Search

In the pursuit of sustainable development, accurate renewable energy demand forecasting holds great significance for climate change mitigation and promoting sustainability. However, renewable energy forecasting has been consistently challenged by seasonality and nonlinearity. Identifying the periodic and nonlinear characteristics concealed within renewable energy sources accurately is still an unexplored problem. Consequently, an innovative nonlinear discrete seasonal grey model is proposed for renewable energy forecasting, which incorporates seasonal dummy variables and a power exponent term for handling the seasonality and nonlinear patterns in time series. Furthermore, an intelligent algorithm matching framework is proposed to augment the flexibility of the newly developed model. For practical purposes, the new methodology is contrasted against a range of benchmarks encompassing statistical, machine-learning, and traditional grey models in forecasting the quarterly total renewable energy consumption in the United States. The proposed model exhibits over 27% improvement rates over its counterparts, achieving the most superior predictive accuracies of 1.45%, 39.27, and 0.79 in MAPEP , RMSEP , and MASEP metrics, respectively. Furthermore, the probability density and sample size analyses are conducted to validate the robustness of the new model, confirming its adaptability and stability towards algorithm randomness and historical information volume. Consequently, the novel model is employed to forecast the short-to-long-terms renewable energy consumption in the U.S., showcasing an upward trend and seasonal fluctuations of the consumption for the forthcoming 24 quarters from 2023Q4 to 2029Q3. These insights can offer valuable implications to the stakeholders such as energy suppliers, utility managers, and policy advocates, highlighting actionable strategies for optimizing renewable energy consumption forecasting and aiding sustainable development initiatives. • An innovative nonlinear discrete seasonal grey model is proposed for renewable energy forecasting. • The optimum algorithm matching the novel model is determined from five alternatives. • The Monte Carlo Simulation and parameter sensitivity analysis advance the robustness. • PSO with the optimal parameter group has been selected for searching coefficients. • The new model possesses higher accuracy and robustness than various competitors. [ABSTRACT FROM AUTHOR]

Woody biomass energy makes up a large share of renewable energy consumption in the EU, and the largest share in countries like Denmark. However, little is known about how the public perceive it. This paper presents the results of a questionnaire-based survey of the public in Denmark focusing on attitudes toward woody biomass for energy. The main findings are that, while more people favor than oppose it, a large proportion are undecided about the use of woody biomass. The survey also revealed a lack of knowledge about this energy source. A Best-Worst Scaling methodology revealed that Danes prioritize environmental sustainability concerns – namely biodiversity loss, the hindering of the development of other renewable energy sources and the climate change mitigation potential of woody biomass – over societal and/or economic ones when it comes to the promotion of woody biomass. Finally, it was found that concern about climate change, belief in the mitigation potential of woody biomass, and being younger explained the formation of positive attitudes toward woody biomass. Policy makers aiming to take public concerns into account in discussions about Denmark's energy future should focus more on minimizing the negative environmental impacts associated with woody biomass rather than on its economic benefits. [Display omitted] [ABSTRACT FROM AUTHOR]

To mitigate climate change, many studies have been conducted to identify the determinants of CO 2 emissions. However, a consensus has not been reached yet on the issue because past work has often not considered the unobserved individual heterogeneity across countries. Therefore, this study revisits the environment-energy-growth nexus by employing a panel quantile regression to incorporate the effects of renewable energy consumption and technological innovation within the research background of global 30 countries over the period 1980–2014. The advantage of this method is considering the distributional heterogeneity to provide a detailed description of linkage between the CO 2 emissions and driving factors at different emissions levels. The results show that the effects of determinants on CO 2 emissions are heterogeneous. For high-emissions countries, the function of renewable energy consumption is limited in reducing CO 2 emissions due to the smaller proportion of renewable energy use. Moreover, technological innovation greatly affects countries with relatively higher CO 2 emissions. Therefore, one option is to financially support and apply technological innovations to generate renewable energy at lower costs as well as increase energy efficiency. Moreover, transforming the economic growth mode is helpful to transfer from non-renewable to renewable sources of energy to meet energy demand. [ABSTRACT FROM AUTHOR]

