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运用三维欧拉模型模拟近路反应性气态空气污染物的扩散。

Simulating near-road reactive dispersion of gaseous air pollutants using a three-dimensional Eulerian model.

机构信息

Zachry Department of Civil Engineering, Texas A&M University, College Station, TX, USA.

出版信息

Sci Total Environ. 2013 Jun 1;454-455:348-57. doi: 10.1016/j.scitotenv.2013.03.039. Epub 2013 Apr 9.

Abstract

In this study, the TAMNROM-3D model, a 3D Eulerian near-road air quality model with vehicle induced turbulence parameterization and a MOVES based emission preprocessor, is tested using near-road gaseous pollutants data collected near a rural freeway with 34% heavy duty vehicle traffic. Exhaust emissions of gasses from the vehicles are estimated using a lumped vehicle classification scheme based on the number of vehicle axles and the default county-level MOVES vehicle fleet database. The predicted dilution of CO and NOx in the downwind direction agrees well with observation, although the total NOx emission has to be scaled to 85% of its original emission rate estimated by the MOVES model. Using the atmospheric turbulent diffusion coefficient parameterization of Degrazia et al. (2000) with variable horizontal turbulent diffusion coefficient (Kxx) leads to slightly better predictions than a traditional non-height-dependent Kxx parameterization. The NO2 concentrations can be better predicted when emission of total NOx is split into NO and NO2 using the NO2 to NOx ratio of 29% measured near the road. Simulations using the SAPRC99 photochemical mechanism do not show significant changes in the predicted NO and NO2 concentrations near the road compared to simulations using a simple three-reaction mechanism that involves only NOx and O3. A regional air quality simulation in Houston, Texas during a high O3 episode in August 2000 shows that using the NO2 to NOx ratio of 29% instead of the traditional 5% leads to as much as 6ppb increase in 8-h O3 predictions.

摘要

在这项研究中,TAMNROM-3D 模型被测试,该模型是一个具有车辆诱导湍流参数化和基于 MOVES 的排放前处理器的 3D 欧拉近路空气质量模型,用于收集具有 34%重型车辆交通的农村高速公路附近的近路气态污染物数据。使用基于车辆轴数和默认县一级 MOVES 车辆车队数据库的集中式车辆分类方案来估计车辆排放的气体排放量。在顺风方向上,CO 和 NOx 的预测稀释与观测结果吻合较好,尽管必须将总 NOx 排放量缩小到 MOVES 模型估计的原始排放量的 85%。使用 Degrazia 等人(2000 年)的大气湍流扩散系数参数化,具有可变水平湍流扩散系数(Kxx),比传统的非高度依赖 Kxx 参数化可以更好地预测。当使用道路附近测量的 29%的 NO2 与 NOx 比值将总 NOx 排放分为 NO 和 NO2 时,可以更好地预测 NO2 浓度。与使用仅涉及 NOx 和 O3 的简单三反应机制相比,使用 SAPRC99 光化学反应机制进行模拟不会导致道路附近预测的 NO 和 NO2 浓度发生显著变化。在 2000 年 8 月臭氧高发期间,在德克萨斯州休斯顿进行的区域空气质量模拟表明,使用 29%的 NO2 与 NOx 比值而不是传统的 5%,会导致 8 小时 O3 预测值增加多达 6ppb。

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