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19 pages, 1037 KB

Open AccessArticle

Effects of Manufacturing Agglomeration on Pollutant Emissions: The Role of Energy Intensity in China

by Yidai Feng and Huaxi Yuan

Sustainability 2025, 17(24), 11225; https://doi.org/10.3390/su172411225 - 15 Dec 2025

Viewed by 391

Abstract

Manufacturing agglomeration (MA) is an important driving force for both sustained economic expansion and structural upgrading. Understanding whether and how MA contributes to energy conservation and pollutant mitigation is essential for promoting China’s green transition and offers valuable insight for emerging economies pursuing [...] Read more.

Manufacturing agglomeration (MA) is an important driving force for both sustained economic expansion and structural upgrading. Understanding whether and how MA contributes to energy conservation and pollutant mitigation is essential for promoting China’s green transition and offers valuable insight for emerging economies pursuing sustainable growth. The paper first theoretically examines the mechanisms linking MA, energy intensity (EI), and pollutant emission (PE). To overcome the regression bias caused by the heterogeneity of pollutant types among cities, the comprehensive index of PE is constructed. The empirical analysis yields two principal findings. First, MA significantly reduces PE, and this relationship remains robust after a series of tests. Second, EI plays a significant mediating role between MA and PE, that is, MA can achieve the reduction targets of PE by reducing EI. Therefore, in addition to its established role in fostering economic growth, MA should be utilized for its environmental advantages. Policymakers should give greater weight to the capacity of MA to enhance energy conservation and emission reduction, so as to stimulate the positive interaction among MA, EI, and PE, and thereby formulate more differentiated policies. Full article

(This article belongs to the Special Issue Advances in Energy Economics, Energy Policy and Sustainability Transition)

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21 pages, 538 KB

Open AccessArticle

The Impact of New Energy Demonstration Cities in China on Inclusive Green Growth: Evidence from Causal Inference Based on Double Machine Learning

by Yafei He, Bixuan Sun and Shan Huang

Sustainability 2025, 17(24), 11155; https://doi.org/10.3390/su172411155 - 12 Dec 2025

Viewed by 420

Abstract

The construction of New Energy Demonstration Cities (NEDC) represents a crucial policy initiative in advancing China’s energy transition and serves as an institutional innovation to promote inclusive green growth (IGG) at the urban level. Based on panel data for 278 prefecture-level cities in [...] Read more.

The construction of New Energy Demonstration Cities (NEDC) represents a crucial policy initiative in advancing China’s energy transition and serves as an institutional innovation to promote inclusive green growth (IGG) at the urban level. Based on panel data for 278 prefecture-level cities in China from 2011 to 2021, this study employs a double machine learning model to identify the causal impact of the NEDC on IGG and to further explore the underlying mechanisms. The empirical results show that the policy significantly enhances IGG overall. However, the positive effects are mainly observed in non-resource-based and non-old industrial cities, while the impacts in resource-based and old industrial cities are statistically insignificant. This finding indicates that structural constraints such as the resource curse and Dutch disease remain evident in these regions. Mechanism analysis reveals that the NEDC promotes IGG primarily through technological innovation and employment creation, forming a chained mediating pathway of ‘NEDC → technological innovation → employment creation → IGG.’ This study enriches the literature on the economic effects of energy reform pilot policies and provides empirical evidence and policy insights for achieving IGG goals in both China and other countries. Full article

(This article belongs to the Special Issue Advances in Energy Economics, Energy Policy and Sustainability Transition)

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22 pages, 681 KB

Open AccessArticle

Government Subsidies and the Competitiveness of Energy Storage Enterprises: The Moderating Effect of Electricity Price

by Manli Zhao, Xinhua Zhang, Qianqian Zhang and Li Luo

Sustainability 2025, 17(23), 10789; https://doi.org/10.3390/su172310789 - 2 Dec 2025

Viewed by 466

Abstract

Compared with single indicators such as total factor productivity and financial performance, enterprise competitiveness represents the pivotal factor for energy storage enterprises (ESEs) to survive, develop and maintain a leading position in the market. Government subsidies are crucial for guiding the development of [...] Read more.

