major Autoimmune Disease, Hefei, China.
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6
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Oduniyi OS, Riveros JM, Hassan SM, Çıtak F. Testing the theory of Kuznet curve on environmental pollution during pre- and post-Covid-19 era. Sci Rep 2023; 13:12851. [PMID: 37553418 PMCID: PMC10409723 DOI: 10.1038/s41598-023-38962-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2023] [Accepted: 07/18/2023] [Indexed: 08/10/2023] Open
Abstract
Covid-19 has brought about significant changes in people's daily lives, leading to a slowdown in economic activities and the implementation of restrictions and lockdowns. As a result, there have been noticeable effects on the environment. In this study, we examine the impact of Covid-19 total cases on the monthly average of carbon monoxide emissions in developed economies known for heavy pollution, covering the period from 2014 to 2023. We apply the Ambiental Kuznets curve approach to analyze the data. By employing different panel estimation techniques such as fixed effects and Driscoll-Kraay regressions, we observe a marked shift in environmental dynamics during the post-Covid era. This shift alters the statistical significance of the N-shaped Kuznets curve, rendering the relationship between economic activity and environmental impact non-significant. Interestingly, the Covid-related variables utilized in the various estimations are not statistically significant in explaining the long-term environmental effects.
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Affiliation(s)
| | - John M Riveros
- Estudios Y Evaluación de La Gestión Pública Colombian, Colombia, USA
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Xu J, Yin X, Jiang T, Wang S, Wang D. Effects of air pollution control policies on intracerebral hemorrhage mortality among residents in Tianjin, China. BMC Public Health 2023; 23:858. [PMID: 37170126 PMCID: PMC10173217 DOI: 10.1186/s12889-023-15735-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2022] [Accepted: 04/22/2023] [Indexed: 05/13/2023] Open
Abstract
BACKGROUND Exposure to air pollution is an important risk factor for intracerebral hemorrhage (ICH), which is a major cause of death worldwide. However, the relationship between ICH mortality and air quality improvement has been poorly studied. This study aims to evaluate the impact of the air pollution control policies in the Beijing-Tianjin-Hebei region on ICH mortality among Tianjin residents. METHODS This study used an interrupted time series analysis. We fitted autoregressive integrated moving average (ARIMA) models to assess the changes in ICH deaths before and after the interventions of air pollution control policies based on the data of ICH deaths in Tianjin collected by the Tianjin Center for Disease Control and Prevention. RESULTS Between 2009 and 2020, there were 63,944 ICH deaths in Tianjin, and there was an overall decreasing trend in ICH mortality. The intervention conducted in June 2014 resulted in a statistically significant (p = 0.03) long-term trend change, reducing the number of deaths from ICH by 0.69 (95% confidence interval [CI]: -1.30 to -0.07) per month. The intervention in October 2017 resulted in a statistically significant (p = 0.04) immediate decrease of 25.74 (95% CI: -50.62 to -0.85) deaths from ICH in that month. The intervention in December 2017 caused a statistically significant (p = 0.04) immediate reduction of 26.58 (95% CI: -52.02 to -1.14) deaths from ICH in that month. The intervention in March 2018 resulted in a statistically significant (p = 0.02) immediate decrease of 30.40 (95% CI: -56.41 to -4.40) deaths from ICH in that month. No significant differences were observed in the changes of male ICH mortality after any of the four interventions. However, female ICH deaths showed statistically significant long-term trend change after the intervention in June 2014 and immediate changes after the interventions in December 2017 and March 2018. Overall, the interventions prevented an estimated 5984.76 deaths due to ICH. CONCLUSION During the study period, some interventions of air pollution control policies were significantly associated with the reductions in the number of deaths from ICH among residents in Tianjin. ICH survivors and females were more sensitive to the protective effects of the interventions. Interventions for air pollution control can achieve public health gains in cities with high levels of air pollution.
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Affiliation(s)
- Jiahui Xu
- School of Public Health, Tianjin Medical University, Tianjin, China
- NCDs Preventive Department, Tianjin Centers for Disease Control and Prevention, No. 6 Huayue Road, Hedong District, Tianjin, 300011, China
| | - Xiaolin Yin
- School of Public Health, Tianjin Medical University, Tianjin, China
- NCDs Preventive Department, Tianjin Centers for Disease Control and Prevention, No. 6 Huayue Road, Hedong District, Tianjin, 300011, China
| | - Tingting Jiang
- School of Public Health, Tianjin Medical University, Tianjin, China
- NCDs Preventive Department, Tianjin Centers for Disease Control and Prevention, No. 6 Huayue Road, Hedong District, Tianjin, 300011, China
| | - Shiyu Wang
- School of Public Health, Tianjin Medical University, Tianjin, China
- NCDs Preventive Department, Tianjin Centers for Disease Control and Prevention, No. 6 Huayue Road, Hedong District, Tianjin, 300011, China
| | - Dezheng Wang
- School of Public Health, Tianjin Medical University, Tianjin, China.
- NCDs Preventive Department, Tianjin Centers for Disease Control and Prevention, No. 6 Huayue Road, Hedong District, Tianjin, 300011, China.
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Chen C, Gao B, Xu M, Liu S, Zhu D, Yang J, Chen Z. The spatiotemporal variation of PM 2.5-O 3 association and its influencing factors across China: Dynamic Simil-Hu lines. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 880:163346. [PMID: 37031933 DOI: 10.1016/j.scitotenv.2023.163346] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/12/2023] [Revised: 03/31/2023] [Accepted: 04/03/2023] [Indexed: 04/15/2023]
Abstract
In recent years, PM2.5 and O3 composite airborne pollution has become one of the most severe environment issues in China. To get a better understanding and tackle these problems, we employed multi-year data to explore the spatiotemporal variation of the PM2.5-O3 relationship in China and investigated its major driving factors. Firstly, interesting patterns were found that named dynamic Simil-Hu lines, which presented a combined effect of natural and anthropogenic influences, were closely related to the spatial patterns of PM2.5-O3 association across seasons. Furthermore, regions with lower altitudes, higher humidity, higher atmospheric pressure, higher temperature, fewer sunshine hours, more accumulated precipitation, denser population and higher GDP often show positive PM2.5-O3 associations, regardless of seasonal variations. Amongst these factors, humidity, temperature and precipitation were dominant factors. This research suggests that the collaborative governance of composite atmospheric pollution should be implemented dynamically, in consideration of geographical locations, meteorological conditions and socioeconomic conditions.
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Affiliation(s)
- Chenru Chen
- College of Surveying and Geographic Informatics, Tongji University, Shanghai 200092, China
| | - Bingbo Gao
- College of Land Science and Technology, China Agricultural University, Beijing 100091, China.
| | - Miaoqing Xu
- College of Global and Earth System Sciences, Beijing Normal University, Beijing 100875, China
| | - Shuyi Liu
- College of Land Science and Technology, China Agricultural University, Beijing 100091, China
| | - Dehai Zhu
- College of Land Science and Technology, China Agricultural University, Beijing 100091, China
| | - Jianyu Yang
- College of Land Science and Technology, China Agricultural University, Beijing 100091, China
| | - Ziyue Chen
- College of Global and Earth System Sciences, Beijing Normal University, Beijing 100875, China.
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Fu D, Shi X, Zuo J, Yabo SD, Li J, Li B, Li H, Lu L, Tang B, Qi H, Ma J. Why did air quality experience little improvement during the COVID-19 lockdown in megacities, northeast China? ENVIRONMENTAL RESEARCH 2023; 221:115282. [PMID: 36639012 PMCID: PMC9830900 DOI: 10.1016/j.envres.2023.115282] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/26/2022] [Revised: 12/25/2022] [Accepted: 01/10/2023] [Indexed: 05/05/2023]
Abstract
To inhibit the COVID-19 (Coronavirus disease 2019) outbreak, unprecedented nationwide lockdowns were implemented in China in early 2020, resulting in a marked reduction of anthropogenic emissions. However, reasons for the insignificant improvement in air quality in megacities of northeast China, including Shenyang, Changchun, Jilin, Harbin, and Daqing, were scarcely reported. We assessed the influences of meteorological conditions and changes in emissions on air quality in the five megacities during the COVID-19 lockdown (February 2020) using the WRF-CMAQ model. Modeling results indicated that meteorology contributed a 14.7% increment in Air Quality Index (AQI) averaged over the five megacities, thus, the local unfavorable meteorology was one of the causes to yield little improved air quality. In terms of emission changes, the increase in residential emissions (+15%) accompanied by declining industry emissions (-15%) and transportation (-90%) emissions resulted in a slight AQI decrease of 3.1%, demonstrating the decrease in emissions associated with the lockdown were largely offset by the increment in residential emissions. Also, residential emissions contributed 42.3% to PM2.5 concentration on average based on the Integrated Source Apportionment tool. These results demonstrated the key role residential emissions played in determining air quality. The findings of this study provide a scenario that helps make appropriate emission mitigation measures for improving air quality in this part of China.
