Challenges in current construction and demolition waste recycling: A China study

An evaluation model for city-scale construction and demolition waste management effectiveness: A case study in China

The growing generation of construction and demolition waste (CDW) has emerged as a prominent challenge on global environmental agendas. However, the effectiveness of CDW management (CDWM) strategies varies among cities. Existing literature predominantly evaluates the effectiveness of CDWM at the project level, offering a localized perspective that fails to capture a city's comprehensive CDWM profile. This localized focus has certain limitations. To fill this gap in city-scale evaluations, this study introduces a novel model for assessing CDWM effectiveness at the municipal level. An empirical investigation was conducted across 11 cities within the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) to operationalize this model. The model defines five distinct levels of CDWM effectiveness. Findings indicate that Hong Kong consistently achieves the highest level (level I), while the majority of cities fall within levels III and IV. This pattern suggests that CDWM effectiveness in the GBA is moderately developed, with uneven progress in CDW management outcomes and supporting systems. Essentially, there is a lack of synchronous development of CDWM results and guarantee systems. The proposed evaluation model enriches existing CDWM research field and offers a framework that may inform future studies in other countries.

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.

Enhancing the Mechanical and Durability Properties of Fully Recycled Aggregate Concrete Using Carbonated Recycled Fine Aggregates

The global construction industry is increasingly utilizing concrete prepared from recycled aggregate as a substitute for natural aggregate. However, the subpar performance of recycled fine aggregate (RFA) has resulted in its underutilization, particularly in the structural concrete exposed to challenging environments, including those involving chlorine salts and freeze-thaw climates. This study aimed to enhance the performance of RFA as a substitute for river sand in concrete as well as fulfill the present demand for fine aggregates in the construction sector by utilizing accelerated carbonation treatment to create fully recycled aggregate concrete (FRAC) composed of 100% recycled coarse and fine aggregates. The impacts of incorporating carbonated recycled fine aggregate (C-RFA) at various replacement rates (0%, 25%, 50%, 75%, and 100%) on the mechanical and durability properties of FRAC were investigated. The results showed that the physical properties of C-RFA, including apparent density, water absorption, and crushing value, were enhanced compared to that of RFA. The compressive strength of C-RFC100 was 19.8% higher than that of C-RFC0, while the water absorption decreased by 14.6%. In a comparison of C-RFC0 and C-RFC100, the chloride permeability coefficients showed a 50% decrease, and the frost resistance increased by 27.6%. According to the findings, the mechanical and durability properties, the interfacial transition zones (ITZs), and micro-cracks of the C-RFC were considerably enhanced with an increased C-RFA content.

Assessing the policy benefits of constructing "Zero-waste Cities" in China: From the perspective of hazardous waste lifecycle management

Based on China's quasi-natural experiment of constructing "Zero-waste Cities", this study assessed its policy benefits on hazardous waste lifecycle management. Utilizing the theory of difference-in-differences analysis, the study quantifies the net benefits of the policy in 10 pilot cities using an average treatment effect formula, and the results indicate a reduction of 162,900 tons/year in waste generation, an increase of 2.3 % in utilization and disposal rate, and a decrease of 28,200 tons/year in end-of-pipe storage. By constructing a regression model and employing robustness tests such as changing control variables, substituting the explained variable, re-matching control groups, and random assignment of pilot sites, the study confirms that the significant policy benefits primarily lie in source reduction, with a reduction intensity of approximately 1.73 tons/100 million yuan of industrial GDP. Additionally, by applying the mixed-effects model and mediation-analysis model, the study finds that the policy benefit of source reduction exhibits a lag effect, and during the pilot period, the main approach to achieving the benefit was through enhancing cleaner production in companies rather than adjusting industrial structures in cites.

Application of Bayesian structural equation modeling in construction and demolition waste management studies: Development of an extended theory of planned behavior

Sustainable construction and demolition waste management relies heavily on the attitudes and actions of its constituents; nevertheless, deep analysis for introducing the best estimator is rarely attained. The main objective of this study is to perform a comparison analysis among different approaches of Structural Equation Modeling (SEM) in Construction and Demolition Waste Management (C&DWM) modeling based on an Extended Theory of Planned Behaviour (Extended TPB). The introduced research model includes twelve latent variables, six independent variables, one mediator, three control variables, and one dependent variable. Maximum likelihood (ML), partial least square (PLS), and Bayesian estimators were considered in this study. The output of SEM with the Bayesian estimator was 85.8%, and among effectiveness of six main variables on C&DWM Behavioral (Depenmalaydent variables), five of them have significant relations. Meanwhile, the variation based on SEM with ML estimator was equal to 78.2%, and four correlations with dependent variable have significant relationship. At the conclusion, the R-square of SEM with the PLS estimator was equivalent to 73.4% and three correlations with the dependent variable had significant relationships. At the same time, the values of the three statistical indices include root mean square error (RMSE), mean absolute percentage error (MPE), and mean absolute error (MSE) with involving Bayesian estimator are lower than both ML and PLS estimators. Therefore, compared to both PLS and ML, the predicted values of the Bayesian estimator are closer to the observed values. The lower values of MPE, RMSE, and MSE and the higher values of R-square will generate better goodness of fit for SEM with a Bayesian estimator. Moreover, the SEM with a Bayesian estimator revealed better data fit than both the PLS and ML estimators. The pattern shows that the relationship between research variables can change with different estimators. Hence, researchers using the SEM technique must carefully consider the primary estimator for their data analysis. The precaution is necessary because higher error means different regression coefficients in the research model.

