Energy Strategy Reviews最新文献_第5页

Exploring knowledge structure of “dual carbon” policies: Combining computational text mining and knowledge graph “双碳”政策的知识结构探索：结合计算文本挖掘和知识图

IF 7.9 2区工程技术 Q1 ENERGY & FUELS

Energy Strategy Reviews

Pub Date : 2025-11-01 DOI: 10.1016/j.esr.2025.101976

Yuan Fu , Peihan Wen , Junlin Wu , Yujiao Shu

To support energy transition and climate action, China has announced its “dual carbon” goals and introduced a series of related policies. However, these policies remain disorganised and scattered across various platforms and formats, posing significant challenges for accessibility and effective utilisation. To address this, we propose an integrated approach that combines computational text mining with knowledge graph construction to uncover the underlying knowledge structure of the policy systems. Specifically, our method considers both the external attributes and internal conceptual content of policies. We develop an adaptive knowledge extraction framework that incorporates multiple text mining techniques. By examining the network structure of the resulting policy-oriented knowledge graph, we identify key patterns and problems in the current policy system spanning dimensions such as citation networks, institutional roles, legal force, thematic focus, objectives, and implementation measures. Results indicate that the top-level documents play both a leading and bridging role, and that China is complementing administrative directives with increasing use of market and financial instruments. The analysis also highlights areas for improvement, including strengthening inter-provincial coordination, enacting specialised legislation, and refining the specificity and standards of policy implementation. The insights offer valuable strategic guidance for Chinese policymakers while offering transferable implications for other nations pursuing climate and energy strategy goals.

为支持能源转型和气候行动，中国宣布了“双碳”目标，并出台了一系列相关政策。然而，这些政策仍然杂乱无章，分散在不同的平台和格式中，对可访问性和有效利用构成了重大挑战。为了解决这个问题，我们提出了一种将计算文本挖掘与知识图构建相结合的集成方法，以揭示策略系统的底层知识结构。具体来说，我们的方法考虑了策略的外部属性和内部概念内容。我们开发了一个融合多种文本挖掘技术的自适应知识提取框架。通过研究政策导向知识图谱的网络结构，我们确定了当前政策体系中的关键模式和问题，涵盖了引文网络、制度角色、法律效力、专题重点、目标和实施措施等维度。结果表明，高层文件既起着主导作用，也起着桥梁作用，中国正在通过越来越多地使用市场和金融工具来补充行政指令。分析还强调了需要改进的领域，包括加强省际协调，制定专门立法，完善政策执行的具体内容和标准。这些见解为中国决策者提供了有价值的战略指导，同时也为其他追求气候和能源战略目标的国家提供了可转移的启示。

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引用次数: 0

Decoding electric vehicle adoption intention in densely populated cities: An integrated hybrid SEM–ANN approach 人口密集城市电动汽车使用意向解码：一种集成的混合SEM-ANN方法

IF 7.9 2区工程技术 Q1 ENERGY & FUELS

Energy Strategy Reviews

Pub Date : 2025-11-01 DOI: 10.1016/j.esr.2025.101964

Ruiqi Chang , Razib Chandra Chanda , Ali Vafaei-Zadeh , Haniruzila Hanifah

Rapid urbanization in densely populated cities has led to a dramatic increase in fossil fuel-powered vehicles, worsening air pollution, and public health concerns. Addressing these challenges requires sustainable mobility solutions, among which the adoption of electric vehicles (EVs) stands out as a viable alternative. However, customers' decision-making toward EV adoption remains complex and underexplored, particularly in developing countries. To bridge this gap, this study investigates the key antecedents shaping attitudes toward EVs and their influence on adoption intention. Adopting a quantitative research design, data were collected from 363 licensed drivers in Bangladesh through purposive sampling. To enhance the rigor and reliability of results, a multistage analytical approach was employed, combining linear modelling (PLS-SEM) and non-linear analysis (ANN). The PLS-SEM findings revealed that eco-friendly benefit, perceived return, operational economic benefit, and neuroticism are the most critical antecedents influencing attitude. Attitude, in turn, was found to strongly predict EV adoption intention. Complementing these results, Artificial Neural Network (ANN) analysis ranked the relative importance of the antecedents, highlighting neuroticism (100 %) as the most influential predictor of attitude, which itself emerged as the strongest driver of EV adoption intention. Additionally, risk aversion was identified as a moderator of the relationship between attitude and EVs adoption intention. Overall, the integration of PLS-SEM and ANN confirmed the pivotal role of attitude in shaping EV adoption intention in densely populated cities. The findings provide valuable insights for both academic researchers and industry stakeholders in understanding customer decision-making dynamics and promoting environmentally sustainable transportation.

