COVID-19 pandemic persuaded lockdown effects on environment over stone quarrying and crushing areas

The effects of COVID-19 on agriculture supply chain, food security, and environment: a review

COVID-19 has a deep impact on the economic, environmental, and social life of the global population. Particularly, it disturbed the entire agriculture supply chain due to a shortage of labor, travel restrictions, and changes in demand during lockdowns. Consequently, the world population faced food insecurity due to a reduction in food production and booming food prices. Low-income households face food security challenges because of limited income generation during the pandemic. Thus, there is a need to understand comprehensive strategies to meet the complex challenges faced by the food industry and marginalized people in developing countries. This research is intended to review the agricultural supply chain, global food security, and environmental dynamics of COVID-19 by exploring the most significant literature in this domain. Due to lockdowns and reduced industrial production, positive environmental effects are achieved through improved air and water quality and reduced noise pollution globally. However, negative environmental effects emerged due to increasing medical waste, packaging waste, and plastic pollution due to disruptions in recycling operations. There is extensive literature on the effects of COVID-19 on the environment and food security. This study is an effort to review the existing literature to understand the net effects of the pandemic on the environment and food security. The literature suggested adopting innovative policies and strategies to protect the global food supply chain and achieve economic recovery with environmental sustainability. For instance, food productivity should be increased by using modern agriculture technologies to ensure food security. The government should provide food to vulnerable populations during the pandemic. Trade restrictions should be removed for food trade to improve international collaboration for food security. On the environmental side, the government should increase recycling plants during the pandemic to control waste and plastic pollution.

Characteristics of airborne particles in stone quarrying areas: Human exposure assessment and mitigation

This investigation aims to assess the levels of human exposure to airborne particulate matter (PM) in various locations of a natural stone quarry for the first time based on simultaneous measurements of both PM mass and number concentrations (PMC and PNC). A quarry located in Danang city, Vietnam, considered to be a "hotspot" of air pollution in the city, was selected for detailed investigations. Both PMC and PNC were found to be significantly higher (1.2-6.0 times) within the quarry compared to surrounding areas. Mechanical activities during mining, notably crushing, screening, hauling, and loading stones, contributed to increased emissions of PM in the coarser mode (1-10 μm) compared to the accumulation mode (0.1-1 μm) and thus increased deposition of PM1-10 in the human upper respiratory tract. In contrast, combustion activities, especially the diesel engine exhaust from various machines and vehicles used in the quarry, resulted in increased emissions of small particles in the accumulation mode that dominated the PNC and in their deposition in the lower respiratory tract. Simultaneous measurements of PNC and PMC revealed that the PM counts were strongly associated with PM deposition in the alveolar region (accounting for ≈ 76% of total PNC of particles less than 10 μm, N10), while the PM mass concentration was a better indicator of the deposition of PM in the head airway region (≈92% of total PMC of PM10). Overall, this study demonstrates the significance of measuring both PNC and PMC to assess PM exposure levels, regional respiratory doses, and potential health effects associated with human exposure to PM generated from stone quarrying activities. The novelty of this work is the integration of real-time mass and number concentrations of PM over the size range from 20 nm to 10 μm to provide insights into respiratory deposited doses of size-fractionated PM among quarry workers.

From Over-Tourism to Under-Tourism via COVID-19: Lessons for Sustainable Tourism Management

With various strains of the novel coronavirus emerging during the last few years, there is a need to reinvent and manage the tourism industry by engaging various stakeholders. Industry and policymakers need to observe the shift and curate tourism-related products and offerings accordingly. In light of the increasing demand for innovations and future directions in the post-COVID-19 period, this article conducts a bibliometric analysis for sustainable tourism studies spanning the years 1990-2021. This paper presents an integrative review of tourism, environment and sustainable tourism to reveal geographical, contextual, and methodological directions for future research. The comprehensive analysis includes contributions on topics and methods, country collaborations, and thematic analysis. The findings are consistent with the Sustainable Development Goals of sustainable production and consumption (SDG-12), with a particular emphasis on sustainable tourism to promote local culture and create jobs (SDG-12.b) and on sustainable growth (SDG-13). The study's findings can be used to inform future policies and directions; for example, the findings indicate that the hospitality industry is facing challenges that necessitate new regulations to address its socioeconomic and environmental impacts.

Effect of lockdown and associated mobility changes amid COVID-19 on air quality in the Kathmandu Valley, Nepal

The COVID-19 pandemic caused a setback for Nepal, leading to nationwide lockdowns. The study analyzed the impact of lockdown on air quality during the first and second waves of the COVID-19 pandemic in the Kathmandu Valley. We analyzed 5 years of ground-based air quality monitoring data (2017-2021) from March to July and April to June for the first and second wave lockdowns, respectively. A significant decrease in PM2.5 (particulate matter with an aerodynamic diameter ≤ 2.5 μm) concentrations was observed during the lockdowns. The highest rate of decline in PM2.5 levels was observed during May and July compared to the pre-pandemic year. The PM2.5 concentration during the lockdown period remained within the WHO guideline limit and NAAQS for the maximum number of days compared to the lockdown window in the pre-pandemic years (2017-2019). Likewise, lower PM2.5 levels were observed during the second wave lockdown, which was characterized by a targeted lockdown approach (smart lockdown). We found a significant correlation of PM2.5 concentration with community mobility changes (i.e., walking, driving, and using public transport) from the Spearman correlation analysis. Lockdown measures restricted human mobility that led to a lowering of PM2.5 concentrations. Our findings can be helpful in developing urban air quality control measures and management strategies, especially during high pollution episodes.

Quantitative assessment of land surface temperature and vegetation indices on a kilometer grid scale

Due to expanding populations and thriving economies, studies into the built environment's thermal characteristics have increased. This research tracks and predicts how land use and land cover (LULC) changes may affect ground temperatures, urban heat islands, and city thermal fields (UTFVI). The current study examines land surface temperature (LST), urban thermal field variance index (UTFVI), normalized difference built-up index (NDBI), normalized difference vegetation index (NDVI), and land use land cover (LULC) on a kilometer scale. According to the comparative study, the mean LST decreases by 3 °C and the NDVI increases considerably. Correlation analysis showed that LST and NDVI are inversely connected, while LST and NDBI are positively correlated. NDVI and NDBI have a strong negative association, while LST and UTFVI have a positive correlation. Urban planners and environmentalists can study the LST's effects on land surface parameters in different environmental contexts during the lockout period. The urban heat island (UHI) phenomenon, in which the land surface qualities of an urban region cause a change in the urban thermal environment, forms and intensifies over an urban area. The minimum and maximum LST in grid number 1 in 2009 was 20.30 °C and 29.91 °C, respectively, with a mean LST of 25.1 °C. There was a decline in the minimum and maximum LST in grid number 1 in 2020 with a minimum and maximum LST of 17.31 °C and 25.35 °C, respectively, with a mean LST of 21.33 °C. There was a 3.8 °C drop in the LST of this grid. The minimum and maximum NDVI were also - 0.16 and 0.59, respectively, with an average NDVI value of 0.21. Therefore, it is essential to evaluate and foresee the impact of LULC change on the thermal environment and examines the connection between LULC shifts with subsequent changes in land surface temperature (LST) along with the UHI phenomenon. Maps of the UTFVI reveal positive UHI phenomena, with the highest UTFVI zones occurring over the developed area and none over the adjacent rural territory. During the summer months, the urban area with the strongest UTFVI zone grows noticeably larger than it does during the winter months during the forecasted years. Future policymakers and city planners can mitigate the effects of heat stress and create more sustainable urban environments by evaluating the expected distribution maps of LULC, LST, UHI, and UTFVI.

