Energy Strategy Reviews最新文献_第7页

Decoding the Nexus: Energy poverty, digital economy, and efficient resource management 解读关系：能源贫困、数字经济和有效的资源管理

IF 7.9 2区工程技术 Q1 ENERGY & FUELS

Energy Strategy Reviews

Pub Date : 2026-03-01 Epub Date: 2026-02-25 DOI: 10.1016/j.esr.2025.102033

Ummara Razi , Aaron Yaw Ahali , Yuriy Bilan

In the era of escalating environmental challenges, such as climate change and resource depletion, efficient resource management is essential for fostering sustainable economic and ecological development. For newly industrialised economies (NICs), it is imperative to identify the factors influencing efficient resource management. Therefore, this aims to evaluate the effect of energy poverty, digital economy, and eco-innovation on efficient resource management (ERM) for NIC countries from 2000 to 2022, addressing a critical gap in the ERM literature. By confirming cross-sectional dependence, slope homogeneity, and the first order of integration, the study identifies cointegration among these variables. The study employed the “Method of Moments Quantile Regression (MMQR)” approach to explore the distributional heterogeneity of established correlations across different quantiles of efficient resource management. The MMQR results highlight that energy poverty, industrial efficiency, digital economy, and eco-innovation enhance ERM in newly industrialised countries. In contrast, the economic growth abates the ERM. The study's findings are crucial for formulating effective policies to reduce energy poverty and promote efficient resource management to retain sustainable development and natural resource consumption.

在气候变化和资源枯竭等环境挑战日益加剧的时代，有效的资源管理是促进经济和生态可持续发展的关键。对于新兴工业化经济体而言，确定影响资源有效管理的因素是当务之急。因此，本研究旨在评估2000年至2022年能源贫困、数字经济和生态创新对NIC国家有效资源管理（ERM）的影响，以弥补ERM文献中的一个关键空白。通过确认横截面相关性、斜率均匀性和一阶积分，研究确定了这些变量之间的协整。本研究采用“矩量分位数回归法”（MMQR）方法，探讨有效资源管理不同分位数间已建立相关性的分布异质性。MMQR结果强调，能源贫困、工业效率、数字经济和生态创新增强了新兴工业化国家的ERM。相反，经济增长削弱了汇率机制。这项研究的结果对于制定有效的政策以减少能源贫困和促进有效的资源管理以保持可持续发展和自然资源消耗至关重要。

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引用次数: 0

A framework for decision making under deep uncertainty in hard-to-abate industries: An application case for investment in a German steel plant 在难以消除的行业中，深度不确定性下的决策框架：德国钢铁厂投资的应用案例

IF 7.9 2区工程技术 Q1 ENERGY & FUELS

Energy Strategy Reviews

Pub Date : 2026-03-01 Epub Date: 2026-03-11 DOI: 10.1016/j.esr.2026.102185

Manish Gaebelein-Khanra , Marian Klobasa , Parag Patil

Decarbonising hard-to-abate industries is necessary for climate goals, yet investment choices are hindered by deep uncertainty. This study develops an ambiguity-aware investment evaluation framework that accounts for parameter uncertainty, probability ambiguity, and downside risk. Scenario-level net present values are computed under alternative electricity and hydrogen system narratives and evaluated using a loss law–invariant model-set approach. Probability ambiguity is represented by an ambiguity set of admissible scenario-probability vectors defined through per-scenario bounds implied by multiple probability views, and performance is assessed using worst-case mean and worst-case expected shortfall over this set. The framework is applied to a primary steel investment in Germany, comparing Natural Gas–DRI–EAF, imported-hydrogen DRI–EAF, and on-site electrolysis based DRI–EAF configurations. Electricity procurement prices come from an agent based market simulation for 2035, while fuel and policy inputs vary across 18 discrete scenarios. Natural Gas–DRI–EAF is most robust with a worst-case mean NPV of €10.83 bn and a 4.7% reduction from the Base expected value. Electrolyser–DRI–EAF with lower CAPEX and tariff relief approaches this benchmark with a worst-case mean NPV of €10.53 bn, and tariff relief increases worst-case mean performance by about €4.9 bn relative to no discounts. Imported-hydrogen DRI–EAF is ambiguity-fragile, with Base expected NPV of €7.82 bn falling to €4.57 bn under worst-case mean. For industrial decision makers, the framework indicates whether a pathway remains acceptable under pessimistic probability weightings and tail protection, and it identifies which parameters drive downside exposure. For policy and regulatory analysts, the remaining robustness gap even under tariff relief indicates where additional risk-sharing or cost-relief instruments are needed to improve performance in the adverse states that determine worst-case and tail outcomes. A sensitivity analysis with non-stationary second-decade price regimes confirms that the main conclusions do not rely on stationary annual cash flows.

