Magnetic density separation (MDS) can separate millimetre-sized non-ferromagnetic particles, although suitable combinations of magnet inclination (θ) and magnetic-liquid magnetization (M_f) depend on the separator geometry. We developed an operating map from a calibrated quasi-static density-matching model. Five measurements of magnetic-liquid density were interpolated piecewise linearly and combined with an exponential field-decay expression to calculate three bottom density-matching positions. Feasible conditions had to satisfy position ordering, tank and magnetic-field coverage, a 3.0 cm feed-zone boundary, and a minimum middle-product collection width of 0.45 cm. For θ = 12° and M_f = 5300 A/m, the calculated x_h, x_l, and W_m were 21.920, 27.577, and 5.656 cm, respectively. The tested input perturbations and grid refinements produced only small changes in the reported metrics. Three independent separation runs, with triplicate ICP measurements for each sample, demonstrated density-based product partitioning at the selected condition. Broader validation will require testing additional operating conditions.

Fast in-line identification of contaminants in recycled coarse aggregates (RCA) is essential for quality control of the processing of RCA. However, robust classification from single-shot spectra remains challenging under practical operating conditions. Laser-induced breakdown spectroscopy (LIBS) offers potential for fast, non-contact material identification, but direct recognition from raw single-shot LIBS spectra is difficult because the signals are high-dimensional and affected by shot-to-shot variability. This challenge becomes more pronounced in multi-material settings, where spectral overlap and local heterogeneity make contaminants less distinguishable across classes. To address these challenges, an explainable spectral-attention network is proposed for single-shot LIBS spectral classification based on an Explainable Convolutional Transformer Network (ECT-Net). The model integrates a convolutional layer for local spectral feature extraction directly from standard normal variate (SNV)-preprocessed spectra and sequence downsampling, a Transformer encoder for modelling longer-range dependencies across spectral regions, and a global average pooling head for compact multi-class prediction. The framework was evaluated on a balanced ten-class dataset comprising 24,000 single-shot LIBS spectra acquired experimentally under realistic conveyor-belt conditions with RCA and contaminants commonly existing in construction and demolition waste recycling. The proposed lightweight Explainable Convolutional Transformer Network (ECT-Lite) achieved a test macro-averaged F1 score of 98.59%, with a corresponding test accuracy of 98.63%. Attention visualization confirmed that the model focused on physically meaningful wavelength regions. These results demonstrate the effectiveness of the proposed ECT-Lite for SNV-preprocessed single-shot LIBS spectra in recycling-oriented multi-material recognition.

Ensuring consistent quality of recycled aggregates is essential for their wider use in circular construction. Laser-induced breakdown spectroscopy (LIBS) enables rapid elemental inspection, yet its performance in automated sorting systems is strongly shaped by how raw spectra are represented. This study adopts a representation-first benchmarking perspective and evaluates four representative feature families, namely variance-driven Principal Component Analysis (PCA), manifold learning-based Isomap, label-driven Partial Least Squares Discriminant Analysis (PLS-DA), and cepstral envelope-line separation, together with a raw-spectrum logistic-regression baseline and a histogram gradient boosting (HGB) reference model. The benchmark uses 24,000 single-shot spectra collected from ten material classes under conveyor-belt conditions, and repeated stratified random-split evaluation is used to assess the robustness of the comparative results across data splits. Across the evaluated models, cepstral features deliver the strongest overall performance, while PCA and the raw-spectrum logistic-regression baseline remain closely competitive. Isomap broadens the comparison toward non-linear manifold-based embeddings but does not improve performance in the present dataset, and PLS-DA shows the weakest stability under strong channel collinearity and class overlap. The results indicate that explicit feature extraction is not uniformly beneficial across all methods, but that spectral representation remains a major source of performance variation under controlled conveyor-like LIBS acquisition. In particular, cepstral features provide the most favourable balance among classification performance, robustness to baseline variation, and compactness, whereas PCA remains attractive when interpretability is prioritised. These findings provide a controlled benchmark and practical guidance for designing reliable and explainable LIBS-based quality-assurance pipelines for recycled-aggregate processing.

