There are many advantages of the hydropower industry, as an environmentally friendly resource, and also some challenges that need to be overcome to fully exploit this sustainable and renewable natural resource. The primary objective of this study is to find out the impact of hydropower factors and economic growth on the agriculture industry output among the EU27 nations within the time factor 1990 to 2021. Adopting the autoregressive distributed lag (ARDL), the findings show a significant positive effect could occur in agriculture industry growth of the European Union (EU13)-emerging economies using hydropower factors than in EU14-emerged economies. On one hand, among additional factors, economic growth and institutional quality contribute more positively to agriculture growth in EU13 economies than in EU14 economies. On the other hand, population density contributes more negatively to agriculture growth in EU13 economies than in EU14 economies. The findings show there can be a positive significant growth increase in the EU13 agriculture industry using fossil fuel output than in EU14 economies. The results show that growth could be sustained in the agricultural industry of the European nations by increasing the level of hydropower production as this will help in attaining sustainable development by the year 2030. This will therefore help in mitigating the effect of climatic changes due to environmental pollution. The projected calculations were seen to be reliable and valid and this was attested to by the three estimators used in the study (pooled mean group, mean group, and dynamic fixed effect). This study recommended that European nations could leverage hydroelectricity to achieve sustainable growth and development. The legislative arms of the government of these European nations should as well show more interest in green energy to achieve security and sustainable development in hydroelectricity production. Decision-makers in the EU nations should buttress more emphasis on sustainable means through which hydropower could be used to attain sustainable irrigation systems for the agriculture industry and thus minimize the demand for fossil fuels and reduce CO2-related emissions in the future tine ahead.
Attaining Sustainable Development Goals (SDGs) is important to control the adverse impacts of climate change and achieve sustainable development. Among the 17 SDGs, target 13 emphasizes enhancing urgent actions to combat climate-related changes. This target is also dependent on target 7, which advocates enhancing access to cheap alternative sustainable energy. To accomplish these targets, it is vital to curb the transport CO2 emissions (TCO2) which increased by approximately 80% from 1990 to 2019. Thus, this study assesses the role of transport renewable energy consumption (TRN) in TCO2 by taking into consideration transport fossil fuel consumption (TTF) and road infrastructure (RF) from 1970 to 2019 for the United States (US) with the intention to suggest some suitable mitigation policies. Also, this study assessed the presence of transport environmental Kuznets curve (EKC) to assess the direction of transport-induced growth. The study used the Bayer-Hanck cointegration test which utilizes four different cointegration techniques to decide cointegration along with the Gradual Shift causality test which considers structural shift and fractional integration in time series data. The long-run findings of the Dynamic Ordinary Least Squares (DOLS) test, which counters endogeneity and serial correlation, revealed that the transport renewable energy use mitigates as well as Granger causes TCO2. However, transport fossil fuel usage and road infrastructure enhance TCO2. Surprisingly, the transport EKC is invalid in the case of the US, and increased growth levels are harmful to the environment. The association between TCO2 and economic growth is similar to a U-shaped curve. The Spectral Causality test revealed the growth hypothesis regarding transport fossil fuel use and economic growth connection, which suggests that policymakers should be cautious while decreasing the usage of transport fossil fuels because it may hamper economic progress. These findings call for revisiting growth strategies and increasing green energy utilization in the transport sector to mitigate transport emissions.
We employ the new Method of Moments Quantile Regression approach to expose the role of natural resources, renewable energy, and globalization in testing Environment Kuznets Curve (EKC) in MINT panel covering the years 1995-2018. The outcome validates the EKC curve between economic progress and carbon emissions from the third quantile to the extreme highest quantile. The result also shows that natural resources increase CO2 emissions at the lowest quantile and then turn insignificant from the middle to the highest quantiles due to the potential utilization of resources in a sustainable manner. The renewable energy mitigates CO2 emissions at the lower half quantiles. Still, for upper quantiles, the results are unexpected and imply that the countries' total energy mix depends heavily on fossil fuels. As far as globalization is concerned, the significant results from medium to upper quantiles reveal that as globalization heightens due to foreign direct investment or trade, energy consumption also expands, leading to the worst environment quality. Thus, the present study's consequences deliver guidelines for policymakers to utilize natural resources sustainably and opt technologies based on clean energy, which may offset environmental degeneration.
