Amplified ozone pollution in cities during the COVID-19 lockdown

Air pollution and health impacts during the COVID-19 lockdowns in Grenoble, France

It is undeniable that exposure to outdoor air pollution impacts the health of populations and therefore constitutes a public health problem. Any actions or events causing variations in air quality have repercussions on populations' health. Faced with the worldwide COVID-19 health crisis that began at the end of 2019, the governments of several countries were forced, in the beginning of 2020, to put in place very strict containment measures that could have led to changes in air quality. While many works in the literature have studied the issue of changes in the levels of air pollutants during the confinements in different countries, very few have focused on the impact of these changes on health risks. In this work, we compare the 2020 period, which includes two lockdowns (March 16 - May 10 and a partial shutdown Oct. 30 - Dec. 15) to a reference period 2015-2019 to determine how these government-mandated lockdowns affected concentrations of NO₂, O₃, PM_2.5, and PM₁₀, and how that affected human health factors, including low birth weight, lung cancer, mortality, asthma, non-accidental mortality, respiratory, and cardiovascular illnesses. To this end, we structured 2020 into four periods, alternating phases of freedom and lockdowns characterized by a stringency index. For each period, we calculated (1) the differences in pollutant levels between 2020 and a reference period (2015-2019) at both background and traffic stations; and (2) the resulting variations in the epidemiological based relative risks of health outcomes. As a result, we found that relative changes in pollutant levels during the 2020 restriction period were as follows: NO₂ (-32%), PM_2.5 (-22%), PM₁₀ (-15%), and O₃ (+10.6%). The pollutants associated with the highest health risk reductions in 2020 were PM_2.5 and NO_2, while PM₁₀ and O₃ changes had almost no effect on health outcomes. Reductions in short-term risks were related to reductions in PM_2.5 (-3.2% in child emergency room visits for asthma during the second lockdown) and NO₂ (-1.5% in hospitalizations for respiratory causes). Long-term risk reductions related to PM_2.5 were low birth weight (-8%), mortality (-3.3%), and lung cancer (-2%), and to NO₂ for mortality (-0.96%). Overall, our findings indicate that the confinement period in 2020 resulted in a substantial improvement in air quality in the Grenoble area.

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..

Consequences of pre and post confinement on the atmospheric air pollutants during spread of COVID-19 in India

COVID-19, a severe respiratory syndrome, was diagnosed in Wuhan, China, and in the last week of January 2020, it was reported in India. The drastic speed of spreading of COVID-19 imposed a total lockdown in India for the first time in four stages. This leads to restrictions on transport, industries, coal-based power plants, etc. During these stages of lockdown, a detailed analysis was done to study the effect of confinement on various air pollutants, PM₁₀, PM_2.5, SO₂, CO, NH₃, and NO_x (NO, NO₂) over the thirteen different stations situated at different states in India. The data were compared with pre-confinement duration at different locations in India. During confinement, the air pollutants showed less value when compared with the pre-confinement stage alarming everyone and also the Indian government to bring up rules and regulations for better air quality index so that such pandemics should be reduced.

Impact of Covid-19 partial lockdown on PM2.5, SO2, NO2, O3, and trace elements in PM2.5 in Hanoi, Vietnam

Covid-19 lockdowns have improved the ambient air quality across the world via reduced air pollutant levels. This article aims to investigate the effect of the partial lockdown on the main ambient air pollutants and their elemental concentrations bound to PM_2.5 in Hanoi. In addition to the PM_2.5 samples collected at three urban sites in Hanoi, the daily PM_2.5, NO₂, O₃, and SO₂ levels were collected from the automatic ambient air quality monitoring station at Nguyen Van Cu street to analyze the pollution level before (March 10th-March 31st) and during the partial lockdown (April 1st-April 22nd) with "current" data obtained in 2020 and "historical" data obtained in 2014, 2016, and 2017. The results showed that NO₂, PM_2.5, O₃, and SO₂ concentrations obtained from the automatic ambient air quality monitoring station were reduced by 75.8, 55.9, 21.4, and 60.7%, respectively, compared with historical data. Besides, the concentration of PM_2.5 at sampling sites declined by 41.8% during the partial lockdown. Furthermore, there was a drastic negative relationship between the boundary layer height (BLH) and the daily mean PM_2.5 in Hanoi. The concentrations of Cd, Se, As, Sr, Ba, Cu, Mn, Pb, K, Zn, Ca, Al, and Mg during the partial lockdown were lower than those before the partial lockdown. The results of enrichment factor (EF) values and principal component analysis (PCA) concluded that trace elements in PM_2.5 before the partial lockdown were more affected by industrial activities than those during the partial lockdown.

Estimating changes in air pollutant levels due to COVID-19 lockdown measures based on a business-as-usual prediction scenario using data mining models: A case-study for urban traffic sites in Spain

In response to the COVID-19 pandemic, governments declared severe restrictions throughout 2020, presenting an unprecedented scenario of reduced anthropogenic emissions of air pollutants derived mainly from traffic sources. To analyze the effect of these restrictions derived from COVID-19 pandemic on air quality levels, relative changes in NO, NO₂, O₃, PM10 and PM2.5 concentrations were calculated at urban traffic sites in the most populated Spanish cities over different periods with distinct restrictions in 2020. In addition to the changes calculated with respect to the observed air pollutant levels of previous years (2013-2019), relative changes were also calculated using predicted pollutant levels for the different periods over 2020 on a business-as-usual scenario using Multiple Linear Regression (MLR) models with meteorological and seasonal predictors. MLR models were selected among different data mining techniques (MLR, Random Forest (RF), K-Nearest Neighbors (KNN)), based on their higher performance and accuracy obtained from a leave-one-year-out cross-validation scheme using 2013-2019 data. A q-q mapping post-correction was also applied in all cases in order to improve the reliability of the predictions to reproduce the observed distributions and extreme events. This approach allows us to estimate the relative changes in the studied air pollutants only due to COVID-19 restrictions. The results obtained from this approach show a decreasing pattern for NO_x, with the largest reduction in the lockdown period above -50%, whereas the increase observed for O₃ contrasts with the NO_x patterns with a maximum increase of 23.9%. The slight reduction in PM10 (-4.1%) and PM2.5 levels (-2.3%) during lockdown indicates a lower relationship with traffic sources. The developed methodology represents a simple but robust framework for exploratory analysis and intervention detection in air quality studies.

Meteorology-normalized variations of air quality during the COVID-19 lockdown in three Chinese megacities

To avoid the spread of COVID-19, China implemented strict prevention and control measures, resulting in dramatic variations in air quality. Here, we applied a machine learning algorithm (random forest model) to eliminate meteorological effects and characterize the high-resolution variation characteristics of air quality induced by COVID-19 in Beijing, Wuhan, and Urumqi. Our RF model estimates showed that the highest decrease in deweathered PM_2.5 in Wuhan (-43.6%) and Beijing (-14.0%) was at traffic stations during lockdown period (February 1- March 15, 2020), while it was at industry stations in Urumqi (-54.2%). Deweathered NO₂ decreased significantly in each city (∼30%-50%), whereas accompanied by a notable increase in O₃. The diurnal patterns show that the morning peaks of traffic-related NO₂ and CO almost disappeared. Additionally, our results suggested that meteorological effects offset some of the reduction in pollutant concentrations. Adverse meteorological conditions played a leading role in the variation in PM_2.5 concentration in Beijing, which contributed to +33.5%. The true effect of lockdown reduced the PM_2.5 concentrations in Wuhan, Beijing, and Urumqi by approximately 14.6%, 17.0%, and 34.0%, respectively. In summary, lockdown is the most important driver of the decline in pollutant concentrations, but the reduction of SO₂ and CO is limited and they are mainly influenced by changing trends. This study provides insights into quantifying variations in air quality due to the lockdown by considering meteorological variability, which varies greatly from city to city, and provides a reference for changes in city scale pollutant concentrations during the lockdown.

