Chemometric Fingerprinting of Petroleum Hydrocarbons Within Oil Sands Tailings Using Comprehensive Two-Dimensional Gas Chromatography

Abstract

Base Mine Lake (BML) is the first full-scale demonstration of water-capped tailing technology in a pit lake to reclaim lands impacted by surface mining in the Alberta Oil Sands Region (AOSR). Biogeochemical cycling and/or exchange near the fluid water interface (FWI) of the organic-rich fluid fine tailings (FFT) can hinder the reclamation process. To monitor this activity, sedimentary depth profiles were collected from three platforms (P1 to P3) at BML. Seventy-four chromatographically well-resolved petroleum hydrocarbon (PHC) isomers were quantified at each depth interval using comprehensive two-dimensional gas chromatography time-of-flight mass spectrometry (GC × GC/TOFMS). The range of total concentrations of all isomers examined across the FFT was the highest at P1 (range = 3.6 × 10⁰–5.5 × 10³ ng/g TOC), second highest at P2 (range = 3.8 × 10⁰–1.9 × 10³ ng/g TOC), and lowest at P3 (range = 5.6 × 10⁰–7.1 × 10² ng/g TOC). The elevated levels of the same isomers across platforms suggest a consistent source fingerprint. While the source fingerprint was mostly consistent across the platforms and depths, Principal Component Analysis (PCA) identified small differences between geospatial locations caused by variations in specific isomer concentrations. Hierarchical Clustering Analysis (HCA) identified the isomers responsible for the PCA separation, showing that the concentrations of low-molecular-weight n-alkanes (C11–C13) and drimane varied compared to the heavier PHCs with depth. These alkanes are the most biodegradable of the compounds identified in this study, and their variations may reflect biogeochemical cycling within the FFT. Combining these statistical tools provided deeper insight into how isomer concentrations vary with depth, helping to identify possible influences like changing inputs, biogeochemical cycling, and species exchange with the water column.

1. Introduction

Surface mining operations in the Athabasca Oil Sands Region (AOSR) of northern Alberta have generated over 1.18 trillion liters of tailings, a slurry composed of residual hydrocarbons, sand, clay, and oil sands process water (OSPW). These tailings gradually settle and consolidate into fluid fine tailings (FFT) [1,2]. The FFT matrix contains 25 to 35% (w/w) solids in the form of clay, sorbed petroleum hydrocarbons (PHCs), and unextracted bitumen (3 to 5% (w/w) and <1% (w/w) unrecovered naphtha (for tailings where naphtha was used during extraction), with the remaining matrix dominated by OSPW [3,4]. The Tailing Management Framework (TMF) issued by the Alberta Energy Regulators in 2015 has encouraged oil sand operators to continue their investigation into management strategies for the reduction in their FFT inventory [1]. One approach to managing these tailings is water-capped tailings technology (WCTT). This method involves placing FFTs at the base of an exhausted mine pit and capping it with water to form a pit lake (PL). Over time, the FFT consolidates and stabilizes beneath the water cover, helping isolate contaminants and support eventual ecological recovery [5].

The focus of this study is Base Mine Lake (BML) (Figure 1), the first full-scale PL in the Athabasca Oil Sands Region (AOSR) commissioned by Syncrude, Alberta, Canada in 2012 [5]. As of October 2012, the FFT deposit underlying BML had reached a maximum thickness of 48 m and was submerged under a 52 million m³ water cover, with a surface area of approximately 8 km² and an average depth of 6.5 m. Settlement and densification of the FFT between 2012 and 2017 resulted in a water cap depth increase to roughly 10.5 m. Freshwater additions, ranging from 2 to 6 million m³, to BML have been undertaken to simulate future water inflow from adjacent reclaimed landforms [2]. Water is currently pumped from the BML water cap for utilization in the oil sands extraction process such that the lake maintains a surface elevation of 308.7 ± 0.5 m above sea level [2]. Field studies beginning in 2015 have extensively characterized the temporal and spatial geochemistry of OCC mobilization from the fluid water interface (FWI) into the overlaying water column [5,6].

