Cleaner Engineering and Technology最新文献

{"title":"Identifying and analyzing obstacles to ESG-driven sustainable transition in third-party logistics: A WINGS–ISM approach under interval-valued spherical fuzzy modeling","authors":"Detcharat Sumrit,&nbsp;Rodsak Kongsakul","doi":"10.1016/j.clet.2026.101157","DOIUrl":"10.1016/j.clet.2026.101157","url":null,"abstract":"<div><div>This study investigates the hierarchical structure and causal relationships among obstacles hindering the ESG driven sustainable transition of small and medium sized third-party logistics firms. Drawing on the resource-based view (RBV) and institutional (INT) theory, eleven obstacles are identified and validated, comprising eight endogenous and three exogenous factors. To address ambiguity, hesitation, and partial knowledge in expert judgments, the study adopts interval valued spherical fuzzy sets, which allow the simultaneous representation of membership, non-membership, and hesitancy degrees within bounded intervals. Compared with conventional Type 1 and Type 2 fuzzy sets, this approach provides greater expressive flexibility without imposing excessive computational or interpretability burdens in small expert panel studies. Using the Weighted Influence Nonlinear Gauge System (WINGS), six endogenous obstacles are revealed as dominant driving barriers, indicating that limitations in financial capacity, technological and digital infrastructure, process standardization, and sustainability capabilities primarily constrain ESG implementation, consistent with RBV logic emphasizing firm specific resources. In contrast, exogenous obstacles related to organizational culture, strategic alignment, regulatory coherence, governmental incentives, and stakeholder collaboration function mainly as dependent effect factors shaped by institutional conditions. Using Interpretive Structural Modeling (ISM) further identifies a five-level hierarchy, with obsolete technological infrastructure emerging as the root barrier. The study provides actionable insights for managers and policymakers seeking to design capability-oriented interventions and supportive institutional mechanisms to accelerate ESG transitions in SME logistics and other service intensive sectors.</div></div>","PeriodicalId":34618,"journal":{"name":"Cleaner Engineering and Technology","volume":"31 ","pages":"Article 101157"},"PeriodicalIF":6.5,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146191375","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}

{"title":"Systematic digital framework for optimizing changeover cleaning in pharmaceutical industries","authors":"Megha Das,&nbsp;Gintaras V. Reklaitis,&nbsp;Zoltan K. Nagy","doi":"10.1016/j.clet.2026.101164","DOIUrl":"10.1016/j.clet.2026.101164","url":null,"abstract":"<div><div>A generalized and systematic framework for optimizing the changeover cleaning process in pharmaceutical manufacturing has been developed, with its application demonstrated in various scenarios to facilitate better decision-making regarding cleaning. This framework enhances cleaning decision-making by incorporating detailed modeling of various cleaning mechanisms tailored to common vessel configurations and cleaning modes prevalent in the industry. By extending the approach to entire process flowsheets comprising multiple unit operations, the framework proves effective in quantifying and demonstrating rational utilization of washing solvents and better non-productive downtime management associated with cleaning activities. The comprehensive analysis yields insights for the identification of optimal cleaning conditions that achieve regulatory cleanliness standards while minimizing operational cleaning costs by approximately up to 91% and environmental footprint quantified in terms of reduction in washing solvent consumption by approximately up to 87% when cleaned in the hybrid mode compared to cleaning all the unit operations in the same mode (i.e. either batch or continuous mode of cleaning). Overall, the proposed integrative methodology supports informed decision-making that advances greener, cost-effective, and operationally efficient cleaning strategies at the flowsheet level.</div></div>","PeriodicalId":34618,"journal":{"name":"Cleaner Engineering and Technology","volume":"31 ","pages":"Article 101164"},"PeriodicalIF":6.5,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146191486","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}

