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<p>Forest carbon sink potential assessment in arid regions remains a critical challenge for climate change mitigation. This study integrates multi-source remote sensing and forest inventory data to model Xinjiang’s forest age and carbon density (2019 baseline: 186.76 Mg/hm<sup>2</sup> biomass, 93.38 Mg/hm<sup>2</sup> carbon density, 46-year average age), revealing a south-to-north “low-high-low” spatial pattern. Using predictive models excluding anthropogenic and natural disturbances, we project forest carbon stock to reach 203.71 ± 2.31 Tg C by 2030 and 283.08 ± 4.23 Tg C by 2060, with declining carbon sink rates (3.67 ± 0.57 Tg C/a in 2019–2030 vs. 2.65 ± 0.56 Tg C/a in 2031–2060). Notably, Xinjiang’s forests could offset 14.6% and 9.5% of regional CO<sub>2</sub> emissions during these periods. Economic cost analysis via panel fixed benefit modeling identifies afforestation suitability in Northeast Xinjiang, while conservation measures are prioritized elsewhere, particularly in high-elevation ridge zones. This research provides a methodological framework for arid region carbon sink enhancement and informs region-specific forest management strategies under climate change.</p>

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Assessing the potential for carbon storage enhancement in forests of Xinjiang Uygur autonomous region, China

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年8月14日

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  • Zhizhong Chen,
  • Mei Zan,
  • Jingjing Kong

摘要

Forest carbon sink potential assessment in arid regions remains a critical challenge for climate change mitigation. This study integrates multi-source remote sensing and forest inventory data to model Xinjiang’s forest age and carbon density (2019 baseline: 186.76 Mg/hm2 biomass, 93.38 Mg/hm2 carbon density, 46-year average age), revealing a south-to-north “low-high-low” spatial pattern. Using predictive models excluding anthropogenic and natural disturbances, we project forest carbon stock to reach 203.71 ± 2.31 Tg C by 2030 and 283.08 ± 4.23 Tg C by 2060, with declining carbon sink rates (3.67 ± 0.57 Tg C/a in 2019–2030 vs. 2.65 ± 0.56 Tg C/a in 2031–2060). Notably, Xinjiang’s forests could offset 14.6% and 9.5% of regional CO2 emissions during these periods. Economic cost analysis via panel fixed benefit modeling identifies afforestation suitability in Northeast Xinjiang, while conservation measures are prioritized elsewhere, particularly in high-elevation ridge zones. This research provides a methodological framework for arid region carbon sink enhancement and informs region-specific forest management strategies under climate change.