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预测城市更新过程中的大规模拆迁废物产生:混合三部曲方法。

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

机构信息

College of Civil Engineering, Shenzhen University, Nanshan, Shenzhen 518000, China.

College of Civil Engineering, Shenzhen University, Nanshan, Shenzhen 518000, China.

出版信息

Waste Manag. 2019 Apr 15;89:1-9. doi: 10.1016/j.wasman.2019.03.063. Epub 2019 Mar 29.

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.

摘要

由于中国土地资源有限,拆除和重建现有建筑物成为满足城市更新要求的重要手段,在此过程中会产生大量的拆除废物。然而,由于缺乏基本数据和技术支持,很难高效地预测大规模拆除废物的产生。本研究旨在提出一种基于废物产生率(WGR)和总建筑面积(GFA)两个指标的城市更新中大规模拆除废物产生的混合三部曲方法。WGR 是根据不同的建筑类型和结构类型,通过现场测量和现有行业标准数据来衡量的。相应地分析了拆除废物的组成和比例。GFA 是基于图像识别技术和谷歌地球获取的。选择了 200 栋建筑物作为样本进行 GFA 准确性验证,其误差范围大多控制在 10%以内。最后,以深圳市城市更新为例,对大规模拆除废物产生进行了预测,验证了所提出的混合三部曲方法。结果表明,将产生 4940 万吨拆除废物。本研究的结果提高了现有大规模拆除废物预测方法的准确性和速度,表明其具有广泛应用的巨大潜力。本研究为拆除企业、运输企业、回收企业和政府部门在城市更新过程中精确管理大规模拆除废物提供了指导。

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