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This paper estimates the impact of the COVID-19 on air travel demand and emissions in Brazil, the largest aviation market in Latin America. Combining detailed flight data and data on combustion emission factors, we estimate the CO

Abstract Urban resilience (UR) is a central concept in enabling cities to be prepared for disasters and unexpected events caused by climate change-induced extreme weather conditions. The field is dedicated to developing solutions and models in this regard. In particular, the emergence of the ongoing COVID-19 pandemic has threatened certain industries and has compelled cities to re-evaluate and address resilience. This study aims to provide an overview of the subject by examining the academic and industrial literature on UR, categorizing publications, analyzing major trends, as well as highlighting gaps and providing future research recommendations. In this context, 146 journal articles and 9 industrial reports published up to the end of 2020 were examined. Journal articles have been examined under three headings as literature reviews, conceptual models, and analytical models. The approaches and analytical techniques discussed in the field are also examined in the review. These examinations and classifications constitute the originality of the study. Examination of industrial reports has provided us with the opportunity to understand the practices discussed and suggested by practitioners in this field. The results show that the most commonly arising issue in UR is climate change. Finally, the research gaps and future suggestions are presented.

Stringent pollution control measures are generally applied to improve air quality, especially in the Spring Festival in China. Meanwhile, human activities are reduced significantly due to nationwide lockdown measures to curtail the COVID-19 spreading in 2020. Herein, to better understand the influence of control measures and meteorology on air pollution, this study compared the variation of pollution source and their health risk during the 2019 and 2020 Spring Festival in Linfen, China. Results revealed that the average concentration of PM

A novel series of bis- (Abdelhamid et al., 2017, Banerjee et al., 2018, Bharanidharan et al., 2022)thiadiazoles was synthesized from the reaction of precursor dimethyl 2,2′-(1,2-diphenylethane-1,2-diylidene)-bis(hydrazine-1-carbodithioate) and hydrazonyl chlorides in ethanol under ultrasonic irradiation. Spectral tools (IR. NMR, MS, elemental analyses, molecular dynamic simulation, DFT and LUMO and HOMO) were used to elucidate the structure of the isolated products. Molecular docking for the precursor, 3 and ligands 6a-i to two COVID-19 important proteins M$^{pro}$ and RdRp was compared with two approved drugs, Remdesivir and Ivermectin. The binding affinity varied between the ligands and the drugs. The highest recorded binding affinity of 6c with M$^{pro}$ was (−9.2 kcal/mol), followed by 6b and 6a, (−8.9 and −8.5 kcal/mol), respectively. The lowest recorded binding affinity was (−7.0 kcal/mol) for 6 g. In comparison, the approved drugs showed binding affinity (−7.4 and −7.7 kcal/mol), for Remdesivir and Ivermectin, respectively, which are within the range of the binding affinity of our ligands. The binding affinity of the approved drug Ivermectin against RdRp recoded the highest (−8.6 kcal/mol), followed by 6a, 6 h, and 6i are the same have (−8.2 kcal/mol). The lowest reading was found for compound 3 ligand (−6.3 kcal/mol). On the other side, the amino acids also differed between the compounds studied in this project for both the viral proteins. The ligand 6a forms three H-bonds with Thr 319(A), Sr 255(A) and Arg 457(A), whereas Ivermectin forms three H-bonds with His 41(A), Gly143(A) and Gln 18(A) for viral M$^{pro}$. The RdRp amino acids residues could be divided into four groups based on the amino acids that interact with hydrogen or hydrophobic interactions. The first group contained 6d, 6b, 6 g, and Remdesivir with 1–4 hydrogen bonds and hydrophobic interactions 1 to 10. Group 2 is 6a and 6f exhibited 1 and 3 hydrogen bonds and 15 and 14 hydrophobic interactions. Group 3 has 6e and Ivermectin shows 4 and 3 hydrogen bonds, respectively and 11 hydrophobic interactions for both compounds. The last group contains ligands 3, 6c, 6 h, and 6i gave 1–3 hydrogen bonds and 6c and 3 recorded the highest number of hydrophobic interactions, 14 for both 6c and 6 h. Pro Tox-II estimated compounds’ activities as Hepatoxic, Carcinogenic and Mutagenic, revealing that 6f-h were inactive in all five similar to that found with Remdesivir and Ivermectin. The drug-likeness prediction was carried out by studying physicochemical properties, lipophilicity, size, polarity, insolubility, unsaturation, and flexibility. Generally, some properties of the ligands were comparable to that of the standards used in this study, Remdesivir and Ivermectin.

During the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic, alcohol consumption increased markedly. Nearly one in four adults reported drinking more alcohol to cope with stress. Chronic alcohol abuse is now recognized as a factor complicating the course of acute respiratory distress syndrome and increasing mortality. To investigate the mechanisms behind this interaction, a combined acute respiratory distress syndrome and chronic alcohol abuse mouse model was developed by intratracheally instilling the subunit 1 (S1) of SARS-CoV-2 spike protein (S1SP) in K18-human angiotensin-converting enzyme 2 (ACE2) transgenic mice that express the human ACE2 receptor for SARS-CoV-2 and were kept on an ethanol diet. Seventy-two hours after S1SP instillation, mice on an ethanol diet showed a strong decrease in body weight, a dramatic increase in white blood cell content of bronchoalveolar lavage fluid, and an augmented cytokine storm, compared with S1SP-treated mice on a control diet. Histologic examination of lung tissue showed abnormal recruitment of immune cells in the alveolar space, abnormal parenchymal architecture, and worsening Ashcroft score in S1SP- and alcohol-treated animals. Along with the activation of proinflammatory biomarkers [NF-κB, STAT3, NLR family pyrin domain-containing protein 3 (NLRP3) inflammasome], lung tissue homogenates from mice on an alcohol diet showed overexpression of ACE2 compared with mice on a control diet. This model could be useful for the development of therapeutic approaches against alcohol-exacerbated coronavirus disease 2019.

