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Evaluation of Carbon Emission Efficiency in the Construction Industry Based on the Super-Efficient Slacks-Based Measure Model: A Case Study at the Provincial Level in China

Author(s):


ORCID

ORCID
Medium: journal article
Language(s): English
Published in: Buildings, , n. 9, v. 13
Page(s): 2207
DOI: 10.3390/buildings13092207
Abstract:

Rapid urbanization and an increasing carbon footprint have underscored the need for sustainable practices in the construction industry. With the aim of prioritizing global sustainable development, the measurement of carbon emission efficiency in the construction industry (CEECI) has emerged as a critical indicator. Nevertheless, a comprehensive exploration of carbon emission efficiency within the Chinese construction sector remains limited, despite the pressing demand to mitigate carbon emissions. To address this research gap, this study aims to provide valuable policy recommendations for effectively reducing carbon emissions. We conducted a thorough assessment of both the total carbon emissions and the carbon emission intensity in 30 provinces and cities across China from 2010 to 2020. Utilizing the slacks-based measure (SBM) model with non-desired outputs, we evaluated the static CEECI, including the spatial correlation analysis and the evaluation of the carbon reduction potential in the construction industry (CRPCI). Additionally, the dynamic CEECI was quantified using the Malmquist–Luenberger (ML) index model, followed by an index decomposition analysis. The findings reveal several noteworthy insights: (1) There exists a positive correlation between carbon emissions in the construction industry and the economic scale. Generally, less developed areas (e.g., central and western regions of China) exhibit higher levels of carbon emission intensity (CEICI), while more developed areas (e.g., eastern regions of China) demonstrate lower levels of CEICI. (2) The CEECI across various provinces and cities demonstrates a clear spatial positive autocorrelation, while the CRPCI exhibits a negative correlation with the CEECI, with larger CRPCI values observed predominantly in western China. (3) Technological progress (MLTC) emerges as a crucial factor influencing the CEECI in our dynamic analysis. These findings offer valuable insights for policymakers to develop focused strategies to effectively mitigate carbon emissions nationwide.

Copyright: © 2023 by the authors; licensee MDPI, Basel, Switzerland.
License:

This creative work has been published under the Creative Commons Attribution 4.0 International (CC-BY 4.0) license which allows copying, and redistribution as well as adaptation of the original work provided appropriate credit is given to the original author and the conditions of the license are met.

  • About this
    data sheet
  • Reference-ID
    10737455
  • Published on:
    02/09/2023
  • Last updated on:
    14/09/2023
 
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