Impacts of COVID-19 on energy demand and consumption: Challenges, lessons and emerging opportunities

The relation between mental health and career-related stress among prospective graduates in higher education stage during the COVID-19 pandemic: an evidence based on network analysis

Introduction

The outbreak of the COVID-19 pandemic has disrupted people's routine, bringing uncertainty and stress, leading to mental health issues. This situation is particularly acute among Chinese prospective graduates in higher education stage as they cannot predict the outcomes of their studies, graduation, and career development, and therefore experience career-related stress.

Methods

This study included 4041 prospective graduates in higher education stage (using handy sampling) recruited in March 2020 as participants (M Age = 22.56, SD = 1.865), utilizing a Sparse Gaussian Graphical Model for regularized partial correlation network analysis of depression symptoms (by PHQ-9), anxiety symptoms (by GAD-7), and career-related stress, which aims to explore the role of career-related stress in the symptom networks of depression and anxiety among prospective graduates in their final semester.

Results

The results revealed that fatigue, sad mood, and psychomotor symptoms in depression, as well as uncontrollable worry and trouble relaxing in anxiety, were central symptoms in the network. Additionally, sad mood and guilt belonging to depressive symptoms, and feeling afraid, restlessness, and irritability belonging to anxiety symptoms, served as bridge symptoms connecting symptom communities. Specifically, guilt as a depressive symptom showed a strong association with employment stress in career-related stress. There were no significant differences in network structure and global strength based on participants' gender. However, despite no significant differences in network structure, the global strength of prospective graduates from Wuhan was significantly lower than samples from non-Hubei provinces, possibly indicative of a Typhoon Eye Effect.

Discussion

The findings of this study can inspire psychological professionals in higher education institutions to provide support for mental interventions and therapies for prospective graduates, and addressing career development issues.

Urbanization and renewable energy consumption in the emerging ASEAN markets: A comparison between short and long-run effects

The emerging markets in the ASEAN region, such as Indonesia, Malaysia, the Philippines, Thailand and Vietnam, have put great effort into achieving dual objectives: (i) supporting economic growth and (ii) combating environmental degradation simultaneously. These objectively depend on the fast urbanization taking place in these countries. While increased energy consumption from urbanization supports economic growth, urbanization is a key driver of environmental degradation. This paper examines a potential link between urbanization and renewable energy consumption, primarily ignored in current literature, particularly in the ASEAN-5 countries. Findings from this paper indicate that, despite the adverse effect of urbanization on renewable energy consumption in the short run, a positive effect is found in the long run for these emerging ASEAN markets, except Malaysia. The Philippines appears to balance well between urbanization and renewable energy consumption in the short and long run. Policy implications have emerged based on the findings of this paper.

On an Aggregated Estimate for Human Mobility Regularities through Movement Trends and Population Density

This article introduces an analytical framework that interprets individual measures of entropy-based mobility derived from mobile phone data. We explore and analyze two widely recognized entropy metrics: random entropy and uncorrelated Shannon entropy. These metrics are estimated through collective variables of human mobility, including movement trends and population density. By employing a collisional model, we establish statistical relationships between entropy measures and mobility variables. Furthermore, our research addresses three primary objectives: firstly, validating the model; secondly, exploring correlations between aggregated mobility and entropy measures in comparison to five economic indicators; and finally, demonstrating the utility of entropy measures. Specifically, we provide an effective population density estimate that offers a more realistic understanding of social interactions. This estimation takes into account both movement regularities and intensity, utilizing real-time data analysis conducted during the peak period of the COVID-19 pandemic.

Ternary logic in the optical controlled-SWAP gate based on Laguerre-Gaussian modes of light

The need set by a computational industry to increase processing power, while simultaneously reducing the energy consumption of data centers, became a challenge for modern computational systems. In this work, we propose an optical communication solution, that could serve as a building block for future computing systems, due to its versatility. The solution arises from Landauer's principle and utilizes reversible logic, manifested as an optical logical gate with structured light, here represented as Laguerre-Gaussian modes. We introduced a phase-shift-based encoding technique and incorporated multi-valued logic in the form of a ternary numeral system to determine the similarity between two images through the free space communication protocol.

Energy saving effects of digital technologies from a life-cycle-analytical perspective: evidence from China

Digital technology has become a key driver of industrial transformation and resource utilization. However, no consensus has been reached on the exact relationship between digital technology and energy utilization. This study adopted a comprehensive index system to investigate the impact of digital technologies on energy utilization across 30 provinces in China. The results reveal a non-linear relationship between digital technologies and energy efficiency in China (represented by an N-curve), which is validated by robustness tests. This indicates digital technology exerts a fast-slow-rapid impact on improving energy efficiency throughout its initial-rapid-stable developmental stages. Geographically, this effect is more pronounced in eastern and central China, as well as in areas with lower energy efficiency. Furthermore, the impact of digital technology on total energy consumption can be characterized by an inverted N-shaped curve. As regional energy efficiency improves, the energy consumption associated with the development of digital technologies gradually decreases. These findings can contribute valuable insights for enhancing energy efficiency and provide practical guidance for the formulation of energy and digital technology policies.

Gel Biopolymer Electrolytes Based on Saline Water and Seaweed to Support the Large-Scale Production of Sustainable Supercapacitors

Climate change and the demand for clean energy have challenged scientists worldwide to produce/store more energy to reduce carbon emissions. This work proposes a conductive gel biopolymer electrolyte to support the sustainable development of high-power aqueous supercapacitors. The gel uses saline water and seaweed as sustainable resources. Herein, a biopolymer agar-agar, extracted from red algae, is modified to increase gel viscosity up to 17-fold. This occurs due to alkaline treatment and an increase in the concentration of the agar-agar biopolymer, resulting in a strengthened gel with cohesive superfibres. The thermal degradation and agar modification mechanisms are explored. The electrolyte is applied to manufacture sustainable and flexible supercapacitors with satisfactory energy density (0.764 Wh kg-1 ) and power density (230 W kg-1 ). As an electrolyte, the aqueous gel promotes a long device cycle life (3500 cycles) for 1 A g-1 , showing good transport properties and low cost of acquisition and enabling the supercapacitor to be manufactured outside a glove box. These features decrease the cost of production and favor scale-up. To this end, this work provides eco-friendly electrolytes for the next generation of flexible energy storage devices.

A review on nickel-rich nickel-cobalt-manganese ternary cathode materials LiNi0.6Co0.2Mn0.2O2 for lithium-ion batteries: performance enhancement by modification

The new energy era has put forward higher requirements for lithium-ion batteries, and the cathode material plays a major role in the determination of electrochemical performance. Due to the advantages of low cost, environmental friendliness, and reversible capacity, high-nickel ternary materials are considered to be one of ideal candidates for power batteries now and in the future. At present, the main design idea of ternary materials is to fully consider the structural stability and safety performance of batteries while maintaining high energy density. Ternary materials currently face problems such as low lithium-ion diffusion rate and irreversible collapse of the structure, although the battery performance can be improved utilizing coating, ion doping, etc., the actual demand requires a more effective modification method based on the intrinsic properties of the material. Based on the summary of the current research status of the ternary material LiNi0.6Co0.2Mn0.2O2 (NCM622), a comparative study of the modification paths of the material was conducted from the level of molecular action mechanism. Finally, the major problems of ternary cathode materials and the future development direction are pointed out to stimulate more innovative insights and facilitate their practical applications.

