Search Results (2,140)

Industrial food processing generates substantial byproducts, resulting in environmental challenges and economic losses. This study explores the biovalorization of sugar-rich barbecue sauce waste streams through fermentation to create value-added ingredients for sauce production and promote circular economy practices. The barbecue stream was diluted with water at 25 and 50% incorporation levels and fermented at room temperature for 12 days using a microbial consortium comprising three lactic acid bacteria (Lactiplantibacillus plantarum, Lacticaseibacillus rhamnosus, and Weisella confusa) and one yeast (Saccharomyces boulardii). Laboratory-scale fermentation was monitored by measuring pH, total soluble solids, titratable acidity, sugar consumption, and metabolite production. The consortium demonstrated effective performance, reducing pH and TSS and increasing titratable acidity for both incorporation levels over 12 days. The fermented samples were characterized by their antioxidant capacity, color, protein content, humidity, and viscosity. The total phenolic content and antioxidant activity (DPPH) increased significantly (p < 0.05), and the viscosity increased by 254.3% and 48.3% for the fermented streams with 25% and 50% incorporation, respectively. Antimicrobial assays revealed that the fermented samples inhibited typical spoilage bacteria and yeast. This work highlights the potential of fermentation to upcycle barbecue waste, with antimicrobial characteristics contributing to extended shelf life, sustainable food production, and circular economic practices. Full article

Urban coastal wetlands along the Peruvian Pacific coast are increasingly affected by urban expansion, pollution, and hydrological alterations, compromising their ecological integrity. In this context, the spatiotemporal variation of the aquatic macrophyte community and its relationship with limnological conditions and drivers of change were evaluated in the Santa Rosa wetland (Chancay, Lima). The objective is to evaluate the spatiotemporal variation of the aquatic macrophyte community in the Santa Rosa wetland and analyze its relationship with physicochemical limnological variables and drivers of change. Sampling was conducted during two contrasting hydrological seasons in 2022: T1 (low-water season) and T2 (high-water season), at six sampling points (P1–P6). Physicochemical variables (water depth, temperature, pH, conductivity, total dissolved solids—TDS, total suspended solids—TSS, dissolved oxygen—DO, turbidity, nitrate—NO₃⁻, ammonium—NH₄⁺, phosphate—PO₄³⁻, and dissolved organic matter—DOM) were measured, and the relative abundance of aquatic macrophytes was evaluated. Drivers of change were identified through direct observation and a structured matrix, with phosphate a PCoA performed to summarize spatiotemporal trends. Data were analyzed using Principal Component Analysis (PCA), Co-inertia analysis, and Multi-Response Permutation Procedures (MRPP). Significant spatiotemporal variation was observed in physicochemical parameters (p < 0.05), with moderate covariation between the two matrices (RV = 0.47). A total of ten aquatic macrophyte species were recorded, with higher abundance of Pontederia crassipes and Pistia stratiotes in T1, and Hydrocotyle ranunculoides and Bacopa monnieri in T2. The most relevant drivers of change were solid waste, livestock grazing, organic contamination, and urban expansion. Spatial heterogeneity was observed in the drivers of change affecting the Santa Rosa wetland, forming a mosaic of areas with different impact profiles. Despite multiple anthropogenic pressures, the Santa Rosa wetland maintains a limnological structure and a functionally coupled macrophyte community, suggesting that essential ecological processes are maintained within the temporal scope of this study. The observed covariation between physicochemical conditions and vegetation confirms the persistence of essential ecological processes, even within an altered urban context. This study demonstrates that integrating biotic components, limnological variables, and drivers of change is fundamental to understanding and monitoring the ecological dynamics of urban wetlands along the Peruvian coast. Full article

This research analyzed the role of Green Marketing (GM) and Artificial Intelligence (AI) in promoting Corporate Sustainability (CS) across the environmental, social, and economic dimensions within the industrial sector in the Palestinian territories. Given the limited empirical evidence from developing and resource-constrained contexts, an explanatory sequential mixed-methods design was employed. The quantitative phase involved a survey of 500 valid respondents, and the data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The quantitative findings were complemented by fifteen in-depth semi-structured interviews to further interpret and validate the survey results. The results indicate that GM showed the largest effect size and functions as a strategic approach for embedding sustainability values into organizational activities. AI also demonstrated a positive and supportive role by enhancing operational efficiency and monitoring capabilities within industrial processes. The interaction between AI and GM showed a statistically significant but relatively small effect, particularly in the social sustainability dimension, suggesting that AI may help reinforce the effectiveness of green marketing practices. The qualitative findings further illustrate how GM contributes to internal accountability, eco-design initiatives, stakeholder trust, and competitive positioning, while AI supports waste management, resource optimization, employee safety monitoring, forecasting accuracy, and sustainability reporting verification. Overall, the results suggest that GM and AI jointly contribute to improving corporate sustainability practices, with GM providing strategic direction and AI supporting operational implementation. This study contributes to the literature on sustainability, marketing, and digital transformation by providing empirical evidence on the interaction between green marketing and artificial intelligence in promoting corporate sustainability within a developing-country context. Full article

