GAS CHROMATOGRAPHIC DETERMINATION OF STYRENE
AND OTHER VOLATILE ORGANIC COMPOUNDS IN
POLYSTYRENE FOOD PACKAGING
SUSIE LU LING
UNIVERSITI TEKNOLOGI MALAYSIA
iii
Specially dedicated to my beloved husband, kids,
and family members
iv
ACKNOWLEDGEMENTS
First and foremost I would like to thank God for His mercy and grace. His
love and guidance has strengthened me through the good and tough times of my
study.
I would like to thank my supervisor, Professor Dr. Mohd Marsin Sanagi, for
his supervision, encouragement and thoughtful guidance throughout the project. I
am indebted to his faith in me which motivated me to proceed and persist to
complete my thesis.
I also wish to extend my sincere gratitude to my co-supervisors, Assoc. Prof.
Dr. Wan Aini Wan Ibrahim and Assoc. Prof. Dr Ahmedy Abu Naim for their
kindness and support. I would like to thank my post-graduate friends and all the
members of the research group for their advice and support.
I would also like to thank the Ministry of Health and Public Service
Department (JPA) for financial support and a studentship for myself. Many thanks
should be given to the Public Health Laboratory of Johor Bahru (PHLJB) for
providing laboratory facilities to make this research feasible.
I am particularly
grateful to the technical staffs of the Food Packaging Unit, PHLJB for their technical
assistance.
I wish to extend a heartfelt appreciation to all of my family members who
have given me encouragement and motivation, and have the utmost confidence in my
endeavour.
Last but not least, I must emphasize that I could not have persisted
without my husband, Jimmy, for his love, support and understanding.
v
ABSTRACT
Testing of food packaging materials with reliable method gives consumers
the assurance to the safety of the products. In this study, material and migration
tests of styrene and other volatile organic compounds (VOCs) (toluene,
ethylbenzene, iso-propylbenzene and n-propylbenzene) for polystyrene food
packaging, using gas chromatography-flame ionization detection (GC-FID) are
presented. In the material test, dissolution technique using dichloromethane was
used to extract the analytes from the samples. The developed method was validated
for specificity, detection limits, linearity, precision and accuracy. The applicability of
the method to determine the targeted analytes in a number of commercial polystyrene
food packaging was demonstrated. The results show that the dissolution technique
with direct injection using GC-FID is effective for simultaneous analysis of five
analytes in polystyrene food packaging. This direct injection method with limit of
quantification (LOQ) of 8 mg/kg was lacking in sensitivity for migration study.
Hence, headspace-solid phase microextraction (HS-SPME) technique was applied for
migration test using water as food simulant. The effects of extraction variables
including sample volume, elutropic strength, extraction temperature, extraction time,
desorption time, sample agitation, and salt addition on the amounts of the extracted
analytes were studied and optimal conditions were obtained for HS-SPME
extraction. The method was validated, and the LOQ obtained at ppb and sub-ppb
level was sensitive enough to detect the VOCs in the migration test. The optimized
method was applied to test the analytes migration from polystyrene bowls and cups
at storage temperatures ranging from 24°C to 80°C for 30 min. Styrene and
ethylbenzene were observed to migrate from the samples into the food simulant. The
migration of analyte was found to be strongly dependent upon the storage
temperature. The maximum observed migration was from the polystyrene cup at
simulating condition of 80°C for 30 min. The HS-SPME is useful as an alternative
method to determine the migration of VOCs from food packaging material into food
simulant.
vi
ABSTRAK
Pengujian bahan pembungkus makanan dengan kaedah yang berkeyakinan
boleh memberi jaminan kepada pengguna berkenaan keselamatan produk itu.
Dalam kajian ini, ujian bahan dan ujian migrasi untuk stirena and sebatian mudah
meruap (VOCs) yang lain (toluena, etilbenzena, iso-propilbenzena dan npropilbenzena) bagi pembungkus polistirena dengan menggunakan kromatografi
gas-pengesanan ion nyala (GC-FID) dibentangkan. Dalam ujian bahan, teknik
pemelarutan menggunakan diklorometana telah digunakan untuk mengekstrak analit
dari sampel. Keadah yang dibangunkan telah disahihkan bagi ketentuan, had
pengesanan, lineariti, kejituan dan ketepatan. Penggunaan keadah tersebut bagi
mengesan analit dalam beberapa jenis pembungkus makanan polistirena komersial
telah diterangkan. Keputusan menunjukkan teknik pemelarutan dengan suntikan
terus menggunakan GC-FID adalah berkesan untuk menganalisis lima jenis analit
dengan serentak dalam pembungkus makanan polistirena. Kaedah suntikan terus
mempunyai had kuantiti (LOQ) 8 mg/kg adalah kurang sensitif untuk ujian migrasi,
jadi, teknik ruang kepala-pengekstrakan mikro fasa pepejal (HS-SPME) telah
digunakan untuk ujian migrasi dan air digunakan sebagai makanan simulasi. Kesan
pembolehubah pengekstrakan termasuk isipadu sampel, kekuatan elutropik, suhu
pengekstrakan, masa pengekstrakan, masa nyahjerapan, pengacauan sampel, dan
penambahan garam ke atas amaun analit terekstrak telah diuji dan keadaan optimum
yang diperolehi telah digunakan untuk pengekstrakan HS-SPME. Kaedah ini telah
disahihkan, dan LOQ yang didapati pada tahap ppb dan sub-ppb yang cukup sensitif
untuk mengesan VOCs dalam ujian migrasi. Kaedah yang optimum telah digunakan
untuk menganalisis analit yang berpindah dari mangkuk dan cawan polistirena pada
suhu penyimpanan dengan julat dari 24°C ke 80°C. Stirena dan etilbenzena didapati
telah berpindah dari sampel ke dalam makanan simulasi. Migrasi analit didapati
bergantung kepada suhu penyimpanan. Migrasi yang maksimum telah didapati dari
cawan polistirena pada keadaan simulasi 80°C selama 30 min. HS-SPME adalah
berguna sebagai kaedah alternatif bagi penentuan migrasi VOCs dari pembungkus
makanan ke dalam makanan simulasi.
vii
TABLE OF CONTENTS
CHAPTER
TITLE
TITLE PAGE
PAGE
i
DECLARATION
ii
DEDICATION
iii
ACKNOWLEDGEMENTS
iv
ABSTRACT
v
ABSTRAK
vi
TABLE OF CONTENTS
vii
LIST OF TABLES
xiii
LIST OF FIGURES
xvi
LIST OF SYMBOLS/ABBREVIATIONS/
1
NOTATION/TERMINOLOGY
xviii
LIST OF APPENDICES
xxi
INTRODUCTION
1
1.1
Food Packaging
1
1.2
Research Background
2
1.3
Statement of Hypothesis
3
1.4
Research Aim
4
1.5
Research Objectives
4
1.6
Scope of Study
4
1.7
Outline of the Thesis
5
viii
2
LITERATURE REVIEW
6
2.1
Styrene
6
2.2
Physical and Chemical properties
6
2.3
Sources
7
2.4
Routes of Exposure
8
2.4.1
8
2.5
Styrene in Food
Uses of styrene
9
2.5.1
General Purpose Grade Polystyrene (GPPS)
10
2.5.2
Expandable Polystyrene (EPS)
10
2.5.3
High Impact Grade Polystyrene (HIPS)
11
2.5.4
Glass Reinforced Plastic (GRP)
11
2.5.5
Styrene Copolymers
11
2.6
Additives Used in Polystyrene Food Packaging
12
2.7
Health Effects
12
2.7.1
Styrene and Its Metabolite
13
2.7.2
Other Volatile Organic Compounds (VOCs)
14
2.8
Chemical Residues in Food Packaging Materials
15
2.9
Migration Studies
16
2.10
Legislation Control for Polystyrene Food Packaging
17
2.10.1 European Food Contact Regulations
18
2.10.2 U.S. Food and Drugs Administration (FDA)
Regulations
19
2.10.3 Japan Food Sanitation Law
20
Analytical Methodology
21
2.11.1 Method Application in Food Packaging
Analysis
22
2.12
Evaluation of Sample Preparation Techniques
23
2.13
Solid-Phase Microextraction (SPME)
25
2.13.1 SPME Sampling Techniques
25
2.11
ix
2.13.2 Parameters which Effect the Absorption
3
Process
26
2.13.2.1 Selection of Fiber Coatings
26
2.13.2.2 Time and Temperature of the
Extraction Process
27
2.13.2.3 pH Modification and Addition of
Salt
27
2.13.2.4 Addition of Solvent
27
2.13.2.5 Agitation of the Sample
28
2.13.2.6 Volume of the Sample
28
2.13.2.7 Matrix Effects
28
2.13.2.8 Derivatization
29
2.13.3 Interfaces to Analytical Instrumentation
29
2.13.4 SPME Applications
30
2.13.5 Advantages of SPME
31
EXPERIMENTAL
32
3.1
Experimental Layout
32
3.2
Analytes and Chemicals
32
3.3
Instrumentation
34
3.4
Samples
34
3.5
Identification of Packaging Materials
35
3.6
Material Test Procedure
35
3.6.1
Standard Preparation
35
3.6.2
Sample Preparation – Dissolution Technique
36
3.6.2.1 Material Test
36
3.6.2.2 Migration Test
36
3.6.3 Gas Chromatographic Conditions
37
3.6.4 Analysis and Quantification
37
3.6.5 Quality Control Measures
38
x
3.7
3.8
3.9
4
HS-SPME Method
39
3.7.1
Standard Preparation
39
3.7.2
Food Simulant and Leaching Conditions
39
3.7.3
Sample Preparation
40
3.7.4
HS-SPME Extraction
41
3.7.5
Instrumental Conditions
41
3.7.6
Analysis and Quantification
41
3.7.7
Optimization of SPME parameters
42
Method Validation
42
3.8.1
Specificity
42
3.8.2
Limit of Detection (LOD) and Limit of
Quantification (LOQ)
43
3.8.2.1 Signal-to-noise (S/N)
44
3.8.2.2 Blank Determination
44
3.8.2.3 Linear Regression
44
3.8.2.4 Checking a Predetermined Limit of
Quantification (LOQ)
45
3.8.3
Linearity Study
46
3.8.4
Accuracy
46
3.8.5
Precision
47
3.8.5.1 Instrument Precision
47
3.8.5.2 Method Precision
47
Data Analysis
48
METHOD DEVELOPMENT IN THE
DETERMINATION OF VOLATILE ORGANIC
COMPOUNDS IN POLYSTYRENE FOOD
PACKAGING BY DISSOLUTION METHOD
49
4.1
Identification of Packaging Materials
49
4.2
Material Test
50
4.2.1
Sample Preparation
52
4.2.2
Chromatographic Conditions
54
4.2.3
Quantification Method
55
xi
4.2.4 Method Validation
4.2.4.1
Specificity
57
4.2.4.2
LOD and LOQ
59
(a) Signal-to-noise (S/N)
60
(b) Blank Determination
61
(c) Linear Regression
62
(d) Comparison of LOD and LOQ of
Different Approaches
64
(e) Checking a Predetermined Limit
of Quantification (LOQ)
65
Linearity Test
67
(a) Inspection of y-Residual Plot
67
(b) Validation of Assumption
69
4.2.4.4
Accuracy
70
4.2.4.5
Precision
72
(a) Instrument Precision
72
(b) Method Precision
73
4.2.4.3
4.2.5 Application of Method to the Analysis of
Polystyrene Food Packaging
4.3
57
74
4.2.5.1 Quality Assurance
75
4.2.5.2 Analyte Concentration in Samples
75
Migration Test
76
4.3.1
Selection of Control Sample
77
4.3.2
Sample Homogeneity
78
4.3.3
Migration of Analyte at Different
Temperature
79
xii
5
APPLICATION OF SOLID-PHASE
MICROEXTRACTION TO THE STUDY OF THE
MIGRATION OF VOCs FROM POLYSTYRENE
FOOD PACKAGING INTO WATER AS FOOD
SIMULANT
81
5.1
Preamble
81
5.2
Instrumental Conditions
81
5.3
Optimization of SPME Parameters
82
5.3.1
Fiber Coating Selection
83
5.3.2
Sample Volume Studies
83
5.3.3
Elutropic Strength Studies
84
5.3.4
Extraction Temperature Studies
85
5.3.5
Extraction Time Studies
87
5.3.6
Desorption Time Studies
88
5.3.7
Sample Agitation
89
5.3.8
Addition of Salt
90
5.4
5.5
6
Performance of the Method
91
5.4.1
LOD and LOQ
91
5.4.2
Linearity
93
5.4.3
Precision
95
5.4.4
Accuracy
96
Application of the Method
CONCLUSIONS AND SUGGESTIONS FOR FURTHER
STUDIES
97
101
6.1
Conclusions
101
6.2
Suggestions for Further Studies
103
REFERENCES
104
Appendix A
115
xiii
LIST OF TABLES
TABLE NO.
TITLE
PAGE
2.1
Four common classes of food simulants
17
2.2
Japanese specification for polystyrene food contact
materials: (a) Material test; and (b) Migration test
21
3.1
Description of analytes and internal standard
33
3.2
Description of chemicals
33
3.3
Migration conditions used for testing of polystyrene cups
37
3.4
Preparation of calibration standard for migration test
39
3.5
Evaluation of SPME parameters
42
4.1
Characteristic wave numbers obtained from polystyrene
samples
50
Comparison of the extraction efficiencies for different
sample extraction techniques
53
Mean concentration of analytes in samples obtained by
internal standard method and standard addition method
56
Comparison of precision and accuracy using internal
standard and sample addition method
56
Concentration recovered from ten different types of spiked
samples
58
4.6
Evaluation of specificity for the targeted analytes
59
4.7
Concentration of analytes and number of replicates used for
determination of LOD and LOQ
59
Data obtained for each test compound based on signal-tonoise approach
60
4.2
4.3
4.4
4.5
4.8
xiv
The mean concentration and standard deviation of blank
obtained using blank determination approach
61
Parameters of linear ordinary least-squares regression for the
five test compounds at seven different levels of
concentration
62
Results of the statistical evaluation of the linear regression
curve
63
4.12
Summary of estimated LOD by different approaches
64
4.13
Summary of estimated LOQ by different approaches
64
4.14
Check for predetermined LOQ of 0.2 µg/mL
65
4.15
Check for predetermined LOQ of 0.4 µg/mL
66
4.16
Results of regression test and lack-of-fit test
69
4.17
Summary of findings of linearity tests for the five analytes
70
4.18
% recovery of the analytes at different spiking levels: (a) 10
mg/kg; (b) 200 mg/kg; and (c) 400 mg/kg
71
4.19
Intra-day and inter-day precisions for the five analytes
73
4.20
Precision of method based on different sample matrices
74
4.21
Categories of PS samples and number of replicates used for
the analysis
75
Concentrations of the five analytes found in different PS
samples
76
Concentration of ethylbenzene and styrene in control
samples
77
4.24
Concentration of ethylbenzene and styrene in samples
78
4.25
Estimation of ethylbenzene and styrene migrated from
polystyrene cup using dissolution method
80
Data obtained for each test compound based on signal-tonoise approach
92
Results for regression test and lack-of-fit test
95
4.9
4.10
4.11
4.22
4.23
5.1
5.2
xv
5.3
Summary of findings for linearity testing using HS-SPME
95
5.4
Three different concentration levels applied for precision
testing
95
5.5
Intra-day and inter-day precision for migration test method
96
5.6
Evaluation of method accuracy by extraction recovery, p=3
97
5.7
Mean concentration of analytes migrated from samples into
water solution
99
xvi
LIST OF FIGURES
FIGURE NO.
TITLE
PAGE
2.1
Structure of styrene
7
3.1
Polystyrene cup with 1 cm rim mark
40
4.1
Resin identification code for styrene
49
4.2
FTIR spectra of (a) reference styrene; (b) PS bowl; and
(c) PS container
51
Comparison of the analyte response using different sample
extraction techniques, p=6
52
GC-FID separation of analytes at 10 µg/mL on a DBWAX column, 30 m, 0.25 mm I.D., 0.25 µm film
thickness. GC conditions as described in 3.6.3. Peaks: 1
= Toluene; 2 = Ethylbenzene; 3 = iso-Propylbenzene; 4 =
n-Propylbenzene; 5 = Styrene and 6 = 1,4-Diethylbenzene
(ISTD)
54
GC chromatogram of an expanded polystyrene cup by
using GC conditions as described in 3.6.3. Peaks: 1 =
Ethylbenzene; 2 = Styrene and 3 = 1,4-Diethylbenzene
(ISTD)
54
Residual plots for (a) Styrene; (b) Toluene; (c)
Ethylbenzene; (d) iso-Propylbenzene and (e) nPropylbenzene with limits ±t(0.05, np-2).Sres
68
Mean recovery of the analytes based on different
concentration levels of spiking
72
GC chromatogram of analyte mixture using HS-SPME
method. Peak: 1 = Toluene (45 ppb); 2 = Ethylbenzene
(15 ppb); 3 = iso-Propylbenzene (5 ppb); 4 = nPropylbenzene (5 ppb); 5 = Styrene (10 ppb); and 6 = 1,4diethylbenzene (ISTD, 5 ppb)
82
4.3
4.4
4.5
4.6
4.7
5.1
xvii
Effect of sample volume on extraction efficiency of
analytes
84
5.3
Studies of elutropic strength effect on the targeted analytes
85
5.4
Effect of extraction temperature on analyte extraction
efficiency
86
5.5
Extraction time profile for the five analytes
87
5.6
Desorption time profile for the five analytes
88
5.7
Effect of sample agitation rate on the extraction efficiency
of analytes
90
5.8
Salting out effect on the five analytes
91
5.9
Residual plot of the targeted analytes (a) Toluene; (b)
Ethylbenzene; (c) iso-Propylbenzene ; (d) nPropylbenzene; and (e) Styrene with limits ±t(0.05, np2).Sres
94
GC chromatogram showing the analytes migrated from a
polystyrene cup. Peaks: 1 = Ethylbenzene; 2 = Styrene;
and 3 = 1,4-diethylbenzene (ISTD)
98
5.2
5.10
xviii
LIST OF SYMBOLS/ABBREVIAITIONS/NOTATION/TERMINOLOGY
a
–
Intercept of regression line
ABS
–
Acrylonitrile butadiene styrene
ATR
–
Attenuated total reflection
b
–
Slope of regression line
BTEX
–
Benzene, toluene, ethylbenzene and xylene
C
–
Capacity
CE
–
Capillary electrophoresis
CFR
–
Code of Federal Regulations
CS2
–
Carbon Disulphide
CW
–
Carbowax
CW-TPR –
Carbowax – templated resin
DCM
–
Dichloromethane
DMA
–
Dimethylacetamide
DMF
–
Dimethylformamide
DNA
–
Deoxyribonucleic acid
DVB
–
Divinylbenzene
EB
–
Ethylbenzene
EC
–
European Commission
EPS
–
Expanded polystyrene
FDA
–
Food and Drug Administration
FT-IR
–
Fourier transform infrared spectroscopy
GC
–
Gas chromatography
GC-FID
–
Gas chromatography - flame ionization detection
GC-MS
–
Gas chromatography – mass spectrometry
GPPS
–
General purpose grade polystyrene
GRP
–
Glass reinforced plastic
HIPS
–
High impact grade polystyrene
xix
HPLC
–
High performance liquid chromatography
HS-SPME –
Headspace solid-phase microextraction
IARC
–
International Agency on Research for cancer
ICH
–
International Conference on Harmonization
I.D.
