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An in-depth investigation into the evolutionary characteristics, transmission mechanisms, and optimization pathways of electricity consumption linkages across China’s industrial sectors highlights their substantial theoretical and practical significance in achieving the “dual carbon” goals and advancing high-quality economic development. This study investigates the structural characteristics and developmental trends of electricity consumption linkages across China’s industrial sectors using an enhanced hypothetical extraction method. The analysis draws on national input–output tables and sector-specific electricity consumption data during the period from 2002 to 2020. Key transmission routes between industrial sectors are identified through path analysis and average path length calculations. The findings reveal that China’s industrial electricity consumption structure is marked by notable scale expansion and differentiation. The magnitude of inter-sectoral electricity flows continues to grow steadily. The evolution of these linkages exhibits clear phase-specific patterns, while the intensity of electricity consumption connections across sectors shows pronounced heterogeneity. Furthermore, the transmission path analysis revealed differentiated characteristics of electricity influence transmission, with generally shorter internal paths within sectors, significant cross-sectoral transmission differences, and manufacturing demonstrating good transmission accessibility with moderate path distances to major sectors. These insights provide a robust foundation for designing differentiated energy conservation policies, as well as for optimizing the overall structure of industrial electricity consumption. Full article

Decarbonization of the Greek economy requires significant investments in clean technologies. This will boost demand for goods and services and will create multiplier effects on output value added and employment, though reliance on imported technologies might increase the trade deficit. This study employs input–output analysis to estimate the direct, indirect, and multiplier effects of green transition investments on Greek output, value added, employment, and imports across five-year intervals from 2025 to 2050. Two scenarios are considered: the former is based on the National Energy and Climate Plan (NECP), driven by a large-scale exploitation of RES and technologies promoting electrification of final demand, while the latter (developed in the context of the CLEVER project) prioritizes energy sufficiency and efficiency interventions to reduce final energy demand. In the NECP scenario, GDP increases by 3–10% (relative to 2023), and employment increases by 4–11%. The CLEVER scenario yields smaller direct effects—owing to lower investment levels—but larger induced impacts, since energy savings boost household disposable income. The consideration of three sub-scenarios adopting different levels of import-substitution rates in key manufacturing sectors exhibits pronounced divergence, indicating that targeted industrial policies can significantly amplify the domestic economic benefits of the green transition. Full article

To remain competitive in the decarbonization process of the economy worldwide, energy companies must preserve their market value to attract new investors and remain resilient throughout the transition to net zero. This article examines the market value of US energy companies during the period 2012–2024 in relation to their power generation mix. Panel regression analyses reveal that Tobin’s q and price-to-book ratios increase significantly for solar and wind power, while they experience moderate increases for natural gas power. In contrast, Tobin’s q and price-to-book ratios decline for nuclear and coal power. Furthermore, accounting-based profitability, measured by the return on assets (ROA), does not show significant variation with any type of power generation. The findings suggest that market investors prefer solar, wind, and natural gas power generation, thereby attributing greater value (that is, demanding lower risk compensation) to green companies compared to traditional ones. These insights provide guidance to executives, investors, and policy makers on how the power generation mix can influence strategic decisions in the energy sector. Full article

The transportation sector, as a major source of carbon emissions, plays a crucial role in the realization of dual carbon goals worldwide. In this study, an improved least absolute shrinkage and selection operator (LASSO) is used to identify six key factors affecting transportation carbon emissions (TCEs) in China. Aiming at the spatio-temporal characteristics of transportation carbon emissions, a CNN-BiLSTM neural network model is constructed for the first time for prediction, and an improved whale optimization algorithm (EWOA) is introduced for hyperparameter optimization, finding that the prediction model combining spatio-temporal characteristics has a more significant prediction accuracy, and scenario forecasting was carried out using the prediction model. Research indicates that over the past three decades, TCEs have demonstrated a rapid growth trend. Under the baseline, green, low-carbon, and high-carbon scenarios, peak carbon emissions are expected in 2035, 2031, 2030, and 2040. The adoption of a low-carbon scenario represents the most advantageous pathway for the sustainable progression of China’s transportation sector. Consequently, it is imperative for China to accelerate the formulation and implementation of low-carbon policies, promote the application of clean energy and facilitate the green transformation of the transportation sector. These efforts will contribute to the early realization of dual-carbon goals with a positive impact on global sustainable development. Full article