Environmental Ethics and Mental Health during COVID-19

As the cause of the COVID-19 pandemic, climate change, population density, ecological changes, etc. natural phenomena are shown. The physical, chemical, biological, socioeconomic, cultural and psychological effects of COVID-19 have been felt all over the world. COVID-19 negatively affects the environment with an unbalanced increase in medical waste and disposable products, while quarantine and pandemic measures have given an opportunity for nature to renew itself. The causes and consequences of COVID-19 have brought the concepts of environmental health and therefore environmental ethics to the agenda of healthcare professionals. As the environmental ethics attitudes and behaviors of health professionals develop, health professionals will be able to take initiatives to create these attitudes and behaviors in society. Environmental ethics has been evaluated in the context of public health, mostly in the physical health. However, environmental ethics is also very important in terms of community mental health. Living in an unhealthy environment threatens mental health. Because people want to live in a safe environment, every factor that threatens this trust poses a risk for mental health. There is actually literally no way to talk about happiness in an environment where there is no environmental order and nature is deteriorated and polluted. Therefore, we aimed to explain the concepts of environmental health, environmental ethics and mental health during the COVID-19 process. Thus, an important strategy development in the pandemic process can be achieved by enabling the assessment and management of the causes of the COVID-19 pandemic from a broader perspective.

Assessment of NO2 concentrations over industrial state Jharkhand, at the time frame of pre, concurrent, and post-COVID-19 lockdown along with the meteorological behaviour: an overview from satellite and ground approaches

Burning of fossil fuels in the form of coal or gasoline in thermal power plants, industries, and automobiles is a prime source of nitrogen dioxide (NO₂), a major air pollutant causing health problems. In this paper, spatio-temporal unevenness of NO₂ concentrations via both spaceborne Sentinel-5P and ground-based in situ data have been studied for the period of 2017-2021. Annual and seasonal distribution of TROPOMI-NO₂ depict consistency over the Jharkhand region, highlighting six hotspot regions. As compared to 2019, a notable dip of 11% in the spatial annual average TROPOMI-NO₂ was achieved in 2020, which were elevated again by 22% in 2021 as the lockdown gradually goes out of the picture. Among eight ground-monitoring stations, Tata and Golmuri stations always displayed a higher level of TROPOMI-NO₂ ranges up to 15.2 ×10¹⁵molecules.cm^-2 and 16.9 ×10¹⁵molecules.cm^-2 respectively, as being located in the highly industrialised district of Jamshedpur. A big percentage reduction of up to 30% in TROPOMI-NO₂ has been reported in Jharia and Bastacola stations in Dhanbad in the lockdown phase of 2020 compared to 2019. Good agreement between TROPOMI-NO₂ and surface-NO₂ has been achieved with R = 0.8 and R = 0.71 during winter and post-monsoon respectively. Among four meteorological parameters, TROPOMI-NO₂ was majorly found to be influenced by precipitation, having R = 0.6-0.8 for almost all stations. More advanced satellite algorithms and ground-based data may be used to estimate NO₂ in places where monitoring facilities are limited and thus can help in air pollution control policy.

The Nexus Between COVID-19 Factors and Air Pollution

BACKGROUND AND OBJECTIVE

There have been significant effects of the current coronavirus-19 (COVID-19) infection outbreak on many facets of everyday life, particularly the environment. Despite the fact that a number of studies have already been published on the topic, an analysis of those studies' findings on COVID-19's effects on environmental pollution is still lacking. The goal of the research is to look into greenhouse gas emissions and air pollution in Bangladesh when COVID-19 is under rigorous lockdown. The specific drivers of the asymmetric relationship between air pollution and COVID-19 are being investigated.

METHODS

The nonlinear relationship between carbon dioxide ( C O 2 ) emissions, fine particulate matter ( P M 2 . 5 ) , and COVID-19, as well as its precise components, are also being investigated. To examine the asymmetric link between COVID-19 factors on C O 2 emissions and P M 2 . 5 , we employed the nonlinear autoregressive distributed lag (NARDL) model. Daily positive cases and daily confirmed death by COVID-19 are considered the factors of COVID-19, with lockdown as a dummy variable.

RESULTS

The bound test confirmed the existence of long-run and short-run relationships between variables. Bangladesh's strict lockdown, enforced in reaction to a surge of COVID-19 cases, reduced air pollution and dangerous gas emissions, mainly C O 2 , according to the dynamic multipliers graph.

Impact assessment of COVID-19 global pandemic on water, environment, and humans

One of the most significant threats to global health since the Second World War is the COVID-19 pandemic. Due to COVID-19 widespread social, environmental, economic, and health concerns. Other unfavourable factors also emerged, including increased trash brought on by high consumption of packaged foods, takeout meals, packaging from online shopping, and the one-time use of plastic products. Due to labour shortages and residents staying at home during mandatory lockdowns, city municipal administrations' collection and recycling capacities have decreased, frequently damaging the environment (air, water, and soil) and ecological and human systems. The COVID-19 challenges are more pronounced in unofficial settlements of developing nations, particularly for developing nations of the world, as their fundamental necessities, such as air quality, water quality, trash collection, sanitation, and home security, are either non-existent or difficult to obtain. According to reports, during the pandemic's peak days (20 August 2021 (741 K cases), 8 million tonnes of plastic garbage were created globally, and 25 thousand tonnes of this waste found its way into the ocean. This thorough analysis attempts to assess the indirect effects of COVID-19 on the environment, human systems, and water quality that pose dangers to people and potential remedies. Strong national initiatives could facilitate international efforts to attain environmental sustainability goals. Significant policies should be formulated like good quality air, pollution reduction, waste management, better sanitation system, and personal hygiene. This review paper also elaborated that further investigations are needed to investigate the magnitude of impact and other related factors for enhancement of human understanding of ecosystem to manage the water, environment and human encounter problems during epidemics/pandemics in near future.

Meteorological, PM2.5 and PM10 factors on SARS-COV-2 transmission: The case of southern regions in Chile

There are several determinants of a population's health, including meteorological factors and air pollution. For example, it is well known that low temperatures and air pollution increase mortality rates in infant and elderly populations. With the emergence of SARS-COV-2, it is important to understand what factors contribute to its mitigation and control. There is some research in this area which shows scientific evidence on the virus's behavior in the face of these variables. This research aims to quantify the impact of climatic factors and environmental pollution on SARS-COV-2 specifically the effect on the number of new infections in different areas of Chile. At the local level, historical information available from the Department of Statistics and Health Information, the Chilean National Air Quality Information System, the Chilean Meteorological Directorate, and other databases will allow the generation of panel data suitable for the analysis. The results show the significant effect of pollution and climate variables measured in lags and will allow us to explain the behavior of the pandemic by identifying the relevant factors affecting health, using heteroskedastic models, which in turn will serve as a contribution to the generation of more effective and timely public policies for the control of the pandemic.

Changes in physicochemical, heavy metals and air quality linked to spot Aplocheilus panchax along Mahanadi industrial belt of India under COVID-19-induced lockdowns

Positive effects of COVID-19-induced lockdowns on environment are well documented although pre-planned experiments for such analyses and appearance of fish species are lacking. We hypothesize that spotting the fish Aplocheilus panchax along the industrial belt of Mahanadi River near Cuttack in a never seen manner could be due to the regenerated environment. Heavy metals, water and air qualities along with spotting A. panchax in up, mid and downstream of Mahanadi River near Jagatpur industrial basins were analysed during pre-(end of March 2020) and after 60 days of lockdowns (last week of May 2020). An overall 45, 61, 79, 100, 97 and 90% reduction of Fe, Cu, Ni, Cd, Pb and Zn was recorded in the studied area after lockdowns, respectively. Similarly, dissolved oxygen and pH were elevated by 26 and 7%, respectively. Water temperature, conductivity and total dissolved solute levels were reduced by 7, 46 and 15%, respectively, which were again elevated during post-lockdowns during 2021 as observed from the Landsat-8 OLI satellite data. Air NO₂, SO₂, NH₃, PM_2.5, PM₁₀ and CO levels were alleviated by 58.75, 80.33, 72.22, 76.28, 77.33 and 80.15%, respectively. Finally, for the first time, about 12 A. panchax fish per 100 m shore line in the area were spotted. The observed lockdown-induced environmental healing at the studied area could contribute to the appearance of A. panchax in the study site and therefore a stringent environmental audit is suggested during post-COVID-19 periods to make the regenerated environmental status long lasting in such habitats.

