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Alhajeri NS, Al-Fadhli FM, Aly A, Allen DT. Quantifying the impact of urban road traffic on air quality: activity pre-pandemic and during partial and full lockdowns. ENVIRONMENTAL MONITORING AND ASSESSMENT 2024; 196:418. [PMID: 38570428 DOI: 10.1007/s10661-024-12572-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/26/2023] [Accepted: 03/23/2024] [Indexed: 04/05/2024]
Abstract
The impact of partial and full COVID lockdowns in 2020 on vehicle miles traveled (VMT) in Kuwait was estimated using data extracted from the Directions API of Google Maps and a Python script running as a cronjob. This approach was validated by comparing the predictions based on the app to measuring traffic flows for 1 week across four road segments considered in this study. VMT during lockdown periods were compared to VMT for the same calendar weeks before the pandemic. NOx emissions were estimated based on VMT and were used to simulate the spatial patterns of NOx concentrations using an air quality model (AERMOD). Compared to pre-pandemic periods, VMT was reduced by up to 25.5% and 42.6% during the 2-week partial and full lockdown episodes, respectively. The largest reduction in the traffic flow rate occurred during the middle of these 2-week periods, when the traffic flow rate decreased by 35% and 49% during the partial and full lockdown periods, respectively. The AERMOD simulation results predicted a reduction in the average maximum concentration of emissions directly related to VMT across the region by up to 38%, with the maximum concentration shifting to less populous residential areas as a result of the lockdown.
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Affiliation(s)
- Nawaf S Alhajeri
- Department of Environmental Technology Management, College of Life Sciences, Kuwait University, 13060, Safat, Kuwait.
| | - Fahad M Al-Fadhli
- Department of Chemical Engineering, College of Engineering and Petroleum, Kuwait University, 13060, Safat, Kuwait
| | - Ahmed Aly
- Department of Chemical Engineering, College of Engineering and Petroleum, Kuwait University, 13060, Safat, Kuwait
| | - David T Allen
- Center for Energy and Environmental Resources, The University of Texas at Austin, 10100 Burnet Road, Building 133, M.S. R7100, Austin, TX, 78758, USA
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Humphrey JL, Kinnee EJ, Robinson LF, Clougherty JE. Disentangling impacts of multiple pollutants on acute cardiovascular events in New York city: A case-crossover analysis. ENVIRONMENTAL RESEARCH 2024; 242:117758. [PMID: 38029813 DOI: 10.1016/j.envres.2023.117758] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/14/2022] [Revised: 10/29/2023] [Accepted: 11/21/2023] [Indexed: 12/01/2023]
Abstract
BACKGROUND Ambient air pollution contributes to an estimated 6.67 million deaths annually, and has been linked to cardiovascular disease (CVD), the leading cause of death. Short-term increases in air pollution have been associated with increased risk of CVD event, though relatively few studies have directly compared effects of multiple pollutants using fine-scale spatio-temporal data, thoroughly adjusting for co-pollutants and temperature, in an exhaustive citywide hospitals dataset, towards identifying key pollution sources within the urban environment to most reduce, and reduce disparities in, the leading cause of death worldwide. OBJECTIVES We aimed to examine multiple pollutants against multiple CVD diagnoses, across lag days, in models adjusted for co-pollutants and meteorology, and inherently adjusted by design for non-time-varying individual and aggregate-level covariates, using fine-scale space-time exposure estimates, in an exhaustive dataset of emergency department visits and hospitalizations across an entire city, thereby capturing the full population-at-risk. METHODS We used conditional logistic regression in a case-crossover design - inherently controlling for all confounders not varying within case month - to examine associations between spatio-temporal nitrogen dioxide (NO2), fine particulate matter (PM2.5), sulfur dioxide (SO2), and ozone (O3) in New York City, 2005-2011, on individual risk of acute CVD event (n = 837,523), by sub-diagnosis [ischemic heart disease (IHD), heart failure (HF), stroke, ischemic stroke, acute myocardial infarction]. RESULTS We found significant same-day associations between NO2 and risk of overall CVD, IHD, and HF - and between PM2.5 and overall CVD or HF event risk - robust to all adjustments and multiple comparisons. Results were comparable by sex and race - though median age at CVD was 10 years younger for Black New Yorkers than White New Yorkers. Associations for NO2 were comparable for adults younger or older than 69 years, though PM2.5 associations were stronger among older adults. DISCUSSION Our results indicate immediate, robust effects of combustion-related pollution on CVD risk, by sub-diagnosis. Though acute impacts differed minimally by age, sex, or race, the much younger age-at-event for Black New Yorkers calls attention to cumulative social susceptibility.
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Affiliation(s)
- Jamie L Humphrey
- Center Public Health Methods; RTI International, Research Triangle Park, NC, 27709, USA
| | - Ellen J Kinnee
- University Center for Social and Urban Research, University of Pittsburgh, Pittsburgh, PA, 15260, USA
| | - Lucy F Robinson
- Department of Epidemiology and Biostatistics, Dornsife School of Public Health, Drexel University, Philadelphia, PA, 19104, USA
| | - Jane E Clougherty
- Department of Environmental and Occupational Health, Dornsife School of Public Health, Drexel University, Philadelphia, PA, 19104, USA.
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Åstrand A, Kiddle SJ, Siva Ganesh Mudedla R, Porwal S, Chafekar K, Agrawal S, Seminario C, Chalmers JD, Psallidas I. Effect of COVID-19 on Bronchiectasis Exacerbation Rates: A Retrospective U.S. Insurance Claims Study. Ann Am Thorac Soc 2024; 21:261-270. [PMID: 37962905 PMCID: PMC10848910 DOI: 10.1513/annalsats.202211-944oc] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Accepted: 11/13/2023] [Indexed: 11/15/2023] Open
Abstract
Rationale: Bronchiectasis is a chronic, progressive disease of bronchial dilation, inflammation, and scarring leading to impaired mucociliary clearance and increased susceptibility to infection. Identified causes include previous severe respiratory infections. A small, single-center UK study demonstrated a reduction in bronchiectasis exacerbations during the first year of the coronavirus disease (COVID-19) pandemic. No studies have been conducted in a U.S. (commercially insured) cohort to date. Objectives: To explore the impact of the COVID-19 pandemic on the frequency of exacerbations in a large cohort of commercially insured U.S. patients with bronchiectasis by testing the hypothesis that U.S. patients with bronchiectasis had fewer exacerbations during the pandemic. Methods: This retrospective observational cohort study used health insurance claims data from Optum's deidentified Clinformatics Data Mart database, which included U.S. patients and their covered dependents. Eligible patients were ⩾18 years of age with bronchiectasis; patients with other respiratory conditions were excluded. The main study cohort excluded patients with frequent asthma and/or chronic obstructive pulmonary disease diagnoses. The primary objective was to compare the bronchiectasis exacerbation rates before and during the COVID-19 pandemic. Results: The median number of exacerbations per patient per year decreased significantly from the year before the COVID-19 pandemic to the first year of the pandemic (1 vs. 0; P < 0.01). More patients had zero exacerbations during the first year of the pandemic than the year prior (57% vs. 24%; McNemar's chi-square = 122.56; P < 0.01). Conclusions: In a U.S. population-based study of patients with International Classification of Diseases codes for bronchiectasis, the rate of exacerbations during Year 1 of the COVID-19 pandemic was reduced compared with the 2-year time period preceding the pandemic.
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Affiliation(s)
- Annika Åstrand
- Late-Stage Development, Respiratory & Immunology, AstraZeneca, Gothenburg, Sweden
| | - Steven J. Kiddle
- Data Science & Advanced Analytics, Data Science & Artificial Intelligence, Research & Development, and
| | | | | | | | - Shubh Agrawal
- Integrated Evidence, ZS Associates, Bangalore, India
| | - Carlos Seminario
- Late-Stage Development, Respiratory & Immunology, AstraZeneca, Gaithersburg, Maryland; and
| | - James D. Chalmers
- Division of Molecular and Clinical Medicine, University of Dundee, Dundee, United Kingdom
| | - Ioannis Psallidas
- Late-Stage Development, Respiratory & Immunology, AstraZeneca, Cambridge, United Kingdom
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Zuo H, Jiang Y, Yuan J, Wang Z, Zhang P, Guo C, Wang Z, Chen Y, Wen Q, Wei Y, Li X. Pollution characteristics and source differences of VOCs before and after COVID-19 in Beijing. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 907:167694. [PMID: 37832670 DOI: 10.1016/j.scitotenv.2023.167694] [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: 09/14/2023] [Accepted: 10/07/2023] [Indexed: 10/15/2023]
Abstract
During the outbreak of the COVID-19, the change in the way of people's living and production provided the opportunity to study the influence of human activity on Volatile organic compounds (VOCs) in the atmosphere. Therefore, this study analyzed VOCs concentration and composition characteristics in urban area of Beijing from 2019 to 2020. The results showed that the concentration of VOCs in Chaoyang district in 2020 was 73.1ppbv, lower than that in 2019 (92.8ppbv), and alkanes (45 % and 47 %) were the most dominant components. The concentrations of isopentane, n-pentane, n-hexane, and OVOCs significantly increased in 2020. According to the results of the PMF model, the contribution of VOCs from vehicle and pharmaceutical-related emissions increased to 45.8 % and 27.1 % in 2020, while coal combustion decreased by 23.7 %. This is likely linked to the strict implementation of the coal conversion policy, as well as the increment in individual travel and pharmaceutical production during the pandemic. The calculation results of OFP and SOAFP indicated that toluene had an increased impact on the formation of O3 and SOA in the Chaoyang district in 2020. Notably, VOCs emitted by vehicles have the highest potential for secondary generation. In addition, VOCs from vehicles and industries pose the greatest health risks, together accounting for 77.4 % and 79.31 % of the total carcinogenic risk in 2019 and 2020. Although industrial emission with the high proportions of halocarbons was controlled to some extent during the pandemic, the carcinogenic risk in 2020 was 3.74 × 10-6, which still exceeded the acceptable level, and more attention and governance efforts should be given to.
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Affiliation(s)
- Hanfei Zuo
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China; School of Materials Science and Chemical Engineering, Harbin Engineering University, Harbin 150006, China
| | - Yuchun Jiang
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Jing Yuan
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China; School of Materials Science and Chemical Engineering, Harbin Engineering University, Harbin 150006, China
| | - Ziqi Wang
- College of Arts and Sciences, University of Cincinnati, Cincinnati, State of Ohio 45221, USA
| | - Puzhen Zhang
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Chen Guo
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Zhanshan Wang
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Ye Chen
- School of Materials Science and Chemical Engineering, Harbin Engineering University, Harbin 150006, China
| | - Qing Wen
- School of Materials Science and Chemical Engineering, Harbin Engineering University, Harbin 150006, China
| | - Yongjie Wei
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Xiaoqian Li
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China; School of Materials Science and Chemical Engineering, Harbin Engineering University, Harbin 150006, China.
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Mananga ES, Lopez E, Diop A, Dongomale PJT, Diane F. The impact of the air pollution on health in New York City. J Public Health Res 2023; 12:22799036231205870. [PMID: 38034845 PMCID: PMC10687960 DOI: 10.1177/22799036231205870] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2022] [Accepted: 09/07/2023] [Indexed: 12/02/2023] Open
Abstract
New York City is attempting to find a solution to an issue that many states and cities face: how to minimize air pollution so that it has fewer negative impacts on human health. Despite having the highest population in the United States (US), New York City typically has reasonably clean air. As the City and State of New York have worked to reduce emissions from local and regional sources, the air quality in New York City has improved during the past few decades. Despite these advancements, air pollution still poses a severe hazard to the health of everyone living in New York's environment. Various diseases including respiratory, circulatory, neurological, gastrointestinal, and urinary illnesses, which can be fatal, are intimately associated with air pollution. This review article will concentrate on how air pollution affects respiratory diseases such as asthma in children. In addition to analyzing the severe effects of air pollution on the vulnerable population, this review article will highlight the health repercussions of air pollution on New York City and its residents. furthermore, we argue for potential ideas and discoveries while also putting up a policy option to lower air pollution.
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Affiliation(s)
- Eugene S Mananga
- The Graduate Center, The City University of New York, New York, NY, USA
- Department of Engineering, Physics, and Technology, Bronx Community College, The City University of New York, Bronx, NY, USA
- Extension School, Harvard University, Cambridge, MA, USA
| | - Erika Lopez
- Department of Engineering, Physics, and Technology, Bronx Community College, The City University of New York, Bronx, NY, USA
| | - Aissata Diop
- Department of Engineering, Physics, and Technology, Bronx Community College, The City University of New York, Bronx, NY, USA
| | - Paulin JT Dongomale
- Department of Geosciences and Geological and Petroleum Engineering, Missouri University of Science and Technology, Rolla, MO, USA
| | - Fambougouri Diane
- Department of Engineering, Physics, and Technology, Bronx Community College, The City University of New York, Bronx, NY, USA
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Bush T, Bartington S, Pope FD, Singh A, Thomas GN, Stacey B, Economides G, Anderson R, Cole S, Abreu P, Leach FCP. The impact of COVID-19 public health restrictions on particulate matter pollution measured by a validated low-cost sensor network in Oxford, UK. BUILDING AND ENVIRONMENT 2023; 237:110330. [PMID: 37124118 PMCID: PMC10121078 DOI: 10.1016/j.buildenv.2023.110330] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/12/2022] [Revised: 04/14/2023] [Accepted: 04/17/2023] [Indexed: 05/03/2023]
Abstract
Emergency responses to the COVID-19 pandemic led to major changes in travel behaviours and economic activities with arising impacts upon urban air quality. To date, these air quality changes associated with lockdown measures have typically been assessed using limited city-level regulatory monitoring data, however, low-cost air quality sensors provide capabilities to assess changes across multiple locations at higher spatial-temporal resolution, thereby generating insights relevant for future air quality interventions. The aim of this study was to utilise high-spatial resolution air quality information utilising data arising from a validated (using a random forest field calibration) network of 15 low-cost air quality sensors within Oxford, UK to monitor the impacts of multiple COVID-19 public heath restrictions upon particulate matter concentrations (PM10, PM2.5) from January 2020 to September 2021. Measurements of PM10 and PM2.5 particle size fractions both within and between site locations are compared to a pre-pandemic related public health restrictions baseline. While average peak concentrations of PM10 and PM2.5 were reduced by 9-10 μg/m3 below typical peak levels experienced in recent years, mean daily PM10 and PM2.5 concentrations were only ∼1 μg/m3 lower and there was marked temporal (as restrictions were added and removed) and spatial variability (across the 15-sensor network) in these observations. Across the 15-sensor network we observed a small local impact from traffic related emission sources upon particle concentrations near traffic-oriented sensors with higher average and peak concentrations as well as greater dynamic range, compared to more intermediate and background orientated sensor locations. The greater dynamic range in concentrations is indicative of exposure to more variable emission sources, such as road transport emissions. Our findings highlight the great potential for low-cost sensor technology to identify highly localised changes in pollutant concentrations as a consequence of changes in behaviour (in this case influenced by COVID-19 restrictions), generating insights into non-traffic contributions to PM emissions in this setting. It is evident that additional non-traffic related measures would be required in Oxford to reduce the PM10 and PM2.5 levels to within WHO health-based guidelines and to achieve compliance with PM2.5 targets developed under the Environment Act 2021.
