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Energy Transition and the Collaborative Governance for Reduction of Pollution and Carbon Emissions

A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Energy Sustainability".

Deadline for manuscript submissions: 31 August 2026 | Viewed by 3310

Special Issue Editors

Prof. Dr. Feng Wang

E-Mail Website
Guest Editor
School of Economics and Management, China University of Mining and Technology, Xuzhou, China
Interests: green and low-carbon economics; energy and environmental finance; econometrics; regional economics
Prof. Dr. Lingyun He

E-Mail Website
Guest Editor
School of Economics and Management, China University of Mining and Technology, Xuzhou, China
Interests: green finance; energy and environmental economics and policy
Prof. Dr. Zhangqi Zhong

E-Mail Website
Guest Editor
School of Economics and Trade, Guangdong University of Foreign Studies, Guangzhou 510006, China
Interests: environmental regulation; technological innovation; environmental governance; environmental pollution; greenhouse gas emissions accounting; carbon leakage
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

(1) Energy is essential to human survival and development. Since the First Industrial Revolution, the extensive usage of fossil fuels has promoted social progress, but it has also caused a series of problems, such as resource depletion, environmental pollution and geopolitical tension. Green and low-carbon transformation and development of energy will consequently be crucial for the future of humanity. In addition, greenhouse gas emissions and pollutant emissions share the same root and interact with each other, and energy transition is the key to improving pollution and carbon reduction. Therefore, comprehensively clarifying the issues of energy transition and the collaborative governance for the reduction in pollution and carbon emissions is of great significance for strengthening energy security, improving ecological quality, reducing climate damage risks, and increasing economic benefits. We are pleased to invite you to provide issue-oriented and cutting-edge research, both theoretical and empirical, that focuses on the intersection of energy transition and pollution and carbon reduction, with a particular emphasis on topics related to system modeling, factor analysis, path optimization, and policy evaluation.

(2) This Special Issue aims to explore the innovative theory and practice that refers to energy transition, environmental impact assessment, pollution and carbon reduction, synergistic scenario modeling and quantification for sustainability.

(3) In this Special Issue, original research articles and reviews are welcome. Research areas may include (but are not limited to) the following:

  1. Energy transition and energy security;
  2. Collaborative governance for carbon abatement and pollution reduction;
  3. Drivers of energy transition and paths in energy supply, consumption, technology, and governance;
  4. Energy conservation and emission reduction in carbon-intensive industries;
  5. Blockchain and green development;
  6. Energy transition and pollution and carbon reduction and their synergies at temporal and spatial scales;
  7. Energy transition and carbon neutrality;
  8. Climate change, carbon emissions, and energy transition;
  9. Construction of the new energy system.

We look forward to receiving your contributions.

Prof. Dr. Feng Wang
Prof. Dr. Lingyun He
Prof. Dr. Zhangqi Zhong
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sustainability is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • carbon abatement and pollution reduction
  • energy transition
  • collaborative governance
  • energy security
  • energy system
  • green and low-carbon development
  • climate change
  • environmental governance

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Published Papers (3 papers)