Waste separation in private households remains difficult to promote, particularly in urban contexts, where anonymity limits informal social monitoring. This proof-of-concept study tested, for the first time, self-administration of images of “watching eyes” as an intervention. About 22% of all households living in the district of Riedberg in Frankfurt/Main, Germany, received a letter asking residents to attach eye cues to kitchen and outdoor waste bins to prompt appropriate separation of organic from residual waste. Objective data from weighed collection trucks showed a measurable behavioral effect compared to control conditions, with a 5–8% increase in biowaste volumes. While this study does not allow causal inference because waste was measured only at the group level, it does suggest that, when applied by residents themselves, social nudges might enhance self-awareness about environmentally conscious behavior. Accompanying survey responses displayed ceiling effects, presumably because only highly motivated individuals participated. Importantly, some signs of reactance were also observed, with some participants perceiving the intervention as intrusive and regulatory. Although low-cost and easy to apply, self-administration of watching-eyes cues requires careful communication and attention to psychological reactions to avoid resistance while encouraging the formation and maintenance of target habits in private environments. Full article

Surgical wards constitute a significant contributor to global medical waste (MW), accounting for over one-third of total healthcare sector trash. Medical interventions produce hazardous, infectious, and potentially toxic byproducts, making effective MW management crucial, especially where current mechanisms are insufficient. Substantial disparities persist between high-income and low- and middle-income countries regarding MW infrastructure, enforcement, and adoption of safe, sustainable treatment technologies. Proper segregation, recycling, treatment, and disposal are key to protecting public health, environmental integrity, and promoting healthcare sustainability. Waste treatment technologies divide into thermal and physico-chemical processes, requiring thorough evaluation of advantages, disadvantages, and suitability for each waste type. This narrative review updates MW knowledge by synthesizing data from scientific literature, institutional documents, and regulatory sources. Key quantitative data indicate operating rooms generate up to 30% of total hospital waste, with recyclable materials representing over 40% of that volume. Improper segregation rates remain high, and incineration remains dominant despite sustainability concerns. The Romanian case study highlights progressive EU alignment, enforcing standardized MW classification, color-coded segregation, and specialized disposal protocols in surgical wards. Despite legal compliance, Romania is advancing incrementally, with systematic audits, digital tracking, and national outcome-based evaluations yet to be fully established. The Plastic Surgery Unit at Oradea County Emergency Clinical Hospital demonstrates good protocol adherence; however, strengthening data feedback mechanisms would enhance hospital-wide performance optimization and strategic waste reduction. Training and monitoring represent important areas for continued development. Coordinated professional engagement, modernized infrastructure, and enforceable audits are identified as critical priorities for improving MW handling in surgical environments. Future research should emphasize management innovation, evidence-based policy formulation, and a systematic strategy to achieve sustainable MW. Full article

Urban waste management remains a significant challenge for achieving environmental sustainability and advancing smart city infrastructures. This study proposes a multimodal vision–language framework that integrates real-time object detection with automated semantic interpretation and structured semantic analysis for intelligent urban waste monitoring. A custom dataset including 2247 manually annotated images was constructed from publicly available sources (TrashNet and TACO), enabling robust multi-class detection across six waste categories. Two state-of-the-art object detection models, YOLOv8m and YOLOv10m, were trained and evaluated using a fixed 70/15/15 train–validation–test split. Under this configuration, YOLOv8m achieved a mAP@50 of 90.5% and a mAP@50–95 of 87.1%, slightly outperforming YOLOv10m (89.5% and 86.0%, respectively). Moreover, YOLOv8m demonstrated superior inference efficiency, reaching 120 FPS compared to 105 FPS for YOLOv10m. To obtain a more reliable estimate of performance stability across data partitions, stratified 5-Fold Cross-Validation was conducted. YOLOv8m achieved an average Precision of 0.9324 and an average mAP@50–95 of 0.9315 ± 0.0575 across folds, suggesting generally stable performance across data partitions, while also revealing variability associated with dataset heterogeneity. Beyond object detection, the framework integrates MiniGPT-4 to generate context-aware textual descriptions of detected waste items, thereby enhancing semantic interpretability and user engagement. Furthermore, GPT-5 Vision is incorporated as a structured auxiliary semantic classification and category-suggestion module that analyzes object crops and multi-class scenes, producing constrained JSON-formatted outputs that include category labels, concise descriptions, and recyclability indicators. Overall, the proposed YOLOv8–MiniGPT-4–GPT-5 Vision pipeline shows that combining accurate real-time detection with multimodal semantic reasoning can improve interpretability and support interactive, semantically enriched waste analysis in smart-city and environmental monitoring scenarios. Full article

