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LAGRANGIAN VS. EULERIAN DISPERSION MODELING: EFFECTS OF WIND SHEAR ON POLLUTION DISPERSION

机译:拉格朗日VS. EULERIAN色散建模:风切变对污染色散的影响

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摘要

Using an accurate numerical method for simulating the advection and diffusion of pollution puffs it is demonstrated that point releases of pollution grow into a shape reflecting the vertical wind shear profile experienced by the puff within a time scale of a less than four hours. For distances beyond several 10s of kilometers from a release point, shear-related dispersion effects are probably the dominant mechanism affecting the area and magnitude of surface impacts. For assessing long-range pollutant dispersion, the common assumption that pollutants disperse as horizontally spherical "puffs" in the atmosphere is inherently inaccurate since shear-induced horizontal spreading of pollution is not a homogeneous "turbulent-like" diffusion process. A Lagrangian puff model can simulate an area impacted by a pollution puff only if larger shear-dependent horizontal puff dispersions are assumed. However, even if impacted areas are reasonably simulated, peak concentrations will be severely underestimated since atmospheric puffs influenced by even small amounts of wind shear are nonspherical. If horizontal dispersion coefficients in a Lagrangian puff model are adjusted so that peak concentrations are correctly simulated, then the calculated pollution impact area will be severely skewed. In shear environments, no choice of horizontal dispersion coefficients in a single-puff Lagrangian model will yield reasonable correlations with puffs that are skewed into nonspherical shapes by atmospheric wind shear.
机译:使用精确的数值方法来模拟污染抽吸的对流和扩散,结果表明污染的点释放在不到四小时的时间范围内增长为反映抽吸所经历的垂直风切变曲线的形状。对于距离释放点超过几十公里的距离,与剪切有关的分散效应可能是影响表面影响的面积和程度的主要机制。为了评估远程污染物的扩散,通常的假设是污染物在大气中以水平球形“粉扑”的形式扩散,这固有地是不准确的,因为剪切引起的污染物水平扩散不是均匀的“湍流状”扩散过程。拉格朗日粉扑模型仅在假定较大的依赖于剪切的水平粉扑分散体的情况下才能模拟受污染粉扑影响的区域。但是,即使对受影响的区域进行了合理的模拟,峰值浓度也将被严重低估,因为受少量风切变影响的吹气是非球形的。如果调整拉格朗日粉扑模型中的水平弥散系数,以便正确模拟峰值浓度,那么计算出的污染影响面积将严重偏斜。在剪切环境中,单吹拉格朗日模型中的水平弥散系数的选择将不会与由于大气风切变而歪斜成非球形形状的吹产生合理的相关性。

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