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Quantifying Short-Chain Chlorinated Paraffin Congener Groups Bo Yuan, Christian Bogdal, Urs Berger, Matthew MacLeod, Wouter A Gebbink, Tomas Alsberg, and Cynthia A. de Wit Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.7b02269 • Publication Date (Web): 16 Aug 2017 Downloaded from http://pubs.acs.org on August 20, 2017
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Quantifying Short-Chain Chlorinated Paraffin Congener Groups
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Bo Yuan1*, Christian Bogdal2, Urs Berger3, Matthew MacLeod1, Wouter A. Gebbink4, Tomas
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Alsberg1, Cynthia A. de Wit1
4 5
1
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Svante Arrhenius väg 8, SE-10691 Stockholm, Sweden
7
2
8
Zurich, Vladimir-Prelog-Weg 1, CH-8093 Zürich, Switzerland
9
3
Department of Environmental Science and Analytical Chemistry, Stockholm University,
Institute for Chemical and Bioengineering, Swiss Federal Institute of Technology, ETH
Department Analytical Chemistry, Helmholtz Centre for Environmental Research - UFZ,
10
Permoserstraße 15, DE-04318, Leipzig, Germany
11
4
12
Wageningen, Netherlands
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* Corresponding author address and e-mail:
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Svante Arrhenius väg 8, SE-10691 Stockholm, Sweden; bo.yuan@aces.su.se.
RIKILT, Wageningen University & Research, PO box 230, Akkermaalsbos 2, 67080 AE,
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Accurate quantification of short-chain chlorinated paraffins (SCCPs) poses an exceptional
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challenge to analytical chemists. SCCPs are complex mixtures of chlorinated alkanes with
18
variable chain length and chlorination level; congeners with a fixed chain length (n) and
19
number of chlorines (m) are referred to as a “congener group” CnClm. Recently, we resolved
20
individual CnClm by mathematically deconvolving soft ionization high-resolution mass
21
spectra of SCCP mixtures. Here we extend the method to quantifying CnClm by introducing
22
CnClm specific response factors (RFs) that are calculated from 17 SCCP chain-length
23
standards with a single carbon chain length and variable chlorination level. The signal pattern
24
of each standard is measured on APCI-QTOF-MS. RFs of each CnClm are obtained by
25
pairwise optimization of the normal distribution’s fit to the signal patterns of the 17 chain-
26
length standards. The method was verified by quantifying SCCP technical mixtures and
27
spiked environmental samples with accuracies of 82–123% and 76–109%, respectively. The
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absolute differences between calculated and manufacturer-reported chlorination degrees were
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-0.4–1.0%Cl for SCCP mixtures of 49–71%Cl. The quantification method has been replicated
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with ECNI magnetic sector MS and ECNI-Q-Orbitrap-MS. CnClm concentrations determined
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with the three instruments were highly correlated (R2 > 0.90) with each other.
Abstract
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Introduction
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Chlorinated paraffins (CPs) are economical and practical industrial additives, widely used in
34
plastics, metal-cutting fluids, paints, sealants and adhesives.1 Annual global production of
35
these chlorinated n-alkanes rose to 1 million tons in 2009.2 CPs fall into three categories:
36
short-chain (SCCPs, C10 – 13), medium-chain (MCCPs, C14 – 17) and long-chain CPs (LCCPs,
37
C≥18), and are further subcategorized into their weight percentage of chlorine substituents on
38
the carbon chain3, e.g. 52 %Cl and 70 %Cl. CPs, especially SCCPs, have been reported to be
39
ubiquitous and persistent in the environment and to accumulate in biota.4-8 SCCPs are toxic to
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aquatic organisms9 and possibly carcinogenic to humans.10 The Persistent Organic Pollutants
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Review Committee (POPRC) of the Stockholm Convention has listed SCCPs as POP
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candidates.9 Moreover, the European Chemicals Agency also added SCCPs to the candidate
43
list of substances of very high concern.11
44
The analysis, especially, the accurate quantification of SCCPs is an extremely demanding
45
task.12 This is mainly due to the extreme complexity of SCCP formulations, which are
46
produced as mixtures of tens of thousands of individual isomers with low position selectivity
47
of chlorine substitution during industrial synthesis.13,
48
individual congeners are available; complete separation of individual SCCP congeners has not
49
been achieved. To date, only semi-quantitative analysis of congener groups is achievable.15
50
Generally, SCCP quantification is attempted by treating all the congener groups (CnClm) in an
51
analyte as one compound, but this results in unpredictable errors. The quantification results of
52
the same sample vary significantly depending on the choice of standards.16, 17 The differences
53
between the chlorination degree of the SCCPs in the samples and in the standards can result
14
Very few analytical standards for
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in differences of up to an order of magnitude in the quantified concentration.18 The difference
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can be significantly reduced by mathematically deconvolving unknown SCCPs mixtures into
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linear combinations of several reference standards, as recently described by Bogdal et al.19
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So far, only one single attempt has been reported for the quantification of congener groups by
58
applying individual pure synthesized congeners as standards.20 The response factors (RFs) of
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C10Clm (m = 5 – 9) were adopted from the ones of corresponding individual congeners,
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calculated by the ratio of instrument detector response to analyte concentration or mass. The
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comparisons of relative RFs of monochlorine substituted C10 congeners supported the
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practicality of the method; however, the quantification was restricted by accuracy of congener
63
identification and by the availability of individual standards.17
64
The identification of SCCP congener groups relies on detection of pseudo-molecular ions by
65
soft ionization mass spectrometry, but interferences between CPs lead to overlapping mass
66
spectra. Even commonly available high-resolution mass spectrometry with a resolving power
67
in the range of 10,000 suffers from critical mass interferences. In a recent study, we
68
demonstrated that CP congener groups could be resolved by deconvolving soft ionization
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mass spectra of CPs, which is a prerequisite for accurate congener group quantification.21 To
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extend the method for quantitative analysis of individual congener groups in complex
71
samples, RFs for each congener group are required.
