Unprecedented Temporary Reduction in Global Air Pollution Associated with COVID-19 Forced Confinement: A Continental and City Scale Analysis

Impact of coronavirus-driven reduction in aerosols on precipitation in the western United States

Among the many impacts of COVID-19, the pandemic led to improved air quality conditions in the countries under quarantine due to the shutdown of industries, drastically reduced traffic, and lockdowns. Meanwhile, the western United States, particularly the coastal areas from Washington to California, received much less precipitation than normal during early 2020. Is it possible that this reduction in precipitation was driven by the reduced aerosols due to the coronavirus? Here we show that the reduction in aerosols resulted in higher temperatures (up to ∼0.5 °C) and generally lower snow amounts but cannot explain the observed low precipitation amounts over this region. In addition to an assessment of the effects of the coronavirus-related reduction in aerosols on precipitation across the western United States, our findings also provide basic information on the potential impacts different mitigation efforts aimed at reducing anthropogenic aerosols would have on the regional climate.

Concentration and size distribution of atmospheric particles in southern Italy during COVID-19 lockdown period

Many countries imposed lockdown (LD) to limit the spread of COVID-19, which led to a reduction in the emission of anthropogenic atmospheric pollutants. Several studies have investigated the effects of LD on air quality, mostly in urban settings and criteria pollutants. However, less information is available on background sites, and virtually no information is available on particle number size distribution (PNSD). This study investigated the effect of LD on air quality at an urban background site representing a near coast area in the central Mediterranean. The analysis focused on equivalent black carbon (eBC), particle mass concentrations in different size fractions: PM_2.5 (aerodynamic diameter D_a < 2.5 μm), PM₁₀ (D_a < 10 μm), PM_10-2.5 (2.5 < D_a < 10 μm); and PNSD in a wide range of diameters (0.01-10 μm). Measurements in 2020 during the national LD in Italy and period immediately after LD (POST-LD period) were compared with those in the corresponding periods from 2015 to 2019. The results showed that LD reduced the frequency and intensity of high-pollution events. Reductions were more relevant during POST-LD than during LD period for all variables, except quasi-ultrafine particles and PM_10-2.5. Two events of long-range transport of dust were observed, which need to be identified and removed to determine the effect of LD. The decreases in the quasi-ultrafine particles and eBC concentrations were 20%, and 15-22%, respectively. PM_2.5 concentration was reduced by 13-44% whereas PM_10-2.5 concentration was unaffected. The concentration of accumulation mode particles followed the behaviour of PM_2.5, with reductions of 19-57%. The results obtained could be relevant for future strategies aimed at improving air quality and understanding the processes that influence the number and mass particle size distributions.

Analysis of the meteorological factors affecting the short-term increase in O3 concentrations in nine global cities during COVID-19

Surface ozone (O3) is a major air pollutant around the world. This study investigated O3 concentrations in nine cities during the Coronavirus disease 2019 (COVID-19) lockdown phases. A statistical model, named Generalized Additive Model (GAM), was also developed to assess different meteorological factors, estimate daily O3 release during COVID-19 lockdown and determine the relationship between the two. We found that: (1) Daily O3 significantly increased in all selected cities during the COVID-19 lockdown, presenting relative increases from -5.7% (in São Paulo) to 58.9% (in Guangzhou), with respect to the average value for the same period in the previous five years. (2) In the GAM model, the adjusted coefficient of determination (R2) ranged from 0.48 (Sao Paulo) to 0.84 (Rome), and it captured 51-85% of daily O3 variations. (3) Analyzing the expected O3 concentrations during the lockdown, using GAM fed by meteorological data, showed that O3 anomalies were dominantly controlled by meteorology. (4) The relevance of different meteorological variables depended on the cities. The positive O3 anomalies in Beijing, Wuhan, Guangzhou, and Delhi were mostly associated with low relative humidity and elevated maximum temperature. Low wind speed, elevated maximum temperature, and low relative humidity were the leading meteorological factors for O3 anomalies in London, Paris, and Rome. The two other cities had different leading factor combinations.