Estimating changes in air pollutant levels due to COVID-19 lockdown measures based on a business-as-usual prediction scenario using data mining models: A case-study for urban traffic sites in Spain

In response to the COVID-19 pandemic, governments declared severe restrictions throughout 2020, presenting an unprecedented scenario of reduced anthropogenic emissions of air pollutants derived mainly from traffic sources. To analyze the effect of these restrictions derived from COVID-19 pandemic on air quality levels, relative changes in NO, NO₂, O₃, PM10 and PM2.5 concentrations were calculated at urban traffic sites in the most populated Spanish cities over different periods with distinct restrictions in 2020. In addition to the changes calculated with respect to the observed air pollutant levels of previous years (2013-2019), relative changes were also calculated using predicted pollutant levels for the different periods over 2020 on a business-as-usual scenario using Multiple Linear Regression (MLR) models with meteorological and seasonal predictors. MLR models were selected among different data mining techniques (MLR, Random Forest (RF), K-Nearest Neighbors (KNN)), based on their higher performance and accuracy obtained from a leave-one-year-out cross-validation scheme using 2013-2019 data. A q-q mapping post-correction was also applied in all cases in order to improve the reliability of the predictions to reproduce the observed distributions and extreme events. This approach allows us to estimate the relative changes in the studied air pollutants only due to COVID-19 restrictions. The results obtained from this approach show a decreasing pattern for NO_x, with the largest reduction in the lockdown period above -50%, whereas the increase observed for O₃ contrasts with the NO_x patterns with a maximum increase of 23.9%. The slight reduction in PM10 (-4.1%) and PM2.5 levels (-2.3%) during lockdown indicates a lower relationship with traffic sources. The developed methodology represents a simple but robust framework for exploratory analysis and intervention detection in air quality studies.

The impact of the COVID-19 pandemic on air pollution: A global assessment using machine learning techniques

In response to the COVID-19 pandemic, most countries implemented public health ordinances that resulted in restricted mobility and a resultant change in air quality. This has provided an opportunity to quantify the extent to which carbon-based transport and industrial activity affect air quality. However, quantification of these complex effects has proven to be difficult, depending on the stringency of restrictions, country-specific emission source profiles, long-term trends and meteorological effects on atmospheric chemistry, emission levels and in-flow from nearby countries. In this study, confounding factors were disentangled for a direct comparison of pandemic-related reductions in absolute pollutions levels, globally. The non-linear relationships between atmospheric processes and daily ground-level NO 2 , PM₁₀, PM_2.5 and O 3 measurements were captured in city- and pollutant-specific XGBoost models for over 700 cities, adjusting for weather, seasonality and trends. City-level modelling allowed adaptation to the distinct topography, urban morphology, climate and atmospheric conditions for each city, individually, as the weather variables that were most predictive varied across cities. Pollution forecasts for 2020 in absence of a pandemic were generated based on weather and formed an ensemble for country-level pollution reductions. Findings were robust to modelling assumptions and consistent with various published case studies. NO 2 reduced most in China, Europe and India, following severe government restrictions as part of the initial lockdowns. Reductions were highly correlated with changes in mobility levels, especially trips to transit stations, workplaces, retail and recreation venues. Further, NO 2 did not fully revert to pre-pandemic levels in 2020. Ambient PM_2.5 pollution, which has severe adverse health consequences, reduced most in China and India. Since positive health effects could be offset to some extent by prolonged exposure to indoor pollution, alternative transport initiatives could prove to be an important pathway towards better health outcomes in these countries. Increased O 3 levels during initial lockdowns have been documented widely. However, our analyses also found a subsequent reduction in O 3 for many countries below what was expected based on meteorological conditions during summer months (e.g., China, United Kingdom, France, Germany, Poland, Turkey). The effects in periods with high O 3 levels are especially important for the development of effective mitigation strategies to improve health outcomes.

Effect of COVID-19 Response Policy on Air Quality: A Study in South China Context

Mass suspension of anthropogenic activities is extremely rare, the quarantine due to the coronavirus disease 2019 (COVID-19) represents a natural experiment to investigate the impact of anthropogenic activities on air quality. The mitigation of air pollution during the COVID-19 lockdown has been reported from a global perspective; however, the air pollution levels vary in different regions. This study initiated a novel synthesis of multiple-year satellite observations, national ground measurements towards SO2, NO2 and O3 and meteorological conditions to evaluate the impact of the COVID-19 lockdown in Beihai, a specific city in a less developed area in southwest China, to reveal the potential implications of control strategies for air pollution. The levels of the major air pollutants during the COVID-19 lockdown (LP) and during the same period of previous years (SP) were compared and a series of statistical tools were applied to analyze the sources of air pollution in Beihai. The results show that air pollutant levels decreased with substantial diversity during the LP. Satellite-retrieved NO2 and SO2 levels during the LP decreased by 5.26% and 22.06%, while NO2, SO2, PM2.5 and PM10 from ground measurements during the LP were 25.6%, 2.7%, 22.2% and 22.2% lower than during SP, respectively. Ground measured SO2 concentrations during the LP were only 2.7% lower than during the SP, which may be attributed to uninterrupted essential industrial activities, such as power plants. Polar plots analysis shows that NO2 concentrations were strongly associated with local emission sources, such as automobiles and local industry. Additionally, the much lower levels of NO2 concentrations during the LP and the absence of an evening peak may highlight the significant impact of the traffic sector on NO2. The decrease in daily mean O3 concentrations during the LP may be associated with the reduction in NO2 concentrations. Indications in this study could be beneficial for the formulation of atmospheric protection policies.

Decisive role of ozone formation control in winter PM2.5 mitigation in Shenzhen, China

During the COVID-19 lockdown, atmospheric PM_2.5 in the Pearl River Delta (PRD) showed the highest reduction in China, but the reasons, being a critical question for future air quality policy design, are not yet clear. In this study, we analyzed the relationships among gaseous precursors, secondary aerosols and atmospheric oxidation capacity in Shenzhen, a megacity in the PRD, during the lockdown period in 2020 and the same period in 2021. The comprehensive observational datasets showed large lockdown declines in all primary and secondary pollutants (including O₃). We found that, however, the daytime concentrations of secondary aerosols during the lockdown period and normal period were rather similar when the corresponding odd oxygen (O_x≡O₃+NO₂, an indicator of photochemical processing avoiding the titration effect of O₃ by freshly emitted NO) were at similar levels. Therefore, reduced O_x, rather than the large reduction in precursors, was a direct driver to achieve the decline in secondary aerosols. Moreover, O_x was also found to determine the spatial distribution of intercity PM_2.5 levels in winter PRD. Thus, an effective strategy for winter PM_2.5 mitigation should emphasize on control of winter O₃ formation in the PRD and other regions with similar conditions.

A potential controlling approach on surface ozone pollution based upon power big data

Surface ozone pollution has attracted extensive attention with the decreasing of haze pollution, especially in China. However, it is still difficult to efficiently control the pollution in time despite numbers of reports on mechanism of ozone pollution. Here we report a method for implementing effective control of ozone pollution through power big data. Combining the observation of surface ozone, NO2, meteorological parameters together with hourly electricity consumption data from volatile organic compounds (VOCs) emitting companies, a generalized additive model (GAM) is established for quantifying the influencing factors on the temporal and spatial distribution of surface ozone pollution from 2020 to 2021 in Anhui province, central China. The average R2 value for the modelling results of 16 cities is 0.82, indicating that the GAM model effectively captures the characteristics of ozone. The model quantifies the contribution of input variables to ozone, with both NO2 and industrial VOCs being the main contributors to ozone, contributing 33.72% and 21.12% to ozone formation respectively. Further analysis suggested the negative correlation between ozone and NO2, revealing VOCs primarily control the increase in ozone. Under scenarios controlling for a 10% and 20% reduction in electricity use in VOC-electricity sensitive industries that can be identified by power big data, ozone concentrations decreased by 9.7% and 19.1% during the pollution period. This study suggests a huge potential for controlling ozone pollution through power big data and offers specific control pathways.

