Pub Date : 2025-10-13DOI: 10.1016/j.clet.2025.101093
Viktória Pitás, Béla Varga, Attila J. Trájer, Viola Somogyi
The effective biological treatment of concentrated and highly toxic coking wastewater (CWW) depends on several operational and technological parameters. This study investigates the adaptation of activated sludge to varying hydraulic and nutrient load, both on a technological, and a microbial scale, by evaluating six years’ operational data of a full-scale European coking wastewater treatment plant (CWWTP). Using machine learning ensemble methods (XGBoost, Random Forest, and Gradient Boosting), the volumetric Chemical Oxygen Demand (COD) load was identified as the most significant predictor of effluent COD compliance. The formerly unattainable Best Available Techniques (BAT) target of 220 mg COD/L in the effluent of the biological treatment step was kept stable under a volumetric load of 0.20 kg COD/m3 d and a specific load of 0.04 kg COD/kg MLVSSd. The identified loading threshold values are 0.30 kg COD/m3 d, which equals 0.05 kg COD/kg MLVSSd in the examined technology. Microbial analysis revealed significant shifts in community composition across loading periods, with functional genera adapting to phenol and SCN− loads. Further 39% reduction in the effluent residual COD is achievable with a well-chosen physico-chemical post-treatment, which basically affects the reuse potential of the treated effluent.
高浓度高毒焦化废水的有效生物处理取决于几个操作和技术参数。本研究通过评估欧洲一家全规模焦化废水处理厂（CWWTP） 6年的运行数据，在技术和微生物规模上研究了活性污泥对不同水力和养分负荷的适应性。使用机器学习集成方法（XGBoost、Random Forest和Gradient Boosting），将体积化学需氧量（COD）负荷确定为出水COD合规性的最重要预测因子。在容量负荷为0.20 kg COD/m3 d、比负荷为0.04 kg COD/kg MLVSS·d的条件下，生物处理步骤出水COD 220 mg /L的最佳可用技术（Best Available Techniques， BAT）指标保持稳定。确定的加载阈值为0.30 kg COD/m3 d，即0.05 kg COD/kg MLVSS⋅d。微生物分析显示，在不同的负荷时期，群落组成发生了显著变化，功能属适应苯酚和SCN−负荷。通过精心选择的物化后处理，可以进一步减少39%的出水残留COD，这基本上影响了处理后出水的再利用潜力。
{"title":"Adaptation of activated sludge to varying hydraulic and nutrient load in a coke oven wastewater treatment plant","authors":"Viktória Pitás, Béla Varga, Attila J. Trájer, Viola Somogyi","doi":"10.1016/j.clet.2025.101093","DOIUrl":"10.1016/j.clet.2025.101093","url":null,"abstract":"<div><div>The effective biological treatment of concentrated and highly toxic coking wastewater (CWW) depends on several operational and technological parameters. This study investigates the adaptation of activated sludge to varying hydraulic and nutrient load, both on a technological, and a microbial scale, by evaluating six years’ operational data of a full-scale European coking wastewater treatment plant (CWWTP). Using machine learning ensemble methods (XGBoost, Random Forest, and Gradient Boosting), the volumetric Chemical Oxygen Demand (COD) load was identified as the most significant predictor of effluent COD compliance. The formerly unattainable Best Available Techniques (BAT) target of 220 mg COD/L in the effluent of the biological treatment step was kept stable under a volumetric load of 0.20 kg COD/m<sup>3</sup> d and a specific load of 0.04 kg COD/kg MLVSS<span><math><mi>⋅</mi></math></span>d. The identified loading threshold values are 0.30 kg COD/m<sup>3</sup> d, which equals 0.05 kg COD/kg MLVSS<span><math><mi>⋅</mi></math></span>d in the examined technology. Microbial analysis revealed significant shifts in community composition across loading periods, with functional genera adapting to phenol and SCN<sup>−</sup> loads. Further 39% reduction in the effluent residual COD is achievable with a well-chosen physico-chemical post-treatment, which basically affects the reuse potential of the treated effluent.</div></div>","PeriodicalId":34618,"journal":{"name":"Cleaner Engineering and Technology","volume":"29 ","pages":"Article 101093"},"PeriodicalIF":6.5,"publicationDate":"2025-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145325814","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}
Pub Date : 2025-10-10DOI: 10.1016/j.clet.2025.101090
Hossein Saberi , Hamid Saberi
Modeling the compressive behavior of fiber-reinforced polymer (FRP)-confined recycled aggregate concrete (RAC) is essential for practical engineering applications. Existing models often overlook the nonlinear effects of recycled aggregate content on concrete strength, limiting their accuracy. To address this gap and promote sustainable construction, this study proposes a novel approach for predicting the stress-strain behavior of FRP-confined RAC under compression. Tاhe method integrates clustering techniques and singular value decomposition (SVD) to extract nonlinear relationships between key system parameters and stress-strain curves. The least squares method is then used to optimize unknown system parameters. A dataset comprising 81 stress-strain curves from eight references, totaling 2452 digitized data points at a strain rate of 0.0005, was used to train the model. The proposed approach is validated against experimental results, demonstrating high accuracy in capturing the mechanical behavior of FRP-confined RAC. These findings provide a more reliable predictive tool for structural engineers and contribute to the advancement of sustainable concrete technologies.
