Green Energy and Resources最新文献

A mini review on AI-driven thermal treatment of solid Waste: Emission control and process optimization 人工智能驱动固体废物热处理技术综述：排放控制与工艺优化

Green Energy and Resources Pub Date : 2025-06-01 DOI: 10.1016/j.gerr.2025.100132

Dongjie Pang , Cristina Moliner , Tao Wang , Jin Sun , Xinyan Zhang , Yingping Pang , Xiqiang Zhao , Zhanlong Song , Ziliang Wang , Yanpeng Mao , Wenlong Wang

{"title":"A mini review on AI-driven thermal treatment of solid Waste: Emission control and process optimization","authors":"Dongjie Pang , Cristina Moliner , Tao Wang , Jin Sun , Xinyan Zhang , Yingping Pang , Xiqiang Zhao , Zhanlong Song , Ziliang Wang , Yanpeng Mao , Wenlong Wang","doi":"10.1016/j.gerr.2025.100132","DOIUrl":"10.1016/j.gerr.2025.100132","url":null,"abstract":"<div><div>The advent of novel waste disposal methodologies, which are energy-efficient and environmentally benign, has created opportunities for the deployment of artificial intelligence technologies in the management of solid waste treatment. This review examines the deployment of AI-optimized control algorithms in processes including pyrolysis, incineration, and gasification. The application of machine learning models, including linear regression (LR), genetic algorithm (GA), support vector machine (SVM), artificial neural networks (ANN), decision trees (DT), and Extreme Gradient Boosting (XGBoost), enables real-time monitoring of performance and dynamic adjustment of parameters to enhance energy recovery and minimize pollution. The implementation of AI-based solutions enables the optimization of key characteristics, such as temperature and oxygen levels, with the objective of achieving optimal energy efficiency while minimizing the emission of harmful substances, including CO, NOx, and dioxins. Notwithstanding these advancements, challenges remain in hyperparameter tuning, probabilistic assessments, and feature generation. A comprehensive understanding of future technologies will necessitate a synthesis of knowledge and data-oriented approaches, the design of autonomous control systems, and the integration of digital twin technologies to bridge the gap between theory and practice.</div></div>","PeriodicalId":100597,"journal":{"name":"Green Energy and Resources","volume":"3 2","pages":"Article 100132"},"PeriodicalIF":0.0,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144239406","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Flame acceleration in unconfined lean hydrogen-oxygen mixtures using a hemispherical soap bubble method 用半球形肥皂泡法在无约束贫氢-氧混合物中加速火焰

Green Energy and Resources Pub Date : 2025-06-01 DOI: 10.1016/j.gerr.2025.100129

Wookyung Kim , Keita Tanaka , Akihiro Ueda , Sushil Raut , Yangkyun Kim , Hongliang Luo

引用次数: 0

Time-series signal analysis of sustainable process intensification: Characterization method development of gas-solid fluidized bed hydrodynamics towards AI-enhanced algorithms 可持续过程强化的时间序列信号分析：气固流化床流体力学向ai增强算法的表征方法发展

Green Energy and Resources Pub Date : 2025-06-01 DOI: 10.1016/j.gerr.2025.100128

Yue Yuan , Silu Chen , Meifeng Li , Jesse Zhu , Lihui Feng , Tinghui Zhang , Kaiqiao Wu , Donovan Chaffart

