Positive effects of COVID-19 lockdown on air quality of industrial cities (Ankleshwar and Vapi) of Western India

Crop residue burning increased during the COVID-19 lockdown: A case study of rural India

The customary practice of crop residue burning (CRB) is a major policy concern across several developing economies because of the associated increase in air pollution and reduction in soil quality. CRB poses a hazard to public health and sustainable farmland management. We collected original survey data from a panel of 400 wheat farmers on CRB choices during April-May of 2019 and 2020 - with the latter coinciding with India's COVID-19 nationwide lockdown. This timeline of events facilitated a unique identification of changes in CRB that are attributable to the lockdown. Several studies find that lockdowns during 2020 had beneficial effects on the environment owing to reduced economic activity. However, our findings indicate that CRB may have unintentionally increased during the lockdown. A binary variable regression framework analyzes the determinants of CRB choices of farmers over two years. We control for farmers' opinions on various socioeconomic aspects of the pandemic lockdown to examine its effects on their CRB decisions. The lockdown significantly increased the likelihood of CRB by up to 12%. Furthermore, farmers who lost agricultural income and those compelled to sell assets during the lockdown were 22% and 19% more inclined, respectively, to choose CRB. Labor mobility ceased during the lockdown and increased the cost of environmentally friendly farmland management; this increased the likelihood of CRB by 6%. This study contributes to a growing literature on the unintentional consequences of pandemic lockdowns.

Air-water exchange and risk assessment of phthalic acid esters during the early phase of COVID-19 pandemic in tropical riverine catchments of India

Given the increased load of waste plastic in the solid waste stream after the outbreak of the COVID-19 pandemic, we investigated the fate of selected plastic additives along open burning dumps, industrial and residential transects in tropical riverine catchments of India. Polyurethane foam disk passive air samples, surface water and community stored water (CSW) samples were collected along the Adyar River (AR), Cooum River (CR) and canals in Chennai and Daman Ganga River (DG) in Vapi. Among the quantified phthalic acid esters (PAEs), a widely used plastic additive, di(2-ethylhexyl) phthalate (DEHP), was ubiquitous across all the transects. More open drains and leaching of littered single-use plastic items can be the reason for significantly higher (p < 0.05) levels of PAEs in CR over other rivers with a dominance of di-n-butyl phthalate (DnBP). Prevalence of open burning of dumped plastic waste was the possible primary emission source of PAEs in these riverine catchments. Excluding highly soluble dimethyl phthalate (DMP), air-water exchange processes reflected the secondary emission of all the PAEs from the surface water along the open burning sites. Despite the cleansing effect of the oceanic air mass from the Bay of Bengal and the Indian Ocean, the average atmospheric PAE level was two-fold higher in Chennai than Vapi. Even though Vapi is a coastal city along the Arabian Sea, it was impacted by inland air masses during the sampling event. Open burning dumpsites showed a five-fold increase in atmospheric priority PAEs in Chennai city after the outbreak of the COVID-19 pandemic. DnBP was the major contributor to estrogenicity in CSW and DG, and also posed maximum risk for fishes in the open burning transect of these tropical rivers.

Analysing role of airborne particulate matter in abetting SARS-CoV-2 outbreak for scheming regional pandemic regulatory modalities

The mutating SARS-CoV-2 necessitates gauging the role of airborne particulate matter in the COVID-19 outbreak for designing area-specific regulation modalities based on the environmental state-of-affair. To scheme the protocols, the hotspots of air pollutants such as PM2.5, PM10, NH3, NO, NO2, SO2, and and environmental factors including relative humidity (RH), and temperature, along with COVID-19 cases and mortality from January 2020 till December 2020 from 29 different ground monitoring stations spanning Delhi, are mapped. Spearman correlation coefficients show a positive relationship between SARS-COV-2 with particulate matter (PM2.5 with r > 0.36 and PM10 with r > 0.31 and p-value <0·001). Besides, SARS-COV-2 transmission showed a substantial correlation with NH3 (r = 0.41), NO2 (r = 0.36), and NO (r = 0.35) with a p-value <0.001, which is highly indicative of their role in SARS-CoV-2 transmission. These outcomes are associated with the source of PM and its constituent trace elements to understand their overtone with COVID-19. This strongly validates temporal and spatial variation in COVID-19 dependence on air pollutants as well as on environmental factors. Besides, the bottlenecks of missing latent data, monotonous dependence of variables, and the role air pollutants with secondary environmental variables are discussed. The analysis set the foundation for strategizing regional-based modalities considering environmental variables (i.e., pollutant concentration, relative humidity, temperature) as well as urban and transportation planning for efficient control and handling of future public health emergencies.

Aerosol demasking enhances climate warming over South Asia

Anthropogenic aerosols mask the climate warming caused by greenhouse gases (GHGs). In the absence of observational constraints, large uncertainties plague the estimates of this masking effect. Here we used the abrupt reduction in anthropogenic emissions observed during the COVID-19 societal slow-down to characterize the aerosol masking effect over South Asia. During this period, the aerosol loading decreased substantially and our observations reveal that the magnitude of this aerosol demasking corresponds to nearly three-fourths of the CO2-induced radiative forcing over South Asia. Concurrent measurements over the northern Indian Ocean unveiled a ~7% increase in the earth's surface-reaching solar radiation (surface brightening). Aerosol-induced atmospheric solar heating decreased by ~0.4 K d-1. Our results reveal that under clear sky conditions, anthropogenic emissions over South Asia lead to nearly 1.4 W m-2 heating at the top of the atmosphere during the period March-May. A complete phase-out of today's fossil fuel combustion to zero-emission renewables would result in rapid aerosol demasking, while the GHGs linger on.

Change in the air due to the coronavirus outbreak in four major cities of India: What do the statistics say?

The onset of the novel Coronavirus (COVID-19) has impacted all sectors of society. To avoid the rapid spread of this virus, the Government of India imposed a nationwide lockdown in four phases. Lockdown, due to COVID-19 pandemic, resulted a decline in pollution in India in general and in dense cities in particular. Data on key air quality indicators were collected, imputed, and compiled for the period 1st August 2018 to 31st May 2020 for India's four megacities, namely Delhi, Mumbai, Kolkata, and Hyderabad. Autoregressive integrated moving average (ARIMA) model and machine learning technique e.g. Artificial Neural Network (ANN) with the inclusion of lockdown dummy in both the models have been applied to examine the impact of anthropogenic activity on air quality parameters. The number of indicators having significant lockdown dummy are six (PM_2.5, PM₁₀, NOx, CO, benzene, and AQI), five (PM_2.5, PM₁₀, NOx, SO₂ and benzene), five (PM₁₀, NOx, CO, benzene and AQI) and three (PM_2.5, PM₁₀, and AQI) for Delhi, Kolkata, Mumbai and Hyderabad respectively. It was also observed that the prediction accuracy significantly improved when a lockdown dummy was incorporated. The highest reduction in Mean Absolute Percentage Error (MAPE) is found for CO in Hyderabad (28.98%) followed by the NOx in Delhi (28.55%). Overall, it can be concluded that there is a significant decline in the value of air quality parameters in the lockdown period as compared to the same time phase in the previous year. Insights from the COVID-19 pandemic will help to achieve significant improvement in ambient air quality while keeping economic growth in mind.

