Accurate analysis of polycyclic aromatic hydrocarbons (PAHs) and alkylated PAHs homologs in crude oil for improving the gas chromatography/mass spectrometry performance

The common gas chromatography/mass spectrometry (GC/MS) approaches such as selective ion monitoring (SIM) or single ion extraction (SIE) from full scan data produce the error (over- or underestimation) estimates for the high level alkylated polycyclic aromatic hydrocarbons (PAHs). In order to rectify the error, the alkylated PAHs in the crude oil samples are quantified by deeply investigating the existing full scan data of 1D GC/MS, instead of resuming with the complex and inaccessible equipments (multidimensional gas chromatography or mass spectrometry). The aim of this study is to provide the detailed qualitative and quantitative basis data (confirming ions, relative abundance, retention indices, and area counts) of the high level alkylated PAHs by a comprehensive three-step method: (1) the potential confirming ions per isomer are selected by exploring the multiple fragment patterns formation mechanism; (2) the reasonable confirming ions are estimated by comparing extracted ion chromatography (EIC) of the potential confirming ions; (3) after deconvolution, composite chromatograms of the reasonable confirming ions illustrate the basis data by assigning peaks for target PAHs definitively. The validation data, resulting concentrations and diagnostic ratios for each homolog are compared with those obtained from SIM. The experimental data demonstrate that significant inaccurate identifications and concentration estimates are obtained when SIM mode is used for C-4 Naphthalene (C-4 N), C-3 Phenanthrene (C-3 P), C-4 Phenanthrene (C-4 P), C-3 Dibenzothiophene (C-3 D), C-3 Fluorene (C-3 F), C2-4 Chrysene (C2-4 C) and C-1 Fluoranthene (C-1 Flt). This study evaluates the usefulness of the previous fragmentation patterns, and confirms compound presence by GC/MS using the different spectral deconvolution software. This approach is developed as a broad screen for environmental samples (including petrol, diesel fuel and coal tar), with only the crude oil results being presented here. (C) 2013 Elsevier Inc. All rights reserved.