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Stochastic analysis of concentration field in a wake region

机译:尾流区浓度场的随机分析

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摘要

Introduction Identifying geographic locations in urban areas from which air pollutants enter the atmosphere is one of the most important information needed to develop effective mitigation strategies for pollution control. Materials and methods Stochastic analysis is a powerful tool that can be used for estimating concentration fluctuation in plume dispersion in a wake region around buildings. Only few studies have been devoted to evaluate applications of stochastic analysis to pollutant dispersion in an urban area. This study was designed to investigate the concentration fields in the wake region using obstacle model such as an isolated building model. We measured concentration fluctuations at centerline of various downwind distances from the source, and different heights with the frequency of 1 KHz. Concentration fields were analyzed stochastically, using the probability density functions (pdf). Stochastic analysis was performed on the concentration fluctuation and the pdf of mean concentration, fluctuation intensity, and crosswind mean-plume dispersion. Results The pdf of the concentration fluctuation data have shown a significant non-Gaussian behavior. The lognormal distribution appeared to be the best fit to the shape of concentration measured in the boundary layer. We observed that the plume dispersion pdf near the source was shorter than the plume dispersion far from the source. Our findings suggest that the use of stochastic technique in complex building environment can be a powerful tool to help understand the distribution and location of air pollutants.
机译:引言确定城市中空气污染物进入大气的地理位置,是制定有效的污染控制策略所需要的最重要的信息之一。材料和方法随机分析是一种功能强大的工具,可用于估算建筑物周围尾流区域中羽流分散中的浓度波动。很少有研究致力于评估随机分析在城市污染物扩散中的应用。本研究旨在使用障碍模型(例如,隔离建筑模型)调查尾流区域的浓度场。我们以1 KHz的频率测量了距源头不同顺风距离和不同高度的中心线的浓度波动。使用概率密度函数(pdf)随机分析浓度场。随机分析浓度波动和平均浓度,波动强度和侧风均质-色散的pdf。结果浓度波动数据的pdf显示出显着的非高斯行为。对数正态分布似乎最适合边界层中测得的浓度形状。我们观察到,靠近源的羽流散布比远离源的羽流散布短。我们的发现表明,在复杂的建筑环境中使用随机技术可以成为帮助了解空气污染物的分布和位置的强大工具。

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