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Before the COVID-19 pandemic, ventilation in buildings was not always given its due importance. The World Health Organization has highlighted the important role of air exchange with the outdoors in improving the air quality in buildings; buildings should, therefore, be equipped with mechanical ventilation or adequate air conditioning systems. This paper aims to investigate different retrofit solutions for air conditioning, evaluating them in terms of energy consumption and cost and the impact of increased outdoor air exchange rates on countering the propagation of COVID-19; the latter is the main novelty of the paper. As a case study, we take an existing office building located in Central Italy that was previously not equipped with a mechanical ventilation system (a system with primary air was introduced during the study). The energy analysis was conducted using dynamic simulation software after validation through energy bills; energy and economic analyses were conducted considering different external-air exchange rates. An optimal number of outdoor air changes was found to mitigate the risk of COVID-19 infection, a finding in line with the international literature. The increase in air changes with outdoor air leads to a rise in energy consumption and costs. These values were evaluated for different air conditioning systems and operational schedules. These drawbacks can be made less significant by combining interventions in the system with energy-efficiency measures applied to the building envelope. [ABSTRACT FROM AUTHOR]

Air conditioning systems can play a positive or negative role in the spread of COVID-19 infection. The importance of sufficient outdoor air changes in buildings was highlighted by the World Health Organization, therefore these should be guaranteed by mechanical ventilation systems or adequate air conditioning systems. The proposed case study concerns the optimal number of outdoor air changes to limit COVID-19 contagion for a school building in Central Italy. The Wells–Riley model is used to assess the risk of airborne infection, while energy consumption is calculated by a dynamic energy simulation software. The scope of the paper offers an innovative method to define the optimal ventilation strategy for the building's HVAC system design to reduce the risk of infection with limited increases in energy consumption and greenhouse gas emissions. Results show that the desirable approach is the one in which the same low value of contagion risk is set in all rooms. This new approach results in significant energy savings, compared to the most common ones (setting the same high outdoor air rates for all rooms) to counteract the risk of infection. Finally, the zero-emission building target is verified by introducing a suitable photovoltaic system to offset pollutant emissions. [ABSTRACT FROM AUTHOR]

The smart city has been a growing utopia, a brilliant image of a city of the future, in the past twenty years. Since its birth, at the end of the previous century, several changes have been seen in urban areas, both aligned and detached from this concept. On the one side, digital implementation seems to be growing in all the major cities, especially in the service sector, which are experiencing a proliferation of new solutions, tools and modalities of interactions. On the other side, new concepts are rising such as the "digital twin", the "15-minute city", and the "metaverse city", evidencing both the necessity to continuously innovate and reach higher levels of digitalization but also the need to focus on people's life. This paper aims to provide a contribution to the understanding of the concept's evolution at the forefront of climate change with the aim to detect the elements of innovation, focusing on implementation roadmaps and trends but also searching for evolutions in research due to the COVID-19 pandemic. The hypothesis is that some changes of direction could have been triggered by the pandemic due to the urgency of finding concrete solutions. The conclusions will show that it is possible to detect some of them, especially in the technological domain. [ABSTRACT FROM AUTHOR]

In this paper, using data from Romania, we analysed the changes in electricity consumption generated during the COVID-19 crisis, and the measures taken against the spread of the coronavirus to limit the effects of the pandemic. Using a seasonal autoregressive econometric model, we found that, beyond seasonal (weekly, monthly, quarterly, yearly) effects, the average daily electricity real consumption in Romania, during the state of the emergency period (16 March 16 to 14 May 2020) decreased by −194.8 MW (about −2.9%), compared to the historical data (2006–March 2022), and this decrease is not due to the action of some random factors, and it is not a manifestation of domain-specific seasonality. The literature discusses the hypothesis that during the pandemic time, the profile of daily electricity consumption on weekdays was close to the typical Sunday profile. We tested a similar hypothesis for Romania. As a methodology, we tried to go beyond the simple interpretation of statistics and graphics (as found in most papers) and we calculated some measures of distances (the Mahalanobis distance, Manhattan distance) and similarity (coefficient of correlation, cosines coefficient) between the vectors of daily electricity real consumptions, by hourly intervals. As the time interval, we have analysed, for Romania, the electricity real consumption over the period January 2006–March 2022, by day of the week and within the day, by hourly intervals (5911 observations). We found (not very strong) evidence supporting a hypothesis that, in the pandemic crisis, the profile of electricity consumption approaches the weekend pattern only for the state of the emergency period, and we could not find the same evidence for the state of the alert period (June 2020–March 2022). The strongest closeness is to the hourly consumption pattern of Saturday. That is, for Romania, in terms of electricity consumption, "under lockdown, every day is a Sunday" (Staffell) it is rather "under lockdown, every day is (almost) a Saturday"! During the state of the alert period, consumption returned to the pre-crisis profile. Since certain behaviours generated by the pandemic have been maintained in the medium and long term (distance learning, working from home, online sales, etc.), such studies can have policy implications, especially for setting energy policy measures (e.g., in balancing load peaks). [ABSTRACT FROM AUTHOR]

This paper investigates the effects of coronavirus disease 2019 (COVID-19) on the performance of arbitrage trading in the energy market using daily data covering the period between 1 January 2015 and 5 December 2021. The investigation was achieved by utilizing a parametric pairs-trading model, where pairs of energy-related securities, including futures, stocks and ETFs traded in the United States, are formed. The empirical results suggest that the out-of-sample performances of pair trading declined sharply in the face of COVID-19. Dividing the whole data sample into two sub-samples, we found that the strategy performed well before COVID-19 but yielded poor results in the pandemic era. The analysis presented in this paper could serve as a benchmark for arbitrage-based trading models in the energy market during the pandemic. [ABSTRACT FROM AUTHOR]

Accurate electricity demand forecasting is essential for global energy security, reducing costs, ensuring grid stability, and informing decision making in the energy sector. Disruptions often lead to unpredictable demand shifts, posing greater challenges for short-term load forecasting. Understanding electricity demand patterns during a pandemic offers insights into handling future disruptions. This study aims to develop an effective forecasting model for daily electricity peak demand, which is crucial for managing potential disruptions. This paper proposed a hybrid approach to address scenarios involving both government intervention and non-intervention, utilizing integration methods such as stepwise regression, similar day selection-based day type criterion, variational mode decomposition, empirical mode decomposition, fast Fourier transform, and neural networks with grid search optimization for the problem. The electricity peak load data in Thailand during the year of the COVID-19 situation is used as a case study to demonstrate the effectiveness of the approach. To enhance the flexibility and adaptability of the approach, the new criterion of separating datasets and the new criterion of similar day selection are proposed to perform one-day-ahead forecasting with rolling datasets. Computational analysis confirms the method's effectiveness, adaptability, reduced input, and computational efficiency, rendering it a practical choice for daily electricity peak demand forecasting, especially in disrupted situations. [ABSTRACT FROM AUTHOR]