Investigation of industry 4.0 technologies mediating effect on the supply chain performance and supply chain management practices

The aim of the present article purposefully explores how industry 4.0 may alter conventional methods of administration by performance of supply chain. Nowadays, the business activities/processes have been raised and all are directly associated with industrial revolution. Industry 4.0 acts as a go-between for improved supply chain efficiency and more traditional forms of logistics management. Discovering the transformative effects of industry 4.0 on supply chain management by reading on, however, SCM practices, this study considers the questioner-based data from September 2021 to March 2022 for China economy. Interestingly, the findings of structural equation model (SEM) describe the supportive response of revolution (the fourth industrial revolution) to supply chain management in the previously described field. The consequences of this research argue that the supportive role of technological progress in industrial revolution brings efficient supply chain management. Moreover, the performance indicators under the supply chain work well due to significant progress in industry 4.0. In concluding remarks, such types of advanced technologies serve as an intermediate between the management and practices of supply chain. However, the results provide light on the basic principles behind the success. In addition, these technologies make it possible to significantly improve the performance by allowing process unification, mechanization, and automation and introducing innovative analytic capabilities and supply chain operations including procurement, production, and inventory management, and marketing may work together more efficiently. Some of these processes include marketing, inventory management, and procurement. These improvements are attainable through the implementation of innovative scientific capabilities.

Does energy-consuming right trading have double dividend effect on firm's economic performance and carbon emission?

Whether the market-based environmental regulation policy can achieve a win-win situation of economic growth and carbon emission reduction has always been an academic controversial topic. Taking the pilot policy of energy-consuming right trading (ECRT) of China in 2016 as a quasi-natural experiment, this paper uses the difference-in-differences (DID) method to investigate the policy impact of ECRT on the economic performance and carbon emissions of firms. An economy-environment composite index has been conducted for testing double dividend effect of ECRT. The empirical results show that ECRT can improve the economic performance and reduce carbon emissions of firms significantly. The double dividend effect is more significant in high-carbon emission firms, non-state-owned firms and prior to COVID-19 pandemic. ECRT policy has Porter innovation mechanism, in which innovation input is the main contribution of economic dividend effect and green technology innovation is the main contribution of environmental dividend effect. The conclusions of this paper provide empirical evidence and policy implications for realizing the common development of economy and environment, accelerating the process of emission reduction and building a national energy trading market.

Digital technology and its application in supply chain management: new evidence from China's economy

The purpose of this article is to investigate the influence that practices using information technology (IT) have on the development of a competitive advantage across the supply chain. An organization has a competitive advantage when it has qualities that give the required foundations for it to separate itself from other organizations that are also in its industry. Pressure is applied to the corporate environment as a result of competition and ongoing changes, such as the introduction of new products and technical advancements, the decline of product lifestyles, and the proliferation of products. In order to maintain a competitive edge and achieve financial success in business, organizations are necessary for responding to changes in the market. Through the use of supply chain markets, companies are able to react quickly to unforeseen shifts in the market, and these shifts may be turned into lucrative business possibilities. One of the most significant things that firms can do to assist themselves is make use of information technology to improve their supply chain management agility. From March 2021 through January 2022, the area of China will have a total sample size of 247 persons fill out a questionnaire as part of the data collection process. In each and every questionnaire, the measurements were taken using a Likert scale with five points. The partial least square-structural equation modeling (PLS-SEM) approach is used to the causal model in order to assess the model's reliability and validity. This technique is used to evaluate the causal model. The findings indicate that information technology has a favorable impact on the adaptability of supply chain management systems. In addition, the findings that were collected have shown that there are four factors that influence the SCM systems. These factors are the IT skills and knowledge, the integration of IT-based systems, the IT infrastructure, and the design of global position system and geographic information systems. In addition, this research offers practitioners recommendations for implementing digital technology for supply chain management and building suitable business strategies at various stages of digitalization.

Economic development, social media awareness, and technological innovation in biogas sector under climate change in the post-COVID-19 pandemic conditions

After COVID-19, financing for emerging nation reserves in renewable energy bases was deemed a crucial aspect of sustainable development. Investing in biogas energy plants can be highly beneficial for lowering the use of fossil fuels. Using a survey of shareholders, investors, biogas energy professionals, and active social media participants in Pakistan, this study evaluates the intentions of individual investors to invest in biogas energy plants. The primary purpose of this study is to increase investment intent for biogas energy projects following COVID-19. This study focuses on financing biogas energy plants in the post-COVID-19 era and evaluates the research's assumptions using partial least squares structural equation modeling (PLS-SEM). The study employed the technique of purposive sampling to acquire data for this investigation. The results indicate that attitudes, perceived biogas energy benefits, perceived investment attitudes, and supervisory structure evaluations inspire one's propensity to finance biogas vitality plant efforts. The study found a link between eco-friendly responsiveness, monetary benefits, and investors' actions. The aspiration of investors to mark such reserves was set up to be unpretentious by their risk aversion. Conferring to the facts, evaluating the monitoring structure is the critical factor. The previous studies on investment behavior and other forms of pro-environmental intent and action yielded contradictory results. In addition, the regulatory environment was evaluated to see how the theory of planned behavior (TPB) affects financiers' objectives to participate in biogas power plants. The consequences of the study indicate that feelings of pride and discernment of energy expansively affect people's desire to invest in biogas plants. Biogas energy efficacy has little effect on investors' decisions to invest in biogas energy plants. This study offers policymakers practical ideas on enhancing investments in biogas energy plants.

The concern about main crises such as the Covid-19 pandemic, the war in Ukraine, and climate change's impact on energy-saving behavior

The number of crises experienced around the world forces people to reconsider and reassess various aspects of their lives. The energy crisis caused by the war in Ukraine and uncontrolled climate change revealed the importance of energy-saving behavior. Thus, the aim of this paper is to analyze the concerns about current crises such as the Covid-19 pandemic, the war in Ukraine, and climate change's impact on energy-saving behavior and changes in environmental concern. Referring to the survey conducted in Lithuania in 2022, where 1000 respondents participated, the results revealed that the war in Ukraine was the most concerning problem. The level of climate change concern was slightly lower. Meanwhile, the Covid-19 pandemic was the least important problem in Lithuania in 2022. Furthermore, respondents stated that the Covid-19 pandemic contributed to the changes in environmental concern and energy-saving actions more than the war in Ukraine did. Meanwhile, the Generalized Linear Model results revealed that only the war in Ukraine positively and significantly influenced energy-saving behavior. The Covid-19 pandemic concern negatively affected energy-saving behavior, while the climate change concern factor affected it indirectly, as the interaction of attitudes toward energy consumption. Thus, this study revealed the main aspect of and how to encourage energy-saving behavior in the context of the main current crises.

Do banking sector development, economic growth, and clean energy consumption scale up green finance investment for a sustainable environment in South Asia: evidence for newly developed RALS co-integration

Concern about climate change is spreading around the globe. The urge to comprehend the environmental effects and take action is sharply rising. Regarding this, the banking industry has a great chance to offer a solution in terms of green financial solutions and can meet the needs of carbon-conscious organizations to combat and defend our planet. Therefore, in light of this, according to the greatest understanding of the authors, this is the first study to investigate the role of banking sector development, economic growth, and clean energy consumption in scaling up green finance investment in South Asian nations, taking carbon emissions, foreign direct investment, remittances, inflation, and trade openness as control variables. This study uses a novel residual augmented least squares-Engle and Granger (RALS-EG) co-integration to test the long-term link and the quantile autoregressive distributed lag (QARDL) econometric approach to extract the association across the quantiles (q0.05-q0.95) for the period 2000-2020. The outcomes of QARDL show that banking sector development, economic growth, clean energy, carbon emissions, foreign direct investment, remittances, and trade openness play a positive role in attracting green finance in the long term. However, only inflation has a negative influence on scaling up finance in South Asian nations. Therefore, the concerned authorities (government, central banks, environmentalists, and policymakers) are urged to implement green finance policies and strategies as suggested and recommended by the results of this study.

