Bedoukian   RussellIPM   RussellIPM   Piezoelectric Micro-Sprayer


Home
Animal Taxa
Plant Taxa
Semiochemicals
Floral Compounds
Semiochemical Detail
Semiochemicals & Taxa
Synthesis
Control
Invasive spp.
References

Abstract

Guide

Alphascents
Pherobio
InsectScience
E-Econex
Counterpart-Semiochemicals
Print
Email to a Friend
Kindly Donate for The Pherobase

« Previous Abstract"Data on combustion, performance and emissions of a 6.8?ª+L, 6-cylinder, Tier II diesel engine"    Next AbstractInvasive mechanism and management strategy of Bemisia tabaci (Gennadius) biotype B: progress report of 973 Program on invasive alien species in China »

Analyst


Title:Airborne passive Fourier transform infrared remote sensing of methanol vapor from industrial emissions
Author(s):Wan B; Small GW;
Address:"Department of Chemistry & Optical Science and Technology Center, University of Iowa, Iowa City, IA 52242, USA"
Journal Title:Analyst
Year:2008
Volume:20080911
Issue:12
Page Number:1776 - 1784
DOI: 10.1039/b802557f
ISSN/ISBN:1364-5528 (Electronic) 0003-2654 (Linking)
Abstract:"Passive Fourier transform infrared (FT-IR) remote sensing measurements are applied to the detection of methanol vapor plumes released from a chemical manufacturing facility. With the spectrometer mounted in a downward-looking mode on a fixed-wing aircraft, overflights of the facility are made during the methanol release. Signal processing and pattern recognition methods are applied to the acquired data for the purpose of constructing an automated classification algorithm for the methanol detection. The analysis is based on the use of short, digitally filtered segments of the raw interferogram data collected by the spectrometer. The classifiers are trained with data collected on the ground by use of an experimental protocol designed to simulate background conditions observed from the air. Optimization of the digital filtering and interferogram segment parameters leads to successful classifiers based on 100 or 120 interferogram points. The optimal interferogram segment location is found to be 95-points displaced from the centerburst, and the best performing digital filters are centered on the methanol C-O stretching band at 1036 cm(-1) and have a passband full-width at half-maximum of 100 to 160 cm(-1). The best classifiers achieve classification errors of less than 1% and are observed to be resistant to possible interference effects from species such as ethanol and ozone. This work demonstrates the utility of airborne passive FT-IR remote sensing measurements of volatile organic compounds under complex background conditions such as those encountered while monitoring an operating industrial facility"
Keywords:
Notes:"PubMed-not-MEDLINEWan, Boyong Small, Gary W eng England 2008/12/17 Analyst. 2008 Dec; 133(12):1776-84. doi: 10.1039/b802557f. Epub 2008 Sep 11"

 
Back to top
 
Citation: El-Sayed AM 2024. The Pherobase: Database of Pheromones and Semiochemicals. <http://www.pherobase.com>.
© 2003-2024 The Pherobase - Extensive Database of Pheromones and Semiochemicals. Ashraf M. El-Sayed.
Page created on 29-12-2024