Article pubs.acs.org/ac
An Added Dimension: GC Atmospheric Pressure Chemical Ionization FTICR MS and the Athabasca Oil Sands Mark P. Barrow,*,† Kerry M. Peru,‡ and John V. Headley‡ †
Department of Chemistry, University of Warwick, Coventry, CV4 7AL United Kingdom Water Science and Technology Division, Environment Canada, 11 Innovation Boulevard, Saskatoon, Saskatchewan S7N 3H5 Canada
‡
S Supporting Information *
ABSTRACT: The Athabasca oil sands industry, an alternative source of petroleum, uses large quantities of water during processing of the oil sands. In keeping with Canadian environmental policy, the processed water cannot be released to natural waters and is thus retained on-site in large tailings ponds. There is an increasing need for further development of analytical methods for environmental monitoring. The following details the first example of the application of gas chromatography atmospheric pressure chemical ionization Fourier transform ion cyclotron resonance mass spectrometry (GC-APCI-FTICR MS) for the study of environmental samples from the Athabasca region of Canada. APCI offers the advantages of reduced fragmentation compared to other ionization methods and is also more amenable to compounds that are inaccessible by electrospray ionization. The combination of GC with ultrahigh resolution mass spectrometry can improve the characterization of complex mixtures where components cannot be resolved by GC alone. This, in turn, affords the ability to monitor extracted ion chromatograms for components of the same nominal mass and isomers in the complex mixtures. The proof of concept work described here is based upon the characterization of one oil sands process water sample and two groundwater samples in the area of oil sands activity. Using the new method, the Ox and OxS compound classes predominated, with OxS classes being particularly relevant to the oil sands industry. The potential to resolve retention times for individual components within the complex mixture, highlighting contributions from isomers, and to characterize retention time profiles for homologous series is shown, in addition to the ability to follow profiles of double bond equivalents and carbon number for a compound class as a function of retention time. The method is shown to be well-suited for environmental forensics.
C
ongoing need to improve environmental monitoring in the Athabasca region for anthropogenic influences.23 A variety of analytical methods are used for the monitoring program.24 Mass spectrometry (MS) is among the techniques at the forefront of the advances in this area. The approaches have included: gas chromatography mass spectrometry (GC-MS),25−27 two-dimensional GC-MS,28−31 and liquid chromatography (LC) MS.32−35 Some of the most promising advances have resulted from the application of ultrahigh resolution mass spectrometry, with Fourier transform ion cyclotron resonance (FTICR)36−38 mass spectrometry playing a particularly prominent role. The first use of FTICR mass spectrometry for oil sands-related samples was in 2004,9 and Orbitrap mass spectrometry was first applied in 2011.39 Ultrahigh resolution mass spectrometry is particularly well-suited to the analysis of complex mixtures due to the ability to resolve multiple peaks of the same nominal mass, with low
onsumption of crude oil continues to rise, accompanied by increases in the price per barrel.1,2 As a result, other sources of petroleum, many of which were considered not economically viable, are now being exploited. One of these sources is the Athabasca oil sands, situated in northern Alberta, Canada. The oil sands are a mixture of bitumen (60%), water (30%), and solids such as clay and sand (10%).3 The Athabasca oil sands reserves are estimated to represent 1.7 trillion barrels, with 173 billion barrels being economically recoverable using current technology. Following surface mining of the oil sands, a modified version of the Clark alkaline hot water extraction process can be used to extract the bitumen.4 The extraction process requires large volumes of water, where approximately two to four barrels of water are required to produce one barrel of oil. Due to a zero discharge policy, this oil sands process water (OSPW) is retained in on-site tailings ponds. As of 2009, the estimated volume of water being stored was approximately 109 m3.5 OSPW is known to contain compounds which can be toxic to aquatic organisms, including naphthenic acids6−19 and polycyclic aromatic hydrocarbons.16,20−22 As a consequence, there is an © 2014 American Chemical Society
Received: May 7, 2014 Accepted: July 18, 2014 Published: July 18, 2014 8281
dx.doi.org/10.1021/ac501710y | Anal. Chem. 2014, 86, 8281−8288
Analytical Chemistry
Article
wide range of compounds and fragmentation is minimized. As a result of coupling the three techniques, complex samples can be characterized, where both the retention time and m/z of each component can be recorded and, due to the ultrahigh resolving power, the extracted ion chromatograms (EICs) of coeluting components may be followed. These features, in turn, are shown to be well-suited to the determination of isomers for a given molecular composition in oil sands environmental samples. The GC-APCI-FTICR MS experiments represent the first application of this analytical method for characterization of samples from the oil sands region of Athabasca, Canada. The proof-of-concept study involved the study of three samples: one OSPW sample and two groundwater samples acquired in the vicinity of the industrial site. The ability to monitor for the presence of isomers within complex mixtures has potential for improving environmental monitoring methods.
