Compound Identification in Organic Aerosols Using Temperature-Programmed Thermal Desorption Particle Beam Mass Spectrometry

1999 ◽  
Vol 71 (16) ◽  
pp. 3428-3435 ◽  
Author(s):  
Herbert J. Tobias ◽  
Paul J. Ziemann
Keyword(s):  
Mass Spectrometry ◽  
Thermal Desorption ◽  
Organic Aerosols ◽  
Particle Beam ◽  
Compound Identification ◽  
Temperature Programmed

Real-Time Chemical Analysis of Organic Aerosols Using a Thermal Desorption Particle Beam Mass Spectrometer

2000 ◽  
Vol 33 (1-2) ◽  
pp. 170-190 ◽  
Author(s):  
Herbert J. Tobias ◽  
Peter M. Kooiman ◽  
Kenneth S. Docherty ◽  
Paul J. Ziemann
Keyword(s):  
Chemical Analysis ◽  
Real Time ◽  
Mass Spectrometer ◽  
Thermal Desorption ◽  
Organic Aerosols ◽  
Particle Beam

Online analysis of secondary organic aerosols from OH-initiated photooxidation and ozonolysis of α-pinene, β-pinene, Δ3-carene and d-limonene by thermal desorption–photoionisation aerosol mass spectrometry

2017 ◽  
Vol 14 (2) ◽  
pp. 75 ◽  
Author(s):  
Wenzheng Fang ◽  
Lei Gong ◽  
Liusi Sheng
Keyword(s):  
Mass Spectrometry ◽  
Thermal Desorption ◽  
Mass Spectra ◽  
Secondary Organic Aerosols ◽  
Organic Aerosols ◽  
Organic Aerosol ◽  
Oxidation Products ◽  
Online Analysis ◽  
Aerosol Mass ◽  
Aerosol Mass Spectrometry

Environmental contextSecondary organic aerosol, formed by oxidation of volatile precursors such as monoterpenes, is a major contributor to the total atmospheric organic aerosol. We focus on the online mass spectrometric analysis of the aerosol generated by oxidation products of four major monoterpenes in an environmental chamber. Numerous important monoterpene oxidation products were clearly observed and provided a direct comparison of the formation of biogenic secondary organic aerosols. AbstractWe present here thermal desorption–tunable vacuum ultraviolet time-of-flight photoionisation aerosol mass spectrometry (TD-VUV-TOF-PIAMS) for online analysis of biogenic secondary organic aerosols (BSOAs) formed from OH-initiated photooxidation and dark ozonolysis of α-pinene, β-pinene, Δ3-carene and d-limonene in smog chamber experiments. The ‘soft’ ionisation at near-threshold photon energies (≤10.5eV) used in this study permits direct measurement of the fairly clean mass spectra, facilitating molecular identification. The online BSOA mass spectra compared well with previous offline measurements and most of the important monoterpene oxidation products were clearly found in the online mass spectra. Oxidation products such as monoterpene-derived acids (e.g. pinic acid, pinonic acid, 3-caronic acid, limononic acid, limonalic acid), ketones (e.g. norpinone, limonaketone), aldehydes (e.g. caronaldehyde, norcaronaldehyde, limononaldehyde) and multifunctional organics (e.g. hydroxypinonaldehydes, hydroxy-3-caronic aldehydes, hydroxylimononic acid) were tentatively identified. The online TD-VUV-TOF-PIAMS mass spectra showed that the OH-initiated photooxidation and ozonolysis of the same monoterpenes produced some similar BSOA products; for example, 3-caric acid, 3-caronic acid, 3-norcaronic acid, 3-norcaralic acid, caronaldehyde and norcaronaldehyde were observed in both photooxidation and ozonolysis of Δ3-carene. However, they could be formed through different pathways. Some of the same products and isomers (e.g. 10-oxopinonic acid, pinonic acid, norpinic acid, hydroxyl pinonaldehyde, norpinonic acid, norpinone) were formed during the photooxidation and ozonolysis of α-pinene and β-pinene. However, several different BSOA products were generated in these photooxidation and ozonolysis reactions due to their different parent structures. The OH–monoterpene reaction generated higher-molecular-weight products than O3–monoterpene owing to multiple OH additions to the unsaturated carbon bond. The online observation of key BSOA products provided a direct comparison of BSOA formation among different monoterpenes and insights into the formation pathways in the OH-initiated photooxidation and ozonolysis of monoterpenes.