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Affiliation(s)
- Tony Bush
- Department of Engineering Science, University of Oxford, Parks Road, Oxford, OX1 3PJ, UK
- Apertum Consulting, Harwell, Oxfordshire, UK
| | - Suzanne Bartington
- Institute of Applied Health Research, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
| | - Francis D Pope
- School of Geography, Earth and Environmental Sciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
| | - Ajit Singh
- Institute of Applied Health Research, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
- School of Geography, Earth and Environmental Sciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
| | - G Neil Thomas
- Institute of Applied Health Research, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
| | - Brian Stacey
- Ricardo Energy and Environment, The Gemini Building, Fermi Avenue, Harwell, Didcot, OX11 0QR, UK
| | - George Economides
- Oxfordshire County Council, County Hall, New Road, Oxford, OX1 1ND, UK
| | - Ruth Anderson
- Oxfordshire County Council, County Hall, New Road, Oxford, OX1 1ND, UK
| | - Stuart Cole
- Oxfordshire County Council, County Hall, New Road, Oxford, OX1 1ND, UK
| | - Pedro Abreu
- Oxford City Council, Town Hall, St Aldate's, Oxford, OX1 1BX, UK
| | - Felix C P Leach
- Department of Engineering Science, University of Oxford, Parks Road, Oxford, OX1 3PJ, UK
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Aboagye EM, Effah NAA, Effah KO. A bibliometric analysis of the impact of COVID-19 social lockdowns on air quality: research trends and future directions. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023:10.1007/s11356-023-27699-3. [PMID: 37219782 DOI: 10.1007/s11356-023-27699-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Received: 10/26/2022] [Accepted: 05/12/2023] [Indexed: 05/24/2023]
Abstract
Social lockdowns improved air quality during the COVID-19 pandemic. Governments had previously spent a lot of money addressing air pollution without success. This bibliometric study measured the influence of COVID-19 social lockdowns on air pollution, identified emerging issues, and discussed future perspectives. The researchers examined the contributions of countries, authors, and most productive journals to COVID-19 and air pollution research from January 1, 2020, to September 12, 2022, from the Web of Sciences Core Collection (WoS). The results showed that (a) publications on the COVID-19 pandemic and air pollution were 504 (research articles) with 7495 citations, (b) China ranked first in the number of publications (n = 151; 29.96% of the global output) and was the main country in international cooperation network, followed by India (n = 101; 20.04% of the total articles) and the USA (n = 41; 8.13% of the global output). Air pollution plagues China, India, and the USA, calling for many studies. After a high spike in 2020, research published in 2021 declined in 2022. The author's keywords have focused on "COVID-19," "air pollution," "lockdown," and "PM25." These keywords suggest that research in this area is focused on understanding the health impacts of air pollution, developing policies to address air pollution, and improving air quality monitoring. The COVID-19 social lockdown served as a specified procedure to reduce air pollution in these countries. However, this paper provides practical recommendations for future research and a model for environmental and health scientists to examine the likely impact of COVID-19 social lockdowns on urban air pollution.
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Affiliation(s)
| | | | - Kwaku Obeng Effah
- Law School, Zhongnan University of Economics and Law, Wuhan, China
- Department Political Science, University of Ghana, Legon, Accra, Ghana
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Cha Y, Song CK, Jeon KH, Yi SM. Factors affecting recent PM 2.5 concentrations in China and South Korea from 2016 to 2020. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 881:163524. [PMID: 37075994 DOI: 10.1016/j.scitotenv.2023.163524] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/13/2023] [Revised: 04/11/2023] [Accepted: 04/11/2023] [Indexed: 05/03/2023]
Abstract
This study used observational data and a chemical transport model to investigate the contributions of several factors to the recent change in air quality in China and South Korea from 2016 to 2020. We focused on observational data analysis, which could reflect the annual trend of emission reduction and adjust existing emission amounts to apply it into a chemical transport model. The observation data showed that the particulate matter (PM2.5) concentrations during winter 2020 decreased by -23.4 % (-14.68 μg/m3) and - 19.5 % (-5.73 μg/m3) in China and South Korea respectively, compared with that during winter 2016. Meteorological changes, the existing national plan for a long-term emission reduction target, and unexpected events (i.e., Coronavirus disease 2019 (COVID-19) in China and South Korea and the newly introduced special winter countermeasures in South Korea from 2020) are considered major factors that may affect the recent change in air quality. The impact of different meteorological conditions on PM2.5 concentrations was assessed by conducting model simulations by fixing the emission amounts; the results indicated changes of +7.6 % (+4.77 μg/m3) and + 9.7 % (+2.87 μg/m3) in China and South Korea, respectively, during winter 2020 compared to that during winter 2016. Due to the existing and pre-defined long-term emission control policies implemented in both countries, PM2.5 concentration significantly decreased from winter 2016-2020 in China (-26.0 %; -16.32 μg/m3) and South Korea (-9.1 %; -2.69 μg/m3). The unexpected COVID-19 outbreak caused the PM2.5 concentrations in China to decrease during winter 2020 by another -5.0 % (-3.13 μg/m3). In South Korea, the winter season special reduction policy, which was introduced and implemented in winter 2020, and the COVID-19 pandemic may have contributed to -19.5 % (-5.92 μg/m3) decrease in PM2.5 concentrations.
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Affiliation(s)
- Yesol Cha
- Department of Urban and Environmental Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan, Republic of Korea
| | - Chang-Keun Song
- Department of Urban and Environmental Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan, Republic of Korea; Graduate School of Carbon Neutrality, Ulsan National Institute of Science and Technology (UNIST), Ulsan, Republic of Korea.
| | - Kwon-Ho Jeon
- Department of Climate and Air Quality Research, National Institute of Environmental Research (NIER), Incheon, Republic of Korea
| | - Seung-Muk Yi
- Institute of Health and Environment, Seoul National University, Seoul, Republic of Korea; Graduate School of Public Health, Seoul National University, Seoul, Republic of Korea
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Panesar R, Grossman J, Nachman S. Antibiotic use among admitted pediatric patients in the United States with status asthmaticus before and during the COVID-19 pandemic. J Asthma 2023; 60:647-654. [PMID: 35634914 DOI: 10.1080/02770903.2022.2083636] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
OBJECTIVE Hospital admission trends of children with status asthmaticus diminished during the Coronavirus-19 (COVID-19) pandemic of 2020, possibly secondary to several factors such as school closures and use of face masks. What effect this had on antibiotic prescribing practices has yet to be described. The objective of our study was to evaluate the use of antibiotics in hospitalized children with a diagnosis of status asthmaticus before and during the COVID pandemic.Methods: A retrospective cross-sectional analysis was conducted using the TriNetX® cloud-based program with a national and institutional database. Each database was queried for all inpatient pediatric encounters from 3 to 18 years old, admitted with a diagnosis of status asthmaticus in the spring seasons of 2017-2019. Admission data and antibiotic usage were queried during the COVID-19 pandemic year of 2020 from both databases and compared amongst all study years.Results: In 2020, there was an overall decrease in the number of admissions as compared to the average number from 2017-2019, by 76.9% in the national database (p < 0.05) and 91.2% in the institutional database. The rates of antibiotic prescriptions significantly dropped among the national database (p < 0.001, z = 3.39) and remained non-significantly changed among the institutional database (p = 0.944 and z = 0.073).Conclusions: Our study demonstrates that the COVID-19 pandemic year of 2020 coincided with a significant decrease in hospital admissions and antibiotic prescribing prevalence among children with status asthmaticus on a national level. Nonetheless, our reported trends in antibiotic prescribing are still grossly similar to that of pre-pandemic times and may demonstrate a continued need for antimicrobial stewardship.
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Affiliation(s)
- Rahul Panesar
- Department of Pediatric Critical Care Medicine, Stony Brook University Children's Hospital, Stony Brook, NY, USA
| | - Jeremy Grossman
- Department of Internal Medicine-Pediatrics, Stony Brook University Children's Hospital, Stony Brook, NY, USA
| | - Sharon Nachman
- Department of Pediatric Infectious Disease, Stony Brook University Children's Hospital, Stony Brook, NY, USA
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Jana A, Kundu S, Shaw S, Chakraborty S, Chattopadhyay A. Spatial shifting of COVID-19 clusters and disease association with environmental parameters in India: A time series analysis. ENVIRONMENTAL RESEARCH 2023; 222:115288. [PMID: 36682443 PMCID: PMC9850905 DOI: 10.1016/j.envres.2023.115288] [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: 06/23/2022] [Revised: 12/23/2022] [Accepted: 01/10/2023] [Indexed: 05/19/2023]
Abstract
BACKGROUND The viability and virulence of COVID-19 are complex in nature. Although the relationship between environmental parameters and COVID-19 is well studied across the globe, in India, such studies are limited. This research aims to explore long-term exposure to weather conditions and the role of air pollution on the infection spread and mortality due to COVID-19 in India. METHOD District-level COVID-19 data from April 26, 2020 to July 10, 2021 was used for the study. Environmental determinants such as land surface temperature, relative humidity (RH), Sulphur dioxide (SO2), Nitrogen dioxide (NO2), Ozone (O3), and Aerosol Optical Depth (AOD) were considered for analysis. The bivariate spatial association was used to explore the spatial relationship between Case Fatality Rate (CFR) and these environmental factors. Further, the Bayesian multivariate linear regression model was applied to observe the association between environmental factors and the CFR of COVID-19. RESULTS Spatial shifting of COVID-19 cases from Western to Southern and then Eastern parts of India were well observed. The infection rate was highly concentrated in most of the Western and Southern regions of India, while the CFR shows more concentration in Northern India along with Maharashtra. Four main spatial clusters of infection were recognized during the study period. The time-series analysis indicates significantly more CFR with higher AOD, O3, and NO2 in India. CONCLUSIONS COVID-19 is highly associated with environmental parameters and air pollution in India. The study provides evidence to warrant consideration of environmental parameters in health models to mediate potential solutions. Cleaner air is a must to mitigate COVID-19.
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Affiliation(s)
- Arup Jana
- Department of Population and Development, International Institute for Population Sciences, Deonar, Mumbai, 400088, India.
| | - Sampurna Kundu
- Center of Social Medicine and Community Health, Jawaharlal Nehru University, Delhi, 110067, India.
| | - Subhojit Shaw
- Department of Population and Development, International Institute for Population Sciences, Deonar, Mumbai, 400088, India.
| | - Sukanya Chakraborty
- IMPRS Neuroscience, Max Planck Institute of Multidisciplinary Sciences, University of Goettingen, Germany.
| | - Aparajita Chattopadhyay
- Department of Population and Development, International Institute for Population Sciences, Deonar, Mumbai, 400088, India.
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Ma R, Zhang Y, Zhang Y, Li X, Ji Z. The Relationship between the Transmission of Different SARS-CoV-2 Strains and Air Quality: A Case Study in China. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2023; 20:ijerph20031943. [PMID: 36767307 PMCID: PMC9916065 DOI: 10.3390/ijerph20031943] [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: 12/13/2022] [Revised: 01/07/2023] [Accepted: 01/17/2023] [Indexed: 06/11/2023]
Abstract
Coronavirus Disease 2019 (COVID-19) has been a global public health concern for almost three years, and the transmission characteristics vary among different virus variants. Previous studies have investigated the relationship between air pollutants and COVID-19 infection caused by the original strain of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, it is unclear whether individuals might be more susceptible to COVID-19 due to exposure to air pollutants, with the SARS-CoV-2 mutating faster and faster. This study aimed to explore the relationship between air pollutants and COVID-19 infection caused by three major SARS-CoV-2 strains (the original strain, Delta variant, and Omicron variant) in China. A generalized additive model was applied to investigate the associations of COVID-19 infection with six air pollutants (PM2.5, PM10, SO2, CO, NO2, and O3). A positive correlation might be indicated between air pollutants (PM2.5, PM10, and NO2) and confirmed cases of COVID-19 caused by different SARS-CoV-2 strains. It also suggested that the mutant variants appear to be more closely associated with air pollutants than the original strain. This study could provide valuable insight into control strategies that limit the concentration of air pollutants at lower levels and would better control the spread of COVID-19 even as the virus continues to mutate.
