Use of recycled construction and demolition waste as substrate in constructed wetlands for the wastewater treatment of cheese production.

Recycled building debris has recently emerged as a suitable wetland infill substrate due to its low density, exceptional water absorption capabilities, and high porosity. This study investigated, for the first time, the use of construction demolition wastes (CDW), and rock processing residues (RPR) as substrate materials in vertical-horizontal flow hybrid constructed wetlands for the treatment of cheese production wastewater. Results showed that the use of both CDW as well as RPR, as substrate material, provided an equal or even better quality of treated wastewater compared to the conventional use of gravel as a substrate. High removal efficiencies were recorded for turbidity (CDW: 91-92%, RPR: 97%), solids (CDW: 85-88%, RPR: 96-97%), organic matter (CDW: 79-84%, RPR: 96-98%), and total phosphorus (CDW: 72-76%, RPR: 87%) for both examined recycled materials. During the experiment, different loadings rates (HLR) were tested: 25 mm d-1 and 37.5 mm d-1. Radiological measurements indicate that, their use did not cause toxic effects on the environment, as the amounts of radioactivity found in the effluent of the systems are not significant. Increasing the hydraulic loading rate appeared to have no negative effect on pollutant removal, as the systems and plants were fully acclimated and mature. This approach offers several advantages, including the use of readily available and abundant waste material, potential cost savings, and the environmental benefits of recycling CDW and RPR instead of disposing of them in landfills.

Effect of electrochemical treatment in mitigating OH- leaching from cement paste and its microscopic analysis at BSE imaging.

The present study concerns the electrochemical treatment between steel embedment and an external mesh in mitigating OH- ion leaching from the cement paste into external water, which was ensured by a microscopic observation on the surface of the cement paste specimen at the backscattered electron (BSE) image analysis and by measuring the leaching rate for OH- ions with time. The electrochemical properties for the treatment included 1000 mA/m2 current density and 4 weeks duration. As a result, the pH at the electrochemical treatment in the external water accounted for 9.32 in the pH, while the untreated specimen indicated 13.46, implying a quite reduction of OH- ion leaching to a water environment. The porosity on the surface was reduced to lower the access of external water, while the decomposition of C-S-H gel was lowered. Due to the precipitation of Ca(OH)2, a further solidification of hydration phases could lower OH- ion leaching.

Axial compression behavior of carbon fiber reinforced polymer confined partially encased recycled concrete columns.

Partially encased concrete (PEC) has better mechanical properties as a structure where steel and concrete work together. Due to the increasing amount of construction waste, recycled aggregate concrete (RAC) is being considered by more people. However, although RAC has more points, the performance is inferior to natural aggregate concrete (NAC). To narrow or address this gap, lightweight, high-strength and corrosion-resistant CFRP can be used, also protecting the steel flange of the PEC structure. Therefore, carbon fiber reinforced polymer (CFRP) confined partially encased recycled coarse aggregate concrete columns were studied in this paper. With respect to different slenderness ratios, recycled coarse aggregate(RCA) replacement ratios, and number of CFRP layers, the performance of the proposed CFRP restrained columns are reported. The RCA replacement ratio is analyzed to be limited negative impact on the bearing capacity, generally within 6%. As for the slenderness ratio, the bearing capacity increased with it. However, wrapping CFRP significantly increased the bearing capacity. Considering the arch factor, a simple formula for calculating the ultimate strength of CFRP-confined partially encased RAC columns is developed based on EC4 and GB50017-2017. By comparison with the experimental values, the error is within 10%.

A formulation for asphalt concrete air void during service life by adopting a hybrid evolutionary polynomial regression and multi-gene genetic programming.