The paper endeavours to explore and analyse some critical issues in the oil and gas market that cropped up around the spread of COVID-19 and tries to identify the key drivers and triggers pertaining therewith. The spread of the first wave that began in March 2020 is crucial because of the global economic downturn that ensued due to lockdown and imposed restrictions coupled with a protracted oil price war that began between Saudi Arabia and Russia. The paper tries to address some key research questions to understand the triggers and drivers around the pandemic. These are: (1) whether the behaviour of OPEC or its key players around the pandemic could be considered uniquely different; (2) what could the triggers be for the increased volatilities that cropped up in both physical and financial markets during the pandemic; (3) what was really different about the oil market crisis around the pandemic that transformed it to an unprecedented storage crisis; (4) what really went wrong with the much-hyped U.S. shale boom during the pandemic that led to the bankruptcy of several oil and gas companies, followed by huge job losses. The paper relies on a structured review of relevant secondary literature to address these exploratory questions and builds upon a retrospective rumination on the world oil market from 1960 to 2020. This is complemented by an analysis of supporting data and evidence obtained from various sources. Considering the intertwining of oil and financial markets around the pandemic, the lessons and findings from the paper would not only be highly relevant for policymakers and stakeholders in the oil and gas sector but would be equally relevant for those in the financial markets. [ABSTRACT FROM AUTHOR]

The impact of the COVID-19 pandemic on the economy and society has gained the interest of academics and policymakers in recent years. Our paper aims to investigate and systemize the evidence from 1901 publications belonging to the top 1% of worldwide topics by prominence. This paper helps estimate a pandemic's short-run and longer-run effects on energy economics and environmental pollution. By systematizing the literature, we analyze key parameters influencing the deviation of previous worldwide economic and environmental development trajectories due to the COVID-19 pandemic. This paper examines research on the consequences of COVID-19 in five dimensions, particularly the impact of COVID-19 on (1) the environment and climate change, (2) sustainable development, (3) renewable energy and energy policy, and (4) methodology for forecasting and evaluating the energy sector and economic sectors. Our results indicate that the pandemic crisis's impact on achieving sustainable development goals in the context of energy change and pollution is controversial and complex. On the one hand, scientists are unequivocal about the positive impact of the COVID-19 pandemic on improving air quality and reducing CO2 emissions. Nevertheless, the long-term effects are threatened by gaps between countries in economic prosperity and different vaccination rates. Most studies have found that only a joint social effort and international collaboration can move to a clean energy system. In addition, using the Scopus database and modern tools of machine analysis, we determine leading authors in the subject area of "renewable energy, sustainability, and the environment", as well as the top networks and scientific communities that appear within energy. The analysis of this manuscript can be helpful to policymakers and stakeholders in developing comprehensive energy efficiency programs and energy-saving strategies to achieve SDG targets. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has disrupted global energy markets and caused significant socio-economic impacts worldwide, including the energy sector due to lockdowns and restricted economic activity. This paper presents a comprehensive and analytical review of the impact of COVID-19 on the energy sector and explores the potential role of artificial intelligence (AI) in mitigating its effects. This review examines the changes in energy demand patterns during the pre-, mid-, and post-pandemic periods, analyzing their implications for the energy industries, including policymaking, communication, digital technology, energy conversion, the environment, energy markets, and power systems. Additionally, we explore how AI can enhance energy efficiency, optimize energy use, and reduce energy wastage. The potential of AI in developing sustainable energy systems is discussed, along with the challenges it poses in the energy sector's response to the pandemic. The recommendations for AI applications in the energy sector for the transition to a more sustainable energy future, with examples drawn from previous successful studies, are outlined. Information corroborated in this review is expected to provide important guidelines for crafting future research areas and directions in preparing the energy sector for any unforeseen circumstances or pandemic-like situations. [ABSTRACT FROM AUTHOR]

Based on the spillover index and an improved spillover asymmetric measure method, this paper studies the volatility spillover and its asymmetric effect between crude oil and agricultural commodity futures in pre- and post-outbreak of COVID-19. We find that the total volatility spillover is higher with pre-outbreak of COVID-19. In addition, the volatility spillover caused by China's crude oil is more prominent than international crude oil around the COVID-19, which highlights the necessity of risk control through the establishment of an energy financial market in China. Finally, although the asymmetric effect of volatility spillover has always existed, crude oil was less impacted by good news post-outbreak of COVID-19, indicating that the outbreak of COVID-19 makes assets dominated by commodity attributes more sensitive to bad news. These findings are beneficial for investors to establish a cross-sector risk hedging portfolio, and provide empirical evidence for policymakers to ensure energy and food security. [ABSTRACT FROM AUTHOR]

This paper investigates the interrelations between stock returns and crude oil prices for European oil-importing/exporting countries. A vector autoregression (VAR) model is applied to estimate the significance of stock market responses to changes in oil prices during the pandemic period 2019–2021. A Granger causality test is applied to find the direction and the intensity of the relation between crude oil and the indices of the European stock markets. The findings of this paper hold with or without the COVID-19 pandemic episode and reveal the interaction between the European stock markets and the crude oil prices. The results indicate that in steady periods, before the COVID-19 outbreak and after the announcement of vaccinations, there is no interdependence between crude oil and stock prices, whereas in high volatility periods, the causality from stock markets to oil prices increases and both oil-exporting and -importing countries are equally influenced. These findings have implications both for investors and fund managers. [ABSTRACT FROM AUTHOR]

Purpose: The study discusses COVID-19's short-term impact on Israel's renewable energy start-up sector from March to July 2020. Results and contributions: The interviewed companies were experiencing supply chain disruption, logistical issues, and restrictions in work access, all of which negatively impacted business operations. Moreover, companies reported revenue losses and difficulty in securing funding, interpreted here as financial distress. In some cases, companies cut back on staff. Insights from the literature on the global financial crisis (GFC) were used here to discuss patterns discerned from the interviews. Policy recommendations are presented at the end based on both the interpretation of data and a literature review. Methodology: This paper combined the qualitative research analysis of COVID-19's impacts on energy start-up companies assessed by a questionnaire during interviews with a literature analysis on the previous GFC. Gap: This study aimed to clarify the issues experienced by the start-up companies in the renewable energy sector in Israel during the first months of the pandemic and contributes to the COVID-19 narrative in the energy sector, focusing on a topic that has not been thoroughly discussed at present. Relevance: The paper contains unique primary data on the short-term financial impact of COVID-19 on renewable energy start-up companies, and recommends policies to assist these companies and effectively respond to their financial needs in times of crisis. The paper points out that the absence of such a financial policy for start-up companies might pose risks to the companies' growth and innovation, and have harmful consequences for the renewable energy sector, energy transition, and climate goals. The attention currently given to initial short-term measures should shift toward a more structural and long-term approach. Impact: The paper wants to capture the attention of policymakers and the research community in evaluating and adequately addressing the financial needs of the start-up sector, which is a crucial segment of the economy, and is indispensable for achieving long-term goals such as energy transition. [ABSTRACT FROM AUTHOR]

