Quantifying Short-Chain Chlorinated Paraffin Congener Groups

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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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Environmental Science & Technology

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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

3

Alsberg1, Cynthia A. de Wit1

4 5

1

6

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; [email protected].

RIKILT, Wageningen University & Research, PO box 230, Akkermaalsbos 2, 67080 AE,

1 ACS Paragon Plus Environment


15

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Accurate quantification of short-chain chlorinated paraffins (SCCPs) poses an exceptional

17

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

28

absolute differences between calculated and manufacturer-reported chlorination degrees were

29

-0.4–1.0%Cl for SCCP mixtures of 49–71%Cl. The quantification method has been replicated

30

with ECNI magnetic sector MS and ECNI-Q-Orbitrap-MS. CnClm concentrations determined

31

with the three instruments were highly correlated (R2 > 0.90) with each other.

Abstract


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Introduction

33

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

40

aquatic organisms9 and possibly carcinogenic to humans.10 The Persistent Organic Pollutants

41

Review Committee (POPRC) of the Stockholm Convention has listed SCCPs as POP

42

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



54

in differences of up to an order of magnitude in the quantified concentration.18 The difference

55

can be significantly reduced by mathematically deconvolving unknown SCCPs mixtures into

56

linear combinations of several reference standards, as recently described by Bogdal et al.19

57

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

59

C10Clm (m = 5 – 9) were adopted from the ones of corresponding individual congeners,

60

calculated by the ratio of instrument detector response to analyte concentration or mass. The

61

comparisons of relative RFs of monochlorine substituted C10 congeners supported the

62

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

69

mass spectra of CPs, which is a prerequisite for accurate congener group quantification.21 To

70

extend the method for quantitative analysis of individual congener groups in complex

71

samples, RFs for each congener group are required.

72

To overcome the challenge of SCCP quantification, we developed a mathematical method

73

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

75

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

77

the average chlorination degree, were accurately quantified in SCCP mixture standards,

78

technical products and SCCPs spiked to environmental samples. This is the first study

79

providing RFs of individual SCCP congener groups from a set of commercial standards with

80

a single carbon chain length and variable chlorination level. These RFs, in combination with

81

the presented deconvolution procedure, allow quantifying concentrations of individual

82

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.

85

EXPERIMENTAL PROCEDURES

86

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

89

reference standards of various concentrations, four binary mixtures of an SCCP reference

90

standard and a Cn chain length standard, eleven SCCP technical products, and six

91

environmental sample extracts spiked with known amounts of SCCPs. The linear range of the

92

instrumental response and the limit of detection (LOD) for each CnClm were further

93

determined by dilution series of the SCCP reference standards. For method comparison,

94

SCCPs in ten environmental samples were quantified with two independent methods, relying

95

on the one hand on the new RFs, and on the other hand on the pattern-deconvolution

96

procedure.19 Moreover, the new method was applied on a GC/ECNI- sector-MS and a



97

GC/ECNI-Q-Orbitrap-MS. Finally, SCCP results in the samples of an interlaboratory study

98

were compared between APCI-QTOF-MS and GC/ECNI-Q-Orbitrap-MS.

99

Chain Length Standards. (1) C10 50.18 Cl% (w/w), (2) C10 55.00 %Cl, (3) C10 60.09 %Cl,

100

(4) C10 65.02 %Cl, (5) C11 50.21 %Cl, (6) C11 55.20 %Cl, (7) C11 60.53 %Cl, (8) C11 65.25

101

%Cl, (9) C12 45.32 %Cl, (10) C12 50.18 %Cl, (11) C12 55.00 %Cl, (12) C12 65.08 %Cl, (13)

102

C12 69.98 %Cl, (14) C13 50.23 %Cl, (15) C13 55.03 %Cl, (16) C13 59.98 %Cl, and (17) C13

103

65.18 %Cl were used undiluted. All Cn reference standards were 10 ng/µL in cyclohexane and

104

purchased from Dr. Ehrenstorfer GmbH (Augsburg, Germany).

105

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

107

each SCCP reference standard was prepared at concentrations of 100, 75, 50, 25, 10 and 5.0

108

ng/µL. SCCPs 63.0 %Cl was further diluted at concentrations of 1.0, 0.50, 0.25 and 0.10

109

ng/µL to obtain the LOD for GC/ECNI-Q-Orbitrap-MS, which provided noise-free ion

110

chromatograms.22

111

Binary Mixtures of Reference Standards. Known amounts of the SCCPs and the Cn

112

reference standards were mixed. They were (1) SCCPs 51.5 %Cl mixed with C13 50.23 %Cl,

113

(2) SCCPs 55.5 %Cl mixed with C13 55.03 %Cl, (3) SCCPs 63.0 %Cl mixed with C11 65.25

114

%Cl, and (4) SCCPs 63.0 %Cl mixed with C12 69.98 %Cl. Detailed formulations are shown in

115

Table 1.

116

SCCP Technical Products. Eleven products covered a wide range of chlorination degrees,

117

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

119

products were diluted to the range of 40 – 110 ng/µL for measurement (see Table 1).