Bitumen, aggregate, and air void (VA) are the three primary ingredients of asphalt concrete. VA changes over time as a function of four factors: traffic loads and repetitions, environmental regimes, compaction, and asphalt mix composition. Due to the high as-constructed VA content of the material, it is expected that VA will reduce over time, causing rutting during initial traffic periods. Eventually, the material will undergo shear flow when it reaches its densest state with optimum aggregate interlock or refusal VA content. Therefore, to ensure the quality of construction, VA in asphalt mixture need to be modeled throughout the service life. This study aims to implement a hybrid evolutionary polynomial regression (EPR) combined with a teaching-learning based optimization (TLBO) algorithm and multi-gene genetic programming (MGGP) to predict the VA percentage of asphalt mixture during the service life. For this purpose, 324 data records of VA were collected from the literature. The variables selected as inputs were original as-constructed VA, VA orig (%); mean annual air temperature, MAAT (°F); original viscosity at 77 °F, η o r i g , 77 (Mega-Poises); and time (months). EPR-TLBO was found to be superior to MGGP and existing empirical models due to the interquartile ranges of absolute error boxes equal to 0.67%. EPR-TLBO had an R2 value of more than 0.90 in both the training and testing phases, and only less than 20% of the records were predicted utilizing this model with more than 20% deviation from the observed values. As determined by the sensitivity analysis, η o r i g , 77 is the most significant of the four input variables, while time is the least one. A parametric study showed that regardless of MAAT , η o r i g , 77 , of 0.3 Mega-Poises, and VA orig above 6% can be ideal for improving the pavement service life. It was also witnessed that with an increase of MAAT from 37 to 75 °F, the serviceability of asphalt concrete takes 15 months less on average.

PAAD: Panelization algorithm for architectural designs.

Due to the competitive nature of the construction industry, the efficiency of requirement analysis is important in enhancing client satisfaction and a company's reputation. For example, determining the optimal configuration of panels (generally called panelization) that form the structure of a building is one aspect of cost estimation. However, existing methods typically rely on rule-based approaches that may lead to suboptimal material usage, particularly in complex designs featuring angled walls and openings. Such inefficiency can increase costs and environmental impact due to unnecessary material waste. To address these challenges, this research proposes a Panelization Algorithm for Architectural Designs, referred to as PAAD, which utilizes a genetic evolutionary strategy built on the 2D bin packing problem. This method is designed to balance between strict adherence to manufacturing constraints and the objective of optimizing material usage. PAAD starts with multiple potential solutions within the predefined problem space, facilitating dynamic exploration of panel configurations. It approaches structural rules as flexible constraints, making necessary corrections in post-processing, and through iterative developments, the algorithm refines panel sets to minimize material use. The methodology is validated through an analysis against an industry implementation and expert-derived solutions, highlighting PAAD's ability to surpass existing results and reduce the need for manual corrections. Additionally, to motivate future research, a synthetic data generator, the architectural drawing encodings used, and a preliminary interface are also introduced. This not only highlights the algorithm's practical applicability but also encourages its use in real-world scenarios.

Neutralization of ricin toxin on building interior surfaces using liquid decontaminants.

Ricin is a highly toxic protein, capable of inhibiting protein synthesis within cells, and is produced from the beans of the Ricinus communis (castor bean) plant. Numerous recent incidents involving ricin have occurred, many in the form of mailed letters resulting in both building and mail sorting facility contamination. The goal of this study was to assess the decontamination efficacy of several commercial off-the-shelf (COTS) cleaners and decontaminants (solutions of sodium hypochlorite [bleach], quaternary ammonium, sodium percarbonate, peracetic acid, and hydrogen peroxide) against a crude preparation of ricin toxin. The ricin was inoculated onto four common building materials (pine wood, drywall joint tape, countertop laminate, and industrial carpet), and the decontaminants were applied to the test coupons using a handheld sprayer. Decontamination efficacy was quantified using an in-vitro cytotoxicity assay to measure the quantity of bioactive ricin toxin extracted from test coupons as compared to the corresponding positive controls (not sprayed with decontaminant). Results showed that decontamination efficacy varied by decontaminant and substrate material, and that efficacy generally improved as the number of spray applications or contact time increased. The solutions of 0.45% peracetic acid and the 20,000-parts per million (ppm) sodium hypochlorite provided the overall best decontamination efficacy. The 0.45% peracetic acid solution achieved 97.8 to 99.8% reduction with a 30-min contact time.