对难以减排的行业进行脱碳是实现气候目标的必要条件，但投资选择却受到深度不确定性的阻碍。本研究开发了一个考虑参数不确定性、概率模糊性和下行风险的模糊性感知投资评估框架。在替代电力和氢系统叙述下计算情景级净现值，并使用损失定律不变模型集方法进行评估。概率模糊性由通过多个概率视图隐含的每个场景边界定义的可接受的场景概率向量的模糊性集表示，并且使用该集的最坏情况平均值和最坏情况预期不足来评估性能。该框架应用于德国的一次钢铁投资，比较了天然气DRI-EAF、进口氢气DRI-EAF和基于现场电解的DRI-EAF配置。2035年的电力采购价格来自基于代理的市场模拟，而燃料和政策输入在18个离散情景中有所不同。天然气- dri - eaf最稳健，最坏情况下的平均净现值为108.3亿欧元，比基本预期值减少4.7%。具有较低资本支出和关税减免的电解铝- dri - eaf接近这一基准，最坏情况下的平均净现值为105.3亿欧元，相对于没有折扣，关税减免使最坏情况下的平均绩效提高了约49亿欧元。进口氢气dr - eaf是模糊脆弱的，在最坏情况下，基础预期净现值为78.2亿欧元，降至45.7亿欧元。对于行业决策者来说，该框架表明在悲观概率权重和尾部保护下，路径是否仍然可以接受，并确定哪些参数会导致下行风险。对于政策和监管分析师来说，即使在关税减免的情况下，仍然存在的稳健性差距表明，在决定最坏情况和尾部结果的不利状态下，需要额外的风险分担或成本减免工具来改善绩效。对非平稳的第二个十年价格机制进行的敏感性分析证实，主要结论并不依赖于固定的年度现金流量。

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引用次数: 0

Inexpensive renewable electricity enables Saudi Arabia's fuel price reforms 廉价的可再生电力推动了沙特阿拉伯的燃料价格改革

IF 7.9 2区工程技术 Q1 ENERGY & FUELS

Energy Strategy Reviews

Pub Date : 2026-03-01 Epub Date: 2026-02-02 DOI: 10.1016/j.esr.2026.102081

Walid Matar

Saudi Arabia is currently implementing fuel price reforms. The reforms are being executed in phases, where the ultimate goal is to have fuel prices approach their market equivalent values. Using the KAPSARC Energy Model, this analysis shows that such reforms would be more costly for Saudi Arabia without the availability and cost reductions of renewable electricity technologies. Solar photovoltaic technologies, in particular, have made enacting fuel price reforms more tenable. As the use of oil products for power generation and industrial processes cease due to price reforms, renewable technologies mitigate the scarcity of natural gas. For instance, lower natural gas use by the electricity sector would result in a market-clearing (meaning, demand equals supply) natural gas price of 3–4 $/mmBtu in 2040 with the deployment of renewable technologies. The projected rise in Saudi natural gas supply and these prices are sufficient to accommodate nearly 50 GW of renewable electricity capacity. Comparatively, this natural gas price would be above 7 $/mmBtu without renewable electricity. The advent of inexpensive renewable electricity lowers fuel costs for all natural gas users in industry and utilities. Moreover, the marginal electricity generation cost with renewable electricity drops by 30 %, on average. While renewable electricity reduces energy system costs, the magnitude of these benefits is highly dependent on the exogenously-defined domestic gas availability and the global LNG price. These findings suggest aligning fuel price regulations with renewable electricity deployment to minimize cost shocks and reduce oil use in industrial and utility sectors.