{"title":"Time-series signal analysis of sustainable process intensification: Characterization method development of gas-solid fluidized bed hydrodynamics towards AI-enhanced algorithms","authors":"Yue Yuan , Silu Chen , Meifeng Li , Jesse Zhu , Lihui Feng , Tinghui Zhang , Kaiqiao Wu , Donovan Chaffart","doi":"10.1016/j.gerr.2025.100128","DOIUrl":"10.1016/j.gerr.2025.100128","url":null,"abstract":"<div><div>Sustainable manufacturing is pivotal to promoting societal advancements that balance the progressive growth of human needs with the gradual exhaustion of natural resources and the environmental impact of current manufacturing technologies. Gas-solid fluidization, a key process intensification technique, has advanced sustainability for over a century. The complex nature of these systems has led to numerous analysis algorithms for assessing time-series signals critical to observe the fluidization hydrodynamics. This work reviews widely used signal analysis methods for processing the commonly-measured time-series signals for fluidization, specifically focusing on pressure drop and optical signals. Despite their widespread implementation, these methods have limited potential due to the limited visibility of optical signals and the inability of pressure signals to provide localized fluidization system information. Veritably, the traditional algorithms cannot consider all influencing factors and handle flawed, large-scale signals.</div><div>Artificial intelligence (AI) has emerged as a promising solution to overcome these limitations. Nevertheless, AI-enhanced methods for fluidization signal analysis are still nascent. This work emphasizes the potential of AI to enhance understanding of complex fluidization behavior, particularly heterogeneous agglomerations, through reviewing signal analysis methods from traditional numerical methods to AI-driven approaches. Furthermore, this study highlights the future steps necessary to adequately expand upon machine learning-based analysis methodologies and extends a call to arms for future research establishment within this field. These advancements will support the development of sustainable manufacturing technologies that balance industrial progress with environmental responsibility.</div></div>","PeriodicalId":100597,"journal":{"name":"Green Energy and Resources","volume":"3 2","pages":"Article 100128"},"PeriodicalIF":0.0,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144212354","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

ZnCl2-activated S/N-doped biochar for low-temperature NH3-SCR of NOx: Performance and pathway analysis zncl2活化S/ n掺杂生物炭用于NOx的低温NH3-SCR：性能和途径分析

Green Energy and Resources Pub Date : 2025-06-01 DOI: 10.1016/j.gerr.2025.100133

Shuangshuang Yan , Dongmei Bi , Chengxizi Zhang , Zhisen He , Yu Ni , Kang Yue , Shanjian Liu

{"title":"ZnCl2-activated S/N-doped biochar for low-temperature NH3-SCR of NOx: Performance and pathway analysis","authors":"Shuangshuang Yan , Dongmei Bi , Chengxizi Zhang , Zhisen He , Yu Ni , Kang Yue , Shanjian Liu","doi":"10.1016/j.gerr.2025.100133","DOIUrl":"10.1016/j.gerr.2025.100133","url":null,"abstract":"<div><div>Carbon-based catalysts for low-temperature denitrification were prepared from wheat straw via ZnCl<sub>2</sub> activation and thiourea doping. The catalysts were systematically characterized using BET surface area analysis, NH<sub>3</sub>-TPD, XPS, and transient response experiments. The ZnCl<sub>2</sub>-activated catalyst exhibited a NO<sub><em>x</em></sub> reduction efficiency of 45.1%. To further enhance the denitrification performance, the Z<sub>1.2</sub> biochar was co-doped with sulfur and nitrogen. Experimental results demonstrated that the SN<sub>2.5</sub>Z<sub>1.2</sub>/AC biochar catalyst achieved a maximum NO conversion of 88% within the temperature range of 50–260°C and exhibited stable activity in long-term durability tests. Sulfur and nitrogen co-doping markedly increased the number of strong acid sites and surface chemisorbed oxygen (O<sub>α</sub>), thereby facilitating the formation of N-6 functional groups. The presence of C-SO<sub>3</sub>-H species may be a critical factor contributing to the enhanced NO<sub>x</sub> conversion. The denitrification process over sulfur- and nitrogen-doped biochar follows both the Eley-Rideal (E-R) and Langmuir-Hinshelwood (L-H) mechanisms, wherein •NH<sub>2</sub> radicals play a pivotal role in the reduction of NO to its gaseous and adsorbed forms.</div></div>","PeriodicalId":100597,"journal":{"name":"Green Energy and Resources","volume":"3 2","pages":"Article 100133"},"PeriodicalIF":0.0,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144306436","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Exploring the relationship between climate change, air pollutants and human health: Impacts, adaptation, and mitigation strategies 探索气候变化、空气污染物与人类健康之间的关系：影响、适应和缓解策略