{"title":"Recycled aggregate concrete confined with FRP under compression: A machine learning-driven framework and parametric analysis","authors":"Hossein Saberi , Hamid Saberi","doi":"10.1016/j.clet.2025.101090","DOIUrl":"10.1016/j.clet.2025.101090","url":null,"abstract":"<div><div>Modeling the compressive behavior of fiber-reinforced polymer (FRP)-confined recycled aggregate concrete (RAC) is essential for practical engineering applications. Existing models often overlook the nonlinear effects of recycled aggregate content on concrete strength, limiting their accuracy. To address this gap and promote sustainable construction, this study proposes a novel approach for predicting the stress-strain behavior of FRP-confined RAC under compression. Tاhe method integrates clustering techniques and singular value decomposition (SVD) to extract nonlinear relationships between key system parameters and stress-strain curves. The least squares method is then used to optimize unknown system parameters. A dataset comprising 81 stress-strain curves from eight references, totaling 2452 digitized data points at a strain rate of 0.0005, was used to train the model. The proposed approach is validated against experimental results, demonstrating high accuracy in capturing the mechanical behavior of FRP-confined RAC. These findings provide a more reliable predictive tool for structural engineers and contribute to the advancement of sustainable concrete technologies.</div></div>","PeriodicalId":34618,"journal":{"name":"Cleaner Engineering and Technology","volume":"29 ","pages":"Article 101090"},"PeriodicalIF":6.5,"publicationDate":"2025-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145325211","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}
Pub Date : 2025-10-09DOI: 10.1016/j.clet.2025.101094
Moslem Savari , Mohammad Shokati Amghani , Ashraf Malekian
The sustainability of water resources and their optimal utilization have emerged as critical global challenges. In Iran, water scarcity combined with population growth has intensified pressure on existing water supplies. Given the agricultural sector's substantial share in freshwater consumption, effective water resource management in this domain is particularly vital. One promising solution is the use of treated wastewater (TWW), which offers considerable economic, environmental, and social benefits. However, its adoption by farmers faces notable barriers. This study aims to investigate the factors influencing Iranian farmers' willingness to use TWW for irrigating agricultural crops. The research employs the Diffusion of Innovation (DOI) theoretical framework to analyze farmers' adoption behavior. Additionally, the study controls for individual-level variables within the model—an approach that has received limited attention in previous structural and model-based research. The statistical population comprises farmers in Tehran Province, located in central Iran. Data were collected via a structured questionnaire and analyzed using structural equation modeling (SEM). The results demonstrate the effectiveness of the DOI framework, with all hypothesized relationships proving statistically significant. The model explains 60.1 % of the variance in farmers' acceptance of TWW for irrigation purposes. Key DOI constructs—relative advantage, compatibility, complexity, observability, and trialability—were found to significantly influence adoption. Despite its contributions, the study is limited by its geographic focus, the absence of broader cultural, institutional, and economic considerations, and constraints on the generalizability of its findings. Nevertheless, the results provide a valuable foundation for designing extension programs, educational initiatives, and policy support mechanisms aimed at promoting sustainable agriculture through the use of alternative water resources.