沙特阿拉伯目前正在实施燃油价格改革。改革正在分阶段实施，最终目标是使燃油价格接近市场等值。利用KAPSARC能源模型，这一分析表明，如果没有可再生电力技术的可用性和成本的降低，这种改革对沙特阿拉伯来说将会更加昂贵。特别是太阳能光伏技术，使得燃料价格改革更加站得住脚。由于价格改革，石油产品在发电和工业过程中的使用已经停止，可再生能源技术缓解了天然气的短缺。例如，随着可再生能源技术的部署，电力部门天然气使用量的减少将导致市场出清（即需求等于供应），到2040年天然气价格将达到3-4美元/百万英热。预计沙特天然气供应的增长和这些价格足以容纳近50 吉瓦的可再生电力容量。相比之下，如果没有可再生电力，天然气价格将超过7美元/百万英热。廉价的可再生电力的出现降低了工业和公用事业中所有天然气用户的燃料成本。此外，可再生电力的边际发电成本平均下降了30% %。虽然可再生电力降低了能源系统成本，但这些效益的大小高度依赖于外部定义的国内天然气供应和全球液化天然气价格。这些发现建议将燃料价格法规与可再生电力部署相结合，以最大限度地减少成本冲击，并减少工业和公用事业部门的石油使用。

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引用次数: 0

How the facets of energy security impact the support for energy sources: Evidence from UK households 能源安全的各个方面如何影响对能源的支持：来自英国家庭的证据

IF 7.9 2区工程技术 Q1 ENERGY & FUELS

Energy Strategy Reviews

Pub Date : 2026-03-01 Epub Date: 2026-03-04 DOI: 10.1016/j.esr.2026.102152

Andreas Markoulakis, Eleanya Nduka

Using UK household data, we examine empirically how different facets of energy security, energy vulnerability, affordability, reliability and imports dependency impact the support for three different energy sources: renewables, nuclear and shale gas extraction. We find that each facet can have a differential impact in the probability of support for each energy source and in general, as energy security concerns decline, households are becoming less likely to support each energy source, however, the effects are larger for nuclear and shale gas compared to renewables. Our findings are robust to potential endogeneity concerns which are addressed by using instrumental variables. The above results may serve as valuable evidence for policy appraisal, providing policymakers with insights into the varying impacts of different aspects of energy security when formulating future energy policies aimed at achieving net-zero targets.

利用英国家庭数据，我们实证研究了能源安全、能源脆弱性、可负担性、可靠性和进口依赖的不同方面如何影响对三种不同能源的支持：可再生能源、核能和页岩气开采。我们发现，每个方面对支持每种能源的可能性都有不同的影响，总的来说，随着能源安全问题的下降，家庭支持每种能源的可能性越来越小，然而，与可再生能源相比，核能和页岩气的影响更大。我们的发现是稳健的潜在内生性问题，这是通过使用工具变量来解决。上述结果可以作为政策评估的宝贵证据，为政策制定者在制定旨在实现净零目标的未来能源政策时，提供对能源安全不同方面的不同影响的见解。

引用次数: 0

Consumer vs producer subsidies for renewable energy: The role of perception efficiency and policy portfolio in a power supply chain 消费者与生产者对可再生能源的补贴：感知效率和政策组合在电力供应链中的作用

