Waste Management Bulletin最新文献

{"title":"The Green Pulse of Hospitality: Assessing Green Supply Chain Practices on Organisational Performance in the Sri Lankan Hotel Industry","authors":"R.M.H.N. Bandara,&nbsp;R.A.D.T. Ranathunga Arachchi,&nbsp;L.D.C. Gunasekara,&nbsp;N.A.T. De Zoysa,&nbsp;Anuja A. Lokeshwara,&nbsp;Chapa S.R.B. Refaie","doi":"10.1016/j.wmb.2025.100279","DOIUrl":"10.1016/j.wmb.2025.100279","url":null,"abstract":"<div><div>In the modern competitive business environment, sustainability has become the key theme in organisational performance (OP), compelling organisations to adopt environmentally friendly operations in the business world. The hotel industry is a significant contributor to national economies, and it is steadily incorporating green practices to improve operational efficiency and reduce environmental impact. Though green supply chain management (GSCM) has been a subject of significant interest in manufacturing and logistic settings, GSCM in the hospitality industry, particularly in developing nations such as Sri Lanka, is still a largely unexplored area. To bridge this gap, the current study investigates the relationship between GSCM practices and OP with a particular focus on the moderating effects of hotel star classification. A cross-sectional, deductive research design was used, and Partial Least Squares Structural Equation Modelling (PLS-SEM) was the method of analysis. A web-based survey of 167 star-class hotels in Sri Lanka gained a high response rate of 88.44%. GSCM practices were represented as a second-order construct with five dimensions: eco design, green purchasing, internal environment management, investment recovery, and reverse logistics. The findings reveal that GSCM practices have a significant positive impact on OP. However, the star ratings of the hotels had no significant effect on this relationship, meaning the positive impact of GSCM practices are consistent across the industry. This finding indicates the need to investigate additional moderating variables such as ownership patterns and environmental certifications. Future comparative studies in various Asian nations with different cultural, legislative, and market settings may advance our understanding of GSCM practices<!--> <!-->in<!--> <!-->hospitality industry.</div></div>","PeriodicalId":101276,"journal":{"name":"Waste Management Bulletin","volume":"4 1","pages":"Article 100279"},"PeriodicalIF":0.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145977782","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":"Modelling consumer intent for purchase recycled products: a pathway to future sustainability","authors":"Jisha J. ,&nbsp;K. Martina Rani ,&nbsp;Aldrin Joseph ,&nbsp;Himakumari V. ,&nbsp;Smrithi K.S. ,&nbsp;B. Giri Babu","doi":"10.1016/j.wmb.2026.100280","DOIUrl":"10.1016/j.wmb.2026.100280","url":null,"abstract":"<div><div>Despite increasing global concern for environmental sustainability, the adoption of recycled products remains limited, particularly in developing economies where consumer skepticism and entrenched purchasing habits persist. This study examines the key determinants influencing consumers’ intentions to purchase recycled products in alignment with Sustainable Development Goal 12 (Responsible Consumption and Production). Specifically, it analyzes the effects of environmental attitude, trust, perceived credibility, and perceived product quality on purchasing decisions. A structured questionnaire survey was administered to 315 urban consumers in India using purposive sampling. The findings reveal that environmental attitude is the most influential predictor of recycled product purchase intention, indicating that environmentally conscious consumers are more likely to engage in sustainable consumption. Trust and perceived credibility also significantly affect purchasing behavior, emphasizing the importance of authenticity and reputation in fostering acceptance of recycled products. Although perceived product quality has a comparatively weaker influence, it remains relevant in meeting expectations related to usability and design. The study contributes theoretically by integrating psychological, perceptual, and normative factors into an SDG 12–oriented behavioral framework. Practically, it provides insights for marketers and policymakers to enhance communication strategies, build consumer trust, and promote circular economy practices.