Assessing the impact of COVID-19 on economic recovery: role of potential regulatory responses and corporate liquidity

We use a variety of organization-level datasets to examine the effectiveness and efficiency of the nations for the coronavirus epidemic. COVID-19 subsidies appear to have saved a significant number of jobs and maintained economic activity during the first wave of the epidemic, according to conclusions drawn from the experiences of EU member countries. General allocation rules may yield near-optimal outcomes in favor of allocation, as firms with high ecological footprints or zombie firms have lower access to government financing than more favorable, commercially owned, and export-inclination firms. Our assumptions show that the pandemic has a considerable negative impact on firm earnings and the percentage of illiquid and non-profitable businesses. Although they are statistically significant, government wage subsidies have a modest impact on corporate losses compared to the magnitude of the economic shock. Larger enterprises, which receive a lesser proportion of the aid, have more room to increase their trade liabilities or liabilities to linked entities. In contrast, according to our estimations, SMEs stand a greater danger of insolvency.

Sectoral analysis of electricity consumption during the COVID-19 pandemic: Evidence for unregulated and regulated markets in Colombia

We conduct a sectoral analysis of electricity consumption during the Coronavirus disease 2019 (COVID-19) pandemic for the primary sectors that make up Colombia's unregulated and regulated markets. Applying a model of seemingly unrelated regression equations to examine data between February 2015 and May 2021, we evidence the recomposition of electricity consumption related to mandatory preventive isolation during the pandemic. Average consumption in the residential sector increased by 16.9% as working from home became prevalent. In contrast, unregulated market sectors subjected to quarantines presented a significant decrease in consumption, up to 32% in the financial sector. While industries that were not subjected to mandatory confinement, such as health, food (agriculture), and water supply, had no significant effect. Our results are relevant for informing demand forecasts and planning network expansions to guarantee the reliability of the supply as pandemic practices such as working from home become permanent.

Connectedness of COVID vaccination with economic policy uncertainty, oil, bonds, and sectoral equity markets: evidence from the US

We examine the connectedness of the COVID vaccination with the economic policy uncertainty, oil, bonds, and sectoral equity markets in the US within time and frequency domain. The wavelet-based findings show the positive impact of COVID vaccination on the oil and sector indices over various frequency scales and periods. The vaccination is evidenced to lead the oil and sectoral equity markets. More specifically, we document strong connectedness of vaccinations with communication services, financials, health care, industrials, information technology (IT) and real estate equity sectors. However, weak interactions exist within the vaccination-IT-services and vaccination-utilities pairs. Moreover, the effect of vaccination on the Treasury bond index is negative, whereas the economic policy uncertainty shows an interchanging lead and lag relation with vaccination. It is further observed that the interrelation between vaccination and the corporate bond index is insignificant. Overall, the impact of vaccination on the sectoral equity markets and economic policy uncertainty is higher than on oil and corporate bond prices. The study offers several important implications for investors, government regulators, and policymakers.

Assessing eco-label knowledge and sustainable consumption behavior in energy sector of Pakistan: an environmental sustainability paradigm

The energy needs of Pakistan have increased many folds in recent years due to improved lifestyle, ever-increasing population, and economic development. Though the government and private sectors are considering efficient energy resources to overcome energy scarcity in the country, studies focusing on assessing consumers' sustainable consumption behavior in the form of energy-saving home appliances are limited in the country. This study aims to address this research gap and also contribute by augmenting the theoretical mechanism of the theory of planned behavior by including three unique dimensions (eco-label knowledge, attitude toward environment, and customer green trust) to comprehensively analyze sustainable consumption behavior in the Pakistani context. An analysis is performed on survey data of 631 consumers in the four largest cities of Pakistan: Karachi, Lahore, Faisalabad, and Islamabad. For the purpose of evaluating formulated hypotheses, the structural equation modeling approach is employed. Empirical findings suggest that eco-label knowledge positively and significantly influences attitude toward environment and consumer green trust. Similarly, attitude toward environment and consumer green trust has a positive and significant influence on purchase intention. Moreover, a significant positive relationship exists between consumer green trust and purchase intention. The research outcomes further disclose that purchase intention positively and significantly influence paying attention to environmental labels. These findings contribute to the literature on sustainable consumption behavior and provide academics and practitioners with future directions to transform social norms, raise consumers' awareness, and redesign policy frameworks through integrative and consistent efforts.

Research on the impact of COVID-19 on the spatiotemporal distribution of carbon dioxide emissions in China

Since the outbreak of COVID-19 at the end of 2019, the Chinese government has imposed strict control measures on affected cities, which may have impacted the spatial and temporal pattern of carbon dioxide emissions. This paper follows the quantitative analysis method, experimental method, mathematical method, etc., and quantitatively studies the impact of the epidemic on China's carbon emissions. The combination model of ARIMA and BP neural network is used to predict the actual impact of epidemic situation on China's carbon emissions in 2020, and the spatial autocorrelation analysis method is used to analyze the spatial characteristics of China's provincial carbon emissions, which indicate that China's carbon emissions have consistently maintained a growth trend, from 2.05 billion tons in 2005 to 3.89 billion tons in 2019. Furthermore, the growth rate of carbon emissions and the changing trend of the emission intensity are the same, dropping from 12% in 2005 to 3% in 2019. The emission intensity also dropped from 1.1 in 2005 to 0.6 in 2019, indicating that the trend of increasing carbon emissions in northern provinces and Xinjiang changed significantly from 2005 to 2019. The overall carbon emissions of the 30 provinces in 2020 are predicted to be 4.068 billion tons, while the actual energy carbon emissions will be 3.921 billion tons, suggesting that the pandemic significantly reduced carbon emissions. Among affected provinces, carbon emissions from Hubei, Jiangsu, Shandong, Shanghai, and other places changed significantly, from 0.99, 0.25, 0.43, and 76 million tons in 2019 to 0.88, 0.24, 0.42, and 72 million tons in 2020, respectively. The results show a positive spatial correlation between China's provincial carbon emissions; the high-high and bottom-high agglomeration are mainly among the provinces, mainly distributed in North China and East China. Although the pandemic seriously impacts China's carbon emissions, each province's spatial relationship has not changed significantly.

What are the pandemic's shocks on carbon emission trading? The different management applications

Maintaining the stability of the carbon market is of great significance for China to meet its goal of "Double Carbon," but at the beginning of 2020 the COVID-19 pandemic emerged and the economy was greatly affected. A natural question is whether it impacted domestic carbon markets. This paper thus presents the event research method on eight carbon emission trading markets in China, because it can timely exhibit the benefits investors gained during the COVID-19 pandemic and also can overcome the difficulty of separating those benefits from the overall performance of the carbon market via high-frequency data. The results herein confirm that China's carbon market has reacted negatively to the COVID-19 pandemic, which mainly relates to the mandatory blockade and isolation policy adopted by the central government. The production and operation activities of enterprises decreased along with the demand for carbon quotas. Because of the panic, investors also had a negative attitude towards the carbon market, influencing the supply and demand curve of carbon quotas and causing a decline in carbon prices. Under the effectiveness of government epidemic prevention and control policies, we further find that the negative impact was gradually eliminated. Overall, our findings offer some important information for the decision-making of governments, carbon market investors, and policymakers.