IF 7.9 2区工程技术 Q1 ENERGY & FUELS

Energy Strategy Reviews

Pub Date : 2026-03-01 Epub Date: 2026-01-28 DOI: 10.1016/j.esr.2026.102086

Daoming Dai , Lingyu Huang , Lianbiao Cui

The global transition to renewable energy (RE) hinges on the design of effective and economically efficient policy portfolios. This study develops a Stackelberg game-theoretic model of a power supply chain—comprising a generation company, a retailer, and consumers—to dissect the intricate relationships between subsidy policies, market mechanisms, and consumer behavioral characteristics. We rigorously evaluate three policy scenarios: No Subsidy (N), Subsidized Consumers (C), and Subsidized Generation Companies (G). The model explicitly quantifies subsidy perception efficiency gap between consumers and producers, and it embeds this analysis within an integrated framework combining Renewable Energy Certificate (REC) trading and Renewable Portfolio Standards (RPS). Our findings reveal that the effectiveness of a subsidy is determined not by its target (consumer vs. generation company) but by the recipient's perception efficiency. Subsidies enhance social welfare only when this efficiency surpasses a critical threshold. Furthermore, consumer environmental preferences emerge as a consistently positive driver of green power adoption and social welfare across all scenarios. We also identify a welfare-maximizing threshold for REC prices, whereas overly stringent RPS mandates are shown to be detrimental. These insights provide a robust theoretical foundation for designing coordinated, consumer-aware RE policies that can accelerate the energy transition while optimizing social welfare.

全球向可再生能源的过渡取决于有效和经济高效的政策组合的设计。本研究建立了由发电公司、零售商和消费者组成的电力供应链的Stackelberg博弈论模型，以剖析补贴政策、市场机制和消费者行为特征之间的复杂关系。我们严格评估了三种政策情景：无补贴(N)、补贴消费者(C)和补贴发电公司(G)。该模型明确量化了消费者和生产者之间的补贴感知效率差距，并将这一分析嵌入到可再生能源证书（REC）交易和可再生能源投资组合标准（RPS）的综合框架中。我们的研究结果表明，补贴的有效性不是由其目标（消费者与发电公司）决定的，而是由接受者的感知效率决定的。只有当这种效率超过一个临界阈值时，补贴才能提高社会福利。此外，消费者的环境偏好在所有情况下都是绿色能源采用和社会福利的积极驱动因素。我们还确定了REC价格的福利最大化门槛，而过度严格的RPS授权被证明是有害的。这些见解为设计协调的、消费者意识到的可再生能源政策提供了坚实的理论基础，这些政策可以加速能源转型，同时优化社会福利。

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引用次数: 0

Data-driven smart governance for dual-dimensional optimization of urban renewable energy systems: Enhancing transition depth and breadth 数据驱动的城市可再生能源系统双维度优化智能治理：提升转型深度和广度

IF 7.9 2区工程技术 Q1 ENERGY & FUELS

Energy Strategy Reviews

Pub Date : 2026-03-01 Epub Date: 2026-01-28 DOI: 10.1016/j.esr.2026.102087

Hongti Song , Wei Chen

Data governance is increasingly recognized as a critical institutional instrument for facilitating energy system transformation, yet its role in reshaping the structural characteristics of urban renewable energy transitions remains insufficiently understood. This study exploits China’s National Big Data Pilot (NBDP) policy as a quasi-natural experiment and employs panel data from 291 Chinese cities spanning 2008–2022 to investigate the impact of data governance on urban renewable energy transitions. Employing a double machine learning (DML) framework, we identify the causal effects of the NBDP on multidimensional transition outcomes. The results show that the policy significantly accelerates urban renewable energy transition, with the strongest effects observed in transition breadth, followed by depth and level. Mechanism analysis reveals that renewable energy technological innovation serves as a key mediating channel, promoting substitution deepening while partially constraining short-term diversification due to path dependence. In contrast, heightened government attention to green development exerts a negative indirect effect on transition level and depth and does not mediate diversification outcomes. Further analysis indicates that the policy effects are significantly amplified in cities with more advanced digital infrastructure and higher energy demand intensity. By introducing a dual-dimensional “depth–breadth” framework, this study extends existing measures of energy transition and provides robust causal evidence on how digital governance reshapes the structural evolution of urban energy systems.