Impact analysis of COVID-19 pandemic control measures on nighttime light and air quality in cities

The COVID-19 pandemic has profoundly affected human society on a global scale. COVID-19 pandemic control measures have led to significant changes in nighttime light (NTL) and air quality. Four cities that were severely impacted by the pandemic and that implemented different pandemic control measures, namely, Wuhan (China), Delhi (India), New York (United States), and Rome (Italy), were selected as study areas. The Visible Infrared Imaging Radiometer Suite (VIIRS) and air quality data were used to study the variation characteristics of NTL and air quality in the four cities in 2020. NTL brightness in Wuhan, Delhi, New York, and Rome decreased by 8.88%, 17.18%, 8.21%, and 6.33%, respectively, compared with pre-pandemic levels; in the resumption phase Wuhan and Rome NTL brightness recovered by 13.74% and 3.38%, but Delhi and New York decreased by 16.23% and 4.99%. Nitrogen dioxide (NO2) concentrations in the lockdown periods of Wuhan, Delhi, New York, and Rome decreased by 65.07%, 68.75%, 55.59%, and 56.81%, respectively; PM2.5 decreased by 49.25%, 69.40%, 52.54%, and 66.67%. Air quality improved, but ozone (O3) concentrations increased significantly during the lockdown periods. The methods presented herein can be used to investigate the impact of pandemic control measures on urban lights and air quality.

A review of the environmental implications of the COVID-19 pandemic in the United Arab Emirates

This paper reviews the environmental implications associated with the COVID-19 pandemic at the individual and community levels in the UAE. The positive effects emanating from the pandemic include improved air quality and reduced contamination of public spaces with pollutants. On the other hand, far-reaching negative effects include poor disposal of medical plastic waste and facemasks and the rise in unhygienic health practices amongst residents of UAE. The long-term ecological implications of the pandemic are still not well understood. The findings shed the light on the importance of addressing the consequences of the COVID-19 pandemic through preventative policies and strategies for better environmental health and readiness for future crises. Future research could assess the long-term environmental conse-quences of the pandemic on the UAE.

Machine Learning and Meteorological Normalization for Assessment of Particulate Matter Changes during the COVID-19 Lockdown in Zagreb, Croatia

In this paper, the authors investigated changes in mass concentrations of particulate matter (PM) during the Coronavirus Disease of 2019 (COVID-19) lockdown. Daily samples of PM1, PM2.5 and PM10 fractions were measured at an urban background sampling site in Zagreb, Croatia from 2009 to late 2020. For the purpose of meteorological normalization, the mass concentrations were fed alongside meteorological and temporal data to Random Forest (RF) and LightGBM (LGB) models tuned by Bayesian optimization. The models' predictions were subsequently de-weathered by meteorological normalization using repeated random resampling of all predictive variables except the trend variable. Three pollution periods in 2020 were examined in detail: January and February, as pre-lockdown, the month of April as the lockdown period, as well as June and July as the "new normal". An evaluation using normalized mass concentrations of particulate matter and Analysis of variance (ANOVA) was conducted. The results showed that no significant differences were observed for PM1, PM2.5 and PM10 in April 2020-compared to the same period in 2018 and 2019. No significant changes were observed for the "new normal" as well. The results thus indicate that a reduction in mobility during COVID-19 lockdown in Zagreb, Croatia, did not significantly affect particulate matter concentration in the long-term..

Characteristic changes of ozone and its precursors in London during COVID-19 lockdown and the ozone surge reason analysis

The London COVID-19 lockdown reduced emissions from anthropogenic sources, providing unique conditions for air contamination research. This research uses tropospheric ozone (O3), volatile organic compounds (VOCs) and NOx (NO+NO2) hourly monitoring data at the London Marylebone Road station from 2001 to 2020 to investigate the effects of lockdown on (O3) and its precursors. Both NOx and VOCs pollution showed a decreasing trend between 2001 and 2021, with a gradual increase in O3 in contrast. During the COVID-19 lockdown period (from 23rd March to July 4, 2020), there was a surge in O3 concentration, accompanied by a sharp reduction in NOx concentrations. Because all the monitoring VOCs/NOx results were less than eight during the lockdown, indicating that O3 formation in urban London was in the VOC-limited regime. The rapid increase in O3 concentrations caused by the lockdown was closely related to the rapid decrease in NOx emissions.