Dynamic interlinkages between the crude oil and gold and stock during Russia-Ukraine War: evidence from an extended TVP-VAR analysis

The Russia-Ukraine significantly influences the oil market. We employ a time-varying parameter vector autoregression (TVP-VAR) in combination with an extended joint connectedness approach to identify the sources of the oil market's volatility by studying interlinkages between the crude oil and gold and stock market by characterizing the connectedness of four markets starting from January 1, 2018 to April 8, 2022. Our attention is mostly paid to the period marked by the event that Russia invaded Ukraine on 24 February, 2022. Our results demonstrate that the war shocks appear to influence the system-wide dynamic connectedness, which signifies the interlinkages among the considered markets. Net total directional connectedness suggests that the oil and gold markets appear to be the net transmitter of spillover shocks in the system. However, there are shifts in the roles of these two markets during the time of the Russia-Ukraine war shock. Pairwise connectedness highlights the significance of the oil market in transmitting the adverse influences of shocks to other markets, especially during the Russia-Ukraine war.

Covid-19 and energy sector: Unique opportunity for switching to clean energy

The novel coronavirus (2019-nCoV) was extended to 213 countries globally by August 2021. The world has been threatened by rising infection rates and emerged as the catastrophic event in the field of health triggering the international emergency panic button. COVID-19's sudden arrival wreaked havoc on the world economic picture, particularly in the energy sector. A steep drop in oil prices, as well as an imbalance in energy, was the result of strict travel restrictions, fewer transportation options, and people's fears of a flu pandemic. However, confined mobility and a drop in energy demand coated the environment with a silver line and drowned the nation's economic opportunities. Industrial transport, and not to mention every conventional energy-related thing, is completely devastated, but renewables were immunized. Wind, solar, hydrothermal, hydrogen, biomass-based energy systems were on high gear yielding maximum results in counterbalancing the demand-supply chain. Moreover, the pandemic created an opportunity to showcase the importance of renewable energy and tackle the difficult emergency like now. In addition to this, the mindset of the investors was slowly fading away from conventional fuels and shifting towards renewable energy. However, it is too early to state the booming renewables at the moment, and no idea about its long-time survival. Thus, the present review gives a clear picture of the current status of fossils and renewables, the impact of a pandemic, energy investments, government policy standings, threats, and opportunities, and finally, the key takeaways avoiding energy scarcity in once a lifetime disaster situation.

World Energy Economics and Geopolitics amid COVID-19 and Post-COVID-19 Policy Direction

COVID-19 has placed a focus on the global energy industry. The global energy system in 2020 and beyond was covered in this article. The epidemic had immediate implications on energy demand, particularly for oil, and on energy bills. According to the IEA, understanding the development of the low-carbon energy system and the eventual demise of the current system based on fossil fuels is crucial for predicting the future of global energy geopolitics. Since renewables are the goal of post-COVID-19, geopolitical tensions between nations that produce fossil fuels have been brought to light. Three guidelines are suggested in this paper for the switch to renewable energy sources in order to slow global warming. First, place a focus on immediate policy changes that have a long-term impact on the energy transition. Utilize the upcoming midterm energy transition opportunities. Fresh, uncompromised policy frameworks should be developed. As the pandemic scenario is almost settled, additional research is needed to comprehend the widespread and catastrophic repercussions of post-COVID-19 on energy geopolitics, including variations in energy demand and price, wake of economic recovery, macroeconomic instability, Ukraine crisis and anticipating geopolitical consequences for renewables and fossil fuel economics. More national and regional focus is needed on long-term policy designs and justifications. The effectiveness of altering the sustainable development objectives related to energy or maintaining the current goals with the suggested policy design can also be examined in further research. Key challenges and recommendations are highlighted in order to ensure a successful long-term energy transition that can serve as a reference for energy policymakers in all countries.

Modeling, Energy Performance and Economic Analysis of Rooftop Solar Photovoltaic System for Net Energy Metering Scheme in Malaysia

Energy is one of the essential inputs for modernization and social development. Energy demand is increasing, and the primary energy source is fossil fuels, which negatively impact the environment. Energy saving and renewables are the potential solutions which could minimize environmental impact. This paper investigates the energy-saving and solar photovoltaic energy potential of an educational institution, Politeknik Sultan Azlan Shah (PSAS), Malaysia. The feasibility analysis was conducted by assuming that PSAS joined the Net Energy Metering (NEM 3.0) program, where PSAS, as a NEM consumer, has a tripartite supply agreement with renewable energy (SARE) with a distribution licensee known as Tenaga National Berhad (TNB). This paper focuses on zero capital expenditure (CAPEX) saving through a 20-year contract. This paper proposes a rooftop solar photovoltaic diagram using a NEM meter installed in the ring distribution system at PSAS. The estimated savings to be obtained by PSAS in the 20 years that the contract is in force are calculated based on the assumption that the installed solar system has a capacity of 688 kW. The maximum value of power generated by the system for a year is 990,720 kWh. The feasibility analysis found that the cumulative net savings estimate for PSAS based on the overall calculation for 21 years of solar use is RM 3,534,250. Meanwhile, the cumulative assessment of carbon emission reduction obtained in the same period is 14,559,760 kg CO2 or 14,559.76 tons of CO2, which would save 363,994 mature trees from being cut down.

An integrated analysis of COVID-19 impacts on energy and environment: Lessons learnt

Carbon neutrality, sustainable development and reducing our impact on the environment is the top priority in future measures. The COVID-19 pandemic brought challenges to every sector at a global scale but can provide valuable insight to reach these goals. The main objective of this work is to provide an integrated analysis of the impact of the COVID-19 pandemic, focused on energy and its related aspects, i.e., environment and costs. Mainland Portugal was used as a case study and two years were analysed, one pre pandemic (2019) and another post pandemic (2020). In 2020, the majority of sectors - Transport, Services, Industry and Agriculture & Fisheries - show a reduction of energy consumption, atmospheric emissions, carbon footprint and related monetary and social costs. In contrast, the Domestic sector presents an overall increase, with maximums of 25.4% in electricity consumption (during Spring), 0.72% in the PM10 (particulate matter) and NOx (nitrogen dioxides) emissions (in Summer), and 2.9% in carbon footprint (in Spring). The integrated analysis proposed in this work was crucial to identify the paths to a post pandemic world focused on the different aspects of sustainability - new concepts of mobility and workplace, as well as increased investment in energy performance and renewable energy sources. This study showed that changing our energy consumption patterns could significantly affect future greenhouse gas emissions, and contribute to the sustainable growth of the economy, while maintaining good progress towards climate-neutral goals.

Assessing the impact of R&D Investments, government subsidies on energy efficiency: empirical analysis from the Chinese listed firms

China's "Made in China (2025)" strategic plan aims to increase the industrial sector's ability to innovate independently. Cleaner production and green technology will also be used to build green industrial systems. To help achieve these goals, the Chinese government has implemented research and development (R&D) preferential policies. Over the years 2010-2020, this article examines how government subsidies and R&D spending will affect China's energy-intensive enterprises' energy efficiency using the CS-ARDL approach. It also evaluates the effectiveness of economic growth, urbanization, and financial resources on energy efficiency. The outcome reveals that R&D expenditures and economic growth contribute to energy efficiency. Likewise, the findings of urbanization, financial resources, and government subsidies are inversely associated with energy efficiency. Moreover, the panel causality test results show the bi-directional association between urbanization and energy efficiency, government subsidies and energy efficiency, and economic growth and energy efficiency. Likewise, the one-way causal association from R&D expenditures to energy efficiency and from financial resources to energy efficiency. The findings suggest the imperative policies to boost the level of energy efficiency.

