Analysis of petroleum compositional similarity using multiway principal components analysis (MPCA) with comprehensive two-dimensional gas chromatographic data

Applying biomarkers as paleoenvironmental indicators to reveal the organic matter enrichment of shale during deep energy exploration: a review

Analysis of biomarkers in geological materials such as shales is very crucial because they can provide useful information on the depositional conditions and environments, organic matter input, thermal maturity as well as the geological age of shales in some cases. The paleoenvironment, and its impact on organic matter enrichment of the shales, plays a vital role in the exploration and development of the resource. Paleoenvironmental reconstruction can be conducted using elemental, isotopic, maceral, and biomarker proxies. However, the literature on the biomarkers for paleoenvironment reconstruction to reveal the organic matter enrichment of shales in many petroleum systems throughout the world is still insufficient. Hence, this paper seeks to critically review the application of biomarkers during paleoenvironmental reconstruction in shales. The uses of biomarkers as indicators of modern and ancient marine and brackish/saline lacustrine depositional environments are considered. This review shows that biomarkers could be used to establish the sedimentary depositional environments, redox conditions, and organic matter enrichments of shales that are critical to deep energy exploitation. Nevertheless, despite the fact that biomarkers are significant indicators of depositional conditions, secondary processes such as source facies, thermal maturity, migration, and reservoir alteration can greatly influence their uses as paleoenvironmental condition indicators in source rocks and oils. Hence, for a reliable paleoenvironmental evaluation, there is a need to combine isotopic, elemental and maceral proxies with biomarkers.

Detailed Speciation of Semi-Volatile and Intermediate-Volatility Organic Compounds (S/IVOCs) in Marine Fuel Oils Using GC × GC-MS

Ship emissions contribute substantial air pollutants when at berth. However, the complexity and diversity of the marine fuels utilized hinder our understanding and mapping of the characteristics of ship emissions. Herein, we applied GC × GC-MS to analyze the components of marine fuel oils. Owing to the high separation capacity of GC × GC-MS, 11 classes of organic compounds, including b-alkanes, alkenes, and cyclo-alkanes, which can hardly be resolved by traditional one-dimensional GC-MS, were detected. Significant differences are observed between light (-10# and 0#) and heavy (120# and 180#) fuels. Notably, -10# and 0# diesel fuels are more abundant in b-alkanes (44~49%), while in 120# and 180#, heavy fuels b-alkanes only account for 8%. Significant enhancement of naphthalene proportions is observed in heavy fuels (20%) compared to diesel fuels (2~3%). Hopanes are detected in all marine fuels and are especially abundant in heavy marine fuels. The volatility bins, one-dimensional volatility-based set (VBS), and two-dimensional VBS (volatility-polarity distributions) of marine fuel oils are investigated. Although IVOCs still take dominance (62-66%), the proportion of SVOCs in heavy marine fuels is largely enhanced, accounting for ~30% compared to 6~12% in diesel fuels. Furthermore, the SVOC/IVOC ratio could be applied to distinguish light and heavy marine fuel oils. The SVOC/IVOC ratios for -10# diesel fuel, 0# diesel fuel, 120# heavy marine fuel, and 180# heavy marine fuel are 0.085 ± 0.046, 0.168 ± 0.159, 0.504, and 0.439 ± 0.021, respectively. Our work provides detailed information on marine fuel compositions and could be further implemented in estimating organic emissions and secondary organic aerosol (SOA) formation from marine fuel storage and evaporation processes.

Analytical chemistry solutions to hazard evaluation of petroleum refining products

Products of petroleum refining are substances that are both complex and variable. These substances are produced and distributed in high volumes; therefore, they are heavily scrutinized in terms of their potential hazards and risks. Because of inherent compositional complexity and variability, unique challenges exist in terms of their registration and evaluation. Continued dialogue between the industry and the decision-makers has revolved around the most appropriate approach to fill data gaps and ensure safe use of these substances. One of the challenging topics has been the extent of chemical compositional characterization of products of petroleum refining that may be necessary for substance identification and hazard evaluation. There are several novel analytical methods that can be used for comprehensive characterization of petroleum substances and identification of most abundant constituents. However, translation of the advances in analytical chemistry to regulatory decision-making has not been as evident. Therefore, the goal of this review is to bridge the divide between the science of chemical characterization of petroleum and the needs and expectations of the decision-makers. Collectively, mutual appreciation of the regulatory guidance and the realities of what information these new methods can deliver should facilitate the path forward in ensuring safety of the products of petroleum refining.

