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  4. Developing and Evaluating Techniques for Localizing Pollutant Emission Sources with Open-Path Fourier Transform Infrared Measurements and Wind Data
 
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Developing and Evaluating Techniques for Localizing Pollutant Emission Sources with Open-Path Fourier Transform Infrared Measurements and Wind Data

Resource
JOURNAL OF THE AIR & WASTE MANAGEMENT ASSOCIATION v.58 n.10 pp.1360- 1369
Journal
Journal of the Air & Waste Management Association
Date Issued
2008
Date
2008
Author(s)
Wu, Chang-Fu
DOI
10.3155/1047.3289.58.10.1360
URI
http://ntur.lib.ntu.edu.tw//handle/246246/155766
Abstract
This paper presents the simulation and field evaluation results of two approaches to localize pollutant emission sources with open-path Fourier transform infrared (OP-FTIR) spectroscopy. The first approach combined the plume's peak location information reconstructed from the Smooth Basis Function Minimization (SBFM) algorithm and the wind direction data to calculate source projection lines. In the second approach, the plume's peak location was determined with the Monte Carlo methodology by randomly sampling within the beam segment having the largest path-integrated concentration. We first conducted a series of simulation studies to investigate the sensitivity of using different basis functions in the SBFM algorithm. It was found that fitting with the beta and Weibull basis functions generally gave better estimates of the peak locations than with the normal basis function when the plumes were mainly within the OP-FTIR's monitoring line. However, for plumes that were symmetric to the peak position or spread over the OP-FTIR, fitting with the normal basis function gave better performance. In the field experiment, two tracer gases were released simultaneously from two locations and the OP-FTIR collected data downwind from the sources with a maximum beam path length of 97 m. For the first approach, the release locations were within the 0. 25- to 0.5-probability area only after the uncertainty of the peak locations was included in the calculation process. The second approach was easy to implement and still performed as satisfactorily as the first approach. The distances from the sources to the best-fit lines (i.e., the regression lines) of the estimated locations were smaller than 10 m.
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journal article
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