New tools for sample preparation and instrumental analysis of

New tools for sample preparation and instrumental analysis of dioxins in environmental samples

Lan Do

Department of Chemistry

Doctoral Thesis

Umeå 2013

© Lan Do, pp. i-iii, 1-39 ; Umeå, 2013 This work is protected by the Swedish Copyright Legislation (Act 1960:729)

ISBN: 978-91-7459-684-7

Cover picture: Lan Do

Electronic version available at http://umu.diva-portal.org/

Printed by: VMC, KBC, Umeå University

Umeå, Sweden 2013

Papers I and II are reprinted with permission from Elsevier and The Royal Society

of Chemistry, respectively

To my families and my älskling

Abstract

Abstract

Polychlorinated dibenzo-p-dioxins (PCDDs) and dibenzofurans (PCDFs), two groups

of structurally related chlorinated aromatic hydrocarbons, are of high concern due to

their global distribution and extreme toxicity. Since they occur at very low levels,

their analysis is complex, challenging and hence there is a need for efficient, reliable

and rapid alternative analytical methods. Developing such methods was the aim of

the project this thesis is based upon.

During the first years of the project the focus was on the first parts of the analytical

chain (extraction and clean-up). A selective pressurized liquid extraction (SPLE)

procedure was developed, involving in-cell clean-up to remove bulk co-extracted

matrix components from sample extracts. It was further streamlined by employing a

modular pressurized liquid extraction (M-PLE) system, which simultaneously

extracts, cleans up and isolates planar PCDD/Fs in a single step. Both methods were

validated using a wide range of soil, sediment and sludge reference materials. Using

dichloromethane/n-heptane (DCM/Hp; 1/1, v/v) as a solvent, results statistically

equivalent to or higher than the reference values were obtained, while an alternative,

less harmful non-chlorinated solvent mixture - diethyl ether/n-heptane (DEE/Hp;

1/2, v/v) – yielded data equivalent to those values.

Later, the focus of the work shifted to the final instrumental analysis. Six gas

chromatography (GC) phases were evaluated with respect to their chromatographic

separation of not just the 17 most toxic congeners (2,3,7,8-substituted PCDD/Fs),

but all 136 tetra- to octaCDD/Fs. Three novel ionic liquid columns performed much

better than previously tested commercially available columns. Supelco SLB-IL61

offered the best overall performance, successfully resolving 106 out of the 136

compounds, and 16 out of the 17 2,3,7,8-substituted PCDD/Fs. Another ionic liquid

(SLB-IL111) column provided complementary separation. Together, the two columns

separated 128 congeners. The work also included characterization of 22 GC columns’

selectivity and solute-stationary phase interactions. The selectivities were mapped

using Principal Component Analysis (PCA) of all 136 PCDD/F’s retention times on

the columns, while the interactions were probed by analyzing both the retention

times and the substances’ physicochemical properties.

Key words: PCDD/Fs, dioxins, pressurized liquid extraction, PLE, selective SPLE,

modular M-PLE, soil, sediment, sludge, gas chromatography, new stationary phases,

multivariate data analysis, selectivity, interaction.

Table of contents

i

Table of contents

List of papers ii

Abbreviations iii

1 Introduction 1

1.1 Polychlorinated dibenzo-p-dioxins/furans (PCDD/Fs) 1

1.2 Analytical challenges in studies of PCDD/Fs 3

1.3 Aims of this thesis 4

2 Pressurized liquid extraction (PLE) 5

2.1 Principles of operation 5

2.2 Selective pressurized liquid extraction (SPLE) 6

2.2.1 Paper I: Method development 6

2.2.1.1 Solvent selection 7

2.2.1.2 Optimization of extraction parameters 8

2.2.1.3 Validation 9

2.2.1.4 Outlook 10

2.3 Modular pressurized liquid extraction (M-PLE) 10

2.3.1 Paper II: Method development 11

2.3.1.1 Optimization of the carbon trap 12

2.3.1.2 M-PLE performance with low sample intake 12

2.3.1.3 M-PLE performance with high sample intake 14

2.3.1.4 Outlook 15

3 Gas chromatography (GC) 17

3.1 Principles 17

3.2 Summary of Paper III 18

3.2.1 New stationary phases with specificity for dioxins 18

3.2.2 Column combinations 23

3.2.3 Outlook 24

3.3 Summary of Paper IV 25

3.3.1 Multivariate data analysis 25

3.3.2 Column characterization 26

3.3.2.1 First PCA modeling of the retention times 26

3.3.2.2 PLS modeling of the physicochemical properties 27

3.3.2.3 Second PCA modeling of the retention times and physicochemical

properties 28

3.3.2.4 Suitable GC × GC column combinations for dioxin analysis 28

3.3.3 Outlook 28

4 Detection and quantification 30

5 Conclusions and future prospects 31

6 Acknowledgements 32

7 References 34

List of papers

ii

List of papers

This thesis is based on the following papers:

I Do, L., Lundstedt, S., Haglund, P. “Optimization of selective pressurized

liquid extraction for extraction and in-cell clean-up of PCDD/Fs in soils and

sediments”, Chemosphere 90 (2013) 2414-2419

II Do, L., Hoang, X.T., Lundstedt, S., Haglund, P. “Modular pressurized liquid

extraction for simultaneous extraction, clean-up and fractionation of

PCDD/Fs in soil, sediment and sludge samples”, Analytical Methods 5 (2013)

1231-1237

III Do, L., Liljelind, P., Zhang, Z., Haglund, P. “Comprehensive profiling of 136

tetra- to octapolychlorinated dibenzo-p-dioxins and dibenzofurans using

ionic liquid columns and column combinations”, Submitted manuscript

IV Do, L., Geladi, P., Haglund, P. “Multivariate data analysis to characterize GC

columns for dioxin analysis”, Manuscript

Author contribution:

Paper I: The author contributed extensively to the planning of the experiments,

performed all of the experimental work, and wrote the paper.

Paper II: The author contributed extensively to the planning of the experiments and

supervised Hoang X. T., a Master’s student who performed some of the

experimental work. The author also performed some of the experimental work

and wrote the paper.

Paper III: The author was heavily involved in the planning of the experiment,

performed most of the experimental work and wrote the paper. The author

supervised a Master’s student Mamoon H. A., who also was involved in the

experiments and the data evaluation.

Paper IV: The author was involved in the planning of the experiment, contributed

substantially to the data evaluation, and wrote the paper. The multivariate

data analysis was done by Paul Geladi.

Abbreviations

iii

Abbreviations

AhR Aryl hydrocarbon receptor

CRM Certified reference material

CCF Central composite face

DCM Dichloromethane

DCM/Hp Dichloromethane/n-heptane

DEE Diethyl ether

DEE/Hp Diethyl ether/n-heptane

ELISA Enzyme-linked immunosorbent assay

GC Gas chromatography

GC/HRMS Gas chromatography/high resolution mass spectrometry

GC × GC Comprehensive two-dimensional gas chromatography

GC × GC/MS Comprehensive two-dimensional gas chromatography/mass

spectrometry

GLC Gas-liquid chromatography

GSC Gas-solid chromatography

Hp n-heptane

HRMS High resolution mass spectrometry

IS Internal standard

M-PLE Modular pressurized liquid extraction

m/z Mass-to-charge

PAHs Polycyclic aromatic hydrocarbons

PBDD/Fs Polybrominated dibenzo-p-dioxins and dibenzofurans

PBDEs Polybrominated diphenylethers

PC Principal component

PCA Principal component analysis

PCDDs Polychlorinated dibenzo-p-dioxins

PCDFs Polychlorinated dibenzofurans

PCDD/Fs Polychlorinated dibenzo-p-dioxins/furans

PCBs Polychlorinated biphenyls

PLE Pressurized liquid extraction

PLE-C Pressurized liquid extraction with integrated carbon trap

PLS Partial least square

POPs Persistent organic pollutants

RSD Relative standard deviation

SPLE Selective pressurized liquid extraction

TEF Toxic equivalency factor

TEQ Toxic equivalent

TOF Time-of-flight

WHO World Health Organization

Introduction

1

1 Introduction

1.1 Polychlorinated dibenzo-p-dioxins/ dibenzofurans (PCDD/Fs)

O

O

Clx ClyO

Clx Cly1

2

3

4

7

6

9

8

1

2

3

46

7

8

9

Figure 1. General structural formula and substitution positions of PCDDs (left) and PCDFs (right).

Polychlorinated dibenzo-p-dioxins (PCDDs) and dibenzofurans (PCDFs), so called

‘dioxins’, are structurally similar planar compounds that feature two chlorine

substituted benzene rings connected by one (furan) or two (dioxin) oxygen bridges

(Figure 1). The three-ring heterocyclic backbone structure can be substituted with

one to eight chlorine atoms in eight different positions, which are denoted 1-4 and 6-

9 in Figure 1. This yields a total of 75 possible dioxin and 135 possible furan

congeners. Congeners with the same number of chlorines comprise a homologous

group; differences in the distribution of chlorines within such groups give rise to

different isomers.

The toxicity of the PCDD/Fs is highly

dependent on the locations of the substituted

chlorines. Of the 210 PCDD/Fs, the 17

congeners with chlorines in the 2,3,7,8

positions are the most toxic, with half-lives of

2-7 years in humans [2]. Their toxicity arises

from their ability to bind to the aryl

hydrocarbon receptor (AhR). This has a

number of adverse consequences, including the

induction of reproductive disorders,

immunotoxicity, cancer, weight loss, and acute

chloracne among others. Because the AhR-

mediated response is different for each

congener, the concept of toxic equivalency

factors (TEFs) was developed to assess their

toxicity. These TEF values relate the toxicity of

each congener to the toxicity of 2,3,7,8-

tetrachlorodibenzo-p-dioxin (2,3,7,8-TeCDD),

which is considered the most toxic congener

[1]. The TEF value of 2,3,7,8-TeCDD is equal to

1. All of the other congeners consequently have TEF values of less than 1, with the

exception of 1,2,3,7,8-PeCDD, which also has a TEF of 1. The congeners’ TEF values

Table 1. WHO-TEF values for PCDD/Fs [1].