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To overcome the challenge of SCCP quantification, we developed a mathematical method
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that was applied to measurement results using atmospheric pressure chemical ionization
74
quadrupole time-of-flight mass spectrometry (APCI-QTOF-MS). First, the RF of each CnClm
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was calculated from selected SCCP chain length standards; thereafter, each CnClm in a sample
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was quantified by the corresponding RF. By quantifying CnClm, the sum of SCCPs, as well as
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the average chlorination degree, were accurately quantified in SCCP mixture standards,
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technical products and SCCPs spiked to environmental samples. This is the first study
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providing RFs of individual SCCP congener groups from a set of commercial standards with
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a single carbon chain length and variable chlorination level. These RFs, in combination with
81
the presented deconvolution procedure, allow quantifying concentrations of individual
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congener group in samples. We also show that our method is applicable in combination with
83
other soft ionization instruments, such as electron capture negative ionization (ECNI) coupled
84
to a magnetic sector MS (denoted sector MS) or a Q-Orbitrap MS.
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EXPERIMENTAL PROCEDURES
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Method Overview. The method was developed using APCI-QTOF-MS. A total of 17 Cn
87
chain length standards (4 C10, 4 C11, 5 C12 and 4 C13) were analyzed to derive the RFs of the
88
corresponding CnClm. The calculated RFs were then verified by quantifying three SCCP
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reference standards of various concentrations, four binary mixtures of an SCCP reference
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standard and a Cn chain length standard, eleven SCCP technical products, and six
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environmental sample extracts spiked with known amounts of SCCPs. The linear range of the
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instrumental response and the limit of detection (LOD) for each CnClm were further
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determined by dilution series of the SCCP reference standards. For method comparison,
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SCCPs in ten environmental samples were quantified with two independent methods, relying
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on the one hand on the new RFs, and on the other hand on the pattern-deconvolution
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procedure.19 Moreover, the new method was applied on a GC/ECNI- sector-MS and a
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GC/ECNI-Q-Orbitrap-MS. Finally, SCCP results in the samples of an interlaboratory study
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were compared between APCI-QTOF-MS and GC/ECNI-Q-Orbitrap-MS.
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Chain Length Standards. (1) C10 50.18 Cl% (w/w), (2) C10 55.00 %Cl, (3) C10 60.09 %Cl,
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(4) C10 65.02 %Cl, (5) C11 50.21 %Cl, (6) C11 55.20 %Cl, (7) C11 60.53 %Cl, (8) C11 65.25
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%Cl, (9) C12 45.32 %Cl, (10) C12 50.18 %Cl, (11) C12 55.00 %Cl, (12) C12 65.08 %Cl, (13)
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C12 69.98 %Cl, (14) C13 50.23 %Cl, (15) C13 55.03 %Cl, (16) C13 59.98 %Cl, and (17) C13
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65.18 %Cl were used undiluted. All Cn reference standards were 10 ng/µL in cyclohexane and
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purchased from Dr. Ehrenstorfer GmbH (Augsburg, Germany).
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SCCP Reference Standards. (1) SCCPs (C10-13) 51.5 %Cl, (2) SCCPs 55.5 %Cl, and (3)
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SCCPs 63.0 %Cl all 100 ng/µL in cyclohexane (Dr. Ehrenstorfer GmbH). A dilution series of
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each SCCP reference standard was prepared at concentrations of 100, 75, 50, 25, 10 and 5.0
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ng/µL. SCCPs 63.0 %Cl was further diluted at concentrations of 1.0, 0.50, 0.25 and 0.10
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ng/µL to obtain the LOD for GC/ECNI-Q-Orbitrap-MS, which provided noise-free ion
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chromatograms.22
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Binary Mixtures of Reference Standards. Known amounts of the SCCPs and the Cn
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reference standards were mixed. They were (1) SCCPs 51.5 %Cl mixed with C13 50.23 %Cl,
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(2) SCCPs 55.5 %Cl mixed with C13 55.03 %Cl, (3) SCCPs 63.0 %Cl mixed with C11 65.25
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%Cl, and (4) SCCPs 63.0 %Cl mixed with C12 69.98 %Cl. Detailed formulations are shown in
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Table 1.
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SCCP Technical Products. Eleven products covered a wide range of chlorination degrees,
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which have been declared by their manufacturers as (1, 2) 49 %Cl, (3) 50 %Cl, (4) 56 %Cl, (5)
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59 %Cl, (6, 7) 60 %Cl, (8) 63 %Cl, (9) 64 %Cl, (10) 70 %Cl and (11) 71 %Cl. These
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products were diluted to the range of 40 – 110 ng/µL for measurement (see Table 1).
