Shifting from techno-economic to socio-ecological priorities: Incorporating landscape preferences and ecosystem services into the siting of renewable energy infrastructure.

This study examines the siting scenarios for renewable energy installations (REI) in a mountainous region of Europe (Switzerland), incorporating the external costs of ecosystem services and, innovatively, social preferences. This approach challenges the prevalent techno-economic siting paradigm, which often overlooks these externalities. To minimize the external costs of the scenarios while maximizing energy yield, Marxan, an optimization software, was employed. The energy target for all scenarios is set at 25 TWh/a, stemming from the energy gap anticipated due to the phase-out of Swiss nuclear reactors by 2050. This target is met using renewable energy infrastructure such as wind, roof-mounted photovoltaic, and ground-mounted photovoltaic systems. By integrating social preferences into the optimization, this study showcases a promising implementation that transcends the software's intended applications. It complements techno-economic approaches and offers alternative decision-making avenues. The conventional "roof first" strategy proved ineffective in preventing extensive land use for the development of new renewable energy infrastructure. Strategies incorporating ground-mounted photovoltaic infrastructure were more spatially, ecologically, and socially efficient than those without. The strategy optimized for energy yield exhibited the highest spatial efficiency but incurred significant ecosystem service costs and, surprisingly, had low social costs. In contrast, the strategy prioritizing ecosystem services was the most efficient in terms of ecosystem service costs but had elevated social costs and was spatially less efficient than other strategies. The strategy optimized for social preferences incurred the lowest social costs and excelled in spatial efficiency and ecosystem service costs. Notably, this strategy employed a limited number of planning units linked to both high ecosystem service and social costs. The findings underscore that incorporating social preferences significantly enhances the evaluation of siting options. This inclusion allows for the social acceptance of investments to be factored into costs, facilitating more informed and inclusive decisions.

Risk allocation schemes between public and private sectors in green energy projects.

In this research, we analyse how project risk allocation strategies impact the volume of private investment in renewable energy projects with the participation of both the public and private sectors. To this purpose, we analyse a sample formed by 2215 projects performed in 73 developing countries in the period 1997-2019 involving the following technologies: solar, hydro, wind, waste, biogas, biomass, and geothermal. Our findings reveal that those projects performed through governance schemes in which the private partner takes more project responsibilities attract more private money. Additional drivers for attracting private investment at the project level and institutional level are found. Furthermore, we reveal that the transference of project risks to the private partner emerges as a very relevant project feature that interacts with some of the project and institutional factors, revealing both complementary and substitution effects. The significance of this research extends beyond academia, since there are factors influencing private investment that can be controlled by various stakeholders in projects (such as policymakers, private investors, and project managers). Understanding their impact, significance, and interaction effects-factors that sometimes moderate or accentuate private investment-is crucial. The identified patterns illuminate optimal risk allocation practices, offering practical insights to enhance the effectiveness and sustainability of projects.

Perception of photovoltaic energy consumption in the Spanish primary sector. An environmentally profitable alternative.

Agriculture and livestock farming are activities that depend on energy consumption. Photovoltaic self-consumption systems can reduce the production costs of these actors, especially in periods of high-energy price volatility. This work aimed to determine the degree of implementation of photovoltaic self-consumption systems, their relationship with the economic impact of the energy crisis, and the perception of producers to use renewable energy sources in the Spanish agricultural system as it is one of the most important at European level. For this purpose, a survey of the Spanish agricultural and livestock system, involving 396 primary producers, was carried out between December 2022 and March 2023. The results suggest that self-consumption systems are in place in 49.1% of all farms and that these have had a positive effect in alleviating the rising energy costs suffered by the Spanish primary sector. In summary, Spanish primary producers generally have a favorable perception of the use of renewable energies on their farms, especially photovoltaic. However, the cluster analysis shows the fact that there are two types of producers, active and passive, from an environmental point of view. The characterization of this type of producers can help the Spanish Administration to improve the efficiency of its energy strategy, and can be a source of inspiration for the governments of other countries.