mass errors affording higher confidence in the assignments of elemental compositions. Compared to lower resolution methods, more information can typically be obtained from an ultrahigh resolution mass spectrum, as more components can be observed and assigned. FTICR mass spectrometry is wellestablished within the field of “petroleomics,” where highly complex mixtures such as crude oils have been characterized.40−46 Since the earliest application to samples from the Athabasca region, FTICR mass spectrometry has made a number of significant contributions. The influence of sample preparation methods upon the data has been demonstrated,18,47 highlighting the importance of comparing analytical data that has been obtained under similar sample extraction conditions. OSPWrelated organic components containing heteroatoms other than oxygen, such as nitrogen and sulfur, were also observed, demonstrating the broader complexity of such samples, which had not previously been observed using lower resolution techniques.14,16 A comparison of positive-ion and negative-ion data from both electrospray ionization (ESI), one of the most commonly used ionization methods, and atmospheric pressure photoionization (APPI) sources highlighted even further complexity. For example, nonpolar components could be observed by APPI but were not amenable to ESI.16 Grewer et al.48 later reiterated some of these findings, focusing upon the assignment of “oxy-naphthenic acids.” It was stated that more than 50% of the peaks could not be categorized as “naphthenic acids”, and the question was raised regarding what range of organic components were present. Headley et al.19 compared river and lake water profiles with those associated with industrial sites in the oil sands region. Studies of such environmental samples demonstrated that natural and anthropogenic sources could be distinguished, with the ratios of the sulfur-containing compound classes having particular potential for environmental monitoring. While ultrahigh resolution mass spectrometry has played a significant role in providing a more accurate understanding of the complexity of the organic profiles of water samples from Athabasca, there is a growing need to more fully address the role of structure of components in the context of environmental toxicity and potential for improved environmental forensics. Tandem mass spectrometry experiments are useful for structural determination but can be misleading where the parent ion is a mixture of structural isomers with the same elemental composition and, therefore, same mass. An alternative approach is the use of chromatography, where structural isomers can be separated prior to mass spectrometry or indeed tandem mass spectrometry experiments. Solouki and co-workers have previously demonstrated the coupling of GC with an FTICR mass spectrometer using electron ionization (EI).49−51 EI has the advantage of being able to ionize a wide range of compounds, but the high energy electrons also induce fragmentation of the ionized compounds. The extensive fragmentation of ions can present challenges for the characterization of complex mixtures. By contrast, ESI, which has been widely used for the analysis of complex mixtures, has the disadvantage of being amenable only to highly polar and ionic compounds, but has the advantage of being a “soft” ionization technique, minimizing fragmentation. The work described herein illustrates the application of coupling of GC instrumentation with atmospheric pressure chemical ionization (APCI) and a high field FTICR mass spectrometer. APCI is particularly suitable for the characterization of complex mixtures as it is amenable to the ionization of a
■
