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利用光学遥感测量和改进的一维径向羽流映射技术定位污染物排放源。

Locating pollutant emission sources with optical remote sensing measurements and an improved one-dimensional radial plume mapping technique.

作者信息

Wu Chang-fu, Lin Shih-Chun, Yeh Cheng-Kai

机构信息

Department of Public Health, National Taiwan University, Taipei 100, Taiwan.

出版信息

J Environ Monit. 2012 Apr;14(4):1203-10. doi: 10.1039/c2em10380j. Epub 2012 Mar 2.

DOI:10.1039/c2em10380j
PMID:22382995
Abstract

Previous studies have shown that there was a relatively large amount of uncertainty along the major wind direction in the results of locating emission sources using the one-dimensional radial plume mapping (RPM(1D)) technique based on optical remote sensing measurements. This paper proposes setting up an additional monitoring line that is perpendicular to the original scanning beam geometry to reduce this uncertainty. We first conducted a computer simulation study using the Gaussian dispersion model to generate the downwind concentrations of plumes from 400 source locations in a 201 m × 201 m spatial domain under various wind directions (n = 181). The optical remote sensing instrument was assumed to be at (0, 0) with two perpendicular monitoring lines, each of which had three beam segments of equal length. Each pair of the reconstructed downwind concentration profiles was then used to trace back to the source locations. The results showed that the accuracy of the method and its uncertainty were improved by using the proposed two-line RPM(1D) approach rather than the original one-line RPM(1D) approach at most simulated source locations. In a follow-up field experiment, a tracer gas was released at the coordinate of (100, 100). The release location was covered within the 0.25- to 0.5-probability area of the estimated results, and the distance between the actual and estimated source locations was 18.4 m (9.2% of the longest beam path).

摘要

先前的研究表明,基于光学遥感测量,使用一维径向羽流映射(RPM(1D))技术定位排放源的结果在主要风向沿线存在相对较大的不确定性。本文提出设置一条垂直于原始扫描光束几何形状的额外监测线,以减少这种不确定性。我们首先使用高斯扩散模型进行了计算机模拟研究,在201 m×201 m的空间域中,在各种风向(n = 181)下生成来自400个源位置的羽流顺风浓度。假设光学遥感仪器位于(0, 0)处,有两条垂直的监测线,每条监测线有三个等长的光束段。然后,每对重建的顺风浓度剖面用于追溯源位置。结果表明,在大多数模拟源位置,使用所提出的双线RPM(1D)方法比原始的单线RPM(1D)方法提高了该方法的精度及其不确定性。在后续的现场实验中,在(100, 100)坐标处释放了一种示踪气体。释放位置覆盖在估计结果的0.25至0.5概率区域内,实际源位置与估计源位置之间的距离为18.4 m(最长光束路径的9.2%)。

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