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Carbon Emissions in the Energy Sector: Trends, Challenges, and Solutions

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A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "B: Energy and Environment".

Deadline for manuscript submissions: closed (10 June 2026) | Viewed by 9375

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Editors

Dr. Lei Chen

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Guest Editor

Guangzhou Institute of Energy Conversion, Chinese Academy of Sciences, Guangzhou 510640, China
Interests: energy strategy; spatiotemporal distribution of carbon emissions; driving mechanism analysis
Special Issues, Collections and Topics in MDPI journals

Dr. Yongyang Wang

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Guest Editor

School of Hydraulic Engineering, Dalian University of Technology, Dalian 116023, China
Interests: carbon emission dynamics; decarbonization strategies; artificial intelligence applications in energy system modeling; the design of regulatory pathways for integrating renewable energy sources

Dr. Linlin Xia

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Guest Editor

School of Ecology, Environment and Resources, Guangdong University of Technology, Guangzhou 510006, China
Interests: urban metabolism; environmental systems analysis; ecological planning and management

Dr. Feng Liu

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Guest Editor

School of Economics and Management, China University of Mining and Technology, Xuzhou 221116, China
Interests: renewable energy integration; decarbonization strategies; energy sector modelling
Special Issues, Collections and Topics in MDPI journals

Dr. Ruwei Wang

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Guest Editor

College of Environmental and Climate, Guangdong Provincial Key Laboratory of Environmental Pollution and Health, Jinan University, Guangzhou 511443, China
Interests: industrial pollution source apportionment; emission characteristics of pahs; driving force mechanisms; environmental chemical kinetics

Special Issue Information

Dear Colleagues,

In the collective global effort to address climate change, the energy sector—as the largest source of greenhouse gas emissions—bears enormous responsibility for emission reduction. The transition from traditional fossil fuels to renewable energy is widely recognized as the core pathway for decarbonizing this sector. This transition not only mitigates climate change but also promotes energy sustainability and security. Governments, businesses, and communities worldwide are increasingly investing in renewable energy technologies such as solar, wind, and hydroelectric power. As these technologies become more efficient and cost-effective, the adoption rate is expected to accelerate, further reducing the dependency on fossil fuels and their associated environmental impacts. However, the intermittent and volatile nature of renewable energy introduces significant operational risks to power grids when deployed at scale. Achieving emissions reduction in the power sector while ensuring grid reliability demands urgent academic attention. The aim of this Special Issue is to systematically analyze successful historical decarbonization strategies within the power sector, explore prevailing challenges in energy-related emission mitigation, and identify viable pathways for a resilient, low-carbon energy future.

Our aim is to gather diverse perspectives from researchers, policymakers, and industry experts to comprehensively evaluate past efforts, current trends, and future possibilities. By examining both technological advancements and institutional frameworks, we seek to elucidate the multifaceted nature of decarbonization and its implications for energy security and sustainability. Furthermore, we envision this Special Issue as a catalyst for fostering interdisciplinary collaborations and innovative solutions tailored to address the unique challenges posed by the transition to a low-carbon energy system.

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

The development and application of renewable energy technologies, such as solar, wind, and geothermal power.

Innovative approaches to enhance energy storage solutions for balancing supply and demand in a low-carbon grid.

The analysis of the economic and social impacts of decarbonization strategies on various stakeholders within the power sector.

Policy recommendations and regulatory frameworks that can facilitate the transition to a low-carbon energy system.

Interdisciplinary studies exploring the synergies between energy efficiency, emissions reduction, and grid reliability.

Dr. Lei Chen
Dr. Yongyang Wang
Dr. Linlin Xia
Dr. Feng Liu
Dr. Ruwei Wang
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-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Energies 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 2600 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

low-carbon energy transition
variable renewable energy
flexible resources
energy sector modelling
carbon accounting
fossil energy
decarbonization strategies
renewable energy integration

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Related Special Issue

Toward a Low-Carbon Future: Green Growth, New Energy Solutions, and Sustainable Development in Energies