The DIGIT experiment was launched at the Tournemire Underground Research Laboratory (URL) with the aim of determining the effects of temperature on the transfer of tracers mimicking the most mobile radionuclides in the Toarcian clay rock. The properties of this rock are similar to those of the host rocks being considered for a future deep geological repository for high-level radioactive waste (HLW). The experiment involves the monitoring of the interaction between a test water doped with stable halides and deuterium at constant concentration, and the porewater of the Toarcian clay rock under constant ambient conditions, as well as at higher temperature induced by artificial heating. This experiment seeks to partially address questions regarding the potential spread of contaminants during the thermal phase of HL waste packages. Specifically, the in situ experiment aims to evaluate the role of scale effects, thermodiffusion, a process that combines Fick’s law, the Soret effect, and convection in the transfer of radionuclides. This paper is the second part of a companion paper dedicated to predictive calculations and the installation of the experimental device. It presents the main experimental and modeling results obtained since the beginning of the installation and after 20 months of heat at 70 °C. The test was carried out in five phases, finishing with a sampling campaign: a phase 0 called “initial conditions”, followed by a pure diffusion phase (5 months), then three phases in a heated period lasting 1 year and 8 months. In total, 47 rock cores were analyzed, with approximately 170 samples tested by four diffusion methods (radial, outgoing, through and in vapor-phase) to determine the tracer concentrations in the porewater, their water content and their diffusive transport parameters. The results show a decrease in tracer concentrations with distance from the test zone, in the directions parallel and perpendicular to the stratification. The anisotropy of the medium results in greater migration in the direction parallel to the stratification. Thermal properties also confirm anisotropy with a higher thermal conductivity in the direction parallel to the stratification. Finally, an activation energy of 22.9 ± 1.7 kJ·mol⁻¹ could be proposed by NMR for deuterium, indicating diffusion behavior following an Arrhenius law between 30 and 70 °C. The experimental data allowed for the calibration of a 2D axisymmetric numerical model using the commercial finite element software COMSOL Multiphysics^®. The Fick’s law corrected by an Arrhenius law best reproduces the penetration of deuterium and anions. The Soret effect, integrated into certain scenarios, is only significant for anions’ migration, using a fitted Soret coefficient of 0.1 K⁻¹, as proposed in the literature for the Callovo-Oxfordian, the host rock of the Cigéo project in the east of France. The calibration of the simulated data with the experimental data allowed for the characterization of damaged and/or disturbed zones evolving over time. Simulations over 150 years, the duration of the thermal maximum for HLW packages, show that advection—modeled by Darcy’s law—would have a negligible role in this context due to the low permeability of the upper Toarcian. In conclusion, the DIGIT test showed that, for the Upper Toarcian clay rocks at the Tournemire URL in France, diffusion, corrected for the effect of temperature, is the mechanism that characterizes the transport of radionuclide analogues. The study showed that thermodiffusion has a limited influence on deuterium migration but remains significant for anions in the case of a coupling between temperature correction and thermodiffusion. The test also highlighted the impact of temperature on the spatiotemporal development of a damaged and/or disturbed zone. These new and relevant results in the field will need to be confirmed later through additional experiments. Full article

This study focuses on an integrated conceptual framework for smart municipal waste management that combines Pay-as-you-throw (PAYT) with digital technologies emerging from the Internet of Things (IoT), Artificial Intelligence, and blockchain. In the literature, a key limitation has long been recognised: the fragmented implementation of technological solutions and economic instruments in waste management systems. This model is proposed as a multi-layer architecture that integrates user identification, real-time data collection, predictive optimisation, and automated tariff calculation. The framework is expected to reduce mixed-waste volumes and improve operational efficiency while ensuring traceability and transparency in waste management. The framework also provides a practical basis for implementing circular economy principles and advancing climate and urban sustainability goals by linking user behaviour to cost allocation and data-driven monitoring. The findings highlight that measurable environmental benefits depend on the structural integration of behavioural incentives, real-time monitoring, and transparent data governance. The framework demonstrates how PAYT-based incentives, combined with digital monitoring, can reduce mixed waste volumes and associated emissions. Full article