Isomers TEF-2005

2,3,7,8-TeCDF 0.1

1,2,3,7,8-PeCDF 0.03

2,3,4,7,8-PeCDF 0.3

1,2,3,4,7,8-HxCDF 0.1

1,2,3,6,7,8-HxCDF 0.1

2,3,4,6,7,8-HxCDF 0.1

1,2,3,7,8,9-HxCDF 0.1

1,2,3,4,6,7,8-HpCDF 0.01

1,2,3,4,7,8,9-HpCDF 0.01

OCDF 0.0003

2,3,7,8-TCDD 1

1,2,3,7,8-PeCDD 1

1,2,3,4,7,8-HxCDD 0.1

1,2,3,6,7,8-HxCDD 0.1

1,2,3,7,8,9-HxCDD 0.1

1,2,3,4,6,7,8-HpCDD 0.01

OCDD 0.0003

Introduction

2

were most recently updated in 2005, by the World Health Organization (WHO)

(Table 1). The total dioxin-like toxicity of a sample is expressed in units of toxic

equivalents (TEQ), and is determined by multiplying the concentration of each dioxin

congener by its TEF value and summing the resulting products. TEQ values are

commonly used to compare the dioxin toxicities of different samples, but one should

be aware that the TEQ and TEF concepts were originally developed for assessing risks

associated with human food consumption, under the assumption that the dioxin-

containing materials would be ingested orally. In soil/sediment samples, where

contaminants may adsorb strongly to the sample matrix, the TEQ value may

overestimate the sample’s overall toxicity because it does not properly reflect the

bioavailability of the contaminants.

Natural sources of PCDD/Fs such as forest fires, volcanoes and biological processes [3, 4] make only minor contributions to the total dioxin load. Most dioxins are

formed unintentionally during:

i) combustion processes in which organic and inorganic compounds are burned

together in the presence of chlorine. This can occur during the incineration of

municipal solid waste, biomass burning and during accidental fires or backyard

burning [5-8].

ii) chemical processes such as the bleaching of pulp with chlorine gas [9, 10], the

production of chlorine via the chloralkali process using graphite electrodes [10,

11], and the production of organochlorine chemicals such as polychlorinated

biphenyls (PCBs) and chlorophenols (in which case dioxins are formed as

byproducts) [12, 13].

Due to technological improvements and regulations, industrial emissions of

PCDD/Fs have been substantially reduced, and the current primary sources of these

compounds are waste incineration and sinter plants. However, emissions from non-

industrial sources such as domestic solid fuel combustion are barely decreased, and

may be responsible for the majority of PCDD/F emissions in the near future [14].

Because PCDD/Fs are highly persistent and undergo long-range transport, they

have been identified in all environmental compartments that have been studied

across the globe. Soils and sediments are considered to be the main repositories of

PCDD/Fs due to their low water solubility and low volatility. Consequently, soils and

sediments at old industrial sites often retain serious levels of these compounds

decades after their initial contamination. High dioxin levels (0.14 - 3000 µg/kg d.w.

TEQ) have been observed in contaminated soils at former Swedish sawmill sites,

where chlorophenol agents that were contaminated with dioxins had been used to

preserve wood [15]. These contaminated sites pose a risk to humans and animals

living in their immediate vicinity, but also contribute to the global spread of dioxins

throughout the environment. Figure 2 illustrates the various pathways by which

human beings may be exposed to dioxins: they can enter the food chain via vegetables

or terrestrial organisms and then become biomagnified in predators. Alternatively,

the pollutants may associate with colloidal particles that are subsequently

transported from the contaminated soils into the groundwater and nearby rivers,

Introduction

3

where the pollutants may be stored in sediments or taken up by aqueous organisms

[16]. The dioxins may also evaporate into the air or adsorb onto aerosol and dust

particles. All of these processes may result in human exposure and could thus

threaten human health. Consequently, there is a need for efficient measurement

techniques that can be used to monitor dioxin levels in several compartments of the

environment.

Figure 2. Potential pathways of dioxin exposure [17].

1.2 Analytical challenges in studies of PCDD/Fs

The quantitative analysis of PCDD/Fs in environmental samples is challenging due

to their low concentrations and the common presence of multiple interfering

compounds whose concentrations may be orders of magnitude greater. Complex

multi-step protocols are typically required to determine such trace components.

Important steps include i) extraction of the target analytes from the matrix, ii)

removal of co-extractable organic materials such as lipids, sulfur and humic

materials, iii) fractionation of the dioxins to remove other interfering compounds, iv)

separation of target analytes from non-target compounds and sources of interference

using a gas chromatography (GC) column, and finally v) detection of the target

analytes using a selective mass spectrometer. Traditional protocols for dioxin analysis

usually involve an initial Soxhlet extraction followed by a multi-column clean-up

process and analysis by gas chromatography/high resolution mass spectrometry

(GC/HRMS) [18-21]. However, such approaches are very labor intensive, costly as

well as time consuming, and also use large quantities of purified organic solvents.

Dioxin analysis using GC/HRMS typically costs $500–$1000 per sample, and takes

around 25h in total [22, 23]. In addition, because there are 136 PCDD/Fs, with four

to eight chlorines per molecule, all of which have relatively similar physicochemical

properties, conventional GC columns (such as the DB-5) cannot fully separate all of

the isomers present within typical samples. In particular, the 17 2,3,7,8-substituted

dioxins and furans are not readily separated from the other isomers. It is therefore

Introduction

4

usually necessary to perform a confirmatory analysis using a second GC column. As

such, there is a pressing need for more efficient methods.

1.3 Aims of this thesis

The aim of the work presented in this thesis was to develop new methods for dioxin

analysis, with two key goals. The first goal was to establish a method for high-

throughput sample preparation based on modular pressurized liquid extraction (M-

PLE), a coupling system that permits the simultaneous, single-step extraction, clean-

up and fractionation of PCDD/Fs. Papers I and II describe the development of such

a method and its application in the analysis of environmental solid samples. The

second goal was to improve the GC separation of PCDD/Fs. Six GC columns,

including three coated with ionic liquid phases, were evaluated with respect to their

chromatographic separation of the 136 tetra- to octaCDD/Fs. This also involved the

characterization of the column selectivity and interaction of the solutes on 22 GC

columns during the chromatographic separation. Comparative studies along these

lines are described in Papers III and IV.

Pressurized liquid extraction (PLE)

5

2 Pressurized liquid extraction (PLE)

2.1 Principles of operation

PLE is an automated extraction technique that uses organic solvents at elevated

temperatures and pressures to extract organic pollutants from solid matrices [24, 25].

PLE systems consist of a stainless steel extraction cell into which the sample is

placed, an oven, a pump, a gas tank, solvent bottles, collection vials and various

pressure control valves. Figure 3 shows the general setup of such a system. During a

typical extraction, the cell is:

1) loaded into the oven

2) filled with the organic solvent

3) heated and pressurized to predefined levels

4) extracted in several static cycles; at the end of each static cycle, the extract is

transferred to the collection vial and fresh solvent is pumped through the cell to

initiate the next static cycle until finish

5) purged with nitrogen gas to discharge residual solvent from the cell into the

collection vial

6) depressurized

Figure 3. General setup of a pressurized liquid extraction system (adapted with permission from

Pouralinazar et al., 2012 [26]).

High extraction temperatures increase the rates of diffusion and mass transfer

during the extraction process as well as the solubility of the analyte in the extraction

solvent and the rate of analyte desorption from the matrix (by disrupting analyte-

matrix interactions). High pressures help to maintain the solvent in the liquid state at

higher temperatures while also increasing the efficiency of sample wetting and matrix

penetration, thereby enhancing extraction efficiency. The use of high temperatures

and pressures also reduces the time required for the extraction process and the


6

volume of solvent used. Moreover, the method is amenable to automation and offers

considerable flexibility. Interest in PLE has therefore grown considerably over the 18

years since its introduction, and it is increasingly regarded as a promising alternative

to many tedious and solvent-consuming extraction techniques such as Soxhlet

extraction and sonication [24, 25, 27, 28].

2.2 Selective pressurized liquid extraction (SPLE)

The exhaustive extraction achieved when using PLE is valuable because it means

that quantitative analyte recovery can be achieved in only a few minutes via a static

extraction process. However, PLE is also relatively unselective, and the resulting

extracts are rich in co-extracted materials that need to be removed using complex

clean-up procedures [29]. In 1996, Dionex reported that the introduction of alumina

into PLE cells eliminated fat from extracted biota samples [30]. Since then, the

concept of SPLE, i.e. PLE extraction with integrated clean-up achieved by adding

specific matrix retainers, has become increasingly popular. A number of papers have

been published describing strategies for extracting persistent organic pollutants

(POPs) from food/feed or abiotic samples with in-cell clean-up [31-41]. For example,

Wiberg and Sporring et al. [34-36] used sulfuric acid-impregnated silica to remove

lipids from food and feed samples during PCB extraction. Chuang et al. [37]

developed a SPLE strategy for extracting PCDD/Fs from sediment and soil samples in

which multilayer adsorbents are used to retain the sample matrix. Ong et al. [40]

utilized silica to retain humic matter and other polar co-extractants in an SPLE

process for extracting polycyclic aromatic hydrocarbons (PAHs) from soil samples.