</div></div>","PeriodicalId":101276,"journal":{"name":"Waste Management Bulletin","volume":"4 1","pages":"Article 100280"},"PeriodicalIF":0.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146037082","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":"The evolving landscape of AI-driven risk management in the biogas production: A systematic and bibliometric review","authors":"Mohamed Abourida ,&nbsp;Michael Short ,&nbsp;Oleksiy V. Klymenko ,&nbsp;Noor M. Khamis ,&nbsp;Charf Mahammedi ,&nbsp;M.K.S. Al-Mhdawi ,&nbsp;Abdel-Hamed Sakr","doi":"10.1016/j.wmb.2025.100271","DOIUrl":"10.1016/j.wmb.2025.100271","url":null,"abstract":"<div><div>This review presents the first combined systematic and bibliometric review synthesising artificial intelligence (AI)-driven approaches to risk management in biogas production within wastewater treatment plants (WWTPs), with emphasis on decision-optimisation and operational safety. Seven academic databases: Scopus, Web of Science, IEEE Xplore, ScienceDirect, SpringerLink, Taylor &amp; Francis, and Google Scholar were systematically searched from 2015 to March 2025, and screening followed PRISMA 2020 guidelines. Of 3,716 retrieved records, 109 studies met the inclusion criteria. Bibliometric mapping (VOSviewer) and qualitative synthesis identified five thematic clusters: (i) biogas process safety, (ii) IoT integration and renewable-energy, (iii) optimisation and supply-chain resilience, (iv) AI-driven decision-support frameworks, and (v) advanced machine-learning techniques. The analysis reveals a marked increase in publications since 2020, reflecting a shift from conceptual modelling toward applied digital risk solutions. Europe and China remain leading contributors, although collaboration networks are fragmented and methodological heterogeneity persists. Full-scale validation of AI models in operational WWTP-based biogas plants remains limited, with most studies relying on laboratory experiments, simulations, or pilot-scale data. Constraints include publication bias, database coverage, English-language restrictions, inconsistent performance metrics, and limited access to long-term Supervisory Control and Data Acquisition (SCADA) Systems datasets. The review demonstrates that AI-driven methods have significant potential to improve safety, operational efficiency, and regulatory assurance in biogas facilities. However, achieving practical and scalable implementation will require rigorous multi-site validation, standardised evaluation indicators, integration of explainable AI, and alignment with plant-level risk-governance frameworks.</div></div>","PeriodicalId":101276,"journal":{"name":"Waste Management Bulletin","volume":"4 1","pages":"Article 100271"},"PeriodicalIF":0.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145884129","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":"Study of the phase composition (Zn, ZnO) of anodes recovered from spent alkaline batteries, with respect to their residual voltage","authors":"Juan Carlos Rodriguez Lopez ,&nbsp;Enrique Vigueras Santiago ,&nbsp;N. García-González ,&nbsp;V.H. Castrejón-Sánchez ,&nbsp;Marco Camacho-López ,&nbsp;Susana Hernández López","doi":"10.1016/j.wmb.2026.100281","DOIUrl":"10.1016/j.wmb.2026.100281","url":null,"abstract":"<div><div>The development of advanced materials with tailored properties has long been a cornerstone of technological innovation. Increasingly, attention is shifting toward the transformation of end-of-life waste into valuable resources. Spent alkaline batteries, when improperly disposed of as electronic waste (e-waste), pose significant environmental hazards due to their content of toxic metals, which can leach into soil and groundwater. These metals may also undergo physicochemical transformations through interactions with other waste materials. This study investigates the anode recovered from spent alkaline batteries discharged to varying residual voltages. The recovery process involved manual separation, followed by washing with deionized water, filtration, and drying at 50 °C for 48 h prior to characterization. The resulting particles exhibited photoluminescent properties that correlated with the residual voltage of the batteries. Structural analysis revealed the coexistence of Zinc and Zinc Oxide (Zn/ZnO) phases at voltages above 0.78 V, while only ZnO was present below this threshold. The ZnO content was found to depend on the degree of battery depletion, with the residual voltage directly influencing the Zn/ZnO phase ratio.