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<p>Electric power resources are crucial for modern society and play an essential role in driving social progress. UN Sustainable Development Goal 7 calls for ensuring access to affordable, reliable, sustainable, and modern energy for all. Achieving equitable energy distribution is both an economic issue and a major challenge concerning social equity and sustainable development. Using spatial downscaling to obtain fine-scale electric power consumption (EPC) distribution for inequality analysis is imperative. This study proposes an E-NPBL framework integrating nighttime light, population density, building volume, and land use to model high-quality EPC spatial datasets. It analyzes EPC inequality from three perspectives: spatial heterogeneity, urban–rural gaps, and its relationship with development and environmental outcomes. Key findings: (1) The EPC grid data achieves high accuracy in state-level validation across the U.S., China, Australia, Brazil, and South Africa (<i>R</i>² = 0.96, RMSE = 2.82E10, MRE = 32.38%). (2) Under rapid urbanization, the urban–rural EPC gap is narrowing in high-income countries but widening in middle- and low-income countries. (3) Inequality in EPC relative to population, GDP, and CO₂ emissions is decreasing over time. This spatial analysis helps policymakers identify energy-disparate regions, crucial for advancing sustainable development.</p>

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Detecting global electric consumption patterns from a spatial perspective and analyzing their inequality at different scales

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年5月13日

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  • Jinke Liu,
  • Wei Guo,
  • Xuesheng Zhao,
  • Ximin Cui,
  • Andreas Rienow

摘要

Electric power resources are crucial for modern society and play an essential role in driving social progress. UN Sustainable Development Goal 7 calls for ensuring access to affordable, reliable, sustainable, and modern energy for all. Achieving equitable energy distribution is both an economic issue and a major challenge concerning social equity and sustainable development. Using spatial downscaling to obtain fine-scale electric power consumption (EPC) distribution for inequality analysis is imperative. This study proposes an E-NPBL framework integrating nighttime light, population density, building volume, and land use to model high-quality EPC spatial datasets. It analyzes EPC inequality from three perspectives: spatial heterogeneity, urban–rural gaps, and its relationship with development and environmental outcomes. Key findings: (1) The EPC grid data achieves high accuracy in state-level validation across the U.S., China, Australia, Brazil, and South Africa (R² = 0.96, RMSE = 2.82E10, MRE = 32.38%). (2) Under rapid urbanization, the urban–rural EPC gap is narrowing in high-income countries but widening in middle- and low-income countries. (3) Inequality in EPC relative to population, GDP, and CO₂ emissions is decreasing over time. This spatial analysis helps policymakers identify energy-disparate regions, crucial for advancing sustainable development.