Analysis of changes in air pollution quality and impact of COVID-19 on environmental health in Iran: application of interpolation models and spatial autocorrelation

In the global COVID-19 epidemic, humans are faced with a new challenge. The concept of quarantine as a preventive measure has changed human activities in all aspects of life. This challenge has led to changes in the environment as well. The air quality index is one of the immediate concrete parameters. In this study, the actual potential of quarantine effects on the air quality index and related variables in Tehran, the capital of Iran, is assessed, where, first, the data on the pollutant reference concentration for all measuring stations in Tehran, from February 19 to April 19, from 2017 to 2020, are monitored and evaluated. This study investigated the hourly concentrations of six particulate matters (PM), including PM2.5, PM10, and air contaminants such as nitrogen dioxide (NO₂), sulfur dioxide (SO2), ozone (O3), and carbon monoxide (CO). Changes in pollution rate during the study period can be due to reduced urban traffic, small industrial activities, and dust mites of urban and industrial origins. Although pollution has declined in most regions during the COVID-19 quarantine period, the PM2.5 rate has not decreased significantly, which might be of natural origins such as dust. Next, the air quality index for the stations is calculated, and then, the interpolation is made by evaluating the root mean square (RMS) of different models. The local and global Moran index indicates that the changes and the air quality index in the study area are clustered and have a high spatial autocorrelation. The results indicate that although the bad air quality is reduced due to quarantine, major changes are needed in urban management to provide favorable conditions. Contaminants can play a role in transmitting COVID-19 as a carrier of the virus. It is suggested that due to the rise in COVID-19 and temperature in Iran, in future studies, the effect of increased temperature on COVID-19 can be assessed.

Comprehensive analysis of ambient air quality during second lockdown in national capital territory of Delhi

The lockdown imposed in Delhi, due to the second wave of the COVID-19 pandemic has led to significant gains in air quality. Under the lockdown, restrictions were imposed on movement of people, operation of industrial establishments and hospitality sector amongst others. In the study, Air Quality Index and concentration trends of six pollutants, i.e. PM_2.5, PM₁₀, NO₂, SO₂, CO, and O₃ were analysed for National Capital Territory of Delhi, India for three periods in 2021 (pre-lockdown: 15 March to 16 April 2021, lockdown: 17 April to 31 May 2021 and post-lockdown: 01 June to 30 June). Data for corresponding periods in 2018-2020 was also analysed. Lockdown period saw 6 days in satisfactory AQI category as against 0 days in the same category during the pre-lockdown period. Average PM_2.5, PM₁₀, NO₂ and SO₂ concentrations reduced by 22%, 31%, 25% and 28% respectively during lockdown phase as compared to pre-lockdown phase, while O₃ was seen to increase. Variation in meteorological parameters and correlation of pollutants has also been examined. The significant improvement arising due to curtailment of certain activities in the lockdown period indicates the importance of local emission control, and helps improve the understanding of the dynamics of air pollution, thus highlighting policy areas to regulatory bodies for effective control of air pollution.

Spatiotemporal characteristics of PM2.5 and ozone concentrations in Chinese urban clusters

Despite China's public commitment to emphasise air pollution investigation and control, trends in PM_2.5 and ozone concentrations in Chinese urban clusters remain unclear. This study quantifies the spatiotemporal variations in PM_2.5 and surface ozone at the scale of Chinese urban clusters by using a long-term integrated dataset from 2015 to 2020. Nonlinear Granger causality testing was used to explore the spatial association patterns of PM_2.5 and ozone pollution in five megacity cluster regions. The results show a significant downward trend in annual mean PM_2.5 concentrations from 2015 to 2020, with a decline rate of 2.8 μg m^-3 yr^-1. By contrast, surface ozone concentrations increased at a rate of 2.1 μg m^-3 yr^-1 over the 6 years. The annual mean PM_2.5 concentrations in urban clusters show significant spatial clustering characteristics, mainly in Beijing-Tianjin-Hebei (BTH), Fenwei Plain (FWP), Northern slope of Tianshan Mountains urban cluster (NSTM), Sichuan Basin urban cluster (SCB), and Yangtze River Delta (YRD). Surface ozone shows severe summertime pollution and distributional variability, with increased ozone pollution in major urban clusters. The highest increases were observed in BTH, Yangtze River midstream urban cluster (YRMR), YRD, and Pearl River Delta (PRD). Nonlinear Granger causality tests showed that PM_2.5 was a nonlinear Granger cause of ozone, further supporting the literature's findings that PM_2.5 reduction promoted photochemical reaction rates and stimulated ozone production. The nonlinear test statistic passed the significance test in magnitude and statistical significance. FWP was an exception, with no significant long-term nonlinear causal link between PM_2.5 and ozone. This study highlights the challenges of compounded air pollution caused primarily by ozone and secondary PM_2.5. These results have implications for the design of synergistic pollution abatement policies for coupled urban clusters.

Heterogeneous impacts of mobility restrictions on air quality in the State of Sao Paulo during the COVID-19 pandemic

Air quality in the State of Sao Paulo was evaluated during the first general State plan of mobility restrictions due to the COVID-19 pandemic (24th March to May 31, 2020). Nitrogen dioxide (NO₂), ozone (O₃), particulate matter PM₁₀ and PM_2.5 and sulphur dioxide (SO₂) concentrations were assessed in cities of the Sao Paulo State with a monitoring station and compared to historical data. Linear regression models were built to investigate the relationship between the isolation of the population - determined using mobile phone monitoring data - and the concentration of each pollutant during the studied period. Although the reduction of pollutants such as NO₂, SO₂ and PM_2.5 is very clear, the economic and climatic characteristics of each region were decisive in the general behaviour of O₃ and PM₁₀. It was not possible to establish a correlation between the pollutants and the isolation index, partly due to the lack of data, partly due to the compliance of the population to those measurements, which was variable over time. Another important limitation factor was the absence of data related to the pollutants of interest in many of the stations. However, the isolation measures carried out in the State opened the opportunity to individually assess the air quality measurements in each of the stations, enabling an understanding that will allow in the future the design of air quality policies together with local sanitary policies.

Association of population migration with air quality: Role of city attributes in China during COVID-19 pandemic (2019-2021)

Atmospheric pollution studies have linked diminished human activity during the COVID-19 pandemic to improve air quality. This study was conducted during January to March (2019-2021) in 332 cities in China to examine the association between population migration and air quality, and examined the role of three city attributes (pollution level, city scale, and lockdown status) in this effect. This study assessed six air pollutants, namely CO, NO₂, O₃, PM₁₀, PM_2.5, and SO₂, and measured meteorological data, with-in city migration (WCM) index, and inter-city migration (ICM) index. A linear mixed-effects model with an autoregressive distributed lag model was fitted to estimate the effect of the percent change in migration on air pollution, adjusting for potential confounding factors. In summary, lower migration was associated with decreased air pollution (other than O₃). Pollution change in susceptibility is more likely to occur in NO₂ decrease and O₃ increase, but unsusceptibility is more likely to occur in CO and SO₂, to city attributes from low migration. Cities that are less air polluted and population-dense may benefit more from decreasing PM₁₀ and PM_2.5. The associations between population migration and air pollution were stronger in cities with stringent traffic restrictions than in cities with no lockdowns. Based on city attributes, an insignificant difference was observed between the effects of ICM and WCM on air pollution. Findings from this study may gain knowledge about the potential interaction between migration and city attributes, which may help decision-makers adopt air-quality policies with city-specific targets and paths to pursue similar air quality improvements for public health but at a much lower economic cost than lockdowns.

Adoption of innovative strategies to mitigate supply chain disruption: COVID-19 pandemic

COVID-19 pandemic outbreak caused supply chain (SC) disruption and threatened human life across the world, which could be mitigated through innovative strategies. Based on this scenario, this study examines the impact of COVID-19 on green practices, SC crisis mitigation strategies, smart technologies, and sustainable supply chain performance in the Pakistani manufacturing industry. Data was collected from Pakistani firms and employed structural equation modeling for testing hypotheses. The empirical results found that the COVID-19 pandemic is statistically related to green practices, SC crisis mitigation strategies, and smart technologies, while it harms sustainable supply chain performance. Moreover, green practices, SC crisis mitigation strategies, and smart technologies positively contribute to sustainable supply chain performance. The results of this study also confirmed the mediating role of green practices, SC crisis mitigation strategies, and smart technologies and moderating role organizational commitment in the context of a developing economy’s manufacturing industry. This study enhances awareness and understanding and contributes to the existing literature on verifying the link between COVID-19 pandemic and green practices, SC crisis mitigation strategies, and smart technologies to increase sustainable supply chain performance during a pandemic disruption in the Pakistani context. This study supports the managers of supply chain and manufacturing firms in adopting green practices and smart technologies. Also, it helps in the formation and successful implementation of SC crisis mitigation strategies during the crisis.