Advanced tuning of the ion management parameters in GC × GC-HRMS using a Fourier transform Orbitrap mass analyzer for pixel-based data handling and multivariate analysis

GC × GC investigations are well known to generate a substantial amount of information-rich and structurally complex data, requiring advanced data processing strategies like chemometrics. Many workflows are available for data handling and processing, such as the peak-table and pixel-based approaches. The goal of this work is to present a solution based on method development to solve the missing pixel problem that may be encountered in experiments performed with GC and GC × GC coupled to the Fourier transform orbital ion trap (FT-Orbitrap) mass analyzer. Data input is vital for pixel-based chemometric analyses, as some post-processing solutions may lead to significant loss of chemical information in the data set. Hence, a key requisite is that the chemical information is consistently indexed in the data arrays for proper pixel-based data handling and analysis. In this study, we carefully evaluated the ion management parameters to preserve the intrinsic structure and information of the data arrays of the GC × GC-FT-Orbitrap for future pixel-oriented chemometric analysis. The most acceptable conditions yielded acquisition rates up to 42.6 spectra per s, while a routine setting of 24.7 Hz was successfully employed in analyses of different petroleum fractions, producing both consistent tensor sizes and acceptable peak reconstructions. A data acquisition rate of 24.7 spectra per s and a mass resolving power of 15 000 allowed the resolution of a mass split of only 0.004 Da - which is an interesting configuration for challenging applications in petroleomics. Using such advanced settings, the missing pixel problem was reduced from up to 30% to much less than 0.04% of the data array dimension. Thus, the proposed configuration can be employed in studies that require pixel-oriented multivariate data analysis.

A Comparative Analysis of Analytical Techniques for Rapid Oil Spill Identification

The complex chemical composition of crude oils presents many challenges for rapid chemical characterization in the case of a spill. A number of approaches are currently used to "fingerprint" petroleum-derived samples. Gas chromatography coupled with mass spectrometry (GC-MS) is the most common, albeit not very rapid, technique; however, with GC-MS alone, it is difficult to resolve the complex substances in crude oils. The present study examined the potential application of ion mobility spectrometry-mass spectrometry (IMS-MS) coupled with chem-informatic analyses as an alternative high-throughput method for the chemical characterization of crude oils. We analyzed 19 crude oil samples from on- and offshore locations in the Gulf of Mexico region in the United States using both GC-MS (biomarkers, gasoline range hydrocarbons, and n-alkanes) and IMS-MS (untargeted analysis). Hierarchical clustering, principal component analysis, and nearest neighbor-based classification were used to examine sample similarity and geographical groupings. We found that direct-injection IMS-MS performed either equally or better than GC-MS in the classification of the origins of crude oils. In addition, IMS-MS greatly increased the sample analysis throughput (minutes vs hours per sample). Finally, a tabletop science-to-practice exercise, utilizing both the GC-MS and IMS-MS data, was conducted with emergency response experts from regulatory agencies and the oil industry. This activity showed that the stakeholders found the IMS-MS data to be highly informative for rapid chemical fingerprinting of complex substances in general and specifically advantageous for accurate and confident source-grouping of crude oils. Collectively, the present study shows the utility of IMS-MS as a technique for rapid fingerprinting of complex samples and demonstrates its advantages over traditional GC-MS-based analyses when used for decision-making in emergency situations. Environ Toxicol Chem 2021;40:1034-1049. © 2020 SETAC.

Chiral x achiral multidimensional liquid chromatography. Application to the enantioseparation of dintitrophenyl amino acids in honey samples and their fingerprint classification

Most HPLC enantiomer separations are performed with columns packed with a chiral stationary phase (CSP) operated with an achiral mobile phase. The intrinsically limited chemical selectivity of most CSPs to the simultaneous resolution of several pairs of enantiomers means that complex mixtures of diverse pairs of enantiomers cannot be resolved in a single run due to peak overlapping. Moreover, some drawbacks remain when the analyte is present in very complex samples containing other achiral compounds which can co-elute with the enantiomer peaks. Multidimensional chromatography becomes an option to increase peak capacity and resolve these samples. The aim of this work was to study an online fully comprehensive 2D-LC mode utilizing a combination of a chiral column in the first dimension and an achiral column in the second dimension. The 2D-LC system was built with an active flow splitter pump in order to easily adjust the volume of sample transferred into the second dimension and to independently optimize the flow rate in the first dimension. The present LCxLC method was optimized for the separation of amino acids present in honey samples, taking into account key parameters that influence the bidimensional peak capacity (orthogonality, sampling frequency, etc.). The amino acids have been preconcentrated on a cation-exchange column followed by derivatization. Several amino acids present in different honey samples have been identified and the data generated has been analyzed by principal component analysis.

