A Model for Predicting the Generation of Demolition Waste During the Urban Renewal Process

Bo Yu, Jiayuan Wang (), Zhengdao Li, Huanyu Wu, Yani Lai and Jie Li
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Bo Yu: Shenzhen University
Jiayuan Wang: Shenzhen University
Zhengdao Li: Shenzhen University
Huanyu Wu: The University of Adelaide
Yani Lai: Shenzhen University
Jie Li: Shenzhen University

A chapter in Proceedings of the 23rd International Symposium on Advancement of Construction Management and Real Estate, 2021, pp 1014-1027 from Springer

Abstract: Abstract Demolition waste (DW) faces a significant challenge due to massive urban development and renovation activities. It is therefore imperative to accurately estimate and predict the generation of DW. However, the previous research on the generation of DW was mainly aimed at the single building. The delayed time that buildings are demolished was not taken into account in the previous time predication model established. In this study, an accurate model for predicting the generation of DW during the large-scale urban renewal process was proposed. Case studies were conducted in a rapidly developing Special Economic Zone of Shenzhen in South China, and the dismantling of 459 urban renewal projects planned to be demolished between 2010 and 2016 was systematically investigated based on field study and GOOGLE EARTH. In addition, GOOGLE EARTH was used to calculate the lag time of DW generation and BIGEMAP was used to determine the gross floor area of urban renewal projects. Also, the estimation and prediction model of the quantity, generation time of DW was further established. The Houhai Cun urban renewal project was chosen as a representative case. The predicted results showed that it would generate 28277.88 tons of DW in November 2022. The generation location was predicted on southeast side of Dengliang Road, Yuehai Street, Nanshan District, Shenzhen. The findings of this study provide the valuable reference for the number, scale and location of DW comprehensive utilization enterprises and landfills. Besides, the prediction model considering the lag time of the DW generation is much in line with the actual situation, which improves the accuracy of the research method.

Keywords: Demolition waste; Urban renewal; Prediction model; GOOGLE EARTH; BIGEMAP (search for similar items in EconPapers)
Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-981-15-3977-0_77

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DOI: 10.1007/978-981-15-3977-0_77

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