An important task for the European Union is to transpose agreements and international standards in regulation and directives that are binding on member states. The resultant European action plans and directives identify priority areas in the building and energy sectors where circular economy principles can be applied. Italy records a general circular materials rate of 20.8%, surpassing the mean European value. But low recycling rates are still registered in the construction sector. This paper aims to assess the position of Italy with respect to the European regulatory framework on circularity in the energy transition of buildings. Firstly, the government’s initiatives and technical standards are introduced and commented upon. Secondly, the study illustrates the current Italian platforms, networks, and public and private initiatives highlighting opportunities and obstacles that the energy sector has to overcome in the area of circularity. It emerges that Italian policies still use voluntary tools that are not sufficiently in line with an effective circular economy model. Moreover, data collection plays a crucial role in accelerating the implementation of future actions. Italy should consider the foundation of a National Observatory for the Circular Economy to elaborate European directives, harmonize regional policies, and promote the implementation of effective practices. Full article

The mining industry (MI) in mineral-rich regions is pivotal for economic growth but is challenged by significant pollution and emissions. This study examines Guangxi, a representative region in China, in light of the country’s “Dual Carbon” goals. We quantified carbon emissions from the MI from 2005 to 2021, employing the generalized Divisia index method (GDIM) to analyze the factors driving these emissions. Additionally, a system dynamics (SD) model was developed, integrating economic, demographic, energy, environmental, and policy variables to assess decarbonization strategies and the potential for carbon decoupling. The key findings include the following: (1) Carbon accounting analysis reveals a rising emission trend in Guangxi’s MI, predominantly driven by electricity consumption, with the non-ferrous metal mining sector contributing the largest share of total emissions. (2) The primary drivers of carbon emissions were identified as economic scale, population intensity, and energy intensity, with periodic fluctuations in sector-specific drivers necessitating coordinated policy adjustments. (3) Scenario analysis showed that the Emission Reduction Scenario (ERS) is the only approach that achieves a carbon peak before 2030, indicating that it is the most effective decarbonization pathway. (4) Between 2022 and 2035, carbon decoupling from total output value is projected to improve under both the Energy-Saving Scenario (ESS) and ERS, achieving strong decoupling, while the resource extraction shows limited decoupling effects often displaying an expansionary connection. This study aims to enhance the understanding and promote the advancement of green and low-carbon development within the MI in mineral-rich regions. Full article

The green transformation of traditional energy structures and the development of the new energy industry are crucial drivers of sustainable development in the country. The ASEAN Plan of Action for Energy Cooperation (2016–2025; APAEC [2016–2025]), established in 2016, has significantly promoted the growth of the new energy sector and enhanced energy structures across Association of Southeast Asian Nations (ASEAN). This initiative has also inspired these countries to develop corresponding industrial policies aimed at supporting the new energy vehicle (NEV) industry, resulting in significant growth in this sector within the ASEAN region. This paper analyzes the factors influencing the development of the NEV industry in the context of ASEAN’s new energy policies, drawing empirical insights from data collected across six ASEAN countries from 2013 to 2024. Following the implementation of the APAEC (2016–2025), it was observed that ASEAN countries reached a consensus on energy development and cooperation, collaboratively advancing the NEV industry through regional policies. Furthermore, factors such as national governance, financial development, education levels, and the size of the automotive market positively contribute to the growth of the NEV industry in ASEAN. Conversely, high energy consumption can hinder its progress. Additionally, further research indicates that the APAEC (2016–2025) has exerted a more pronounced impact on countries with robust automotive industry foundations or those prioritizing relevant policies. The findings of this paper offer valuable insights for ASEAN countries in the formulating policies for the NEV industry, optimizing energy structures, and achieving low-carbon energy transition and sustainable development. Full article

Evaluating the renewable energy potential, such as that of solar photovoltaics (PV), is important for developing renewable energy policies. This study investigated rooftop solar PV potential in Thailand based on open-source geographic information system (GIS) building footprints, solar PV power output, and the most recent land use data (2022). GIS-based overlay analysis, buffering, fishnet modeling, and spatial join operations were applied to assess rooftop availability across various building types, taking into account PV module installation parameters and optimal panel orientation. Economic feasibility and sensitivity analyses were conducted using standard economic metrics, including net present value (NPV), internal rate of return (IRR), payback period, and benefit–cost ratio (BCR). The findings showed a total rooftop solar PV power generation potential of 50.32 TWh/year, equivalent to 25.5% of Thailand’s total electricity demand in 2022. The Central region contributed the highest potential (19.59 TWh/year, 38.94%), followed by the Northeastern (10.49 TWh/year, 20.84%), Eastern (8.16 TWh/year, 16.22%), Northern (8.09 TWh/year, 16.09%), and Southern regions (3.99 TWh/year, 7.92%). Both commercial and industrial sectors reflect the financial viability of rooftop PV installations and significantly contribute to the overall energy output. These results demonstrate the importance of incorporating rooftop solar PV in renewable energy policy development in regions with similar data infrastructure, particularly the availability of detailed and standardized land use data for building type classification. Full article