Lundstedt et al. [31] developed this approach further by combining in-cell

purification with fractionation in order to separate the PAHs from their oxygenated

derivatives. Similarly, Poerschmann et al. [41] used SPLE to fractionate neutral lipids

from polar phospholipids. In all of these cases, the results obtained using SPLE were

not only equivalent to or even better than those obtained by traditional methods, but

the SPLE approach was also preferable in terms of time and cost.

2.2.1 Paper I: Method development

The purpose of Paper I was to develop an SPLE method for the extraction and in-

cell clean-up of PCDD/Fs in soils and sediments. The developments were done on the

ASE200 with 22 mL cell. The SPLE cell was packed with multiple silica layers (20%

KOH-silica, neutral silica and 40% H2SO4-silica). The dried sample was mixed with

Celite (1:1, w/w) and placed in the cell on top of the silica, as shown in Figure 4.

During the extraction process, PCDD/Fs along with other POPs and organic

compounds were extracted from the matrix and flushed through the multilayer silica

plug, which retained polar and hydrolysable compounds, removing them from the

final extract. The extracts were then treated with activated copper and passed


7

through a carbon column to separate the planar compounds (PCDD/Fs) from the

non-planar ones (other POPs) prior to GC/HRMS analysis.

Figure 4. SPLE cell packing (Paper I).

2.2.1.1 Solvent selection

The choice of solvent is important to obtain a quantitative extraction of the target

analytes. For the samples investigated, binary solvent mixtures proved to be more

effective than single solvents. This is presumably because binary mixtures have some

of the properties of both of their constituents, enabling them to dissolve a wide range

of compounds with different polarities [42, 43]. Dichloromethane (DCM) has been

identified as an efficient extraction solvent for dioxins [37, 44], and is suitable for

SPLE because it does not react with the sulfuric acid in the multilayer silica plug [45].

However DCM can have adverse effects on human health and is harmful to the

environment [46]. Therefore, a less toxic alternative with similar physicochemical

properties to DCM was sought. After a preliminary investigation, diethyl ether (DEE)

was identified as a suitable alternative. Two binary solvent mixtures were evaluated

in the studies reported in Paper I: dichloromethane/n-heptane (DCM/Hp) and

diethyl ether/n-heptane (DEE/Hp).

The next step was to determine the optimal proportions of DCM/Hp and DEE/Hp

in terms of maximizing the amount of PCDD/Fs extracted while minimizing the

amount of co-extracted material. The certified soil CRM-529 was used as reference

sample and was extracted with six solvent mixtures: DCM/Hp (1/10, 1/4, 1/1, v/v)

and DEE/Hp (1/10, 1/4, 1/1, v/v). The SPLE results obtained with each mixture were

then compared to those achieved using a reference method based on Soxhlet

extraction followed by external clean-up and fractionation columns [47] (Figure 5).

The performance of each mixture was evaluated based on the PCDD/F concentration

in the SPLE extract as a percentage of that achieved using the Soxhlet method (%

extracted). It was apparent that solvent mixtures containing lower proportions of the

polar solvent afforded less efficient extractions (Figure 5), meaning that it is

necessary to include a polar solvent in order to achieve exhaustive dioxin extraction,

and that an excessively high n-heptane (Hp) content will reduce the solvent strength.

The best SPLE extraction efficiency was achieved using DCM/Hp (1/1, v/v). The

Sample

40% H2SO4-silica

Active silica

20% KOH-silica

2 filter papers


8

extraction efficiency achieved using DEE/Hp (1/1, v/v) was similar to that obtained

with DEE/Hp (1/4, v/v). However, SPLE with DEE/Hp (1/1, v/v) caused severe

leaching of the acid from the H2SO4-silica and should therefore be avoided.

Consequently, DEE/Hp (1/2, v/v) and DCM/Hp (1/1, v/v) were selected as the

optimal solvent mixtures.

Figure 5. PCDD/F extraction percentages (% extracted) achieved using SPLE with six solvent mixtures

(relative to the reference Soxhlet method). Error bars indicate 95% confidence intervals based on triplicate

analyses.

2.2.1.2 Optimization of extraction parameters

A central composite face (CCF) design was used to optimize three extraction

parameters: temperature, number of extraction cycles and extraction time per cycle.

Pressure was not included as an optimization parameter because several previous

studies have shown that it has negligible effects on extraction efficiency [24, 48-51].

Temperature was found to be the most important parameter, and had a strong

positive effect on the extraction efficiency (i.e. more dioxins are extracted at higher

temperatures). The second most significant parameter was the extraction time, which

also had a positive influence. The extraction time required depends on the sorption of

the analytes to the sample matrix. For “aged” samples in which the analytes have

penetrated deeply into the matrix and are therefore strongly sorbed, longer extraction

times are required to achieve complete desorption. The third parameter, number of

extraction cycles had no significant effect on the extraction efficiency and so only two

cycles were used to minimize the quantity of co-extracted material.

0

20

40

60

80

100

% E

xtra

cted


9

a) b)

Figure 6. PCDD/F extraction percentages (% extracted, relative to the reference Soxhlet method)

achieved during the optimization of SPLE settings for a) DCM/Hp (1/1, v/v) and b) DEE/Hp (1/2, v/v) plotted

as a function of the extraction temperature and extraction time

Results of the optimization can be visualized using response surface plots. Figure 6

shows the response surfaces for the ‘% extracted’ as functions of the extraction

temperature and time. The optimal domain (shown in red) that provides the highest

extraction efficiencies covers a fairly large area, which corresponds to the optimal

conditions. According to these models, the optimal extraction temperatures are

148°C for SPLE methods using DCM/Hp (1/1, v/v) and 160°C for SPLE methods

using DEE/Hp (1/2, v/v).

However, it was subsequently found that extraction temperatures above 120°C

should be avoided because they cause the leaching of H2SO4 from the 40% H2SO4-

silica followed by water formation from the neutralization of free H2SO4 by KOH-

silica during the extraction. The extractions were therefore performed at lower

temperatures in order to avoid this problem. The final extraction conditions selected

were two cycles of 11 minutes each at 110°C for SPLE methods using DCM/Hp (1/1,

v/v) and two cycles of 12 minutes each at 110°C for SPLE methods using DEE/Hp

(1/2, v/v).

2.2.1.3 Validation

The optimized conditions were validated by applying them to three certified

reference materials (CRMs): the soil CRM-529, the clay CRM-530 and the sediment

WMS-01. The SPLE results were compared to either the certified values or those

achieved using a Soxhlet based method, both in terms of individual congener

concentrations and total TEQs. In all cases, the relative standard deviations (RSDs)

for the triplicate extractions were below 12%, which was within acceptable limits. The

accuracy (trueness) of the TEQ values of SPLEDCM/Hp and SPLEDEE/Hp compared to

the certified TEQ values was +11% and +8% for the clay sample, +8% and -7% for the

sediment sample, +8% and -10% for the soil sample, respectively. The congener

concentrations determined using the SPLE methods generally agreed well with the

certified and Soxhlet values with the exception of those highly chlorinated (Hp-Oc)

% Extracted % Extracted


10

congeners, for which the SPLEDCM/Hp values tended to be higher than the reference

values. This indicates that SPLE methods using optimized conditions provide even

better extraction efficiencies than the certified/Soxhlet methods. It was also found

that the mean of the concentrations for each congener obtained by SPLEDEE/Hp was

slightly lower than those determined using SPLEDCM/Hp. This suggests that DCM/Hp

mixtures provide somewhat greater SPLE extraction efficiencies than DEE/Hp,

which probably reflects differences in solvent selectivity between the more

polarizable DCM and the slightly basic DEE. However, DEE/Hp may be the

preferable option due to its lower environmental impact.

2.2.1.4 Outlook

Our SPLE method provides numerous advantages relative to conventional methods

for dioxin analysis, which involve Soxhlet extraction and open column clean-up. It

combines two steps (extraction and bulk matrix removal), resulting in a more

automated, faster, and more cost-efficient procedure with reduced solvent

consumption and scope for high throughput (a series of 24 samples can be extracted).

While SPLE with in-cell clean-up is not a new approach and there have been several

publications in this area, most of them have focused on extracting POPs in biological

samples, which is much more straightforward than extracting soil and sediment

samples. This is because of the strong sorption of organic pollutants in aged samples

with a closed pore-structure that limits molecular diffusion. The SPLE method

developed in this work is novel and efficient (having been optimized using

chemometrics), and reliably extracts dioxins from these difficult matrices. When used

in combination with congener-specific GC/HRMS analysis, it provides a wealth of

information that can be used for risk assessment. Conversely, alternatives such as the

SPLE method with enzyme-linked immunosorbent assay (ELISA) detection,

developed by Chuang et al. [37] and used for solid samples, do not provide any

information on the relative proportions or TEQ contributions of individual

congeners.