Artificial neural network, machine learning modelling of compressive strength of recycled coarse aggregate based self-compacting concrete.

This research study aims to understand the application of Artificial Neural Networks (ANNs) to forecast the Self-Compacting Recycled Coarse Aggregate Concrete (SCRCAC) compressive strength. From different literature, 602 available data sets from SCRCAC mix designs are collected, and the data are rearranged, reconstructed, trained and tested for the ANN model development. The models were established using seven input variables: the mass of cementitious content, water, natural coarse aggregate content, natural fine aggregate content, recycled coarse aggregate content, chemical admixture and mineral admixture used in the SCRCAC mix designs. Two normalization techniques are used for data normalization to visualize the data distribution. For each normalization technique, three transfer functions are used for modelling. In total, six different types of models were run in MATLAB and used to estimate the 28th day SCRCAC compressive strength. Normalization technique 2 performs better than 1 and TANSING is the best transfer function. The best k-fold cross-validation fold is k = 7. The coefficient of determination for predicted and actual compressive strength is 0.78 for training and 0.86 for testing. The impact of the number of neurons and layers on the model was performed. Inputs from standards are used to forecast the 28th day compressive strength. Apart from ANN, Machine Learning (ML) techniques like random forest, extra trees, extreme boosting and light gradient boosting techniques are adopted to predict the 28th day compressive strength of SCRCAC. Compared to ML, ANN prediction shows better results in terms of sensitive analysis. The study also extended to determine 28th day compressive strength from experimental work and compared it with 28th day compressive strength from ANN best model. Standard and ANN mix designs have similar fresh and hardened properties. The average compressive strength from ANN model and experimental results are 39.067 and 38.36 MPa, respectively with correlation coefficient is 1. It appears that ANN can validly predict the compressive strength of concrete.

Bond performance between hybrid fiber-reinforced concrete and BFRP bars under freeze-thaw cycle.

This study applied the pull-out test to examine the influence of freeze-thaw cycles and hybrid fiber incorporation on the bond performance between BFRP bars and hybrid fiber-reinforced concrete. The bond-slip curves were fitted by the existing bond-slip constitutive model, and then the bond strength was predicted by a BP neural network. The results indicated that the failure mode changed from pull-out to splitting for the BFRP bar ordinary concrete specimens when the freeze-thaw cycles exceeded 50, while only pull-out failure occurred for all BFRP bar hybrid fiber-reinforced concrete specimens. An increasing trend was shown on the peak slip, but a decreasing trend was shown on the bond stiffness and bond strength when freeze-thaw cycles increased. The bond strength could be increased significantly by the incorporation of basalt fiber (BF) and cellulose fiber (CF) under the same freezing and thawing conditions as compared to concrete specimens without fibers. The Malvar model and the Continuous Curve model performed best in fitting the ascending and descending sections of the bond-slip curves, respectively. The BP neural network also accurately predicted the bond strength, with relative errors of predicted bond strengths ranging from 3.75% to 13.7%, and 86% of them being less than 10%.

Experimental study on the effect of different cement content on the improvement of dynamic characteristics of seismic-prone poor soil.