Diverse spillover effects of COVID-19 control measures on air quality improvement: evidence from typical Chinese cities

The COVID-19 prevention and control measures are taken by China's government, especially traffic restrictions and production suspension, had spillover effects on air quality improvement. These effects differed among cities, but these differences have not been adequately studied. To provide more knowledge, we studied the air quality index (AQI) and five air pollutants (PM2.5, PM10, SO2, NO2, and O3) before and after the COVID-19 outbreak in Shanghai, Wuhan, and Tangshan. The pollution data from two types of monitoring stations (traffic and non-traffic stations) were separately compared and evaluated. We used monitoring data from the traffic stations to study the emission reduction caused by traffic restrictions. Based on monitoring data from the non-traffic stations, we established a difference-in-difference model to study the emission reduction caused by production suspension. The COVID-19 control measures reduced AQI and the concentrations of all pollutants except O3 (which increased greatly), but the magnitude of the changes differed among the three cities. The control measures improved air quality most in Wuhan, followed by Shanghai and then Tangshan. We investigated the reasons for these differences and found that differences in the characteristics of these three types of cities could explain these differences in spillover effects. Understanding these differences could provide some guidance and support for formulating differentiated air pollution control measures in different cities. For example, whole-process emission reduction technology should be adopted in cities with the concentrated distribution of continuous process enterprises, whereas vehicles that use cleaner energy and public transport should be vigorously promoted in cities with high traffic development level.

Impact of the Levels of COVID-19 Pandemic Prevention and Control Measures on Air Quality: A Case Study of Jiangsu Province, China

In order to control the spread of the COVID-19 pandemic, the prevention and control measures of public health emergencies were initiated in all provinces of China in early 2020, which had a certain impact on air quality. In this study, taking Jiangsu Province in China as an example, the air pollution levels in different regions under different levels of pandemic prevention and control (PPC) measures are evaluated. The implementation of the prevention and control policies of COVID-19 pandemic directly affected the concentration of air pollutants. No matter what level of PPC measures was implemented, the air quality index (AQI) and pollutant concentrations of NO2, CO, PM10 and PM2.5 were all reduced by varied degrees. The higher the level of PPC measures, the greater the reduction was in air pollutant concentrations. Specifically, NO2 was the most sensitive to PPC policies. The concentrations of CO and atmospheric particulate matter (PM10 and PM2.5) decreased most obviously under the first and second level of PPC. The response speed of air quality to different levels of PPC measures varied greatly among different cities. Southern Jiangsu, which has a higher level of economic development and is dominated by secondary and tertiary industries, had a faster response speed and a stronger responsiveness. The results of this study reflect the economic vitality of different cities in economically advanced regions (i.e., Jiangsu Province) in China. Furthermore, the results can provide references for the formulation of PPC policies and help the government make more scientific and reasonable strategies for air pollution prevention and control.

Quantifying ecological and health risks of ground-level O3 across China during the implementation of the "Three-year Action Plan for Cleaner Air"

After China implemented the Air Pollution Prevention and Control Action Plan (APPCAP), PM_2.5 concentrations decreased but were still higher than national standards in major areas and ozone (O₃) concentration increased unintentionally. To further decrease PM_2.5 concentrations and reduce days with severe air pollution, the government promulgated the "Three-year (2018-2020) Action Plan for Cleaner Air" (the Three-year Action Plan) in 2018. During the three-year Action Plan, a few studies reported a continuous decline in PM_2.5, but it is unclear whether O₃ and its effects also increase with the decrease of PM_2.5 like during APPCAP. In this study, for the first time, we systematically assessed changes in ground-level O₃ concentrations and related ecological and health risks during the period of the Three-year Action Plan using nationwide O₃ measurements. The national MDA8, Exceedance, and SOMO35 indicators were reduced by 3.8%, 28.5%, and 12.6%, respectively, ecological risk indicators of M12, M7, SUM06, AOT40, and W126 were reduced by 5.4%, 5.6%, 19.5%, 15.4%, and 18.6%, respectively, from 2018 to 2020. Spatially, the greatest reduction in all the indicators except MDA8 occurred in Pearl River Delta, followed by Fen Wei Plains, while Beijing-Tianjin-Hebei, Chengdu-Chongqing, and Yangtze River Delta presented relatively small reductions. Between 2018 and 2020, the production losses caused by O₃ for wheat and rice decreased by 21.4% and 17.6%, respectively. Long-term exposure to O₃ across China over 2020 was estimated to cause about 160,795 (95% CI: 81,515-312,983) for all-cause mortality, 107,128 (95% CI: 36,703-173,823) for cardiovascular mortality, and 34,444 (95% CI: 0-72,609) for respiratory mortality, indicating decreases of 9.93%, 9.86%, and 9.78%, respectively, compared to the year 2018. Taken together, our results provided the first direct evidence for China's efforts to control O₃ pollution in recent years.

COVID-19, air quality and space monitoring

Due to the worldwide spread of the coronavirus disease 2019 (COVID-19), human mobility and economic activity have slowed down considerably since early 2020. A relatively high number of those infected develop serious pneumonia leading to progressive respiratory failure, system disease and often death. Apart from close human-to-human contact, the acceleration and global diffusion of this pandemic has been shown to be associated with changes in atmospheric chemistry and air pollution by microscopic particulate matter (PM). Breathing air with high concentrations of nitrogen dioxide and PM can result in over-expression of the angiotensin converting enzyme-2 (ACE-2) leading to stress of organs, such as heart and kidneys. Satellite monitoring can play a crucial role in spatio-temporal surveillance of the disease by producing data on pollution as proxy for industrial activity, transport and traffic circulation. Real-time monitoring of COVID-19 in air and chemical pollution of the atmospheric boundary layer available from Earth-observing satellites commuting with Health Information Systems (HIS) would be useful for decision makers involved with public health.

Effects of the COVID-19 lockdown and recovery on People's mobility and air quality in the United Arab Emirates using satellite and ground observations

The stringent COVID-19 lockdown measures in 2020 significantly impacted people's mobility and air quality worldwide. This study presents an assessment of the impacts of the lockdown and the subsequent reopening on air quality and people's mobility in the United Arab Emirates (UAE). Google's community mobility reports and UAE's government lockdown measures were used to assess the changes in the mobility patterns. Time-series and statistical analyses of various air pollutants levels (NO₂, O₃, SO₂, PM₁₀, and aerosol optical depth-AOD) obtained from satellite images and ground monitoring stations were used to assess air quality. The levels of pollutants during the initial lockdown (March to June 2020) and the subsequent gradual reopening in 2020 and 2021 were compared with their average levels during 2015-2019. During the lockdown, people's mobility in the workplace, parks, shops and pharmacies, transit stations, and retail and recreation sectors decreased by about 34%-79%. However, the mobility in the residential sector increased by up to 29%. The satellite-based data indicated significant reductions in NO₂ (up to 22%), SO₂ (up to 17%), and AOD (up to 40%) with small changes in O₃ (up to 5%) during the lockdown. Similarly, data from the ground monitoring stations showed significant reductions in NO₂ (49% - 57%) and PM₁₀ (19% - 64%); however, the SO₂ and O₃ levels showed inconsistent trends. The ground and satellite-based air quality levels were positively correlated for NO₂, PM₁₀, and AOD. The data also demonstrated significant correlations between the mobility and NO₂ and AOD levels during the lockdown and recovery periods. The study documents the impacts of the lockdown on people's mobility and air quality and provides useful data and analyses for researchers, planners, and policymakers relevant to managing risk, mobility, and air quality.

The ecology of COVID-19 and related environmental and sustainability issues

Around the globe, human behavior and ecosystem health have been extensively and sometimes severely affected by the unprecedented COVID-19 pandemic. Most efforts to study these complex and heterogenous effects to date have focused on public health and economics. Some studies have evaluated the pandemic's influences on the environment, but often on a single aspect such as air or water pollution. The related research opportunities are relatively rare, and the approaches are unique in multiple aspects and mostly retrospective. Here, we focus on the diverse research opportunities in disease ecology and ecosystem sustainability related to the (intermittent) lockdowns that drastically reduced human activities. We discuss several key knowledge gaps and questions to address amid the ongoing pandemic. In principle, the common knowledge accumulated from invasion biology could also be effectively applied to COVID-19, and the findings could offer much-needed information for future pandemic prevention and management.

