可视化城市空气质量使用aermod, calpuff和CFD模型:一个关键的审查

N. Ridzuan, U. Ujang, S. Azri, T. Choon
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引用次数: 5

摘要

摘要空气质量水平的下降会影响人体健康,尤其是呼吸和循环系统。这是因为有害颗粒会通过暴露在周围环境中进入人体。空气污染事件的存在是影响城区空气质量较低的原因之一。为了监测这一事件,需要对城市空气质量进行适当的管理,以解决和减少对人类和环境的影响。管理城市空气质量的方法之一是模拟环境空气污染物。因此,本文回顾了AERMOD, CALPUFF和CFD三种建模工具,以实现城市空气污染物的可视化。这三个工具在模拟空气质素方面各具功能。AERMOD适用于短距离色散模型,CALPUFF适用于大范围色散模型。CFD模型的不同之处在于,该模型不仅适用于空气质量建模,还可以用于服装通风等广泛的应用。正因为如此,AERMOD和CALPUFF模型可以被归为空气质量建模工具组,而CFD建模工具则被归为另一组,即非特定的建模工具组,可以在许多研究领域实现。早期的空气质量研究产生了二维(2D)可视化结果。但是这种技术也有一些缺点。它不能提供在现实世界中感知到的三维(3D)污染物的高度信息和确切位置。此外,它不能很好地代表整个研究区域的风运动。为了克服这一问题,需要在城市空气质量研究中实施三维可视化。因此,本文旨在更好地理解建模工具与可视化技术用于所执行的研究结果。
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VISUALISING URBAN AIR QUALITY USING AERMOD, CALPUFF AND CFD MODELS: A CRITICAL REVIEW
Abstract. Degradation of air quality level can affect human’s health especially respiratory and circulatory system. This is because the harmful particles will penetrate into human’s body through exposure to surrounding. The existence of air pollution event is one of the causes for air quality to be low in affected urban area. To monitor this event, a proper management of urban air quality is required to solve and reduce the impact on human and environment. One of the ways to manage urban air quality is by modelling ambient air pollutants. So, this paper reviews three modelling tools which are AERMOD, CALPUFF and CFD in order to visualise the air pollutants in urban area. These three tools have its own capability in modelling the air quality. AERMOD is better to be used in short range dispersion model while CALPUFF is for wide range of dispersion model. Somehow, it is different for CFD model as this model can be used in wide range of application such as air ventilation in clothing and not specifically for air quality modelling only. Because of this, AERMOD and CALPUFF model can be classified in air quality modelling tools group whereas CFD modelling tool is classified into different group namely a non-specific modelling tool group which can be implemented in many fields of study. Earlier air quality researches produced results in two-dimensional (2D) visualization. But there are several of disadvantages for this technique. It cannot provide height information and exact location of pollutants in three-dimensional (3D) as perceived in real world. Moreover, it cannot show a good representation of wind movement throughout the study area. To overcome this problem, the 3D visualization needs to be implemented in the urban air quality study. Thus, this paper intended to give a better understanding on modeling tools with the visualization technique used for the result of performed research.
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