EXPERIMENTAL SECTION Samples were collected from a region of Athabasca River Basin, Alberta, Canada; one OSPW sample and two groundwater samples were obtained. The collection sites related to a given transect along a groundwater flow path in the Athabasca region.52 The two groundwater samples are referred to as “Groundwater 1” and “Groundwater 2.” The samples were filtered under vacuum, acidified to pH 4.5, and extracted using Strata-X-A solid phase extraction sorbent (Phenomenex Torrance, CA, USA). The extracts were then methylated using BF3-methanol53 prior to gas chromatography separation and mass spectrometry analysis. A 7890A GC (Agilent Technologies, Santa Clara, California, USA) was coupled to an APCI source (Bruker Daltonik, Bremen, Germany), which was in turn coupled to a 12 T solariX FTICR mass spectrometer (Bruker Daltonik, Bremen, Germany), resulting in the setup for GC-APCI-FTICR MS experiments. For each experiment, 2 μL of sample was injected into the GC and helium was used as the carrier gas for the 30 m HP-5 column (Agilent Technologies, Santa Clara, California, USA). The oven temperature was held at 40 °C for 1 min before being increased at a rate of 20 °C min−1 until a final temperature of 280 °C was reached. The oven was then maintained at 280 °C for 20 min. It may be noted that there is a compromise between the duration of the GC stage and the file size of the complete GC-APCI-FTICR data; longer GC experiments result in larger ultimate file sizes. For the following work, experiments associated with each sample resulted in files that were approximately 20−30 GB in size. The interface of the GC to the mass spectrometer was a heated probe, maintained at 290 °C, which was fitted to the APCI source. Samples were ionized by a corona discharge needle in the APCI source prior to analysis using the FTICR mass spectrometer. In between experiments, hexane blanks were run to ensure there was no carryover between samples. Positive-ion, broadband, magnitude mode54−56 mass spectra were acquired, using the detection range of m/z 98−3000 and operating the instrument in chromatography mode. 2 MW data sets37,38 were obtained (with an acquisition time of approximately 0.56 s for the following data), the data were zero-filled57 once, and sine-bell apodization58,59 was applied. A fast Fourier transform (FFT) was used to convert from the time domain to the frequency domain; from the relationship between frequency and m/z, the data could then be converted to mass spectra. After sine-bell apodization, the mass spectra had an associated resolving power of approximately 330,000 (fwhm) at m/z 200 or 220,000 (fwhm) at m/z 300, for example; as is well-known for 8282
dx.doi.org/10.1021/ac501710y | Anal. Chem. 2014, 86, 8281−8288
Analytical Chemistry
Article
Figure 1. Total ion chromatograms for an OSPW sample and two groundwater samples.
Figure 2. Three-dimensional representation of m/z versus retention time for the OSPW sample.
Figure 3. Example extracted ion chromatograms from the OSPW sample, showing ions of the same nominal m/z. Ultrahigh resolving power affords the ability to monitor EICs within narrow m/z ranges, making it possible to monitor contributions from different isomers in complex mixtures. Compounds belonging to the O1, O2, O3, and O4 classes are shown here; all observed with the same nominal m/z (m/z 251) and eluting on similar time scales.
FTICR mass spectrometry, should higher resolving power be required, longer acquisition times (larger data sets) can instead be used. The mass spectra were processed and analyzed using a combination of DataAnalysis 4.0 SP5 (Bruker Daltonik, Bremen, Germany), MZmine 2,60 Composer 1.0.6 RC3 (Sierra Analytics, Modesto, CA, USA), and Aabel 3.0.6 (Gigawiz Ltd. Co., Tulsa, OK, USA). From the total ion chromatogram (TIC), time
sections could be taken and the resulting mass spectra were generated. The minimum size of each time section would be the time for a single scan (approximately one second) and the maximum size would be the full length of the TIC. Each time section produces an individual mass spectrum which must be processed and analyzed, with shorter time sections leading to a greater number of mass spectra. There is therefore a balance 8283
dx.doi.org/10.1021/ac501710y | Anal. Chem. 2014, 86, 8281−8288
Analytical Chemistry
Article
Figure 4. Broadband positive-ion GC-APCI-FTICR mass spectra for the OSPW sample, represented as a function of retention time.