Our goal is to examine the efficiency of different intraday electricity markets and if any of their price prediction models are more accurate than others. This paper includes a comprehensive review of Germany, France, and Norway's (NOR1) day-ahead and intraday electricity market prices. These markets represent different energy mixes which would allow us to analyze the impact of the energy mix on the efficiencies of these markets. To draw conclusions about extreme market conditions, (i) we reviewed the market data linked to COVID-19. We expected higher volatility in the lockdowns than before and therefore decrease in the efficiency of the prediction models. With our analysis, (ii) we want to draw conclusions as to whether a mix based mainly on renewable energies such as that in Norway implies lower volatilities even in times of crisis. This would answer (iii) whether a market with an energy mix like Norway is more efficient in highly volatile phases. For the analysis, we use data visualization and statistical models as well as sample and out-of-sample data. Our finding was that while the different price and volatility levels occurred, the direction of the market was similar. We could find evidence that our expectations (i–iii) were met. [ABSTRACT FROM AUTHOR]

Heating, ventilation, and air conditioning (HVAC) systems play a crucial role in either increasing or decreasing the risk of airborne disease transmission. High ventilation, for instance, is a common method used to control and reduce the infection risk of airborne diseases such as COVID-19. On the other hand, high ventilation will increase energy consumption and cost. This paper proposes an optimal HVAC controller to assess the trade-off between energy consumption and indoor infection risk of COVID-19. To achieve this goal, a nonlinear model predictive controller (NMPC) is designed to control the HVAC systems of a university building to minimize the risk of COVID-19 transmission while reducing building energy consumption. The NMPC controller uses dynamic models to predict future outputs while meeting system constraints. To this end, a set of dynamic physics-based models are created to capture heat transfer and conservation of mass, which are used in the NMPC controller. Then, the developed models are experimentally validated by conducting experiments in the ETLC building at the University of Alberta, Canada. A classroom in the building is equipped with a number of sensors to measure indoor and outdoor environmental parameters such as temperature, relative humidity, and CO 2 concentration. The validation results show that the model can predict room temperature and CO 2 concentration by 0.8%, and 2.4% mean absolute average errors, respectively. Based on the validated models, the NMPC controller is designed to calculate the optimal airflow and supply air temperature for every 15 min. The results for real case studies show that the NMPC controller can reduce the infection risk of COVID-19 transmission below 1% while reducing energy consumption by 55% when compared to the existing building controller. [ABSTRACT FROM AUTHOR]

The EU's updated bioeconomy strategy stated that "... low bioeconomy added value in the CEE is at odds with their high, and, compared to other European regions, yet underutilized biomass potential" [[13]]. Furthermore, the bioeconomy contributes to the circular economy, more specifically to the sustainable carbon cycles of biomass production and processing, as it promotes the sustainable and efficient exploitation of renewable resources in closed material and energy loops substituting for fossil-based products. The BIOEAST macro regional initiative that has been going on since 2016 aims to help build up knowledge-based agriculture, aquaculture, and forestry in the bioeconomy by contributing to the national-level bioeconomy strategy and action plan development. In the creation of this Special Issue, the editors identified circular bioeconomy, i.e., sustainable optimization of the value of biomass through its cascading use [[1]], as the key engine of the future economic growth of post-COVID economic recovery. [Extracted from the article]

Predicting energy demand in adverse scenarios, such as the COVID-19 pandemic, is critical to ensure the supply of electricity and the operation of essential services in metropolitan regions. In this paper, we propose a deep learning model to predict the demand for the next day using the "IEEE DataPort Competition Day-Ahead Electricity Demand Forecasting: Post-COVID Paradigm" database. The best model uses hybrid deep neural network architecture (convolutional network–recurrent network) to extract spatial-temporal features from the input data. A preliminary analysis of the input data was performed, excluding anomalous variables. A sliding window was applied for importing the data into the network input. The input data was normalized, using a higher weight for the demand variable. The proposed model's performance was better than the models that stood out in the competition, with a mean absolute error of 2361.84 kW. The high similarity between the actual demand curve and the predicted demand curve evidences the efficiency of the application of deep networks compared with the classical methods applied by other authors. In the pandemic scenario, the applied technique proved to be the best strategy to predict demand for the next day. [ABSTRACT FROM AUTHOR]

This paper investigates the month-wise impact of COVID-19 conditions on residential load due to people's presence at home during office hours in Memphis city, Tennessee, USA. The energy consumption patterns of four consumers are analyzed based on the data available from pre-COVID to continuing COVID-19 situations. It is observed that the energy consumptions from April 2020 to June 2021 for all families have increased during office hours than that of pre-COVID months. Therefore, the impacts of the increased loads on distribution transformer are analyzed in terms of hottest spot, top-oil temperature, and loss of transformer life. Moreover, an experimental setup is made to produce the harmonics in currents of non-linear residential load which has detrimental effects on temperature rise of distribution transformer. In addition, this work proposes implementation of harmonic filter at the load side considering the impact of harmonics produced by loads to reduce the temperature rise due to the increased load consumption and presence of harmonics in currents produced by the load. The rise in temperatures and the loss of life of distribution transformer with and without the proposed solutions are simulated in MATLAB to show the efficacy of the proposed solution. Moreover, cost value analysis among different methods, which can be implemented to reduce the adverse impact on distribution transformer, are provided to rank the available methods. [ABSTRACT FROM AUTHOR]

Today, one of the main priorities in Europe is to introduce measures to increase environmental protection. Therefore, SMEs operating in the branch related to renewable energy are essential for several EU priorities. SMEs can also be vulnerable, especially during times of crisis, which could negatively affect renewable energy development. Therefore, this paper aims to evaluate and analyze the financial security management of renewable energy SMEs during the COVID-19 pandemic. The research is conducted on SMEs operating in the renewable energy sector in Poland. The research periods are 2019 (before the COVID-19 crisis) and 2020 (during the crisis). By analyzing different financial performance ratios, we found that SMEs operating in the energy sector have been able to stabilize and maintain their current economic position compared to the past. The results of this study indicate that the receivables collection period, cash conversion cycle, and operating cycle could have been insignificantly shorter during the COVID-19 crisis. Furthermore, to have stronger financial security, SMEs have adopted a conservative policy in which the share of accounts receivable in current assets has been significantly reduced during COVID-19. In contrast, an insignificant increase in liquidity, quick ratios, and inventory turnover have been observed. In general, Polish SMEs have chosen to adopt conservative strategies during COVID-19 to have better liquidity security. [ABSTRACT FROM AUTHOR]

