A wide variety of sampling techniques and strategies are needed to analyze polycyclic aromatic compounds (PACs) and interpret their distributions in various environmental media (i.e., air, water, ...snow, soils, sediments, peat and biological material). In this review, we provide a summary of commonly employed sampling methods and strategies, as well as a discussion of routine and innovative approaches used to quantify and characterize PACs in frequently targeted environmental samples, with specific examples and applications in Canadian investigations. The pros and cons of different analytical techniques, including gas chromatography – flame ionization detection (GC-FID), GC low-resolution mass spectrometry (GC-LRMS), high performance liquid chromatography (HPLC) with ultraviolet, fluorescence or MS detection, GC high-resolution MS (GC-HRMS) and compound-specific stable (δ13C, δ2H) and radiocarbon (Δ14C) isotope analysis are considered. Using as an example research carried out in Canada’s Athabasca oil sands region (AOSR), where alkylated polycyclic aromatic hydrocarbons and sulfur-containing dibenzothiophenes are frequently targeted, the need to move beyond the standard list of sixteen EPA priority PAHs and for adoption of an AOSR bitumen PAC reference standard are highlighted.
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•Review of methods to collect samples for PAC analysis in the Canadian environment.•Review of techniques used to quantify or characterize PACs in environmental samples.•High-resolution MS and compound-specific isotope analysis offer unparalleled insight.•The list of 16 EPA PAHs is insufficient for studies in Canada’s oil sands region.•The adoption of an Athabasca oil sands bitumen PAC reference standard is proposed.
A comprehensive review of sampling methods, strategies and analytical techniques used to quantify and characterize PACs in the Canadian environment.
The sources and spatial distribution of polycyclic aromatic hydrocarbons (PAHs) atmospheric deposition in the boreal forests surrounding bitumen production operations in the Athabasca Oil Sands ...Region (AOSR), Alberta, Canada were investigated as part of a 2014 passive in-situ bioindicator source apportionment study. Epiphytic lichen species Hypogymnia physodes samples (n = 127) were collected within a 150 km radius of the main surface oil sand production operations and analyzed for total sulfur, total nitrogen, forty-three elements, twenty-two PAHs, ten groups of C1-C2-alkyl PAHs and dibenzothiophenes (polycyclic aromatic compounds; PACs), five C1- and C2-alkyldibenzothiophenes, and retene. The ΣPAH + PAC in H. physodes ranged from 54 to 2778 ng g−1 with a median concentration of 317 ng g−1. Source apportionment modeling found an eight-factor solution that explained 99% of the measured ΣPAH + PAC lichen concentrations from four anthropogenic oil sands production sources (Petroleum Coke, Haul Road Dust, Stack Emissions, Raw Oil Sand), two local/regional sources (Biomass Combustion, Mobile Source), and two lichen biogeochemical factors. Petroleum Coke and Raw Oil Sand dust were identified as the major contributing sources of ΣPAH + PAC in the AOSR. These two sources accounted for 63% (43.2 μg g−1) of ΣPAH + PAC deposition to the entire study domain. Of this overall 43.2 μg g−1 contribution, approximately 90% (39.9 μg g−1) ΣPAH + PAC was deposited within 25 km of the closest oil sand production facility. Regional sources (Biomass Combustion and Mobile Sources) accounted for 19% of ΣPAH + PAC deposition to the entire study domain, of which 46% was deposited near-field to oil sand production operations. Source identification was improved over a prior lichen-based study in the AOSR through incorporation of PAH and PAC analytes in addition to inorganic analytes.
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•Epiphytic lichen PAH bioindicator study conducted in Athabasca Oil Sands Region•Receptor modeling elucidated and quantified significant contributing sources.•C1-C2-alkyl PAHs and dibenzothiophenes utilized as tracer species•Petroleum coke and raw oil sand dust accounted for 67% of near field SPAH deposition.•Petroleum coke source required the use of C1-C2-alkyl PAH tracer species to resolve.
•A method for determining PAHs and PACs in lichens by GC-TOF-MS is described.•GC-TOF mass spectra show possibility for misclassifying C3 and C4 PACs.•Data are compared with other lichen-PAH and ...passive sampling-PAC studies.•Standardization of methodological reporting among investigators is needed.