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Affiliation(s)
- Ruiqing Ma
- School of Geography and Tourism, Shaanxi Normal University, Xi’an 710119, China
- International Joint Research Centre of Shaanxi Province for Pollutants Exposure and Eco-Environmental Health, Xi’an 710119, China
| | - Yeyue Zhang
- School of Geography and Tourism, Shaanxi Normal University, Xi’an 710119, China
- International Joint Research Centre of Shaanxi Province for Pollutants Exposure and Eco-Environmental Health, Xi’an 710119, China
| | - Yini Zhang
- School of Geography and Tourism, Shaanxi Normal University, Xi’an 710119, China
- International Joint Research Centre of Shaanxi Province for Pollutants Exposure and Eco-Environmental Health, Xi’an 710119, China
| | - Xi Li
- School of Geography and Tourism, Shaanxi Normal University, Xi’an 710119, China
- International Joint Research Centre of Shaanxi Province for Pollutants Exposure and Eco-Environmental Health, Xi’an 710119, China
| | - Zheng Ji
- School of Geography and Tourism, Shaanxi Normal University, Xi’an 710119, China
- International Joint Research Centre of Shaanxi Province for Pollutants Exposure and Eco-Environmental Health, Xi’an 710119, China
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12
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Urrutia-Mosquera JA, Flórez-Calderón LÁ. Impact of Confinement on the Reduction of Pollution and Particulate Matter Concentrations. Reflections for Public Transport Policies. ENVIRONMENTAL PROCESSES 2023; 10:2. [PMCID: PMC9758684 DOI: 10.1007/s40710-022-00611-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/22/2022] [Accepted: 11/11/2022] [Indexed: 08/12/2023]
Abstract
Different initiatives have been implemented to improve air quality in large cities, such as encouraging travel by sustainable modes of transport, promoting electro-mobility, or the car-free day. However, to date, we have not found statistics that indicate to what extent the concentration levels of particulate matter PM 2.5 , PM 10 and nitrogen oxides (NO x ) pollutants decrease as a result of public policy. We used official data from the Chilean Government’s national air quality information system (SINCA) for the Santiago metropolitan region and estimated the impact of the confinement by COVID-19 on the ambient concentration average values of NO x gases and particulate matter PM 2.5 and PM 10 , which are the main air pollutants produced by the transport sector after CO 2 . We found that in general there are significant differences between the average levels of gas emissions for 2020 compared to 2019. In particular, we found that, for the months of total confinement May-July, the monthly average levels decreased between 7% and 19% for particulate matter PM 2.5 , between 18% and 50% for PM 10 and between 34% and 48% for NO x . With the return to the new normality, these improvements in ambient concentration levels may be affected by the increase in private transport trips, due to the reluctance of citizens to return to mass public transport. Our results, therefore, represent the maximum impact that can be expected in reducing ambient concentration levels in the city of Santiago of Chile when a mobility reduction of gasoline vehicles is implemented. The reduction of PM 2.5 , PM 10 and NO x was no more than 7%, 18% and 34%, respectively. The average concentration of PM 2.5 decreased by 7–19% compared to previous years. The average concentration of PM 10 decreased by 18% and 50% compared to previous years. Concentrating commuting on public transport would help reduce levels of PM 10 and PM 2.5 .
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Affiliation(s)
| | - Luz Ángela Flórez-Calderón
- Department of Transportation and Logistics Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile
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13
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Investigating the impact of the COVID-19 pandemic on crime incidents number in different cities. JOURNAL OF SAFETY SCIENCE AND RESILIENCE 2022; 3:340-352. [PMCID: PMC8849845 DOI: 10.1016/j.jnlssr.2021.10.008] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/08/2021] [Revised: 10/18/2021] [Accepted: 10/19/2021] [Indexed: 05/28/2023]
Abstract
The COVID-19 pandemic is strongly affecting many aspects of human life and society around the world. To investigate whether this pandemic also influences crime, the differences in crime incidents numbers before and during the pandemic in four large cities (namely Washington DC, Chicago, New York City and Los Angeles) are investigated. Moreover, the Granger causal relationships between crime incident numbers and new cases of COVID-19 are also examined. Based on that, new cases of COVID-19 with significant Granger causal correlations are used to improve the crime prediction performance. The results show that crime is generally impacted by the COVID-19 pandemic, but it varies in different cities and with different crime types. Most types of crimes have seen fewer incidents numbers during the pandemic than before. Several Granger causal correlations are found between the COVID-19 cases and crime incidents in these cities. More specifically, crime incidents numbers of theft in Washington DC, Chicago and New York City, fraud in Washington DC and Los Angeles, assault in Chicago and New York City, and robbery in Los Angeles and New York City, are significantly Granger caused by the new case of COVID-19. These results may be partially explained by the Routine Activity theory and Opportunity theory that people may prefer to stay at home to avoid being infected with COVID-19 during the pandemic, giving fewer chances for crimes. In addition, involving new cases of COVID-19 as a variable can slightly improve the performance of crime prediction in terms of some specific types of crime. This study is expected to obtain deeper insights into the relationships between the pandemic and crime in different cities, and to provide new attempts for crime prediction during the pandemic.
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14
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Li X, Farrukh M, Lee C, Khreis H, Sarda S, Sohrabi S, Zhang Z, Dadashova B. COVID-19 impacts on mobility, environment, and health of active transportation users. CITIES (LONDON, ENGLAND) 2022; 131:103886. [PMID: 35935595 PMCID: PMC9345890 DOI: 10.1016/j.cities.2022.103886] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/05/2022] [Revised: 06/05/2022] [Accepted: 07/30/2022] [Indexed: 06/15/2023]
Abstract
Active transportation could be an effective way to promote healthy physical activity, especially during pandemics like COVID-19. A comprehensive evaluation of health outcomes derived from COVID-19 induced active transportation can assist multiple stakeholders in revisiting strategies and priorities for supporting active transportation during and beyond the pandemic. We performed a two-step reviewing process by combining a scoping review with a narrative review to summarize published literature addressing the influence of COVID-19 on mobility and the environment that can lead to various health pathways and health outcomes associated with active transportation. We summarized the COVID-19 induced changes in active transportation demand, built environment, air quality, and physical activity. The results demonstrated that, since the pandemic began, bike-sharing users dropped significantly while recreational bike trips and walking activities increased in some areas. Meanwhile, there have been favorable changes to the air quality and the built environment for active transportation users. We then discussed how these changes impact health outcomes during the pandemic and their implications for urban planning and policymaking. This review also suggests that walking and biking can make up for the reduced physical activities during the pandemic, helping people stay active and healthy.
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Affiliation(s)
- Xiao Li
- Texas A&M Transportation Institute, Bryan, TX, USA
| | - Minaal Farrukh
- School of Public Health, Texas A&M University, College Station, TX, USA
| | - Chanam Lee
- Department of Landscape Architecture and Urban Planning, Texas A&M University, College Station, TX, USA
| | - Haneen Khreis
- School of Clinical Medicine, University of Cambridge, Cambridge, UK
| | - Soham Sarda
- University of California Berkeley, Berkeley, CA, USA
| | | | - Zhe Zhang
- Department of Geography, Texas A&M University, College Station, TX, USA
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15
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Shearston JA, Cerna-Turoff I, Hilpert M, Kioumourtzoglou MA. Quantifying diurnal changes in NO 2 due to COVID-19 stay-at-home orders in New York City. HYGIENE AND ENVIRONMENTAL HEALTH ADVANCES 2022; 4:100032. [PMID: 36926117 PMCID: PMC9580220 DOI: 10.1016/j.heha.2022.100032] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/21/2022] [Revised: 10/18/2022] [Accepted: 10/18/2022] [Indexed: 11/16/2022]
Abstract
Introduction Policy responses to the COVID-19 pandemic, such as the NY on Pause stay-at-home order (March 22 - June 8, 2020), substantially reduced traffic and traffic-related air pollution (TRAP) in New York City (NYC). We evaluated the magnitude of TRAP decreases and examined the role of modifying factors such as weekend/weekday, road proximity, location, and time-of-day. Methods Hourly nitrogen dioxide (NO2) concentrations from January 1, 2018 through June 8, 2020 were obtained from the Environmental Protection Agency's Air Quality System for all six hourly monitors in the NYC area. We used an interrupted time series design to determine the impact of NY on Pause on NO2 concentrations, using a mixed effects model with random intercepts for monitor location, adjusted for meteorology and long-term trends. We evaluated effect modification through stratification. Results NO2 concentrations decreased during NY on Pause by 19% (-3.2 ppb, 95% confidence interval [CI]: -3.5, -3.0), on average, compared to pre-Pause time trends. We found no evidence for modification by weekend/weekday, but greater decreases in NO2 at non-roadside monitors and weak evidence for modification by location. For time-of-day, we found the largest decreases for 5 am (27%, -4.5 ppb, 95% CI: -5.7, -3.3) through 7 am (24%, -4.0 ppb, 95% CI: -5.2, -2.8), followed by 6 pm and 7 pm (22%, -3.7 ppb, 95% CI: -4.8, -2.6 and 22%, -4.8, -2.5, respectively), while the smallest decreases occurred at 11 pm and 1 am (both: 11%, -1.9 ppb, 95% CI: -3.1, -0.7). Conclusion NY on Pause's impact on TRAP varied greatly diurnally. Decreases during early morning and evening time periods are likely due to decreases in traffic. Our results may be useful for planning traffic policies that vary by time of day, such as congestion tolling policies.
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Affiliation(s)
- Jenni A Shearston
- Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, 722 W 168th St., 11th Floor, New York, NY, 10032, USA
| | - Ilan Cerna-Turoff
- Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, 722 W 168th St., 11th Floor, New York, NY, 10032, USA
| | - Markus Hilpert
- Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, 722 W 168th St., 11th Floor, New York, NY, 10032, USA
| | - Marianthi-Anna Kioumourtzoglou
- Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, 722 W 168th St., 11th Floor, New York, NY, 10032, USA
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16
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Abiotic factors play important roles in complexity and characterization of aroma precursors in Vidal blanc grape. Food Res Int 2022; 162:112015. [DOI: 10.1016/j.foodres.2022.112015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2022] [Revised: 09/26/2022] [Accepted: 09/28/2022] [Indexed: 11/20/2022]
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17
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Air quality in the New Delhi metropolis under COVID-19 lockdown. SYSTEMS AND SOFT COMPUTING 2022. [PMCID: PMC8818446 DOI: 10.1016/j.sasc.2022.200035] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Air pollution has been on continuous rise with increase in industrialization in metropolitan cities of the world. Several measures including strict climate laws and reduction in the number of vehicles were implemented by several nations. The COVID-19 pandemic provided a great opportunity to understand the daily human activities effect on air pollution. Majority nations restricted industrial activities and vehicular traffic to a large extent as a measure to restrict COVID-19 spread. In this paper, we analyzed the impact of such COVID19-induced lockdown on the air quality of the city of New Delhi, India. We analyzed the average concentration of common gaseous pollutants viz. sulfur dioxide (SO2), ozone (O3), nitrogen dioxide (NO2), and carbon monoxide (CO). These concentrations were obtained from the tropospheric column of Sentinel-5P (an earth observation satellite of European Space Agency) data. We observed that the city observed a significant drop in the level of atmospheric pollutant’s concentration for all the major pollutants as a result of strict lockdown measure. Such findings are also validated with pollutant data obtained from ground based monitoring stations. We observed that near-surface pollutant concentration dropped significantly by 50% for PM2.5, 71.9% for NO2, and 88% for CO, after the lockdown period. Such studies would pave the path for implementing future air pollution control measures by environmentalists.
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18
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Investigating the impacts of COVID-19 lockdown on air quality, surface Urban Heat Island, air temperature and lighting energy consumption in City of Melbourne. ENERGY STRATEGY REVIEWS 2022; 44:100963. [PMCID: PMC9452421 DOI: 10.1016/j.esr.2022.100963] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/18/2021] [Revised: 08/15/2022] [Accepted: 09/06/2022] [Indexed: 06/17/2023]
Abstract
The COVID-19 pandemic has threatened city economies and residents' public health and quality of life. Similar to most cities, Melbourne imposed extreme preventive lockdown measures to address this situation. It would be reasonable to assume that during the two phases of lockdowns, in autumn (March) and winter (June to August) 2020, air quality parameters, air temperature, Surface Urban Heat Island (SUHI), and lighting energy consumption most likely increased. As such, to test this assumption, Sentinel 5, ERA-5 LAND, Sentinel 1 and 2, NASA SRTM, MODIS Aqua and Terra, and VIIRS satellite imageries are utilized to investigate the alterations of NO₂, SO₂, CO, UV Aerosol Index (UAI), air temperature, SUHI, and lighting energy consumption factors in the City of Melbourne. Furthermore, satellite imageries of SentiThe results indicate that the change rates of NO₂ (1.17 mol/m2) and CO (1.64 mol/m2) factors were positive. Further, the nighttime SUHI values increased by approximately 0.417 °C during the winter phase of the lockdown, while during the summer phase of the lockdown, the largest negative change rate was in NO₂ (−100.40 mol/m2). By contrast, the largest positive change rate was in SO₂ and SUHI at night. The SO₂ values increased from very low to 330 μm mol/m2, and the SUHI nighttime values increased by approximately 4.8 °C. From the spatial point of view, this study also shows how the effects on such parameters shifted based on the urban form and land types across the City of Melbourne by using satellite data as a significant resource to analyze the spatial coverage of these factors. The findings of this study demonstrate how air quality factors, SUHI, air temperature, and lighting energy consumption changed from pre-lockdown (2019) to lockdown (2020), offering valuable insights regarding practices for managing SUHI, lighting energy consumption, and air pollution.
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19
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Tan E. The Long-Term Impact of COVID-19 Lockdowns in Istanbul. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:ijerph192114235. [PMID: 36361120 PMCID: PMC9654864 DOI: 10.3390/ijerph192114235] [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: 09/17/2022] [Revised: 10/19/2022] [Accepted: 10/28/2022] [Indexed: 06/03/2023]
Abstract
The World Health Organization (WHO) have set sustainability development goals to reduce diseases, deaths, and the environmental impact of cities due to air pollution. In Istanbul, although average pollutant concentrations have been on a downward trend in recent years, extreme values and their annual exceedance numbers are high based on the air quality standards of WHO and the EU. Due to COVID-19 lockdowns, statistically significant reductions in emissions were observed for short periods. However, how long the effect of the lockdowns will last is unknown. For this reason, this study aims to investigate the impact of long-term lockdowns on Istanbul's air quality. The restriction period is approximated to the same periods of the previous years to eliminate seasonal effects. A series of paired t-tests (p-value < 0.05) were applied to hourly data from 12 March 2016, until 1 July 2021, when quarantines were completed at 36 air quality monitoring stations in Istanbul. The findings reveal that the average air quality of Istanbul was approximately 17% improved during the long-term lockdowns. Therefore, the restriction-related changes in emission distributions continued in the long-term period of 476 days. However, it is unknown how long this effect will continue, which will be the subject of future studies. Moreover, it was observed that the emission probability density functions changed considerably during the lockdowns compared to the years before. Accordingly, notable decreases were detected in air quality limit exceedances in terms of both excessive pollutant concentrations and frequency of occurrence, respectively, for PM10 (-13% and -13%), PM2.5 (-16% and -30%), and NO2 (-3% and -8%), but not for O3 (+200% and +540%) and SO2 (-10% and +2.5%).
