Search Results (292)

Driven by environmental concerns and aligned with the principles of the circular economy, urban plastic waste—including packaging materials, disposable items, non-functional objects, and industrial scrap—is increasingly being collected, recycled, and marketed as a potential substitute for virgin polymers. However, the use of recycled polymers introduces uncertainties that can significantly affect both the durability and the further recyclability of the resulting products. This paper demonstrates how spectroscopic analysis in the mid-infrared (MIR) and near-infrared (NIR) regions can be applied well beyond the basic identification of the main polymeric component, typically performed during the sorting stage of recycling processes. A detailed interpretation of spectral data, based on well-established correlations between spectroscopic response and material structure, enables the classification of recycled polymers according to specific physicochemical properties, such as chemical composition, molecular architecture, and morphology. In this context, infrared spectroscopy not only provides a reliable comparison with the corresponding virgin polymer references but also proves particularly effective in assessing the homogeneity of recycled materials and the reproducibility of their properties—factors not inherently guaranteed due to the variability of input sources. As a case study, we present a robust protocol for determining the polypropylene content in recycled polyethylene samples. Full article

Composites are essential materials in a wide range of industrial and medical applications due to their unique functional properties. One of the main issues of composites arises at their end-of-life stage, especially in terms of the recyclability process and its quantitative evaluation. In this study, we present a quantitative methodology for assessing the quality of composite recycling, using a paraffin-based microcomposite with the addition of tungsten particles (at one concentration 50 wt.%) as an example. Our approach combines visible-light microscopy with digital image processing techniques to obtain quantitative metrics related to recycling efficiency. The tools utilized—recognized as relatively common and uncomplicated for use in various scientific fields—have shown that the value of average particle density significantly decreased from a primary value of 43.30% to 8.30%. Consequently, the presented results confirm the usefulness of the method for the quantitative assessment of the quality of the recycling process. Full article

This study develops an ontology-based decision support framework to enhance sustainable polymer recycling within the circular economy. The framework, constructed in Protégé (OWL 2), systematically captures polymer categories with emphasis on polyethylene terephthalate (PET), polylactic acid (PLA), and rigid polyvinyl chloride (PVC) as well as recycling processes, waste classifications, and sustainability indicators such as carbon footprint. Semantic reasoning was implemented using the Semantic Web Rule Language (SWRL) and SPARQL Protocol and RDF Query Language (SPARQL) to infer optimal material flows and sustainable pathways. Validation through a UK industrial case study confirmed both the framework’s applicability and highlighted barriers to large-scale recycling, including performance gaps between virgin and recycled polymers. The comparative analysis showed carbon footprints of 2.8 kg CO₂/kg for virgin PET, 1.5 kg CO₂/kg for PLA, and 2.1 kg CO₂/kg for PVC, underscoring material-specific sustainability challenges. Validation through a UK industrial case study further highlighted additive complexity in PVC as a major barrier to large scale recycling. Bibliometric and thematic analyses conducted in this study revealed persistent gaps in sustainability metrics, lifecycle assessment, and semantic support for circular polymer systems. By integrating these insights, the proposed framework provides a scalable, data-driven tool for evaluating and optimising polymer lifecycles, supporting industry transitions toward resilient, circular, and net-zero material systems. Full article

To advance the application of sustainable recycled aggregate concrete (RAC) in bridge engineering, this study introduces a novel reinforced RAC-filled circular steel tubular (RRACFCST) column, leveraging the dual confinement of an external steel tube and an internal reinforcement cage. Its primary novelty is a comprehensive analytical framework integrating a new theoretical model by using limit analysis, ferrule theory, and the twin shear unified strength theory. Then, a rigorously validated nonlinear finite element model that incorporated material nonlinearity and interface effects was used to validate the proposed theoretical model. The results demonstrate the significant performance of the steel reinforcement cage, which enhanced the axial bearing capacity by 17.86%, and an optimal recycled aggregate replacement rate of 70% yielded the bearing capacity, with 100% replacement still achieving a 13.3% higher capacity than unconfined conventional concrete, demonstrating how effective confinement can compensate for and overcome the inherent deficiencies of RCA. Conversely, larger diameter–thickness ratios would reduce the strength by 33.7%. These quantifiable findings provide critical design insights and a validated predictive tool, establishing the RRACFCST column as a promising and high-performance sustainable solution for bridge structures. Full article