{"title":"From theory to practice: a methodological roadmap for mapping, assessing, and implementing industrial symbiosis","authors":"Pawel Krzeminski ,&nbsp;Aleksandar Anastasovski ,&nbsp;Aleksandar Erceg ,&nbsp;Biljana Činčurak Erceg ,&nbsp;Carlos G. Dosoretz ,&nbsp;Massimo Borg ,&nbsp;Paul Refalo ,&nbsp;Radu Godina ,&nbsp;Angela Neves ,&nbsp;Vaida Jonaitienė ,&nbsp;Cansu Özcan Kılcan ,&nbsp;Alan H. Tkaczyk ,&nbsp;Aida Szilagyi ,&nbsp;Vasiliki Skoulou ,&nbsp;Yvonne Ryan ,&nbsp;Almudena Muñoz Puche","doi":"10.1016/j.clet.2026.101159","DOIUrl":"10.1016/j.clet.2026.101159","url":null,"abstract":"<div><div>Industrial symbiosis (IS) is a collaborative approach where industries share and reallocate resources, such as materials, energy, water, and by-products, create mutual benefits and contribute to a circular economy. This concept is limited due to the complexity of implementation and challenges with understanding the roadmap for their establishment. This study aims to bridge the gap between theory and practice by developing a comprehensive, methodologically grounded roadmap for implementing industrial symbiosis. The research combines a review of existing literature with the analysis of real-world case studies to identify and systematize the essential phases, tools, and success factors involved in the industrial symbiosis implementation process.</div><div>A detailed roadmap comprised key phases: mapping the current situation, identifying potential synergies, assessing feasibility, selecting the most appropriate opportunities, and implementing initiatives. The paper analyzes the relevant methods, tools and criteria for each phase. Particular attention is paid to key success factors, including resource and technology compatibility, geographical aspects, environmental impact, economic viability, and regulatory compliance. The importance of collaboration between different stakeholders and the role of intermediaries in the industrial symbiosis implementation process are highlighted. Based on the realized industrial symbiosis case studies, a few recommendations are given to support adopting industrial symbiosis strategies. The proposed roadmap emphasizes the importance of detailed resource flow mapping, multi-criteria assessment, and stakeholder collaboration with key success factors laying in evaluating technical, economic, environmental, and regulatory dimensions using appropriate tools.</div><div>Based on the research findings, the proposed roadmap consolidates fragmented approaches, supports strategic planning and provides practical guidance for companies and practitioners looking to integrate industrial symbiosis into their business. It contributes to a better understanding of the complexity of industrial symbiosis implementation and provides a framework for the wider adoption of these practices in the industry. This research contributes to the operationalization of industrial symbiosis by offering a replicable and adaptable roadmap. Further research should explore digital tools for synergy identification and assess policy mechanisms that can incentivize industrial symbiosis implementation at regional and national levels.</div></div>","PeriodicalId":34618,"journal":{"name":"Cleaner Engineering and Technology","volume":"31 ","pages":"Article 101159"},"PeriodicalIF":6.5,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146191489","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}

{"title":"Review of industrial bioethanol production with a focus on volatile fermentation byproducts","authors":"Mahyar Mahdavi ,&nbsp;Aida Rashidi ,&nbsp;Bruce Dvorak ,&nbsp;Ashraf Aly Hassan","doi":"10.1016/j.clet.2026.101200","DOIUrl":"10.1016/j.clet.2026.101200","url":null,"abstract":"<div><div>The recent surge in biofuel production, particularly bioethanol production, marks a major stride toward renewable and sustainable fuel solutions. Bioethanol, derived from biomass, is mainly produced from starch- or sugar-rich crops, such as corn, wheat, and sugarcane, particularly in the United States and Brazil. However, the industrial production of bioethanol poses environmental challenges, notably the emission of volatile organic compounds (VOCs) from manufacturing facilities. This review explores VOC emissions associated with fermentation for ethanol production, with the aim of elucidating the formation mechanisms, prevention, monitoring, and treatment of volatile fermentation byproducts. Regulatory mandates require ethanol plants to mitigate the annual mass of hazardous air pollutant (HAP) emissions, which are traditionally managed using carbon dioxide scrubbers and regenerative thermal oxidizers. However, these conventional techniques require substantial amounts of water and natural gas. This review analyzes conventional and novel VOC removal methods in ethanol plants, offering comprehensive insights into this process. Additionally, the paper evaluates various Nebraska ethanol plants, comparing VOC and HAP emissions between large and small facilities, both with and without continuous emissions monitoring systems (CEMS). Results indicate smaller facilities employing CEMS are able to operate their air emissions systems more efficiently.</div></div>","PeriodicalId":34618,"journal":{"name":"Cleaner Engineering and Technology","volume":"31 ","pages":"Article 101200"},"PeriodicalIF":6.5,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147612628","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}

