Drivers of environmental degradation in Turkey: Designing an SDG framework through advanced quantile approaches

Turkey is a laggard in terms of the achievement of its Sustainable Development Goals (SDGs), and one of the primary issues it faces is environmental deterioration. Therefore, a policy-level reorientation may be needed to address this relevant issue. From this standpoint, this research assesses the impact of renewable energy (RE) use and financial development on the emissions of CO2 as well as the role of urbanization and agriculture, utilizing a dataset stretching between 1985 and 2019. By applying the innovative quantile-on-quantile regression (QQR) and non-parametric Granger causality in quantiles techniques, the study assesses the ways in which the quantiles of the independent variables affect the quantiles of CO2 emissions. The outcomes from the QQR show that in all quantiles, financial development, economic growth, urbanization, and agriculture impact CO2 emissions positively, while in the middle quantiles, the influence of renewable energy use on CO2 is negative. Furthermore, the outcomes from the non-parametric Granger causality test disclosed that in mean and variance, all the variables could predict CO2 emissions at different quantiles. A complete SDG-oriented policy framework has been proposed based on the research’s findings so that Turkey may move toward reaching its SDG 13 and SDG 7 targets

The Environmental Aspects of Renewable Energy Consumption and Structural Change in Sweden: A new perspective from wavelet-based granger causality approach

The current paper assessed the time-frequency analysis interrelationship between CO2 emissions and financial development, economic growth, renewable energy use, structural change, and non-renewable energy use in Sweden. We utilized a quarterly dataset stretching from 1980-2019. In order to unlock these interrelationships, we leverage wavelet tools (wavelet-based Granger causality and wavelet coherence). The wavelet-based Granger causality (WGC) test accounts for the issue of multiple time scales in a time series analysis. Another uniqueness of the WGC lies in its resistance to distribution assumption and misspecification in a time series model. Additionally, the wavelet coherence estimator instantaneously evaluates correlation and causality among the interacting indicators in a model. The outcomes of the wavelet coherence exposed that renewable energy, financial development, economic growth, structural change, and trade openness enhance the environment\u27s quality while nonrenewable energy intensifies CO2. Moreover, the WGC shows that all the variables can predict each other. Based on these findings, policymakers in Sweden should focus more on improving public understanding of renewable energy and environmental preservation. We believe that Sweden\u27s shift to service-sector-led growth will help to safeguard the environment

Dynamic Effect of Disintegrated Energy Consumption and Economic Complexity on Environmental Degradation in Top Economic Complexity Economies

The current paper explores the influence of disintegrated energy and economic complexity on CO2 emissions (CO2) in the top economic complexity economies. The model also incorporates other drivers of CO2, such as technological innovation and economic growth. The current research utilizes data stretching from 1993 to 2018. The research employed Westerlund cointegration, fully modified OLS (FMOLS), dynamic OLS (DOLS), and method of moments quantile regression (MMQR) to evaluate these interconnections. The outcomes of the slope heterogeneity and cross-sectional dependence affirmed the use of second-generation techniques. The study confirmed the long-run association between CO2 and the regressors. The results of the MMQR disclosed that in each quantile (0.1–0.90), renewable energy enhances the quality of the environment, while economic complexity and nonrenewable energy intensify CO2. In addition, technological innovation enhances the quality of the environment from 0.1– 0.70 quantiles, while from 0.80–90 quantiles, technological innovation intensifies CO2. The EKC is also validated in each quantile (0.1–0.90). The DOLS, FE-OLS, and FMOLS outcomes also affirm the MMQR outcomes. These outcomes encourage policymakers to implement holistic economic and environmental policies that prioritize greener production processes for environmental reasons and meet the United Nations SDGs 7, 8, 13, and 17

Does information and communication technology impede environmental degradation? fresh insights from non-parametric approaches