Investigating impacts of COVID-19 on urban mobility and emissions

The COVID-19 pandemic has severely impacted human activities in a way never documented in modern history. The prevention policies and measures have abruptly changed well-established urban mobility patterns. In this context, we exploit different sources of urban mobility data to gain insights into the effects of restrictive policies on the daily mobility and exhaust emissions in pandemic and post-pandemic periods. Manhattan, the most densely populated borough in New York City, is chosen as the study area. We collect data generated by taxis, sharing bikes, and road detectors between 2019 and 2021, and estimate exhaust emissions using the COPERT (Computer Programme to calculate Emissions from Road Transport) model. A comparative analysis is conducted to identify important changes in urban mobility and emission patterns, with a particular focus on the lockdown period in 2020 and its counterparts in 2019 and 2021. The results of the paper fuel the discussion on urban resilience and policy-making in a post pandemic world.

Air quality change and public perception during the COVID-19 lockdown in India

This study aims at analyzing the change in air quality following the COVID-19 lockdown in India and its perception by the general public. Air quality data for 100 days recorded at 193 stations throughout India were analyzed between 25th March to 17th May 2020. A nationwide online survey was conducted to obtain public perceptions of air quality improvement (n = 1750). On average, approximately 40% improvement in the air quality index was observed, contributed by a reduction in 40% of PM₁₀, 44% of PM_2.5, 51% of NO₂ and 21% of SO₂. There was a significant difference between the levels of all the pollutants before and after the lockdown (p < 0.05), except ozone. The correlation between PM₁₀ and PM_2.5 with ozone was significant after the lockdown period, indicating that a significant portion of the particulates present in the atmosphere after the lockdown period is secondary. The values of PM_2.5/PM₁₀ were found to be >0.5 in North East states and this observation points to the long-distance transport of PM_2.5 from other places. The survey for public perception showed that 60% of the respondents perceived improvement in air quality. Household emissions were perceived to be a significant source of pollution after the lockdown. An odds ratio (OR) of 17 (95%, CI: 6.42, 47.04) indicated a very high dependence of perception on actual air quality. OR between air quality and health improvement was 5.2 (95%, CI: 2.69, 10.01), indicating significant health improvement due to air quality improvement. Google Trends analysis showed that media did not influence shaping the perception. There was a significant improvement in the actual and perceived air quality in India after the COVID-19-induced lockdown. PM₁₀ levels had the most decisive influence in shaping public perception.

Air pollution attributed disease burden and economic growth in India: Estimating trends and inequality between states

Background

Air pollution is one of the major contributors to the disease burden in India after malnutrition. We examined the relation, and state-wise disparities in air pollution attributed to disease burden (APADB) concerning gross state domestic product (GSDP) and growth in motor vehicles in India.

Methods

We retrieved disability-adjusted life year (DALY) estimates for India due to air pollution from the Global Burden of Disease Studies, injuries, and Risk Factors Study (GBD). We examined the association between APADB with GSDP and the growth in the number of registered motor vehicles in India during the 2011 to 2019 period. Concentration indices and Lorenz curves were used to explore the variation in APADB across individual states.

Findings

Except for a few states, APADB is inversely proportional to GSDP. Growth in motor vehicles was also negatively correlated with the APADB in n=19 states. The concentration index explained a 47% inequality in APADB between individual states and exhibited a decline (45%) during 2019 compared to 2011. The unevenness in APADB among Indian states is evident from the analysis as the states occupying the 6^th or 7^th decile and above in terms of GDP, urbanization and population contribute more than 60 per cent of the total APADB.

Interpretation

The APADB is inversely correlated with GSDP for most of the states, and the negative correlations were conspicuous when APADB per 100,000 population was analysed. The concentration index and Lorenz revealed the presence of APADB inequality between states in terms of GSDP, population, urbanisation, and total factories.

Funding

Not applicable.

Frequency distribution of pollutant concentrations over Indian megacities impacted by the COVID-19 lockdown

The megacities experience poor air quality frequently due to stronger anthropogenic emissions. India had one of the longest lockdowns in 2020 to curb the spread of COVID-19, leading to reductions in the emissions from anthropogenic activities. In this article, the frequency distributions of different pollutants have been analysed over two densely populated megacities: Delhi (28.70° N; 77.10° E) and Kolkata (22.57° N; 88.36° E). In Delhi, the percentage of days with PM_2.5 levels exceeding the National Ambient Air Quality Standards (NAAQS) between 25 March and 17 June dropped from 98% in 2019 to 61% in 2020. The lockdown phase 1 brought down the PM₁₀ (particulate matter having an aerodynamic diameter ≤ 10 μm) levels below the daily NAAQS limit over Delhi and Kolkata. However, PM₁₀ exceeded the limit of 100 μgm^-3 during phases 2-5 of lockdown over Delhi due to lower temperature, weaker winds, increased relative humidity and commencement of limited traffic movement. The PM_2.5 levels exhibit a regressive trend in the highest range from the year 2019 to 2020 in Delhi. The daily mean value for PM_2.5 concentrations dropped from 85-90 μgm^-3 to 40-45 μgm^-3 bin, whereas the PM₁₀ levels witnessed a reduction from 160-180 μgm^-3 to 100-120 μgm^-3 bin due to the lockdown. Kolkata also experienced a shift in the peak of PM₁₀ distribution from 80-100 μgm^-3 in 2019 to 20-40 μgm^-3 during the lockdown. The PM_2.5 levels in peak frequency distribution were recorded in the 35-40 μgm^-3 bin in 2019 which dropped to 15-20 μgm^-3 in 2020. In line with particulate matter, other primary gaseous pollutants (NO_x, CO, SO₂, NH₃) also showed decline. However, changes in O₃ showed mixed trends with enhancements in some of the phases and reductions in other phases. In contrast to daily mean O₃, 8-h maximum O₃ showed a reduction over Delhi during lockdown phases except for phase 3. Interestingly, the time of daily maximum was observed to be delayed by ~ 2 h over Delhi (from 1300 to 1500 h) and ~ 1 h over Kolkata (from 1300 to 1400 h) almost coinciding with the time of maximum temperature, highlighting the role of meteorology versus precursors. Emission reductions weakened the chemical sink of O₃ leading to enhancement (120%; 11 ppbv) in night-time O₃ over Delhi during phases 1-3.

