• Energy Research
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• Silesian University of Technology close

The global spread of the COVID-19 virus has led to difficulties in many branches of the economy, including significant effects on the urban transport industry. Thus, countries around the world have introduced different mobility policies during the pandemic. Due to government restrictions and the changed behaviors of transport users, companies providing modern urban mobility solutions were forced to introduce new business practices to their services. These practices are also apparent in the context of the electric shared mobility industry. Although many aspects and problems of electric shared mobility have been addressed in scientific research, pandemic scenarios have not been taken into account. Noticing this research gap, we aimed to update a previously developed model of factors that influence the operation of electric shared mobility by incorporating aspects related to the COVID-19 pandemic and its impact on this industry. This article aims to identify the main factors influencing the electric shared mobility industry during the COVID-19 and post-lockdown periods, together with their operation areas and the involved stakeholders. The research was carried out on the basis of expert interviews, social network analysis (SNA), and the use of the R environment. The article also presents sustainable transport management recommendations for cities and transport service operators, which can be implemented after a lockdown caused by an epidemic. The results in this paper can be used to support transport modeling and the creation of new policies, business models, and sustainable development recommendations. The contents will also be helpful to researchers worldwide in preparing literature reviews for articles related to sustainable management in the COVID-19 pandemic reality.

This paper presents an assessment of the impact of the COVID-19 pandemic on the waste management sector, and then, based on laboratory tests and computer calculations, indicates how to effectively manage selected waste generated during the pandemic. Elemental compositions—namely, C, H, N, S, Cl, and O—were determined as part of the laboratory tests, and the pyrolysis processes of the above wastes were analysed using the TGA technique. The calculations were performed for a pilot pyrolysis reactor with a continuous flow of 240 kg/h in the temperature range of 400–900 °C. The implemented calculation model was experimentally verified for the conditions of the refuse-derived fuel (RDF) pyrolysis process. As a result of the laboratory tests and computer simulations, comprehensive knowledge was obtained about the pyrolysis of protective masks, with particular emphasis on the gaseous products of this process. The high calorific value of the pyrolysis gas, amounting to approx. 47.7 MJ/m3, encourages the management of plastic waste towards energy recovery. The proposed approach may be helpful in the initial assessment of the possibility of using energy from waste, depending on its elemental composition, as well as in the assessment of the environmental effects.

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.

This article presents the research on the analysis of the impact of social isolation caused by the COVID-19 pandemic on gaseous air pollutant concentrations. For this purpose, the authors presented (thermal maps) and analyzed the concentrations of selected gases such as NO2, CO, SO2, and PM2.5 particles during the strict quarantine period in Poland and other EU countries. Statistical analysis of the concentration level of these gases was performed. It was noticed that in Poland, Germany, and France, the concentrations of such gases as CO, NO2, and PM2.5 particles decreased, while in Italy and Spain, the tendency was the opposite. To verify whether the discovered dependencies are not a natural continuation of the trends shaping the given phenomenon, the time series of gas and PM2.5 particle emissions were analyzed. On this basis, the emission forecast up to 2023 was created, using the ARIMA class models. The obtained results allowed to construct five scenarios for the development of NO2, CO, SO2, and PM2.5 emissions until 2023, considering the impact of the COVID-19 pandemic. It was stated that in the optimistic scenario, in 2023, a decrease in CO, NO2, and PM2.5 emissions could be achieved by maximums of 51%, 95%, and 28%, respectively.

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.

This article’s aim is to explain the impact of technology entrepreneurship phenomenon on waste management enterprise performance in the conditions of COVID-19 pandemic. The concept of technology entrepreneurship according to the configuration approach and the category of high-performance organization are the theoretical bases of empirical investigation. For the implementation of empirical research, Fuzzy set Qualitative Comparative Analysis (FsQCA) was adopted. The research sample included a group of producers of Refused Derived Fuel (RDF) as a central part of the waste to energy industry located in Poland. The research results showed that the waste to energy sector is highly immune to pandemic threats. While during COVID-19, the basic economic parameters (i.e., sales, profitability and employment) of the entire industry in Poland clearly decreased, the same parameters in the case of the waste to energy industry remained at the same level. The research results allow the formulation of two high-performance models of technology entrepreneurship in the waste to energy industry under COVID-19 conditions. The first model is based on traditional technologies and hierarchical organizational structures, and the second is using innovative technologies and flexible structures. Both technology entrepreneurship models are determined by their emergence as complementary to implementation strategies and the opportunity-oriented allocation of resources within business model portfolios.

This paper presents the results of the technological and economic analysis of mine water treatment systems before their discharge into the environment. The following analysis enabled us to determine the profitability of the investment, taking into account the TSS (total suspended solids) concentration in mine water. The simulation results showed that it is economically profitable to apply a water treatment system if natural sedimentation carried out in underground mine water passages, or in sedimentation tanks located on the ground, is ineffective for TSS removal. Economic and financial parameters allow us to conclude that all analyzed variants of the application of a pre-treatment system are characterized by high economic effectiveness. This mainly results from the high profitability of an analyzed investment, comparatively low capital expenditure, and present low market percentage rates. The most profitable variant (TSS concentration is 1000 mg/dm3) brings significant economic indicators, i.e., high NPV–Net Present Value (100 319 270.28 PLN), a high NPVR–Net Present Value Ratio (8.96 PLN/PLN), and a short discount payback period (1 year 236.6 days). A high internal rate of return (157.8%) for this variant reduces the risk of losing profitability in a situation of growing capital costs in the monetary market.

Coughing and sneezing are the main ways of spreading coronavirus-2019 (SARS-CoV-2). People sometimes need to work together at close distances. This study presents the results of the computational fluid dynamics (CFD) simulation of the dispersion and transport of respiratory droplets emitted by an infected person who coughs in an indoor space with an air ventilation system. The resulting information is expected to help in risk assessment and development of mitigation measures to prevent the infection spread. The turbulent flow of air in the indoor space is simulated using the k-ε model. The particle equation of motion included the drag, the Saffman lift, the Brownian force and gravity/buoyancy forces. The innovation of this study includes A: Using the Eulerian–Lagrangian CFD model for the simulation of the cough droplet dispersion. B: Assessing the infection risk by the Wells–Riley equation. C: A safer design for the ventilation system (changing the ventilation supplies and exhausts in the indoor space and choosing the right location for air ventilation). The droplet distribution in the indoor space is strongly influenced by the air ventilation layout. The air-curtain flow pattern significantly reduces the dispersion and spreading of virus-infected cough droplets. When the ventilation air flow occurs along the room length, it takes about 115 s for the cough droplets to leave the space. However, when the ventilation air flow is across the width of the indoor space and there are air curtain-type air flow patterns in the room, it takes about 75 s for the cough droplets to leave the space.