Forecasting return and profit is a primary challenge for financial practitioners and an even more critical issue when it comes to forecasting energy market returns. This research attempts to propose an effective method to predict the Brent Crude Oil return, which results in remarkable performance compared with the well-known models in the return prediction. The proposed hybrid model is based on long short-term memory (LSTM) and convolutional neural network (CNN) networks where the autoregressive integrated moving average (ARIMA) and generalized autoregressive conditional heteroscedasticity (GARCH) outputs are used as features, along with return lags, price, and macroeconomic variables to train the models, resulting in significant improvement in the model's performance. According to the obtained results, our proposed model performs better than other models, including artificial neural network (ANN), principal component analysis (PCA)-ANN, LSTM, and CNN. We show the efficiency of our proposed model by testing it with a simple trading strategy, indicating that the cumulative profit obtained from trading with the prediction results of the proposed 2D CNN-LSTM model is higher than those of the other models presented in this research. In the second part of this study, we consider the spread of COVID-19 and its impact on the financial markets to present a precise LSTM model that can reflect the impact of this disease on the Brent Crude Oil return. This paper uses the significance test and correlation measures to show the similarity between the series of Brent Crude Oil during the SARS and the COVID-19 pandemics, after which the data during the SARS period are used along with the data during COVID-19 to train the LSTM. The results demonstrate that the proposed LSTM model, tuned by the SARS data, can better predict the Brent Crude Oil return during the COVID-19 pandemic. [ABSTRACT FROM AUTHOR]

An effective energy management system (EMS) was designed based on the Stateflow (SF) approach for a grid-connected nanogrid (NG) composed of a photovoltaic (PV) array with a battery bank and supercapacitor (SC) energy storage system (ESS). The PV energy system, battery bank and SC (ESS), dual active bridge DC/DC converters, DC/AC inverters, control algorithms, and controllers were developed to test the operation of the NG. The average and high-frequency power components are separated using frequency division of the ESS power utilizing a low-pass filter; the average power is absorbed by the battery bank, while the high-frequency power is absorbed by the SC. The aim of this paper is to design an EMS to manage the energy of a grid-connected NG system considering the availability of the PV array, ESS, and demand requirements. Different scenarios of operation were tested to check the EMS behaviour during the day with a random demand profile, including: (1) a PV array with the grid supplying the load without an EMS; (2) a PV array, batteries, and the grid supplying the load with an EMS; (3) a PV array, batteries, an SC, and the grid supplying the load with an EMS; (4) a PV array, batteries, an SC, and the grid supplying the load with an EMS, with load profile reduction by 20% due to COVID-19. As per the simulation results, the proposed EMS enables the flow of power in the NG system and demonstrates the impact on the ESS by minimising carbon emissions via a reduction in grid consumption. Furthermore, the SF method is regarded as a helpful alternative to popular design approaches employing conventional software tools. [ABSTRACT FROM AUTHOR]

The aim of this paper was to examine whether the COVID-19 epidemic has slowed the fulfilment of one of the core tasks of the energy sector "Ensure Access to Affordable, Reliable, Sustainable and Modern Energy for All" (SDG7) taking into account corporate social responsibility. Four research questions and hypotheses were posed, relating to the perspectives of local authorities, the activities of large energy companies, the impact of the epidemic on the implementation of the SDG7 and, in addition, to the understanding of CSR principles from the point of view of ordinary entrepreneurs. A qualitative descriptive analysis based on two reliable databases and a survey procedure (Question 4) was used to answer the research questions posed. The goal was achieved by positively confirming three hypotheses and testing one negatively, relating to COVID-19's slowing role in SDG7 implementation. The analysis showed that the 2020–2021 epidemic in Poland has led to more initiatives in this area, contrary to expectations. However, they were linked to the simultaneous implementation of other SDGs, which distorted their importance for achieving Goal 7. In summary, although energy companies were more active than expected during the epidemic, they had a low contribution to SDG 7. This also applies to local authorities. An analysis of the knowledge about CSR in a group of entrepreneurs from the Lublin district (case study) confirmed the opinion appearing in the literature about the lack of understanding of the concept and the need for its application. [ABSTRACT FROM AUTHOR]

The emergence of the new SARS-CoV-2 virus two years ago strongly affected economic life and labour markets around the world. The pandemic affected many sectors, including the mining industry. Coal companies have had to cope with the challenges and adapt their operations to the situation. Due to the peculiarities of the mines, not only to the hazardous factors and conditions prevailing underground but also to the large number of employees who usually move in groups in the plants, the emergence of a new threat caused by a biological agent posed a real challenge for them. The aim of this paper was to present the initiatives and measures taken in the coal mining sector to ensure the safety of workers during a pandemic. The guidelines for the operation of mining plants during the SARS-CoV-2 epidemic were analysed, as well as the identification of locations in mining plants particularly vulnerable to infection with the virus. We also presented how the pandemic period affected the operations of a selected coal company in Poland from an economic point of view. [ABSTRACT FROM AUTHOR]

Risk disclosures contribute to financial stability by providing stakeholders with a better understanding of companies' risk exposures and risk management practices. Presently, corporate risk has been accelerated by the COVID-19 pandemic, and the level of disclosure varies across industries, companies, and organizations. Due to the strategic importance of the energy industry, the paper aims to assess COVID-19-related risk disclosure in the biggest electricity companies in Central and Eastern European countries, and to identify the main determinants of the disclosure. For this purpose, risk disclosure was assessed based on publicly available data disclosed by the 10 biggest public electricity companies operating in this region. Our findings indicate that factors such as the company's size, leverage, and profitability do not significantly affect COVID-19-related risk disclosure in financial reports; nevertheless, COVID-19 risk disclosure in non-financial reports is significantly correlated with the company's assets and revenues. Moreover, there is a significantly strong positive relationship between the scope of COVID-19-related risk disclosure in the management reports and the number of women on the company's management board. COVID-19-related risk disclosure in management board's reports is significantly higher than disclosure in non-financial reports and explanatory notes of financial statements. Our results suggest that risk disclosure is needed to mitigate information asymmetry, especially in pandemic situations. [ABSTRACT FROM AUTHOR]

The date assumed as the beginning of the pandemic in Poland is 4 March 2020, the date of the first confirmed case of the virus. This article presents the actions undertaken by the management of underground hard coal mining plants concerning the risk of epidemic related to SARS-CoV-2. This work shows a set of implemented recommendations, guidelines and decisions, which were established after the appearance of the first wave of cases in Poland. What is more, it discusses measures aiming at reducing the risk of spreading the coronavirus among the mineworkers. The suggestions for different variants of the decision-making process concerning the pandemic and which have an enormous impact on the operating expenses of the company are also made. The paper presents the results of the study on actions taken in individual mining companies and good work practices recommended to be applied. [ABSTRACT FROM AUTHOR]