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Affiliation(s)
- Elçin Tan
- Department of Meteorological Engineering, Aeronautics and Astronautics Faculty, Istanbul Technical University, Maslak, 34469 Istanbul, Turkey
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20
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Hassan MA, Mehmood T, Lodhi E, Bilal M, Dar AA, Liu J. Lockdown Amid COVID-19 Ascendancy over Ambient Particulate Matter Pollution Anomaly. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:13540. [PMID: 36294120 PMCID: PMC9603700 DOI: 10.3390/ijerph192013540] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/31/2022] [Revised: 10/10/2022] [Accepted: 10/15/2022] [Indexed: 06/16/2023]
Abstract
Air is a diverse mixture of gaseous and suspended solid particles. Several new substances are being added to the air daily, polluting it and causing human health effects. Particulate matter (PM) is the primary health concern among these air toxins. The World Health Organization (WHO) addressed the fact that particulate pollution affects human health more severely than other air pollutants. The spread of air pollution and viruses, two of our millennium's most serious concerns, have been linked closely. Coronavirus disease 2019 (COVID-19) can spread through the air, and PM could act as a host to spread the virus beyond those in close contact. Studies on COVID-19 cover diverse environmental segments and become complicated with time. As PM pollution is related to everyday life, an essential awareness regarding PM-impacted COVID-19 among the masses is required, which can help researchers understand the various features of ambient particulate pollution, particularly in the era of COVID-19. Given this, the present work provides an overview of the recent developments in COVID-19 research linked to ambient particulate studies. This review summarizes the effect of the lockdown on the characteristics of ambient particulate matter pollution, the transmission mechanism of COVID-19, and the combined health repercussions of PM pollution. In addition to a comprehensive evaluation of the implementation of the lockdown, its rationales-based on topographic and socioeconomic dynamics-are also discussed in detail. The current review is expected to encourage and motivate academics to concentrate on improving air quality management and COVID-19 control.
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Affiliation(s)
- Muhammad Azher Hassan
- Tianjin Key Lab of Indoor Air Environmental Quality Control, School of Environmental Science and Engineering, Tianjin University, Tianjin 300072, China
| | - Tariq Mehmood
- College of Ecology and Environment, Hainan University, Haikou 570228, China
- Department of Environmental Engineering, Helmholtz Centre for Environmental Research—UFZ, D-04318 Leipzig, Germany
| | - Ehtisham Lodhi
- The SKL for Management and Control of Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
| | - Muhammad Bilal
- School of Surveying and Land Information Engineering, Henan Polytechnic University, Jiaozuo 454000, China
| | - Afzal Ahmed Dar
- School of Environmental Science and Engineering, Shaanxi University of Science and Technology, Xi’an 710000, China
| | - Junjie Liu
- Tianjin Key Lab of Indoor Air Environmental Quality Control, School of Environmental Science and Engineering, Tianjin University, Tianjin 300072, China
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21
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Statistical modeling approach for PM10 prediction before and during confinement by COVID-19 in South Lima, Perú. Sci Rep 2022; 12:16737. [PMID: 36202880 PMCID: PMC9537318 DOI: 10.1038/s41598-022-20904-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2022] [Accepted: 09/20/2022] [Indexed: 11/08/2022] Open
Abstract
AbstractA total of 188,859 meteorological-PM$$_{10}$$
10
data validated before (2019) and during the COVID-19 pandemic (2020) were used. In order to predict PM$$_{10}$$
10
in two districts of South Lima in Peru, hourly, daily, monthly and seasonal variations of the data were analyzed. Principal Component Analysis (PCA) and linear/nonlinear modeling were applied. The results showed the highest annual average PM$$_{10}$$
10
for San Juan de Miraflores (SJM) (PM$$_{10}$$
10
-SJM: 78.7 $$\upmu$$
μ
g/m$$^{3}$$
3
) and the lowest in Santiago de Surco (SS) (PM$$_{10}$$
10
-SS: 40.2 $$\upmu$$
μ
g/m$$^{3}$$
3
). The PCA showed the influence of relative humidity (RH)-atmospheric pressure (AP)-temperature (T)/dew point (DP)-wind speed (WS)-wind direction (WD) combinations. Cool months with higher humidity and atmospheric instability decreased PM$$_{10}$$
10
values in SJM and warm months increased it, favored by thermal inversion (TI). Dust resuspension, vehicular transport and stationary sources contributed more PM$$_{10}$$
10
at peak times in the morning and evening. The Multiple linear regression (MLR) showed the best correlation (r = 0.6166), followed by the three-dimensional model LogAP-LogWD-LogPM$$_{10}$$
10
(r = 0.5753); the RMSE-MLR (12.92) exceeded that found in the 3D models (RMSE $$<0.3$$
<
0.3
) and the NSE-MLR criterion (0.3804) was acceptable. PM$$_{10}$$
10
prediction was modeled using the algorithmic approach in any scenario to optimize urban management decisions in times of pandemic.
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22
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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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23
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Zhang J, Lim YH, Andersen ZJ, Napolitano G, Taghavi Shahri SM, So R, Plucker M, Danesh-Yazdi M, Cole-Hunter T, Therming Jørgensen J, Liu S, Bergmann M, Jayant Mehta A, H. Mortensen L, Requia W, Lange T, Loft S, Kuenzli N, Schwartz J, Amini H. Stringency of COVID-19 Containment Response Policies and Air Quality Changes: A Global Analysis across 1851 Cities. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2022; 56:12086-12096. [PMID: 35968717 PMCID: PMC9454244 DOI: 10.1021/acs.est.2c04303] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/16/2022] [Revised: 08/03/2022] [Accepted: 08/04/2022] [Indexed: 06/15/2023]
Abstract
The COVID-19 containment response policies (CRPs) had a major impact on air quality (AQ). These CRPs have been time-varying and location-specific. So far, despite having numerous studies on the effect of COVID-19 lockdown on AQ, a knowledge gap remains on the association between stringency of CRPs and AQ changes across the world, regions, nations, and cities. Here, we show that globally across 1851 cities (each more than 300 000 people) in 149 countries, after controlling for the impacts of relevant covariates (e.g., meteorology), Sentinel-5P satellite-observed nitrogen dioxide (NO2) levels decreased by 4.9% (95% CI: 2.2, 7.6%) during lockdowns following stringent CRPs compared to pre-CRPs. The NO2 levels did not change significantly during moderate CRPs and even increased during mild CRPs by 2.3% (95% CI: 0.7, 4.0%), which was 6.8% (95% CI: 2.0, 12.0%) across Europe and Central Asia, possibly due to population avoidance of public transportation in favor of private transportation. Among 1768 cities implementing stringent CRPs, we observed the most NO2 reduction in more populated and polluted cities. Our results demonstrate that AQ improved when and where stringent COVID-19 CRPs were implemented, changed less under moderate CRPs, and even deteriorated under mild CRPs. These changes were location-, region-, and CRP-specific.
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Affiliation(s)
- Jiawei Zhang
- Department
of Public Health, University of Copenhagen, 1014 Copenhagen, Denmark
| | - Youn-Hee Lim
- Department
of Public Health, University of Copenhagen, 1014 Copenhagen, Denmark
| | | | - George Napolitano
- Department
of Public Health, University of Copenhagen, 1014 Copenhagen, Denmark
| | | | - Rina So
- Department
of Public Health, University of Copenhagen, 1014 Copenhagen, Denmark
| | - Maude Plucker
- Department
of Public Health, University of Copenhagen, 1014 Copenhagen, Denmark
| | - Mahdieh Danesh-Yazdi
- Department
of Environmental Health, Harvard TH Chan
School of Public Health, Boston, Massachusetts 02115, United States
- Program
in Public Health, Department of Family, Population & Preventive
Medicine, Stony Brook University School
of Medicine, Stony Brook, New York 11794-8434, United States
| | - Thomas Cole-Hunter
- Department
of Public Health, University of Copenhagen, 1014 Copenhagen, Denmark
| | | | - Shuo Liu
- Department
of Public Health, University of Copenhagen, 1014 Copenhagen, Denmark
| | - Marie Bergmann
- Department
of Public Health, University of Copenhagen, 1014 Copenhagen, Denmark
| | - Amar Jayant Mehta
- Department
of Public Health, University of Copenhagen, 1014 Copenhagen, Denmark
| | - Laust H. Mortensen
- Department
of Public Health, University of Copenhagen, 1014 Copenhagen, Denmark
- Methods
and Analysis, Statistics Denmark, 2100 Copenhagen, Denmark
| | - Weeberb Requia
- School
of Public Policy and Government, Fundação
Getúlio Vargas, Brasilia, Distrito Federal 72125590, Brazil
| | - Theis Lange
- Department
of Public Health, University of Copenhagen, 1014 Copenhagen, Denmark
| | - Steffen Loft
- Department
of Public Health, University of Copenhagen, 1014 Copenhagen, Denmark
| | - Nino Kuenzli
- Swiss Tropical
and Public Health Institute (Swiss TPH), Basel 4051, Switzerland
- University
of Basel, Basel 4001, Switzerland
| | - Joel Schwartz
- Department
of Environmental Health, Harvard TH Chan
School of Public Health, Boston, Massachusetts 02115, United States
| | - Heresh Amini
- Department
of Public Health, University of Copenhagen, 1014 Copenhagen, Denmark
- Department
of Environmental Health, Harvard TH Chan
School of Public Health, Boston, Massachusetts 02115, United States
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Chen W, Duanmu L, Qin Y, Yang H, Fu J, Lu C, Feng W, Guo L. Lockdown-induced Urban Aerosol Change over Changchun, China During COVID-19 Outbreak with Polarization LiDAR. CHINESE GEOGRAPHICAL SCIENCE 2022; 32:824-833. [PMID: 36091644 PMCID: PMC9446648 DOI: 10.1007/s11769-022-1303-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/07/2022] [Accepted: 07/12/2022] [Indexed: 05/24/2023]
Abstract
Depending on various government policies, COVID-19 (Corona Virus Disease-19) lockdowns have had diverse impacts on global aerosol concentrations. In 2022, Changchun, a provincial capital city in Northeast China, suffered a severe COVID-19 outbreak and implemented a very strict lockdown that lasted for nearly two months. Using ground-based polarization Light Detection and Ranging (LiDAR), we detected real-time aerosol profile parameters (EC, extinction coefficient; DR, depolarization ratio; AOD, aerosol optical depth), as well as air-quality and meteorological indexes from 1 March to 30 April in 2021 and 2022 to quantify the effects of lockdown on aerosol concentrations. The period in 2022 was divided into three stages: pre-lockdown (1-10 March), strict lockdown (11 March to 10 April), and partial lockdown (11-30 April). The results showed that, during the strict lockdown period, compared with the pre-lockdown period, there were substantial reductions in aerosol parameters (EC and AOD), and this was consistent with the concentrations of the atmospheric pollutants PM2.5 (particulate matter with an aerodynamic diameter ≤ 2.5 µm) and PM10 (particulate matter with an aerodynamic diameter ≤ 10 µm), and the O3 concentration increased by 8.3%. During the strict lockdown, the values of EC within 0-1 km and AOD decreased by 16.0% and 11.2%, respectively, as compared to the corresponding period in 2021. Lockdown reduced the conventional and organized emissions of air pollutants, and it clearly delayed the time of seasonal emissions from agricultural burning; however, it did not decrease the number of farmland fire points. Considering meteorological factors and eliminating the influence of wind-blown dust events, the results showed that reductions from conventional organized emission sources during the strict lockdown contributed to a 30% air-quality improvement and a 22% reduction in near-surface extinction (0-2 km). Aerosols produced by urban epidemic prevention and disinfection can also be identified using the EC. Regarding seasonal sources of agricultural straw burning, the concentrated burning induced by the epidemic led to the occurrence of heavy pollution from increased amounts of atmospheric aerosols, with a contribution rate of 62%. These results indicate that there is great potential to further improve air quality in the local area, and suggest that the comprehensive use of straw accompanied by reasonable planned burning is the best way to achieve this.
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Affiliation(s)
- Weiwei Chen
- Key Laboratory of Wetland Ecology and Environment, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun, 130102 China
| | - Lingjian Duanmu
- Key Laboratory of Wetland Ecology and Environment, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun, 130102 China
- College of Biological and Agricultural Engineering, Jilin University, Changchun, 130022 China
| | - Yang Qin
- Jilin Provincial Ecological Environment Monitoring Center, Changchun, 130012 China
| | - Hongwu Yang
- Hongke Photonics Company, Liaoyuan, 136200 China
| | - Jing Fu
- Key Laboratory of Wetland Ecology and Environment, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun, 130102 China
| | - Chengwei Lu
- The Department of Ophthalmology, The First Hospital of Jilin University, Changchun, 130021 China
| | - Wei Feng
- Key Lab of Groundwater Resources and Environment, Jilin University, Changchun, 130021 China
| | - Li Guo
- College of Biological and Agricultural Engineering, Jilin University, Changchun, 130022 China
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25
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Cao X, Liu X, Hadiatullah H, Xu Y, Zhang X, Cyrys J, Zimmermann R, Adam T. Investigation of COVID-19-related lockdowns on the air pollution changes in augsburg in 2020, Germany. ATMOSPHERIC POLLUTION RESEARCH 2022; 13:101536. [PMID: 36042786 PMCID: PMC9392961 DOI: 10.1016/j.apr.2022.101536] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/29/2022] [Revised: 08/15/2022] [Accepted: 08/15/2022] [Indexed: 06/15/2023]
Abstract
The COVID-19 pandemic in Germany in 2020 brought many regulations to impede its transmission such as lockdown. Hence, in this study, we compared the annual air pollutants (CO, NO, NO2, O3, PM10, PM2.5, and BC) in Augsburg in 2020 to the record data in 2010-2019. The annual air pollutants in 2020 were significantly (p < 0.001) lower than that in 2010-2019 except O3, which was significantly (p = 0.02) higher than that in 2010-2019. In a depth perspective, we explored how lockdown impacted air pollutants in Augsburg. We simulated air pollutants based on the meteorological data, traffic density, and weekday and weekend/holiday by using four different models (i.e. Random Forest, K-nearest Neighbors, Linear Regression, and Lasso Regression). According to the best fitting effects, Random Forest was used to predict air pollutants during two lockdown periods (16/03/2020-19/04/2020, 1st lockdown and 02/11/2020-31/12/2020, 2nd lockdown) to explore how lockdown measures impacted air pollutants. Compared to the predicted values, the measured CO, NO2, and BC significantly reduced 18.21%, 21.75%, and 48.92% in the 1st lockdown as well as 7.67%, 32.28%, and 79.08% in the 2nd lockdown. It could be owing to the reduction of traffic and industrial activities. O3 significantly increased 15.62% in the 1st lockdown but decreased 40.39% in the 2nd lockdown, which may have relations with the fluctuations the NO titration effect and photochemistry effect. PM10 and PM2.5 were significantly increased 18.23% an 10.06% in the 1st lockdown but reduced 34.37% and 30.62% in the 2nd lockdown, which could be owing to their complex generation mechanisms.