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Research

21 pages, 3423 KB

Open AccessArticle

Environmental Assessment of Closed-Loop Regeneration of Spent LFP Batteries Based on Factory-Level Inventory Data

by Ying Xia, Yipin Duan, Shuai Nie, Zihao Zhang, Qian Xiao and Guotian Cai

Energies 2026, 19(16), 3749; https://doi.org/10.3390/en19163749 - 10 Aug 2026

Viewed by 248

Abstract

The rapid expansion of electric vehicles is generating large volumes of spent lithium iron phosphate (LFP) batteries, yet the environmental performance of closed-loop regeneration under industrial conditions remains insufficiently quantified. Here we develop a life cycle assessment of a closed-loop recycling–regeneration pathway using factory-level inventory data from an integrated plant, benchmarking 1 kg of regenerated LFP cathode-active material (CAM) at the plant gate against virgin LFP CAM (ecoinvent v3.10; ReCiPe 2016 Midpoint). Relative to virgin production, the closed-loop route reduces global warming potential (GWP100) by 7.73% (from 6.59 to 6.08 kg CO₂-eq kg⁻¹ CAM), fossil fuel potential (FFP) by 3.80%, surplus ore potential (SOP) by 97.57%, and carcinogenic human toxicity (HTPc) by 36.72%—a clear but heterogeneous advantage, large for mineral resources and modest for climate. Iron phosphate and lithium carbonate recovery dominate the burdens, with H₂O₂ being the largest single GWP100 contributor (23.7%) and the most sensitive inventory parameter, while the SOP advantage is highly robust. Grid-decarbonization scenarios widen the GWP100 reduction to 22.4% under near-zero-carbon electricity. The carbon competitiveness of closed-loop LFP regeneration is therefore governed by the balance between avoided virgin-material burdens and reagent- and energy-intensive recovery operations. Full article

(This article belongs to the Special Issue Carbon Emissions in the Energy Sector: Trends, Challenges, and Solutions)

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29 pages, 7867 KB

Open AccessArticle

Operation Optimization of Electric Vehicle Battery Swapping Stations via Virtual Power Plant and Carbon Trading

by Xieyu Hu, Yuping Huang, Yilin Huang, Yongjian Zhao, Zhouchun Huang and Yu Liang

Energies 2026, 19(10), 2341; https://doi.org/10.3390/en19102341 - 13 May 2026

Viewed by 404

Abstract

Battery swapping stations (BSSs) serve as critical nodes for electric vehicle energy supply and power load regulation, representing important regulatory resources in modern power systems and making their operational optimization essential for reducing carbon emissions and improving energy efficiency. To address the lack of carbon emission management and low battery utilization efficiency in existing BSS operations, this study proposes a collaborative optimization method that integrates virtual power plants (VPPs) and carbon trading mechanisms. The proposed approach dynamically adjusts charging and discharging schedules to achieve coordinated optimization of energy costs and carbon emissions. A comprehensive BSS operational model considering VPP participation and carbon trading is established, comparing the performance between conventional operation modes and collaborative mechanisms, followed by optimization analysis of four strategic approaches. The simulation results demonstrate that the proposed method effectively promotes collaborative optimization of BSS in both VPP and carbon trading markets. Through flexible strategy combinations, the approach significantly reduces overall carbon emissions while maximizing both the economic and environmental benefits of BSS operations, providing important support for the sustainable development of modern power systems. Full article

(This article belongs to the Special Issue Carbon Emissions in the Energy Sector: Trends, Challenges, and Solutions)

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20 pages, 2217 KB

Open AccessArticle

Assessment of the Usability of Low-GWP Blended Refrigerants for Water-Source Heat Pumps

by Mehmet Özçelik, Atilla G. Devecioğlu and Vedat Oruç

Energies 2026, 19(6), 1534; https://doi.org/10.3390/en19061534 - 20 Mar 2026

Viewed by 570

Abstract

This study investigates the applicability of alternative low-global warming potential (GWP) refrigerant blends in water-source heat pump systems. Binary and ternary refrigerant mixtures were generated using REFPROP 10 to identify suitable candidates. Among 379 novel blends, 18 mixtures with glide temperatures below 10 °C, high critical temperatures, and GWP values lower than 750 were selected for analysis. Thermodynamic analyses were conducted for the selected refrigerants at target water outlet temperatures ranging from 35 to 75 °C, with a heat source temperature of 15 °C and an evaporation temperature of 5 °C. In addition, compressor discharge temperature, volumetric heating capacity, and coefficient of performance (COP) were evaluated. Among the refrigerants, MX1 was recommended for condenser temperatures of 40–80 °C in large-scale heat pump and district heating applications. For refrigerants with GWP values below 150, MX7 exhibited the highest COP and second-law efficiency (η_II) and is therefore suitable for small-capacity systems. In the GWP range of 150–750, MX16 demonstrated the highest COP and η_II values over the entire temperature range. Overall, MX7 achieved the highest COP and η_II among all refrigerants considered, while MX4 emerged as the most favorable mixture in terms of low GWP (below 150) and thermophysical performance. Full article

(This article belongs to the Special Issue Carbon Emissions in the Energy Sector: Trends, Challenges, and Solutions)