Temporal air quality (NO2, O3, and PM10) changes in urban and rural stations in Catalonia during COVID-19 lockdown: an association with human mobility and satellite data

In this study, changes in air quality by NO₂, O₃, and PM₁₀ in Barcelona metropolitan area and other parts of Catalonia during the COVID-19 lockdown with respect to pre-lockdown and to previous years (2018 and 2019) were evaluated. Selected air monitoring stations included 3 urban (Gràcia, Vall d'Hebron, and Granollers), 1 control site (Fabra Observatory), 1 semi-urban (Manlleu), and 3 rural (Begur, Bellver de Cerdanya, and Juneda). NO₂ lockdown levels showed a diminution, which in relative terms was maximum in two rural stations (Bellver de Cerdanya, - 63% and Begur, - 61%), presumably due to lower emissions from the ceasing hotel and ski resort activities during eastern holidays. In absolute terms and from an epidemiologic perspective, decrease in NO₂, also reinforced by the high amount of rainfall registered in April 2020, was more relevant in the urban stations around Barcelona. O₃ levels increased in the transited urban stations (Gràcia, + 42%, and Granollers, + 64%) due to the lower titration effect by NO_x. PM₁₀ lockdown levels decreased, mostly in Gràcia, Vall d'Hebron, and Granollers (- 35, - 39%, and - 39%, respectively) due to traffic depletion (- 90% in Barcelona's transport). Correlation among mobility index in Barcelona (- 100% in retail and recreation) and contamination was positive for NO₂ and PM₁₀ and negative for O₃ (P < 0.001). Satellite images evidenced two hotspots of NO₂ in Spain (Madrid and Barcelona) in April 2018 and 2019 that disappeared in 2020. Overall, the benefits of lockdown on air quality in Catalonia were evidenced with NO₂, O₃ and PM₁₀ levels below WHOAQG values in most of stations opposed to the excess registered in previous years.

First Chinese ultraviolet-visible hyperspectral satellite instrument implicating global air quality during the COVID-19 pandemic in early 2020

In response to the COVID-19 pandemic, governments worldwide imposed lockdown measures in early 2020, resulting in notable reductions in air pollutant emissions. The changes in air quality during the pandemic have been investigated in numerous studies via satellite observations. Nevertheless, no relevant research has been gathered using Chinese satellite instruments, because the poor spectral quality makes it extremely difficult to retrieve data from the spectra of the Environmental Trace Gases Monitoring Instrument (EMI), the first Chinese satellite-based ultraviolet-visible spectrometer monitoring air pollutants. However, through a series of remote sensing algorithm optimizations from spectral calibration to retrieval, we successfully retrieved global gaseous pollutants, such as nitrogen dioxide (NO2), sulfur dioxide (SO2), and formaldehyde (HCHO), from EMI during the pandemic. The abrupt drop in NO2 successfully captured the time for each city when effective measures were implemented to prevent the spread of the pandemic, for example, in January 2020 in Chinese cities, February in Seoul, and March in Tokyo and various cities across Europe and America. Furthermore, significant decreases in HCHO in Wuhan, Shanghai, Guangzhou, and Seoul indicated that the majority of volatile organic compounds (VOCs) emissions were anthropogenic. Contrastingly, the lack of evident reduction in Beijing and New Delhi suggested dominant natural sources of VOCs. By comparing the relative variation of NO2 to gross domestic product (GDP), we found that the COVID-19 pandemic had more influence on the secondary industry in China, while on the primary and tertiary industries in Korea and the countries across Europe and America.