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Research

22 pages, 300 KB  
Article
To Cooperate Proactively or Pay Fines? Unpacking the Dual Effects of Government Intervention and Market Incentives on Carbon Emissions Intensity in Power Enterprises
by Jia Wang and Xinhua Zhang
Sustainability 2025, 17(23), 10826; https://doi.org/10.3390/su172310826 - 3 Dec 2025
Viewed by 141
Abstract
This study identified the impact patterns of carbon price fluctuations and excess penalty mechanisms on power companies’ carbon emissions from the dual perspectives of market incentives and government intervention to address the issues of insufficient incentives for power companies to reduce emissions and [...] Read more.
This study identified the impact patterns of carbon price fluctuations and excess penalty mechanisms on power companies’ carbon emissions from the dual perspectives of market incentives and government intervention to address the issues of insufficient incentives for power companies to reduce emissions and environmental regulation mechanisms for emission reduction. Three main conclusions are revealed by the study: First, carbon emissions are significantly suppressed by the Environmental Protection Law of the People’s Republic of China (EPLPRC), with an inverse U-shaped link between carbon allowance pricing (CAP) and carbon emissions intensity (CEI). Moreover, the two exhibit synergistic effects. Second, two important transmission mechanisms are unit material cost (UMC) and green technological innovation (GHI). Third, there is significant variation in the results of emission reduction. While the inverted U-shaped effect of carbon allowance prices is most noticeable among medium-to-large non-state-owned businesses and in areas with rapid increase in thermal power capacity, EPLPRC works better for small non-state-owned businesses and large state-owned businesses. We also note that in areas where the expansion of thermal power generation is slower, dual environmental policies show significant synergistic impacts. These results offer direction for developing distinct carbon reduction strategies and promoting the power industry’s low-carbon transition. Full article
(This article belongs to the Special Issue Energy Transition and the Collaborative Governance for Reduction of Pollution and Carbon Emissions)
21 pages, 1920 KB  
Article
Reinforcement Learning-Based Energy Management in Community Microgrids: A Comparative Study
by Olimpiu Nicolae Moga, Adrian Florea, Claudiu Solea and Maria Vintan
Sustainability 2025, 17(23), 10696; https://doi.org/10.3390/su172310696 - 28 Nov 2025
Viewed by 232
Abstract
Energy communities represent an important step towards clean energy; however, their management is a complex task due to various factors such as fluctuating demand and energy prices, variable renewable generation, and external factors such as power outages. This paper investigates the effectiveness of [...] Read more.
Energy communities represent an important step towards clean energy; however, their management is a complex task due to various factors such as fluctuating demand and energy prices, variable renewable generation, and external factors such as power outages. This paper investigates the effectiveness of a Reinforcement Learning agent, based on the Proximal Policy Optimisation (PPO) algorithm, for energy management across three different energy community configurations. The performance of the PPO agent is compared against a Rule-Based Controller (RBC) and a baseline scenario using solar generation but no active management. Simulations were run in the CityLearn framework to simulate real world data. Across the three evaluated community configurations, the PPO agent achieved its greatest improvement over a single run in the scenario where all participants were prosumers (Schema 3), with a reduction of 9.2% in annual costs and carbon emissions. The main contribution of this work is demonstrating the viability of Reinforcement Learning agents in energy optimization problems, providing an alternative to traditional RBCs for energy communities. Full article
(This article belongs to the Special Issue Energy Transition and the Collaborative Governance for Reduction of Pollution and Carbon Emissions)
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25 pages, 658 KB  
Article
Can Climate Risk Disclosure Attract Analyst Coverage? A Study Based on the Dual Perspective of Information Supply and Demand
by Mengxue Li and Sheng Yao
Sustainability 2025, 17(9), 3960; https://doi.org/10.3390/su17093960 - 28 Apr 2025
Cited by 2 | Viewed by 2216
Abstract
In the context of the intensifying global climate change and its associated risks, the interaction between corporate climate risk disclosure and analyst forecasting behavior has become a pivotal scholarly focus in sustainability research. This study uses a sample of 20,978 firm-year observations from [...] Read more.
In the context of the intensifying global climate change and its associated risks, the interaction between corporate climate risk disclosure and analyst forecasting behavior has become a pivotal scholarly focus in sustainability research. This study uses a sample of 20,978 firm-year observations from non-financial Chinese A-share listed companies over the period 2007–2021 to examine the impact of corporate climate risk disclosure on analyst coverage, applying ordinary least squares (OLS) regression. The results reveal a positive relationship between corporate climate risk disclosure and analyst coverage. This positive effect is more prominent in firms with lower annual report readability, a higher proportion of independent institutional investors, and in contexts involving team analysts or analysts from large brokerage firms. Mechanism analysis reveals two pathways for increased analyst coverage: increasing institutional investors’ demand for information and reducing analysts’ reliance on on-site research to uncover private information. Further research reveals that severe and chronic risk disclosures attract more analyst coverage than transition risk disclosures. Additionally, climate risk disclosure can significantly reduce analyst forecast dispersion and long-term forecast bias. Overall, this study holds important implications for improving corporate climate risk disclosure practices and enhancing analysts’ role as information intermediaries. Full article
(This article belongs to the Special Issue Energy Transition and the Collaborative Governance for Reduction of Pollution and Carbon Emissions)
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