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28 pages, 2155 KB

Open AccessArticle

Deep Reinforcement Learning for Battery Energy Storage Optimization and Residential Decarbonization in Grid-Deficient Environments: An Iraqi Case Study

by Ahmed Mohammed, Badr M. Abdullah, Ali Shubbar, Qian Zhang, Omar Aldhaibani, Jeff Cullen and Amer Salih

Energies 2026, 19(5), 1233; https://doi.org/10.3390/en19051233 - 1 Mar 2026

Cited by 2 | Viewed by 1387

Abstract

In grid-deficient environments, residential energy systems face severe carbon emission penalties due to mandatory reliance on diesel standby generators during supply interruptions. In Iraq, summer peak loads routinely exceed grid capacity, triggering prolonged generator operation and dramatically increasing household carbon footprints. This study presents a deep Q-network (DQN) reinforcement learning framework for intelligent battery energy storage system (BESS) scheduling, targeting carbon emissions reduction through strategic peak shaving. The DQN agent learns optimal battery dispatch strategies by internalizing diurnal patterns in load and solar generation through temporal state features, enabling anticipatory control without requiring explicit external forecasting models. The system is trained on one-year operational data from a representative Iraqi residential installation and evaluated over the critical summer period (122 days, 35.5% grid unavailability). The results demonstrate a 54.8%

{CO}_{2}

reduction (306.5 kg versus 677.4 kg baseline), a 25.5% reduction in generator runtime, and a 23.7% reduction in operating costs for the studied configuration. The learned policy approaches 89.6% of perfect-foresight MILP performance while executing 35,000 times faster. A reward function sensitivity analysis across five weighting schemes confirms that the 20:1 carbon-to-cost priority ratio optimally balances environmental and economic objectives. Ablation studies quantify the mechanism contributions: anticipatory pre-charging accounts for 58% of the total improvement, discharge optimization for 44%, and real-time PV coordination for 22%. These findings establish DQN-based BESS optimization as a practically deployable decarbonization approach for residential systems in grid-constrained developing regions. Full article

(This article belongs to the Special Issue Carbon Emissions in the Energy Sector: Trends, Challenges, and Solutions)

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25 pages, 3260 KB

Open AccessArticle

Signal-Guided Cooperative Optimization Method for Active Distribution Networks Oriented to Microgrid Clusters

by Zihao Wang, Shuoyu Li, Kai Yu, Wenjing Wei, Guo Lin, Xiqiu Zhou, Yilin Huang and Yuping Huang

Energies 2025, 18(24), 6614; https://doi.org/10.3390/en18246614 - 18 Dec 2025

Viewed by 616

Abstract

To achieve low-carbon collaborative operation of active distribution networks (ADNs) and microgrid clusters, this paper proposes a signal-guided collaborative optimization method. Firstly, a spatiotemporal carbon intensity equilibrium model (STCIEM) is constructed, overcoming the limitations of centralized carbon emission flow models in terms of data privacy and equitable distribution, and enabling distributed and precise carbon emission measurement. Secondly, a dual-market mechanism for carbon and electricity is designed to support peer-to-peer (P2P) carbon quota trading between microgrids and ADN-backed clearing, enhancing market liquidity and flexibility. In terms of scheduling strategy optimization, the multi-agent deep deterministic policy gradient (MADDPG) algorithm is incorporated into the carbon-electricity cooperative game framework, enabling differentiated energy scheduling under constraints. Simulation results demonstrate that the proposed method can effectively coordinate the operation of energy storage, gas turbines, and demand response, reduce system carbon intensity, improve market fairness, and enhance overall economic performance and robustness. The study shows that this framework provides theoretical support and practical reference for future distributed energy consumption and carbon neutrality paths. Full article

(This article belongs to the Special Issue Carbon Emissions in the Energy Sector: Trends, Challenges, and Solutions)

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17 pages, 1139 KB

Open AccessFeature PaperArticle

Mining Social Discourse to Validate Behavioral Drivers: A Mixed-Methods Study on Rural Rooftop Photovoltaic Adoption in China