人口密集城市的快速城市化导致化石燃料驱动的车辆急剧增加，空气污染恶化，以及公众健康问题。应对这些挑战需要可持续的交通解决方案，其中电动汽车（ev）的采用是一个可行的替代方案。然而，消费者对电动汽车的决策仍然很复杂，而且尚未得到充分探索，尤其是在发展中国家。为了弥补这一差距，本研究调查了影响电动汽车态度的关键因素及其对采用意愿的影响。采用定量研究设计，通过有目的抽样从孟加拉国的363名有执照的司机中收集数据。为了提高结果的严谨性和可靠性，采用了线性建模（PLS-SEM）和非线性分析（ANN）相结合的多阶段分析方法。PLS-SEM结果显示，生态效益、感知回报、经营经济效益和神经质是影响态度的最重要前因。态度，反过来，被发现强烈预测电动汽车的采用意愿。与这些结果相辅相成的是，人工神经网络（ANN）分析对前因的相对重要性进行了排序，强调神经质（100% %）是态度最具影响力的预测因子，而神经质本身又成为电动汽车采用意愿的最强驱动因素。此外，风险厌恶是态度与电动汽车采用意愿之间关系的调节因子。总体而言，PLS-SEM和人工神经网络的整合证实了态度在人口密集城市形成电动汽车采用意愿方面的关键作用。研究结果为学术研究人员和行业利益相关者了解客户决策动态和促进环境可持续交通提供了宝贵的见解。

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引用次数: 0

Decarbonizing East China's energy landscape: The role of geothermal energy in the energy-water-food nexus 脱碳的华东能源格局：地热能在能源-水-粮食关系中的作用

IF 7.9 2区工程技术 Q1 ENERGY & FUELS

Energy Strategy Reviews

Pub Date : 2025-11-01 DOI: 10.1016/j.esr.2025.101961

Lyu Wenhui , Wing-Keung Wong , Siao-Yun Wei , Zilola Shamansurova , Gadah Albasher , Akbar mansor

This paper seeks to fill this knowledge gap by examining the relationships between economic factors, flexibility modelling and geothermal innovation as a nexus in East China. Energy and water are intensively influencing the production of food, which indicates the utmost significant role of the energy-food-water nexus (EWF) in the current literature. Although de-carbonization is urgently needed due to climate change, the gap in the research regarding the development of the models that improve the EWF nexus and renewable energy production is present. With the help of an extensive evaluation framework and pioneer models, this study explores how geothermal energy can help resolve energy poverty and address the issue of de-carbonization. Moreover, the research paper explores the possibility of hydrogen produced by surplus electricity generated by geothermal energy. The economic perspective of the analysis is to assess the cost-effectiveness, investment, and financial incentives to increase renewable resources, especially geothermal energy, of the EWF nexus. The study provides a strategic implementation plan with specific milestones in 2030, 2040 and 2050, showing the longer-term advantages of combining economic roadmaps with technology to create a sustainable and low-carbon world. The study's findings indicate that harnessing geothermal energy to fulfill energy demands can eliminate energy poverty and enhance the EWF nexus in the region. Based on these results, the study recommends that policymakers in selected countries develop applicable strategies to harness the benefits of geothermal energy sources, achieving the goals of renewable energy generation and EWF nexus enhancement.