{"title":"Application of the diffusion of innovation theory to identify factors affecting the use of treated wastewater in crop irrigation: a study in Tehran province","authors":"Moslem Savari , Mohammad Shokati Amghani , Ashraf Malekian","doi":"10.1016/j.clet.2025.101094","DOIUrl":"10.1016/j.clet.2025.101094","url":null,"abstract":"<div><div>The sustainability of water resources and their optimal utilization have emerged as critical global challenges. In Iran, water scarcity combined with population growth has intensified pressure on existing water supplies. Given the agricultural sector's substantial share in freshwater consumption, effective water resource management in this domain is particularly vital. One promising solution is the use of treated wastewater (TWW), which offers considerable economic, environmental, and social benefits. However, its adoption by farmers faces notable barriers. This study aims to investigate the factors influencing Iranian farmers' willingness to use TWW for irrigating agricultural crops. The research employs the Diffusion of Innovation (DOI) theoretical framework to analyze farmers' adoption behavior. Additionally, the study controls for individual-level variables within the model—an approach that has received limited attention in previous structural and model-based research. The statistical population comprises farmers in Tehran Province, located in central Iran. Data were collected via a structured questionnaire and analyzed using structural equation modeling (SEM). The results demonstrate the effectiveness of the DOI framework, with all hypothesized relationships proving statistically significant. The model explains 60.1 % of the variance in farmers' acceptance of TWW for irrigation purposes. Key DOI constructs—relative advantage, compatibility, complexity, observability, and trialability—were found to significantly influence adoption. Despite its contributions, the study is limited by its geographic focus, the absence of broader cultural, institutional, and economic considerations, and constraints on the generalizability of its findings. Nevertheless, the results provide a valuable foundation for designing extension programs, educational initiatives, and policy support mechanisms aimed at promoting sustainable agriculture through the use of alternative water resources.</div></div>","PeriodicalId":34618,"journal":{"name":"Cleaner Engineering and Technology","volume":"29 ","pages":"Article 101094"},"PeriodicalIF":6.5,"publicationDate":"2025-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145269619","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}
Pub Date : 2025-10-07DOI: 10.1016/j.clet.2025.101092
Mohammad Khajouei, Brajesh K. Singh, Mohammad Latifi, Jamal Chaouki
High-purity phosphorus production from varying grades of phosphate ore typically involves energy-intensive and operationally complex processes. In this study, thermodynamic analyses and experimental validations were performed to evaluate the feasibility of phosphorus gas production through a sustainable process comprising thermal decomposition and smelting of phosphate ores. The thermal treatment, conducted without a reducing agent, facilitated the removal of carbon dioxide (CO2) and heavy metals from the ore, simplifying downstream processing and reducing the size of required equipment. Experimental results confirmed that fluorapatite remains stable up to 900 °C and begins decomposing at higher temperatures, aligning closely with thermodynamic predictions. The subsequent smelting step, conducted with carbon as the reducing agent and silica as the fluxing agent, enabled over 95 % recovery of gaseous phosphorus at 1500 °C under optimal conditions.
Thermodynamic and experimental findings demonstrated that higher-grade phosphate ores necessitate higher operating temperatures for smelting. Optimal temperature ranges for thermal treatment and smelting of low-to high-grade phosphate ores were determined to be 800–1100 °C and 1300–1600 °C, respectively. Heavy metals such as cadmium, arsenic, and lead were fully removed during thermal treatment, while chromium, uranium, and vanadium predominantly remained in the slag phase during smelting. Zinc was the only heavy metal likely to co-mingle with gaseous phosphorus in the proposed process. The results validate the importance of fluxing and reducing agents in optimizing phosphorus recovery and highlight the potential for sustainable high-temperature processes. The influence of temperature, fluxing agents, and gaseous reactants on phosphorus recovery is thoroughly discussed, providing critical insights for process optimization.