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Affiliation(s)
- Xin Cao
- School of Sport Science, Beijing Sport University, Beijing, 100084, China
- Joint Mass Spectrometry Center, Cooperation Group Comprehensive Molecular Analytics, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstr. 1, Neuherberg, 85764, Germany
| | - Xiansheng Liu
- University of the Bundeswehr Munich, Faculty for Mechanical Engineering, Institute of Chemical and Environmental Engineering, 85577 Neubiberg, Germany
- Institute of Environmental Assessment and Water Research (IDAEA-CSIC), 08034, Barcelona, Spain
| | | | - Yanning Xu
- School of Environmental and Municipal Engineering, Qingdao University of Technology, Qingdao, 266525, China
| | - Xun Zhang
- Beijing Key Laboratory of Big Data Technology for Food Safety, School of Computer Science and Engineering, Beijing Technology and Business University, Beijing, 100048, China
| | - Josef Cyrys
- Research Unit Analytical BioGeoChemistry, German Research Center for Environmental Health, Ingolstädter Landstr. 1, 85764 Neuherberg, Germany
| | - Ralf Zimmermann
- Joint Mass Spectrometry Center, Cooperation Group Comprehensive Molecular Analytics, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstr. 1, Neuherberg, 85764, Germany
- Joint Mass Spectrometry Center, Chair of Analytical Chemistry, University of Rostock, Rostock, 18059, Germany
| | - Thomas Adam
- Joint Mass Spectrometry Center, Cooperation Group Comprehensive Molecular Analytics, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstr. 1, Neuherberg, 85764, Germany
- University of the Bundeswehr Munich, Faculty for Mechanical Engineering, Institute of Chemical and Environmental Engineering, 85577 Neubiberg, Germany
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26
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Baimatova N, Omarova A, Muratuly A, Tursumbayeva M, Ibragimova OP, Bukenov B, Kerimray A. Seasonal Variations and Effect of COVID-19 Lockdown Restrictions on the Air Quality in the Cities of Kazakhstan. ENVIRONMENTAL PROCESSES 2022. [PMCID: PMC9395825 DOI: 10.1007/s40710-022-00603-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
The objective of this study was to investigate the impact of COVID-19 lockdown on different air pollutants in eight cities of Kazakhstan by employing the data from the National Air Quality Monitoring Network. We selected eight cities located in different regions of the country with varied climatic and geographic conditions and emissions sources, providing good conditions for studying the differences in responses of air quality to COVID-19. Due to severe winters, the heating season in Kazakhstan has a significant impact on air quality; therefore, annual winter/spring changes in air quality were also compared. The positive effect of the COVID-19 lockdown (spring 2020) on NO2 and CO levels was observed in 5 and 3 cities, respectively (out of 8). Total Suspended Particles and SO2 exhibited a more complicated response to COVID-19 lockdown: cities had a varying effect. No impact of lockdown measures was observed in industrial cities (Ust-Kamenegorsk and Karagandy), but seasonal changes were significant. In addition, despite some improvements during the lockdown period, the air quality in seven out of eight cities was still below the safety levels. The atmospheric quality in urban areas of Kazakhstan has not improved significantly due to the lockdown measures. This study underscores the importance of imposing stricter air quality emission control over industrial enterprises and coal-fired power plants. Response of air quality to COVID-19 lockdown in eight cities of Kazakhstan was examined The positive effect of the COVID-19 lockdown on NO2 and CO was observed in 5 and 3 cities, respectively The effect of the quarantine measures on SO2 and TSP was different in different cities Industrial cities were not affected by the lockdown, but seasonal changes were significant NO2 and SO2 concentrations exceeded the WHO limits during the COVID-19 lockdown period
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Affiliation(s)
- Nassiba Baimatova
- Center of Physical-Chemical Methods of Research and Analysis, Faculty of Chemistry and Chemical Technology, Al-Farabi Kazakh National University, 96a Tole bi Street, 050012 Almaty, Kazakhstan
| | - Anara Omarova
- Center of Physical-Chemical Methods of Research and Analysis, Faculty of Chemistry and Chemical Technology, Al-Farabi Kazakh National University, 96a Tole bi Street, 050012 Almaty, Kazakhstan
| | - Aset Muratuly
- Center of Physical-Chemical Methods of Research and Analysis, Faculty of Chemistry and Chemical Technology, Al-Farabi Kazakh National University, 96a Tole bi Street, 050012 Almaty, Kazakhstan
| | - Madina Tursumbayeva
- Center of Physical-Chemical Methods of Research and Analysis, Faculty of Chemistry and Chemical Technology, Al-Farabi Kazakh National University, 96a Tole bi Street, 050012 Almaty, Kazakhstan
- Department of Meteorology and Hydrology, Al-Farabi Kazakh National University, Almaty, Kazakhstan
| | - Olga P. Ibragimova
- Center of Physical-Chemical Methods of Research and Analysis, Faculty of Chemistry and Chemical Technology, Al-Farabi Kazakh National University, 96a Tole bi Street, 050012 Almaty, Kazakhstan
| | - Bauyrzhan Bukenov
- Center of Physical-Chemical Methods of Research and Analysis, Faculty of Chemistry and Chemical Technology, Al-Farabi Kazakh National University, 96a Tole bi Street, 050012 Almaty, Kazakhstan
| | - Aiymgul Kerimray
- Center of Physical-Chemical Methods of Research and Analysis, Faculty of Chemistry and Chemical Technology, Al-Farabi Kazakh National University, 96a Tole bi Street, 050012 Almaty, Kazakhstan
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27
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Benita F, Fuentes L, Guzmán LA, Martínez R, Carlos Muñoz J, Neo H, Rodríguez-Leiva S, Soza-Parra J. Comparing COVID-19 in the antipodes: Insights from pandemic containment strategies on both sides of the Pacific. TRANSPORTATION RESEARCH INTERDISCIPLINARY PERSPECTIVES 2022; 15:100660. [PMID: 35875330 PMCID: PMC9294080 DOI: 10.1016/j.trip.2022.100660] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/15/2021] [Revised: 07/07/2022] [Accepted: 07/15/2022] [Indexed: 06/15/2023]
Abstract
That the COVID-19 pandemic is unprecedented in terms of its scale, spread and shocks can be evinced by the myriad of ever-changing responses cities all around the world have rolled out throughout the different waves of outbreaks. Although the threat is similar across the world, it took some time before its reach became global and the waves of outbreak are experienced by cities at different times. While this staggered spread imply that some cities might manage the virus better as they learn from the experiences of cities which had been amongst the earliest to face the virus, the reality is more complicated. In the early stages of the pandemic, the global consensus on the best way to contain the virus swiftly converged in the interlinked strategies of restricting the movement of people and minimizing their social contact. However, the effectiveness of these strategies differ greatly between cities. To that end, this study focuses on COVID-19 responses in two regions (Latin America and Southeast Asia) and examines the evolution of the first wave of COVID-19 outbreaks during 2020 in Singapore, Jakarta (Indonesia), Bogotá (Colombia) and Santiago (Chile). The study is based on a comparative approach and uses a variety of data sources, namely morphology, density, housing concentration, mobility, and governance in the four analyzed cities. The goal is to shed light on the response of city governments in these two different regions in terms of mobility restrictions in order to reduce the cases of new infections. The results show the relevance of urban policies and their territorial approaches, particularly in terms of mobility and public transport networks in the four cities.
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Affiliation(s)
- Francisco Benita
- Engineering Systems and Design, Singapore University of Technology and Design, Singapore, Singapore
| | - Luis Fuentes
- Instituto de Estudios Urbanos, Pontificia Universidad Católica de Chile, Chile
| | - Luis A Guzmán
- Departamento de Ingeniería Civil y Ambiental, Grupo de Sostenibilidad Urbana y Regional, SUR, Universidad de los Andes, Bogotá, Colombia
| | - Rafael Martínez
- Lee Kuan Yew Centre for Innovative Cities, Singapore University of Technology and Design, Singapore, Singapore
| | - Juan Carlos Muñoz
- Department of Transport Engineering and Logistics, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Harvey Neo
- Lee Kuan Yew Centre for Innovative Cities, Singapore University of Technology and Design, Singapore, Singapore
| | | | - Jaime Soza-Parra
- 3 Revolutions Future Mobility Program, Institute of Transportation Studies, University of California at Davis, Davis, CA, USA
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28
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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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29
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Yao Y, Artigas FJ, Fan S, Gao Y. Impact of the COVID-19 Pandemic on Air Quality in Metropolitan New Jersey. WATER, AIR, AND SOIL POLLUTION 2022; 233:289. [PMID: 35875407 PMCID: PMC9296220 DOI: 10.1007/s11270-022-05764-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/14/2021] [Accepted: 07/10/2022] [Indexed: 06/15/2023]
Abstract
UNLABELLED Improved air quality has been the silver lining of the pandemic since early 2020. The air quality in northern New Jersey (NJ) was continuously measured during the COVID-19 pandemic and through the three stages of recovery, i.e., the Stay-at-home stage, Reopening stage 1, and Reopening stage 2. A significant change in air quality was observed during the Stay-at-home stage (March 16 to May 16, 2020) as most people stayed home and industrial activity decreased 60%. Compared to 2019, carbon dioxide (CO2) decreased 17%, carbon monoxide (CO) decreased 7%, and nitrogen oxides (NOx) decreased 51% during the Stay-at-home stage in 2020. However, the ground-level ozone (O3) increased in 2020 because of the reduced NOx emission and the possibly increased levels of volatile organic compounds (VOCs) due to warmer weather. With the step-by-step reopening process, the difference in local CO2 levels between 2019 and 2020 was reduced, and the NOx concentration returned to its 2019 level. The CO2 concentrations were positively correlated with CO, and the NOx concentrations were negatively correlated with O3. Under the COVID-19 pandemic in 2020, NJ consumed 14% less natural gas and 21% less gasoline; therefore, the CO2, CO, and NOx emissions and concentration levels were reduced besides the effects of meteorology parameters on air quality in metropolitan New Jersey. Our findings support that replacing fossil fuels with electric or renewable energy in the transportation systems and industry could be beneficial for the concentration reduction of certain greenhouse gases. SUPPLEMENTARY INFORMATION The online version contains supplementary material available at 10.1007/s11270-022-05764-w.
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Affiliation(s)
- Ying Yao
- Meadowlands Environmental Research Institute, New Jersey Sports and Exposition Authority, 1 Dekorte Park Plaza, Lyndhurst, NJ 07071 USA
- Department of Earth and Environmental Sciences, Rutgers University, Newark, NJ 07102 USA
| | - Francisco J. Artigas
- Meadowlands Environmental Research Institute, New Jersey Sports and Exposition Authority, 1 Dekorte Park Plaza, Lyndhurst, NJ 07071 USA
- Department of Earth and Environmental Sciences, Rutgers University, Newark, NJ 07102 USA
| | - Songyun Fan
- Department of Earth and Environmental Sciences, Rutgers University, Newark, NJ 07102 USA
| | - Yuan Gao
- Department of Earth and Environmental Sciences, Rutgers University, Newark, NJ 07102 USA
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30
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Serio C, Masiello G, Cersosimo A. NO 2 pollution over selected cities in the Po Valley in 2018-2021 and its possible effects on boosting COVID-19 deaths. Heliyon 2022; 8:e09978. [PMID: 35873538 PMCID: PMC9297682 DOI: 10.1016/j.heliyon.2022.e09978] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2022] [Revised: 04/01/2022] [Accepted: 07/13/2022] [Indexed: 11/29/2022] Open
Abstract
This work analyzes nitrogen dioxide (NO2) pollution over a set of cities in the Po Valley in northern Italy, using satellite and in situ observations. The cities include Milan, Bergamo, and Brescia, the first area of the COVID-19 outbreak and diffusion in Italy, with a higher mortality rate than in other parts of Italy and Europe. The analysis was performed for three years, from May 2018 to April 2021, including the period of first-wave diffusion of COVID-19 over the Po Valley, that is, January 2020–April 2020. The study aimed at giving a more general picture of the NO2 temporal and spatial variation, possibly due to the lockdown adopted for the pandemic crisis containment and other factors, such as the meteorological conditions and the seasonal cycle. We have mainly investigated two effects: first, the correlation of NO2 pollution with atmospheric parameters such as air and dew point temperature, and second the possible correlation between air quality and COVID-19 deaths, which could explain the high mortality rate. We have found a good relationship between air quality and temperature. In light of this relationship, we can conclude that the air quality improvement in March 2020 was primarily because of the lockdown adopted to prevent and limit virus diffusion. We also report a good correlation between NO2 pollution and COVID-19 deaths, which is not seen when considering a reference city in the South of Italy. The critical factor in explaining the difference is the persistence of air pollution in the Po Valley in wintertime. We found that NO2 pollution shows a seasonal cycle, yielding a non-causal correlation with the COVID-19 deaths. However, causality comes in once we read the correlation in the context of current and recent epidemiological evidence and leads us to conclude that air pollution may have acted as a significant risk factor in boosting COVID-19 fatalities.
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Affiliation(s)
- Carmine Serio
- School of Engineering, University of Basilicata, Potenza, Italy
| | - Guido Masiello
- School of Engineering, University of Basilicata, Potenza, Italy
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31
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Trivedi SK, Patra P, Singh A, Deka P, Srivastava PR. Analyzing the research trends of COVID-19 using topic modeling approach. JOURNAL OF MODELLING IN MANAGEMENT 2022. [DOI: 10.1108/jm2-02-2022-0045] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Purpose
The COVID-19 pandemic has impacted 222 countries across the globe, with millions of people losing their lives. The threat from the virus may be assessed from the fact that most countries across the world have been forced to order partial or complete shutdown of their economies for a period of time to contain the spread of the virus. The fallout of this action manifested in loss of livelihood, migration of the labor force and severe impact on mental health due to the long duration of confinement to homes or residences.
Design/methodology/approach
The current study identifies the focus areas of the research conducted on the COVID-19 pandemic. Abstracts of papers on the subject were collated from the SCOPUS database for the period December 2019 to June 2020. The collected sample data (after preprocessing) was analyzed using Topic Modeling with Latent Dirichlet Allocation.