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Affiliation(s)
- Donglei Fu
- State Key Laboratory of Urban Water Resource and Environment, Harbin Institute of Technology, 73 Huanghe Road, Harbin, Heilongjiang, 150000, China; School of Environment, Harbin Institute of Technology, 73 Huanghe Road, Harbin, Heilongjiang, 150000, China; Heilongjiang Provincial Key Laboratory of Polar Environment and Ecosystem, 73 Huanghe Road, Harbin, Heilongjiang, 150000, China; College of Urban and Environmental Sciences, Peking University, Beijing, 100091, China
| | - Xiaofei Shi
- State Key Laboratory of Urban Water Resource and Environment, Harbin Institute of Technology, 73 Huanghe Road, Harbin, Heilongjiang, 150000, China; School of Environment, Harbin Institute of Technology, 73 Huanghe Road, Harbin, Heilongjiang, 150000, China; Heilongjiang Provincial Key Laboratory of Polar Environment and Ecosystem, 73 Huanghe Road, Harbin, Heilongjiang, 150000, China; CASIC Intelligence Industry Development Co., Ltd, 50 Yongding Road, Beijing, 100089, China
| | - Jinxiang Zuo
- State Key Laboratory of Urban Water Resource and Environment, Harbin Institute of Technology, 73 Huanghe Road, Harbin, Heilongjiang, 150000, China; School of Environment, Harbin Institute of Technology, 73 Huanghe Road, Harbin, Heilongjiang, 150000, China
| | - Stephen Dauda Yabo
- State Key Laboratory of Urban Water Resource and Environment, Harbin Institute of Technology, 73 Huanghe Road, Harbin, Heilongjiang, 150000, China; School of Environment, Harbin Institute of Technology, 73 Huanghe Road, Harbin, Heilongjiang, 150000, China; Heilongjiang Provincial Key Laboratory of Polar Environment and Ecosystem, 73 Huanghe Road, Harbin, Heilongjiang, 150000, China
| | - Jixiang Li
- College of Urban and Environmental Sciences, Peking University, Beijing, 100091, China
| | - Bo Li
- State Key Laboratory of Urban Water Resource and Environment, Harbin Institute of Technology, 73 Huanghe Road, Harbin, Heilongjiang, 150000, China; School of Environment, Harbin Institute of Technology, 73 Huanghe Road, Harbin, Heilongjiang, 150000, China; Heilongjiang Provincial Key Laboratory of Polar Environment and Ecosystem, 73 Huanghe Road, Harbin, Heilongjiang, 150000, China
| | - Haizhi Li
- Heilongjiang Provincial Ecological and Environmental Monitoring Center, 2 Weixing Road, Harbin, Heilongjiang, 150000, China
| | - Lu Lu
- State Key Laboratory of Urban Water Resource and Environment, Harbin Institute of Technology, 73 Huanghe Road, Harbin, Heilongjiang, 150000, China; School of Environment, Harbin Institute of Technology, 73 Huanghe Road, Harbin, Heilongjiang, 150000, China; Heilongjiang Provincial Key Laboratory of Polar Environment and Ecosystem, 73 Huanghe Road, Harbin, Heilongjiang, 150000, China
| | - Bo Tang
- State Key Laboratory of Urban Water Resource and Environment, Harbin Institute of Technology, 73 Huanghe Road, Harbin, Heilongjiang, 150000, China; School of Environment, Harbin Institute of Technology, 73 Huanghe Road, Harbin, Heilongjiang, 150000, China; Heilongjiang Provincial Key Laboratory of Polar Environment and Ecosystem, 73 Huanghe Road, Harbin, Heilongjiang, 150000, China
| | - Hong Qi
- State Key Laboratory of Urban Water Resource and Environment, Harbin Institute of Technology, 73 Huanghe Road, Harbin, Heilongjiang, 150000, China; School of Environment, Harbin Institute of Technology, 73 Huanghe Road, Harbin, Heilongjiang, 150000, China; Heilongjiang Provincial Key Laboratory of Polar Environment and Ecosystem, 73 Huanghe Road, Harbin, Heilongjiang, 150000, China.
| | - Jianmin Ma
- College of Urban and Environmental Sciences, Peking University, Beijing, 100091, China.
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10
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Gao C, Zhang F, Fang D, Wang Q, Liu M. Spatial characteristics of change trends of air pollutants in Chinese urban areas during 2016-2020: The impact of air pollution controls and the COVID-19 pandemic. ATMOSPHERIC RESEARCH 2023; 283:106539. [PMID: 36465231 PMCID: PMC9701570 DOI: 10.1016/j.atmosres.2022.106539] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/09/2022] [Revised: 11/07/2022] [Accepted: 11/22/2022] [Indexed: 05/26/2023]
Abstract
Air pollution is a threat to public health in China, and several actions and plans have been implemented by Chinese authorities in recent years to mitigate it. This study examined the spatial distribution of changes in urban air pollutants (UAP) in 336 Chinese cities from 2016 to 2020 and their responses to air pollution controls and the COVID-19 pandemic. Based on the harmonic model, decreases in fine particles (PM2.5), inhalable particles (PM10), nitrogen dioxide (NO2), sulfur dioxide (SO2), and carbon monoxide (CO) levels were found in 90.7%, 91.9%, 75.2%, 94.3%, and 88.7% of cities, respectively, while an increase in ozone (O3) was found in 87.2% of cities. Notable spatial heterogeneity was observed in the air pollution trends. The greatest improvement in air quality occurred mainly in areas with poor air quality, such as Hebei province and its surrounding cities. However, some areas (i.e., Yunnan and Hainan provinces) with good air quality showed a worsening trend. During the 13th Five-Year Plan period (2016-2020), the remarkable effects of PM2.5 and SO2 pollution control plans were confirmed. Additionally, economic growth in 74.2% of the Chinese provinces decoupled from air quality after implementing pollution control measures. In 2020, several Chinese cities were locked down to reduce the spread of COVID-19. Except for SO2, the national air pollution in 2020 improved to a greater extent than that in 2016-2019; In particularly, the contribution of simulated COVID-19 pandemic to NO2 reduction was 66.7%. Overall, air pollution control actions improved urban PM2.5, PM10, SO2, and CO, whereas NO2 was reduced primarily because of the COVID-19 pandemic.
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Affiliation(s)
- Chanchan Gao
- College of Geography and Tourism, Hengyang Normal University, Hengyang 421000, China
- Shanghai Key Lab for Urban Ecological Processes and Eco-Restoration, School of Ecological and Environmental Sciences, East China Normal University, Shanghai 200241, China
| | - Fengying Zhang
- China National Environmental Monitoring Center, Beijing 100012, China
| | - Dekun Fang
- China National Environmental Monitoring Center, Beijing 100012, China
| | - Qingtao Wang
- School of Landscape and Ecological Engineering, Hebei University of Engineering, Handan 056038, Hebei Province, China
| | - Min Liu
- Key Lab of Forensic Science, Ministry of Justice, China (Academy of Forensic Science), Shanghai 200063, China
- Shanghai Key Lab for Urban Ecological Processes and Eco-Restoration, School of Ecological and Environmental Sciences, East China Normal University, Shanghai 200241, China
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11
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Llaguno-Munitxa M, Bou-Zeid E. Role of vehicular emissions in urban air quality: The COVID-19 lockdown experiment. TRANSPORTATION RESEARCH. PART D, TRANSPORT AND ENVIRONMENT 2023; 115:103580. [PMID: 36573137 PMCID: PMC9771761 DOI: 10.1016/j.trd.2022.103580] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/11/2022] [Revised: 11/17/2022] [Accepted: 12/18/2022] [Indexed: 06/17/2023]
Abstract
While the decrease in air pollutant concentration during the COVID-19 lockdown is well documented, neighborhood-scale and multi-city data have not yet been explored systematically to derive a generalizable quantitative link to the drop in vehicular traffic. To bridge this gap, high spatial resolution air quality and georeferenced traffic datasets were compiled for the city of London during three weeks with significant differences in traffic. The London analysis was then augmented with a meta-analysis of lower-resolution studies from 12 other cities. The results confirm that the improvement in air quality can be partially attributed to the drop of traffic density, and more importantly quantifies the elasticity (0.71 for NO2 & 0.56 for PM2.5) of their linkages. The findings can also inform on the future impacts of the ongoing shift to electric vehicles and micro-mobility on urban air quality.