Green Energy and Resources Pub Date : 2025-06-01 DOI: 10.1016/j.gerr.2024.100074

Gibson Owhoro Ofremu , Babatunde Yusuf Raimi , Samuel Omokhafe Yusuf , Beatrice Akorfa Dziwornu , Somtochukwu Godfrey Nnabuife , Adaeze Mary Eze , Chisom Assumpta Nnajiofor

{"title":"Exploring the relationship between climate change, air pollutants and human health: Impacts, adaptation, and mitigation strategies","authors":"Gibson Owhoro Ofremu , Babatunde Yusuf Raimi , Samuel Omokhafe Yusuf , Beatrice Akorfa Dziwornu , Somtochukwu Godfrey Nnabuife , Adaeze Mary Eze , Chisom Assumpta Nnajiofor","doi":"10.1016/j.gerr.2024.100074","DOIUrl":"10.1016/j.gerr.2024.100074","url":null,"abstract":"<div><div>The innumerable impact of climate change is a global menace to human health. This paper conveys a comprehensive review of scientific literature to explore the relationship between climate change, air pollutants, and human health. The integral relationship between climate change and health is complex and has a significant impact on every facet of human life. The impact can either be direct (e.g., exposures due to extreme heat, storms, flooding, and air pollution) or indirect (e.g., displacement, food security, and variation in water). The rising temperature of the planet could lead to increasingly severe health impacts from climate change in the future. It is important to take stringent climate actions to mitigate the climate change risk and adapt to the impacts that are already happening. To lessen the speed and severity of climate change, mitigation focuses on cutting greenhouse gas emissions. Options for adaptation include things like advancing to higher ground to stop sea levels from increasing, growing new crops that can grow in a new environment, or using novel construction methods. Investing in novel or enhanced technology, infrastructure, and research is frequently required for adaptation. The review emphasized the importance of considering both short-term and long-term adaptation strategies as well as mitigation efforts, which call for steps to address the root cause by halting or reducing the growth in fossil fuel emissions that might severely and completely increase the earth's scorching temperatures. The results of this study provide insightful viewpoints on adaptation measures, and mitigation strategies for decision-makers, experts in public health, and researchers working in the field of climate change and its effects on human health.</div></div>","PeriodicalId":100597,"journal":{"name":"Green Energy and Resources","volume":"3 2","pages":"Article 100074"},"PeriodicalIF":0.0,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141052124","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Review of machine learning applications for predicting the quality of biomass briquettes for sustainable and low-carbon energy solutions 回顾机器学习在预测可持续和低碳能源解决方案生物质压块质量方面的应用

Green Energy and Resources Pub Date : 2025-05-13 DOI: 10.1016/j.gerr.2025.100130

Constance Nakato Nakimuli , Fred Kaggwa , Johan De Greef , David Kilama Okot , Julien Blondeau , Simon Kawuma

{"title":"Review of machine learning applications for predicting the quality of biomass briquettes for sustainable and low-carbon energy solutions","authors":"Constance Nakato Nakimuli , Fred Kaggwa , Johan De Greef , David Kilama Okot , Julien Blondeau , Simon Kawuma","doi":"10.1016/j.gerr.2025.100130","DOIUrl":"10.1016/j.gerr.2025.100130","url":null,"abstract":"<div><div>This review discusses how Machine Learning has been applied to predict the quality of biomass briquettes produced from agricultural and municipal solid organic waste, which are crucial for advancing green and low-carbon energy solutions. Traditional methods of assessment of briquette quality involve destructive laboratory experiments, do not favor sample reuse, are time-consuming, and labor-intensive, posing barriers to efficient production. This paper reviews literature on various Machine Learning models applied for predicting and optimizing briquette quality parameters, including combustion, physical, and emission properties. Several Machine Learning models have shown promising results in predicting and optimizing these key parameters for example, a Random Forest model with R<sup>2</sup> of 0.9936 in deformation energy prediction and Artificial Neural Networks with R<sup>2</sup> of 0.8936 in the prediction of impact resistance. By enhancing the accuracy and efficiency of briquette quality predictions, Machine Learning algorithms contribute to the development of high-quality biomass briquettes, thereby creating sustainable and low-carbon energy systems. This review points to critical literature gaps regarding model generalizability across diverse biomass feedstocks and integration of broader quality parameters. Addressing these gaps will advance AI-based solutions, promote greener energy practices, and support sustainable development. The findings are intended to aid researchers, industry professionals, and policymakers in advancing the production of high-quality biomass briquettes for cleaner energy and sustainable development.</div></div>","PeriodicalId":100597,"journal":{"name":"Green Energy and Resources","volume":"3 3","pages":"Article 100130"},"PeriodicalIF":0.0,"publicationDate":"2025-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144570600","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Microbial biomass conversion for hydrogen production: A review 微生物生物质转化制氢研究进展