Although ICT has played a critical role in the socio-economic growth of human cultures, it has also brought with it significant environmental risks. Nevertheless, scholars remain divided on this topic; some believe that ICT has had a positive influence on the quality of the environment, while others believe that ICT has created major environmental issues. Hence, this research is another effort to assess the effects of ICT on CO2 emissions in the top 10 ICT nations (Denmark, Japan, Luxemburg, South Korea, Netherlands, Iceland, Norway, Sweden, Switzerland, and the United Kingdom) using a dataset from the period between 1986Q1 and 2019Q4. All prior studies have established symmetric association between ICT and CO2. As a result, we applied the novel non-parametric approaches (quantile-on-quantile regression and Granger causality in quantile) to assess this association. The findings from the QQR uncovered that in the majority of the quantiles, for Denmark, Japan, Luxemburg, Netherland, Norway, Sweden, United Kingdom and Switzerland, the effect of ICT on CO2 emissions is negative, while in the majority of the quantiles, the effect of ICT on CO2 emissions is positive for the Netherlands, South Korea, and Iceland. Furthermore, we applied the novel Granger causality in the quantiles approach and the outcomes provided evidence of bidirectional causality between CO2 emissions and ICT in all the selected nations. The study proposes that sustainable ICT should be used to improve carbon reduction and energy savings potential by optimizing other industries, including managing and monitoring energy usage

The dynamic impact of biomass and natural resources on ecological footprint in BRICS economies: A quantile regression evidence

Many emerging economies, including the BRICS economies, are having difficulty meeting the Sustainable Development Goals’ (SDGs) objectives. Consequently, this research discusses the creation of an SDG framework for the BRICS economies, which can be utilized as a model for other blocs. To achieve this purpose, this research probes into the effect of biomass energy usage on ecological footprint in the BRICS economies between 1992 and 2018, considering the roles of gross capital formation, natural resources, and globalization. The novel Methods of Moments-Quantile-Regression (MMQR) approach with fixed effects is used, the outcomes of which reveal that in all quantiles (10th to 90th), globalization and biomass energy use mitigate environmental degradation, whereas economic growth, natural resources, and gross capital formation contribute to environmental degradation. The present research applied a series of techniques such as panel FMOLS, and DOLS, FE-OLS, the outcomes of which disclosed that globalization and biomass energy utilization help mitigate environmental degradation, while economic growth, natural resources, and gross capital formation improve environmental degradation. On the basis of the study’s findings, we suggest a shift in energy policies away from fossil fuels toward renewable energy alternatives by taking measures regarding the innovation of biomass to improve conversion efficiency

Research Progress, Trends, and Current State of Development on PEMFC-New Insights from a Bibliometric Analysis and Characteristics of Two Decades of Research Output

The consumption of hydrogen could increase by sixfold in 2050 compared to 2020 levels, reaching about 530 Mt. Against this backdrop, the proton exchange membrane fuel cell (PEMFC) has been a major research area in the field of energy engineering. Several reviews have been provided in the existing corpus of literature on PEMFC, but questions related to their evolutionary nuances and research hotspots remain largely unanswered. To fill this gap, the current review uses bibliometric analysis to analyze PEMFC articles indexed in the Scopus database that were published between 2000-2021. It has been revealed that the research field is growing at an annual average growth rate of 19.35%, with publications from 2016 to 2012 alone making up 46% of the total articles available since 2000. As the two most energy-consuming economies in the world, the contributions made towards the progress of PEMFC research have largely been from China and the US. From the research trend found in this investigation, it is clear that the focus of the researchers in the field has largely been to improve the performance and efficiency of PEMFC and its components, which is evident from dominating keywords or phrases such as 'oxygen reduction reaction', 'electrocatalysis', 'proton exchange membrane', 'gas diffusion layer', 'water management', 'polybenzimidazole', 'durability', and 'bipolar plate'. We anticipate that the provision of the research themes that have emerged in the PEMFC field in the last two decades from the scientific mapping technique will guide existing and prospective researchers in the field going forward

A roadmap toward achieving sustainable environment: evaluating the impact of technological innovation and globalization on load capacity factor

Technological innovations have been a matter of contention, and their environmental consequences remain unresolved. Moreover, studies have extensively evaluated environmental challenges using metrics such as nitrogen oxide emissions, sulfur dioxide, carbon emissions, and ecological footprint. The environment has the supply and demand aspect, which is not a component of any of these indicators. By measuring biocapacity and ecological footprint, the load capacity factor follows a certain ecological threshold, allowing for a thorough study on environmental deterioration. With the reduction in load capacity factor, the environmental deterioration increases. In the context of the environment, the interaction between technological innovation and load capacity covers the demand and supply side of the environment. In light of this, employing the dataset ranging from 1980 to 2017 for the case of South Africa, the bound cointegration test in conjunction with the critical value of Kripfganz and Schneider showed cointegration in the model. The study also employed the ARDL, whose outcome revealed that nonrenewable energy usage and economic growth contribute to environmental deterioration, whereas technological innovation and globalization improve the quality of the environment. This study validated the hypothesis of the environmental Kuznets curve for South Africa, as the short-term coefficient value was lower than the long-term elasticity. Furthermore, using the frequency-domain causality test revealed that globalization and economic growth predict load capacity in the long term, and nonrenewable energy predicts load capacity factors in the long and medium term. In addition, technological innovation predicts load capacity factors in the short and long term. Based on the findings, we propose that policymakers should focus their efforts on increasing funding for the research and development of green technologie