The European Union launched a set of policies as part of its 2020 climate and energy package aimed at meeting its 20/20/20 headline targets for smart, sustainable and inclusive growth. This paper evaluates how successful new-to-the-market climate change mitigation technologies (CCMT) are in helping EU member states (MS) reach these goals and, furthermore, whether there are differences between sectors subject to EU-wide polices. To do so, we relate CCMT patent counts to two specific headline targets: (1) achieving 20% of gross final energy consumption from renewables, and (2) achieving a 20% increase in energy efficiency. Our results provide the first ex-post evaluation of the effectiveness of these technologies for combating climate change. Moreover, our sectoral impact assessment points to significant differences in the way in which these technologies contribute to policy goals across the sectors. [ABSTRACT FROM AUTHOR]

The residential sector is the third largest energy-consuming sector in Mexico and an important contributor to energy related carbon dioxide emissions after transport and industry. The objective of this study is to evaluate the implementation and social acceptance of energy efficient technologies and renewable technologies in the so called sustainable social housing program in Mexico City, and compare the real reduction of CO 2 emissions to the theoretical potential. To do so, two estimations are developed: 1) the technical and economic CO 2 emission reduction potential of energy efficiency and renewable energy technologies in new social housing in Mexico City, and 2) the real avoided emissions based on social acceptance of technologies obtained by housing surveys and physical revision of performance status of implemented technologies. We found that due to lack of information and training to households an important part of dwellers ended up rejecting mitigation technologies developing what we called the socially neglected effect of mitigation technologies. These results were used to estimate three scenarios for year 2025: baseline, mitigation and neglected effect. Due to the neglected effect a reduction of 25% with respect to the baseline scenario was obtained instead of 45% of emission reduction in year 2025. In the case of efficient lighting and refrigerators, where Minimum Energy Efficient Standards are in place the socially neglected effect disappears once the replacement of old to new technologies takes place. This result shows that minimum energy performance standards are the main mitigation policy to eliminate socially neglected effect in the long run. Obligatory standards for installation of solar water heaters can be developed as well, although it is important to develop additional follow-up policies for adequate installation of these technologies. [ABSTRACT FROM AUTHOR]

With the growing literature related to climate change mitigation measures and policy interventions, a systematic review of the application of computable general equilibrium (CGE) model is inevitable. Therefore, this article aims to characterise the relevant studies, define a comparative framework to identify the current state-of-the-art and the gaps in applied general equilibrium models. Firstly, the systematic review found a total of 301 research articles from Scopus and Web of Science databases and finally analysed 154 articles based on inclusion and exclusion criteria from 67 refereed journals. The review analysis found that application of CGE model is very vital in addressing climate change mitigation issues at the national, regional and global levels. However, China attracted the most substantial research interests followed by the USA, India and Australia, among others, which are in line with their share of greenhouse gas emissions in the world. Most of the research themes focus on the carbon tax, emission reduction target, emission trading, renewable energy, energy efficiency, and carbon capture and storage as primary drivers of low carbon economy. Nevertheless, there is a trend of employing more static CGE model compared to the dynamic CGE, although application of the latter has a limitation of providing right inputs to the macroeconomic policy. Finally, research directions and gaps envision other complementary models such as dynamic stochastic general equilibrium (DSGE) and agent-based model (ABM) for proper policy interventions. [ABSTRACT FROM AUTHOR]