Green Energy and Resources Pub Date : 2025-05-10 DOI: 10.1016/j.gerr.2025.100131

Muhamad Reda Galih Pangestu , Shaikh Abdur Razzak , Shihab Uddin

{"title":"Microbial biomass conversion for hydrogen production: A review","authors":"Muhamad Reda Galih Pangestu , Shaikh Abdur Razzak , Shihab Uddin","doi":"10.1016/j.gerr.2025.100131","DOIUrl":"10.1016/j.gerr.2025.100131","url":null,"abstract":"<div><div>The escalating demand for clean and sustainable energy sources has propelled hydrogen to the forefront of alternative fuel research. Microbial biomass conversion, a bio-based process utilizing microorganisms to convert organic matter into hydrogen, presents a promising avenue for achieving this goal. This review provides a comprehensive overview of possible microbial biomass conversion methods, including both light-dependent and light-independent methods, and compares their hydrogen production rates (HPRs). Light-dependent methods such as photo-fermentation offer HPRs exceeding 3 m<sup>3</sup>/dm<sup>3</sup>, suggesting highly efficient hydrogen generation possibilities. However, most rely on indirect processes or specific light conditions, potentially hindering H<sub>2</sub> production. Dark fermentation (DF) demonstrates significantly higher HPRs, up to 12 m<sup>3</sup>/d/m<sup>3</sup>, with no light requirements, making it a strong contender for large-scale production. Microbial electrolysis cells (MECs) show even greater HPRs of up to 72 m<sup>3</sup>/d/m<sup>3</sup>, competing favorably in hydrogen generation feasibility. Despite promising advancements, challenges remain in scaling up these processes for commercial viability. While current research achieves high HPRs, reactor volumes are typically below 1 L. This review explores opportunities and challenges associated with scaling up, particularly focusing on integrating DF and MECs. Combining these methods holds promise for enhancing stability and achieving efficient energy recovery.</div></div>","PeriodicalId":100597,"journal":{"name":"Green Energy and Resources","volume":"3 3","pages":"Article 100131"},"PeriodicalIF":0.0,"publicationDate":"2025-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144580901","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Corrigendum to ‘Exploring the landscape of machine learning-aided research in biofuels and biodiesel: A bibliometric analysis’ [Green Energy Res. 2 (2024) 100089] “探索生物燃料和生物柴油中机器学习辅助研究的前景：文献计量分析”的勘误表[Green Energy Res. 2 (2024) 100089]

Green Energy and Resources Pub Date : 2025-05-05 DOI: 10.1016/j.gerr.2025.100117

Avinash Alagumalai, Hua Song

引用次数: 0

Dynamic process of hydrogen flow and spontaneous combustion in tubes featuring different configurations after leakage from 35 and 70 MPa 35 MPa和70 MPa泄漏后不同构型管内氢气流动和自燃的动态过程