associated with C14H18O4, C18H18O, C15H22O3, and C16H26O2 can be observed at approximately m/z 251.128, 251.143, 251.164, and 251.201, respectively), highlighting that multiple components may coelute. As a convenient method of categorization throughout, the heteroatom content is used to denote the compound class; for example, a compound containing a number of carbon atoms, a number of hydrogen atoms, and two oxygen atoms would be categorized as part of the “O2” class. Ultrahigh resolution thus remains an important tool for detailed characterization of complex mixtures, even where hyphenated methods may be employed. From the preliminary work shown here, it can be seen that the EICs for the C18H18O and C15H22O3 species represented a convolution of two or more peaks. This indicates that compounds of the same m/z but different retention times, and therefore same molecular formulas but different structures, were detected. The findings provide evidence for contributions from isomeric components within samples from the Athabasca region. Further work involving the use of authentic standards would be necessary to establish their identities. The EICs for a homologous series (DBE = 3, Z = −4) are shown in the Supporting Information (Figure S2). Mass spectra can be produced by sampling time sections from the TICs. The length of these time sections is determined by the user and represents a compromise between useful chromatographic information and the quality of the mass spectra. From the principle of signal averaging, acquiring multiple scans improves the signal-to-noise ratio. The length of each scan depends upon the performance requirements, as using longer acquisition times results in higher resolving power. For FTICR instruments, the time scale of an entire scan, from accumulation of ions to nondestructive detection, is typically of an order of seconds, depending on the experimental parameters. Two minute time sections have been used here, although longer or shorter sections could be chosen, as required. Figure 4 shows the mass spectra resulting from 2 min time sections, starting at 9 min and ending at 21 min, for the OSPW sample. Heavier components become more prevalent with increasing retention time. At shorter retention times, a limited number of lower mass components predominate. To determine the origins of these contributions, each of the ultrahigh resolution mass spectra can be analyzed to accurately determine the molecular composition for each peak.
between the chosen size of the time sections and the amount of subsequent data analysis required. For the following work, 2 min time sections were chosen. Following assignments of molecular compositions for each peak in a mass spectrum, the data was categorized according to heteroatom content, carbon number, and double bond equivalents (DBE) or “hydrogen deficiency” (Z). A variety of visualization methods were then used to represent the data.61
■
RESULTS AND DISCUSSION The TICs for the three samples investigated are shown in Figure 1. Following the total output as a function of time alone produces relatively few distinguishing features for complex mixtures, as the GC alone cannot resolve the components. Coupling with a mass spectrometer, so that the data can be measured as a function of both retention time and m/z, provides greater information. A three-dimensional representation of the data for the OSPW sample is shown in Figure 2; an alternative representation is shown in the Supporting Information (Figure S1). The majority of the components elute within the retention times of approximately 9−13 min and approximately with the range of m/z 200−300. While GC-MS is a well-established technique, the mass spectrometer used typically has low resolving power. The work described here is believed to be the first example of coupling gas chromatography and APCI to a mass spectrometer of ultrahigh resolving power for the analysis of complex samples relating to the oil sands industry. The necessity for ultrahigh resolving power to resolve ions of the same nominal mass, following the prior separation using GC, is illustrated by Figure 3. The ultrahigh resolution makes it possible to follow the extracted ion chromatograms (EICs) within very narrow m/z regions; the EICs here for each m/z were followed to within a window of ±0.005, although this window size can be changed as required during data analysis. This affords the possibility of monitoring contributions from different isomers within complex mixtures. The ability to determine the structural isomers in turn is expected to help improve the understanding of the toxicity of oil sands complex mixtures. Within a narrow m/z region shown in Figure 3 (approximately m/z 251.128−251.201), for instance, examples of EICs for four compound classes (O1, O2, O3, and O4) can be seen (ions 8284
dx.doi.org/10.1021/ac501710y | Anal. Chem. 2014, 86, 8281−8288
Analytical Chemistry
Article
Figure 5. Bar charts of percentage contribution to total signal versus selected compound classes, represented as a function of retention time.
Following the assignment of the peaks in each mass spectrum for each time section, the results can be represented using
different methods. Figure 5 shows bar charts of the percentage contribution from selected compound classes as a function of 8285
dx.doi.org/10.1021/ac501710y | Anal. Chem. 2014, 86, 8281−8288
Analytical Chemistry
Article
Figure 6. Plot showing contributions to each 2 min time section from different homologous series from the O2 class as a function of retention time. The data shown here is for the OSPW sample.
