高分辨率建模甲羽:验证和灵敏度实验,探索排放量化方法
Rakesh Yuvaraj1,2, Thomas Lauvaux1,2, Charbel Abdallah1
1Groupe de Spectrométrie Moléculaire et Atmosphérique (GSMA), Université de Reims-Champagne Ardenne, UMR CNRS 7331, Reims 51100, France.
Environmental science & technology
|January 30, 2026
概括
这项研究使用火力学模拟 (FDS) 与大模拟 (LES) 准确量化甲 (CH4) 羽毛. 该模型通过无人机数据验证,改进了排放测量.
科学领域:
- 环境科学环境科学
- 大气科学 大气科学
- 计算流体动力学 计算流体动力学
背景情况:
- 来自各种来源的甲 (CH4) 排放量量化是具有挑战性的,因为复杂的羽毛动态和大气变化.
- 卫星和空中平台检测到CH4,但精确的量化受到微小大气变化所阻碍.
- 无人驾驶飞行器 (UAV) 的测量在羽毛量化方面面临不确定性.
研究的目的:
- 为了解决基于无人机的CH4羽毛测量的不确定性.
- 为了验证大模拟 (LES) 模式中的火力学模拟 (FDS) 模型,用于CH4羽毛量化.
- 提高甲排放量定量方法的准确性.
主要方法:
- 在大模拟 (LES) 模式中使用火力动力学模拟 (FDS).
- 利用来自LiDAR数据集的平均风力数据.
- 验证了FDS模型与无人机在受控释放实验中的现场CH4度数据.
主要成果:
- 对于直径>0.6厘米的管道,FDS准确地复制了观察到的CH4的幅度和时空变化.
- 气体出口速度,障碍物和地形形态显著影响近场羽毛动力学.
- 气体温度在更高的质量流速下会影响羽毛的行为.
结论:
- 高分辨率的 LES 建模,特别是 FDS,为了解 CH4 羽流动力学增加了重大价值.
- 经过验证的FDS-LES模型可以改进目前的甲排放量化方法.
- 准确的CH4排放量化对于环境监测和减缓工作至关重要.
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