Optimal sizing and power losses reduction of photovoltaic systems using PSO and LCL filters.

The integration of renewable energy systems into electricity grids is a solution for strengthening electricity distribution networks (SEDNs). Renewable energies such as solar photovoltaics are suitable for reinforcing a low-voltage line by offering an electrical energy storage system. However, the integration of photovoltaic systems can lead to problems of harmonic distortion due to the presence of direct current or non-linear feedback in networks from other sources. Therefore, connection standards exist to ensure the quality of the energy before injection at a point of common coupling (PCC). In this work, particle swarm optimization (PSO) is used to control a boost converter and to evaluate the power losses and the harmonic distortion rate. The test on the IEEE 14 bus standard makes it possible to determine the allocation or integration nodes for other sources such as biomass, wind or hydrogen generators, in order to limit the impact of harmonic disturbances (LIHs). The evaluation of the harmonic distortion rate, the power losses as well as the determination of the system size is done using an objective function defined based on the integration and optimization constraints of the system. The proposed model performs better since the grid current and voltage are stabilized in phase after the photovoltaic source is injected.

Clean energy transition and climate vulnerabilities: A comparative analysis of European and non-European developed countries.

Currently, the world faces an existential threat of climate change, and every government across the globe is trying to come up with strategies to tackle the severity of climate change in every way possible. To this end, the use of clean energy rather than fossil fuel energy sources is critical, as it can reduce greenhouse gas emissions and pave the way for carbon neutrality. This study examines the impact of the energy cleanability gap on four different climate vulnerabilities, such as ecosystem, food, health, and housing vulnerabilities, considering 47 European and non-European high-income countries. The study considers samples from 2002 to 2019. This study precedes the empirical analysis in the context of a quadratic relationship between the energy cleanability gap and climate vulnerability. The study uses system-generalized methods of the moment as the main technique, while panel quantile regression is a robustness analysis. Fixed effect and random effect models have also been incorporated. The study finds that the energy cleanability gap and all four climate vulnerabilities demonstrate a U-shaped relationship in both European and non-European countries, implying that when the energy cleanability gap increases, climate vulnerability decreases, but after reaching a certain threshold, it starts to increase. Development expenditure is found to be negatively affecting food and health vulnerabilities in European nations, while it increases food vulnerability and decreases health vulnerability in non-European nations. Regarding industrialization's impact on climate vulnerabilities, the study finds opposite effects for the European and non-European economies. On the other hand, for both groups, trade openness decreases climate vulnerabilities. Based on these results, the study recommends speeding up the energy transition process from fossil fuel energy resources towards clean energy resources to obtain carbon neutrality in both European and non-European groups.

Achieving Decentralized, Electrified, and Decarbonized Ammonia Production.

The rapid reduction in the cost of renewable energy has motivated the transition from carbon-intensive chemical manufacturing to renewable, electrified, and decarbonized technologies. Although electrified chemical manufacturing technologies differ greatly, the feasibility of each electrified approach is largely related to the energy efficiency and capital cost of the system. Here, we examine the feasibility of ammonia production systems driven by wind and photovoltaic energy. We identify the optimal regions where wind and photovoltaic electricity production may be able to meet the local demand for ammonia-based fertilizers and set technology targets for electrified ammonia production. To compete with the methane-fed Haber-Bosch process, electrified ammonia production must reach energy efficiencies of above 20% for high natural gas prices and 70% for low natural gas prices. To account for growing concerns regarding access to water, geospatial optimization considers water stress caused by new ammonia facilities, and recommendations ensure that the identified regions do not experience an increase in water stress. Reducing water stress by 99% increases costs by only 1.4%. Furthermore, a movement toward a more decentralized ammonia supply chain driven by wind and photovoltaic electricity can reduce the transportation distance for ammonia by up to 76% while increasing production costs by 18%.