Exposure Risk of Global Surface O3 During the Boreal Spring Season

Surface ozone (O₃) is an oxidizing gaseous pollutant; long-term exposure to high O₃ concentrations adversely affects human health. Based on daily surface O₃ concentration data, the spatiotemporal characteristics of O₃ concentration, exposure risks, and driving meteorological factors in 347 cities and 10 major countries (China, Japan, India, South Korea, the United States, Poland, Spain, Germany, France, and the United Kingdom) worldwide were analyzed using the MAKESENS model, Moran' I analysis, and Generalized additive model (GAM). The results indicated that: in the boreal spring season from 2015 to 2020, the global O₃ concentration exhibited an increasing trend at a rate of 0.6 μg/m³/year because of the volatile organic compounds (VOCs) and NOx changes caused by human activities. Due to the lockdown policies after the outbreak of COVID-19, the average O₃ concentration worldwide showed an inverted U-shaped growth during the study period, increasing from 21.9 μg/m³ in 2015 to 27.3 μg/m³ in 2019, and finally decreasing to 25.9 μg/m³ in 2020. According to exposure analytical methods, approximately 6.32% of the population (31.73 million people) in the major countries analyzed reside in rapidly increasing O₃ concentrations. 6.53% of the population (32.75 million people) in the major countries were exposed to a low O₃ concentration growth environment. Thus, the continuous increase of O₃ concentration worldwide is an important factor leading to increasing threats to human health. Further we found that mean wind speed, maximum temperature, and relative humidity are the main factors that determine the change of O₃ concentration. Our research results are of great significance to the continued implementation of strict air quality policies and prevention of population hazards. However, due to data limitations, this research can only provide general trends in O₃ and human health, and more detailed research will be carried out in the follow-up.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s12403-022-00463-7.

Meteorological Normalisation Using Boosted Regression Trees to Estimate the Impact of COVID-19 Restrictions on Air Quality Levels

The global COVID-19 pandemic that began in late December 2019 led to unprecedented lockdowns worldwide, providing a unique opportunity to investigate in detail the impacts of restricted anthropogenic emissions on air quality. A wide range of strategies and approaches exist to achieve this. In this paper, we use the "deweather" R package, based on Boosted Regression Tree (BRT) models, first to remove the influences of meteorology and emission trend patterns from NO, NO2, PM10 and O3 data series, and then to calculate the relative changes in air pollutant levels in 2020 with respect to the previous seven years (2013-2019). Data from a northern Spanish region, Cantabria, with all types of monitoring stations (traffic, urban background, industrial and rural) were used, dividing the calendar year into eight periods according to the intensity of government restrictions. The results showed mean reductions in the lockdown period above -50% for NOx, around -10% for PM10 and below -5% for O3. Small differences were found between the relative changes obtained from normalised data with respect to those from observations. These results highlight the importance of developing an integrated policy to reduce anthropogenic emissions and the need to move towards sustainable mobility to ensure safer air quality levels, as pre-existing concentrations in some cases exceed the safe threshold.

Air quality index variation before and after the onset of COVID-19 pandemic: a comprehensive study on 87 capital, industrial and polluted cities of the world

BACKGROUND

Coronavirus disease 2019 (COVID-19) pandemic provided an opportunity for the environment to reduce ambient pollution despite the economic, social and health disruption to the world. The purpose of this study was to investigate the changes in the air quality indexes (AQI) in industrial, densely populated and capital cities in different countries of the world before and after 2020. In this ecological study, we used AQI obtained from the free available databases such as the World Air Quality Index (WAQI). Bivariate correlation analysis was used to explore the correlations between meteorological and AQI variables. Mean differences (standard deviation: SD) of AQI parameters of different years were tested using paired-sample t-test or Wilcoxon signed-rank test as appropriate. Multivariable linear regression analysis was conducted to recognize meteorological variables affecting the AQI parameters.

RESULTS

AQI-PM2.5, AQI-PM10 and AQI-NO2 changes were significantly higher before and after 2020, simultaneously with COVID-19 restrictions in different cities of the world. The overall changes of AQI-PM2.5, AQI-PM10 and AQI-NO2 in 2020 were - 7.36%, - 17.52% and - 20.54% compared to 2019. On the other hand, these results became reversed in 2021 (+ 4.25%, + 9.08% and + 7.48%). In general, the temperature and relative humidity were inversely correlated with AQI-PM2.5, AQI-PM10 and AQI-NO2. Also, after adjusting for other meteorological factors, the relative humidity was inversely associated with AQI-PM2.5, AQI-PM10 and AQI-NO2 (β = - 1.55, β = - 0.88 and β = - 0.10, P < 0.01, respectively).