2.3 Modular pressurized liquid extraction (M-PLE)

Despite the advantages of SPLE, it still requires a subsequent carbon column to

separate dioxins from other interfering compounds. An alternative approach is to use

pressurized liquid extraction with integrated carbon trap (PLE-C), which fractionates

chemical mixture based on the planarity of their constituents directly on activated

carbon. For example, it can be used to separate non-planar ortho-substituted PCBs

from planar PCDD/Fs. PLE-C has proved to be useful for sample preparation when

determining PCDD/Fs in biotic and abiotic samples [23, 52-54]. However, the

resulting extracts usually contain additional co-extracted materials from the matrix

that must be removed via an external clean-up step using a multilayer silica column

or some other appropriate method. We hypothesized that by combining shape-


11

selective PLE-C and SPLE with in-cell clean-up, it might be possible to streamline the

extraction and purification process and to take advantage of the synergistic

properties of both techniques. This approach, which combines extraction, clean-up

and fractionation in a single step is called M-PLE. The first M-PLE was developed

using the Dionex ASE200 system by Erik Spinnel and Peter Haglund [45, 55] in

2008. The procedure has primarily been used to separate PCBs from

chlorinated/brominated dioxins in biological samples, with some success. However,

the M-PLE extraction cell used in the original protocol was rather small (possible

maximum capacity is 22 ml in the ASE200), which limited the quantity of absorbent

material that could be used for in-cell clean-up. Consequently, the original protocol

did not completely eliminate co-extracted materials.

2.3.1 Paper II: Method development

The purpose of this study was to optimize the M-PLE approach for use with non-

biological samples and non-chlorinated solvents. The new protocol designed to use

the new Dionex ASE350 system, which has a larger cell volume than the ASE200 and

should thus avoid the size limitations mentioned above.

The M-PLE strategy is illustrated in Figure 7. Two extraction cells were connected

using an in-house manufactured adapter consisting of two cylindrical stainless steel

guides with threading identical to the original PLE end-caps, and a central PEEK disc

located in the center. The guides align the two extraction cell compartments, and the

compression unit of the PLE system presses the extraction compartments against the

PEEK disc to create a seal. This setup proved to be leak free. Figure 7 also outlines the

developed extraction protocol. Cell 1 is filled with the sample and multiple layers of

silica, as described in Paper I. Cell 2 is filled with a carbon-Celite mixture. The

internal volumes of Cell 1 and Cell 2 can be adjusted to suit the situation at hand:

cells of 1, 5, 11 and 22 mL are available for the ASE200 instrument while cells of 1, 5,

10, 34, and 66 mL can be used with the ASE350. The extraction protocol involves

three steps. In step one (forward elution), the whole system is extracted with

DCM/Hp (1/1, v/v) or DEE/Hp (1/2, v/v) at which matrix components are retained

by the acid-base silica, while persistent compounds such as PCBs and dioxins pass

from Cell 1 to Cell 2. In Cell 2, planar compounds such as PCDD/Fs and non-ortho

PCBs adsorb onto the carbon, while non-planar compounds such as ortho-

chlorinated PCBs pass through the carbon trap and elute in the first fraction

(Fraction 1). In step two, Cell 1 is removed, after which Cell 2 is sealed with a fresh

end cap and inverted. In step three, the inverted cell is extracted with toluene,

yielding a second fraction (Fraction 2) that contains the dioxins.


12

Figure 7. Schematic illustration of the cell packing sequence and M-PLE protocol that was developed for

the analysis of PCDD/Fs in solid samples.

2.3.1.1 Optimization of the carbon trap

A good balance between the carbon trap capacity and the elution strength of the

extraction solvent is essential for effective fractionation. A simple experiment was

therefore conducted to optimize the carbon trap: Cell 1 was filled with clean sand (no

silica was added) and spiked with a mixture of internal standards (IS) that included

17 13C-labelled 2,3,7,8-substituted PCDD/Fs and four 13C-labelled non-ortho PCBs.

Cell 2 was then filled with various carbon/Celite mixtures ranging from 0.5-15%

carbon (w/w). The two solvent mixtures and the associated optimized extraction

conditions from Paper I were reused, with one difference: a higher extraction

temperature was used in the M-PLEDEE/Hp experiments to enhance the extraction

efficiency. The adsorbent capacity was estimated by varying the amount of carbon in

the trap to determine the minimum amount of carbon required to retain all of the

PCDD/Fs while minimizing the retention of coplanar non-ortho PCBs. The results

indicated that the lower the carbon content of the trap, the greater the breakthrough

of non-ortho PCBs and dioxins. However, no combination of carbon content and

eluent composition provided a complete separation of coplanar PCBs from PCDD/Fs.

Both compound classes were quantitatively trapped when the carbon content of Cell

2 was greater than 1%. With a carbon content of 1%, non-ortho PCBs started to break

through but the PCDD/Fs were strongly retained in the carbon. With a carbon

content of 0.5%, some PCDD/Fs started to pass through the trap.

2.3.1.2 M-PLE performance with low sample intake

Traps containing 1% carbon/Celite were used for M-PLE extraction of samples with

high or moderate PCDD/F contents. In such cases, it is sufficient to use 1 g of sample

Celite

Sample

H2SO4-silica

Activated silica

KOH-silica

Adaptor

Carbon/Celite

Cell 1

Cell 2

Fraction 1

(non-planar compounds)

1. Forward elution

Fraction 2

(planar compounds, incl.

PCDD/Fs)

2a. Dissemble 2b. Backward elution


13

material in the extraction. Analyses of a wide range of solid matrices, including the

industrial reference soil CRM-529, the reference sediment WMS-01, and two

intercalibration samples (Soil C and Sludge C) yielded measured concentrations that

agreed well with the certified/Soxhlet/consensus values. The RSDs were below 21%

for all of the triplicate measurements. The precision of the TEQ values ranged from 2-

9%; this satisfies the requirements outlined in EC regulation 1883/2006, which

pertains to dioxin residues in solid samples [56].

Table 2. TEQ values (pg/g) for four samples extracted using traditional Soxhlet or M-PLE methods.

CRM-529 WMS-01 Soil C Sludge C

Certified/Consensus - 59 ± 20 140 ± 35 46 ± 17

Soxhlet 7500 ± 260 64 ± 5 - -

M-PLEDCM/Hp 7400 ± 160 68 ± 3 160 ± 6 45 ± 3

M-PLEDEE/Hp 6700 ± 300 68 ± 5 140 ± 5 37 ± 3

Although the M-PLE and Soxhlet results were in good agreement with respect to

overall PCDD/F concentrations, the Hp-OCDD/F concentrations determined using

the SPLE method with DCM/Hp (1/1, v/v) were somewhat greater than those

determined using the Soxhlet protocol as reported in Paper I. The same effect was

observed when using the M-PLE method with DCM/Hp in Paper II, which suggests

that the higher concentrations measured in the previous experiments were accurate.

This implies that the optimized M-PLE protocol using DCM/Hp as the extraction

solvent may be more efficient than the Soxhlet based method. If so, this is

presumably due to the higher temperatures and pressures used in the PLE-methods,

and the more selective extraction achieved when using a binary solvent. When

performing M-PLE with DEE/Hp (1/2, v/v), the extraction temperature was

increased from 110°C to 140°C because preliminary investigations demonstrated that

the extraction efficiency at 110°C was unacceptably low. In order to prevent acid

leaching at this higher temperature, the composition of the multilayer silica plug was

changed: whereas the protocol outlined in Paper I calls for 6 g of KOH–silica, 1 g of

silica, and 2.5 g of 20% H2SO4-silica, the revised M-PLEDEE/Hp protocol uses 6 g of

KOH-silica, 4 g of silica, and 2.5 g of 20% H2SO4-silica. The use of a larger silica plug

was made possible by the bigger cell of the ASE350 instrument. Although the M-

PLEDEE/Hp protocol was reasonably efficient, it was less so than the M-PLEDCM/Hp

protocol. Nevertheless, it yielded results that agreed well with the certified/Soxhlet

values.

The M-PLE approach was also tested on fly ash #1879, which is an in-house

reference material used for accreditation monitoring in the lab. A 1 g fly ash sample

was loaded directly into the M-PLE cell without acid treatment and then extracted

with DCM/Hp (1/1, v/v) at 110°C. Under these conditions, the extracted quantities of

all congeners were significantly lower than the reference values obtained using the

traditional Soxhlet method (Figure 8), even after increasing the extraction

temperature to 130°C or 150°C quantitative dioxin recovery was not achieved,


14

meaning that the M-PLE conditions were not sufficiently exhaustive to extract all of

the dioxins from a carbon-rich matrix such as fly ash.

Figure 8. Concentrations (pg/g) of PCDD/Fs extracted from fly ash by the reference Soxhlet method and

by the M-PLE method with DCM/Hp (1/1, v/v) at three extraction temperatures: 110°C, 130°C and 150°C.

2.3.1.3 M-PLE performance with high sample intake

In environmental analysis, it is common to use samples of more than 1 g in cases

where the PCDD/F content is low or the samples are heterogeneous. However, high

sample intakes (≥ 2 g) proved to be a challenge for the current M-PLE strategy,

resulting in significant breakthrough of IS. This effect became more pronounced as

the sample intake increased (Figure 9a). The level of breakthrough observed when

using the DEE/Hp method, which has a higher extraction temperature, was even

worse than that observed with the DCM/Hp protocol. This was probably due to

increased competition for the adsorption sites in the carbon plug. To increase the

trap’s tolerance, its carbon content was raised from 1% carbon/Celite to 3%. Under

these conditions, samples of up to 8 g could be extracted (Figure 9b).

0

2000

4000

6000

8000

10000

12000

14000

16000

18000

Reference Temp 110C Temp 130C Temp 150C


15

a) b)

Figure 9. Distributions (%) of 13C-PCDD/Fs in the first and second fractions obtained using the M-PLE

method with a) 1% carbon/Celite and b) 3% carbon/Celite.

Intercalibration Sediment C was used to validate the 3% carbon/Celite trap with

sample masses of 2-8 g using the ASE350 instrument. The M-PLE results obtained in

this way agreed well with the Soxhlet results, with some exceptions for highly

chlorinated congeners. The overall TEQs were within 95% uncertainty of the Soxhlet

values, and no breakthrough of IS was observed. Consequently, this protocol should

be suitable for use with high sample intakes. However, one should be aware of that

this approach may result in more extensive extract contamination, potentially

necessitating an additional clean-up step. It should therefore only be used when

needed.