Automatic identification of illegal construction and demolition waste landfills: A computer vision approach

Dozens of landslide accidents are reported at construction and demolition waste (CDW) landfills worldwide every year. Those accidents could be avoided via timely inspection in which the identification of illegal CDW landfills at a large scale plays a critical role. Traditional field surveys are time-consuming, labor-intensive, which is not effective in large-scale detection of landfills. To address this issue, a methodology is proposed in this study for the automatic identification of CDW landfills in large-scale areas by utilizing semantic segmentation of remote sensing imagery. Deep learning is employed to achieve automatic identification and a case study is conducted to showcase the models. The results shown that: (1) The model proposed in this study can effectively identify CDW landfills, with an accuracy of 96.30 % and an IoU of 74.60 %. (2) DeepLabV3+ demonstrated superior performance over Pspnet and HRNet, though HRNet approached DeepLabV3+ in performance with appropriate optimizations. (3) Case study results indicate the potential existence of 52 CDW landfills in Shenzhen, includng 4 official landfills and 48 suspected illegal CDW landfills, mainly in Longhua, Guangming, and Baoan districts. The method proposed in this study provides an effective approache to identify large-scale illegal CDW landfills and has great significance for supervising CDW landfills.

Identifying and prioritizing sustainability indicators for China's assessing demolition waste management using modified Delphi-analytic hierarchy process method

Addressing the sustainability issues arising from construction and demolition waste management (DWM) has gained little traction due to the lack of incentives, stringent regulations, and systematic guidance. This study aims to empower systematic decision-making concerning DWM alternative selection by developing a sustainability assessment framework by coupling a modified Delphi method with the multicriteria decision analysis technique. First, the study identifies a comprehensive inventory of indicators across three dimensions of sustainability in the context of DWM. Next, the study combines a modified Delphi method with the analytic hierarchy process to validate and prioritize the selected sustainability indicators. For the first time, insights regarding the DWM sustainability indicators from China's construction industry practitioners' perspectives are elicited using a mixed method comprising online semistructured interviews and two rounds of questionnaire surveys. Experts participating in the research are mostly based in Guangzhou and Shenzhen, where local governments exhaust all efforts in promoting carbon-neutral and sustainable development. The findings reveal that eight sustainability indicators were regarded as the determinants for the sustainability performance of DWM, with the global warming potential (32%), energy efficiency (16.1%) and land use (13.5%) receiving the highest preference scores (weights) based on the experts' judgment. Notably, the economic factors like the total cost (6.54%) appeared not highly prioritized by the local experts as typically did in the previous studies from developing countries.

Study on Capillary Water Absorption of Waterborne-Polyurethane-Modified Recycled Coarse Aggregate Concrete

The reuse of construction and demolition waste as a substitute for natural coarse aggregate in the production of recycled concrete has been widely used. In order to study the capillary water absorption performance of waterborne-polyurethane-modified recycled aggregate concrete (WPUMRC), the effects of different curing systems, polymer-cement ratios, and waterborne polyurethane addition methods on the cumulative water absorption and the rate of capillary water absorption of WPUMRC were analyzed, and through MIP tests, the micro modification mechanism of waterborne polyurethane in recycled concrete was analyzed. The results indicate that the optimal curing system for both DC (waterborne polyurethane is added separately from water) and HC (waterborne polyurethane is mixed with some effective water and then added) is the 14 d standard curing-14 d indoor natural drying curing system. Waterborne polyurethane can fill the pores and micro-cracks inside WPUMRC or interweave with the hydration products of cement to form a spatial network structure, reducing the porosity, and thereby improving the capillary water absorption performance of WPUMRC. Based on the MIP test results, the grey correlation method was used to establish the relationship between capillary water absorption and the pore structure of WPUMRC under the optimal curing system. In addition, the prediction model of capillary water absorption in recycled concrete was established according to the test results, which can be used to predict WPUMRC's capillary water absorption performance.

Stakeholders' purchase intention of products with recycled content: a combination of SEM and BPNN approach

The rapid urban renewal progress has generated a large amount of construction and demolition (C&D) waste in China. According to the concept of circular economy (CE), producing products with recycled content (PwRC) is an effective solution to achieve sustainable C&D waste management. However, the low market acceptance of PwRC affects stakeholders' purchase intention, which hinders the development of the PwRC industry. In order to clarify the stakeholders' purchase intention and investigate the influencing mechanism of stakeholders' purchase intention, a novel method which combines structural equation modeling (SEM) with a back-propagation neural network (BPNN) is proposed. The method makes full use of the causal analysis ability of SEM and the nonlinear characteristics of BPNN to simulate and to verify the path of product cues, perceived value, and behavioral intention of stakeholders. The results reveal that the brand and materials of PwRC can affect stakeholders' perceived value, and in turn, affect their purchase intention. Focus on the brand and materials of PwRC will help recycled product manufacturers and governments to promote stakeholders' purchase intention and the development of the C&D waste recycled products market.

Strategies to promote construction and demolition waste management in the context of local dynamics

Achieving a broad analysis of construction and demolition waste (CDW) management without considering local scale dynamics, and its detailed characteristics, is a constraint that has made it challenging to optimally engage in an integrated assessment of the circular economy principles in the construction sector. In this sense, this research demonstrates that investing in local strategies is important, involving municipalities and micro and small construction companies. Firstly, the results reveal the importance of having controlled sites, under local responsibility, for the preliminary storage of CDW, creating in waste producers the habit of separating waste onsite, reducing costs and limitations for municipalities. Secondly, frequent supervision actions at construction sites are also important at this scale, as they facilitate progress in terms of encouraging compliance with mandatory legal procedures and good practices for CDW management. But it is easier to improve practice through direct onsite procedures than it is with bureaucratic legal requirements alone. Thirdly, procedural control, implemented by municipal technicians in conjunction with other strategies, also helps to promote CDW management, this being associated with processes of public and private construction works subjected to license or prior control, in opposition to what has been accomplished so far. But the research also demonstrated that regular awareness, training, and supervision actions might increase the likelihood of improvements in behaviour on the local scale, in the sense that stakeholders acquire new habits, which, over time, might lead to better results locally and, as a consequence, influence other scales of intervention.