CONCLUSIONS

The results indicated that air quality generally improved for all pollutants except carbon monoxide and ozone in 2020; however, changes in 2021 have been reversed, which may be due to the reduction of some countries' restrictions. Although this quality improvement was temporary, it is an important result for planning to control environmental pollutants.

Google Earth Engine based spatio-temporal analysis of air pollutants before and during the first wave COVID-19 outbreak over Turkey via remote sensing

Air pollution is one of the vital problems for the sustainability of cities and public health. The lockdown caused by the COVID-19 outbreak has become a natural laboratory, enabling to investigate the impact of human/industrial activities on the air pollution. In this study, we investigated the spatio-temporal density of TROPOMI-based nitrogen dioxide (NO₂) and sulfur dioxide (SO₂) products, and MODIS-derived Aerosol Optical Depth (AOD) from January 2019 to September 2020 (also covering the first wave of the COVID-19) over Turkey using Google Earth Engine (GEE). The results showed a significant decrease in NO₂ and AOD, while SO₂ unchanged and had slightly higher concentrations in some regions during the lockdown compared to 2019. The relationship between air pollutants and meteorological parameters during the lockdown showed that air temperature and pressure were highly correlated with air pollutants, unlike precipitation and wind speed. Moreover, Purchasing Managers' Index (PMI) data, indicator of economic/industrial activities, also provided poor correlation with air pollutants. TROPOMI-based NO₂ and SO₂ were compared with station-based pollutants for three sites (suburban, urban, and urban-traffic classes) in Istanbul, revealing 0.83, 0.70 and 0.65 correlation coefficients for NO₂, respectively, while SO₂ showed no significant correlation. Besides, AOD data were validated using two AERONET sites providing 0.86 and 0.82 correlation coefficients. Overall, the satellite-based data provided significant outcomes for the spatio-temporal evaluation of air quality, especially during the first wave of the COVID-19 lockdown.

Situation of Urban Mobility in Pakistan: Before, during, and after the COVID-19 Lockdown with Climatic Risk Perceptions

The coronavirus pandemic (COVID-19) has impacted the usual global movement patterns, atmospheric pollutants, and climatic parameters. The current study sought to assess the impact of the COVID-19 lockdown on urban mobility, atmospheric pollutants, and Pakistan’s climate. For the air pollution assessment, total column ozone (O3), sulphur dioxide (SO2), and tropospheric column nitrogen dioxide (NO2) data from the Ozone Monitoring Instrument (OMI), aerosol optical depth (AOD) data from the Multi-angle Imaging Spectroradiometer (MISR), and dust column mass density (PM2.5) data from the MERRA-2 satellite were used. Furthermore, these datasets are linked to climatic parameters (temperature, precipitation, wind speed). The Kruskal–Wallis H test (KWt) is used to compare medians among k groups (k > 2), and the Wilcoxon signed-rank sum test (WRST) is for analyzing the differences between the medians of two datasets. To make the analysis more effective, and to justify that the variations in air quality parameters are due to the COVID-19 pandemic, a Generalized Linear Model (GLM) was used. The findings revealed that the limitations on human mobility have lowered emissions, which has improved the air quality in Pakistan. The results of the study showed that the climatic parameters (precipitation, Tmax, Tmin, and Tmean) have a positive correlation and wind speed has a negative correlation with NO2 and AOD. This study found a significant decrease in air pollutants (NO2, SO2, O3, AOD) of 30–40% in Pakistan during the strict lockdown period. In this duration, the highest drop of about 28% in NO2 concentrations has been found in Karachi. Total column O3 did not show any reduction during the strict lockdown, but a minor decline was depicted as 0.38% in Lahore and 0.55% in Islamabad during the loosening lockdown. During strict lockdown, AOD was reduced up to 23% in Islamabad and 14.46% in Lahore. The results of KWt and WRST evident that all the mobility indices are significant (p < 0.05) in nature. The GLM justified that restraining human activities during the lockdown has decreased anthropogenic emissions and, as a result, improved air quality, particularly in metropolitan areas.