As cities confront intensifying environmental challenges and increasing expectations for sustainable governance, extending Environmental, Social, and Governance (ESG) evaluation frameworks to the urban scale has become a pressing need. However, existing ESG systems are typically designed for corporate contexts, lacking city-specific indicators, integrated data representations, and reliable ESG information with high spatial and temporal resolution for informed decision-making. This study proposes a comprehensive ESG evaluation framework tailored to green cities, which consists of three core components: (1) The construction of a green-oriented ESG indicator system with an expert-informed weighting system; (2) the design of a GIS-BIM-IoT integrated ontology that semantically aligns spatial, infrastructure, and observational data with ESG dimensions; and (3) the implementation of a web-based data integration and visualization platform that dynamically aggregates and visualizes ESG insights. A case study involving a primary school and an air quality monitoring station in Hong Kong demonstrates the system’s capability to infer material recycling rates and pollution concentration scores using ontology-driven reasoning and RDF-based knowledge graphs. The results are rendered in an interactive 3D urban interface, supporting real-time, multi-scale ESG evaluation. This framework transforms ESG assessment from a static reporting tool into a strategic asset for transparent, adaptive, and evidence-based urban sustainability governance. Full article

River sediments have attracted increasing attention as alternative raw materials for sustainable cementitious materials due to their abundant availability and silica–alumina-rich composition. In this study, a systematic literature search was conducted in Web of Science and Google Scholar using combinations of the keywords “river sediment,” “cementitious materials,” “activation,” and “pozzolanic activity,” covering publications up to July 2025. In addition, a citation network tool (Connected Papers) was employed to trace related works and ensure comprehensive coverage of emerging studies. This review systematically examines the properties of river sediments from diverse regions, along with activation and modification techniques such as alkali/acid activation, thermal calcination, and mechanical milling. Their applications in various cementitious systems are analyzed, with mix design models compared to elucidate the effects of replacing fine aggregates, coarse aggregates, and cement on workability, strength, and durability. Multi-scale characterization via XRD, FTIR, and TG-DSC reveals the mechanisms of C–S–H and C–A–S–H gel formation, pore refinement, and interfacial transition zone densification. The review highlights three key findings: (1) moderate sediment replacement (20–30%) improves strength without compromising flowability; (2) alkali–water glass activation and calcination at 600–850 °C effectively enhance pozzolanic activity; and (3) combining the minimum paste thickness theory with additives such as water reducers, fibers, or biochar enables high-performance and low-carbon concrete design. This review provides a comprehensive theoretical foundation and technical pathway for the high-value utilization of river sediments, carbon reduction in concrete, and sustainable resource recycling. Full article

This study examines the pedagogical potential of LEGO^® SERIOUS PLAY^® (LSP) in optometric education, aiming to foster critical reflection on optics, sustainability, and professional identity. A qualitative interpretative phenomenological analysis was conducted with 48 students from Optics and Optometry and Renewable Energies programs at ISEC Lisboa. Participants took part in LSP sessions focused on optics and sustainability, using metaphorical models to express their reflections. Data were collected via observations, group discussions, and open-ended questionnaires, and analyzed with Grounded Theory. In the optics theme, models revealed both scientific and symbolic views, with visual correction (46.7%), professional roles (21.3%), and perception (14.7%) being most frequent. Statistically significant differences appeared by academic background (p < 0.001) and experience (p = 0.0018): optometry students emphasized clinical roles, while environmental students highlighted perception. For sustainability, main categories included sustainable practices (41.7%), polluting industries (15.3%), ecological footprint (13.9%), and social responsibility (12.5%). Actions proposed included recycling, reuse, and biodegradable materials. Age was linked to action-oriented responses (p = 0.038), with no differences by gender or nationality. LSP emerged as an effective tool for deep reflection, interdisciplinary learning, and ethical engagement, supporting integration of sustainability and identity in technical education. Further research should explore its long-term educational impact. Full article

Plastic pollution has emerged as a critical environmental challenge due to the widespread accumulation of petrochemical plastics in natural ecosystems. Conventional waste management strategies, including mechanical recycling and incineration, have demonstrated limited efficiency in addressing the persistence of plastics such as polyethylene, polypropylene, polyethylene terephthalate, and polyvinyl chloride. While incineration eliminates plastic material, it does not promote circularity and may generate toxic emissions. As a sustainable alternative, microbial biodegradation involves bacteria, fungi, and actinomycetes capable of degrading synthetic polymers through enzymatic processes. This review provides a comprehensive overview of microbial degradation of major plastics such as polyethylene, polypropylene, polyethylene terephthalate, and polyvinyl chloride, highlighting key strains, degradation rates, and enzymatic mechanisms. Importantly, biodegradation research also informs the development of in situ remediation technologies and supports new recycling strategies. Advances in protein engineering and synthetic biology are discussed for enhancing degradation efficiency. However, scaling biodegradation to environmental conditions remains challenging due to variable temperature, pH, microbial competition, and potentially toxic intermediates. Despite these limitations, microbial biodegradation represents a promising ecofriendly approach to address plastic waste and promote a biobased circular economy. Future work should integrate microbial processes into existing recycling infrastructure and design robust consortia guided by omics tools. Full article