Exploring the impact of climate technology, financial inclusion and renewable energy on ecological footprint: Evidence from top polluted economies.

Most South Asian countries' economies have grown dramatically during the past few decades. However, in light of their environmental sustainability goals, the quality of such growth performances by South Asian nations is called into doubt by the concurrent degradation in environmental quality. Consequently, reducing the environmental challenges these nations encounter is prioritized on the agendas of the relevant authorities. This study aimed to analyze the effect of the top 11 most polluted countries' levels of financial inclusion, technological innovation, consumption of renewable energy, and adoption of climate technology on environmental deterioration from 2000 to 2022. Therefore, this research aims to use cutting-edge panel data econometric techniques to investigate the factors contributing to high carbon footprints in the world's most polluted nations. The results support an inverted U-shaped relationship between economic growth and carbon footprints, crediting the environmental Kuznets curve concept. In addition, it has been shown that TECH, REC, and CT can reduce carbon footprints in both the short and long term, while GDP and financial inclusion only affect carbon footprints in the long term. The results further endorsed the pollution haven hypothesis by showing that GDP positively affects carbon footprint. As a result, leading polluting economies need to strengthen their financial sectors, create green technology, migrate to renewable energy, and limit financial inclusion to improve environmental quality.

Enhancing the control of doubly fed induction generators using artificial neural networks in the presence of real wind profiles.

This study tackles the complex task of integrating wind energy systems into the electric grid, facing challenges such as power oscillations and unreliable energy generation due to fluctuating wind speeds. Focused on wind energy conversion systems, particularly those utilizing double-fed induction generators (DFIGs), the research introduces a novel approach to enhance Direct Power Control (DPC) effectiveness. Traditional DPC, while simple, encounters issues like torque ripples and reduced power quality due to a hysteresis controller. In response, the study proposes an innovative DPC method for DFIGs using artificial neural networks (ANNs). Experimental verification shows ANNs effectively addressing issues with the hysteresis controller and switching table. Additionally, the study addresses wind speed variability by employing an artificial neural network to directly control reactive and active power of DFIG, aiming to minimize challenges with varying wind speeds. Results highlight the effectiveness and reliability of the developed intelligent strategy, outperforming traditional methods by reducing current harmonics and improving dynamic response. This research contributes valuable insights into enhancing the performance and reliability of renewable energy systems, advancing solutions for wind energy integration complexities.

The adoption of renewable energy towards environmental sustainability: Evidence from Partial Least Square Structural Equation Modelling (PLS-SEM).

The effect of carbon emissions on the environment has made some of the Sustainable Development Goals difficult to achieve. Despite the efforts of international bodies, there is still a need to address the problem since the transition is not complete. Therefore, this study investigates the effect of globalization, economic growth, financial inclusion, renewable energy, and government institutions on carbon emissions from the period of 1998 to 2021. To be able to assess both the direct and indirect effects of the variables, the Partial Least Square Structural Equation Modelling is employed, where renewable energy serves as the mediator, and the Two-Stage Least Squares is employed as the robustness check. The findings of the study reveal that globalization promotes the use of renewable energy, but financial inclusion has a negative effect on renewable energy use. Renewable energy has a direct positive and significant effect on carbon emissions. Financial inclusion has an indirect negative and significant effect on carbon emissions. The results imply that more enlightenment on financial inclusion will help a smooth transition, and globalization should be embraced when all environmental regulations are enforced.

Does financial inclusion and information communication technology affect environmental degradation in oil-producing countries?

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.

Shaping a greener future: The role of geopolitical risk, renewable energy and financial development on environmental sustainability using the LCC hypothesis.