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Affiliation(s)
- Maider Llaguno-Munitxa
- Faculty of Architecture, Architectural Engineering and Urban Planning, UCLouvain, Place du Levant 1, 1348 Ottignies-Louvain-la-Neuve, Belgium
| | - Elie Bou-Zeid
- Department of Civil and Environmental Engineering, Princeton University, Princeton, NJ, USA
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12
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Investigating the association between air pollutants' concentration and meteorological parameters in a rapidly growing urban center of West Bengal, India: a statistical modeling-based approach. MODELING EARTH SYSTEMS AND ENVIRONMENT 2023; 9:2877-2892. [PMID: 36624780 PMCID: PMC9812750 DOI: 10.1007/s40808-022-01670-6] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/23/2022] [Accepted: 12/28/2022] [Indexed: 01/06/2023]
Abstract
The ambient air quality in a city is heavily influenced by meteorological conditions. The city of Siliguri, known as the "Gateway of Northeast India", is a major hotspot of air pollution in the Indian state of West Bengal. Yet almost no research has been done on the possible impacts of meteorological factors on criterion air pollutants in this rapidly growing urban area. From March 2018 to September 2022, the present study aimed to determine the correlations between meteorological factors, including daily mean temperature (℃), relative humidity (%), rainfall (mm), wind speed (m/s) with the concentration of criterion air pollutants (PM2.5, PM10, NO2, SO2, CO, O3, and NH3). For this research, the trend of all air pollutants over time was also investigated. The Spearman correlation approach was used to correlate the concentration of air pollutants with the effect of meteorological variables on these pollutants. Comparing the multiple linear regression (MLR) and non-linear regression (MLNR) models permitted to examine the potential influence of meteorological factors on concentrations of air pollutants. According to the trend analysis, the concentration of NH3 in the air of Siliguri is rising, while the concentration of other pollutants is declining. Most pollutants showed a negative correlation with meteorological variables; however, the seasons impacted on how they responded. The comparative regression research results showed that although the linear and non-linear models performed well in predicting particulate matter concentrations, they performed poorly in predicting gaseous contaminants. When considering seasonal fluctuations and meteorological parameters, the results of this research will definitely help to increase the accuracy of air pollution forecasting near future.
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13
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Zhan C, Jiang W, Min H, Gao Y, Tse CK. Human migration-based graph convolutional network for PM2.5 forecasting in post-COVID-19 pandemic age. Neural Comput Appl 2023; 35:6457-6470. [PMID: 36467631 PMCID: PMC9684777 DOI: 10.1007/s00521-022-07876-0] [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: 03/17/2022] [Accepted: 09/21/2022] [Indexed: 11/24/2022]
Abstract
Due to the coronavirus disease 2019 pandemic, local authorities always implanted non-pharmaceutical interventions, such as maintaining social distance to reduce human migration. Besides, previous studies have proved that human migration highly influenced air pollution concentration in an area. Therefore, this study aims to explore whether human migration can work as a significant factor in the post-pandemic age to help PM2.5 concentration forecasting. In this work, we first analyze the variations of PM2.5 in 11 cities of Hubei from 2015 to 2020 and further compare PM2.5 trends with the migration trends of Hubei province in 2020. Experimental results indicate that the human migration indirectly affected the urban PM2.5 concentration. Then, we established a graph data structure based on the migration network describing the migration flow size between any two areas in the Hubei province and proposed a migration attentive graph convolutional network (MAGCN) for forecasting PM2.5. Combined with the migration data. The proposed model can attentively aggregate the information of neighbor nodes through migration weights. Experimental results indicate that the proposed MAGCN can forecast PM2.5 concentration accurately.
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Affiliation(s)
- Choujun Zhan
- School of Computer, South China Normal University, Guangzhou, Guangdong China ,School of Electrical and Computer Engineering, Nanfang College Guangzhou, Guangzhou, Guangdong China
| | - Wei Jiang
- School of Electrical and Computer Engineering, Nanfang College Guangzhou, Guangzhou, Guangdong China
| | - Hu Min
- School of Electrical and Computer Engineering, Nanfang College Guangzhou, Guangzhou, Guangdong China
| | - Ying Gao
- School of Computer Science and Engineering, South China University of Technology, Guangzhou, Guangdong China
| | - C. K. Tse
- Department of Electrical Engineering, City University of Hong Kong, Hong Kong, China
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14
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Huang Z, Loo BPY, Axhausen KW. Travel behaviour changes under Work-from-home (WFH) arrangements during COVID-19. TRAVEL BEHAVIOUR & SOCIETY 2023; 30:202-211. [PMID: 36247182 PMCID: PMC9537156 DOI: 10.1016/j.tbs.2022.09.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/20/2021] [Revised: 06/16/2022] [Accepted: 09/27/2022] [Indexed: 06/16/2023]
Abstract
Life, including working style and travel behaviour, has been severely disrupted by the COVID-19 pandemic. The unprecedented number of work-from-home (WFH) employees after the outbreak of COVID-19 has attracted much scholarly attention. As it is generally believed that WFH arrangements are not ephemeral, it is imperative to study the impacts of WFH on travel behaviour and its impact on sustainable transport in the post-pandemic era. In relation, this study uses a set of longitudinal GPS tracking data in Switzerland to examine changes in trip characteristics (i.e. travel distance, travel time), travel behaviours (i.e. travel frequency, peak hour departure, trip destination, travel mode), and activities (i.e. trip pattern diversity, trip purpose, and time spent at home). Two groups of participants (WFH and Non-WFH) are identified and compared through three periods (pre-COVID, during lockdown, and post lockdown) from September 2019 to October 2020. Results show that more significant reductions of trip distance, travel time, travel frequency, morning peak hours trips, trips to the CBD are observed among the WFH group. These changes helped to mitigate negative transport externalities. Meanwhile, active transport trips, trip pattern diversity, leisure trips, and time spent at home also increased more significantly for the WFH group when compared to their counterparts. Hence, promoting WFH may not only be beneficial to teleworkers but also to the wider community through more sustainable transport. Future research direction and policy implications are also discussed.
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Affiliation(s)
- Zhiran Huang
- Department of Geography, the University of Hong Kong, Hong Kong, China
| | - Becky P Y Loo
- Department of Geography, the University of Hong Kong, Hong Kong, China
- School of Geography and Environment, Jiangxi Normal University, China
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15
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do Nascimento CM, de Oliveira SA, Santana OA, Carvalho H. Changes in air pollution due to COVID-19 lockdowns in 2020: Limited effect on NO 2, PM 2.5, and PM 10 annual means compared to the new WHO Air Quality Guidelines. J Glob Health 2022; 12:05043. [PMID: 36403165 PMCID: PMC9677514 DOI: 10.7189/jogh.12.05043] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
Background Lockdowns have been fundamental to decreasing disease transmission during the COVID-19 pandemic even after vaccines were available. We aimed to evaluate and compare changes in air quality during the first year of the pandemic in different cities around the world, investigate how these changes correlate with changes in mobility, and analyse how lockdowns affected air pollutants' annual means. Methods We compared the concentrations of NO2, PM2.5, and PM10 in 42 cities around the world in the first months of the pandemic in 2020 to data from 2016-2019 and correlated them with changes in mobility using Human Development Indexes (HDIs). Cities with the highest decreases in air pollutants during this period were evaluated for the whole year 2020. We calculated the annual means for these cities and compared them to the new World Health Organization (WHO) Air Quality Guidelines. A Student's t-test (95% confidence interval) was used to evaluate significant changes. Results Highest decreases in NO2, PM2.5, and PM10 were between -50 and -70%. Cities evaluated for the whole year 2020 generally showed a recovery in air pollution levels after the initial months of the pandemic, except for London. These changes positively correlated with year-long mobility indexes for NO2 and PM2.5 for some cities. The highest reductions in air pollutants' annual means were from -20 to -35%. In general, decreases were higher for NO2, compared to PM2.5 and PM10. All analysed cities showed annual means incompliant with the new WHO Air Quality Guidelines for NO2 of 10 μg/m3, with values 1.7 and 4.3 times higher. For PM2.5, all cities showed values 1.3 to 7.6 times higher than the WHO Guidelines of 5 μg/m3, except for New Delhi, with a value 18 times higher. For PM10, only New York complied with the new guidelines of 15 μg/m3 and all the other cities were 1.1 to 4.2 times higher, except for New Delhi, which was 11 times higher. Conclusions These data show that even during a pandemic that highly affected mobility and economic activities and decreased air pollution around the world, complying with the new WHO Guidelines will demand a global strategical effort in the way we generate energy, move in and around the cities, and manufacture products.