The FFT at BML is known to support anaerobic microbial processes, including methanogenesis, sulphate reduction, and fermentation of labile hydrocarbons. These processes influence the mobility of oxygen-consuming constituents (OCCs), which complicates long-term water quality predictions [1,6]. The FFT underlying a PL is expected to be anoxically dominated by diverse microbial communities capable of anaerobic methanotrophy, methanogenesis, and nitrate and sulphur reduction [3,4,7]. Fermentation of PHCs sorbed to FFT produces H² and acetate, which may be subsequently utilized by these anaerobic microbial communities [5]. As FFT settles and densifies, porewater containing OCCs derived from these anaerobic microbial degradations of labile PHCs, such as gases (e.g., H₂S, CH₄), dissolved organic carbon (DOC), and dissolved ions (e.g., NH₄⁺, HS⁻, and Fe²⁺), have the potential to be mobilized into to the overlying water cap [8]. Oxidation processes, including microbial methanotrophy and abiotic reactions, play a central role in modulating methane cycling in fluid fine tailings. As methane is generated through anaerobic methanogenesis, the availability of oxidants (e.g., oxygen, nitrate, and sulfate) controls its mobility and emission to the water cap. Understanding the biogeochemical cycling of petroleum hydrocarbons (PHCs) within the FFT and their exchange with the water column is crucial for predicting long-term water quality [7]. However, the complex mix of residual PHCs in FFT, often appearing as an unresolved complex mixture, makes it difficult to track the cycling of individual isomers [9].

This study applies the increased peak capacity of comprehensive two-dimensional gas chromatography coupled to time-of-flight mass spectrometry (GC × GC/TOFMS) to assess the variability of residual hydrocarbons derived from inputs of naphtha and/or bitumen within near-surface FFT (defined herein as the region extending 0.2–1.9 m from FWI from FWI) and a reference sample below these depths (range = 3.8–5.0 m from FWI) at BML in 2017. GC × GC offers superior separation power over conventional GC, enabling the differentiation of structurally similar isomers commonly found in petroleum-related contaminants. The TOFMS detector, combined with advanced deconvolution algorithms, enhances the identification of co-eluting compounds, improving confidence in peak assignments for non-target analysis. Chemometric fingerprinting, used here to refer to the integration of GC × GC/TOFMS with multivariate statistics like PCA and HCA, extends traditional hydrocarbon profiling by capturing species-level resolution. This allows for better assessment of source contributions, transformation patterns, and spatial variability in complex matrices such as FFT. The goal was to determine the source fingerprint for PHC attribution and apply statistical techniques to assess how PHC isomers differ between platforms, which could indicate in situ biogeochemical cycling and the potential release of OCCs into the overlying water cap.

2. Materials and Methods

2.1. Site Location and Sampling Method

Sampling of FFT was conducted in July 2017 where eighteen FFT samples were collected from the proximity of three platforms located in BML P1 (six samples), P2 (six samples), and P3 (six samples) using a non-commercial pneumatic piston sampling device deployed from a specialized sampling boat as per the protocol from [2]. While passive samplers are increasingly used for time-integrated monitoring of hydrophobic contaminants and can offer cleaner extracts and lower detection limits, this study focuses on grab sampling to capture spatial trends and concentration gradients across BML. The primary focus of sampling was the samples collected from the near-surface FFT depth profile (0.2–1.9 m from FWI), which have been proposed by Dompierre [2] to undergo exchange with the water column. Four samples from each platform were collected from just below the FFT–Water cap (FWI) interface in increments of 0.2 m, one sample was collected 0.5 m from the previous set of samples, and a sample was collected below these depths (range = 3.8–5.0 m from FWI) in each platform as a point of reference. At platform 3, the sample from the 0.2 m depth did not contain sufficient sediment for analysis, and, thus, the first sample analyzed was from 0.4 m from the FWI. Although unequal depths across platforms may appear inconsistent, the design reflects logistical constraints and sediment availability, while still ensuring comparative coverage across biologically and chemically active zones. This approach enables the exploration of depth-related variability in contaminant speciation, redox conditions, and potential source/sink dynamics within the FFT.

