Search Results (23,120)

Sustainable management of sugar agro-industrial value chains requires a multidimensional approach that integrates economic, environmental, and social criteria. Current literature addresses risk management, circularity, and artificial intelligence in isolation, without an integrated framework that generates synergistic value. The objective of this research is to validate an integrated framework for the sustainable management of sugar agro-industrial value chains. A mixed-methods, qualitative-quantitative, descriptive-retrospective study was conducted on the Cuban sugar agro-industry during 2023–2025. The procedure was structured into five phases and 10 stages; Petri net simulation was used to validate its logical consistency. Material, economic-financial, and knowledge flows were mapped; 16 stakeholder groups and their influence–dependence relationships were analyzed; 41 risks were identified, of which six were classified as critical. Simulation-based scenario modeling, which integrates risk, circularity, and AI interventions, projects an average potential reduction of 33.4% in total chain lead time, pending empirical validation. Petri nets confirmed the absence of connectivity errors, free-choice violations, and flow noise, formally validating the logical consistency of the procedure. The research supports the hypothesis that an integrated framework combining risk management, circularity, and AI, validated using Petri nets for logical consistency, projects improvements in the efficiency and sustainability of the value chain. Full article

Tire and road wear particles (TRWPs) are major sources of non-exhaust traffic emissions. However, a limited understanding of their generation mechanisms and the lack of efficient collection methods under realistic driving conditions hinder accurate assessment. This study addresses these challenges by developing a vehicle-based methodology for the controlled recovery and characterization of TRWPs in the near-field region, rather than for direct quantification of real-world emissions. An autonomous electric vehicle was employed to ensure stable driving conditions and eliminate exhaust interference. Near-field distribution of TRWPs was visualized using a high-sensitivity optical scattering system. Based on this, a sealed tire enclosure with a high-power on-vehicle vacuum collection system was designed to enhance particle containment and recovery. Controlled circular driving tests were conducted on a dedicated outdoor test track under well-defined and repeatable conditions to enable system-level evaluation of TRWP generation and collection relative to measured tire wear. Particles were analyzed by thermogravimetric analysis, microscopy, scanning electron microscopy–energy-dispersive X-ray spectroscopy, and particle imaging. The results demonstrated stable, reproducible TRWP generation with ~60% collection efficiency relative to tire mass loss. These values are reported as system-dependent recovery indicators rather than precise emission estimates. Additional tests with an expanded recovery protocol indicated that collection efficiency can increase to ~81% (range: 73–91%), highlighting the influence of collection coverage. The collected TRWPs exhibited heterogeneous morphology, bimodal size distribution, and a mixed rubber–mineral composition in the 10–100 μm range. Spatial analysis revealed that TRWPs predominantly accumulated within a narrow zone around the driving lane. While the controlled experimental configuration enables reproducible particle generation and high-efficiency recovery, it represents a simplified driving scenario and may not fully capture the variability of real-world traffic conditions, including straight-line driving and transient maneuvers. Overall, this study demonstrates a technical framework for reproducible and comparative recovery of tire-associated particles under identical, well-defined conditions. The approach is intended to support controlled characterization studies while explicitly acknowledging limitations related to representativeness, particle origin attribution, and quantitative emission relevance, rather than to establish emission factors or mechanistic descriptions of TRWP generation. Full article

One of the bottlenecks in realizing all-optical computing is the lack of on-chip all-optical logic devices that combine compactness, low loss, and high robustness. Valley photonic crystals (VPCs) have become an important solution for realizing such devices, relying on the excellent transmission characteristics of topological valley states. However, existing structures still face issues such as limited design flexibility. In this paper, a high-performance topological all-optical logic device based on VPCs consisting of circular ring dielectric columns is designed and demonstrated. By introducing the inner radius as an independent design parameter, we construct a new type of VPC and systematically investigate its influence on the photonic band gap. Based on this, we design a beam splitter with high operational bandwidth and low insertion loss (<0.5 dB) and then realize fundamental OR and XOR logic gates, achieving extinction ratios of 18.9 dB for the OR gate and up to 44 dB for the XOR gate at an operating frequency of 193.5 THz. The platform also supports the NOT gate and, through cascading, can implement more logic functions such as the AND gate. Full article