2.3.1.4 Outlook

The M-PLE procedure is an automated version of the original Stalling method for

dioxin analysis, which involves Soxhlet extraction followed by clean-up on gravity-fed

columns filled with multiple layers of silica, acid- or base-modified silica, and

activated carbon. The new protocol has the advantage that extraction and clean-up

are performed in a single step rather than three. As such, the M-PLE method has all

the advantages of the SPLE method described in Paper I but is even more amenable

to automation due to the incorporation of a carbon trap. Compared to the pioneering

M-PLE work of Erik Spinnel [45, 55], this M-PLE protocol is more robust and

therefore applicable to a wider range of solid samples. In addition, it can be used with

environmentally friendly non-chlorinated extraction solvents (DEE/Hp). Other

automated extraction and clean-up methods for dioxin analyses are commercially

available at present, such as the PowerPrep system (FMS) [57-59]. However, these

use costly disposable adsorbent cartridges, consume large quantities of pure solvent,

0%

20%

40%

60%

80%

100%

2 g 5 g 10 g 15 g 2 g 4 g 8 g

DCM/Hp DEE/Hp

Fr 1 Fr 2

1% carbon /Celite

0%

20%

40%

60%

80%

100%

2 g 4 g 8 g 2 g 4 g 8 g

DCM/Hp DEE/Hp

Fr 1 Fr 2

3% carbon /Celite


16

have low sample throughput (six parallel samples) and are tricky to operate. These

drawbacks are counterbalanced by the fact that the PowerPrep system (FMS) can be

used for multi-class analysis and can be integrated into different sample preparation

units, making it possible to leave samples unattended for several hours. In principle,

our M-PLE method should also permit multi-class analysis, since the first M-PLE

fraction (which contains ortho-PCBs and other non-planar compounds) could be

analyzed by comprehensive two-dimensional GC mass spectrometry (GC × GC/MS)

analysis while the second M-PLE fraction (which contains non-ortho PCBs and other

planar compounds) can be analyzed using GC/HRMS or GC × GC/MS, depending on

the user’s interests.

Gas chromatography (GC)

17

3 Gas chromatography (GC)

3.1 Principles

In gas chromatography (Figure 10), the sample to be separated is vaporized in a hot

injector and then carried through a chromatographic column by a stream of an inert

gaseous mobile phase (carrier gas) [60]. The sample components are separated based

on differences in the solutes’ vapor pressures and/or the intensity of their

interactions with the stationary phase interactions, causing what is known as

retention. There are two types of GC stationary phases available: gas-solid

chromatography (GSC) in which a solid adsorbent serves as the stationary phase, and

gas-liquid chromatography (GLC) in which a thin-film liquid stationary phase is

coated onto the wall of a capillary column or spread on an inert support. Nowadays,

most environmental analyses of POPs are conducted using coated GLC capillary

columns for chromatographic separation.

Figure 10. Schematic of a gas chromatograph.

Models describing the retention [61] and retention index [62] values for specific

compounds in GLC systems have been presented in the literature. In brief, non-polar

stationary phases interact with solutes via weak dispersive and induced dipole forces;

the retention of analytes on a non-polar phase is therefore largely determined by

their vapor pressure, which is strongly dependent on the column temperature. In

contrast, polar stationary phases have functional groups that can form strong

interface interactions such as dipole-dipole, dipole-induced dipole, ion-dipole or ion-

induced dipole interactions. Consequently, analyte retention on polar columns is

governed by both vapor pressure and solute-stationary phase interactions. For

complex environmental samples, especially those that contain compounds with large

numbers of isomers (e.g. dioxins, PCBs, or PBDEs…) having somewhat identical mass

spectra, GC separation is an essential component of the analytical chain and has a

profound impact on the likelihood of successfully identifying and quantifying each

individual isomer.

DetectorInjector

Column

Column oven

Syringe


18

3.2 Summary of Paper III

3.2.1 New stationary phases with specificity for dioxins

Paper III describes a study in which several novel stationary phases were evaluated

based on their ability to separate the 136 tetra- to octaCDD/F congeners with special

emphasis on the seventeen 2,3,7,8-substituted ones. The 74 mono- to tri-CDD/F

congeners were not included in the study because several of them are not

commercially available and they are of limited toxicological interest. The analysis was

performed by injecting standard mixtures of dioxins directly into the GC/HRMS

instrument. In total, 22 columns were compared. For six columns, we obtained data

by conducting experiments, while data for the remaining 16 were obtained from the

scientific literature (Table 3). Ionic liquids consist of asymmetrically substituted N or

P cations (e.g. imidazolium, pyrrolidinium, or pyridinium ions) counterbalanced with

inorganic anions (e.g. Cl-, PF6-, or BF4-) [63-68]. The ionic liquid nature such as

extreme polarity and diverse solvation interactions (hydrogen bonds, dispersion

interactions, interactions with electrons, etc.) makes them capable of separating a

wide range of compounds. Ionic liquid stationary phases have been commercially

available since 2009 and have found applications in the analysis of biodiesels [69],

fatty acid methyl esters [67, 70], fragrances [70], and in separating some PCBs and

PAHs [63]. However, they have not previously been used to analyze dioxins. We

therefore included three ionic liquid columns in our study, along with two shape-

selective columns (one coated with a liquid crystal, LC-50, and one with

cyclodextrins, DEXcst) and one highly efficient (low bleed) non-polar column (DB-

XLB).

Of the six columns tested in our laboratories, the three ionic liquid columns (SLB-

IL111, SLB-IL76, and SLB-IL61) achieved better chromatographic separation than the

LC-50, DEXcst and DB-XLB columns (Table 3). The superiority of the ionic liquid

columns was especially pronounced for the separations of TeCDD/Fs and PeCDD/Fs

(Figures 11-13). The SLB-IL61 offered the best overall performance, successfully

resolving 106 out of 136 compounds, and also resolving 16 of the 17 2,3,7,8-

substituted PCDD/Fs. The SLB-IL111 and SLB-IL76 resolved or partially separated

100 congeners, but the SLB-IL111 separated more of the 2,3,7,8-PCDD/F congeners

(14) than the SLB-IL76 (12). Overall, the most notable of the new columns were the

SLB-IL111 and SLB-IL61. Of the columns whose performance was evaluated based on

literature data, the only one that could match the ionic liquid columns was the

Smectic liquid crystal column, which resolved 103 congeners and separated 12

2,3,7,8-substituted PCDD/Fs. Unfortunately, the Smectic column is no longer on the

market.


19

Table 3. Performance of the tested columns (grey background) and several literature columns (white

background) in the separation of 136 PCDD/F congeners. The best separations achieved for each class of

compounds are those in boxes.

Column Source Phase PCDFs PCDDs PCDD/Fs

2,3,7,8-PCDD/Fs

Supelco polarity scalec

Ref ++ +- -- ++ +- -- ++ +- -- ++ +- --

DB-XLB Agilent Non-polar, proprietary 31 19 37 20 11 18 51 30 55 12 2 3 8+

DEXcst Restek Chiral, proprietary CDa 30 19 38 18 11 20 48 30 58 7 4 6 ?

LC-50 Restek Liquid crystal 28 13 46 21 10 18 49 23 64 10 2 5 ?

SLB-IL61 Supelco Polar, Ionic liquid 53 12 22 34 7 8 87 19 30 15 1 1 61



DB-1 Agilent Non-polar, 100%

dimethyl

16 11 60 16 13 20 32 24 80 5 7 5 5 [71]

VF-Xms Agilent Non-polar, proprietary 30 12 45 22 8 19 52 20 64 14 2 1 8+ [72]

VF-5ms Agilent Non-polar, 5% phenyl 30 10 47 24 7 18 54 17 65 13 1 3 8 [72]

DB-5ms Agilent Non-polar, 5% phenyl 28 14 45 18 12 19 46 26 64 9 5 3 8 [72]

DB-5 Agilent Non-polar, 5% phenyl 17 11 59 15 9 25 32 20 84 6 5 6 8 [71]

5Sil MS Restek Non-polar, 5% phenyl 29 15 43 25 5 19 54 20 62 13 2 2 8 [73]

Dioxin2 Restek Non-polar, proprietary 21 16 50 13 11 25 34 27 75 7 6 4 8 [74, 75]

BPX-DXN SGE Non-polar, proprietary 23 13 51 21 7 21 44 20 72 10 4 3 8 [76]

Equity-5 Supelco Non-polar, 5% phenyl 20 18 49 23 5 21 43 23 70 7 6 4 8 [72]

DB-17 Agilent Semi-polar, 50% phenyl 26 20 41 19 6 24 45 26 65 11 3 3 21 [71]

DB-210 Agilent Polar, 50%

trifluoropropyl

18 22 47 16 9 24 34 31 71 9 3 5 34 [71]

DB-225 Agilent Polar, 50% cyanopropyl,

50% phenyl

25 26 36 25 10 14 50 36 50 10 3 4 40 [71]

CPS-1 Discont.b Polar, 75% cyanopropyl,

25% phenyl

43 9 35 28 4 17 71 13 52 11 2 4 60 [71]

SP-2331 Supelco Polar, 90% cyanopropyl,

10% phenyl

44 10 33 24 5 20 68 15 53 13 2 2 76 [71]

CP-Sil 88 Agilent Polar, 100% cyanopropyl 42 11 34 24 7 18 66 18 52 12 3 2 81 [71]