Global economies have recently been concerned about sustainable environmental management by reducing emissions and tackling ecological footprints. The rapid economic expansion and investment in traditional manufacturing further raises environmental degradation. China surpasses other emerging economies in the economic growth race yet has remained the top pollution-emitting economy for the last few decades, necessitating scholarly attention. This study examines the influencing factors of ecological footprints in China from the perspective of COP27. Using the extended dataset from 1988 to 2021, this study uses several time series diagnostic tests and verifies the existence of the long-run association between the study variables. Consequently, the non-linear scattered data leads to non-parametric (method of moment quantile regression) adoption. The empirical results indicate that only economic growth is a significant factor in environmental quality degradation in China. However, improving renewable energy usage, research and development, and foreign direct investment reduces the country's ecological footprint. Hence, the latter variables substantially lead to environmental sustainability. The robustness of the results is confirmed via a robust non-parametric estimator and causality test. Based on the empirical results, this study recommends increased investment in research and development, renewable production, and foreign direct investment enhancement.
The energy profile of India is dominated by fossil fuels, which create concerns over resource and environmental sustainability as fossil fuels are non-renewable and high carbon emitting. This scenario has necessitated the call for more renewables to replace fossil fuels to address resource and environmental sustainability concerns. This study, therefore, investigates the possibility of switching the fossil fuels of oil, coal, and natural gas for renewable energy in India. Using annual Indian data spanning more than four decades, a transcendental logarithmic production function based on a second-order Taylor Series approximation is estimated with the ridge regression technique. To achieve robustness, two equations with gross domestic product and adjusted net savings as regressands are estimated to proxy economic growth and sustainable development, respectively. The empirical results show substantial substitution possibilities between the fuels for both gross domestic product and adjusted net savings equations. The empirical findings show that India has the capacity to satisfy its energy needs through renewables to pursue not only economic growth but sustainable development. To actualize this potential, the Indian government should promote investment in renewables as this also promotes economic growth and development.
Extensive theoretical and empirical evidence supports the crucial role of savings in driving a nation's economic growth and development. However, previous studies have not considered their potential environmental implications. This study aims to explore the influence of savings and remittances on the Developing-8 countries (D-8) from 1989 to 2019, using the panel autoregressive distributed (ARDL) model. The findings reveal that national savings and remittances, in the long run, help mitigate environmental degradation in the D-8 countries but energy use and population growth stimulate carbon dioxide (CO2) emissions. In contrast, economic growth does not significantly affect these countries' environmental quality in the long run. However, none of the explanatory variables have any significant relationship with CO2 emissions in the short run. Therefore, policymakers in the D-8 countries are strongly encouraged to prioritize the enhancement of national savings across the three economic agents to maximize the positive effects of savings on environmental quality. Government savings can be increased by reducing deficits and borrowings, while corporate savings can be encouraged by implementing investment tax credits and promoting research and development. Additionally, governments can embark on public enlightenment campaigns on financial education and provide incentives to encourage household savings.
This study aims to investigate the relationship between renewable energy and ecological footprint during the period of 1994-2018 from selected developing countries in Europe (Czechia, Croatia, Poland, Romania, Romania, and Turkey). In this context, the ecological footprint (EF), which has recently been the most widely used environmental indicator in the literature and is known as the most comprehensive because it includes many environmental factors, has been determined as the dependent variable. As independent variables, renewable energy consumption (REC), energy-related tax revenue (ETR), and energy productivity (EP) are included in the model. GDP and development of environment-related technologies (DET), which affect the ecological footprint in the model, are determined as control variables. As a result of the panel data analysis, according to the Durbin-Hausman cointegration test result, a long-term relationship between the variables was determined. According to the CCE estimator analysis, it can be said that there is a positive relationship between ETR and GDP variables and EF. For the AMG estimator analysis, it can be said that there is a positive relationship between GDP and EP variables and EF. Finally, according to the results of the Konya Causality test, a unidirectional causality relationship is detected from environmental technologies to the ecological footprint in Turkey, and a unidirectional causality relationship from the ecological footprint to GDP in Czechia, Romania, and Turkey. Furthermore, no causality relationship is detected between other variables. Based on the results, several policy implications are suggested.