This study (Part B) examines the potential utilization of municipal solid waste (MSW) ash, produced in a semi-industrial incinerator in Israel, as a partial substitute for cement and natural sand in industrial concrete mixtures. The ash was produced at the temperature range 600–850 °C, and the ash was characterized using XRD and SEM to determine its mineralogical composition and morphology. The results indicate that ash composition is dominated by calcium-rich phases, with hatrurite (Ca₃SiO₅) representing approximately 51–66 wt.% of the identified crystalline phases, along with calcite, MgO, and silica phases. The ash consists of irregular, porous particles with a broad distribution. Concrete performance was evaluated in both fresh and hardened states. In terms of fresh concrete properties, it is observed that concrete containing ash showed improved workability, better workability retention, and better concrete density compared to concrete without ash. In terms of hardened concrete properties, the use of MSW ash as a partial sand replacement preserved the mechanical performance of the concrete, with compressive strength remaining within approximately 2% of the reference mixture. These findings suggest that semi-industrially produced MSW ash is more suitable as a fine aggregate replacement than as a supplementary cementitious material and represents a promising route for reducing landfill disposal and promoting circular economy practices in the construction industry. Full article

Transitioning from conventional wastewater treatment to circular wastewater management requires novel technologies that enable resource recovery, energy efficiency, and resilience under variable conditions. Within the NAMOR project, hybrid microalgae–bacteria Membrane PhotoBioReactors (MPBRs) are assessed as a sustainable solution for decentralized wastewater treatment and reuse. This study focuses on screening and optimizing mixed microalgae–bacterial consortia to treat municipal wastewater streams in the Mediterranean region, with an emphasis on achieving high nutrient removal, biomass productivity and robustness. A diverse set of strains will be evaluated under controlled temperature, light and nutrient regimes to enhance the symbiotic synergy between photosynthetic microalgae and heterotrophic bacteria, while minimizing aeration demand. Based on these results, a pilot demo in Lagadas, Greece, will integrate the optimized consortia into a moving-bed PBR equipped with polymeric carriers and membrane filtration for advanced effluent polishing, intended to produce reclaimed water for irrigation and biomass for valorisation into fertilizers or biogas. Full article

In response to the growing challenge of electronic waste, we developed an open-source pick-and-remove system for recovering electronic components for reuse. This platform is based on a repurposed 3-D printer chassis, an infrared pre-heater, and a hot-air soldering station. The system is designed for easy adoption in academic laboratories and FabLabs. A literature review highlights the potential of electronic components recovery, while preliminary tests demonstrate high recovery rates and minimal environmental impact of the proposed system. This work aims to support the transition to a circular electronics economy by making component recovery accessible and providing additional value to electronic waste. Full article

The valorization of industrial mining and organic wastes in construction materials constitutes a key strategy for reducing the environmental impact of the sector. In this context, the present study aims to evaluate the sustainability of innovative Artificial Lightweight Aggregates (ALAs) manufactured from mixtures of inorganic industrial wastes—such as granite and slate cutting sludge and aggregate washing sludge—together with organic wastes, like cork dust, coffee grounds, and olive pits. The methodology included a Life Cycle Assessment (LCA), considering different waste compositions and manufacturing conditions. The results show that the developed ALAs exhibit favorable environmental performance as their bulk density decreases, with an overall environmental impact lower than that of conventional lightweight aggregates made from expanded clay, achieving a reduction in the carbon footprint of up to 7%. Likewise, the comparative analysis reveals that the process stage with the greatest environmental impact is the heat energy required during the sintering stage in the rotary kiln, which in some cases accounts for more than 90% of the total impact. In summary, the results demonstrate the feasibility of obtaining ALAs manufactured solely from waste with a lower carbon footprint compared to traditional expanded clay aggregates. Furthermore, the study highlights that the process stages with the highest contributions to environmental impact are the transport of raw materials and the high-temperature sintering of the ALAs in the rotary kiln. Thus, their production from waste contributes to the valorization of by-products, fostering circular economy strategies and supporting decarbonization processes within the construction sector. Full article

This study investigates the feasibility of recycling scallop shells as a partial substitute for natural coarse aggregates in concrete at replacement rates of 20%, 30%, and 40% by mass. The originality of the work lies in combining conventional mechanical and durability tests with a six-month environmental monitoring protocol under simulated rainfall and an end-of-life regulatory interpretation of chemical release. Processed shells were used as a 2/20 mm coarse fraction and characterized by a density of 2713 kg/m³, a water absorption of 2.93%, and a Los Angeles coefficient of 15.1. At 28 days, compressive strength decreased from 33.7 MPa for the reference concrete to 27.9 MPa, 28.1 MPa, and 26.7 MPa for SS20, SS30, and SS40, respectively. Water-accessible porosity increased from 7.8% to 9.9%, and carbonation depth after 70 days increased from 6.2 mm to 12.8 mm at 40% shell replacement. In contrast, chloride ion migration decreased from 19.0 × 10⁻¹² m²/s for the reference concrete to 17.4, 16.3, and 12.1 × 10⁻¹² m²/s at 90 days for SS20, SS30, and SS40, respectively. Environmental monitoring showed low runoff concentrations for anions and trace metals, all below the French regulatory thresholds considered in this work. Under the conditions of this study, shell replacement up to 30% appears technically feasible for non-structural or lightly loaded applications, while the environmental behavior remained compatible with an inert end-of-life classification. Full article