</div></div>","PeriodicalId":101276,"journal":{"name":"Waste Management Bulletin","volume":"4 1","pages":"Article 100281"},"PeriodicalIF":0.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146090233","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":"Detecting volume changes in municipal solid waste landfill using airborne laser scanning","authors":"O. Brovkina ,&nbsp;M. Pikl ,&nbsp;F. Zemek ,&nbsp;J. Michálek","doi":"10.1016/j.wmb.2025.100272","DOIUrl":"10.1016/j.wmb.2025.100272","url":null,"abstract":"<div><div>Accurate and operative monitoring of municipal solid waste (MSW) landfills is critical for operational safety, spatial planning, and regulatory compliance. Traditional point-based surveying methods are precise, but they are limited in spatial density coverage and hence, efficiency. The objective of the study is to evaluate the application of airborne laser scanning (ALS) for detecting volume changes at operational MSW landfill in the Czech Republic. Specifically, the study determines optimal spatial resolution of digital terrain model (DTM) from ALS for estimation of landfill volume, estimates uncertainties related to slope steepness and different vegetation cover affecting the accuracy of ALS-derived DTM, and formalizes and applies the method for detecting landfill volume changes using ALS. Two ALS datasets (10 points/m²) were collected in a five-month interval and processed at multiple spatial resolutions (0.3 m to 1.5 m). GPS reference points were measured for ALS data co-registration and to assess the accuracy of ALS-derived elevations. Positional errors and their propagation into elevation errors were quantified, and vegetation-induced uncertainties were considered. Results indicate that DTM resolutions of 0.3–0.8 m provide the most reliable estimates of volume change, especially in heterogeneous areas such as vegetated slopes. Differences in the standard deviation (SD) of elevation changes for selected areas at the landfill between the DTM resolution of 0.3 m and coarser resolutions were minimal for stable surfaces such as roads and compacted waste (0.01–0.02 m), but higher for vegetated areas, where the SD increased by up to 0.10 m due to surface roughness and variable laser penetration through the canopy. Comparison with independent GPS reference points showed that finer DTMs (0.3 and 0.5 m) reduced both bias and variability (mean differences ≤ 0.23 m, SD ≤ 0.24 m), whereas coarser DTMs (0.8 and 1.5 m) increased systematic errors due to surface smoothing and vegetation-induced misclassification. The findings recommend acquiring ALS data in early spring or late autumn, when vegetation cover is minimal and the influence of canopy on DTM accuracy is reduced. The study presents a novel workflow integrating ALS data with error modeling to improve landfill monitoring protocols. While the workflow was demonstrated on a specific site, it has potential for adaptation and application in other MSW landfills.</div></div>","PeriodicalId":101276,"journal":{"name":"Waste Management Bulletin","volume":"4 1","pages":"Article 100272"},"PeriodicalIF":0.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145694292","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":"Regionalized composition analysis of Norwegian residual waste and its implications for recycling, emission accounting, and food waste avoidance","authors":"Kim Rainer Mattson,&nbsp;Johan Berg Pettersen","doi":"10.1016/j.wmb.2026.100283","DOIUrl":"10.1016/j.wmb.2026.100283","url":null,"abstract":"<div><div>Residual waste generation within municipal solid waste is characterized as a mix of various waste fractions that are either correctly or incorrectly discarded in residual bins. We denote this as residuals and assess its average and regional composition in Norway, based on the collection of 90 waste composition analysis. There is substantial variability between generation origins, and a clear pattern of lower food waste sorting in urban areas. Greenhouse gas emission of treating the various compositions with waste