Although approximately half of global lithium consumption is used in the rechargeable battery industry, lithium is also in demand for other specialized applications, such as high-temperature lubricants, ceramics, glass, and pharmaceuticals. The growing need for efficient lithium recovery and recycling underscores the importance of fast and accurate analytical tools for determining lithium concentrations in non-compliant and waste materials generated by industrial processes. In this paper, we present a machine learning-based procedure utilizing Laser-Induced Breakdown Spectroscopy (LIBS) to accurately quantify lithium concentrations in lithium-rich non-compliant materials derived from the industrial production of enamels used for coating metallic surfaces. This procedure addresses challenges such as strong self-absorption and matrix effects, which limit the effectiveness of conventional univariate calibration methods. By employing a multivariate approach, we developed a single model capable of quantifying lithium content across a wide concentration range. A comparison of the LIBS results with those obtained using conventional laboratory analysis (Inductively Coupled Plasma–Optical Emission Spectrometry, ICP-OES) confirms that LIBS can deliver the speed, precision, and reliability required for potential routine applications in the lithium recovery and recycling industry. Full article

Polymer recycling is challenging due to practical classification difficulties. Even when the polymer matrix is identified, the presence of various polymeric composites complicates their accurate classification. In this study, Fourier-transform infrared spectroscopy (ATR-FTIR) was used in combination with artificial neural networks (ANNs) to quantitatively predict the mineral filler content in polypropylene (PP) composites. Calibration curves were developed to correlate ATR-FTIR spectral features (600–1700 cm⁻¹) with the concentration (wt.%) of three mineral fillers: talc (PP-Talc), calcium carbonate (PP-CaCO₃), and glass fiber (PP-GF). ANN models developed in MATLAB 2024a achieved prediction errors below 7.5% and regression coefficients (R²) above 0.98 for all filler types. The method was successfully applied to analyze a commercial recycled pellet, and its predictions were validated by X-ray fluorescence (XRF) and energy-dispersive X-ray spectroscopy (EDX). This approach provides a simple, rapid, and non-destructive tool for non-expert users to identify both the type and amount of mineral filler in recycled polymer materials, thereby reducing misclassification in their commercialization or quality control in industrial formulations. Full article

Accurately modelling and simulating the stiffness modulus of asphalt mixtures is essential for reliable pavement design and performance prediction under varying environmental and loading conditions. The preceding is commonly achieved through master curves, which relate stiffness to loading frequency at a reference temperature. However, conventional master curves face two primary limitations. Firstly, temperature is not treated as a state variable; instead, its effect is indirectly considered through shift factors, which can introduce inaccuracies due to their lack of thermodynamic consistency across the entire range of possible temperatures. Secondly, conventional master curves often encounter convergence difficulties when calibrated with experimental data constrained to a narrow frequency spectrum. In order to address these shortcomings, this investigation proposes a novel formulation known as the Thermo-Stiffness Integration (TSI) model, which explicitly incorporates both temperature and frequency as state variables to predict the stiffness modulus directly, without relying on supplementary expressions such as shift factors. The TSI model is built on thermodynamics-based principles (such as Eyring’s rate theory and activation free energy) and leverages the time–temperature superposition principle to create a physically consistent representation of the mechanical behaviour of asphalt mixtures. This manuscript presents the development of the TSI model along with its application in a case study involving eight asphalt mixtures, including four hot-mix asphalts and four warm-mix asphalts. Each type of mixture contains recycled concrete aggregates at replacement levels of 0%, 15%, 30%, and 45% as partial substitutes for coarse natural aggregates. This diverse set of materials enables a robust evaluation of the model’s performance, even under non-traditional mixture designs. For this case study, the TSI model enhances computational stability by approximately 4 to 45 times compared to conventional master curves. Thus, the main contribution of this research lies in establishing a valuable mathematical tool for both scientists and practitioners aiming to improve the design and performance assessment of asphalt mixtures in a more physically realistic and computationally stable approach. Full article