{"title":"Thermodynamic and experimental insights toward an eco-friendly phosphorus production","authors":"Mohammad Khajouei, Brajesh K. Singh, Mohammad Latifi, Jamal Chaouki","doi":"10.1016/j.clet.2025.101092","DOIUrl":"10.1016/j.clet.2025.101092","url":null,"abstract":"<div><div>High-purity phosphorus production from varying grades of phosphate ore typically involves energy-intensive and operationally complex processes. In this study, thermodynamic analyses and experimental validations were performed to evaluate the feasibility of phosphorus gas production through a sustainable process comprising thermal decomposition and smelting of phosphate ores. The thermal treatment, conducted without a reducing agent, facilitated the removal of carbon dioxide (CO<sub>2</sub>) and heavy metals from the ore, simplifying downstream processing and reducing the size of required equipment. Experimental results confirmed that fluorapatite remains stable up to 900 °C and begins decomposing at higher temperatures, aligning closely with thermodynamic predictions. The subsequent smelting step, conducted with carbon as the reducing agent and silica as the fluxing agent, enabled over 95 % recovery of gaseous phosphorus at 1500 °C under optimal conditions.</div><div>Thermodynamic and experimental findings demonstrated that higher-grade phosphate ores necessitate higher operating temperatures for smelting. Optimal temperature ranges for thermal treatment and smelting of low-to high-grade phosphate ores were determined to be 800–1100 °C and 1300–1600 °C, respectively. Heavy metals such as cadmium, arsenic, and lead were fully removed during thermal treatment, while chromium, uranium, and vanadium predominantly remained in the slag phase during smelting. Zinc was the only heavy metal likely to co-mingle with gaseous phosphorus in the proposed process. The results validate the importance of fluxing and reducing agents in optimizing phosphorus recovery and highlight the potential for sustainable high-temperature processes. The influence of temperature, fluxing agents, and gaseous reactants on phosphorus recovery is thoroughly discussed, providing critical insights for process optimization.</div></div>","PeriodicalId":34618,"journal":{"name":"Cleaner Engineering and Technology","volume":"29 ","pages":"Article 101092"},"PeriodicalIF":6.5,"publicationDate":"2025-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145269616","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}
This research investigates the integration of photovoltaic (PV) rooftop systems with vanadium redox flow batteries (VRFB) for residential energy storage applications. Using solar irradiance data from the Bangkok Metropolitan Region and residential load profiles based on energy consumption statistics for Thai households, simulations were conducted using Homer Pro to evaluate system performance and optimize component sizing. The results showed that increasing PV capacity leads to significant surplus energy, which can be effectively stored in VRFB systems. A configuration consisting of a 6 kW PV system and a 35 kWh VRFB achieved an energy storage efficiency of 80.14 %, reduced electricity costs by 35 % compared to grid-only usage, and lowered annual CO2 emissions by 4.73 ton CO2/year relative to conventional fossil-based systems. Additionally, the system enhanced grid independence by fully eliminating peak demand fluctuations and maintained stable operation under varying solar conditions. These findings offered practical insights for the design of efficient and sustainable PV-VRFB systems in residential settings.
{"title":"Performance analysis of vanadium redox flow battery for residential photovoltaic integrated energy storage system","authors":"Akeratana Noppakant , Surasak Noituptim , Sawek Pratummet , Supapradit Marsong , Wanwinit Wijittemee , Sarun Nakthanom , Boonyang Plangklang","doi":"10.1016/j.clet.2025.101087","DOIUrl":"10.1016/j.clet.2025.101087","url":null,"abstract":"<div><div>This research investigates the integration of photovoltaic (PV) rooftop systems with vanadium redox flow batteries (VRFB) for residential energy storage applications. Using solar irradiance data from the Bangkok Metropolitan Region and residential load profiles based on energy consumption statistics for Thai households, simulations were conducted using Homer Pro to evaluate system performance and optimize component sizing. The results showed that increasing PV capacity leads to significant surplus energy, which can be effectively stored in VRFB systems. A configuration consisting of a 6 kW PV system and a 35 kWh VRFB achieved an energy storage efficiency of 80.14 %, reduced electricity costs by 35 % compared to grid-only usage, and lowered annual CO<sub>2</sub> emissions by 4.73 ton CO<sub>2</sub>/year relative to conventional fossil-based systems. Additionally, the system enhanced grid independence by fully eliminating peak demand fluctuations and maintained stable operation under varying solar conditions. These findings offered practical insights for the design of efficient and sustainable PV-VRFB systems in residential settings.</div></div>","PeriodicalId":34618,"journal":{"name":"Cleaner Engineering and Technology","volume":"29 ","pages":"Article 101087"},"PeriodicalIF":6.5,"publicationDate":"2025-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145269618","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}
Pub Date : 2025-10-02DOI: 10.1016/j.clet.2025.101089
Abdul-Mugis Yussif , Ridwan Taiwo , Pshtiwan Shakor , Tong Han , Saeed Reza Mohandes , Maxwell Fordjour Antwi-Afari , Kamal Qazi , Atul Kumar Singh , Mary Subaja Christo , Mohd Asif Shah