Improved air quality leads to enhanced vegetation growth during the COVID-19 lockdown in India

The direct effect of pandemic induced lockdown (LD) on environment is widely explored, but its secondary impacts remain largely unexplored. Therefore, we assess the response of surface greenness and photosynthetic activity to the LD-induced improvement of air quality in India. Our analysis reveals a significant improvement in air quality marked by reduced levels of aerosols (AOD, -19.27%) and Particulate Matter (PM 2.5, -23%) during LD (2020)from pre-LD (March-September months for the period 2017-2019). The vegetation exhibits a positive response, reflected by the increase in surface greenness [Enhanced Vegetation Index (EVI, +10.4%)] and photosynthetic activity [Solar Induced Fluorescence (SiF, +11%)], during LD from pre-LD that coincides with two major agricultural seasons of India; Zaid (March-May) and Kharif (June-September). In addition, the croplands show a higher response [two-fold in EVI (14.45%) and four-fold in SiF (17.7%)] than that of forests. The prolonged growing period (phenology) and high rate of photosynthesis (intensification) led to the enhanced greening during LD owing to the reduced atmospheric pollution. This study, therefore, provides new insights into the response of vegetation to the improved air quality, which would give ideas to counter the challenges of food security in the context of climate pollution, and combat global warming by more greening.

Exploring the effect of COVID-19 pandemic lockdowns on urban cooling: A tale of three cities

COVID-19 pandemic has had a major impact on our society, environment and public health, in both positive and negative ways. The main aim of this study is to monitor the effect of COVID-19 pandemic lockdowns on urban cooling. To do so, satellite images of Landsat 8 for Milan and Rome in Italy, and Wuhan in China were used to look at pre-lockdown and during the lockdown. First, the surface biophysical characteristics for the pre-lockdown and within-lockdown dates of COVID-19 were calculated. Then, the land surface temperature (LST) retrieved from Landsat thermal data was normalized based on cold pixels LST and statistical parameters of normalized LST (NLST) were calculated. Thereafter, the correlation coefficient (r) between the NLST and index-based built-up index (IBI) was estimated. Finally, the surface urban heat island intensity (SUHII) of different cities on the lockdown and pre-lockdown periods was compared with each other. The mean NLST of built-up lands in Milan (from 7.71 °C to 2.32 °C), Rome (from 5.05 °C to 3.54 °C) and Wuhan (from 3.57 °C to 1.77 °C) decreased during the lockdown dates compared to pre-lockdown dates. The r (absolute value) between NLST and IBI for Milan, Rome and Wuhan decreased from 0.43, 0.41 and 0.16 in the pre-lockdown dates to 0.25, 0.24, and 0.12 during lockdown dates respectively, which shows a large decrease for all cities. Analysis of SUHI for these cities showed that SUHII during the lockdown dates compared to pre-lockdown dates decreased by 0.89 °C, 1.78 °C, and 1.07 °C respectively. The results indicated a high and substantial impact of anthropogenic activities and anthropogenic heat flux (AHF) on the SUHI due to the substantial reduction of huge anthropogenic pressure in cities. Our conclusions draw attention to the contribution of COVID-19 lockdowns (reducing the anthropogenic activities) to creating cooler cities.

Correlating the trends of COVID-19 spread and air quality during lockdowns in Tier-I and Tier-II cities of India-lessons learnt and futuristic strategies

The present study focuses on the impact of early imposed lockdowns and following unlocking phases on the status of air quality in six Tier-I and nine Tier-II cities of India as compared to the pre-lockdown measures. Furthermore, the study highlights the possible correlation of air quality index (AQI) with the initial trend of COVID-19 issues including the vaccination cases. Based on the statistical data analysis, we observed that the long-term averages for representing the short-term pre-lockdown conditions can impose a healing effect to the observed anomalies in air pollution data. However, the reduction in air pollution during the imposed lockdown series was only a phenomenal consequence, and the trends started reversing during the later phases of partial unlocking, where the correlation showed reversing trends. Being a yearly averaged parameter, the marginal reductions in the exceedance factor (EF) alone could not dictate air quality compared to the AQI. As there is incoherent variability in the pollutant distributions among the cities during various phases of the study, the trend analysis served as a preferable criterion to choose the preferred sources of variations. Based on the results, the correlation analysis revealed that air quality expressed in terms of AQI can act as an important precursor to estimate the critical phase of COVID-19 spread and the effectiveness of various control measures taken during each phase. Based on our proposed ranking, Kolkata and Patna are ranked first in the Tier-I and Tier-II cities respectively according to their responsiveness to the various institutionalized restrictions in terms of air quality parameters.

Assessment of the dynamics of urban surface temperatures and air pollution related to COVID-19 in a densely populated City environment in East Java

The COVID-19 pandemic that has hit the whole world has caused losses in various aspects. Several countries have implemented lockdowns to curb the spread of the SARS-CoV-2 virus that caused death. However, for developing countries such as Indonesia, it is not suitable for lockdown because it considers the economic recession. Instead, the Large-scale Social Restrictions (LSSR) regulation is applied, the same as the partial lockdown. Thus, it is hypothesized that implementing LSSR that limits anthropogenic activities can reduce heat emissions and air pollution. Utilization of remote sensing data such as Terra-MODIS LST and Sentinel-5P images to investigate short-term trends (i.e., comparison between baseline year and COVID-19 year) in surface temperature, Surface Urban Heat Islands Intensity (SUHII), and air pollution such as NO₂, CO, and O₃ in Malang City and Surabaya City, East Java Province. Spatial downscaling of LST using the Random Forest Regression technique was also carried out to transform the spatial resolution of the Terra-MODIS LST image to make it feasible on a city scale. Raster re-gridding was also implemented to refine the Sentinel-5P spatial resolution. The accuracy of LST spatial downscaling results is quite satisfactory in both cities. Surface temperatures in both cities slightly decreased (below 1 °C) during LSSR was applied (P < 0.05). SUHII in both cities experienced a slight increase in both cities during LSSR. NO₂ gas was reduced significantly (P < 0.05) in Malang City (∼38%) and Surabaya City (∼28%) during LSSR phase due to reduced vehicle traffic and restrictions on anthropogenic activities. However, CO and O₃ gases did not indicate anomaly during LSSR. Moreover, this study provides insight into the correlation between SUHII change and the distribution of air pollution in both cities during the pandemic year. Air temperature and wind speed are also added as meteorological factors to examine their effect on air pollution. The proposed models of spatial downscaling LST and re-gridding satellite-based air pollution can help decision-makers control local air quality in the long and short term in the future. In addition, this model can also be applied to other ecological research, especially the input variables for ecological spatial modeling.

Association Between Air Pollution, Climate Change, and COVID-19 Pandemic: A Review of the Recent Scientific Evidence

Background: Recent studies indicated the possible relationship between climate change, environmental pollution, and Coronavirus Disease 2019 (COVID-19) pandemic. This study reviewed the effects of air pollution, climate parameters, and lockdown on the number of cases and deaths related to COVID-19. Methods: The present review was performed to determine the effects of weather and air pollution on the number of cases and deaths related to COVID-19 during the lockdown. Articles were collected by searching the existing online databases, such as PubMed, Science Direct, and Google Scholar, with no limitations on publication dates. Afterwards, this review focused on outdoor air pollution, including PM2.5, PM10, NO2, SO2, and O3, and weather conditions affecting severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)/COVID-19. Results: Most reviewed investigations in the present study showed that exposure to air pollutants, particularly PM2.5 and NO2, is positively related to COVID-19 patients and mortality. Moreover, these studies showed that air pollution could be essential in transmitting COVID-19. Local meteorology plays a vital role in coronavirus spread and mortality. Temperature and humidity variables are negatively correlated with virus transmission. The evidence demonstrated that air pollution could lead to COVID-19 transmission. These results support decision-makers in curbing potential new outbreaks. Conclusions: Overall, in environmental perspective-based COVID-19 studies, efforts should be accelerated regarding effective policies for reducing human emissions, bringing about air pollution and weather change. Therefore, using clean and renewable energy sources will increase public health and environmental quality by improving global air quality.