–
Internal diameter
IPB
–
iso-Propylbenzene
ISTD
–
Internal standard
IUPAC
–
International Union of Pure and Applied Chemistry
JHOSPA –
Japan Hygienic Olefin and Styrene Plastics Association
KCl
–
Potassium chloride
LC-MS
–
Liquid chromatography - mass spectrometry
LLE
–
Liquid-liquid extraction
LOD
–
Limit of detection
LOQ
–
Limit of quantification
MAE
–
Microwave-assisted extraction
MEK
–
Methyl ethyl ketone
n
–
Number of samples or levels of standard solutions
NPB
–
n-Propylbenzene
OML
–
Overall migration limit
OLS
–
Ordinary least square regression
p
–
Number of replicates
PA
–
Polyacrylate
PAHs
–
Polycyclic aromatic compounds
PDMS
–
Polydimethylsiloxane
ppb
–
Part per billion
ppm
–
Part per million
ppt
–
Part per trillion
PS
–
Polystyrene
PTFE
–
Polytetrafluoroethylene
PVC
–
Polyvinyl chloride
QC
–
Quality control
r
–
Repeatability
RSD
–
Relative standard deviation
RT
–
Retention time
xx
SA
–
Standard addition
SAN
–
Styrene acrylonitrile
Sb
–
Standard deviation of blank
Sres
–
Standard deviation of y-residuals
Sy0
–
Standard deviation of y-intercepts
SBR
–
Styrene butadiene rubber
SFE
–
Supercritical fluid extraction
SML
–
Specific migration limit
S/N
–
Signal-to-noise ratio
SPE
–
Solid-phase extraction
SPME
–
Solid-phase micorextraction
UV
–
Ultra violet
VOCs
–
Volatile organic compounds
xxi
LIST OF APPENDICES
APPENDIX
A
TITLE
Presentations and Publications
PAGE
115
CHAPTER 1
INTRODUCTION
1.1
Food Packaging
Food packaging plays an important role to promote safe transportation,
delivery and storage of food. Packaging makes food more convenient and gives the
food greater safety assurance from microorganisms, biological and chemical changes
such that the expensive and time consuming packaged foods can enjoy a longer shelf
life [1]. In this modern society, packaging materials are also used for food
preparation, and packaged foods are placed in ovens, microwaves, and even in
boiling water. As a result, packaging becomes an indispensable element in the food
sector.
With the advances in technology, various new packaging materials have been
developed for food packaging applications. Plastic packaging technologies have
been developing vigorously and some plastic containers have actually succeeded in
replacing metal, glass and paper in many applications [2]. The main advantage in
using plastics for packaging purposes is that most of the polymers have excellent
physical properties such as strength and toughness, low weight and flexibility, as
well as resistance to cracking [3].
The polymers used for plastic packaging materials are generally considered to
be inert; however a large number of chemical adjuncts may be present in the finished
products.
These substances either added deliberately during manufacturing and
processing or, unavoidably, as residues from polymerization reactions. The
2
chemicals added include plasticizers, antioxidants, release compounds, heat and light
stabilizers, lubricants, antistatic chemicals, adhesives, pigments, and many other
compounds.
The addition of such substances is essential to assist production
processes or to enhance the properties and stability of the final product [3].
However, the use of such a wide range of chemicals inevitably gives rise to concern
amongst both legislators and consumers. The problem was of particular concern
since packaging can involve a long and intimate contact between the food and its
container during storage at wholesale, retail outlets, and in the home.
1.2
Research Background
Among the major polymers used in food packaging, polystyrene (PS) has
made up a large volume of the consumption of plastic containers. It is widely used
as food service packaging because of its extremely strong yet lightweight, provides
excellent insulation, and less expensive than many other food service packaging
options. It is used for disposable cutlery, meat trays, yoghurt containers, clear eggs
cartons, lids, vending cups and others.
With the increasing popularity of
convenience foods, polystyrene is most commonly used for packing of take-away
foods in some fast-food joints, hawkers and food court outlets.
The usage conditions of polystyrene food packaging range from low
temperatures for periods of days or weeks, for example packaged dairy and meat
products, to high temperatures approaching the boiling point of water for short
periods of time, for example vending cups and instant noodle bowls. The low
molecular weight constituents present in the polystyrene plastic have the potential to
migrate into the foodstuff in contact with the plastic especially during extended
periods of time, or at the elevated temperatures. The principal classes of substances,
which can migrate from polystyrene plastics to foods and beverages, are: residual
monomers, low molecular weight components (oligomers) and various additives.
Substances migrating to foodstuffs are of concern if they present a possible health
3
hazard to the consumer, or cause unacceptable changes to the organoleptic properties
of the food or beverages.
In Malaysia, food packaging is widely used due to the changing of food
consumption patterns and increasing preferences for convenience and fast food.
There is still lacking of controlling and monitoring of chemical residues in food
packaging available in the market or food service establishment as well as regulatory
compliance by packaging industries. Therefore, it is necessary to develop reliable
and efficient method for testing of chemicals in food packaging materials in order to
provide assurance to consumers about the safety of the product.
1.3
Statement of Hypothesis
The most tedious, labour intensive and important task encountered in the
analytical laboratory is the sample preparation.
Techniques to improve sample
preparations are necessary in order to isolate the components of interest from the
matrix prior to separation, identification and quantification. In the case of food
packaging, the complexity and diversity of contaminants present in food packaging
materials have resulted in the development of various analytical techniques for their
extraction and analysis including microwave-assisted extraction (MAE), supercritical
fluid extraction (SFE) and others.
Numerous studies have focused on styrene
monomer in polystyrene resins or specific foods and its migration to food or food
simulants. However, only limited information is available on other volatile organic
compounds (VOCs) in polystyrene food packaging and their migration. Based on the
existing techniques available, it is expected that a simple, fast, reproducible and
efficient analytical method could be developed for the determination of styrene and
other volatile organic compounds simultaneously in polystyrene food packaging, and
also their migration into food simulant.
4
1.4
Research Aim
The aim of this study is to develop a gas chromatographic method to
determine residual styrene and other VOCs including toluene, ethylbenzene, isopropylbenzene and n-propylbenzene in polystyrene food packaging and to study their
migration into food simulant.
1.5
Research Objectives
The objectives of this research are as follows:
(i)
To develop a simple extraction technique for residual styrene and other VOCs
in polystyrene food packaging.
(ii)
To apply solid-phase microextraction (SPME) technique to determine
migration of styrene and other VOCs from polystyrene packaging into food
simulant (water).
(iii)
To study the performance characteristics of the developed method.
(iv)
To apply the developed method for the determination of styrene and other
VOCs in polystyrene food packaging samples and their migration into food
simulant.
1.6
Scope of Study
The scope of research covers method development, method validation and
applicability of method for sample testing. Analytes of interest were styrene and
four other VOCs, namely toluene, ethylbenzene, iso-propylbenzene and npropylbenzene. Method development includes material test and migration test of the
analytes for polystyrene food packaging. In the case of material test, the analytes
were extracted using dissolution method and detection using gas chromatography
(GC). SPME with GC was used for migration study and water was chosen as food
5
simulant. Experimental SPME conditions, which include sample volume, absorption
and desorption time, temperature, stirring speed and ionic strength were optimized.
Quantification of the analytes were achieved by internal standard calibration using
1,4-diethylbenzene as internal standard. The developed method was evaluated with
different performance characteristics including limit of detection (LOD), limit of
quantification (LOQ), linearity, precision and accuracy. The method was applied to
the analysis of various kinds of commercially available polystyrene food packaging.
1.7
Outline of the Thesis
This thesis consists of six chapters. Chapter 1 introduces the research
background, research aim, research objectives and scope of this study. Chapter 2
compiles the literature reviews including general information regarding styrene, its
application in food packaging, and testing and legislation control of food packaging.
Chapter 3 describes the experimental set up and the procedures applied in this study
for testing of food packaging. Chapter 4 explains the development, validation and
application of the method for determination of VOCs in polystyrene food packaging.
Chapter 5 reports and discusses the results of SPME application to study the
migration of VOCs from polystyrene food packaging into water as food simulant.
The final chapter concludes the findings of this study and suggests areas for further
research.
6
CHAPTER 2
LITERATURE REVIEW
2.1
Styrene
Styrene is a petroleum by-product and monomer used in the manufacture of
numerous types of plastics. Styrene was first extracted by Bonastre in 1831 by
distilling storax balsam [4]. Storax balsam is naturally exuded from the storax tree
called Liquidambar orientalis. A synthetic styrene was first prepared by Berthelot in
1869 but no commercial application were attempted for many years because the
polymers was brittle and cracked easily. The styrene polymer was first produced
commercially in 1930 in Germany and then in the United States in 1937 [5].
Production of styrene was greatly increased in both Germany and United States
during the Second World War, particularly for the manufacture of synthetic rubbers
based on styrene-butadiene copolymers. After the Second World War, styrene has
been employed extensively in the production of plastics for a wide range of
applications including use as food packaging materials [2].
2.2
Physical and Chemical Properties
Styrene is a colourless, viscous liquid with a distinctive and penetrating
odour. Styrene is polymerized very easily by heating. On exposure to light and air,
it slowly polymerizes and undergoes oxidation with the formation of peroxides. Its
molecular mass is 104.15 with a melting point of -30.6°C and boiling point of
145.2°C. It is slightly soluble in water (water solubility: 310 mg/L), soluble in
7
ethanol, ether, acetone and carbon disulfide, and very soluble in benzene and
petroleum ether [6].
Styrene belongs to aromatic hydrocarbon group and its molecular formula is
C8H8 and its chemical structure is shown in Figure 2.1.
Figure 2.1: Structure of styrene
2.3
Sources
Styrene occurs naturally as a degradation product in cinnamic acid-containing
plants, e.g. balsamic trees, and by-product of fungal and microbial metabolism [7].
Styrene can be found in air, water and soil. Styrene is quickly broken down in the
air, usually within 1-2 days. Styrene evaporates from shallow soils and surface
water. Styrene that remains in soil or water may be broken down by bacteria. Its
presence in air is principally due to emissions from industrial processes involving
styrene and its polymers and copolymers. Other sources of styrene in the
environment include automobile exhaust, cigarette smoke and other forms of
combustion and incineration of styrene polymers [8].
Styrene is manufactured commercially from ethylbenzene by means of
catalytic dehydrogenation. Styrene is produced with high purity usually in the range
of 99.7-99.9% [9].
catalyst
C6H5-CH2-CH3
ethylbenzene
C6H5-CH=CH2 + H2
styrene
hydrogen
8
2.4
Routes of Exposure
Human exposure to styrene is mainly from inhalation of air containing it.
Styrene is present in low concentrations in unpolluted rural areas. In polluted urban
air and within 1 km of styrene polymerization units, the concentration can be 20-30
µg/m3 with an estimated daily intake of 400 – 600 µg/person living in the area [9,10].
Occupational exposure to styrene occurs during monomer manufacture,
transportation, and polymerization. Styrene is absorbed through the skin and the
respiratory tract. Highest exposures have been measured in the reinforced plastic
industry [11,12].
Cigarette smoking and exposure to environmental tobacco smoke may be
important sources of styrene exposure. The styrene content of cigarette smoke has
been reported to be 18-48 µg/cigarette [8]. Study has shown that smoking making a
significant contribution of styrene in indoor air [6].
Styrene is not usually found in drinking water. When it is found in water, the
main source is usually traceable to an industrial source or to improper disposal. Soil
may become contaminated with styrene by spills, land filling with wastes, and
industrial discharges. Thus, styrene may leach into groundwater around hazardous
waste sites.
2.4.1
Styrene in Food
Styrene has been identified as a natural constituent in a wide variety of foods
and beverages. The formation of styrene in foods and beverages can occur in several
ways.
It can be formed by bacteria during the storage of grain or during the
fermentation of grapes [7]. It is possible that styrene can be formed during the
9
biodegradation of some flavorant molecules such as cinnamic acid, cinnamyl
benzoate and cinnamyl acetate which have similar structure to styrene [13].
Studies of styrene levels in several raw agricultural commodities reported that
cinnamon contained highest measured concentrations of styrene (169 -39,200 ng/g).
Styrene concentrations in beef samples ranged from 5.25 to 7.85 ng/g and in coffee
beans from 1.57 to 7.85 ng/g. Wheat, pecan, oats, strawberries, and peaches showed
styrene concentration less than 3 ng/g [13].
Styrene can be transferred to food from polystyrene packaging material.
Styrene was detected in various foods packed with styrene packaging materials and
the concentrations detected vary from ppb levels to ppm levels. Styrene has been
reported to convey disagreeable odours and taste at 0.2 – 0.5 mg/kg [10].
2.5
Uses of Styrene
Styrene is used to make a variety of styrene plastics, from expandable foam
to higher end engineering plastics. End uses of styrene include disposable food
service products, cabinets for electronics, compact disc holders, paper coatings, boat
hulls, and interior automotive components. In the construction industry, it is used to
produce pipe products, tanks, lighting fixture, insulation, and various corrosion
resistant and rubber products.
Styrene is used in the production of a number of polymers and copolymers
which have a wide range of food contact applications. The performance and price
factor of polystyrene makes it idle for using it as a packaging material. Packaging
materials need to prevent food from spoiling as well as protect it from damage during
transport, storage as well as through the process of sale, and all of this while
maintaining the strictest hygiene.
Polystyrene meets all these demands hence
making it a suitable material for packaging [17].
10
Basically, polystyrene polymer includes general-purpose grade polystyrene
(GPPS), expanded polystyrene (EPS), high impact grade polystyrene (HIPS) and
glass reinforced plastic (GRP).
2.5.1
General Purpose Grade Polystyrene (GPPS)
GPPS, also known as crystal polystyrene, has a transparent and clear
appearance. It is a hard polymer with good electrical properties, easy processing
characteristics and a high resistance to acids, alkalis and the lower alcohols.
However, it also possesses poor gas barrier properties, poor impact strength, and ease
of stress cracking. It is easy to process, and relatively inexpensive and is used in a
wide range of applications where toughness is of secondary importance, such as
plates, drinking goblets and dessert tubs [17,18,19].
2.5.2
Expandable Polystyrene (EPS)
Expandable polystyrene (EPS) is fabricated from polystyrene containing a
low boiling point hydrocarbon foaming agent such as pentane and a nucleating agent.
It is also known as foamed polystyrene.
EPS exhibits excellent resistance to
bacterial and mould growth and is virtually impervious to water, grease and oil. It is
also very light, non-abrasive and, because of its cellular structure, possesses excellent
cushioning properties and low thermal conductivity.
These various properties
combined with its low cost and ease of production have resulted in its extensively
used as cushioning packaging and food packaging such as food trays, containers, and
disposable beverage cups [20].
11
2.5.3
High Impact Grade Polystyrene (HIPS)
HIPS is manufactured with the incorporation of various rubbers such as
polybutadiene, styrene butadiene rubber to overcome the brittleness of the material.
The addition of rubber serves to prevent crack propagation and increases
extensibility although with some loss of transparency and tensile strength. HIPS has
found a wide application in the packaging of a large number of food commodities,
for example container for dairy products, tubs for a wide variety of foods and
vending cups [2,18].
2.5.4
Glass Reinforced Plastic (GRP)
Styrene is employed as a cross-linking agent with polyester resins to produce thermosetting, insoluble and infusible
products; these cross-linked resins are brittle and, in consequence, are almost always reinforced with glass-fibre.
GRP has very light weight, low corrosion characteristic and good strength; it
is used extensively in the fabrication of large bulk containers for both the
transportation and storage of a wide range of food stuffs [18].
2.5.5
Styrene Copolymers
Styrene is co-polymerized with other materials to make product such as
styrene butadiene rubber (SBR), acrylonitrile butadiene styrene plastics (ABS),
styrene acrylonitrile plastics (SAN) and others. These styrene co-polymers provide
more heat, chemical, and oil resistance than GPPS and HIPS, while also showing
improved stress cracking.
12
SAN is used for internal trays and fittings in refrigerators, household utensils
such as coffee percolators and for luncheon boxes. ABS is used in the fabrication of
tubs for soft margarine, also used in refrigerator linings, in kitchen appliances such as
food mixers and in the production of piping for use in the food industry [18].