Development of the Athabasca Oil Sands Region in northeastern Alberta, Canada has contributed polycyclic aromatic hydrocarbons (PAHs) and polycyclic aromatic compounds (PACs), which include alkyl PAHs and dibenzothiophenes, to the regional environment. A new analytical method was developed for quantification of PAHs and PACs in the epiphytic lichen bioindicator species Hypogymnia physodes for use in the development of receptor models for attribution of PAH and PAC concentrations to anthropogenic and natural emission sources. Milled lichens were extracted with cyclohexane, and extracts were cleaned on silica gel using automated solid phase extraction techniques. Quantitative analysis was performed by gas chromatography with selected ion monitoring (GC-SIM-MS) for PAHs, and by GC with time-of-flight mass spectrometry (GC-TOF-MS) for PACs. PACs were quantitated in groups using representative reference compounds as calibration standards. Analytical detection limits were ≤2.5ngg−1 for all individual compounds. Precision as measured by laboratory duplicates was variable; for individual analytes above 5ngg−1 the mean absolute difference between duplicates was typically <20%. Selection of single-analyte markers for source attribution should include consideration of data quality indicators. Use of TOF-MS to spectrally characterize PAC group constituents identified significant challenges for the accurate quantitation of PACs with more than two carbons in their side chain(s). Total PAH concentrations in lichen samples ranged from 12 to 482ngg−1. Total PACs in each sample varied from a fraction of total PAHs to more than four times total PAHs. Results of our analyses of H. physodes are compared with other studies using other species of lichens as PAH receptors and with passive monitoring data using polyurethane foam (PUF) samplers in the Athabasca Oil Sands Region (AOSR). This study presents the first analytical methodology developed for the determination of PACs in an epiphytic lichen bioindicator species.
Temporal and spatial atmospheric deposition trends of elements to the boreal forest surrounding bitumen production operations in the Athabasca Oil Sands Region (AOSR), Alberta, Canada were ...investigated as part of a long-term lichen bioindicator study. The study focused on eight elements (sulfur, nitrogen, aluminum, calcium, iron, nickel, strontium, vanadium) that were previously identified as tracers for the major oil sand production sources. Samples of the in situ epiphytic lichen Hypogymnia physodes were collected in 2002, 2004, 2008, 2011, 2014, and 2017 within a ~150 km radius from the center of surface oil sand production operations in the AOSR. Site-specific time series analysis conducted at eight jack pine upland sites that were repeatedly sampled generally showed significant trends of increasing lichen concentrations for fugitive dust linked elements, particularly at near-field (<25 km from a major oil sands production operation) sample locations. Multiple regional scale geostatistical models were developed and evaluated to characterize broad-scale changes in atmospheric deposition based on changes in H. physodes elemental concentrations between 2008 and 2014. Empirical Bayesian kriging and cokriging lichen element concentrations with oil sands mining, bitumen upgrading, coke materials handling, and limestone quarry/crushing influence variables produced spatial interpolation estimates with the lowest validation errors. Gridded zonal mean lichen element concentrations were calculated for the two comprehensive sampling years (2008, 2014) and evaluated for spatial and temporal change. Lichen sulfur concentrations significantly increased in every grid cell within the domain with the largest increases (44–88%) in the central valley in close proximity to the major surface oil sand production operations, while a minor nitrogen concentration decrease (−20%) in a single grid cell was observed. The areal extent of fugitive dust element deposition generally increased with significantly higher deposition to lichens restricted to the outer grids of the enhanced deposition field, reflecting new and expanding surface mining activity.
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•H. physodes is an effective indicator of gas and particulate atmospheric deposition.•Geostatistical models were developed/evaluated to elucidate atmospheric deposition.•Cokriging with production influence variables provided the lowest validation errors.•Highest lichen concentrations were observed near surface oil sand production sites.•Significant temporal and spatial deposition trends were observed between 2004 and 2017.
► We studied 256 men to see if PFOA and PFOS impacted semen quality or hormones. ► Blood and semen were analyzed for PFAs and reproductive and thyroid hormones. ► Semen quality was assessed using ...standard clinical methods. ► Neither PFOA nor PFOS was significantly associated with functional semen parameters. ► LH, but not FSH, was positively correlated with plasma PFOA and PFOS.
A total of 256 men were studied to evaluate whether serum concentrations of perfluorooctanoate (PFOA) and perfluorooctane sulfonate (PFOS) impacted semen quality or reproductive hormones. Blood and semen were collected and analyzed for perfluorochemicals and reproductive and thyroid hormones. Semen quality was assessed using standard clinical methods. Linear and logistic modeling was performed with semen profile measurements as outcomes and PFOS and PFOA in semen and plasma as explanatory variables. Adjusting for age, abstinence, and tobacco use, there was no indication that PFOA or PFOS was significantly associated with volume, sperm concentration, percent motility, swim-up motility and concentration, and directional motility (a function of motility and modal progression). Follicle-stimulating hormone was not associated with either PFOA or PFOS. Luteinizing hormone was positively correlated with plasma PFOA and PFOS, but not semen PFOS. Important methodological concerns included the lack of multiple hormonal measurements necessary to address circadian rhythms.
A 2014 case study investigated the relative accumulation efficiency of polycyclic aromatic hydrocarbons (PAHs), total sulfur (S), total nitrogen (N), major and minor elements and Pb isotopes in five ...common lichen species at three boreal forest sites in the Athabasca Oil Sands Region (AOSR) in northeastern Alberta, Canada to identify the optimum lichen species for future biomonitoring. Differences in concentrations of PAHs, multiple elements, and Pb isotopes in fruticose (Bryoria furcellata, Cladina mitis, Evernia mesomorpha) and foliose (Hypogymnia physodes and Tuckermannopsis americana) lichens were found along a 100 km distance gradient from the primary oil sands operations. Integration of insights from emission source samples and oil sands mineralogy in consort with aerosol collection indicates incorporation of more fine particulate matter (PM) into foliose than fruticose lichen biomass. Contrasting PAH with element concentrations allowed lichen species specific accumulation patterns to be identified. The ability of lichen species to incorporate different amounts of gas phase (S and N), petrogenic (V, Ni, Mo), clay (low Si/Al and more rare earth elements), and sand (higher Si/Al and Ti) components from the oil sand operations reflects aerosol particle size and lichen physiology differences that translate into differences in PM transport distances and lichen accumulation efficiencies. Based on these findings Hypogymnia physodes is recommended for future PAH biomonitoring and source attribution studies.