Traffic restrictions during COVID-19 lockdown improve air quality and reduce metal biodeposition in tree leaves

The coronavirus disease (COVID-19) has had a great global impact on human health, the life of people, and economies all over the world. However, in general, COVID-19´s effect on air quality has been positive due to the restrictions on social and economic activity. This study aimed to assess the impact on air quality and metal deposition of actions taken to reduce mobility in 2020 in two different urban locations. For this purpose, we analysed air pollution (NO₂, NO, NO_x, SO_2, CO, PM_10, O₃) and metal accumulation in leaves of Tilia cordata collected from April to September 2020 in two cities in northern Spain (Pamplona-PA and San Sebastián-SS). We compared their values with data from the previous year (2019) (in which there were no mobility restrictions) obtained under an identical experimental design. We found that metal accumulation was mostly lower during 2020 (compared with 2019), and lockdown caused significant reductions in urban air pollution. Nitrogen oxides decreased by 33%-44%, CO by 24%-38%, and PM₁₀ by 16%-24%. The contents of traffic-related metals were significantly reduced in both studied cities. More specifically, significant decreases in metals related to tyre and brake wear (Zn, Fe, and Cu) and road dust resuspension (Al, Ti, Fe, Mn, and Ca) were observed. With these results, we conclude that the main reason for the improvement in urban air pollutants and metals was the reduction in the use of cars due to COVID-19 lockdown. In addition, we offer some evidence indicating the suitability of T. cordata leaves as a tool for biomonitoring metal accumulation. This information is relevant for future use by the scientific community and policy makers to implement measures to reduce traffic air pollution in urban areas and to improve environmental and human health.

Assessment of the coronavirus disease 2019 (COVID-19) pandemic imposed lockdown and unlock effects on black carbon aerosol, its source apportionment, and aerosol radiative forcing over an urban city in India

A nationwide lockdown was imposed in India due to the Coronavirus Disease 2019 (COVID-19) pandemic which significantly reduced the anthropogenic emissions. We examined the characteristics of equivalent black carbon (eBC) mass concentration and its source apportionment using a multiwavelength aethalometer over an urban site (Ahmedabad) in India during the pandemic induced lockdown period of year 2020. For the first time, we estimate the changes in BC, its contribution from fossil (eBC ff ) and wood (eBC wf ) fuels during lockdown (LD) and unlock (UL) periods in 2020 with respect to 2017 to 2019 (normal period). The eBC mass concentration continuously decreased throughout lockdown periods (LD1 to LD4) due to enforced and stringent restrictions which substantially reduced the anthropogenic emissions. The eBC mass concentration increased gradually during unlock phases (UL1 to UL7) due to the phase wise relaxations after lockdown. During lockdown period eBC mass concentration decreased by 35%, whereas during the unlock period eBC decreased by 30% as compared to normal period. The eBC wf concentrations were higher by 40% during lockdown period than normal period due to significant increase in the biomass burning emissions from the several community kitchens which were operational in the city during the lockdown period. The average contributions of eBC ff and eBC wf to total eBC mass concentrations were 70% and 30% respectively during lockdown (LD1 to LD4) period, whereas these values were 87% and 13% respectively during the normal period. The reductions in BC concentrations were commensurate with the reductions in emissions from transportation and industrial activities. The aerosol radiative forcing reduced significantly due to the reduction in anthropogenic emissions associated with COVID-19 pandemic induced lockdown leading to a cooling of the atmosphere. The findings in the present study on eBC obtained during the unprecedented COVID-19 induced lockdown can provide a comprehensive understanding of the BC sources and current emission control strategies, and thus can serve as baseline anthropogenic emissions scenario for future emission control strategies aimed to improve air quality and climate.

Asthma and COPD exacerbation in relation to outdoor air pollution in the metropolitan area of Berlin, Germany

Background

Ambient air pollution poses a major risk for the development and aggravation of respiratory diseases. Evidence suggests that even in low-level air pollution environments there is a risk for an increase in adverse respiratory symptoms. We examined whether variations in daily air pollution levels of nitrogen dioxide, ozone, or particulate matter in Berlin, Germany were associated with hospital admissions of chronic obstructive pulmonary disease (COPD) and asthma patients in a time series analysis.

Methods

We calculated single and multi-pollutant models, investigated possible lags in effect, and analysed the influence of meteorological variables on the results. Data from January 2005 through December 2015 were used to quantify the concentration–response.

Results

The risk ratio for asthma patients to be hospitalised on the same day of NO₂ exposure was 1.101 per 10 µg/m³ NO₂ increase (95% CI: 1.013 to 1.195), for COPD patients 1.123 (95% CI: 1.081 to 1.168). Neither the exposure to ozone (95% CI: 0.904 to 1.020), PM₁₀ (95% CI: 0.990 to 1.127), nor PM_2.5 (95% CI: 0.981 to 1.148) was associated with an increased risk ratio for asthma patients to be hospitalised. Risk ratios for the hospital admission of COPD patients were also not increased due to ozone (95% CI: 0.981 to 1.033), PM₁₀ (95% CI: 0.988 to 1.032), or PM_2.5 (95% CI: 0.966 to 1.019) exposure. The presented risk ratios and confidence intervals relate to the day of exposure. We found no increased hospitalisation risks with a delayed occurrence on subsequent days.

Conclusions

A quantifiable, statistically significant increase in risk for asthma and COPD exacerbations owing to NO₂ exposure at levels well below European regulatory limit values was observed.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12931-022-01983-1.

COVID-19 pandemic: impacts on air quality and economy before, during and after lockdown in China in 2020

ABSTRACTThis paper comprehensively evaluates the dynamic effects on China's environment and economy during the COVID-19 pandemic. Results show that the COVID-19 lockdown resulted in a temporary improvement in air quality. Furthermore, nitrogen dioxide (NO₂) levels in the atmosphere in China were 36% lower than in the week after last year's Lunar New Year holiday, but this also led to an economic downturn. Moreover, the aerosol optical depth (AOD) decreased significantly. During the back-to-work period, the economy recovered and there was an increase in energy consumption, and CO₂, NO₂ emissions sharply increased to pre-lockdown levels. In the post-lockdown period, the AOD was lower than that of the same period last year. This study can provide reference for environmental policy making, as it demonstrates to what extent the control of pollution sources can improve air quality. Precise emission reduction and regional joint prevention and control are important and effective means for the prevention and control of O₃ pollution. The health and economic benefits of COVID-19 pandemic control measures are incalculable. And this can provide an effective scientific basis and theoretical support for the prevention and control of air pollution.

A Clustering Spatial Estimation of Marginal Economic Losses for Vegetation Due to the Emission of VOCs as a Precursor of Ozone

The economic losses of vegetation caused by ozone were usually evaluated with existing ozone concentrations. However, in the case a new project is assessed, the marginal losses induced by the additional emissions of ozone’s precursors are required. As ozone is VOC-sensitive in China, this study used novel approaches to assess the marginal economic losses (MELs) for vegetation due to the emission of VOCs as a precursor of ozone, which integrated the geographically constrained AHC algorithm with the spatial regression and applied the cluster-specific coefficients of VOC emissions to the MEL estimation. The new approaches reduce the regression sigma2 from 94.5 to 64.6. The marginal contributions of VOC emissions to ozone concentrations range from 0.123 to 1.180 μg/m3 per kilotonne of emissions per year per 0.25 × 0.25 degree. Negative marginal contributions of NOx emissions were found in Southeast China and the Yunan Guizhou Plateau. County-level marginal increases in AOT40s and MELs due to VOC emissions for crops, semi-natural products, and coniferous and deciduous forests were presented as maps. These values are exceedingly large in Northeast China and the Yunan Guizhou Plateau. Due to the high timber prices, sensitivities to ozone, and long growing seasons, MELs of forests are higher than those of other vegetation types, and thus factories with VOC emissions should be away from the surrounding areas of forests.

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.

