Energy Intensity of Steel Manufactured Utilising EAF Technology as a Function of Investments Made: The Case of the Steel Industry in Poland

A review of simulation and numerical modeling of electric arc furnace (EAF) and its processes

Electric Arc Furnaces (EAFs) play a pivotal part in the steel industry, offering a versatile of producing high-quality steel. This paper conducts an in-depth examination of the EAF, along with exploring mathematical modeling and optimization techniques pertinent to this furnace. Additionally, it delves into the global steel production capacity employing this technology, introduces different processes associated with EAF, scrutinizes the energy balance of EAFs, and provides an overview of numerical and simulation modeling in this context. The core focus of this extensive review is the diverse landscape of EAF simulation methods. It places particular emphasis on understanding the key components and stages of the EAF process, including charging, melting, refining, tapping, and slag removal. The review delves into the wide array of approaches and methodologies employed in EAF modeling, spanning from innovative computational fluid dynamics (CFD) and finite element analysis to the intricacies of mathematical and thermodynamic models. Furthermore, the paper underscores the importance of simulation in predicting and enhancing crucial aspects such as heat transfer, chemical reactions, and fluid dynamics within the EAF. By doing so, it contributes to the optimization of energy efficacy and the ultimate quality of steel produced in these furnaces. In conclusion, this review identifies gaps in existing knowledge and offers valuable recommendations for improving mathematical process models, underscoring the continuous efforts to enhance the efficiency, sustainability, and environmental impact of steel production processes. In conclusion, several techniques aimed at enhancing both production rates and the quality of the melting process in EAF have been put forward.

CO2 Emissions and Macroeconomic Indicators: Analysis of the Most Polluted Regions in the World

There is no sector of the economy that is not dependent on the state of development of the energy sector. This sector produces a significant share of global CO2 emissions. Harmful CO2 emissions and greenhouse gas emissions accelerate global warming. Therefore, more and more countries are adopting a strategy for the transition to carbon-neutral energy. However, energy independence and economic competitiveness are closely linked. One cannot analyze them separately. Given these facts, we focused on conducting an econometric study of the impact of key macroeconomic indicators on the level of СО2 emissions into the air in the United States and the Asia-Pacific region as the regions with the largest СО2 emissions. The modeling was carried out using the method of a correlation–regression analysis with the subsequent construction of econometric models. The quality of the built econometric models was checked using the coefficient of determination and Fisher’s criterion. The sample of statistics was formed from all the available values of the World Bank’s annual indicators for the period 1970–2020. The findings achieved showed that: (i) The results of our study confirmed the dependence of СО2 emissions on macroeconomic factors such as GDP, exports and imports, the rate of inflation, and unemployment. It allows the governments of many countries to use research findings to diagnose, monitor, and forecast macroeconomic outcomes to reduce or maintain allowable СО2 emissions. (ii) Identifying and assessing economic losses from environmental pollution by СО2 emissions using econometric models will allow to ensure effective public environmental and economic policies aimed at reducing harmful СО2 emissions into the air. It may be regarded as the practical importance of our study.