Using Comprehensive Two-Dimensional Gas Chromatography Retention Indices To Estimate Environmental Partitioning Properties for a Complete Set of Diesel Fuel Hydrocarbons

Abstract

Comprehensive two-dimensional gas chromatography (GCxGC) provides nearly complete composition data for some complex mixtures such as petroleum hydrocarbons. However, the potential wealth of physical property information contained in the corresponding two-dimensional chromatograms is largely untapped. We developed a simple but robust method to estimate GCxGC retention indices for diesel-range hydrocarbons. By exploiting n-alkanes as reference solutes in both dimensions, calculated retention indices were insensitive to uncertainty in the enthalpy of gas-stationary-phase transfer for a suite of representative diesel components. We used the resulting two-dimensional retention indices to estimate the liquid vapor pressures, aqueous solubilities, air-water partition coefficients, octanol-water partition coefficients, and vaporization enthalpies of a nearly complete set of diesel fuel hydrocarbons. Partitioning properties were typically estimated within a factor of 2; this is not as accurate as some previous estimation or measurement methods. However, these relationships may allow powerful and incisive analysis of phase-transfer processes affecting petroleum hydrocarbon mixtures in the environment. For example, GCxGC retention data might be used to quantitatively deconvolve the effects of water washing and evaporation on environmentally released diesel fuels.

Combining biomarker and bulk compositional gradient analysis to assess reservoir connectivity

“…The second dimension of separation greatly enhances the resolution of the technique, and for complex mixtures such as crude oil and environmental samples the number of components resolved with GC×GC exceeds that resolved with traditional GC by an order of magnitude (Arey et al, 2007;Arey et al, 2005;Bertsch, 2000;Betancourt et al, 2009;Gaines et al, 2006;Liu and Lee, 2000;Phillips and Beens, 1999;Prazen et al, 2001;Wang and Walters, 2007). The instrumentation used for this measurement has been described previously, and details particular to this application are presented as Supplementary Material (Betancourt et al, 2009;Nelson et al, 2006).…”

Using comprehensive two-dimensional gas chromatography to explore the geochemistry of the Santa Barbara oil seeps

“…Several years ago, we developed a simple but robust method to estimate GC × GC retention indices for petroleum hydrocarbons. By exploiting n-alkanes as reference solutes in both dimensions, we were able to calculate retention indices that were insensitive to the uncertainty in the enthalpy of gas-stationary phase transfer for a suite of representative components (Arey et al, 2005). The resulting two-dimensional retention indices can then be used to estimate the liquid vapor pressures, aqueous solubilities, octanol-water partition coefficients, and vaporization enthalpies of a wide range of petroleum hydrocarbons which, in turn, can be used to investigate phase transfer processes affecting petroleum hydrocarbon mixtures in the environment.…”

“…Evaporation and dissolution act on compounds eluting early on the x-axis and late on the y-axis of GC × GC images, respectively, as described earlier (Arey et al 2005. Evaporation would likely be limited to the time oil resides at the sea surface, as opposed to dissolution, which would occur both in the slick and after deposition into the sediment.…”

“…This supports our interpretation that biodegradation, rather than gas-washing or water-washing in the reservoir, caused the observed compound losses. (Arey et al, 2005 To identify biodegradation trends among compounds less abundant than those visualized in difference chromatograms ( Figures 5A and B), an algorithm was developed to track compounds between similarly sourced samples, based on GC × GC retention times. This algorithm tracked the concentration changes of a large number of individual compounds from one sample to another, in an automated fashion.…”

Chapter 4 Data Acquisition, Visualization, and Analysis

“…Ni et al [26] showed that peak pattern variations over widely varying chromatographic conditions could be modeled well by affine transformations (i.e., translation, scale, and shear). As illustrated in Chapter 3, several approaches have been put forward for two-dimensional indexing [27][28][29][30][31], but none has yet achieved wide acceptance and research continues. A robust approach for dealing with two-dimensional retention-time transformations that can be tailored to specific applications is to locate and identify target peaks relative to the positions of many other peaks in the sample, not just a few standard markers.…”