Figure 7. Plots of double bond equivalents versus carbon number for the OSPW sample, shown as a function of time.
time, for each of the three samples; an alternative representation of the data for the OSPW sample is shown in Figure S3 in the Supporting Information. At retention times of 9−13 min, the O2
compound class was predominant. During retention times of 13−19 min, a greater proportion of the signal was associated with the other Ox classes (e.g., O1, O3, O4, O5, and O6) and also the 8286
dx.doi.org/10.1021/ac501710y | Anal. Chem. 2014, 86, 8281−8288
Analytical Chemistry
Article
a mass spectrometer which can offer ultrahigh resolving power has made it possible to resolve the isobaric, coeluting components that were present within the complex oil sands environmental samples investigated. As a result, it was also possible to follow the extracted ion chromatograms of individual molecular compositions, determining the relationship with retention time. The visualization of such data provided preliminary indications of the presence of isomers, which is important to further the understanding of toxicity of oil sands environmental samples. Further work will be necessary to identify the structures of the isomers. Among the predominant components were the O2 class, which would be grouped as naphthenic acids. The retention times of the Ox species typically increased with increasing DBE. A number of sulfur-containing components, belonging to OxS classes, were also detected, with the most significant contribution being found within the OSPW sample, particularly the O3S class. While the sulfur-containing compounds were less prominent in the two groundwater samples, the presence of these components in environmental samples in the vicinity of oil sands activity warrants further study. The preliminary work has demonstrated the potential for GCAPCI-FTICR MS as a complementary method to be used for environmental monitoring.
OxS classes (O2S, O3S, O4S, O5S, O6S, and O7S). The two groundwater samples were taken from a transect along a groundwater flow path, where previous work monitored attenuation of the naphthenic acid contributions as a function of distance from the source.52 Ultrahigh resolution mass spectrometry can prove useful in determining subtle differences between the profiles of the organic components present within the samples. The contribution from the OxS classes was greatest for the OSPW sample and lowest for the Groundwater 2 sample, for example. Work by Headley et al.19 has demonstrated that the OxS classes may be diagnostic for samples from areas of oil sands activity and potentially serve to distinguish the origins of the samples. While the bar charts can provide a useful overview of the composition of the mass spectrum, the data can be analyzed in more detail. For example, for each contribution from a compound class, it is possible to provide a further breakdown in terms of double bond equivalents. Figure 6 shows the contributions to each 2 min time section from the different homologous series (same heteroatom content and DBE) constituting the O2 class, present within the OSPW sample, as a function of retention time. It can be seen that the series for 2.5 and 3.5 DBE (3 and 4 for the neutral compounds; Z = −4 and −6) at lower retention times provided the largest percentage contribution. This correlates with the predominant peaks observed in Figure 4 and the strong contributions from the O2 class during the 9−11 min and 11−13 min time scales. Figure 6 also highlights that the retention times increased with increasing DBE (or Z). To provide further information, the distribution of both DBE and carbon number for a given compound class can be visualized. Plots of DBE versus carbon number are shown for the O2, O3, and O4 classes over three retention times for the OSPW sample in Figure 7. The total contribution for each of the Ox classes as a function of time is also shown in Figure S4 in the Supporting Information. The O2 components displayed a strong contribution at 11−13 min, particularly for a DBE range of 2.5 to 4.5 for the protonated ions (DBE = 3−5 for the neutral, methylated compounds, Z = −4 to −8), which then decreased with retention time and where higher DBE species (DBE = 5−11 for the neutral, compounds, Z = −8 to −20) became more prevalent. By contrast, the O4 species increased in contribution with retention time, with major contributions at higher retention times spanning the range of approximately DBE = 5−11 for neutral, methylated compounds (Z = −8 to −20). The carbon number range for the O4 class was similar to that observed for the O2 class, supporting the theory that they are not dimers. At 9−11 min, the starting DBE for the O4 class was 3.5 for the protonated ion (DBE = 4 for the neutral, methylated compound, Z = −6), which was 1 DBE higher than for the O2 class. This would be consistent with the presence of dicarboxylic acid species.
■
ASSOCIATED CONTENT
* Supporting Information S
Figure S1: Plot of m/z vs retention time for the OSPW sample. Figure S2: TIC (top) and EICs for part of a homologous series observed within the OSPW sample. Figure S3: Contributions from selected compound classes as a function of time for the OSPW sample. Figure S4: Contributions from the Ox classes for each sample as a function of time. This material is available free of charge via the Internet at http://pubs.acs.org/
■
AUTHOR INFORMATION
Corresponding Author
*E-mail:
[email protected]. Notes
The authors declare no competing financial interest.
■
ACKNOWLEDGMENTS The authors gratefully acknowledge the Program of Energy Research and Development (PERD) for providing funding and David Stranz (Sierra Analytics) for helpful contributions.