Air quality in the New Delhi metropolis under COVID-19 lockdown

Air pollution has been on continuous rise with increase in industrialization in metropolitan cities of the world. Several measures including strict climate laws and reduction in the number of vehicles were implemented by several nations. The COVID-19 pandemic provided a great opportunity to understand the daily human activities effect on air pollution. Majority nations restricted industrial activities and vehicular traffic to a large extent as a measure to restrict COVID-19 spread. In this paper, we analyzed the impact of such COVID19-induced lockdown on the air quality of the city of New Delhi, India. We analyzed the average concentration of common gaseous pollutants viz. sulfur dioxide (SO2), ozone (O3), nitrogen dioxide (NO2), and carbon monoxide (CO). These concentrations were obtained from the tropospheric column of Sentinel-5P (an earth observation satellite of European Space Agency) data. We observed that the city observed a significant drop in the level of atmospheric pollutant’s concentration for all the major pollutants as a result of strict lockdown measure. Such findings are also validated with pollutant data obtained from ground based monitoring stations. We observed that near-surface pollutant concentration dropped significantly by 50% for PM_2.5, 71.9% for NO2, and 88% for CO, after the lockdown period. Such studies would pave the path for implementing future air pollution control measures by environmentalists.

Temporal and spatial impact of lockdown during COVID-19 on air quality index in Haryana, India

This paper presents the evaluation of air quality in different districts of Haryana. Geo-spatial techniques were used to estimate gaseous and particulate pollutant's spatial and temporal variation during complete nationwide lockdown period and same month of previous year 2019 (March to May). Data of six fixed pollutants were collected from Central Pollution Control Board (CPCB). In this context, the data of air pollutants (PM₁₀, PM_2.5, O₃, NOx, SO₂, and CO) were analyzed for 2019 and 2020. The Spatio-temporal distribution of the Air Quality Index (AQI) clearly depicts difference in lockdown and unlock period. The result was showed that the air quality was very poor to satisfactory in 2019 and an improvement was observed from satisfactory to good in 2020 due to COVID-19 lockdown. On the basis of result, it will be concluded that automobile and industry are the major contributor in increase the pollutant concentration.

Improvements in SO2 pollution in India: role of technology and environmental regulations

India relies heavily on coal-based thermal power plants to meet its energy demands. Sulphur dioxide (SO₂) emitted from these plants and industries is a major air pollutant. Analysis of spatial and temporal changes in SO₂ using accurate and continuous observations is required to formulate mitigation strategies to curb the increasing air pollution in India. Here, we present the temporal changes in SO₂ concentrations over India in the past four decades (1980-2020). Our analysis shows that the Central and East India, and Indo-Gangetic Plain (IGP) are the hotspots of SO₂, as these regions house a cluster of thermal power plants, petroleum refineries, steel manufacturing units, and cement Industries. Thermal power plants (51%), and manufacturing and construction industries (29%) are the main sources of anthropogenic SO₂ in India. Its concentration over India is higher in winter (December-February) and lower in pre-monsoon (March-May) seasons. The temporal analyses reveal that SO₂ concentrations in India increased between 1980 and 2010 due to high coal burning and lack of novel technology to contain the emissions during the period. However, SO₂ shows a decreasing trend in recent decade (2010-2020) because of the environmental regulations and implementation of effective control technologies such as the flue gas desulphurisation (FGD) and scrubber. Since 2010, India's renewable energy production has also been increased substantially when India adopted a sustainable development policy. Therefore, the shift in energy production from conventional coal to renewable sources, solid environmental regulation, better inventory, and effective technology would help to curb SO₂ pollution in India. Both economic growth and air pollution control can be performed hand-in-hand by adopting new technology to reduce SO₂ and GHG emissions.

The Long-Term Impact of COVID-19 Lockdowns in Istanbul

The World Health Organization (WHO) have set sustainability development goals to reduce diseases, deaths, and the environmental impact of cities due to air pollution. In Istanbul, although average pollutant concentrations have been on a downward trend in recent years, extreme values and their annual exceedance numbers are high based on the air quality standards of WHO and the EU. Due to COVID-19 lockdowns, statistically significant reductions in emissions were observed for short periods. However, how long the effect of the lockdowns will last is unknown. For this reason, this study aims to investigate the impact of long-term lockdowns on Istanbul's air quality. The restriction period is approximated to the same periods of the previous years to eliminate seasonal effects. A series of paired t-tests (p-value < 0.05) were applied to hourly data from 12 March 2016, until 1 July 2021, when quarantines were completed at 36 air quality monitoring stations in Istanbul. The findings reveal that the average air quality of Istanbul was approximately 17% improved during the long-term lockdowns. Therefore, the restriction-related changes in emission distributions continued in the long-term period of 476 days. However, it is unknown how long this effect will continue, which will be the subject of future studies. Moreover, it was observed that the emission probability density functions changed considerably during the lockdowns compared to the years before. Accordingly, notable decreases were detected in air quality limit exceedances in terms of both excessive pollutant concentrations and frequency of occurrence, respectively, for PM₁₀ (-13% and -13%), PM_2.5 (-16% and -30%), and NO₂ (-3% and -8%), but not for O₃ (+200% and +540%) and SO₂ (-10% and +2.5%).

COVID-19 Restriction Movement Control Order (MCO) Impacted Emissions of Peninsular Malaysia Using Sentinel-2a and Sentinel-5p Satellite

The unprecedented outbreak of Coronavirus Disease 2019 (COVID-19) has impacted the whole world in every aspect including health, social life, economic activity, education, and the environment. The pandemic has led to an improvement in air quality all around the world, including in Malaysia. Lockdowns have resulted in industry shutting down and road travel decreasing which can reduce the emission of Greenhouse Gases (GHG) and air pollution. This research assesses the impact of the COVID-19 lockdown on emissions using the Air Pollution Index (API), aerosols, and GHG which is Nitrogen Dioxide (NO₂) in Malaysia. The data used is from Sentinel-5p and Sentinel-2A which monitor the air quality based on Ozone (O₃) and NO₂ concentration. Using an interpolated API Index Map comparing 2019, before the implementation of a Movement Control Order (MCO), and 2020, after the MCO period we examine the impact on pollution during and after the COVID-19 lockdown. Data used Sentinel-5p, Sentinel-2A, and Air Pollution Index of Malaysia (APIMS) to monitor the air quality that contains NO₂ concentration. The result has shown the recovery in air quality during the MCO implementation which indirectly shows anthropogenic activities towards the environmental condition. The study will help to enhance and support the policy and scope for air pollution management strategies as well as raise public awareness of the main causes that contribute to air pollution.