2.6
Additives Used in Polystyrene Food Packaging
Polymer additives are used in plastic materials to improve its melting and
molding properties, and to enhance or improve specific resin characteristics.
Additives help to improve the strength, stability, chemical resistance and weathering
properties of plastic products. Common additives used in polystyrene food contact
materials include antioxidants, UV stabilizers, processing lubricants, antistatic
agents, flame retardants and colorants [21].
Additives are normally present in small quantities, and the concentration of
various additives added dependent upon their desired function. Their concentrations
are typically less than 1%, but may range from 0.1% to 10% for some flame
retardants [21]. Surface additives are attached to the exterior and are incompatible
with the polymer. Surface additives include mineral oils, waxes, esters and fatty
acids.
2.7
Health Effects
Various kinds of chemicals present in the production of styrene plastics.
These compounds such as residual monomer, low molecular weight components and
the various additives can migrate from polystyrene plastics to foods and beverages.
The main concern is that the migrated compounds may pose a potential threat to
human health.
13
2.7.1
Styrene and Its Metabolite
The acute toxicity of styrene has been well studied.
Styrene has been
described to cause subjective symptoms of irritation of the eyes, throat and
respiratory tract at approximate concentration of 10-100 ppm (43 – 426 mg/m3) or
higher [8,11]. Cases of styrene-induced asthma and contact dermatitis have also been
reported [11].
Styrene can act as a depressant on the central nervous system, causing
neurological impairment. A number of epidemiological studies have suggested that
styrene is associated with neuropsychological deficits, such as slowing of reaction
time and vestibulomotor dysfunction, at exposure levels of around or more than 50
ppm (210 mg/m3) [6,9,14].
Genotoxic effects have been observed in the blood cells of reinforced plastics
workers for various endpoints at styrene exposure levels of around 20 – 30 ppm (85 –
128 mg/m3) and above. DNA breakage has been observed at exposure below 10 ppm
[6,9].
Several epidemiological studies have suggested the workers exposed to
styrene in the reinforced plastics industry have increased risk of lymphatic and
haematopoietic tumors as increased with average intensity of exposure and time
since first exposure, however, they do not indicate an increase in risk with increasing
cumulative exposure to styrene [9,15].
Styrene was tested for carcinogenicity in mice and rats by oral administration
and in rats by inhalation exposure. Animal cancer studies have produced variable
results and provide limited evidence for carcinogenicity [6,11,15]. World Health
Organization’s International Agency for Research on Cancer (IARC) has classified
styrene as a Group 2B carcinogen that is possibly carcinogenic to humans [15].
14
Styrene-7,8-oxide is a reactive metabolite of styrene and shows positive
carcinogenic results in oral exposure bioassays. There is sufficient evidence in
experimental animals for the carcinogenicity of styrene-7,8-oxide, although
inadequate evidence in humans. Styrene oxide has been detected in workers exposed
to styrene [11,15]. IARC has classified styrene-7,8-oxide as a Group 2A carcinogen,
probably carcinogenic to humans [16].
2.7.2
Other Volatile Organic Compounds (VOCs)
Besides styrene monomer, other VOCs present in the plastic packaging could
have the potential health effects to human. Ethylbenzene is an important synthetic
chemical that is produced in large quantities as a precursor for styrene and
polystyrene. [20]. It is well absorbed from the skin, lungs and gastrointestinal tract
and an irritant of the eyes, skin and mucous membranes [77]. Ethylbenzene is a
known carcinogen based on animal studies but inadequate evidence in humans for its
carcinogenicity.
IARC classified ethylbenzene as a Group 2B carcinogen [77].
Toluene is a common organic reagent, used as a solvent for many applications in
packaging industries. Dizziness and intoxication were reported to workers exposed
to toluene at 40 ppm for 6 hours [78]. Toluene is a neurotoxin which is most
prominent in the central nervous system after acute and chronic exposure [79,80]. nPropylbenzene occurs as a natural constituent in petroleum, is used in the
manufacture of iso-propylbenzene and methylstyrene. iso-Propylbenzene is also
known as cumene, is a skin and eye irritant. It has a potent central nervous system
depressant action characterized by a slow induction period and long duration of
narcotic effects in animals [81]. Acute inhalation exposure to iso-propylbenzene
may
cause
headaches,
dizziness,
drowsiness,
slight
incoordination,
and
unconsciousness in humans [81]. Toluene, iso-propylbenzene and n-propylbenzene
are not classifiable in terms of human carcinogenicity due to inadequate evidence in
humans [82,83].
15
2.8
Chemical Residues in Food Packaging Materials
Many different plastics are used by the packaging industry and although the
polymers themselves are generally considered to be inert, all articles of plastics
packaging will contain a variety of low molecular weight components which might
have the potential to migrate into contacting foods and contaminate them, thus
possibly causing tainting or toxicological problems. The volatile organic compounds
(VOCs) produced in the extrusion-coating process can migrate from the packaging to
its content and modify its organoleptic properties [22]. The VOCs in packaging
materials are mostly produced by thermo oxidative degradation of polyolefin in the
extrusion coating process [23].
Numerous publications reported residual styrene present in polystyrene
pellets or resins [18,24,25] and commercial food packaging [18,26,27,28]. The
reported residual styrene concentrations in polystyrene or styrene copolymers are
generally within a range from 100 ppm to 3000 ppm [20]. Other VOCs such as
toluene, ethylbenzene and cumene were also detected in some polystyrene contact
materials [24,26,27]. The residual monomer and other VOCs can arise because of
incomplete removal during the devolatilisation process and also because of
breakdown of the polymer during processing. When polystyrene is heated to about
300oC, breakdown occurs and results substantially in monomeric styrene [19].
Studies on styrene migration from food contact materials into foods were
reported [18,26,30,31]. Most of the foods which had come into contact with styrene
polymers or copolymers were found to contain a measurable quantity of styrene from
5 ppb to 30 ppb with up to 50 ppb in few cases [32,33,34,35]. The levels of styrene
in food varied with the nature of the food, the level of residual styrene in the
packaging and the length and temperature of storage [18]. Higher levels of styrene
were generally found for products with high fat content or packed in small containers
[30].
16
Other VOCs present in the commercial polystyrene resins may vary
depending on the technical process used. Ito S. et al. [27] reported the volatile
substances (sum of toluene, ethylbenzene, iso-propylbenzene, n-propylbenzene and
styrene) in the range of 692 ppm to 861 ppm in polystyrene food contact plastic
wares. Kusch, P. and Knupp, G. [28,29]
also detected these VOCs in expanded
polystyrene using SPME technique with GC-MS.
2.9
Migration Studies
The migration of chemicals from polymer packaging materials into food
varies with the physical and chemical characteristics of the polymer and of the food,
the residual content of chemical in the polymer, the diffusion coefficient, the
diffusion distance, and the duration of the migration process [24,37]. Several studies
have shown that styrene and other VOCs migrated out into the contacting food.
Styrene was detected in food packed in styrene polymers such as milk and cream
product, nut product, oils and fats product [30,84]. Ethylbenzene was identified in
table-ready foods with an average content of 14.6 ppb with the highest level found in
margarine [85].
Ethylbenzene was also detected in eggs stored in polystyrene
package material at the concentrations from 4 ppb up to 28 ppb [86].
Fleming-
Jones, M.E. and Smith, R.E. [87] reported styrene, toluene, ethylbenzene, isopropylbenzene and n-propylbenzene were among the VOCs detected in 70 table
ready foods for a period of five years studies (1996 – 2000).
Due to the complexity of food composition, it is difficult to use foods
themselves for migration studies. In addition, foods may be stored for long periods
in contact with plastics, testing over equivalent periods of time are impractical.
Hence, accelerated tests by using food simulants at elevated temperatures are
employed to represent the extreme conditions of extraction encountered with the
different groups of foods [3]. The simulant selected must reflect the chemical and
physical properties of the food. Basically, the food simulants fall into four separate
classes as shown in Table 2.1 [3].
17
Table 2.1: Four common classes of food simulants [3]
Class
Food Simulant
Food Group
A
Distilled water
Foods with pH values of 4.5 and above
B
Dilute solutions of acids
Acidic foods with pH values less than 4.5
C
Ethanol/water mixtures
Alcoholic foods
D
Fatty food simulants
Fatty foods
(eg: n-heptane, diethylether,
ethanol, coconut oil, olive oil
etc)
The migration rate of styrene into water or fatty food simulants was found to
be directly proportional to the residual styrene concentration in polymers and to the
storage time [36]. Murphy et al. [37] reported the amount of styrene migrating from
both GPPS and HIPS polymers into cooking oil was proportional to the square root
of the time of exposure, and the total amount of styrene migrating was proportional
to the residual levels of styrene in the polymers. Similar findings were reported by
Lehr et al. [38] and Lickly et al. [17].
2.10
Legislation Control for Polystyrene Food Packaging
The purposes of establishing law and regulation regarding food contact
materials are to prevent the contamination of food by the packaging, to protect the
health of the consumer and to remove technical barriers to trade.
In Malaysia, Food contact materials are regulated under the Food Act 1983
and Food Regulations 1985 [39]. Part VI of the Food Regulations 1985 sets forth the
general requirement for the safe packaging of food, and prohibits food packaging
from rendering food imperious to human health or contributing to its deterioration.
The regulations also include maximum residue limit of lead, antimony, arsenic and
cadmium that migrated to the food. There are no specific regulation regarding
18
monomers used except for vinyl chloride monomer, and no provisions prescribe
those substances that may or may not be used in food packaging.
The regulatory systems for food contact materials may vary from country to
country. The following are brief descriptions of regulatory requirements for food
contact materials particularly for polystyrene in Europe, United States and Japan.
2.10.1 European Food Contact Regulations
In the European Community, food contact materials and articles are regulated
by three types of directives:
(i)
Framework regulation (EC) No 1935/2004 sets up general requirements for
all food contact materials [40].
(ii)
Specific directives cover single groups of materials and articles listed in the
Framework directive.
These specific directives currently cover three groups
of materials and articles: ceramics, regenerated cellulose film and plastics.
(iii)
Directives on individual substances or groups of substances used in the
manufacture of materials and articles intended for food contact.
Three
groups of substances are regulated individually in these directives, i.e. vinyl
chloride monomer in plastics, nitrosamines in rubber teats and soothers and
certain epoxy derivatives in plastics and coatings.
Plastic materials including styrene plastics are regulated by the Commission
Directive 2002/72/EC [41]. For styrene polymers, the migration of the finished
articles should not exceed the following limits:
(i)
an overall migration limit (OML) of 10 mg/dm2 of the article surface,
(ii)
an overall migration limit (OML) of 60 mg/kg of the constituents released
into foodstuffs for the following kinds of articles:
19
(a)
articles which are containers or are comparable to containers or which
can be filled, with a capacity of not less than 500 mL and not more than
10 L;
(b)
articles which can be filled and for which it is impracticable to estimate
the surface area in contact with foodstuff;
(c)
(iii)
caps, gaskets, stoppers or similar devices for sealing.
for high impact polystyrene, butadiene migration must be “nondetectable”(detection limit of method 0.02 mg/kg food) or alternatively,
residual butadiene content in the finished article must be less than 1 mg/kg.
For styrene monomer, no SML was established.
(iv)
certain additives used for manufacturing of styrene plastics, additionally
SML may be imposed and must comply with the applicable regulations.
To enforce overall and special migration limits, special directives set out
procedures for analyses as follows:
(i)
Council Directive 82/711/ EEC and its amendments – basic rules for
migration tests such as the conditions of contact (time, temperature and food
simulants) [42].
(ii)
Council Directive 85/572/EEC - provides a list of food simulants to be used
in migration tests for the various types of foodstuffs [43].
2.10.2 U.S. Food and Drug Administration (FDA) Regulations
Regulations for food contact materials are found in the Code of Federal
Regulations (CFR) Title 21- Food and Drugs under the following parts:
20
(i)
Part 177 – Indirect Food Additives: Polymers lists standards for polymers
acceptable for use in components of single and repeat use food contact
surfaces
(ii)
Part 178 – Indirect Food Additives: Adjuvant, production aids, and sanitizers
include standards for certain polymer additives.
Regulations for polystyrene and rubber-modified polystyrene are contained in
the Code of Federal Regulations (CFR) Title 21 Part 177.1640.
Polystyrene basic
polymers used for food contact materials shall contain not more than 1 weight
percent of total residual styrene monomer, and when used in contact with fatty foods,
such polystyrene basic polymers shall contain not more than 0.5 weight percent of
total residual styrene monomer. For rubber-modified polystyrene basic polymers,
shall contain not more than 0.5 weight percent of total residual styrene monomer
[44]. Certain additives used for polystyrene food contact material shall comply with
CFR Title 21 Part 178.
2.10.3 Japan Food Sanitation Law
The Japanese regulatory framework for food contact materials is based on the
1947 Food Sanitation Law [45]. Specific regulations also promulgated for 12 kinds
of plastic packaging materials including polystyrene. These regulations set forth
end-test specifications for the particular plastic resin; however, they do not list
permissible additives for use in manufacturing these resins.
Besides the mandatory specifications that exist under Japanese Law, there are
voluntary standards developed by various business groups in Japan. For example,
the Japan Hygienic Olefin and Styrene Plastics Association (JHOSPA) has
developed voluntary specifications for materials that are recognized as suitable for
use in food packaging, Japan Hygienic PVC Association has established voluntary
“positive lists” of materials that are appropriate for use in food-contact applications.
Japan Printing Ink Makers Association has established “negative lists” and identifies
21
materials or substances that are deemed unsuitable for use in the printing on food
packaging materials.
Besides Japan, countries like Taiwan [46] and Thailand [47] also contained
similar regulations regarding end test products for certain plastic materials. The end
test specifications for polystyrene food contact materials are shown in Table 2.2.
Table 2.2: Japanese specification for polystyrene food contact materials [45]:
(a) material test; and (b) migration test
(a) material test
Substances
Specification
Volatile substances
- not more than 5000 ppm
(sum of styrene, toluene, ethylbenzene,
- not more than 2000 ppm for polystyrene foam
iso-propylbenzene, and n-propylbenzene)
- not more than 1500 ppm for polystyrene plastic that contact
with milk, milk product and product of the like
- not more than 1000 ppm styrene and ethylbenzene
respectively
(b) migration test
Leaching solution
Migration condition
Specification
n-heptane
25°C / 1 h
- residue after evaporation : not more than 240 ppm
20% ethanol
60°C / 30 min
- residue after evaporation: not more than 30 ppm
water
60°C / 30 min
- residue after evaporation: not more than 30 ppm
2.11
Analytical Methodology
Analytical methods are important in studying the migration of packaging
components from the package or food contacting material into the food. They are
used by regulatory bodies to ensure public safety by monitoring foods for excessive
and potentially harmful levels of contaminants from packaging, and to ensure the
packaging industries comply with the regulatory requirements. Methodology is also
required to establish databases to evaluate changing residue levels as well as to
calculate dietary intakes [48].
22
2.11.1 Method Application in Food Packaging Analysis
Several methods for analysis of styrene and other VOCs in food packaging,
food simulants and in foods have been developed. Some methods were very simple
and easy to perform such as dissolution method and dissolution-precipitation method.
The polymer was dissolved in a suitable organic solvent such as dimethylformamide
(DMF) [18,29], dimethylacetamide (DMA) [18,49],
or dichloromethane (DCM)
[25,50]. An aliquot of the sample solution was directly injected into GC-FID using
suitable capillary column and temperature program.
In dissolution-precipitation
method, methanol was added to precipitate the polymer, and a small volume of the
supernatant was injected into GC.
Besides direct injection, the headspace technique could be applied [18,50,51].
The sample was put in a closed sealed vial with suitable solvent, and heated until the
plastic had fully dissolved and equilibrium had been reached, the headspace was
sampled manually or automatically and injected into GC-FID or GC-MS. The direct
injection technique did not require an equilibration step, thus shorten the analysis
time, however, the headspace technique was capable of achieving higher sensitivity
and better reproducibility [18].
Reversed-phase liquid chromatographic method had been reported for the
determination
of
styrene
in
food
contact
materials
[52],
however
gas
chromatographic method was the most widely used technique for the residual styrene
analysis in polymer or copolymer.
The method used for determination of styrene migrated into food simulants
depending on the types of simulants used. If organic solvent such as diluted ethanolwater was used, the simulant was normally directly injected into liquid
chromatograph with UV detecter [24,37,38] When aqueous simulant such as water,
3% acetic acid were used, organic solvent such as dichloromethane was used to
extract styrene and a portion of the organic layer was taken and injected into GC-FID
[53].
For cooking oil used as simulant, the styrene levels was determined by GC-
23
MS after purging the oil and trapping the analyte on activated charcoal. The analyte
was then further dissolved in carbon disulphide (CS2) and the supernatant was
injected into GC-MS [34,35]. To reduce the extraction procedure of the sample, GCMS coupled with headspace was used to determine the migration of styrene from
food packaging materials into food simulants as mentioned above [3,31,32,36].
For quantification of styrene in food, it was found that headspace GC-FID did
not have a sufficiently low limit of detection, and the styrene residue present in food
was normally at very low concentration. Thus it was necessary to preconcentrate the
styrene by distillation of an aqueous or methanolic slurry of the food, extracting the
distillate with hexane and injecting the extract into GC-FID.
The head-space
technique using GC-MS was preferred in which direct analysis of foods may be
formed in the selected ion mode [2,36,37,38], and this can achieve higher sensitivity
than using GC-FID.
For the above analysis, besides external standard calibration was used for
quantification, some chemicals such as deuterated styrene [36,49], m-xylene [54]
were also used as internal standard for determination of styrene monomer in food
contact materials, food simulants and foods.
