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Sustainable Energy, Environment and Low-Carbon Development

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

Deadline for manuscript submissions: 18 December 2025 | Viewed by 11152

Special Issue Editors

State Key Laboratory of Urban Water Resource and Environment, School of Environment, Harbin Institute of Technology, Harbin 150090, China
Interests: algae; anaerobic fermentation/digestion; energy and resource recovery; sludge treatment; biological treatment processes; advanced oxidation process
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Guest Editor
School of Water Conservancy and Civil Engineering, Northeast Agricultural University, Harbin 150030, China
Interests: biological wastewater treatment; bioelectrochemical system; emerging containments; anaerobic fermentation/digestion; energy and resource recovery
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Special Issue Information

Dear Colleagues,

Environmental problems such as industrial, domestic and agricultural pollution are becoming more and more serious around the world, causing a series of ecological problems and threatening human health. On the other hand, the insufficient supply of energy and the greenhouse gas emissions caused by fossil fuels also restrict the sustainable development of the economy and society. We hope to contribute to the construction of a low-carbon, green and sustainable society.

Here, we will continue to work in this direction. This Special Issue focuses on how green energy technologies can help reduce environmental pollution and achieve low-carbon sustainable development. The purpose of this Special Issue is to bring together innovative academicians and industrial experts in related fields and to establish an academic platform on the communication of the latest research and developmental activities.

Dr. Hongyu Ren
Prof. Dr. Fanying Kong
Guest Editors

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Keywords

  • environmental problems
  • environment pollution
  • green energy technologies
  • sustainable development
  • bioenergy
  • energy conversion and management
  • water–energy–food nexus
  • recycling technologies
  • low-carbon development

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Related Special Issue

Published Papers (6 papers)

