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The green GDP accounting system based on the BP neural network: an environmental pollution perspective

  • Yinglun Zhu
  • , Yingying Xu*
  • , Yuhui Luo
  • *Corresponding author for this work
  • China Foreign Affairs University
  • Anhui University

Research output: Contribution to journalArticlepeer-review

Abstract

Introduction: The green GDP accounting system has become the focus of sustainable development, but a comprehensive accounting of environmental pollution cost and resource depletion cost has not yet been formed. Methods: This study measures environmental pollution cost and resource loss cost, and establishes the green GDP accounting system based on the SEEA-2012. To analyze the environmental effects brought by the adoption of green GDP accounting system, a BP neural network model including green GDP, traditional GDP and global climate indicators is constructed to predict the global climate changes. Results: The empirical results show that after the adoption of the green GDP accounting system, the global climate extreme weather can be reduced, the sea level will be lowered, and the climate problem is thus alleviated.

Original languageEnglish
Article number1277717
JournalFrontiers in Environmental Science
Volume11
DOIs
StatePublished - 2023

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 12 - Responsible Consumption and Production
    SDG 12 Responsible Consumption and Production
  2. SDG 13 - Climate Action
    SDG 13 Climate Action

Keywords

  • BP neural network
  • GDP
  • GDP accounting system
  • carbon emission
  • climate changes
  • environmental effect

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