Smectic Discont. Liquid crystal 42 17 28 28 16 5 70 33 33 12 0 5 ? [71]

a Cyclodextrin added in 14% cyanopropylphenyl/86% dimethyl polysiloxane

b Production discontinued

c Based on McReynolds constants and normalized against the Supelco SLB-IL100, which is similar in

polarity to TCEP (1,2,3-tris[2- cyanoethoxypropane]), the most polar of the traditional stationary phases

[65]

8+ means the polarity is slightly greater than 8

++ Peak well separated, valley 85-100%; +- Peak partially separated, valley 5 - 85%; -- Peak coeluted


20

22.00 24.00 26.00 28.00 30.00 32.00 34.00 36.00 38.00 40.00 42.00 44.00

%

0

100

13

68

13

47

12

37

/24

68

13

78

/13

79

14

68

12

68

/13

69

16

78

12

49

14

69

23

78

/12

39

23

68

23

67

/23

46

12

89

13

67

13

49

12

78

24

67

23

481

34

612

48

12

38

12

34

23

47

12

69

34

67

12

47

13

48

12

46

/14

78

12

36

14

67

12

79

12

67

SLB-IL76

28.00 30.00 32.00 34.00 36.00 38.00 40.00 42.00 44.00 46.00 48.00

%

0

100

13

68

13

79

13

78

13

47

12

47

14

68

13

67

12

48

13

48

13

69

13

46 1

24

6/1

26

81

47

8

24

68

/12

37

23

68

16

78

/12

34

/1

23

8/1

23

6

13

49

14

67

/12

78

12

49

12

79

14

69

12

67

23

47

24

67

23

48

12

392

37

8

12

89

34

67

23

67 2

34

6/1

26

9

SLB-IL61m/z 303.9016

LC-50

8.50 9.00 9.50 10.00 10.50 11.00 11.50 12.00 12.50 13.00 13.50 14.00 14.50 15.00

%

0

100

13

68

14

68

24

68

13

46

12

46

/12

48

/1

34

8/1

47

81

26

8/1

34

7

12

47

/13

69

13

67

/14

67

16

78

13

78

23

68

12

36

/14

69

/12

34

13

49

/13

79

12

49

12

38 2

34

8/2

46

7/1

27

8

12

67

/23

46

12

69

/12

37

12

79

23

47

/23

78

12

39 2

36

7

34

67

12

89

22.50 23.00 23.50 24.00 24.50 25.00 25.50 26.00 26.50 27.00 27.50 28.00 28.50

%

0

100

13

68

14

68

13

46

24

68

/12

46

13

78

/13

47

/1

34

81

24

71

24

81

36

7

12

68

/14

67

16

78

/13

69

/12

34

14

78

24

67

/12

37

23

68

14

69

/12

38

/12

36

13

49

/12

78

12

67

23

46

23

47

/23

48

23

672

37

8/3

46

7

12

8913

79

12

49

12

79

12

69

12

39

DB-XLB

14.00 14.50 15.00 15.50 16.00 16.50 17.00 17.50 18.00 18.50 19.00 19.50 20.00 20.50

%

0

100

13

68

14

68

13

46 12

46

/13

78

13

47

/13

48

13

79

/13

67

12

47

12

48

12

68

/24

68

14

78

/14

67

13

69

/16

78

12

37

/12

34

/1

23

8/1

23

61

46

9

13

49

12

78

12

49

12

67

/24

67

12

79

23

68

23

46

12

39

/12

69

23

47 23

48

/34

67

23

67

/23

78

12

89

βDEXcst

30.00 38.00 40.00 42.00 44.00 46.00 48.00 50.00 52.00 54.00 56.00 58.00

%

0

100

////

13

68

13

47

13

78

/13

79

14

68

12

47

13

67 13

46

/13

69

12

48

16

78

12

36

13

49

12

79

24

67

14

69

/12

67

23

47 2

36

7/1

26

9

12

89

13

48 14

67

12

49

12

78 23

78

23

48

12

68

14

78

12

46 1

23

72

46

8

12

38

12

34

23

68

12

39

23

46

34

67

SLB-IL111

m/z 303.9016

m/z 303.9016

m/z 303.9016

m/z 303.9016

m/z 303.9016

Figure 11. TeCDF chromatograms obtained using the SLB-IL61, SLB-IL76, SLB-IL111, LC-50, DEXcst

and DB-XLB columns.


21

39.00 40.00 41.00 42.00 43.00 44.00 45.00 46.00 47.00 48.00 49.00 50.00

%

0

100

36.00 37.00 38.00 39.00 40.00 41.00 42.00 43.00 44.00 45.0027.00 28.00 29.00 30.00 31.00 32.00 33.00 34.00 35.00

%

0

100

42.00 44.00 46.00 48.00 50.00 52.00 54.00 56.00 58.00 60.00 62.00

%

0

100

12.00 13.00 14.00 15.00 16.00 17.00 18.00 19.00 20.00 21.00

%

0

100

19.00 20.00 21.00 22.00 23.00 24.00 25.00 26.00 27.00 28.00

%

0

100

29.00 30.00 31.00 32.00 33.00 34.00 35.00 36.00 37.00 38.00 39.00

%

0

100

13

46

8

14

67

81

24

6713

46

7/1

36

78

12

46

8

13

47

8/1

23

68

13

46

9/1

23

46

12

47

8

13

47

9

12

47

91

24

69

23

46

8/1

23

47

/1

23

48

12

37

8

12

36

7/1

26

78

12

48

9/1

23

49

/23

47

8

12

37

9 12

67

9

23

46

7

12

36

9

12

38

9

13

46

8

13

67

8

12

36

8/1

34

78

/13

46

7/

13

47

9/1

46

78

12

46

8

12

47

9/1

23

46

/13

46

9

12

46

7

12

46

9

12

37

8

12

34

7/1

23

48

12

37

9

12

36

7/1

26

78

23

46

8

12

67

9

23

46

7

12

36

9

12

48

9

12

38

9

13

46

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SLB-IL76

SLB-IL61m/z 339.8597

LC-50

DB-XLB

βDEXcst

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m/z 339.8597

m/z 339.8597

m/z 339.8597

m/z 339.8597

m/z 339.8597

23

46

8/1

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69

Figure 12. PeCDF chromatograms obtained using the SLB-IL61, SLB-IL76, SLB-IL111, LC-50, DEXcst

and DB-XLB columns.


22

30.00 32.00 34.00 36.00 38.00 40.00 42.00 44.00 46.00

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SLB-IL76

SLB-IL61m/z 321.8936

LC-50

DB-XLB

βDEXcst

SLB-IL111

m/z 321.8936

m/z 321.8936

m/z 321.8936

m/z 321.8936

m/z 321.8936

22.00 24.00 26.00 28.00 30.00 32.00 34.00 36.00 38.00 40.00

%

0

100

12

67

Figure 13. TeCDD chromatograms obtained using the SLB-IL61, SLB-IL76, SLB-IL111, LC-50, DEXcst

and DB-XLB columns.


23

3.2.2 Column combinations

The ultimate aim of Paper III was to identify a single stationary phase that can

resolve all 136 congeners and the seventeen 2,3,7,8-substituted PCDD/Fs. However,

no such phase could be found. Therefore, to improve the final separation, dual and

triple column combinations were evaluated by injecting the dioxins onto individual

GC columns and summing the separations achieved for each congener on each

column in the tested combination. As shown in Table 4, all of the best combinations

in this theoretical analysis featured the Smectic column. The unique shape-selectivity

of this column enabled it to resolve congeners that were not resolved on the other

columns. Its lack of commercial availability is therefore particularly disappointing.

Alternative shape-selective columns such as the LC-50 did not offer adequate

performance, possibly because they had a lower liquid crystal content, different

selectivities and poor chromatographic peak shapes. The best combinations of

commercially available columns all included ionic liquid phases.

Table 4. Separation of 136 PCDD/Fs with dual column combinations. In each cell, the upper digit stands

for total number of resolved congeners while the lower digit stands for total number of resolved 2,3,7,8-

substituted congeners.


24

Based on the chromatograms and the results presented in Table 3, it was clear that

two of the ionic liquid columns had different selectivities. The SLB-IL61 column

exhibit Wax (polyethylene glycol)-type selectivity and performed better in the

separation of PCDDs. Conversely, the SLB-IL111 column has an extremely polar

stationary phase that can form multiple solvation interactions, and was particularly

effective at separating PCDFs. Consequently, the best dual column combination that

did not include the Smectic column was SLB-IL61/SLB-IL111, which resolved 128 of

the 136 PCDD/F congeners and completely resolved the 2,3,7,8-PCDD/Fs. The best

triple-column combination was DB-225/SLB-IL61/SLB-IL111, which separated five

more congeners than the SLB-IL61/SLB-IL111 duo. However, no combination

separated all of the congeners.

Existing ionic liquid columns suffer from some technical problems; in future, it will

be necessary to increase the stability of their stationary phases and to overcome

problems with dehalogenation.

3.2.3 Outlook

Over the past decade there have been ongoing attempts to develop an analyte-

specific GC column that can separate all of the 2,3,7,8-substituted dioxins in a single

run. The work presented in Paper III aimed higher than this, targeting all 136 tetra-

to octa-chlorinated DD/Fs. Although the SLB-IL111 and SLB-IL61 cannot resolve all

of these congeners, they both separated more than 100 congeners and exhibited

complementary selectivities. By performing dual analyses and combining the results,

it was possible to separate or partially separate all of the 2,3,7,8-PCDD/Fs and 128 of

the 136 highly chlorinated congeners. Since the current standard procedure for

quantifying the seventeen 2,3,7,8-PCDD/Fs involves sequential injections on two

columns (one DB5-type and one polar column) [18-21], it may well be desirable to

instead use the combination of ionic liquid columns identified in this work and

thereby simultaneously obtain data for the 2,3,7,8-PCDD/Fs and for most of the 136

tetra- to octaCDD/Fs.