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Research

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19 pages, 538 KB  
Article
Natural Gas and Biogas Mixtures in Smart Cities: A Mathematical Model of Its Proposal for Use with Biogas Produced by Biomass Plants and Mixture Density Control According to the Biogas Composition
by Jorge Luis Mírez Tarrillo and J. C. Hernandez
Energies 2025, 18(17), 4617; https://doi.org/10.3390/en18174617 - 30 Aug 2025
Viewed by 492
Abstract
This article presents a proposal for blending natural gas and biogas with a control system with feedback to ensure a constant mixture density. To achieve this, we propose the following: a mathematical model to determine the gas density based on its composition; a [...] Read more.
This article presents a proposal for blending natural gas and biogas with a control system with feedback to ensure a constant mixture density. To achieve this, we propose the following: a mathematical model to determine the gas density based on its composition; a control system whose main components are a gas mixer, valves, and a natural gas storage tank to regulate the biogas density, where its inputs are gases from biomass plants and the natural gas grid; mathematical models to calculate the volume of natural gas required in the storage tank. It is assumed that the composition at the outlet of the biogas plants is measured and that there are no losses of any kind; a case study simulation is then performed. All models consider random variation in gas composition over time. The main results are as follows: (a) reduced natural gas consumption, the promotion of biogas production and use and of mixtures of lower methane compared to natural gas, and the facilitation of the pumping of the gas mixtures; (b) all the biogas produced is used; (c) different piping, sources, storage tanks, consumers, and mixer schemes, considering the concepts of cities, microgrids, smart grids, and smart cities. Full article
(This article belongs to the Special Issue Sustainable Energy, Environment and Low-Carbon Development)
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29 pages, 753 KB  
Article
Sustainable Thermal Energy Storage Systems: A Mathematical Model of the “Waru-Waru” Agricultural Technique Used in Cold Environments
by Jorge Luis Mírez Tarrillo
Energies 2025, 18(12), 3116; https://doi.org/10.3390/en18123116 - 13 Jun 2025
Viewed by 3948
Abstract
The provision of food in pre-Inca/Inca cultures (1000 BC–≈1532 AD) in environments near Lake Titikaka (approximately 4000 m above sea level) was possible through an agricultural technique called “Waru-Waru”, which consists of filling the space (volume) between rows of land containing plants that [...] Read more.
The provision of food in pre-Inca/Inca cultures (1000 BC–≈1532 AD) in environments near Lake Titikaka (approximately 4000 m above sea level) was possible through an agricultural technique called “Waru-Waru”, which consists of filling the space (volume) between rows of land containing plants that are cultivated (a series of earth platforms surrounded by water canals) with water, using water as thermal energy storage to store energy during the day and to regulate the temperature of the soil and crop atmosphere at night. The problem is that these cultures left no evidence in written documents that have been preserved to this day indicating the mathematical models, the physics involved, and the experimental part they performed for the research, development, and innovation of the “Waru-Waru” technique. From a review of the existing literature, there is (1) bibliography that is devoted to descriptive research (about the geometry, dimensions, and shapes of the crop fields (and more based on archaeological remains that have survived to the present day) and (2) studies presenting complex mathematical models with many physical parameters measured only with recently developed instrumentation. The research objectives of this paper are as follows: (1) develop a mathematical model that uses finite differences in fluid mechanics, thermodynamics, and heat transfer to explain the experimental and theory principles of this pre-Inca/Inca technique; (2) the proposed mathematical model must be in accordance with the mathematical calculation tools available in pre-Inca/Inca cultures (yupana and quipu), which are mainly based on arithmetic operations such as addition, subtraction, and multiplication; (3) develop a mathematical model in a sequence of steps aimed at determining the best geometric form for thermal energy storage and plant cultivation and that has a simple design (easy to transmit between farmers); (4) consider the assumptions necessary for the development of the mathematical model from the point of view of research on the geometry of earth platforms and water channels and their implantation in each cultivation area; (5) transmit knowledge of the construction and maintenance of “Waru-Waru” agricultural technology to farmers who have cultivated these fields since pre-Hispanic times. The main conclusion is that, in the mathematical model developed, algebraic mathematical expressions based on addition and multiplication are obtained to predict and explain the evolution of soil and water temperatures in a specific crop field using crop field characterization parameters for which their values are experimentally determined in the crop area where a “Waru-Waru” is to be built. Therefore, the storage of thermal energy in water allows crops to survive nights with low temperatures, and indirectly, it allows the interpretation that the Inca culture possessed knowledge of mathematics (addition, subtraction, multiplication, finite differences, approximation methods, and the like), physics (fluids, thermodynamics, and heat transfer), and experimentation, with priority given to agricultural techniques (and in general, as observed in all archaeological evidence) that are in-depth, exact, practical, lasting, and easy to transmit. Understanding this sustainable energy storage technique can be useful in the current circumstances of global warming and climate change within the same growing areas and/or in similar climatic and environmental scenarios. This technique can help in reducing the use of fossil or traditional fuels and infrastructure (greenhouses) that generate heat, expanding the agricultural frontier. Full article
(This article belongs to the Special Issue Sustainable Energy, Environment and Low-Carbon Development)
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23 pages, 6791 KB  
Article
Modeling Ecological Risk in Bottom Sediments Using Predictive Data Analytics: Implications for Energy Systems
by Bartosz Przysucha, Monika Kulisz, Justyna Kujawska, Michał Cioch, Adam Gawryluk and Rafał Garbacz
Energies 2025, 18(9), 2329; https://doi.org/10.3390/en18092329 - 2 May 2025
Viewed by 548
Abstract
Sediment accumulation in dam reservoirs significantly impacts hydropower efficiency and infrastructure sustainability. Bottom sediments often contain heavy metals such as Cr, Ni, Cu, Zn, Cd, and Pb, which can pose ecological risks and affect water quality. Moreover, excessive sedimentation reduces reservoir capacity, increases [...] Read more.
Sediment accumulation in dam reservoirs significantly impacts hydropower efficiency and infrastructure sustainability. Bottom sediments often contain heavy metals such as Cr, Ni, Cu, Zn, Cd, and Pb, which can pose ecological risks and affect water quality. Moreover, excessive sedimentation reduces reservoir capacity, increases turbine wear, and raises operational costs, ultimately hindering energy production. This study examined the ecological risk of heavy metals in bottom sediments and explored predictive approaches to support sediment management. Using 27 sediment samples from Zemborzyce Lake, the concentrations of selected heavy metals were measured at two depths (5 cm and 30 cm). Ecological risk index (ERI) values for the deep layer were predicted based on surface data using artificial neural networks (ANNs) and multiple linear regression (MLR). Both models showed a high predictive accuracy, demonstrating the potential of data-driven methods in sediment quality assessment. The early identification of high-risk areas allows for targeted dredging and optimized maintenance planning, minimizing disruption to dam operations. Integrating predictive analytics into hydropower management enhances system resilience, environmental protection, and long-term energy efficiency. Full article
(This article belongs to the Special Issue Sustainable Energy, Environment and Low-Carbon Development)
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19 pages, 2262 KB  
Article
Development of Advanced Machine Learning Models for Predicting CO2 Solubility in Brine
by Xuejia Du and Ganesh C. Thakur
Energies 2025, 18(5), 1202; https://doi.org/10.3390/en18051202 - 28 Feb 2025
Cited by 2 | Viewed by 1332
Abstract
This study explores the application of advanced machine learning (ML) models to predict CO2 solubility in NaCl brine, a critical parameter for effective carbon capture, utilization, and storage (CCUS). Using a comprehensive database of 1404 experimental data points spanning temperature (−10 to [...] Read more.
This study explores the application of advanced machine learning (ML) models to predict CO2 solubility in NaCl brine, a critical parameter for effective carbon capture, utilization, and storage (CCUS). Using a comprehensive database of 1404 experimental data points spanning temperature (−10 to 450 °C), pressure (0.098 to 140 MPa), and salinity (0.017 to 6.5 mol/kg), the research evaluates the predictive capabilities of five ML algorithms: Decision Tree, Random Forest, XGBoost, Multilayer Perceptron, and Support Vector Regression with a radial basis function kernel. Among these, XGBoost demonstrated the highest overall accuracy, achieving an R2 value of 0.9926, with low root mean square error (RMSE) and mean absolute error (MAE) of 0.0655 and 0.0191, respectively. A feature importance analysis revealed that pressure has the most impactful effect and positively correlates with CO2 solubility, while temperature generally exhibits a negative effect. A higher accuracy was found when the developed model was compared with one well-established empirical model and one ML-based model from the literature. The results underscore the potential of ML models to significantly enhance prediction accuracy over a wide data range, reduce computational costs, and improve the efficiency of CCUS operations. This work demonstrates the robustness and adaptability of ML approaches for modeling complex subsurface conditions, paving the way for optimized carbon sequestration strategies. Full article
(This article belongs to the Special Issue Sustainable Energy, Environment and Low-Carbon Development)
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22 pages, 1660 KB  
Article
Evaluating the Environmental Impact of Heat Pump Systems: An Integrated Approach to Sustainable Building Operations
by Mahdiyeh Zafaranchi, William T. Riddell, Nicholas B. Chan, Elizabeth Saliba and Luke Leung
Energies 2025, 18(2), 388; https://doi.org/10.3390/en18020388 - 17 Jan 2025
Cited by 1 | Viewed by 2839
Abstract
This study evaluates the energy consumption and embodied carbon emissions of various heat pump systems for an office building in Chicago, IL, U.S., over a 50-year lifespan, including the operation, manufacturing, and construction phases. The analyzed systems include air source heat pumps (ASHP) [...] Read more.
This study evaluates the energy consumption and embodied carbon emissions of various heat pump systems for an office building in Chicago, IL, U.S., over a 50-year lifespan, including the operation, manufacturing, and construction phases. The analyzed systems include air source heat pumps (ASHP) in Air to Air and Air to Water configurations, and ground source heat pumps (GSHP) in Soil to Air and Soil to Water configurations. A traditional HVAC system serves as the baseline for comparison. Advanced simulation tools, including Rhino, Grasshopper, TRACE 700, and One Click LCA, were used to identify the optimal HVAC system for sustainable building operations. Unlike prior studies focusing on GSHP versus traditional HVAC systems, this research directly compares GSHP and ASHP configurations, addressing a significant gap in the sustainable HVAC system design literature. The GSHP (Soil to Water) system demonstrated the lowest energy intensity at 100.8 kWh/m2·yr, a 41.8% improvement over the baseline, and the lowest total embodied carbon emissions at 3,882,164 kg CO2e. In contrast, the ASHP (Air to Air) system, while reducing energy consumption relative to the baseline, exhibited the highest embodied carbon emissions among the heat pump configurations due to its higher operational energy demands. The study highlights the significance of the operating phase in embodied carbon contributions. These findings emphasize the importance of a holistic design approach that considers both operational and embodied impacts to achieve sustainable building designs. Full article
(This article belongs to the Special Issue Sustainable Energy, Environment and Low-Carbon Development)
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Review