The recent progress report of Sustainable Development Goals (SDG) 2023 highlighted the extreme reactions of environmental degradation. This report also shows that the current efforts for achieving environmental sustainability (SDG 13) are inadequate and a comprehensive policy agenda is needed. However, the present literature has highlighted several determinants of environmental degradation but the influence of geopolitical risk on environmental quality (EQ) is relatively ignored. To fill this research gap and propose a inclusive policy structure for achieving the sustainable development goals. This study is the earliest attempt that delve into the effects o of geopolitical risk (GPR), financial development (FD), and renewable energy consumption (REC) on load capacity factor (LCF) under the framework of load capacity curve (LCC) hypothesis for selected Asian countries during 1990-2020. In this regard, we use several preliminary sensitivity tests to check the features and reliability of the dataset. Similarly, we use panel quantile regression for investigating long-run relationships. The factual results affirm the existence of the LCC hypothesis in selected Asian countries. Our findings also show that geopolitical risk reduces environmental quality whereas financial development and REC increase environmental quality. Drawing from the empirical findings, this study suggests a holistic policy approach for achieving the targets of SDG 13 (climate change).

Linking energy-based circularity with environment in high-income economies.

A circular economy is a regenerative approach that emphasizes resource efficiency, waste reduction, and the reuse of materials for a sustainable world. By adopting circular practices, we can reduce the negative impact of traditional linear economic models on the environment. According to the International Renewable Energy Agency (IRENA), the world is generating only 26% of total energy production from circular practices, which positively impacts environmental health. Therefore, this study aims to evaluate the empirical estimation of circular practices regarding energy on the environment. The current study focuses on the association between the circular economic index, economic growth, trade, digitization, energy use, and the financial development index on the environment in 29 high-income countries from 1990 to 2019. The study employs the second-generation econometric technique Driscoll-Kraay to empirically estimate the association among the variables of interest after confirming cross-sectional dependency within the data set. The study findings reveal that circular practices improve high-income countries' environmental conditions. Furthermore, the study confirms the association between economic growth, financial development index, energy use, trade, and digitization on the environment, and it leads to a more sustainable situation. Policies are drawn based on findings for policymakers toward a sustainable world.

Do renewable energy sources perfectly displace non-renewable energy sources? Evidence from Asia-Pacific economies.

The existing scholarly discourse surrounding the energy transition has long operated on the assumption of perfect displacement of non-renewable energy. However, an evolving set of studies highlights an intricate web of inefficiencies and complexities that prevent the perfect displacement of fossil fuel energy with renewable energy production. Since this could carry serious implications for the environmental targets of several economies, it is crucial to accurately and continuously measure the actual extent of fossil fuel displacement. Within this framework, this study empirically investigates the extent of non-renewable energy displacement by renewable energy for a balanced panel of seven Asia-Pacific (APAC) countries between 1989 and 2015. The outcome function also controls for globalisation, real GDP per capita, and crude oil prices. After implementing the necessary diagnostics, the panel cointegration establishes a significant long-run relationship among the selected variables. The PMG-ARDL estimation indicates that renewable energy production and globalisation significantly reduce the fossil fuel energy production, whereas real GDP per capita and crude oil prices induce it positively. However, the coefficient of renewable energy production is only - 0.39, indicating that more than 2.5 units of renewable electricity are necessary to displace a unit of non-renewable energy. As such, this study concludes that the current energy transition in Asia-Pacific region is not perfect. These results are robust to the usage of the FGLS estimation technique. The study suggests the adoption of a new energy transition that allows greater displacement of fossil fuel energy as well as gradual reduction in overall energy use.

Exploring the asymmetric effect of fiscal policy instruments in encountering environmental degradation: proposing an SDG framework for India.

