No abstract

Focusing on the O 2 class, a set of crude oils from Llanos Orientales Basin, Colombia, were classified in terms of biodegradation levels using negative ion mode electrospray Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) and chemometric analysis. The O 2 class, which is mainly composed of naphthenic carboxylic acids, was monitored because these polar crude oil constituents are known to be substantially affected by microbial activity. Principal component analysis (PCA) applied on the O 2 profile was able to classify the crude oils into three groups: biodegraded, mixture, and nonbiodegraded. From the relative abundances of the O 2 class, a clear trend on acid distribution could be directly correlated with biodegradation: a rising in abundance of saturated acids with low double-bond equivalent (DBE) values (despite the lowering observed for fatty acids with DBE = 1), expressed by the A/C index. The combined use of two indexes, the A/C index and a new index also based on saturated acid abundances, the SA index, is proposed as an effective strategy to monitor biodegradation. This approach showed to be particularly useful to fill blanks on discrete biodegradation classification and when samples are actually composed of a mixture of oils with contrasting biodegradation levels. Results are in good agreement with predictions based on classical hydrocarbon biomarker analysis.

The partial least-squares (PLS) calibration method as a chemometric tool was used to develop a calibration model using Fourier transform infrared spectroscopy (FTIR) spectra data of biodiesel samples from different sources, such as cotton, castor, and palm, which were mixed with raw soybean oil to simulate an adulteration system. The PLS calibration method was applied with and without variable selection to quantify the amount of raw soybean oil present in these samples. Classic methods of variable selection, such as forward and stepwise, were applied to all origins together and each one separately. Variable selection improves not only the stability of the model to the colinearity in multivariate spectra but also the interpretability of the relationship between the model and the sample composition, which means that it becomes easier to determine and quantify the amount of raw soybean oil mixed in each biodiesel source.

We propose the use of the low-field 1 H NMR technique to predict various properties of petroleum fractions with °API ranging from 21.7 to 32.7. The experimental data obtained by standard methodologies (ASTM D-1218, D 445-06, D-664-06, D-2892, and D-4052) were correlated with the mean values of the 1 H transverse relaxation time in the range between 25 and 675 ms. Results of the present work showed good correlations between the NMR relaxation data with viscosity, total acid number, refractive index, and API gravity. The main advantage of the proposed method is its nondestructiveness, together with its speed and the fact that it does not require solvents/dilution. This allows the assessment of several properties of petroleum fractions simultaneously, based on the output of only one NMR experiment, leading to large economy in terms of energy, time, and costs.

No abstract

Low-field (1) H NMR was used in this work for the analysis of mixtures involving crude oils and water. CPMG experiments were performed to determine the transverse relaxation time (T2 ) distribution curves, which were computed by the inverse Laplace transform of the echo decay data. The instrument's ability of quantifying water and petroleum in biphasic mixtures following different methodologies was tested. For mixtures between deionized water and petroleum, one achieved excellent results, with root mean squared error of cross-validation (RMSECV) of 0.8% for a regression between the water content (wt %) and the relative area of the water peak in the T2 distribution curve, or a standard deviation of 0.9% for the relationship between the water content and the relative water peak area, corrected by the relative hydrogen index of the crude. In the case of biphasic mixtures of Mn(2+) -doped water and crude oils, the best result of RMSECV = 1.6% was achieved by using the raw magnetization decay data for a partial least squares regression.

The dissolution of organic matter into water via oxidative processes, named oxycracking, has been practiced for a long time for the removal of organic pollutants, in which oxygen induces breakage and functionalization of organic molecules. Recently, oxycracking has been explored as an alternative approach to handling the increased amount of solid residues produced in oil sands upgrading activities that involve carbon rejection in solvent deasphalting units. This study uses an asphaltene-rich feedstock, operationally known as petroleum pitch, isolated from an Athabasca bitumen vacuum residue, which was submitted to oxycracking reactions at 200 and 220 °C. The feed and water-soluble fractions isolated at pH 1, termed acid-soluble oxidized asphaltenes (ASOA), were analyzed by ultrahigh-resolution mass spectrometry [Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS)] using electrospray and atmospheric pressure photoionization ion sources. FTICR-MS analysis revealed extensive oxidation of all compound classes originally present in the asphaltene-rich feed. Double bond equivalent (DBE) distribution plots show that sequential carboxylation (formation of a carboxyl group) occurs progressively with an increasing reaction temperature, leading to the incorporation of up to 15 oxygen atoms per molecule, whereas simultaneous decarboxylation reactions produce a CO2-rich gas phase. ASOA samples also show lower overall carbon number distributions than the asphaltene feed, which is direct evidence of C–C bond cleavage during the oxycracking process. In addition, molecular fragments detected in ASOA after carbon–carbon bond cleavages showed not only lower carbon numbers but also lower DBEs per molecule, consistent with a more dominant archipelago architecture for the parent asphaltene molecules.

Many of the molecular proxies commonly used for paleoenvironmental reconstruction are focused on a limited set of glycerol ether lipids, mainly due to the lack of more comprehensive analytical methods and instrumentation able to deal with a more diverse range of species. In this study, we describe an FTICR-MS-based method for rapid, nontargeted screening of ether lipid biomarkers in recent marine sediments. This method involves simplified sample preparation and enables rapid identification of known and novel ether lipid species. Using this method, we were able to identify complete series of core glycerol dialkyl glycerol tetraethers (GDGTs with 0 to 8 alicyclic rings), including the complete resolution of GDGT-4 and the unexpected detection of GDGTs with more than 5 rings, in sediments from mesophilic marine environments (sea surface temperature, SST, of 24-25 °C). Additionally, mono- and dihydroxy-GDGT analogs (including novel species with >2 rings), as well as glycerol dialkanol diethers, GDDs (including novel species with >5 rings) were detected. Finally, we putatively identified other, previously unreported groups of glycerol ether lipid species. Adequacy of the APPI-P FTICR-MS data for the determination of commonly used GDGT-based proxy indices was demonstrated. The results of this study show great potential for the use of FTICR-MS as both a rapid method for determining existing proxy indices and, perhaps more importantly, as a tool for the early detection of possible new biomarkers and proxies that may establish novel geochemical relationships between archaeal ether lipids and key environmental-, energy-, and climate-related system variables.