Technology adoption path of construction and demolition waste recycling under governmental subsidy: a theoretical model

To achieve sustainable development, waste recycling is regarded as an ideal method to dispose of construction and demolition (C&D) waste. The economy is seen as the priority factor influencing recycling technology adoption. Hence, the subsidy is generally used to cross the economic barrier. To illustrate the recycling technology adoption path under governmental subsidy, this paper constructs a non-cooperative game model to investigate the impact of governmental subsidy on the C&D waste recycling technology adoption. By taking adoption profit, opportunity cost, and initial adoption marginal cost into consideration, the best time to adopt recycling technology and adoption behavior is discussed in detail in four scenarios. Results show that the governmental subsidy has a positive impact on C&D waste recycling technology adoption, and the subsidy could advance the adoption time of recyclers. If the subsidy proportion can reach 70% of the cost, recyclers will adopt recycling technology at the initial time. The results could contribute to a deeper understanding of C&D waste management by promoting the development of C&D waste recycling projects and also provide references to governments.

Determinants of contractor's construction and demolition waste recycling intention in China: Integrating theory of planned behavior and norm activation model

The abundant generation of construction and demolition waste (CDW) poses a threat to the sustainable development in China and recycling plays a vital role in complying with circular economy zero-waste goal. In this study, we first investigate the determinants of contractor's intention to recycle CDW by establishing an integrative model of the theory of planned behavior (TPB) and the norm activation model (NAM) with rational and moral considerations. Based on the questionnaire data of 210 valid responses, structural equation modeling is employed to test the proposed hypotheses and analyze the integrative structural model. The results show that the integrative model with adequate reliability and validity fits the empirical data well and the explanation power is superior to that of initial TPB model and NAM model, demonstrating the appropriateness of merging TPB and NAM in the area of CDW recycling research. Moreover, it is found that personal norms are the most critical determinant enhancing the CDW recycling intention, followed by perceived behavioral control. Although subjective norms fail to directly affect the CDW recycling intention, they can significantly strengthen personal norms and perceived behavioral control. These findings provide useful insights for government to develop effective management strategies to motivate CDW recycling intention of contractors.

Identifying factors affecting the low uptake of reprocessed construction materials: A systematic literature review

The success of demolition waste reverse logistics supply chains (DWRLSCs) depend on the market uptake of reprocessed construction materials (RCMs) since resource recovery will not be viable without a well-developed consumption process. However, usage of RCMs is sparse while there is also limited focus in existing research on their market uptake. Therefore, this systematic literature review (SLR) attempts to discern trends in research on the use of RCMs and identify factors that limit their uptake. 52 articles from three databases published between 2000 and 2021 were selected for descriptive and content analyses. Descriptive analysis showed growing research interest in the area over the last 5 years. Content analysis was underpinned by Attitude-Behaviour-Context (ABC) Theory which focuses on pro-environmental consumer decisions. As predicted by the theory, a mix of personal and contextual factors affect the low uptake of RCMs. Negative attitudes, reluctance to change the status quo and limited decision-making capabilities were identified as personal factors that limit the use of RCMs. Similarly, contextual factors such as price, quality, information availability, market availability, sourcing lead times and lack of regulations, standards, and specifications inhibit the use of such materials. The review also proposes several future research directions to expand knowledge around this domain.

Exploring the restrictive factors for the development of the construction waste recycling industry in a second-tier Chinese city: a case study from Jinan

Recycling construction waste in urban cities has attracted wide attention in the government department and building industry worldwide owing to numerous benefits in economics, the environment, and society for sustainable development. Most of the research was focused on the scope of first-tier/new first-tier cities. At the same time, less attention has been paid to second-tier cities, which should be further considered because of their significant potential for increasing construction waste. Jinan is one of the pilot cities for construction waste treatment in China. This city has been chosen as the case in this study to explore critical restrictive factors for developing the construction waste recycling industry (CWRI) in second-tier cities with the adoption of combined methods of the DEMATEL-ISM-EWM. It was revealed by the results that (1) the government is the main stakeholder. In addition, the legislation, management system, incentive/support for stakeholders, and technical standards were closely associated with CWRI development in Jinan. Low landfill fees and natural ore tax rates are unique and vital restrictive factors that should receive more attention. (2) Other key restrictive factors that should be given priority were (i) the lack of green design for designers, (ii) poor classification and management of construction waste for constructors on site, (iii) tight operating funds and insufficient publicity for recycling enterprises, and (iv) insufficient research funds for research institutions. Finally, a comparison of the similarities and differences of the restrictive factors on CWRI development between second-tier and first-tier/new first-tier cities was conducted, and a series of reasonable suggestions were provided, considering the perspective of stakeholders. The research will offer a valuable reference for industry practitioners and academics interested in CWRI.