■
REFERENCES
(1) Barrow, M. P. Biofuels 2010, 1, 651−655. (2) Murray, J.; King, D. Nature 2012, 481, 433−435. (3) Gu, G.; Xu, Z.; Nandakumar, K.; Masliyah, J. H. Fuel 2002, 81, 1859−1869. (4) Schramm, L. L.; Stasiuk, E. N.; MacKinnon, M. Surfactants in Athabasca oil sands slurry conditioning, flotation recovery, and tailings processes; Cambridge University Press: Cambridge, 2000. (5) Han, X.; MacKinnon, M. D.; Martin, J. W. Chemosphere 2009, 76, 63−70. (6) Rogers, V. V.; Wickstrom, M.; Liber, K.; MacKinnon, M. D. Toxicol. Sci. 2002, 66, 347−355. (7) Barrow, M. P.; McDonnell, L. A.; Feng, X.; Walker, J.; Derrick, P. J. Anal. Chem. 2003, 75, 860−866. (8) Headley, J. V.; McMartin, D. W. J. Environ. Sci. Health A Tox. Hazard Subst. Environ. Eng. 2004, A39, 1989−2010. (9) Barrow, M. P.; Headley, J. V.; Peru, K. M.; Derrick, P. J. J. Chromatogr. A 2004, 1058, 51−59. (10) Clemente, J. S.; Fedorak, P. M. Chemosphere 2005, 60, 585−600.
■
CONCLUSION GC-APCI-FTICR MS was demonstrated for the first time as a method for the analysis of environmental samples from the oil sands producing region of Athabasca, in Canada. The usage of APCI as an ionization method allows for reduced fragmentation, compared to traditional ionization methods that are coupled with GC systems, such as EI. APCI is also suitable for a wide range of compound classes which may be present in complex mixtures, rather than only the polar and ionic species which are accessible by ESI. GC analysis alone cannot sufficiently resolve all of the components within the complex mixtures. Coupling the GC with 8287
dx.doi.org/10.1021/ac501710y | Anal. Chem. 2014, 86, 8281−8288
Analytical Chemistry
Article
(11) Nero, V.; Farwell, A.; Lee, L. E. J.; Van Meer, T.; MacKinnon, M. D.; Dixon, D. G. Ecotoxicol. Environ. Safe. 2006, 65, 252−264. (12) Smith, D. F.; Schaub, T. M.; Rahimi, P.; Teclemariam, A.; Rodgers, R. P.; Marshall, A. G. Energy Fuels 2007, 21, 1309−1316. (13) Headley, J. V.; Peru, K. M.; Barrow, M. P. Mass Spectrom. Rev. 2009, 28, 121−134. (14) Headley, J. V.; Peru, K. M.; Armstrong, S. A.; Han, X. M.; Martin, J. W.; Mapolelo, M. M.; Smith, D. F.; Rogers, R. P.; Marshall, A. G. Rapid Commun. Mass Spectrom. 2009, 23, 515−522. (15) Da Campo, R.; Barrow, M. P.; Shepherd, A. G.; Salisbury, M.; Derrick, P. J. Energy Fuels 2009, 23, 5544−5549. (16) Barrow, M. P.; Witt, M.; Headley, J. V.; Peru, K. M. Anal. Chem. 2010, 82, 3727−3735. (17) Headley, J. V.; Peru, K. M.; Mishra, S.; Meda, V.; Dalai, A. K.; McMartin, D. W.; Mapolelo, M. M.; Rodgers, R. P.; Marshall, A. G. Rapid Commun. Mass Spectrom. 2010, 24, 3121−3126. (18) Headley, J. V.; Barrow, M. P.; Peru, K. M.; Derrick, P. J. J. Environ. Sci. Health A Tox. Hazard. Subst. Environ. Eng. 2011, 46, 844−854. (19) Headley, J. V.; Barrow, M. P.; Peru, K. M.; Fahlman, B.; Frank, R. A.; Bickerton, G.; McMaster, M. E.; Parrott, J.; Hewitt, L. M. Rapid Commun. Mass Spectrom. 