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碳农业实践评估:模拟弗兰德斯,比利时土壤有机碳的空间变化

Stefano Spotorno¹, Anne Gobin², Fien Vanongeval²

¹Department of Civil, Chemical and Environmental Engineering (DICCA), University of Genoa, Via Opera Pia 15, Genova 16145, Italy; University School for Advanced Studies IUSS, Pavia, Italy.

The Science of the total environment

|February 29, 2024

概括

覆盖作物等碳农业实践可以将农业土壤的碳排放量减少高达60%. 土壤有机碳 (SOC) 水平对基线碳输入和土壤初始碳含量最敏感.

科学领域:

农业科学农业科学
环境科学环境科学
气候变化缓解缓解气候变化缓解

背景情况:

土壤有机碳 (SOC) 捕获对于减缓气候变化和可持续农业至关重要.
欧盟 (EU) 激励温室气体 (GHG) 减少,增加了对农业中创新的碳封存战略的需求.
碳农业 (CF) 提供了一个有前途的方法,但缺乏用于计算SOC动态的标准化工具.

研究的目的:

使用RothC模型,对比利时弗兰德斯的SOC动态进行空间分析.
模拟和评估特定CF实践,即覆盖作物 (CC) 和CC作物轮换对SOC的影响.
在RothC模型中识别影响SOC变化的关键变量.

主要方法:

利用RothC模型对比利时弗兰德斯的农业地块的SOC进行空间分析.
模拟了两个CF实践:单独使用覆盖作物和包含覆盖作物的作物轮换.
通过比较与类似研究的结果来评估模型性能,并使用Pearson相关系数分析变量灵敏度.

主要成果:

模拟的CF实践表明,农业土壤碳排放的减缓潜力高达当前预测的60%.
对于总SOC的RothC模型的结果对"正常运行" (BAU) 碳输入 (r=-0.78) 和初始碳含量 (r=-0.50) 非常敏感.
弗兰德斯目前的CF实践可能不足以实现碳净封存,这凸显了需要更有效的解决方案.

结论:

覆盖作物和增强的作物轮换显示出减轻农业土壤碳排放的潜力.
对SOC动态的准确建模需要更大的数据可用性和可访问性.
对更强大的CF策略进行进一步的研究是必要的,以实现农业土壤中显著的净碳捕获.

关键词:

土壤中的碳捕集.覆盖作物覆盖作物改善了作物旋转的情况.这是RothC RothC.土壤有机碳 (SOC) 是一种有机碳.

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