本文试图通过考察经济因素、弹性模型和地热创新之间的关系来填补这一知识空白。能源和水在很大程度上影响着食物的生产，这表明能源-食物-水关系（EWF）在当前文献中发挥着最重要的作用。尽管气候变化迫切需要脱碳，但在改善EWF联系和可再生能源生产的模型开发方面的研究仍存在空白。借助广泛的评估框架和先锋模型，本研究探讨了地热能如何帮助解决能源贫困和解决脱碳问题。此外，研究论文还探讨了利用地热能产生的剩余电力生产氢气的可能性。分析的经济角度是评估增加可再生资源，特别是地热能的EWF关系的成本效益、投资和财政激励。该研究提供了一个战略实施计划，其中包括2030年、2040年和2050年的具体里程碑，显示了将经济路线图与技术相结合以创造一个可持续和低碳世界的长期优势。研究结果表明，利用地热能满足能源需求可以消除能源贫困，增强该地区的EWF联系。根据这些结果，该研究建议选定国家的决策者制定适用的战略，利用地热能的好处，实现可再生能源发电和增强EWF联系的目标。

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引用次数: 0

Comprehensive bibliometric analysis of electric vehicle research: Trends, emerging topics, and sustainability insights 电动汽车研究的综合文献计量分析：趋势、新兴主题和可持续性见解

IF 7.9 2区工程技术 Q1 ENERGY & FUELS

Energy Strategy Reviews

Pub Date : 2025-11-01 DOI: 10.1016/j.esr.2025.101963

Amir Ali Mostaghis , Negin Mirzaei , Hossein Yousefi , Ahmad Hajinezhad , Mahmood Abdoos

This study provides a comprehensive bibliometric analysis based on over 85,000 papers sourced from the SCOPUS database between 2016 and early 2025. Utilizing VOSviewer, the EV research domain was categorized into 15 thematic clusters based on a keyword co-occurrence threshold of 34. Cluster labels were assigned according to the most frequent and central terms, and further validated through manual inspection of representative publications. Recent developments and emerging trends in each criterion have been outlined, using network, overlay, and density maps. Sustainability insights were derived from clusters such as “Environment,” “Sustainability and Resource Management,” and “Hydrogen,” highlighting contributions to carbon reduction, circular economy, and green fuel transitions. China has the most published papers overall, and India and United States follow after, showcasing global research distribution. Notably, the dominance of China and the rapid growth of hydrogen-related research emerged as key findings. Emerging trends include the application of artificial intelligence (AI) in EV infrastructure and the rise of hydrogen supply chain logistics emphasizing the combination of sustainable energy sources, technology acceptance, and developing modeling techniques. Findings of this study provide valuable insights for researchers, policymakers, and industry stakeholders. Through this study, the multidisciplinary nature of EV research has been underlined, with clear implications for sustainable transportation systems. Findings of this study provide valuable insights for researchers, policymakers, and industry stakeholders, offering a structured evidence base to guide investment decisions, policy design, and the strategic advancement of electric mobility systems.

本研究基于2016年至2025年初来自SCOPUS数据库的85000多篇论文进行了全面的文献计量分析。基于关键词共现阈值34，利用VOSviewer将EV研究领域划分为15个主题类。根据最频繁和中心术语分配聚类标签，并通过对代表性出版物的人工检查进一步验证。使用网络、覆盖和密度图，概述了每个标准的最新发展和新趋势。可持续性见解来自“环境”、“可持续性与资源管理”和“氢”等集群，突出了对碳减排、循环经济和绿色燃料转型的贡献。中国发表的论文总数最多，印度和美国紧随其后，显示出全球研究分布。值得注意的是，中国的主导地位和氢相关研究的快速增长成为关键发现。新兴趋势包括人工智能（AI）在电动汽车基础设施中的应用，以及强调可持续能源、技术接受和开发建模技术相结合的氢供应链物流的兴起。本研究的发现为研究人员、政策制定者和行业利益相关者提供了有价值的见解。通过这项研究，强调了电动汽车研究的多学科性质，对可持续交通系统具有明确的影响。本研究结果为研究人员、政策制定者和行业利益相关者提供了有价值的见解，为指导电动交通系统的投资决策、政策设计和战略推进提供了结构化的证据基础。

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引用次数: 0

Maghreb's renewable power future for climate mitigation: insights from the TIMES-MAGe model 马格里布可再生能源缓解气候变化的未来：来自TIMES-MAGe模型的见解