Mineral grinding often represents a major fraction of total energy costs and coarse pre-concentration can significantly decrease unnecessary processing of barren material. Compressed-air ejection is effective at industrial scale, but suffers from low accuracy at millimeter scale. An opto-magnetic sorting process for coarse pre-concentration of REE-bearing particles before grinding was developed and assessed at labscale. The process combines image-based optical thresholding, water-based wetting of selected particles, magnetite adhesion to wetted surfaces, and magnetic lifting. This process thus couples selective magnetite coating (enabled by localized wetting) and magnetic lifting for particle sorting. The process was run in a reject-oriented mode to facilitate early mass rejection before subsequent comminution. Lab-scale experiments on rauhaugite revealed increasing pre-concentration with decreasing particle size, resulting in a low-grade fraction of 30.4 wt% of the 2–4 mm feed for possible early rejection. The high-grade fraction (57% of the 2–4 mm feed) achieved a TREO concentration of 2.32%, reflecting an enrichment factor of approximately 1.35 compared to the feed (1.71%), consistent with a partial realization of the intrinsic upgrading potential of the ore at this mass yield, as inferred from the TREO distribution of RGB-classified particles. The lab system processed 84 kg/h, corresponding to approximately 1 tonne of feed processed within 12 h. Based on an instantaneous power demand of ∼ 0.8 kW, this corresponds to an energy consumption of ∼ 9.6 kWh/tonne under steady-state conditions. The process also exhibited low water usage (∼5.7 L/tonne feed) and > 99% magnetite recyclability (after 3 runs). Beyond REE beneficiation, the proposed approach shows potential for selective pre-concentration of heterogeneous particulate streams requiring localized actuation.

To alleviate the excessive extraction from natural resources and to properly manage construction waste, recycled concrete technology is globally recognized as an eco-friendly way to address these escalating challenges. This study explores the influence of three particle size distributions (PSD) (upper, median, and lower limits) and two curing conditions (normal: 19–25 °C, humidity 48–56 %; lab standard: 20 ± 2 °C, humidity ≥ 95 %) on the compressive strength, tensile splitting strength, and strength development of recycled concrete through a series of experiments. The detailed data make up the research gap in this aspect and reveal that the influence of the PSD on the compressive strength and tensile splitting strength is limited. However, a favourable curing condition benefits the mechanical properties of recycled concrete, especially in resisting tension. In terms of compressive strength, this study indicates that recycled concrete has the potential to replace natural aggregates totally and is feasible to be applied in almost all practical engineering applications, which provides a solid foundation for the future of sustainable construction.

The authors regret that the original version of this article contained numerical errors in Figure 2 within the main text and Table A1 of Appendix A. Supplementary data. Corrections that need to be made are presented as follows: • For Figure 2 in the main text, the label “0∼4mm SS (42.5%)” of a flow should be corrected to “0∼4mm SS (44.5%)”, as shown in Fig. C1 below. [Figure presented]• In Table A1 of Appendix A, the electricity usage for the “Wet processing” under the S1 BAU WP scenario should be corrected to “400 kWh” instead of “60,000 kWh”.The authors would like to apologise for any inconvenience caused and state that the changes reported do not affect the scientific results and conclusions of the manuscript.

This study presents a method for recovering cement-rich powder from recycled fine aggregates by thermal shock, during which particles are fragmented and spalled due to differential thermal stress. When recycled fine aggregates (RFA) are exposed to high temperatures, the cement paste-rich boundary between the aggregates is weakened and spalled, liberating cement rich particles due to thermal shock. To investigate this phenomenon, experiments have been carried out by subjecting fine recycled aggregates to high temperatures ranging from 500 °C to 700 °C at different residence times. The result suggests that the particles split and crackle due to thermo-mechanical changes. Following thermal treatment, gentle milling completes the liberation process of recycled cement-rich powder (RCP). The composition of the recovered powder confirms the feasibility of the recovery method. To understand the thermo-mechanical process better, modelling efforts have been carried out on a spherical concrete particle of known diameter. The model predicts the temperature profile, residence time and radial stress inside the particle. According to the model, a 2 mm particle experiences a radial stress high enough to overcome the tensile strength of the concrete within 35 s, causing cracks due to the thermal gradient created between the inner and outer surfaces of the particle. These predictions have been verified by experimental results in the laboratory. This approach not only enhances recovery of RCP but also promotes sustainable construction practices.

The construction industry urgently requires a resilient information system for effective coordination of data transmission among various stakeholders, including both the public and private sectors. Such an advanced digital solution would not only enhance transparency along the value chain but also improve both the quality of and confidence in recycled materials. Achieving circularity and reducing environmental impact are closely tied to the efficient management of material flows and life cycles. Within this context, Material Passports (MPs) are posited as a foundational element, particularly when integrated with a digital database. This integration is particularly beneficial for increasing the circularity of concrete, beginning with end-of-life concrete, a major contributor to global construction and demolition waste. MPs effectively transmit crucial information about the quality of recycled aggregates, thereby enabling their use in future construction projects. This study explores the feasibility of employing Radio Frequency Identification (RFID) technology as an MP, aiming to enhance sustainability in the concrete industry by improving transparency, traceability, and data reliability in the recycled concrete supply chain. Extensive laboratory tests carried out in three distinct experimental phases revealed that RFID tags exhibit remarkable resilience to mechanical stress typical in the supply chain and consistently maintain readability when embedded in concrete. The water content in concrete samples was identified as a significant factor influencing initial tag readability, although readability improved over time. Other factors, such as the type of aggregates, particle size distribution, and proximity to steel rebar, had minimal to modest impacts on tag performance. Additionally, the study confirmed that the readability of RFID tags remains robust at typical transport speeds, which highlights the potential of an RFID-based system in advancing supply chain management. This study provides a solid foundation for future research in this evolving area.