Lockdown Amid COVID-19 Ascendancy over Ambient Particulate Matter Pollution Anomaly

Air is a diverse mixture of gaseous and suspended solid particles. Several new substances are being added to the air daily, polluting it and causing human health effects. Particulate matter (PM) is the primary health concern among these air toxins. The World Health Organization (WHO) addressed the fact that particulate pollution affects human health more severely than other air pollutants. The spread of air pollution and viruses, two of our millennium's most serious concerns, have been linked closely. Coronavirus disease 2019 (COVID-19) can spread through the air, and PM could act as a host to spread the virus beyond those in close contact. Studies on COVID-19 cover diverse environmental segments and become complicated with time. As PM pollution is related to everyday life, an essential awareness regarding PM-impacted COVID-19 among the masses is required, which can help researchers understand the various features of ambient particulate pollution, particularly in the era of COVID-19. Given this, the present work provides an overview of the recent developments in COVID-19 research linked to ambient particulate studies. This review summarizes the effect of the lockdown on the characteristics of ambient particulate matter pollution, the transmission mechanism of COVID-19, and the combined health repercussions of PM pollution. In addition to a comprehensive evaluation of the implementation of the lockdown, its rationales-based on topographic and socioeconomic dynamics-are also discussed in detail. The current review is expected to encourage and motivate academics to concentrate on improving air quality management and COVID-19 control.

Analysis of the Lockdown Effects on the Economy, Environment, and COVID-19 Spread: Lesson Learnt from a Global Pandemic in 2020

Lockdown policies have been implemented to reduce COVID-19 transmission worldwide. However, the shutdown of activities has resulted in large economic losses, and it has been widely reported that lockdown measures have resulted in improved air quality. Therefore, many previous studies have attempted to investigate the impacts of the COVID-19-induced lockdowns on the economy, environment, and COVID-19 spread. Nevertheless, the heterogeneity among countries worldwide in the economic, environmental, and public health aspects and the spatial effects of decomposition have not been well investigated in the existing related literature. In this study, based on the cross-sectional data of 158 countries in 2020 and the proposed nonlinear simultaneous spatial econometric models, we investigate the nonlinear and spatial impacts of the COVID-19-induced lockdowns on the economy, environment, and COVID-19 spread. The findings show that lockdowns have had statistically significant negative economic impacts and beneficial environmental consequences but no effect on COVID-19 spread. Noteworthily, this study also found the length of lockdown periods to affect the three domains of interest differently, with a piece of empirical evidence that the imposition of lockdowns for more than 31 days a year could result in economic impairments but contribute to environmental improvements. Lockdowns were shown to have substantially reduced PM2.5 not only in the countries that imposed the measures but also indirectly in the neighboring countries as a spatial spillover effect.

Greenhouse Gas Emission: Perception during the COVID-19 Pandemic

The period 2020/2021 was an unprecedented and historic time for industrial, economic, and societal activities all over the world with great challenges to human health, the ecosystems, and other aspects of human endeavors owing to the COVID-19 or SARS-CoV-2 (CV-19) pandemic which is now a topical aspect of research interest. Despite the negative impacts of the CV-19 pandemic, there are also positive reports during the CV-19 pandemic such as the reduction of gas flare, reduction in the burning of fossil fuels from automobile exhaust and a reduction in the other ensuing factors of greenhouse gases emissions (which is one of the major drives for global warming and climate change as well as other environmental effluences). Hence, this brief perspective review study is centered on greenhouse gas (GHG) emission. The study employs a methodical approach to analyze some already available research studies from existing publications and databases on GHG emission using the perception during the CV-19 pandemic. The specific findings from this review show that, from the meteorological perspective, the global response to the catastrophe ensuing from the CV-19 pandemic has a great influence on the reduction of GHGs, the reduction in the burning of fossil fuels from automobiles and industrial devices, and the reduction in the other ensuing factors of GHG emission. Hence, it will not be far from the truth to conclude that there is a possible positive connection between the CV-19 pandemic and GHG emissions. The study has a direct impact on the environment owing to the negative and positive environmental consequences of the CV-19 pandemic. Suggestions and recommendations in the form of future prospects of GHG emission vis-à-vis global warming and climate change are also discussed. Furthermore, suggestions on how to improve food security and agriculture during a pandemic such as the CV-19 outbreak period are highlighted.

CO2 emissions persistence: Evidence using fractional integration

The main cause of climate change are carbon dioxide emissions. In the context of the COVID-19 pandemic, the number of emissions has been significantly reduced for the first time in many years. Now it is necessary to answer the question of whether CO2 emissions are stationary or not, because the results will let us know whether environmental policies have to be strengthened rather than relaxed in intensity. To this end, this paper investigates the persistence in CO2 emissions in a group of countries to determine if shocks in the series have permanent or transitory effects. The results, based on fractional integration indicate evidence of mean reversion, with values of the differencing parameter constrained between 0 and 1 in all cases, independently of the assumption made about the error term (white noise or autocorrelation). Focusing on the areas under examination, it is obtained that the EU27+UK, Japan and the US present the lowest degrees of integration, while Russia, China and India display the highest values. Decreasing time trends are only observed for the EU27+UK and US.

An insight on the impact of COVID-19 on the global and Turkish mining industry

BACKGROUND: COVID-19 affected numerous industries and the mining industry has not been immune to the adverse impacts caused by the pandemic. OBJECTIVE: This study examines the importance of the mining industry and its benefits to the economy of the producing countries. The paper also gives an insight into the pre-COVID global and Turkish mining industries and investigates the impact of the pandemic on the global and Turkish mining sectors. Furthermore, the study suggests numerous measures that should be adopted in mines to limit the spread of COVID-19 and conduct mining operations safely and efficiently. METHODS: An extensive literature review was conducted and relevant papers on the importance and benefits of the mining industry, the Turkish and global mining industry, and the impact of COVID-19 on the Turkish and global mining industry were studied. RESULTS: The COVID-19 crisis has deeply affected metal and mineral production and the economic sectors that depend on the mining industry for supplies. The most significant impacts caused by the COVID-19 pandemic on the global mining industry consist of the drastic decline in demand and production and the decrease in the prices of several commodities. As with any complex global situation, the mining industries of some countries were affected more than others by the COVID-19 crisis. The Turkish mining industry was to some extent affected by the COVID-19 crisis, but it quickly recovered. CONCLUSIONS: An efficient planning of operations and adopting effective measures and precautions enable limiting the spread of COVID-19 in quarries and mines.

COVID-19 Tweets Classification during Lockdown Period Using Machine Learning Classifiers

In recent years, COVID-19 has been regarded as the most dangerous pandemic for several countries. On various social media platforms, such as Twitter, Facebook, and Instagram, a variety of rumours, hypes, and news are published. This might have a detrimental impact on people’s life. As a result, social media platforms have always had a difficult time authenticating this fake information. Different machine learning (ML) and deep learning (DL) classifiers were used in this work to categorize the continuing impacts of tweets and forecast their after-effects. Support vector machine (SVM), random forest (RF), decision tree (DT), and k-nearest neighbor (KNN) were used for classification, while AdaBoost and convolutional neural network (CNN) were utilized for future effects. The tweets dataset from Kaggle was used to train the SVM, RF, KNN, and DT models, which were then assessed on multiple evaluation criteria such as accuracy, precision, recall, and F1-score, using a 70 : 30 ratio. The CNN and AdaBoost, on the other hand, have been taught to detect the mean square error, root mean square error, and mean absolute error. With 0.74 and 0.73 percent score out of 1, respectively, RF and SVM exhibit the best accuracy in impact when classifying the outcomes on the obtained dataset. In terms of a regression problem, CNN beat the ADA Regressor across the board.

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.