Building a whole process policy framework promoting construction and demolition waste utilization in China

The generation of construction and demolition waste¹ (CDW) in China has increased dramatically in recent decades due to the rapid urbanization. Yet there is a very limited utilization of this waste, meaning that there is an urgent need to address this issue in order to reduce the reliance on virgin materials and improve the lived environment in China. This problem contrasts with the EU experience where many member states already exceed an 80% utilization rate of CDW due to extensive policy measures. We argue that the supervision of CDW is an important and underestimated element in addressing this waste stream, and that China and other rapidly developing states can build on the EU experience to address this issue rapidly and efficiently. This paper took a comparative policy analytical approach to summarize advanced experiences promoting CDW utilization, highlighting 14 advanced policy measures. We then conducted a case study approach applied to a Chinese metropolitan city, Wuhan, to identify the key measures to promote CDW utilization in the local area by questionnaire. On this basis, we then proposed a whole process supervision framework for the six most important policy measures, to cover the whole process of the generation, transport and recycling of this waste. This approach provides a mode for policymakers to prioritize the most important policy measures to address CDW problem in China through a timely and data-driven process.

Characterization of Three Types of Recycled Aggregates from Different Construction and Demolition Waste: An Experimental Study for Waste Management

Achieving sustainable management and efficient use of natural resources stands out as one of the goals included in the Goals for Sustainable Development in the 2030 Agenda. The construction sector is currently far from presenting an efficient model in terms of treating waste generated by it. Variations in the physical and chemical properties of recycled aggregates coming from construction and demolition waste are one of the main reasons of their limited use in the production of construction materials. This research presents a physicochemical characterization of three different types of recycled aggregates coming from different types of waste: concrete, ceramic and mixed. Physical characterization shows that recycled concrete aggregate has better physical properties compared with mixed recycled aggregate and ceramic recycled aggregate, which makes it more suitable for use in masonry mortars and concrete, due to its higher dry density (2210.33 kg/m3), its lower content of fines (5.17%), its lower friability coefficient (24.60%), and its water absorption coefficient (6.70%). Chemical characterization shows that none of the tested recycled aggregates contains traces of harmful chemical agents that exceed the limits established by the reference regulations. Finally, the statistical analysis shows good homogeneity for these raw materials, obtaining low coefficients of variation and values within the recommended in each of the calculated confidence intervals.

The role of construction industry and construction policy on sustainable rural development in China

Recently, rural development has depended on the construction industry's success due to the high employment rate in the construction industry and its development role in the rural areas, and this phenomenon needs research focus. Hence, the current article examines the impact of the construction industry (construction industry revenue and growth) and construction policy (construction industry subsidies) on sustainable rural development in China. The study also used the control variable of gross domestic product (GDP) and industrialization. The article has collected secondary data from the Ministry of Housing and Urban-Rural Development and World Development Indicators (WDI) from 1991 to 2020. The article has applied the Augmented Dickey-Fuller (ADF) test to examine stationarity and quantile autoregressive distributed lag (QARDL) model to investigate the association among variables. The results revealed that the construction industry revenue, growth, construction policy GDP, and industrialization positively link sustainable rural development in China. Thus, the findings exposed that if the country's construction industry improved, rural development also increased accordingly. This study guides the policy development authorities to develop effective policies related to improvement in the construction industry that will enhance sustainable rural development.

Simulation Analysis of Implementation Effects of Construction Waste Reduction Policies

The development of the construction industry generates construction waste which could contribute to environmental issues. Construction waste reduction management plays an important role in directly reducing emissions and solving the environmental pollution caused by construction waste. The limited rationality hypothesis and an evolutionary game model are used to construct a simulation model for the effects of environmental policies’ influences on the behavior of government and construction enterprises in construction waste reduction activities. Simulation results show that: (1) The government and enterprises evolve in the same direction under the sewage fees system or the subsidy system. The relationship between the initial ratio of the two sides and the position of the saddle point determines the evolution direction of the system. (2) The government could adjust the sewage fees rate, the penalty ratio, and the upper limit of construction waste emission to obtain a superior effect under the sewage fees system. As the subsidy system, the government could adjust the unit subsidy and the upper limit of construction waste emissions by enterprises. (3) The evolution times of the different systems are different. The time required to evolve to a stable state is shorter under the sewage fees system. Under the subsidy system, the time to evolve to a non-reduced state is longer, and the time to evolve to a reduced state is about the same as the time for the government to evolve to a checked state. The time required to evolve to the reduced state is about the same as the time required for the government to evolve to the checked state. This study develops an evolutionary game model between the government and construction enterprises in construction waste reduction activities. This study helps the government analyze the influence of various policies on enterprises’ reduction behaviors. The findings could help the government formulate appropriate policies to guide enterprises in waste reduction.

Waste management and green technology: future trends in circular economy leading towards environmental sustainability

The effective treatment of waste to be used as a resource in future has a major role in achieving environmental sustainability and moving towards circular economy. The current research is aimed to provide in-depth detail regarding prominent trends and research themes, evolution, future research orientation, main characteristics, and mapping of research publications on waste management, technological innovation in circular economy domain from the year 2000 to 2021. Different analyses including text mining and bibliometric and content analyses were applied to answer the research question and provide the details on aforementioned variables. From the bibliometric analyses, a total of 1118 articles were drawn out from the Scopus database to conceptualize the core body of research. As a result, the following themes were identified: electronic waste, circular economy transition, plastic waste, bio-based waste management, lifecycle assessment, and ecological impacts, and construction and demolition waste management. The highlighted features, future research orientation, and prominent research perspective can provide guideline for future research to enrich the literature through conducting studies on provided research directions and help lead waste management and technological innovation policymakers, professionals, and practitioners in moving towards circular transition.