The impact of stay-at-home orders on air-quality and COVID-19 mortality rate in the United States

Since the beginning of the pandemic in the U.S., most jurisdictions issued mitigation strategies, such as restricting businesses and population movements. This provided an opportunity to measure any positive implications on air quality and COVID-19 mortality rate during a time of limited social interactions. Four broad categories of stay-at-home orders (for states following the order for at least 40 days, for states with less than 40 days, for states with the advisory order, and the states with no stay-at-home order) were created to analyze change in air quality and mortality rate. Ground-based monitoring data for particulate matter (PM2.5, PM10), nitrogen dioxide (NO2), sulfur dioxide (SO2) and carbon monoxide (CO) was collected during the initial country-wide lockdown period (15 March-15 June 2020). Data on confirmed COVID-19 cases and deaths were also collected to analyze the effects of the four measures on the mortality trend. Findings show air quality improvement for the states staying under lockdown longer compared to states without a stay-at-home order. All stay-at-home order categories, except states without measures were observed a decrease in PM2.5 and the core-based statistical areas (CBSAs) within the longer mitigation states had an improvement of their air quality index (AQI).

Air Quality in the Italian Northwestern Alps during Year 2020: Assessment of the COVID-19 «Lockdown Effect» from Multi-Technique Observations and Models

The effect of COVID-19 confinement regulations on air quality in the northwestern Alps is assessed here based on measurements at five valley sites in different environmental contexts. Surface concentrations of nitrogen oxides (NO and NO2), ozone (O3), particulate matter (PM2.5 and PM10), together with a thorough microphysical (size), chemical, and optical (light absorption) aerosol characterisation, complemented by observations along the vertical column are considered. Even in the relatively pristine environment of the Alps, the «lockdown effect» is well discernible, both in the early confinement phase and in late 2020. The variations observed during the first confinement period in the city of Aosta (−61% NO, −43% NO2, +5% O3, +9% PM2.5, −12% PM10, relative to average 2015–2019 conditions) are attributed to the competing effects of air pollution lockdown-induced changes (−74%, −52%, +18%, −13%, −27%, relative to the counterfactual scenario for 2020 provided by a predictive statistical model trained on past measurements) and meteorology (+52%, +18%, −11%, +25%, +20%, relative to average conditions). These changes agree well with the ones obtained from a chemical transport model with modified emissions according to the restrictions. With regard to column-integrated quantities and vertical profiles, the NO2 column density decreases by >20% due to the lockdown, whereas tropospheric aerosols are mainly influenced by large-scale dynamics (transport of secondary particles from the Po basin and mineral dust from the Sahara desert and the Caspian Sea), except a shallow layer about 500 m thick close to the surface, possibly sensitive to curtailed emissions (especially exhaust and non-exhaust particles from road traffic and fugitive emissions from the industry).

Impact of COVID-19 lockdown upon the air quality and surface urban heat island intensity over the United Arab Emirates

The 2019 pandemic of Severe Acute Respiratory Syndrome-Corona Virus Diseases (COVID-19) has posed a substantial threat to public health and major global economic losses. The Northern Emirates of the United Arab Emirates (NEUAE) had imposed intense preventive lockdown measures. On the first of April 2020, a lockdown was implemented. It was assumed, due to lower emissions, that the air quality and Surface Urban Heat Island Intensity (SUHII) had been strengthened significantly. In this research, three parameters for Nitrogen Dioxide (NO2), Aerosol Optical Depth (AOD), and SUHII variables were examined through the NEUAE. we evaluated the percentage of the change in these parameters as revealed by satellite data for 2 cycles in 2019 (March 1st to June 30th) and 2020 (March 1st to June 30th). The core results showed that during lockdown periods, the average of NO2, AOD, and SUHII levels declined by 23.7%, 3.7%, and 19.2%, respectively, compared to the same period in 2019. Validation for results demonstrates a high agreement between the predicted and measured values. The agreement was as high as R2=0.7, R2=0.6, and R2=0.68 for NO2, AOD, and night LST, respectively, indicating significant positive linear correlations. The current study concludes that due to declining automobile and industrial emissions in the NEUAE, the lockdown initiatives substantially lowered NO2, AOD, and SUHII. In addition, the aerosols did not alter significantly since they are often linked to the natural occurrence of dust storms throughout this time of the year. The pandemic is likely to influence several policy decisions to introduce strategies to control air pollution and SUHII. Lockdown experiences may theoretically play a key role in the future as a possible solution for air pollution and SUHII abatement.