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Environmental Samples. SCCPs were quantified in ten environmental samples, consisting of
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5 pooled fish samples, 3 sediment and 2 lubricant samples (Table S1). No replicate analyses
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were performed. For matrix effect tests, additional 6 environmental extracts, with non-
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detectable SCCP concentrations, consisting of 3 fish and 3 sediment, were spiked with known
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amounts of SCCPs reference standards (Table 1). The extraction and clean-up procedure is
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given in our previous work.21
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Table 1. Method validation using binary mixtures of SCCP reference standards, 11 SCCP technical products, and spiked environmental extracts. SCCPs (ng in 100 µL cyclohexane) Category
487 ng SCCP 51.5 %Cl + 372 ng C13 50.23 %Cl 420 ng SCCP 55.5 %Cl + 409 ng C13 55.03 %Cl 382 ng SCCP 63.0 %Cl + 379 ng C11 65.25 %Cl 346 ng SCCP 63.0 %Cl + 253 ng C12 69.98 %Cl Witaclor 149 Witaclor 159 Witaclor 63 Witaclor 171P Hüls 60C Technical Hüls 64 products Hüls 70 Cereclor 50Lv Cereclor 60L Cereclor 70L Hordalub 17 Herring-1 spiked with 651 ng SCCP 55.5 %Cl Herring-2 spiked with 4490 ng SCCP 55.5 %Cl Spiked Herring-3 spiked with 4260 ng SCCP 51.5 %Cl environmental Sediment-B1 spiked with 530 ng SCCP 63.0 %Cl extracts Sediment-B2 spiked with 643 ng SCCP 63.0 %Cl Sediment-B3 spiked with 4200 ng SCCP 51.5 %Cl * accuracy = calculated SCCPs ÷ assigned SCCPs; † absolute deviation = calculated %Cl – assigned %Cl. Binary mixtures of reference standards
128 129
chlorination degree
Formulation assigned
calculated
859 829 761 598 9060 7030 10600 9080 9200 8540 7770 8390 4610 6740 4800 651 4490 4260 530 643 4200
781 703 703 579 8160 8260 10600 7940 9220 8810 6370 9320 4700 7830 5240 496 4910 4610 524 677 4520
accuracy*
assigned
calculated
91% 85% 92% 97% 90% 118% 100% 88% 100% 103% 82% 111% 102% 116% 109% 76% 109% 108% 99% 105% 108%
50.95 %Cl 55.27 %Cl 64.12 %Cl 66.06 %Cl 49 %Cl 59 %Cl 63 %Cl 71 %Cl 60 %Cl 64 %Cl 70 %Cl 50 %Cl 60 %Cl 70 %Cl 49 %Cl 55.5 %Cl 55.5 %Cl 51.5 %Cl 63.0 %Cl 63.0 %Cl 51.5 %Cl
50.92 %Cl 54.37 %Cl 63.99 %Cl 66.25 %Cl 48.91 %Cl 59.15 %Cl 63.28 %Cl 70.85 %Cl 60.51 %Cl 64.38 %Cl 71.00 %Cl 49.90 %Cl 60.06 %Cl 69.95 %Cl 49.15 %Cl 55.40 %Cl 55.03 %Cl 51.91 %Cl 62.94 %Cl 62.77 %Cl 51.71 %Cl
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absolute deviation† –0.03 %Cl –0.90 %Cl –0.13 %Cl +0.19 %Cl –0.09 %Cl +0.15 %Cl +0.28 %Cl –0.15 %Cl +0.51 %Cl +0.38 %Cl +1.00 %Cl –0.10 %Cl +0.06 %Cl –0.05 %Cl +0.15 %Cl –0.10 %Cl –0.47 %Cl +0.41 %Cl +0.06 %Cl –0.23 %Cl +0.21 %Cl
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Interlaboratory Samples. Reference standard (Ampoule A), sediment extract cleaned up by
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the organizer (Ampoule B), and raw sediment extract (Ampoule C) were obtained from
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QUASIMEME (Quality Assurance of Information on Marine Environmental Monitoring in
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Europe, Phase III) for method validation and instrumental comparison. The extracts of
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Ampoule B and Ampoule C were from the same sediment.23 Sediment extract (Ampoule C)
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was cleaned-up with copper powder, sulfuric acid silica and deactivated silica24 before
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instrumental analysis. Each ampoule was analyzed in triplicate.
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All the SCCP standards, technical products and extracts of environmental samples were
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dissolved in 100 µL of cyclohexane. Each solution or extract was mixed with 20 ng
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Dechlorane 603 (Occidental Chemical Corp.) as volumetric standard before injection into the
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instruments.
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Instrumental Methods. The instrumental settings of APCI-QTOF-MS and GC/ECNI-sector-
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MS have been described previously21 with several adjustments. Detailed instrumental
143
settings are given in the Supporting Information Text S1-S3. Most notably, APCI-QTOF-MS
144
adopted a cone voltage of 20 V to maximize the detection of Cl3 and Cl4 congener groups.
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GC/ECNI-Q-Orbitrap-MS was operated under the maximum resolution of 120,000 FWHM
146
with a reagent gas flow rate of 1.4 mL/min, a maximum injection time of 250 ms, and the
147
automatic gain control target of 5e6.
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Instrumental Data Acquisition and Processing. Mass spectral data were acquired and the
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overlapping ions were deconvolved by the processing approach described in our previous
150
work.21 Briefly, the full scan spectra from the APCI-QTOF-MS was background subtracted;
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gas chromatographic “humps” using GC/ECNI-MS were integrated by an automatic
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algorithm. Accurate instrument responses of [M + Cl] – of CnCl2 – CnCln+2 in APCI-QTOF-
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MS and the responses of [M – Cl] – of CnCl5 – CnCln in GC/ECNI-sector-MS were
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deconvolved from the mass spectra. The responses of [M – Cl] – in GC/ECNI-Q-Orbitrap-MS
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were used for quantification without deconvolution. For detailed data processing see the
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Supporting Information, Text S1 and Text S2.