2.12
Evaluation of Sample Preparation Techniques
In the last few decades, there have been major advances in the developments
in instrumental analysis. However, most analytical instruments cannot handle the
sample matrices directly. Sample preparation methods have often lagged behind.
Sample preparation, such as extraction, concentration and isolation of analytes,
greatly influences the reliable and accurate analysis of food.
The extraction of volatile compounds is usually carried out using either
headspace, or purge and trap techniques, while for a semi-volatile and non-volatile
compounds, liquid-liquid extraction (LLE) and solid-phase extraction (SPE) are
24
commonly used. Some classical extraction procedures such as Soxhlet extraction
and ultrasonic extraction are still being used. All these techniques are effective but
have limitations. Headspace analysis is largely confined to highly concentrated
samples and purge-and trap, although very sensitive, is expensive and prone to leaks,
sample carryover and contamination. LLE requires large volumes of high-purity
solvents and cannot be easily automated, SPE needs less solvent, but for trace
analysis, a large volume of sample is required and it is susceptible to high baseline
blanks, channeling, and if the sample contains particulate matter, plugging of the
sorbent beds [55]. Classical extraction procedures usually consist of many steps,
including purification of the extract, with consequent greater analyte losses and
longer sample preparation time.
Several new approaches for the extraction of organic analytes from different
matrices have been proposed, including supercritical fluid extraction (SFE),
microwave-assisted extraction (MAE) and others.
The use of these techniques
improved recoveries in the determination of most organic additives, as well as
permitted considerable reductions in solvent volume and extraction time. However,
these techniques require complicated and expensive equipment, the use of high flowrates that can sometimes be incompatible with on-line operation [56].
Several extraction techniques including Soxhlet, MAE, SFE, headspace
extraction and dissolution-precipitation techniques were evaluated and compared to
determine the residual styrene content in polystyrene granules. It was found that the
most efficient method was dissolution-precipitation method [50]. The dissolutionprecipitation method is based on solubility differences between the analyte(s) of
interest and the other components in the matrix. Variables to consider include the
rate of precipitate formation, co-precipitation of additional components and even post
precipitation. The solvents have been used for dissolution of polystyrene polymer
are methyl ethyl ketone (MEK), DMA, DMF, chloroform and DCM.
Re-
precipitation of polymer is usually carried out with ethanol or methanol.
The
resulting supernatant is then filtered or centrifuged to settle the low molecular weight
waxes [21].
consuming.
The dissolution-precipitation procedure is easy, although time-
25
The need of an efficient and fast extraction technique has give rise to the
development of solid-phase microextraction (SPME) technique. Nowadays, the most
recommended technique for the analysis of VOCs in liquid or solid samples is
SPME, as it is a simple technique for the direct analysis of samples without using
solvents.
2.13
Solid-phase Microextraction (SPME)
SPME was developed by Pawliszyn and co-workers in 1989; it is an excellent
alternative to the aforementioned techniques. The SPME device consists of a fused
silica fiber coated with a layer of an immobilized sorbent, typically 5-100 µm thick.
The analytes are adsorbed directly from an aqueous or gaseous phase onto a fused
silica fiber with a liquid-polymeric phase. The entire assembly is mounted in a
modified syringe needle which, after exposure to the sampling media, is inserted into
a heated injector, and the chemicals adsorbed on the polymeric film are thermally
desorbed and analyzed.
Hence, sampling, extraction and concentration are
accomplished in a single step [57].
2.13.1 SPME Sampling Techniques
Two basic types of sampling can be performed using SPME: direct
extraction, and headspace extraction (HS-SPME). In direct sampling, the fiber is
directly immersed in the liquid or gaseous sample, while in HS-SPME, the fiber is
suspended in the space above the sample. Direct extraction can be applied to the
analysis of gaseous and relatively clean liquid samples. HS-SPME is better for
analyzing dirtier liquid samples and can also be applied to solid samples. With
PDMS coating, the results for the most volatile compounds were better using the
extraction from headspace [58]. For HS-SPME, the fiber is placed in the vapor
phase of the liquid or solid sample and is not in contact with the sample, and
therefore has a longer lifetime. In the direct sampling mode, the fiber is directly
inserted into the sample; therefore its lifetime decreases [56].
26
2.13.2 Parameters which Affect the Absorption Process
SPME is an equilibrium process which involves the partition coefficient of
the analyte between the fiber coating and sample matrix. Thus, the optimization of
parameters is extremely important. Though full equilibrium is not necessary for high
accuracy and precision from SPME, consistent sampling parameters are essential.
2.13.2.1 Selection of Fiber Coatings
The choice of the most suitable coating is very important for achieving good
selectivity for the target analytes. A number of polymers are available commercially
as coatings for SPME fibers. Polydimethylsiloxane (PDMS) and polyacrylate (PA)
were the first coated fibers to be used for SPME. PDMS is apolar and presents a
high affinity for non-polar compounds such as BTEX compounds (benzene, toluene,
ethylbenzene and xylene), volatile organic compounds (VOCs) and some pesticides.
Polyacrylate is a more polar coating fiber and extracts more polar compounds such as
phenols and their derivatives and some pesticides. Coatings containing the more
porous and adsorbent materials, divinylbenzene (DVB), and carboxen blended in
PDMS or Carbowax (CW), have been introduced: PDMS-DVB, PDMS-carboxen
and CW-DVB. These fibers are more polar than PA and are suitable for extracting
more polar compounds such as alcohols and ethers. Moreover, carboxin-PDMS
fibers have a larger surface area and show great potential for extracting organic
compounds, such as VOCs with low molecular weight, from the air. The Carbowaxtemplated resin (CW-TPR), owing to the pore dimension in the coating, is designed
to reduce molecular weight discrimination between analytes which vary in chain
length. The development of new polymeric coatings will improve the selectivity and
sensitivity of SPME for different classes of analytes [58,59].
27
2.13.2.2 Time and Temperature of the Extraction Process
Since SPME is based on equilibrium distribution process, the maximum
amount of analyte will be extracted at the equilibrium time. Compounds with low
distribution constants have long equilibrium times, so an extraction time shorter than
the equilibrium time has to be selected.
The extraction temperature has two
opposing effects on the SPME process. An increase in temperature during extraction
enhances the diffusion of analytes towards the fiber.
However, this increase in
temperature reduces the distribution constant of the analytes because the absorption
step is an exothermic process [58].
2.13.2.3 pH Modification and Addition of Salt
The pH of the sample can be adjusted to values which enhance the presence
of neutral form in the extraction of acid and basic analytes such as phenols and
amines. The addition of a salt usually increases the ionic strength of the sample. This
reduces the solubility of analytes which are more easily retained. This effect is not
general and depends on the polarity of the analyte, the concentration of salt, and the
sample matrix. Sodium chloride, sodium hydrogencarbonate, potassium carbonate
and ammonium sulphate are generally used for this purpose [56].
2.13.2.4 Addition of Solvent
The presence of organic solvent in water samples usually reduces the amount
of analyte extracted. On the other hand, in soils and sludges, the addition of water or
organic solvent to the sample matrix helps to remove analytes from the matrix and to
enhance the diffusion of analytes from the sample towards the fiber coating.
28
2.13.2.5 Agitation of the Sample
Sample agitation enhances extraction and reduces extraction time, especially
for higher molecular weight analytes with high diffusion coefficients. However,
inconsistent stirring causes poor precision and is worse than no stirring [60].
Sonication promotes analyte adsorption, but can add heat to the sample.
2.13.2.6 Volume of the Sample
The sample volume is directly related to the sensitivity of the method. For
higher sensitivity from HS-SPME, the sample headspace should be as small as
possible in order to concentrate the analytes before they diffuse towards the fiber
coating [61]. The repeatability was found to be sample volume dependent, with
higher volume, relative standard deviation (RSD) values increased [62].
2.13.2.7 Matrix Effects
Many aspects involved in the matrix effect, namely ionic strength, percentage
of organic solvent in the sample, presence of compounds that can react with the
analtye. Organic matter such as humic and fulvic acids which are present in real
water samples can reduce the amount of analyte extracted, owing to the interaction
between dissolved organic matter and the analytes.
If under non-equilibrium
conditions, other parameters related to kinetic aspects such as viscosity differences
between calibrants and samples may also be involved in the matrix effect [63].
29
2.13.2.8 Derivatization
Derivatization may be used to enable very polar compounds to be extracted
using SPME. The derivatization agent may be added either in a matrix, or bonded to
the SPME fibre, where the analytes are adsorbed and derivatised simultaneously
[59].
2.13.3 Interfaces to Analytical Instrumentation
SPME can be coupled easily to gas chromatography (GC), GC-mass
spectrometry (GC-MS), high performance liquid chromatography (HPLC) or LC-MS
and also capillary electrophoresis (CE) [55,58,64,65]. Among the analytical
instruments mentioned, SPME-GC interface is most frequently used.
SPME can easily be coupled to GC because the injection port of the GC can
be used for the thermal desorption of analytes from the fiber. When the temperature
increases, the affinity of analytes towards the fiber is reduced and they are liberated.
Moreover, the flow of carrier gas within a GC injector also helps to remove the
analytes from the fiber and to transfer them into the gas chromatographic column.
Insert liners with low volumes are required to ensure rapid transfer of desorbed
analytes to the chromatographic column [88].
Desorption is usually achieved in less than two minutes for most compounds.
Thermal desorption in GC can be affected by several parameters such as the
temperature of the GC injector and the flow rate of the carrier gas that determines the
desorption time of the SPME process. In general, the injector temperature is set at
the maximum temperature for the stability of the fiber coating.
However, the
compounds with high molecular weight normally need higher desorption
temperatures than this. Consequently, these compounds can remain retained in the
fiber coating and appear in subsequent analyses (carry-over effect). High desorption
times can help to reduce this carry-over effect [58].
30
A wide range of applications has been developed for the determination of
environmental pollutants, e.g. pesticides and BTEX compounds by SPME-GC
coupling [64,66,76]. SPME-GC has been automated simply by using a modified
commercial autosampler.
2.13.4 SPME Applications
SPME has been used successfully to analyze environmental pollutants in a
variety of matrices such as soils or sludges, water, and air. A wide range of analytes
from volatile to non-volatile compounds has been determined by SPME. These
analytes
include
environmental
pollutants
such
as
pesticides,
phenols,
polychlorinated biphenyls, polycyclic aromatic compounds (PAHs) [55,64,66,67],
and to a lesser extent, inorganic compounds, for example its use for extracting
inorganic lead and lead tetraethyl from water [58,59]. SPME technique was also
used for toxicological and pharmacological analysis of body fluids and also for
extraction of flavors, off-flavors, pesticides and other contaminants from various
food samples such as vegetables and fruits, beverages, dairy products and meat
[68,69,70,71,72,73,74].
Recently, SPME technique has extended to testing of volatile compounds in
different packaging matrices.
These include testing of residual solvents and
monomers in polymers [75], odour-causing VOCs [23] and matrix effect in
packaging [63]. The major of the packaging materials studied were multilayer food
packaging consisted of cellulose, paper, polyethylene and aluminum, few cases
reported on polystyrene packaging.
31
2.13.5 Advantages of SPME
SPME offers numerous advantages over other sample preparation methods.
The technique is inexpensive, simple and portable; it can be easily automated for
increased sample throughput. SPME integrates sampling, extraction, concentration
and sample introduction into a single step, therefore it is fast and much less labor
intensive than conventional sample preparation techniques. The application of SPME
covers a wide range of matrices and analytes from volatile to non-volatile
compounds.
It has been used successfully to analyze gaseous, liquid and solid
samples [58]. Since the technique requires only small amounts of sample, it reduces
interfering background in some analyses such as pesticide analysis. It eliminates use
of organic solvents, thus reduce handling of organic solvents which may be harmful
to health and to the environment, decreases purchase and disposal costs of solvents.
The sensitivity of determination using SPME technique is very high, it can detect up
to ppt levels for some compounds, thus facilitating trace analysis [56].
The
simplicity of SPME technique is ideal for quick screening and field analyses [76].
32
CHAPTER 3
EXPERIMENTAL
3.1
Experimental Layout
The experimental work was divided into two parts based on the two different
types of testing and sample extraction techniques.
The first part describes the
determination of the analytes in polystyrene packaging material by using dissolution
extraction technique, and refers as material test in the following content. The second
part describes the migration of the analytes from polystyrene packaging material into
food simulant by using SPME extraction technique, and refers as migration test.
3.2
Analytes and Chemicals
The test compounds selected for this study were styrene and four other VOCs
namely toluene, ethylbenzene (EB), iso-propylbenzene (IPB) and n-propylbenzene
(NPB) as listed in Table 3.1. 1,4-diethylbenzene was used as internal standard
(ISTD) for calibration. Table 3.2 describes the chemicals required to perform the
material and migration tests. Deionized water was prepared using an aquaMAXultra water purification system (Younglin Instrument, Korea).
33
Table 3.1: Description of analytes and internal standard
Analyte (purity)
Formula
Styrene (99.9%)
C6H5CH=CH2
Molecular
weight
Structure
104
Sigma-Aldrich
(Germany)
92
Sigma-Aldrich
(Germany)
106
Sigma-Aldrich
(Germany)
120
Sigma-Aldrich
(Germany)
120
Kanto Chemical
(Japan)
134
Sigma-Aldrich
(Germany)
CH 2
Toluene (99.9%)
C6H5CH3
CH3
Ethylbenzene
(99.8%)
C6H5CH2CH3
iso-Propylbenzene
(99.9%)
C6H5CH(CH3)2
n-Propylbenzene
(99.9%)
C6H5CH2CH2CH3
1,4-diethylbenzene
(ISTD) (99.9%)
C6H4(CH2CH3)2
CH3
CH3
Brand
CH3
CH 3
H 3C
CH3
Table 3.2: Description of chemicals
Chemicals
Formula
Purity
Brand
Dichloromethane
CH2Cl2
Ultra Resi-analyzed
for organic residue
analysis
99.8%
J.T. Baker
(USA)
Methanol
CH3OH
HPLC grade
99.99%
Fisher
Scientific
(UK)
Potassium
chloride
KCl
Reagent grade
99.5%
Scharlau
Chemie
(Spain)
Grade
34
3.3
Instrumentation
Gas chromatographic analyses were performed with a Shimadzu (Kyoto,
Japan) GC-17A gas chromatograph equipped with flame-ionization detector (GCFID) and a Shimadzu AOC-20i autosampler. The chromatographic data were
analyzed and processed using a Shimadzu Class-VP 4.3 acquisition program. A
Nicolet 5700 (USA) Fourier transform infrared spectroscopy (FT-IR) equipped with
attenuated total reflection (ATR) was used to identify and confirm the type of
packaging materials. A Branson 2510E-MT brand ultrasonic bath from USA origin
was employed for sample agitation. The glass microsyringes from Halmiton (USA)
of various capacities ranged from 10 µL to 1000 µL were used for standard
preparation.
Waterbath and hot air oven (Memmert, Germany) were used for preparation
of sample for migration test. The SPME was performed manually with a SPME
holder and fiber assemblies from Supelco (Bellefonte, PA, USA), together with a
stirring hot plate from Brandstead, Thermolyne, USA. A laser thermometer (ST60
Pro Plus, Raytek Corporation, USA) was used to monitor the temperature of the
leaching solution.
3.4
Samples
The commercial polystyrene food packaging samples were obtained from
local hypermarkets. The samples were purchased as the products would normally be
sold, i.e. for packaged food products; the sample was in contact with its food content,
where as for cutlery wares, the sample taken was not in contact with the food
product.
35
3.5
Identification of Packaging materials
The sample was identified and confirmed to be polystyrene packaging
material by FT-IR prior to testing. The sample was directly placed on the ATR
window, and the sample was scanned from the range of 4000 cm-1 to 400 cm-1
wavelength. The IR spectra obtained for the sample was matched against the FT-IR
library (HR Hummel Polymer and Additives, Hummel Polymer Sample Library) to
confirm the type of polymer in the packaging material.
3.6
Material Test Procedure
3.6.1
Standard Preparation
Individual stock solution at 10,000 µg/mL was prepared by mass in
dichloromethane (DCM).
A secondary mix standard solution was prepared by
diluting the primary standard in DCM to give concentration of 1,000 µg/mL.
Stock solution of 1,4-diethylbenzene (ISTD) was prepared by dissolving the
standard in DCM at concentration of 10,000 µg/mL. A 100 µg/mL ISTD solution
was prepared by dilution of stock solution in DCM and this solution was used for
preparation of calibration standard and sample solution.
Calibration standard solutions ranged from 0.4 µg/mL to 80 µg/mL were
prepared by diluting of secondary standard solution in DCM and adding 1 mL of 100
µg/mL ISTD solution (equivalent to 10 µg/mL) to each level of standard solution.
36
3.6.2
Sample Preparation - Dissolution Technique
3.6.2.1 Material Test
Sample was cut into small pieces and about 0.5 g of each sample was used for
testing. The exact weight of each sample was recorded. The sample was then put in
10 mL graduated glass tube and DCM (~8 mL) was added for dissolving the
polymer. The solution was shaken and sonicated by using sonicator for 5 min to
speed up the dissolution process. At this stage, it was necessary to wait until the
sample was totally dissolved. After complete dissolution, 1 mL of 100 µg/mL ISTD
was added to each sample and make up to final volume of 10 mL with DCM. The
solution was vigorously shaken for few seconds and transferred to a 2 mL GC vial
for instrument analysis.
3.6.2.2 Migration test
Study on the migration of the analytes from polystyrene cups into water as
food simulant was performed based on exposing the test sample and control sample
to water at different storage conditions (Table 3.3). The samples were extracted by
dissolution technique using DCM and quantification of the analytes was carried out
for both test sample and control sample. It was assumed that the difference in
concentration of the analyte in control sample and test sample was due to the
migration of the analyte to the food simulant.