Findings
Based on the research papers published within the mentioned timeframe, the study identifies the 10 most prominent topics that formed the area of interest for the COVID-19 pandemic research.
Originality/value
While similar studies exist, no other work has used topic modeling to comprehensively analyze the COVID-19 literature by considering diverse fields and domains.
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32
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Lin GY, Chen WY, Chieh SH, Yang YT. Chang impact analysis of level 3 COVID-19 alert on air pollution indicators using artificial neural network. ECOL INFORM 2022; 69:101674. [PMID: 36568861 PMCID: PMC9760264 DOI: 10.1016/j.ecoinf.2022.101674] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2022] [Revised: 05/08/2022] [Accepted: 05/09/2022] [Indexed: 01/27/2023]
Abstract
In this study, mean monthly and diurnal variations in fine particulate matters (PM2.5), nitrate, sulfate, and gaseous precursors were investigated during the Level 3 COVID-19 alert from May 19 to July 27 in 2021. For comparison, the historical data during the identical period in 2019 and 2020 were also provided to determine the effect of the Level 3 COVID-19 alert on aerosols and gaseous pollutants concentrations in Taichung City. A machine learning model using the artificial neural network technique coupled with a kinetic model was applied to predict NOx, O3, nitrate (NO3 -), and sulfate (SO4 2-) to investigate potential emission sources and chemical reaction mechanism. D during the Level 3 COVID-19 alert, a decrease in NOx concentration due to a decrease in traffic flow under the NOx-saturated regime was observed to enhance the secondary NO3 - and O3 formation. The present models were shown to predict 80.1, 77.0, 72.6, and 67.2% concentrations of NOx, O3, NO3 -, and SO4 2-, respectively, which could help decision-makers for pollutant emissions reduction policies development and air pollution control strategies. It is recommended that more long-term datasets, including water soluble inorganic salts (WIS), precursors including OH radicals, NH3, HNO3, and H2SO4, be provided by regulatory air quality monitoring stations to further improve the prediction model accuracy.
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Mehmood K, Mushtaq S, Bao Y, Bibi S, Yaseen M, Khan MA, Abrar MM, Ulhassan Z, Fahad S, Petropoulos GP. The impact of COVID-19 pandemic on air pollution: a global research framework, challenges, and future perspectives. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2022; 29:52618-52634. [PMID: 35262893 PMCID: PMC8906062 DOI: 10.1007/s11356-022-19484-5] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/12/2021] [Accepted: 02/24/2022] [Indexed: 05/17/2023]
Abstract
As a result of extreme modifications in human activity during the COVID-19 pandemic, the status of air quality has recently been improved. This bibliometric study was conducted on a global scale to quantify the impact of the COVID-19 pandemic on air pollution, identify the emerging challenges, and discuss the future perspectives during the course of the ongoing COVID-19 pandemic. For this, we have estimated the scientific production trends between 2020 and 2021 and investigated the contributions of countries, institutions, authors, and most prominent journals metrics network analysis on the topic of COVID-19 combined with air pollution research spanning the period between January 01, 2020, and June 21, 2021. The search strategy retrieved a wide range of 2003 studies published in scientific journals from the Web of Sciences Core Collection (WoSCC). The findings indicated that (1) publications on COVID-19 pandemic and air pollution were 990 (research articles) in 2021 with 1870 citations; however, the year 2020 witnessed only 830 research articles with a large number 16,600 of citations. (2) China ranked first in the number of publications (n = 365; 18.22% of the global output) and was the main country in international cooperation network, followed by the USA (n = 278; 13.87% of the global output) and India (n = 216; 10.78 of the total articles). (3) By exploring the co-occurrence and links strengths of keywords "COVID-19" (1075; 1092), "air pollution" (286; 771), "SARS-COV-2" (252; 1986). (4) The lessons deduced from the COVID-19 pandemic provide defined measures to reduce air pollution globally. The outcomes of the present study also provide useful guidelines for future research programs and constitute a baseline for researchers in the domain of environmental and health sciences to estimate the potential impact of the COVID-19 pandemic on air pollution.
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Affiliation(s)
- Khalid Mehmood
- Key Laboratory of Meteorological Disaster, Ministry of Education (KLME), Joint International Research Laboratory of Climate and Environment Change (ILCEC)/Collaborative Innovation Center On Forecast and Evaluation of Meteorological Disasters (CIC-FEMD)/CMA Key Laboratory for Aerosol-Cloud-Precipitation, Nanjing University of Information Science & Technology, Nanjing, 210044, China
- School of Atmospheric Physics, Nanjing University of Information Science & Technology, Nanjing, 210044, China
- School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, Nanjing, 210044, China
| | | | - Yansong Bao
- Key Laboratory of Meteorological Disaster, Ministry of Education (KLME), Joint International Research Laboratory of Climate and Environment Change (ILCEC)/Collaborative Innovation Center On Forecast and Evaluation of Meteorological Disasters (CIC-FEMD)/CMA Key Laboratory for Aerosol-Cloud-Precipitation, Nanjing University of Information Science & Technology, Nanjing, 210044, China.
- School of Atmospheric Physics, Nanjing University of Information Science & Technology, Nanjing, 210044, China.
| | - Sadia Bibi
- Institute of Soil and Environmental Sciences, University of Agriculture Faisalabad, Faisalabad, 38040, Pakistan
| | - Muhammad Yaseen
- Faculty of Sciences, Department of Mathematics and Statistics, University of Agriculture Faisalabad, Faisalabad, 38040, Pakistan
| | - Muhammad Ajmal Khan
- Deanship of Library Affairs, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia
| | - Muhammad Mohsin Abrar
- College of Resources and Environment, Zhongkai University of Agriculture and Engineering, 510225, Guangzhou, China
- Engineering and Technology Research Center for Agricultural Land Pollution and Integrated Prevention, Guangzhou, China
| | - Zaid Ulhassan
- Institute of Crop Sciences, Ministry of Agriculture and Rural Affairs, Laboratory of Spectroscopy Sensing, Zhejiang University, Hangzhou, 310058, China
| | - Shah Fahad
- Hainan Key Laboratory for Sustainable Utilization of Tropical Bioresource, College of Tropical Crops, Hainan University, Haikou, 570228, Hainan, China.
- Department of Agronomy, University of Haripur, Haripur, Khyber Pakhtunkhwa, Pakistan.
| | - George P Petropoulos
- Department of Geography, Harokopio University of Athens, El. Venizelou 70, 17671, Kallithea, Athens, Greece
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Impact Of Covid-19 Transport Restrictions On Ambient Air Pollutant Concentrations And Asthma-Related Hospital Admissions. Public Health 2022; 211:66-71. [PMID: 36029546 PMCID: PMC9289007 DOI: 10.1016/j.puhe.2022.07.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2022] [Revised: 07/06/2022] [Accepted: 07/08/2022] [Indexed: 11/22/2022]
Abstract
Objectives Exposure to air pollution is a known risk factor for asthma exacerbations and hospitalisations. This study aimed to identify if COVID-19 transport restrictions led to improvements in air quality in Dublin and if this had an impact on asthma-related hospital admissions. Study design This was a population-based retrospective cohort study. Methods Daily concentration levels of particulate matter (PM2.5 and PM10) and nitrogen dioxide (NO2) were obtained from the Environmental Protection Agency (EPA). The Hospital In-Patient Enquiry (HIPE) system provided the daily number of asthma-related hospital admissions in Dublin. The figures for 2018–2019 were compared with the period of transport restrictions (from March 2020). Results During the period of transport restrictions, there was a significant decrease in mean daily concentrations in both PM2.5 (8.9 vs 7.8 μg/m3, P = 0.002) and NO2 (24.0 vs 16.7 μg/m3, P < 0.001). There was also a significant reduction in the mean number of daily asthma admissions (4.5 vs 2.8 admissions, P < 0.001). Only NO2 showed a statistically significant correlation with asthma admissions (r = 0.132, P < 0.001). Conclusion Transport restrictions introduced to mitigate against COVID-19 led to lower pollutant levels and improved air quality. Previously described associations between pollutants and asthma would indicate that these improvements in air quality contributed to the reduction in asthma-related admissions. The complex nature of PM is the likely explanation for the lack of correlation between its concentration and asthma admissions, unlike NO2 whose primary source is vehicular emissions. Public Health needs to advocate for transport policies, which can improve air quality and hence improve human health.
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The Impact of COVID-19 Control Measures on Air Quality in Guangdong Province. SUSTAINABILITY 2022. [DOI: 10.3390/su14137853] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/10/2022]
Abstract
COVID-19 control measures had a significant social and economic impact in Guangdong Province, and provided a unique opportunity to assess the impact of human activities on air quality. Based on the monitoring data of PM2.5, PM10, NO2, and O3 concentrations from 101 air quality monitoring stations in Guangdong Province from October 2019 to April 2020, the PSCF (potential source contribution factor) analysis and LSTM (long short-term memory) neural network were applied to explore the impact of epidemic control measures on air quality in Guangdong Province. Results showed that during the lockdown, the average concentration of PM2.5, PM10, NO2, and O3 decreased by 37.84%, 51.56%, 58.82%, and 24.00%, respectively. The ranges of potential sources of pollutants were reduced, indicating that air quality in Guangdong Province improved significantly. The Pearl River Delta, characterized by a high population density, recorded the highest NO2 concentration values throughout the whole study period. Due to the lockdown, the areas with the highest concentrations of O3, PM2.5, and PM10 changed from the Pearl River Delta to the eastern and western Guangdong. Moreover, LSTM simulation results showed that the average concentration of PM2.5, PM10, NO2, and O3 decreased by 46.34%, 54.56%, 70.63%, and 26.76%, respectively, which was caused by human-made impacts. These findings reveal the remarkable impact of human activities on air quality and provide effective theoretical support for the prevention and control of air pollution in Guangdong Province.
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O'Leary H, Parr S, El-Sayed MMH. The breathing human infrastructure: Integrating air quality, traffic, and social media indicators. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 827:154209. [PMID: 35240171 DOI: 10.1016/j.scitotenv.2022.154209] [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: 12/07/2021] [Revised: 02/17/2022] [Accepted: 02/24/2022] [Indexed: 06/14/2023]
Abstract
Outdoor air pollution is a complex system that is responsible for the deaths of millions of people annually, yet the integration of interdisciplinary data necessary to assess air quality's multiple metrics is still lacking. This case study integrates atmospheric indicators (concentrations of criteria pollutants including particulate matter and gaseous pollutants), traffic indicators (permanent traffic monitoring station data), and social indicators (community responses in Twitter archives) representing the interplay of the three critical pillars of the United Nations' Triple Bottom Line: environment, economy, and society. During the watershed moment of the COVID-19 pandemic lockdowns in Florida, urban centers demonstrated the gaps and opportunities for understanding the relationships, through correlations rather than causations, between urban air quality, traffic emissions, and public perceptions. The relationship between the perception and the traffic variables were strongly correlated, however no correlation was observed between the perception and actual air quality indicators, except for NO2. These observations might consequently infer that traffic serves as people's proxy for air quality, regardless of actual air quality, suggesting that social media messaging around asthma may be a way to monitor traffic patterns in areas where no infrastructure currently exists or is prohibited to build. It also indicates that people are less likely to be reliable sensors to accurately measure air quality due to bias in their observations of traffic volume and/or confirmation biases in broader social discourse. Results presented herein are of significance in demonstrating the capacity for interdisciplinary studies to consider the predictive capacities of social media and air pollution, its use as both lever and indicator of public support for air quality legislation and clean-air transitions, and its ability to overcome limitations of surface monitoring stations.
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Affiliation(s)
- Heather O'Leary
- Department of Anthropology, University of South Florida, St. Petersburg, FL 33701, USA
| | - Scott Parr
- Department of Civil Engineering, Embry-Riddle Aeronautical University, Daytona Beach, FL 32114, USA
| | - Marwa M H El-Sayed
- Department of Civil Engineering, Embry-Riddle Aeronautical University, Daytona Beach, FL 32114, USA.
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Azad S, Ghandehari M. Emissions of nitrogen dioxide in the northeast U.S. during the 2020 COVID-19 lockdown. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2022; 312:114902. [PMID: 35364514 PMCID: PMC9758611 DOI: 10.1016/j.jenvman.2022.114902] [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: 08/01/2021] [Revised: 03/08/2022] [Accepted: 03/13/2022] [Indexed: 06/14/2023]
Abstract
We have quantified the emissions of Nitrogen dioxide (NO2) in the Northeast megalopolis of the United States during the COVID-19 lockdown. The measurement of NO2 emission serves as the indicator for the emission of the group of nitrogen oxides (NOx). Approximately 56% of NO2 emissions in the US are from mobile sources, and the remainder is from stationary sources. Since 2002, clean air regulations have resulted in approximately 5% compound annual reduction of NOx emissions in the US (8.2% in the study area). Therefore, when studying the impact of sporadic events like an epidemic on emissions, it is necessary to account for the persistent reduction of emissions due to policy driven emission reduction measures. Using spaceborne sensors, ground monitors, National Emission Inventory data, and the US Motor Vehicle Emission Simulator, we quantified the reduction of total NOx emissions, distinguishing stationary sources from on-road mobile sources (trucks and automobiles). When considering total NOx emissions (stationary and mobile combined), we find that the pandemic restrictions resulted in 3.4% reduction of total NOx emissions in the study area in 2020. This is compared to (and in addition to) the expected 8.2% policy driven reduction of NOx emissions in 2020. This somewhat low reduction of emissions is because most stationary sources (factories, power plants, etc.) were operational during the pandemic. Truck traffic, a significant source of mobile emissions, also did not decline significantly (average 4.8% monthly truck traffic reduction in the study area between March and August 2020), as they were delivering goods during the lockdown. On the other hand, automobile traffic, responsible for 24% of total NOx emissions, dropped significantly, 52% in April, returning to near normal after 5 months. While the reduction of automobile traffic was significant, especially in the early months of the pandemic, its effect on emissions was relatively insignificant.
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Affiliation(s)
- Shams Azad
- New York University, Tandon School of Engineering, Department of Civil and Urban Engineering, 6 MetroTech Center, Brooklyn, NY, 11201, USA.
| | - Masoud Ghandehari
- New York University, Tandon School of Engineering, Department of Civil and Urban Engineering, 6 MetroTech Center, Brooklyn, NY, 11201, USA.