Harvesting remains one of the main bottlenecks in microalgae-based technologies. Although microalgae hold great promise for industrial biotechnology, their growth in dilute suspensions makes biomass recovery challenging. Conventional harvesting methods are often energy-intensive and costly, limiting large-scale implementation. This study applies a life cycle assessment (LCA) to evaluate the environmental performance of a laboratory-scale magnetic harvesting process of Chlorella vulgaris (C. vulgaris) using Fe₃O₄ microparticles in combination with polyaluminum chloride (PAC) and polyacrylamide (PAM), followed by magnetic oscillation for particle detachment and subsequent reuse. Electricity consumption was identified as the dominant environmental hotspot across most impact categories, with the detachment step accounting for nearly two-thirds of the total energy demand, a step often overlooked in previous LCA studies. The global warming potential (GWP) is consistent with typical laboratory-scale assessments and is mainly driven by energy inefficiencies associated with small processing volumes. The values obtained and the scale-up literature indicate that further optimization and future industrial-scale production will decrease these values into a realistic and competitive range. Sensitivity analysis showed that replacing grid electricity with photovoltaic power significantly reduces environmental impacts. The use of NaOH as a reagent also contributed substantially to environmental impacts. Reusing magnetic particles (4 cycles) reduced material resource depletion by up to fourfold, which is a very relevant result bearing in mind the principles of sustainability and circularity. Full article

In this paper, we describe a method for computing calendar time forecasts in a local area for large earthquakes of a target magnitude M_T using a count of small earthquakes in the magnitude range M_S to M_T in the area. Using the idea that the Gutenberg–Richter (GR) relation is valid throughout the surrounding region, we define an ensemble of earthquakes in larger surrounding regions to be used in computing the forecast. What follows is simple data mining. “Local” is defined by the probability of a large earthquake occurring within a defined circle of arbitrary radius surrounding a point of interest. The main (and for that matter, the only) assumption for all these works is that the GR magnitude–frequency relation holds. The method has significant skill, as defined by the Receiver Operating Characteristic (ROC) test, which improves as the time since the last major earthquake increases. The probability is conditioned on the number of small earthquakes n(t), with M ≥ M_S = 3.49, that have occurred since the last large earthquake. The probability is computed directly as the Positive Predictive Value (PPV) associated with the ROC curve. The method is compared with the UCERF3 forecasts for the UCERF3-defined geographic boxes centered on Los Angeles and San Francisco and serves as an indicative benchmark. The method is then applied to a 125 km radius circular area around Los Angeles, California, following the 17 January 1994 magnitude M6.7 Northridge earthquake, and short-term forecasts (1-year and 5-year) are computed. We further apply the method to six additional geographic regions with validation by comparison with an estimate of the time-independent conditional Poisson probability. These regions are Athens, Greece; Chengdu, China; Jakarta, Indonesia; Lima, Peru; Santiago, Chile; and Tangshan, China. Full article

Bio-based and biodegradable polymer composites based on polylactic acid (PLA) and polybutylene succinate-co-adipate (PBSA) were developed for rigid food packaging applications. Agro-industrial residues consisting of ground leaves and branches derived from tangerine tree cultivation (pruning) were used as fillers at high loading (30 wt%) before (PRE) or after (POST) extraction of bioactive compounds. The influence of blend composition (PLA/PBSA 60/40 and 30/70), filler extraction, and the addition of antioxidants (0.5 wt%) on material properties was systematically investigated. Composites were processed via extrusion and injection molding and characterized through FTIR, SEM, tensile testing and thermal analysis. The results show that polymer blend morphology affects mechanical behavior, with co-continuous structures (60/40) exhibiting improved ductility compared to dispersed systems (30/70). The incorporation of lignocellulosic residues increased stiffness but reduced elongation at break. Extraction treatment significantly modified filler morphology and interfacial interactions, slightly improving dispersion and processability. The effect of the extracted bioactive compounds on the thermal stabilization of biocomposites was also investigated. Overall, the findings demonstrate the potential of combining biodegradable polymer blends with treated agricultural residues to produce sustainable rigid packaging materials while supporting a bio-circular approach. In fact, preliminary extraction of valuable compounds from tangerine pruning waste appears to be a convenient strategy for its efficient cascade valorization. Full article

