Literature DB >> 31739769

An empirical study on waste generation rates at different stages of construction projects in China.

Qiankun Wang1, Lei Chen1,2, Ruibo Hu1, Zhigang Ren1, Yanting He2, Daoru Liu1, Ziqi Zhou2.   

Abstract

Estimation of construction waste generation is critical to construction waste management decisions. However, current construction waste estimation methods have various limitations (e.g. small samples). To address those limitations, this research conducts an empirical study to evaluate the waste generation rate of different types of waste at different construction stages. In this study, construction waste from 148 new-built residential construction sites in China were sorted and weighted on site and their waste generation rates were estimated separately. The results indicated that the amount of inorganic nonmetallic waste with a generation rate of 16.59 kg m-2 was the highest among the five types of waste (i.e. inorganic nonmetallic waste, organic waste, metallic waste, composite waste, hazardous waste), while the waste generation rate for the underground construction stage, which was 27.57 kg m-2, was the highest among the three stages (i.e. underground stage, superstructure stage, finishing stage). Compared with previous data, the new waste generation rate proposed in this research can better estimate the actual waste generation situation in construction sites, which provides reliable information for proper decision-making. Furthermore, based on the result of the empirical study, some recommendations for construction waste reduction are proposed.

Entities:  

Keywords:  Construction waste; construction stages; construction waste management; waste generation rate; waste reduction

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Year:  2019        PMID: 31739769     DOI: 10.1177/0734242X19886635

Source DB:  PubMed          Journal:  Waste Manag Res


  2 in total

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2.  Life Cycle Assessment of Construction and Demolition Waste from Railway Engineering Projects.

Authors:  Jianling Huang; Yang Yin; Lei Zheng; Sibo Zhang; Qingyun Zhao; Huihua Chen
Journal:  Comput Intell Neurosci       Date:  2022-04-28
  2 in total

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