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从全球土壤中排放的氧化的数据驱动估计基于占主导地位的植被覆盖

Xingshuai Tian¹, Yulong Yin¹, Kai He¹

¹College of Resources and Environmental Sciences, National Academy of Agriculture Green Development, China Agricultural University, Beijing, China.

Global change biology

|July 18, 2023

概括

全球土壤氧化 (NO) 排放量很大,森林是主要的来源. 这项研究利用广泛的数据绘制了NO排放的地图,为缓解策略提供了关键的见解.

科学领域:

环境科学环境科学
生物地质化学生物地质化学
大气化学大气化学

背景情况:

土壤是全球二氧化 (NO) 排放的主要来源,但目前的估计存在很大的不确定性.
有限的观测和多因素影响导致土壤NO排放估计的不确定性.

研究的目的:

通过将现场观测与高分辨率环境数据相结合,绘制全球土壤NOx排放的地图.
计算全球和国家NO预算,并确定不同土地覆盖类型 (耕地,草地,森林) 对这些排放的贡献.
为了确定土壤NO排放的关键驱动因素.

主要方法:

整合了来自全球分布的地点的1356个现场NO观测结果.
利用高分辨率的气候,土壤和管理实践数据进行映射.
开发了基于数据的模型来估计全球和国家土壤NO排放量.

主要成果:

在2014年,总的地表NO2排放量估计为9.4 Tg N年−1.
森林贡献了最大的份额 (5.9 Tg N年−1),其次是草原 (1.7 Tg N年−1) 和耕地 (1.8 Tg N年−1).
土壤NO排放主要受到输入,水输入和土壤pH的影响. 在57%的受调查国家中,森林主导了NO排放.

结论:

通过使用数据驱动模型,提供全球和国家土壤NOx排放的更新,可靠的库存.
这些发现对于指导缓解土壤NO排放的指导至关重要.
这些估计可以与生物地质化学模型相结合,用于进一步的研究和政策制定.

关键词:

背景二氧化排放情况数据驱动模型是基于数据的模型.占主导地位的植被覆盖.全球土壤全球土壤影响因素的影响因素.土壤中氧化排放的排放量

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