Abstract In this work, an advanced dynamically adaptive unstructured mesh technique is introduced to photochemical modeling, which provides a consistent way to resolve the complex chemical transport processes over a wide range of spatial scales from meters (near point sources) up to hundred kilometers without the Gaussian distribution assumption (often used in existing subgrid Plume-in-Grid (PinG) models, such as RPM and SCICHEM). To assess the performance of the new photochemical model, the numerical results (NO x and O 3 ) have been compared to the Southern Oxidants Study (SOS) 1999 aircraft plume measurements, where the range of the emission intensity is from 1.8 to 13.9 ton/h. The relative error in the peak value of NO x and O 3 is between 10%–20% within 66 km downwind distance. The results show that the use of dynamically adaptive meshes can reproduce the details of the plume chemistry evolution: the slender puff structure of high NO x concentrations within a few kilometers width near the point sources, and the wing-like structure of ozone concentration during the plume growth, which is hard to capture for the PinG models or photochemical grid models.

中文翻译：

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一种新的各向异性自适应网格光化学模型，用于电厂羽流中臭氧的形成

摘要 在这项工作中，一种先进的动态自适应非结构​​化网格技术被引入到光化学建模中，它提供了一种一致的方法来解决从米（近点源）到数百公里的广泛空间尺度上的复杂化学输运过程，而无需高斯分布假设（常用于现有的子网格 Plume-in-Grid (PinG) 模型，例如 RPM 和 SCICHEM）。为了评估新光化学模型的性能，将数值结果（NO x 和 O 3 ）与南方氧化剂研究 (SOS) 1999 年飞机羽流测量值进行了比较，其中排放强度范围为 1.8 至 13.9 吨/ H。NO x 和O 3 峰值的相对误差在66 km顺风距离内在10%~20%之间。