This study addresses a critical gap in circular construction practices by assessing the use of high-quality Recycled Coarse Aggregates (RCA) from end-of-life concrete on an industrial scale. Unlike previous studies, which predominantly relied on theoretical mix designs or laboratory-level experiments, this research focuses on real-world applicability, employing commercially produced RCA and conventional production methods in industrial settings to identify upscaling challenges. Advanced Dry Recovery technology is utilized to produce high-quality RCA for both ready-mix and prefab concrete production. To ensure practical relevance, the research examines three water-to-cement ratios for ready-mix concrete and three strength classes for prefab concrete, all prepared and cast in a commercial setting using standard industrial practices. The results show that by selecting the appropriate application for RCA, there is potential for concrete companies to produce mixes using 100% RCA that meet standard requirements in terms of fresh, mechanical, and durability properties without the need for extra treatments or specific mixing methods, particularly when the water absorption of RCA is less than 4%. Achieving optimal performance requires adjustments in the mix design, specifically by considering the effective water-to-cement ratio. Additionally, the study underscores the impact of the parent concrete's properties on the RCA quality. This research not only demonstrates the feasibility of employing RCA in industrial-scale concrete production along with its associated challenges but also highlights the potential for enhancing circularity in the construction industry through large-scale adoption of RCA, thereby contributing to sustainable and circular construction practices.

Lack of knowledge and tools hampers circular transition in the construction industry. This study analyzes the potential of a framework of circular indicators put forward by the Building Research Establishment Environmental Assessment Method (BREEAM-C) as an answer to the prevailing need of a metric for building circularity assessment to promote circular construction. A qualitative analysis approach is adopted, involving literature review, comparative case study and semi-structured interviews conducted for collecting expert opinions. An in-depth scrutiny of the BREEAM-C indicators revealed that they are rooted in circular principles, cover building circularity realizable through circular strategies, and have given due consideration to circularity in different impact areas, structural layers and life-cycle stages of buildings. Moreover, BREEAM-C indicators not only show capacity in identifying CE-related practices implemented, but also serve as benchmarks testifying that CE principles/strategies are incorporated in the design, construction, operation and management of the buildings. Despite having room for expansion, BREEAM-C has proven to be applicable and practical with potential for use in Taiwan as confirmed by expert opinions. Nevertheless, adaptation/localization is required to cater for different concerns with respect to climate and safety as well as local context and legislations.

Meeting the current demand for concrete requires not only mining tons of gravel and sand, but also burning large amounts of fossil fuel resources in cement kilning. Consequently, concrete recycling is crucial to achieving a material-efficient society, especially with the application of various categories of concrete and the goal of phasing out fossil fuels. A comparative life cycle assessment (LCA) is used to assess the engineering material footprint (EMF) and the fossil fuel material footprint (FMF) in closed-loop recycling of three types of concrete: siliceous concrete, limestone concrete, and lightweight aggregate concrete. This study aims to investigate the impact of (i) concrete categories, (ii) methods to model recycling, and (iii) using renewable energy sources on the material footprint in concrete recycling. The results highlight that the concrete recycling system can reduce 99% of the EMF and 66–93% of the FMF compared with the baseline system, in which concrete waste is landfilled. All three recycling modeling approaches indicate that concrete recycling can considerably reduce EMF and FMF compared with the baseline system, primarily resulting from the displacement of virgin raw materials. Using alternative diesels is more sensitive than adopting renewable electricity in reduction of the FMF in concrete recycling. Replacing diesel with electrolysis- and coal-based synthetic diesel for concrete recycling could even increase the FMF, while using biodiesel made from rapeseed and wood-based synthetic diesel can reduce 47–51% and 84–89% of the FMF, respectively, compared to the virgin diesel-based recycling system. Finally, we discussed the multifunctionality and rebound effects of recycling, and double-counting risk in material and energy accounting.

