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The containment of the spread of COVID-19 pandemic and limitations on commercial activities, mobility and manufacturing sector have significantly affected waste management. Waste management is critical to human development and health outcomes, especially during the COVID-19 pandemic. The invaluable service provided by the waste management sector ensures that the unusual heaps of waste that poses health risks and escalate the spread of COVID-19 is avoided. In this study, we assess the impact of COVID-19 pandemic on waste management by observing lockdown and social distancing measures. We found that the quantity of waste increased across countries observing the social distancing measure of staying at home. The intensification of single-use products and panic buying have increased production and consumption, hence thwarting efforts towards reducing plastic pollution. However, several countries have thus far instituted policies to ensure sustainable management of waste while protecting the safety of waste handlers.

The institution of social distancing and punitive measures to contain the spread of COVID-19 through human-to-human transmission has environmental, health and economic impact. While the global pandemic has led to the enhancement of the health system and decline of emissions, economic development appears deteriorating. Here, we present the global environmental, health and economic dimension of the effect of COVID-19 using qualitative and empirical assessments. We report the health system policies, environmental sustainability issues, and fiscal, monetary and exchange rate measures introduced during lockdown across countries. While air pollution is reported to have declined, municipal and medical waste is increasing. The COVID-19 global pandemic uncertainty ranks the UK as the country with the highest uncertainty level among 143 countries. The USA has introduced 100% of pre-COVID-19 crisis level GDP, the highest policy cut-rate among 162 countries. Science, innovation, research and development underpin COVID-19 containment measures implemented across countries. Our study demonstrates the need for future research to focus on environment-health-economic nexus—a trilemma that has a potential trade-off.

Many articles have been written in the medical field related to the Covid-19 outbreak that has surrounded the World and killed many people. However, its environmental and energy impacts have not been sufficiently studied. Some sources argue that Covid-19 outbreak reduces pollution environmentally, while others say that environmentally significant damages await us. On the other hand, it is wondered how the global flexible renewable energy sector will react to Covid-19 outbreak. In this study, the effects of Covid-19 outbreak in terms of the environment and renewable energy sector in the literature were examined in detail and the findings obtained were discussed. The main aim of this study is to shed light on the future studies of environmental and renewable energy researchers.

Community transmission of COVID-19 is happening in Bangladesh—the country which did not have a noteworthy health policy and legislative structures to combat a pandemic like COVID-19. Early strategic planning and groundwork for evolving and established challenges are crucial to assemble resources and react in an appropriate timely manner. This article, therefore, focuses on the public perception of comparative lockdown scenario analysis and how they may affect the sustainable development goals (SDGs) and the strategic management regime of COVID-19 pandemic in Bangladesh socio-economically as well as the implications of the withdrawal of partial lockdown plan. Scenario-based public perceptions were collected via a purposive sampling survey method through a questionnaire. Datasets were analysed through a set of statistical techniques including classical test theory, principal component analysis, hierarchical cluster analysis, Pearson’s correlation matrix and linear regression analysis. There were good associations among the lockdown scenarios and response strategies to be formulated. Scenario 1 describes how the death and infection rate will increase if the Bangladesh Government withdraws the existing partial lockdown. Scenario 2 outlines that limited people’s movement will enable low-level community transmission of COVID-19 with the infection and death rate will increase slowly ( r  = 0.540, p  < 0.01). Moreover, there will be less supply of necessities of daily use with a price hike ( r  = 0.680, p  < 0.01). In scenario 3, full lockdown will reduce community transmission and death from COVID-19 ( r  = 0.545, p  < 0.01). However, along with the other problems gender discrimination and gender-based violence will increase rapidly ( r  = 0.661, p  < 0.01). Due to full lockdown, the formal and informal business, economy, and education sector will be hampered severely ( R  = 0.695). Subsequently, there was a strong association between the loss of livelihood and the unemployment rate which will increase due to business shutdown ( p  < 0.01). This will lead to the severe sufferings of poor and vulnerable communities in both urban and rural areas ( p  < 0.01). All these will further aggravate the humanitarian needs of the most vulnerable groups in the country in the coming months to be followed which will undoubtedly affect the Bangladesh targets to achieve the SDGs of 2030 and other development plans that need to be adjusted. From our analysis, it was apparent that maintaining partial lockdown with business and economic activities with social distancing and public health guidelines is the best strategy to maintain. However, as the government withdrew the partial lockdown, inclusive and transparent risk communication towards the public should be followed. Recovery and strengthening of the health sector, economy, industry, agriculture, and food security should be focused on under the “new normal standard of life” following health guidelines and social distancing. Proper response plans and strategic management are necessary for the sustainability of the nation. Graphic abstract

The fatal novel coronavirus (COVID-19) pandemic disease smashes the normal tempo of global socio-economic and cultural livelihood. Most of the countries impose a lockdown system with social distancing measures to arrest the rapid transmission of this virus into the human body. The objective of this study is to examine the status of air quality during and pre-COVID-19 lockdown and to recommend some long-term sustainable environmental management plan. The pollution data like PM 10 , PM 2.5 , O 3 , SO 2 , NO 2 and CO have been obtained from State Pollution Control Board under Govt. of West Bengal. Similarly, various land surface temperature (LST) maps have been prepared using LANDSAT-8 OLI and LANDSAT-7 ETM + images of USGS. The maps of NO 2 and aerosol concentration over Indian subcontinent have been taken from ESA and NASA. The digital thematic maps and diagrams have been depicted by Grapher 13 and Arc GIS 10.3 platforms. The result shows that the pollutants like CO, NO 2 and SO 2 are significantly decreased, while the average level of O 3 has been slightly increased in 2020 during the lockdown due to close-down of all industrial and transport activities. Meanwhile, around 17.5% was the mean reduction of PM 10 and PM 2.5 during lockdown compared with previous years owing to complete stop of vehicles movement, burning of biomass and dust particles from the construction works. This study recommends some air pollution-tolerant plant species (in urban vacant spaces and roof tops) for long-term cohabitation among environment, society and development.

