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<p>This study aims to explore and analyze carbon dioxide (CO₂) emission accounting methods, with a focus on comparing the basic principles, advantages, disadvantages, and applicable scopes of three major methods: actual measurement, material balance, and emission factor methods. Meanwhile, the principles, development and application of major energy models (such as LEAP, input-output models, LCA, STIRPAT, LMDI, and neural networks) are reviewed, and it is proposed that the combination of multiple models into a hybrid prediction framework is a crucial path for the further advancement of carbon dioxide emission accounting. Offering insightful information to enhance the precision and scientific rigor of CO<sub>2</sub> emission estimations is the purpose of this endeavor.</p>

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A review of researches on carbon dioxide emission accounting and evaluation

  • 期刊论文

  • 发表日期：

    2026年3月20日

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  • Feng Lin,
  • Honglei Ding,
  • Wenhuan Wang,
  • Chaojie Wei,
  • Fan Han,
  • Yifeng Xu,
  • Ziyi Zhang,
  • Jie Song,
  • Weiguo Pan

摘要

This study aims to explore and analyze carbon dioxide (CO₂) emission accounting methods, with a focus on comparing the basic principles, advantages, disadvantages, and applicable scopes of three major methods: actual measurement, material balance, and emission factor methods. Meanwhile, the principles, development and application of major energy models (such as LEAP, input-output models, LCA, STIRPAT, LMDI, and neural networks) are reviewed, and it is proposed that the combination of multiple models into a hybrid prediction framework is a crucial path for the further advancement of carbon dioxide emission accounting. Offering insightful information to enhance the precision and scientific rigor of CO2 emission estimations is the purpose of this endeavor.