Aside from their good performance in separation, it is possible that incorporating

ionic liquid columns into GC × GC/MS protocols may provide additional benefits.

Uncoupling the two separation steps makes it possible to fully exploit differences in

the selectivities of the two columns used, without running the risk of re-mixing

previously separated congeners [77-79]. It may even become possible to achieve full

congener separation using one injection rather than two or more. However, current

GC × GC/MS protocols that use time-of-flight (TOF) mass spectrometers have limits

of detection that are an order of magnitude greater than can be achieved with

magnetic sector high-resolution mass spectrometry instrument, and there is

currently no provider of commercial GC × GC/MS hardware/software for use with

instruments of the latter type.


25

3.3 Summary of Paper IV

In Paper III, we discussed the possibility of using dual/triple column combinations

in one-dimensional GC to separate the 136 tetra- to octa-CDD/Fs. In the study

described in Paper IV, we characterized the columns’ selectivity with the long-term

goal to further improve the separation of the 136 PCDD/Fs, preferably using

comprehensive two-dimensional gas chromatography (GC × GC) to minimize the

number of injections and columns required. The selection of columns for GC × GC is

based on differences in modes of separation. Frequently, a non-polar column is used

in the first dimension to separate solutes, primarily based on differences in vapor

pressure, and a column with a different type of selectivity in the second dimension for

additional separation. The main objective of the study reported in Paper IV was to

use multivariate data analysis to characterize the selectivity and solute-stationary

phase interactions of the 22 GC columns listed in Table 4. The results from the

characterization were used to recommend suitable column combinations for GC ×

GC.

3.3.1 Multivariate data analysis

Differences in column selectivity and solute-stationary phase interaction can be

evaluated by principal component analysis (PCA) and partial least squares (PLS)

regression. PCA is a multivariate technique designed to extract and display the

systematic variation in a data matrix X.

Information on the absolute retention times of the 136 PCDD/Fs on the 22 GC

columns was compiled from scientific literature [71-74, 76, 80, 81] and our

experiments [82] and was subjected to PCA in order to characterize the columns’

selectivity. Another dataset, consisting of both absolute retention times and

physicochemical properties of all congeners, was used in a second PCA to explain the

column selectivity in term of intermolecular interactions.

The physicochemical properties included in the second PCA were selected using

PLS regression, in which variables assigned to the X-block (here, retention times) are

used to predict responses assigned to the Y-block (here, physicochemical properties).

Nine properties: aqueous solubility (-lgSw), energy of the highest occupied molecular

orbital (EHOMO), energy of the lowest unoccupied molecular orbital (ELUMO), the most

positive partial charge on a hydrogen atom (qH+), the most negative atomic partial

charge in a molecule (q-), dipole moment of the molecule (µ), mean molecular

polarizability (α), molecular volume (Vm) and n-octanol/water partition coefficient

(lgKow) were selected from literature [83, 84] to represent the charge distribution and

intermolecular interaction. The results reflected the degree of correlation between the

retention times and the 9 physicochemical properties.


26

3.3.2 Column characterization

3.3.2.1 First PCA modeling of the retention times

The PCA modeling of the retention times identified two principal components

(PCs) that explained 83% of the variance in retention times of the 136 PCDD/Fs on

the 22 GC columns. The first (PC 1) explained 64% of the total variance and was

strongly influenced by the degree of chlorination, which is strongly related to the

vapor pressure of the PCDD/Fs. The second (PC 2) explained only 19% of the total

variation, but provided important indications of selectivity difference. The columns in

the negative (lower) part of the PC 2 have low polarity, and the corresponding part of

the variable (loading) plot is occupied by congeners with a low charge separation, i.e.

with chlorine atoms well dispersed over the molecules (1,3,6,8-TCDF, 1,3,6,8-TCDD,

1,3,4,6,8-PeCDF, 1,2,4,6,8-PeCDF, and 1,2,4,7,9-PeCDF). In contrast, the positive

(upper) part of the PC 2 is occupied with polar columns and congeners with

continuous regions of chlorine substitutents, such as: 3,4,6,7-TCDF, 1,2,8,9-TCDF,

2,3,7,8-TCDF, 2,3,4,6,7-PeCDF, and 1,2,3,8,9-PeCDF. Thus, these congeners may

interact with polar columns through, for instance, dipolar and charge transfer

interactions.

The score plot displays the distribution of the observations (here columns)

projected onto a two-dimensional plot, in which observations located close to each

other are similar whereas those far away from each other are dissimilar, and

observations located diametrically opposite to each other in the plot have opposite

effects on the modeled system. Closer investigation of the column clustering in the

score plot in Figure 14 revealed four different classes of columns. The trifluoropropyl

phase (DB-210) appeared isolated, probably because it has intermediate selectivity.

Class I is located in the lower-left corner of the score plot and includes non-polar

phases like Dioxin 2, BPX-DXN, 5Sil MS, Equity-5, DB-1, DB-5ms, VF-5ms, and DB-

5. As they are located in the region of low charge separation, the separation by these

columns is strongly governed by vapor pressure and weak dispersive and induced

dipole forces.

Class II includes the three ionic liquid columns (SLB-IL61, SLB-IL111, and SLB-

IL76), located in the upper-left corner of the score plot. These columns are expected

to interact with the analytes through strong forces like ion-dipole, dipole-dipole and

ion-induced dipole interactions.

Class III is located in the middle of the plot, between Classes I and II. It includes all

the high percentage phenyl and cyanopropyl phases involved in the study, ordered

according to the amount of cyanopropyl groups: DB-17 (50% phenyl) < DB-225 (50%

phenyl, 50% cyanopropyl) < CPS-1 (25% phenyl, 75% cyanopropyl) < SP-2331 (10%

phenyl, 90% cyanopropyl) < CP-Sil 88 (100% cyanopropyl). These vary in polarity

from moderately polar to highly polar, and may interact through dipole-induced

dipole and dipole-dipole interactions.


27

Figure 14. Score plot of the first two components of the first PCA model, where the variables were the

retention times and the observations were the 22 GC columns.

Class IV appears to be shape-selective. Columns in this class are widely spread on

the right side of the score plot, and include two non-polar columns (VF-Xms and DB-

XLB), a chiral column (DEXcst) and two liquid crystal columns (SB-Smectic and

LC-50). The latter two are mesomorphic shape-selective phases [85, 86] with ordered

structures that strongly retain planar molecules. It was noticed that the mesomorphic

molecular structures of SB-Smectic is arranged in layers, whereas the long axes of the

LC-50 mesomorphic side chains maintain a parallel arrangement. The former

provide more shape selectivity. The third shape-selective column (DEXcst) is a

chiral column that offers a different separation mechanism: host-guest complexation.

The appearance of non-polar columns (DB-XLB and VF-Xms) together with three

shape-selective columns was unexpected. Their phase compositions are proprietary,

we only know that DB-XLB contains arylene groups with polarity in the range of 12%

phenyl-methylsiloxane [87] and that VF-Xms is “highly arylene modified” [88]. Their

polymer chains are probably modified in a way that decreases their flexibility to such

degree that they obtain liquid crystal properties and, thus, become shape-selective.

3.3.2.2 PLS modeling of the physicochemical properties

Results from the PLS analysis are displayed in Table 5. R2, the explained variation,

is a measure of how much the variation in X can be described by Y. R2 ≥ 80% meant

high degree of explanation or correlation. As seen in Table 5, the two most strongly

correlated descriptors to the retention times were aqueous solubility (-lgSw) and

mean molecular polarizability (), with R2 ≥ 80% for all models. The lipophilicity (n-

-0.01 -0.005 0 0.005 0.01

-4

-2

0

2

4

6

x 10-3

Scores on PC 1 (64.28%)

Score

s o

n P

C 2

(19.3

5%

)

Equity-5

DB-5ms VF-5ms

VF-Xms

DB-1

DB-5

DB-17 DB-210

DB-225

CPS-1

SP-2331 CP-Sil 88

Smectic

Dioxin2

DB-XLB

DEX

LC-50

IL61

IL76

IL111

BPX-DXN 5Sil MS

Class I

Class IVClass II

Class III


28

octanol/water partition coefficient lgKow) was also well correlated, unsurprisingly as

lgKow is inversely correlated to aqueous solubility (-lgSw). The other descriptors were

moderately or poorly correlated.

Table 5. The explained variation R2 (%) between individual descriptor and the retention times.

Property Abbr. PCDD/Fs PCDDs PCDFs TeCDD/Fs TeCDFs

Aqueous solubility -lgSw 96 98 95 96 89

HOMO energy EHOMO 85 82 74 85 -

LUMU energy ELUMO 77 - 80 77 -

Most positive charge on H qH+ 17.5 - - 17.5 -

Most negative atomic charge q- 3 - 61 3 62

Dipolar moment µ 50 - - 50 61

Molecular polarizabiliy 96 99 96 96 91

Molecular volume Vm 38 91 - 38 -

Lipophilicity lgKow 84 88 80 84 63

3.3.2.3 Second PCA modeling of the retention times and physicochemical

properties

The second PCA model included retention times and three physicochemical

properties (-lgSw, , lgKow) of PCDD/Fs to evaluate the structure-property-retention

relationships. However, it was a limited success. All the physicochemical descriptors

clustered together in a corner isolated from the rest in the resulting plots, and the

distribution of the 22 GC columns was quite similar to the first PCA. This indicated

that the co-variation of these physicochemical descriptors was strong and highly

correlated to molecular size. More descriptors are needed to capture variations in

electron density and molecular shape among isomeric PCDD/Fs.