incineration were assessed, showing that CO₂-equivalent emissions vary by up to 13% depending on waste origins, and estimate that approximately 54%, 55%, and 64% of rural, suburban, and urban residuals could potentially be recyclable, with a significant potential for reducing avoidable food waste. Successful implementation of the national “food waste avoidance” strategy could see the avoided generation and consequently production of 110kt of food for Norwegian households. Suggested improvements focus on convenient and clear sorting practices, better resolution on non-household residual compositions, and more multidisciplinary and regionalized research approaches.</div></div>","PeriodicalId":101276,"journal":{"name":"Waste Management Bulletin","volume":"4 1","pages":"Article 100283"},"PeriodicalIF":0.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146090232","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":"Valorisation of organic wastes through black soldier fly (Hermetia illucens) Larvae: Impacts on Growth, nutritional Composition, and bioconversion efficiency","authors":"Pawan Chapagaee ,&nbsp;Sandesh Thapa ,&nbsp;Sushil Shrestha ,&nbsp;Bigyan Puri ,&nbsp;Anup Ghimire ,&nbsp;Dipak Raj Bist ,&nbsp;Lokendra Khatri ,&nbsp;Adhiraj Kunwar","doi":"10.1016/j.wmb.2025.100278","DOIUrl":"10.1016/j.wmb.2025.100278","url":null,"abstract":"<div><div>Organic waste accumulation poses a significant environmental challenge, necessitating effective waste management strategies. The black soldier fly serves as a beneficial insect, aiding in waste reduction and animal feed production, while its frass contributes to sustainable soil improvement. Therefore, this study is aimed to investigate the bioconversion efficiency, growth performance, longevity, waste reduction, and nutritional composition of <em>Hermetia illucens</em> (Black soldier fly; BSF) larvae reared on five different urban organic wastes: restaurant waste, vegetable waste, fruit waste, kitchen waste, and butchery chicken waste following completely randomized design (CRD) with five urban waste treatment and four replications. The results revealed the highest larval growth rate and bioconversion found on restaurant waste 12.02 ± 0.47 mg/day and 6.97 ± 0.15 % respectively. Larva reared on butchery chicken waste showed highest larval mortality (76.02 ± 0.42 %) and life cycle duration (57 days). Also, the highest decomposition rate of waste was found on kitchen waste (0.73 ± 0.02) and fruit waste (0.72 ± 0.009). The highest waste reduction rate was found on kitchen waste (73.66 ± 2.70 %) and restaurant waste (62 ± 0.94 %). Larvae reared on restaurant waste exhibited highest crude protein content (37 ± 0.44 %DM), whereas highest crude fat was found on larva reared on butchery chicken waste (47.4 ± 0.64 %DM). The study highlights how BSF can efficiently decrease waste quantities and transform nutrient-balanced urban organic wastes into high-value biomass. The most promising substrates for large-scale BSF rearing and circular bio economy applications in developing nations like Nepal were found to be kitchen and restaurant wastes.</div></div>","PeriodicalId":101276,"journal":{"name":"Waste Management Bulletin","volume":"4 1","pages":"Article 100278"},"PeriodicalIF":0.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145884249","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":"An analytical framework for medical waste forecasting using machine learning: Paving the path toward zero waste in healthcare","authors":"S M Shahinur Rahman,&nbsp;Md Ruhul Amin,&nbsp;A M Almas Shahriyar Azad,&nbsp;Md. Ariful Haque,&nbsp;Md. Limonur Rahman Lingkon","doi":"10.1016/j.wmb.2025.100270","DOIUrl":"10.1016/j.wmb.2025.100270","url":null,"abstract":"<div><div>This study presents a robust framework for accurately forecasting medical waste (MW) generation in healthcare settings, addressing escalating environmental and public health concerns. Using machine learning (ML) models, including Linear Regression (LR), Support Vector Regression (SVR), Long Short-Term Memory (LSTM), and Random Forest (RF), the research integrates critical patient-related variables, such as indoor and outdoor patient counts, surgeries, and deaths. Based on eight years of comprehensive data (2016–2023) from the medical colleges in Rajshahi, Bangladesh, the LR model