Building green for sustainability cannot be over-emphasised, considering the current environmental crises. Green buildings minimise environmental degradation and reduce consumption of depletable resources while providing maximum occupancy satisfaction. Despite the numerous studies of risk assessment in Green Building Construction Projects (GBCPs), limited attention has been given to methodologies that enable risk evaluation from the projects' inception to the end of their service life. Secondly, the existing methods do not consider the accumulated knowledge and experience obtained from previous risk assessment models. Finally, existing studies fail to provide a detailed description of each risk, as they only list them, leading to ambiguity in the practical sense. A scientometric analysis was performed to reveal the current research trend of risk identification in GBCPs. This study systematically reviewed relevant literature from the last two decades until the end of 2024 to collate the most influential risks associated with GBCPs. From the systematic literature review, a total of forty-two (42) risks were identified and defined clearly before further grouping them into nine (9) mutually exclusive categories to ease targeted assessments. The knowledge-based approach was proposed for identifying and evaluating the risks due to its unique nature of enabling long-term analysis by tapping into the accumulated knowledge and experience from previous evaluation models. The knowledge-based approach emphasises establishing a strong foundation involving risk scope definition, identification, analysis, response planning, execution, and monitoring and control as a feedback system supporting risk evaluation throughout the service life of the project. After the analysis, it was found that the risk evaluation studies in GBCPs need to create assessment models that consider the post-construction variables and the accumulated knowledge of previous evaluations. Secondly, a clear description of each risk eases its categorisation for tailor-targeted assessment. The current limitations include limited collaboration between developing and developed countries and a scarcity of empirical research in developing nations. The study proposes future research opportunities in green building risk studies to promote research growth, highlights the need for holistic risk management frameworks, and fosters sustainable construction practices globally.
{"title":"A comprehensive literature review on risk identification and assessment in green building construction projects","authors":"Abdul-Mugis Yussif , Ridwan Taiwo , Pshtiwan Shakor , Tong Han , Saeed Reza Mohandes , Maxwell Fordjour Antwi-Afari , Kamal Qazi , Atul Kumar Singh , Mary Subaja Christo , Mohd Asif Shah","doi":"10.1016/j.clet.2025.101089","DOIUrl":"10.1016/j.clet.2025.101089","url":null,"abstract":"<div><div>Building green for sustainability cannot be over-emphasised, considering the current environmental crises. Green buildings minimise environmental degradation and reduce consumption of depletable resources while providing maximum occupancy satisfaction. Despite the numerous studies of risk assessment in Green Building Construction Projects (GBCPs), limited attention has been given to methodologies that enable risk evaluation from the projects' inception to the end of their service life. Secondly, the existing methods do not consider the accumulated knowledge and experience obtained from previous risk assessment models. Finally, existing studies fail to provide a detailed description of each risk, as they only list them, leading to ambiguity in the practical sense. A scientometric analysis was performed to reveal the current research trend of risk identification in GBCPs. This study systematically reviewed relevant literature from the last two decades until the end of 2024 to collate the most influential risks associated with GBCPs. From the systematic literature review, a total of forty-two (42) risks were identified and defined clearly before further grouping them into nine (9) mutually exclusive categories to ease targeted assessments. The knowledge-based approach was proposed for identifying and evaluating the risks due to its unique nature of enabling long-term analysis by tapping into the accumulated knowledge and experience from previous evaluation models. The knowledge-based approach emphasises establishing a strong foundation involving risk scope definition, identification, analysis, response planning, execution, and monitoring and control as a feedback system supporting risk evaluation throughout the service life of the project. After the analysis, it was found that the risk evaluation studies in GBCPs need to create assessment models that consider the post-construction variables and the accumulated knowledge of previous evaluations. Secondly, a clear description of each risk eases its categorisation for tailor-targeted assessment. The current limitations include limited collaboration between developing and developed countries and a scarcity of empirical research in developing nations. The study proposes future research opportunities in green building risk studies to promote research growth, highlights the need for holistic risk management frameworks, and fosters sustainable construction practices globally.</div></div>","PeriodicalId":34618,"journal":{"name":"Cleaner Engineering and Technology","volume":"29 ","pages":"Article 101089"},"PeriodicalIF":6.5,"publicationDate":"2025-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145325214","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}
This study investigates the potential of torrefied rubberwood pellets (TWP) as a sustainable biofuel, using waste from southern Thailand's wood processing industry. A multi-criteria framework combining experimental analysis, CO2 emission, and an Economic Environmental Index (EEI) was employed to optimize torrefaction conditions and evaluate industrial scalability. The optimal conditions were identified to be 288 °C for 30 min, resulting in a volumetric energy density of 16.10 GJ m−3 and an eco-efficiency of 0.16 %YE (kg CO2_eq/kg biomass)−1 USD−1. This demonstrates a critical balance between energy quality and environmental impact. Compared to conventional wood pellets, torrefaction reduced CO2 emissions by 27 %. GIS mapping was used to plan regional logistics routes, while scenario analyses demonstrated enhanced profitability (EEI ratio: 2.73) and carbon credit opportunities, reducing 2275 kg CO2_eq per ton of coal replaced. The study establishes TWP as a carbon-negative biofuel suitable for power generation and cement production, supporting Thailand's transition to a circular bioeconomy. By bridging technological innovation with regional waste valorization, this research provides a replicable model for sustainable biomass utilization in tropical agro-industrial contexts.