IF 7.9 2区工程技术 Q1 ENERGY & FUELS

Energy Strategy Reviews

Pub Date : 2025-11-01 DOI: 10.1016/j.esr.2025.101918

Yasmine Ayed , Patricia Fortes , Rafat Al Afif

The Maghreb's power-sector transition hinges on implementing the region's Nationally Determined Contributions and Low-Emission Development Strategies. Using The Integrated Market Allocation Energy Flow Optimization Model system (TIMES) energy-modelling framework, this study traces the evolution of the electricity systems of Tunisia, Morocco, and Algeria from 2018 to 2050, assessing renewable energy targets, decarbonization feasibility, and the value of regional electricity trade. All three countries can exceed their renewable electricity targets: Onshore wind and solar photovoltaic jointly comprise over 90 % of the capacity, while Concentrated solar power plays a limited role. Flexible technology deployment is expected to result in a 25 % reduction in electricity prices in Morocco and Tunisia, and a 10 % reduction in Algeria, by 2030. Power sector decarbonization requires 130 GW of renewable energy capacity and 28 GW of storage, with a cumulative investment of €17 billion. Regional electricity trade enables cost savings, reducing Algeria's investment needs by 18 %, and allows Morocco and Tunisia to export up to 71 % and 54 % of their interconnector capacity. These results underscore the importance of regional cooperation and provide valuable insights for aligning national energy strategies with long-term climate objectives.

马格里布的电力部门转型取决于实施该地区的国家自主贡献和低排放发展战略。利用综合市场配置能源流优化模型系统（TIMES）能源建模框架，本研究追踪了2018年至2050年突尼斯、摩洛哥和阿尔及利亚电力系统的演变，评估了可再生能源目标、脱碳可行性和区域电力贸易价值。这三个国家都可以超额完成可再生能源发电目标：陆上风能和太阳能光伏发电合计占装机容量的90%以上，而聚光太阳能发电的作用有限。预计到2030年，灵活的技术部署将使摩洛哥和突尼斯的电价降低25%，阿尔及利亚的电价降低10%。电力部门的脱碳需要130吉瓦的可再生能源容量和28吉瓦的储能容量，累计投资为170亿欧元。区域电力贸易可以节省成本，将阿尔及利亚的投资需求减少18%，并允许摩洛哥和突尼斯分别出口其互连能力的71%和54%。这些结果强调了区域合作的重要性，并为使国家能源战略与长期气候目标保持一致提供了宝贵的见解。

{"title":"Maghreb's renewable power future for climate mitigation: insights from the TIMES-MAGe model","authors":"Yasmine Ayed , Patricia Fortes , Rafat Al Afif","doi":"10.1016/j.esr.2025.101918","DOIUrl":"10.1016/j.esr.2025.101918","url":null,"abstract":"<div><div>The Maghreb's power-sector transition hinges on implementing the region's Nationally Determined Contributions and Low-Emission Development Strategies. Using The Integrated Market Allocation Energy Flow Optimization Model system (TIMES) energy-modelling framework, this study traces the evolution of the electricity systems of Tunisia, Morocco, and Algeria from 2018 to 2050, assessing renewable energy targets, decarbonization feasibility, and the value of regional electricity trade. All three countries can exceed their renewable electricity targets: Onshore wind and solar photovoltaic jointly comprise over 90 % of the capacity, while Concentrated solar power plays a limited role. Flexible technology deployment is expected to result in a 25 % reduction in electricity prices in Morocco and Tunisia, and a 10 % reduction in Algeria, by 2030. Power sector decarbonization requires 130 GW of renewable energy capacity and 28 GW of storage, with a cumulative investment of €17 billion. Regional electricity trade enables cost savings, reducing Algeria's investment needs by 18 %, and allows Morocco and Tunisia to export up to 71 % and 54 % of their interconnector capacity. These results underscore the importance of regional cooperation and provide valuable insights for aligning national energy strategies with long-term climate objectives.</div></div>","PeriodicalId":11546,"journal":{"name":"Energy Strategy Reviews","volume":"62 ","pages":"Article 101918"},"PeriodicalIF":7.9,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145413232","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Qatar's LNG exports: Advancing efficiency in electricity generation and reducing carbon emissions in the global energy transition 卡塔尔的液化天然气出口：在全球能源转型中提高发电效率和减少碳排放