A mini-review: positive impact of COVID-19 on Arial health and ecology

COVID-19 can cause global pandemics; however, no specific vaccine has been recommended for COVID-19. Nearly 216 countries are trying to stop the spread of the disease, recover from it, and improve its mobility. In a way that people have not experienced in recent years, the COVID-19 pandemic affected humans through the year 2020. To stop the spread of the disease, many governments declared a complete lockdown.The nationwide lockdown had some positive effects on the environment even though it led to a decline in global economic growth. Air pollution levels reduced dramatically as a result of this lockdown on pollution. Most of Europe's populated cities saw a reduction in NO2 concentration of 45-54%. COVID-19 and air, water, and ecology are connected via two pathways, one occurring before the spread of the disease and the other following after. As a result of industrial activity, transportation, and high human density, pollutants were high in many areas before the disease spread. There was a reduction in population movements as well as a decline in human activities which resulted in a reduction in carbon dioxide emissions, an improvement of the ozone layer, as well as improvements in the Earth's weather and environment. As a result of a COVID-19 pandemic, human activities are negatively impacted, and the environment is positively affected. Our objective is to provide an assessment of the impact of human activities on the environment and ecology. During times of lockdown, there is a correlation between atmospheric changes and the behavior of natural creatures. Several significant findings are presented, including air pollution reduction, air quality improvement, ozone healing, and ecological sustainability. COVID-19 is beneficial for aerial health, aquatic health, and ecology in this paper.

Evaluation of Istanbul from the environmental components' perspective: what has changed during the pandemic?

This study aims to determine the 1-year change over the pandemic period in Istanbul, the megacity with the highest population in Turkey, based on environmental components. Among the environmental topics, water consumption habits, changes in air quality, changes due to noise elements, and most importantly, the changes in usage habits of disposable plastic materials that directly affect health have been revealed. The results obtained showed that, in Istanbul, 8.1 × 10⁸ gloves should be considered waste, and considering the population living in districts along coastal areas, the number of waste masks that are likely to end up in the sea was 325.648 pieces/day. The results of the air quality and noise measurements during the pandemic showed that reductions in parallel with human activities were recorded with the lockdown effect. The average noise values of the districts along both sides of the Bosporus, where urbanization is concentrated, were between 50 and 59 dB. The precautions taken during the pandemic have had an effective role in reducing air pollution in Istanbul. In the measurements, the parameters with effective reductions were PM₁₀ (7-47%), PM_2.5 (13-48%), NO₂ (13-38%), and SO₂ (10-56%). As a result, Istanbul's year of changes during the pandemic period, in terms of water, air, noise, and solid plastic wastes, which are the most important components of the environment, is presented.

Analysis of Particulate Matter Concentration Changes before, during, and Post COVID-19 Lockdown: A Case Study from Victoria, Mexico

The lockdown measures implemented due to the SARS-CoV-2 pandemic to reduce the epidemic curve, in most cases, have had a positive impact on air quality indices. Our study describes the changes in the concentration levels of PM2.5 and PM10 during the lockdown and post-lockdown in Victoria, Mexico, considering the following periods: before the lockdown (BL) from 16 February to 14 March, during the lockdown (DL) from 15 March to 2 May, and in the partial lockdown (PL) from 3 May to 6 June. When comparing the DL period of 2019 and 2020, we document a reduction in the average concentration of PM2.5 and PM10 of −55.56% and −55.17%, respectively. Moreover, we note a decrease of −53.57% for PM2.5 and −51.61% for PM10 in the PL period. When contrasting the average concentration between the DL periods of 2020 and 2021, an increase of 91.67% for PM2.5 and 100.00% for PM10 was identified. Furthermore, in the PL periods of 2020 and 2021, an increase of 38.46% and 31.33% was observed for PM2.5 and PM10, respectively. On the other hand, when comparing the concentrations of PM2.5 in the three periods of 2020, we found a decrease between BL and DL of −50.00%, between BL and PL a decrease of −45.83%, and an increase of 8.33% between DL and PL. In the case of PM10, a decrease of −48.00% between BL and DL, −40.00% between BL and PL, and an increase of 15.38% between the DL and PL periods were observed. In addition, we performed a non-parametric statistical analysis, where a significant statistical difference was found between the DL-2020 and DL-2019 pairs (x2 = 1.204) and between the DL-2021 and DL-2019 pairs (x2 = 0.372), with a p<0.000 for PM2.5, and the contrast between pairs of PM10 (DL) showed a significant difference between all pairs with p<0.01.

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.

COVID-19 and urban rivers: Effects of lockdown period on surface water pollution and quality- A case study of the Zarjoub River, north of Iran

Due to the spreading of the coronavirus (COVID-19) in Iran, restrictions and lockdown were announced to control the infection. In order to determine the effects of the lockdown period on the status of the water quality and pollution, the concentrations of Al, As, Ba, Cr, Cu, Mo, Ni, Pb, Se, and Zn, together with Na⁺, Mg²⁺, Ca²⁺ and electrical conductivity (EC), were measured in the Zarjoub River, north of Iran, in both pre-lockdown and post-lockdown periods. The results indicated that water pollution and associated human health risk reduced by an average of 30% and 39%, respectively, during the lockdown period. In addition, the multi-purpose water quality index also improved by an average of 34%. However, the water salinity and alkalinity increased during the lockdown period due to the increase of municipal wastewater and the use of disinfectants. The major sources of pollution were identified as weathering, municipal wastewater, industrial and agricultural effluents, solid waste, and vehicular pollution. PCA-MLR receptor model showed that the contribution of mixed sources of weathering and municipal wastewater in water pollution increased from 23 to 50% during the lockdown period. However, the contribution of mixed sources of industrial effluents and solid wastes reduced from 64 to 45%. Likewise, the contribution of traffic-related sources exhibited a reduction from 13% in the pre-lockdown period to 5% together with agricultural effluent in the post-lockdown period. Overall, although the lockdown period resulted in positive impacts on diminishing the level of water pollution caused by industrial and vehicular contaminants, the increase of municipal waste and wastewater is a negative consequence of the lockdown period.

Urban greenery for air pollution control: a meta-analysis of current practice, progress, and challenges

Most governmental initiatives in India, to leash down urban air pollution, have yielded little results till date, largely due to purely technocratic vision, which is shrouded by technological, economic, social, institutional, and political hardships. We present this reflective article on urban greenery, as a proposition to urban authorities (e.g., pollution regulators, environmental systems' managers, urban landscape planners, environmental policy makers), shift from purely technocratic way of thinking to thinking with nature, by strategic greening of urban spaces, for long-term air pollution prevention and control measures. To that end, we offer a meta-analysis of recent (post 2005) global literature using four-stage PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) approach. We open the narrative by briefing about main pollutant filtration mechanisms by trees, followed by cognitive aspects of species selection (e.g., deciduous vs. evergreen, air pollution tolerance index, environmental stressors). Till date, most Indian studies on urban greenery mostly but focused on physiological aspects of trees. Here, we draw attention of urban authorities to an equally compelling, but yet less explored, aspect: design criteria, with reference to two most common urban configurations, namely, street canyon and open road. With pictorial depictions, we enumerate various categories of street canyons and discuss aspect ratio (building height to street width) and various wind flow regimes (isolated roughness, wake interface, and skimming), that the urban authorities should be cognizant about to maximize pollutant removal efficiency. For open road, we discuss vegetation barriers, with special emphasis on canopy porosity/density functions. In the final sections, we reflect on a potential systems' thinking approach for on-ground implementation, comprising of revamping of urban forestry programs, research and development, community mobilization and stakeholder engagement, and strategic outreach. In addition, we emphasize on means to harness co-benefits of urban greenery, beyond mere pollutant removal, to garner support from urban residents' communities. Last but not the least, we also caution the urban authorities about the undesirable outcomes of urban greenery that will require more process-level research.

An application of artificial intelligence for investigating the effect of COVID-19 lockdown on three-dimensional temperature variation in equatorial Africa

We present interesting application of artificial intelligence for investigating effect of the COVID-19 lockdown on 3-dimensional temperature variation across Nigeria (2°-15° E, 4°-14° N), in equatorial Africa. Artificial neural networks were trained to learn time-series temperature variation patterns using radio occultation measurements of atmospheric temperature from the Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC). Data used for training, validation and testing of the neural networks covered period prior to the lockdown. There was also an investigation into the viability of solar activity indicator (represented by the sunspot number) as an input for the process. The results indicated that including the sunspot number as an input for the training did not improve the network prediction accuracy. The trained network was then used to predict values for the lockdown period. Since the network was trained using pre-lockdown dataset, predictions from the network are regarded as expected temperatures, should there have been no lockdown. By comparing with the actual COSMIC measurements during the lockdown period, effects of the lockdown on atmospheric temperatures were deduced. In overall, the mean altitudinal temperatures rose by about 1.1 °C above expected values during the lockdown. An altitudinal breakdown, at 1 km resolution, reveals that the values were typically below 0.5 °C at most of the altitudes, but exceeded 1 °C at 28 and 29 km altitudes. The temperatures were also observed to drop below expected values at altitudes of 0-2 km, and 17-20 km.