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29 pages, 8271 KB  
Review
A Review of Offshore Renewable Energy for Advancing the Clean Energy Transition
by Annette von Jouanne, Emmanuel Agamloh and Alex Yokochi
Energies 2025, 18(18), 4798; https://doi.org/10.3390/en18184798 - 9 Sep 2025
Viewed by 1091
Abstract
Offshore renewable energy resources are abundant and widely available worldwide, offering significant contributions to the clean energy net-zero carbon emission targets. This paper reviews strong and emerging offshore renewable energy sources, including wind (fixed bottom and floating), hydrokinetic wave and tidal energy, floating [...] Read more.
Offshore renewable energy resources are abundant and widely available worldwide, offering significant contributions to the clean energy net-zero carbon emission targets. This paper reviews strong and emerging offshore renewable energy sources, including wind (fixed bottom and floating), hydrokinetic wave and tidal energy, floating solar photovoltaics (FPVs) and hybrid energy systems. A literature review of recent sources yields a timely comprehensive comparison of the levelized cost of electricity (LCOE), technology readiness levels (TRLs), capacity factors (CFs) and global generation installed and potential, where offshore wind is recognized as being the strongest contributor to the clean energy transition and thus receives the most attention. Offshore wind grid integration, converter technologies, criticality, resiliency and energy storage integration are presented, in addition to challenges and research directions. While wave, tidal and FPV will never dominate the global grid, they have vital roles to play in the global energy transition; thus, they are reviewed, including technologies, installations, potential, challenges and research directions. Offshore hybrid energy systems, combining different offshore renewable energy sources, are also discussed along with example installations. The paper concludes with a discussion of the potential environmental impacts of offshore renewable energy development, including recommendations. Full article
(This article belongs to the Special Issue Sustainable Energy, Environment and Low-Carbon Development)
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