The present work estimates the increased risk of coronavirus disease (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 by establishing the linkage between the mortality rate in the infected cases and the air pollution, specifically Particulate Matters (PM) with aerodynamic diameters ≤ 10 µm and ≤ 2.5 µm. Data related to nine Asian cities are analyzed using statistical approaches, including the analysis of variance and regression model. The present work suggests that there exists a positive correlation between the level of air pollution of a region and the lethality related to COVID-19, indicating air pollution to be an elemental and concealed factor in aggravating the global burden of deaths related to COVID-19. Past exposures to high level of PM 2.5 over a long period, is found to significantly correlate with present COVID-19 mortality per unit reported cases ( p  < 0.05) compared to PM 10 , with non-significant correlation ( p  = 0.118). The finding of the study can help government agencies, health ministries and policymakers globally to take proactive steps by promoting immunity-boosting supplements and appropriate masks to reduce the risks associated with COVID-19 in highly polluted areas.

The novel coronavirus (2019-nCoV) originated in China has now covered around 213 countries globally. It has posed health calamities which have threatened the world with the emergence. Owing to the number of confirmed cases still rising every day, it has now become a phase of an international health emergency. Sudden outbreak of coronavirus disease 2019 (COVID-19) has brought global declines in the commodity process. This has majorly affected the demand as well as supply of the commodities. The oil market has been severely affected due to the outrageous collapse in the demand majorly due to travel restrictions which has also caused the steepest decline in oil prices. The prices of both precious and industrial metals have also fallen, although the price drop is less than that of oil prices. The agriculture industry is one of the least affected so far by this pandemic due to its indirect relation with economic activities. However, the ultimate impact of COVID-19 pandemic will greatly depend on the severity and duration of its outspread, but it is expected to have long-lasting implications.

COVID-19 is a highly infectious disease caused by SARS-CoV-2, first identified in China and spread globally, resulting into pandemic. Transmission of virus takes place either directly through close contact with infected individual (symptomatic/asymptomatic) or indirectly by touching contaminated surfaces. Virus survives on the surfaces from few hours to days. It enters the human body through nose, eyes or mouth. Other sources of contamination are faeces, blood, food, water, semen etc. Parameters such as temperature/relative humidity also play an important role in transmission. As the disease is evolving, so are the number of cases. Proper planning and restriction are helping in influencing the trajectory of the transmission. Various measures are undertaken to prevent infection such as maintaining hygiene, using facemasks, isolation/quarantine, social/physical distancing, in extreme cases lockdown (restricted movement except essential services) in hot spot areas or throughout the country. Countries that introduced various mitigation measures had experienced control in transmission of COVID-19. Python programming is conducted for change point analysis (CPA) using Bayesian probability approach for understanding the impact of restrictions and mitigation methods in terms of either increase or stagnation in number of COVID-19 cases for eight countries. From analysis it is concluded that countries which acted late in bringing in the social distancing measures are suffering in terms of high number of cases with USA, leading among eight countries analysed. The CPA week in comparison with date of lockdown and first reported case strongly correlates (Pearson’s r  = − 0.86 to − 0.97) to cases, cases per unit area and cases per unit population, indicating earlier the mitigation strategy, lesser the number of cases. The overall paper will help the decision makers in understanding the possible steps for mitigation, more so in developing countries where the fight against COVID-19 seems to have just begun.

Originating from Wuhan, China, COVID-19 is spreading rapidly throughout the world. The transmission rate is reported to be high for this novel strain of coronavirus, called severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), as compared to its predecessors. Major strategies in terms of clinical trials of medicines and vaccines, social distancing, use of personal protective equipment (PPE), and so on are being implemented in order to control the spread. The current study concentrates on lockdown and social distancing policy followed by the Indian Government and evaluates its effectiveness using Bayesian probability model (BPM). The change point analysis (CPA) done through the above approach suggests that the states which implemented the lockdown before the exponential rise of cases are able to control the spread of the disease in a much better and efficient way. The analysis has been done for states of Maharashtra, Gujarat, Madhya Pradesh, Rajasthan, Tamil Nadu, West Bengal, Uttar Pradesh, and Delhi as union territory. The highest value of Δ (delta) is reported for Gujarat and Madhya Pradesh with a value of 9.6 weeks, while the lowest value is 4.7, evidently for Maharashtra which is the worst affected. All of the states indicate a significant correlation ( p  < 0.05, tstat > tcritical) for Δ, i.e., the difference in the time period of CPA and lockdown with cases per population (CPP) and cases per unit area (CPUA), while weak correlation ( p  < 0.1 and tstat < tcritical) is exhibited by delta and cases per unit population density (CPD). For both CPP and CPUA, tstat > tcritical indicating a significant correlation, while Pearson’s correlation indicates the direction to be negative. Further analysis in terms of identification of high-risk areas has been studied from the Voronoi approach of GIS based on the inputs from BPM. All the states follow the above pattern of high population, high case scenario, and the boundaries of risk zones can be identified by Thiessen polygon (TP) constructed therein. The findings of the study help draw strategic and policy-driven response for India, toward tackling COVID-19 pandemic.