Electrical conductivity and electrochemical studies of Cr-doped MoO3 nanoflakes for energy storage applications

The growing demand for electricity has increased the interest of the researchers towards exploration of energy storing devices (ESDs). With the motif for developing electrochemical energy storage devices, this research work is focussed on the study of MoO₃ nanoparticles and its doping with chromium as an efficient electrode material for energy storage applications. The nanoparticles were synthesized by hydrothermal method and were examined by powder X-ray diffraction, which determined the thermodynamically stable orthorhombic phase of MoO₃, and their morphologies were examined using scanning electron microscopy displaying flake-like structures. The typical vibrational bands of Mo-O were identified from Infra-red and Raman spectral analysis. The ultra violet diffuse reflectance spectra revealed the decrease in optical band gap after doping with chromium. The temperature dependent AC and DC conductivities were enhanced on doping. Electrochemical behaviour of the nanoparticles was probed by cyclic voltammetry (CV), electrochemical impedance spectroscopy (EIS) measurements and galvanostatic charge-discharge (GCD) analysis for which specific capacitance (C _sp) value of 334 Fg^-1 was achieved for Cr-doped MoO₃ nanoparticles. The electrochemical performance of the sample was found to be increased after doping with Cr.

The impact of COVID-19 on the US renewable and non-renewable energy consumption: a sectoral analysis based on quantile on quantile regression approach

The repercussions of the novel coronavirus (COVID-19) pandemic go well beyond health concerns, affecting virtually every aspect of our lives, including daily energy consumption. Therefore, this study explores the impact of COVID-19 on renewable and non-renewable energy consumption in the USA, which has been severely affected by the recent pandemic. We conducted a detailed analysis of the energy consumption demands of various sectors in response to the COVID-19 outbreak. Our in-depth analysis comprises two parts. Initially, we determine the monthly growth change by utilizing the month-on-month method. Subsequently, we used the quantile-on-quantile approach of Sim and Zhou (2015) on data spanning from December 2019 to August 2021 to explore the impact of COVID-19 on energy consumption across the whole distribution. The study's outcomes underscored that compared to renewable energy, non-renewable energy consumption was more affected by the COVID-19 lockdown, and the overall energy consumption (both renewable and non-renewable) remained low. These findings accentuate global strategic management tools to tackle COVID-19 cooperatively and restore the energy mix. Such measures are critical for energy access, security, and evenhandedness.

On the emergence of a health-pollutant-climate nexus in the wake of a global pandemic

COVID-19 has wreaked havoc throughout the planet within a short time frame, inducing substantial morbidity and mortality in the global population. The primary procedures commonly used to manage the pandemic can produce various environmental pollutants, primarily contaminants of emerging concern such as plastics, chemical disinfectants, and pharmaceutical waste. There is a huge influx of various environmental pollutants due to the pandemic effect. We, therefore, introduce the term "envirodemics" depicting the exacerbated surge in the amount of pandemic-induced pollutants. The general toxicity pattern of common chemical ingredients in widely used disinfectants shows negative impacts on the environment. We have identified some of the significant imprints of the pandemic on localizing the Sustainable Development Goals-environment interaction and their implications on achieving the goals in terms of environmental benefits. Climate change impacts are now widespread and have a profound effect on pollutant fluxes and distribution. The climate change signatures will impact the pandemic-induced enhanced fluxes of pollutants in the global waters, such as their transport and transformation. In this study, possible interactions and emerging pathways involving an emerging climate-health-pollutant nexus are discussed. The nexus is further elaborated by considering plastic as an example of an emerging pollutant that is produced in huge quantities as a by-product of COVID management and disaster risk reduction. Additionally, regulatory implications and future perspectives concerning the unleashed nexus are also discussed. We hope that this communication shall call for incisive investigations in the less explored realm concerning the health-pollutant-climate nexus.

Investigating the impacts of COVID-19 lockdown on air quality, surface Urban Heat Island, air temperature and lighting energy consumption in City of Melbourne

The COVID-19 pandemic has threatened city economies and residents' public health and quality of life. Similar to most cities, Melbourne imposed extreme preventive lockdown measures to address this situation. It would be reasonable to assume that during the two phases of lockdowns, in autumn (March) and winter (June to August) 2020, air quality parameters, air temperature, ^{Surface Urban Heat Island} (SUHI), and lighting energy consumption most likely increased. As such, to test this assumption, Sentinel 5, ERA-5 LAND, Sentinel 1 and 2, NASA SRTM, MODIS Aqua and Terra, and VIIRS satellite imageries are utilized to investigate the alterations of NO₂, SO₂, CO, ^{UV Aerosol Index} (UAI), air temperature, SUHI, and lighting energy consumption factors in the City of Melbourne. Furthermore, satellite imageries of SentiThe results indicate that the change rates of NO₂ (1.17 mol/m²) and CO (1.64 mol/m²) factors were positive. Further, the nighttime SUHI values increased by approximately 0.417 °C during the winter phase of the lockdown, while during the summer phase of the lockdown, the largest negative change rate was in NO₂ (−100.40 mol/m²). By contrast, the largest positive change rate was in SO₂ and SUHI at night. The SO₂ values increased from very low to 330 μm mol/m^2, and the SUHI nighttime values increased by approximately 4.8 °C. From the spatial point of view, this study also shows how the effects on such parameters shifted based on the urban form and land types across the City of Melbourne by using satellite data as a significant resource to analyze the spatial coverage of these factors. The findings of this study demonstrate how air quality factors, SUHI, air temperature, and lighting energy consumption changed from pre-lockdown (2019) to lockdown (2020), offering valuable insights regarding practices for managing SUHI, lighting energy consumption, and air pollution.

The negative impact of the COVID-19 on renewable energy growth in developing countries: Underestimated

According to the United Nations Environment Programme, the COVID-19 pandemic has created challenges for the economy and the energy sector, as well as uncertainty for the renewable energy industry. However, the impact on renewable energy during the pandemic has not been consistently determined. Instead of relying on data from year-to-year comparisons, this study redesigned the analytical framework for assessing the impact of a pandemic on renewable energy. First, this research designed an "initial prediction-parameter training-error correction-assignment combination" forecasting approach to simulate renewable energy consumption in a "no pandemic" scenario. Second, this study calculates the difference between the "pandemic" and "no pandemic" scenarios for renewable energy consumption. This difference represents the change in renewable energy due to the COVID-19 pandemic. Various techniques such as nonlinear grey, artificial neural network and IOWGA operator were incorporated. The MAPEs were controlled to within 5% in 80% of the country samples. The conclusions indicated that renewable energy in China and India declined by 8.57 mtoe and 3.19 mtoe during COVID-19 period. In contrast, the rise in renewable energy in the US is overestimated by 8.01 mtoe. Overall, previous statistics based on year-to-year comparisons have led to optimistic estimates of renewable energy development during the pandemic. This study sheds light on the need for proactive policy measures in the future to counter the global low tide of renewable energy amid COVID-19.