IF 7.9 2区工程技术 Q1 ENERGY & FUELS

Energy Strategy Reviews

Pub Date : 2025-11-01 DOI: 10.1016/j.esr.2025.101978

Yakubu Abdul-Salam , Farouk Abdul-Salam

This study examines the role of Qatari liquefied natural gas (LNG) exports in the global energy transition, focusing on efficiency improvements in electricity generation and end-use emissions reductions. Using a panel data econometric approach, the study empirically assesses the impact of Qatari LNG on power generation efficiency across importing countries. Additionally, a counterfactual scenario framework is employed to quantify the end-use emissions reductions achieved through the substitution of coal and oil with LNG. Findings reveal that Qatari LNG has significantly improved efficiency in thermal electricity generation across importing countries, although diminishing marginal returns emerge at higher LNG penetration levels. Regarding end-use emissions reductions, Qatari LNG exports have cumulatively avoided 3525.66 Mt

{CO}_{2}

between 1997 and 2022, equivalent to 10.08 % of global energy-related

{CO}_{2}

emissions in 2022. Over the past decade, annual emissions reductions from Qatari LNG have stabilised at about 234.61 Mt

{CO}_{2}

, surpassing the total energy-related emissions of major economies such as Spain and the Netherlands in 2022. These reductions correspond to an estimated annual global environmental benefit of $40.95 billion. These findings highlight the critical role of Qatari LNG exports to efficiency enhancements and emissions reductions, reinforcing its role in advancing decarbonization across diverse power systems. However, the results underscore the limitations of LNG in long-term sustainability as efficiency gains plateau and continued reliance on fossil fuels may induce carbon lock-in. While Qatari LNG provides a crucial transition pathway, its role should be complemented by accelerated investments in renewables and carbon abatement technologies.

本研究考察了卡塔尔液化天然气（LNG）出口在全球能源转型中的作用，重点是提高发电效率和减少最终用途排放。该研究采用面板数据计量经济学方法，实证评估了卡塔尔液化天然气对进口国发电效率的影响。此外，采用反事实情景框架来量化通过用液化天然气替代煤炭和石油实现的最终用途减排。研究结果显示，卡塔尔液化天然气显著提高了进口国的火力发电效率，尽管液化天然气渗透率越高，边际收益就越少。在最终用途减排方面，卡塔尔液化天然气出口在1997年至2022年期间累计避免了3525.66 Mt CO2，相当于2022年全球能源相关CO2排放量的10.08% %。在过去十年中，卡塔尔液化天然气的年减排量稳定在23461 Mt CO2左右，超过了2022年西班牙和荷兰等主要经济体的能源相关总排放量。这些减少相当于估计每年全球环境效益409.5亿美元。这些发现突出了卡塔尔液化天然气出口对提高效率和减少排放的关键作用，加强了其在推进各种电力系统脱碳方面的作用。然而，研究结果强调了液化天然气在长期可持续性方面的局限性，因为效率的提高趋于平稳，对化石燃料的持续依赖可能会导致碳锁定。虽然卡塔尔液化天然气提供了一个关键的过渡途径，但它的作用应该通过加速对可再生能源和碳减排技术的投资来补充。

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引用次数: 0

Introduction of electric vehicles in Saudi Arabia: Impacts on oil consumption, CO2 emissions, and electricity demand 沙特阿拉伯引进电动汽车：对石油消耗、二氧化碳排放和电力需求的影响

IF 7.9 2区工程技术 Q1 ENERGY & FUELS

Energy Strategy Reviews

Pub Date : 2025-11-01 DOI: 10.1016/j.esr.2025.101982

Muhammad Javid, Raed Ali Al-Mestneer

In this study, we estimate and project the number of internal combustion engine (ICE) vehicles in Saudi Arabia up to 2050. The projected number of vehicles is then used to estimate and project the oil demand and CO₂ emissions associated with the transport sector by 2050. Based on the projected number of ICE vehicles, we design three scenarios for developing electric vehicles (EVs) (high, moderate, and low—growth scenarios) to determine the impact of EV expansion on future oil demand, CO₂ emissions, and electricity demand for EVs.