Asian countries are facing difficulties in attaining sustainable development goals (SDGs), and India is not an exception to it, with environmental degradation being one of the primary issues. Therefore, a policy-level reorientation may be required to address it. From this standpoint, fiscal policy instruments may come in handy towards fully integrating the SDGs into its agenda. The present investigation designs an SDG framework for India that could serve as an example for other Asian nations. This study introduces a new investigation exploring the relationship between fiscal policy instruments and environmental quality in India by examining the environmental Kuznets curve (EKC) hypothesis from 1990 to 2021. A nonlinear autoregressive distributed lag (NARDL) model is applied for empirical examination. The findings indicate that positive and negative shocks in fiscal policy instruments have significant impact on carbon emissions in both the long and short run. The study has also found evidence of an "inverted U-shape" EKC for India. These results are valuable from a policy perspective for India and other Asian countries to address environmental issues. The study has also outlined potential outcomes that may benefit India's fiscal policy in resolving environmental issues and attaining better economic growth. In the end, the study proposes a policy framework that supports SDG 7, SDG 8, SDG 12, SDG 13, and SDG 17 objectives.

Renewable energy, inequality and environmental degradation.

The connection between income inequality and environmental degradation remains a topic of persistent debate, marked by inconsistencies in both theoretical and empirical studies. This study offers a novel contribution to this discourse by investigating the simultaneous influences of renewable energy and income inequality on environmental degradation. Utilizing data from 158 nations from 2000 to 2017, our research reveals a crucial moderating role of renewable energy in the nexus between income inequality and environmental degradation. The study's key finding is that the impact of income inequality on environmental degradation is contingent on the level of renewable energy development. In scenarios with limited renewable energy, income equality leads to increased environmental degradation. However, when renewable energy is more developed, income equality contributes to reducing environmental degradation. This novel insight suggests that renewable energy development can mitigate the trade-off between pursuing income equality and environmental sustainability, thereby enabling their simultaneous achievement. The research also highlights that a more equitable income distribution enhances the environmental benefits of renewable energy. Further analysis demonstrates the significant role played by household consumption behavior and social norms in shaping this phenomenon. By adding these new dimensions to the existing literature, the study significantly enriches the understanding of the complex interplay among economic factors, renewable energy, and environmental sustainability.

Assessing the impact of geopolitical, economic, and institutional factors on China's environmental management in the Russian-Ukraine conflicting era.

In contemporary times, geopolitical risk, and natural resources prices are susceptible due to the Russian-Ukraine conflict. In the meantime, emerging economies are struggling to explore the factors that could reduce ecological challenges and enhance environmental management. This research aims to analyze several economic, environmental, political, and institutional variables to ascertain their influence on greenhouse gas emissions in China. Covering the latest period from 1990 to 2022, various time series tests, including normality, stationarity, and cointegration tests. The results confirm that the variables studied have a stable pattern over time and are connected in the long run. The non-normal distribution of variables leads to opt novel moment quantile regression, where the results are tested for robustness via parametric approaches. The empirical results asserted that economic growth, natural resource prices, and trade significantly enhance ecological challenges (emissions). However, globalization, geopolitical risk, and institutional quality significantly reduce such environmental challenges. The results are robust, and both unidirectional and bidirectional causal associations confirm the importance of these variables in environmental management. Based on the results, this study recommends engagement in environmentally-friendly trading, investment in clean and green energy, and strengthening institutional quality for the region's environmental recovery.

Revisiting the EKC framework concerning COP-28 carbon neutrality management: Evidence from Top-5 carbon embittering countries.

In the aftermath of the 28th Conference of the Parties (CoP) climate summit in the UAE, the majority of developing countries encounter challenges in attaining their objectives of carbon neutrality for a sustainable economy. The association of economic factors such as economic growth, governance structures, forest area, renewable energy consumption, technological innovation, and urbanization with environmental elements (carbon footprint) is vital for sustainable economic development and environmental management strategies. Therefore, this research reveals this association in five selected high-emitting countries spanning from 1990 to 2022. This research utilizes the Environmental Kuznets Curve (EKC) framework to investigate the interrelationship between these variables. To do so, this study employs the cross-sectional autoregressive distributed lags (CS-ARDL) statistical technique to determine the short- and long-term impacts of the variables under investigation on carbon footprint. In contrast, the mean group (MG) and common correlated effect mean group (CCEMG) have been applied for robustness. The findings revealed that GDP, urbanization, and forest area have positive associations with carbon footprints, whereas GDP square, renewable energy consumption, technological innovation, and governance effectiveness have inverse relationships with carbon footprints. These findings provide all stakeholders with valuable policy recommendations and management advice for accelerating the transition of renewable energy to low-carbon and green growth.

