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Rethinking industrial land-use in American rust cities towards sustainability based on a block-level model.
Han, Zhixiu; Xie, Wei; Yu, Huajun; Xie, Hongyi; Li, Yang; Wang, Yutao.
Afiliación
  • Han Z; Fudan Tyndall Center and Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP(3)), Department of Environmental Science and Engineering, Fudan University, Shanghai, 200438, China.
  • Xie W; Fudan Tyndall Center and Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP(3)), Department of Environmental Science and Engineering, Fudan University, Shanghai, 200438, China.
  • Yu H; Fudan Tyndall Center and Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP(3)), Department of Environmental Science and Engineering, Fudan University, Shanghai, 200438, China.
  • Xie H; Fudan Tyndall Center and Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP(3)), Department of Environmental Science and Engineering, Fudan University, Shanghai, 200438, China.
  • Li Y; Center for International Development, Harvard University, 79 JFK Street, 02138, Cambridge, MA, USA. Electronic address: yang_li@hks.harvard.edu.
  • Wang Y; Fudan Tyndall Center and Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP(3)), Department of Environmental Science and Engineering, Fudan University, Shanghai, 200438, China; IRDR International Center of Excellence on Risk Interconnectivity and Governance on Weather/Clim
J Environ Manage ; 352: 120067, 2024 Feb 14.
Article en En | MEDLINE | ID: mdl-38219672
ABSTRACT
Urban land is a fundamental but scarce resource that carries intensive human socio-economic activities. The demographic decline and housing vacancy issues that emerged with de-industrialization have raised concerns regarding the sustainable utilization of urban land resources, particularly in the American Rust Belt region. In this context, a comprehensive analysis of industrial land use can offer valuable insights to support the sustainable planning of shrinking cities. However, existing urban land research exhibits insufficient resolution at the sectoral scale and impedes the evaluation of industrial land use efficiency within the urban context. To address this gap, we established an integrated land use estimation framework for economic sectors based on multi-source data, which enables the assessment of land use efficiency at a finer sectoral scale. The method was then applied to the city of Detroit, Cleveland, and Pittsburgh. The results demonstrate that the current industrial land mix in the three cities is dominated by service-providing industries, but the land usage by goods-producing sectors in these cities presents a relatively high level of efficiency. The Moran's I value indicates a clustered tendency for the main economic sectors. The land use area results reveal that Other Services occupies the most land area in Detroit (2.29 million m2) and Cleveland (2.04 million m2). While in Pittsburgh, Professional Scientific and Technical Services (1.44 million m2) is the largest. In terms of the economic output, Management of Companies and Enterprises is the most efficient sector in Detroit (20.28 thousand $/m2) and Cleveland (29.43 thousand $/m2), while Pittsburgh's Public Administration (11.73 thousand $/m2) is the most efficient. As many other cities in the world are about to enter the era of de-industrialization or low growth, the outcomes can also serve as a reference to guide their sustainable revitalization in line with the SDGs.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Urbanización / Industrias Límite: Humans País/Región como asunto: Asia Idioma: En Revista: J Environ Manage Año: 2024 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Urbanización / Industrias Límite: Humans País/Región como asunto: Asia Idioma: En Revista: J Environ Manage Año: 2024 Tipo del documento: Article País de afiliación: China