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A comparison of Lagrangian dispersion models coupled to a meteorological model for high stack air pollution forecast

机译:拉格朗日色散模型耦合到高堆气污染预测气象模型的比较

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Since 1994, operational air pollution forecast is routinely applied at the As Pontes coal-fired power plant, with a 350-m stack, in order to prevent local fumigation episodes. Over the last ten years, several improvements in the numerical models were done, to obtain more accurate air pollution forecasts on a daily basis. In this work, a comparison of the results obtained for different periods, using two different lagrangian dispersion models, Adaptive Puff Model 2 (APM2) and Lagrangian Particle Model (LPM), is presented. Both models, in different ways, were coupled to the same non-hydrostatic meteorological prediction model, Advanced Regional Prediction System (ARPS) adapted to this environment. From the results obtained, it can be seen that both models can reproduce the location of the main plume impacts measured in the area. However, LPM impacts are usually farther and shorter in time than APM2 impacts, in agreement with field data.
机译:自1994年以来,运营空气污染预测经常应用于Pontes燃煤发电厂,350米堆叠,以防止局部熏蒸集。在过去的十年中,完成了数值模型的几种改进,以每天获得更准确的空气污染预测。在这项工作中,呈现了使用两种不同的拉格朗日色散模型,自适应PUFF模型2(APM2)和拉格朗日粒子模型(LPM)的不同周期获得的结果的比较。两种模型以不同的方式耦合到相同的非静液压气象预测模型,适应这种环境的高级区域预测系统(ARP)。从获得的结果中,可以看出,两种模型可以再现在该区域中测量的主羽流的位置的位置。然而,与现场数据同意,LPM影响通常比APM2的影响更远,而不是APM2影响。

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