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.

Assessing and predicting the illegal dumping risks in relation to road characteristics.

Using historical data to assess illegal dumping risks has significant potential to enhance the effectiveness of waste management in low-population density counties where the ability to patrol and regulate illegal dumping is limited. Using big data and geographical analysis to identify high-risk areas plays an important role in improving the effectiveness of supervision related to illegal dumping. However, current methods for classifying risk areas have limited accuracy. Taking an area in South Australia as an example, this study aims to improve the accuracy of classifying risk areas by using geo-information technology and machine learning methods. The results show that combining illegal dumping locations with road characteristics allows the high-risk areas to be refined to road sections. Compared with identifying the whole road or area as a high-risk spot, this result could be beneficial for monitoring illegal dumping in real life. Moreover, this model allows the analysis of factors that affect illegal dumping locations. Results show that the influencing factors for different risk levels of illegal dumping vary significantly. The model developed in this research can effectively distinguish risk levels according to these factors, and the model classification accuracy can reach 85%. In addition, there are priorities amongst these factors. This finding could help environmental authorities to allocate equipment and personnel with consideration of varying level of importance of those factors. This study has both technical contributions to identify high risk areas of illegal dumping, and theoretical implications for its management.

Cost-benefit analysis of demolition waste management via agent-based modelling: A case study in Shenzhen.

The economic instrument is an effective approach to encourage demolition contractors to conduct low-impact waste management. It is essential for project managers and decision-makers to better understand the cost-benefit of demolition waste (DW) management, to promote development of an effective waste management plan. This study explores the interactive dynamics and adaptive nature between stakeholders, where the cost-benefit of DW management is analysed through the agent-based modelling approach. Shenzhen, a leading city in China in the management of DW, was selected as the study area. It was revealed that if the traditional demolition method is adopted as the primary choice, the net benefit of demolition of buildings in the study case will reach -131.4 billion yuan, i.e. the cost will surpass the revenue. If the selective demolition method is widely used by demolition contractors, simulation results indicate that the net benefit will reach 33.3 billion yuan, an increase of 125.34%, compared to the situation in which the traditional demolition method is widely implemented. Based on the simulation, an optimal management framework for DW management stakeholders was constructed. The research results can provide a decision-making basis for the government and relevant departments to formulate DW management measures.