Our projections indicate that by 2050, the total number of ICE vehicles in Saudi Arabia could reach 29.6 million, approximately 2.5 times the 2023 level. Scenario projections of EVs show that by 2050, the number of EVs could reach 14.8 million in the high-growth scenario, 11.9 million in the moderate-growth scenario, and 8.9 million in the low-growth scenario. By 2050, the electricity for EVs in Saudi Arabia is projected to reach 47.7 TWh per year in the high-growth scenario, 38.2 TWh per year in the moderate-growth scenario, and 28.6 TWh per year in the low-growth scenario.

The adoption of EVs in Saudi Arabia can play a pivotal role in helping the country achieve its ambitious targets for reducing carbon emissions and curbing domestic oil consumption. Vehicle electrification can also support broader development objectives, such as enhancing inclusive mobility, improving local air quality, strengthening energy security, and advancing industrial policy initiatives.

在这项研究中，我们估计和预测到2050年沙特阿拉伯内燃机（ICE）车辆的数量。然后使用预计的车辆数量来估计和预测到2050年与运输部门相关的石油需求和二氧化碳排放量。基于内燃机汽车的预计数量，我们设计了三种发展电动汽车的情景（高、中、低增长情景），以确定电动汽车扩张对未来石油需求、二氧化碳排放和电动汽车电力需求的影响。我们的预测表明，到2050年，沙特阿拉伯的ICE车辆总数将达到2960万辆，约为2023年水平的2.5倍。电动汽车情景预测显示，到2050年，高增长情景下电动汽车保有量可达1480万辆，中等增长情景下为1190万辆，低增长情景下为890万辆。到2050年，沙特阿拉伯的电动汽车电力预计将在高增长情景下达到47.7 TWh /年，在中等增长情景下达到38.2 TWh /年，在低增长情景下达到28.6 TWh /年。在沙特阿拉伯，电动汽车的普及可以在帮助该国实现减少碳排放和抑制国内石油消费的宏伟目标方面发挥关键作用。汽车电气化还可以支持更广泛的发展目标，如增强包容性交通、改善当地空气质量、加强能源安全和推进产业政策倡议。

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引用次数: 0

Unveiling energy poverty trajectories: A longitudinal analysis using machine learning 揭示能源贫困轨迹：使用机器学习的纵向分析

IF 7.9 2区工程技术 Q1 ENERGY & FUELS

Energy Strategy Reviews

Pub Date : 2025-11-01 DOI: 10.1016/j.esr.2025.101998

Santiago Budría , Eduardo Fermé , Diogo Nuno Freitas

Identifying at-risk populations is essential for designing effective energy poverty interventions. Using data from the HILDA Survey, a longitudinal dataset representative of the Australian population, and a multidimensional index of energy poverty, we develop a machine learning model combined with SHAP (SHapley Additive exPlanations) values to document the short- and long-term effects of individual and contextual factors — such as income, energy prices, and regional conditions — on future energy poverty outcomes. The findings emphasize the importance of policies focused on income stability and may be used to shift the policy focus from reactive measures, which address existing poverty, to preventive strategies that target households showing early signs of vulnerability.

确定风险人群对于设计有效的能源贫困干预措施至关重要。利用HILDA调查（一个代表澳大利亚人口的纵向数据集）的数据和能源贫困的多维指数，我们开发了一个结合SHAP （SHapley Additive exPlanations）值的机器学习模型，以记录个人和环境因素（如收入、能源价格和区域条件）对未来能源贫困结果的短期和长期影响。研究结果强调了以收入稳定为重点的政策的重要性，并可用于将政策重点从针对现有贫困的反应性措施转向针对出现早期脆弱迹象的家庭的预防性战略。

引用次数: 0

Gathering "Energy" to achieve "Affluence": Research on the ecological prosperity effects of new energy industry agglomeration —Re-examining the Environmental Kuznets Curve based on Chinese data 聚集“能量”实现“富裕”：新能源产业集聚的生态繁荣效应研究——基于中国数据的环境库兹涅茨曲线再检验