Anthropogenic activities and advancements in industries boost global energy demand and increase fossil fuel consumption, causing several global environmental problems, such as climate change. As a climate change mitigation strategy, the use of renewable energy technologies has gained unprecedented interest. In particular, the thermochemical processing of lignocellulosic biomass integrated with other renewable energy technologies has emerged rapidly. It is critical to select appropriate integrated renewable energy system configurations for sustainable and feasible power generation towards higher environmental benefits. Understanding the possible configurations of thermochemical lignocellulosic biomass processing technologies (gasification, pyrolysis, hydrothermal gasification, or hydrothermal carbonization) integrated with renewable energy technologies (solar thermal, fuel cell, fusion power, or energy storage) is crucial for the further development and propagation of the integrated renewable energy system. Hence, we provide a systematic review of the thermochemical conversion of lignocellulosic biomass integrated with the other renewable energy technologies. Finally, the challenges associated with the implementation of these systems and suggestions for future research on the systems are discussed. • Renewable energy technology is integrated with thermochemical biomass conversion process. • The integrated bioenergy systems help overcome limitations of single-source energy systems. • Challenges and prospects for the integrated systems are highlighted. [ABSTRACT FROM AUTHOR]

• Feasibility of net zero-energy (nZE) for residential and commercial building stock. • Accommodation of nZE conditions by current power distribution network. • Proposed framework integrated synthetic population and activities. • Case study on dense urban area in noncold climate. • nZE transformation pathways explored as different from those for cold climate. The transformation to net zero-energy (nZE) building stocks involves harvesting of renewable energy, enhancement of building energy efficiency, incorporation of various supply-side options, and advanced energy management. Although several studies have evaluated the feasibility of nZE for residential areas in cold regions, only a few studies have been conducted on dense urban regions in noncold climate. Additionally, the accommodation of such building stock transformation by the current power distribution network has not been clarified to date. Thus, this study proposes a novel framework integrating synthetic population, activity, building stock, and power distribution network to explore transformation pathways. This was further demonstrated by a case study on a densely populated region covering four cities in Tokyo, Japan. The results signified that complete dissemination of popular energy efficiency measures can reduce the energy demand by 40%. With the reduction in energy demand, nearly nZE condition can be realized only if the building roof area is completely covered by photovoltaics. In particular, one half of the generation would be utilized locally, whereas the remaining would be exported. Moreover, the power distribution network can accommodate the transformation with a slight increase in power distribution loss up to 1% and a modest reinforcement requirement owing to line overloading. Conclusively, this study revealed that the transformation and reinforcement requirement are significantly distinct from those required in cold regions. [ABSTRACT FROM AUTHOR]

Climate change mitigation has been a global effort and energy generation is one of the primary sources of GHG emissions. There is a need to transition from fossil-based energy to renewable-based energy. One of the platforms to nourish the work is Eco-Industrial Park (EIP) which it promotes resource efficiency, industrial symbiosis, and circular economy practice. There is a need to explore an optimal configuration of multiple renewable energy (RE) systems in a centralised EIP facility that generates electricity for internal consumption and exports the excess energy to the grid. This model developed a mixed-integer non-linear programming (MINLP) model that considers RE from biogas, biomass, micro-hydro, and solar sources for a centralised water hub. The energy generated is primarily used for the main processes involved in the facility as the excess energy will be supplied to the grid. A case study and two scenarios were assessed, and the results offered simultaneous technical, economic, and environmental benefits, which are in the forms of multiple RE generations, additional yearly profit, and GHG emission avoidance from fossil source. This will further strengthen the envisioned role of EIP as it is also capable of supporting the United Nations Sustainable Development Goal (UNSDG) and RE100 agenda. • A MINLP model to optimise renewable energy generation for Total Site was developed. • The model is a part of a framework to optimise energy, water, and material streams. • The model considers energy generation via solar, micro hydro, biomass, and biogas. • The proposed installation could suffice the core processes energy needs. • Additional profit is up to 39% and GHG emission reduction can be up to 70%. [ABSTRACT FROM AUTHOR]