The transition to green energy in the transport sector is becoming a priority in the context of global climate challenges and the European Green Deal. This paper investigates the development of alternative fuelling stations, particularly electric vehicle (EV) charging infrastructure and hydrogen stations, across EU countries with a focus on Poland. It combines a policy and technology overview with a quantitative scientific analysis, offering a multidimensional perspective on green infrastructure deployment. A Pearson correlation analysis reveals significant links between charging station density and both GDP per capita and the share of renewable energy. The study introduces an original Infrastructure Accessibility Index (IAI) to compare infrastructure availability across EU member states and models Poland’s EV charging station demand up to 2030 under multiple growth scenarios. Furthermore, the article provides a comprehensive overview of biofuels, including first-, second-, and third-generation technologies, and highlights recent advances in hydrogen and renewable electricity integration. Emphasis is placed on life cycle considerations, energy source sustainability, and economic implications. The findings support policy development toward zero-emission mobility and the decarbonisation of transport systems, offering recommendations for infrastructure expansion and energy diversification strategies. Full article

Demand Side Management (DSM) plays a crucial role in modern energy systems, enabling more efficient use of energy resources and contributing to the sustainability of the power grid. This study examines DSM strategies within a multi-environment context encompassing residential, commercial, and industrial sectors, with a focus on diverse appliance types that exhibit distinct operational characteristics and user preferences. Initially, a single-objective optimization approach using Genetic Algorithms (GAs) is employed to minimize the total energy cost under a real Time-of-Use (ToU) pricing scheme. This heuristic method allows for the effective scheduling of appliance operations while factoring in their unique characteristics such as power consumption, usage duration, and user-defined operational flexibility. This study extends the optimization problem to a multi-objective framework that incorporates the minimization of CO₂ emissions under a real annual energy mix while also accounting for user discomfort. The Non-dominated Sorting Genetic Algorithm II (NSGA-II) is utilized for this purpose, providing a Pareto-optimal set of solutions that balances these competing objectives. The inclusion of multiple objectives ensures a comprehensive assessment of DSM strategies, aiming to reduce environmental impact and enhance user satisfaction. Additionally, this study monitors the Peak-to-Average Ratio (PAR) to evaluate the impact of DSM strategies on load balancing and grid stability. It also analyzes the impact of considering different periods of the year with the associated ToU hourly schedule and CO₂ emissions hourly profile. A key innovation of this research is the integration of detailed, category-specific metrics that enable the disaggregation of costs, emissions, and user discomfort across residential, commercial, and industrial appliances. This granularity enables stakeholders to implement tailored strategies that align with specific operational goals and regulatory compliance. Also, the emphasis on a user discomfort indicator allows us to explore the flexibility available in such DSM mechanisms. The results demonstrate the effectiveness of the proposed multi-objective optimization approach in achieving significant cost savings that may reach 20% for industrial applications, while the order of magnitude of the trade-offs involved in terms of emissions reduction, improvement in discomfort, and PAR reduction is quantified for different frameworks. The outcomes not only underscore the efficacy of applying advanced optimization frameworks to real-world problems but also point to pathways for future research in smart energy management. This comprehensive analysis highlights the potential of advanced DSM techniques to enhance the sustainability and resilience of energy systems while also offering valuable policy implications. Full article

The European Union promotes decarbonization in energy-intensive industries like glass manufacturing. Collaboration between industry and researchers focuses on reducing CO₂ emissions through hydrogen (H₂) integration as a natural gas substitute. However, to the best of the authors’ knowledge, no updated real-world case studies are available in the literature that consider the on-site implementation of an electrolyzer for autonomous hydrogen production capable of meeting the needs of a glass manufacturing plant within current technological constraints. This study examines a representative hollow glass plant and develops various decarbonization scenarios through detailed process simulations in Aspen Plus. The models provide consistent mass and energy balances, enabling the quantification of energy demand and key cost drivers associated with H₂ integration. These results form the basis for a scenario-specific techno-economic assessment, including both on-grid and off-grid configurations. Subsequently, the analysis estimates the levelized costs of hydrogen (LCOH) for each scenario and compares them to current and projected benchmarks. The study also highlights ongoing research projects and technological advancements in the transition from natural gas to H₂ in the glass sector. Finally, potential barriers to large-scale implementation are discussed, along with policy and infrastructure recommendations to foster industrial adoption. These findings suggest that hybrid configurations represent the most promising path toward industrial H₂ adoption in glass manufacturing. Full article