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Affiliation(s)
- Cleonilde Maria do Nascimento
- Department of Biophysics and Radiobiology, Biological Sciences Centre, Federal University of Pernambuco, Recife, Pernambuco, Brazil,Department of Immunology, Aggeu Magalhães Institute (IAM), Oswaldo Cruz Foundation (FIOCRUZ), Recife, Pernambuco, Brazil
| | - Sheilla Andrade de Oliveira
- Department of Immunology, Aggeu Magalhães Institute (IAM), Oswaldo Cruz Foundation (FIOCRUZ), Recife, Pernambuco, Brazil
| | - Otacílio Antunes Santana
- Department of Biophysics and Radiobiology, Biological Sciences Centre, Federal University of Pernambuco, Recife, Pernambuco, Brazil
| | - Helotonio Carvalho
- Department of Biophysics and Radiobiology, Biological Sciences Centre, Federal University of Pernambuco, Recife, Pernambuco, Brazil,Department of Immunology, Aggeu Magalhães Institute (IAM), Oswaldo Cruz Foundation (FIOCRUZ), Recife, Pernambuco, Brazil
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16
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Liu S, Yang X, Duan F, Zhao W. Changes in Air Quality and Drivers for the Heavy PM 2.5 Pollution on the North China Plain Pre- to Post-COVID-19. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:ijerph191912904. [PMID: 36232204 PMCID: PMC9566441 DOI: 10.3390/ijerph191912904] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/31/2022] [Revised: 09/27/2022] [Accepted: 09/29/2022] [Indexed: 06/03/2023]
Abstract
Under the clean air action plans and the lockdown to constrain the coronavirus disease 2019 (COVID-19), the air quality improved significantly. However, fine particulate matter (PM2.5) pollution still occurred on the North China Plain (NCP). This study analyzed the variations of PM2.5, nitrogen dioxide (NO2), sulfur dioxide (SO2), carbon monoxide (CO), and ozone (O3) during 2017-2021 on the northern (Beijing) and southern (Henan) edges of the NCP. Furthermore, the drivers for the PM2.5 pollution episodes pre- to post-COVID-19 in Beijing and Henan were explored by combining air pollutant and meteorological datasets and the weighted potential source contribution function. Results showed air quality generally improved during 2017-2021, except for a slight rebound (3.6%) in NO2 concentration in 2021 in Beijing. Notably, the O3 concentration began to decrease significantly in 2020. The COVID-19 lockdown resulted in a sharp drop in the concentrations of PM2.5, NO2, SO2, and CO in February of 2020, but PM2.5 and CO in Beijing exhibited a delayed decrease in March. For Beijing, the PM2.5 pollution was driven by the initial regional transport and later secondary formation under adverse meteorology. For Henan, the PM2.5 pollution was driven by the primary emissions under the persistent high humidity and stable atmospheric conditions, superimposing small-scale regional transport. Low wind speed, shallow boundary layer, and high humidity are major drivers of heavy PM2.5 pollution. These results provide an important reference for setting mitigation measures not only for the NCP but for the entire world.
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17
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Wang F, Zhang X, Wang F, Song M, Li Z, Ming J. Urban air quality in Xinjiang and snow chemistry of Urumqi Glacier No. 1 during COVID-19's restrictions. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2022; 29:76026-76035. [PMID: 35665455 PMCID: PMC9166164 DOI: 10.1007/s11356-022-21167-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/18/2021] [Accepted: 05/25/2022] [Indexed: 06/15/2023]
Abstract
The unprecedented COVID-19 outbreak impacted the world in many aspects. Air pollutants were largely reduced in cities worldwide in 2020. Using samples from two snow pits dug separately in 2019 and 2020 in Urumqi Glacier No. 1 (UG1) in the Xinjiang Uygur Autonomous Region (Xinjiang), China, we measured water-stable isotopes, soluble ions, and black and organic carbon (BC and OC). Both carbon types show no significant variations in the snow-pit profiles dated from 2018 through 2020. The deposition of anthropogenically induced soluble ions (K+, Cl-, SO42-, and NO3-) in the snow decreased to 20-40% of their respective concentrations between 2019 and 2020; however, they increased 2- to fourfold from 2018 to 2019. We studied the daily concentrations of SO2 (2019-2020), NO2 (2015-2020), CO (2019-2020), and PM2.5 (2019-2020) measured in the sixteen major cities and towns across Xinjiang. The variabilities in these air pollutants were supposed to illustrate the air quality in the urban area and represent the change in the source area. The NO2 decreased in response to mobility restrictions imposed by local governments, while SO2, CO, and PM2.5 did not consistently correspond. This difference indicates that the restriction measures primarily affected traffic. The increases in chemical species in the snow from 2018 to 2019 and the subsequent decreases from 2019 to 2020 were consistent with the variations in SO2 and NO2 measured in urban air and estimated by MERRA-2 model. Therefore, the pandemic could possibly have an impact on snow chemistry of the Tien-Shan glaciers via reduced traffic and industrial intensity; more evidence would be obtained from ice cores, tree rings, and other archives in the future.
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Affiliation(s)
- Feiteng Wang
- State Key Laboratory of Cryospheric Science, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, 730000, China
| | - Xin Zhang
- State Key Laboratory of Cryospheric Science, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, 730000, China
| | - Fanglong Wang
- State Key Laboratory of Cryospheric Science, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, 730000, China
| | - Mengyuan Song
- State Key Laboratory of Cryospheric Science, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, 730000, China
| | - Zhongqin Li
- State Key Laboratory of Cryospheric Science, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, 730000, China
| | - Jing Ming
- Beacon Science & Consulting, Adelaide, SA, 5000, Australia.
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18
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Wong YJ, Shiu HY, Chang JHH, Ooi MCG, Li HH, Homma R, Shimizu Y, Chiueh PT, Maneechot L, Nik Sulaiman NM. Spatiotemporal impact of COVID-19 on Taiwan air quality in the absence of a lockdown: Influence of urban public transportation use and meteorological conditions. JOURNAL OF CLEANER PRODUCTION 2022; 365:132893. [PMID: 35781986 PMCID: PMC9234473 DOI: 10.1016/j.jclepro.2022.132893] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/19/2021] [Revised: 06/01/2022] [Accepted: 06/24/2022] [Indexed: 05/19/2023]
Abstract
The unprecedented outbreak of COVID-19 significantly improved the atmospheric environment for lockdown-imposed regions; however, scant evidence exists on its impacts on regions without lockdown. A novel research framework is proposed to evaluate the long-term monthly spatiotemporal impact of COVID-19 on Taiwan air quality through different statistical analyses, including geostatistical analysis, change detection analysis and identification of nonattainment pollutant occurrence between the average mean air pollutant concentrations from 2018-2019 and 2020, considering both meteorological and public transportation impacts. Contrary to lockdown-imposed regions, insignificant or worsened air quality conditions were observed at the beginning of COVID-19, but a delayed improvement occurred after April in Taiwan. The annual mean concentrations of PM10, PM2.5, SO2, NO2, CO and O3 in 2020 were reduced by 24%, 18%, 15%, 9.6%, 7.4% and 1.3%, respectively (relative to 2018-2019), and the overall occurrence frequency of nonattainment air pollutants declined by over 30%. Backward stepwise regression models for each air pollutant were successfully constructed utilizing 12 meteorological parameters (R2 > 0.8 except for SO2) to simulate the meteorological normalized business-as-usual concentration. The hybrid single-particle Lagrangian integrated trajectory (HYSPLIT) model simulated the fate of air pollutants (e.g., local emissions or transboundary pollution) for anomalous months. The changes in different public transportation usage volumes (e.g., roadway, railway, air, and waterway) moderately reduced air pollution, particularly CO and NO2. Reduced public transportation use had a more significant impact than meteorology on air quality improvement in Taiwan, highlighting the importance of proper public transportation management for air pollution control and paving a new path for sustainable air quality management even in the absence of a lockdown.
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Affiliation(s)
- Yong Jie Wong
- Research Center for Environmental Quality Management, Graduate School of Engineering, Kyoto University, 520-0811, Japan
| | - Huan-Yu Shiu
- Graduate Institute of Environmental Engineering, National Taiwan University, 10617, Taiwan
| | - Jackson Hian-Hui Chang
- Department of Atmospheric Sciences, National Central University, 32001, Taiwan
- Preparatory Center for Science and Technology (PPST), Universiti Malaysia Sabah, 88400, Malaysia
| | - Maggie Chel Gee Ooi
- Institute of Climate Change, National University of Malaysia (UKM), Bangi, 43600, Malaysia
| | - Hsueh-Hsun Li
- Graduate Institute of Environmental Engineering, National Taiwan University, 10617, Taiwan
| | - Ryosuke Homma
- Research Center for Environmental Quality Management, Graduate School of Engineering, Kyoto University, 520-0811, Japan
| | - Yoshihisa Shimizu
- Research Center for Environmental Quality Management, Graduate School of Engineering, Kyoto University, 520-0811, Japan
| | - Pei-Te Chiueh
- Graduate Institute of Environmental Engineering, National Taiwan University, 10617, Taiwan
| | - Luksanaree Maneechot
- Environmental Engineering and Disaster Management Program, School of Interdisciplinary Studies, Mahidol University Kanchanaburi Campus (MUKA), Kanchanaburi, 71150, Thailand
| | - Nik Meriam Nik Sulaiman
- Department of Chemical Engineering, Faculty of Engineering, University of Malaya, 50603, Kuala Lumpur, Malaysia
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Galán-Madruga D. Urban air quality changes resulting from the lockdown period due to the COVID-19 pandemic. INTERNATIONAL JOURNAL OF ENVIRONMENTAL SCIENCE AND TECHNOLOGY : IJEST 2022; 20:7083-7098. [PMID: 36035638 PMCID: PMC9391654 DOI: 10.1007/s13762-022-04464-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/13/2021] [Revised: 03/08/2022] [Accepted: 08/05/2022] [Indexed: 06/12/2023]
Abstract
This work aims to quantify potential pollution level changes in an urban environment (Madrid city, Spain) located in South Europe due to the lockdown measures for preventing the SARS-CoV-2 transmission. Polluting 11 species commonly monitored in urban zones were attended. Except for O3, a prompt target pollutant levels abatement was reached, intensely when implanted stricter measures and moderately along those measures' relaxing period. In the case of TH and CH4, it is evidenced a progressive diminution over the lockdown period. While the highest decreasing average changes relapsed on NOx (NO2: - 40.0% and NO: - 33.3%) and VOCs (C7H8: - 36.3% and C6H6: - 32.8%), followed by SO2 (- 27.0%), PM10 (- 19.7%), CO (- 16.6%), CH4 (- 14.7%), TH (- 11.6%) and PM2.5 (- 10.1%), the O3 level slightly raised 0.4%. These changes were consistently dependent on the measurement station location, emphasizing urban background zones for SO2, CO, C6H6, C7H8, TH and CH4, suburban zones for PM2.5 and O3, urban traffic sites for NO and PM10, and keeping variations reasonably similar at all the stations in the case of NO2. Those pollution changes were not translated in variations on geospatial pattern, except for NO, O3 and SO2. Although the researched urban atmosphere improvement was not attributable to meteorological conditions' variations, it was in line with the decline in traffic intensity. The evidenced outcomes might offer valuable clues to air quality managers in urban environments regarding decision-making in favor of applying punctual severe measures for quickly and considerably relieving polluting high load occurred in urban environments. Supplementary Information The online version contains supplementary material available at 10.1007/s13762-022-04464-6.
