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  • 1
    Language: English
    In: Proceedings of the National Academy of Sciences of the United States of America, 19 May 2015, Vol.112(20), pp.6325-30
    Description: High-volume hydraulic fracturing (HVHF) has revolutionized the oil and gas industry worldwide but has been accompanied by highly controversial incidents of reported water contamination. For example, groundwater contamination by stray natural gas and spillage of brine and other gas drilling-related fluids is known to occur. However, contamination of shallow potable aquifers by HVHF at depth has never been fully documented. We investigated a case where Marcellus Shale gas wells in Pennsylvania caused inundation of natural gas and foam in initially potable groundwater used by several households. With comprehensive 2D gas chromatography coupled to time-of-flight mass spectrometry (GCxGC-TOFMS), an unresolved complex mixture of organic compounds was identified in the aquifer. Similar signatures were also observed in flowback from Marcellus Shale gas wells. A compound identified in flowback, 2-n-Butoxyethanol, was also positively identified in one of the foaming drinking water wells at nanogram-per-liter concentrations. The most likely explanation of the incident is that stray natural gas and drilling or HF compounds were driven ∼ 1-3 km along shallow to intermediate depth fractures to the aquifer used as a potable water source. Part of the problem may have been wastewaters from a pit leak reported at the nearest gas well pad-the only nearby pad where wells were hydraulically fractured before the contamination incident. If samples of drilling, pit, and HVHF fluids had been available, GCxGC-TOFMS might have fingerprinted the contamination source. Such evaluations would contribute significantly to better management practices as the shale gas industry expands worldwide.
    Keywords: Marcellus Shale ; High-Volume Hydraulic Fracturing ; Natural Gas ; Shale Gas ; Water Quality ; Water Movements ; Extraction and Processing Industry -- Methods ; Groundwater -- Chemistry ; Natural Gas -- Adverse Effects ; Water Pollutants, Chemical -- Analysis ; Water Supply -- Analysis
    ISSN: 00278424
    E-ISSN: 1091-6490
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  • 2
    Language: English
    In: Journal of Chromatography A, June 1, 2012, Vol.1240, p.156(9)
    Description: To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.chroma.2012.03.072 Byline: Song Yang (a), Jeremy S. Nadeau (c), Elizabeth M. Humston-Fulmer (c), Jamin C. Hoggard (c), Mary E. Lidstrom (a)(b), Robert E. Synovec (c) Keywords: GC-MS; PARAFAC; Peak deconvolution;.sup.12C/.sup.13C isotopomer determination; Metabolomics;.sup.13C flux analysis Abstract: a* GC-MS with chemometrics for analyzing coeluting.sup.12C and.sup.13C labeled contributions. a* The stacked samples in GC-MS create a three-dimensional data cube. a* PARAFAC is utilized for mathematical peak deconvolution and isotopic isolation. a* The accuracy and precision of metabolomics and.sup.13C flux analysis are enhanced. Author Affiliation: (a) Department of Chemical Engineering, University of Washington, Seattle, WA 98195-2180, USA (b) Department of Microbiology, University of Washington, Seattle, WA 98195-2180, USA (c) Department of Chemistry, University of Washington, Seattle, WA 98195-1700, USA Article History: Received 25 January 2012; Revised 17 March 2012; Accepted 21 March 2012
    Keywords: Mass Spectrometry ; Chromatography
    ISSN: 0021-9673
    Source: Cengage Learning, Inc.
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  • 3
    Language: English
    In: Journal of chromatography, 2012, Vol.1240, pp.156-164
    Description: A novel method for the analysis of nearly co-eluting ¹²C and ¹³C isotopically labeled metabolites has been developed and evaluated for gas chromatography coupled to mass spectrometry (GC–MS) data. The method utilizes parallel factor analysis (PARAFAC) with two-dimensional GC–MS data when sample replicates are aligned and stacked in series to create a three-dimensional data cube for mathematical peak deconvolution and ¹²C and ¹³C contribution isolation, with the intent of increasing the accuracy and precision of quantitative metabolomics and ¹³C flux analysis. The platform is demonstrated with ¹³C-labeled metabolite extracts, generated via biosynthesis, added as an internal standard to unlabeled ¹²C metabolites extracted from the methanol-utilizing bacterium Methylobacterium extorquens AM1. Eleven representative metabolites that are common targets for flux analysis were chosen for validation. Good quantitative accuracy and precision were acquired for a 5.00μM known metabolite concentration (for the 11 metabolites), with an average predicted concentration of 5.07μM, and a RSD range of 1.2–13.0%. This study demonstrates the ability to reliably deconvolute ¹²C-unlabeled and ¹³C-labeled contributions for a given metabolite. Additionally, using this chemical analysis platform, a dynamic flux experiment is presented in which the incorporation of ¹³C-labeled cell extract can be detected in the methane-utilizing bacterium Methylosinus trichosporium OB3b and measured temporally. ; p. 156-164.
    Keywords: Metabolites ; Chemometrics ; Chemical Analysis ; Gas Chromatography-Mass Spectrometry ; Factor Analysis ; Bacteria ; Methylobacterium Extorquens ; Biosynthesis ; Metabolomics ; Methylosinus Trichosporium
    ISSN: 0021-9673
    Source: AGRIS (Food and Agriculture Organization of the United Nations)
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  • 4
    Language: English
    In: Journal of Chromatography A, 01 June 2012, Vol.1240, pp.156-164
    Description: ► GC–MS with chemometrics for analyzing coeluting C and C labeled contributions. ► The stacked samples in GC–MS create a three-dimensional data cube. ► PARAFAC is utilized for mathematical peak deconvolution and isotopic isolation. ► The accuracy and precision of metabolomics and C flux analysis are enhanced. A novel method for the analysis of nearly co-eluting C and C isotopically labeled metabolites has been developed and evaluated for gas chromatography coupled to mass spectrometry (GC–MS) data. The method utilizes parallel factor analysis (PARAFAC) with two-dimensional GC–MS data when sample replicates are aligned and stacked in series to create a three-dimensional data cube for mathematical peak deconvolution and C and C contribution isolation, with the intent of increasing the accuracy and precision of quantitative metabolomics and C flux analysis. The platform is demonstrated with C-labeled metabolite extracts, generated via biosynthesis, added as an internal standard to unlabeled C metabolites extracted from the methanol-utilizing bacterium AM1. Eleven representative metabolites that are common targets for flux analysis were chosen for validation. Good quantitative accuracy and precision were acquired for a 5.00 μM known metabolite concentration (for the 11 metabolites), with an average predicted concentration of 5.07 μM, and a RSD range of 1.2–13.0%. This study demonstrates the ability to reliably deconvolute C-unlabeled and C-labeled contributions for a given metabolite. Additionally, using this chemical analysis platform, a dynamic flux experiment is presented in which the incorporation of C-labeled cell extract can be detected in the methane-utilizing bacterium OB3b and measured temporally.
    Keywords: Gc–MS ; Parafac ; Peak Deconvolution ; 12c/13c Isotopomer Determination ; Metabolomics ; 13c Flux Analysis ; Chemistry
    ISSN: 0021-9673
    E-ISSN: 18733778
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