This study investigates the effects of three solid waste powders—fly ash (FA), silica fume (SF), and phosphogypsum (P)—on the drying shrinkage behavior of metakaolin-based geopolymers. To systematically evaluate the performance and underlying mechanisms, a comprehensive experimental program was conducted, including compressive strength and elastic modulus testing, early-age and variable-humidity drying shrinkage monitoring, mercury intrusion porosimetry, and microcalorimetry analysis. Results demonstrate that all three materials effectively reduce drying shrinkage through distinct mechanisms. The incorporation of 30% FA optimized the capillary pore network and densified the matrix, achieving a peak compressive strength of 53.51 MPa and an elastic modulus of 9.23 GPa. SF exhibited a dose-dependent effect; at an optimal content of 7%, it enhanced compressive strength by 28.3% through its nucleation effect and micro-aggregate filling. However, excessive SF (9%) led to pore coarsening and increased shrinkage. Although P incorporation slightly reduced mechanical strength, it decreased cumulative porosity by up to 8% and formed needle-like Wairakite-Ca crystals that provided micro-structural support, resulting in a net shrinkage reduction of up to 137.83 µε. This study provides a scientific basis for designing low-shrinkage, low-carbon geopolymers by tailoring solid waste incorporation to engineer multiscale pore structures. Full article

Coal-fired power plants can adversely affect aquatic ecosystems through wastewater discharge, waste landfills, and the atmospheric deposition of toxic substances released during coal combustion. These processes degrade the water quality of nearby surface and underground water bodies. The study presents the impact of the coal-fired power plant Contour Global Maritza East 3 on the ecological status of the Sokolitsa River, reflected by changes in the composition and structure of the sensitive phytobenthos and macrozoobenthos communities and supporting environmental variables, including water temperature, pH, dissolved oxygen, conductivity, nutrients, sulfates, calcium, and calcium carbonate hardness. Methods for monitoring and assessing the ecological status of surface water bodies compliant with European and national legislation were applied to the studied biological quality elements and key physicochemical variables. Historical monitoring data from a ten-year period, 2013–2022, together with data collected during the study in 2023 and 2024 were analyzed and evaluated. The results indicated a significant increase in most physicochemical variables downstream of the CFPP compared with the upstream site, including water temperature, conductivity, calcium carbonate hardness, calcium, sulfates and nitrogen (N) nutrients (ammonium N, nitrite N, nitrate N, total N). The ecological status of the river deteriorated, as indicated by the negatively affected aquatic habitats and the changes in the taxonomic richness and abundance of the studied organism groups. Full article

Distributed recycling of high-density polyethylene (HDPE) into filament for use in material extrusion 3D printing has been proposed as part of a circular economy. There is a gap in the understanding of the potential for HDPE to release contaminants that are potentially hazardous to human health during reuse. Herein, HDPE from post-consumer packaging waste was sorted into food and non-food (NF) streams and virgin HDPE was taken as a benchmark material. All materials were extruded into filaments and recycled multiple times while monitoring emissions. In general, particle and organic chemical emissions decreased by 93 to 99% and 73 to 99%, respectively, with increased reprocessing cycle without appreciable decline in mechanical (Young’s modulus decreased by 5 to 16%), processability (melt flow index stable from 0.2 to 0.7 g/10 min for waste plastics), and thermal properties (crystallinity ranged from a 6% decrease to a 9% increase) of plastics. An exception was a sub-stream of NF plastic that had increased particle emissions (up to 3100%) with reprocessing cycle. Reductions in emissions during filament extrusion appeared to be more influenced by reprocessing cycle than by any specific process step (grinding, etc.). The progressive decline in emissions without appreciable loss of polymer integrity could be exploited to pre-condition HDPE to reduce potential hazardous emissions prior to extruding into filament. This work helps fill the knowledge gap on approaches to recycling plastics in distributed settings such as home-based businesses, which is critical for developing effective recommendations for controls to enable safe work practices such as the use of ventilation to minimize exposures. Full article

