College of Environmental Science and Engineering, Ocean University of China, 238 Songling Road, Laoshan District, Tsingtao (Qingdao) 266100, China.
College of Environmental Science and Engineering, Ocean University of China, 238 Songling Road, Laoshan District, Tsingtao (Qingdao) 266100, China.
Ecotoxicol Environ Saf. 2014 Feb;100:242-50. doi: 10.1016/j.ecoenv.2013.10.018. Epub 2013 Nov 11.
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 C4 Naphthalene (C4 N), C3 Phenanthrene (C3 P), C4 Phenanthrene (C4 P), C3 Dibenzothiophene (C3 D), C3 Fluorene (C3 F), C2-4 Chrysene (C2-4 C) and C1 Fluoranthene (C1 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.
常见的气相色谱/质谱（GC/MS）方法，如选择离子监测（SIM）或从全扫描数据中提取单一离子（SIE），会对高水平烷基化多环芳烃（PAHs）产生误差（高估或低估）估计。为了纠正这些误差，可以通过深入研究 1D GC/MS 的现有全扫描数据，而不是使用复杂且难以获得的设备（多维气相色谱或质谱）来定量分析原油样品中的烷基化 PAHs。本研究的目的是通过综合三步法提供高水平烷基化 PAHs 的详细定性和定量基础数据（确认离子、相对丰度、保留指数和面积计数）：（1）通过探索多碎片模式形成机制选择每个异构体的潜在确认离子；（2）通过比较潜在确认离子的提取离子色谱（EIC）来估算合理的确认离子；（3）经过解卷积，合理确认离子的复合色谱图通过明确分配目标 PAHs 的峰来展示基础数据。验证数据、每个同系物的浓度和诊断比与 SIM 获得的结果进行比较。实验数据表明，当使用 SIM 模式对 C4 萘（C4 N）、C3 菲（C3 P）、C4 菲（C4 P）、C3 二苯并噻吩（C3 D）、C3 芴（C3 F）、C2-4 屈（C2-4 C）和 C1 荧蒽（C1 Flt）进行分析时，会得到不准确的鉴定和浓度估计。本研究评估了以前的碎片模式的有用性，并通过使用不同的光谱解卷积软件，通过 GC/MS 确认化合物的存在。该方法作为环境样品（包括汽油、柴油燃料和煤焦油）的广谱筛查方法，这里仅呈现了原油的结果。
