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 AbstractBiomarkers and asthma management: analysis and potential applications    Next AbstractDiscrimination and geo-spatial mapping of atmospheric VOC sources using full scan direct mass spectral data collected from a moving vehicle »

Rapid Commun Mass Spectrom


Title:Discrimination of constructed air samples using multivariate analysis of full scan membrane introduction mass spectrometry (MIMS) data
Author(s):Richards LC; Davey NG; Fyles TM; Gill CG; Krogh ET;
Address:"Applied Environmental Research Laboratories, Chemistry Department, Vancouver Island University, Nanaimo, British Columbia, Canada. Department of Chemistry, University of Victoria, Victoria, British Columbia, Canada"
Journal Title:Rapid Commun Mass Spectrom
Year:2018
Volume:32
Issue:4
Page Number:349 - 360
DOI: 10.1002/rcm.8049
ISSN/ISBN:1097-0231 (Electronic) 0951-4198 (Linking)
Abstract:"RATIONALE: Volatile and semi-volatile organic compounds (S/VOCs) are important atmospheric pollutants affecting both human and environmental health. They are directly measured as an unresolved mixture using membrane introduction mass spectrometry (MIMS). We apply chemometric techniques to discriminate, classify, and apportion air samples from a variety of sources. METHODS: Full scan mass spectra of lab-constructed air samples were obtained using a polydimethylsiloxane membrane interface and an electron ionization ion trap mass spectrometer. Normalized full scan spectra were analyzed using principal component analysis (PCA), cluster analysis, and k-nearest neighbours (kNN) for sample discrimination and classification. Multivariate curve resolution (MCR) was used to extract pure component contributions. Similar techniques were applied to VOC mixtures sampled from different woodsmoke emissions and from the headspace above aqueous hydrocarbon solutions. RESULTS: PCA successfully discriminated 32 constructed VOC mixtures from nearly 300 air samples, with cluster analysis showing similar results. Further, kNN classification (k = 1) correctly classified all but one test set sample, and MCR successfully identified the pure compounds used to construct the VOC mixtures. Real-world samples resulting from the combustion of different wood species and those associated with water contaminated with different commercial hydrocarbon products were similarly discriminated by PCA. CONCLUSIONS: Chemometric techniques have been evaluated using full scan MIMS spectra with a series of VOC mixtures of known composition containing known compounds, and successfully applied to samples with known sources, but unknown molecular composition. These techniques have application to source identification and apportionment in real-world environmental samples impacted by atmospheric pollutants"
Keywords:Air Pollutants/*analysis Environmental Monitoring/*methods Hydrocarbons/analysis Mass Spectrometry/*methods Multivariate Analysis Principal Component Analysis Smoke/analysis Volatile Organic Compounds/analysis;
Notes:"MedlineRichards, L C Davey, N G Fyles, T M Gill, C G Krogh, E T eng England 2017/12/27 Rapid Commun Mass Spectrom. 2018 Feb 28; 32(4):349-360. doi: 10.1002/rcm.8049"

 
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 17-11-2024