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Quantification Procedure. The procedure consists of deriving the response factors of
158
individual CnClm, with the aim to quantify CnClm in different SCCP mixtures. According to
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the definition of RF,25 the RF of CnClm can be calculated using the equation below:
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RF(C Cl ) = (
161
where Area (CnClm) is the instrumental response of CnClm (signal area). If the concentration
162
(CnClm) is known, RF (CnClm) can be directly calculated by Equation 1.
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Unfortunately, the list of available CnClm congener group standards is not comprehensive. As
164
substitutes, we use Cn chain length standards, which are single-chain length congener
165
mixtures composed of several CnClm with different numbers of chlorine substituents (n fixed,
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m variable). The composition of CnClm is unknown; however, the total concentration and
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chlorination degree (%Cl) of the standards were provided by the manufacturers.
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Relative amounts of each CnClm have been found to follow a Gaussian curve in CP mixture
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standards.26 Based on the characteristics of the Cn standards (n and %Cl are known), we
170
applied Gaussian distribution to describe the CnClm composition. In other words, the closer
171
the %Cl of CnClm to that of the total chlorine content of the Cn standard, the higher its
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proportion in the Cn standard. For example, C10Cl5, C10Cl6 and C10Cl7, the chlorination
( )
)
(1)
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degrees of which are 56.36 %Cl, 60.96 %Cl and 64.73 %Cl, respectively, are the three most
174
abundant congener groups in the C10 60.09 %Cl reference standard (Figure 1). In this way, the
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relative amount of CnClm in a Cn reference standard (noted fi(CnClm|xm,σi)) can be described
176
by the Gaussian distribution function:
&
(' (%*+ ), ,- ,
177
(C Cl | , ) =
178
where the chlorination degree of the Cn standard i (%Cli) is the center of the peak, and the
179
unknown variable σi is the standard deviation describing how close the congener groups are
180
clustered. xm is the %Cl of CnClm, which can be calculated from the molecular formula:
181
= %./(C H"1"& Cl ) = ".6∙1.667∙("1"&)123.53∙
182
The relative amount of each CnClm in Cn standard i can be normalized to its percentage
183
composition:
184
C Cl % = ∑
185
So the concentration of CnClm in the standard can be calculated as
186
Concentration (C Cl ) = Concentration (C ) ∙ C Cl %
187
Now the RF of CnClm in the standard i, or Equation 1, can be re-written as
188
RF (C Cl ) =
189
where RFi (CnClm) only depends on the unknown σi.
√"#
∙e
(2)
23.53∙
8 ( |9 , ) 8 ( |9 , )
;
∙ 100
(3)
(4)
( )
E FG GH I' ,- J ( )∙ ∑; E FG GH I' ,- J
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(5)
(6)
Relative composition
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0.50 40%
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%Cl (C10) = 60.09 %Cl (C10Cl5) = 56.36
%Cl (C10Cl6) = 60.96
20% 0.25
%Cl (C10Cl7) = 64.73
0% 0.00
# Cl
1 2 3 4 5 6 7 8 9 101112
191
Figure 1. .Schematic Gaussian distribution of C10Clm in the C10 60.09 %Cl reference
192
standard. The curve is the Gaussian peak, the center of which is 60.09 %Cl. The columns
193
represent one possible relative composition of each C10Clm calculated from Equation 4 setting
194
σi of 0.05.
195
σi is calculated by an iterative computation (Solver Add-in in Microsoft Excel 2013). Figure 2
196
shows the flowchart of the computation. The initial value of σi is set at 0.05 in each C10
197
standard, which is an empirical value for fast iteration. The initial σi is based on all the
198
computation solutions in this study, and is therefore suitable for all the instances in this study
199
(Figures S1 to S11). Then RFi (C10Clm) is calculated using Equation 6. Pairwise comparisons
200
are made between selected RF (C10Clm) of two C10 standards (i and j) in the form of the
201
square residual (SR):
202
SR = L
MN (;O )&MNP (;O ) QR (G;O GH )SQRP (G;O GH ) ,
T
"
(7)
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where RFi (C10Clm) and RFj (C10Clm) are the RF of C10 standard i and j, respectively.
204
All the σi are iteratively updated until the sum of square residuals (SSR) is minimized.
205
Substituting the optimized σi into Equation 6 then yields the RF (C10Clm) in all the C10
206
standards (Figure 3). We used pairwise comparisons in the optimization to avoid overfitting
207
based on very low concentrations of congener groups in the tails of the Gaussian distribution.
208
The RFs of C10Cl3 – C10Cl10 are the average RFs in the pairwise compared Cn standards. For
209
example, RF (C10Cl5) is the average of those in C10 50.18 %Cl and in C10 55.00 %Cl. The RFs
210
of congener groups C10Cl11 and C10Cl12 are only from C10 65.02 %Cl. Likewise, the RFs of
211
C11 – C13 are calculated by their corresponding Cn standards (see flowcharts of C11 – C13 in
212
Figures S1 to S3).