The bottom ash is increasingly used as a substitute aggregate material in road construction in China, and road salting is the major salt source in groundwater. Continuous rainfall releases soluble salts from the bottom ash subgrade into the surrounding soil and groundwater, resulting in potential hazards. Different methods were employed to simulate and collect runoff water during rainfall events, including batch leaching test, dynamic leaching test and constant head test, to assess environmental impact of bottom ash as road basement materials under continuous rainfall conditions. This study simulated the seepage of bottom ash backfill roads under different rainfall intensities, rainfall times, and rainfall pH values. A comprehensive sampling and laboratory testing program was undertaken to characterize the environmental impact of soluble salts from bottom ash. The obtained results reveal that the leaching concentrations of Cl⁻ and SO₄²⁻ exceed the limit specified in the class V standard of surface water, which are 2.06–2.17 times and 1.08–1.25 times, respectively. By examining the long-term environmental influence under the condition of continuous rainfall, the leaching of Cl⁻ mainly occurs in the early leaching stage, and the maximum leaching concentration reaches 19,700 mg/L. The release concentration of Cl⁻ begins to be lower than the class V standard of surface water when continuous rainfall approaches the total rainfall for 13 months. The cumulative release of Cl⁻ in the bottom ash is 2.8–5.4 mg/g. Both rainfall intensity and rain pH affect the release of Cl⁻. The obtained results derived from the constant head tests indicate that stagnant water caused by rainfall deteriorates the release of soluble salt into the groundwater in only 1 day, especially at the early stage of 12 h. This work provides some basic information about how to minimize damage to the surrounding environment caused by the leaching of salt in bottom ash.

The construction sector is the biggest driver of resource consumption and waste generation in Europe. The European Union (EU) is making efforts to move from its traditional linear resource and waste management system in the construction sector to a level of high circularity. Based on the theory of circular economy, a new paradigm called waste hierarchy was introduced in the EU Waste Framework Directive. This work uses the framework of the waste hierarchy to analyze the practice of construction and demolition waste (CDW) management in Europe. We explore the evolution of the waste hierarchy in Europe and how it compares with the circular economy. Then, based on the framework, we analyze the performance of CDW management in each EU member state. Innovative treatment methods of CDW, focusing on waste concrete, is investigated. This brings insight into optimizing and upgrading the CDW management in light of advanced technologies and steering the pathway for transitioning the EU towards a circular society.

To upcycle End-of-Life (EoL) concrete from demolished buildings, it is essential to efficiently identify the different materials that may contaminate it. The precise identification and classification of materials and contaminants are vital processes for in-line quality inspection of recycled concrete aggregates transported on a conveyor belt. In this study, a total of eight potential contaminants are considered as target contaminant materials in the streams made of coarse and fine aggregates resulting from the upcycling of EoL concrete. These contaminants degrade the quality of the aggregates even at low concentrations, so it is essential to identify the presence of such contaminants along with the main products of recycling which are recycled coarse aggregates (RCA) and recycled fine aggregates (RFA). An efficient method is proposed to identify and classify EoL concrete waste along with RCA and RFA in motion on conveyor belts via laser-induced breakdown spectroscopy (LIBS) coupled with a cluster-based identification algorithm. The model is verified with an accuracy of 0.97, a precision (weighted average) of 0.98, a recall (weighted average) of 0.97, and an F1-score (weighted average) of 0.98 for the validation set, under the optimal conditions. This study suggests that LIBS may be well suited for fast and in-line analysis of recycled concrete aggregates in industrial applications. This approach presents an innovative approach for the quality characterization of secondary materials produced from EoL concrete being transported on conveyor belts, and therefore can be of great value for the processing and high-end utilization of EoL concrete.

One of the main challenges of bottom ash reutilization is heavy metal and salts' leaching potential. The effect of wet treatment on chemical composition and leaching toxicity of bottom ash were investigated in this study to mitigate this leaching potential. Batch leaching and column leaching tests were first conducted to investigate the leaching behavior of the targeted elements (Cu, Zn, Ni, Cl-, and SO42-) from raw bottom ash and treated bottom ash after wet treatment. X-ray fluorescence analysis was used to analyze the chemical composition of bottom ash, and sequential extraction procedure (SEP) operation was done to analyze the chemical species of the heavy metals of bottom ash. The obtained results showed that the wet treatment applied on raw bottom ash posed a slight influence on the concentration of most of the major elements, 5.57-18.18%. SEP results showed the acid extractable Zn that accounted for 22.4-24.5% of the total Zn, and the iron manganese oxide bound Ni was 25.2-28.4%, and the organic matter bound Cu was 21.4-31.7%. The wet treatment reduced the concentrations and leachable amount of the targeted pollutants, which could decrease the leaching concentration of Cu by 77.1%, Zn by 34.7%, Ni by 100%, Cl by 30.1%, and SO42- by 51.4% based on the batch leaching tests under acid condition. The column leaching tests also suggest that wet treatment decreases Cu, Zn, and Cl- leaching concentration in bottom ash. This indicates that wet treatment improves the suitability of municipal solid waste incineration bottom ash for reutilization in China.