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 PM, PM, SO, NO, CO and O 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 (R > 0.8 except for SO) to simulate the meteorological normalized business-as-usual concentration. The hybrid single-particle Lagrangian integrated trajectory (HYSPLIT) model simulated the fate of air pollutants ( local emissions or transboundary pollution) for anomalous months. The changes in different public transportation usage volumes ( roadway, railway, air, and waterway) moderately reduced air pollution, particularly CO and NO. 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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http://dx.doi.org/10.1016/j.jclepro.2022.132893 | DOI Listing |
PLoS One
January 2025
Escuela de Ingeniería Química, Pontificia Universidad Católica de Valparaíso, Valparaíso, Chile.
In this comprehensive analysis of Chile's air quality dynamics spanning 2016 to 2021, the utilization of data from the National Air Quality Information System (SINCA) and its network of monitoring stations was undertaken. Quintero, Puchuncaví, and Coyhaique were the focal points of this study, with the primary objective being the construction of predictive models for sulfur dioxide (SO2), fine particulate matter (PM2.5), and coarse particulate matter (PM10).
View Article and Find Full Text PDFMedicine (Baltimore)
January 2025
Centro Universitario de Enfermería Cruz Roja, University of Seville, Seville, Spain.
Background: There is an increased prevalence of mental health problems in various population groups as a result of the COVID-19 pandemic and its consequences, especially regarding anxiety, stress, depression, fear, and sleep disturbances, require to be investigated longitudinally.
Objective: This study aimed to determine the impact that the COVID-19 pandemic had on the mental health of Nursing students, as well as to examine other associated factors such as anxiety, fear, sleep disturbances, and coping strategies.
Method: This systematic review and meta-analysis were designed following the PRISMA guidelines and were registered in PROSPERO with code CRD42024541904.
Int J Environ Health Res
January 2025
Department of Oncology, Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China.
Environ Monit Assess
January 2025
Municipal Budgetary Educational Institution "Lyceum of the City of Yurga", St. Kirova, 7, Yurga, Kemerovo Region, 652055, Russia.
In Kemerovo Region (Kuzbass, Southwest Siberia), there is the largest coal basin in Russia and one of the largest in the world. Active moss biomonitoring was applied to assess the impact of potentially toxic elements on air pollution in five urban areas of the region. In each of the chosen urban regions, the moss bags were exposed in November and December of 2022 at locations with varying degrees of anthropogenic pressure.
View Article and Find Full Text PDFEnviron Monit Assess
January 2025
Laboratory for Ecotoxicology and Environmental Forensics, University of Benin, PMB 1154, Benin City, Nigeria.
This research was carried out to assess the concentrations of carbon monoxide (CO) and formaldehyde (HCHO) in Edo State, Southern Nigeria, using remote sensing data. A secondary data collection method was used for the assessment, and the levels of CO and HCHO were extracted annually from Google Earth Engine using information from Sentinel-5-P satellite data (COPERNISCUS/S5P/NRTI/L3_) and processed using ArcMap, Google Earth Engine, and Microsoft Excel to determine the levels of CO and HCHO in the study area from 2018 to 2023. The geometry of the study location is highlighted, saved and run, and a raster imagery file of the study area is generated after the task has been completed with a 'projection and extent' in the Geographic Tagged Image File Format (.
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