2011, 25, 1899−1909. (20) Headley, J. V.; Akre, C.; Conly, F. M.; Peru, K. M.; Dickson, L. C. Environ. Forensics 2001, 2, 335−345. (21) Colavecchia, M. V.; Backus, S. M.; Hodson, P. V.; Parrott, J. L. Environ. Toxicol. Chem. 2004, 23, 1709−1718. (22) Kelly, E. N.; Short, J. W.; Schindler, D. W.; Hodson, P. V.; Ma, M.; Kwan, A. K.; Fortin, B. L. Proc. Natl. Acad. Sci. U.S.A. 2009, 106, 22346− 22351. (23) Schindler, D. Nature 2010, 468, 499−501. (24) Headley, J. V.; Peru, K. M.; Mohamed, M. H.; Frank, R. A.; Martin, J. W.; Hazewinkel, R. R.; Humphries, D.; Gurprasad, N. P.; Hewitt, L. M.; Muir, D. C.; Lindeman, D.; Strub, R.; Young, R. F.; Grewer, D. M.; Whittal, R. M.; Fedorak, P. M.; Birkholz, D. A.; Hindle, R.; Reisdorph, R.; Wang, X.; Kasperski, K. L.; Hamilton, C.; Woudneh, M.; Wang, G.; Loescher, B.; Farwell, A.; Dixon, D. G.; Ross, M.; Pereira, A. d. o. s. . S.; King, E.; Barrow, M. P.; Fahlman, B.; Bailey, J.; McMartin, D. W.; Borchers, C. H.; Ryan, C. H.; Toor, N. S.; Gillis, H. M.; Zuin, L.; Bickerton, G.; McMaster, M.; Sverko, E.; Shang, D.; Wilson, L. D.; Wrona, F. J. J. Environ. Sci. Health A Tox. Hazard. Subst. Environ. Eng. 2013, 48, 1145−1163. (25) Clemente, J. S.; Prasad, N. G. N.; MacKinnon, M. D.; Fedorak, P. M. Chemosphere 2003, 50, 1265−1274. (26) Merlin, M.; Guigard, S. E.; Fedorak, P. M. J. Chromatogr. A 2007, 1140, 225−229. (27) Scott, A. C.; Young, R. F.; Fedorak, P. M. Chemosphere 2008, 73, 1258−1264. (28) Hao, C.; Headley, J. V.; Peru, K. M.; Frank, R.; Yang, P.; Solomon, K. R. J. Chromatogr. A 2005, 1067, 277−284. (29) Rowland, S. J.; Scarlett, A. G.; Jones, D.; West, C. E.; Frank, R. A. Environ. Sci. Technol. 2011, 45, 3154−3159. (30) Rowland, S. J.; West, C. E.; Scarlett, A. G.; Jones, D.; Frank, R. A. Rapid Commun. Mass Spectrom. 2011, 25, 1198−1204. (31) West, C. E.; Scarlett, A. G.; Tonkin, A.; O’Carroll-Fitzpatrick, D.; Pureveen, J.; Tegelaar, E.; Gieleciak, R.; Hager, D.; Petersen, K.; Tollefsen, K. E.; Rowland, S. J. Water Res. 2013, 51, 206−215. (32) Clemente, J. S.; Yen, T. W.; Fedorak, P. M. J. Environ. Eng. Sci. 2003, 2, 177−186. (33) Yen, T. W.; Marsh, W. P.; MacKinnon, M. D.; Fedorak, P. M. J. Chromatogr. A 2004, 1033, 83−90. (34) Bataineh, M.; Scott, A. C.; Fedorak, P. M.; Martin, J. W. Anal. Chem. 2006, 78, 8354−8361. (35) Pereira, A. S.; Bhattacharjee, S.; Martin, J. W. Environ. Sci. Technol. 2013, 47, 5504−5513. (36) Amster, I. J. J. Mass Spectrom. 1996, 31, 1325−1337. (37) Marshall, A. G.; Hendrickson, C. L.; Jackson, G. S. Mass Spectrom. Rev. 1998, 17, 1−35. (38) Barrow, M. P.; Burkitt, W. I.; Derrick, P. J. Analyst 2005, 130, 18− 28.