Improving Contractors' Participation of Resource Utilization in Construction and Demolition Waste through Government Incentives and Punishments

This paper develops a simulation model for analyzing how government incentives and punishments improve contractors' participation in resource utilization of construction and demolition waste (RUCDW) based on system dynamics theory. The construction industry's long-term objective is to become more sustainable and resource-effective, and as part of this objective, generated construction and demolition waste should be recycled and resource utilized. However, most contractors have little willingness to engage in RUCDW because it increases their costs. The government thus plays a vital role in improving their participation in RUCDW through a range of educational tools such as advertisements, professional training, incentives, and punishments. Among these approaches, incentives and punishments are considered the most effective because they directly change project costs. We use the Vensim software package for numerical simulation and data collected from Suzhou, China are used to demonstrate and validate the developed model. Simulation results show that the government can improve contractors' participation in RUCDW through three kinds of incentives and punishments: (1) subsidizing RUCDW; (2) increasing landfill fees; and 3) issuing fines for illegal dumping. Comprehensive application of multiple policies has a stronger effect than single policies. The established model is therefore a valuable tool for assessing the dynamic effects of government incentives and punishments on RUCDW ahead of implementation, which can provide guidance for policymakers.

Management system for engineering and decoration waste: An exploratory study in Shenzhen

Rapid urban development and renewal have caused large amounts of engineering and decoration waste to be produced. These wastes pose serious risks to the environment. Disposal and management of this waste have become problematic. A mean of 11.4 × 10⁶ m³ of engineering and decoration waste will be produced each year in Shenzhen between 2018 and 2035. Engineering and decoration waste are currently mainly sent to landfill, but this requires large amounts of land and can cause serious environmental pollution. There are problems including irregular emissions, a disorderly transportation market, and inadequate disposal facilities, so policies for managing engineering and decoration waste need to be established. In this study, a hybrid approach was used to develop a system for managing the whole engineering and decoration waste system (generation, collection & transportation, and disposal). The system was developed after determining waste emission and disposal requirements through site visits, clarifying problems involved in waste collection and transportation through interviews, identifying suitable management practices in an expert seminar, and developing a management system through desktop surveys. It was found that new buildings produce 0.02-0.04 (m³ waste)/(m² building) and 0.11-0.13 (m³ decoration waste)/(m² building) and that emission limits are required. Construction enterprises employ private trucks to transport waste, and illegal dumping occurs. Directed collection and transportation is required. Public welfare requires a mechanism for managing engineering and decoration waste with clear responsibilities. Government-authorized construction and operation should be explored and implemented. A propagable engineering and decoration waste management system is proposed with three management modules, generation, collection & transportation, and disposal, to act as a strategy for improving engineering and decoration waste.

Estimating the Carbon Emission of Construction Waste Recycling Using Grey Model and Life Cycle Assessment: A Case Study of Shanghai

Great efforts have been exerted in reducing carbon emissions in design, construction and operation stages. However, little attention is paid to the quantification of carbon emissions in construction waste recycling at the end-of-life stage. This study aims to quantitatively analyze the carbon emission of construction waste in Shanghai City, PR China. A grey model is used to forecast the generation amount of construction waste, and a life cycle assessment is performed to estimate the carbon emission of construction waste. In this study, both the carbon emission of recycling activities (environmental costs), and the equivalent amount of carbon generated from alternative materials (environmental benefit) are considered. Here, recycling 1 ton (t) of construction waste in Shanghai can save 100.4 kg CO2−e. The total carbon-emission-saving potential can be increased from 0.31 million t CO2−e (2022) to 0.35 million t CO2−e (2031). The carbon emission of recycling concrete, brick, steel, wood and mortar, identified as the key components of construction waste, is investigated. This research can help to reduce carbon emissions and further achieve carbon neutrality for Shanghai City. The proposed methods can also be applied to other regions, especially when the data for construction waste are insufficient.

Determinants of Satisfaction with Solid Waste Management Services: A Central-Local Comparison in China

The Chinese central government proclaimed a mandatory or demonstration waste separation policy in some cities or counties to manage the increasing amounts of generated waste since 2017. Many cities and regions have also begun to build waste separation management systems and institutions, and community managers have created waste management rules and provided separation management services under the guidance of local government. However, little is known about how these policies or services have performed and the degree of residents’ satisfaction, especially regarding the central government. Therefore, the purpose of this study was to analyze the consequence of these policies using residents’ community and national satisfaction levels with solid waste management services (SWMS) and their determinants. An online survey in 2021 showed that the overall satisfaction levels of communities and national SWMS are similar, but the differences between rural and urban regions are significant. Residents’ satisfaction with community SWMS in urban regions was higher than national satisfaction, and the results in rural regions was contrary. The determinants of community and national satisfaction were also different and varied by region. To improve satisfaction, the government need to standardize basic management systems in different types of regions, gradually improve management services and institutions in rural areas and non-pilot cities and provide special services or facilities for less healthy residents.

Quantitative Evaluation of Waste Separation Management Policies in the Yangtze River Delta Based on the PMC Index Model

Numerous policies have been formulated and implemented to strengthen waste separation management activities in many countries. Waste separation management policies (WSMPs) must be evaluated as the precondition for reducing deviations from policy implementation and improving waste separation performance. Based on text mining technology and the construction of a policy modeling consistency (PMC) index model, we conducted a quantitative evaluation of 22 WSMPs issued by central governmental departments and provinces in the Yangtze River Delta, China from 2013 to 2021 and analyzed their optimization paths. The results suggest that the PMC index of the selected WSMPs has an upward trend. The average PMC index of 22 WSMPs was 6.906, indicating good quality in the policy texts. The PMC index identified seven, nine, five, and one of the policies as being perfect, excellent, good, and acceptable, respectively. The characteristics of WSMPs were further illustrated through PMC surface charts. Based on this, optimization paths for WSMPs with lower PMC indexes are proposed, which indicate that existing WSMPs have great potential for optimization in terms of harsher constraint regulations, context-appropriate incentives, and cultivation of market participants. Finally, this study provides a beneficial reference for similar cities or countries to improve their performance in the management of waste separation and environmental protection.