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Ghanim MS, Muley D, Kharbeche M. ANN-Based traffic volume prediction models in response to COVID-19 imposed measures. SUSTAINABLE CITIES AND SOCIETY 2022; 81:103830. [PMID: 35291578 PMCID: PMC8906893 DOI: 10.1016/j.scs.2022.103830] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/09/2021] [Revised: 02/21/2022] [Accepted: 03/08/2022] [Indexed: 05/14/2023]
Abstract
Many countries around the globe have imposed several response measures to suppress the rapid spread of the COVID-19 pandemic since the beginning of 2020. These measures have impacted routine daily activities, along with their impact on economy, education, social and recreational activities, and domestic and international travels. Intuitively, the different imposed policies and measures have indirect impacts on urban traffic mobility. As a result of those imposed measures and policies, urban traffic flows have changed. However, those impacts are neither measured nor quantified. Therefore, estimating the impact of these combined yet different policies and measures on urban traffic flows is a challenging task. This paper demonstrates the development of an artificial neural networks (ANN) model which correlates the impact of the imposed response measure and other factors on urban traffic flows. The results show that the adopted ANN model is capable of mapping the complex relationship between traffic flows and the response measures with a high level of accuracy and good performance. The predicted values are closed to the observed ones. They are clustered around the regression line, with a coefficient of determination ( R 2 ) of 0.9761. Furthermore, the developed model can be generalized to determine the anticipated demand levels resulted from imposing any of the response measures in the post-pandemic era. This model can be used to manage traffic during mega-events. It can be also utilized for disaster or emergency situations, where traffic flow estimates are highly required for operational and planning purposes.
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Affiliation(s)
| | - Deepti Muley
- Qatar Transportation and Traffic Safety Center, Department of Civil Engineering, Qatar University, P.O. Box 2713, Doha, Qatar
| | - Mohamed Kharbeche
- Qatar Transportation and Traffic Safety Center, Qatar University, P.O. Box 2713, Doha, Qatar
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Suresh S, Modi R, Sharma AK, Arisutha S, Sillanpää M. Pre-COVID-19 pandemic: effects on air quality in the three cities of India using fuzzy MCDM model. JOURNAL OF ENVIRONMENTAL HEALTH SCIENCE & ENGINEERING 2022; 20:41-51. [PMID: 34868597 PMCID: PMC8627843 DOI: 10.1007/s40201-021-00754-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/15/2021] [Accepted: 10/23/2021] [Indexed: 06/13/2023]
Abstract
Due to urbanization and industrialization pollution level increases. Air pollution directly affects to human health. Air Quality Indices (AQI) method is related to measuring the concentration of different pollutants PM10, NO2, SO2 and other pollutants. The fuzzy Logic air quality index calculates in single value of AQI defines limits 0 to 1. In this study, a comparison of air quality data of three cities was conducted with the help of fuzzy logic algorithm. It used to evaluating Indices through fuzzy multi criteria decision making (MCDM) framework in which linguistic terms of experts opinion and perception, accordingly computing matrix is constructed for sub criteria. There are five linguistic terms used in this framework to create membership functions such as high significant, significant, average significant, low significant and not significant. The three cities, Bangalore, Mysore, and Hubli-Dharwad air quality datas was taken for analysis and evaluating indices during pre-COVID years (2017, 2018, and 2019). The AQI value shows that Bangalore has the highest pollution level while Mysore has the lowest. Using the fuzzy theory, results show that Bangalore and Hubli-Dharwad decrease in pollution level by -0.074921% and -0.04797%. Negative sign shows the decrease pollution level while Mysore increase pollution level by 0.011792%. Overall the results show that AQI of Mysore city is low compared to Bangalore and Hubli-Dharwad. Also, this study reveals air quality disseminated through industrial processes and automobile emissions in India cities during pre-COVID pandemic years.
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Affiliation(s)
- S. Suresh
- Department of Chemical Engineering, Maulana Azad National Institute of Technology Bhopal, 462 003 Madhya Pradesh, India
| | - Rahul Modi
- Department of Civil Engineering, Maulana Azad National Institute of Technology Bhopal, 462 003 Madhya Pradesh, India
| | - A. K. Sharma
- Department of Civil Engineering, Maulana Azad National Institute of Technology Bhopal, 462 003 Madhya Pradesh, India
| | - S. Arisutha
- Energy Centre, Maulana Azad National Institute of Technology & Eco-Science and Technology, Bhopal-462 003, Madhya Pradesh, India
| | - Mika Sillanpää
- Institute of Research and Development, Duy Tan University, Da Nang, 550000 Vietnam
- Faculty of Environment and Chemical Engineering, Duy Tan University, Da Nang, 550000 Vietnam
- Department of Chemical Engineering, School of Mining, Metallurgy and Chemical Engineering, University of Johannesburg, P. O. Box 17011, Doornfontein, 2028 South Africa
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Sönmez VZ, Ayvaz C, Ercan N, Sivri N. Evaluation of Istanbul from the environmental components' perspective: what has changed during the pandemic? ENVIRONMENTAL MONITORING AND ASSESSMENT 2022; 194:462. [PMID: 35644795 PMCID: PMC9148846 DOI: 10.1007/s10661-022-10105-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/07/2022] [Accepted: 05/15/2022] [Indexed: 06/15/2023]
Abstract
This study aims to determine the 1-year change over the pandemic period in Istanbul, the megacity with the highest population in Turkey, based on environmental components. Among the environmental topics, water consumption habits, changes in air quality, changes due to noise elements, and most importantly, the changes in usage habits of disposable plastic materials that directly affect health have been revealed. The results obtained showed that, in Istanbul, 8.1 × 108 gloves should be considered waste, and considering the population living in districts along coastal areas, the number of waste masks that are likely to end up in the sea was 325.648 pieces/day. The results of the air quality and noise measurements during the pandemic showed that reductions in parallel with human activities were recorded with the lockdown effect. The average noise values of the districts along both sides of the Bosporus, where urbanization is concentrated, were between 50 and 59 dB. The precautions taken during the pandemic have had an effective role in reducing air pollution in Istanbul. In the measurements, the parameters with effective reductions were PM10 (7-47%), PM2.5 (13-48%), NO2 (13-38%), and SO2 (10-56%). As a result, Istanbul's year of changes during the pandemic period, in terms of water, air, noise, and solid plastic wastes, which are the most important components of the environment, is presented.
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Affiliation(s)
- Vildan Zülal Sönmez
- Department of Environmental Engineering, Istanbul University-Cerrahpasa, Istanbul, Turkey
| | - Coşkun Ayvaz
- Department of Environmental Engineering, Istanbul University-Cerrahpasa, Istanbul, Turkey
| | - Nevra Ercan
- Department of Chemical Engineering, Istanbul University-Cerrahpasa, Istanbul, Turkey
| | - Nüket Sivri
- Department of Environmental Engineering, Istanbul University-Cerrahpasa, Istanbul, Turkey
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41
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de Palma A, Vosough S, Liao F. An overview of effects of COVID-19 on mobility and lifestyle: 18 months since the outbreak. TRANSPORTATION RESEARCH. PART A, POLICY AND PRACTICE 2022; 159:372-397. [PMID: 35350704 PMCID: PMC8947947 DOI: 10.1016/j.tra.2022.03.024] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/26/2021] [Revised: 01/24/2022] [Accepted: 03/15/2022] [Indexed: 05/06/2023]
Abstract
The outbreak of SARS-COV-2 has led to the COVID-19 pandemic in March 2020 and caused over 4.5 million deaths worldwide by September 2021. Besides the public health crisis, COVID-19 affected the global economy and development significantly. It also led to changes in people's mobility and lifestyle during the COVID-19 pandemic. In addition to short-term changes, the drastic transformation of the world may account for the potentially disruptive long-term impacts. Recognizing the adverse effects of the COVID-19 pandemic is crucial in mitigating the negative behavioral changes that directly relate to people's psychological and social well-being. It is important to stress that citizens and governments face an uncertain situation since nobody knows exactly how the viruses and cures will develop. Better understanding uncertainties and evaluating behavioral changes contribute to addressing the future of urban development, public transportation, and behavioral strategies to tackle COVID-19 negative consequences. The major sources of impacts on short-term (route, departure time, mode, teleshopping, and teleworking) and medium and long-term (car ownership, work location, choice of job, and residential location) mobility decisions are mostly reviewed and discussed in this paper.
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Affiliation(s)
- André de Palma
- THEMA, Department of Economics, CY Cergy Paris Université, France
| | - Shaghayegh Vosough
- Spatial Planning and Transport Research Group, Aalto University, Finland
| | - Feixiong Liao
- Urban Planning and Transportation Group, Eindhoven University of Technology, the Netherlands
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Lange CL, Smith VA, Kahler DM. Pittsburgh Air Pollution Changes During the COVID-19 Lockdown. ENVIRONMENTAL ADVANCES 2022; 7:100149. [PMID: 34877562 PMCID: PMC8638247 DOI: 10.1016/j.envadv.2021.100149] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/18/2021] [Revised: 11/22/2021] [Accepted: 11/30/2021] [Indexed: 06/13/2023]
Abstract
The rapid spread of COVID-19 resulted in various public lockdowns across the globe. Previous studies showed that resultant travel restrictions improved air quality. The novel results presented here focus on source-specific changes and compare air quality for multiple years controlled for precipitation. This study sought to analyze air pollution changes in Pittsburgh, a city where an industrial past and present has led to elevated levels of particulate matter with representative diameter of ≤ 2.5μm (PM2.5). Data from the Allegheny County Health Department, from monitors located near a variety of site types, were analyzed with generalized linear models that used a gamma distribution with a log link to determine the magnitude and significance of changes in air pollution during the COVID-19 lockdown. The hypothesis was that nitrogen dioxide (NO2), which is primarily linked to vehicular traffic, would decrease significantly while potential decreases in particulate matter (PM2.5 and PM10) would be less apparent. Results of the regression models showed that NO2 was significantly reduced during lockdown at both monitoring sites and that PM10 was also significantly reduced at the majority of monitoring sites. However, decreases in PM2.5 pollution were only observed at half of the monitoring locations, and the location which observed the greatest decreases is located adjacent to an industrial source. Decreases in PM2.5 at this monitoring site were likely a result of reduced industrial processes both dependent and independent of the COVID-19 lockdown. This study suggests that industrial sources are a larger contributor of particulate matter than vehicular transportation in the city of Pittsburgh and that future air pollution reduction efforts should focus attention on emission reduction at these industrial facilities.
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Affiliation(s)
- Carissa L Lange
- Center for Environmental Research and Education, Duquesne University, 600 Forbes Ave. Pittsburgh, PA, 15282 USA
| | - Valerie A Smith
- Department of Population Health Sciences, Duke University, 215 Morris St. Durham, NC, 27708, USA
- Division of General Internal Medicine, Department of Medicine, Duke University, 200 Morris St. Durham, NC, 27708, USA
- Center of Innovation to Accelerate Discovery and Practice Transformation, Durham VAMC 508 Fulton St. Durham, NC, 27705, USA
| | - David M Kahler
- Center for Environmental Research and Education, Duquesne University, 600 Forbes Ave. Pittsburgh, PA, 15282 USA
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Wang W, Yang S, Yin K, Zhao Z, Ying N, Fan J. Network approach reveals the spatiotemporal influence of traffic on air pollution under COVID-19. CHAOS (WOODBURY, N.Y.) 2022; 32:041106. [PMID: 35489858 PMCID: PMC9058978 DOI: 10.1063/5.0087844] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/10/2022] [Accepted: 03/16/2022] [Indexed: 06/14/2023]
Abstract
Air pollution causes widespread environmental and health problems and severely hinders the quality of life of urban residents. Traffic is critical for human life, but its emissions are a major source of pollution, aggravating urban air pollution. However, the complex interaction between traffic emissions and air pollution in cities and regions has not yet been revealed. In particular, the spread of COVID-19 has led various cities and regions to implement different traffic restriction policies according to the local epidemic situation, which provides the possibility to explore the relationship between urban traffic and air pollution. Here, we explore the influence of traffic on air pollution by reconstructing a multi-layer complex network base on the traffic index and air quality index. We uncover that air quality in the Beijing-Tianjin-Hebei (BTH), Chengdu-Chongqing Economic Circle (CCS), and Central China (CC) regions is significantly influenced by the surrounding traffic conditions after the outbreak. Under different stages of the fight against the epidemic, the influence of traffic in some regions on air pollution reaches the maximum in stage 2 (also called Initial Progress in Containing the Virus). For the BTH and CC regions, the impact of traffic on air quality becomes bigger in the first two stages and then decreases, while for CC, a significant impact occurs in phase 3 among the other regions. For other regions in the country, however, the changes are not evident. Our presented network-based framework provides a new perspective in the field of transportation and environment and may be helpful in guiding the government to formulate air pollution mitigation and traffic restriction policies.
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Affiliation(s)
- Weiping Wang
- School of National Safety and Emergency
Management, Beijing Normal University, Zhuhai 519087,
China
| | | | - Kai Yin
- School of Traffic and Transportation, Beijing
Jiaotong University, Beijing 100044, China
| | - Zhidan Zhao
- China Complexity Computation Lab, Department of
Computer Science, School of Engineering, Shantou University, Shantou
515063, China
| | - Na Ying
- China State Key Laboratory of Environmental
Criteria and Risk Assessment, Chinese Research Academy of Environmental
Sciences, Beijing 100012, China
| | - Jingfang Fan
- School of Systems Science, Beijing Normal
University, Beijing 100875, China
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The Impact of COVID-19 Related Changes on Air Quality in Birmingham, Alabama, United States. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:ijerph19063168. [PMID: 35328857 PMCID: PMC8951610 DOI: 10.3390/ijerph19063168] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/12/2022] [Revised: 02/26/2022] [Accepted: 02/28/2022] [Indexed: 11/17/2022]
Abstract
Air pollution is responsible for a wide range of health effects in exposed populations. Variations in local air pollution can affect local population health outcomes. The strict regulations imposed during the peak of the COVID-19 pandemic ('lockdowns') resulted in a unique situation where human mobility was limited significantly, resulting in improved air quality in several major cities. The main goal of this study was to investigate if lockdowns during the COVID-19 pandemic significantly impacted air quality in Birmingham, Alabama-a city with a history of high air pollution levels-with a focus on PM2.5 (Particulate Matter with an aerodynamic diameter ≤2.5 µm) and NO2 (Nitrogen dioxide). Daily air pollutant and traffic data were obtained for the Birmingham Metropolitan Area for the period January to October 2020, and previous years. Mean PM2.5 and NO2 concentrations and traffic volumes during the official city/state lockdown period (24 March to 30 April 2020) were compared to pre- and post-lockdown means. The mean PM2.5 and NO2 concentrations during the lockdown did not significantly differ from that of the pre- or post-lockdown periods. However, NO2 significantly decreased even after the lockdown order was removed, with the mean decreasing significantly compared to pre-lockdown and lockdown periods. Both PM2.5 and NO2 annual means in 2020 were significantly lower than the annual means in 2019, indicating the occurrence of significant changes over the longer term that were not limited by defined lockdown periods. Traffic significantly increased after the lockdown order was removed but did not correlate with the two pollutants studied. Therefore, we conclude that the Stay at Home/lockdown regulations and other COVID-19 restrictions had an impact on the air quality of Birmingham Alabama; although these lockdown impacts varied for each pollutant and were not limited only by the official lockdown dates/periods.