{"title":"Metaheuristic-optimized machine learning models for predicting compressive strength and assessing sustainability of waste glass powder additive mortars","authors":"Izzeddin Donmez ,&nbsp;Kadir Gucluer","doi":"10.1016/j.clet.2026.101156","DOIUrl":"10.1016/j.clet.2026.101156","url":null,"abstract":"<div><div>The importance of waste management, waste recycling and ecological efficiency is felt more deeply every day. In this process where technological advances are developing rapidly, good studies can be carried out with the perspective of multidisciplinary approaches. For this purpose, in this study, it is aimed to evaluate and develop machine learning models optimized with meta-heuristic algorithms for the prediction of compressive strengths of mortars containing waste glass powder (WGP) with high accuracy in terms of sustainability. In this direction, Light Gradient Boosting Machine (LightGBM), Categorical Boosting (CB), Extremely Randomized Trees (ERT) and Random Forest (RF) algorithms were applied using a data set of 281 test result data compiled from 17 different scientific studies; the hyperparameters of these models were optimized with Particle Swarm Optimization (PSO) and Dwarf Mongoose Optimization (DMO) methods. At the same time, the most decisive variables within the mixture parameters were determined according to the SHAP-based variable importance analysis method. The experimental validation study, conducted to assess the real-world applicability and generalization capability of the optimized PSO-RF model, yielded an R² value of 0.841 based on comparisons performed on 60 test samples. In addition, the model was supported with sustainability analyses in terms of embodied energy (MJ/kg) and carbon emission (kg CO₂/kg); the ecological efficiency potential of waste glass powder usage was revealed. According to the obtained data, it was determined that the developed model has high prediction not only in theoretical data sets but also in the application field.</div></div>","PeriodicalId":34618,"journal":{"name":"Cleaner Engineering and Technology","volume":"31 ","pages":"Article 101156"},"PeriodicalIF":6.5,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146191373","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}

{"title":"Highly efficient photocatalytic conversion of CO2 to hydrocarbons using visible-active co-doped TiO2/ PDMS nanocomposite","authors":"Majed Bahadorian ,&nbsp;Farzaneh Arabpour Roghabadi ,&nbsp;Vahid Ahmadi ,&nbsp;Afsanehsadat Larimi","doi":"10.1016/j.clet.2026.101147","DOIUrl":"10.1016/j.clet.2026.101147","url":null,"abstract":"<div><div>Considering the rising emission of the carbon dioxide (CO₂) and its detrimental effects on the environment, conversion of CO₂ into value-added products has emerged as a critical area of research. In particular, the photocatalytic reduction of CO₂ into fuels using solar energy has recently attracted significant attention. In this study, a nanocomposite of co-doped titanium dioxide (TiO₂) nanoparticles with polydimethylsiloxane (PDMS) is utilized for photocatalytic reduction of CO₂. Photo, chemical, and thermal-stable PDMS serves as a transparent flexible binder for photocatalyst nanoparticles, facilitating their usage and recycling. To make TiO₂ photocatalysts visible-active, reduce the charge recombination rate, and improve the charge transport and lifetime, they are co-doped using nonmetal nitrogen (N) and metal silver (Ag) with different concentrations. Following the optical, morphological, and structural analysis of the photocatalysts, their photocatalytic performance is evaluated in a fixed gas bed photoreactor. The TiO₂ photocatalyst shows the lowest yield for methane (3.2 μmol/g catalyst) and ethane (0.42 μmol/g catalyst). While, the yield for methane and ethane using Ag-N-TiO₂ photocatalyst reaches 34.42 and 1.01 μmol/g catalyst, respectively. Remarkably, when the PDMS-Ag-N-TiO₂ nanocomposite is employed, the highest methane and ethane yield of 122.21 and 10.22 μmol/g catalyst are achieved, respectively. Thus, in the presence of PDMS polymer, instantaneous quadrupolar interactions occur between its siloxane groups and carbon dioxide molecules. This promotes the adsorption of greater amounts of CO₂, making it more available for the photocatalytic reduction reaction and thereby enhancing hydrocarbon production.</div></div>","PeriodicalId":34618,"journal":{"name":"Cleaner Engineering and Technology","volume":"31 ","pages":"Article 101147"},"PeriodicalIF":6.5,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146191372","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}