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Figure 2. Iterative computation of the σi in the C10 chain length standards using APCI-QTOF-
215
MS. Two SR values were applied for C10Cl6 due to the results shown in Figure 3.
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217
Method Development Using APCI-QTOF-MS
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CnClm Response Factor, Linear Range and LOD. The iterative computation converged the
219
pairwise compared RFs. The relative differences of 27 out of 36 pairs were below 20 %
220
(Figure 3 and Figures S1-S3), with an average of 14% for all pairs. The calculated RFs are
221
provided in Figure 4. The RFs for individual congener groups are generally highest for
222
congener groups with an intermediate level of chlorines on the carbon chain. The linear range
223
and limits of detection (LOD, three times signal to noise) of all C10 – C13 congener groups
224
using APCI-QTOF-MS are shown in Table S2. Linear correlation coefficients of individual
225
CnClm were >0.97. LODs of individual SCCP congener groups varied from 0.2 – 100 pg/µL.
Relative RF to Cl12
RESULTS
140
2% 2% 8%
70 7% 1%
0
5%
43%
Cl3 226
17%
Cl4
Cl5
C10 50.18%Cl
Cl6
Cl7
Cl8
55.00%Cl
Cl9 Cl10 Cl11 Cl12 60.09%Cl
65.02%Cl
227
Figure 3. Response factors of C10Cl3 – C10Cl12 congener groups calculated by the C10 chain
228
length standards. The dashed line gives the average RF of the pairwise compared chain length
229
standards. The relative difference between the highest/lowest RF and the average is shown as
230
a percentage. As an example, the highest and the lowest RFs of C10Cl6 in pairwise compared
231
chain length standards were marked with full lines. The RF of C10Cl6 was derived from three
232
chain length standards due to the high relative differences.
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234
235 236
Figure 4. Relative RF of SCCP congener groups on APCI-QTOF-MS, GC/ECNI-sector-MS
237
and GC/ECNI-Q-Orbitrap-MS. The RFs were the average values of the RFs calculated by
238
substituting the optimized σi (Figure 2, Figure S7-S17) into Equation 6. All the average RFs
239
were then normalized to the smallest RF, which was C13Cl2, C10Cl5 and C10Cl5 congener
240
groups, on APCI-QTOF-MS, GC/ECNI-sector-MS and GC/ECNI-Q-Orbitrap-MS,
241
respectively.
242
Quantification. The total CP concentrations determined in the dilution series (n = 6) of
243
51.5 %Cl, 55.5 %Cl and 63.0 %Cl SCCP reference standards were close to the theoretical
244
concentrations with accuracies of 95 - 123%, 97 - 117%, and 82 - 113%, respectively.
245
Accuracies for quantifying mixed SCCP and Cn reference standards, SCCP technical products
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and spiked environmental samples were between 85% - 97%, 86% - 118%, and 76% - 109%,
247
respectively. SCCP congener group patterns are shown in Tables S3 and S4.
248
Ten environmental samples were quantified with two different methods, i.e., the new method
249
based on the calculated RFs and the recently introduced pattern-deconvolution procedure.19
250
The pattern-deconvolution method provided concentrations of SCCPs that are slightly lower
251
than the concentrations quantified by the calculated RFs by a factor of 0.72− 0.93. Detailed
252
pattern deconvolution, the comparison of the results and SCCP congener group patterns are
253
given in the Supporting Information, Text S4, Table S1 and Table S5, respectively. The
254
goodness-of-fit between the sample pattern and its deconvolved pattern is evaluated by the
255
coefficient of determination R2. R2 between the reconstructed patterns and the measured
256
patterns were 0.43 – 0.79.
257
Measurement of Chlorination Degrees. For the reference standards at different
258
concentrations (n = 6), the calculated chlorination degrees were between 51.1 – 51.5 %Cl,
259
55.2 – 55.8 %Cl, and 62.9 – 63.2 %Cl, which is consistent with the respective indications of
260
51.5 %Cl, 55.5 %Cl and 63.0 %Cl, provided by the manufacturers. Absolute deviations range
261
from -0.4 %Cl to 0.3 %Cl. The chlorination degrees of the SCCPs spiked into the
262
environmental extracts were calculated with slightly higher deviations between -0.5 %Cl and
263
0.4 %Cl. The deviations of technical products were between -0.2 %Cl and 1.0 %Cl (Table 1).
264
The chlorination degree of the CP products we analyzed with resolution at individual chain
265
lengths are similar to the total chlorination degree of the product. For instance, the
266
chlorination degrees of C10, C11, C12 and C13 CPs were calculated as 63.3 %Cl, 62.7 %Cl,
267
62.5 %Cl and 64.0 %Cl, respectively, in SCCP 63.0 %Cl. This is consistent with Gao et al.
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268
who obtained similar chlorination degrees of SCCP impurities as those of the CP products
269
(named CP-42, CP-52 and CP-70).26
270
Application with GC/ECNI-MS
271
The iterative computations for calculating RFs using GC/ECNI-sector-MS and GC/ECNI-Q-
272
Orbitrap-MS are shown in Figures S4-S7 and Figure S8-S11, respectively. The calculated
273
RFs of both GC/ECNI-MS instruments are shown in Figure 4. Similar to the results of APCI-
274
QTOF-MS, the RFs are generally highest for congener groups with an intermediate level of
275
chlorines on the carbon chain. GC/ECNI-MS is rather insensitive to Cl5 congener groups. No
276
C12Cl5 was detected in our study. The instrument showed no response to congener groups
277
with less than five chlorines or more than the number of carbons in the chain.