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Affiliation(s)
- D. Galán-Madruga
- Department of Atmospheric Pollution, National Center for Environment Health, Health Institute Carlos III, Ctra. Majadahonda a Pozuelo Km 2,2. Majadahonda, 28220 Madrid, Spain
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20
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Zeng J, Wang C. Temporal characteristics and spatial heterogeneity of air quality changes due to the COVID-19 lockdown in China. RESOURCES, CONSERVATION, AND RECYCLING 2022; 181:106223. [PMID: 35153377 PMCID: PMC8825306 DOI: 10.1016/j.resconrec.2022.106223] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/16/2021] [Revised: 01/19/2022] [Accepted: 02/05/2022] [Indexed: 05/16/2023]
Abstract
Previous studies have evaluated the impact of lockdown measures on air quality during the COVID-19 pandemic in China, but few have focused on the temporal characteristics and spatial heterogeneity of the impact across all 337 prefecture cities. In this study, we estimated the impact of the lockdown measures on air quality in each of 337 cities using the Regression Discontinuity in Time method. There was a short-term influence from January 24th to March 31th in 2020. The 337 cities could be divided into six categories showing different response and resilience patterns to the epidemic. Fine particulate matter (PM2.5) in 89.5% of the cities was sensitive to the lockdown measures. The change of air pollutants showed high spatial heterogeneity. The provinces with a greater than 20% reduction in PM2.5 and PM10 and greater than 40% reduction in NO2 during the impact period were mainly concentrated southeast of the "Hu Line". Compared to the no-pandemic scenario, the national annual average concentration of PM2.5, NO2, PM10, SO2, and CO in 2020 were decreased by 6.3%, 10.6%, 7.4%, 9.0%, and 12.5%, respectively, while that of O3 increased by 1.1%.This result indicates that 2020 can still be used as a baseline for setting and allocating air improvement targets for the next five years.
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Affiliation(s)
- Jinghai Zeng
- State Key Joint Laboratory of Environment Simulation and Pollution Control (SKLESPC), School of Environment, Tsinghua University, Beijing 100084, China
- Department of Atmospheric Environment (Atmospheric Environment Administration of the Beijing-Tianjin-Hebei Region and Surrounding Areas), Ministry of Ecology and Environment, Beijing 100005, China
| | - Can Wang
- State Key Joint Laboratory of Environment Simulation and Pollution Control (SKLESPC), School of Environment, Tsinghua University, Beijing 100084, China
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21
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Wu Q, Li T, Zhang S, Fu J, Seyler BC, Zhou Z, Deng X, Wang B, Zhan Y. Evaluation of NOx emissions before, during, and after the COVID-19 lockdowns in China: A comparison of meteorological normalization methods. ATMOSPHERIC ENVIRONMENT (OXFORD, ENGLAND : 1994) 2022; 278:119083. [PMID: 35350168 PMCID: PMC8949849 DOI: 10.1016/j.atmosenv.2022.119083] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/07/2021] [Revised: 03/04/2022] [Accepted: 03/21/2022] [Indexed: 06/14/2023]
Abstract
Meteorological normalization refers to the removal of meteorological effects on air pollutant concentrations for evaluating emission changes. There currently exist various meteorological normalization methods, yielding inconsistent results. This study aims to identify the state-of-the-art method of meteorological normalization for characterizing the spatiotemporal variation of NOx emissions caused by the COVID-19 pandemic in China. We obtained the hourly data of NO2 concentrations and meteorological conditions for 337 cities in China from January 1, 2019, to December 31, 2020. Three random-forest based meteorological normalization methods were compared, including (1) the method that only resamples meteorological variables, (2) the method that resamples meteorological and temporal variables, and (3) the method that does not need resampling, denoted as Resample-M, Resample-M&T, and Resample-None, respectively. The comparison results show that Resample-M&T considerably underestimated the emission reduction of NOx during the lockdowns, Resample-None generates widely fluctuating estimates that blur the emission recovery trend during work resumption, and Resample-M clearly delineates the emission changes over the entire period. Based on the Resample-M results, the maximum emission reduction occurred during January to February 2020, for most cities, with an average decrease of 19.1 ± 9.4% compared to 2019. During April of 2020 when work resumption initiated to the end of 2020, the emissions rapidly bounced back for most cities, with an average increase of 12.6 ± 15.8% relative to those during the strict lockdowns. Consequently, we recommend using Resample-M for meteorological normalization, and the normalized NO2 concentration dynamics for each city provide important implications for future emission reduction.
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Affiliation(s)
- Qinhuizi Wu
- Department of Environmental Science and Engineering, Sichuan University, Chengdu, Sichuan, 610065, China
| | - Tao Li
- Department of Environmental Science and Engineering, Sichuan University, Chengdu, Sichuan, 610065, China
| | - Shifu Zhang
- Department of Environmental Science and Engineering, Sichuan University, Chengdu, Sichuan, 610065, China
| | - Jianbo Fu
- Department of Environmental Science and Engineering, Sichuan University, Chengdu, Sichuan, 610065, China
| | - Barnabas C Seyler
- Department of Environmental Science and Engineering, Sichuan University, Chengdu, Sichuan, 610065, China
| | - Zihang Zhou
- Chengdu Academy of Environmental Sciences, Chengdu, Sichuan, 610072, China
| | - Xunfei Deng
- Institute of Digital Agriculture, Zhejiang Academy of Agricultural Sciences, Hangzhou, Zhejiang, 310021, China
| | - Bin Wang
- Department of Environmental Science and Engineering, Sichuan University, Chengdu, Sichuan, 610065, China
| | - Yu Zhan
- Department of Environmental Science and Engineering, Sichuan University, Chengdu, Sichuan, 610065, China
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22
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Analysis of Particulate Matter Concentration Changes before, during, and Post COVID-19 Lockdown: A Case Study from Victoria, Mexico. ATMOSPHERE 2022. [DOI: 10.3390/atmos13050827] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Abstract
The lockdown measures implemented due to the SARS-CoV-2 pandemic to reduce the epidemic curve, in most cases, have had a positive impact on air quality indices. Our study describes the changes in the concentration levels of PM2.5 and PM10 during the lockdown and post-lockdown in Victoria, Mexico, considering the following periods: before the lockdown (BL) from 16 February to 14 March, during the lockdown (DL) from 15 March to 2 May, and in the partial lockdown (PL) from 3 May to 6 June. When comparing the DL period of 2019 and 2020, we document a reduction in the average concentration of PM2.5 and PM10 of −55.56% and −55.17%, respectively. Moreover, we note a decrease of −53.57% for PM2.5 and −51.61% for PM10 in the PL period. When contrasting the average concentration between the DL periods of 2020 and 2021, an increase of 91.67% for PM2.5 and 100.00% for PM10 was identified. Furthermore, in the PL periods of 2020 and 2021, an increase of 38.46% and 31.33% was observed for PM2.5 and PM10, respectively. On the other hand, when comparing the concentrations of PM2.5 in the three periods of 2020, we found a decrease between BL and DL of −50.00%, between BL and PL a decrease of −45.83%, and an increase of 8.33% between DL and PL. In the case of PM10, a decrease of −48.00% between BL and DL, −40.00% between BL and PL, and an increase of 15.38% between the DL and PL periods were observed. In addition, we performed a non-parametric statistical analysis, where a significant statistical difference was found between the DL-2020 and DL-2019 pairs (x2 = 1.204) and between the DL-2021 and DL-2019 pairs (x2 = 0.372), with a p<0.000 for PM2.5, and the contrast between pairs of PM10 (DL) showed a significant difference between all pairs with p<0.01.