2.2. Chemicals and Reagents

Dichloromethane, methanol, and hexane (distilled in glass) were purchased from EMO Millipore Corporation (Oakville, ON, Canada). The following compounds were purchased and used as recovery/internal standards in this study: m-terphenyl (96%, Sigma-Aldrich, Oakville, ON, Canada) and benzo[a]anthracene-d12 (98%, Sigma-Aldrich). The following standards were purchased for semi-quantification of target compounds: 1-methylnaphthalene (95%, Sigma-Aldrich), 2-ethylnaphthalene (98%, Sigma-Aldrich), 2,3,5-trimethylnaphthalene (98%, Sigma-Aldrich), 1,4,6,7-tetramethylnaphthalene (98%, Sigma-Aldrich), 1-methylfluorene (98%, Sigma-Aldrich), 1,8-dimethyl-9H-fluorene (98%, Sigma-Aldrich), 9-methylanthracene (98%, Sigma-Aldrich), 9,10-dimethylanthracene (98%, Sigma-Aldrich), 3-methylbenzothiophene (96%, Sigma-Aldrich), 4-methyldibenzothiophene (96%, Sigma-Aldrich), 4,6-dimethyldibenzothiophene (97%, Sigma-Aldrich), Supelco SS TCL Polynuclear Aromatic Hydrocarbon Mix in methylene chloride–benzene (Sigma-Aldrich), and Supelco C7–C40 Saturated Alkane Mixture in hexane (Sigma-Aldrich).

2.3. Extraction Procedure

The method for total lipid extraction (TLE) of the solvent extractable organics from FFT is summarized in Dereviankin 2020 [10]. Briefly, 500 mL Nalgene bottles containing FFT were thawed overnight and freeze-dried for 72 h to remove residual moisture. The freeze-dried FFT sample was aliquoted in triplicate and spiked with recovery standard, m-terphenyl. A 1:1 hexane–acetone solution was introduced into the sample matrix to extract the organic constituents from the FFT. The mixture underwent microwave extraction with a MARS Microwave Extractor (Serial # MD7382, Oakville, ON, Canada) with the following parameters: power at 100%, ramp to 115 °C, and hold for 10 min. The microwaved extract was decanted and passed through a 1.5 µm VWR glass microfiber filter (product number: 691, 28333-125, Oakville, ON, Canada) and washed with hexane. Samples were diluted to their final volume with hexane, and the extract was transferred into GCMS vials using a 0.45 µm PTEE filter syringe. Prior to analysis, all vials were spiked with benzo[a]anthracene-d12 as the internal standard.

2.4. Instrumental Analysis: GC × GC/QTOF

The FFT total lipid extracts were analyzed using a Pegasus 4D system (LECO Corp., St Joseph, MI, USA). The non-polar/polar (NP/P) column orientation utilized a DB1-MS column (60 m × 0.25 mm × 0.25 μm film thickness, ON, CAN) as the primary column and a DB-17ms column (1.25 m × 0.10 mm × 0.10 μm film thickness, ON, CAN) as the secondary column. This setup was selected after method optimization specific to BML FFT samples, as it provided the optimal resolution of both aromatic hydrocarbons and low molecular weight (C7–C12) paraffins—species critical to tracking biogeochemical lability. A modulation period of 7.5 s was chosen based on prior tests showing that longer periods mitigated peak wrapping and improved the resolution of heavier alkylated species. Full details on method development and optimization can be found in Dereviankin [10]. The primary oven was programmed to hold at 80 °C for 15 min and ramp to 335 °C at a rate of 1.66 °C/min. The secondary oven offset was set to +5 °C relative to the primary oven. A modulation period of 7.5 s was used. The modulator temperature offset was +3 °C relative to the secondary oven. The ion source and transfer line temperatures were set to 240 °C and 280 °C, respectively. Helium was used as the carrier gas at a flow rate of 1 mL/min. The time-of-flight mass spectrometer was scanned over a mass range of m/z 40 to 600 at a sample acquisition rate of 100 scans/s with a solvent delay set to 1300 s. The detector voltage was offset by 100 V with an acquisition voltage of 1678. Data processing of GC × GC/QTOFMS data was performed by ChromaTOF version 4.50.8.0 (LECO Corp), which included automatic peak finding with mass spectral deconvolution. Library searches were conducted with the NIST/EPA/NIH Mass Spectral Library 2008 (NIST 08, Gaithersburg, MC, USA) and a user library containing alkylated polyaromatic hydrocarbon reference standards.