本研究调查了碳化橡胶木颗粒（TWP）作为可持续生物燃料的潜力，使用来自泰国南部木材加工业的废物。采用实验分析、二氧化碳排放和经济环境指数（EEI）相结合的多准则框架来优化焙烧条件和评估工业可扩展性。最佳条件为288°C， 30 min，其体积能量密度为16.10 GJ m−3，生态效率为0.16% YE （kg CO2_eq/kg生物量）−1 USD−1。这表明了能源质量和环境影响之间的关键平衡。与传统木屑颗粒相比，焙烧减少了27%的二氧化碳排放量。GIS制图用于规划区域物流路线，而情景分析表明，提高了盈利能力（EEI比率：2.73）和碳信用机会，每吨替代煤炭减少2275 kg CO2_eq。该研究确定TWP是一种适用于发电和水泥生产的负碳生物燃料，支持泰国向循环生物经济过渡。通过将技术创新与区域废物增值相结合，本研究为热带农业工业环境下的可持续生物质利用提供了一个可复制的模型。
{"title":"Exploiting torrefied rubberwood pellets for sustainable energy in Southern Thailand: Integrated techno-economic and environmental optimization","authors":"Wipawee Dechapanya , Jannisa Kasawapat , Jonathon Huw Lewis , Attaso Khamwichit","doi":"10.1016/j.clet.2025.101085","DOIUrl":"10.1016/j.clet.2025.101085","url":null,"abstract":"<div><div>This study investigates the potential of torrefied rubberwood pellets (TWP) as a sustainable biofuel, using waste from southern Thailand's wood processing industry. A multi-criteria framework combining experimental analysis, CO<sub>2</sub> emission, and an Economic Environmental Index (EEI) was employed to optimize torrefaction conditions and evaluate industrial scalability. The optimal conditions were identified to be 288 °C for 30 min, resulting in a volumetric energy density of 16.10 GJ m<sup>−3</sup> and an eco-efficiency of 0.16 %Y<sub>E</sub> (kg CO<sub>2_eq</sub>/kg biomass)<sup>−1</sup> USD<sup>−1</sup>. This demonstrates a critical balance between energy quality and environmental impact. Compared to conventional wood pellets, torrefaction reduced CO<sub>2</sub> emissions by 27 %. GIS mapping was used to plan regional logistics routes, while scenario analyses demonstrated enhanced profitability (EEI ratio: 2.73) and carbon credit opportunities, reducing 2275 kg CO<sub>2_eq</sub> per ton of coal replaced. The study establishes TWP as a carbon-negative biofuel suitable for power generation and cement production, supporting Thailand's transition to a circular bioeconomy. By bridging technological innovation with regional waste valorization, this research provides a replicable model for sustainable biomass utilization in tropical agro-industrial contexts.</div></div>","PeriodicalId":34618,"journal":{"name":"Cleaner Engineering and Technology","volume":"29 ","pages":"Article 101085"},"PeriodicalIF":6.5,"publicationDate":"2025-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145222748","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}
Pub Date : 2025-09-25DOI: 10.1016/j.clet.2025.101088
Sepehr Sanaye, Armin Farvizi
Wind energy as a renewable and sustainable type of energy has been attractive from past eras. Three helical blade vertical axis wind turbine (VAWT-3-HB) is suitable for the use in urban areas with low-speed wind flow due to its low required amount of torque for self-starting and its low noise generation. The optimization of VAWT-3-HB with application of Artificial -Neural -Network (ANN) and Genetic -Algorithm (GA) which are very important tools for proper design and improving the performance and of this category of wind turbine still is not covered in literature. For GA optimization procedure, the average power coefficient () was the objective function which had to be maximized. Design variables were airfoil chord length, helical angle, and the blade tip speed ratio which were selected after extensive 3-D-CFD simulation runs and examining all effective parameters. The optimal values of these parameters were obtained 0.42 m, 30 , and 1.4 respectively. at the optimum point was 0.1845 with 218 % rise (in comparison with 0.058 before optimization). Results of a 3-D-CFD simulation run with optimal values of design variables showed a good match between average power coefficients predicted by ANN-GA and predicted by 3-D-CFD simulation run with about 0.21 % difference.
