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Prediction of large-scale demolition waste generation during urban renewal: A hybrid trilogy method

Author:
Yu, Bo, Wang, Jiayuan, Li, Jie, Zhang, Jingrong, Lai, Yani, Xu, Xiaoxiao
Source:
Waste management 2019 v.89 pp. 1-9
ISSN:
0956-053X
Subject:
Internet, buildings, business enterprises, case studies, industry, land resources, prediction, recycling, transportation, wastes, China
Abstract:
As a result of land resources constraining in China, demolition and reconstruction of existing buildings become an important means to meet the requirement of urban renewal, in which a large amount of demolition waste is generated. However, it is difficult to predict the generation of large-scale demolition waste with high efficiency due to the lack of basic data and technical support. This study aims to propose a hybrid trilogy method for predicting the generation of large-scale demolition waste during urban renewal based on two indicators of waste generation rate (WGR) and gross floor area (GFA). WGR was measured based on on-site measurement and existing industry standard data according to different building types and structure types. Composition and proportion of demolition waste were correspondingly analyzed. GFA was obtained based on image recognition technology and Google Earth. Two hundred buildings were selected as samples to verify GFA accuracy, whose error ranges were mostly controlled within 10%. Finally, prediction of large-scale demolition waste generation in Shenzhen was conducted as a case study during urban renewal for verification of the hybrid trilogy method proposed. Results show that 49.40 million tons of demolition waste will be generated. Findings of this study improve the accuracy and speed of existing prediction methods for large-scale demolition waste, indicating great potential for wide application. The current research provides guidance for demolition enterprises, transportation enterprises, recycling enterprises, and government departments to manage large-scale demolition waste precisely during urban renewal.
Agid:
6359293