COVID-19, the environment and animal life in Malawi compared to other countries: A brief scooping review for a research agenda in the developing countries

The impact of COVID-19 on the human population in Malawi has been documented. However, its impact on the animal population and the environment has not been thoroughly researched. Because of the well-known inter-relationship between human and animal populations and the environment, a study based on a brief scooping review of previous related studies, media and survey reports, was conducted. The findings reveal that except for a few selected studies, the research gap on COVID-19's impact on the environment and animals in Malawi is wide compared to other countries. Nonetheless, from the few identified related studies, this study has revealed that as the restriction of movement and closure of borders disrupted the supply chain of forest resources in the country, the COVID-19 pandemic has led to increased pressure on forests as a coping strategy due to significant loss of jobs in the informal sector. Although the quality of water and air improved in most parts of the globe due to reduced human activity, there is no substantial literature on the same in Malawi partly due to ineffective monitoring systems. However, COVID-19 has exposed the deficiencies in water security in Malawi, thereby creating opportunities to address them. Conversely, increased demand for water at household levels due to restricted movements contributed to environmental pollution at suburb levels. In particular, the less developed and overpopulated countries suffered from land pollution due to poor disposal of plastic generated from hospitals and personal protection equipment. Elsewhere, studies show that minimal human interference with animals outside homes resulted in an increase of fish and bird biomasses. But, unemployment rates caused by the pandemic have seriously contributed to illegal poaching in developing countries. Therefore, a rapid assessment of the impact of the pandemic on environment in Malawi, to generate the evidence needed for policy makers to use in support of the affected and also plan for the recovery and sustainability of wildlife, is recommended.

Investigation of pre and post environmental impact of the lockdown (COVID-19) on the water quality of the Capibaribe and Tejipió rivers, Recife metropolitan region, Brazil

The coronavirus pandemic has seriously affected human health, although some improvements on environmental indexes have temporarily occurred, due to changes on socio-cultural and economic standards. The objective of this study was to evaluate the impacts of the coronavirus and the influence of the lockdown associated with rainfall on the water quality of the Capibaribe and Tejipió rivers, Recife, Northeast Brazil, using cloud remote sensing on the Google Earth Engine (GEE) platform. The study was carried out based on eight representative images from Sentinel-2. Among the selected images, two refer to the year 2019 (before the pandemic), three refer to 2020 (during a pandemic), two from the lockdown period (2020), and one for the year 2021. The land use and land cover (LULC) and slope of the study region were determined and classified. Water turbidity data were subjected to descriptive and multivariate statistics. When analyzing the data on LULC for the riparian margin of the Capibaribe and Tejipió rivers, a low permanent preservation area was found, with a predominance of almost 100% of the urban area to which the deposition of soil particles in rivers are minimal. The results indicated that turbidity values in the water bodies varied from 6 mg. L-1 up to 40 mg. L-1. Overall, the reduction in human-based activities generated by the lockdown enabled improvements in water quality of these urban rivers.

Air Pollution, Oxidative Stress, and the Risk of Development of Type 1 Diabetes

Despite multiple studies focusing on environmental factors conducive to the development of type 1 diabetes mellitus (T1DM), knowledge about the involvement of long-term exposure to air pollution seems insufficient. The main focus of epidemiological studies is placed on the relationship between exposure to various concentrations of particulate matter (PM): PM1, PM2.5, PM10, and sulfur dioxide (SO2), nitrogen dioxide (NO2), carbon monoxide (O3), versus the risk of T1DM development. Although the specific molecular mechanism(s) behind the link between increased air pollution exposure and a higher risk of diabetes and metabolic dysfunction is yet unknown, available data indicate air pollution-induced inflammation and oxidative stress as a significant pathway. The purpose of this paper is to assess recent research examining the association between inhalation exposure to PM and associated metals and the increasing rates of T1DM worldwide. The development of modern and more adequate methods for air quality monitoring is also introduced. A particular emphasis on microsensors, mobile and autonomous measuring platforms, satellites, and innovative approaches of IoT, 5G connections, and Block chain technologies are also presented. Reputable databases, including PubMed, Scopus, and Web of Science, were used to search for relevant literature. Eligibility criteria involved recent publication years, particularly publications within the last five years (except for papers presenting a certain novelty or mechanism for the first time). Population, toxicological and epidemiological studies that focused particularly on fine and ultra-fine PM and associated ambient metals, were preferred, as well as full-text publications.

Did Covid-19 lockdown positively affect the urban environment and UN- Sustainable Development Goals?

This work quantifies the impact of pre-, during- and post-lockdown periods of 2020 and 2019 imposed due to COVID-19, with regards to a set of satellite-based environmental parameters (greenness using Normalized Difference Vegetation and water indices, land surface temperature, night-time light, and energy consumption) in five alpha cities (Kuala Lumpur, Mexico, greater Mumbai, Sao Paulo, Toronto). We have inferenced our results with an extensive questionnaire-based survey of expert opinions about the environment-related UN Sustainable Development Goals (SDGs). Results showed considerable variation due to the lockdown on environment-related SDGs. The growth in the urban environmental variables during lockdown phase 2020 relative to a similar period in 2019 varied from 13.92% for Toronto to 13.76% for greater Mumbai to 21.55% for Kuala Lumpur; it dropped to −10.56% for Mexico and −1.23% for Sao Paulo city. The total lockdown was more effective in revitalizing the urban environment than partial lockdown. Our results also indicated that Greater Mumbai and Toronto, which were under a total lockdown, had observed positive influence on cumulative urban environment. While in other cities (Mexico City, Sao Paulo) where partial lockdown was implemented, cumulative lockdown effects were found to be in deficit for a similar period in 2019, mainly due to partial restrictions on transportation and shopping activities. The only exception was Kuala Lumpur which observed surplus growth while having partial lockdown because the restrictions were only partial during the festival of Ramadan. Cumulatively, COVID-19 lockdown has contributed significantly towards actions to reduce degradation of natural habitat (fulfilling SDG-15, target 15.5), increment in available water content in Sao Paulo urban area(SDG-6, target 6.6), reduction in NTL resulting in reducied per capita energy consumption (SDG–13, target 13.3).