by Yuan Meng, Yuwei Chen, Huarong Long, Feng Liu, Tao Lv and Lei Chen

Energies 2025, 18(24), 6477; https://doi.org/10.3390/en18246477 - 10 Dec 2025

Viewed by 726

Abstract

County-wide distributed rooftop photovoltaic (DRPV) systems, as an emerging form of renewable energy development, constitute a critical component for the low-carbon energy transition and carbon reduction. However, the pilot implementation in China has faced many challenges, with resistance from rural residents being a key issue requiring urgent resolution. This study aimed to investigate the underlying factors influencing their participation in DRPV and identify the key determinants. The topic modeling and evolutionary analysis were first conducted based on the multi-platform online textual data. The theoretical model was constructed combining the antecedent variables identified by the online textual analysis and the classic Unified Theory of Acceptance and Use of Technology (UTAUT) framework. This model was validated through questionnaire surveys and structural equation modeling. The results revealed that facilitating conditions were the core determinant of rural residents’ participation in DRPV systems. Government-led safeguard mechanisms served as the primary enhancer of perceived convenience. Additionally, effort expectancy (0.301), performance expectancy (0.253), and social influence (0.424) all positively correlated with participation intention, with social influence exhibiting the strongest impact. Notably, rural residents equally prioritize environmental benefits and economic returns from DRPV systems. These findings provided policy insights for promoting DRPV projects in the future. Full article

(This article belongs to the Special Issue Carbon Emissions in the Energy Sector: Trends, Challenges, and Solutions)

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19 pages, 3537 KB

Open AccessArticle

Energy-Saving and Detailed Techno-Economic Assessment of the CO₂ Avoided Cost for Emerging Designs of a Solvent-Based CO₂ Capture Facility

by Abdelmalek Bellal, Fatah Ben Moussa and Seif Eddine Bellal

Energies 2025, 18(21), 5608; https://doi.org/10.3390/en18215608 - 25 Oct 2025

Cited by 1 | Viewed by 1269

Abstract

Proposed process intensification in the literature claims relevant savings in operational cost through optimization of the energy required to operate a typical solvent-based CO₂ capture facility, meanwhile granting the same capture performance. However, the techno-economic assessment for these proposed designs is not well developed and not fairly compared using a detailed and standardized cost evaluation technique that follows the association for the advancement of cost engineering (ACEE) class 4 costing methodology. This limitation makes it difficult and less viable to decide which solution is more cost-effective in consideration of the integration market with coal or natural gas combined cycle power plants. This work suggests a standardized methodology for cost evaluation and ultimately aids in formulating an accurate and high-fidelity guideline for industrial deployment of the proposed technologies, covering analysis on the flue gas compression (FGC) and lean vapor compression (LVC) configurations. Design, simulation, sensitivity analysis, and optimization are conducted initially to build a baseline design that closely represents an existing commercial design, such as Cansolv and Petra Nova technologies. The energy saving from the two configurations is analyzed in parallel to the investment cost, levelized cost of electricity (LCOE), and the CO₂ avoided cost. It was found that FGC improved the capture performance of the baseline design, but at the same time raised the cost of operation and investment by a higher magnitude, making the CO₂ avoided cost $98.2/tonneCO₂, which is $16 higher than that of the baseline design. Meanwhile, LVC has been defined as an attractive configuration for lowering the CO₂ avoided cost. Full article

(This article belongs to the Special Issue Carbon Emissions in the Energy Sector: Trends, Challenges, and Solutions)

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18 pages, 257 KB

Open AccessArticle

The Impact of ESG on Corporate Value Under the ‘Dual Carbon’ Goals: Empirical Evidence from Chinese Energy Listed Companies

by Pengwei He, Qiutong Chen and Li Chen

Energies 2025, 18(18), 4811; https://doi.org/10.3390/en18184811 - 10 Sep 2025

Cited by 6 | Viewed by 3060

Abstract

As China pursues its dual carbon goals—peaking carbon emissions by 2030 and achieving carbon neutrality by 2060, the energy sector is central to the country’s climate strategy. This study investigates the impact of Environmental, Social, and Governance (ESG) performance on firm value in China’s energy sector, an industry critical to national carbon emissions and energy consumption. Using a panel dataset of 20,225 firm-year observations from A-share listed firms between 2016 and 2023, we apply regression models to assess how ESG performance affects firm value, with controls for industry characteristics and policy effects. The results show that ESG performance significantly enhances firm value, especially among non-state-owned firms and those in high-pollution industries. ESG performance also facilitates access to green bond financing, providing firms with enhanced capital for green investments, thereby boosting market value. Furthermore, we find that firms in regions with higher green development attention benefit more from ESG practices, with local carbon trading policies playing a key role in improving firm competitiveness and market performance. This study provides critical insights into how ESG strategies and carbon governance policies influence firm performance in the energy sector. The findings offer practical implications for policymakers aiming to support low-carbon industrial transformation and for firms seeking to integrate sustainability into their long-term strategic planning. These insights are crucial for driving the successful implementation of China’s dual carbon strategy. Full article

(This article belongs to the Special Issue Carbon Emissions in the Energy Sector: Trends, Challenges, and Solutions)

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