Air pollution (AP) is one of the major causes of health risks as it leads to widespread morbidity and mortality each year. Its environmental impacts include acid rains, reduced visibility, but more importantly and significantly, it affects human health. The price tag of not managing AP is seen in the rise of chronic obstructive pulmonary disease (COPD), cardiovascular disease, and respiratory ailments like asthma and chronic bronchitis. But as the world battles the corona pandemic, COVID-19 lockdown has abruptly halted human activity, leading to a significant reduction in AP levels. The effect of this reduction is captured by reduced cases of morbidity and mortality associated with air pollution. The current study aims to monetarily quantify the decline in health impacts due to reduced AP levels under lockdown scenario, as against business as usual, for four cities-Delhi, London, Paris, and Wuhan. The exposure assessment with respect to pollutants like particulate matter (PM 2.5 and PM 10 ), NO 2 , and SO 2 are evaluated. Value of statistical life (VSL), cost of illness (CoI), and per capita income (PCI) for disability-adjusted life years (DALY) are used to monetize the health impacts for the year 2019 and 2020, considering the respective period of COVID-19 lockdown of four cities. The preventive benefits related to reduced AP due to lockdown is evaluated in comparison to economic damage sustained by these four cities. This helps in understanding the magnitude of actual damage and brings out a more holistic picture of the damages related to lockdown.

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.

Amid COVID-19, there have been rampant increase in the use of Personal Protective Equipment (PPE) kits by frontline health and sanitation communities, to reduce the likelihoods of infections. The used PPE kits, potentially being infectious, pose a threat to human health, terrestrial, and marine ecosystems, if not scientifically handled and disposed. However, with stressed resources on treatment facilities and lack of training to the health and sanitation workers, it becomes vital to vet different options for PPE kits disposal, to promote environmentally sound management of waste. Given the various technology options available for treatment and disposal of COVID-19 patients waste, Life Cycle Assessment, i.e., cradle to grave analysis of PPE provides essential guidance in identifying the environmentally sound alternatives. In the present work, Life Cycle Assessment of PPE kits has been performed using GaBi version 8.7 under two disposal scenarios, namely landfill and incineration (both centralized and decentralized) for six environmental impact categories covering overall impacts on both terrestrial and marine ecosystems, which includes Global Warming Potential (GWP), Human Toxicity Potential (HTP), Eutrophication Potential (EP), Acidification Potential (AP), Freshwater Aquatic Ecotoxicity Potential (FAETP) and Photochemical Ozone Depletion Potential (POCP). Considering the inventories of PPE kits, disposal of PPE bodysuit has the maximum impact, followed by gloves and goggles, in terms of GWP. The use of metal strips in face-mask has shown the most significant HTP impact. The incineration process (centralized−3816 kg CO2 eq. and decentralized−3813 kg CO2 eq.) showed high GWP but significantly reduced impact w.r.t. AP, EP, FAETP, POCP and HTP, when compared to disposal in a landfill, resulting in the high overall impact of landfill disposal compared to incineration. The decentralized incineration has emerged as environmentally sound management option compared to centralized incinerator among all the impact categories, also the environmental impact by transportation is significant (2.76 kg CO2 eq.) and cannot be neglected for long-distance transportation. Present findings can help the regulatory authority to delineate action steps for safe disposal of PPE kits.

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,

Simulation has been performed on fully lead-free inorganic cesium germanium tri-iodide (CsGeI3) perovskite solar cell heterostructure and achieved a champion power conversion efficiency (PCE) of ∼18.30% with significantly improved device parameters. The influence of thickness of an electron transport layer, a hole transport layer, an absorber, defect density, doping concentration, electron affinity, temperature, and series resistance issued for the optimization of the lead-free device is studied. It is confirmed via the scaps simulation results that this device is perfectly optimized with the experimental results and demonstrates the maximum possible improved power conversion efficiency in a fully inorganic lead-free CsGeI3 perovskite solar cell device. The final optimized device performance parameters are as follows: %PCE = 18.30%, %FF = 75.46%, Jsc = 23.31 mA/cm2, and Voc = 1.04 V. In the future, this efficiency may offer prominent potential as a substitute in a highly efficient green solar absorber material for photovoltaic applications after confirmation in the laboratory.

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.

COVID-19 has taken the world by storm, with the majority of nations still being challenged by the novel coronavirus. The present work attempts to evaluate the spread of COVID-19 in India using the Susceptible-Exposed-Infectious-Removed (SEIR) model to establish the impact of socio-behavioural aspects, especially social distancing. The impact of environmental factors like temperature and relative humidity (RH) using statistical methods, including Response Surface Methodology (RSM) and Pearson’s correlation, is also studied on numbers of COVID-19 cases per day. Here we report the resultant changes of lockdowns-unlocks initiated by the Government of India for COVID-19, as against the scenario of total lockdown. The phased unlocks and crowded gatherings result in an increase in the number of cases and stretch the mitigation timeline of COVID-19 spread, delaying the flattening of the curve. The SEIR model predictions have been fairly validated against the actual cases. The daily spread of COVID-19 cases is also fairly correlated with temperature in Indian cities, as supported by well-established causation of the role of higher temperatures in disrupting the lipid layer of coronavirus, but is greatly undermined by the key factor of social distancing and gets confounded with other multiple unknown co-varying environmental factors. However, the analysis couldn’t clearly establish the role of RH in affecting daily COVID-19 cases. Hence, it becomes essential to include environmental parameters into epidemiological models like SEIR and to systematically plan controlled laboratory experiments and modeling studies to draw conclusive inferences, assisting policymakers and stakeholders in formulating comprehensive action plans to alleviate the COVID-19 spread.

The ongoing pandemic of coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has resulted in unprecedented disease burden, healthcare costs, and economic impacts worldwide. Despite several measures, SARS-CoV-2 has been extremely impactful due to its extraordinary infection potential mainly through coronavirus-borne saliva respiratory and droplet nuclei of an infected person and its considerable stability on surfaces. Although the disease has affected over 180 countries, its extent and control are significantly different across the globe, making it a strong case for exploration of its behavior and dependence across various environmental pathways and its interactions with the virus. This has spurred efforts to characterize the coronavirus and understand the factors impacting its transmission and survival such as aerosols, air quality, meteorology, chemical compositions and characteristics of particles and surfaces, which are directly or indirectly associated with coronaviruses infection spread. Nonetheless, many peer-reviewed articles have studied these aspects but mostly in isolation; a complete array of coronavirus survival and transmission from an infected individual through air- and water-borne channels and its subsequent intractions with environmental factors, surfaces, particulates and chemicals is not comprehensively explored. Particulate matter (PM) is omnipresent with variable concentrations, structures and composition, while most of the surfaces are also covered by PM of different characteristics. Learning from the earlier coronavirus studies, including SARS and MERS, an attempt has been made to understand the survival of SARS-CoV-2 outside of the host body and discuss the probable air and water-borne transmission routes and its interactions with the outside environment. The present work 1) Helps appreciate the role of PM, its chemical constituents and surface characteristics and 2) Further identifies gaps in this field and suggests possible domains to work upon for better understanding of transmission and survival of this novel coronavirus.