Compared with single indicators such as total factor productivity and financial performance, enterprise competitiveness represents the pivotal factor for energy storage enterprises (ESEs) to survive, develop and maintain a leading position in the market. Government subsidies are crucial for guiding the development of the energy storage industry. As countries globally increase their financial backing for ESEs, efficiently utilizing these subsidies has become a major focus. In this study, we examine the impact and mechanisms of government subsidies on the competitiveness of ESEs, using panel data from 248 listed ESEs in China between 2014 and 2023. Employing a range of analytical methods, including two-way fixed effects regression, instrumental variable estimation, and propensity score matching (PSM) tests, the findings demonstrate that government subsidies significantly enhance the competitiveness of ESEs, particularly for non-state-owned ESEs, energy storage system integration enterprises, and ESEs in resource-rich provinces. Further analysis indicates that research and development (R&D) expenditure and financial constraints act as key channels through which subsidies influence competitiveness. Furthermore, electricity prices exert a positive effect on the competitiveness of ESEs, with government subsidies and electricity prices exhibiting a significant substitution relationship in this regard. These findings offer valuable insights for exploring the role of government subsidies in advancing the sustainable development of the energy storage industry and supporting the transition towards achieving dual-carbon goals, while also providing important references for the development of the energy storage industry in other emerging economies. Full article

(This article belongs to the Special Issue Advances in Energy Economics, Energy Policy and Sustainability Transition)

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24 pages, 3177 KB

Open AccessArticle

National-Scale Electricity Consumption Forecasting in Turkey Using Ensemble Machine Learning Models: An Interpretability-Centered Approach

by Ahmet Sabri Öğütlü

Sustainability 2025, 17(21), 9829; https://doi.org/10.3390/su17219829 - 4 Nov 2025

Viewed by 865

Abstract

This study presents an advanced, interpretability-focused machine learning framework for forecasting electricity consumption in Turkey over the period 2016–2024. The proposed approach is based on a high-dimensional dataset that incorporates a diverse set of variables, including sector-specific electricity usage (residential, industrial, lighting, agricultural, [...] Read more.

This study presents an advanced, interpretability-focused machine learning framework for forecasting electricity consumption in Turkey over the period 2016–2024. The proposed approach is based on a high-dimensional dataset that incorporates a diverse set of variables, including sector-specific electricity usage (residential, industrial, lighting, agricultural, and commercial), electricity production, trade metrics (imports and exports in USD), and macroeconomic indicators such as the Industrial Production Index (IPI). A comprehensive set of eight state-of-the-art regression algorithms—including ensemble models such as CatBoost, LightGBM, Random Forest, and Bagging Regressor—were developed and rigorously evaluated. Among these, CatBoost emerged as the most accurate model, achieving R² values of 0.9144 for electricity production and 0.8247 for electricity consumption. Random Forest and LightGBM followed closely, further confirming the effectiveness of tree-based ensemble methods in capturing nonlinear relationships in complex datasets. To enhance model interpretability, SHAP (SHapley Additive exPlanations) and traditional feature importance analyses were applied, revealing that residential electricity consumption was the dominant predictor across all models, accounting for more than 70% of the variance explained in consumption forecasts. In contrast, macroeconomic indicators and temporal variables showed marginal contributions, suggesting that electricity demand in Turkey is predominantly driven by internal sectoral consumption trends rather than external economic or seasonal dynamics. In addition to historical evaluation, scenario-based forecasting was conducted for the 2025–2030 period, incorporating varying assumptions about economic growth and population trends. These scenarios demonstrated the model’s robustness and adaptability to different future trajectories, offering valuable foresight for strategic energy planning. The methodological contributions of this study lie in its integration of high-dimensional, multivariate data with transparent, interpretable machine learning models, making it a robust and scalable decision-support tool for policymakers, energy authorities, and infrastructure planners aiming to enhance national energy resilience and policy responsiveness. Full article

(This article belongs to the Special Issue Advances in Energy Economics, Energy Policy and Sustainability Transition)

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20 pages, 1164 KB

Open AccessArticle

Public Acceptance and Willingness to Pay for Nuclear Energy in Saudi Arabia

by Fahad Alzahrani, Rady Tawfik, Latefa A. Alnaim and Raga M. Elzaki

Sustainability 2025, 17(17), 7917; https://doi.org/10.3390/su17177917 - 3 Sep 2025

Cited by 1 | Viewed by 2193

Abstract

This study investigates the public acceptance and willingness to pay (WTP) for nuclear energy in Saudi Arabia, a country seeking to diversify its energy portfolio under Vision 2030. Utilizing a cross-sectional survey of 403 residents, the research employs descriptive statistics, regression analysis, and [...] Read more.