The improvement of sandy soils with poor seismic properties to modify their dynamic characteristics is of great importance in seismic design for engineering sites. In this study, a series of dynamic tests on sandy soils sandy soils with poor seismic conditions were conducted using the GCTS resonant column system to investigate the improvements effects of different cement contents on dynamic characteristic parameters. The research findings are as follows: The cement content has certain influences on the dynamic shear modulus, dynamic shear modulus ratio, the maximum dynamic shear modulus, and the damping ratio of sandy soils with poor seismic properties. Among them, the influence on dynamic shear modulus is limited, while the damping ratio is significantly affected. The addition of cement to seismic-poor sandy soils significantly enhances their dynamic characteristics. The most noticeable improvement is observed when the cement content is 8%. Through curve fitting analysis, a relationship equation is established between the maximum dynamic shear modulus and the cement content, and the relevant parameters are provided. A comparative test between the improved soils and the remolded soils reveals that the addition of cement significantly improves the seismic performance of the poor soils. The recommended values for the range of variation of the dynamic shear modulus ratio and damping ratio are provided, considering the effect of improvement. These research findings provide reference guidelines for seismic design and engineering sites.

Resource utilization of drinking water treatment aluminum sludge in green cementing materials: Hydration characteristics and hydration kinetics.

As a byproduct of water treatment, drinking water treatment aluminum sludge (DWTAS) has challenges related to imperfect treatment and disposal, which has caused potential harm to human health and the environment. In this paper, heat treatment DWTAS as a supplement cementitious material was used to prepare a green cementing material. The results show that the 800°C is considered as the optimum heat treatment temperature for DWTAS. DWTAS-800°C is fully activated after thermal decomposition to form incompletely crystallized highly active γ-Al2O3 and active SiO2. The addition of DWTAS promoted the formation of ettringite and C-(A)-S-H gel, which could make up for the low early compressive strength of cementing materials to a certain extent. When cured for 90 days, the compressive strength of the mortar with 30% DWTAS-800°C reached 44.86 MPa. The dynamic process was well simulated by Krstulovic-Dabic hydration kinetics model. This study provided a methodology for the fabrication of environmentally friendly and cost-effective compound cementitious materials and proposed a "waste-to-resource" strategy for the sustainable management of typical solid wastes.

Potential environmental impact of mycelium composites on African communities.

The ecological and economic benefits of mycelium composites offer a promising opportunity for supporting sustainable development in Africa. This study focuses on assessing the environmental impact of mycelium composites for building and construction (MCBs) by conducting a life cycle assessment (LCA) in the context of Africa. It is demonstrated that the potential environmental impact of MCBs is substantially influenced by the use and source of electrical power for autoclaves, incubators, and ovens, making the culturing and post-processing phases the major environmental hotspots. The impact of MCB production is also relative to the energy mix of specific countries, being higher in countries that rely on fossil fuel energy (e.g., South Africa) and lower in those that rely more on renewable sources (e.g., Democratic Republic of the Congo, DRC). Furthermore, the impact of MCB production is found to be sensitive to travel distance, suggesting that situating production facilities closer to agricultural, agro-industrial, and/or forestry waste sources could be more beneficial than interregional sourcing, for example. It is also demonstrated that MCBs have the potential to be a more ecologically sustainable alternative to some conventional construction materials (e.g., concrete) over an entire life cycle. Based on the insights obtained from this LCA, some recommendations have been proposed to address potential environmental repercussions pre-emptively and proactively: this is particularly important for nations, mainly in the Global South, that exhibit low resilience to climate change due to limited economic resources. Furthermore, with the rapid expansion of mycelium composite technology, there is a need to increase awareness about its potential environmental impact and, ultimately, to mitigate its potential contribution to pressing environmental concerns (e.g., global warming and climate change). Consequently, this study also adds to the existing body of literature on LCA studies, delineating key factors for consideration in future LCA studies and providing guidance for the sustainable establishment and expansion of this technology.

Investigation on damage evolution mechanism of various FRP strengthened concrete subjected to chemical-freeze-thaw coupling erosion.