Impact of the Coronavirus Pandemic Lockdown on Atmospheric Nanoparticle Concentrations in Two Sites of Southern Italy

During the new coronavirus infection outbreak, the application of strict containment measures entailed a decrease in most human activities, with the consequent reduction of anthropogenic emissions into the atmosphere. In this study, the impact of lockdown on atmospheric particle number concentrations and size distributions is investigated in two different sites of Southern Italy: Lecce and Lamezia Terme, regional stations of the GAW/ACTRIS networks. The effects of restrictions are quantified by comparing submicron particle concentrations, in the size range from 10 nm to 800 nm, measured during the lockdown period and in the same period of previous years, from 2015 to 2019, considering three time intervals: prelockdown, lockdown and postlockdown. Different percentage reductions in total particle number concentrations are observed, −19% and −23% in Lecce and −7% and −4% in Lamezia Terme during lockdown and postlockdown, respectively, with several variations in each subclass of particles. From the comparison, no significant variations of meteorological factors are observed except a reduction of rainfall in 2020, which might explain the higher levels of particle concentrations measured during prelockdown at both stations. In general, the results demonstrate an improvement of air quality, more conspicuous in Lecce than in Lamezia Terme, during the lockdown, with a differed reduction in the concentration of submicronic particles that depends on the different types of sources, their distance from observational sites and local meteorology.

Global, continental, and national variation in PM2.5, O3, and NO2 concentrations during the early 2020 COVID-19 lockdown

Lockdowns implemented in response to COVID-19 have caused an unprecedented reduction in global economic and transport activity. In this study, variation in the concentration of health-threatening air pollutants (PM_2.5, NO₂, and O₃) pre- and post-lockdown was investigated at global, continental, and national scales. We analyzed ground-based data from >10,000 monitoring stations in 380 cities across the globe. Global-scale results during lockdown (March to May 2020) showed that concentrations of PM_2.5 and NO₂ decreased by 16.1% and 45.8%, respectively, compared to the baseline period (2015-2019). However, O₃ concentration increased by 5.4%. At the continental scale, concentrations of PM_2.5 and NO₂ substantially dropped in 2020 across all continents during lockdown compared to the baseline, with a maximum reduction of 20.4% for PM_2.5 in East Asia and 42.5% for NO₂ in Europe. The maximum reduction in O₃ was observed in North America (7.8%), followed by Asia (0.7%), while small increases were found in other continents. At the national scale, PM_2.5 and NO₂ concentrations decreased significantly during lockdown, but O₃ concentration showed varying patterns among countries. We found maximum reductions of 50.8% for PM_2.5 in India and 103.5% for NO₂ in Spain. The maximum reduction in O₃ (22.5%) was found in India. Improvements in air quality were temporary as pollution levels increased in cities since lockdowns were lifted. We posit that these unprecedented changes in air pollutants were mainly attributable to reductions in traffic and industrial activities. Column reductions could also be explained by meteorological variability and a decline in emissions caused by environmental policy regulations. Our results have implications for the continued implementation of strict air quality policies and emission control strategies to improve environmental and human health.

COVID-19 Pandemic and Environmental Health: Effects and the Immediate Need for a Concise Risk Analysis

COVID-19 pandemic, as another disease emerging in the interface between animals and humans, has revealed the importance of interdisciplinary collaborations such as the One Health initiative. Environmental Health, whose role in the One Health concept is well established, has been associated with COVID-19 pandemic via various direct and indirect pathways. Modern lifestyle, climate change, environmental degradation, exposure to chemicals such as endocrine disruptors, and exposure to psychological stress factors impact human health negatively. As a result, many people are in the disadvantageous position to face the pandemic with an already impaired immune system due to their exposure to environmental health hazards. Moreover, the ongoing pandemic has been associated with outdoor and indoor air pollution, water and noise pollution, food security, and plastic pollution issues. Also, the inadequate infrastructure, the lack of proper waste and wastewater management, and the unequal social vulnerability reveal more linkages between Environmental Health and COVID-19 pandemic. The significant emerging ecological risk and its subsequent health implications require immediate risk analysis and risk communication strategies.