This study investigates the public acceptance and willingness to pay (WTP) for nuclear energy in Saudi Arabia, a country seeking to diversify its energy portfolio under Vision 2030. Utilizing a cross-sectional survey of 403 residents, the research employs descriptive statistics, regression analysis, and a SWOT analysis to explore the socio-economic and perceptual drivers of public attitudes. The findings reveal that 82.4% of participants support nuclear energy, with a mean WTP of 38.2% of their monthly electricity bill for its development. Key factors positively influencing acceptance include age and knowledge about nuclear energy, while environmental concerns and being married are associated with lower support. Notably, trust in government oversight (64.8%) and the prospect of a new energy source (62.7%) are major reasons for support, whereas health and environmental risks (74.6%) are the primary concerns for opponents. This study provides crucial, evidence-based insights for policymakers, marking the first Saudi-specific research to jointly examine WTP, acceptance determinants through econometric modeling, and strategic implications via SWOT analysis, highlighting the need for targeted public engagement and transparent communication strategies to address public concerns and ensure the successful and sustainable integration of nuclear energy into Saudi Arabia’s energy mix. Full article

(This article belongs to the Special Issue Advances in Energy Economics, Energy Policy and Sustainability Transition)

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44 pages, 708 KB

Open AccessArticle

Industrial Intellectual Property Reform Strategy, Manufacturing Craftsmanship Spirit, and Regional Energy Intensity

by Siyu Liu, Juncheng Jia, Chenxuan Yu and Kun Lv

Sustainability 2025, 17(17), 7725; https://doi.org/10.3390/su17177725 - 27 Aug 2025

Viewed by 961

Abstract

To systematically reveal the influence mechanisms and spatial effects of industrial intellectual property (IP) reform strategies and manufacturing craftsmanship spirit on regional energy intensity, this study aims to provide theoretical support and practical pathways for emerging market economies pursuing dual goals of energy [...] Read more.

To systematically reveal the influence mechanisms and spatial effects of industrial intellectual property (IP) reform strategies and manufacturing craftsmanship spirit on regional energy intensity, this study aims to provide theoretical support and practical pathways for emerging market economies pursuing dual goals of energy efficiency governance and manufacturing transformation. Based on a “technology–culture synergistic innovation ecology” theoretical framework, the study deepens the understanding of energy intensity governance and introduces two spatial weight matrices—the economic distance matrix and the nested economic–geographic matrix—to uncover the spatial heterogeneity of policy and cultural effects. Using panel data from 30 Chinese provinces from 2010 to 2022 (excluding Tibet, Hong Kong, Macao, and Taiwan), we construct an index of manufacturing craftsmanship spirit (CSM) and its four dimensions—excellence in detail, persistent dedication, breakthrough orientation, and innovation inheritance—via the entropy method. Empirical analysis is conducted through Spatial Difference-in-Differences (SDID) and Double Machine Learning (DML) models. The results show that: (1) Industrial IP reform strategies significantly reduce local energy intensity through improved property rights definition and technology transaction mechanisms, but may increase energy intensity in economically proximate regions due to intensified technological competition. (2) All four dimensions of craftsmanship spirit indirectly mitigate regional energy intensity via distinct pathways, with particularly strong mediating effects from persistent dedication and innovation inheritance. In contrast, breakthrough orientation shows no significant impact, possibly due to limitations from the current stage of the technology lifecycle. (3) Spatial spillover effects are heterogeneous: under the nested economic–geographic matrix, IP reform strategies reduce neighboring regions’ energy intensity through synergistic effects, while under the economic distance matrix, competitive spillovers lead to an increase in adjacent energy intensity. Based on these findings, we propose the following: deepening IP reform strategies to build a technology–culture synergistic ecosystem; enhancing regional policy coordination to avoid technology lock-in; systematically cultivating the core of craftsmanship spirit; and establishing a dynamic incentive mechanism for breakthrough orientation. These measures can jointly drive systemic improvements in regional energy efficiency. Full article

(This article belongs to the Special Issue Advances in Energy Economics, Energy Policy and Sustainability Transition)