The corrosion resistance of FRP-reinforced ordinary concrete members under the combined action of harsh environments (i.e., alkaline or acidic solutions, salt solutions) and freeze-thaw cycles is still unclear. To study the mechanical and apparent deterioration of carbon/basalt/glass/aramid fiber cloth reinforced concrete under chemical and freeze-thaw coupling. Plain concrete blocks and FRP-bonded concrete blocks were fabricated. The tensile properties of the FRP sheet and epoxy resin sheet before and after chemical freezing, the compressive strength of the FRP reinforced test block, and the bending capacity of the prismatic test block pasted with FRP on the prefabricated crack side were tested. The deterioration mechanism of the test block was analyzed through the change of surface photos. Based on the experimental data, the Lam-Teng constitutive model of concrete reinforced by alkali-freeze coupling FRP is modified. The results indicate that, in terms of apparent properties, with the increase in the duration of chemical freeze-thaw erosion, the surface of epoxy resin sheets exhibits an increase in pores, along with the emergence of small cracks and wrinkles. The texture of FRP sheets becomes blurred, and cracks and wrinkles appear on the surface. In terms of failure modes, as the number of chemical coupling erosion cycles increases, the location of failure in epoxy resin sheets becomes uncertain, and the failure plane tilts towards the direction of the applied load. The failure mode of FRP sheets remains unchanged. However, the bonding strength between FRP sheets and concrete decreases, resulting in a weakened reinforcement effect. In terms of mechanical properties, FRP sheets undergo the most severe degradation in the coupled environment of acid freeze-thaw cycles. Among them, GFRP experiences the largest degradation in tensile strength, reaching up to 30.17%. In terms of tensile performance, the sheets rank from highest to lowest as follows: CFRP, BFRP, AFRP, and GFRP.As the duration of chemical freeze-coupled erosion increases, the loss rate of compressive strength for specimens bonded with CFRP is the smallest (9.62% in salt freeze-thaw environment), while the loss rate of bearing capacity is higher for specimens reinforced with GFRP (33.8% in acid freeze-thaw environment). In contrast, the loss rate of bearing capacity is lower for specimens reinforced with CFRP (13.6% in salt freeze-thaw environment), but still higher for specimens reinforced with GFRP (25.8% in acid freeze-thaw environment).

Improved U-net network asphalt pavement crack detection method.

Road crack detection is one of the important parts of road safety detection. Aiming at the problems such as weak segmentation effect of basic U-Net on pavement crack, insufficient precision of crack contour segmentation, difficult to identify narrow crack and low segmentation accuracy, this paper proposes an improved U-net network pavement crack segmentation method. VGG16 and Up_Conv (Upsampling Convolution) modules are introduced as backbone network and feature enhancement network respectively, and the more abstract features in the image are extracted by using the Block depth separable convolution blocks, and the multi-scale features are captured and enhanced by higher level semantic information to improve the recognition accuracy of narrow cracks in the road surface. The improved network embedded the Ca(Channel Attention) attention mechanism in U-net's jump connection to enhance the crack portion to suppress background noise. At the same time, DG_Conv(Depthwise GSConv Convolution) module and UnetUp(Unet Upsampling) module are added in the decoding part to extract richer features through more convolutional layers in the network, so that the model pays more attention to the detailed part of the crack, so the segmentation accuracy can be improved. In order to verify the model's ability to detect cracks in complex backgrounds, experiments were carried out on CFD and Deepcrack datasets. The experimental results show that compared with the traditional U-net network F1-score and mIoU have increased by 13.6% and 9.9% respectively. Superior to advanced models such as U-net, Segnet and Linknet in accuracy and generalization ability, the improved model provides a new method for asphalt pavement crack detection. The model is more conducive to practical application and ground deployment, and can be applied in road maintenance projects.

Study on triaxial compression performance and damage characteristics of fiber-reinforced ecological matrix cementing gangue gypsum fill material.