Municipal solid waste (MSW) management is a critical challenge to advancing recycling and circular economy approaches. This review provides a comprehensive overview of MSW management, encompassing sourcing, policy frameworks, characterization techniques, separation technologies, preprocessing strategies, and utilization pathways. First, generation patterns and sourcing mechanisms are discussed in both U.S. and global contexts, with emphasis on the influence of policy frameworks on waste reduction and diversion. Second, characterization techniques are evaluated, focusing on physical and chemical analysis for material recyclability. Third, sorting technologies are critically reviewed, covering conventional methods and emerging sensor-based approaches. Preprocessing techniques are then evaluated for their role in improving downstream conversion efficiency. Finally, valorization pathways such as waste-to-syngas, waste-to-biochar, and waste-to-sustainable aviation fuel (SAF) are assessed in terms of their role in climate mitigation and the circular economy. It is anticipated that this review will provide a foundational reference for researchers, policymakers, and industry stakeholders aiming to strengthen the recyclability infrastructure and maximize the efficiency of MSW management systems in the framework of the circular economy. Full article

At present, treated wastewater may still contain residual nutrients and micropollutants, including heavy metals, pharmaceuticals, and dyes, which can negatively affect receiving water bodies. Increasingly stringent environmental regulations, including Directive (EU) 2024/3019, require both enhanced removal of these contaminants and greater integration of renewable energy sources in wastewater treatment plants. This paper presents a review of biomass-based wastewater polishing technologies employing biological agents such as microalgae, fungi, bacteria, co-cultures and duckweed for the removal of residual contaminants from treated effluents. The compiled data indicate that while optimal conditions can drive pollutant removal efficiencies beyond 90%, system performance varies widely depending on species selection, wastewater characteristics, and operational conditions (e.g., pH, temperature, salinity, nutrient availability, and light intensity). In addition to effluent polishing, the produced biomass can be valorized for bioenergy generation, contributing to renewable energy production and supporting circular economy principles in wastewater treatment plants. Despite these benefits, biomass harvesting remains a major technical and economic bottleneck, often representing a significant share of operational costs and limiting large-scale implementation. Overall, biomass-based treatment technologies are a promising approach for improving effluent quality and supporting renewable energy objectives; however, further advances in biomass recovery are required for broader application. Full article

Surfactin is a lipopeptide biosurfactant with significant industrial potential, but high production costs have hindered its commercialization. In this study, we developed a sustainable and cost-effective bioprocess for surfactin biosynthesis using Bacillus subtilis 55033, utilizing kitchen waste as the primary fermentation substrate without any previous pretreatment—an advantage that simplifies the process and reduces costs compared to previous reports. To maximize productivity, the fermentation parameters were systematically optimized through single-factor and orthogonal experimental designs. The optimal conditions were as follows: a fermentation temperature of 31 °C, a duration of 48 h, a 5% v/v inoculum, a 7% w/v solid-to-liquid ratio, an initial pH of 7.5, and an agitation speed of 200 rpm. Under these conditions, the surfactin yield reached 371.67 mg/L, an increase of 100.5% from 185.4 mg/L prior to optimization. We performed a comparative analysis of the surfactin biosynthetic gene clusters between B. subtilis 55033 and the model strain B. subtilis 168. The produced surfactin exhibited potent antagonistic activity against aquatic pathogens, significantly inhibiting the growth of several species of Vibrio and the division and hatching of Cryptocaryon irritans Tomonts. These findings demonstrate that our platform not only provides a high-value valorization route for organic waste but also enables preliminary exploration of surfactin applications in aquaculture, in line with the principles of a circular bioeconomy. Full article

Forest carbon assessment requires methods that capture the combined effects of stand structure, site conditions, carbon pools, operational emissions, and circular-economy processes. This study aimed to develop and optimize hybrid machine learning models for predicting the gross CO₂e (carbon dioxide equivalent) balance of Polish forest stands using measurable stand- and site-related variables. The research was based on a primary dataset describing forest management in major Polish macroregions in 2020–2024. After data cleaning and preprocessing, multiple machine learning algorithms, including ensemble, boosting, neural, and hybrid models, were trained, validated, and tested. Model performance was assessed using standard regression metrics, overfitting diagnostics, learning curves, and SHAP (Shapley Additive Explanations). Most models achieved high predictive accuracy, with six of ten algorithms reaching R² values above 0.90 on the test set. The reduction in strongly correlated variables helped limit multicollinearity and excessive overlap between predictors and the target variable, supporting a more reliable interpretation of model performance. The CatBoost algorithm achieved the highest predictive performance on the test set (R² = 0.948), while also recording the lowest root mean squared error (RMSE = 152.242). However, the Decision Tree demonstrated the weakest generalization performance (R² = 0.806) on the test set. SHAP analysis identified tree height as the most influential predictor, followed by tree age, number of trees, species composition, and selected habitat features. The novelty of the study lies in integrating hybrid machine learning, interpretable modelling, and circular-economy-related carbon balance components into a single framework for rapid and operational forest carbon assessment in Polish forest stands. Full article