Spatiotemporal impact of COVID-19 on Taiwan air quality in the absence of a lockdown: Influence of urban public transportation use and meteorological conditions

The unprecedented outbreak of COVID-19 significantly improved the atmospheric environment for lockdown-imposed regions; however, scant evidence exists on its impacts on regions without lockdown. A novel research framework is proposed to evaluate the long-term monthly spatiotemporal impact of COVID-19 on Taiwan air quality through different statistical analyses, including geostatistical analysis, change detection analysis and identification of nonattainment pollutant occurrence between the average mean air pollutant concentrations from 2018-2019 and 2020, considering both meteorological and public transportation impacts. Contrary to lockdown-imposed regions, insignificant or worsened air quality conditions were observed at the beginning of COVID-19, but a delayed improvement occurred after April in Taiwan. The annual mean concentrations of PM₁₀, PM_2.5, SO₂, NO₂, CO and O₃ in 2020 were reduced by 24%, 18%, 15%, 9.6%, 7.4% and 1.3%, respectively (relative to 2018-2019), and the overall occurrence frequency of nonattainment air pollutants declined by over 30%. Backward stepwise regression models for each air pollutant were successfully constructed utilizing 12 meteorological parameters (R² > 0.8 except for SO₂) to simulate the meteorological normalized business-as-usual concentration. The hybrid single-particle Lagrangian integrated trajectory (HYSPLIT) model simulated the fate of air pollutants (e.g., local emissions or transboundary pollution) for anomalous months. The changes in different public transportation usage volumes (e.g., roadway, railway, air, and waterway) moderately reduced air pollution, particularly CO and NO₂. Reduced public transportation use had a more significant impact than meteorology on air quality improvement in Taiwan, highlighting the importance of proper public transportation management for air pollution control and paving a new path for sustainable air quality management even in the absence of a lockdown.

The Atmospheric Environment Effects of the COVID-19 Pandemic: A Metrological Study

Since the COVID-19 outbreak, the scientific community has been trying to clarify various problems, such as the mechanism of virus transmission, environmental impact, and socio-economic impact. The spread of COVID-19 in the atmospheric environment is variable and uncertain, potentially resulting in differences in air pollution. Many scholars are striving to explore the relationship between air quality, meteorological indicators, and COVID-19 to understand the interaction between COVID-19 and the atmospheric environment. In this study, we try to summarize COVID-19 studies related to the atmospheric environment by reviewing publications since January 2020. We used metrological methods to analyze many publications in Web of Science Core Collection. To clarify the current situation, hotspots, and development trends in the field. According to the study, COVID-19 research based on the atmospheric environment has attracted global attention. COVID-19 and air quality, meteorological factors affecting the spread of COVID-19, air pollution, and human health are the main topics. Environmental variables have a certain impact on the spread of SARS-CoV-2, and the prevalence of COVID-19 has improved the atmospheric environment to some extent. The findings of this study will aid scholars to understand the current situation in this field and provide guidance for future research.

Integrated process analysis retrieval of changes in ground-level ozone and fine particulate matter during the COVID-19 outbreak in the coastal city of Kannur, India

The Community Multi-Scale Air Quality (CMAQ) model was applied to evaluate the air quality in the coastal city of Kannur, India, during the 2020 COVID-19 lockdown. From the Pre1 (March 1-24, 2020) period to the Lock (March 25-April 19, 2020) and Tri (April 20-May 9, 2020) periods, the Kerala state government gradually imposed a strict lockdown policy. Both the simulations and observations showed a decline in the PM_2.5 concentrations and an enhancement in the O₃ concentrations during the Lock and Tri periods compared with that in the Pre1 period. Integrated process rate (IPR) analysis was employed to isolate the contributions of the individual atmospheric processes. The results revealed that the vertical transport from the upper layers dominated the surface O₃ formation, comprising 89.4%, 83.1%, and 88.9% of the O₃ sources during the Pre1, Lock, and Tri periods, respectively. Photochemistry contributed negatively to the O₃ concentrations at the surface layer. Compared with the Pre1 period, the O₃ enhancement during the Lock period was primarily attributable to the lower negative contribution of photochemistry and the lower O₃ removal rate by horizontal transport. During the Tri period, a slower consumption of O₃ by gas-phase chemistry and a stronger vertical import from the upper layers to the surface accounted for the increase in O₃. Emission and aerosol processes constituted the major positive contributions to the net surface PM_2.5, accounting for a total of 48.7%, 38.4%, and 42.5% of PM_2.5 sources during the Pre1, Lock, and Tri periods, respectively. The decreases in the PM_2.5 concentrations during the Lock and Tri periods were primarily explained by the weaker PM_2.5 production from emission and aerosol processes. The increased vertical transport rate of PM_2.5 from the surface layer to the upper layers was also a reason for the decrease in the PM_2.5 during the Lock periods.

Assessing temporal correlation in environmental risk factors to design efficient area-specific COVID-19 regulations: Delhi based case study

Amid ongoing devastation due to Serve-Acute-Respiratory-Coronavirus2 (SARS-CoV-2), the global spatial and temporal variation in the pandemic spread has strongly anticipated the requirement of designing area-specific preventive strategies based on geographic and meteorological state-of-affairs. Epidemiological and regression models have strongly projected particulate matter (PM) as leading environmental-risk factor for the COVID-19 outbreak. Understanding the role of secondary environmental-factors like ammonia (NH₃) and relative humidity (RH), latency of missing data structuring, monotonous correlation remains obstacles to scheme conclusive outcomes. We mapped hotspots of airborne PM_2.5, PM₁₀, NH₃, and RH concentrations, and COVID-19 cases and mortalities for January, 2021-July,2021 from combined data of 17 ground-monitoring stations across Delhi. Spearmen and Pearson coefficient correlation show strong association (p-value < 0.001) of COVID-19 cases and mortalities with PM_2.5 (r > 0.60) and PM₁₀ (r > 0.40), respectively. Interestingly, the COVID-19 spread shows significant dependence on RH (r > 0.5) and NH₃ (r = 0.4), anticipating their potential role in SARS-CoV-2 outbreak. We found systematic lockdown as a successful measure in combatting SARS-CoV-2 outbreak. These outcomes strongly demonstrate regional and temporal differences in COVID-19 severity with environmental-risk factors. The study lays the groundwork for designing and implementing regulatory strategies, and proper urban and transportation planning based on area-specific environmental conditions to control future infectious public health emergencies.

The regional impact of the COVID-19 lockdown on the air quality in Ji'nan, China

A number of strict lockdown measures were implemented in the areas most affected by COVID-19 in China, including Ji’nan city, from 24 January to 7 February 2020. Due to these forced restrictions, the pollution levels in cities across the country drastically decreased within just a few days. Since traffic pollution and industrial emissions are important factors affecting regional air quality, congestion has a significant impact on the environment. Therefore, using the aid of air quality data for six pollutants (PM₁₀, PM_2.5, SO₂, NO₂, CO and O₃) from 11 monitoring stations (located in urban, suburban and urban-industrial regions) across Ji’nan, we employed the air quality index (AQI) to investigate the spatial pattern of air quality in the pre-COVID-19 (pre-COVID) and COVID-19-related lockdown (COVID lockdown) periods. The results showed that air quality significantly improved during the COVID lockdown period. Among the selected pollutants, compared to the corresponding pre-COVID levels, the greatest reduction was observed for the concentration of NO₂ (54.02%), while the smallest reduction was observed for the concentration of SO₂ (27.92%). The PM_2.5 (38.73%), PM₁₀ (44.92%) and CO (30.60%) levels also decreased during the COVID lockdown period; only the O₃ concentration increased (37.42%) during this period. Overall, air quality improved by approximate improvements of 37.33% during the COVID lockdown period. Approximately 35.48%, 37.01% and 43.43% in the AQI were observed in urban, suburban and urban-industrial regions, respectively. Therefore, the AQI exhibited remarkable regional differences in Ji'nan. This study demonstrates the contributions of the transportation sector and local emissions to improving air quality in typical urban areas, and these research results can provide guidance for the further monitoring of air pollution in northern Chinese cities.

