在中国种植树木的碳封存潜力
Ling Yao1, Tang Liu1, Jun Qin2,3
1State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, PR China.
Nature communications
|September 27, 2024
概括
中国中国中国中国.
科学领域:
- 环境科学 环境科学
- 林业林业 林业 林业 林业
- 气候变化缓解缓解 气候变化缓解
背景情况:
- 中国雄心勃勃的碳中和目标需要有效的植林战略.
- 优化树木种植以最大限度地封存碳需要严格的评估.
研究的目的:
- 开发一种机器学习框架,用于评估树木生长的适宜性和碳捕获潜力.
- 在中国种植树木的各种场景下绘制碳汇潜力图.
主要方法:
- 使用机器学习框架集成各种环境变量.
- 量化树木生长适宜性及其与树木数量的关系.
- 树木种植和生物质碳储量之间确立的相关性.
主要成果:
- 确定了种植树木的最佳位置和策略,以最大限度地减少碳排放.
- 在不同的场景中映射了碳汇潜力.
- 预计种植447亿棵树可以扣留5.9 PgC,使中国2020年工业二氧化碳排放量翻一番.
结论:
- 现有森林内的树木密集化是碳捕获的经济可行和有效策略.
- 建议在大规模种植计划中优先考虑树木密集化.
- 在协调生态系统管理政策下,中国的森林资源可能增加96亿立方米.
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