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The balance between water supply and demand is essential for industrial growth, affecting economic, social, and environmental sustainability. Our research employs a Gaussian process regression for demand prediction. Additionally, it takes into account water limits and policy thresholds when determining the supply, thereby defining a range of uncertainty for both the industrial demand and the supply. A pattern recognition method matches this trade-off range, identifying three patterns to support water management. The study focuses on the analysis of industrial water supply and demand dynamics under uncertain conditions in nine cities (Baiyin, Dingxi, Gannan, Lanzhou, Linxia, Pingliang, Qingyang, Tianshui, and Wuwei) in Gansu Province of China's Yellow River Basin in 2030. The results of the study show that industrial water use in Baiyin, Linxia, Dingxi, and Tianshui cities falls into Pattern I, providing water resources to support industrial development. Industrial water use in Wuwei, Pingliang, Qingyang, and Gannan cities represents Pattern II, which maintains a balance between supply and demand while allowing flexibility in water demand. Finally, the industrial water use in Lanzhou city is characterized by Pattern III, which requires optimization through structural, technological, and management improvements to mitigate the negative impacts of water scarcity on the sustainable development of the economy and society. The results of the research can be used as a reference for policy making in water resources planning and management in the basin. [ABSTRACT FROM AUTHOR]

Against the backdrop of the global goal of "carbon neutrality", the advancement of electric vehicles (EVs) holds substantial importance for diminishing the reliance on fossil fuels, mitigating vehicular emissions, and fostering the transition of the automotive sector towards a sustainable, low-carbon paradigm. The wide application of electric vehicles not only reduces the dependence on non-renewable resources such as oil, but also concurrently effectuates a substantial reduction in carbon emissions within the transportation sector. In the realm of electric vehicles, ternary lithium batteries (NCM) and lithium iron phosphate batteries (LFP) are two widely used batteries. This study examines the resource utilization and environmental repercussions associated with the production of 1 kW ternary lithium batteries and lithium iron phosphate batteries, employing a life cycle assessment (LCA) framework. The importance of clean energy in reducing environmental pollution and global warming potential is revealed by introducing five different power generation types and the regional power generation structure in China into the power battery production process. The findings of the investigation indicate that lithium iron phosphate batteries exhibit pronounced superiority in terms of environmental sustainability, while ternary lithium batteries are more advantageous in terms of performance. The mitigation of environmental pollution associated with battery production can be significantly achieved by the holistic integration of clean energy sources and the systematic optimization of manufacturing processes. Specific interventions encompass enhancing the energy efficiency of the production process, incorporating renewable energy sources for power generation, and minimizing the utilization of hazardous materials. By implementing these strategies, the battery sector can advance towards a more environmentally benign and sustainable trajectory. [ABSTRACT FROM AUTHOR]

The European Green Deal (EGD) is a package of policy initiatives launched by the European Commission in December 2019, which aims to set the European Union (EU) on the path to a green transition with the final goal of achieving climate neutrality by 2050. The package includes interlinked initiatives covering the climate, the environment, energy, transport, industry, agriculture, and sustainable finance. It is thus evident that holistic and scientifically sound decision support systems are crucial to help EU policymakers and stakeholders in monitoring the progress of countries towards the implementation of the EGD. Indeed, the multidimensionality of this policy initiative lends itself well to its integration into a Multiple Criteria Decision Aiding (MCDA) approach to the identification of priorities for action. Therefore, this research aims to evaluate the progress of the EU countries towards the implementation of the European Green Deal, using MCDA. The PROMETHEE II method was applied to the data for EU countries, using 26 key indicators collected from the Eurostat database and organized into three thematic clusters. The results enabled us to calculate overall scores measuring the degree of implementation of the EGD by the EU countries, and their profiles with respect to the key indicators and thematic clusters. By analyzing these profiles, strengths and weaknesses were identified. Thus, the fundamental novelty of this research consists of the first concrete application of a holistic and 'ready-to-use' decision-making tool that can be adopted by EU policymakers and stakeholders to draw up a roadmap towards climate neutrality. [ABSTRACT FROM AUTHOR]

The Philippines aspires for a clean energy future but has become increasingly reliant on imported fossil fuels due to rising energy demands. Despite renewable energy targets and a coal moratorium, emissions reductions have yet to materialize. This study evaluates the potential of offshore wind (floating and fixed), floating solar PV, in-stream tidal, and nuclear power to contribute to a Net-Zero energy plan for the Philippines, utilizing the Open-Source Energy Modelling System (OSeMOSYS). Seven scenarios were analyzed, including least-cost, renewable energy targets; Net-Zero emissions; and variations in offshore wind growth and nuclear power integration. Floating solar PV and offshore wind emerged as key decarbonization technologies, with uptake in all scenarios. Achieving Net-Zero CO2 emissions by 2050 proved technically feasible but requires substantial capital, particularly after 2037. Current renewable energy targets are inadequate to induce emissions reductions; and a higher target of ~42% by 2035 was found to be more cost-effective. The addition of nuclear power showed limited cost and emissions benefits. Emissions reductions were projected to mainly occur after 2038, highlighting the need for more immediate policy action. Recommendations include setting a higher renewables target, offshore wind capacity goals, a roadmap for floating solar PV, and better incentives for private investment in renewables and electric transport. [ABSTRACT FROM AUTHOR]