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.

Assessing the change of ambient air quality patterns in Jiangsu Province of China pre-to post-COVID-19

Following the outbreak of the novel coronavirus in early 2020, to effectively prevent the spread of the disease, major cities across China suspended work and production. While the rest of the world struggles to control COVID-19, China has managed to control the pandemic rapidly and effectively with strong lockdown policies. This study investigates the change in air pollution (focusing on the air quality index (AQI), six ambient air pollutants nitrogen dioxide (NO₂), ozone (O₃), sulphur dioxide (SO₂), carbon monoxide (CO), particulate matter with aerodynamic diameters ≤10 μm (PM₁₀) and ≤2.5 μm (PM_2.5)) patterns for three periods: pre-COVID (from 1 January to May 30, 2019), active COVID (from 1 January to May 30, 2020) and post-COVID (from 1 January to May 30, 2021) in the Jiangsu province of China. Our findings reveal that the change in air pollution from pre-COVID to active COVID was greater than in previous years due to the government's lockdown policies. Post-COVID, air pollutant concentration is increasing. Mean change PM_2.5 from pre-COVID to active COVID decreased by 18%; post-COVID it has only decreased by 2%. PM₁₀ decreased by 19% from pre-COVID to active COVID, but post-COVID pollutant concentration has seen a 23% increase. Air pollutants show a positive correlation with COVID-19 cases among which PM_2.5, PM₁₀ and NO₂ show a strong correlation during active COVID-19 cases. Metrological factors such as minimum temperature, average temperature and humidity show a positive correlation with COVID-19 cases while maximum temperature, wind speed and air pressure show no strong positive correlation. Although the COVID-19 pandemic had numerous negative effects on human health and the global economy, the reduction in air pollution and significant improvement in ambient air quality likely had substantial short-term health benefits; the government must implement policies to control post-COVID environmental issues.

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.

Impact of lockdown and crop stubble burning on air quality of India: a case study from wheat-growing region

The emergence of COVID-19 has brought the entire planet to a halt. Many countries, including India, were compelled to shut down most urban, industrial, social and other activities as a result of the pandemic. Due to a series of complete lockdowns imposed in India from March 24 to May 17, 2020, and state-wise local level restrictions afterward, have resulted in significant reduction of emissions of numerous atmospheric pollutants. The objective of this study is to analyse the change in concentration of various pollutants such as nitrogen oxide (NO₂), carbon monoxide (CO) and aerosol optical depth (AOD) due to lockdown and also to quantify the contribution of crop stubble burning to air pollution. The Sentinel-5P based NO₂ and CO observations for 2019 and 2020 and Moderate Resolution Imaging Spectroradiometer (MODIS)-based AOD observations for 2016-2020 were used for detecting the variations. The obtained results showed a significant decrease in NO₂ levels during various stages of lockdown. Small decrease in CO levels was observed across most part of the India. With a few exceptions, such as coastal and desert regions, there was a moderate decrease in AOD levels. Furthermore, to study the contribution of NO₂, CO and AOD from crop stubble burning, MODIS observations on active fire events were obtained from Visible Infrared Imaging Radiometer Suite (VIIRS). The burning of crop stubble increased NO₂ emissions by 22 to 80%. CO levels, on the other hand, have risen by 7 to 25%. A considerable variation in AOD was reported, ranging from 1 to 426%.

Assessment of Meteorological Variables and Air Pollution Affecting COVID-19 Cases in Urban Agglomerations: Evidence from China

The 2019 novel coronavirus disease (COVID-19) has become a severe public health and social problem worldwide. A limitation of the existing literature is that multiple environmental variables have not been frequently elaborated, which is why the overall effect of the environment on COVID-19 has not been conclusive. In this study, we used generalized additive model (GAM) to detect the relationship between meteorological and air pollution variables and COVID-19 in four urban agglomerations in China and made comparisons among the urban agglomerations. The four urban agglomerations are Beijing-Tianjin-Hebei (BTH), middle reaches of the Yangtze River (MYR), Yangtze River Delta (YRD), and the Pearl River Delta (PRD). The daily rates of average precipitation, temperature, relative humidity, sunshine duration, and atmospheric pressure were selected as meteorological variables. The PM_2.5, PM₁₀, sulfur dioxide (SO₂), nitrogen dioxide (NO₂), ozone (O₃), and carbon monoxide (CO) contents were selected as air pollution variables. The results indicated that meteorological and air pollution variables tended to be significantly correlated. Moreover, the nature of the relationship between severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and meteorological and air pollution variables (i.e., linear or nonlinear) varied with urban agglomerations. Among the variance explained by GAMs, BTH had the highest value (75.4%), while MYR had the lowest value (35.2%). The values of the YRD and PRD were between the above two, namely 45.6% and 62.2%, respectively. The findings showed that the association between SARS-CoV-2 and meteorological and air pollution variables varied in regions, making it difficult to obtain a relationship that is applicable to every region. Moreover, this study enriches our understanding of SARS-CoV-2. It is required to create awareness within the government that anti-COVID-19 measures should be adapted to the local meteorological and air pollution conditions.

COVID-19 lockdown and environmental pollution: an Indian multi-state investigation

Originating from China, COVID-19 became the first-ever coronavirus pandemic, wreaking havoc in 218 nations. The lack of a potential treatment exacerbated by the inability of the healthcare infrastructure to contain the viral trajectory led to a worldwide lockdown. The anthropogenic halt presented an unprecedented background to quantify the effect of the anthroposphere on environmental pollution. Consequently, we analyzed the variations in the air (PM₁₀, PM_2.5, NO₂, SO₂) and water pollutants (BOD, COD, DO, coliform) using real-time monitoring data in the majorly hit Indian metropolitan states during the lockdown in contrast to 2019 levels. The overall AQI (air quality index) de-escalated by -31.35%, -34.35%, -32.63%, -29.25% in Delhi, Tamil Nadu, West Bengal, and Karnataka, respectively, from the 2019 levels. The daily concentrations of NO₂, PM_2.5, and PM₁₀ plunged tremendously. The exact pre-disposing factors responsible for higher COVID-19 transmission in some geographical centers remain elusive. Investigations have corroborated putative links between air pollutants and COVID-19 mortalities. Therefore, we further mapped PM_2.5, PM₁₀, NO₂, and SO₂ to co-relate with COVID-19 infectivity and mortality across the study states. Significant (P < 0.001) positive correlation between COVID-19 transmission was established for all pollutants with maximum co-relation with AQI followed by NO₂. River Ganga water in Uttarakhand was deemed "fit for drinking" for the first time in two decades. An aggregate of -71.94, -61.32, and -77.94 decrease in BOD, COD, total coliform levels, and an 11.75 rise in the average DO levels from 2019 data. This study will better assist the future framework of health and environment restoration policies.

Have any effect of COVID-19 lockdown on environmental sustainability? A study from most polluted metropolitan area of India

The long-term lockdown due to COVID-19 has beneficial impact on the natural environment. India has enforced a lockdown on 24th March 2020 and was subsequently extended in various phases. The lockdown due to the sudden spurt of the COVID-19 pandemic has shown a significant decline in concentration of air pollutants across India. The present article dealt with scenarios of air quality concentration of air pollutants, and effect on climatic variability during the COVID-19 lockdown period in Kolkata Metropolitan Area, India. The result showed that the air pollutants are significantly reduced and the air quality index (AQI) was improved during the lockdown months. Aerosol concentrations decreased by - 54.94% from the period of pre-lockdown. The major air pollutants like particulate matters (PM_2.5, PM₁₀), sulphur dioxide (SO₂), carbon monoxide (CO) and Ozone (O₃) were observed the maximum reduction ( - 40 to  - 60%) in the COVID-19 lockdown period. The AQI has been improved by 54.94% in the lockdown period. On the other hand, Sen's slope rank and the Mann-Kendal trend test showed the daily decreased of air pollutants rate is  - 0.051 to  - 1.586 μg /m3. The increasing trend of daily minimum, average, and maximum temperature from the month of March to May in this year (2020s) are 0.091, 0.118, and 0.106 °C which is lowest than the 2016s to 2019s trend. Therefore, this research has an enormous opportunity to explain the effects of the lockdown on air quality and climate variability, and it can also be helpful for policymakers and decision-makers to enact appropriate measures to control air pollution.