showed the most reliable outcomes, achieving <span><math><msup><mrow><mi>R</mi></mrow><mn>2</mn></msup></math></span> values between 0.91 and 0.95 for all waste categories and outperforming others with mean absolute errors (<em>MAE</em>) as low as 1.39 kg for recyclable waste. Projections reveal a significant 50 % surge in general waste by 2030, reaching approximately 987.75 tons, while infectious waste will grow from 66.54 to 735.23 tons. Monte Carlo simulations quantified variability across waste categories, demonstrating fluctuations within <span><math><mrow><mo>±</mo><mn>5</mn><mo>%</mo></mrow></math></span> of mean values, ensuring robustness. Finally, the research represents a novel policy recommendation for zero waste generation at the study location, which advocates for category-specific MW management strategies, aligning with Sustainable Development Goals (SDGs) 3 (Good Health and Well-being), 12 (Responsible Consumption and Production), and 13 (Climate Action). This work introduces a novel precedent for incorporating artificial intelligence into healthcare operations to attain zero waste generation while tackling public health and environmental issues. Thus, this work offers an innovative methodology that integrates machine learning to link patient data with waste generation, providing practical insights for resource optimization and operational planning.</div></div>","PeriodicalId":101276,"journal":{"name":"Waste Management Bulletin","volume":"4 1","pages":"Article 100270"},"PeriodicalIF":0.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145694291","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":"Scoping mushroom cultivation in the Northern Territory: Applying a circular economy approach","authors":"Waseem Ahmed ,&nbsp;Yujuan Li ,&nbsp;Edward Mwando ,&nbsp;Kamaljit Sangha ,&nbsp;Tham Dong ,&nbsp;Cheng-Yuan Xu","doi":"10.1016/j.wmb.2025.100275","DOIUrl":"10.1016/j.wmb.2025.100275","url":null,"abstract":"","PeriodicalId":101276,"journal":{"name":"Waste Management Bulletin","volume":"4 1","pages":"Article 100275"},"PeriodicalIF":0.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145884128","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":"Tracking the plastic footprint: a bibliometric mapping of microplastics research in Asia (2015–2025)","authors":"Ronilo P. Antonio","doi":"10.1016/j.wmb.2025.100274","DOIUrl":"10.1016/j.wmb.2025.100274","url":null,"abstract":"<div><div>The growing crisis of microplastic pollution poses serious environmental and public health challenges, yet despite Asia’s central role in plastic leakage and research growth, its scholarly landscape over the past decade remains unmapped. This study addresses this gap by conducting a comprehensive bibliometric analysis of 3,797 Scopus-indexed articles published between 2015 and 2025, employing an integrated approach that combines performance analysis, co-citation analysis, and co-word analysis using VOSviewer software. The results reveal an exponential surge in research output since 2019, with China, India, and Indonesia emerging as key contributors. Citation analysis highlights seminal works on atmospheric transport, soil contamination, and human ingestion as influential drivers of the field. Co-citation mapping identifies four intellectual clusters, mainly foundational conceptual frameworks, environmental pathways, global plastics accounting, and ecological impacts. Meanwhile co-word analysis uncovers three thematic domains: pollution sources and detection, ecological and biological effects, and environmental fate and transport. Overlay visualization further demonstrates a temporal shift from early descriptive and methodological studies toward interdisciplinary, solution-oriented research integrating ecological risk assessment and human health concerns. By synthesizing a decade of scholarship, this study provides a critical evidence base for guiding future research priorities and informs risk assessment strategies, policy design, and global governance efforts aimed at mitigating the escalating microplastics crisis.</div></div>","PeriodicalId":101276,"journal":{"name":"Waste Management Bulletin","volume":"4 1","pages":"Article 100274"},"PeriodicalIF":0.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145884248","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}