Interpreting comprehensive two-dimensional gas chromatography using peak topography maps with application to petroleum forensics

Background

Comprehensive two-dimensional gas chromatography \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$(GC \times GC)$$\end{document}(GC×GC) provides high-resolution separations across hundreds of compounds in a complex mixture, thus unlocking unprecedented information for intricate quantitative interpretation. We exploit this compound diversity across the \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$(GC \times GC)$$\end{document}(GC×GC) topography to provide quantitative compound-cognizant interpretation beyond target compound analysis with petroleum forensics as a practical application. We focus on the \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$(GC \times GC)$$\end{document}(GC×GC) topography of biomarker hydrocarbons, hopanes and steranes, as they are generally recalcitrant to weathering. We introduce peak topography maps (PTM) and topography partitioning techniques that consider a notably broader and more diverse range of target and non-target biomarker compounds compared to traditional approaches that consider approximately 20 biomarker ratios. Specifically, we consider a range of 33–154 target and non-target biomarkers with highest-to-lowest peak ratio within an injection ranging from 4.86 to 19.6 (precise numbers depend on biomarker diversity of individual injections). We also provide a robust quantitative measure for directly determining “match” between samples, without necessitating training data sets.

Results

We validate our methods across 34 \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$(GC \times GC)$$\end{document}(GC×GC) injections from a diverse portfolio of petroleum sources, and provide quantitative comparison of performance against established statistical methods such as principal components analysis (PCA). Our data set includes a wide range of samples collected following the 2010 DeepwaterHorizon disaster that released approximately 160 million gallons of crude oil from the Macondo well (MW). Samples that were clearly collected following this disaster exhibit statistically significant match \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$(99.23 \pm 1.66 )\,\%$$\end{document}(99.23±1.66)% using PTM-based interpretation against other closely related sources. PTM-based interpretation also provides higher differentiation between closely correlated but distinct sources than obtained using PCA-based statistical comparisons. In addition to results based on this experimental field data, we also provide extentive perturbation analysis of the PTM method over numerical simulations that introduce random variability of peak locations over the \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$(GC \times GC)$$\end{document}(GC×GC) biomarker ROI image of the MW pre-spill sample (sample \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\#1$$\end{document}#1 in Additional file 4: Table S1). We compare the robustness of the cross-PTM score against peak location variability in both dimensions and compare the results against PCA analysis over the same set of simulated images. Detailed description of the simulation experiment and discussion of results are provided in Additional file 1: Section S8.

Conclusions

We provide a peak-cognizant informational framework for quantitative interpretation of \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$(GC \times GC)$$\end{document}(GC×GC) topography. Proposed topographic analysis enables \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$(GC \times GC)$$\end{document}(GC×GC) forensic interpretation across target petroleum biomarkers, while including the nuances of lesser-known non-target biomarkers clustered around the target peaks. This allows potential discovery of hitherto unknown connections between target and non-target biomarkers.

Electronic supplementary material

The online version of this article (doi:10.1186/s13065-016-0211-y) contains supplementary material, which is available to authorized users.

Oil species identification technique developed by Gabor wavelet analysis and support vector machine based on concentration-synchronous-matrix-fluorescence spectroscopy

Concentration-synchronous-matrix-fluorescence (CSMF) spectroscopy was applied to discriminate the oil species by characterizing the concentration dependent fluorescence properties of petroleum related samples. Seven days weathering experiment of 3 crude oil samples from the Bohai Sea platforms of China was carried out under controlled laboratory conditions and showed that weathering had no significant effect on the CSMF spectra. While different feature extraction methods, such as PCA, PLS and Gabor wavelet analysis, were applied to extract discriminative patterns from CSMF spectra, classifications were made via SVM to compare their respective performance of oil species recognition. Ideal correct rates of oil species recognition of 100% for the different types of oil spill samples and 92% for the closely-related source oil samples were achieved by combining Gabor wavelet with SVM, which indicated its advantages to be developed to a rapid, cost-effective, and accurate forensic oil spill identification technique.

Comprehensive Chemical Characterization of Hydrocarbons in NIST Standard Reference Material 2779 Gulf of Mexico Crude Oil