Do renewable energy consumption and financial development contribute to environmental quality in MINT nations? Implications for sustainable development

Maintaining a balance between the well-being of the economy and the environment has become a top priority for governments globally. In the contemporary age, world economies, particularly the emerging ones like MINT nations, highlight the need for eco-friendly economic expansion. The MINT nations are thriving economically but are having difficulty reducing their Ecological footprint (EF). This paper aimed to determine if factors such as population density, renewable energy, foreign direct investment, economic growth, and financial development impact ecological footprint in the MINT countries between 1990 and 2018. The study applied ample advanced econometrics such as method of moments quantile regression (MMQR), augmented mean group (AMG) and Common Correlated Effects Mean Group (CCEMG). The overall results indicated that the variables are integrated at the first difference and are cointegrated. The AMG, CCEMG and MMQR results reveal that economic growth deteriorates ecological well-being by promoting the EF while foreign direct investment, population density and renewable energy assists in enhancing it by mitigating the EF in the MINT nations. In addition, financial development does not exert a significant effect on EF. The Dumitrescu Hurlin Panel Causality results show unidirectional causality from economic growth, financial development, population density, and renewable energy to EF. Based on these results policy recommendations are suggested

Role of Renewable Energy Consumption and Technological Innovation to Achieve Carbon Neutrality in Spain: Fresh Insights From Wavelet Coherence and Spectral Causality Approaches

This research offers a new perceptive of the dynamic connection between CO2 and globalization, technological innovation (TI), economic growth, and renewable energy (REN) consumption in Spain. The current research applied the wavelet tools to assess these interconnection utilizing data stretching from 1980 to 2018. The outcomes of these analyses disclose that the association among the series evolves over frequency and time. The current analysis uncovers notable wavelet coherence and strong lead and lag connections in the frequency domain, whereas the time domain indicates inconsistent correlations among the variables of interest. The outcomes of the wavelet analysis from the economic perspective affirm that in the short and medium term, globalization, economic growth, and TI contribute to environmental degradation; however, in the long term, globalization, economic growth, and TI do not contribute to the degradation of the environment. Moreover, at different frequencies, REN consumption helps mitigate environmental degradation in Spain. Furthermore, the spectral causality test unveiled that in the long term, REN utilization, globalization, TI, and economic growth can predict CO2 emissions in Spain. Copyright © 2021 Zhao, Ramzan, Adebayo, Oladipupo, Adeshola and Agyekum.This research was funded by the School of International Trade and Economics, Shandong University of Finance and Economics, 250014, Jinan, Shandong, China

An Adaptive Protection Scheme Based on a Modified Heap-Based Optimizer for Distance and Directional Overcurrent Relays Coordination in Distribution Systems

This paper proposes an adaptive protection scheme (APS) based on the original heap-based optimization (HBO) and a modified HBO (MHBO). APS is used to solve protection relays coordination problems that include directional overcurrent relays (DOCRs) as well as the distance relay’s second zone times. The complexity of the coordination problem increases with the impact of distributed generators (DGs) switching (ON/OFF). Topological changes in grid configuration frequently occur in distributing networks, equipped with DGs, causing changes in the values and direction of short circuit currents. This issue becomes a challenge for protection systems to avoid relays miscoordination and save a network’s reliability. In the proposed MHBO, the Original HBO is modified by three points, population are divided into subgroups, then they are unified into one group gradually, those subgroups are exchanging some search agents between themselves, these search agents are called travelling agents, and the last one is about, upgrading an internal equation in the original algorithm. For validating the proposed relays coordination, the IEEE 8-bus test system, and the IEEE 14-bus distribution network are selected as case studies. The obtained simulated results of the proposed algorithm show better performance compared with those obtained by the previous algorithms