Impacts of the COVID-19 confinement on air quality, the Land Surface Temperature and the urban heat island in eight cities of Andalusia (Spain)

The COVID-19 outbreak and ensuing global lockdown situation have generated a very negative impact on the world economy, but they have also lent us a unique opportunity to research and better grasp the impacts of human activity on environmental pollution and urban climates. Such studies will be of vital importance for decision-making on measures needed to mitigate the effects of climate change in urban areas, in order to turn them into resilient environments. This study looks at eight cities in the region of Andalusia (southern Spain) to comprehensively assess their environmental quality with parameters (Pm10, So2, No2, Co and O3) obtained from meteorological stations. The aim was to determine how these parameters affect the Land Surface Temperature (LST) and the Surface Urban Heat Island (SUHI), on the basis of Sentinel 3 satellite thermal images. Knowing to what extent improved air quality can reduce the LST and SUHI of cities will be essential in the context of future environmental studies on which to base sustainable decisions. The geographic situation of cities in the Mediterranean Sea basin, highly vulnerable to climate change, and the high pollution rates and high daily temperature variations of these urban areas make them particularly attractive for analyses of this sort. During the confinement period, average reductions of some environmental pollutants were achieved: So2 (-33.5%), Pm10 (-38.3%), No2 (-44.0%) and Co (-26.5%). However, the environmental variable O3 underwent an average growth of 5.9%. The LST showed an average reduction of -4.6 °C (-19.3%), while the SUHI decreased by 1.02 °C (-59.8%). These values exhibit high spatio-temporal variations between day and night, and between inland and coastal cities.

Air Quality during the COVID–19 Lockdown and Unlock Periods in India Analyzed Using Satellite and Ground-based Measurements

Abstract

A nationwide lockdown was imposed in India from 24 March 2020 to 31 May 2020 to contain the spread of COVID-19. The lockdown has changed the atmospheric pollution across the continents. Here, we analyze the changes in two most important air quality related trace gases, nitrogen dioxide (NO₂) and tropospheric ozone (O₃) from satellite and surface observations, during the lockdown (April–May 2020) and unlock periods (June–September 2020) in India, to examine the baseline emissions when anthropogenic sources were significantly reduced. We use the Bayesian statistics to find the changes in these trace gas concentrations in different time periods. There is a strong reduction in NO₂ during the lockdown as public transport and industries were shut during that period. The largest changes are found in IGP (Indo-Gangetic Plain), and industrial and mining areas in Eastern India. The changes are small in the hilly regions, where the concentrations of these trace gases are also very small (0–1 × 10¹⁵ molec./cm²). In addition, a corresponding increase in the concentrations of tropospheric O₃ is observed during the period. The analyses over cities show that there is a large decrease in NO₂ in Delhi (36%), Bangalore (21%) and Ahmedabad (21%). As the lockdown restrictions were eased during the unlock period, the concentrations of NO₂ gradually increased and ozone deceased in most regions. Therefore, this study suggests that pollution control measures should be prioritized, ensuring strict regulations to control the source of anthropogenic pollutants, particularly from the transport and industrial sectors.

Highlights

• Most cities show a reduction up to 15% of NO₂ during the lockdown

• The unlock periods show again an increase of about 40–50% in NO₂

• An increase in tropospheric O₃ is observed together with the decrease in NO₂

Supplementary Information

The online version contains supplementary material available at 10.1007/s40710-022-00585-9.

Impact of COVID-19 lockdown on ambient noise levels in seven metropolitan cities of India

The paper analyzed the impact of lockdown on the ambient noise levels in the seventy sites in the seven major cities of India and ascertained the noise scenario in lockdown period, and on the Janta Curfew day in comparison to the pre-lock down period and year 2019 annual average values. It was observed that the majority of the noise monitoring sites exhibited a decrement in ambient day and night equivalent noise levels on the national Janta Curfew day and Lockdown period as compared with the normal working days attributed to the restricted social, economical, industrial, urbanization activity and reduced human mobility. A mixed pattern was observed at a few sites, wherein the ambient day and night equivalent noise levels during Janta curfew day and Lockdown period had been reported to be higher than that on the normal working days. The study depicts the noise scenario during the lockdown and pre-lockdown period for seventy sites in India and shall be instrumental in analyzing the consequences and implications of imposing lockdowns in future on the environmental noise pollution in Indian cities.

COVID-19 pandemic: What can we learn for better air quality and human health?

The COVID-19 lockdown resulted in improved air quality in many cities across the world. With the objective of what could be the new learning from the COVID-19 pandemic and subsequent lockdowns for better air quality and human health, a critical synthesis of the available evidence concerning air pollution reduction, the population at risk and natural versus anthropogenic emissions was conducted. Can the new societal norms adopted during pandemics, such as the use of face cover, awareness regarding respiratory hand hygiene, and physical distancing, help in reducing disease burden in the future? The use of masks will be more socially acceptable during the high air pollution episodes in lower and middle-income countries, which could help to reduce air pollution exposure. Although post-pandemic, some air pollution reduction strategies may be affected, such as car-pooling and the use of mass transit systems for commuting to avoid exposure to airborne infections like coronavirus. However, promoting non-motorized modes of transportation such as cycling and walking within cities as currently being enabled in Europe and other countries could overshadow such losses. This demand focus on increasing walkability in a town for all ages and populations, including for a differently-abled community. The study highlighted that for better health and sustainability there. is also a need to promote other measures such as work-from-home, technological infrastructure, the extension of smart cities, and the use of information technology.

Spatio-temporal variation in fine particulate matter and effect on air quality during the COVID-19 in New Delhi, India

Novel Coronavirus disease has affected almost all the countries; which leads to the pandemic, impacting adversely on environment. The impact on environment during pre-and during lockdowns needs an attention to correlate the pollutants from industrial emissions and other factors. Therefore, the current study demonstrates the changes in fine particulate matter PM_2.5, PM₁₀ and effect on air quality during lockdown. The highest reduction was observed in lockdown I (25 March - 14 April) as compared to others lockdowns (between 15 April and 31st May 2020) due to the complete shutdown of industrial, transport, and construction activities. A significant reduction in PM_2.5 and PM₁₀ from 114.27 μg/m³ and 194.48 μg/m³ for pre-lockdown period to 41.41 μg/m³ and 86.81 μg/m³ for lockdown I was observed. The levels of air quality index fall under satisfactory category for lockdown I whereas satisfactory to moderate category for other lockdowns. The present study revealed a strong correlation between PM_2.5 and PM₁₀ levels during the pre-lockdown period (0.71) and through lockdown IV (0.76), which indicate that change in the PM₁₀ level influences the PM_2.5 level greatly. The findings of the present study could be scaled up nationwide and might be useful in formulating air pollution reduction policies in the future.