Comprehensive chemical information is needed to understand the environmental fate and impact of hydrocarbons released during oil spills. However, chemical information remains incomplete because of the limitations of current analytical techniques and the inherent chemical complexity of crude oils. In this work, gas chromatography (GC)-amenable C9-C33 hydrocarbons were comprehensively characterized from the National Institute of Standards and Technology Standard Reference Material (NIST SRM) 2779 Gulf of Mexico crude oil by GC coupled to vacuum ultraviolet photoionization mass spectrometry (GC/VUV-MS), with a mass balance of 68 ± 22%. This technique overcomes one important limitation faced by traditional GC and even comprehensive 2D gas chromatography (GC×GC): the necessity for individual compounds to be chromatographically resolved from one another in order to be characterized. VUV photoionization minimizes fragmentation of the molecular ions, facilitating the characterization of the observed hydrocarbons as a function of molecular weight (carbon number, NC), structure (number of double bond equivalents, NDBE), and mass fraction (mg kg(-1)), which represent important metrics for understanding their fate and environmental impacts. Linear alkanes (8 ± 1%), branched alkanes (11 ± 2%), and cycloalkanes (37 ± 12%) dominated the mass with the largest contribution from cycloalkanes containing one or two rings and one or more alkyl side chains (27 ± 9%). Linearity and good agreement with previous work for a subset of >100 components and for the sum of compound classes provided confidence in our measurements and represents the first independent assessment of our analytical approach and calibration methodology. Another crude oil collected from the Marlin platform (35 km northeast of the Macondo well) was shown to be chemically identical within experimental errors to NIST SRM 2779, demonstrating that Marlin crude is an appropriate surrogate oil for researchers conducting laboratory research into impacts of the DeepWater Horizon disaster.

Recalcitrance and degradation of petroleum biomarkers upon abiotic and biotic natural weathering of Deepwater Horizon oil

Petroleum biomarkers such as hopanoids, steranes, and triaromatic steroids (TAS) are commonly used to investigate the source and fate of petroleum hydrocarbons in the environment based on the premise that these compounds are resistant to biotic and abiotic degradation. To test the validity of this premise in the context of the Deepwater Horizon disaster, we investigated changes to these biomarkers as induced by natural weathering of crude oil discharged from the Macondo Well (MW). For surface slicks collected from May to June in 2010, and other oiled samples collected on beaches in the northern Gulf of Mexico from July 2010 until August 2012, hopanoids with up to 31 carbons as well as steranes and diasteranes were not systematically affected by weathering processes. In contrast, TAS and C32- to C35-homohopanes were depleted in all samples relative to 17α(H),21β(H)-hopane (C30-hopane). Compared to MW oil, C35-homohopanes and TAS were depleted by 18 ± 10% and 36 ± 20%, respectively, in surface slicks collected from May to June 2010, and by 37 ± 9% and 67 ± 10%, respectively, in samples collected along beaches from April 2011 through August 2012. Based on patterns of relative losses of individual compounds, we hypothesize biodegradation and photooxidation as main degradation processes for homohopanes and TAS, respectively. This study highlights that (i) TAS and homohopanes can be degraded within several years following an oil spill, (ii) the use of homohopanes and TAS for oil spill forensics must account for degradation, and (iii) these compounds provide a window to parse biodegradation and photooxidation during advanced stages of oil weathering.

Oxygenated weathering products of Deepwater Horizon oil come from surprising precursors

Following the release of crude oil from the Macondo well in 2010, a wide range of weathering processes acted on the spilled oil. A recent study revealed that samples from this spill were oxidized into oxygenated hydrocarbons (OxHC) comprising more than 50% of the extracted hydrocarbons. The precursors of these compounds were not identified despite using a wide range of analytical tools, including gas chromatography (GC). To search for these precursors, over 40 samples were analyzed by comprehensive two-dimensional gas chromatography (GC×GC), one of the largest studies of its kind to date. Partial least squares regression was employed to elucidate the GC×GC peaks that could be the precursors of OxHC in our samples. We found that the formation of OxHC correlated with the disappearance of saturated hydrocarbons, including alkylcyclopentanes, alkyl cyclohexanes, alkylated bicyclic saturated compounds, tricyclic terpanpoids, and alkylbenzenes. These results indicate a previously under-reported chemodynamic process in oil spill weathering.

Post-incident monitoring to evaluate environmental damage from shipping incidents: chemical and biological assessments

Oil and chemical spills in the marine environment are an issue of growing concern. Oil exploration and exploitation is moving from the continental shelf to deeper waters, and to northern latitudes where the risk of an oil spill is potentially greater and may affect pristine ecosystems. Moreover, a growing number of chemical products are transported by sea and maritime incidents of hazardous and noxious substances (HNS) are expected to increase. Consequently, it seems timely to review all of the experience gained from past spills to be able to cope with appropriate response and mitigation strategies to combat future incidents. Accordingly, this overview is focused on the dissemination of the most successful approaches to both detect and assess accidental releases using chemical as well as biological approaches for spills of either oil or HNS in the marine environment. Aerial surveillance, sampling techniques for water, suspended particles, sediments and biota are reviewed. Early warning bioassays and biomarkers to assess spills are also presented. Finally, research needs and gaps in knowledge are discussed.