The applications of MCDM methods in COVID-19 pandemic: A state of the art review

Likened to the economic calamity of World War Two, the COVID-19 pandemic has sparked fears of a deep economic crisis, killed more than six million people worldwide and had a ripple effect on all aspects of life. MCDM (multi-criteria decision making) methods have become increasingly popular in modeling COVID-19 problems owing to the multi-dimensionality of this crisis and the complexity of health and socio-economic systems. This paper is aimed to review 72 papers published in 37 leading peer-reviewed journals indexed in Web of Science that used MCDM methods in different areas of COVID-19 pandemic. In this paper, data retrieval follows the PRISMA protocol for systematic literature reviews. 35 countries have contributed to this multidisciplinary research and India is identified as the leading country in this field followed by Turkey and China. Also 36 articles, namely 50% of papers are presented in the form of international cooperation. "Applied Soft Computing" is the journal with the highest number of articles whereas "Journal of infection and public health" and "Operations Management Research" are ranked in the second place. The results indicate that AHP (including fuzzy AHP) is the most popular MCDM method applied in 37.5% of papers followed by TOPSIS and VIKOR. This review reveals that the use of MCDM methods is one of the most attractive research areas in the field of COVID-19. As a result, one of the main purposes of this work is to identify diverse applications of MCDM methods in the COVID-19 pandemic. Most studies i.e. 69% (49 papers) of the papers combined various fuzzy sets with MCDM methods to overcome the problem of uncertainty and ambiguity while analyzing information. Nevertheless, the main drawback of those papers has been the lack of theoretical justifications. In fact, fuzzy MCDM methods impose heavy computational load and there is no general consensus on the clear advantage of fuzzy methods over crisp methods in terms of the solution quality. We hope the researchers who applied fuzzy MCDM methods to COVID-19-related research understand the theoretical basis of MCDM methods and the serious challenges associated with basic operations of fuzzy numbers to avoid potential disadvantages. This paper contributes to the body of knowledge via suggesting a deep vision to critique the fuzzy MCDM methods from mathematical perspective.

A multiscale integrated analysis of the COVID-19 restrictions: The energy metabolism of UK and the related socio-economic changes

The COVID-19 pandemic and the related lockdown restrictions have imposed a wide range of impacts that need to be analysed based on the specific characteristics of countries. By comparing socio-economic and energy data for the four quarters of 2020 to the same period of 2019, the MuSIASEM approach is used, for the first time, to investigate the energy metabolism of UK during a period of economic downturn. Results show that the commercial and the public administration activities have been able to achieve energy efficiency increases, and the residential sector has accounted for energy-related economies of scale. The industrial and the other activity sectors, on the contrary, have raised the energy intensity of production. Comparted to time series data, scenarios, and modelling exercises, the MuSIASEM approach integrates a wide range of intensive and extensive variables across different scales of analysis and investigate how specific socio-economic and energy structures have reacted to the COVID-19 crisis. The methodology can be easily replicated for other case studies and results can support the design of recovery and sustainable transition strategies.

Assessing the management student's entrepreneurial intentions: Role of entrepreneurship education and technology transfer

Entrepreneurship education is considered as an important way to influence the competitiveness of any country or industry. Therefore, entrepreneurship education provides opportunities to progress to a more competitive educational environment. This paper examines the impact of students' entrepreneurship education in China on their entrepreneurial intentions. Perceived entrepreneurial capacity, education in entrepreneurship, and attitudes toward entrepreneurship are all factors in the model developed to predict entrepreneurial intention. Structured equation modeling (SEM) is being used to test 98 management students from various universities in China. The findings show that there is statistically significant and positive relationship among entrepreneurship learning, entrepreneurial attitude, entrepreneurship education, and management students' entrepreneurial intention. Perceived behavioral control and perceive social rule significantly improve management students' entrepreneurial intention. Moreover, technology transfer correlates statistically with students' entrepreneurial intentions. Thus, universities are being encouraged to offer entrepreneurial training modules to increase their students' entrepreneurial intent.

Analysis of energy management schemes for renewable-energy-based smart homes against the backdrop of COVID-19

This article reviews energy management schemes for smart homes integrated with renewable energy resources in the context of the COVID-19 pandemic. The incorporation of distributed renewable energy system has initiated an acute transition from the traditional centralized energy management system to independent demand responsive energy systems. Renewable energy-based Smart Home Energy Management Systems (SHEMSs) play a vital role in the residential sector with the increased and dynamic electricity demand during the COVID-19 pandemic to enhance the efficacy, sustainability, economical benefits, and energy conservation for a distribution system. In this regard, the reviews of various energy management schemes for smart homes appliances and associated challenges has been presented. Different energy scheduling controller techniques have also been analyzed and compared in the COVID-19 framework by reviewing several cases from the literature. The utilization and benefits of renewable-based SHEMS have also been discussed. In addition, both micro and macro-level socio-economic implications of COVID-19 on SHEMSs are discussed. A conclusion has been drawn given the strengths and limitations of different energy scheduling controllers and optimization techniques in the context of the COVID-19 pandemic. It is observed that renewable-energy-based SHEMS with improved multi-objective meta-heuristic optimization algorithms employing artificial intelligence are better suited to deal with the dynamic residential energy demand in the pandemic. It is hoped that this review, as a fundamental platform, will facilitate the researchers aiming to investigate the performance of energy management and demand response schemes for further improvement, especially during the pandemic.

Estimation of Energy Profile and Possible Energy Savings of Unclassified Buildings

In the European Union, only 1% of the building stock is renovated every year. According to the EU strategy, around 75% of the existing building stock needs to be renovated by 2050. Energy efficiency programs mainly support residential and public building stocks; this article considers military dormitories as a type of unclassified building. It is very important to improve energy efficiency to reduce energy consumption and improve the microclimate in these buildings, since the staff is there 24/7. This paper analyzes the energy consumption and measures the indoor air quality in 13 nonrenovated military dormitories. The personnel in unclassified buildings have limited options for remote work in the case of COVID-19 outbreak. Thus, the retrofitting and maintenance of such buildings must be planned carefully. There is a significant lack of IAQ measurements in unclassified buildings. This study presents a wide analysis of energy consumption, indoor air parameters, and occupant satisfaction. On the basis of real data, four retrofitting scenarios were evaluated in IDA ICE dynamic simulation software. The simulation results showed that, in the case of a deep renovation scenario, the theoretical energy savings could be 77.6–79.3% of the used energy. This paper discusses the solar energy potential of onsite energy production for increasing the efficiency and energy supply resilience of unclassified buildings. The results of this study can be applied to other countries with climate conditions similar to Latvia.

Relationships between urban form and air quality: A reconsideration based on evidence from China's five urban agglomerations during the COVID-19 pandemic

The outbreak of Coronavirus disease 2019 (COVID-19) led to the widespread stagnation of urban activities, resulting in a significant reduction in industrial pollution and traffic pollution. This affected how urban form influences air quality. This study reconsiders the influence of urban form on air quality in five urban agglomerations in China during the pandemic period. The random forest algorithm was used to quantitate the urban form-air quality relationship. The urban form was described by urban size, shape, fragmentation, compactness, and sprawl. Air quality was evaluated by the Air Quality Index (AQI) and the concentration of six pollutants (CO, O3, NO2, PM2.5, PM10, SO2). The results showed that urban fragmentation is the most important factor affecting air quality and the concentration of the six pollutants. Additionally, the relationship between urban form and air quality varies in different urban agglomerations. By analyzing the extremely important indicators affecting air pollution, the urban form-air quality relationship in Beijing-Tianjin-Hebei is rather complex. In the Chengdu-Chongqing and the Pearl River Delta, urban sprawl and urban compactness are extremely important indicators for some air pollutants, respectively. Furthermore, urban shape ranks first for some air pollutants both in the Triangle of Central China and the Yangtze River Delta. Based on the robustness test, the performance of the random forest model is better than that of the multiple linear regression (MLR) model and the extreme gradient boosting (XGBoost) model.