278
For GC/ECNI-sector-MS, accuracies of SCCP concentrations lay between 69% – 154% and
279
75% – 115%, when measuring the dilution series (n = 6) of SCCP 63.0 %Cl reference
280
standard and spiked environmental extracts (n = 3), respectively. The chlorination degree of
281
SCCP 63.0 %Cl was calculated as 63.0 – 63.3 %Cl. For GC/ECNI-Q-Orbitrap-MS,
282
accuracies of SCCP concentrations lay between 74% – 114% and 79% – 124%, when
283
measuring the dilution series (n = 6) of SCCP 63.0 %Cl reference standard and spiked
284
environmental extracts (n = 6), respectively. The chlorination degree of SCCP 63.0 %Cl was
285
calculated as 63.4 – 63.8 %Cl.
286
Interlaboratory Samples
287
Total SCCPs in the reference standard (Ampoule A), cleaned up sediment extract (Ampoule B)
288
and sediment extract (Ampoule C) cleaned up in this study were quantified at 100 ± 22%, 96
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± 8% and 97 ± 15% of the assigned values23 using APCI-QTOF-MS, and at 105 ± 7%, 117 ±
290
17% and 100 ± 23% using GC/ECNI-Q-Orbitrap-MS. R2 between the patterns of three
291
ampoules measured by two individual instruments were 0.96, 0.80 and 0.92, respectively
292
(Figure S12). R2 between the patterns of Ampoule B and Ampoule C measured by the same
293
instrument are R2 = 0.89 for APCI-QTOF-MS and R2 = 0.92 for GC/ECNI-Q-Orbitrap-MS.
294
295
To the best of our knowledge, there is no direct way to confirm the congener group pattern of
296
a CP mixture. Producers only provide the carbon chain length range and total chlorination
297
degree of a technical product or a reference standard. Carbon chain lengths of CPs are
298
determined by their paraffin raw materials, which can be analyzed ahead of synthesis 27-29 or
299
after synthesis by dechlorination/hydrogenation GC/FID.30, 31 Chlorination degree is usually
300
measured by combustion analysis of total chlorine.32 Although soft ionization techniques
301
offer the possibility of congener group-specific analysis of CPs,19 congener group
302
quantification was still tantalizingly out of reach. The missing link is a known amount of
303
CnClm. Our method fills this gap by a mathematical solution which derives the RF of each
304
CnClm from chain length standards. The novel method generated comparable results using
305
instruments with two different ion sources and three different ion selection technologies,
306
which to our knowledge has not been achieved by any other quantification methods before.
307
This indicates that our method can potentially be applied in most laboratories equipped with
308
similar instruments, and be in tandem with novel ionization/ion-selection/separation
309
instruments in the future.
DISCUSSION
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310
Chlorination Degree. The calculated RFs were verified by quantification and chlorination
311
degree measurement of SCCPs produced by different manufacturers, indicating that these RFs
312
can be applied for SCCPs synthesized under different industrial production conditions.
313
Chlorination degrees of the analyzed CP mixtures ranged from 49 %Cl to 71 %Cl. Based on
314
the congener group specific RFs applied to the APCI-QTOF-MS or by GC/ECNI -MS
315
measurements, the chlorination degrees of these CP mixtures could be calculated with
316
absolute deviations of less than 1 %Cl. Studies based on CH4/CH2Cl2-NICI or ECNI-LRMS,
317
reported for a CP mixture with 63.0 %Cl (manufacturer’s declaration), a chlorination degree
318
of 60.5 %Cl and 66.2 %Cl, respectively.33, 34 Similarly, the deuterodechlorination method,
319
which has the advantage of providing congener group profiles of CP mixtures, reported a
320
chlorination degree of 60.9 %Cl for the 63.0 %Cl mixture.26 The absolute deviations of the
321
existing methods are at least a factor of 10 higher than the ones measured by APCI-QTOF-
322
MS or by GC/ECNI-sector-MS with the RF based method.
323
Quantification. Quantification using CnClm RFs is a flexible alternative to the existing
324
methods. Differences in the congener group patterns have been reported between
325
environmental matrices and also within the same matrix.12, 35-38 As a result, it is unlikely that
326
CnClm patterns of technical mixtures match all CPs in environmental samples. However,
327
quantification by individual CnClm response factor bypasses this problem. Using independent
328
RFs of singular groups instead of total RFs of mixtures, any combination of CnClm in
329
environmental samples is possible to quantify. For illustration, we mixed a Cn chain length
330
standard and SCCP reference standard and obtained results comparable to the theoretical
331
concentrations.
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332
Deviations between CnClm patterns of technical mixtures and those of environmental samples
333
can be reduced by pattern deconvolution.19 It uses the patterns of various SCCP reference
334
mixtures to reconstruct a pattern which matches the pattern of a real sample. In this study, the
335
higher the value of R2, the better a reconstructed pattern fits its sample pattern, and the higher
336
agreement between two quantification methods (Figure S13). Total SCCPs quantified by
337
pattern deconvolution are consistently lower than the ones quantified by the calculated RFs.
338
This is because the pattern-deconvolution method quantifies SCCPs by total responses of all
339
CnClm. The RFs of CnClm near the extremes of the chlorination levels such as Cl3 and Cl12
340
congener groups, are lower than total RF of a SCCP mixture. Therefore using pattern
341
deconvolution, the concentrations of those CnClm are underestimated.