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•Five lichen species collected from three site transect in Athabasca Oil Sands Region.•Lichen specific concentration gradients in PAHs, S, N, and 32 elements were found.•Different coarse and fine particulate matter multi-element fingerprints identified.•Oil sands mineralogy and Pb isotopes provided particulate matter source insights.•Size dependent incorporation of aerosols in foliose and fruticose lichens documented.
A comprehensive filter-based particulate matter polycyclic aromatic hydrocarbon (PAH) source apportionment study was conducted at the Wood Buffalo Environmental Association Bertha Ganter-Fort McKay ...(BGFM) community monitoring station from 2014 to 2015 to quantify ambient concentrations and identify major sources. The BGFM station is located in close proximity to several surface oil sands production facilities and was previously found to be impacted by their air emissions. 24-hour integrated PM2.5 and PM10–2.5 samples were collected on a 1-in-3-day schedule yielding 108 complete organic/inorganic filter sets for source apportionment modeling. During the study period PM2.5 averaged 8.6 ± 11.8 μg m−3 (mean ± standard deviation), and PM10–2.5 averaged 8.5 ± 9.5 μg m−3. Wind regression analysis indicated that the oil sands production facilities were significant sources of PM2.5 mass and black carbon (BC), and that wildland fires were a significant source of the highest PM2.5 (>10 μg m−3) and BC events. A six-factor positive matrix factorization (PMF) model solution explained 95% of the measured PM2.5 and 78% of the measured ΣPAH. Five sources significantly contributed to PM2.5 including: Biomass Combustion (3.57 μg m−3; 40%); Fugitive Dust (1.86 μg m−3; 28%); Upgrader Stack Emissions (1.44 μg m−3; 21%); Petrogenic PAH (1.20 μg m−3; 18%); and Transported Aerosol (0.43 μg m−3 and 6%). However, the analysis indicated that only the pyrogenic PAH source factor significantly contributed (78%) to the measured ΣPAH. A five-factor PMF model dominated by fugitive dust sources explained 98% of PM10–2.5 mass and 86% of the ΣPAH. The predominant sources of PM10–2.5 mass were (i) Haul Road Dust (4.82 μg m−3; 53%), (ii) Mixed Fugitive Dust (2.89 μg m−3; 32%), (iii) Fugitive Oil Sand (0.88 μg m−3; 10%), Mobile Sources (0.23 μg m−3; 2%), and Organic Aerosol (0.06 μg m−3; 1%). Only the Organic Aerosol source significantly contributed (86%) to the measured ΣPAH.
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•Ambient PM PAH source apportionment study conducted in Athabasca Oil Sands Region.•Receptor modeling elucidated and quantified significant contributing PM sources.•C1- and C2-alkyl PAHs and dibenzothiophenes utilized as tracer species.•One pyrogenic PM2.5 source factor contributed 78% of the measured ΣPAH.•One organic aerosol PM10–2.5 source factor contributed 86% of the measured ΣPAH.
Polybrominated diphenyl ethers (PBDEs) are used commercially as additive flame retardants and have been shown to transfer into environmental compartments, where they have the potential to ...bioaccumulate in wildlife and humans. Of the 209 possible PBDEs, 2,2′,4,4′-tetrabromodiphenyl ether (BDE-47) is usually the dominant congener found in human blood and milk samples. BDE-47 has been shown to have endocrine activity and produce developmental, reproductive, and neurotoxic effects. The objective of this study was to develop a physiologically based pharmacokinetic (PBPK) model for BDE-47 in male and female (pregnant and non-pregnant) adult rats to facilitate investigations of developmental exposure. This model consists of eight compartments: liver, brain, adipose tissue, kidney, placenta, fetus, blood, and the rest of the body. Concentrations of BDE-47 from the literature and from maternal–fetal pharmacokinetic studies conducted at RTI International were used to parameterize and evaluate the model. The results showed that the model simulated BDE-47 tissue concentrations in adult male, maternal, and fetal compartments within the standard deviations of the experimental data. The model's ability to estimate BDE-47 concentrations in the fetus after maternal exposure will be useful to design in utero exposure/effect studies. This PBPK model is the first one designed for any PBDE pharmaco/toxicokinetic description. The next steps will be to expand this model to simulate BDE-47 pharmacokinetics and distributions across species (mice), and then extrapolate it to humans. After mouse and human model development, additional PBDE congeners will be incorporated into the model and simulated as a mixture.
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