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Multi-scale modeling of roadway air quality impacts: Development and evaluation of a Plume-in-Grid model

机译:道路空气质量影响的多尺度建模:网格羽状模型的开发和评估

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摘要

Eulerian three-dimensional (3D) grid-based models are widely used in air quality modeling. In such models, emissions are instantaneously diluted within the grid cells and, therefore, the near-source impacts of large point and line sources cannot be properly resolved. Plume-in-Grid models (PinG) use a subgrid-scale treatment to better represent local source contributions in an Eulerian grid-based simulation. PinG models already exist for point sources. However, modeling emissions from roadway traffic with point sources implies a very large computational burden. We present here a new PinG model that uses a Gaussian line source model, better suited than point sources to model roadway traffic emissions, embedded within an Eulerian model. The model is evaluated with a large dataset of nitrogen dioxide (NO_2) concentrations over a 800 km road network. The PinG model leads to greater NO_2 concentrations and shows better performance than the Eulerian model.
机译:基于欧拉三维(3D)网格的模型广泛用于空气质量建模。在这样的模型中,排放在网格单元内被即时稀释,因此,大的点和线源的近源影响无法得到适当解决。网格羽状模型(PinG)使用亚网格规模的处理方法,以更好地表示基于欧拉网格的模拟中的本地源贡献。点源的PinG模型已经存在。但是,使用点源对道路交通的排放进行建模意味着很大的计算负担。我们在此展示一种新的PinG模型,该模型使用嵌入在欧拉模型中的高斯线源模型,比点源更适合于模型道路交通排放。该模型使用800公里公路网上的大型二氧化氮(NO_2)浓度数据集进行了评估。 PinG模型导致的NO_2浓度更高,并且表现出比欧拉模型更好的性能。

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