120

Environmental Samples. SCCPs were quantified in ten environmental samples, consisting of

121

5 pooled fish samples, 3 sediment and 2 lubricant samples (Table S1). No replicate analyses

122

were performed. For matrix effect tests, additional 6 environmental extracts, with non-

123

detectable SCCP concentrations, consisting of 3 fish and 3 sediment, were spiked with known

124

amounts of SCCPs reference standards (Table 1). The extraction and clean-up procedure is

125

given in our previous work.21



126 127

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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

8

ACS Paragon Plus Environment

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

131

the organizer (Ampoule B), and raw sediment extract (Ampoule C) were obtained from

132

QUASIMEME (Quality Assurance of Information on Marine Environmental Monitoring in

133

Europe, Phase III) for method validation and instrumental comparison. The extracts of

134

Ampoule B and Ampoule C were from the same sediment.23 Sediment extract (Ampoule C)

135

was cleaned-up with copper powder, sulfuric acid silica and deactivated silica24 before

136

instrumental analysis. Each ampoule was analyzed in triplicate.

137

All the SCCP standards, technical products and extracts of environmental samples were

138

dissolved in 100 µL of cyclohexane. Each solution or extract was mixed with 20 ng

139

Dechlorane 603 (Occidental Chemical Corp.) as volumetric standard before injection into the

140

instruments.

141

Instrumental Methods. The instrumental settings of APCI-QTOF-MS and GC/ECNI-sector-

142

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.

145

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.

148

Instrumental Data Acquisition and Processing. Mass spectral data were acquired and the

149

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;

151

gas chromatographic “humps” using GC/ECNI-MS were integrated by an automatic



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152

algorithm. Accurate instrument responses of [M + Cl] – of CnCl2 – CnCln+2 in APCI-QTOF-

153

MS and the responses of [M – Cl] – of CnCl5 – CnCln in GC/ECNI-sector-MS were

154

deconvolved from the mass spectra. The responses of [M – Cl] – in GC/ECNI-Q-Orbitrap-MS

155

were used for quantification without deconvolution. For detailed data processing see the

156

Supporting Information, Text S1 and Text S2.

157

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

159

the definition of RF,25 the RF of CnClm can be calculated using the equation below:

160

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.

163

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,

166

m variable). The composition of CnClm is unknown; however, the total concentration and

167

chlorination degree (%Cl) of the standards were provided by the manufacturers.

168

Relative amounts of each CnClm have been found to follow a Gaussian curve in CP mixture

169

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

172

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

175

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


(5)

(6)

Relative composition


190

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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203

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).



213 214

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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216

217

Method Development Using APCI-QTOF-MS

218

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.



233

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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246

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.



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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289

± 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



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



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


Page 22 of 31

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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] –



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.


Page 24 of 31

Page 25 of 31


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.



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

(1) Fiedler, H., Short-Chain Chlorinated Paraffins: Production, Use and International Regulations. In Handb Environ Chem, Boer, J., Ed. Springer Berlin Heidelberg: 2010; pp 140.

455 456 457

(2) Glüge, J.; Wang, Z.; Bogdal, C.; Scheringer, M.; Hungerbühler, K., Global production, use, and emission volumes of short-chain chlorinated paraffins–A minimum scenario. Sci Total Environ 2016, 573, 1132-1146.

458 459 460 461

(3) Tomy, G. T.; Stern, G. A., Analysis of C-14-C-17 polychloro-n-alkanes in environmental matrixes by accelerated solvent extraction-nigh-resolution gas chromatography/electron capture negative ion high-resolution mass spectrometry. Anal Chem 1999, 71, (21), 48604865.

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(4) Iozza, S.; Muller, C. E.; Schmid, P.; Bogdal, C.; Oehme, M., Historical profiles of chlorinated paraffins and polychlorinated biphenyls in a dated sediment core from Lake Thun (Switzerland). Environ Sci Technol 2008, 42, (4), 1045-50.

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(5) Friden, U. E.; McLachlan, M. S.; Berger, U., Chlorinated paraffins in indoor air and dust: concentrations, congener patterns, and human exposure. Environ Int 2011, 37, (7), 1169-74.

ACKNOWLEDGEMENTS

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(38) Yuan, B.; Fu, J.; Wang, Y.; Jiang, G., Short-chain chlorinated paraffins in soil, paddy seeds (Oryza sativa) and snails (Ampullariidae) in an e-waste dismantling area in China: Homologue group pattern, spatial distribution and risk assessment. Environ Pollut 2017, 220, 608-615.

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(41) Reth, M.; Zencak, Z.; Oehme, M., New quantification procedure for the analysis of chlorinated paraffins using electron capture negative ionization mass spectrometry. J Chromatogr A 2005, 1081, (2), 225-31.

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(42) Glüge, J.; Bogdal, C.; Scheringer, M.; Buser, A. M.; Hungerbühler, K., Calculation of Physicochemical Properties for Short- and Medium-Chain Chlorinated Paraffins. J Phys Chem Ref Data 2013, 42, (2), 023103.

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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.

578 579

(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.

580 581 582 583

(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.

584



585

586 587 588 589 590 591

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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592 593


For TOC only.


Quantifying Short-Chain Chlorinated Paraffin Congener Groups

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