Pharmaceutical residues in aquatic environments represent a significant pollution concern, particularly in regions experiencing rapid healthcare and industrial growth. This study presents a sensitive and environmentally sustainable analytical method for monitoring paracetamol (PAR), ibuprofen (IBU), and diclofenac sodium (DIC) in pharmaceutical wastewater from Al-Kharj Governorate, Saudi Arabia. The method integrates off-line solid-phase extraction (SPE) with field-amplified sample stacking (FASS) prior to capillary electrophoresis (CE), enabling effective dual preconcentration and enhanced detection sensitivity. Key parameters affecting separation and enrichment, including background electrolyte composition, pH, injection conditions, stacking efficiency, and SPE sorbent selection, were systematically optimized. Under optimal conditions, the SPE–CE–FASS method demonstrated excellent linearity (r² ≥ 0.997) over the concentration range of 10–1000 ng L⁻¹, with strong precision (intra- and inter-day RSD ≤ 6%) and high recoveries (91.8–98.5%) in pharmaceutical wastewater samples. Matrix-based limits of detection were 4.0 ng L⁻¹ for PAR, 3.5 ng L⁻¹ for IBU, and 3.0 ng L⁻¹ for DIC. The method was successfully applied to real wastewater samples, where all target analytes were detected at environmentally relevant concentrations. Owing to its low solvent consumption, reduced waste generation, and high sensitivity, the proposed SPE–CE–FASS method offers a reliable, cost-effective, and environmentally friendly approach for routine monitoring of pharmaceutical residues in complex wastewater matrices. Full article

This study explores the potential of seeds from fruit and vegetable processing waste as feedstocks for biodiesel biocomponent production. Fatty acid methyl esters (FAMEs), obtained through a transesterification reaction, were extracted using ultrasound-assisted extraction and identified by gas chromatography–mass spectrometry (GC–MS) in selected ion monitoring (SIM) mode. A total of 31 to 34 individual FAME compounds were identified across all samples. The fatty acid profiles varied both quantitatively and qualitatively depending on the raw material; however, unsaturated FAMEs predominated over saturated ones in all cases. The highest proportions were observed for γ-linolenic acid (C18:3n6), particularly in apple, melon, lemon, and pumpkin seeds. Substantial contributions of oleic acid (C18:1n9c) were found in apple, quince, cherry, and melon seeds, while linolelaidic acid (C18:2n6t) dominated in melon, pumpkin, quince, and cherry seeds. The highest total FAME contents were recorded for apple, melon, lemon, and pumpkin seeds, while the lowest values were observed in apricot and pepper seeds. Among the materials studied, grape seeds proved to be the most promising feedstock, exhibiting a favorable cetane number and a beneficial fatty acid profile characterized by high monounsaturated fatty acid (MUFA) content, low polyunsaturated fatty acid (PUFA) content, and a moderate fraction of saturated fatty acids (SFAs). Plum and peach seeds also showed significant potential, but their higher PUFA levels may compromise oxidative stability and could require antioxidant supplementation or blending with MUFA-rich feedstocks. Full article

Electronic waste (e-waste) continues to increase globally, yet conventional bins cannot distinguish hazardous batteries and devices from recyclable metals. This article presents an AI- and IoT-enabled smart dustbin that automatically identifies and segregates general waste, metals, and electronic or battery-based hazards while providing real-time monitoring through a cloud-based dashboard. The system integrates inductive sensing, Time-of-Flight detection, an Espressif Systems Platform 32 (ESP32)-CAM module, and Google Gemini 1.5 Flash for image classification. The prototype achieved a waste segregation accuracy of 93.5% with a total cycle time of 4–6 s per item. The touch-free lid, swift mechanical actuation, and compact 59 × 59 × 100 cm footprint make the dustbin suitable for deployment in campuses, offices, and shopping malls. Dual ESP32 controllers, cloud connectivity through Message Queuing Telemetry Transport (MQTT), Firebase, and a Streamlit web interface enable automated alerts through Discord and email, demonstrating a scalable and energy-efficient approach to sustainable e-waste management. Full article

Four areas in the Kongo Central Province, western Democratic Republic of the Congo, with unexploited phosphate deposits were investigated to assess the composition of phosphatic materials and to evaluate pollution hazards, including radiological hazards arising from naturally occurring radionuclides. In those areas, phosphate rocks were sampled and analyzed for P₂O₅ content (by ED-XRF), and for the naturally occurring radionuclides ²³⁸U, ²²⁶Ra, ²³²Th, ⁴⁰K (by gamma-ray spectrometry). Phosphate rocks displayed P₂O₅ content ranging from 1.06 to 24.42% (dry weight) and exceptionally high ²³⁸U and ²²⁶Ra activity concentrations (up to 3069 and 2273 Bq kg⁻¹, respectively), significantly exceeding global averages in soils. Radiological hazard indices, including the radium equivalent (RaEq), annual effective dose and lifetime cancer risk, confirmed potential health risks associated with phosphate-rich rocks. With the upcoming development of phosphate deposits in DRC, such phosphate materials might become future sources of both geochemical contamination and radiological exposure, emphasizing the need for suitable radiation monitoring and waste management plans prior to and during mineral resource exploitation. Full article