Polypropylene fiber was equally mixed into alkali-activated slag fly ash geopolymer in order to ensure the filling effect of mine goaf and improve the stability of cemented gangue paste filling material with ecological matrix. Triaxial compression tests were then conducted under various conditions. The mechanical properties and damage characteristics of composite paste filling materials are studied, and the damage evolution model of paste filling materials under triaxial compression is established, based on the deviatoric stress-strain curve generated by the progressive failure behavior of samples. Internal physical and chemical mechanisms of the evolution of structure and characteristics are elucidated and comprehended via the use of SEM-EDS and XRD micro-techniques. The results show that the fiber can effectively improve the ultimate strength and the corresponding effective stress strength index of the sample within the scope of the experimental study. The best strengthening effect is achieved when the amount of NaOH is 3% of the mass of the solid material, the amount of fiber is 5‰ of the mass of the solid material, and the length of the fiber is about 12 mm. The action mode of the fiber in the sample is mainly divided into single-grip anchoring and three-dimensional mesh traction. As the crack initiates and develops, connection occurs in the matrix, where the fiber has an obvious interference and retardation effect on the crack propagation, thereby transforming the brittle failure into a ductile failure and consequently improving the fracture properties of the ecological cementitious coal gangue matrix. The theoretical damage evolution model of a segmented filling body is constructed by taking the initial compaction stage end point as the critical point, and the curve of the damage evolution model of the specimen under different conditions is obtained. The theoretical model is verified by the results from the triaxial compression test. We concluded that the experimental curve is in good agreement with the theoretical curve. Therefore, the established theoretical model has a certain reference value for the analysis and evaluation of the mechanical properties of paste filling materials. The research results can improve the utilization rate of solid waste resources.

Contact with Wet Cement-A Preventable Cause of Chemical Burn: Case Report and Discussion.

GENERAL PURPOSE: To review the management of a patient with a chemical burn from wet cement. TARGET AUDIENCE: This continuing education activity is intended for physicians, physician assistants, nurse practitioners, and registered nurses with an interest in skin and wound care. LEARNING OBJECTIVES/OUTCOMES: After participating in this educational activity, the participant will:1. Recognize the clinical presentation of a patient with a chemical burn from contact with wet cement.2. Describe features related to the pathophysiology of alkali burns from wet cement.3. Select the proper decontamination procedure after exposure to wet cement.4. Identify steps in the treatment of a patient with a chemical burn from contact with wet cement.

Alkali burn from wet cement is an often unrecognized and completely preventable chemical injury. The prevalence of cement burns is likely underestimated because of a lack of awareness and knowledge among both individuals who work with cement and healthcare providers. Chemical injuries have important differences compared with thermal burns: they are usually produced by longer exposure to noxious agents as opposed to short-term exposure that is quickly stopped. As a result, first aid approaches are different. Chemical burns from cement can be avoided with adequate skin and eye protection as well as immediate first aid if contact occurs. Manufacturers of bagged cement place warning notices on packaging, but these can be small and go unnoticed by consumers. Construction workers and amateur do-it-yourselfers should avoid direct contact with cement for any prolonged amount of time. Watertight boots, gloves, and clothing will prevent contact, and any accidental splash on exposed skin should be immediately washed away. Education and awareness of the consequences of cement burns are the best prevention.

Roadmap to a net-zero carbon cement sector: Strategies, innovations and policy imperatives.

The cement industry plays a significant role in global carbon emissions, underscoring the urgent need for measures to transition it toward a net-zero carbon footprint. This paper presents a detailed plan to this end, examining the current state of the cement sector, its carbon output, and the imperative for emission reduction. It delves into various low-CO2 technologies and emerging innovations such as alkali-activated cements, calcium looping, electrification, and bio-inspired materials. Economic and policy factors, including cost assessments and governmental regulations, are considered alongside challenges and potential solutions. Concluding with future prospects, the paper offers recommendations for policymakers, industry players, and researchers, highlighting the roadmap's critical role in achieving a carbon-neutral cement sector.

Development of an environmentally foamed concrete incorporating red mud.