Advances in financial inclusions have contributed to economic growth and poverty alleviation, addressing environmental implications and implementing measures to mitigate climate change. Financial inclusions force advanced countries to progress their policies in a manner that does not hinder developing countries' current and future development. Consequently, this research examined the asymmetric effects of information and communication technology (ICT), financial inclusion, consumption of primary energy, employment to population ratio, and human development index on CO2 emissions in oil-producing countries (UAE, Nigeria, Russia, Saudi Arabia, Norway, Kazakhstan, Kuwait, Iraq, USA, and Canada). The study utilizes annual panel data spanning from 1990 to 2021. In addition, this study investigates the validity of the Environmental Kuznets Curve (EKC) trend on the entire sample, taking into account the effects of energy consumption and population to investigate the impact of financial inclusion on environmental degradation. The study used quantile regression, FMOLS, and FE-OLS techniques. Preliminary outcomes revealed that the data did not follow a normal distribution, emphasizing the need to use quantile regression (QR). This technique can effectively detect outliers, data non-normality, and structural changes. The outcomes from the quantile regression analysis indicate that ICT consistently reduces CO2 emissions in all quantiles (ranging from the 1st to the 9th quantile). In the same way, financial inclusion, and employment to population ratio constrains CO2 emissions across each quantile. On the other side, primary energy consumption and Human development index were found to increase CO2 emissions in each quantile (1st to 9th). The findings of this research have implications for both the academic and policy domains. By unraveling the intricate interplay between financial inclusion, ICT, and environmental degradation in oil-producing nations, the study contributes to a nuanced understanding of sustainable development challenges. Ultimately, the research aims to guide the formulation of targeted policies that leverage financial inclusion and technology to foster environmentally responsible economic growth in oil-dependent economies.
High conversion ratio dc-dc converters have received significant attention in renewable energy systems, primarily due to their necessary high-gain characteristics. This research proposes a high step-up ratio full-bridge resonant cascaded (FBRC) dc-dc converter designed for use in photovoltaics (PV), fuel cells (FC), electric vehicles (EV), and other low-voltage output energy sectors to achieve high voltage gain. This converter contains a full-bridge cell with a boost input inductor, a diode-capacitor cascaded stage that replaces the transformer as a voltage multiplier and an inductor-capacitor (LC) parallel-series resonant network across the FB terminal. One of the strategic features of the converter is its high voltage step-up characteristic combined with lower duty cycle operation that limits the maximum current through the active devices, making it particularly suitable for systems that generate low output voltage. In addition, zero-voltage switching (ZVS) is achieved during the turn-off and turn-on operation of the FB switches from 25% to full load, thereby lessening the switching losses. Moreover, the diminished necessity for passive components and the decreased voltage stress on both active and passive devices lead to the use of smaller and more cost-effective components. The theoretical analysis of the proposed converter is validated using a 500 W laboratory-scale prototype wherein high-performance SiC-based MOSFETs have been utilized as switching devices. It offers reduced ripples, with input current ripple at 5% and output voltage ripple at 0.76%. When the load is 400 W and 60 V as the input voltage, the maximum efficiency is found 95.8% at 400 V output voltage. The proposed dc-dc converter, with its high voltage gain and reduced component stress, shows significant promise for application in renewable energy systems.
Energy is an indispensable factor for the economic growth and development of a country. Energy consumption is rapidly increasing worldwide. To fulfill this energy demand, alternative energy sources and efficient utilization are being explored. Various sources of renewable energy and their efficient utilization are comprehensively reviewed and presented in this paper. Also the trend in research and development for the technological advancement of energy utilization and smart grid system for future energy security is presented. Results show that renewable energy resources are becoming more prevalent as more electricity generation becomes necessary and could provide half of the total energy demands by 2050. To satisfy the future energy demand, the smart grid system can be used as an efficient system for energy security. The smart grid also delivers significant environmental benefits by conservation and renewable generation integration.
In recent years, renewable energy sources have been considered the most encouraging resources for grid and off-grid power generation. This paper presents an improved current control strategy for a three-phase photovoltaic grid-connected inverter (GCI) under unbalanced and nonlinear load conditions. It is challenging to suppress the harmonic content in the output current below a pre-set value in the GCI. It is also difficult to compensate for unbalanced loads even when the grid is under disruption due to total harmonic distortion (THD) and unbalanced loads. The primary advantage and objective of this method is to effectively compensate for the harmonic current content of the grid current and microgrid without the use of any compensation devices, such as active and passive filters. This method leads to a very low THD in both the GCI currents and the current exchanged with the grid. The control approach is designed to control the active and reactive power and harmonic current compensation, and it also corrects the system unbalance. The proposed control method features the synchronous reference frame (SRF) method. Simulation results are presented to demonstrate the effective performance of the proposed method.
