Publications by authors named "Radulescu Magdalena"

This study investigates the impact of Bitcoin's energy and water consumption on environmental sustainability, focusing on the load capacity factor (LCF) and the roles of energy transition green technology in major cryptocurrency-producing nations. Utilizing the method of moments quantile regression (MMQR) approach, the findings reveal a negative impact of mining energy consumption on environmental sustainability, particularly in the lower quantiles, with a stronger negative effect in the higher quantiles. Energy transition plays a critical role in moderating this impact, though the shift towards cleaner energy sources has not been sufficient to mitigate the adverse environmental effects.

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This study aims to examine the landscape transformation and temperature dynamics using multiple spectral indices. The processes of temporal fluctuations in the land surface temperature is strongly related to the morphological features of the area in which the temperature is determined, and the given factors significantly affect the thermal properties of the surface. This research is being conducted in Pakistan to identify the vegetation cover, water bodies, impervious surfaces, and land surface temperature using decadal remote sensing data with four intervals during 1993-2023 in the Mardan division, Khyber Pakhtunkhwa.

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Sustainable development constitutes a comprehensive framework that integrates various economic, social, and environmental dimensions. Within this paradigm, the environmental aspect assumes particular prominence. In this context, we focus on the relationship between pro-environmental policies and sustainable development in China, the world's largest polluter.

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China and the United States have the highest demand for fossil fuel energy for transportation and power generation, which promotes growth while also damaging the environment. Policymakers, and environmental scientists, are increasingly interested in understanding key strategies to improve energy efficiency to mitigate fossil fuel energy demand and sustain the environment and growth. In this context, this study uses augmented mean groups (AMG) and common correlated effects mean group (CCEMG) estimators to reveal the impact of China-US technological innovation, transportation infrastructure, and power generation on fossil fuel energy demand and fossil fuel energy intensity from 1995 to 2020.

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The world is facing crucial challenges such as environmental degradation, social inequality, and slow economic growth due to the current transformative era. These challenges constitute a significant barrier to unlocking the world's full potential. In response, green growth has emerged as a focal point in global discourse due to the pivotal shift of legislators and researchers from conventional economic growth to sustainable and green growth.

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Successfully integrating renewable energy sources depends on eco-friendliness, financial technology, and economic growth (GDP). This paper examines the dynamic effect of innovative financial and green technology on renewable energy for 38 emerging economies from 2006 to 2021. Using the dynamic First-difference Generalized Method of Moments (FD-GMM) model, the analysis identifies a critical GDP threshold of 1831.

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Free movement of production factors in the enlarged EU has led to immigration flows from East to West and from South to North with a significant impact on EU labor markets. Fiscal federalism also determined large immigration flows into EU area and affected unemployment rate in the EU countries. The aim of this paper is to investigate the impact of factors such as number of immigrants, tax on profits, social contributions, economic growth and population growth on unemployment rates in EU area using a panel quantile regression and an PMG-ARDL approach as robustness test during 1991-2020.

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This paper is the first comprehensive research to examine the effect of circular economy on environment employing two environmental degradation indicators (CO emissions, ecological footprint) and one environmental quality indicator (load capacity factor) for 57 Belt and Road Initiative (BRI) countries during 2000-2019. The effect of other variables such as renewable energy, industrialization, and globalization was also controlled. The study applied the cross-sectional autoregressive distributed lag method (CS-ARDL), the augmented mean group (AMG), and common correlated effects mean group (CCEMG) methods as a robustness checks.

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This article investigates the dynamic impact of green energy consumption (GE), financial inclusion (FI), and military spending (MS) on environmental sustainability (ES) by utilizing a sample of 121 countries from 2003 to 2022. The dataset is divided into high-income, upper-middle income and low and lower-middle-income countries. We employed a two-step system GMM approach, which was further robust through panel Quantile and Driscoll-Kraay (D-K) regressions.

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This study analyses the impact of GDP per capita, domestic credit, savings, and population on the environment in Pakistan from 1995 to 2019. The country has consistently been ranked eighth, fifth, and eight as an environmentally vulnerable nation from 1998 to 2017, 1999 to 2018, and 2000 to 2019, respectively. Therefore, the study explores the role of environmental awareness as a potential strategy for making peace with nature.

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This paper evaluates the impact of the National Renewable Energy Action Plans (NREAP) that was prepared under the (2009/28/EC) Directive of the European Commission by using Türkiye as a case study. We aimed to reveal the causal impacts of the plan on renewable energy generation based on different technologies such as hydro, wind, and solar, along with the impacts on greenhouse gas emissions. To do this, we used the synthetic control method.

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Smart, secure, and environmentally friendly smart cities are all the rage in urban planning. Several technologies, including the Internet of Things (IoT) and edge computing, are used to develop smart cities. Early and accurate fire detection in a Smart city is always desirable and motivates the research community to create a more efficient model.

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Understanding the complex interactions between the economy and the environment is crucial for promoting sustainable development and mitigating the negative impact of human activities on the Planet. The importance of this issue for Serbia is evident as the country strives to balance economic growth and environmental protection to ensure a sustainable and resilient future. Therefore, the main objective of this study is to investigate and model the relationship between CO emissions, economic growth, electricity consumption, and trade openness in Serbia.