Diverting demolition waste toward secondary markets through integrated reverse logistics supply chains: A systematic literature review

Construction industry has adopted reverse logistics (RL) concept to manage high volumes of demolition waste (DW). However, DW RL supply chains (RLSCs) were found to be suffering from uncertainties, information deficiencies, and uncoordinated material flows. Improving supply chain integration (SCI), specifically external integration, across DW RLSCs was identified as a possible solution to overcome such problems. Despite this, studies that focus on external integration in DW RLSCs are limited. Using a systematic literature review (SLR), this study explores external integration in DW RLSCs. Sixty-six articles from three databases published between 2006 and 2020 were subjected to descriptive and content analysis. Arrangement of material, information, and financial flows across DW RLSCs, inhibitors of external integration, and potential measures for improving external integration were analyzed. Accordingly, material, information, and financial flows across DW RLSCs were mapped, and inhibitors of external integration, along with potential measures for improving external integration were identified. As the key outcome of this SLR, these findings were developed into a conceptual framework, which shows the main factors that inhibit and improve external integration in DW RLSCs. The framework will be useful in guiding further empirical research and informing industry practice. Several future research directions are also proposed to expand knowledge around the research domain.

RGB-D fusion models for construction and demolition waste detection

The development of urbanization has brought a large amount of construction and demolition waste (CDW), which occupy land and cause adverse ecological effects. To effectively solve the negative impact of CDW, it needs to be recycled. Accurate waste classification is key to successful waste management. However, the current waste classification methods mainly use color images to classify, which cannot meet the needs of accurate classification. This paper built an RGB-depth (RGB-D) detection platform, using a color camera and a laser line-scanning sensor to collect RGB images and depth images. In order to use RGB images and depth images for feature fusion more effectively, this paper proposed three fusion models: RGB-D concat、RGB-D Ci-add and RGB-D Ci-concat. All these models based on an instance segmentation network called mask region convolutional neural network (Mask R-CNN), which can accurately segment the contours of each object while classifying them. The experimental results show that the mAPs of the RGB-D Ci-add / concat model are 1.33% to 1.72% higher than those of the RGB model, and the classification accuracy is 1.92% ∼ 2.27% higher. In addition, all the proposed models can meet the real-time requirement of online detection. Due to the excellent comprehensive performance of the RGB-D Ci-concat model, it can be regarded as the final detection model of the robot, which can improve the sorting efficiency of CDW further.

The Durability of Recycled Fine Aggregate Concrete: A Review

With the rapid development of urbanization, many new buildings are erected, and old ones are demolished and/or recycled. Thus, the reuse of building materials and improvements in reuse efficiency have become hot research topics. In recent years, scholars around the world have worked on improving recycle aggregates in concrete and broadening the scope of applications of recycled concrete. This paper reviews the findings of research on the effects of recycled fine aggregates (RFAs) on the permeability, drying shrinkage, carbonation, chloride ion penetration, acid resistance, and freeze–thaw resistance of concrete. The results show that the content of old mortar and the quality of recycled concrete are closely related to the durability of prepared RFA concrete. For example, the drying shrinkage value with a 100% RFA replacement rate is twice that of normal concrete, and the depth of carbonation increases by approximately 110%. Moreover, the durability of RFA concrete decreases as the RFA replacement rate and the water–cement ratio improve. Fortunately, the use of zeolite materials such as fly ash, silica fume, and meta kaolin as surface coatings for RFAs or as external admixtures for RFA concrete had a positive effect on durability. Furthermore, the proper mixing methods and/or recycled aggregates with optimized moisture content can further improve the durability of RFA concrete.

Potential Energy Savings from Circular Economy Scenarios Based on Construction and Agri-Food Waste in Italy

In this study, our aim was to explore the potential energy savings obtainable from the recycling of 1 tonne of Construction and Demolition Waste (C&DW) generated in the Metropolitan City of Naples. The main fraction composing the functional unit are mixed C&DW, soil and stones, concrete, iron, steel and aluminium. The results evidence that the recycling option for the C&DW is better than landfilling as well as that the production of recycled aggregates is environmentally sustainable since the induced energy and environmental impacts are lower than the avoided energy and environmental impacts in the life cycle of recycled aggregates. This LCA study shows that the transition to the Circular Economy offers many opportunities for improving the energy and environmental performances of the construction sector in the life cycle of construction materials by means of internal recycling strategies (recycling C&DW into recycled aggregates, recycled steel, iron and aluminum) as well as external recycling by using input of other sectors (agri-food by-products) for the manufacturing of construction materials. In this way, the C&D sector also contributes to realizing the energy and bioeconomy transition by disentangling itself from fossil fuel dependence.