2.5. Statistical Analysis

Univariate, multivariate, and parametric statistical analyses were performed using JMP Software Package (Version 15.1) and customized code in R Studio (Version 1.2.5033). Data were tested for normality and homogeneity of variance using Shapiro–Wilk (α = 0.05). Data that did not meet the parametric assumptions of normality and homoscedasticity were log-transformed [11]. Principal component analysis (PCA) and Hierarchical Clustering Analysis (HCA) were performed using JMP Software Package (Version 15.1) and customized code in R Studio (Version 1.2.5033), following the log transformation of the dataset. Isomers that were not present in more than 75% of the samples were removed from the dataset prior to incorporation into HCA and PCA.

3. Results

3.1. Identification and Quantification of Solvent Extractable Organics Derived from 2017 BML near Surface FFT Total Lipid Extracts

Unique isomers were confirmed by analyzing electron ionization (EI) spectra, comparing them to mass spectral databases, and validating them with reference standards when possible. In total, 69 individual alkylated poly-cyclic aromatic hydrocarbon isomers of 15 chemical species were semi-quantified with the alkylated reference standard: two isomers of C1-naphthalene, nine isomers of C2-naphthalene, eight isomers of C3-naphthalene, fourteen isomers of C4-naphthalene, four isomers of C1-fluorene, five isomers of C2-fluorene, four isomers of C1-phenanthrene, eight isomers of C2-phenanthrene, four isomers of C1-benzothiopehene, three isomers of dibenzothiophenes, and six isomers of C2-dibenzothiophene. One petroleum biomarker was identified (drimane) and semi-quantified with the closest available standard. Three n-alkanes (C11–C13) were quantified with authentic standards. Species concentrations were normalized to total organic carbon (TOC) content within FFT TLE.

3.2. Spatial Distribution of Solvent Extractable Petroleum Hydrocarbon Concentrations in Fluid Fine Tailings

The BML FFT samples were analyzed for the percentage of TOC, which was used as a measure of residual bitumen concentration. The TOC percentage ranged from 5% to 14%, showing no clear pattern with depth or sample platform location. The total concentration of chemical species, representing the sum of all identified isomers for each species, varied with both depth and sample platform location, as shown in the depth profile (Figure 2). The organic compounds were linked to TOC levels, as indicated by the correlation between the depth trends for total species concentrations and TOC. This suggests the FFT may be a sink, retaining these organic compounds. When normalized to TOC, the concentrations of chemical species varied inconsistently with depth (Figure 2). The highest normalized concentrations were at P1 (range = 3.6 × 10⁰–5.5 × 10³ ng/g TOC), followed by P2 (range = 3.8 × 10⁰–1.9 × 10³ ng/g TOC), which had a similar range but a lower maximum concentration. The lowest normalized concentrations were consistently found at P3 (range = 5.6 × 10⁰–7.1 × 10² ng/g TOC).

3.3. Depth-Dependent Variation in Species Concentration

The concentration depth profiles at each platform showed clear and consistent patterns with depth (Figure 2). All PAH species were correlated with depth, displaying similar trends across all platforms. In contrast, the concentrations of alkanes and drimane followed a different depth-dependent pattern that was consistent across all three platforms, setting them apart from the PAH trends.

At P3, the site with the lowest range of species concentration, the concentration of species was generally consistent from the samples collected nearest the FWI (0.4 m from FWI) and then gradually increased to a maximum concentration at 1.0 m from FWI, apart from C13 n-alkane, which had the lowest concentration at 1.0 m (Figure 2C). After the maximum species concentrations at 1.0 m from FWI, the depth intervals were followed by a relatively minor decrease in concentration to the deepest sample collected at 5.0 m from FWI. All species, except for the lower-molecular-weight n-alkanes and drimane, followed a correlated trend with depth.

At P1, the site with the highest range of TOC-normalized concentrations, the TOC-normalized concentration of species was generally consistent except for the sample collected nearest the FWI (0.2 m from FWI), which was depleted for most species, except for the n-alkanes (Figure 2A). The subsequent depth interval at 0.4 m from FWI exhibited the largest abundance of species, which was followed by a decrease at 0.6 m and a subsequent increase at 0.8 m from the FWI (Figure 2A). After this fluctuation, the species concentrations generally remained consistent until the deepest samples were at 5.0 m from the FWI.