Changing Air Quality and the Ozone Weekend Effect during the COVID-19 Pandemic in Toronto, Ontario, Canada

Air pollutants, NO, NO2, and O3, were examined from April to June 2020 and compared to a 10-year (2010–2019) climatology of these pollutants for two monitoring sites in Toronto, Ontario, Canada, coinciding with local lockdown measures during the first wave of the COVID-19 pandemic. NO and NO2 values were lower than any of the preceding 10 years at the two Toronto sites for both weekdays and weekends. Ozone concentrations did not have a corresponding decrease and in fact increased for weekdays, similar to other parts of the world. The well-documented ozone weekend effect was considerably muted during the morning rush hour throughout this pandemic period. A Fisher exact test on hourly averaged data revealed statistically significant record hourly minimums for NO and NO2, but this was not found for ozone, consistent with the aggregate ranking results. These findings are likely the result of considerably reduced vehicular traffic during this time and ozone chemistry in a NOx-saturated (VOC limited) environment. This has important implications for ozone abatement strategies.

Air quality improvement and its relation to mobility during COVID-19 lockdown in Marmara Region, Turkey

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, PM_2.5, 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, PM_2.5, and NO₂ obtained from 11 stations operated by the Ministry of Environment and Urbanization and Google mobility data are used in this study. Average PM_2.5 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 PM_2.5, 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.

The impact of lockdown on nitrogen dioxide (NO2) over Central Asian countries during the COVID-19 pandemic

Nitrogen dioxide (NO₂) is one of the main air pollutants, formed due to both natural and anthropogenic processes, which has a significant negative impact on human health. The COVID-19 pandemic has prompted countries to take various measures, including social distancing or stay-at-home orders. This study analyzes the impact of COVID-19 lockdown measures on nitrogen dioxide (NO₂) changes in Central Asian countries. Data from TROPOspheric Monitoring Instrument (TROPOMI) on the Sentinel-5 Precursor satellite, as well as meteorological data, make it possible to assess changes in NO₂ concentration in countries and major cities in the region. In particular, the obtained satellite data show a decreased tropospheric column of NO₂. Its decrease during the lockdown (March 19-April 14) ranged from - 5.1% (Tajikistan) to - 11.6% (Turkmenistan). Based on the obtained results, it can be concluded that limitations in anthropogenic activities have led to improvements in air quality. The possible influence of meteorology is not assessed in this study, and the implied uncertainties cannot be quantified. In this way, the level of air pollution is expected to decrease as long as partial or complete lockdown continues.

Air pollution perception in ten countries during the COVID-19 pandemic

As largely documented in the literature, the stark restrictions enforced worldwide in 2020 to curb the COVID-19 pandemic also curtailed the production of air pollutants to some extent. This study investigates the perception of the air pollution as assessed by individuals located in ten countries: Australia, Brazil, China, Ghana, India, Iran, Italy, Norway, South Africa and the USA. The perceptions towards air quality were evaluated by employing an online survey administered in May 2020. Participants (N = 9394) in the ten countries expressed their opinions according to a Likert-scale response. A reduction in pollutant concentration was clearly perceived, albeit to a different extent, by all populations. The survey participants located in India and Italy perceived the largest drop in the air pollution concentration; conversely, the smallest variation was perceived among Chinese and Norwegian respondents. Among all the demographic indicators considered, only gender proved to be statistically significant.

Remote sensing study of ozone, NO2, and CO: some contrary effects of SARS-CoV-2 lockdown over India

Escalating emissions of several air pollutants over South Asia could play a detrimental role in the regional and global atmosphere. Therefore, it is necessary to investigate these emissions within the boundary layer and at higher heights utilizing satellite data that are more inclusionary, where limited in situ observations are available. Here, we utilize the Infrared Atmospheric Sounding Interferometer (IASI), Ozone Monitoring Instruments (OMI), TROPOspheric Monitoring Instrument (TROPOMI), and Global Ozone Monitoring Experiment (GOME-2) hyperspectral satellite data to assess the changes in emission sources during Indian lockdown with a primary focus on the tropospheric profiles of ozone and carbon monoxide (CO). A significant reduction (> 20%) in the tropospheric ozone was seen over northern and northeast regions compared to 2018, while a dramatic increase (> 20%) compared to 2019 was seen. The subtropical dynamics mainly contributed to the increased ozone over the northern region. An analysis of the ozone production regime showed mostly NO2 limited regime over the major part of India and VOC limited regime over thermal power plants regions. Unlike in the boundary layer, where CO showed reduction (15-20%), CO profiles showed a consistent increase (as high as 31%) in the free troposphere over the majority of cities and thermal power plants. The CO total column also showed an increase (~ 20%) over central and western India and a slight decrease (5%) over northern India. Similar to CO, an increase (~ 15%) of NO2 column over the western region was observed particularly compared to 2019. However, unlike ozone and CO, reduction of tropospheric NO2 columns was seen over the major part of India, with the highest reduction over northern regions (20-52%). Furthermore, homogeneous yearly differences (> 30%) between OMI and TROPOMI NO2 observations were also seen distinctly over the remote areas. Contrary to surface-based studies, the present study shows an increase in CO, ozone (decrease), and NO2 at several locations and in the free troposphere during the lockdown.

A Health Impact and Economic Loss Assessment of O3 and PM2.5 Exposure in China From 2015 to 2020

China is in a critical air quality management stage. Rapid industrial development and urbanization has resulted in non-ignorable air pollution, which seriously endangers human health. Assessment of the health impacts and economic losses of air pollution is essential for the prevention and control policy formulation. Based on ozone (O₃) and fine particulate matter concentration (PM_2.5) monitoring data in 331 Chinese cities from 2015 to 2020, this study evaluated the health effects and the corresponding economic losses of O₃ and PM_2.5 pollution on three health endpoints. The ratio of population exposed to O₃ levels that exceeded the Chinese Ambient Air Quality Standards (CAAQS) increased from 13.35% in 2015 to 14.15% in 2020, which resulted in 133,415 (2015) - 156,173 (2020) all-cause deaths, 88,941 (2015) - 104,051 (2020) cardiovascular deaths, and 28,614 (2015) - 33,456 (2020) respiratory deaths. The ratio of population exposed to PM_2.5 levels that exceeded the CAAQS decreased, but in many regions, especially in North China and the Yangtze River Delta, the PM_2.5 concentration remained high. By 2020, nearly half of the population in China was still exposed to PM_2.5 levels that exceeded the CAAQS, and the corresponding economic losses reached CNY 3.46 and 3.05 billion, respectively. These results improved the understanding of the spatial-temporal variation trends of major air pollutants at city scale in China, and emphasize the continued coordination urgently needed for controlling O₃ and PM_2.5 following the implementation of the 2013 policy to mitigate air pollution to protect human health.

Increased Shamal winds and dust activity over the Arabian Peninsula during the COVID-19 lockdown period in 2020

While anthropogenic pollutants have decreased during the lockdown imposed as an effort to contain the spread of the Coronavirus disease 2019 (COVID-19), changes in particulate matter (PM) do not necessarily exhibit the same tendency. This is the case for the eastern Arabian Peninsula, where in March-June 2020, and with respect to the same period in 2016-2019, a 30 % increase in PM concentration is observed. A stronger than normal nocturnal low-level jet and subtropical jet over parts of Saudi Arabia, in response to anomalous convection over the tropical Indian Ocean, promoted enhanced and more frequent episodes of Shamal winds over the Arabian Peninsula. Increased surface winds associated with the downward mixing of momentum to the surface fostered, in turn, dust lifting and increased PM concentrations. The stronger low-level winds also favoured long-range transport of aerosols, changing the PM values downstream. The competing effects of reduced anthropogenic and increased dust concentrations leave a small positive signal (<5 W m^-2) in the net surface radiation flux (R_net), with the former dominating during daytime and the latter at night. However, in parts of the Arabian Gulf, Sea of Oman and Iran R_net increased by >20 W m^-2 with respect to the baseline period, owing to a clearer environment and weaker winds. It is concluded that a reduction in anthropogenic emissions due to the lockdown does not necessarily go hand in hand with lower particulate matter concentrations. Therefore, emissions reduction strategies need to account for feedback effects in order to reach the planned long-term outcomes.

