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Optimizing scope 3 emissions in the automotive manufacturing industry: a multidisciplinary approach

  • Release time:2026-03-21
  • Hits:

  • DOI number: 

    10.1007/s44246-024-00131-2

  • Journal: 

    Carbon Research

  • Key Words: 

    Scope 3 emissions, Automotive industry, Carbon footprint, Machine learning, Text analytics, Sustainable development

  • Abstract: 

    The acceleration of global climate change poses enormous challenges to the automotive manufacturing industry, a key sector in reducing greenhouse gas (GHG) emissions. Particularly, Scope 3 emissions, encompassing indirect emissions, often constitute the largest carbon footprint component in this sector, yet their quantification and man- agement remain challenging. This paper proposes an interdisciplinary approach that integrates cloud computing, text analysis, and machine learning, and systematically details its implementation, key benefits, and potential applica- tions. Through this methodology, the paper seeks to provide the automotive industry with innovative and actionable insights to tackle the complexities of Scope 3 emissions. It focuses on enhancing the accuracy of emission quanti- fication and optimizing supply chains, aiming to reduce the overall carbon footprint. Moreover, this paper outlines the future challenges and directions for these technologies and methodologies in sustainable development and envi- ronmental management. This work underlines the critical role of interdisciplinary approaches in resolving environ- mental challenges, setting the stage for the automotive industry to forge paths towards a greener future.

  • Translation or Not: 

    no

  • Date of Publication: 

    2024-05-20

  • Included Journals: 

    EI
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