Telemedicine and cystic fibrosis: Do we still need face-to-face clinics?

There has been growing interest in telemedicine for cystic fibrosis over recent years based largely on convenience for patients and/or increasing the frequency of surveillance and early detection which, it is assumed, could improve treatment outcomes. During 2020, the covid-19 pandemic catalysed the pace of development of this field, as CF patients were presumed to be at high risk of infection. Most clinics adapted to digital platforms with provision of lung function monitoring and sample collection systems. Here, we present the views of multidisciplinary team members at a large paediatric CF centre on what has worked well and what requires further optimisation in the future. In response to the question posed, 'Do we still need face to face clinics?' our answer is 'Yes, but not every time, and not for everyone'.

Mathematical Model and Analysis on the Impact of Awareness Campaign and Asymptomatic Human Immigrants in the Transmission of COVID-19

In this study, an autonomous type deterministic nonlinear mathematical model that explains the transmission dynamics of COVID-19 is proposed and analyzed by considering awareness campaign between humans and infectives of COVID-19 asymptomatic human immigrants. Unlike some of other previous model studies about this disease, we have taken into account the impact of awareness c between humans and infectives of COVID-19 asymptomatic human immigrants on COVID-19 transmission. The existence and uniqueness of model solutions are proved using the fundamental existence and uniqueness theorem. We also showed positivity and the invariant region of the model system with initial conditions in a certain meaningful set. The model exhibits two equilibria: disease (COVID-19) free and COVID-19 persistent equilibrium points and also the basic reproduction number, R₀ which is derived via the help of next generation approach. Our analytical analysis showed that disease-free equilibrium point is obtained only in the absence of asymptomatic COVID-19 human immigrants and disease (COVID-19) in the population. Moreover, local stability of disease-free equilibrium point is verified via the help of Jacobian and Hurwitz criteria, and the global stability is verified using Castillo-Chavez and Song approach. The disease-free equilibrium point is both locally and globally asymptotically stable whenever R₀ < 1, so that disease dies out in the population. If  R₀ > 1, then disease-free equilibrium point is unstable while the endemic equilibrium point exists and stable, which implies the disease persist and reinvasion will occur within a population. Furthermore, sensitivity analysis of the basic reproduction number, R₀ with respect to model parameters, is computed to identify the most influential parameters in transmission as well as in the control of COVID-19. Finally, some numerical simulations are illustrated to verify the theoretical results of the model.

Investigations on air quality of a critically polluted industrial city using multivariate statistical methods: Way forward for future sustainability

Industrially developed cities affect public health, and can directly cause inconvenience to the nearby societies especially due to their associated air pollution. In this context, the present study was conducted in Jharsuguda district of Odisha state (India), which is a well-known worldwide hub of industrial clusters. The study area is having mainly medium to large scale industries which makes it prone to poor air quality. A total of twelve air pollutants, namely, PM₁₀, PM_2.5, SO₂, NO₂, CO, O₃, NH₃, and heavy metals (Cu, Mn, Ni, Pb, Zn) were monitored during winter season, at the 16 locations of study area. The air quality data was further assessed using multivariate analysis, and the obtained information was presented using histogram plots, box plots, cluster analysis, principal component analysis (PCA), analysis of variance (ANOVA) analysis, and air quality index (AQI). The statistical analysis results revealed that PM₁₀ and PM_2.5 levels exceeded the permissible limits of study area, ∼40 and 30% of sampling times, respectively. Contrary, values of other pollution parameters were observed to be well within the permissible limits. The cluster analysis distinguishingly summarized the monitoring data into four clusters types, named as severely polluted, moderately polluted, satisfactory, and fine. The PCA analysis of monitored data resulted in identification of prominent emission sources of analyzed pollutants. These sources were mainly found to be associated with coal burning in power plants, agricultural activities, vehicular emissions, and mining activities. The minimum AQI was observed as 87 at Orient (mine no. 4) and Kinjirma which is under satisfactory category, whereas maximum AQI was observed at Bhedabahal with a value of 132 which is under moderate category. Overall, the results of this study indicated that the air pollution of industrial areas must be evaluated thoroughly on regular basis, considering the sustainability of societies and expanding industries.

Characteristics of equivalent black carbon aerosols over Doon Valley in NW Indian Himalaya during COVID-19 lockdown 2020

Recently, black carbon (BC) has been identified as a potential transmitter for COVID-19 besides being responsible for climate change and serious health hazards. To mitigate the dreaded consequences of COVID-19 pandemic, the Government of India declared a nationwide lockdown on March 24, 2020. Accordingly, observations on equivalent black carbon (EBC) aerosols using AE 51 Aethalometer were performed during different lockdowns in Doon Valley. During April, May, June, and July, the monthly average EBC mass concentration recorded 2.12 ± 1.14 μg m^-3, 2.58 ± 1.46 μg m^-3, 2.74 ± 1.49 μg m^-3, and 2.12 ± 1.32 μg m^-3, respectively. A comparison of diurnal variation patterns with earlier studies indicates a significant reduction in EBC mass concentration levels. Bipolar NWR analysis for April and May depicts that relatively high EBC concentration was experienced with prominent south-easterly winds. The EBC concentration level during daytime was high compared to nighttime hours. Preliminary visualization of scanning electron micrographs indicates the variable morphology of aerosols. The bulk particle EDX spectral analysis indicates C, O, Na, F, Al, Si, K, Ca, and Ti elements with a dominance of C and O. Windblown dust seems to be the major contributor to the ambient aerosols. Furthermore, MODIS recorded the fire anomaly (attributed to the wheat stubble burning) starting from mid of April to early-June along the Indo-Gangetic Basin. Heavy loading of polluted aerosols was visible in CALIPSO data imageries. HYSPLIT cluster trajectories indicate that the study region is strongly influenced by the air mass transporting from the Gangetic Plain, Iran, Pakistan, Afghanistan, and Gulf region.