IF 7.9 2区工程技术 Q1 ENERGY & FUELS

Energy Strategy Reviews

Pub Date : 2025-11-01 DOI: 10.1016/j.esr.2025.101979

Qing Ma , Yu Yan

The agglomeration of new energy industries has sparked a vivid discussion on its ecological welfare effects, capturing the attention of academic circles and policymakers. This paper explores the intrinsic relationships and dynamic evolution patterns between new energy industry agglomeration and ecological prosperity. It further discusses whether new energy industry agglomeration ameliorates the EKC phenomenon and investigates the selection of moderating effect pathways. The study applies comparative regression with Difference and System GMM models, stepwise regression via the Spatial Durbin Model (SDM), and interactive regression through PVAR. The key findings are summarized as follows: (1) The impact of new energy industry's economic development on environmental pollution exhibits an inverted U-shaped curve, aligning with the EKC theory. Additionally, new findings show that it presents positive U-shaped curves with common prosperity and ecological welfare performance, respectively. (2) Spatial spillover analysis reveals that the agglomeration of new energy industry does not exhibit a "green paradox" effect on environmental pollution. Specifically, the local direct effect of pollution suppression is approximately twice the indirect spillover effect on neighboring regions; its impact on local welfare shifts from "ecological curse" to "well-being" but inhibits adjacent areas via an "agglomeration shadow effect". This study innovatively links the "EKC theory" and "welfare-based view " to the discussion of new energy on ecological prosperity from the lens of agglomeration effects.

新能源产业集聚引发了关于其生态福利效应的热烈讨论，引起了学术界和政策制定者的关注。本文探讨了新能源产业集聚与生态繁荣之间的内在联系和动态演化模式。进一步探讨了新能源产业集聚是否改善了EKC现象，并探讨了调节效应路径的选择。采用差分模型和系统GMM模型进行比较回归，采用空间Durbin模型逐步回归，采用PVAR进行交互回归。研究发现：(1)新能源产业经济发展对环境污染的影响呈倒u型曲线，与EKC理论一致。此外，新的研究结果表明，共同繁荣和生态福利绩效分别呈现正u型曲线。(2)空间溢出分析表明，新能源产业集聚对环境污染不存在“绿色悖论”效应。具体而言，污染抑制的局部直接效应约为对周边地区间接溢出效应的两倍；它对当地福利的影响从“生态诅咒”转向“福祉”，但通过“集聚阴影效应”抑制了邻近地区。本研究创新性地将“EKC理论”和“福利基础观”结合起来，从集聚效应的角度探讨新能源对生态繁荣的影响。

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引用次数: 0

Advancing renewable energy strategies: Integrating technological innovation and economic complexity for sustainable resource management 推进可再生能源战略：整合技术创新和可持续资源管理的经济复杂性

