通过陆地-河流-大气气流的混合建模,估计长江流域的河流N2O排放
Huihang Sun1, Yu Tian1, Wei Zhan1
1State Key Lab of Urban Water Resource and Environment, School of Environment, Harbin Institute of Technology, Harbin, 150090, China.
Water research
|October 28, 2023
概括
由于控制,长江的氧化 (N2O) 排放量减少,但城市河流的N2O排放量较高. 有针对性的管理是减少这些温室气体排放的关键.
科学领域:
- 环境科学 环境科学
- 生物地质化学生物地质化学
- 气候变化研究 气候变化研究
背景情况:
- 河流生态系统是全球主要的氧化 (N2O) 来源.
- 在不断变化的环境条件下了解河流中的N2O动态至关重要,但仍然不太了解.
- 人类活动对河流系统的负荷和N2O排放有重大影响.
研究的目的:
- 研究河流生态系统中N2O转移的模式.
- 量化人类和自然变化对N2O排放的影响.
- 开发河流N2O排放的预测模型.
主要方法:
- 开发了一个复合模型链,集成基于机制的建模和机器学习.
- 分析了2000年至2019年在长江流域的N2O排放和排放数据.
- 在城市与农村河流环境中比较N2O流量.
主要成果:
- 长江流域的N2O排放量从2000年的4.7亿克/年下降到2019年的2.8亿克/年.
- 通过控制改善水质是减少排放的主要驱动因素.
- 城市河流的N2O流量显著增加,与排放强度相关的非线性增加.
结论:
- 人类驱动的控制有效地减少了研究盆地的河流N2O排放.
- 与农村地区相比,城市N2O排放对排放的反应不同.
- 区域差异化的管理策略是有效减少N2O排放的必要条件.
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