Proposed Design of Walk-Through Gate (WTG): Mitigating the Effect of COVID-19

The world is facing a new challenge to overcome the pandemic disease of Coronavirus (COVID-19). An outbreak of COVID-19 to more than 213 countries and territories caused damage to the economy of every country. The proper vaccine to combat this pandemic disease is not invented yet. Due to the lockdown situation, there is a shortage of daily used products globally. To overcome the issue of food shortage and economic survival, the world has to ease the lockdown rules and become operational with the precautionary measures. COVID-19 has a fast transmission rate, therefore, while living with COVID-19, breaking the fast transmission chain of COVID-19 is the only vital solution. Furthermore, there is a dire need to disinfect every individual and his luggage at the entrance of every shopping mall, hospital, public and private institutions, bus stops, metro stations, and railway stations. Hence, the proposed walk-through gate (WTG) with different sensors, i.e., infrared thermal camera, UV disinfectant sensor, disinfectant spraying system, touch-less hand sanitizer, and box having a face mask with a dustbin to discard the previous mask can provide an effective and efficient relief. The world cannot stop working and cannot survive for more than 3–6 months in a lockdown, hence the proposed idea is to install the disinfectant automated spraying WTG with a security walk-through gate at every possible entrance to conform living with the COVID-19 disease such as many other diseases. Breaking the transmission chain is the only solution to win the battle against COVID-19 until an effective vaccine invention.

The Impacts of the COVID-19 Lockdown on Air Quality in the Guanzhong Basin, China

The Corona Virus Disease 2019 (COVID-19) appeared in Wuhan, China, at the end of 2019, spreading from there across China and within weeks across the whole world. In order to control the rapid spread of the virus, the Chinese government implemented a national lockdown policy. It restricted human mobility and non-essential economic activities, which, as a side effect, resulted in the reduction of the emission of pollutants and thus the improvement of the air quality in many cities in China. In this paper, we report on a study on the changes in air quality in the Guanzhong Basin during the COVID-19 lockdown period. We compared the concentrations of PM2.5, PM10, SO2, NO2, CO and O3 obtained from ground-based monitoring stations before and after the COVID-19 outbreak. The analysis confirmed that the air quality in the Guanzhong Basin was significantly improved after the COVID-19 outbreak. During the emergency response period with the strictest restrictions (Level-1), the concentrations of PM2.5, PM10, SO2, NO2 and CO were lower by 37%, 30%, 29%, 52% and 33%, respectively, compared with those before the COVID-19 outbreak. In contrast, O3 concentrations increased substantially. The changes in the pollutant concentrations varied between cities during the period of the COVID-19 pandemic. The highest O3 concentration changes were observed in Xi’an, Weinan and Xianyang city; the SO2 concentration decreased substantially in Tongchuan city; the air quality had improved the most in Baoji City. Next, to complement the sparsely distributed air quality ground-based monitoring stations, the geographic and temporally weighted regression (GTWR) model, combined with satellite observations of the aerosol optical depth (AOD) and meteorological factors was used to estimate the spatial and temporal distributions of PM2.5 and PM10 concentrations with a resolution of 6 km × 6 km before and after the COVID-19 outbreak. The model was validated by a comparison with ground-based observations from the air quality monitoring network in five cities in the Guanzhong Basin with excellent statistical metrics. For PM2.5 and PM10 the correlation coefficients R2 were 0.86 and 0.80, the root mean squared errors (RMSE) were 11.03 µg/m3 and 14.87 µg/m3 and the biases were 0.19 µg/m3 and −0.27 µg/m3, which led to the conclusion that the GTWR model could be used to estimate the PM concentrations in locations where monitoring data were not available. Overall, the PM concentrations in the Guanzhong Basin decreased substantially during the lockdown period, with a strong initial decrease and a slower one thereafter, although the spatial distributions remained similar.