342
Congener Group Response Factor. So far, studies have reported on CP compositional
343
results based on instrumental responses of CnClm directly or with experimental calibration.33,
344
39, 40
345
same.40 Also for the ECNI-MS method, most studies consider the RF of congener groups to
346
be identical,41 or assume that the RFs are positive-linearly related to the number of chlorine
347
atoms on the carbon chain.39 In our study, the RFs of CnClm in both methods were found to be
348
generally highest for congener groups with an intermediate level of chlorines on the carbon
349
chain. The intermolecular interactions might be the reason.42 The interaction forces such as H-
350
bonding forces43, 44 may influence the molecular spatial structure and thus influence the
351
ionization and/or fragmentation.
352
Congener groups with the highest responses in the chain length standards were selected for
353
pairwise comparison. The response factors of most congener groups were derived from two
For the APCI-MS method, the RFs of all congener groups were considered to be the
21 ACS Paragon Plus Environment
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354
chain length standards. We added one more chain length standard into the comparison for the
355
congener groups which showed the high differences of response factors, such as C10Cl6 in
356
Figure 3. The response factors are similar to each other in the compared standards; however,
357
the RFs can be significantly different in the chain length standards with very different
358
chlorination degrees. For instance, the relative difference of the calculated RF (C11Cl5) is
359
merely 3% between the RF (C11Cl5) of C11 50.21 %Cl and 55.20 %Cl, but 49% when the RF
360
(C11Cl5) of C11 60.53 %Cl is added into pairwise comparison. Thus, the RFs are dependent on
361
the chain length standards that are selected for the pairwise comparison, and for chlorination
362
degrees with low response in the standards can vary by factors of up to 2 to 3. Another source
363
of uncertainty in the quantification is that the proportions of some congener groups might
364
deviate considerably from values estimated on the tails of the Gaussian distributions. Finally,
365
possible compositional differences of positional isomers might also contribute to the RF
366
differences.
367
Gaussian Distribution. The Gaussian distribution calculation is a nonlinear algorithm. In
368
principle it could be possible to calculate the RFs using a linear algorithm. However, the
369
response factor of each CnClm was not identical among different Cn chain length standards,
370
which cannot be described by a linear algorithm, as shown in the Supporting Information,
371
Text S5.
372
The Gaussian equation provides an adjustable theoretical composition of congener groups in a
373
chain length standard. The equation possesses several advantages: (a) it leaves room for RF
374
differences between chain length standards due to its adjustability; (b) it defines a pattern of
375
covariant between congener groups to avoid extreme results; (c) it estimates the relative
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376
amounts of insensitive congener groups, such as Cl1 and Cl2, even if their instrumental
377
responses are below LOD. Even if the real congener group distribution might be slightly
378
different from Gaussian distribution, especially for congener groups on the tails, its influence
379
on the calculated RFs can be reduced by pairwise comparison of several chain length
380
standards.
381
Instrumental Data Processing and MS Resolution. For APCI-QTOF-MS and GC/ECNI-
382
sector-MS, the instrumental signal of all CnClm was processed by deconvolution of the mass
383
spectra before calculation of their response factors, because quantifying a CnClm requires an
384
accurate detection, i.e., interferences from the other congener groups have to be eliminated.
385
The quantification ions of CPs commonly have the same nominal masses as several other CP
386
fragment ions.21 Using an instrument with a resolution of 10,000, there are still interferences
387
with the detection of [CnClm + Cl] – by [CnClm+1 + Cl – HCl] – in APCI-MS, and interference
388
with the detection of [CnClm – Cl] – mainly by [CnClm+1 – Cl – HCl] – in ECNI-MS. The latter
389
interference ([CnClm+1 – Cl – HCl] –) was verified using GC/ECNI-Q-Orbitrap-MS, when the
390
resolution reached 120,000 (Figure S14). The interference can be resolved either by
391
deconvolution of the mass spectra21, 45 (Figure S15) or by sufficient MS resolution.
392
This type of interference may result in insolubility of the response factors. In one of our tests
393
for instance, chain length standard C13 59.98 %Cl should contain more C13Cl8 (the %Cl of
394
which is 61.71) than C13 65.18 %Cl, but when the collision energy of APCI-QTOF-MS was 5
395
V, the detection of [C13Cl8 + Cl] – showed quite the opposite results. This was because
396
varying amounts of [C13Cl9 + Cl – HCl] –, [C13Cl10 + Cl – 2HCl] – and [C13Cl11 + Cl – 3HCl] –
23 ACS Paragon Plus Environment
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397
interfered with [C13Cl8 + Cl] – in both standards.21 The collision energy was thereafter
398
adjusted to 0.7 V to avoid the generation of [CnClm + Cl – 2HCl] – and [CnClm + Cl – 3HCl] –.
399
Comparison between APCI and ECNI. APCI-MS is capable of detecting a wider range of
400
congener groups (covering CnCl2 to CnCln+2), than ECNI-MS (covering CnCl5 to CnCln).