(39) Headley, J. V.; Peru, K. M.; Janfada, A.; Fahlman, B.; Gu, C.; Hassan, S. Rapid Commun. Mass Spectrom. 2011, 25, 459−462. (40) Hughey, C. A.; Hendrickson, C. L.; Rodgers, R. P.; Marshall, A. G.; Qian, K. Anal. Chem. 2001, 73, 4676−4681. (41) Qian, K.; Robbins, W. K.; Hughey, C. A.; Cooper, H. J.; Rodgers, R. P.; Marshall, A. G. Energy Fuels 2001, 15, 1505−1511. (42) Purcell, J. M.; Juyal, P.; Kim, D. G.; Rodgers, R. P.; Hendrickson, C. L.; Marshall, A. G. Energy Fuels 2007, 21, 2869−2874. (43) Smith, D. F.; Rahimi, P.; Teclemariam, A.; Rodgers, R. P.; Marshall, A. G. Energy Fuels 2008, 22, 3118−3125. (44) Marshall, A. G.; Rodgers, R. P. Proc. Natl. Acad. Sci. U.S.A. 2008, 105, 18090−18095. (45) Cho, Y.; Qi, Y.; O’Connor, P. B.; Barrow, M. P.; Kim, S. J. Am. Soc. Mass Spectrom. 2014, 25, 154−157. (46) Griffiths, M. T.; Da Campo, R.; O’Connor, P. B.; Barrow, M. P. Anal. Chem. 2014, 86, 527−534. (47) Headley, J. V.; Peru, K. M.; Barrow, M. P.; Derrick, P. J. Anal. Chem. 2007, 79, 6222−6229. (48) Grewer, D. M.; Young, R. F.; Whittal, R. M.; Fedorak, P. M. Sci. Total Environ. 2010, 408, 5997−6010. (49) Szulejko, J. E.; Solouki, T. Anal. Chem. 2002, 74, 3434−3442. (50) Heffner, C.; Silwal, I.; Peckenham, J. M.; Solouki, T. Environ. Sci. Technol. 2007, 41, 5419−5425. (51) Luo, Z.; Heffner, C.; Solouki, T. J. Chromatogr. Sci. 2009, 47, 75− 82. (52) Savard, M. M.; Ahad, J. M. E.; Gammon, P.; Calderhead, A. I.; Rivera, A.; Martel, R.; Klebek, M.; Headley, J. V.; Lefebvre, R.; Welsh, B.; Smirnoff, A.; Pakdel, H.; Benoit, N.; Liao, S.; Jautzy, J.; Gagnon, C.; Vaive, J.; Girard, I.; Peru, K. A Local Test Study Distinguishes Natural from Anthropogenic Groundwater Contaminants Near an Athabasca Oil Sands Mining Operation; Geological Survey of Canada, Open File 7195, Natural Resources Canada, 2012. (53) Ahad, J. M.; Pakdel, H.; Savard, M. M.; Simard, M. C.; Smirnoff, A. Anal. Chem. 2012, 84, 10419−10425. (54) Xian, F.; Hendrickson, C. L.; Blakney, G. T.; Beu, S. C.; Marshall, A. G. Anal. Chem. 2010, 82, 8807−8812. (55) Qi, Y.; Thompson, C. J.; Van Orden, S. L.; O’Connor, P. B. J. Am. Soc. Mass Spectrom. 2011, 22, 138−147. (56) Qi, Y.; Barrow, M. P.; Li, H.; Meier, J. E.; Van Orden, S. L.; Thompson, C. J.; O’Connor, P. B. Anal. Chem. 2012, 84, 2923−2929. (57) Comisarow, M. B.; Melka, J. D. Anal. Chem. 1979, 51, 2198−2203. (58) Aarstol, M.; Comisarow, M. B. Int. J. Mass Spectrom. Ion Proc. 1987, 76, 287−297. (59) Qi, Y.; Li, H.; Wills, R. H.; Perez-Hurtado, P.; Yu, X.; Kilgour, D. P.; Barrow, M. P.; Lin, C.; O’Connor, P. B. J. Am. Soc. Mass Spectrom. 2013, 24, 828−834. (60) Pluskal, T.; Castillo, S.; Villar-Briones, A.; Oresic, M. BMC Bioinformatics 2010, 11, 395. (61) Barrow, M. P.; Headley, J. V.; Peru, K. M.; Derrick, P. J. Energy Fuels 2009, 23, 2592−2599.
8288
dx.doi.org/10.1021/ac501710y | Anal. Chem. 2014, 86, 8281−8288