{"title":"Sustainably developing lithium resources from low-temperature sedimentary-basin brines","authors":"Xiaolong Peng,&nbsp;Chunqing Jiang,&nbsp;Wanju Yuan,&nbsp;Zhuoheng Chen","doi":"10.1016/j.clet.2026.101189","DOIUrl":"10.1016/j.clet.2026.101189","url":null,"abstract":"<div><div>Global electrification is accelerating research and development of using direct lithium extraction (DLE) technologies to unlock sedimentary-basin (SB) lithium (Li) brine resources. However, the techno-economic and environmental viability of these moderate-to-low grade ([Li] &lt;150 mg/L) and low-temperature (T_FM &lt;150 °C) brines remains poorly quantified. Here, we develop an integrated techno-economic–environmental framework that combines Monte Carlo simulations with coupled wellbore heat-loss, emission, and economic models to assess SB Li-brine development. We quantify the trade-offs between economic viability (in terms of Return on Sales) and environmental sustainability (in terms of carbon intensity, CI) for standalone DLE and three integrated pathways: geothermal heat recovery (GHR), geothermal power generation (GPG), and CO₂ capture (CC). Using Alberta's Devonian brines as a case study, we find that although most standalone DLE scenarios are economically viable, only 37.4% can achieve CI below the representative hard rock benchmark (∼15 kg CO_2e/kg LCE). GHR integration appears to be the most effective sustainable strategy as it can enable net-negative emissions and deliver 0.85-10.90 PJ/year of surplus heat. Implementation, however, still depends on local infrastructure and energy market conditions. Finally, we establish a game-theory-informed strategy matrix in [Li]-T_FM space to guide resource prioritization and sustainable strategy selection. This framework provides a transferable basis for optimizing sustainable lithium recovery from similar low-temperature SB brines worldwide.</div></div>","PeriodicalId":34618,"journal":{"name":"Cleaner Engineering and Technology","volume":"31 ","pages":"Article 101189"},"PeriodicalIF":6.5,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147612627","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}