37
Table 3.3: Migration conditions used for testing of polystyrene cups
Test
1
2
3
4
3.6.3
Sample
(n = 3)
Control A
Leaching solution
Replicate, p
Water, 25oC
Holding Condition
(±1oC)
25oC, 30 min
Sample A
Water, 40oC
40oC, 30 min
3
Control B
Water, 25oC
25oC, 30 min
3
Sample B
Water, 60oC
60oC, 30 min
3
o
o
3
Control C
Water, 25 C
25 C, 30 min
3
Sample C
Water, 80oC
80oC, 30 min
3
Control D
Water, 25oC
25oC, 30 min
3
Sample D
Water, 90oC
90oC, 30 min
3
Gas Chromatographic Conditions
Gas chromatographic analyses were performed with GC-FID as mentioned in
3.3. The GC-FID system was equipped with a DB-WAX capillary column (30 m;
0.25 mm I.D. with 0.25 µm film thickness). The injector and detector temperatures
were 220°C and 260°C respectively. The column temperature was kept at 40°C for
3 min, then increased at 10°C/min to 120°C and further increased to 250°C at
40°C/min; the temperature was held at 250°C for 5 min. The carrier gas was helium
of purity of 99.99%, further purified by passing through a gas purifier containing
molecular sieve 5A and an oxygen-adsorbing gas purifier (Chromatography Research
Supplies, Inc., USA). The inlet was operated in split mode with a split ratio of 10:1,
and split flow of 10 mL/min.
3.6.4
Analysis and Quantification
Extracts of polystyrene samples from 3.6.2 were placed in the auto-sampler
compartment and 1 µL of the extract was injected directly into GC via auto injector.
Test compounds were identified by comparison of their retention times (RT) with
those of standard compounds. Quantitative determination involved the use of 5 point
38
internal standard calibration curves, and standards ranged from 0.4 µg/mL to 80
µg/mL. Calibration curve was generated graphically by plotting peak area ratio
(analyte peak area/ISTD peak area) against the concentration ratio (analyte
concentration/ ISTD concentration) using Shimadzu Class-VP 4.3 acquisition
program. A new calibration curve was generated for every batch of sample analysis.
Based on the calibration curve, the analyte concentration (µg/mL) was
obtained. Therefore, the actual concentration of the analyte in the test sample (µg/g)
was calculated using the formula below:
analyte conc. in sample ( μg / g ) =
3.6.5
conc. ( μg / mL)
× sample volume (mL)
sample weight ( g )
Quality Control Measures
Quality control measures were carried out for every batch of samples
analyzed.
The control measures included equipment performance checks and
extraction recovery.
For every batch of sample, a reagent blank was prepared and
analyzed together with the samples to ensure there was no contamination from
reagent and glassware used. An independent mix standard solution at 10 µg/mL
were prepared and treated as QC sample. The QC sample was injected at the
beginning and end of every batch run, and the difference in retention time and peak
area of the analyte between the two runs was calculated. The performance of GCFID was considered acceptable if the retention time shift was less than 5% and the
peak area difference was less than 20%.
Extraction recovery was performed by
spiking the sample with 1 mL of 100 µg/mL mix standard solution before proceed
with sample extraction. A spiked sample was analyzed with every batch of samples.
39
3.7
HS-SPME Method
3.7.1
Standard Preparation
Stock solution of each test compound was made in methanol and standard
solution was prepared by diluting of the stock solution in methanol. Stock solution
and intermediate solution of 1,4-diethylbenzene (ISTD) was prepared similarly as the
test compounds. Table 3.4 shows the concentration of each test compound and ISTD
for stock and secondary standard solutions.
The calibration standard was prepared
by spiking 10 mL of purified deionized water with 10 µL of different amounts of the
secondary standard and ISTD; these solutions were used for calibration.
Table 3.4: Preparation of calibration standard for migration test
Test compound
Level 1
Level 2
Level 3
Styrene
Stock
solution
(µg /mL)
200
1.0
5.0
15.0
Toluene
900
4.5
22.5
67.5
Ethylbenzene
300
1.5
7.5
22.5
iso-Propylbenzene
100
0.5
2.5
7.5
n-Propylbenzene
100
0.5
2.5
7.5
1,4-diethylbenzene
(ISTD)
200
5.0
5.0
5.0
3.7.2
Secondary Standard Solution (ng/mL)
Food Simulant and Leaching Conditions
Water was chosen as food simulant or leaching solution to represent food
group with pH of 4.5 and above. The leaching solution was prepared by heating the
purified deionized water using waterbath to the temperature required for the
migration study.
40
Migration test was performed at three different temperatures, i.e. 24°C
(laboratory room temperature), 60°C and 80°C and the incubation time was 30 min.
The hot air oven was used to maintain the temperature at 60°C and 80°C. The
leaching condition used was either at room temperature for 30 min, or maintained at
the temperature of the leaching solution used and held for 30 min.
3.7.3
Sample Preparation
The capacity of each sample (C) was determined by filling the test specimen
with water up to 1 cm rim mark from the top of each sample as shown in the Fig. 3.1.
The water was then transferred to measuring cylinder to obtain the capacity of each
test specimen.
1cm
Fig. 3.1: Polystyrene cup with 1 cm rim mark
The sample was filled with the leaching solution according to the measured
capacity (C) of each sample and kept at two different conditions as described in
3.7.2. After exposing the sample to the leaching conditions for 30 min, the leaching
solution was immediately transferred to glass bottle and capped. The test solution
was kept in the chiller for 15 min to cool down, followed by leaving at room
temperature until it reached 24°C. 10 mL of the test solution was dispensed using
glass pipette into a 22 mL head space vial for SPME extraction.
41
3.7.4
HS-SPME Extraction
The analytes were extracted with HS-SPME technique using a 100 µm
PDMS fiber and 22 mL head space vials.
The new fiber was conditioned at the
injection port at 250°C for 30 min. An aliquot of 10 mL of test solution obtained
from section 3.7.3 was placed in a 22 mL vial and 10 µL of 5 µg/mL ISTD was
added to the vial. After placing a 0.8 cm long stir bar in the vial, it was sealed with a
headspace cap with a PTFE-faced septum. The vial was shaking vigorously for few
seconds and left at room temperature for 5 min. After 5 min pre-incubation, the fiber
was inserted into the centre of the vial and placed about 2 mm above the water
sample. The extraction time was 5 min with constant stirring at 800 rpm to speed up
equilibrium process. Once extraction time was completed, the fiber was immediately
retracted into the protective sheath, removed from the vial, and transferred into the
injector of the gas chromatograph for thermal desorption.
3.7.5
Instrumental Conditions
The injector port of GC was equipped with an insert of 0.8 mm I.D. for
SPME analysis. The instrument parameters set up were the same as the material test
described in section 3.6.3 with the exception that the injector was programmed to
split mode 0.5 min after starting the analysis run, and the holding time of the final
temperature of the column oven at 250°C was shortened to 2 min.
3.7.6
Analysis and Quantification
The fiber was thermally desorbed in the injector at 220°C for 3 min and the
analysis was started. The analytes were separated by the capillary column, and
identified by FID. The calibration was performed by internal standard method using
three levels calibration curve. The fiber blank was performed at the beginning and
end of each batch run to ensure there was no memory effect.
42
3.7.7
Optimisation of SPME Parameters
The sample volume, elutropic strength, extraction temperature and time,
stirring rate, salting out effect and desorption time were studied in order to get the
optimum conditions that would have the best extraction efficiency.
Table 3.5
describes the range of variables that were evaluated for different SPME parameters.
Table 3.5: Evaluation of SPME parameters
SPME parameters
Variables
Range
Sample volume
volume (mL)
5, 10, 15
Elutropic strength
methanol (%)
0.1, 0.5, 1, 5, 15
Extraction
temperature (°C)
24, 40, 60, 80
Extraction
time (min)
1, 5 , 15, 30, 35, 45
Salting out effect
addition of KCl
with 30% KCl or without KCl
Sample agitation
stirring rate (RPM)
0, 200, 400, 600, 800, 1000
Desorption
time (min)
1, 3, 5
3.8
Method Validation
Several performance characteristics were evaluated to demonstrate the
suitability of the method for the analytical task, and ensure that accurate and
consistent analytical data can be obtained with validated methods.
3.8.1
Specificity
This test is based on standard additions of the compound of interest. The
concentrations of the compounds added should cover the scope of the method. One
standard addition is made for each sample and the spiked concentration covered the
expected contents of the sample and other different concentrations within the scope
of the method.
43
The specificity is verified by adjusting a straight line between added
concentration (v) and recovered (r) concentrations in the form of regression line:
r = a + bv
(3.1)
Two hypothesis tests are carried out to confirm specificity:
i.
t-test (t1) is used to test the hypothesis that the slope is significantly equally to
1.0.
t1 =
ii.
b −1
Sb
(3.2)
t-test (t2) is used to test the hypothesis that the intercept is significantly equal
to 0.0.
t2 =
a
Sa
(3.3)
The method is deemed to be specific if t1 and t2 values are lower than tcritical, bilateral[n2; 1%] , where n-2 is the degree of freedom (dof) and n is the total number of
samples.
3.8.2
Limit of Detection (LOD) and Limit of Quantification (LOQ)
There are several approaches for assessing the LOD and LOQ.
Three
approaches namely signal-to-noise ratio, blank determination and linear regression
based on ICH and EURACHEM guidelines were evaluated for LOD and LOQ of the
material test. For migration test, signal-to-noise ratio was used to calculate LOD and
LOQ.
44
3.8.2.1 Signal-to-noise (S/N)
By using the signal-to-noise method, the peak-to-peak noise around the
analyte retention time is measured, and subsequently, the concentration of the analyte
that would yield a signal equal to certain value of noise-to-signal ratio is estimated.
In this study, the noise magnitude was measured by auto-integrator of the instrument.
A signal-to-noise ratio (S/N) of three was used for estimating LOD and signal-tonoise ratio of ten was used for estimating LOQ.
3.8.2.2 Blank Determination
LOD is expressed as the analyte concentration corresponding to the sample
blank value plus three standard deviations and LOQ is the analyte concentration
corresponding to the sample blank value plus ten standard deviations as shown in
equations below:
LOD ≅ xbi + 3S bi
(3.4)
LOQ ≅ xbi + 10S bi
(3.5)
where xbi is the mean concentration of the blank and S bi is the standard deviation of
the blank.
3.8.2.3 Linear Regression
For a linear calibration curve, it is assumed that the instrument response y is
linearly related to the standard concentration x for a limited range of concentration. It
can be expressed in a model such as:
y = a + bx
(3.6)
45
This model is used to compute the sensitivity b and the LOD and LOQ.
Therefore the LOD and LOQ can be expressed as:
LOD ≅
3S a
b
(3.7)
LOQ ≅
10 S a
b
(3.8)
where S a is the standard deviation of the response and b is the slope of the calibration
curve. The standard deviation of the response S a was estimated by the standard
deviation of both y-residuals, S res and y-intercepts, S y 0 of regression lines.
3.8.2.4 Checking a Predetermined Limit of Quantification (LOQ)
A check was introduced to ensure that the LOQ values obtained from the
three approaches were achievable practically. Independent standard solutions at the
LOQ level were analyzed 10 times on different days (p=10). The mean, xQL and
standard deviations, S QL of 10 measurements were calculated.
The following
conditions must be met in order for LOQ values to be considered acceptable.
(i)
the measured mean quantity
xQL must not be different from the
predetermined quantification limit LOQ:
if
LOQ − xQL
S QL
<10, then LOQ is considered to be valid.
n
NOTE: 10 is purely conventional value relating to the LOQ criterion.
46
(ii)
the LOQ must be other than 0:
if 5 S QL <LOQ, then the LOQ is other than 0.
NOTE: A value of 5 corresponds to an approximate value for the spread of the
standard deviation, taking into account risk α and risk ß to ensure that the
LOQ is other than 0. This is equivalent to checking that the coefficient of
variation for LOQ is lower than 20%.
3.8.3
Linearity Study
The approach used to evaluate linearity range was based on IUPAC
Guidelines. A series of calibration solutions was prepared in different concentration
levels. The standard solutions were prepared freshly each day and analyzed over a
period of days.
Data obtained was fitted with a simple ordinary least squares
regression (OLS) and slope (b), intercept (a), standard deviation of the slope (Sb),
determination coefficient (r2) were estimated using the function LINEST of
Microsoft Excel program. Once the parameters were estimated, the models must be
validated by means of the regression model test (Freg), lack-of-fit test (Flof) and
finally a significant test (t-test) to confirm whether the y-intercept passes through the
origin.
3.8.4
Accuracy
Since matrix blank was not available for this study, recovery studies were
used to evaluate the accuracy of the method applied. The sample was fortified with
three levels of standard solutions and analyzed together with the unfortified sample
in duplicate. The mean percentage recovery was calculated using the formula below:
% re cov ery =
(measured conc. in fortified sample − measured conc. in unfortified sample)
(known increment in conc.)
47
3.8.5
Precision
Precision was evaluated based on instrument precision and method precision.
3.8.5.1 Instrument Precision
Instrument precision is based on intra-day and inter-day repeatability. A
series of standard solution of different concentration levels was analyzed repeatedly
in the same day (intra-day) and on different day (inter-day). The precision was
expressed as relative standard deviation (RSD).
3.8.5.2 Method Precision
The precision of the method was determined based on the repeatability, r
obtained through duplicate analysis (p) of several samples (n) over a short period of
time. The following equations were used to calculate repeatability.
q
Sr =
∑w
i =1
2
i
2n
(3.9)
In which: Sr = the repeatability standard deviation
n = the number of test materials analyzed in duplicate
wi = the absolute differences between duplicates
Repeatability, r = 2.8S r
(3.10)
48
3.9
Data Analysis
Microsoft office excels (2003) spreadsheet was chosen to store, display raw
data and to perform statistical calculations with the built-in statistical functions.
49
CHAPTER 4
METHOD DEVELOPMENT IN THE DETERMINATION OF VOLATILE
ORGANIC COMPOUNDS IN POLYSTYRENE FOOD PACKAGING
BY DISSOLUTION METHOD
4.1
Identification of Packaging Materials
There are various kinds of packaging materials used for food applications. It
is difficult to differentiate the type of material based on the physical observation of
the packaging. In addition, not all commercially available food packages containing
specified resin identification code as indicated in Fig. 4.1. This code is usually
printed or embossed at the base of the polystyrene container or tray for recycling
purposes.
Fig. 4.1: Resin identification code for styrene
Fourier transform infrared spectroscopy (FT-IR) is a powerful tool to identify
the type of packaging material. With the complement of attenuated total reflection
(ATR) accessory, the sample preparation step has become very easy and simple. The
values and characteristic bands of the styrene polymer are listed in Table 4.1.
50
Table 4.1: Characteristic wave numbers obtained from polystyrene samples
Functional groups
Wavelength (cm-1)
=C-H
3024 – 3081
-CH2-
2919 – 2921
-CH-
2848 – 2850
C=C
1451; 1492; 1601
The peak in the region of 3024 – 3081 cm-1 is related to the stretching of the
aromatic CH bonds from the styrene sample. Peaks at 1451, 1492 and 1601 cm-1 are
for the C=C phenyl stretching. The peak in 2919 – 2921 cm-1 region is attributed to
the presence of CH2 bond, while peak in 2848 – 2850 cm-1 region is attributed to the
CH bond. The IR spectra of the samples were compared with the built-in spectra of
the FTIR library to confirm the styrene polymer present in the samples. The IR
spectra of selected food packaging samples and reference styrene (from FTIR
library) are shown in Fig. 4.2.
4.2
Material Test
Material test was used to determine the residual chemical substances present
in the finished food packaging product. In this study, five analytes were chosen
namely styrene, toluene, ethylbenzene, iso-propylbenzene and n-propylbenzene.
These compounds are regulated by some countries like Japan, Taiwan and Thailand
for polystyrene food packaging and permissible limit are controlled.
51
(a)
(b)
(c)
Figure 4.2: FTIR spectra of (a) reference styrene; (b) PS bowl; and (c) PS container
52
4.2.1
Sample Preparation
A review of the literature indicated that dissolution method was an effective
extraction method for determination of styrene monomer in food packaging. This
method was the simplest method as compared to other conventional sample
preparation methods for food packaging analysis.
Most of the researchers used
dissolution- precipitation technique for styrene study in which the polymer was reprecipitated with methanol after dissolution in solvent such as dimethylacetamide
(DMA), tetrahydrofuran (THF) or dichloromethane (DCM).
Based on the dissolution method, initial attempt was made to find a simplest
and effective way to isolate and determine styrene, toluene, ethylbenzene, isopropylbenzene and n-propylbenzene in polystyrene food packaging.
An expanded
polystyrene (EPS) bowl was selected for this study and the sample was extracted
using three different techniques. In the first technique (T1), the sample (0.5g) was
dissolved in 10 mL DCM until completely dissolved, and an aliquot was taken for
analysis. In the second technique (T2), after the sample was dissolved in DCM, 2
mL of methanol was added to re-precipitate the polymer and the clear layer of
aliquot was used for further analysis. In the last technique (T3), the same procedure
as T2 was used, but after addition of methanol, the sample was centrifuged at 1500
rpm for 5 min. The sample solutions obtained by using the three techniques were
analyzed by GC-FID in six replicates and the results are shown in Fig. 4.3.
peak area
(µV)
150000
100000
50000
0
Styrene
Toluene
Ethyl
benzene
T1
T2
iso-Propyl
benzene
n-Propyl
benzene
T3
Fig. 4.3: Comparison of the analyte response using different sample extraction
techniques, p = 6
53
The extraction efficiency for T1 was assumed 100%, and used as the basis for
calculating of the extraction efficiencies for T2 and T3 (Table 4.2). It was found that
relatively lower extraction efficiencies for T2 and T3 of all the analytes. This was
probably because some analytes were trapped in the polymer during re-precipitation
step. The centrifugation step in T3 further reduced the extraction efficiency as the
loss of analyte may occur during the transfer of sample solution from the glass tube
into the centrifuge tube.