In this work, an efficient utilization method for red mud (RM) is provided through recycling RM as a mineral admixture for the preparation of foamed concrete (FC). Specifically, FC with different RM contents was prepared and investigated in terms of workability, mechanical properties, and hydration products. Results show that adding RM can significantly shorten the setting time, while it inevitably weakens the mechanical properties and fluidity of FC. However, the compressive strength of FC can still meet the strength predicted by the specification requirements when the RM replaces cement with 60% content (3d > 1.6 MPa). Most importantly, the heavy metals leaching from RM-based FC under the action of rain is still unclear, so a device for simulating stormwater runoff was designed to test the heavy metal leaching risk of RM-based FC. The findings indicate that the solidification of cement and the high basicity of the matrix can effectively reduce the leaching risk of heavy metals from RM in FC. Although the pore structure analysis demonstrates that the porosity and connected pores of FC will be deteriorated as RM concentration increases. The results are of great significance for the recycling of waste and the sustainable development of building materials.

Cement production and CO2 emission cycles in the USA: evidence from MS-ARDL and MS-VARDL causality methods with century-long data.

The cement industry is among the top three polluters among all industries and the examination of the nonlinear and cointegration dynamics between cement production and CO2 emissions has not been explored. Focusing on this research gap, the study employs a novel Markov-switching autoregressive distributed lag (MS-ARDL) model and its generalization to vector error correction, the MS-VARDL model, for regime-dependent causality testing. The new method allows the determination of nonlinear long-run and short-run relations, regime duration, and cement-induced-CO2 emission cycles in the USA for a historically long dataset covering 1900-2021. Empirical findings point to nonlinearity in all series and nonlinear cointegration between cement production and cement-induced CO2 emissions. The phases of regimes coincide closely with NBER's official economic cycles for the USA. The second regime, characterized by expansions, lasts twice as long relative to the first, the contractionary regime, which contains severe economic recessions, as well as economic crises, the 1929 Great Depression, the 1973 Oil Crisis, the 2009 Great Recession, and the COVID-19 Shutdown and Wars, including WWI and II. In both regimes, the adverse effects of cement production on CO2 emissions cannot be rejected with varying degrees both in the long and the short run. Markov regime-switching vector autoregressive distributed lag (MS-VARDL) causality tests confirm unidirectional causality from cement production to CO2 emissions in both regimes. The traditional Granger causality test produces an over-acceptance of causality in a discussed set of cases. Industry-level policy recommendations include investments to help with the shift to green kiln technologies and energy efficiency. National-level policies on renewable energy and carbon capture are also vital considering the energy consumption of cement production.

Technological advances and challenges of reclaimed asphalt pavement (RAP) application in road engineering-a bibliometric analysis from 2000 to 2022.

Reclaimed asphalt pavement (RAP) is a valuable material that can be recycled and reused in road engineering to reduce environmental impact, resource utilization, and economic costs. However, the application of RAP in road engineering presents both opportunities and challenges. This study visually analyzes the knowledge background, research status, and latest knowledge structure of literature related to RAP using scientific metric methods such as VOSviewer and Citespace. The Web of Science (WoS) core collection database identified 2963 research publications from 2000 to 2022. Collaborative networks between highly cited references, journals, authors, academic institutions, countries, and funding organizations are analyzed in this study, along with a co-occurrence analysis of keywords for the RAP research publications. Results showed that the USA has long been a leader in RAP research, China surpassed the USA in annual publication output in 2019, increasing from 2 publications in 2002 to 177 publications in 2022, and has made significant investments in technological aspects. Chang'an University ranked first in total publication output (131 publications, 4.4%). Current major research themes include road performance, recycling technology, regeneration mechanisms, and the life cycle assessment of RAP. In addition, based on cluster analysis of keywords, text content analysis, and SWOT analysis, this study also discusses RAP's challenges and future development directions in road engineering. These findings provide scholars with valuable information to gain insight into technological advances and challenges in the field of RAP.