For P2, the species concentrations generally remained consistent across the near-surface FFT depth intervals with the notable exception of the deepest sample, which had a depleted species concentration and different isomer fingerprint comparable to all other samples (Figure 2B). Following the decline in concentration at 0.4 m from the FWI, most species exhibited a gradual increase to 1.0 m from the FWI. The subsequent samples collected at 1.4 m from the FWI exhibited declining concentrations of species, followed by an increase at 1.9 m from the FWI and a gradual decline to the deepest sample collected at 3.8 m from the FWI.

3.4. Source Attribution Through Depth Interval Fingerprinting

Percentage-normalized isomer fingerprints were compared across samples to analyze variations and identify consistent patterns. The goal was to determine similarities or differences in the percentage-normalized fingerprints. A consistent fingerprint across depths and platforms would indicate similar source attribution of PHCs. Figure 3 shows representative patterns of individual isomer fingerprints for each chemical species at the shallow, middle, and deepest sampled depths. The fingerprints categorized isomers within their respective chemical species classes with alkylated PAH isomers ordered by an increasing degree of alkylation and lower-molecular-weight n-alkanes ordered by increasing carbon number, while drimane was considered a separate chemical species class.

The isomer fingerprint analysis showed correlated patterns across sites and depths, even though the concentrations of chemical species varied. This consistency was driven by the dominance of a single isomer within each chemical species distribution, though some distinct patterns were still observed. In Figure 3, the dominant isomers are highlighted, showing that C1-DBT-C, C1-FL-C, C1-PH-C, C2-DBT-A, C2-FL-C, C2-NAP-E, C2-PH-C, C3-CAP-E, and N4-NAP-K were the prevalent isomers. This consistency suggests a common source fingerprint, indicating that the same PHC source is present across depths and platforms.

At each individual platform, the isomer fingerprint was highly consistent with two exceptions (P1 nearest surface and P2 deepest sample). The isomer fingerprints were the most consistent at P3, the site with the lowest range of species concentration (Figure 2). At this site, concentrations of the PAH isomers were consistent with depth (<1-fold change) except for C2-NAP-H in the near-surface sample (Figure 3). However, the increase in this isomer was not sufficient to affect the species concentration plot in Figure 2. Unlike the PAHs, as noted in the concentration depth profile, the largest variations between depth intervals existed in the concentration of C13 n-alkane and drimane, which underwent a ~5-fold decrease between 0.5 to 1.5 m. These two species displayed distinctive depth profiles, as shown in Figure 2C, showing a systematic relationship.

Isomer fingerprints were also consistent with depth at P1 (Figure 3), the site with the highest range of species concentration, except for the nearest surface sample, which was depleted for most species (Figure 2). Despite the lower concentrations at this depth, the isomeric fingerprint followed the same general pattern as at other depths, with the same isomers being most elevated for each PAH species. The fingerprint of the lower-molecular-weight n-alkanes (C11, C13, and drimane) generally followed the same pattern as the PAHs, though C13 and drimane were the most decoupled, particularly between the deepest two samples. While most species exhibited variations in concentration (max~2-fold change), the lower-molecular-weight n-alkanes C11 and C13 and drimane underwent the largest spatial variations (max~5-fold change) between 0.5 to 1.5 m in depth. These three species displayed distinctive depth profiles, as shown in Figure 2A, showing a systematic relationship.

The isomeric fingerprint at site P2 was also consistent across the near-surface FFT depth intervals but was distinct for the deepest sample (Figure 2). The deepest sample fingerprint exhibited elevated concentrations of C2-NAP-H and C3-NAP-A to C3-NAP-E isomers relative to the other samples, while the remaining species concentration was comparable to those observed for the former depth intervals. The fingerprint for the majority of P2 samples demonstrated elevated concentrations of C2-FL and C2-NAP isomers compared to P1 and P3. As with P1 and P3, while most species exhibited lower spatial variations in concentration (max~2-fold change), the n-alkanes C11-C13 and drimane underwent the largest spatial variations (max~3-fold change) between 0.5 to 1.5 m. These species displayed distinctive depth profiles, where these species are correlated with depth, as shown in Figure 2B, showing a systematic relationship.