The threat of climate change and other risks for ecosystems and human health require a transition of the energy system from fossil fuels towards renewable energies and higher efficiency. The European geographical periphery, and specifically Southern Europe, has considerable potential for renewable energies. At the same time it is also stricken by high levels of public debt and unemployment, and struggles with austerity policies as consequences of the Eurozone crisis. Modeling studies find a broad optimum when searching for a cost-optimal deployment of renewable energy installations. This allows for the consideration of additional policy objectives. Simultaneously, economists argue for an increase in public expenditure to compensate for the slump in private investments and to provide economic stimulus. This paper combines these two perspectives. We assess the potential for renewable energies in the European periphery, and highlight relevant costs and barriers for a large-scale transition to a renewable energy system. We find that a European energy transition with a high-level of renewable energy installations in the periphery could act as an economic stimulus, decrease trade deficits, and possibly have positive employment effects. Our analysis also suggests that country-specific conditions and policy frameworks require member state policies to play a leading role in fostering an energy transition. This notwithstanding, a stronger European-wide coordination of regulatory frameworks and supportive funding schemes would leverage country-specific action. Renewed solidarity could be the most valuable outcome of a commonly designed and implemented European energy transition. [ABSTRACT FROM AUTHOR]

Renewable energy plays a crucial role in both climate change mitigation and adaptation in highly climate-vulnerable nations such as Nepal. This paper reviews various types of renewable energy technologies and their status, potential for adoption, relationship to climate change, and mitigative and adaptive roles in Nepal. Nepal has installed micro-hydro projects, solar power, improved cooking stoves, biogas technology, improved water mills, and wind energy to mitigate and adapt to climate change. There is a growing potential for renewable energy development in Nepal, such as hydropower, solar, wind energy, biogas, and improved cooking stoves. Roughly 70% of Nepal's energy consumption is generated from traditional energy sources while renewable energy accounts for approximately three percent. The gradual increase in the use of renewable energy has reduced greenhouse gas emissions and enhanced carbon sequestration. By adopting renewable energy technologies, Nepal has reduced emissions by 221,129 tCO 2 e from 2017 to 2018. Nepal's second Nationally Determined Contribution targets a 15% increase in national energy use from renewables with a reduction of 23% of CO 2 emissions by 2030 using biogas and improved cooking systems. Furthermore, a significant increase in the adoption of renewable energy has become a pivotal strategy in adaptation to climate change in social, health, and economic sectors resulting in time savings, alternative income sources, improved health and educational status, local job opportunities, and the promotion of social capital. The benefits of adapting to climate change and mitigating CO 2 emissions via renewable energy are significant at the local, national, and international levels. This study recommends that the government of Nepal focus work on energy policy reviews to address local energy demand and climate change issues by utilizing renewable energy resources at the local level, which has global implications. • Suitable, potential renewable energy technologies in Nepal. • The relationship between energy and climate change. • Relevant data on energy and climate change in tables and figures. • Social, economic, and environmental benefits of renewable energy. • Climate change adaptation and mitigation via renewable energy. [ABSTRACT FROM AUTHOR]

The role of low-carbon energy and trade on the environment has drawn several studies that have looked at issues from different perspectives, thus yielding differing conclusions. Considering the current emphasis on the COP25 conference and the commitment to cut down carbon emissions level, this study also draws strength from the United Nations Sustainable development Goals (UNSDGs) that comprises of positive strides for access to clean and responsible energy consumption (SDGs 7, 12) and climate change mitigation issues (SDG-13). To this end, this study is a timely outlook that underpins the case of the European Union (EU) countries as well as the root cause of anthropogenic activities on clean trajectory of global environment. Hence, we investigate the connection between alternative and sustainable energy source, trade, income and emissions in 27 selected European Union economies by utilizing data covering the period 1990–2017 on an annual frequency. We used second-generation panel model estimators to analyze the relationship between the variables in the long-run. Specifically, the long run results from the MG (Mean Group), AMG (Augmented Mean Group), and CCEMG (Common Correlated Effects Mean Group) estimators reveal that sustainable and alternative energy sources have a negative significant impact on pollutant emissions while trade and income have a positive impact on carbon emissions except that the impact of trade is insignificant. Although the positive impact of openness in trade on carbon emission is insignificant, the positive impact suggests that the free-trade policy that is currently in place in the EU should further incorporate sustainable development goals (SDGs) to avoid the outsourcing of carbon emissions among the member countries. Causality tests reveal a feedback hypothesis between renewable energy, income, trade, and carbon emanations. The investigation proposes expanded utilization of sustainable power source to mitigate carbon emissions in the European Union. • Outlook of EU-27 alternative energy and regional trade. • The panel techniques of common correlated effect is employed. • Alternative energy utilization in the regional bloc aids. • Regional trade policy in the EU could posit environmental hardship. • Real income growth in the region hampers environmental sustainability. [ABSTRACT FROM AUTHOR]