The paper presents the results of sociological qualitative research on safety management in work organization. The focus was on how to adapt the workforce to the sanitary regime during the time of the COVID-19 pandemic in the lignite mining and energy sector in the Bełchatów poviat (Łódź voivodeship, Poland). The study aimed to identify the dimensions of safety and the work culture created in crisis conditions as perceived by workers. Based on the conducted analysis, the process of adapting employees to the new rules of work organization was reported, including the transition from fear and anxiety to control over threats and negative emotions. The essence of the research was to support institutional memory to consolidate the existing knowledge and use it in the future. [ABSTRACT FROM AUTHOR]

To obtain the price return and price volatility spillovers between renewable energy stocks, technology stocks, oil futures and carbon allowances under different investment horizons, this paper employs a frequency-dependent method to study the dynamic connectedness between these assets in four frequency bands. The results show that, first, there is a strong spillover effect between these assets from a system-wide perspective, and it's mainly driven by short-term spillovers. Second, in the time domain, technology stocks have a more significant impact on renewable energy stocks compared to crude oil. However, through the study in the frequency domain, we find renewable energy stocks exhibit a more complex relationship with the other two assets at different time scales. Third, renewable energy stocks have significant spillover effect on carbon prices only in the short term. On longer time scales, other factors such as energy prices, climate and policy may have a greater impact on carbon allowance prices. Fourth, the spillover effect of the system is time-varying and frequency-varying. During the European debt crisis, the international oil price decline and the COVID-19 pandemic, the total spillover index of the system has experienced a substantial increase, mainly driven by medium, medium to long or long term spillovers. [ABSTRACT FROM AUTHOR]

Prices of oil and other commodities have fluctuated wildly since the outbreak of the COVID-19 pandemic. It is crucial to explore the causes of price fluctuations and understand the source and path of risk contagion to better mitigate systemic risk and maintain economic stability. The paper adopts the method of network topology to examine the path of risk contagion between China's and foreign commodities, focusing on the dynamic evolution and transmission mechanism of risk contagion during the pandemic. This research found that among China's commodities, energy, grain, and textiles are net recipients of risk contagion, while chemical products and metals are net risk exporters. Among international commodities, industries have positive risk spillover effects on metals and textiles. During the first phase of the pandemic, China's commodities were the main exporters of risk contagion. However, international industries and metals became the main risk exporters and exerted risk spillover on China's commodities in the second phase of the pandemic. Moreover, based on total volatility spillover index of commodities, the risk contagion among the commodities follows three paths: "interest rate → commodities → money supply", "China's economic expectation → commodities → foreign economic expectation", and "commodities → consumer confidence". [ABSTRACT FROM AUTHOR]

The surveyof traffic intensity is used to obtain information on the number of vehicles on roads during the day. Subsequently, it is possible to derive from this the daily, weekly, and other road traffic intensity information. This survey represents the basis for the calculation of the annual average daily traffic volume and the basic characteristics of traffic flow. The COVID-19 pandemic has caused extensive economic and social damage around the world. These damages have also affected traffic. Changes in traffic behavior have mainly affected the reduction in traffic intensity on road networks. Thanks to the reduction in the demand for transport, there has also been a significant reduction in traffic delays, fuel consumption and emissions. An examination of changes in traffic intensity took place at a selected intersection in 2019, 2020 and 2021. This paper describes the effects of reducing the traffic intensity, fuel consumption and emissions obtained by microsimulation. The results obtained confirmed the reduction in traffic, which also contributed to a significant reduction in vehicle delays. [ABSTRACT FROM AUTHOR]

Different technological, socio-economic, geopolitical, and demographic factors have a significant influence on labor markets. Currently, due to COVID-19, the global economy is in a challenging situation, and millions of people from different countries have lost their jobs. The employee's mental health and well-being are in risk conditions. In the coming years, the Polish energy sector will face several transformations. Emerging technologies are intended to deal with the problems in energy management. One of the main industry forces is human capital, people who will be able to project and manage the innovative technologies. Thus, this paper examines the determinants of managerial competences transformation in the energy industry from the labor market perspective. The paper fulfills the research gap in the energy manager profession's transformation in Poland. The aim of the paper was to present the current state of the energy manager profession in Poland. Two methodological approaches were used: the theoretical and practical approaches. Descriptive statistics are provided to present the labor market research results. The findings of the research can contribute to the literature and practice by applying them in the process of developing energy manager competency models, as well as in education programs and training courses for enterprises and universities. [ABSTRACT FROM AUTHOR]

So far, airport security screening has only been analysed in terms of efficiency, level of service, and protection against any acts of unlawful interference. Screening procedures have not yet addressed the need to limit operator-to-passenger contact. However, the pandemic situation (COVID-19) has shown that it is a factor that can be a key protection for the health of passengers and operators. The purpose of this paper was to analyse the feasibility of reducing contact between operators and passengers in the airport security screening system by process management with respect to the power consumption of the system. Experimental research was conducted on a real system. A computer simulation was applied to estimate system performance and power consumption. The paper identifies the important findings that expand upon previous knowledge. The results showed that there are two key factors: the experience of operators and proper system structure. These factors can significantly reduce the number of operator-to-passenger contacts and, in parallel, provide lower energy consumption of the system. The results obtained in this article showed that proper management improves the process by up to 37%. This approach expands the World Health Organization's policy of prevention against COVID-19 and helps to ensure sustainable process management. [ABSTRACT FROM AUTHOR]

The property sector is revitalised to incorporate sustainability, specifically the biophilic design, to encourage human interaction with nature. Thus, there is an urgent need to communicate the biophilic design elements amongst stakeholders, especially the foreign workers, to ensure the project meets the requirement. However, standard project communications management is no longer practical, as the construction industry worldwide has been severely impacted by the Coronavirus Disease 2019 (COVID-19) pandemic. Hence, this paper evaluates the biophilic design elements to be communicated and examines the project communications management breakdown relating to the biophilic design elements in the Malaysian construction industry during the COVID-19 pandemic. Through a systematic literature review (SLR), focus group discussion (FGD) and questionnaire survey on 147 foreign workers, this paper found that from 33 biophilic design element items, only 1 item is categorised as highly critical, whereas another 20 items are categorised as critical. In addition, 43 potential communications management breakdown items from a total of 66 items fall under the critical category. The finding suggests that communication breakdown is caused by the language barrier amongst foreign workers from different ethnicities as well as between foreign workers and the supervisors, since face to face communication is limited during the pandemic. [ABSTRACT FROM AUTHOR]

