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To assess energy-saving effectiveness across industries, a correlation model between industrial electricity consumption and CO₂ concentration enhancement (XCO2en) was established. The quartile method analyzed city-level emission patterns, and time-rolling analysis revealed their dynamic relationship with XCO2en. Key industrial drivers of urban XCO2en increases in different periods and regions were identified for targeted emission reduction. Using classified electricity and XCO2en data from 21 cities in Sichuan (Jan 2019-Dec 2022), the model's performance was validated by a determination coefficient (R2 = 0.7988), showing strong explanatory power. The quartile model and time-rolling analysis effectively reflected electricity consumption and carbon emission patterns across cities and industries in Sichuan Province.

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Dynamic Monitoring of Sectoral Energy-Carbon Efficiency via Electricity-XCO2en Correlation Analytics

  • 会议论文

  • 发表日期：

    2026年

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  • Junli Liu,
  • Han Zhang,
  • Guixue Cheng

摘要

To assess energy-saving effectiveness across industries, a correlation model between industrial electricity consumption and CO₂ concentration enhancement (XCO2en) was established. The quartile method analyzed city-level emission patterns, and time-rolling analysis revealed their dynamic relationship with XCO2en. Key industrial drivers of urban XCO2en increases in different periods and regions were identified for targeted emission reduction. Using classified electricity and XCO2en data from 21 cities in Sichuan (Jan 2019-Dec 2022), the model's performance was validated by a determination coefficient (R2 = 0.7988), showing strong explanatory power. The quartile model and time-rolling analysis effectively reflected electricity consumption and carbon emission patterns across cities and industries in Sichuan Province.