Table 4.2: Comparison of the extraction efficiencies for different sample extraction
techniques
Analyte
Extraction efficiency
T1
T2
T3
Styrene
100
73
72
Toluene
100
64
59
Ethylbenzene
100
56
54
iso-Propylbenzene
100
54
53
n-Propylbenzene
100
84
77
In term of precision, the RSD values obtained based on the six replicates of
analysis showed that T2 and T3 produced better repeatability results as compared to
T1. The RSD values for T1 ranged from 2.71 to 14.25, T2 ranged from 1.43 to 7.77
and T3 ranged from 1.27 to 9.79, with the lowest RSD values for styrene and highest
RSD values for toluene. This showed that with the addition of the methanol, it
helped to precipitate the polymer and remove matrix interference during analysis,
thus, the precision was improved.
In order to compromise between the extraction efficiency and precision, it
was decided to use dissolution technique without re-precipitation for sample
extraction. This technique would reduce the use of additional solvent, shorter time of
sample preparation and better extraction efficiency with the precision within the
satisfactory range.
54
4.2.2
Chromatographic Conditions
GC parameters were optimized to obtain good separations between the
analytes with better sensitivity. The finalized GC conditions were described in
section 3.6.3. With the optimized GC parameters, the five analytes were separated
with well defined peaks as shown in Fig. 4.4. The order of elution for the five
analytes were toluene, ethylbenzene, iso-propylbenzene, n –propylbenzene, styrene
and finally 1,4-diethylbenzene (ISTD).
All analytes were eluted within 13 min and
the total time taken for each run was 19.25 min.
Fig. 4.5 shows an example of
chromatogram obtained from a polystyrene food packaging sample.
1
2
3
4
5
6
0
2.5
5
7.5
Time (minutes)
10
12.5
Fig. 4.4: GC-FID separation of analytes at 10 µg/mL on a DB-WAX column, 30 m,
0.25 mm I.D., 0.25 µm film thickness. GC conditions as described in section 3.6.3.
Peaks: 1 = Toluene; 2 = Ethylbenzene; 3 = iso-Propylbenzene; 4 = n-Propylbenzene;
5 = Styrene; and 6 = 1,4-Diethylbenzene (ISTD)
2
1
0
2.5
5
7.5
Time (minutes)
3
10
12.5
Fig. 4.5: GC chromatogram of an expanded polystyrene cup by using GC conditions
as described in section 3.6.3. Peaks: 1 = Ethylbenzene; 2 = Styrene and 3 = 1,4Diethylbenzene (ISTD)
55
After dissolution of sample in DCM, some sample solution was quite viscous,
therefore some preventive measures were taken to ensure good performance of the
GC, to prolong the shelf life of capillary column, and also to prevent matrix
interference occurred during identification and quantification of analytes using GCFID. The injector port was connected to one meter long pre-column (0.25 mm I.D.)
before joining with the capillary column. The injection plunger was programmed to
be rinsed with DCM five times in between injections. The septum and silica wools
were replaced; glass insert was cleaned with solvent after every 30 injections.
4.2.3
Quantification Method
Quantitative determination was carried out by the method of internal
standard. 1,4-diethylbenzene was used as internal standard as it behaved similarly
as the targeted analytes. As prerequisites, this compound was tested together with
the targeted analytes using the extraction and separation conditions as described in
sections 4.2.1 and 4.2.2, the internal standard was well separated from the five
analytes. Analysis of sample showed that there was no peak observed that has the
same retention time as ISTD suggesting that the internal standard was not present in
the sample.
For quantitative analysis of sample with complex matrices, standard addition
method is usually reported as a better quantification method to overcome matrix
interference. A comparison between internal standard (ISTD) method and standard
addition (SA) method was made by using different sample matrices. Ten samples of
polystyrene packaging consisting of plate, spoon, fork, cup and container were
analyzed in duplicate and quantified using both methods and the mean concentration
obtained for both methods was reported in Table 4.3. As some of the analytes such
as toluene, iso-propylbenzene and n-propylbenzene were not detected in the samples;
spiked samples were used to replace the actual samples.
56
Table 4.3: Mean concentration of analytes in samples obtained by internal standard
method and standard addition method
n
Mean concentration, mg/kg (p=2)
Styrene
Toluene
SA
Ethylbenzene
iso-Propylbenzene
n-Propylbenzene
ISTD
ISTD
ISTD
ISTD
SA
ISTD
SA
SA
SA
1
167.99
172.81
26.34*
37.51*
55.11
76.41
45.26*
55.02*
31.49*
44.43*
2
529.90
485.12
139.54*
128.80*
82.93
77.98
27.06*
23.91*
13.46
9.43
3
199.23
211.60
23.72
22.40
54.55
49.50
9.18
9.81
26.40*
26.71*
4
225.04
254.55
27.58
24.78
21.58*
20.04*
14.36
15.77
8.49
10.58
5
469.43
519.20
47.46
56.07
41.32
47.79
8.06
9.15
25.54*
22.49*
6
902.20
1024.53
32.97*
26.82*
119.73
119.93
30.47*
26.82*
28.80*
27.07*
7
302.93
273.42
20.37*
25.71*
14.72
23.05
21.65*
26.05*
21.50*
26.11*
8
560.72
615.75
19.56*
19.12*
33.68
35.36
9.37
10.00
23.83*
22.59*
9
1075.63
1206.38
17.66*
17.57*
247.14
275.04
35.50
31.34
26.03
20.80
10
757.64
746.93
20.75*
17.53*
61.11
58.82
14.23
17.55
24.11*
24.95*
* Spiked sample
To compare the accuracy and precision of using internal standard method and
standard addition method, statistical evaluation were applied and results are shown in
Table 4.4.
Table 4.4: Comparison of precision and accuracy by internal standard method and
sample addition method
Analyte
Internal Standard (x)
Sample Addition (z)
Sr
Sr
Sr
dm
Sd
22.99
528.58
Mean
conc.
553.60
Sr
Styrene
Mean
conc.
519.06
75.36
5679.05
-34.54
62.48
Zscore
0.55
Toluene
37.56
0.63
0.40
37.67
3.78
14.28
-0.11
6.67
0.02
Ethyl
benzene
73.20
1.46
2.14
69.15
47.94
2298.72
4.05
23.42
0.17
iso-Propyl
benzene
21.28
2.60
6.76
23.40
5.21
27.18
-2.12
3.67
0.58
n-Propyl
benzene
22.40
3.08
9.49
23.55
2.89
8.33
-1.31
4.92
0.27
2
Comparison
2
Mean conc. – mean concentration in mg/kg; Sr – repeatability standard deviation; Sr2 – repeatability
variance; dm – mean difference; Sd – standard deviation of the difference
57
Since the repeatability variance of the internal standard, S2r(x) was smaller
than the sample addition method, S2r(z) for styrene, toluene, ethylbenzene, and isopropylbenzene, it can be concluded that the precision of this internal standard method
is comparable to the standard addition method for the four analytes.
2
2
2
For n2
propylbenzene, S r(x) was greater than S r(z) and the variance ratio (S r(x)/ S r(z)) of
1.1393 was less than the critical value, F(10,10,5%) of 3.717. As the ratio was
below the threshold, it can be concluded that the precision of the internal standard
method is equivalent to the standard addition method.
The accuracy of the two methods were compared using the Z-score, as the Zscore values for all the analytes are below 2, it can be concluded that the accuracy of
the internal standard method was compatible with the standard addition method at
the risk level α=5%. Therefore, the internal standard was used as the quantification
method for this material test. By using the internal standard method, the effect of
small variations due to uncontrollable random errors can be corrected unlike the
external standard method, thus helps to improve the precision of the quantitative
analysis.
4.2.4
Method Validation
The optimized method was validated with the following performance
characteristics to ensure that the method is suitable to be used for sample testing with
reliable results. The performance characteristics are specificity, LOD and LOQ,
linearity test, accuracy and precision.
4.2.4.1 Specificity
The specificity of the method was evaluated to make sure that the method
developed was able to measure accurately and specifically the analyte of interest in
the presence of other components in the polystyrene packaging samples.
The
58
specificity test was based on standard addition method. Ten types of polystyrene
samples were tested and the concentration levels added ranged from 19.98 mg/kg to
999.50 mg/kg.
The amounts of analyte recovered from each sample based on the
concentration added are shown in Table 4.5.
Table 4.5: Concentration recovered from ten different types of spiked samples
Sample
Conc. of
analyte
added, ν
(mg/kg)
(n=10)
Concentration of analyte recovered, r (mg/kg)
Styrene
Toluene
Ethyl
benzene
iso-Propyl
benzene
n-Propyl
benzene
Ice cream
scoop
19.98
24.23
20.50
22.54
20.83
22.17
Sushi
container
19.99
26.86
18.47
20.93
18.52
19.25
Baby Plate
20.00
15.26
20.75
15.41
16.41
17.50
Plate
199.80
241.02
232.23
219.30
225.57
231.57
Measuring
spoon
200.00
212.23
188.01
187.47
183.49
192.87
Container
lip
399.52
382.21
373.65
380.71
386.93
392.42
Spoon
399.60
379.11
362.84
366.04
369.06
368.56
Fork
399.76
420.33
431.96
440.25
427.62
425.60
Ice cream
cup
400.00
351.97
362.77
357.17
358.54
377.05
EPS plate
999.50
1110.14
1118.73
1125.84
1122.85
1117.49
The model coefficients and their standard deviations were computed using
LINEST function of the EXCEL program as shown in Table. 4.6. Based on the
results (Table 4.6), the calculated values of t1 and t2 were less than 3.360, i.e. tcritical
[n-2; 1%], therefore the slope b and intercept a were statistically no different from
1.0 and 0.0 respectively, i.e., the overlap line r = a + bν was equivalent to the line y =
x. The method was considered to be specific for the five analytes to be tested.
59
Table 4.6: Evaluation of specificity for the targeted analytes
Statistics
Value
Styrene
Toluene
Slope, b
1.081
Slope std. dev. , Sb
Critical
value
1.095
Ethyl
benzene
1.105
iso-Propyl
benzene
1.103
n-Propyl
benzene
0.974
0.043
0.044
0.044
0.042
0.042
Intercept, a
-14.103
-21.790
-24.262
-24.215
4.688
Intercept std. dev., Sa
17.706
18.369
18.354
17.352
11.911
Number of
measurements, n
10
10
10
10
10
Degree of freedom,
dof = n-2
8
8
8
8
8
Test for slope, t1
1.886
2.138
2.365
2.452
0.621
3.360a
Test for intercept, t2
0.796
1.186
1.322
1.396
0.394
3.360a
1
0
a
tcritical [n-2, 1%]
4.2.4.2 LOD and LOQ
Three different approaches were applied to determine the LOD and LOQ as
explained in section 3.8.2. For the purpose of comparison between different
approaches, DCM was used as a blank sample. The levels of concentration for each
compound and number of replicates and measurements performed by using different
methods are listed in Table 4.7.
Table 4.7: Concentrations of analytes and number of replicates used for
determination of LOD and LOQ
Method
Levels (µg/mL), n
Replicates, p
Measurements, np
1
Signal-to-noise
0, 0.4
10
20
2
Blank
determination
0, 0.4
10
20
3
Linear regression
0.2, 0.4, 0.6, 0.8,
1.0, 2.0, 4.0
10
70
60
In order to respect measurement independence, each replicate was performed
on a newly prepared standard solution and the replicates were carried out on different
days to take into consideration of run effect. The run effects accounts for day-to-day
variations in the analytical system, such as batches of reagents, recalibration of
instruments, and the laboratory environment changes.
For generation of calibration curve, the concentration levels were chosen in a
range around LOD and LOQ to ensure the homoscedasticity, the independence of the
area dispersion in relation to analyte quantity.
(a)
Signal-to-noise (S/N)
The noise value was calculated based on the peak height of the blank (DCM)
around the retention time of each analyte using auto-integrator. LOD was estimated
as three times the noise value and LOQ was estimated as ten times the noise value as
shown in Table 4.8.
Table 4.8: Data obtained for each test compound based on signal-to-noise approach
Compound
Mean (peak height values), p =10
Blank
% RSD
S/N=3
S/N=10
Styrene
13
25
38
126
Toluene
16
43
49
163
Ethylbenzene
15
44
44
146
iso-Propylbenzene
15
37
45
151
n-Propylbenzene
14
25
41
136
This approach is widely used for instrumental method such as gas
chromatography as it is easy to implement. However, the stability of the instrument
response on day-to-day basis will affect the results obtained. In this study, 10
independent numbers of blank together with the standard solution at level of 0.4
µg/mL were analyzed separately on different days. Due to the run effect of the
61
instrument, the relative standard deviations for the 10 measurements ranged from
25% to 44% for the five test compounds. This method is very much dependent on
individual analyst’s interpretation of how to obtain the magnitude of noise whether
by manual measurement or using auto-integrator of the instrument. Therefore the
values obtained are difficult for comparison between different analysts and
laboratories.
(b)
Blank Determination
Blank determination was carried out by analyzing 10 independent sample
blanks, and the mean concentration and the standard deviations of the blank results
were calculated (Table 4.9).
Table 4.9: The mean concentration and standard deviation of blank obtained using
blank determination approach
Compound
Blank , p=10
Mean conc. ( xbi ), µg/mL
Standard deviation ( S bi )
Styrene
0.05
0.02
Toluene
0.05
0.02
Ethylbenzene
0.05
0.02
iso-Propylbenzene
0.06
0.02
n-Propylbenzene
0.05
0.01
The blank determination approach as described in EURACHEM guide, LOD
is estimated as 3S more than the blank value as it assumes that a signal more than 3
times above the standard deviation of the sample blank value is likely to have arisen
from the measurand.
For this approach, it needs a sample blank for each sample
matrix to be analyzed, and the estimated LOD and LOQ may vary for different
sample matrices. However, getting a true sample blank can be difficult and in certain
situation, reagent blank is used as a blank such as in this study. The LOD and LOQ
estimated by using reagent blank does not take into consideration the matrix
62
interference, and the estimated values can be smaller than that using true sample
blank.
(c)
Linear Regression
Linear least-squares regression parameters were calculated based on the
analysis of ten replicates (p=10) of test compounds at seven different concentration
levels (n-7). The data obtained were used to compute the two coefficient of the
calibration curve and also to perform a lack-of-fit test, which was used to verify that
the selected calibration domain was actually linear. The standard deviation of the
blank was estimated by using both standard deviation of regression residual ( S res )
and y – intercept ( S yo ) as shown in Table 4.10 and results of the statistical evaluation
of the linear regression curve is shown in Table 4.11.
Table 4.10: Parameters of linear ordinary least-squares regression for the five test
compounds at seven different levels of concentration
Compound
(n=7, p=10)
Correlation
coefficient, r
Slope, b
Y-intercept,
a
Y-intercept
standard
deviation,
Residual
standard
deviation,
s yo
sres
Styrene
0.995
802
0.03
13
73
Toluene
0.992
798
18
16
91
Ethylbenzene
0.990
804
17
18
102
iso-Propylbenzene
0.994
804
15
13
78
n-Propylbenzene
0.992
787
36
15
89
63
Table 4.11: Results of the statistical evaluation of the linear regression curve
Compound
Regression test
Freg[1, n(p-1), 5%]
Observed value, Critical value
Fobs (1,63, 5%)
Fcrit (1,63, 5%)
Lack-of-fit test
Flof[n-2, n(p-1), 5%]
Observed value,
Critical value
Fobs (5,63, 5%)
Fcrit (5,63, 5%)
Styrene
12309.553
3.993
0.360
2.361
Toluene
7923.943
3.993
0.714
2.361
Ethylbenzene
6175.352
3.993
0.157
2.361
iso-Propylbenzene
10677.743
3.993
0.223
2.361
n-Propylbenzene
7827.221
3.993
0.286
2.361
The results showed that the test for regression was significant while the F
observed value for each analyte was much higher than the critical value of 3.993,
which corresponded to F(1,63,5%). This meant that the instrumental response was
significantly correlated to the analyte concentration. When the lack-of-fit test was
performed, the Fisher variable associated to the test for the error of model was
smaller than the critical value of 2.361. It was concluded that the error of model was
not significant at the risk level of 5% and the proposed linearity domain could be
accepted.
The linear regression approach can help to solve the problem of difficulty in
obtaining matrix blank for other methods. This is because calibration curve can be
prepared by sample addition method. From this study, the results showed that the yintercept standard deviation and y-residual standard deviation varied greatly. The
values for y-intercept standard deviation were much lower than that y-residual
standard deviation for the five analytes. These results were in agreement with the
study reported by Jerome Vial and Alain Jardy [89]. The values of LOD and LOQ
obtained by this approach can vary depending on the number of concentration levels,
range of concentration used, number of measurement and data heteroscedasticity.
64
(d)
Comparison of LOD and LOQ of Different Approaches
Based on the experimental results, the LOD and LOQ were estimated for the
different approaches and their results are as summarized in Table 4.12 and Table
4.13, respectively.