数据治理越来越被认为是促进能源系统转型的关键制度工具，但其在重塑城市可再生能源转型结构特征方面的作用仍未得到充分认识。本研究利用中国国家大数据试点（NBDP）政策作为准自然实验，采用2008-2022年291个中国城市的面板数据，研究数据治理对城市可再生能源转型的影响。采用双机器学习（DML）框架，我们确定了NBDP对多维转换结果的因果影响。结果表明：政策显著加速了城市可再生能源转型，其影响在转型广度上最强，深度次之，水平次之；机制分析表明，可再生能源技术创新在促进替代深化的同时，也在一定程度上抑制了路径依赖导致的短期多元化。政府对绿色发展的高度重视对转型水平和深度产生负向的间接影响，对多元化结果没有中介作用。进一步分析表明，在数字基础设施更先进、能源需求强度更高的城市，政策效应显著放大。通过引入二维“深度-广度”框架，本研究扩展了现有的能源转型措施，并为数字治理如何重塑城市能源系统的结构演变提供了强有力的因果证据。

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引用次数: 0

Recent advancements and perspectives in lithium-ion battery technology 锂离子电池技术的最新进展与展望

IF 7.9 2区工程技术 Q1 ENERGY & FUELS

Energy Strategy Reviews

Pub Date : 2026-03-01 Epub Date: 2026-01-24 DOI: 10.1016/j.esr.2026.102064

Siddharth Kulkarni, Keru Duan, Gu Pang, Ahmad Bhatti

This paper aims to present a timely review of recent developments and perspectives on Lithium-Ion Battery (LIB) technologies regarding sustainable development, electrochemical efficiency, and machine learning models for forecasting the availability of services such as vehicle-to-home. The paper argues that the world is increasingly demanding sustainable, reliable energy sources because current sources are unstable and fossil-fuel-dependent. Research shows that 85 % or more of the world's energy comes from non-renewable sources, including natural gas, coal, and oil, underscoring the world's persistent reliance on fossil fuels. This study conducts a literature review on recent advances in sustainable LIB development, emphasising emerging chemical technologies, novel energy materials, and innovations in battery manufacturing. Findings indicate a growing demand for LIBs driven by environmental sustainability goals. However, LIB production was constrained by resource scarcity and rising manufacturing costs. To address these issues, researchers are exploring next-generation chemistries, improved material design, and enhanced recycling processes. Additionally, advancements in machine learning and battery-material characterisation are essential to meet evolving consumer demands, including for vehicle-to-home applications.

本文旨在及时回顾锂离子电池（LIB）技术的最新发展和前景，包括可持续发展、电化学效率和用于预测车辆到家庭等服务可用性的机器学习模型。这篇论文认为，由于目前的能源不稳定且依赖化石燃料，世界对可持续、可靠的能源的需求越来越大。研究表明，世界上85%或更多的能源来自不可再生资源，包括天然气、煤炭和石油，这突显了世界对化石燃料的持续依赖。本研究对可持续锂电池发展的最新进展进行了文献综述，重点介绍了新兴的化学技术、新型能源材料和电池制造的创新。研究结果表明，在环境可持续性目标的驱动下，对lib的需求不断增长。然而，锂离子电池的生产受到资源稀缺和制造成本上升的制约。为了解决这些问题，研究人员正在探索下一代化学，改进材料设计和增强回收过程。此外，机器学习和电池材料特性的进步对于满足不断变化的消费者需求至关重要，包括车辆到家庭的应用。