3.5. Chemometric Comparison of the Isomer Fingerprint Between Platforms

The high-resolution depth profiles (Figure 2 and Figure 3) qualitatively demonstrated that PHCs share a consistent source between platforms. Multivariate statistical analysis, including dimensionality reduction and clustering, was used to investigate differences between specific isomers, which may have varying potentials for biogeochemical cycling.

Principal component analysis (PCA, Figure 4) showed that P1 and P2 had distinct signatures that separated from the consistent P3 in PC1 (46% variability) and from each other in PC2 (25% variability). The clustering associated with P1 and P2 depth intervals shared a similar variability in the first principal component, which explained most of the total variance (46%) for isomer concentrations. The two data points from P1 and P2 that were plotted closest to the P3 data were the two most notable outliers in Figure 2. That is, the distinct variability in P1 that was associated with the samples collected nearest the FWI (range = 0.2 m from FWI) and the distinct fingerprint in P2 for the deepest sample (range = 3.8 m from FWI). The similarity between the clustering for these samples and P3 is driven by depleted species concentrations, as illustrated in Figure 3. The samples from P1 and P2 were effectively separated in the second principal component, which explained 25% of the variance. The variability in isomer concentrations driving the directionality of P3 samples in the score plot was strongly influenced by elevated concentrations in two specific isomers (C2-NAP-A and B) compared to the other platforms. The isomer variability in concentration contributing to the separation between P1 and P2 was the elevated concentrations for a subset of lower-molecular-weight isomers (C2-FL and C2-NAP species class) in P2 and the elevated concentration for a subset of C1-BT isomers and drimane in P1. Effectively, the score plot of the PCA determined the relative variability in concentrations between platform species concentrations, while the loading plot affirmed the differences in species variability across the platforms.

Although the PCA identifies distinct isomer differences between platforms, which were not innately apparent in Figure 2, a limitation of the methodology is that the isomers driving separation (C2-NAP, C2-FL species, etc.) cannot be grouped. Hierarchical Clustering Analysis (HCA) provides a mechanism to more directly identify groups of isomers that are similar or distinct between samples. HCA analysis revealed four distinct clusters of depth interval, denoted by groups 1–4 (Figure 5), exhibiting similarities between specific isomers (Figure 5, Groups 1–4). The first cluster of depth intervals identified (Figure 5, Group 1) was the sample collected nearest the FWI in P1 and all the depth intervals of P3, which were depleted for most isomers relative to the other clusters. Within this cluster, P3 depth intervals were separated from the samples collected nearest the FWI in P1 based on the relatively elevated concentrations of two chemical isomers, C2-NAP-A and C2-NAP-B.

Two other strongly consistent groups identified by the HCA were Group 3 (comprised of most depth intervals in P1 (Figure 5, Group 3)) and Group 4 (comprised of the shallow-depth P2 samples (Figure 5, Group 4)). These two clusters were grouped based on the relative concentration of three distinct clusters of isomers (Figure 5, Groups A and B). In Group 3, near-surface samples collected at 0.4 m, 0.8 m, and 1.3 m from the FWI and the deepest sample in P1 clustered together. These samples were characterized by lower concentrations of lighter alkylated PAHs, including C1-NAP-A, C2-NAP-B, D, E, C4-NAP-A, C2-PH-H, C1, and C2-FL species, being depleted comparable to the other depth profiles between platforms (Figure 5, Group A). In contrast, the heavier alkylated PAHs such as C3-NAP, C4-NAP, and C1-DBT (Figure 5, Group C) and the remaining concentration of isomers (Figure 5, Group B) were relatively elevated. Group 4 included near-surface samples collected at 0.4 m, 0.8 m, and 1.0 m from the FWI in P2. These samples showed an opposite pattern to group 3, with increased concentrations of lighter alkylated PAHs (Figure 5, Group A) and consistent levels of heavier alkylated PAHs and C11-C13 n-alkanes (Figure 5, Group C). The remaining isomers were relatively depleted compared to P1 (Figure 5, Group B). Group 2 showed the least consistent pattern of isomers and included the deepest P2 samples and a mid-depth sample from P1. The variability within this cluster suggests inconsistent composition among the isomers (Figure 5, Group 2).

