Advanced Environmental Monitoring 2008
DOI: 10.1007/978-1-4020-6364-0_2
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Radial Plume Mapping: A US EPA Test Method for Area and Fugitive Source Emission Monitoring Using Optical Remote Sensing

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Cited by 19 publications
(16 citation statements)
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“…Gaseous flux from each identified leak was estimated following methods developed for plume mapping using multiple path-integrated concentration measurements [18]. Readings were taken across multiple vertical planes at, and downwind of, the area of interest and used to construct a concentration profile.…”
Section: Methodsmentioning
confidence: 99%
See 1 more Smart Citation
“…Gaseous flux from each identified leak was estimated following methods developed for plume mapping using multiple path-integrated concentration measurements [18]. Readings were taken across multiple vertical planes at, and downwind of, the area of interest and used to construct a concentration profile.…”
Section: Methodsmentioning
confidence: 99%
“…From a given set of planar path-integrated concentration data, random selections of measurements (minimum 5) in the planes were drawn for fitting by SBFM to generate a set of 10,000 possible realizations of two-dimensional concentration fields. The concordance correlation factor (CCF), which compares measured path-integrated concentrations to those specified by identical paths taken through the reconstructed field, was used to assess the validity of each reconstruction [18]. Reconstructions with CCF<0.6 show poor fit to the Gaussian mathematical function, and were therefore discarded.…”
Section: Methodsmentioning
confidence: 99%
“…In this experiment, the number of reflectors went up to 14, and the number of optical rays went up to 20, with the longest length being 39.0 m and the shortest length 12.4 m. The structure of optical rays applied in the SBFM experiment was relatively simple. The structure of optical rays by Hashmonay et al 21 was used in the SBFM experiment [ Fig. 3(b)].…”
Section: Methodsmentioning
confidence: 99%
“…[13] First, using the ground-level PIC data, the values of σ y and m y of Equation 1 are estimated by fitting the data into a univariate Gaussian function via minimization of the sum of squared errors (SSE). With the values of σ y and m y estimated from the groundlevel PIC data, the values of A and σ z of Equation 2 are then estimated from fitting the above-ground PIC data into the bivariate Gaussian function.…”
Section: Vrpm Methodology For Ground-level Emissionmentioning
confidence: 99%