Chen Yiwei, Xie Qiu, Feng Yingbin, Huang Yuxin, Yang Yi, Zhang Tong
School of Management Science and Real Estate, Chongqing University, Chongqing 400045, China; Research Center for Construction Economics and Management, Chongqing 400045, China.
School of Management Science and Real Estate, Chongqing University, Chongqing 400045, China; Research Center for Construction Economics and Management, Chongqing 400045, China.
Waste Manag. 2025 Aug;205:115026. doi: 10.1016/j.wasman.2025.115026. Epub 2025 Jul 23.
Construction and demolition waste generation (CDWG) reduction is a key issue in urban waste management. The complex distribution and regional disparities of CDWG exacerbate the challenges of reduction. Existing research mainly focuses on macro-level national or regional scales, neglecting multi-scale interactions and detailed analysis at city scale. To address this gap, this study proposes a multi-scale STDP framework to systematically analyze the spatiotemporal evolution, driving mechanisms, and generation patterns of CDWG. Using China as a case and applying spatial econometrics and machine learning models, the main findings are as follows: (1) CDWG distribution consistent with Hu-Line, and the gap between two sides of the line gradually widened; (2) CDWG consistently shows spatial autocorrelation, with an "increase-decrease-recovery" fluctuation in aggregation, and city-scale correlation is always lower than at provincial scale; (3) Construction industry development and neighborhood influence are key drivers at provincial scale, while real estate market activity, housing demand, and urban economic level are major drivers at city level. Additionally, CDWG generation patterns for 31 provinces and 351 cities in China are identified, providing direct insights for governmental reduction management. The main theoretical contribution is to reveal that CDWG is driven by multi-scale spatial coupling, and its generation mechanism is the interaction of multiple factors at different geographical scales. The innovation lies in: (1) presenting the finer-grained evolution characteristics and driving factors of CDWG at city scales for the first time and (2) introducing a quantitative indicator to measure the impact of spatial spillover effects from neighboring regions on CDWG.
减少建筑与拆除废物产生量(CDWG)是城市废物管理中的一个关键问题。CDWG的复杂分布和区域差异加剧了减量面临的挑战。现有研究主要集中在宏观层面的国家或区域尺度,忽视了多尺度相互作用以及城市尺度的详细分析。为弥补这一差距,本研究提出了一个多尺度时空动态过程(STDP)框架,以系统分析CDWG的时空演变、驱动机制和产生模式。以中国为例,应用空间计量经济学和机器学习模型,主要研究结果如下:(1)CDWG分布与胡焕庸线一致,且该线两侧的差距逐渐扩大;(2)CDWG始终呈现空间自相关性,聚集情况呈“增加-减少-恢复”波动,且城市尺度的相关性始终低于省级尺度;(3)建筑业发展和邻里影响是省级尺度的关键驱动因素,而房地产市场活动、住房需求和城市经济水平是城市层面的主要驱动因素。此外,还识别了中国31个省份和351个城市的CDWG产生模式,为政府的减量管理提供了直接见解。主要理论贡献在于揭示了CDWG受多尺度空间耦合驱动,其产生机制是不同地理尺度上多种因素的相互作用。创新之处在于:(1)首次呈现了城市尺度上CDWG更细粒度的演变特征和驱动因素;(2)引入了一个定量指标来衡量邻近地区空间溢出效应对CDWG的影响。