COVID-19 Pandemic Lockdown: An Excellent Opportunity to Study the Effects of Trawling Disturbance on Macrobenthic Fauna in the Shallow Waters of the Gulf of Gabès (Tunisia, Central Mediterranean Sea)

This study describes for the first time in the central Mediterranean Sea the effects of bottom trawling on macrobenthic fauna in tidal channels of the Kneiss Islands in the Gulf of Gabès, Tunisia. Following a BACI protocol, two control stations (protected by artificial reefs) and two trawled stations (impacted stations) were sampled during a period with the absence of bottom trawling activity (the COVID-19 pandemic lockdown period from March to May 2020) and during a trawled period. Although bottom trawling had no impact on sediment composition, this anthropogenic activity reduced the concentration of dissolved oxygen and had a noticeable effect on water column turbidity. The absence of trawling led to a significant increase in biomass, number of species, and abundance of total macrofauna. This illustrated the negative effect of trawling activity in shallow waters and the high resilience of macrobenthic communities of the tidal ecosystem of the Kneiss Islands. In the future, it would be very important to control the use of this destructive fishing gear due to its negative impact on the marine habitat and macrofauna, which represents essential prey for fishes and birds living in this protected area.

Spatio-temporal variation and sensitivity analysis of aerosol particulate matter during the COVID-19 phase-wise lockdowns in Indian cities

At the pandemic of COVID-19, the movement of business and other non-essential activities were majorly restricted at the end of March 2020 in India and continued in different lockdown phases until June 2020. By categorically, studying sensitivity towards anthropogenic factors with other environmental implications in urban Indian cities during phase-wise lockdown scenarios will pave the way for a refined Clean Air Programme (CAP). In this study, the aerosol particulate matter variations between the lockdown phases in both spatial and temporal scales have been explored along with cities exceeding national ambient air quality (NAAQ) standards covering different geographical regions of India for their air quality level. The results of the spatial pattern of Copernicus Atmosphere Monitoring System (CAMS) near-real-time data showed a negative change both in Aerosol Optical Depth (AOD) (-0.2 to 0.1) and black carbon AOD (bcAOD) (-0.9 to -0.75). The changes were evident in successive phases of lockdown with an overall AOD reduction of about 70-90%. Southern urban cities showed a significant impact of mobile sources from temporal analysis than other cities. Principal Component Analysis (PCA) for effects of pollutants by anthropogenic factors (mobile and point source) and meteorological factors (wind speed, wind direction, solar radiation, relative humidity) revealed the two significant driving factors. PM reduction was about 50-70%, predominantly due to anthropogenic factors. The factor analysis revealed the influence of meteorological factors between the major urban cities (Delhi, Kolkata, Mumbai, Chennai, Bengaluru, and Hyderabad). Cities that exceed NAAQ standard performed well during phase-wise lockdowns, exceptional to cities in Gangetic plain. This study helps to frame region-specific strategic action plans for the CAP.

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.

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

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

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

BACKGROUND

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

RESULTS

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

CONCLUSIONS

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

The Impact of COVID-19 Pandemic on Blood Transfusion Services: A Perspective from Health Professionals and Donors

Purpose

Since the emergence of the COVI9-19 pandemic, there has been concern about the availability and sufficiency of blood transfusions to meet patient needs. Also, the adequate and safe blood supply is a major issue to fulfill present demands. This study aims to determine the impact of the COVID-19 pandemic on the blood transfusion service and identify solutions to overcome this impact from the perspective of blood donors and healthcare professionals.

Methods

This study was conducted prospectively among Saudi Arabian blood donors and healthcare professionals between May 2020 and May 2021. A group of professional health care professionals and blood donors participated in this study to determine the impact of the COVID-19 pandemic on blood transfusion services and identify possible solutions to overcome the adverse effects on blood system activities.

Results

To understand the impact of pandemic COVID-19 on blood transfusion services in Saudi Arabia, we investigated population dynamics and statistical analysis from different age groups and health care professionals. A total of 424 blood donors and 372 healthcare professionals participated in this study. The suggested solution by the participants to overcome the blood shortage during pandemics was the organization of mobile blood drives at donors’ homes, work, and educational sites. Statically significant associations were found between blood donation during this pandemic and age (p=0.019) and marital status (p=0.001).

Conclusion

The findings of this study highlight the main problems of blood transfusion due to the onset of COVID-19. Hence, the data could be a source of improving blood transfusion and blood donation systems by healthcare centers and on an individual basis. Healthcare professionals use this public management system in hospitals to minimize the adverse effects of the pandemic.

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Variations in the tropospheric concentration of NO2 in the central west of Brazil, MS, and their relationship with the COVID-19

COVID-19 (coronavirus disease 2019) started in late 2019 in Wuhan, China. Subsequently, the disease was disseminated in several cities around the world, where measures were taken to control the spread of the virus through the adoption of quarantine (social isolation and closure of commercial sectors). This article analyzed the environmental impact of the COVID-19 outbreak in the state of Mato Grosso do Sul, Brazil, regarding the variations of nitrogen dioxide (NO₂) in the atmosphere. NO₂ data from the AURA satellite, in the period before the beginning of the epidemic (2005-2019) and during the adoption of the preventive and control measures of COVID-19 in 2020, were acquired and compared. The results obtained from the analysis showed that the blockade from COVID-19, beginning in March 2020, improved air quality in the short term, but as soon as coal consumption in power plants and refineries returned to normal levels (since June 2020), due to the resumption of works, the pollution levels returned to the level of the previous years of 2020. NO₂ levels showed a significant decrease, since they were mainly associated with the decrease in economic growth and transport restrictions that led to a change in energy consumption and a reduction in emissions. This study can complement the scientific community and policy makers for environmental protection and public management, not only to assess the impact of the outbreak on air quality, but also for its effectiveness as a simple alternative program of action to improve air quality.

An Impact Analysis of Artificial Light at Night (ALAN) on Bats. A Case Study of the Historic Monument and Natura 2000 Wisłoujście Fortress in Gdansk, Poland

The artificial light at night (ALAN) present in many cities and towns has a negative impact on numerous organisms that live alongside humans, including bats. Therefore, we investigated if the artificial illumination of the historic Wisłoujście Fortress in Gdańsk, Poland (part of the Natura 2000 network), during nighttime events, which included an outdoor electronic dance music (EDM) festival, might be responsible for increased light pollution and the decline in recent years of the pond bat (Myotis dasycneme). An assessment of light pollution levels was made using the methods of geographical information system (GIS) and free-of-charge satellite remote sensing (SRS) technology. Moreover, this paper reviewed the most important approaches for environmental protection of bats in the context of ecological light pollution, including International, European, and Polish regulatory frameworks. The analysis of this interdisciplinary study confirmed the complexity of the problem and highlighted, too, the need for better control of artificial illumination in such sensitive areas. It also revealed that SRS was not the best light pollution assessment method for this particular case study due to several reasons listed in this paper. As a result, the authors' proposal for improvements also involved practical recommendations for devising suitable strategies for lighting research and practice in the Natura 2000 Wisłoujście Fortress site located adjacent to urban areas to reduce the potential negative impact of ALAN on bats and their natural habitats.