Green Energy and Resources Pub Date : 2025-04-10 DOI: 10.1016/j.gerr.2025.100127

Qin Huang , Zuo-Yu Sun , Ya-Long Du , Jia-Ying Li

{"title":"Dynamic process of hydrogen flow and spontaneous combustion in tubes featuring different configurations after leakage from 35 and 70 MPa","authors":"Qin Huang , Zuo-Yu Sun , Ya-Long Du , Jia-Ying Li","doi":"10.1016/j.gerr.2025.100127","DOIUrl":"10.1016/j.gerr.2025.100127","url":null,"abstract":"<div><div>Hydrogen, as a green energy resource, presents a crucial opportunity to reduce emissions and facilitate the transition to sustainable energy, particularly in the shipping industry. The storage pressure for hydrogen gas (like 35 MPa for metal-composite Type III vessels and 70 MPa for polymer-composite Type IV vessels) is prone to leakage or even rupture, and hydrogen could be spontaneously ignited during pressurized leakage; thus, investigating the dynamics of spontaneous hydrogen combustion is essential for safely advancing hydrogen energy in marine applications. This study numerically examined the development of shockwaves and the spontaneous combustion process during pressurized leakage within tubes featuring various configurations (L-shaped and T-shaped, which are commonly found in actual pipelines) at pressures of 35 and 70 MPa. The results indicated that, upon release from the tested pressures, hydrogen would spontaneously ignite within the upstream sections of the tubes beyond the leakage port, with the flame propagating downstream along with the shockwave development. Notably, shockwave and spontaneous combustion characteristics variations differed across the two tube configurations. Velocity measurements showed that values would be lowest near the corner of the L-shaped tube, whereas they would consistently decline downstream in the T-shaped tube. This suggested that measures to mitigate shockwave effects (thus reducing the likelihood of spontaneous combustion) should be implemented in the upstream section of the tubes, regardless of the configuration. Additionally, pressure readings were highest near the corner of the L-shaped tube and showed a consistent decline downstream in the T-shaped tube. Therefore, protective measures addressing stress intensity should focus on the L-shaped tube's corner and the T-shaped tube's upstream section.</div></div>","PeriodicalId":100597,"journal":{"name":"Green Energy and Resources","volume":"3 2","pages":"Article 100127"},"PeriodicalIF":0.0,"publicationDate":"2025-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143869815","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Solar dryers: A review of mechanism, methods and critical analysis of transport models applicable in solar drying of product 太阳能干燥机：综述了适用于产品太阳能干燥的运输模型的机理、方法和关键分析

Green Energy and Resources Pub Date : 2025-03-01 DOI: 10.1016/j.gerr.2025.100118

Onyinyechi Nnamchi , Cyprian Tom , Godwin Akpan , Murphy Umunna , David Ubong , Mathew Ibeh , Adindu Linus–Chibuezeh , Leonard Akuwueke , Stephen Nnamchi , Augustine Ben , Macmanus Ndukwu

{"title":"Solar dryers: A review of mechanism, methods and critical analysis of transport models applicable in solar drying of product","authors":"Onyinyechi Nnamchi , Cyprian Tom , Godwin Akpan , Murphy Umunna , David Ubong , Mathew Ibeh , Adindu Linus–Chibuezeh , Leonard Akuwueke , Stephen Nnamchi , Augustine Ben , Macmanus Ndukwu","doi":"10.1016/j.gerr.2025.100118","DOIUrl":"10.1016/j.gerr.2025.100118","url":null,"abstract":"<div><div>As the world transitions towards green energy sources solar drying has become a vital technology for sustainable agricultural production, offering a cleaner, more efficient alternative to traditional drying methods. Solar drying has been demonstrated to be a sustainable and eco-friendly drying process for drying and preserving agricultural products, offering advantages over traditional methods that include faster drying rates, improved product quality, and reduced energy costs. This review examines the mechanisms and methods applicable to solar drying, including indirect and direct solar drying, hybrid systems combining solar drying with other heating sources, and thermal storage materials to address challenges such as intermittent solar radiation. The designs of solar drying systems include various solar collector configurations, drying chamber geometries, and air conveyance mechanisms crucial for efficient drying. This review therefore explores different design approaches and their effects on drying performance, highlighting the importance of understanding the complex interactions between system components. Additionally, the approach for Energy and exergy analysis of solar drying systems was explored, providing insights into energy utilization and efficiency. Finally, this review elucidates the complex transport phenomena governing solar drying, including moisture diffusion, heat and mass transfer, and airflow patterns. It identifies knowledge gaps in existing models and future research directions in transport modelling phenomena to advance sustainable, efficient, and scalable solar drying techniques.</div></div>","PeriodicalId":100597,"journal":{"name":"Green Energy and Resources","volume":"3 2","pages":"Article 100118"},"PeriodicalIF":0.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143873968","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0