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31 pages, 1606 KB

Open AccessArticle

Investments, Economics, Renewables and Population Versus Carbon Emissions in ASEAN and Larger Asian Countries: China, India and Pakistan

by Simona-Vasilica Oprea, Adela Bâra and Irina Alexandra Georgescu

Sustainability 2025, 17(14), 6628; https://doi.org/10.3390/su17146628 - 20 Jul 2025

Cited by 1 | Viewed by 1601

Abstract

Our research explores the dynamic relationship between CO₂ emissions and four major influencing factors: foreign direct investment (FDI), economic growth (GDP), renewable energy consumption (REN) and population (POP) in the Association of Southeast Asian Nations (ASEAN) and three large Asian countries—China, India [...] Read more.

Our research explores the dynamic relationship between CO₂ emissions and four major influencing factors: foreign direct investment (FDI), economic growth (GDP), renewable energy consumption (REN) and population (POP) in the Association of Southeast Asian Nations (ASEAN) and three large Asian countries—China, India and Pakistan, collectively referred to as LACs (larger Asian countries), from 1990 to 2022. The study has three main objectives: (1) to assess the short-run and long-run effects of GDP, FDI, REN and POP on CO₂ emissions; (2) to compare the adjustment speeds and environmental policy responsiveness between ASEAN and LAC regions; and (3) to evaluate the role of renewable energy in mitigating environmental degradation. Against the backdrop of increasing environmental challenges and divergent development paths in Asia, this research contributes to the literature by applying a dynamic heterogeneous panel autoregressive distributed lag (panel ARDL) model. Unlike traditional static panel models, the panel ARDL model captures both long-run equilibrium relationships and short-run adjustments, allowing for country-specific dynamics. The results reveal a significant long-run cointegration among the variables. The error correction term (ECT) indicates a faster adjustment to equilibrium in LACs (−1.18) than ASEAN (−0.37), suggesting LACs respond more swiftly to long-run disequilibria in emissions-related dynamics. This may reflect more responsive policy mechanisms, stronger institutional capacities or more aggressive environmental interventions in LACs. In contrast, the slower adjustment in ASEAN highlights potential structural rigidities or delays in implementing effective policy responses, emphasizing the need for enhanced regulatory frameworks and targeted climate strategies to improve policy intervention efficiency. Results show that GDP and FDI increase emissions in both regions, while REN reduces them. POP is insignificant in ASEAN but increases emissions in LACs. These results provide insights into the relative effectiveness of policy instruments in accelerating the transition to a low-carbon economy, highlighting the need for differentiated strategies that align with each country’s institutional capacity, development stage and energy structure. Full article

(This article belongs to the Special Issue Advances in Energy Economics, Energy Policy and Sustainability Transition)

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20 pages, 1079 KB

Open AccessArticle

Green Finance and Energy Structure Transition: Evidence from China

by Wenhua Xu, Qixiang Yuan, Naixin Chen and Jian Ye

Sustainability 2025, 17(11), 4838; https://doi.org/10.3390/su17114838 - 24 May 2025

Cited by 6 | Viewed by 4498

Abstract

To achieve high-quality development, the Chinese government has proposed the establishment of Green Finance Reform and Innovation Pilot Zones (GFRIPZs). Green finance enhances environmental governance, guides capital flows, and supports sustainable economic growth. Against the backdrop of the “dual carbon” goals (carbon peaking [...] Read more.

To achieve high-quality development, the Chinese government has proposed the establishment of Green Finance Reform and Innovation Pilot Zones (GFRIPZs). Green finance enhances environmental governance, guides capital flows, and supports sustainable economic growth. Against the backdrop of the “dual carbon” goals (carbon peaking and carbon neutrality), this study examines whether green finance significantly drives urban energy structure transition and explores its underlying mechanisms. Leveraging the GFRIPZ policy as a quasi-natural experiment, we construct a multi-period Difference-in-Differences (DID) model to systematically analyze the impact of green finance on energy structure transition. The findings reveal that the GFRIPZ policy significantly accelerates urban energy structure transition, with stronger effects observed in resource-based cities, central and western regions, and cities with higher administrative levels. Green finance drives this transition through the mediating effects of green technological innovation and resource allocation efficiency, while the digital economy further amplifies its positive impact. This study concludes that green finance effectively promotes urban energy structure transition and supports high-quality economic development. These findings provide empirical evidence and policy insights for advancing China’s energy revolution and achieving its climate objectives. Full article