The Interplay between Housing Environmental Attributes and Design Exposures and Psychoneuroimmunology Profile-An Exploratory Review and Analysis Paper in the Cancer Survivors' Mental Health Morbidity Context

Adult cancer survivors have an increased prevalence of mental health comorbidities and other adverse late-effects interdependent with mental illness outcomes compared with the general population. Coronavirus Disease 2019 (COVID-19) heralds an era of renewed call for actions to identify sustainable modalities to facilitate the constructs of cancer survivorship care and health care delivery through physiological supportive domestic spaces. Building on the concept of therapeutic architecture, psychoneuroimmunology (PNI) indicators-with the central role in low-grade systemic inflammation-are associated with major psychiatric disorders and late effects of post-cancer treatment. Immune disturbances might mediate the effects of environmental determinants on behaviour and mental disorders. Whilst attention is paid to the non-objective measurements for examining the home environmental domains and mental health outcomes, little is gathered about the multidimensional effects on physiological responses. This exploratory review presents a first analysis of how addressing the PNI outcomes serves as a catalyst for therapeutic housing research. We argue the crucial component of housing in supporting the sustainable primary care and public health-based cancer survivorship care model, particularly in the psychopathology context. Ultimately, we illustrate a series of interventions aiming at how housing environmental attributes can trigger PNI profile changes and discuss the potential implications in the non-pharmacological treatment of cancer survivors and patients with mental morbidities.

The Impact of COVID-19 Lockdowns on Air Quality—A Global Review

The outbreak of the COVID-19 pandemic has emerged as a serious public health threat and has had a tremendous impact on all spheres of the environment. The air quality across the world improved because of COVID-19 lockdowns. Since the outbreak of COVID-19, large numbers of studies have been carried out on the impact of lockdowns on air quality around the world, but no studies have been carried out on the systematic review on the impact of lockdowns on air quality. This study aims to systematically assess the bibliographic review on the impact of lockdowns on air quality around the globe. A total of 237 studies were identified after rigorous review, and 144 studies met the criteria for the review. The literature was surveyed from Scopus, Google Scholar, PubMed, Web of Science, and the Google search engine. The results reveal that (i) most of the studies were carried out on Asia (about 65%), followed by Europe (18%), North America (6%), South America (5%), and Africa (3%); (ii) in the case of countries, the highest number of studies was performed on India (29%), followed by China (23%), the U.S. (5%), the UK (4%), and Italy; (iii) more than 60% of the studies included NO2 for study, followed by PM2.5 (about 50%), PM10, SO2, and CO; (iv) most of the studies were published by Science of the Total Environment (29%), followed by Aerosol and Air Quality Research (23%), Air Quality, Atmosphere & Health (9%), and Environmental Pollution (5%); (v) the studies reveal that there were significant improvements in air quality during lockdowns in comparison with previous time periods. Thus, this diversified study conducted on the impact of lockdowns on air quality will surely assist in identifying any gaps, as it outlines the insights of the current scientific research.

Influence of meteorology, mobility, air mass transport and biomass burning on PM2.5 of three north Indian cities: phase-wise analysis of the COVID-19 lockdown

Recent studies concluded that air quality has improved due to the enforcement of lockdown in the wake of COVID-19. However, they mostly concentrated on the changes during the lockdown period, and the studies considering the consequences of de-escalation of lockdown are inadequate. Therefore, we investigated the changes in fine particulate matter (PM2.5) during the pre-lockdown, strict lockdown, unlocking, and post-lockdown scenarios. In addition, we assessed the influence of meteorology, mobility, air mass transport, and biomass burning on PM2.5 using Google's mobility data, back trajectory model, and satellite-based fire incident data. Average PM2.5 concentrations in Ghaziabad, Noida, and Faridabad decreased by 60.70%, 63.27%, and 60.40%, respectively, during the lockdown. When compared with the preceding year (2019), the reductions during the shutdown period (25 March-31 May) were within the range of 36.34-44.55%. However, considering the entire year, this reduction in PM2.5 is momentary, and a steady increase in traffic density and industrial operations within cities during post-lockdown reflects a potent recovery of aerosol level, during which the average mass of PM2.5 three- to four-folds higher than the lockdown period. Back trajectories and fire activity results showed that biomass burning in the nearby states (Haryana and Punjab) influence aerosol load. We conclude that a partial lockdown in the event of a sudden surge in pollution would be a beneficial approach. However, reducing fossil fuel consumption and switching to more environmentally friendly energy sources, developing green transport networks, and circumventing biomass burning are efficient ways to improve air quality in the long term.

COVID-19 lockdown and particle exposure of road users

INTRODUCTION

In 2020, due to the outbreak of COVID-19, there has been an unprecedented decrease in road traffic in almost all urbanized areas around the globe. This has undoubtedly affected the ambient air quality.

METHODS

In this study mobile and fixed-site measurements of aerosol particle concentrations in the ambient air in one of the busiest streets in Lublin, a mid-sized city in Central Europe (Poland) during the COVID-19 lockdown in the spring of 2020 were performed. Based on the measurements particle doses received by road users during different times of the day were assessed. The obtained results were compared with corresponding pre-COVID-19 measurements also performed in the spring which were available only from 2017.

RESULTS

During lockdown the mass concentration of traffic-related submicrometer PM1 particles and number concentration of ultrafine PN0.1 particles was significantly reduced. This resulted in a decrease of doses inhaled by road users as well as of particle doses deposited in their respiratory tracks. The greatest reductions of respectively over 2 times and over 5 times were observed during the day for total particles and traffic-related particles. Smaller reductions indicating the existence of relatively intensive non-traffic emissions were reported at night.

CONCLUSIONS

Substantial decrease in traffic intensity in the city caused by lockdown restrictions resulted in a significant reduction in the concentration of vehicle-generated particles in the ambient air. This in turn could have resulted in smaller doses inhaled by the inhabitants, specifically road users, which should have a positive impact on their health.

Environmental impacts of coronavirus disease 2019 (COVID-19)

The coronavirus disease (COVID-19), a variant of Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) originated in Wuhan city of China and has now transmitted over the world. Till the April 24, 2020, nearly 144,367,284 confirmed positive cases with 3,066,270 deaths worldwide. The recent studies have reported that SARS-CoV-2 is transmitted through respiratory droplets. Several vaccines are available now. However, the vaccination process has not completed yet. Worldwide lockdown was initiated to restrict gathering, transport and industrial activities. Lockdown due to COVID-19 showed reduction in environmental pollution. The quality of air and water improved in metro cities and in rivers during COVID-19. This review not only provides the updated information related to impact of COVID-19 on air, water and noise pollution, generation of biomedical waste and global environmental sustainable development but also it covers the basic mechanism of COVID-19 transmission.