Implications of COVID-19 on global environmental pollution and carbon emissions with strategies for sustainability in the COVID-19 era

The impacts of COVID-19 on global environmental pollution since its onset in December 2019 require special attention. The rapid spread of COVID-19 globally has led countries to lock down cities, restrict traffic travel and impose strict safety measures, all of which have implications on the environment. This review aims to systematically and comprehensively present and analyze the positive and negative impacts of COVID-19 on global environmental pollution and carbon emissions. It also aims to propose strategies to prolong the beneficial, while minimize the adverse environmental impacts of COVID-19. It systematically and comprehensively reviewed more than 100 peer-reviewed papers and publications related to the impacts of COVID-19 on air, water and soil pollution, carbon emissions as well as the sustainable strategies forward. It revealed that PM_2.5, PM₁₀, NO₂, and CO levels reduced in most regions globally but SO₂ and O₃ levels increased or did not show significant changes. Surface water, coastal water and groundwater quality improved globally during COVID-19 lockdown except few reservoirs and coastal areas. Soil contamination worsened mainly due to waste from the use of personal protective equipment particularly masks and the packaging, besides household waste. Carbon emissions were reduced primarily due to travel restrictions and less usage of utilities though emissions from certain ships did not change significantly to maintain supply of the essentials. Sustainable strategies post-COVID-19 include the development and adoption of nanomaterial adsorption and microbial remediation technologies, integrated waste management measures, "sterilization wave" technology and energy-efficient technologies. This review provides important insight and novel coverage of the environmental implications of COVID-19 in more than 25 countries across different global regions to permit formulation of specific pollution control and sustainability strategies in the COVID-19 and post-COVID-19 eras for better environmental quality and human health.

Long-Term Impacts of COVID-19 Lockdown on the NO2 Concentrations and Urban Thermal Environment: Evidence from the Five Largest Urban Agglomerations in China

Under the threat of COVID-19, many regions around the world implemented lockdown policies to control the spread of the virus. This restriction on both social and economic activities has improved the quality of the environment in certain aspects. However, most previous studies have only focused on the short-term impact of lockdown policies on the urban environment. The long-term effects of lockdown require a more focused exploration and analysis. Thus, five major urban agglomerations in China were selected as the research area; changes in the numerical and spatial distribution of NO2 concentration and surface temperature during four different lockdown stages in 2019, 2020, and 2021 were investigated to analyze the long-term effects of lockdown policies on the urban environment. The results indicated that the impact of shorter lockdowns was short-term and unsustainable; the NO2 concentrations increased again with the resumption of production. Compared with air pollutants, thermal environmental problems are more complex. The effect of the lockdown policy was not reflected in the decrease in the area proportions of the high- and sub-high-temperature regions but rather in the spatial distribution of the high-temperature area, which was manifested as a fragmentation and dispersion of heat source patches. In addition to the severity of the lockdown, the impact of the lockdown policy was also closely related to the level of development and industrial structure of each city. Among the urban environments of the five agglomerations, the most affected were the Yangtze River Delta and Yangtze River Middle-Reach urban agglomerations, which had the largest decline in NO2 concentrations and the most notable fragmentation of heat source patches.

The impact of the COVID-19 lockdown on global air quality: A review

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.

Identification of ozone sensitivity for NO2 and secondary HCHO based on MAX-DOAS measurements in northeast China

In this study, tropospheric formaldehyde (HCHO) vertical column densities (VCDs) were measured using multi-axis differential optical absorption spectroscopy (MAX-DOAS) from January to November 2019 in Shenyang, Northeast China. The maximum HCHO VCD value appeared in the summer (1.74 × 10¹⁶ molec/cm²), due to increased photo-oxidation of volatile organic compounds (VOCs). HCHO concentrations increased from 08:00 and peaked near 13:00, which was mainly attributed to the increased release of isoprene from plants and enhanced photolysis at noon. The HCHO VCDs observed by MAX-DOAS and OMI have a good correlation coefficient (R) of 0.78, and the contributions from primary and secondary HCHO sources were distinguished by the multi-linear regression model. The anthropogenic emissions showed unobvious seasonal variations, and the primary HCHO was relatively stable in Shenyang. Secondary HCHO contributed 82.62%, 83.90%, 78.90%, and 41.53% to the total measured ambient HCHO during the winter, spring, summer, and autumn, respectively. We also found a good correlation (R = 0.78) between enhanced vegetation index (EVI) and HCHO VCDs, indicating that the oxidation of biogenic volatile organic compounds (BVOCs) was the main source of HCHO. The ratio of secondary HCHO to nitrogen dioxide (NO₂) was used as the tracer to analyze O₃-NO_x-VOC sensitivities. We found that the VOC-limited, VOC-NO_x-limited, and NO_x-limited regimes made up 93.67%, 6.23%, 0.11% of the overall measurements, respectively. In addition, summertime ozone (O₃) sensitivity changed from VOC-limited in the morning to VOC-NO_x-limited in the afternoon. Therefore, this study offers information on HCHO sources and corresponding O₃ production sensitivities to support strategic management decisions.

COVID-19 lockdown and natural resources: a global assessment on the challenges, opportunities, and the way forward

BACKGROUND

The Coronavirus (COVID-19) is a global pandemic caused by SARS-CoV-2, which has an enormous effect on human lives and the global environment. This review aimed to assess the global scientific evidence on the impact of COVID-19 lockdown on natural resources using international databases and search engines. Thus, the unprecedented anthropause due to COVID-19 has positive and negative effects on natural resources.

MAIN BODY

This review showed that the unprecedented pandemic lockdown events brought a negative impact on the physical environment, including pollution associated with a drastic increase in person protective equipment, deforestation, illegal poaching and logging, overfishing, disruption of the conservation program and projects. It is noted that the spread of pandemic diseases could be aggravated by environmental pollution and a rapid increase in the global population. Despite these negative impacts of COVID-19, the anthropause appear to have also several positive effects on natural resources such as short term reduction of indoor and outdoor environmental pollutants (PM2.5, PM10, NO2, SO2, CO, and CO2), reduction in noise pollutions from ships, boats, vehicles, and planes which have positive effects on aquatic ecosystems, water quality, birds behaviour, wildlife biodiversity, and ecosystem restoration.

CONCLUSION

Therefore, governments and scientific communities across the globe have called for a green recovery to COVID-19 and implement multi-actor interventions and environmentally friendly technologies to improve and safeguard sustainable environmental and biodiversity management and halt the next pandemic.

Assessing the potential repercussions of the COVID-19 pandemic on global SDG attainment

The coronavirus disease (COVID-19) pandemic has led to a worldwide lockdown, and this restriction on human movements and activities has significantly affected society and the environment. Some effects might be quantitative, but some might be qualitative, and some effects could prolong immediately and/or persistently. This study examined the consequences of global lockdown for human movement and nitrogen dioxide (NO2) emissions using an air pollution index and dataset and satellite image analyses. We also evaluated the immediate (during lockdown) and persistent (after lockdown) effects of lockdown on achieving the SDGs. Our analysis revealed a drastic reduction in human movement and NO2 emissions and showed that many SDGs were influenced both immediately and persistently due to the global lockdown. We observed the immediate negative impacts on four goals and positive impacts on five goals, especially those concerning economic issues and ecosystem conservation, respectively. The persistent effects of lockdown were likely to be predominantly reversed from their immediate impacts due to economic recovery. The global lockdown has influenced the global community's ability to meet the SDGs, and our analysis provides powerful insights into the status of the internationally agreed-upon SDGs both during and after the COVID-19-induced global lockdown.

Supplementary Information

The online version contains supplementary material available at 10.1007/s43621-021-00067-2.

Optimization of a NOx and VOC Cooperative Control Strategy Based on Clean Air Benefits

Serious ambient PM_2.5 and O₃ pollution is one of the most important environmental challenges of China, necessitating an urgent cost-effective cocontrol strategy. Herein, we introduced a novel integrated assessment system to optimize a NO_x and volatile organic compound (VOC) control strategy for the synergistic reduction of ambient PM_2.5 and O₃ pollution. Focusing on the Beijing-Tianjin-Hebei cities and their surrounding regions, which are experiencing the most serious PM_2.5 and O₃ pollution in China, we found that NO_x emission reduction (64-81%) is essential to attain the air quality standard no matter how much VOC emission is reduced. However, the synergistic VOC control is strongly recommended considering its substantially human health and crop production benefits, which are estimated up to 163 (PM_2.5-related) and 101 (O₃-related) billion CHY during the reduction of considerable emissions. Notably, such benefits will be greatly reduced if the synergistic VOC reduction is delayed. This study also highlights the necessity of simultaneous VOC and NO_x emission control in winter while enhancing the NO_x control in the summer, which is contrary to the current control strategy adopted in China. These findings point out the right pathways for future policy making on comitigating PM_2.5 and O₃ pollution in China and other countries.

