工程管理学报2024,Vol.38Issue(6) :26-32.DOI:10.13991/j.cnki.jem.2024.06.005

建筑废弃物资源化碳减排潜力及影响因素时空异质性

Carbon Reduction Potential of Construction Waste Recycling and Spatial-Temporal Heterogeneity of Influencing Factors

汪振双 王宇飞 覃飞 刘景矿
工程管理学报2024,Vol.38Issue(6) :26-32.DOI:10.13991/j.cnki.jem.2024.06.005

建筑废弃物资源化碳减排潜力及影响因素时空异质性

Carbon Reduction Potential of Construction Waste Recycling and Spatial-Temporal Heterogeneity of Influencing Factors

汪振双 1王宇飞 1覃飞 1刘景矿2
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作者信息

  • 1. 东北财经大学 投资工程管理学院,辽宁 大连 116025
  • 2. 广州大学 管理学院,广东 广州 510006
  • 折叠

摘要

建筑废弃物资源化是减污降碳协同增效的重点领域.本文在 2006-2021 年中国建筑废弃物资源化碳减排潜力测算基础上,运用莫兰指数和地理加权回归模型对建筑废弃物资源化碳减排潜力时空特征、空间相关性和影响因素时空异质性进行研究.结果表明:中国建筑废弃物资源化碳减排潜力区域差异显著,总体表现出"东高西低""南高北低"的特征.建筑废弃物资源化碳减排潜力存在显著的空间差异,呈现明显的空间聚集格局.GWR模型的R2值均高于OLS模型的R2值,GWR的回归结果表明建筑废弃物资源化碳减排潜力的影响因素存在明显的时空异质性特征.

Abstract

The resource utilization of construction waste is a key area for synergistic efficiency reduction and carbon reduction.Based on the calculation of carbon reduction potential of construction waste in China from 2006 to 2021,exploratory spatial analysis and geographically weighted regression model were used to study the spatial-temporal characteristics,spatial correlation,and spatial-temporal heterogeneity of carbon reduction potential of construction waste.The results show that there are significant spatial differences in the carbon reduction potential of construction waste,presenting a clear spatial clustering pattern in China.the carbon reduction potential of construction waste in China has an overall pattern of"high in the east and low in the west"and"high in the south and low in the north"..The R2 values of the GWR model are higher than those of the OLS model,and the GWR model can better explain the impact mechanism of carbon reduction potential of construction waste.The regression results of GWR indicate significant spatial-temporal heterogeneity of the influencing factors of carbon reduction potential.

关键词

建筑废弃物/碳减排潜力/异质性/地理加权回归模型/驱动因素

Key words

construction waste/carbon reduction potential/heterogeneity/geographically weighted regression model/driving factors

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出版年

2024
工程管理学报
哈尔滨工业大学 中国建筑业协会管理现代化专业委员会

工程管理学报

CSTPCDCHSSCD
影响因子:1.613
ISSN:1674-8859
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