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Efe B. Air quality improvement and its relation to mobility during COVID-19 lockdown in Marmara Region, Turkey. ENVIRONMENTAL MONITORING AND ASSESSMENT 2022; 194:255. [PMID: 35257238 PMCID: PMC8900962 DOI: 10.1007/s10661-022-09889-7] [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: 06/26/2021] [Accepted: 02/17/2022] [Indexed: 06/03/2023]
Abstract
The outbreak of the novel coronavirus SARS-CoV-2 (hereafter COVID-19) has changed the daily routines of people around the world. When the first case was confirmed on 11 March 2020 in Turkey, the number of cases reached 4500 per day by 10 April in Turkey. Afterwards, the government declared more restrictive lockdown measures for 31 metropolitan cities starting 10 April, and it was implemented for the following weekends, national, and religious holidays. The change in concentrations of PM10, PM2.5, and NO2 during these measures with respect to the pre-lockdown period, the same period in the previous years and for different levels of measures for the cities in the Marmara Region of Turkey was investigated in this study. The daily mean concentrations of PM10, PM2.5, and NO2 obtained from 11 stations operated by the Ministry of Environment and Urbanization and Google mobility data are used in this study. Average PM2.5 and NO2 concentrations during the lockdown period declined with respect to the pre-lockdown period and the previous year for all stations. Average PM10 concentrations during the lockdown of 8 of 11 stations declined, while the rest of the stations increased with respect to the pre-lockdown period. In 9 of the 11 stations, the average concentration of PM10 decreased compared to the previous four years. In 7 of the 11 stations, the number of days exceeding WHO limit for PM10 was decreased during the lockdown period with respect to the pre-lockdown period. For PM2.5, the number of days exceeding WHO limit was decreased during the lockdown period compared to the pre-lockdown period for all the stations. For NO2, the number of days exceeding WHO limit was decreased during the lockdown period compared to the pre-lockdown period for 7 of the 8 stations. There is a significant relationship between mobility decrease and NO2 concentrations in large cities. The correlation coefficients are generally lower in small cities in the study region.
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Affiliation(s)
- Bahtiyar Efe
- Department of Meteorological Engineering, University of Samsun, 19 Mayis, Samsun, Turkey.
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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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Ghahremanloo M, Lops Y, Choi Y, Jung J, Mousavinezhad S, Hammond D. A comprehensive study of the COVID-19 impact on PM 2.5 levels over the contiguous United States: A deep learning approach. ATMOSPHERIC ENVIRONMENT (OXFORD, ENGLAND : 1994) 2022; 272:118944. [PMID: 35043042 PMCID: PMC8758197 DOI: 10.1016/j.atmosenv.2022.118944] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/25/2021] [Revised: 12/26/2021] [Accepted: 01/05/2022] [Indexed: 05/21/2023]
Abstract
We investigate the impact of the COVID-19 outbreak on PM2.5 levels in eleven urban environments across the United States: Washington DC, New York, Boston, Chicago, Los Angeles, Houston, Dallas, Philadelphia, Detroit, Phoenix, and Seattle. We estimate daily PM2.5 levels over the contiguous U.S. in March-May 2019 and 2020, and leveraging a deep convolutional neural network, we find a correlation coefficient, an index of agreement, a mean absolute bias, and a root mean square error of 0.90 (0.90), 0.95 (0.95), 1.34 (1.24) μg/m3, and 2.04 (1.87) μg/m3, respectively. Results from Google Community Mobility Reports and estimated PM2.5 concentrations show a greater reduction of PM2.5 in regions with larger decreases in human mobility and those in which individuals remain in their residential areas longer. The relationship between vehicular PM2.5 (i.e., the ratio of vehicular PM2.5 to other sources of PM2.5) emissions and PM2.5 reductions (R = 0.77) in various regions indicates that regions with higher emissions of vehicular PM2.5 generally experience greater decreases in PM2.5. While most of the urban environments ⸺ Washington DC, New York, Boston, Chicago, Los Angeles, Houston, Dallas, Philadelphia, Detroit, and Seattle ⸺ show a decrease in PM2.5 levels by 21.1%, 20.7%, 18.5%, 8.05%, 3.29%, 3.63%, 6.71%, 4.82%, 13.5%, and 7.73%, respectively, between March-May of 2020 and 2019, Phoenix shows a 5.5% increase during the same period. Similar to their PM2.5 reductions, Washington DC, New York, and Boston, compared to other cities, exhibit the highest reductions in human mobility and the highest vehicular PM2.5 emissions, highlighting the great impact of human activity on PM2.5 changes in eleven regions. Moreover, compared to changes in meteorological factors, changes in pollutant concentrations, including those of black carbon, organic carbon, SO2, SO4, and especially NO2, appear to have had a significantly greater impact on PM2.5 changes during the study period.
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Affiliation(s)
- Masoud Ghahremanloo
- Department of Earth and Atmospheric Sciences, University of Houston, Houston, TX, 77004, USA
| | - Yannic Lops
- Department of Earth and Atmospheric Sciences, University of Houston, Houston, TX, 77004, USA
| | - Yunsoo Choi
- Department of Earth and Atmospheric Sciences, University of Houston, Houston, TX, 77004, USA
| | - Jia Jung
- Department of Earth and Atmospheric Sciences, University of Houston, Houston, TX, 77004, USA
| | - Seyedali Mousavinezhad
- Department of Earth and Atmospheric Sciences, University of Houston, Houston, TX, 77004, USA
| | - Davyda Hammond
- Oak Ridge Associated Universities, Oak Ridge, TN, 37830, USA
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48
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Aragão DP, Oliveira EV, Bezerra AA, Dos Santos DH, da Silva Junior AG, Pereira IG, Piscitelli P, Miani A, Distante C, Cuno JS, Conci A, Gonçalves LMG. Multivariate data driven prediction of COVID-19 dynamics: Towards new results with temperature, humidity and air quality data. ENVIRONMENTAL RESEARCH 2022; 204:112348. [PMID: 34767822 PMCID: PMC8577104 DOI: 10.1016/j.envres.2021.112348] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/11/2021] [Revised: 11/01/2021] [Accepted: 11/02/2021] [Indexed: 05/14/2023]
Abstract
Since the start of the COVID-19 pandemic many studies investigated the correlation between climate variables such as air quality, humidity and temperature and the lethality of COVID-19 around the world. In this work we investigate the use of climate variables, as additional features to train a data-driven multivariate forecast model to predict the short-term expected number of COVID-19 deaths in Brazilian states and major cities. The main idea is that by adding these climate features as inputs to the training of data-driven models, the predictive performance improves when compared to equivalent single input models. We use a Stacked LSTM as the network architecture for both the multivariate and univariate model. We compare both approaches by training forecast models for the COVID-19 deaths time series of the city of São Paulo. In addition, we present a previous analysis based on grouping K-means on AQI curves. The results produced will allow achieving the application of transfer learning, once a locality is eventually added to the task, regressing out using a model based on the cluster of similarities in the AQI curve. The experiments show that the best multivariate model is more skilled than the best standard data-driven univariate model that we could find, using as evaluation metrics the average fitting error, average forecast error, and the profile of the accumulated deaths for the forecast. These results show that by adding more useful features as input to a multivariate approach could further improve the quality of the prediction models.
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Affiliation(s)
- Dunfrey P Aragão
- Universidade Federal do Rio Grande do Norte, Av. Salgado Filho, Campus Universitário, 59.078-970, Natal, 3000, Brazil
| | - Emerson V Oliveira
- Universidade Federal do Rio Grande do Norte, Av. Salgado Filho, Campus Universitário, 59.078-970, Natal, 3000, Brazil
| | - Arthur A Bezerra
- Universidade Federal do Rio Grande do Norte, Av. Salgado Filho, Campus Universitário, 59.078-970, Natal, 3000, Brazil
| | - Davi H Dos Santos
- Universidade Federal do Rio Grande do Norte, Av. Salgado Filho, Campus Universitário, 59.078-970, Natal, 3000, Brazil
| | | | - Igor G Pereira
- Universidade Federal do Rio Grande do Norte, Av. Salgado Filho, Campus Universitário, 59.078-970, Natal, 3000, Brazil
| | | | - Alessandro Miani
- Department of Environmental Science and Policy, University of Milan, Milan, Italy
| | - Cosimo Distante
- Institute of Applied Sciences and Intelligent Systems, via Monteroni sn, 73100, Lecce, Italy
| | - Jordan S Cuno
- Universidade Federal Fluminense, Av. Gal. Milton Tavares de Souza, s/n, São Domingos, 24.210-346, Niteroi, Brazil
| | - Aura Conci
- Universidade Federal Fluminense, Av. Gal. Milton Tavares de Souza, s/n, São Domingos, 24.210-346, Niteroi, Brazil
| | - Luiz M G Gonçalves
- Universidade Federal do Rio Grande do Norte, Av. Salgado Filho, Campus Universitário, 59.078-970, Natal, 3000, Brazil.
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Mondal S, Chaipitakporn C, Kumar V, Wangler B, Gurajala S, Dhaniyala S, Sur S. COVID-19 in New York state: Effects of demographics and air quality on infection and fatality. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 807:150536. [PMID: 34628294 PMCID: PMC8461036 DOI: 10.1016/j.scitotenv.2021.150536] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/10/2021] [Revised: 07/28/2021] [Accepted: 09/19/2021] [Indexed: 05/07/2023]
Abstract
The coronavirus disease 2019 (COVID-19) has had a global impact that has been unevenly distributed among and even within countries. Multiple demographic and environmental factors have been associated with the risk of COVID-19 spread and fatality, including age, gender, ethnicity, poverty, and air quality among others. However, specific contributions of these factors are yet to be understood. Here, we attempted to explain the variability in infection, death, and fatality rates by understanding the contributions of a few selected factors. We compared the incidence of COVID-19 in New York State (NYS) counties during the first wave of infection and analyzed how different demographic and environmental variables associate with the variation observed across the counties. We observed that infection and death rates, two important COVID-19 metrics, to be highly correlated with both being highest in counties located near New York City, considered as one of the epicenters of the infection in the US. In contrast, disease fatality was found to be highest in a different set of counties despite registering a low infection rate. To investigate this apparent discrepancy, we divided the counties into three clusters based on COVID-19 infection, death, or fatality, and compared the differences in the demographic and environmental variables such as ethnicity, age, population density, poverty, temperature, and air quality in each of these clusters. Furthermore, a regression model built on this data reveals PM2.5 and distance from the epicenter are significant risk factors for infection, while disease fatality has a strong association with age and PM2.5. Our results demonstrate that for the NYS, demographic components distinctly associate with specific aspects of COVID-19 burden and also highlight the detrimental impact of poor air quality. These results could help design and direct location-specific control and mitigation strategies.
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Affiliation(s)
- Sumona Mondal
- Department of Mathematics, Clarkson University, Potsdam, NY, USA
| | | | - Vijay Kumar
- Department of Mathematics, Clarkson University, Potsdam, NY, USA
| | - Bridget Wangler
- David D. Reh School of Business, Clarkson University, Potsdam, NY, USA
| | | | - Suresh Dhaniyala
- Department of Mechanical and Aeronautical Engineering, Clarkson University, Potsdam, NY, USA
| | - Shantanu Sur
- Department of Biology, Clarkson University, Potsdam, NY, USA.
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50
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Saha L, Kumar A, Kumar S, Korstad J, Srivastava S, Bauddh K. The impact of the COVID-19 lockdown on global air quality: A review. ENVIRONMENTAL SUSTAINABILITY (SINGAPORE) 2022; 5:5-23. [PMID: 37519773 PMCID: PMC8819204 DOI: 10.1007/s42398-021-00213-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/21/2020] [Revised: 11/08/2021] [Accepted: 12/26/2021] [Indexed: 11/29/2022]
Abstract
The coronavirus disease 2019 (COVID-19) was declared a pandemic by the World Health Organization (WHO) on March 11, 2020. As a preventive measure, the majority of countries adopted partial or complete lockdown to fight the novel coronavirus. The lockdown was considered the most effective tool to break the spread of the coronavirus infection worldwide. Although lockdown damaged national economies, it has given a new dimension and opportunity to reduce environmental contamination, especially air pollution. In this study, we reviewed, analyzed and discussed the available recent literature and highlighted the impact of lockdown on the level of prominent air pollutants and consequent effects on air quality. The levels of air contaminants like nitrogen dioxide (NO2), sulphur dioxide (SO2), carbon monoxide (CO), and particulate matter (PM) decreased globally compared to levels in the past few decades. In many megacities of the world, the concentration of PM and NO2 declined by > 60% during the lockdown period. The air quality index (AQI) also improved substantially throughout the world during the lockdown. Overall, the air quality of many urban areas improved slightly to significantly during the lockdown period. It has been observed that COVID-19 transmission and mortality rate also decreased in correlation to reduced pollution level in many cities.
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Affiliation(s)
- Lala Saha
- Department of Environmental Sciences, Central University of Jharkhand, Ranchi, 835205 India
| | - Amit Kumar
- Department of Botany, Lucknow University, Lucknow, 226007 India
| | - Sanjeev Kumar
- Department of Environmental Sciences, Central University of Jharkhand, Ranchi, 835205 India
| | - John Korstad
- Department of Biology and Global Environmental Sustainability, Oral Roberts University, Tulsa, OK 74171 USA
| | - Sudhakar Srivastava
- Plant Stress Biology Laboratory, Institute of Environment and Sustainable Development, Banaras Hindu University, Varanasi, 221005 India
| | - Kuldeep Bauddh
- Department of Environmental Sciences, Central University of Jharkhand, Ranchi, 835205 India
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