Coronavirus is an extremely infectious and fatal disease that can be spread straight from one individual to another. COVID-19 is currently causing a lot of concern worldwide since it is difficult to detect and prevent. The Internet of Things (IoT) coupled with the wireless sensor network (WSN) has an impact on lowering the medical expenses and improving the treatment results of the infected individual. This paper proposes a secure and energy-efficient WSN architecture combined with machine learning and IoT to recognize and observe the Covid-19 patients. The proposed architecture is designed to determine whether a person has COVID-19 or a typical cold, depending on their symptoms. The proposed architecture utilizes the supervised machine learning techniques such as random forest classifier, multi-layer perceptron, Naive Bayes, logistic regression, support vector machine classifiers to improve the precision of COVID-19 investigation. Energy efficiency is a significant obstacle for the sensor devices' longterm sustainability because signal transmission from many biosensors to the cloud consumes a large amount of energy. The proposed architecture substantially enhances the WSN's power efficiency as well as its longevity. The findings show that the identified variables can assist in forecasting the probability of having a more serious illness in COVID-19 patients and can aid with health resource allocation.

The daily life of people is changing due to the increase in climate change effects. In the times of historic Covid-19 pandemic event, by the precautions like stay at home, people tried to obey those cautions. This kind of protections decreased the CO2 gas emissions by 17%, obtaining the world returned to 2006 gas emissions values. The air became more breathable and the nature began to repair itself without the touch of people. As the population grows, feeding this population became a separate problem. People started to destroy forest areas because more agriculture was needed for more nutrition. Of course, this destruction also had a direct impact on climate change. Humanity once again saw that it had to develop with nature, not against nature. This eye-opening process will force people to act quickly on what needs to be done for climate change. Even though the relatively less emission comes from the agriculture, this sector has to transform itself by new technologies due to its strategical position. Vertical farming alternative is a candidate for this conversion process. Many methods in vertical farming are handled in this chapter. Some cultivation methods as hydroponic, aeroponic and aquaponic systems are dealt also. Energy and water consumption, yield, and scalability criteria are examined for the vertical farming under climate effects. In addition, some newly technologies like artificial intelligence applied to vertical farming are presented in this study. To see the benefit of this agricultural method a feasibility and economic analysis had to be made, so it’s done with real data. Interesting results and inferences have been obtained and presented at the end of the study.

The issue of food waste is a problem that affects the whole society. Food is wasted throughout the food chain. Households are great contributors to the problem. A detailed analysis of municipal waste from the production of 900 Czech households was performed. These datasets allowed for comprehensive insides. The analyses of mixed municipal waste were performed every quarter of the year (summer 2019–spring 2020). The method of municipal waste analysis was supplemented by questionnaire survey among households and 10 in-depth interviews aimed at identifying the main causes of waste. One of the periods in which food waste was measured was affected by the global COVID-19 pandemic. This finding has also been confirmed by findings from other countries. The climatic crisis multiplied by the impacts of COVID-19 has highlighted the need to actively address the issue of food waste.

One “silver lining” of the COVID-19 pandemic has been the reduction in air pollution that followed lockdowns. Unfortunately, this unintended air pollution decline will likely be short-lived. As regions begin to recover their economies, travel and industrial activity will increase the ambient pollutants quickly offsetting the improvement in air quality. Therefore, it is urgent to clarify the causal impact of reopening an economy on air quality during COVID-19. Based on city-level daily air quality data in China, this paper is the first to empirically analyze the causal effect of reopening the economy in the provincial capital Lanzhou on concentrations of four air pollutants using the synthetic control method. The results show that the reopening caused a significant increase in the concentration of NO2 by as much as 30 μg/m3 (an increase of 75% from the lockdown level) and a significant increase in O3 concentrations by 60μg/m3 (a 60% increase) which peaked on the 6th day after the restart. The reopening also led to significant fluctuations in SO2 and CO concentrations. This study contains useful conclusions by providing timely and reliable causal evidence on the lasting impact of COVID-19 on air quality.

We present a comprehensive analysis of the performance and flows of U.S. actively-managed equity mutual funds during the COVID-19 crisis of 2020. We find that most active funds underperform passive benchmarks during the crisis, contradicting a popular hypothesis. Funds with high sustainability ratings perform well, as do funds with high star ratings. Fund out ows surpass pre-crisis trends, but not dramatically. Investors favor funds that apply exclusion criteria and funds with high sustainability ratings, especially environmental ones. Our finding that investors remain focused on sustainability during this major crisis suggests they view sustainability as a necessity rather than a luxury good.