Table 4.12: Summary of estimated LOD by different approaches
Compound
Estimated LOD, µg/mL
Signal-to- noise Blank
determination
Linear regression
S res
S yo
Styrene
0.15
0.10
0.05
0.27
Toluene
0.16
0.12
0.06
0.34
Ethylbenzene
0.16
0.12
0.07
0.38
iso-Propylbenzene
0.17
0.11
0.05
0.29
n-Propylbenzene
0.15
0.09
0.06
0.34
Table 4.13: Summary of estimated LOQ by different approaches
Compound
Estimated LOQ, µg/mL
Signal-to-noise Blank
Linear regression
determination S yo
S res
Styrene
0.50
0.20
0.16
0.91
Toluene
0.54
0.28
0.20
1.15
Ethylbenzene
0.52
0.26
0.22
1.27
iso-Propylbenzene
0.56
0.23
0.17
0.97
n-Propylbenzene
0.51
0.18
0.20
1.13
For LOD, the values obtained by signal-to-noise approach and blank
determination were closed to each other. The linear regression approach by using
S res showed largest values of LOD and by using S yo gave lowest values of LOD for
65
all analytes. For LOQ, similar trend was observed for linear regression approach as
in LOD. However, the signal-to-noise approach presented about 2 times the values
of LOQ as compared to blank determination approach. The LOQ values obtained
by blank determination approach were comparable to linear regression approach
using S yo . From these findings, it seemed that not all the approaches used to estimate
LOD and LOQ in this study were equivalent. The differences between the smallest
and the largest values estimated by the different approaches could vary by a factor of
5 to 6 for both LOD and LOQ.
(e)
Checking a predetermined Limit of Quantification (LOQ)
It is difficult to compare the degree of reliability of LOQ estimates. In order
to check a predetermined LOQ values obtained by statistical or empirical approach, a
mechanism was introduced to ensure that the LOQ value obtained was achievable
practically as described in section 3.8.2d.
Standard solutions (0.2 µg/mL) were
analyzed 10 times independently, and the results obtained are reported in Table 4.14.
Table 4.14: Check for predetermined LOQ of 0.2 µg/mL
Statistic
Measured concentration (µg/mL)
Styrene
Toluene
Ethyl
benzene
iso-Propyl
benzene
n-Propyl
benzene
xQL
0.21
0.20
0.21
0.20
0.20
Std. dev., s QL
0.06
0.04
0.04
0.03
0.03
Total number, n
10
10
10
10
10
Predetermined LOQ
0.2
0.2
0.2
0.2
0.2
0.43
0.05
0.91
0
0.41
0.29
0.21
0.17
0.17
0.14
Mean,
LOQ − xQL
sQL
n
5sQL
It was found that ethylbenzene, iso-propylbenzene and n-propylbenzene met
the two conditions stated in Section 3.8.2.4; the measured mean quantity xQL was not
significantly different from the predetermined LOQ of 0.2 µg/mL. For toluene and
styrene, one of the conditions was not fulfilled, therefore predetermined LOQ of 0.4
µg/mL was tested and the results obtained in Table 4.15.
4.15: Check for predetermined LOQ of 0.4 µg/mL
Statistic
Measured concentration (µg/mL)
Styrene
Toluene
Ethyl
benzene
iso-Propyl
benzene
n-Propyl
benzene
0.42
0.40
0.42
0.40
0.43
Std. dev., s QL
0.041
0.07
0.037
0.056
0.081
Total number, n
10
10
10
10
10
Predetermined LOQ
0.4
0.4
0.4
0.4
0.4
1.29
0.21
1.46
0.16
1.01
0.20
0.35
0.19
0.28
0.40
Mean,
xQL
LOQ − xQL
sQL
n
5sQL
All the five anlytes met the criteria stated at the LOQ values of 0.4 µg/mL,
hence, it is acceptable to use 0.4 µg/mL as LOQ for further testing. This LOQ of 0.4
µg/mL is equivalent to 8 mg/kg in sample. By using direct injection technique for
polymer and copolymer test, LOQ of between 50 – 100 mg/kg, and 10 mg/kg could
be achieved by an experienced analyst [18]. Hence, this method was more sensitive
and suitable to analyze other VOCs of lower residues level besides styrene monomer
in food packaging samples.
67
4.2.4.3 Linearity Test
The linearity range of the method was evaluated based on IUPAC Guidelines.
Standard mixtures of seven concentration levels (n=7) ranged from 0.4 µg/mL
(LOQ) to 80 µg/mL were used to prepare the calibration curve. Fresh calibration
solution was prepared each day, and quantification was carried out for six replicates
(p=6) on different days.
The linear regression values were calculated and the
linearity was evaluated by visual inspection of the linear regression line and yresidual plot.
(a)
Inspection of y-Residual Plot
Experimental data were initially fitted with a simple ordinary least squares
regression (OLS). The slope (b), intercept (a), standard deviation of the slope (Sb),
standard deviation of the intercept (Sa), residual standard deviation (Sres) and
coefficient R2 were calculated by function LINEST of Microsoft Excel.
Linearity was tested by examination of a plot of residuals produced by linear
regression of the responses on the concentrations in the calibration sets studied (Fig.
4.6). The accepted variation of each single point in the residual plot was indicated by
± t(0.05, np-2).Sres at 95% confidence limit and np-2 degree of freedom. The results
show that the residual values were randomly distributed between the positive and
negative values in the range of 10 µg/mL to 80 µg/mL for all the analytes whereas
for 0.4 µg/mL, the residual values tend to be positive. The residual plots also
indicate that some of the data points fell outside the ± t(0.05, np-2).Sres. lines between
50 µg/mL to 80 µg/mL. These outlier data were rejected for further calculation.
Based on the visual inspection of the plot, the calibration model was accepted for all
the analytes from the range of 10 µg/mL to 80 µg/mL. Further statistical test was
performed to confirm the degree of linearity and to further justify whether 0.4 µg/mL
(LOQ) was to be included in the linear range (see subsection 4.2.4.3b).
68
(a)
0.75
0.55
y-residual
0.35
0.15
-0.05
0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
80.0
-0.25
-0.45
-0.65
-0.85
(b)
0.75
0.55
y-residual
0.35
0.15
-0.05
0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
80.0
-0.25
-0.45
-0.65
-0.85
(c)
0.75
0.55
y-residual
0.35
0.15
-0.05
0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
80.0
0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
80.0
0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
80.0
-0.25
-0.45
-0.65
-0.85
(d)
0.75
0.55
y-residual
0.35
0.15
-0.05
-0.25
-0.45
-0.65
-0.85
(e)
0.75
0.55
y-residual
0.35
0.15
-0.05
-0.25
-0.45
Concentration (mg/L)
-0.65
-0.85
p1
p2
p3
p4
p5
p6
Fig. 4.6: Residual plots for (a) Styrene; (b) Toluene; (c) Ethylbenzene; (d) isoPropylbenzene; and (e) n-Propylbenzene with limits ± t(0.05, np-2).Sres
69
(b)
Validation of Assumption
The linearity range was further confirmed by statistical evaluation to test the
acceptability of regression model (Freg) and linearity domain (lack-of-fit test, Flof).
The acceptability of regression model is based on the hypothesis that if the ratio Freg
is higher than the critical value Freg(1, n(p-1), 5%), the regression model is accepted.
Freg(1, n(p-1), 5%) is the value of Fisher Distribution for a and n(p-1) degrees of
freedom at risk level of 5%.
The lack-of-fit test was used to evaluate the
acceptability of the linear regression model. The linearity domain is validated if the
ratio Flof is lower or equal to the critical value F(n-2, n(p-1), 5%), the regression
model is accepted to be a linear model. Table 4.16 summarized the results of
regression test and lack-of-fit test.
Table 4.16: Results of regression test and lack-of-fit test
Analyte
Regression test
Freg[1, n(p-1), 5%]
Fcal
Fcrit
Lack-of-fit test
Flof[n-2, n(p-1), 5%)
Fcal
Fcrit
Styrene
1830.69
7.47
0.47
3.63
Toluene
11913.78
7.47
2.23
3.63
Ethylbenzene
15694.21
7.47
2.73
3.63
iso-Propylbenzene
17328.47
7.47
2.34
3.63
n-Propylbenzene
13148.79
7.47
1.35
3.63
Based on the results, the regression model was acceptable and the linearity domain
was validated. In addition, significant test for y-intercept was performed to check
whether y-intercept of the calibration curve passes through origin. The significant
test was based on student t test as shown in equation below:
t cal =
a
Sa
where tcal is calculated t value, a is an intercept and Sa is an intercept standard
deviation. If tcal is lower or equal to the critical value t distribution for n-2 degree of
70
freedom at the risk level of 5%, the y-intercept is considered not significantly
different from zero. After a series of statistical tests for linearity range, the final
calibration linear equation was constructed and the findings of the linearity tests are
summarized in Table 4.17.
Table 4.17: Summary of findings of linearity tests for the five analytes
Analyte
Linearity
range
(µg/mL)
Least square linear
regression equation
Correlation
coefficient,
r
y-intercept
passes through
origin
Styrene
0.4 - 80
y = 0.0987x-0.0781
0.9991
yes
Toluene
0.4 - 80
y = 0.1028x-0.0958
0.9992
yes
Ethylbenzene
0.4 - 80
y = 0.1046x-0.1605
0.9991
yes
iso-Propylbenzene
0.4 - 80
y = 0.0980-0.0716
0.9991
yes
n-Propylbenzene
0.4 - 80
y = 0.0956x-0.0981
0.9992
yes
4.2.4.4 Accuracy
As there is no certified reference material currently available for the testing of
accuracy for this method, the accuracy was evaluated by recovery studies. Ten test
samples (n=10) which consisted of polystyrene plate, spoon, fork, bottle, bottle cap,
cup and container were spiked at three different concentration levels (1 µg/mL, 10
µg/mL and 20 µg/mL) which were equivalent to about 20 µg/g, 200 µg/g and 400
µg/g in samples. Extraction was accomplished for unspiked and spiked samples. In
this case, the amount of analyte found in the unspiked sample was considered as the
reference value for the extraction yield calculation. The test samples were analyzed
in duplicate (p=2).
Table 4.18 displays the recovery values of each analyte for
different concentration levels.
71
Table 4.18: % recovery of the analytes at different spiking levels: (a) 10 mg/kg, (b)
200 mg/kg and (c) 400 mg/kg
(a) 10 mg/kg
Sample type
Ice cream scoop
Plate
Spoon
Measuring spoon
Sushi container
Bottle Cap
Ice cream cup
Baby cup
Spices container
Fork
Mean recovery, % (p=2)
Toluene
Ethylbenzene
105
118
105
77
117
126
102
94
91
100
97
85
89
57
122
72
88
90
119
77
iso-Propylbenzene
101
83
123
97
93
73
80
79
93
86
n-Propylbenzene
114
93
112
104
95
80
99
91
86
97
(b) 200 mg/kg
Sample type
Ice cream scoop
Plate
Spoon
Measuring
spoon
Sushi Container
Bottle Cap
Ice cream cup
Baby cup
Spices container
Fork
Mean recovery, % (p=2)
Styrene
Toluene Ethylbenzene
61
71
69
70
76
74
77
78
78
88
83
85
iso-Propylbenzene
71
73
79
82
n-Propylbenzene
71
79
81
85
62
104
65
68
95
126
65
79
78
74
76
103
67
92
79
80
80
106
Mean recovery, % (p=2)
Styrene Toluene Ethylbenzene
iso-Propylbenzene
n-Propylbenzene
93
96
86
91
85
88
75
94
95
89
84
84
85
88
64
65
86
72
77
107
85
91
86
91
65
77
88
75
83
105
63
96
75
84
76
107
64
91
75
78
79
108
(c) 400 mg/kg
Sample type
Ice cream scoop
Plate
Spoon
Measuring spoon
Sushi Container
Bottle Cap
Ice cream cup
Baby cup
Spices container
Fork
84
91
85
88
62
80
85
80
81
105
86
92
86
89
63
77
86
78
79
106
The % recovery for the spiking of 1 µg/mL styrene was not reported, because
the test samples contained more than 100 µg/g of residual styrene and therefore large
variation of recovery values were obtained for different samples. The % recovery of
each analyte varied depending on the type of samples and concentration levels.
It
was observed that without taking into consideration of the different sample matrices,
72
the mean recovery was better at the low concentration level (spiked of 1 ppm),
followed by high concentration (spiked of 20 ppm) and the lowest mean recovery
was reported at median concentration (spiked of 10 ppm) as shown in Fig.4.7.
140
% recovery
120
100
80
60
40
20
0
Styrene
Toluene
Ethylbenzene
1ppm
10ppm
iso-Propylbenzene
n-Propylbenzene
20ppm
Fig. 4.7: Mean recovery of the analytes based on different concentration levels of
spiking.
4.2.4.5 Precision
Precision depends only on the distribution of the random errors and has no
relation with the true or specified value. In practice, precision refers to all the
experimental conditions ranging between the conditions of repeatability and those of
reproducibility, and usually expressed as a standard deviation (s) or relative standard
deviation (RSD). In this study, evaluation was made on both instrument and method
precision.
(a)
Instrument precision
The test was carried out by repeated analysis at five different concentration
levels of analytes over a period of time and statistical assessments were performed on
the final results. Table 4.19 shows the results of precision as expressed in relative
standard deviation (RSD). The RSD measures the extent to which the results are
73
spread around their average. The calculated RSD at each concentration level ranged
from 0.30% to 7.52% for intra-day precision and 0.44% to 12.94% for inter-day
precision. All the analytes showed the highest RSD values at the lowest
concentration level (0.4 µg/mL), probably due to the volatility of the analytes.
Table 4.19: Intra-day and inter-day precisions for the five analytes
Conc.
RSD (%)
µg/mL
Intra-day (p = 3)
Styrene
Toluene
EB
Inter-day (p=6)
IPB
NPB
Styrene
Toluene
EB
IPB
NPB
0.4
3.20
6.92
7.52
4.91
5.18
8.17
11.07
11.18
11.20
12.94
10
1.41
0.78
1.01
1.46
1.40
1.28
0.71
0.99
0.44
0.51
30
0.34
0.98
0.58
0.66
0.30
1.61
1.10
1.42
1.51
1.23
50
1.01
0.97
0.90
0.86
0.65
1.15
1.18
0.79
1.25
0.91
70
0.56
0.48
0.60
0.40
0.50
1.15
1.34
1.34
1.38
1.27
EB = Ethylbenzene; IPB = iso-Propylbenzene; NPB = n-Propylbenzene
(b)
Method Precision
Usually, the repeatability and reproducibility are not constant throughout the
range of validity of a method. In this study, precision of the test method to be
applied for different sample matrices was evaluated.
Ten different polystyrene
samples including plate, spoon, fork, stirrer and container were analyzed in duplicate
under the same conditions. As some samples contained residue levels of toluene,
iso-propylbenzene and n-propylbenzene below the LOQ levels, these samples were
spike with 10 µg/mL of standard solution to obtain results for precision calculation.
The results obtained were used to compute the repeatability standard deviation, sr,
and the repeatability, r of the method as explained in section 3.8.5b (Table 4.20).
The results showed that the repeatability values of the analytes ranged from
4.46 to 11.18. The highest repeatability was observed for ethylbenzene (r = 11.18)
while the lowest repeatability was observed for iso-propylbenzene (r = 4.46).
74
Table 4.20: Precision of method based on different sample matrices
Sample
Replicate
Concentration (mg/kg)
(n)
(p)
Styrene
Toluene Ethylbenzene iso-Propylbenzene
n-Propylbenzene
1
1
400.56
47.66
95.24
32.16
22.26
2
398.61
47.26
95.37
38.84
29.79
1
166.79
17.66*
99.18
27.80
21.82
2
169.19
17.93*
94.08
26.07
20.36
1
260.46
23.72*
31.63
13.64
31.84*
2
252.93
23.09*
32.61
14.81
28.25*
1
302.00
26.49
33.71
9.35
23.25*
2
303.85
23.43
33.65
9.39
23.08
1
278.78
91.08
83.27
12.19
9.07
2
280.76
85.79
82.59
12.30
8.77
1
199.01
19.42
59.66
9.68
25.30*
2
199.44
19.80
62.56
8.67
27.49*
1
466.08
31.75
47.66
8.01
28.33*
2
472.77
31.96
47.20
8.10
29.27*
1
220.93
34.89
56.98
12.41
9.41
2
229.15
34.62
53.24
14.81
9.91
1
87.72
18.32
14.79
21.65*
21.50*
2
88.94
19.66
14.99
21.18*
21.13*
1
200.99
17.41*
247.54
14.15
8.72
2
203.26
17.92*
246.74
14.56
8.25
Repeatability std.
dev., Sr
3.1045
1.7359
2.9942
1.5928
1.6764
Repeatability, r
8.69
4.86
11.18
4.46
4.69
2
3
4
5
6
7
8
9
10
*sample spiked with 10 µg/mL standard solution
4.2.5
Application of Method to the Analysis of Polystyrene Food Packaging
The developed method was applied to determine the residual styrene
monomer and four other VOCs in five categories of commercially available PS food
packaging as listed in Table 4.21. IR spectra of films prepared from the packaging
samples confirmed that the polymers contained styrene.
The concentrations of the
analytes in the packaging samples were estimated based on internal standard
calibration. Two determinations were conducted on each commercial sample.
75
Table 4.21: Categories of PS samples and number of replicates used for the analysis
Sample type
Sample, n
Replicate, p
Instant noodle bowls
12
2
Disposable cutlery wares
(spoon, fork, plate, cup, bowl etc)
Cutlery wares
19
2
6
2
Cultured milk bottles
12
2
Food storage containers
6
2
Total samples
55
4.2.5.1 Quality Assurance
Analysis of the samples was carried out in batches, with samples of the
sample group analyzed in a batch. Each batch consisted of one reagent blank, one
QC sample and one spiked sample selected at random from the batch. For VOCs to
be considered to be present in samples, the criteria stated in section 3.6.5 must be
fulfilled. If any batch did not comply with the criteria, the analysis was repeated.
4.2.5.2 Analyte Concentration in Samples
Table 4.22 shows the range of concentration in the different categories of PS
packaging samples. The residual styrene monomer ranged from 57 mg/kg to 1762
mg/kg, with the highest in the PS container and lowest in the cultured milk bottle.