(This article belongs to the Special Issue Advances in Energy Economics, Energy Policy and Sustainability Transition)

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29 pages, 2887 KB

Open AccessArticle

Evaluating the Role of Next-Generation Productive Forces in Mitigating Carbon Lock-In: Evidence from Regional Disparities in China

by Chenchen Song, Zhiling Guo, Xiaoyue Ma, Jijiang He and Zhengguang Liu

Sustainability 2025, 17(9), 4241; https://doi.org/10.3390/su17094241 - 7 May 2025

Viewed by 1184

Abstract

Carbon lock-in (CLI), defined as the structural persistence of fossil-fuel-based systems, poses a significant barrier to decarbonization. As CLI continues to impede China’s progress toward carbon neutrality, understanding the role of next-generation productive forces (NGPFs) in breaking this path dependence has become increasingly [...] Read more.

Carbon lock-in (CLI), defined as the structural persistence of fossil-fuel-based systems, poses a significant barrier to decarbonization. As CLI continues to impede China’s progress toward carbon neutrality, understanding the role of next-generation productive forces (NGPFs) in breaking this path dependence has become increasingly urgent; however, it remains underexplored in empirical research. This study examines the impact of NGPFs on CLI using provincial panel data from 2012 to 2022. Composite indices for NGPFs and CLI are constructed using the entropy weight method. The analysis applies instrumental variable estimation (IV-GMM) to address potential endogeneity, feasible generalized least squares (FGLS) to account for heteroskedasticity, and spatial Durbin models (SDMs) to capture spatial dependence. In addition, quantile regression is used to explore distributional effects, and subsample regressions are conducted to assess regional heterogeneity. The results show that (1) a 1% increase in NGPFs leads to approximately a 0.9643% reduction in CLI, effectively mitigating CLI. (2) NGPF levels are high in Beijing, Shanghai, and Guangdong, while being constrained in Heilongjiang, Gansu, and Qinghai. Provinces like Jiangsu, Zhejiang, and Shandong are rapidly catching up. (3) Shanxi, Inner Mongolia, and Shandong struggle with high comprehensive CLI from carbon-heavy industries; in contrast, Beijing, Shanghai, and Hainan show low CLI. (4) As CLI levels increase (90th percentile), the effectiveness of NGPFs in reducing CLI gradually diminishes (−0.2724). (5) The impact of NGPFs on CLI is not significant in the Eastern region, while in the Central and Western regions, the effects are −1.1365 and −1.0137, respectively. This study offers vital insights for shaping policies that promote sustainable growth and mitigate CLI in China. Full article

(This article belongs to the Special Issue Advances in Energy Economics, Energy Policy and Sustainability Transition)

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29 pages, 6752 KB

Open AccessArticle

Global Climate Risk Perception and Its Dynamic Impact on the Clean Energy Market: New Evidence from Contemporaneous and Lagged R² Decomposition Connectivity Approaches

by Dan Yi, Sheng Lin and Jianlan Yang

Sustainability 2025, 17(8), 3596; https://doi.org/10.3390/su17083596 - 16 Apr 2025

Cited by 3 | Viewed by 1492

Abstract

The acceleration of global climate change presents unprecedented challenges to market stability and sustainable social development. Understanding how market dynamics are impacted by perceptions of climate risk is essential to creating risk management plans that work. Current research frequently concentrates on static evaluations [...] Read more.

The acceleration of global climate change presents unprecedented challenges to market stability and sustainable social development. Understanding how market dynamics are impacted by perceptions of climate risk is essential to creating risk management plans that work. Current research frequently concentrates on static evaluations of how climate risk is perceived, ignoring its dynamic influence on clean energy markets and the intricate channels via which these risks spread. To examine the dynamic influence of climate risk perceptions on clean energy markets, this study builds a spillover network model. We determine the main risk transmission pathways and their temporal variations by looking at changes in market connection over time. Our results demonstrate that climate risk perceptions have a substantial direct and indirect impact on the volatility of clean energy markets. Specifically, the ‘Risk Concern Index (GCTC and GCPC) → Clean Energy Market Index → Climate Policy Uncertainty Index (CPU) → Risk Indices (GCTRI and GCPRI)’ pathway highlights how public and policymaker concerns about climate risk significantly influence market behavior and overall dynamics. Furthermore, the dynamic analysis demonstrates that market spillovers are significantly amplified by economic and geopolitical events, highlighting the necessity of taking external shocks into account when designing policies. This study offers fresh perspectives on how climate risk perception affects clean energy markets, serves as a useful resource for investors and policymakers, and encourages the creation of robust risk management plans and market mechanisms. Full article