Component-Based Model for Building Material Stock and Waste-Flow Characterization: A Case in the Île-de-France Region

Building demolition is one of the main sources of waste generation in urban areas and is a growing problem for cities due to the generated environmental impacts. To promote high levels of circular economy, it is necessary to better understand the waste-flow composition; nevertheless, material flow studies typically focus on low levels of detail. This article presents a model based on a bottom-up macro-component approach, which allows the multiscale characterization of construction materials and the estimation of demolition waste flows, a model that we call the BTP-flux model. Data mining, analytical techniques, and geographic information system (GIS) tools were used to assess different datasets available at the national level and develop a common database for French buildings: BDNB. Generic information for buildings in the BDNB is then enriched by coupling every building with a catalog of macro-components (TyPy), thus allowing the building’s physical description. Subsequently, stock and demolition flows are calculated by aggregation and classified into 32 waste categories. The BTP-flux model was applied in Île-de-France in a sample of 101,320 buildings for residential and non-residential uses, representative of the assessed population (1,968,242 buildings). In the case of Île-de-France, the building stock and the total demolition flows were estimated at 1382 Mt and 4065 kt, respectively. For its inter-regional areas—departments—, stock and demolition waste can vary between 85 and 138 tons/cap and 0.263 and 0.486 tons/cap/year, respectively. The mean of the total demolition wastes was estimated at 0.33 tons/cap/year for the region. Results could encourage scientists, planners, and stakeholders to develop pathways towards a circular economy in the construction sector by implementing strategies for better management of waste recovery and reintegrating in economic circuits, while preserving a maximum of their added value.

Tackling the "last mile" problem in renovation waste management: A case study in China

Solid waste generated from building renovation, called "renovation waste" in this study, represents a major waste management problem. A particular difficulty is sourcing renovation waste arising sporadically from discrete sites for central processing. This can be characterized as a "last mile" problem in renovation waste management (RWM). This study reports good practice for dealing with the RWM last mile problem in a city in China. We conduct qualitative research comprising site investigations and interviews, organized in an in-depth case study. We discover that the city effectively solved the last mile problem by developing a multi-layer, nested waste management system, empowered further by various smart technologies and concerted collaboration from multi-stakeholders coordinated by a determined government. Nevertheless, the longevity of the RWM is contingent on confronting several challenges, including (a) achieving cost and benefit balance, (b) defining clearer standards and policies, and (c) raising stakeholders' awareness of waste management. A general RWM strategy is recommended to establish fluent channels through which to source and qualify renovation waste for central treatment. The study delves into the much neglected world of RWM and provides a valuable reference for tackling similar problems.

Estimating construction waste generation in the Greater Bay Area, China using machine learning

Reliable construction waste generation data is a prerequisite for any evidence-based waste management effort, but such data remains scarce in many developing economies owing to their rudimentary recording systems. By referring to several models proposed for estimating waste generation, this study aims to develop a reliable and accessible method for estimating construction waste generation based on limited publicly available data. The study has two objectives. Firstly, it aims to estimate construction waste generation by focusing on the Greater Bay Area (GBA) in China, one of the world's most thriving regions in terms of construction activities. Secondly, it aims to compare the strengths and weaknesses of various waste quantification models. 43 sets of annual socio-economic, construction-related and C&D waste generation data ranging from 2005 to 2019 were collected from the local government authorities. By analyzing the data using four types of machine learning models, namely multiple linear regression, decision tree, grey models, and artificial neural network, it is found that all calibrated models, with their respective strengths and weaknesses, can produce acceptable results with the testing R² ranging from 0.756 to 0.977. This study also reveals that the 11 cities in the GBA produced a total of about 364 million m³ of construction waste in 2018. The result can be used for monitoring the urban metabolism, quantifying carbon emission, developing a circular economy, valorizing recycled materials, and strategic planning of waste management facilities in the GBA. The research findings also contribute to the methodologies for estimating waste generation using limited data.

Conceptualising the Circular Economy Potential of Construction and Demolition Waste: An Integrative Literature Review

Traditionally, construction and demolition waste (CDW) materials have been considered to be unwanted, surplus, or wastage materials or materials with zero value. Such a conceptualisation only embraces a negative aspect, which underpins the disposal of reusable and recyclable CDW materials in landfills, thus damaging the circular economy and the environment. The scope of this research was to conceptualise the circular economy potential of non-hazardous construction and demolition waste, which can be used as a resource for advancing the circular economy and sustainability in the built environment. Thus, the abbreviation ‘CEPCDR’ is used for this purpose. The study employs an integrative literature review to understand in depth whether the rationale in the existing CDW definitions advocates for the circular economy. Instead, the literature showed that the current definitions mainly support quantitative, economic, or classification needs, respectively. That is because they lack consideration of the dynamic nature of CDW materials, which embraces the spatial and temporal dimensions. The former involves the geographic context in which the CDW phenomenon eventuates, while the latter concerns the lifecycle of materials. This study contributes to the body of knowledge by conceptualising the CEPCDR using a holistic approach that includes five dimensions: the social, economic, environmental, spatial, and temporal perspectives. Furthermore, the study seeks to drive future research in measuring the CEPCDR.

Financial and economic evaluation of construction and demolition waste recycling in Hanoi, Vietnam

Increasing waste generation and the absence of a formal recycling industry are exacerbating the inadequacy of Construction and Demolition Waste (CDW) management in Hanoi, Vietnam. This study assesses potential CDW recycling in Hanoi by estimating the prospective supply of and demand for CDW recycling plants and evaluating their likely costs and benefits. Supply of concrete waste was calculated based on the weight-per-construction-area method whilst demand for recycled concrete aggregates (RCA) was determined by estimating the amount of aggregates for road construction in Hanoi from 2013 to 2017. Two potential models of CDW recycling plants were considered: a stationary plant and a mobile plant, with capacities of 1,000 and 360 tons/day, respectively. Our findings reveal that demand for RCA exceeds waste concrete supply, suggesting a promising market for RCA. Positive Net Present Value and Internal Rate of Return values of the stationary plant indicate its feasibility as an investment option. Meanwhile, the introduction of mobile recycling plants might require governmental intervention to internalize recycling positive externalities. Supporting policies might include a combination of a virgin material tax, green public procurement, and quality standard development.