A combination between the nanostructured photocatalyst and cellulose-based materials promotes a new functionality of cellulose towards the development of new bio-hybrid materials for various applications especially in water treatment and renewable energy. The excellent compatibility and association between nanostructured photocatalyst and cellulose-based materials was induced by bio-combability and high hydrophilicity of the cellulose components. The electron rich hydroxyl group of celluloses helps to promote superior interaction with photocatalyst. The formation of bio-hybrid nanostructured are attaining huge interest nowadays due to the synergistic properties of individual cellulose-based material and photocatalyst nanoparticles. Therefore, in this review we introduce some cellulose-based material and discusses its compatibility with nanostructured photocatalyst in terms of physical and chemical properties. In addition, we gather information and evidence on the fabrication techniques of cellulose-based hybrid nanostructured photocatalyst and its recent application in the field of water treatment and renewable energy.
The power system always has several variations in its profile due to random load changes or environmental effects such as device switching effects when generating further transients. Thus, an accurate mathematical model is important because most system parameters vary with time. Curve modeling of power generation is a significant tool for evaluating system performance, monitoring and forecasting. Several numerical techniques compete to fit the curves of empirical data such as wind, solar, and demand power rates. This paper proposes a new modified methodology presented as a parametric technique to determine the system's modeling equations based on the Bode plot equations and the vector fitting (VF) algorithm by fitting the experimental data points. The modification is derived from the familiar VF algorithm as a robust numerical method. This development increases the application range of the VF algorithm for modeling not only in the frequency domain but also for all power curves. Four case studies are addressed and compared with several common methods. From the minimal RMSE, the results show clear improvements in data fitting over other methods. The most powerful features of this method is the ability to model irregular or randomly shaped data and to be applied to any algorithms that estimating models using frequency-domain data to provide state-space or transfer function for the model.
It is well documented that carbon emissions can be reduced by replacing conventional energy resources with renewable energy resources; thereby, the role of green technology is essential as it protect natural environment. Given that, the United Nations' agenda of "green is clean" may be achievable by adoption of green technologies. The objective of the study is to examine the link between information and communication technology (ICT), economic growth, energy consumption, and carbon dioxide (CO2) emissions in the context of South Korean economy, by using a novel Morlet wavelet approach. The study applies continuous wavelet power spectrum, the wavelet coherency, and the partial and the multiple wavelet coherency to the year during 1973-2016. The outcomes reveal that the connections among the stated variables progress over frequency and time domain. From the frequency domain point of view, the current study discovers noteworthy wavelet coherence and robust lead and lag linkages. From the time-domain sight, the results display robust but not consistent associations among the considered variables. From an economic point sight, the wavelet method displays that ICT helps to reduce environmental degradation in a medium and long run in the South Korean economy. This emphasizes the significance of having organized strategies by the policymakers to cope up with 2 to 3 years of the occurrence of the huge environmental degradation in South Korea.
Given the economic growth and energy consumption patterns, most countries are striving to solve the problems of CO2 emissions reduction to achieve sustainable development. This paper employs an improved DEA model to measure energy and environmental efficiency for some selected countries in central and western Europe. In addition, the DEA window evaluation technique is applied to measure cross-sectional efficiency using two inputs (energy consumption, labor force), a desirable output (gross domestic product), and an undesirable output (CO2 emission) for the period from 2010 to 2014. The study finds that the UK ranks the highest position in term of energy and environmental efficiency. This shows that the UK has more effective policies regarding energy efficiency, consumption, production, import and energy intensity measures for sustainable economic growth as well as environmental protection. Ireland is the second-best country after the United Kingdom. The efficiency scores of the two countries are 0.99 and 0.89 respectively. On the empirical outcomes, this study suggests effective reforms in energy sector for countries with less energy efficiency that are still facing the problem of environmental degradation.
Energy consumption is an important part of life today because without the power a work cannot be done. The energy used today will be lost or waste without renewable energy or power recycle back. In reality, energy use has always had a noticeable impact on the environment. Overconsumption of energy is the main trigger for the global warming that is now threatening to cause devastation in many areas of the world. Each year, electricity consumption in Malaysia is always an increase. This can contribute to the occurrence of global warming. This project will be designed for renewable energy or recycle power to avoid waste of energy from lost. Also, this project consider regarding the Green Technology without polluting the environment. The objective is to develop a prototype or hardware that aims to renewable energy using the 12V DC Motor as a generator which is use rear shaft of table fan as a medium to drive the 12V DC Motor and also to analyze the power consumption of table fan before and after install with hardware. The methods used to design the connector and DC motor holder is using a solidwork software, then construct the circuit simulation using a proteus software and also use a microcontroller PIC16F877A as a controller. The result obtained from the testing and experiments by integrating the hardware part, electrical part and software part. Finally, with the development of a power recycling prototype for renewable energy using DC Motor application, the wasted energy can be reused from conversion to other energy and energy can be used as renewable energy.