The industry is a key driver of economic development. However, changes caused by introduction of modern technologies, and increasing complexity of products and production, directly affect the industrial enterprises and workers. The critics of the Industry 4.0 paradigm emphasized its orientation to new technologies and digitalization in a technocratic way. Therefore, the new industrial paradigm Industry 5.0 appeared very soon and automatically triggered a debate about the role of, and reasons for applying, the new paradigm. Industry 5.0 is complementing the existing Industry 4.0 paradigm with the orientation to the worker who has an important role in the production process, and that role has been emphasized during the COVID-19 pandemic. In this research, there is a brief discussion on main drivers and enablers for introduction of these new paradigms, then a literature-based analysis is carried out to highlight the differences between two paradigms from three important aspects—people, organization, and technology. The conclusion emphasizes the main features and concerns regarding the movement towards Industry 5.0, and the general conclusion is that there is a significant change of the main research aims from sustainability towards human-centricity. At the end, the analysis of maturity models that evaluates enterprises' readiness to introduce features of new paradigms is given as well. [ABSTRACT FROM AUTHOR]

On 11 March 2020, the WHO declared the COVID-19 epidemic to be a global pandemic. This was a consequence of the rapid increase in the number of people with positive test results, the increase in deaths due to COVID-19, and the lack of pharmaceutical drugs. Governments introduced national lockdowns, which have impacted both energy consumption and economies. The purpose of this paper is to answer the following question: do COVID-19 lockdowns affect the business cycle? We used the cycle clock approach to assess the magnitude of decrease in electricity consumption in the three waves of the epidemic, namely, April 2020, November 2021, and April 2021. Additionally, we checked the relation between energy consumption and GDP by means of spectral analysis. Results for selected 28 European countries confirm an impact of the introduced non-pharmaceutical interventions on both energy consumption and business cycle. The reduction of restrictions in subsequent pandemic waves increased electricity consumption, which suggests movement out of the economic recession. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has impacted electricity consumption patterns and such an impact cannot be analyzed by simple data analytics. In China, specifically, city lock-down policies lasted for only a few weeks and the spread of COVID-19 was quickly under control. This has made it challenging to analyze the hidden impact of COVID-19 on electricity consumption. This paper targets the electricity consumption of a group of regions in China and proposes a new clustering-based method to quantitatively investigate the impact of COVID-19 on the industrial-driven electricity consumption pattern. This method performs K-means clustering on time-series electricity consumption data of multiple regions and uses quantitative metrics, including clustering evaluation metrics and dynamic time warping, to quantify the impact and pattern changes. The proposed method is applied to the two-year daily electricity consumption data of 87 regions of Zhejiang province, China, and quantitively confirms COVID-19 has changed the electricity consumption pattern of Zhejiang in both the short-term and long-term. The time evolution of the pattern change is also revealed by the method, so the impact start and end time can be inferred. Results also show the short-term impact of COVID-19 is similar across different regions, while the long-term impact is not. In some regions, the pandemic only caused a time-shift in electricity consumption; but in others, the electricity consumption pattern has been permanently changed. The data-driven analysis of this paper can be the first step to fully interpret the COVID-19 impact by considering economic and social parameters in future studies. [ABSTRACT FROM AUTHOR]

This paper discusses the impact of COVID-19's vulnerability context on Malawi's Energy Sector and outlines mechanisms for enhancing Malawi's energy-sector resilience based on experiences from a range of stakeholders. The investigation was conducted online by inviting purposively selected stakeholders to create presentations responding to thematic questions. The final sample had 19 stakeholders with representation from policy-makers, regulatory bodies, national grid supply players, off-grid players, development agencies, bankers, professional bodies, civil society, and women's rights bodies. The presentations from the stakeholders highlighted how COVID-19 affects the operation costs of energy systems and implementation of energy systems projects in areas that require stimulus packages to contain energy system delivery costs and prevent disruption of essential services amid the COVID-19 pandemic. These services include stakeholder responses to COVID-19 in the energy sector, the role of digital payments particularly when purchasing electricity units, and the state of third-party service providers such as banks and mobile network operators to enhance preparedness and continuity of operations for the energy sector. Based on the findings in these thematic areas and an application of systems thinking in the analysis, the paper finally makes recommendations on how Malawi and similar low-income countries can strategise to enhance energy systems resilience. [ABSTRACT FROM AUTHOR]

The study investigated the changes that occurred in the Mexican power sector before, during, and after the COVID-19 pandemic and its repercussions on the electricity sector and energy sustainability goals. The study was based on the variability of the installed capacity, consumption, generation, and demand of the National Electric System (SEN), covering the period from 2017 to 2021. The data were collected from the Development of the National Electric System (PRODESEN), the Ministry of Energy, the National Energy Balance, and the government's official website. The results indicated that installed capacity and generation increased by 22.83% and 27.86%, respectively, despite the pandemic. This growth was attributed to clean energy, mainly from photovoltaic solar and wind sources. Another finding was that the gross domestic product (GDP), consumption, and demand were seriously affected by COVID-19. They had a fall of 8.2%, 2.2%, and 4.4%, respectively, which translates into a significant economic lag and a slowdown in energy self-sufficiency and the Mexican Energy Transition (TEM). Moreover, the objective of generating 35% and 40% of electrical energy through clean energy will be achieved by 2031 and 2035, instead of 2021 and 2035, respectively. [ABSTRACT FROM AUTHOR]

This study delves into the intricate landscape of biomass utilization within the food and energy markets. It entails a systematic review of the existing literature with the aim of unraveling the complexities of the food and energy discourse, especially in the context of significant market factors influencing biomass use for food and energy. We leveraged the Scopus database to examine 73 pertinent scientific articles carefully selected following the PRISMA framework. The articles were analyzed using the advanced qualitative data analytics tool NVivo 12 Plus. Furthermore, we employed the Biblioshiny R-package tool to extract valuable insights from the metadata, unveiling pivotal trends and providing descriptive statistical details. The findings offer comprehensive insights into the debate on biomass utilization from 2010 to 2023, tracing the influence of the COVID-19 pandemic. We identify regions that have made notable contributions and highlight those that require increased attention. The analysis underscores the collaborative nature of this field, with 281 authors contributing to 39 different sources. Surprisingly, the observed annual growth rate of −10.93% indicates a potential decline in research output in this field. Nevertheless, the sources identified in our research provide a valuable roadmap for further research exploration of the biomass–food–energy nexus. [ABSTRACT FROM AUTHOR]

The challenges of the world economy and their societies, after the outbreak of the COVID-19 pandemic have led policy-makers to seek for effective solutions. This paper examines the oil price volatility response to the COVID-19 pandemic and stock market volatility using daily data. A general econometric panel model is applied to investigate the relationship between COVID-19 infection and death announcements with oil price volatility. The paper uses data from six geographical zones, Europe, Africa, Asia, North America, South America, and Oceania for the period 21 January 2020 until 13 May 2021 and the empirical findings show that COVID-19 deaths affected oil volatility significantly. This conclusion is confirmed by a second stage analysis applied separately for each geographical area. The only geographical area where the existence of correlation is not confirmed between the rate of increase in deaths and the volatility of the price of crude oil is Asia. The conclusions of this study clearly suggest that COVID-19 is a new risk component on top of economic and market uncertainty that affects oil prices and volatility. Overall, our results are useful for policy-makers, especially in the case of a new wave of infection and deaths in the future. [ABSTRACT FROM AUTHOR]