(This article belongs to the Special Issue Advances in Energy Economics, Energy Policy and Sustainability Transition)

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25 pages, 1607 KB

Open AccessArticle

Does the Low-Carbon City Pilot Promote Household Energy Transition in China?

by Yaning Song, Chong Zhuo and Yuyang Deng

Sustainability 2025, 17(7), 2863; https://doi.org/10.3390/su17072863 - 24 Mar 2025

Viewed by 1127

Abstract

How to promote the household energy transition (HET) has become an important response to extreme climate change. Our paper examines whether a low-carbon city pilot (LCCP) can promote HET. We empirically use the Staggered Difference-in-Differences (DID) model to explore its mechanisms. The results [...] Read more.

How to promote the household energy transition (HET) has become an important response to extreme climate change. Our paper examines whether a low-carbon city pilot (LCCP) can promote HET. We empirically use the Staggered Difference-in-Differences (DID) model to explore its mechanisms. The results indicate that the LCCP can substantially promote HET. The primary driving mechanism underlying this transition is enhanced governmental emphasis on carbon emission reduction and elevated public environmental awareness. However, the increased local expenditure on energy conservation and environmental protection does not serve as an effective mechanism. The heterogeneity analysis reveals that the LCCP has the most pronounced impact on HET among high-income groups, whereas the effect on low-income groups is relatively minor. Furthermore, the LCCP significantly promotes HET in the eastern region and urban areas, while the central region tends to inhibit it, and the western region and rural areas show no significant effect. The heterogeneity analysis further reveals that the LCCP is effective in Municipalities and Strong-Capital Provinces, where centralized governance and strong political incentives enhance policy implementation. In contrast, the policy shows limited or even negative effects in Non-Municipal Provinces and Non-Strong-Capital Provinces. We provide valuable policy insights for governments to bolster the LCCP implementation to promote HET and achieve carbon neutrality at an earlier stage. Full article

(This article belongs to the Special Issue Advances in Energy Economics, Energy Policy and Sustainability Transition)

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24 pages, 2042 KB

Open AccessArticle

Social Dimension of Poland’s Sustainable Energy Transition as Assessed by Residents of the Silesian Region

by Ewelina Włodarczyk and Joanna Herczakowska

Sustainability 2025, 17(6), 2707; https://doi.org/10.3390/su17062707 - 19 Mar 2025

Cited by 2 | Viewed by 1825

Abstract

Sustainable development is a key concept that has been formulated over many years and is currently transforming our world. Decisions made in its spirit are influencing the economic and legal order and the daily lives of people in Europe and around the world. [...] Read more.

Sustainable development is a key concept that has been formulated over many years and is currently transforming our world. Decisions made in its spirit are influencing the economic and legal order and the daily lives of people in Europe and around the world. In Poland, achieving sustainable development requires a number of difficult decisions, and one of them is to transform the energy system toward low carbon. Poland’s energy transition is not an easy task in a country where, for many years, the dominant energy resource in terms of availability, resources and price has been coal. In view of such conditions, the Polish energy system has been based on coal, which in Polish conditions is still of strategic importance in meeting energy needs. For this reason, Poland’s planned move away from coal raises many controversies and concerns, especially in areas where mines operate. At the same time, it should be remembered that the mining industry, in addition to mining companies, brings together a large group of mining-related companies working for the benefit of mining. Due to the fact that it is in the territory of the Upper Silesian Coal Basin that about 80% of the documented balance resources of Polish hard coal are located, it was justified to conduct a survey among the residents of the Silesian Province as the group most likely to be affected by this decision. The aim of the survey was to find out the target group’s opinion on Poland’s transition away from coal. In turn, the main research problem was an attempt to answer the question of what percentage of households in the Silesian Province are opposed to Poland’s transition away from coal and what are the most significant factors influencing their opinion. Hence, this study presents the results of an empirical survey conducted among a randomly selected group of residents of the Silesian Province. The size of the research sample was 385 people. The study took into account factors such as age, place of residence, income, the square footage of the dwelling and the method of heating it, as well as respondents’ professional affiliation with the mining, mining-related, gas or energy industry. The results of the survey and analyses show that the vast majority of Upper Silesian residents are against the departure from coal, which is being planned in Poland’s energy transition. In addition, the most significant factors influencing respondents’ opinion on Poland’s move away from coal were identified and evaluated, revealing two social groups with differing views: one group opposes the move away from coal, prioritizing energy independence, energy security, energy prices and jobs over environmental issues; the other group advocates for the transition mainly for environmental reasons. Full article