Greenhouse gasses have adverse effects on global warming and air pollution and need to be optimized by minimizing the contributing factors. This work analyzes the effects of economic growth and energy resources (renewable and nonrenewable) on the emissions of greenhouse gasses (GHG). A 2000-2016 panel data from 25 developing Asian countries is analyzed through a robust Random Effect (RE) approach and Hausman Taylor Regression (HTR). Findings show a positive correlation between economic growth and energy consumption, while a 1% increase in renewable energy consumption results in a 0.193% decrease in carbon emissions. Economic growth and renewable energy are positively correlated in both the short and long term, which implies a valid feedback hypothesis. The findings indicate the significant contribution of nonrenewable energy resources to greenhouse gas emissions and the positive impact of renewable resources on greenhouse gas emissions' control. Furthermore, this study highlights the potential of developing Asian economies to preserve the environment through more robust regional environmental policies and renewable energy resources. In light of this study's findings, policymakers in Asian developing economies should develop policies on Renewable Energy infrastructure (RE) to improve GDP and reduce greenhouse gas emissions.
Southeast Asian countries stand at a crossroads concerning their shared energy future and heavily rely on fossil fuels for transport and electricity. Within Asia, especially India and China lead the world renewable energy generation undergoing a period of energy transition and economic transformation. Southeast Asian countries have huge potentials for sustainable energy sources. However they are yet to perform globally in renewable energy deployment due to various challenges. The primary objective of the study is to examine the renewable energy growth and analyse the government policies to scale up the deployment of renewables for power generation substantially. The study also offers policy recommendations to accelerate renewable energy exploitation sustainably across the region. To achieve the ambitious target of 23% renewables in the primary energy mix by 2025, ASEAN Governments should take proactive measures like removal of subsidies of fossil fuels, regional market integration and rapid implementation of the existing project. Eventually, each of this strategy will necessitate sustained leadership, political determination, and concrete actions from stakeholders, in particular, increased cooperation across the region.
This study analyzes the relationship between globalization, energy consumption, and economic growth among selected South Asian countries to promote the green economy and environment. This study also finds causal association between energy growth and nexus of CO2 emissions and employed the premises of the EKC framework. The study used annual time series analysis, starting from 1985 to 2019. The data set has been collected from the World Development Indicator (WDI). The result of a fully modified ordinary least square (FMOLS) method describes a significantly worse quality environment in the South Asian region. The individual country as Bangladesh shows a positively significant impact on the CO2 emissions and destroys the level of environment regarding non-renewable energy and globalization index. However, negative and positive growth levels (GDP) and square of GDP confirm the EKC hypothesis in this region. This study has identified the causality between GDP growth and carbon emission and found bidirectional causality between economic growth and energy use.
The Southeast Asian countries have experienced significant degrees of economic growth over the years but have not managed to safeguard their environmental attributes in tandem. As a result, the aggravation of the environmental indicators across this region casts a shadow of doubt on the sustainability of the economic growth achievements of the Southeast Asian countries. Against this milieu, this study specifically explores the influence of renewable electricity generation capacity, technological innovation, financial development, and economic growth on the ecological footprints in five Southeast Asian countries namely Indonesia, Malaysia, the Philippines, Thailand, and Vietnam during the period 1985-2016. One of the major novelties of this study is in terms of its approach to assess the renewable energy use-ecological footprint nexus using the renewable electricity generation capacity as an indicator of renewable energy use in the selected Southeast Asian nations. The econometric analysis involves methods that are robust to handling cross-sectional dependency and slope heterogeneity issues in the data. Accordingly, the recently developed Cross-sectional Augmented Autoregressive Distributed Lag estimator is used to predict the short- and long-run impacts on ecological footprints. The major findings suggest that higher renewable electricity generation capacity and technological innovation reduce ecological footprints, while higher financial development and economic growth increase the ecological footprints. Therefore, these findings imply that in forthcoming years, the selected Southeast Asian countries will need to tackle the environmental adversities by enhancing their renewable electricity generation capacities, increasing investment in technological development, greening the financial sector, and adopting environmentally-friendly growth policies. Hence, the implementation of relevant policies, in this regard, can be expected to ensure complementarity between economic growth and environmental welfare across Southeast Asia.