This article analyses how energy sufficiency can be applied in tourism destinations. It begins by highlighting the importance of decarbonizing tourism for climate action, given the sector's high CO2 emissions. Energy sufficiency, a key pillar of the energy transition, is defined as the voluntary reduction in energy demand within climate and CO2 emission constraints. The study investigates how stakeholders interpret and frame this concept, by focusing on strategies that align with the public image of the resort to reduce its energy requirements. The methodology includes semi-structured interviews with key players in Verbier—Val de Bagnes, focus groups with cooperation partners, participant observations at local meetings and events, and analysis of local documentation. Research was undertaken using living lab methods. The results reveal five main categories and eleven subcategories in which local stakeholders frame sufficiency, including oppositional framings, off-framings, selective framings, institutional framings, and disempowering framings. The article concludes with recommendations to reframe sufficiency in order to align with the destination's strategy and representations. While energy sufficiency is often overshadowed by narratives of economic growth, technological innovation, and material abundance, it appears crucial to reframe these narratives and integrate post-growth strategies that prioritize sustainability in tourism planning. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this study is to identify Offshore Wind Energy (OWE) as a key technology that could drive countries toward achieving climate goals. However, there are multiple challenges that this sector faces. Design/methodology/approach: This study aims to identify the challenges faced by the sector globally by systematically reviewing the existing literature in global context and portraying it in the Indian context. Factors are identified using content analysis. Findings: Results suggest high levelized cost of energy as the most discussed challenge for the growth of OWE. Insufficient financial support and policy, initial capital and inadequate technology formed the second, third and fourth most discussed challenges respectively. Research limitations/implications: To reduce the cost of OWE, the distribution companies in India could adopt feed-in tariffs (FiTs) in the early stages of development and make OWE procurement mandatory. The renewable purchase obligation (RPO) in India is specific to solar and non-solar; policy should accommodate offshore wind-specific RPO targets for each state to reach the 2030 target of 30 GW from OWE. Practical implications: To the best of the authors' knowledge, this is the first attempt to study the challenges of OWE development from a global perspective and portray these major challenges in the Indian context and uses content analysis from the existing literature to ascertain the major roadblocks for the development of OWE. Originality/value: The study identifies the unexplored gap in literature that includes futuristic challenges for OWE from climate change. Future studies can explore the possibilities of forecasting based on climate change scenarios and rank the challenges based on their relevance caused by possible damages. [ABSTRACT FROM AUTHOR]

Recent years have witnessed a growing trend in the utilization of Electric Vehicles (EVs), however with the increased usage of EVs, appropriate strategies for supporting the charging demands has not garnered much attention. The absence of adaptable plans in charging may result in minimized participation; further, the charging demands have to be addressed with utmost care for ensuring reliability and efficiency of the grid. In this paper, an efficient EV charging technique based on blockchain based user transaction and smart contract is devised. Here, charge scheduling is performed by acquiring the information the charging demand of the EV over Internet of things. In case the EV does not have sufficient power to reach the target, nearest Charging Station (CS) with the minimal electricity price is identified. The CS is selected considering various factors, such average waiting time, distance, power, traffic, and so on. Here, power prediction is performed using the Deep Maxout Network (DMN), whose weights are adapted based on the devised Exponentially Snake Optimization (ESO) algorithm. Furthermore, the efficacy of the devised ESO-DMN is examined considering metrics, like average waiting time, distance, and number of EVs charged and power and is found to have attained values of 1.937 s, 13.952 km, 55 and 2.876 J. [ABSTRACT FROM AUTHOR]

Decision makers and private investors impacted by the evolution of the carbon price should limit risks associated with investments in decarbonised options, notably for electrified options. This research demonstrates that considering only static future power prices and carbon content might be insufficient when accelerated sectoral electrification effort is foreseen. To illustrate the phenomenon, this research focuses on the conditions and the extent of electrification in decarbonising the chemical sector in Central-West Europe. Specifically, energy transition pathways until 2050 are considered for the power and the chemical sectors using a novel co-optimisation model, minimising the net present cost of both sectors and considering different carbon price scenarios and deployment rates. The findings indicate that not accounting for the power sector constraints when assessing the chemical sector’s transition pathways overestimates greenhouse gas (GHG) reduction potential and underestimates the net present cost by 3% in some scenarios. The results hold in scenarios considering carbon capture technologies. Overall, this research highlights the importance of upstream power sector investments in evaluating preferred pathways for GHG reduction in downstream sectors. Potential welfare losses are found in the case of transition pace asymmetry between the two sectors or resulting from imperfect anticipation of the respective decarbonisation trajectory of each sector.