The rapidly increased generation of construction and demolition (C&D) waste hinders the sustainable development of cities. Establishing an effective C&D waste management system is of great importance for achieving sustainable development goals. The quantification and prediction of C&D waste, forming the basis of waste management, are worthy of further exploration. C&D waste generation is time series data in which future waste generation is closely correlated with past ones. This study proposes a time-series waste prediction framework to predict C&D waste generation with less data volume by coupling generation rate calculation (GRC) and autoregressive integrated moving average (ARIMA) model. It is demonstrated in Sichuan, China, as a case study. The prediction result reveals that C&D waste generation in Sichuan shows an overall increasing trend, and the waste is mainly generated in the central of Sichuan. Chengdu accounts for over 40% of the total generation in the province, followed by Luzhou, Nanchong, and Mianyang. C&D waste generation shows a significant continual rise in Yibin and Zigong. Overall, most cities in Sichuan have issued related policies and tried to strengthen control over the transportation phase. This study provides an alternative to predict and analyze C&D waste generation from spatiotemporal perspectives. It enriches the C&D waste generation data and provides quantification support for C&D waste management at the regional level.
Keywords: ARIMA; Construction and demolition waste; Spatiotemporal analysis; Waste prediction.
© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.