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首页> 外文期刊>Engineering in Life Sciences >A Dispersion Modeling Study of Major VOCs from Non-Point Emission Sources in the Urban Atmospher
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A Dispersion Modeling Study of Major VOCs from Non-Point Emission Sources in the Urban Atmospher

机译:城市大气中非点源排放中主要挥发性有机化合物的色散建模研究

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摘要

To assist with the understanding and solving of toxic air pollutant problems in urban areas, an atmospheric dispersion model, SKYDM, was developed with three preprocessors (meteorology, emission, and topography), and a physical process and chemical decay term based on NOx-O3-RH photochemistry in the actual atmosphere. SKYDM can work with multicomponents in a single model run, as well as with a single compound in a model run and produces 2D meteorological field results due to an integration approach. The present study aims to develop and evaluate a SKYDM at local spatial scales, in the short term. A comparative study is conducted to estimate the effects of model parameters in defining the applicability limits of dispersion models and to examine the integration approach methodology. All simulations are run for volatile organic compounds (VOCs) such as BTXS (Benzene, Toluene, Xylene, and Styrene) emitted from non-point sources, located at 151villages in seven divisions, in a northeastern portion of Seoul, Korea, with eight different meteorological data sets during 2002. Modeled toluene concentrations are compared with those observed at ten monitoring sites. The main findings of the present study are as follows: (a) Model uncertainties are obviously caused by limitations of meteorological conditions and emission and topographical information, by removal processes, and by user errors or application skills - the chemical decay term was a comparatively significant parameter in the removal of toxic air pollutants, (b) the integration approach indicated a correlation between observations and the model, and (c) the SKYDM showed potential as a useful tool for assessing the air quality in urban areas. In further work, the SKYDM will be upgraded to an improving model algorithm with fully detailed input information, and evaluated in comparison with other Gaussian dispersion models.
机译:为了帮助理解和解决城市中的有毒空气污染物问题,开发了一种大气扩散模型SKYDM,该模型具有三个预处理器(气象,排放和地形),以及基于NOx-O3的物理过程和化学衰减项-在实际大气中的RH光化学。由于集成方法,SKYDM可以在单个模型运行中使用多组分,也可以在模型运行中使用单个化合物,并且可以产生2D气象现场结果。本研究旨在在短期内开发和评估当地空间尺度上的SKYDM。进行了一项比较研究,以评估模型参数在定义离散度模型的适用范围方面的效果,并研究集成方法。所有模拟都是针对非定点源排放的挥发性有机化合物(VOC),例如BTXS(苯,甲苯,二甲苯和苯乙烯)进行的,这些源位于韩国首尔东北部的七个分区的151个村中,有八种不同2002年的气象数据集。将模拟的甲苯浓度与在十个监测点观察到的浓度进行了比较。本研究的主要发现如下:(a)模型的不确定性显然是由于气象条件,排放和地形信息的局限性,清除过程以及用户的错误或应用技巧所致-化学衰减项是一个相对重要的因素去除有毒空气污染物的参数,(b)整合方法表明观测值与模型之间具有相关性,(c)SKYDM显示出潜力,可作为评估城市空气质量的有用工具。在进一步的工作中,SKYDM将升级为具有完全详细输入信息的改进模型算法,并与其他高斯色散模型进行比较。

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