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23
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Sharma GK, Tewani A, Gargava P. Comprehensive analysis of ambient air quality during second lockdown in national capital territory of Delhi. JOURNAL OF HAZARDOUS MATERIALS ADVANCES 2022; 6:100078. [PMID: 36919145 PMCID: PMC9427329 DOI: 10.1016/j.hazadv.2022.100078] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/27/2022] [Revised: 04/02/2022] [Accepted: 04/18/2022] [Indexed: 12/23/2022]
Abstract
The lockdown imposed in Delhi, due to the second wave of the COVID-19 pandemic has led to significant gains in air quality. Under the lockdown, restrictions were imposed on movement of people, operation of industrial establishments and hospitality sector amongst others. In the study, Air Quality Index and concentration trends of six pollutants, i.e. PM2.5, PM10, NO2, SO2, CO, and O3 were analysed for National Capital Territory of Delhi, India for three periods in 2021 (pre-lockdown: 15 March to 16 April 2021, lockdown: 17 April to 31 May 2021 and post-lockdown: 01 June to 30 June). Data for corresponding periods in 2018-2020 was also analysed. Lockdown period saw 6 days in satisfactory AQI category as against 0 days in the same category during the pre-lockdown period. Average PM2.5, PM10, NO2 and SO2 concentrations reduced by 22%, 31%, 25% and 28% respectively during lockdown phase as compared to pre-lockdown phase, while O3 was seen to increase. Variation in meteorological parameters and correlation of pollutants has also been examined. The significant improvement arising due to curtailment of certain activities in the lockdown period indicates the importance of local emission control, and helps improve the understanding of the dynamics of air pollution, thus highlighting policy areas to regulatory bodies for effective control of air pollution.
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Affiliation(s)
- Gautam Kumar Sharma
- Central Pollution Control Board, Parivesh Bhawan, East Arjun Nagar, Delhi 110032, India
| | - Ankush Tewani
- Central Pollution Control Board, Parivesh Bhawan, East Arjun Nagar, Delhi 110032, India
| | - Prashant Gargava
- Central Pollution Control Board, Parivesh Bhawan, East Arjun Nagar, Delhi 110032, India
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24
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Costa VBF, Pereira LC, Andrade JVB, Bonatto BD. Future assessment of the impact of the COVID-19 pandemic on the electricity market based on a stochastic socioeconomic model. APPLIED ENERGY 2022; 313:118848. [PMID: 35250149 PMCID: PMC8888072 DOI: 10.1016/j.apenergy.2022.118848] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/12/2021] [Revised: 02/05/2022] [Accepted: 02/25/2022] [Indexed: 05/05/2023]
Abstract
This paper proposes a time-series stochastic socioeconomic model for analyzing the impact of the pandemic on the regulated distribution electricity market. The proposed methodology combines the optimized tariff model (socioeconomic market model) and the random walk concept (risk assessment technique) to ensure robustness/accuracy. The model enables both a past and future analysis of the impact of the pandemic, which is essential to prepare regulatory agencies beforehand and allow enough time for the development of efficient public policies. By applying it to six Brazilian concession areas, results demonstrate that consumers have been/will be heavily affected in general, mainly due to the high electricity tariffs that took place with the pandemic, overcoming the natural trend of the market. In contrast, the model demonstrates that the pandemic did not/will not significantly harm power distribution companies in general, mainly due to the loan granted by the regulator agency, named COVID-account. Socioeconomic welfare losses averaging 500 (MR$/month) are estimated for the equivalent concession area, i.e., the sum of the six analyzed concession areas. Furthermore, this paper proposes a stochastic optimization problem to mitigate the impact of the pandemic on the electricity market over time, considering the interests of consumers, power distribution companies, and the government. Results demonstrate that it is successful as the tariffs provided by the algorithm compensate for the reduction in demand while increasing the socioeconomic welfare of the market.
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Key Words
- AEGs, autonomous energy grids
- ANEEL, National Electricity Agency (Brazilian regulatory agency)
- CGE, computable general equilibrium
- CNN, convolutional neural network
- COVID-19 pandemic
- DG, distributed generation
- ECA, economic consumer added (consumers' surplus)
- ESS, energy storage systems
- EVA, economic value added (regulated power distribution company's surplus)
- EWA, economic wealth added (socioeconomic welfare)
- FEE, financial economical equilibrium
- GDP, gross domestic product
- HVAC, heating, ventilation, and air-conditioning
- IOT, internet of things
- LEAP, Low Emissions Analysis Platform
- ML, machine learning
- MR$, Brazilian currency multiplied by 106
- PM, particulate matter
- Public policies
- Regulated electricity market
- Risk assessment
- Stochastic socioeconomic model
- TAROT, optimized tariff
- VaR, value at risk
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Affiliation(s)
- Vinicius B F Costa
- Institute of Electrical Systems and Energy, Federal University of Itajuba, Itajuba, MG 37500-903, Brazil
| | - Lígia C Pereira
- Institute of Electrical Systems and Energy, Federal University of Itajuba, Itajuba, MG 37500-903, Brazil
| | - Jorge V B Andrade
- Institute of Electrical Systems and Energy, Federal University of Itajuba, Itajuba, MG 37500-903, Brazil
| | - Benedito D Bonatto
- Institute of Electrical Systems and Energy, Federal University of Itajuba, Itajuba, MG 37500-903, Brazil
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25
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Analysis of the Effect of Economic Development on Air Quality in Jiangsu Province Using Satellite Remote Sensing and Statistical Modeling. ATMOSPHERE 2022. [DOI: 10.3390/atmos13050697] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
In recent decades, the economy of China has developed rapidly, but this has brought widespread damage to the environment, which forces us to explore a sustainable, green, economic development model. Therefore, it is particularly necessary to clarify the relationship between economic development and environmental pollution. In this paper, we used satellite remote sensing tropospheric NO2 vertical column density (VCD) as an air quality indicator; the total exports, total imports, and industrial electricity consumption as the economic indicators; and the wind speed, temperature, and planetary boundary layer height as the meteorological factors to perform a Generalized Additive Modeling (GAM) analysis. By deducing the influence of meteorological factors, the relationship between economic indicators and the air quality indicator can be determined. When total exports increased by one billion USD (United States Dollar), the tropospheric NO2 VCDs of Nanjing and Suzhou increased by about 15% and 6%, respectively. The tropospheric NO2 VCDs of Suzhou increased by about 5% when the total imports increased by one billion USD. In addition, when the industrial electricity consumption increased by one billion kWh, the tropospheric NO2 VCDs of Nanjing, Suzhou and Xuzhou increased by about 25%, 12%, and 59%, respectively. This study provides a method to quantify the contribution of economic growth to air pollution, which is helpful for better understanding of the relationship between economic development and air quality.
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26
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Iqbal A, Haq W, Mahmood T, Raza SH. Effect of meteorological factors on the COVID-19 cases: a case study related to three major cities of the Kingdom of Saudi Arabia. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2022; 29:21811-21825. [PMID: 34767172 PMCID: PMC8586838 DOI: 10.1007/s11356-021-17268-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/12/2021] [Accepted: 10/25/2021] [Indexed: 06/13/2023]
Abstract
The COVID-19 pandemic affected the world through its ability to cause widespread infection. The Middle East including the Kingdom of Saudi Arabia (KSA) has also been hit by the COVID-19 pandemic like the rest of the world. This study aims to examine the relationships between meteorological factors and COVID-19 case counts in three cities of the KSA. The distribution of the COVID-19 case counts was observed for all three cities followed by cross-correlation analysis which was carried out to estimate the lag effects of meteorological factors on COVID-19 case counts. Moreover, the Poisson model and negative binomial (NB) model with their zero-inflated versions (i.e., ZIP and ZINB) were fitted to estimate city-specific impacts of weather variables on confirmed case counts, and the best model is evaluated by comparative analysis for each city. We found significant associations between meteorological factors and COVID-19 case counts in three cities of KSA. We also perceived that the ZINB model was the best fitted for COVID-19 case counts. In this case study, temperature, humidity, and wind speed were the factors that affected COVID-19 case counts. The results can be used to make policies to overcome this pandemic situation in the future such as deploying more resources through testing and tracking in such areas where we observe significantly higher wind speed or higher humidity. Moreover, the selected models can be used for predicting the probability of COVID-19 incidence across various regions.
