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Spatial Distribution and Elements of Industrial Agglomeration of Construction and Demolition Waste Disposal Facility: A Case Study of 12 Cities in China

Autor(en): ORCID



Medium: Fachartikel
Sprache(n): Englisch
Veröffentlicht in: Buildings, , n. 4, v. 15
Seite(n): 617
DOI: 10.3390/buildings15040617
Abstrakt:

Site selection is the key to carrying out the industrial layout of construction and demolition waste (CDW) resourcing enterprises. The current study needs more data on CDW industry location. The current construction waste resource utilization rate and industrial layout need to be improved. This study uses statistical and visualization methods to analyze key factors affecting the location of CDW recycling enterprises. Additionally, it identifies planning strategies and policy incentives to drive industry development. The study explicitly adopts global and weighted geographic regression (GWR) analysis methods and uses ArcGIS 10.8 to visualize point of interest (POI) data. It was found that (1) the main factors affecting the spatial distribution of the CDW recycling economy, in order of importance, are river network density, financial subsidies, R&D incentives, the number of building material markets, the value added by the secondary industry, the area of industrial land, and the density of the road network. The three main drivers of site selection decisions are government subsidies, market size, land, and transportation resources. (2) Enterprise industry chain and transportation costs are industrial economic decision-making considerations. Enterprises are generally located on flat terrain, around industrial parks, near the center of urban areas, and close to demand and cost reduction. (3) At the city level, there are more resource-based enterprises in cities with high levels of economic development and strong policy support. The spatial distribution of enterprises is consistent with the direction of urban geographic development. There is a positive global correlation between construction waste resourcing enterprises. Ningbo, western Qingdao, and northern Beijing show high aggregation characteristics. Low–low aggregation characteristics exist in regions other than central Chongqing. High–low aggregation characteristics are found in the center of the main city of Chongqing, eastern Shanghai, and central Nanjing. Low–high aggregation is distributed in northeastern Ningbo, northern Guangzhou, and southern Shenzhen. (4) Regarding industrial agglomeration, except for Nanjing, construction waste industrial agglomeration occurs in all 11 pilot cities. Among them, Shanghai, Xiamen, and Hangzhou have industries that are distributed evenly. Xi’an and Chongqing have a centralized distribution of industries. Guangzhou, Shenzhen, Beijing, Ningbo, and Qingdao have multi-center clustering of industries. Nanning’s industry has a belt-shaped distribution. This research explores the micro elements of industry chain integration in the CDW industry. It combines incentive policies and urban planning at the macro level. Together, these efforts promote sustainable city construction. This research provides CDW location data and dates for future digital twin and city model algorithms. It supports industrial planning, transportation, spatial optimization, carbon emission analysis, city operations, and management and aims to enhance the city’s green and low-carbon operations.

Copyright: © 2025 by the authors; licensee MDPI, Basel, Switzerland.
Lizenz:

Dieses Werk wurde unter der Creative-Commons-Lizenz Namensnennung 4.0 International (CC-BY 4.0) veröffentlicht und darf unter den Lizenzbedinungen vervielfältigt, verbreitet, öffentlich zugänglich gemacht, sowie abgewandelt und bearbeitet werden. Dabei muss der Urheber bzw. Rechteinhaber genannt und die Lizenzbedingungen eingehalten werden.

  • Über diese
    Datenseite
  • Reference-ID
    10820595
  • Veröffentlicht am:
    11.03.2025
  • Geändert am:
    11.03.2025
 
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