3.3.2.4 Suitable GC × GC column combinations for dioxin analysis

Orthogonality is the key factor in selecting suitable column combinations for GC ×

GC separation. Those with maximum orthogonality for separating dioxins are those

belong to different classes and located far away from each other in Figure 14. For

instance, combinations of columns from Classes I & II, Classes II & IV, and Class I or

IV & Class III (only the high percentage cyanopropyl columns) could be appropriate.

3.3.3 Outlook

There have been many attempts to develop new GC columns with specificity for

dioxins, however, there has been no attempt to investigate the selectivity of such

columns or characterize the interactions taking place between dioxins and the

stationary phases to understand the retention mechanism. So far, no publication has


29

been found in these areas. Therefore, the aim of the work presented here was to

achieve such information. The multivariate analyses seem to provide promising

results, though further investigation of the solute-stationary phase interactions with

molecular descriptors is necessary as well as testing the proposed GC × GC column

sets in practice.

Detection and quantification

30

4 Detection and quantification

4.1 High resolution mass spectrometry (HRMS)

The last step of any analytical procedure is to detect (and measure) the analytes.

Currently, HRMS is the most sensitive technique for trace analysis of individual

dioxin congeners as it can distinguish ions with mass-to-charge (m/z) differences of

0.01 amu and can detect femtogram quantities of analytes. Thus, HRMS was used to

detect dioxins in the studies reported in Papers I-IV. Its principle of operation is as

follows: the gaseous effluent from a GC column is introduced via a heated capillary

tube to the ion source of the HRMS instrument, where high-energy electrons ionize

and fragment the analytes into positively charged ions with characteristic m/z ratios.

The positive ions are then extracted and separated using a magnetic field. Only ions

with a specific m/z ratio reach the detector at a given time, while all those with other

m/z ratios are lost. Consequently, the system is usually operated in selected ion

recording (SIR) mode in trace environmental analysis.

4.2 Quantification

The aim of quantification is to convert the analyte detector responses to

concentrations. There are several methods, one of which (‘isotope dilution’) was used

in the project this thesis is based upon. In isotope dilution, samples are “spiked” with

isotope-labeled analytes as IS, which are used to correct for losses during sample

preparation and instrumental variations. The same amount of IS is also added to a

standard solution containing known amounts of the target analytes. After the

detection, a calibration curve is constructed by plotting ratios of the analyte:IS

detector signals (Aanalyte/AIS) against ratios of the known amounts of the analytes and

IS (manalyte/mIS). Then, to determine the amount of an analyte in a sample, the

Aanalyte/AIS ratio is calculated, the manalyte/mIS ratio is obtained from the calibration

curve, and manalyte is derived by multiplying with mIS. This isotope dilution method

was utilized in the studies described in Papers I-II, with 13C-labeled PCDD/Fs (which

have very similar properties to the target analytes; PCDD/Fs) as IS.

Conclusions and future prospects

31

5 Conclusions and future prospects

To conclude the work presented in this thesis, the following important findings are

highlighted as a summary:

Development of an SPLE method with in-cell clean-up for congener-specific

analysis of PCDD/Fs in soil and sediment samples

Expansion of the methodology into a one-step M-PLE method for simultaneous

extraction, clean-up and fractionation of PCDD/Fs in a wide range of solid

samples

Ionic liquid stationary phases was shown to effectively separate tetra- to octa-

CDD/Fs, significantly enhancing profiling of the 136 tetra- to octa-CDDF

congeners

PCA analysis indicated that 22 tested GC columns clustered into four classes

representing different separation modes

What we achieved in this thesis has certainly satisfied an important part of the

ultimate goal for dioxin analysis [22]. We introduced a novel streamlined one-step

M-PLE procedure for extraction, clean-up and fractionation of PCDD/Fs and showed

that it produces data statistically equivalent with standard methodology. We also

improved the GC separation and congener profiling of PCDD/Fs.

What we can do in the future is to involve GC × GC analysis of the M-PLE extracts

to provide the flexibility of multi-residue analysis (e.g. PCDD/Fs, PCBs, PBDD/Fs,

brominated compounds …). The M-PLE could also be tested on other types of solid

samples, e.g. dust, air particles, contaminated concrete ... More M-PLE applicability

in activities such as large-scale pollutant surveys, monitoring programs, pollutant

mapping, etcetera, is needed to enhance its recognition.

Efforts to improve the stability of the ionic liquid columns, especially the

promising SLB-IL111 and SLB-IL 61, are also warranted.

Finally, the most promising GC × GC column combinations should be tested in

practice, and the multivariate data sets obtained should be complemented with

additional molecular descriptors to better understand the structure-property-

retention relationships for the 136 tetra- to octa-CDD/Fs.

Acknowledgements

32

6 Acknowledgements

I would like to take this opportunity to first thank my supervisors Peter Haglund

and Staffan Lundstedt for all your inspiration, help and support during the four

years of PhD study. Peter, I really enjoyed knocking on your office door and

bothering you with questions; the things that I have learnt from you are countless.

Thanks for being my fantastic and super patient teacher! Staffan, you have not only

been an excellent supervisor, but also made the long working days easier to handle by

making funny jokes every now and then, thanks for that ! I would also like to thank

Paul Geladi for all his help with the chemometric analysis and for the good

collaboration.

There is a person who has changed my life completely from the first time we met; a

person with a really big heart that I warmly call back-father/ knight/ hunter/ teacher

or simply Lasse (Lars Lundmark). Thank you so much for offering me an

opportunity to visit Sweden, giving me a chance to grow up, and for taking care of me

like your own child. Thay Nguyen Van Dong, I guess you will never forget my

straying off scandal when I both lost my way and your bike on the way from Willys to

Ålidhem centrum; I’m such a clumsy girl, hahah. Thanks for all the discussions and

problem solving that boosted my confidence. Co Nguyen Anh Mai, my wonderful

back-mother in Umeå and big mother of the Fysikgränd 35, you always prioritized

your students, tried to help them whenever they needed it and brought them together

to make a great social environment. Thank you so much, hope you will be less

“behind schedule”, now and in the future.

This thesis is not a work of me alone, I want to send my best regards to all

colleagues (present/past) in the department for being friendly and helpful. A big

thanks to Per Liljelind for the GC/HRMS analysis, fixing various stuffs in the lab

and nice lunch discussions. Thank you Stina Jansson for sharing your molecular

descriptor data! Big thanks to Rolf, Maria, Sture for all the technical support.

Anteneh Aassefa, I appreciate your efforts in instructing me in MATLAB and

introducing me to Paul, hope that we will have more chances to hang out in the

future. Jin Zhang, it was great that you could help me with those tricky mathematic

calculations. Chau Phan and Phuoc Dinh, I have enjoyed our seven-year

friendships and our multi-topic discussions. Tomas Holmgren, you are the

last/best office mate I’ve been with so far. Kicki Frech, I like your smile as much as

your optimistic attitude, it’s just cheer me up . Kristina Arnoldsson, the

beer/cider/cheese tastings accompanied by Hamlet have been fantastic. Sandra,

Mar, Mehdi, Mandana, Ivan and Qiuju, thanks for the good times together,

both inside and outside the University. I hope we will share more fun in the future.

I would like to thank the Vietnamese community in Umeå, especially the

Fysikgränd 35 girls (Xuan Tam, Khanh Linh, Thien Thanh, Ngoc A and C.

Trang), for coloring up my life with joy. I really miss those karaoke nights, girl

parties and night talks that we spent together. It was a wonderful time! Thien

Acknowledgements

33

Thanh, thanks a lot for understanding me and being my sweet little sister, who

incited me to do the craziest but most meaningful thing in my life! Ngoc A, my

second sweet little sister, you are a special girl who I always enjoy to hang out with.

Thank you for inspiring me by your stories and bringing me to the STEP foundation.

C. Trang, although it’s easy for you to understand me but it’s hard for me to

understand you, you are in my list of best friends; thank you very much for all the

discussions we have had. To my great master student, Xuan Thong, thank you very

much for your accompany and excellent job in the lab.

To the G7 group, especially Lam tac, Vu and Nhat. We have had a lovely time in

the past and although it’ll be rare, I’m sure we’ll have more fun in the future, forever

keeping in touch.

Ba mẹ, con hạnh phúc được làm con của ba mẹ. Cảm ơn ba mẹ đã sinh con ra và

nuôi dạy con lớn khôn. Con bé còi cọc tong teo ngày nào bây giờ đã thành 1 phụ nữ

trưởng thành nhưng mỗi khi về nhà vẫn được chăm chút như đứa trẻ với muôn vàn yêu

thương ♥. U, người chị và cũng là người bạn tuyệt vời nhất của út cưng, cảm ơn U đã luôn giúp đỡ và gánh vác phần trách nhiệm chăm sóc ba thay cho uc. Dũng, cảm ơn

ngươi đã là một đứa em ngoan.

Älsking, my wonderful husband, you are the hot chili pepper that spices up my

life. Thank you for broadening my horizons with Key of awesome, Game of thrones,

American pie, Anime, Biology, Gym training, Lean diet … as well as introducing me to

all your nice friends. It’s great to have a partner who understands me, is patient with

my fluctuations, who cares about me and encourages me, especially when I’m down

with sickness. Without you, I wouldn’t have been able to finish this work. Älsking,

thank you so much for everything you have done. Em iu anh rất nhiều ♥.

References

34

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