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引用次数: 0

Implications of defining exogenous variables in Energy System Modeling with Integrated Assessment Models for transition planning 用综合评估模型定义能源系统模型中外生变量对转型规划的影响

IF 7.9 2区工程技术 Q1 ENERGY & FUELS

Energy Strategy Reviews

Pub Date : 2026-03-01 Epub Date: 2026-02-14 DOI: 10.1016/j.esr.2026.102138

Carlos A.A. Fernandez Vazquez , Francisco Flores , Ray A. Rojas Candia , Julio Pascual , Felipe Feijoo , Sylvain Quoilin

The sustainable transition of energy systems heavily relies on models that provide diverse scopes and applications. This study explores how two modeling approaches can work in tandem and complement each other to provide a more robust framework for analyzing the development of energy systems at the country level. Specifically, we consider an Integrated Assessment Model (GCAM), to evaluate alternative transition scenarios in a country from a multi-sectoral level, and an Energy System Model (PyPSA-Earth), to optimize the expansion of the power system with high geographical and temporal resolution. In this study, we present tailored versions of these tools to analyze Bolivia as the case study, GCAM-Bolivia and PyPSA-BO. Our method employs a unidirectional soft-linking process, using carbon budgets and projected energy demands as the connecting parameters between models. In this sense, GCAM-Bolivia is used to derive six alternative development scenarios based on emission reduction targets until 2050, while PyPSA-BO is used to optimize the electric system expansion, including generation, storage, and transmission capacities. Results show that, regardless of the scenario, solar PV is the dominant technology for capacity expansion in the future and that the growth of the electric sector appears to have a non-linear relation with the emission reduction targets for the energy sector, where only reduction targets above 40% trigger an intensive electrification process. In these cases, a significant expansion of storage and transmission capacities distributed across the country is required to provide flexibility in the system.

能源系统的可持续转型在很大程度上依赖于提供不同范围和应用的模型。本研究探讨了两种建模方法如何协同工作并相互补充，从而为分析国家一级能源系统的发展提供一个更有力的框架。具体来说，我们考虑了一个综合评估模型（GCAM）和一个能源系统模型（PyPSA-Earth），前者从多部门层面评估一个国家的替代转型情景，后者以高地理和时间分辨率优化电力系统的扩张。在本研究中，我们提供了这些工具的定制版本来分析玻利维亚作为案例研究，GCAM-Bolivia和PyPSA-BO。我们的方法采用单向软链接过程，使用碳预算和预计能源需求作为模型之间的连接参数。从这个意义上说，GCAM-Bolivia基于2050年的减排目标推导出了6种替代发展方案，而PyPSA-BO用于优化电力系统扩容，包括发电、存储和传输能力。结果表明，无论在何种情况下，太阳能光伏发电都是未来产能扩张的主导技术，电力部门的增长似乎与能源部门的减排目标存在非线性关系，只有减排目标超过40%才能触发密集的电气化过程。在这些情况下，需要大幅度扩大分布在全国各地的存储和传输能力，以提供系统的灵活性。

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引用次数: 0

Model-based calibration of the elasticity of substitution in energy under high flexibility 基于模型的高柔性能量替代弹性标定

IF 7.9 2区工程技术 Q1 ENERGY & FUELS

Energy Strategy Reviews

Pub Date : 2026-03-01 Epub Date: 2026-02-19 DOI: 10.1016/j.esr.2026.102116

Thomas Baldauf, Hans-Christian Gils, Jens Schmugge, Patrick Jochem

Macroeconomic models of the energy transition depend crucially on elasticity of substitution (EOS) parameters between dirty and clean energy inputs, which are, however, hard to calibrate for future energy systems. Thus, in this paper, we seek determining these values based on a numerical bottom-up optimization model with European scope and a large number of flexibility options. Further, we study the role of flexibility technologies in alternative forms of a macroeconomic production function, considering the EOS as an endogenous function of the renewable energy share and of flexibility installations. Our research therefore provides parameter values for models with endogenous EOS. Nevertheless, when lump-summing flexible inputs into clean inputs, a simple constant elasticity of substitution (CES) function describes the data comparatively well, such that we cannot reject the validity of production functions with exogenous EOS for macroeconomic transition models.