Evaluating strategies for developing renewable energies considering economic, social, and environmental aspects: a case study.

Due to fast industrial expansion and the increasing population in Vietnam, this country is confronting a mounting lack of energy. While this country has considerable renewable energy (RE) potentials, including wind, solar, biomass, and hydropower sources, it has yet to exploit them entirely because of a lack of proper planning. This research aimed to find and assess solutions for encouraging RE growth in Vietnam. RE development solutions were formulated through SWOT analysis and evaluated in terms of their social, economic, and environmental dimensions. The SWARA approach weighed the strategy evaluation criteria. The most influential sub-criteria were initial investment cost, reduction of adverse environmental impacts, and natural capacity of the region, with weights of 0.155, 0.127, and 0.114, respectively. Strategy evaluation was performed using the Gray ARAS, and the results were validated with the Gray COPRAS, the Gray TOPSIS-G, and the Gray MABAC. In the strategy ranking, the top strategy is to reduce the cost of renewable power generation. This can be achieved by using advanced technologies and promoting cooperation between domestic and foreign industries and companies. Increasing domestic and foreign investment in RE infrastructure by providing financial facilities for investors, developing domestic and international cooperation, and creating a competitive environment between different companies to reduce electricity production costs were the most suitable strategies.

Technological innovation, militarization, and environmental change: evidence from BRICS economies.

In the complex international society, the economic development and defense construction of BRICS countries have attracted increasing attention. This article incorporates technological innovation, militarization, and environmental change into a unified analytical framework to assess the potential impact of technological progress and defense military expenditure on the environment in BRICS countries. Based on CSD tests, unit root tests, and cointegration tests, this study constructs a CS-ARDL model to examine the long-term and short-term relationships among various variables from 1990 to 2021. The results show that technological innovation, military expenditure, and economic growth can significantly increase ecological footprint in the long run, while in the short term, technological innovation and economic growth significantly increase ecological footprint, and the impact of military expenditure is not significant. It is suggested that BRICS countries should focus on supporting low-carbon technology policies and research and development investment, while also considering the use of cutting-edge technology to improve military intelligence capabilities in order to reduce the negative impact of technological innovation and military activities on the environment.

Empirical evidence of emissions discourse related to food, beverage, and tobacco production in leading manufacturing nations.

The proliferation of carbon dioxide (CO2) emissions has resulted in significant environmental challenges worldwide, particularly within industrialized nations. The present paper tries to investigate the role of food, beverages, and tobacco in mitigating CO2 emissions in the top industrial countries. Economic growth and renewable and non-renewable energy consumption are integrated as control variable in the empirical model. The study applied the pooled mean group-autoregressive distributed lag (PMG-ARDL) model proposed by (J Appl Econ, 16:289-326, 2001) and Granger causality test for causalities directions. The empirical outcomes suggest the presence of cross-sectional dependence, and variables are integrated of order one and cointegrated. Long-run estimates revealed the presence of inversed U curve proving the validity of the environmental Kuznets curve. Also, the results show that renewable energy (RE) consumption contribute in reducing emissions, while non-renewable energy (NRE) and food, beverages, and tobacco (FBT) led to increase emissions level in the long run. Granger shows bidirectional long-run relationship between CO2 emissions, non-renewable energy, and economic growth. Moreover, Granger recorded no causality between food, beverages, and tobacco and any other variable. We recommend that firms engaged in the production of food, beverages, and tobacco products are increasingly urged to make investments in clean technologies powered by renewable energy sources for their manufacturing processes. This is considered a necessary step to achieve a significant reduction in CO2 emissions over an extended period.