(This article belongs to the Special Issue Advances in Energy Economics, Energy Policy and Sustainability Transition)

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26 pages, 3296 KB

Open AccessArticle

Spatial Effects of New Quality Productivity on the Low-Carbon Transformation of Energy Consumption Structure—Evidence from Provincial Data in China

by Kaimin Yin and Xing Shen

Sustainability 2025, 17(5), 2091; https://doi.org/10.3390/su17052091 - 28 Feb 2025

Cited by 3 | Viewed by 1217

Abstract

The low-carbon transformation of an energy consumption structure (ECS) is related to the sustainable development of society. New quality productivity (NQP) is an important means to promote the green transformation of an ECS. This paper examines the spatiotemporal evolution of NQP development and [...] Read more.

The low-carbon transformation of an energy consumption structure (ECS) is related to the sustainable development of society. New quality productivity (NQP) is an important means to promote the green transformation of an ECS. This paper examines the spatiotemporal evolution of NQP development and low-carbon transformation of an ECS, utilizing panel data from 30 Chinese provinces (2012–2020) through kernel density estimation and spatial analysis methods. The impact of NQP development on the ECS and its spatial spillover effects are empirically analyzed using a two-way fixed-effects model and a spatial Durbin model. The study reveals that NQP development in China is generally positively correlated with ECS, although significant regional disparities exist. A significant positive spatial correlation exists between NQP and ECS. NQP development significantly promotes the transformation of local ECS but exerts a negative spatial spillover effect on neighboring regions. Further analysis reveals that NQP exhibits an “inverted U-shaped” impact on the spatial spillover effects of local ECS. Spatial attenuation analysis indicates that the negative spillover effects of NQP on ECS diminish with geographical distance, with a maximum attenuation boundary of 600 km. The study found that China is currently facing significant regional development imbalances. Promoting the balanced development of NQP is crucial for achieving high-quality and sustainable development. Full article

(This article belongs to the Special Issue Advances in Energy Economics, Energy Policy and Sustainability Transition)

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21 pages, 448 KB

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Effects of the Digital Economy on Reducing Carbon Emissions in China’s Energy-Intensive Manufacturing Enterprises

by Yang Cui, Shihu Yu, Yaqing Liu, Yushang Hu and Zanxin Wang

Sustainability 2025, 17(20), 9287; https://doi.org/10.3390/su17209287 - 19 Oct 2025

Viewed by 861

Abstract

The energy-intensive manufacturing industry is a significant contributor to carbon emissions, necessitating urgent measures to reduce its carbon footprint. The advent of the digital economy has engendered a milieu conducive to the decarbonization of energy-intensive manufacturing enterprises. This paper utilizes panel data from [...] Read more.

The energy-intensive manufacturing industry is a significant contributor to carbon emissions, necessitating urgent measures to reduce its carbon footprint. The advent of the digital economy has engendered a milieu conducive to the decarbonization of energy-intensive manufacturing enterprises. This paper utilizes panel data from A-share listed energy-intensive manufacturing enterprises in China from 2012 to 2024 to empirically analyze the impact of the digital economy on carbon abatement performance. The findings reveal the following: First, the digital economy has a significant effect on enhancing the carbon emission reduction performance of energy-intensive manufacturing enterprises. Second, total factor productivity, R&D investment, and technology innovation have partial mediating effects in this relationship. Third, heterogeneous effects exist across enterprises of six major energy-intensive industries. Fourth, the carbon reduction effect of the digital economy is more significant in central and western regions compared to eastern regions in China. These results underscore the importance of accelerating digital transformation and formulating diversified policies predicated on industries and regions to facilitate the realization of China’s “dual carbon” goals. Full article

(This article belongs to the Special Issue Advances in Energy Economics, Energy Policy and Sustainability Transition)

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