Sustainable shell structures are thin, curved systems such as domes, vaults, and cylindrical shells that achieve strength and stability primarily through membrane action, allowing significant material savings. Their sustainability lies in minimizing embodied energy and CO₂ emissions by using less material, integrating recycled or bio-based components, and applying optimization strategies to extend service life and enable reuse or recycling, all while maintaining structural performance and architectural quality. This review critically examines the state-of-the-art in sustainable shell structures, focusing on their buckling behavior and material-efficient design strategies. Integrating bibliometric analysis with thematic synthesis, the study identifies key research trends, theoretical advancements, and optimization tools that support structural efficiency. Emphasis is placed on recent developments in composite and bio-based materials, imperfection-sensitive buckling models, and performance-based design approaches. Advanced computational methods, including finite element analysis, machine learning, and digital twins, are highlighted as critical in enhancing predictive accuracy and sustainability outcomes. The findings underscore the dual challenge of achieving both structural stability and environmental responsibility, while outlining research gaps and future directions toward resilient, low-impact shell construction. Full article

The growing use of plastics in food packaging has raised concerns about chemical migration into consumables, posing potential health risks. Ensuring the safety of packaging materials is a critical public health priority. This study aimed to validate an analytical method for qualitative and quantitative determination of BPs in bottled water and evaluate their presence in PET and rPET matrices. The method was validated through recovery tests for eight BPs (Bisphenol A, Bisphenol S, Bisphenol F, Bisphenol AF, Bisphenol AP, Bisphenol B, Bisphenol Z, and Bisphenol P). Linearity (R² ≥ 0.990) and high recovery rates proved the method’s stability, reliability, and accuracy. For bottled water, LODs ranged 0.030–0.075 µg/L and LOQs 0.10–0.25 µg/L; for PET/rPET, LODs were 0.00030–0.00075 mg/kg and LOQs 0.0010–0.0025 mg/kg. Mean recoveries in bottled water were in the range 89–109%, in PET from 94% to 117%, and in rPET from 106% to 118%. The results showed that BPA was quantifiable in all matrices, while other BPs remained below the limit of quantification. The validated method provides a robust tool for assessing bisphenol contamination and supports ongoing efforts to enhance food safety and inform regulatory frameworks for sustainable PET recycling. Full article

Life cycle assessment (LCA) is a standardized tool (ISO 14040) used to evaluate the environmental impacts of products and processes across their entire life cycle, from raw material extraction to end-of-life disposal or recycling. It has become particularly important in the context of engineering materials, where sustainability considerations are critical. Despite challenges such as data quality limitations, variations in system boundary definitions, and methodological inconsistencies, LCA remains an essential tool for assessing and improving product sustainability. This work presents a foundational overview of LCA principles and describes a systematic, step-by-step procedure for its effective application. Additionally, this article revisits the fundamental concepts of carbon footprint (CF) analysis as a complementary tool for quantifying greenhouse gas emissions associated with products and activities. CF analysis underscores the necessity of adopting low-carbon materials and manufacturing processes to minimize embodied energy and reduce environmental emissions. Low-carbon materials are characterized by attributes such as being lightweight, recyclable, renewable, bio-based, locally sourced, and safe for public health. Their development balances the reduction of raw material and resource consumption during production, with increasing product performance, recyclability, and service life, reflecting a cradle-to-cradle, circular economy approach. The integration of LCA and CF methodologies provides an integral framework for assessing environmental performance and supports decision-making processes aligned with global sustainability targets. Full article

The United States of America could build 20,000 bases for the Statue of Liberty every year using its construction and demolition waste, and 456 bases using waste glass from jars and bottles. However, some sectors of the population still face a shortage of affordable housing. The challenges of disposing of such large amounts of waste and solving the housing shortage could be addressed together if these materials, considered part of a closed-loop system, were integrated into new building blocks. This research studies compressed earth blocks that incorporate soils and gravels excavated in situ, river sand, crushed concrete from demolition waste, and recycled glass sand. To stabilize the blocks, cement is used at 5, 10, and 15% (by weight). The properties studied include the following: density, apparent porosity, initial water absorption, simple compression, modulus of elasticity, and thermal conductivity. Optical image analysis proved to be a tool for predicting the values of these properties as the stabilizer changed. To assist in decision making regarding the best overall performance of the total 12 mix designs, a ranking system is proposed. The best blocks, which incorporate the otherwise waste materials, exhibited simple compression values up to 7.3 MPa, initial water absorption of 8 g/(cm² × min^0.5) and thermal conductivity of 0.684 W/m·K. Full article