4. Discussion

The spatial distribution of PHC concentrations (Figure 2 and Figure 3) revealed a consistent source signature, indicating a shared origin across samples. This was indicated by the dominance of specific isomers within their respective chemical classes (C1-DBT-C, C1-FL-C, C1-PH-C, C2-DBT-A, C2-FL-C, C2-NAP-E, C2-PH-C, C3-CAP-E, and N4-NAP-K). The presence of a consistent isomer fingerprint aligns with the expectation that the FFT in BML was filled from the same tailing storage facility. While the overall source consistency was expected, the variations in isomer concentrations between platform depth intervals point to possible influences from filling occurring at different times, biogeochemical cycling, and/or species exchange with the water column. The contribution of PHC inputs within P1 and P2 was distinguished by differences in the relative concentration of labile, low-molecular-weight isomers compared to heavier-molecular-weight isomers. Two-way HCA clustering highlighted that both platforms preferentially retained the same higher-molecular-weight polycyclic aromatic hydrocarbons (C3-NAP, C4-NAP, and C1-DBT) across depth intervals. However, P1 showed a depletion of lower-molecular-weight isomers (C1-NAP-A, C2-NAP-B, D, E, C4-NAP-A, C2-PH-H, C1, and C2-FL) compared to P2. This suggests that P1 may have undergone increased biogeochemical cycling, either through anaerobic microbial degradation or species exchange with the water column. Alternatively, the PHC inputs at P1 may have originally been depleted in these lower-molecular-weight isomers relative to the heavier ones. As the lower-molecular-weight species are expected to be preferentially biodegraded and have higher water solubilities [12,13], increased concentration of the lower-molecular-weight species relative to the heavier molecular weight species in P2 may be indicative of the potential release of by-products of biogeochemical cycling and/or species exchange with the water column. In addition to these platform-specific differences, the depth-resolved trends observed across all platforms likely reflect underlying redox gradients, microbial activity, and physicochemical partitioning. These factors influence the fate of labile compounds, such as n-alkanes, which are more readily degraded under anaerobic conditions, compared to the more recalcitrant aromatic hydrocarbons. This enhanced biodegradability of lower-molecular-weight n-alkanes relative to aromatic hydrocarbons likely contributes to their variable distribution, particularly in zones with higher microbial activity or oxygen availability.

5. Conclusions

This study confirmed that PHCs in near-surface FFT at BML originate from a common source. However, PCA and HCA revealed that specific isomer concentrations vary across platforms, likely due to biogeochemical cycling and/or exchange with the overlying water column. Notably, P1 and P2 retained similar higher-molecular-weight isomers (C3-NAP, C4-NAP, and C1-DBT class isomers), while P1 showed depletion in several lower-molecular-weight isomers (C1-NAP-A, C2-NAP-B/D/E, C4-NAP-A, C2-PH-H, C1, and C2-FL), indicating greater alteration or loss. In contrast, P3 exhibited less variation, suggesting minimal alteration. These chemometric tools are essential for distinguishing between original inputs and post-depositional changes, offering a robust framework for environmental forensic assessment of tailings-impacted systems.

While this study provides a comprehensive assessment of PHC depth profiles within Base Mine Lake FFT using GC × GC TOFMS, several limitations should be acknowledged. Source attribution remains partially uncertain due to the potential influence of ongoing biogeochemical transformation processes, such as anaerobic microbial degradation and exchange with the water column. These processes may alter the original chemical fingerprints of labile compounds, particularly lower-molecular-weight n-alkanes. Additionally, the use of grab sampling captures only a snapshot in time and may miss longer-term or seasonally variable trends, which could be more effectively monitored using passive samplers. Future research should incorporate advanced analytical strategies, including deconvolution algorithms and normalization of labile species against more recalcitrant markers, to better resolve degradation effects. Integration of microbial community data could further elucidate the role of biodegradation in PHC dynamics. These directions would strengthen the mechanistic understanding and long-term monitoring frameworks for tailings reclamation.