401
Therefore, the former can accurately measure SCCP chlorination degrees from 49 %Cl to
402
71 %Cl. APCI-QTOF-MS also has better sensitivities for most CnClm groups than GC-ECNI-
403
sector-MS, while GC-Q-Orbitrap-MS has the best sensitivities for most CnCl6-9 groups (Table
404
S6) using current instrument settings. Moreover, the fragment ion spectra in APCI-MS are
405
less complicated than the ions in ECNI-MS,21 which is a bonus for instrumental data
406
processing. However, solvent effects on the APCI-MS method must not be disregarded. The
407
relative responses among SCCP congener groups and the volumetric standard are altered
408
when they are injected in different solvents. The calculated RFs can only be used to quantify
409
samples in the same solvent as the reference standards. In addition, sample matrix has a more
410
significant influence on APCI-QTOF-MS analysis compared to ECNI-MS. This could be seen
411
from the results of QUASIMEME Ampoule B and Ampoule C (Figure S12). The extracts of
412
the two ampoules were from the same sediment cleaned-up in individual procedures. The
413
pattern of Ampoule B measured by APCI-QTOF-MS was slightly different from the one of
414
Ampoule C (R2 = 0.89), while in the case of GC/ECNI-Q-Orbitrap-MS the two patterns were
415
closer to each other (R2 = 0.92). The samples in Ampoule B were cleaned-up without sulfuric
416
acid or acidic silica treatment,23 and a yellowish residue was observed during solvent
417
exchange. This may influence APCI-QTOF-MS analysis since samples were directly injected
418
without chromatographic separation. Acidic silica was applied for clean-up of the extract of
419
Ampoule C, which provided a clear extract for instrument analysis.
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420
The congener group patterns of the reference standard SCCP 63.0 %Cl obtained from three
421
instruments were compared with one another (Figure 5). The congener group patterns are
422
calculated by dividing the concentration of individual congener groups by total concentration
423
of SCCPs. When comparing the patterns obtained between APCI-QTOF-MS and ECNI-Q-
424
Orbitrap-MS, APCI-QTOF-MS and ECNI-sector-MS, ECNI-Q-Orbitrap-MS and ECNI-
425
sector-MS, the coefficients of determination R2 were 0.95, 0.90 and 0.93, respectively. The
426
high R2 values mean that comparable congener group patterns of the same reference standard
427
were achieved on three individual instruments. The patterns we obtained were completely
428
different in ECNI compared to APCI when the instrument response was not multiplied by
429
calibrated RFs.21 This is partly because the lower chlorinated CnClm groups are
430
underestimated for ECNI instruments. QUASIMEME results show that comparable
431
concentrations and congener group patterns can be achieved in real samples independent of
432
the soft ionization methods used. The method we present here can play a key role to address
433
the urgent need for more detailed and accurate measurements of SCCPs in environmental
434
samples and technical products.
20% APCI-QTOF 15% ECNI-Q-Orbitrap 10%
ECNI-sector ECNI-secter
5% 0% #Cl
5
6
7
8
C10
9
10
5
6
7
8
9
10 11
5
C11
6
7
8
9
10 11 12
C12
5
6
7
8
9
10 11 12
C13
435 436
Figure 5. Comparison of SCCP 63.0 %Cl congener group patterns obtained from APCI-
437
QTOF-MS, GC/ECNI-sector-MS and GC/ECNI-Q-Orbitrap-MS. Columns represent
438
percentage compositions of individual congener groups in the reference standard SCCP
439
63.0 %Cl. Error bars represent standard deviations (n = 6) from the mean values.
25 ACS Paragon Plus Environment
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440 441
442
Special thanks to Derek Muir (Environment and Climate Change Canada) for his invaluable
443
suggestions for this study. Ulla Eriksson and Lukas Mustajärvi (ACES) are acknowledged for
444
providing sample extracts. Pascal S. Diefenbacher and Nadja Niggeler (ETH Zürich) are
445
acknowledged for their support with the magnetic sector MS measurements. Martin Krauss
446
and Tobias Schulze (UFZ) are acknowledged for their support with the Q-Orbitrap-MS
447
measurements. Marc Tienstra (RIKILT) is acknowledged for his insight into the Q-Orbitrap-
448
MS measurements. Hildred Crill (IGV) is acknowledged for language editing. The Swiss
449
National Science Foundation (SNF) is acknowledged for providing a travel grant to Bo Yuan
450
to ETH Zürich (grant no. IZK0Z2-163272).
451
452 453 454
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(43) Tomy, G. T.; Tittlemier, S. A.; Stern, G. A.; Muir, D. C. G.; Westmore, J. B., Effects of temperature and sample amount on the electron capture negative ion mass spectra of polychloro-n-alkanes. Chemosphere 1998, 37, (7), 1395-1410.
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(44) Tomy, G. T. The mass spectrometric characterization of polychlorinated n-alkanes and the methodology for their analysis in the environment. University of Manitoba, 1997.
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(45) Yuan, B.; Alsberg, T.; Bogdal, C.; MacLeod, M.; de Wit, C. In Modelling isotopic peak distributions of chlorinated paraffins homologue groups in high resolution mass spectrometry in soft ionization modes, International Symposium on Halogenated Persistent Organic Pollutants 35th Annual Meeting, Dioxin 2015, Sao Paolo, Brazil, 23-28 August 2015.
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Instrumental settings and corresponding mass spectrum deconvolution (Texts S1-S3, Tables S7-S10); a description of pattern deconvolution method (Text S4); an example of RF calculation by a linear algorithm (Text S5); SCCP results in environmental samples (Table S1, Figure S13); instrument performance (Tables S2 and S6); SCCP congener group compositions (Tables S3-S5); examples of resolved congener group (Table S11, Figures S14S16); RF calculations (Figures S1-S11); QUASIMEME results (Figure S12)
Supporting Information
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