scholarly journals Analysis of Pesticide Residues in Fruits, Vegetables, and Milk by Gas Chromatography/Tandem Mass Spectrometry

1999 ◽  
Vol 82 (4) ◽  
pp. 982-990 ◽  
Author(s):  
Robert S Sheridan ◽  
John R Meola
Keyword(s):  
Mass Spectrometry ◽  
Gas Chromatography ◽  
Ion Trap ◽  
Ion Trap Mass Spectrometry ◽  
Food Matrix ◽  
Compound Identification ◽  
Injection Port ◽  
Entire List ◽  
Product Ions ◽  
Temperature Programmed

Abstract A method for detection, quantitation, and confirmation of more than 100 pesticides by gas chromatography (GC) with ion trap mass spectrometry (MS/MS) has been developed. The sensitivity of this method for many analytes is equal to or lower than those of selective GC detectors such as flame photometric detectors and electrolytic conductivity detectors. Using MS/MS, very low detection limits and good confirmation (1 precursor ion and 2 or more product ions) are achieved simultaneously. The entire list of pesticides is screened with 2 injections per sample. Samples are introduced onto the column by a temperature-programmed cold injection to maximize response. Each pesticide is run with its own unique set of parameters, which fragment the compound, retaining only the precursor ion. This ion is then refragmented to create a product spectrum. The selectivity of MS/MS gives a very clean spectrum, making compound identification and confirmation clear, even with a relatively dirty food matrix. If care is taken to maintain the injection port and guard column, this method can reliably identify and confirm more than 100 pesticides at the low parts-per-billion range.

scholarly journals Benchmarking Non-Targeted Metabolomics Using Yeast-Derived Libraries

Metabolites ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 160
Author(s):  
Evelyn Rampler ◽  
Gerrit Hermann ◽  
Gerlinde Grabmann ◽  
Yasin El Abiead ◽  
Harald Schoeny ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Quality Control ◽  
Protein Identification ◽  
Regulatory Elements ◽  
Yeast Fermentation ◽  
Compound Identification ◽  
Targeted Metabolomics ◽  
Targeted Analysis ◽  
Orthogonal State ◽  
Starting Point

Non-targeted analysis by high-resolution mass spectrometry (HRMS) is an essential discovery tool in metabolomics. To date, standardization and validation remain a challenge. Community-wide accepted cost-effective benchmark materials are lacking. In this work, we propose yeast (Pichia pastoris) extracts derived from fully controlled fermentations for this purpose. We established an open-source metabolite library of >200 identified metabolites based on compound identification by accurate mass, matching retention times, and MS/MS, as well as a comprehensive literature search. The library includes metabolites from the classes of (1) organic acids and derivatives (2) nucleosides, nucleotides, and analogs, (3) lipids and lipid-like molecules, (4) organic oxygen compounds, (5) organoheterocyclic compounds, (6) organic nitrogen compounds, and (7) benzoids at expected concentrations ranges of sub-nM to µM. As yeast is a eukaryotic organism, key regulatory elements are highly conserved between yeast and all annotated metabolites were also reported in the human metabolome database (HMDB). Orthogonal state-of-the-art reversed-phase (RP-) and hydrophilic interaction chromatography mass spectrometry (HILIC-MS) non-targeted analysis and authentic standards revealed that 104 out of the 206 confirmed metabolites were reproducibly recovered and stable over the course of three years when stored at −80 °C. Overall, 67 out of these 104 metabolites were identified with comparably stable areas over all three yeast fermentation and are the ideal starting point for benchmarking experiments. The provided yeast benchmark material enabled not only to test for the chemical space and coverage upon method implementation and developments but also allowed in-house routines for instrumental performance tests. Transferring the quality control strategy of proteomics workflows based on the number of protein identification in HeLa extracts, metabolite IDs in the yeast benchmarking material can be used as metabolomics quality control. Finally, the benchmark material opens new avenues for batch-to-batch corrections in large-scale non-targeted metabolomics studies.

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