{"title":"Artificial -neural -network and genetic -algorithm for optimization of helical -blade -vertical -axis -wind -turbine","authors":"Sepehr Sanaye, Armin Farvizi","doi":"10.1016/j.clet.2025.101088","DOIUrl":"10.1016/j.clet.2025.101088","url":null,"abstract":"<div><div>Wind energy as a renewable and sustainable type of energy has been attractive from past eras. Three helical blade vertical axis wind turbine (VAWT-3-HB) is suitable for the use in urban areas with low-speed wind flow due to its low required amount of torque for self-starting and its low noise generation. The optimization of VAWT-3-HB with application of Artificial -Neural -Network (ANN) and Genetic -Algorithm (GA) which are very important tools for proper design and improving the performance and of this category of wind turbine still is not covered in literature. For GA optimization procedure, the average power coefficient (<span><math><mrow><msub><mi>C</mi><mrow><mi>p</mi><mo>−</mo><mi>a</mi><mi>v</mi><mi>e</mi></mrow></msub></mrow></math></span>) was the objective function which had to be maximized. Design variables were airfoil chord length, helical angle, and the blade tip speed ratio which were selected after extensive 3-D-CFD simulation runs and examining all effective parameters. The optimal values of these parameters were obtained 0.42 m, 30 <span><math><mrow><mo>°</mo></mrow></math></span>, and 1.4 respectively. <span><math><mrow><msub><mi>C</mi><mrow><mi>p</mi><mo>−</mo><mi>a</mi><mi>v</mi><mi>e</mi></mrow></msub></mrow></math></span> at the optimum point was 0.1845 with 218 % rise (in comparison with 0.058 before optimization). Results of a 3-D-CFD simulation run with optimal values of design variables showed a good match between average power coefficients predicted by ANN-GA and predicted by 3-D-CFD simulation run with about 0.21 % difference.</div></div>","PeriodicalId":34618,"journal":{"name":"Cleaner Engineering and Technology","volume":"29 ","pages":"Article 101088"},"PeriodicalIF":6.5,"publicationDate":"2025-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145269621","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}
Pub Date : 2025-09-25DOI: 10.1016/j.clet.2025.101086
Md. Tushar Ali, Qauzi Hamidul Bari, Islam M. Rafizul
Unsanitary landfill practices in developing countries like Bangladesh significantly contribute to global greenhouse gas (GHG) emissions, exacerbating climate change impacts. GHG estimation and measurement often rely on approximate input data, overlooking waste height variations and leading to emission inconsistencies. This study employs LandGEM-V-3.03, integrating actual landfill waste deposition from truck scale monitoring, waste generation and collection trends, and a precisely estimated landfill lifespan for improved assessment. Additionally, a static closed flux chamber was used to measure CH4 and CO2 across four seasons at varying waste heights, which were precisely assessed using a LiDAR-based Digital Terrain Model (DTM). The study also examined emission correlations with temperature and humidity. Results show a sharp increase in methane emissions, peaking at 5.8 Gg/year in 2025, driven by waste-damping rates. Humidity exhibits a stronger correlation with methane emissions (R2 = 0.998, 0.944 for model and field) and is statistically significant (p < 0.05), unlike temperature. A similar trend was observed for CO2, where emissions were significantly higher than CH4 (CH4-to-CO2 ratio 0.25 to 0.57) due to both aerobic and anaerobic production modes. Field measurements underestimated emissions by 5–20 %, with the highest emissions and discrepancies occurring during monsoon. Waste height significantly influenced CH4 emissions (R2 = 0.82, p = 0.00), increasing at 2.88 mg/m2/min per meter, while CO2 emissions showed a weaker, statistically insignificant correlation (R2 = 0.4, p > 0.05). The study highlights the critical need for improved landfill management practices and precise emission monitoring for effective GHG mitigation.