{"title":"Electrification of clay calcination for cement decarbonization: Model development and process study","authors":"Roohangiz Shivaee Gariz ,&nbsp;Hao Wu ,&nbsp;Carsten Bang Mikkelsen ,&nbsp;Jens Abildskov ,&nbsp;Peter Arendt Jensen","doi":"10.1016/j.clet.2026.101197","DOIUrl":"10.1016/j.clet.2026.101197","url":null,"abstract":"<div><div>Reducing CO₂ emissions from cement production is essential for climate change mitigation. Electrically heated clay calcination is a novel process that enables the use of renewable electricity to produce calcined clay as a supplementary cementitious material (SCM), offering a practical route to lower clinker use and reducing the carbon footprint of cement. However, the performance of this process has not yet been thoroughly evaluated. In this study, a steady-state Aspen Plus process model of electrically heated clay calcination was developed to evaluate how changes in process layout, operating conditions, and clay feed properties affect process performance, quantified as energy demand, local temperatures, and clay calcination degree. Electrification allows heat recovery by recirculation of a portion of the process gas. At pilot scale with kaolinite-rich clay and targeting a calcination degree of 95%, gas recirculation reduced specific energy demand from 2238 to 1631 kJ/kg of calcined clay and lowered the required hot-gas supply temperature from 1010 to 917 °C. The preheating configuration with two cyclones showed the lowest energy demand. Higher feed rate decreased specific energy demand but increased the required hot-gas supply temperature; a higher gas-to-solid ratio had the opposite effect. Clay characteristics such as clay composition, kinetic model, and clay type were varied to understand their impact on process performance. The model was further applied to a full-scale process to assess scale effects, demonstrating reduced specific energy demand at the industrial scale.</div></div>","PeriodicalId":34618,"journal":{"name":"Cleaner Engineering and Technology","volume":"31 ","pages":"Article 101197"},"PeriodicalIF":6.5,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147612615","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}

{"title":"A hybrid data–physics fusion approach for energy-efficient and comfort-oriented real-time HVAC optimisation with dynamic occupant perception","authors":"Bo Li ,&nbsp;Jonathan Chung Ee Yong ,&nbsp;Lih Jiun Yu ,&nbsp;Jin Yuan Chan ,&nbsp;Ezutah Udoncy Olugu ,&nbsp;Mohammed W. Muhieldeen","doi":"10.1016/j.clet.2026.101181","DOIUrl":"10.1016/j.clet.2026.101181","url":null,"abstract":"<div><div>This study presents a data-driven framework for energy-efficient and thermal comfort-oriented HVAC control, advancing beyond traditional systems constrained by static occupancy assumptions. A hybrid dual-channel predictive architecture is proposed, integrating real-time occupant dynamics through a synergy of physics-based and data-driven models. The framework employs an energy baseline developed in EnergyPlus and a Predicted Mean Vote (PMV) baseline derived from the Fanger equation, enhanced by behaviour-driven incremental modules that form a dual-increment modelling structure for both energy and comfort prediction. Occupant behaviour is captured using a millimetre-wave (mmWave) radar perception system, enabling adaptive and interpretable modelling of human–environment interactions. The integrated predictive model acts as an objective function evaluator within a Multi-Objective Particle Swarm Optimisation (MOPSO) engine, leveraging pre-trained surrogate models to generate Pareto-optimal control strategies in real time. Experimental validation shows a 76% improvement in prediction accuracy compared to static models, alongside an 8.7% reduction in energy consumption and a 56.2% enhancement in thermal comfort relative to conventional control approaches. The proposed method demonstrates strong potential for sustainable HVAC operation in commercial and institutional buildings, promoting energy conservation and reducing carbon emissions.</div></div>","PeriodicalId":34618,"journal":{"name":"Cleaner Engineering and Technology","volume":"31 ","pages":"Article 101181"},"PeriodicalIF":6.5,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147612626","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}

{"title":"Corrigendum to “Characterization of Tharsis mine tailings for ore reprocessing for potential critical materials recovery” [Clean. Eng. Technol. 30 (2026) 101133]","authors":"Gladys A. Ochoa ,&nbsp;Pura Alfonso ,&nbsp;Percy Escalante ,&nbsp;Moacir Medeiros ,&nbsp;Carlos Hoffmann Sampaio ,&nbsp;Josep Oliva ,&nbsp;Jose Luis Cortina ,&nbsp;Ana Belén Hernández ,&nbsp;Manuel Sevilla","doi":"10.1016/j.clet.2026.101175","DOIUrl":"10.1016/j.clet.2026.101175","url":null,"abstract":"","PeriodicalId":34618,"journal":{"name":"Cleaner Engineering and Technology","volume":"31 ","pages":"Article 101175"},"PeriodicalIF":6.5,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147656807","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}