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Affiliation(s)
- Anam Iqbal
- Department of Statistics, Government Graduate College for Women, Sargodha, Punjab, Pakistan
| | - Wajiha Haq
- Department of Economics, School of Social Sciences and Humanities, National University of Sciences and Technology, Islamabad, H-12, Pakistan.
| | - Tahir Mahmood
- Industrial and Systems Engineering Department, King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia
- Interdisciplinary Research Centre for Smart Mobility & Logistics, King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia
| | - Syed Hassan Raza
- School of Economics, Quaid-i-Azam University, Islamabad, Pakistan
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27
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Impact of COVID-19 Pandemic on Air Quality: A Systematic Review. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:ijerph19041950. [PMID: 35206139 PMCID: PMC8871899 DOI: 10.3390/ijerph19041950] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/01/2022] [Revised: 02/02/2022] [Accepted: 02/03/2022] [Indexed: 02/07/2023]
Abstract
With the emergence of the COVID-19 pandemic, several governments imposed severe restrictions on socio-economic activities, putting most of the world population into a general lockdown in March 2020. Although scattered, studies on this topic worldwide have rapidly emerged in the literature. Hence, this systematic review aimed to identify and discuss the scientifically validated literature that evaluated the impact of the COVID-19 pandemic and associated restrictions on air quality. Thus, a total of 114 studies that quantified the impact of the COVID-19 pandemic on air quality through monitoring were selected from three databases. The most evaluated countries were India and China; all the studies intended to evaluate the impact of the pandemic on air quality, mainly concerning PM10, PM2.5, NO2, O3, CO, and SO2. Most of them focused on the 1st lockdown, comparing with the pre- and post-lockdown periods and usually in urban areas. Many studies conducted a descriptive analysis, while others complemented it with more advanced statistical analysis. Although using different methodologies, some studies reported a temporary air quality improvement during the lockdown. More studies are still needed, comparing different lockdown and lifting periods and, in other areas, for a definition of better-targeted policies to reduce air pollution.
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28
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Assessment of Meteorological Variables and Air Pollution Affecting COVID-19 Cases in Urban Agglomerations: Evidence from China. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:ijerph19010531. [PMID: 35010793 PMCID: PMC8744893 DOI: 10.3390/ijerph19010531] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/07/2021] [Revised: 12/14/2021] [Accepted: 12/30/2021] [Indexed: 12/23/2022]
Abstract
The 2019 novel coronavirus disease (COVID-19) has become a severe public health and social problem worldwide. A limitation of the existing literature is that multiple environmental variables have not been frequently elaborated, which is why the overall effect of the environment on COVID-19 has not been conclusive. In this study, we used generalized additive model (GAM) to detect the relationship between meteorological and air pollution variables and COVID-19 in four urban agglomerations in China and made comparisons among the urban agglomerations. The four urban agglomerations are Beijing-Tianjin-Hebei (BTH), middle reaches of the Yangtze River (MYR), Yangtze River Delta (YRD), and the Pearl River Delta (PRD). The daily rates of average precipitation, temperature, relative humidity, sunshine duration, and atmospheric pressure were selected as meteorological variables. The PM2.5, PM10, sulfur dioxide (SO2), nitrogen dioxide (NO2), ozone (O3), and carbon monoxide (CO) contents were selected as air pollution variables. The results indicated that meteorological and air pollution variables tended to be significantly correlated. Moreover, the nature of the relationship between severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and meteorological and air pollution variables (i.e., linear or nonlinear) varied with urban agglomerations. Among the variance explained by GAMs, BTH had the highest value (75.4%), while MYR had the lowest value (35.2%). The values of the YRD and PRD were between the above two, namely 45.6% and 62.2%, respectively. The findings showed that the association between SARS-CoV-2 and meteorological and air pollution variables varied in regions, making it difficult to obtain a relationship that is applicable to every region. Moreover, this study enriches our understanding of SARS-CoV-2. It is required to create awareness within the government that anti-COVID-19 measures should be adapted to the local meteorological and air pollution conditions.
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29
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Skorokhod AI, Rakitin VS, Kirillova NS. Impact of COVID-19 Pandemic Preventing Measures and Meteorological Conditions on the Atmospheric Air Composition in Moscow in 2020. RUSSIAN METEOROLOGY AND HYDROLOGY 2022; 47:183-190. [PMCID: PMC9243816 DOI: 10.3103/s1068373922030037] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/07/2021] [Revised: 12/07/2021] [Accepted: 12/13/2021] [Indexed: 08/03/2023]
Abstract
Changes in the atmospheric composition during different periods of 2020 in Moscow which were associated with the COVID-19 pandemic preventing measures as well as corresponding pollutant emission reduction, are investigated. Surface concentrations of nitrogen dioxide (NO2), carbon monoxide (CO), ozone (O3), aerosol fraction (PM10), and meteorological parameters during different periods of 2020 were compared with similar data for the previous five years. The analysis of ground-based measurements, as well as of high-resolution satellite distributions of CO and NO2 indicated that the concentration of major pollutants and its spatial distribution in the Moscow region were significantly affected by both restrictive measures and abnormal meteorological conditions in 2020.
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Affiliation(s)
- A. I. Skorokhod
- Obukhov Institute of Atmospheric Physics, Russian Academy of Sciences, 119017 Moscow, Russia
| | - V. S. Rakitin
- Obukhov Institute of Atmospheric Physics, Russian Academy of Sciences, 119017 Moscow, Russia
| | - N. S. Kirillova
- Obukhov Institute of Atmospheric Physics, Russian Academy of Sciences, 119017 Moscow, Russia
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30
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Yu D, Li X, Yu J, Shi X, Liu P, Tian P. Whether Urbanization Has Intensified the Spread of Infectious Diseases-Renewed Question by the COVID-19 Pandemic. Front Public Health 2021; 9:699710. [PMID: 34900884 PMCID: PMC8652246 DOI: 10.3389/fpubh.2021.699710] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2021] [Accepted: 10/05/2021] [Indexed: 12/30/2022] Open
Abstract
The outbreak of the COVID-19 epidemic has triggered adiscussion of the relationship between urbanization and the spread of infectious diseases. Namely, whether urbanization will exacerbate the spread of infectious diseases. Based on 31 provincial data from 2002 to 2018 in China, the impact of urbanization on the spread of infectious diseases from the dimensions of "population" and "land" is analyzed in this paper by using the GMM (generalized method of moments) model. The empirical study shows that the population increase brought by urbanization does not aggravate the spread of infectious diseases. On the contrary, urban education, employment and entrepreneurship, housing, medical and health care, and other basic public services brought by population urbanization can help reduce the risk of the spread of infectious diseases. The increasing density of buildings caused by land urbanization increases the risk of the spread of infectious diseases. Moreover, the impact of urbanization on the spread of infectious diseases has regional heterogeneity. Therefore, the prevention and control of disease play a crucial role.
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Affiliation(s)
- Dongsheng Yu
- School of Economics, Zhongnan University of Economics and Law, Wuhan, China
| | - Xiaoping Li
- School of Economics, Zhongnan University of Economics and Law, Wuhan, China
| | - Juanjuan Yu
- School of Economics, Zhongnan University of Economics and Law, Wuhan, China
| | - Xunpeng Shi
- Australia-China Relations Institute, University of Technology Sydney, Sydney, NSW, Australia
| | - Pei Liu
- School of Economics, Zhengzhou University of Aeronautics, Zhengzhou, China
| | - Pu Tian
- School of Economics, Zhongnan University of Economics and Law, Wuhan, China
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31
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Has COVID-19 Lockdown Affected on Air Quality?—Different Time Scale Case Study in Wrocław, Poland. ATMOSPHERE 2021. [DOI: 10.3390/atmos12121549] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
Due to the COVID-19 pandemic, there are series of negative economic consequences, however, in limiting mobility and reducing the number of vehicles, positive effects can also be observed, i.e., improvement of air quality. The paper presents an analysis of air quality measured by concentrations of NO2, NOx and PM2.5 during the most restrictive lockdown from 10 March to 31 May 2020 on the case of Wrocław. The results were compared with the reference period—2016–2019. A significant reduction in traffic volume was identified, on average by 26.3%. The greatest reduction in the concentration of NO2 and NOx was recorded at the station farthest from the city center, characterized by the lowest concentrations: 20.1% and 22.4%. Lower reduction in the average concentrations of NO2 and NOx was recorded at the municipal station (7.9% and 7.7%) and the communication station (6.7% and 10.2%). Concentrations of PMs in 2020 were on average 15% and 13.4% lower than in the reference period for the traffic station and the background station. The long-term impact of the lockdown on air quality was also examined. The analysis of the concentrations of the pollutants throughout 2020, and in the analyzed period of 2021, indicated that the reduction of concentrations and the improvement in air quality caused by the restrictions should be considered as a temporary anomaly, without affecting long-term changes and trends.