Influence of Growing Miscanthus x giganteus on Ecosystem Services of Chernozem

The paper investigates the optimization of ecosystem services of podzolized heavy loamy chernozem (black soil) as a result of the cultivation of the perennial energy culture of Miscanthus x giganteus. The research was conducted on an experimental land plot during 2016–2021. No fertilization was applied to the soil during the experiments, and over the years of research, the growing seasons were accompanied by abnormal droughts, but even under such conditions, the plants of Miscanthus x giganteus gradually increased their yield. At the initial stage of research, in the third year of cultivation, dry biomass of Miscanthus x giganteus was obtained at 14.3 t/ha, in the fourth year–18.6 t/ha, and already in the fifth and sixth years, 21.7 and 24.5 t/ha, respectively. That is, energy-wise, the harvest for the last year was equivalent to 15.9 tons of coal or 12,618 m3 of natural gas. Cultivation of Miscanthus x giganteus on black soil for six years has improved the provision of its ecosystem services, regulation, and ecosystem maintenance services. The possibility of growing perennial energy crops on agricultural soils has been proven by obtaining a significant amount of biomass and a positive phytoremediation effect on the soil by reducing erosion, preserving biodiversity, sequestering carbon, and sustainably improving the ecological situation.

Nexus of COVID-19 and carbon prices in the EU emission trading system: evidence from multifractal and the wavelet coherence approaches

In this paper, we analyzed the role of carbon pricing as a vital tool for achieving the sustainable energy transition and discussed policy implications for reaching this goal in the era of the COVID-19 pandemic. To investigate the connection and cross-correlation between COVID-19 cases and carbon price returns in EU ETS, we applied two novel approaches: the multifractal detrending moving average cross-correlation (MF-X-DMA) and the wavelet coherence techniques. The coverage of data is from 2 March 2020 to 19 March 2021. The results of the MF-X-DMA method show that the cross-correlation is substantial and negatively correlated. Moreover, the results imply the presence of multifractal cross-correlations and that a significant change in the number of COVID-19 cases further impacts carbon price fluctuations. Concerning the wavelet coherence method results, we can also find a strong (negative) relationship between selected variables, and this strong correlation is observed throughout the whole study period. In addition, we observe that in the first wave of the COVID-19 outbreak, the changes in the COVID-19 cases are leading the CO2 price returns (particularly in the 16-32 time scale). The results of this study can have significant implications for policymakers and contributions for environmental experts and investors.

Resilience and complexity measurement for energy efficient global supply chains in disruptive events

The whole world is faced with the COVID-19 epidemic that causes major disruptions in global supply chains. The aim of study is to evaluate the effects of COVID-19 on energy efficient global supply chains (SCs) and to model the global supply chain resilience and energy management affected during the COVID-19 considering trade between Turkey and China, and Turkey and the EU. In this study, firstly using System Dynamics (SD) model, the behavior of countries against COVID-19 for a certain period of time is observed, subsequently the increase in complexity is analyzed with entropy measurement to determine whether the systems are resilient or not and to mark the differences arising from reporting in the first and second wave of the pandemic in the developed model. It is determined that the second wave reporting differences is less than first wave reporting differences except Turkey. From the learning effect perspective, it has been seen that the effect on the economy and foreign trade are less than first wave of pandemic even though the number of patients originating in the second wave are higher. It means that countries responded to the second wave of COVID-19 in a more resilient way. It is found that as a major finding of this study, perceived complexity of the system decreases in the second wave because of the resilience of supply chain considering learning effect and centralized decision making ensure increasing resilience and resilience measure in global supply chains. The study is highly helpful for governments, decision makers and managers to understand and manage the impacts of COVID-19 on global supply chains being resilient and energy efficient.

Optimal waste management during the COVID-19 pandemic

There have been many problems generated by the COVID-19 pandemic. One of them is the worrying increase in the generation of medical waste due to the great risk they represent for health. Therefore, this work proposes a mathematical model for optimal solid waste management, proposing a circular value chain where all types of waste are treated in an intensified industrial park. The model selects the processing technologies and their production capacity. The problem was formulated as a mixed-integer linear programming problem to maximize profits and the waste processed, minimizing environmental impact. The proposed strategy is applied to the case study of the city of New York, where the increase in the generation of medical waste has been very significant. To promote recycling, different tax rates are proposed, depending on the amount of waste sent to the landfill. The results are presented on a Pareto curve showing the trade-off between profits and processed waste. We observed that the taxes promote recycling, even of those wastes that are not very convenient to recycle (from an economic point of view), favoring profits, reducing the environmental impact, and the risk to health inherent to the medical waste.

Photovoltaic rooftop's contribution to improve building-level energy resilience during COVID-19 work-from-home arrangement

The COVID-19 pandemic has introduced opportunities for more research in resilience as globally cities experienced lock-down, causing change to conventional energy consumption pattern especially in the residential sector. This study aims to quantify the increased energy demand during work-from-home arrangement, using high-rise public residential buildings in Hong Kong, where its government announced work-from-home arrangement four times in 2020. Building energy modellings were conducted to compare the total energy demand of residential units during normal and work-from-home arrangements, followed by validation against peer models and empirical data. A 9% residential energy demand increase was demonstrated, hence additional energy supply became desirable for the sake of resilience. This study assesses the possibility to leverage photovoltaic rooftop to supplement the increased energy demand. The photovoltaics' potential contribution was estimated by solar energy simulation and evaluated in terms of the capability to utilize its generation output to supplement the additional energy demand. During the four work-from-home periods, it was shown that a photovoltaic system could have supplemented 6.8% - 11% of the increased energy demand, mainly subject to the air-conditioning operation and solar generation. These findings are valuable to safeguard energy resilience in upcoming grid planning and operation.

Techno-economic evaluation of stand-alone energy supply to a health clinic considering pandemic diseases (COVID-19) challenge

The increase in the number of patients in health care centers boosts electricity consumption. Such a load jump also adversely affects the energy supply, in particular, in rural off-grid systems. To overcome the mentioned challenges, some innovative and practical approaches with available optimization tools should be employed. This study addresses the possibility of developing a challenge prediction-based method for optimizing a reliable and affordable hybrid renewable energy system (HRES) to aid with energy challenges associated with pandemic conditions. The results indicate that the PV/diesel/battery hybrid system with a maximum energy cost of $0.141/kWh and a renewable fraction of more than 50% can meet demand even during the most severe load jumps. Furthermore, the fuel constraints during pandemic years can increase the energy costs up to 2.5 times, and the required photovoltaic installation capacity by about four times. Due to the 20.1% PV output boost, Vertical-axis tracking systems are recommended in areas with limited PV installation space. It is concluded that, by considering the likely effects of pandemics, the supplied energy cost to the rural health clinic equipment and water treatment loads would be between $0.113–0.200/kWh.

Environmental Effects of the COVID-19 Pandemic: The Experience of Bogotá, 2020

During the novel coronavirus disease (COVID-19) pandemic, several environmental factors have influenced activities and protection policy measures in cities. This has had a major effect on climate change and global environmental catastrophe. In many countries, the strategy of closing various activities such as tourism and industrial production stopped normal life, transportation, etc. This closure has a positive impact on the environment. However, the massive use of masks and personal protection could significantly increase pollution worldwide. The impact on the environment needs to be calculated to have information for public health actions. In this study, we present a first overview of the potential impacts of COVID-19 on some environmental matrices in Bogotá, Colombia.

