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<p>Economic growth, consumption upgrading, population aging, and rising healthcare demand have expanded mining activities in remote areas, hindering carbon peaking and neutrality targets. Whether digital technology can mitigate mining-related carbon emissions under demographic pressure is unclear. Using 2005–2019 panel data from 254 Chinese prefecture-level cities, this study applies multiple models to examine mining carbon emission efficiency’s spatial pattern, network structure, and drivers, focusing on heterogeneity and pathways. Results show: ① The spatial linkage network evolved, with stronger connections between the Yellow River Economic Belt and eastern coastal areas, forming a “polar diffusion—gradient leap” pattern, with improved density and connectivity but needing structural optimization. ② Regenerative and mature cities have strong closeness centrality; growth-oriented cities are betweenness hubs. Digital technologies enhance efficiency only in regenerative resource-based cities, suppressing others. ③ Aging affects efficiency in stages. It first reduces efficiency, then improves it, and finally reduces it again. The negative effect becomes very strong in the later stages, both directly and through increased healthcare demand. ④ Digital technology reduces emissions through three mechanisms: promoting low-carbon transformation of elderly consumption-related industries, mitigating aging-induced healthcare burden, and weakening healthcare demand’s negative impact. A “Pressure identification—network analysis—mechanism deconstruction” framework is proposed to support green transformation of resource-based cities amid aging.</p>

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Spatial network structure and drivers of mining carbon emission efficiency in Chinese cities: dual roles of aging and digitalization

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年7月14日

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  • Gang Lin,
  • Yuting Zhang,
  • Zeng Li,
  • Jingying Fu

摘要

Economic growth, consumption upgrading, population aging, and rising healthcare demand have expanded mining activities in remote areas, hindering carbon peaking and neutrality targets. Whether digital technology can mitigate mining-related carbon emissions under demographic pressure is unclear. Using 2005–2019 panel data from 254 Chinese prefecture-level cities, this study applies multiple models to examine mining carbon emission efficiency’s spatial pattern, network structure, and drivers, focusing on heterogeneity and pathways. Results show: ① The spatial linkage network evolved, with stronger connections between the Yellow River Economic Belt and eastern coastal areas, forming a “polar diffusion—gradient leap” pattern, with improved density and connectivity but needing structural optimization. ② Regenerative and mature cities have strong closeness centrality; growth-oriented cities are betweenness hubs. Digital technologies enhance efficiency only in regenerative resource-based cities, suppressing others. ③ Aging affects efficiency in stages. It first reduces efficiency, then improves it, and finally reduces it again. The negative effect becomes very strong in the later stages, both directly and through increased healthcare demand. ④ Digital technology reduces emissions through three mechanisms: promoting low-carbon transformation of elderly consumption-related industries, mitigating aging-induced healthcare burden, and weakening healthcare demand’s negative impact. A “Pressure identification—network analysis—mechanism deconstruction” framework is proposed to support green transformation of resource-based cities amid aging.