IF 7.9 2区工程技术 Q1 ENERGY & FUELS

Energy Strategy Reviews

Pub Date : 2025-11-01 DOI: 10.1016/j.esr.2025.101958

Imran Khan , Inayat Khan , Arshian Sharif , Adeel Ahmed , Mohd Ziaur Rehman

<div><div>Achieving sustainable energy management is essential for addressing global climate challenges and achieving the United Nations Sustainable Development Goals (SDGs), particularly SDGs 7 (Affordable and Clean Energy) and 13 (Climate Action). This study investigates how technological innovation (TI), economic complexity (EC), product complexity index (PCI), and renewable energy consumption (REC) interact to enhance natural resource efficiency (NRE) in resource-rich economies. Using panel data from 1995 to 2022, the study also explores the role of green technologies, digital readiness (DR), and mineral complexity (MC) in fostering a low-carbon future. The findings reveal that in the long run, TI and REC significantly enhance NRE, with coefficients of 0.932 and 0.235, respectively, while technological complexity (TC) and MC have negative effects (coefficients of <span><math><mrow><mo>−</mo><mn>7</mn><mo>.</mo><mn>349</mn></mrow></math></span> and <span><math><mrow><mo>−</mo><mn>3</mn><mo>.</mo><mn>732</mn></mrow></math></span>), indicating challenges in managing resource complexity. In the short run, the negative and significant error correction term (ECT) confirms swift adjustment to equilibrium, with TI and TC showing positive impacts on NRE (coefficients of 2.329 and 3.067), reflecting immediate efficiency gains from technological advancements. The causality analysis reveals that there is unidirectional causality from TI to NRE (W-Stat: 8.243; <span><math><mover><mrow><mi>Z</mi></mrow><mrow><mo>̄</mo></mrow></mover></math></span>: 2.828; <span><math><mrow><mi>p</mi><mo>=</mo><mn>0</mn><mo>.</mo><mn>005</mn></mrow></math></span>), from NRE to financial readiness (FR) (W-Stat: 7.925; <span><math><mover><mrow><mi>Z</mi></mrow><mrow><mo>̄</mo></mrow></mover></math></span>: 2.580; <span><math><mrow><mi>p</mi><mo>=</mo><mn>0</mn><mo>.</mo><mn>010</mn></mrow></math></span>), and from NRE to DR (W-Stat: 9.515; <span><math><mover><mrow><mi>Z</mi></mrow><mrow><mo>̄</mo></mrow></mover></math></span>: 3.819; <span><math><mrow><mi>p</mi><mo>=</mo><mn>0</mn><mo>.</mo><mn>000</mn></mrow></math></span>). Similarly, REC exhibits unidirectional causality towards NRE (W-Stat: 8.511; <span><math><mover><mrow><mi>Z</mi></mrow><mrow><mo>̄</mo></mrow></mover></math></span>: 3.036; <span><math><mrow><mi>p</mi><mo>=</mo><mn>0</mn><mo>.</mo><mn>002</mn></mrow></math></span>), indicating that the adoption of renewable energy sources significantly improves resource efficiency. Unlike previous studies that focus narrowly on energy use or innovation in isolation, this study offers a comprehensive empirical framework integrating digital readiness, economic complexity, and technological innovation to assess their combined impact on NRE. The application of panel cointegration, error correction modeling, and causality analysis over a multi-decade, cross-country dataset enhances the methodological rigor and generalizability of findings. The study also demonstrates the crit

实现可持续能源管理对于应对全球气候挑战和实现联合国可持续发展目标（sdg），特别是可持续发展目标7（负担得起的清洁能源）和13（气候行动）至关重要。本文研究了资源丰富经济体中技术创新（TI）、经济复杂性（EC）、产品复杂性指数（PCI）和可再生能源消耗（REC）如何相互作用以提高自然资源效率（NRE）。利用1995年至2022年的面板数据，该研究还探讨了绿色技术、数字准备度（DR）和矿物复杂性（MC）在促进低碳未来中的作用。结果表明，从长期来看，TI和REC显著提高了NRE（系数分别为0.932和0.235），而技术复杂性（TC）和MC（系数分别为- 7.349和- 3.732）对NRE有负面影响，表明资源复杂性管理面临挑战。在短期内，负且显著的误差修正项（ECT）证实了迅速调整到平衡状态，TI和TC对NRE（系数分别为2.329和3.067）表现出正影响，反映了技术进步带来的直接效率收益。因果关系分析表明，TI与NRE （W-Stat: 8.243; Z′：2.828;p=0.005）、NRE与财务准备（FR）（W-Stat: 7.925; Z′：2.580;p=0.010）、NRE与DR （W-Stat: 9.515; Z′：3.819;p=0.000）之间存在单向因果关系。同样，REC与NRE呈单向因果关系（W-Stat: 8.511; Z: 3.036; p=0.002），表明可再生能源的采用显著提高了资源效率。与以往狭隘地关注能源使用或创新的研究不同，本研究提供了一个综合数字化准备、经济复杂性和技术创新的综合经验框架，以评估它们对NRE的综合影响。在几十年的跨国数据集上，面板协整、误差校正模型和因果关系分析的应用增强了方法的严谨性和研究结果的普遍性。该研究还证明了EC和DR在提高可再生能源效率和支持向低碳经济转型方面的关键作用。通过利用技术进步和优化可再生能源系统，本研究为旨在整合能源系统创新和可持续发展经济战略的政策制定者提供了见解。研究结果提供了对经济和技术协同作用如何推动可再生能源解决方案和促进全球气候行动的全面理解。

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