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32
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Du H, Li J, Wang Z, Yang W, Chen X, Wei Y. Sources of PM 2.5 and its responses to emission reduction strategies in the Central Plains Economic Region in China: Implications for the impacts of COVID-19. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2021; 288:117783. [PMID: 34329065 DOI: 10.1016/j.envpol.2021.117783] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/17/2021] [Revised: 07/09/2021] [Accepted: 07/10/2021] [Indexed: 05/05/2023]
Abstract
The Central Plains Economic Region (CPER) located along the transport path to the Beijing-Tianjin-Hebei area has experienced severe PM2.5 pollution in recent years. However, few modeling studies have been performed on the sources of PM2.5, especially the impacts of emission reduction strategies. In this study, the Nested Air Quality Prediction Model System (NAQPMS) with an online tracer-tagging module was adopted to investigate source sectors of PM2.5 and a series of sensitivity tests were conducted to investigate the impacts of different sector-based mitigation strategies on PM2.5 pollution. The response surfaces of pollutants to sector-based emission changes were built. The results showed that resident-related sector (resident and agriculture), fugitive dust, traffic and industry emissions were the main sources of PM2.5 in Zhengzhou, contributing 49%, 19%, 15% and 13%, respectively. Response surfaces of pollutants to sector-based emission changes in Henan revealed that the combined reduction of resident-related sector and industry emissions efficiently decreased PM2.5 in Zhengzhou. However, reduced emissions in only the Henan region barely satisfied the national air quality standard of 75 μg/m3, whereas a 50%-60% reduction in resident-related sector and industry emissions over the whole region could reach this goal. On severely polluted days, even a 60% reduction in these two sectors over the whole region was insufficient to satisfy the standard of 75 μg/m3. Moreover, a reduction in traffic emissions resulted in an increase in the O3 concentration. The results of the response surface method showed that PM2.5 in Zhengzhou decreased by 19% in response to the COVID-19 lockdown, which approached the observed reduction of 21%, indicating that the response surface method could be employed to study the impacts of the COVID-19 lockdown on air pollution. This study provides a scientific reference for the formulation of pollution mitigation strategies in the CPER.
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Affiliation(s)
- Huiyun Du
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry (LAPC), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China
| | - Jie Li
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry (LAPC), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China; College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing, 100049, China; Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen, 361021, China.
| | - Zifa Wang
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry (LAPC), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China; College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing, 100049, China; Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen, 361021, China
| | - Wenyi Yang
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry (LAPC), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China
| | - Xueshun Chen
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry (LAPC), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China
| | - Ying Wei
- Institute of Urban Meteorology, China Meteorology Administration, Beijing, 100089, China
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33
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Robin RS, Purvaja R, Ganguly D, Hariharan G, Paneerselvam A, Sundari RT, Karthik R, Neethu CS, Saravanakumar C, Semanti P, Prasad MHK, Mugilarasan M, Rohan S, Arumugam K, Samuel VD, Ramesh R. COVID-19 restrictions and their influences on ambient air, surface water and plastic waste in a coastal megacity, Chennai, India. MARINE POLLUTION BULLETIN 2021; 171:112739. [PMID: 34304059 PMCID: PMC8458696 DOI: 10.1016/j.marpolbul.2021.112739] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/31/2020] [Revised: 07/14/2021] [Accepted: 07/15/2021] [Indexed: 05/06/2023]
Abstract
Anthropogenic activities experienced a pause due to the nationwide lockdown, imposed to contain the rapid spread of COVID-19 in the third week of March 2020. The impacts of suspension of industrial activities, vehicular transport and other businesses for three months (25 March-30 June) on the environmental settings of Chennai, a coastal megacity was assessed. A significant reduction in the key urban air pollutants [PM2.5 (66.5%), PM10 (39.5%), NO2 (94.1%), CO (29%), O3 (45.3%)] was recorded as an immediate consequence of the reduced anthropogenic activities. Comparison of water quality of an urban river Adyar, between pre-lockdown and lockdown, showed a substantial drop in the dissolved inorganic N (47%) and suspended particulate matter (41%) during the latter period. During the pandemic, biomedical wastes in India showed an overall surge of 17%, which were predominantly plastic. FTIR-ATR analysis confirmed the polymers such as polypropylene (25.4%) and polyester (15.4%) in the personal protective equipment.
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Affiliation(s)
- R S Robin
- National Centre for Sustainable Coastal Management, Ministry of Environment, Forest and Climate Change, Chennai 600 025, Tamil Nadu, India
| | - R Purvaja
- National Centre for Sustainable Coastal Management, Ministry of Environment, Forest and Climate Change, Chennai 600 025, Tamil Nadu, India
| | - D Ganguly
- National Centre for Sustainable Coastal Management, Ministry of Environment, Forest and Climate Change, Chennai 600 025, Tamil Nadu, India
| | - G Hariharan
- National Centre for Sustainable Coastal Management, Ministry of Environment, Forest and Climate Change, Chennai 600 025, Tamil Nadu, India
| | - A Paneerselvam
- National Centre for Sustainable Coastal Management, Ministry of Environment, Forest and Climate Change, Chennai 600 025, Tamil Nadu, India
| | - R T Sundari
- National Centre for Sustainable Coastal Management, Ministry of Environment, Forest and Climate Change, Chennai 600 025, Tamil Nadu, India
| | - R Karthik
- National Centre for Sustainable Coastal Management, Ministry of Environment, Forest and Climate Change, Chennai 600 025, Tamil Nadu, India
| | - C S Neethu
- National Centre for Sustainable Coastal Management, Ministry of Environment, Forest and Climate Change, Chennai 600 025, Tamil Nadu, India
| | - C Saravanakumar
- National Centre for Sustainable Coastal Management, Ministry of Environment, Forest and Climate Change, Chennai 600 025, Tamil Nadu, India
| | - P Semanti
- National Centre for Sustainable Coastal Management, Ministry of Environment, Forest and Climate Change, Chennai 600 025, Tamil Nadu, India
| | - M H K Prasad
- National Centre for Sustainable Coastal Management, Ministry of Environment, Forest and Climate Change, Chennai 600 025, Tamil Nadu, India
| | - M Mugilarasan
- National Centre for Sustainable Coastal Management, Ministry of Environment, Forest and Climate Change, Chennai 600 025, Tamil Nadu, India
| | - S Rohan
- National Centre for Sustainable Coastal Management, Ministry of Environment, Forest and Climate Change, Chennai 600 025, Tamil Nadu, India
| | - K Arumugam
- National Centre for Sustainable Coastal Management, Ministry of Environment, Forest and Climate Change, Chennai 600 025, Tamil Nadu, India
| | - V D Samuel
- National Centre for Sustainable Coastal Management, Ministry of Environment, Forest and Climate Change, Chennai 600 025, Tamil Nadu, India
| | - R Ramesh
- National Centre for Sustainable Coastal Management, Ministry of Environment, Forest and Climate Change, Chennai 600 025, Tamil Nadu, India.
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The Impact of the Pandemic on Vehicle Traffic and Roadside Environmental Pollution: Rzeszow City as a Case Study. ENERGIES 2021. [DOI: 10.3390/en14144299] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
The development of the COVID-19 pandemic and the related lockdown had a major impact on vehicle traffic in cities. Based on available data from the selected city of Rzeszow, Poland, it was decided to assess changes in vehicle traffic and the impact of these changes on roadside environmental pollution. As part of the research, data from the first half of 2020 regarding vehicle traffic on selected streets of the city and on the city’s inlet routes were analyzed. For the selected road sections, changes in hourly traffic volume in 2020, compared with 2019, were also determined. With data on traffic volume, an attempt was made to estimate the impact of changes in traffic volume on air pollution in the city. Research on air pollution from motor vehicles was focused on a selected section of a city road that was equipped with an automatic air pollution measurement station located very close to the road. Additionally, at the road intersection and in the vicinity of the measuring station, a sensor was installed in the roadway to count passing vehicles. A preliminary analysis of air pollution data revealed that factors such as wind speed and direction and outside temperature had a large impact on measurement results. To eliminate the influence of these factors and to obtain data concerning only contamination originating from motor vehicles traveling along the road, an appropriate mathematical model of the traffic flow–roadside environment system was built. This model was designed to determine the air pollution in the vicinity of the road generated by traffic flow. The constructed model was verified, and the conditions for its use were determined in order to study the impact of traffic and roadside environment on the level of air pollution from harmful exhaust substances. It was shown that at certain times of the day, especially at low temperatures, other sources of harmful emissions related to home heating play a major role in air pollution in the city.
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Quantifying Air Pollutant Variations during COVID-19 Lockdown in a Capital City in Northwest China. ATMOSPHERE 2021. [DOI: 10.3390/atmos12060788] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
In the context of the outbreak of coronavirus disease 2019 (COVID-19), strict lockdown policies were implemented to control nonessential human activities in Xi’an, northwest China, which greatly limited the spread of the pandemic and affected air quality. Compared with pre-lockdown, the air quality index and concentrations of PM2.5, PM10, SO2, and CO during the lockdown reduced, but the reductions were not very significant. NO2 levels exhibited the largest decrease (52%) during lockdown, owing to the remarkable decreased motor vehicle emissions. The highest K+ and lowest Ca2+ concentrations in PM2.5 samples could be attributed to the increase in household biomass fuel consumption in suburbs and rural areas around Xi’an and the decrease in human physical activities in Xi’an (e.g., human travel, vehicle emissions, construction activities), respectively, during the lockdown period. Secondary chemical reactions in the atmosphere increased in the lockdown period, as evidenced by the increased O3 level (increased by 160%) and OC/EC ratios in PM2.5 (increased by 26%), compared with pre-lockdown levels. The results, based on a natural experiment in this study, can be used as a reference for studying the formation and source of air pollution in Xi’an and provide evidence for establishing future long-term air pollution control policies.
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