The article aims to identify the latest trends in research on renewable energy, sustainability and the environment. A total of 92,873 publications from 123 Scopus sources for 2020–2021 are compared using the scoping review method. The results show that the most cited works in this sample are those by authors from the Asian region. The research of these authors focuses on the security, efficiency and reliability of separate elements in energy systems. Besides, the paper considers the problems regarding COVID disease along with the renewable energy sources, perovskite and organic solar panels, nanostructured materials and high energy density. Finally, the paper analyses applications of computer science methods in research on renewable energy, sustainability and the environment. The findings evidently show that recent advancements in computer science methods were not extensively used in the discussed research domain and give a great room for novel strategies of prognosing, simulation and processes optimisation. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has had significant effects on the energy industry, leading to shifts in energy demand and generation patterns worldwide. This has created challenges for the energy sector, including disruptions in energy markets and the need for robust healthcare and electricity infrastructures. The pandemic has also resulted in changes in residential energy consumption, with some communities increasing their energy usage while others saw a decrease. Additionally, the adoption of virtual education during the pandemic has led to energy savings in educational institutions. The pandemic has also impacted electricity systems and grids, requiring ongoing research to address the challenges posed. In other sectors, such as transport and tourism, the pandemic has necessitated innovative measures to ensure passenger safety and has led to a reduction in greenhouse gas emissions in the tourism sector. Overall, the pandemic has brought about a new era for the energy industry, highlighting the need for coherent energy policies and the transition to clean energy. [Extracted from the article]

The recent coronavirus (COVID-19) pandemic has wreaked havoc on the global economy, causing major shifts in energy use and output patterns. For some countries, this has had a significant effect on energy demand and carbon emissions, at least in the short term. Since the United Arab Emirates is currently exerting many efforts towards sustainability, it is important to assess and understand the impacts of the pandemic and the lockdown measurements on the local energy sectors. Data for this analysis were gathered by the Sharjah Electricity Water & Gas Authority (SEWA) for Sharjah City which is the capital of the Emirate of Sharjah. The changes in electricity after the implementation of quarantine and lockdown-like measures were assessed, and the results indicate that the electric power demand in Sharjah City was reduced in the commercial, industrial, and agricultural sectors, whereas the residential and government sectors witnessed a higher power demand. The overall electricity consumption in the year 2020 was reduced by 1.04% in comparison with previous years including 2016 to 2019. The results of this study indicate that the changes in electricity consumption were minimal in Sharjah City as compared to other cities around the world. However, this paper highlights the importance of governmental response during and after a pandemic, and the possible impacts that lockdowns could potentially have in the energy industry worldwide. [ABSTRACT FROM AUTHOR]

In this paper, the use of HVAC systems and non-HVAC control measures to reduce virus-laden bioaerosol exposure in a highly occupied indoor space is investigated. A simulation tool was used to model the fate and transport of bioaerosols in an indoor space in the hotel industry (bar or pub) with three types of HVAC system (central air handling system (CAHS), dedicated outdoor air system (DOAS), and wall unit system (WUS)). Non-HVAC control measures such as portable air cleaners (PAC) and local exhaust fans were considered. Occupant exposure was evaluated for 1 μm bioaerosols, which transport SARS-CoV-2, for 3 h/day of continuous source and exposure. The combined effects of ventilation (400 l/s of outdoor air), recirculated air filtration (90% efficacy), and a PAC with a capacity up to 900 m3/h mitigated the (normalized) integrated exposure of the occupant by 0.66 to 0.51 (CAHS) and 0.43 to 0.36 (DOAS). In the case of WUS, the normalized integrated exposure was reduced by up to 0.2 when the PAC with a capacity of up to 900 m3/h was used. The corresponding electricity consumed increased by 297.4 kWh/year (CAHS) and 482.7 kWh/year (DOAS), while for the WUS it increased by 197.1 kWh/year. [ABSTRACT FROM AUTHOR]

A field survey of indoor environmental measurements and questionnaires on thermal sensation, overall comfort, and behaviors was conducted in four office buildings in Japan by visiting each office every month over a duration of more than a year during the coronavirus disease 2019 (COVID-19) pandemic. The indoor environment was measured concurrently. We obtained 1047 votes from office workers in their 20s to 60s. The regression and Griffiths' methods were used to calculate the indoor comfort temperature. A logistic regression analysis was used to develop the occupant behavior model. Over 70% of the occupants found the indoor environment comfortable at a mean comfort temperature of 23.2 to 25.9 °C. Gender differences were observed in thermal sensation and overall comfort, but a gender difference was observed only in the cooling mode for the indoor comfort temperature. An adaptive model was developed for the office buildings in Nagasaki city to predict the indoor comfort temperature from the outdoor air temperature. The proportions of heating, cooling, and fan usage can be predicted from the outdoor air temperature using a logistic regression analysis. The adaptive model and occupant behavior model are useful for the indoor temperature control of the existing buildings and thermal simulation of the new building design. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has significantly affected the energy sector. The new behavior of industrial and non-commercial consumers changes the energy consumption model. In addition, the constraints associated with the coronavirus crisis have led to environmental effects from declining economic activity. The research is based on evidence from around the world showing significant reductions in emissions and improved air quality. This situation requires rethinking the energy development strategy, particularly the construction of smart grids as a leading direction of energy development. Evaluating the efficiency of smart grids is a vital tool for disseminating successful experience in improving their management. This paper proposes an approach to a comprehensive assessment of smart grids based on a comparative analysis of existing methods, taking into account the changes that need to be considered after the experience gained from the COVID-19 pandemic. The approach provides an accurate set of efficiency indicators for assessing smart grids to account for the direct and indirect effects of smart grids' implementation. This evaluation approach can be helpful to policymakers in developing energy efficiency programs and implementing energy policy. [ABSTRACT FROM AUTHOR]

A demonstration of the relationship between the share of renewables in gross marginal energy and selected countries' economic growth is the basis of this research. The paper seeks to investigate mutual correlations between renewable energy sources and economic growth for two EU economies and how it influences their fluctuations (increase and decrease). The comparative analysis of results was carried out for less-income Polish and high-income Swedish economies. This research used a regression model to answer the research questions examining the presence of correlations between renewable energy sources in gross marginal energy consumption and economic growth. This study analyzes data starting from 1991 to 2022. The results indicated a positive correlation (statistical significance) between Gross Domestic Product and Gross National Income variables for Sweden (84.6% and 83.7%, respectively) and Poland (79.9% and 79.2%, respectively), which influence the use of renewable energy sources. The findings also reveal that the higher economic growth caused by the use of renewables is observed for the leading countries but at the same time the risk of a greater recession is much more likely than in other countries. These findings would help government officials and policymakers to better understand the role of renewable energy in the economic growth of these countries. This study has contributed to the literature on renewable energy sources and statistical reports under the EU energy sector framework. [ABSTRACT FROM AUTHOR]

