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在复杂的水生网络中,驱动因素和溶解N2O度的预测模型
Li Zhang1, Dongli She2, Menghua Xiao3
1College of Agricultural Science and Engineering, Hohai University, Nanjing 211100, China.
酸和水温是内陆水域的氧化 (N2O) 排放的主要驱动因素. 一个新的综合框架准确地量化了这些温室气体来源,以有效减缓.
科学领域:
- 环境科学 环境科学
- 生态生态学 生态生态学
- 生物地质化学生物地质化学
背景情况:
- 内水网络是氧化 (N2O) 的重要来源,氧化是一种强大的温室气体.
- 这些系统的复杂性阻碍了准确的N2O排放量化.
研究的目的:
- 开发一种用于因果推断和N2O排放的非线性预测建模的综合框架.
- 确定中国太湖盆地N2O变化的关键驱动因素.
主要方法:
- 组合结构方程建模 (SEM),机器学习 (ML) 和夏普利添加式扩展 (SHAP).
- 利用一个框架,将因果推理与非线性预测建模结合.
主要成果:
- 酸- (NO3−-N) 和水温 (WT) 是影响N2O变化的主要因素.
- 溶解有机碳 (DOC) 在N2O生产中扮演着双重角色:一个宏观的水槽和一个微观的催化剂.
- 使用四个常规参数的节模型实现了区域评估的令人满意的预测能力 (测试R2 = 0.54).
结论:
- 开发的框架为理解复杂的水生生态系统提供了可扩展和可转移的方法.
- 为盆地规模N2O估计和有针对性的温室气体减排战略提供了一个强大的工具.
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