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This article investigates the performance of three models - Autoregressive Integrated Moving Average (ARIMA), Threshold Autoregressive Moving Average (TARMA) and Evidential Neural Network for Regression (ENNReg) - in forecasting the Brent crude oil price, a crucial economic variable with a significant impact on the global economy. With the increasing complexity of the price dynamics due to geopolitical factors such as the Russo-Ukrainian war, we examine the impact of incorporating information on the war on the forecasting accuracy of these models. Our analysis shows that incorporating the impact of the war can significantly improve the forecasting accuracy of the models, and the ENNReg model with the inclusion of the dummy variable outperforms the other models during the war period.

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The main objective of this study is to examine the impacts of green energy and public investment on the CO2 emissions in North Africa. Moreover, the study also tests the existence of the N-shaped Environmental Kuznets Curve (EKC) hypothesis for North African countries between 1995 and 2018. These factors were analyzed using the Dynamic Ordinary Least Squares (DOLS), Fully Modified Ordinary Least Squares (FMOLS), and Pooled Mean Group (PMG) estimators to obtain estimations of heterogeneous parameters.

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Pollution and energy crisis are actual issues in Europe, including the EU Central and Eastern European states. In this context, the objective of this paper is to assess the impact of economic growth and electricity prices for non-household consumers on pollution. The empirical findings reveal the U pattern for energy industry and inverted U pattern for manufacturing in the period 2007-2021 in the EU countries from Central and Eastern Europe.

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This study aims to demonstrate the impact of renewable energy consumption (REC) on environmental degradation using the EKC hypothesis testing for the BRIC and G-7 countries. Two EKC models were created and tested, with Model 2 including REC and other independent variables such as economic freedom (EF) and economic policy uncertainty (EPU), which affect the level of renewable energy consumption and CO emissions. Empirical findings indicate that the EKC hypothesis is verified faster in the REC-EF-EPU-based EKC model (Model 2) than in the EF-EPU-based EKC model (Model 1) for G-7 countries since the turning point takes place earlier in Model 2 than in Model 1 with REC.

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Due to global and regional climatic dynamics for a couple of decades, agricultural productivity, rural livelihood, and food security have been badly affected in Pakistan. This study was conducted in Punjab, Pakistan, to explore the farmers' understanding of the impacts of climate change, adaptation strategies, determinants, and benefits on agriculture using data from 1080 respondents. Perceived risks by the farmers in the rice-wheat cropping system and the cotton-wheat cropping system were weed infestation, seed rate augmented, low-quality seeds, infestation of crop diseases and pests, change of cropping pattern, increase of input use, decrease of cropping intensity and productivity, decreasing soil fertility, increasing irrigation frequency, and increase of harvesting time.

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This study investigates the impact of environmental technological innovation, economic complexity, energy productivity, the use of renewable electricity generation, and environmental taxes on carbon dioxide (CO) emissions in the G-10 countries for the timeframe from 1995 to 2020. The purpose of the study is to examine the need for a clear plan or strategy to achieve environmental objectives in G-10 countries. In both short-term and long-term projections, the increased use of environment-based technology, economic complexity, and renewable electricity generation has a major positive impact on carbon emission reduction.

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Pollution, war and energy crisis are the CEE countries' most important global actual issues. Therefore, this study aims to investigate the impact of political stability and electricity price in 11 CEE countries in the period 2007-2021 to anticipate the effect of these factors on pollution in times of political and energy crisis. The common results based on DOLS/FMOLS and CCEMG estimations indicate that political stability enhances CO2 emissions, while higher electricity prices for non-household consumers reduce pollution.

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The renewable energy consumption plays a significant role in achieving sustainable development, but a sectoral approach is necessary to design the better recommendations for each sector. In this context, the main objective of this paper is to assess the impact of the use of this type of energy on economic growth in 23 European Union (EU) member states in the period 1990-2020. Besides overall renewable energy consumption, different utilisations of this energy are considered: in industry, transport, in commercial and public services, and for residential purposes.

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As a result of a greater worldwide aspiration for wealth and economic progress, increased use of natural resources for diverse industries resulted in increased pollution emissions, mainly carbon dioxide. Energy security, economic stability, job security, biodiversity loss, climate change, and global warming all require reconciliation and resolution now, more than ever before. This paper explores the causal relationship between CO emissions, economic growth, available energy, and employment for a panel of eight South-Eastern European countries from 1995 to 2019.

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The deployment of energy sources is considered the compassion of several United Nations Sustainable Development Goals (SDGs). Countries should keep balance with the three major proportions of the global energy trilemma: energy security, affordability, energy access, and ecological balance to construct a solid basis for competitiveness and prosperity. In this regard, this study examines the influence of nuclear energy, technological innovations, renewable energy, non-renewable energy, and natural resources on carbon footprint in the highest nuclear energy-producing countries from 1990 to 2019.

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This study empirically estimates the impact of clean and non-clean energy consumption on economic growth and carbon dioxide emissions within the framework of the environmental Kuznets curve and pollution haven hypothesis in the case of PIMC countries from 1980 to 2019. The results of the panel cointegration test proposed by Westerlund (2007) show a long-term equilibrium relationship among the variables of each designated model. The long-term elasticities of economic growth and carbon emission estimated by AMG, CCEMG, and MG estimators indicate that both clean and non-clean energy consumption has a significant impact on economic growth, while carbon emission hinders growth.

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