A multi-step machine learning approach to assess the impact of COVID-19 lockdown on NO2 attributable deaths in Milan and Rome, Italy

BACKGROUND

Air pollution is one of the main concerns for the health of European citizens, and cities are currently striving to accomplish EU air pollution regulation. The 2020 COVID-19 lockdown measures can be seen as an unintended but effective experiment to assess the impact of traffic restriction policies on air pollution. Our objective was to estimate the impact of the lockdown measures on NO2 concentrations and health in the two largest Italian cities.

METHODS

NO2 concentration datasets were built using data deriving from a 1-month citizen science monitoring campaign that took place in Milan and Rome just before the Italian lockdown period. Annual mean NO2 concentrations were estimated for a lockdown scenario (Scenario 1) and a scenario without lockdown (Scenario 2), by applying city-specific annual adjustment factors to the 1-month data. The latter were estimated deriving data from Air Quality Network stations and by applying a machine learning approach. NO2 spatial distribution was estimated at a neighbourhood scale by applying Land Use Random Forest models for the two scenarios. Finally, the impact of lockdown on health was estimated by subtracting attributable deaths for Scenario 1 and those for Scenario 2, both estimated by applying literature-based dose-response function on the counterfactual concentrations of 10 μg/m3.

RESULTS

The Land Use Random Forest models were able to capture 41-42% of the total NO2 variability. Passing from Scenario 2 (annual NO2 without lockdown) to Scenario 1 (annual NO2 with lockdown), the population-weighted exposure to NO2 for Milan and Rome decreased by 15.1% and 15.3% on an annual basis. Considering the 10 μg/m3 counterfactual, prevented deaths were respectively 213 and 604.

CONCLUSIONS

Our results show that the lockdown had a beneficial impact on air quality and human health. However, compliance with the current EU legal limit is not enough to avoid a high number of NO2 attributable deaths. This contribution reaffirms the potentiality of the citizen science approach and calls for more ambitious traffic calming policies and a re-evaluation of the legal annual limit value for NO2 for the protection of human health.

Viral outbreaks detection and surveillance using wastewater-based epidemiology, viral air sampling, and machine learning techniques: A comprehensive review and outlook

A viral outbreak is a global challenge that affects public health and safety. The coronavirus disease 2019 (COVID-19) has been spreading globally, affecting millions of people worldwide, and led to significant loss of lives and deterioration of the global economy. The current adverse effects caused by the COVID-19 pandemic demands finding new detection methods for future viral outbreaks. The environment's transmission pathways include and are not limited to air, surface water, and wastewater environments. The wastewater surveillance, known as wastewater-based epidemiology (WBE), can potentially monitor viral outbreaks and provide a complementary clinical testing method. Another investigated outbreak surveillance technique that has not been yet implemented in a sufficient number of studies is the surveillance of Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) in the air. Artificial intelligence (AI) and its related machine learning (ML) and deep learning (DL) technologies are currently emerging techniques for detecting viral outbreaks using global data. To date, there are no reports that illustrate the potential of using WBE with AI to detect viral outbreaks. This study investigates the transmission pathways of SARS-CoV-2 in the environment and provides current updates on the surveillance of viral outbreaks using WBE, viral air sampling, and AI. It also proposes a novel framework based on an ensemble of ML and DL algorithms to provide a beneficial supportive tool for decision-makers. The framework exploits available data from reliable sources to discover meaningful insights and knowledge that allows researchers and practitioners to build efficient methods and protocols that accurately monitor and detect viral outbreaks. The proposed framework could provide early detection of viruses, forecast risk maps and vulnerable areas, and estimate the number of infected citizens.

Assessment of COVID-19 Lockdown Impact on the Air Quality in Eastern Spain: PM and BTX in Urban, Suburban and Rural Sites Exposed to Different Emissions

In early 2020, the COVID-19 pandemic spread globally, and severe measures to control it were implemented. This study investigates the impact of the lockdown on the air quality of three provinces in the Valencia region, eastern Spain, in the years 2015–2020, focusing on particulate matter (PM). A thorough statistical analysis using different approaches is conducted. Hourly patterns are also assessed. In addition, the role of meteorological parameters on PM is explored. The results indicate an overall PM10 reduction of 16.5% when comparing the lockdown in 2020 and the 2015–2019 period, while PM2.5 increased by 3.1%. As expected, urban zones experienced higher reductions than suburban zones, which experienced a PM concentration increase. The impact of the drastic drops of benzene, toluene and xylene (77.4%, 58.0% and 61.8%, respectively) on the PM values observed in urban sites is discussed. Our study provides insights on the effect of activity changes over a wide region covering a variety of air quality stations, urban, suburban and rural, and different emission types. The results of this work are a valuable reference and suggest the need for considering different factors when establishing scientific air pollution control strategies.

Ozone pollution threatens the production of major staple crops in East Asia

East Asia is a hotspot of surface ozone (O₃) pollution, which hinders crop growth and reduces yields. Here, we assess the relative yield loss in rice, wheat and maize due to O₃ by combining O₃ elevation experiments across Asia and air monitoring at about 3,000 locations in China, Japan and Korea. China shows the highest relative yield loss at 33%, 23% and 9% for wheat, rice and maize, respectively. The relative yield loss is much greater in hybrid than inbred rice, being close to that for wheat. Total O₃-induced annual loss of crop production is estimated at US$63 billion. The large impact of O₃ on crop production urges us to take mitigation action for O₃ emission control and adaptive agronomic measures against the rising surface O₃ levels across East Asia.

Changes in tropospheric ozone concentration over Indo-Gangetic Plains: the role of meteorological parameters

This study seeks to understand and quantify the changes in tropospheric ozone (O3) in lower troposphere (LT), middle troposphere (MT) and upper middle troposphere (UMT) over the Indo-Gangetic Plains (IGPs), India during the COVID-19 lockdown 2020 with that of pre-lockdown 2019. The gridded datasets of ozone from the European Centre for Medium-range Weather Forecasts (ECMWF) reanalysis product, ERA5 in combination with statistical interpolated (IDWs) surface NO2 observations, present a consistent picture and indicate a significant tropospheric ozone enhancement over IGP during COVID-19 lockdown restrictions in May 2020. The Paper also examines the influencing role of meteorological parameters on increasing ozone concentration. Over LT, an increase in O3 concentration (23%) is observed and in MT to UMT an enhancement of about 9–18% in O3 concentration have been seen during May 2020 with respect to May 2019. An investigation on causes of increasing  ozone concentration (35–85 ppbv) from MT to UMT during May 2020 reveals that there was significant rise (by 1–6%) in low cloud cover (LCC). Notably, higher LCC increases the backscattering of upward solar radiation from the top of the atmosphere. A positive difference of 5–25 W/m2 in upward solar radiation (USR) is observed across the entire study region. The result suggests that higher LCC significantly contributed to the enhanced USR. Thereby, resulting in higher photolysis rate that lead to an increase in mid tropospheric ozone concentration during May 2020. The results highlight the importance of LCC as an important pathway in ozone formation and aid in scientific understanding of it.

The Impacts on Greenhouse Gases Emission during the COVID-19 lockdown in the US: An Economic Input-Output Life Cycle Assessment

The SARS-CoV-2 virus pandemic (COVID-19) is causing disruptions to energy, finance, tourism, and trade industries all around the world. These disruptions are the result of quarantining and lockdowns that cause reductions in production and consumptions. This change in production and consumption rates has environmental consequences. This study investigates the environmental effects of COVID-19 lockdown in the United States by Input-Output Life Cycle Assessment (IO-LCA) approach. The analysis is based on extraction of economic data in the US. The simulated results are based on different durations and strategies of lockdown measures. Among all industrial categories, utilities, which include power generation and supply, water supply, and natural gas supply sectors, saw the most significant reductions by approximately 110 kt CO₂-eq in the first quarter and 265 kt CO₂-eq in the second quarter of 2020. The assessed reductions were the results of both direct emission reductions caused by the shutdown of certain industries and also indirect emission reductions from upstream industries. The proposed methodology provides an effective guideline to predict the greenhouse gases emissions, which can be used as a prediction method for different regions in the world.