Design and simulation of a secondary resource recycling system: A case study of lead-acid batteries

The recycling of secondary resources is complicated as consumers, recyclers and governments are all involved in this process. In developing countries, compared to legal recyclers, illegal recyclers not only have cost advantages but also create serious pollution. Inappropriate management policies may cause disorder in the recycling market or inefficient fiscal management. This paper takes China's lead-acid batteries (LABs) from 2000 to 2015 as an example to construct a model of a secondary resource recovery system based on heterogeneous groups and analyzes the environmental and economic impacts of used LAB recycling. By simulating the implementation of different tax cuts, subsidies and regulatory policies by the government in each year, we observe the overall environmental impact of the recycling industry. This study finds that when the total amount of government expenditures is limited, the optimal policy combination emphasizes tax reduction and subsidy policies during the growth period of the recycling industry and uses more funds for supervision in the mature period. Under the balance of fiscal revenues and expenditures, the optimal policy combination can reduce the number of illegal recycling companies and waste lead emissions from the recycling market by 97.9% and 45.8%, respectively. Compared to research conducted using mathematical models and system dynamics models, this result is more in line with the actual situation, and the content is more intuitive. The government needs to adopt different policy combinations in different periods according to the state of the recycling market so that the recycling of secondary resources can achieve the optimal effect.

Simulation analysis of implementation effects of construction and demolition waste disposal policies

Urban development generates large amounts of construction and demolition waste, and the enactment of various policies is an important way to increase resource efficiency. It is urgent to analyse the choices and effects of construction and demolition waste disposal policies around the world. This study analyses and compares the implementation effects of various construction and demolition waste disposal policies and provides suggestions on the selection and formulation of different disposal method policies. A BP neural network and an agent-based model are used to construct a simulation model for the implementation effects of construction and demolition waste disposal policies. The average acceptance willingness is analysed for the three disposal methods of reduction, reuse and recycling under the different policies based on questionnaire survey data. Simulation results show that the implementation effect of the incentive policy as a single policy is superior, and the comprehensive implementation effect of the guidance-incentive-mandatory policy as a combined policy is superior. The implementation effect of combined policies is better than that of single policies. The policies suitable for different disposal methods are inconsistent. Information interaction can effectively improve the implementation effects of different construction and demolition waste disposal policies, especially for single policies. This study innovatively compares the various construction and demolition waste disposal policies and explain the interaction during their implementation. The findings can help the government formulate policies at different stages of construction and demolition waste management and provide a new approach to policy simulation research.

Machine Learning Comparison and Parameter Setting Methods for the Detection of Dump Sites for Construction and Demolition Waste Using the Google Earth Engine

Machine learning has been successfully used for object recognition within images. Due to the complexity of the spectrum and texture of construction and demolition waste (C&DW), it is difficult to construct an automatic identification method for C&DW based on machine learning and remote sensing data sources. Machine learning includes many types of algorithms; however, different algorithms and parameters have different identification effects on C&DW. Exploring the optimal method for automatic remote sensing identification of C&DW is an important approach for the intelligent supervision of C&DW. This study investigates the megacity of Beijing, which is facing high risk of C&DW pollution. To improve the classification accuracy of C&DW, buildings, vegetation, water, and crops were selected as comparative training samples based on the Google Earth Engine (GEE), and Sentinel-2 was used as the data source. Three classification methods of typical machine learning algorithms (classification and regression trees (CART), random forest (RF), and support vector machine (SVM)) were selected to classify the C&DW from remote sensing images. Using empirical methods, the experimental trial method, and the grid search method, the optimal parameterization scheme of the three classification methods was studied to determine the optimal method of remote sensing identification of C&DW based on machine learning. Through accuracy evaluation and ground verification, the overall recognition accuracies of CART, RF, and SVM for C&DW were 73.12%, 98.05%, and 85.62%, respectively, under the optimal parameterization scheme determined in this study. Among these algorithms, RF was a better C&DW identification method than were CART and SVM when the number of decision trees was 50. This study explores the robust machine learning method for automatic remote sensing identification of C&DW and provides a scientific basis for intelligent supervision and resource utilization of C&DW.

Identification and Evaluation of Urban Construction Waste with VHR Remote Sensing Using Multi-Feature Analysis and a Hierarchical Segmentation Method

With rapid urbanization, the disposal and management of urban construction waste have become the main concerns of urban management. The distribution of urban construction waste is characterized by its wide range, irregularity, and ease of confusion with the surrounding ground objects, such as bare soil, buildings, and vegetation. Therefore, it is difficult to extract and identify information related to urban construction waste by using the traditional single spectral feature analysis method due to the problem of spectral confusion between construction waste and the surrounding ground objects, especially in the context of very-high-resolution (VHR) remote sensing images. Considering the multi-feature analysis method for VHR remote sensing images, we propose an optimal method that combines morphological indexing and hierarchical segmentation to extract the information on urban construction waste in VHR images. By comparing the differences between construction waste and the surrounding ground objects in terms of the spectrum, geometry, texture, and other features, we selected an optimal feature subset to improve the separability of the construction waste and other objects; then, we established a classification model of knowledge rules to achieve the rapid and accurate extraction of construction waste information. We also chose two experimental areas of Beijing to validate our algorithm. By using construction waste separability quality evaluation indexes, the identification accuracy of construction waste in the two study areas was determined to be 96.6% and 96.2%, the separability indexes of the construction waste and buildings reached 1.000, and the separability indexes of the construction waste and vegetation reached 1.000 and 0.818. The experimental results show that our method can accurately identify the exposed construction waste and construction waste covered with a dust screen, and it can effectively solve the problem of spectral confusion between the construction waste and the bare soil, buildings, and vegetation.