This paper investigates the energy system of the Basilicata region (southern Italy) to highlight, through a scenario analysis, its possible future development in compliance with the European Commission's long-term vision. The IEA-ETSAP methodology was utilized to model and analyse the Basilicata energy system in a business- as -usual scenario, based on the assumptions of the 2010 Regional Energy and Environmental Policy Plan, and in two low-carbon scenarios, decarbonisation and high energy efficiency, which, in line with the long-term European strategy, foresee an 85% carbon dioxide emission reduction and a 20% energy efficiency increase in 2050. The results highlight that electricity production from renewable energy sources (in particular wind energy), strongly supported by the regional policy, goes beyond the Basilicata Regional Energy-Environmental Plan forecast, with a further increase in the decarbonisation scenarios. In addition, solar thermal and highly efficient technologies are adopted in commercial and residential end-use sectors. An additional 9% reduction in energy consumption is achieved in the high energy efficiency scenario by passive houses. The proposed approach shows the usefulness of a modelling framework typically used for national and supranational analyses to support regional authorities in their decision-making process to obtain results in line with the European and national strategies. Application to the Basilicata region shows the usefulness of a consolidated framework for policy assessment at a local scale to assess regional contribution to the achievement of national climate mitigation targets that tend towards climate neutrality. • The role of regional authorities is essential to reach national decarbonisation goals. • TIMES can be advantageously used for regional energy system modelling and analysis. • Scenario analysis can be a powerful tool for policy evaluation. • A cap on carbon dioxide emissions leads to a 28% increase of electricity production. • Passive houses in Residential allow a further 5% reduction of energy consumption. [ABSTRACT FROM AUTHOR]

In the quest towards a cleaner environment via the mitigation of climate change and its impact, this study examined the validity of the environmental Kuznets curve (EKC) hypothesis, energy efficiency and energy consumption indicators in Kenya. The study employed an autoregressive distributed lag technique, statistically inspired modification of partial least squares regression and Utest method to analyze four models with data spanning 1971 to 2013. Both the autoregressive distributed lag model and the Utest estimation confirmed an inverted u-shaped curve, thus, validating the environmental Kuznets curve hypothesis in Kenya. The study revealed that an increase in energy consumption exacerbates carbon dioxide emissions in the long-run. The statistically inspired modification of partial least squares regression revealed that electricity from renewable energy sources plays a critical role in carbon dioxide emission reduction. An increase in GDP per capita and household consumption expenditure increases energy consumption. Energy imports had no long-run effect due to the recent oil discovery, coal, prospects of nuclear energy and the potential for more renewable energy sources in Kenya. The study highlights that using sustainable technologies like, inter alia, carbon capture and storage in the exploitation of oil and coal are essential to reducing pollution. Rural-urban migration increases the burden on electric power consumption, thus, reducing energy efficiency if conservation options are not enforced. As a policy implication, engaging the public on energy conservation and management options will help curb energy challenges like load shedding — which appears troubling in Africa. • The study examines the validity of the EKC hypothesis in Kenya. • ARDL, SIMPLS regression and Utest methods are used in the study. • ARDL model and the Utest estimation confirms an inverted u-shaped curve in Kenya. • Energy consumption exacerbate CO 2 emissions by 3.6% in the long-run. • Renewable energy consumption negates CO 2 emissions. [ABSTRACT FROM AUTHOR]