Understanding vehicle emissions is essential for developing effective carbon reduction strategies in the transport sector. Conventional emission models often assume homogeneity and linearity, overlooking real-world asymmetries that arise from variations in vehicle design and powertrain configurations. This study explores how machine learning and explainable AI techniques can effectively capture both symmetric and asymmetric emission patterns across different vehicle types, thereby contributing to more sustainable transport planning. Addressing a key gap in the existing literature, the study poses the following question: how do structural and behavioral factors contribute to asymmetric emission responses in internal combustion engine vehicles compared to new energy vehicles? Utilizing a large-scale Spanish vehicle registration dataset, the analysis classifies vehicles by powertrain type and applies five supervised learning algorithms to predict CO₂ emissions. SHapley Additive exPlanations (SHAPs) are employed to identify nonlinear and threshold-based relationships between emissions and vehicle characteristics such as fuel consumption, weight, and height. Among the models tested, the Random Forest algorithm achieves the highest predictive accuracy. The findings reveal critical asymmetries in emission behavior, particularly among hybrid vehicles, which challenge the assumption of uniform policy applicability. This study provides both methodological innovation and practical insights for symmetry-aware emission modeling, offering support for more targeted eco-design and policy decisions that align with long-term sustainability goals. Full article

Agricultural production in southern Angola faces challenges due to unsustainable practices, including inefficient use of water, fertilizers, and machinery, resulting in low yields and environmental degradation. Therefore, clear and measurable indicators are needed to guide farmers toward more sustainable practices. The scientific literature insufficiently addresses this issue, leaving a significant gap in the evaluation of key performance indicators (KPIs) that can guide good agricultural practices (GAPs) adapted to the context of southern Angola, with the goal of promoting a more resilient and sustainable agricultural sector. So, the objective of this study is to identify and assess KPIs capable of supporting the selection of GAPs suitable for maize, potato, and tomato cultivation in the context of southern Angolan agriculture. A systematic literature review (SLR) was conducted, screening 2720 articles and selecting 14 studies that met defined inclusion criteria. Five KPIs were identified as the most relevant: gross margin, net profit, water use efficiency, nitrogen use efficiency, and machine energy. These indicators were analyzed and standardized to evaluate their contribution to sustainability across different GAPs. Results show that organic fertilizers are the most sustainable option for maize, drip irrigation for potatoes, and crop rotation for tomatoes in southern Angola because of their efficiency in low-resource environments. A clear, simple, and effective representation of the KPIs was developed to be useful in communicating to farmers and policy makers on the selection of the best GAPs in the cultivation of different crops. The study proposes a validated KPI-based methodology for assessing sustainable agricultural practices in developing regions such as southern Angola, aiming to lead to greater self-sufficiency and economic stability in this sector. Full article

Currently, Poland is witnessing a dynamic development of the offshore wind energy sector, which will be a key component of the national energy mix. While many international studies have addressed wind energy deployment, there is a lack of research that compares the energy and economic performance of both onshore and offshore wind farms under Polish climatic and spatial conditions, especially in relation to turbine spacing optimization. This study addresses that gap by performing a computer-based simulation analysis of three onshore spacing variants (3D, 4D, 5D) and four offshore variants (5D, 6D, 7D, 9D), located in central Poland (Stęszew, Okonek, Gostyń) and the Baltic Sea, respectively. The efficiency of wind farms was assessed in both energy and economic terms, using WAsP Bundle software and standard profitability evaluation metrics (NPV, MNPV, IRR). The results show that the highest NPV and MNPV values among onshore configurations were obtained for the 3D spacing variant, where the energy yield leads to nearly double the annual revenue compared to the 5D variant. IRR values indicate project profitability, averaging 14.5% for onshore and 11.9% for offshore wind farms. Offshore turbines demonstrated higher capacity factors (36–53%) compared to onshore (28–39%), with 4–7 times higher annual energy output. The study provides new insight into wind farm layout optimization under Polish conditions and supports spatial planning and investment decision making in line with national energy policy goals. Full article

Achieving the construction sector’s dual carbon objectives necessitates scaling green energy adoption in new residential buildings. The current literature critically overlooks four unresolved problems: oversimplified penalty mechanisms, ignoring escalating regulatory costs; static subsidies misaligned with market maturity evolution; systematic exclusion of innovation feedback from energy suppliers; and underexplored behavioral evolution of building owners. This study establishes a government–suppliers–owners evolutionary game framework with dynamically calibrated policies, simulated using MATLAB multi-scenario analysis. Novel findings demonstrate: (1) A dual-threshold penalty effect where excessive fines diminish policy returns due to regulatory costs, requiring dynamic calibration distinct from fixed-penalty approaches; (2) Market-maturity-phased subsidies increasing owner adoption probability by 30% through staged progression; (3) Energy suppliers’ cost-reducing innovations as pivotal feedback drivers resolving coordination failures, overlooked in prior tripartite models; (4) Owners’ adoption motivation shifts from short-term economic incentives to environmentally driven decisions under policy guidance. The framework resolves these gaps through integrated dynamic mechanisms, providing policymakers with evidence-based regulatory thresholds, energy suppliers with cost-reduction targets, and academia with replicable modeling tools. Full article