Short-term load forecasting (STLF) is a fundamental tool for power networks' proper functionality. As large consumers need to provide their own STLF, the residential consumers are the ones that need to be monitored and forecasted by the power network. There is a huge bibliography on all types of residential load forecast in which researchers have struggled to reach smaller forecasting errors. Regarding atypical consumption, we could see few titles before the coronavirus pandemic (COVID-19) restrictions, and afterwards all titles referred to the case of COVID-19. The purpose of this study was to identify, among the most used STLF methods—linear regression (LR), autoregressive integrated moving average (ARIMA) and artificial neural network (ANN)—the one that had the best response in atypical consumption behavior and to state the best action to be taken during atypical consumption behavior on the residential side. The original contribution of this paper regards the forecasting of loads that do not have reference historic data. As the most recent available scenario, we evaluated our forecast with respect to the database of consumption behavior altered by different COVID-19 pandemic restrictions and the cause and effect of the factors influencing residential consumption, both in urban and rural areas. To estimate and validate the results of the forecasts, multiyear hourly residential consumption databases were used. The main findings were related to the huge forecasting errors that were generated, three times higher, if the forecasting algorithm was not set up for atypical consumption. Among the forecasting algorithms deployed, the best results were generated by ANN, followed by ARIMA and LR. We concluded that the forecasting methods deployed retained their hierarchy and accuracy in forecasting error during atypical consumer behavior, similar to forecasting in normal conditions, if a trigger/alarm mechanism was in place and there was sufficient time to adapt/deploy the forecasting algorithm. All results are meant to be used as best practices during power load uncertainty and atypical consumption behavior. [ABSTRACT FROM AUTHOR]

Previous analyses of the PV market (and the impact of the pandemic on it) have focused on the market as a whole. The literature does not contain analyses of selected services sectors (e.g., catering, hotel services) in terms of the use of photovoltaics. There are no studies that would show in which segments the demand profile for electricity most closely matches the production from photovoltaic installations (not to mention the impact of the pandemic). The authors analyzed selected service sectors (catering and hotel) in terms of the use of photovoltaics before and during the COVID-19 pandemic. The paper proposes a comparative methodology for the use of photovoltaics for self-consumption, including statistical analyses and calculations of the self-consumption index for representatives of various selected services sectors. The highest value of the self-consumption ratio at the level of 52% was shown for cafes and restaurants (during the pandemic). Surprisingly, in the pandemic, the self-consumption rate increased for restaurants and cafes for the same size of installations (compared to pre-pandemic times). [ABSTRACT FROM AUTHOR]

The paper aims to detect the differences in stock market performance between companies from the alternative energy sector and main stock market sectors in the first and second years of the COVID-19 pandemic. We used Global Industry Classification Standard to analyse eleven main stock market sectors and the alternative energy sector. Based on the one-factor variance analysis—ANOVA, we reveal the statistically significant differences between the analysed stock market sectors in both 2020 and 2021. The analysis implied that the performance of stock market companies during COVID-19 is sector-specific. Tukey's Honestly Significant Difference (HSD) test for pairwise comparison indicates that the alternative energy sector shows the most differentiation. Its average rate of return in 2020 is the highest and is significantly different for all eleven stock market sectors, while the top constituents from the conventional energy and financial sectors suffered the most. In 2021, a reverse trend in the stock prices can be observed. Companies from the conventional energy and financial sectors achieved the highest positive average weekly rates of return among all of the analysed stock market sectors, while the alternative energy sector performed significantly worse than the other sectors did. Nevertheless, throughout the entire analyses period of 2020–2021, the companies from the alternative energy sector turned out to be the biggest stock market beneficiaries. This study might imply that the COVID-19 pandemic has not hampered but has instead accelerated growing concerns about the environment and climate change. [ABSTRACT FROM AUTHOR]

Energy poverty in Aotearoa New Zealand is well-documented, and tertiary students have been identified as an at-risk group. However, there has been very little research on tertiary students' experiences of energy poverty in New Zealand. This paper used a nationwide online survey to investigate the extent and impact of energy poverty among tertiary students. Furthermore, it aimed to identify disparities between different demographic groups, understand the effects of COVID-19 and evaluate the effectiveness of the support policies available to students. Responses from 522 students were analysed; 85% were under 30 years old, 72% were female, 14% identified as Māori, and 14% reported having long-term disabilities or health concerns. The findings of this study are concerning. Tertiary students in New Zealand are largely living in dwelling conditions that do not meet recommended health standards and exacerbate energy poverty. Energy poverty has adverse effects on their physical and mental health; however, available support is limited or inaccessible. Most significantly, the impact of energy poverty is disproportionally affecting students with long-term disabilities or health concerns as well as students identifying as Māori. Moreover, the impact of COVID-19 further strained students experiencing energy poverty and again, disproportionally affected more vulnerable students. [ABSTRACT FROM AUTHOR]

The introduction of electromobility contributes to an increase in energy efficiency and lower air pollution. European countries have not been among the world's leading countries in this statistic. In addition, there have been different paces in the implementation of electromobility in individual countries. The main purpose of this paper is to determine the directions of change and the degrees of concentration in electromobility in European Union (EU) countries, especially after the economic closure as a result of the COVID-19 pandemic. The specific objectives are to indicate the degree of concentration of electromobility in the EU and changes in this area, especially during the COVID-19 pandemic; to determine the dynamics of changes in the number of electric cars in individual EU countries, showing the variability in this aspect, while also taking into account the crisis caused by COVID-19; to establish the association between the number of electric cars and the parameters of the economy. All EU countries were selected for study by the use of the purposeful selection procedure, as of December 31, 2020. The analyzed period covered the years 2011–2020. It was found that in the longer term, the development of electromobility in the EU, measured by the number of electric cars, is closely related to the economic situation in this area. The crisis caused by the COVID-19 pandemic has influenced the economic situation in all EU countries, but has not slowed down the pace of introducing electromobility, and may have even accelerated it. In all EU countries, in the first year of the COVID-19 pandemic, the dynamics of introducing electric cars into use increased. The growth rate in the entire EU in 2020 was 86%, while in 2019 it was 48%. The reason was a change in social behavior related to mobility under conditions of risk of infection. COVID-19 has become a positive catalyst for change. The prospects for the development of this type of transport are very good because activities related to the development of the electromobility sector perfectly match the needs related to the reduction of pollution to the environment. [ABSTRACT FROM AUTHOR]