Impact of COVID-19 induced lockdown on land surface temperature, aerosol, and urban heat in Europe and North America

The outbreak of SARS CoV-2 (COVID-19) has posed a serious threat to human beings, society, and economic activities all over the world. Worldwide rigorous containment measures for limiting the spread of the virus have several beneficial environmental implications due to decreased anthropogenic emissions and air pollutants, which provide a unique opportunity to understand and quantify the human impact on atmospheric environment. In the present study, the associated changes in Land Surface Temperature (LST), aerosol, and atmospheric water vapor content were investigated over highly COVID-19 impacted areas, namely, Europe and North America. The key findings revealed a large-scale negative standardized LST anomaly during nighttime across Europe (-0.11 °C to -2.6 °C), USA (-0.70 °C) and Canada (-0.27 °C) in March-May of the pandemic year 2020 compared to the mean of 2015-2019, which can be partly ascribed to the lockdown effect. The reduced LST was corroborated with the negative anomaly of air temperature measured at meteorological stations (i.e. -0.46 °C to -0.96 °C). A larger decrease in nighttime LST was also seen in urban areas (by ∼1-2 °C) compared to rural landscapes, which suggests a weakness of the urban heat island effect during the lockdown period due to large decrease in absorbing aerosols and air pollutants. On the contrary, daytime LST increased over most parts of Europe due to less attenuation of solar radiation by atmospheric aerosols. Synoptic meteorological variability and several surface-related factors may mask these changes and significantly affect the variations in LST, aerosols and water vapor content. The changes in LST may be a temporary phenomenon during the lockdown but provides an excellent opportunity to investigate the effects of various forcing controlling factors in urban microclimate and a strong evidence base for potential environmental benefits through urban planning and policy implementation.

Black Carbon Particles Physicochemical Real-Time Data Set in a Cold City: Trends of Fall-Winter BC Accumulation and COVID-19

Black carbon (BC) plays an important role in climate and health sciences. Using the combination of a year real-time BC observation (photoacoustic extinctiometer) and data for PM2.5 and selected co-pollutants, we herein show that annual BC Mass concentration has a bi-modal distribution, in a cold-climate city of Montreal. In addition to the summer peak, a winter BC peak was observed (up to 0.433 μg/m3), lasting over 3 months. A comparative study between two air pollution hotspots, downtown and Montreal international airport indicated that airborne average BC Mass concentration in downtown was 0.344 μg/m3, whereas in the residential areas around Montreal airport BC Mass values were over 400% higher (1.487 μg/m3). During the numerous snowfall events, airborne BC Mass concentration decreased. High-resolution scanning/transmission electron microscopy with energy dispersive X-ray spectroscopy analysis of the snow samples provided evidence that airborne BC particles or carbon nanomaterials were indeed transferred from polluted air to snow. During the COVID-19 lockdown, the BC concentration and selected co-pollutants, decreased up to 72%, confirming the predominance of anthropogenic activities in BC emission. This first cold-climate BC data set can be essential for more accurate air quality and climate modeling. About one-third of the Earth's land surface receive snow annually, the impact of this study on air quality, health and climate change is discussed.

Analysis of Urban Heat Island and Heat Waves Using Sentinel-3 Images: a Study of Andalusian Cities in Spain

ABSTRACT

At present, understanding the synergies between the Surface Urban Heat Island (SUHI) phenomenon and extreme climatic events entailing high mortality, i.e., heat waves, is a great challenge that must be faced to improve the quality of life in urban zones. The implementation of new mitigation and resilience measures in cities would serve to lessen the effects of heat waves and the economic cost they entail. In this research, the Land Surface Temperature (LST) and the SUHI were determined through Sentinel-3A and 3B images of the eight capitals of Andalusia (southern Spain) during the months of July and August of years 2019 and 2020. The objective was to determine possible synergies or interaction between the LST and SUHI, as well as between SUHI and heat waves, in a region classified as highly vulnerable to the effects of climate change. For each Andalusian city, the atmospheric variables of ambient temperature, solar radiation, wind speed and direction were obtained from stations of the Spanish State Meteorological Agency (AEMET); the data were quantified and classified both in periods of normal environmental conditions and during heat waves. By means of Data Panel statistical analysis, the multivariate relationships were derived, determining which ones statistically influence the SUHI during heat wave periods. The results indicate that the LST and the mean SUHI obtained are statistically interacted and intensify under heat wave conditions. The greatest increases in daytime temperatures were seen for Sentinel-3A in cities by the coast (LST = 3.90 °C, SUHI = 1.44 °C) and for Sentinel-3B in cities located inland (LST = 2.85 °C, SUHI = 0.52 °C). The existence of statistically significant positive relationships above 99% (p < 0.000) between the SUHI and solar radiation, and between the SUHI and the direction of the wind, intensified in periods of heat wave, could be verified. An increase in the urban area affected by the SUHI under heat wave conditions is reported.

GRAPHICAL ABSTRACT

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s41748-021-00268-9.

Assessment of COVID-19 pandemic effects on ship pollutant emissions in major international seaports

This study aims to investigate the coronavirus disease (COVID-19) pandemic effects and associated restrictive rules on ship activities and pollutant emissions (CO2, SOX, NOX, PM, CO, CH4) in four major seaports, namely the Ports of Singapore, Long Beach, Los Angeles, and Hamburg. We used 2019 as the baseline year to show the business-as-usual emission and compared with the estimated quantity during the July 2020-July 2021 pandemic period. We also project future ship emissions from August 2021-August 2022 to illustrate two potential port congestion scenarios due to COVID-19. The results show that the ship emissions in all four ports generally increased by an average of 79% because of the prolonged turnaround time in port. Importantly, majority of ship emissions occurred during the extended hoteling time at berth and anchorage areas as longer operational times were needed due to pandemic-related delays, with increases ranging from 27 to 123% in the total emissions across ports. The most affected shipping segments were the container ships and dry bulk carriers which the total emissions of all pollutants increased by an average of 94-142% compared with 2019. Overall, the results of this study provide a comprehensive review of the ship emission outlook amid the pandemic uncertainty.

The impact of improved air-quality due to COVID-19 lockdown on surface meteorological parameters and planetary boundary layer over Gadanki, a tropical rural site in India

The nation-wide lockdowns imposed in India during March--May 2020 (in four phases) to curb the spread of the novel Corona virus, greatly enhanced the near-surface air-quality due to lowering of industrial, transport and human activities. The present study focuses on the changes in the vertical structure of aerosol concentration and how those changes impacted radiation balance, the planetary boundary layer (PBL) height and surface meteorological parameters. Instrumented tower and Ceilometer measurements made at Gadanki (13.45°N, 79.18°E), located in a rural environment, coupled with satellite-derived Aerosol Optical Depth (AOD) data have been used to understand the changes in lockdown period. Significant reduction in backscatter density during the lockdown compared to 2019 indicates that aerosol reduction during the lockdown is not only limited to the surface, rather observed in the entire PBL. Except for the fourth phase of lockdown during which several relaxations have been given for vehicular movement and other anthropogenic activities, the reduction in backscatter density is seen in all phases of lockdown. However, the reduction is prominently seen in the second and third phases. The AOD also reduced by 40% around Gadanki, comparable to that of in urban regions. Due to the reduction in aerosols during the lockdown period, the insolation increases by 60 Wm^-2, which is expected to increase the temperature. However, the increased loss of long-wave radiation (due to reduction in trapping gases) and more rain events during the lockdown period decreased the temperature by ~1 °C. Measurements also suggest that the most of net radiation is partitioned into the latent heat flux increasing the humidity and lowering the PBL height (due to reduced strength of thermals and sensible heat flux).

A Gulf in lockdown: How an enforced ban on recreational vessels increased dolphin and fish communication ranges

From midnight of 26 March 2020, New Zealand became one of the first countries to enter a strict lockdown to combat the spread of COVID-19. The lockdown banned all non-essential services and travel both on land and sea. Overnight, the country's busiest coastal waterway, the Hauraki Gulf Marine Park, became devoid of almost all recreational and non-essential commercial vessels. An almost instant change in the marine soundscape ensued, with ambient sound levels in busy channels dropping nearly threefold the first 12 h. This sudden drop led fish and dolphins to experience an immediate increase in their communication ranges by up to an estimated 65%. Very low vessel activity during the lockdown (indicated by the presence of vessel noise over the day) revealed new insights into cumulative noise effects from vessels on auditory masking. For example, at sites nearer Auckland City, communication ranges increased approximately 18 m (22%) or 50 m (11%) for every 10% decrease in vessel activity for fish and dolphins, respectively. However, further from the city and in deeper water, these communication ranges were increased by approximately 13 m (31%) or 510 m (20%). These new data demonstrate how noise from small vessels can impact underwater soundscapes and how marine animals will have to adapt to ever-growing noise pollution.