Impact of COVID-19 Response Measures on Electricity Sector in Jordan

With the wide spread of new variants of coronavirus that cause the infectious disease COVID-19, governments around the world typically respond by imposing restrictions on people’s activities that range from partial to full lockdowns. This has severe implications on all economic activities, which is manifested by the changes in energy demand. In this study, the impact of COVID-19 on the electricity sector in Jordan is analysed through quantifying the strictness of the government response measures to contain the spread of the pandemic, as calculated by the stringency index, with the electricity demand by the different sectors. Results showed that the minimum peak load in 2020 decreased by 13% as compared to that of 2019. The most affected sectors were the domestic sector, whose share in consumption increased by 8%, and the commercial and hotel sector, whose share decreased by 19%. The concept of an energy-weighted stringency index was introduced to account for the impact of government response measures on the different sectors. The analysis was applied for all Jordan as well as for the three electricity distribution regions. Results also showed that despite measures taken to contain spread of the pandemic, the share of electricity generation by renewables increased from 15% in 2019 to 24% in 2020.

Impact analysis of COVID-19 pandemic on the future green power sector: A case study in the Netherlands

The outbreak of the COVID-19 pandemic has brought significant changes to the power sector. This study proposes general and coherent methodological steps to explore the future impact of lockdown measures on the power sector. In a case study from the Netherlands, two lockdown levels were defined and simulated to identify the influence of the pandemic upon the sector. Moreover, four renewable scenarios were developed to represent the green transition of the Netherlands' power sector up to 2035. For this future power sector, the results show that the green transition can achieve a reduction of 65% in CO2 emissions and 20% in power sector cost. Under the implementation of a simulated lockdown level, electricity demand decreased by 6.3% under Level 1 and 11.9% under Level 2 in 2035. The influences of lockdowns on future power sectors differ with respect to scenario. In addition, Lockdown Level 1 leads to a reduction of 8-12% in emissions and a reduction of 6-8% in cost, and Lockdown Level 2 expands this reduction to 15-21% in emissions and 11-13% in cost. The findings of this exploratory study can elucidate what may happen in the future green power sector if such event arises.

Future assessment of the impact of the COVID-19 pandemic on the electricity market based on a stochastic socioeconomic model

This paper proposes a time-series stochastic socioeconomic model for analyzing the impact of the pandemic on the regulated distribution electricity market. The proposed methodology combines the optimized tariff model (socioeconomic market model) and the random walk concept (risk assessment technique) to ensure robustness/accuracy. The model enables both a past and future analysis of the impact of the pandemic, which is essential to prepare regulatory agencies beforehand and allow enough time for the development of efficient public policies. By applying it to six Brazilian concession areas, results demonstrate that consumers have been/will be heavily affected in general, mainly due to the high electricity tariffs that took place with the pandemic, overcoming the natural trend of the market. In contrast, the model demonstrates that the pandemic did not/will not significantly harm power distribution companies in general, mainly due to the loan granted by the regulator agency, named COVID-account. Socioeconomic welfare losses averaging 500 (MR$/month) are estimated for the equivalent concession area, i.e., the sum of the six analyzed concession areas. Furthermore, this paper proposes a stochastic optimization problem to mitigate the impact of the pandemic on the electricity market over time, considering the interests of consumers, power distribution companies, and the government. Results demonstrate that it is successful as the tariffs provided by the algorithm compensate for the reduction in demand while increasing the socioeconomic welfare of the market.

Optimization of energy efficiency and COVID-19 pandemic control in different indoor environments

The COVID-19 pandemic has led to considerable morbidity and mortality, and consumed enormous resources (e.g. energy) to control and prevent the disease. It is crucial to balance infection risk and energy consumption when reducing the spread of infection. In this study, a quantitative human, behavior-based, infection risk-energy consumption model for different indoor environments was developed. An optimal balance point for each indoor environment can be obtained using the anti-problem method. For this study we selected Wangjing Block, one of the most densely populated places in Beijing, as an example. Under the current ventilation standard (30 m3/h/person), prevention and control of the COVID-19 pandemic would be insufficient because the basic reproduction number (R0 ) for students, workers and elders are greater than 1. The optimal required fresh air ventilation rates in most indoor environments are near or below 60 m3/h/person, after considering the combined effects of multiple mitigation measures. In residences, sports buildings and restaurants, the demand for fresh air ventilation rate is relatively high. After our global optimization of infection risk control (R0  ≤ 1), energy consumption can be reduced by 13.7% and 45.1% on weekdays and weekends, respectively, in contrast to a strategy of strict control (R0  = 1 for each indoor environment).

A Critical Analysis of the Impact of Pandemic on China's Electricity Usage Patterns and the Global Development of Renewable Energy

The COVID-19 pandemic has impacted economic activity in numerous sectors due to multiple forms of disruption, including border closures, a stay-at-home policy, and social isolation; the electricity consumption trends in this region will undoubtedly improve. This article examines the impact of COVID-19 on electricity generation and consumption in China during the first two quarters (Q1-Q2) of 2020 and 2021. Furthermore, several governments' perspectives on COVID-19's implications for renewable energy development, notably offshore wind power and solar photovoltaics (PV), were examined. Results of this article show that COVID-19 impacts the power industry. According to the analysis, during the first two quarters of 2020, the amount of electricity generated and consumed by China decreased by 1.4 and 1.3 percent, respectively, the capacity of the power plants increased by 5.3 GW and coal consumption dropped by 3.6 g/kWh. Investments in the power generation sector increased by 51.5 billion yuan and investment in the power grid grew by 0.7 billion. Additionally, new generation capacity decreased by 378 GW during the first two quarters of 2020. During the first two quarters of 2021, electricity consumption and production grew by 13.7 and 16.2 percent, respectively. Power plants' capacity increased by 9.5 GW, while coal consumption for power supply fell by 0.8 g/kWh. The investment in power generation projects increased by 8.9 billion, while investment in power grid projects increased by 4.7 billion. Compared to last year's same period, 14.92 GW of new capacity was installed. Due to lockdown measures, such as studying at home or working at home, domestic power use in the first two quarters of 2020-2021 increased by 6.6 and 4.5 percent, respectively. To minimize COVID-19's impact on renewable energy development and assist in building offshore wind power plants, economic and financial measures have been put in place to reduce the epidemic's effect on solar PV systems.

Effects of Working from Home on Greenhouse Gas Emissions and the Associated Energy Costs in Six Australian Cities

Working from home (WFH) has been imposed due to the COVID-19 pandemic. The adoption of WFH impacts energy use in the residential, commercial, and transportation sectors. Consequently, this affects the greenhouse gas emission (GHGE) and the associated energy costs to workers and employers. This study estimates the effects of WFH on the GHGE and energy-related costs in the residential, commercial, and transportation sectors. A simple linear model was used to estimate the changes in the GHGEs and cost by a typical employee when WFH practice is adopted for 1.5 and 4 days per week. The adoption of WFH reduces the operational GHGE accounted for commercial buildings and transport. However, it increases the operational GHGE accounted for residential buildings, which is a maximum of about 6% and 12%, respectively, for WFH 1.5 and 4 days. The reduction of GHGE from transport is significantly higher than that of residential buildings. The GHGE reductions from the transport sector are about 30% and 80%, respectively, for WFH 1.5 days and 4 days per week. WFH for 1.5 and 4 days per week reduces the national annual GHGE by about 1.21 Mt CO2-e and 5.76 Mt CO2-e, respectively. Further, the annual transportation cost of an employee is reduced by 30% and 80% in each city when the employee WFH for 1.5 and 4 days per week. The outcomes of this study offer a direction to reduce energy consumption and related costs and potential future research avenues on this topic. Further, the findings also help policymakers develop a hybrid work model for the post-COVID-19 pandemic.