{"title":"Field validation of predictive model for greenhouse gas emissions from unsanitary landfill","authors":"Md. Tushar Ali, Qauzi Hamidul Bari, Islam M. Rafizul","doi":"10.1016/j.clet.2025.101086","DOIUrl":"10.1016/j.clet.2025.101086","url":null,"abstract":"<div><div>Unsanitary landfill practices in developing countries like Bangladesh significantly contribute to global greenhouse gas (GHG) emissions, exacerbating climate change impacts. GHG estimation and measurement often rely on approximate input data, overlooking waste height variations and leading to emission inconsistencies. This study employs LandGEM-V-3.03, integrating actual landfill waste deposition from truck scale monitoring, waste generation and collection trends, and a precisely estimated landfill lifespan for improved assessment. Additionally, a static closed flux chamber was used to measure CH<sub>4</sub> and CO<sub>2</sub> across four seasons at varying waste heights, which were precisely assessed using a LiDAR-based Digital Terrain Model (DTM). The study also examined emission correlations with temperature and humidity. Results show a sharp increase in methane emissions, peaking at 5.8 Gg/year in 2025, driven by waste-damping rates. Humidity exhibits a stronger correlation with methane emissions (R<sup>2</sup> = 0.998, 0.944 for model and field) and is statistically significant (p < 0.05), unlike temperature. A similar trend was observed for CO<sub>2</sub>, where emissions were significantly higher than CH<sub>4</sub> (CH<sub>4</sub>-to-CO<sub>2</sub> ratio 0.25 to 0.57) due to both aerobic and anaerobic production modes. Field measurements underestimated emissions by 5–20 %, with the highest emissions and discrepancies occurring during monsoon. Waste height significantly influenced CH<sub>4</sub> emissions (R<sup>2</sup> = 0.82, p = 0.00), increasing at 2.88 mg/m<sup>2</sup>/min per meter, while CO<sub>2</sub> emissions showed a weaker, statistically insignificant correlation (R<sup>2</sup> = 0.4, p > 0.05). The study highlights the critical need for improved landfill management practices and precise emission monitoring for effective GHG mitigation.</div></div>","PeriodicalId":34618,"journal":{"name":"Cleaner Engineering and Technology","volume":"29 ","pages":"Article 101086"},"PeriodicalIF":6.5,"publicationDate":"2025-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145222749","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}
Pub Date : 2025-09-24DOI: 10.1016/j.clet.2025.101082
Reza Shahin , Maxim A. Dulebenets
Recent studies on Vehicle Routing Problems (VRP) have substantially expanded to incorporate environmental considerations into transportation planning. Traditionally, the predominant objectives in transportation optimization revolved around reducing costs, time, or distance. However, with the increasing significance of sustainability and the management of environmental costs, logistics service providers and retailers have shifted their attention to greening their operations. In light of this, the Pollution-Routing Problem (PRP) has emerged to harmonize economic and environmental facets of transportation efforts. Despite the extensive research on the problem, there exists a notable absence of systematic reviews. As such, this review article sheds light on the evolution of the problem literature from its introduction in 2011 to 2024, reviewing 75 papers. In this study, the research on the PRP is categorized based on the taxonomy, objective function, and methodologies applied throughout the years. Finally, we pinpoint several areas of potential exploration that will serve as a blueprint for future research directions.
{"title":"From cost-centering to sustainability: A review of Pollution Routing Problems","authors":"Reza Shahin , Maxim A. Dulebenets","doi":"10.1016/j.clet.2025.101082","DOIUrl":"10.1016/j.clet.2025.101082","url":null,"abstract":"<div><div>Recent studies on Vehicle Routing Problems (VRP) have substantially expanded to incorporate environmental considerations into transportation planning. Traditionally, the predominant objectives in transportation optimization revolved around reducing costs, time, or distance. However, with the increasing significance of sustainability and the management of environmental costs, logistics service providers and retailers have shifted their attention to greening their operations. In light of this, the Pollution-Routing Problem (PRP) has emerged to harmonize economic and environmental facets of transportation efforts. Despite the extensive research on the problem, there exists a notable absence of systematic reviews. As such, this review article sheds light on the evolution of the problem literature from its introduction in 2011 to 2024, reviewing 75 papers. In this study, the research on the PRP is categorized based on the taxonomy, objective function, and methodologies applied throughout the years. Finally, we pinpoint several areas of potential exploration that will serve as a blueprint for future research directions.</div></div>","PeriodicalId":34618,"journal":{"name":"Cleaner Engineering and Technology","volume":"29 ","pages":"Article 101082"},"PeriodicalIF":6.5,"publicationDate":"2025-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145159171","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}
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