能源转型的宏观经济模型主要依赖于肮脏能源和清洁能源输入之间的替代弹性（EOS）参数，然而，这些参数很难针对未来的能源系统进行校准。因此，在本文中，我们寻求基于具有欧洲范围和大量灵活性选项的数值自下而上优化模型来确定这些值。进一步，我们研究了柔性技术在宏观经济生产函数的替代形式中的作用，将EOS视为可再生能源份额和柔性装置的内生函数。因此，我们的研究为内源性EOS模型提供了参数值。然而，当将柔性投入集中到清洁投入时，一个简单的恒定替代弹性（CES）函数相对较好地描述了数据，因此我们不能拒绝具有外生EOS的生产函数对宏观经济转型模型的有效性。

引用次数: 0

Two birds with one stone: Do poverty alleviation policies reduce carbon emissions in poverty-stricken counties? 一举两得：扶贫政策能减少贫困县的碳排放吗？

IF 7.9 2区工程技术 Q1 ENERGY & FUELS

Energy Strategy Reviews

Pub Date : 2026-03-01 Epub Date: 2026-02-14 DOI: 10.1016/j.esr.2026.102141

Yixin Sun , Jianhui Cong , Zhou Zhou , Limin Han

Poverty eradication and climate mitigation are two central challenges facing developing countries in the process of rural development. Targeted poverty alleviation policy (TPAP) is aimed at ending extreme poverty and may deliver carbon emission reductions beyond its primary policy objective. Hence, we treat China's TPAP as a quasi-natural experiment and employ a Difference-in-Differences (DID) framework to examine the impact of poverty alleviation policies on carbon emissions in poverty-stricken counties. We further examine heterogeneity in the effects of poverty alleviation policies across income levels and targeted renewable energy policies. The empirical findings reveal that the TPAP significantly reduced carbon emissions in poverty-stricken counties relative to the control group, with an average reduction of 0.36%. However, some industry-specific policies, such as the Photovoltaic Poverty Alleviation program, led to an increase in carbon emissions in pilot counties, with a net effect of 0.102. Mechanism analysis demonstrates that industrial poverty alleviation promotes the development of non-agricultural industries. Additional heterogeneity analysis reveals that counties with lower baseline income experienced larger emission reductions, consistent with greater scope for energy structure adjustment and marginal substitution away from traditional energy sources. Overall, this study highlights the heterogeneous climate impacts of poverty alleviation policies and provides evidence-based insights for designing poverty reduction strategies.

消除贫困和减缓气候变化是发展中国家在农村发展过程中面临的两大核心挑战。精准扶贫政策旨在消除极端贫困，并可能实现超出其主要政策目标的碳减排。因此，我们将中国的TPAP作为一个准自然实验，并采用差异中差异（DID）框架来考察扶贫政策对贫困县碳排放的影响。我们进一步研究了不同收入水平的扶贫政策和有针对性的可再生能源政策的影响的异质性。实证结果表明，实施TPAP后，贫困县的碳排放量相对于对照组显著减少，平均减少0.36%。然而，一些特定行业的政策，如光伏扶贫项目，导致试点县的碳排放量增加，净效应为0.102。机制分析表明，产业扶贫促进了非农产业的发展。另一项异质性分析表明，基线收入较低的县的减排幅度更大，这与能源结构调整和传统能源边际替代的空间更大一致。总体而言，本研究突出了扶贫政策的异质性气候影响，并为减贫战略的设计提供了基于证据的见解。

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引用次数: 0