Comprehensive Two-Dimensional Gas Chromatography with Peak Tracking for Screening of Constituent Biodegradation in Petroleum UVCB Substances.

Petroleum substances, as archetypical UVCBs (substances of unknown or variable composition, complex reaction products, or biological substances), pose a challenge for chemical risk assessment as they contain hundreds to thousands of individual constituents. It is particularly challenging to determine the biodegradability of petroleum substances since each constituent behaves differently. Testing the whole substance provides an average biodegradation, but it would be effectively impossible to obtain all constituents and test them individually. To overcome this challenge, comprehensive two-dimensional gas chromatography (GC × GC) in combination with advanced data-handling algorithms was applied to track and calculate degradation half-times (DT50s) of individual constituents in two dispersed middle distillate gas oils in seawater. By tracking >1000 peaks (representing ∼53-54% of the total mass across the entire chromatographic area), known biodegradation patterns of oil constituents were confirmed and extended to include many hundreds not currently investigated by traditional one-dimensional GC methods. Approximately 95% of the total tracked peak mass biodegraded after 64 days. By tracking the microbial community evolution, a correlation between the presence of functional microbial communities and the observed progression of DT50s between chemical classes was demonstrated. This approach could be used to screen the persistence of GC × GC-amenable constituents of petroleum substance UVCBs.

Modeling the GCxGC Elution Patterns of a Hydrocarbon Structure Library To Innovate Environmental Risk Assessments of Petroleum Substances.

Comprehensive two-dimensional gas chromatography (GCxGC) offers unrivaled separation of petroleum substances, which can contain thousands of constituents or more. However, interpreting substance compositions from GCxGC data is costly and requires expertise. To facilitate environmental risk assessments, industries provide aggregated compositional information known as "hydrocarbon blocks" (HCBs), but these proprietary methods do not transparently associate the HCBs with GCxGC chromatogram data. These obstacles frustrate efforts to study the environmental risks of petroleum substances and associated environmental samples. To address this problem, we developed a GCxGC elution model for user-defined petroleum substance compositions. We calibrated the elution model to experimental GCxGC retention times of 56 known hydrocarbons by fitting three tunable model parameters to two candidate instrument methods. With the calibrated model, we simulated retention times for a library of 15,447-15,455 hydrocarbon structures (plus 40-48 predicted as chromatographically unretained) spanning 11 classes of petroleum substance constituents in the C10-C30 range. The resulting simulation data reveal that GCxGC retention times are quantitatively associated with hydrocarbon class and carbon number information throughout the GCxGC chromatogram. These innovations enable the development of transparent and efficient technical methods to investigate the chemical compositions and environmental properties of petroleum substances, including in environmental and lab-weathered samples.

Application of the Target Lipid Model to Assess Toxicity of Heterocyclic Aromatic Compounds to Aquatic Organisms.

Heterocyclic aromatic compounds can be found in crude oil and coal and often co-exist in environmental samples with their homocyclic aromatic counterparts. The target lipid model (TLM) is a modeling framework that relates aquatic toxicity to the octanol-water partition coefficient (KOW ) that has been calibrated and validated for hydrocarbons. A systematic analysis of the applicability of the TLM to heterocyclic aromatic compounds has not been performed. The objective of the present study was to compile reliable toxicity data for heterocycles and determine whether observed toxicity could be successfully described by the TLM. Results indicated that the TLM could be applied to this compound class by adopting an empirically derived coefficient that accounts for partitioning between water and lipid. This coefficient was larger than previously reported for aromatic hydrocarbons, indicating that these heterocyclic compounds exhibit higher affinity to target lipid and toxicity. A mechanistic evaluation confirmed that the hydrogen bonding accepting moieties of the heteroatoms helped explain differences in partitioning behavior. Given the TLM chemical class coefficient reported in the present study, heterocyclic aromatics can now be explicitly incorporated in TLM-based risk assessments of petroleum substances, other products, or environmental media containing these compounds. Environ Toxicol Chem 2021;40:3000-3009. © 2021 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.