No toluene was found above LOQ in instant noodle bowls, cutlery wares and
cultured milk bottles. Toluene was detected in disposable cutlery wares and PS
container of below 90 mg/kg. In contrast, 95% of the sample tested had detectable
ethylbenzene ranging from 10 mg/kg to 872 mg/kg. The highest concentration was
76
detected in PS container. Low levels of iso-propylbenzene and n-propylbenzene were
reported for the five categories of sample at concentration of below 60 µg/g.
Table 4.22: Concentrations of the five analytes found in different PS samples
Sample
Mean concentration (µg/g), p=2
Tolueneb
Ethyl
Styrenea
benzenec
iso-Propyl
benzened
n-Propyl
benzenee
Total
VOCs
Instant noodle
bowls
236 - 925
<LOQ
10 - 190
<LOQ - 25
<LOQ - 22
250 - 1156
Disposable
cutlery wares
65 - 1643
<LOQ - 35
19 - 314
<LOQ - 56
<LOQ - 43
86 - 1905
Cutlery wares
400 - 1138
<LOQ
11 - 209
<LOQ - 21
<LOQ - 17
400 - 2156
Cultured milk
bottles
57 - 514
<LOQ
<LOQ - 91
<LOQ - 33
<LOQ - 21
63 - 552
Food
container
150 - 1762
<LOQ - 88
<LOQ - 872
<LOQ - 45
<LOQ - 30
161 - 1600
recovery: a – 96% to 114%; b – 89% to 112%; c – 87% to 104%; d – 87% to 106%; e – 84% to
124%
The styrene concentrations found in five samples were found to have
exceeded the level permitted by the Japan Sanitary Law, i.e. 1000 ppm. For the total
concentration of the five analytes, all the samples contained the VOCs within the
limit permitted, i.e. 2000 ppm for foamed styrene and 5000 ppm for other PS
samples. Good recovery values were obtained for each analyte between 84% to
124% at the spike concentration of 200 µg/g.
4.3
Migration test
Based on the material test study, it was found that some VOCs residues were
detected in the PS packaging material particularly styrene monomer and
ethylbenzene.
It is of interest to know whether the styrene monomer and
ethylbenzene would migrate to the food when in-contact with this kind of food
packaging. An initial attempt was carried out to use the material test method to
determine migration of selected analytes into food. Due to the complexity of food
composition, the purified deionized water was chosen as food simulant. According
77
to EU and Japan Standard, water represents the food with pH 4.5 and above.
Therefore water represented a wide range of food that normally in contact with
polystyrene packaging.
A migration test was performed based on exposing the test sample and
control sample to water at defined conditions and the residual VOCs that remained in
the material were determined as described in section 3.6.2.2.
4.3.1
Selection of Control Sample
Two types of control samples were taken into consideration for the migration
test. Type 1 control sample consisted of polystyrene cup without any treatment, left
at room temperature at specified time identical to that for the test sample. Type II
control sample consisted of polystyrene cup filled with leaching solution, left at room
temperature at specified time identical to that for the test sample. Both type of
control samples were extracted and analyzed independently in 6 replicates for styrene
and ethylbenzene residues and the results are summarized in Table 4.23.
Table 4.23: Concentration of ethylbenzene and styrene in control samples
Ethylbenzene
Control
Sample
P1
I
211.83
II
207.09
%
difference
(I-II)
Styrene
Control
Sample
I
II
%
difference
(I-II)
2.24
P2
203.29
207.65
P3
232.00
219.00
-2.14
5.60
Concentration, µg/g
P4
P5
P6
222.02 220.40 199.53
228.11 220.02 202.51
-2.74
0.17
-1.49
P1
945.62
926.36
P2
899.41
929.40
P3
942.11
939.44
Concentration, µg/g
P4
P5
P6
985.38 947.16 885.87
987.56 938.65 908.63
2.04
-3.33
0.28
-0.22
0.90
-2.57
mean
214.85
214.06
sd
12.28
9.8
RSD
5.71
4.58
sd
36.13
26.57
RSD
3.87
2.83
0.36
mean
934.26
938.34
-0.44
78
The differences between control sample I and II were less than 6% and 4% for
ethylbenzene and styrene, respectively. The small variations among the control
samples were possibility contributed by the random experimental errors and the
inhomogeneity of the analyte contents among the same batch of samples as indicated
by the RSD obtained for styrene (I - 5.71%, II - 4.58%) and ethylbenzene (I - 3.87%,
II – 2.83%) of the sample replicates. These results conclude that there was no
significant variation in term of residual styrene and ethylbenzene in both types of
control samples. Control Type II was chosen as control sample for studying the
temperature effect. This was to ensure that the control sample was under the same
conditions as those for test sample so that other factors that affect the migration of
styrene and ethyl benzene can be minimized.
4.3.2
Sample Homogeneity
The migration result was obtained based on the concentration difference
between two samples (control and test samples) of the same batch.
It was assumed
that the residual content of styrene and ethylbenzene were similar among the samples
of the same batch. A study was carried out to find out any variation of the residual
content among samples of the same batch. A total of 25 samples of polystyrene cup
was taken from the same batch number as provided by the manufacturer information.
The results of residual styrene and ethylbenzene in the samples are shown in Table
4.24.
Table 4.24: Concentration of ethylbenzene and styrene in samples
Compound
Ethylbenzene
Concentration (µg/g) n = 25
Range
mean
187.33 – 248.40
213.76
S
14.24
RSD (%)
6.66
Styrene
804.83 – 1002.42
52.41
5.64
929.88
79
It was found that among the same batch of samples, there was a small
variation of styrene and ethylbenzene present as indicated by the RSD values of 5.64
and 6.66%, respectively. These results could be due the inhomogeneity of the
residue content in the sample and random experimental errors.
4.3.3 Migration of Analyte at Different Temperature
The disposable EPS cup was chosen for the migration test as this type of PS
cup was usually used for dispensing hot water at fast food outlets and hawker stores.
Four levels of temperature chosen for the study were 40°C, 60°C, 80oC and 90oC.
Temperature of 60°C is normally used for migration testing as recommended by EU
and Japan guidelines. The maximum temperature for polystyrene resin use in food
packaging application as required by Malaysia Standard (MS1558:2002) is 86°C.
Four samples of PS cups were exposed to the leaching solution at the four
different temperature conditions for 30 min; the samples were analyzed in triplicate
together with the control sample as described in section 3.6.2.2. Each test was
analyzed independently and the results are calculated using the formula below:
Amount migrated (%):
= [conc. of analyte in control sample – conc. of analyte in test sample (µg/g)] x 100
conc. of analyte in control sample (µg/g)
The results show that migration of ethylbenzene and styrene occurred at
temperature of 60oC, 80oC and 90oC (Table 4.25). As the temperature increased
from 60oC to 90oC, the migration of styrene seemed to increase from 4.45% (60oC)
to 5.01% (90oC), but there was no significant increase of migration for ethylbenzene.
Based on the findings obtained in section 4.3.2, inhomogeneity of analyte amount in
samples and experimental errors could contribute RSD up to 6.66% for ethylbenzene
and 5.64% for styrene among same batch of samples. Therefore, it is difficult to
80
estimate the migration of the analytes by using dissolution method, and the method
was not sensitive enough to determine the analytes at low level (ppb).
Table 4.25: Estimation of ethylbenzene and styrene migrated from polystyrene cup
using dissolution method
Analyte Amount Migrated (%)
40oC
60oC
80oC
90oC
A1
A2
mean
B1
B2
mean
C1
C2
mean
D1
D2
mean
Ethyl
benzene
-2.59
-1.02
-1.81
4.93
0.17
2.55
2.08
4.48
3.28
2.07
3.61
2.84
Styrene
-3.78
-0.89
-2.34
4.45
1.82
3.14
4.49
3.60
4.05
3.60
6.42
5.01
81
CHAPTER 5
APPLICATION OF SOLID-PHASE MICROEXTRACTION TO
THE STUDY OF THE MIGRATION OF VOCs FROM POLYSTYRENE
FOOD PACKAGING INTO WATER AS FOOD SIMULANT
5.1
Preamble
An alternative migration method using solid-phase microextraction (SPME)
for sample extraction was studied to overcome the problem encountered by using
dissolution method.
Due to the large number of implied variables, and in order to obtain the
optimum conditions for the determination of VOCs in food simulant, a sequential,
systematic procedure was followed.
The first step consisted of GC program
optimization and carried out by extraction of standard solution in aqueous solution
by SPME, and injected into the GC-FID.
5.2
Instrumental Conditions
It was initially assumed that a splitless injection procedure, commonly used
for trace analysis, would produce optimal sensitivity and detection limits. However,
the resulting chromatogram showed significant band broadening. Therefore, after
several adjustment made to compensate for this difficulty, a split ratio of 10:1 was
applied after 0.5 min injection for the production of sharp, well-resolved peaks. By
using the same GC program as for material test, the SPME extraction shows greater
82
separation enhancement capabilities, compared with material test method (Fig. 5.1)
As HS-SPME did not involve solvent; there was no solvent peak in the
chromatogram. The analyte peaks were sharp, well resolved and the analysis was
about 12 min. In order to shorten the analysis time while maintaining the separation
parameters as those for material test, the final column oven temperature program was
shortened to 3 min and thus the total run time per analysis was reduced to 16.75 min.
6
1
2
4
5
3
0
2.5
5
7.5
Time (minutes)
10
12.5
Fig. 5.1: GC chromatogram of analyte mixture using HS-SPME method. Peak: 1 =
Toluene (45 ppb); 2 = Ethylbenzene (15 ppb); 3 = iso-Propylbenzene (5 ppb); 4 = nPropylbenzene (5 ppb); 5 = Styrene (10 ppb); and 6 = 1,4-Diethylbezene (ISTD, 5
ppb)
5.3
Optimization of SPME Parameters
HS-SPME is an equilibrium process that involves the portioning of analytes
from aqueous phase to gas phase and gas phase into the polymeric phase according
to their partition coefficients. Thus, the optimization of parameters is extremely
important to ensure the maximum amount of analyte will be extracted under the
optimum conditions.
The parameters for SPME extraction were evaluated to determine the best
conditions to use for the extraction of VOCs from the aqueous solution. Extraction
temperature and time, sample volume, sample agitation and salt addition were taken
into consideration for overall extraction efficiency. In the experiments, the studied
83
variable was varied according to the specified range; other parameters were fixed as
described in section 3.7.4.
5.3.1 Fiber Coating Selection
The choice of the most suitable coating is very important for achieving good
selectivity for the target analytes. Based on the commercially available fibers and
published data, PDMS was selected for this study. PDMS is non-polar and presents
a high affinity for non-polar compounds and VOCs. It is the most widely used for
VOCs in aqueous solution.
5.3.2
Sample Volume Studies
In HS-SPME, the analytes are distributed among the sample matrix, the fiber
coating, and the headspace. The headspace volumes must generally be small in order
to concentrate the analytes before they diffuse towards the fiber coating. As the
volume of sample is increased, more samples can contribute volatiles to the
headspace. The total amount of analytes that can be adsorbed by the fiber can be
directly related to the sample volume.
Fig. 5.2 shows the variation of response (peak area) with sample volume, it
was observed that peak area response improved as the sample volume increased from
5 mL to 10 mL. Beyond that, further increase in sample volume to 15 mL only
slightly increased the overall response. The sample volume determines the volume
of the headspace, so it affects the response of SPME. The mass transfer from the
liquid phase to the gas phase increases as the volume of the liquid phase is increased.
However, the mass transfer from the liquid phase to the gas phase slows down when
approaching equilibrium stage.
84
80000
70000
peak area (µV)
60000
50000
40000
30000
20000
10000
0
0
10
5
15
20
volume (mL)
toluene
ethylbenzene
iso-propylbenzene
n-propylbenzene
styrene
Fig. 5.2: Effect of sample volume on extraction efficiency of analytes
This study also indicated that the RSD increased as the sample volume
increased. The RSD values ranged from 0.22% to 2.76% at 5 mL of sample volume,
0.35% - 4.56% at 10 mL of sample volume and 4.46% to 9.71% at 15 mL of sample
volume. This may be due to the errors during volume dispensing by using different
types of pipettes. Therefore, sample volume of 10 mL was selected for further
experimental testing.
5.3.3
Elutropic Strength Studies
As the increase of the analyte concentration also increase the volume of
methanol required as spiking solvent, the possible competitive displacement effect of
methanol in the analyte adsorption by the fiber was studied. The small amounts of
added methanol were expected to dissolve completely in the water and not
significantly alter the properties of that phase. Accordingly, studies as described
section 3.7.7 were conducted. The variations of peak area with the amount of
85
methanol are shown in Fig. 5.3. As methanol concentration increased, less analyte
was absorbed.
The decrease in absorption of the analytes in 0.5% methanol was in the range
of 6% to 14%. This is because an increased proportion of methanol in the aqueous
solution decreases the polarity of the aqueous sample so that the distribution constant
decreases. The presence of organic solvent in the sample suppresses the adsorption
of analyte onto the fiber. To overcome the non-linearity attributed to competitive
displacement of the analyte by the spiking solvent, preparation of calibration
standard solution and sample spiking solution was limited to 0.1% methanol.
80000
Peak area (µV)
70000
60000
50000
40000
30000
20000
10000
0
0
2
4
6
8
10
% MeOH
toluene
ethylbenzene
iso-propylbenzene
n-propylbenzene
styrene
Fig. 5.3: Studies of elutropic strength effect on the targeted analytes
5.3.4
Extraction Temperature Studies
In HS-SPME, an increase in extraction temperature leads to an increase of
analyte concentration in the headspace, and helps to facilitate faster extraction.
However, at high temperature, coating headspace partition decreases and the fiber
coating begins to lose its ability to adsorb analytes. Thus the temperature effect
between 24°C – 80°C was studied.
86
80000
Peak area (µV)
70000
60000
50000
40000
30000
20000
10000
0
0
20
40
60
80
100
Temp (°C)
toluene
ethylbenzene
n-propylbenzene
styrene
iso-propylbenzene
Fig. 5.4: Effect of extraction temperature on analyte extraction efficiency
The temperature affects the distribution constants of the equilibrium fiber-gas
and sample-gas; therefore it determines the amounts of analyte extracted from the
fiber. From the experiment, a decrease in peak area was observed when the
extraction temperature increased from laboratory room temperature (24°C) to 80°C
(Fig. 5.4). This can be explained by the exothermic adsorption process by which the
VOCs are partitioned between the headspace and the PDMS coating. A higher
temperature increases the concentration of VOCs in the headspace by decreasing the
partition coefficient between the PDMS coating and the headspace. As a result, the
total amount of VOCs adsorbed into the fiber decreases as extraction temperature
increases. The optimum extraction efficiency for all the analytes was at laboratory
room temperature (24°C). Thus, a temperature of 24°C was selected for further
experiments since this temperature provides a maximum for VOCs and working
under these conditions enables the obtainment of good chromatographic signals.
87
5.3.5
Extraction Time Studies
The influence of extraction time was studied from 1 min to 45 min. The
results are shown in Fig. 5.5.
80000
70000
Peak area (µV)
60000
50000
40000
30000
20000
10000
0
0
10
20
30
40
50
Time (min)
toluene
ethylbenzene
n-propylbenzene
styrene
iso-propylbenzene
Fig. 5.5: Extraction time profile for the five analytes
An increasing efficiency was observed for the five analytes when the longer
extraction time was used (0 – 30 min).
However, the increase was not that
significant from 5 min to 30 min especially for styrene and toluene. The extraction
efficiency reached a maximum at 30 min for toluene, ethylbenzene, isopropylbenzene and n-propylbenzene, however, for styrene a maximum peak area at
35 min was observed. The decrease in peak area after further increase of extraction
time (45 min) was due to the desorption of the analytes from the fiber that were
supposed to compete with the absorption process for excessively long extraction
time.
In order to extract the maximum amount of analyte, the equilibrium time has to
be reached, but this is too long and impractical for routine analysis.
A short
88
extraction time is preferred in rapid detection, and so the extraction time of 5 min
was considered to be adequate for the subsequent experiments as a compromise
between response and analysis time.
5.3.6
Desorption Time Studies
Various desorption times (1, 3 and 5 min) were evaluated (Fig. 5.6). By
decreasing the time of desorption, chromatographic resolution was improved, while
avoiding overlapping of some of the peaks that occurred at longer periods of
desorption. On increasing desorption time from 1 to 3 min, the uptake of most of the
compounds was slightly increased. However, further increased to 5 min and above
gave no significant differences in peak areas for most compounds. On this basis, the
time of desorption yielding the best chromatographic resolution without relevant
decreases in the peak areas of most of the compounds was taken as 3 min.
70000
Peak area (µV)
60000
50000
40000
30000
20000
10000
0
0
1
2
3
4
5
6
Time (min)
toluene
ethylbenzene
n-propylbenzene
styrene
iso-propylbenzene
Fig. 5.6: Desorption time profile for the five analytes
89
In order to determine whether the desorption was completed, the SPME fiber
was again desorbed after each analysis. No carryover was observed, demonstrating
that 3 min were enough for complete desorption of the compounds from the
stationary phase.
5.3.7
Sample Agitation
To minimize the time required for the volatile organic compounds to reach
equilibrium between the fiber stationary phase and the aqueous sample, the stirring
speed of the aqueous solution was optimized. Stirring of the sample reduces the time
needed to reach equilibrium because it enhances the diffusion of analytes towards the
fiber coating and reduces the extraction time for the head-space extraction. In HSSPME, stirring also facilitates mass transfer between the headspace and the aqueous
phase.
The extraction efficiency was enhanced when stirring rate was increased from
0 rpm to 800 rpm except for styrene (Fig.5.7). For toluene, the increase of extraction
efficiency was not observed after the stirring rate reached 800 rpm, and the
extraction efficiencies for ethylbenzene, iso-propylbenzene and n-propylbenzene also
increased slowly at the same time. The extraction efficiency for styrene was slightly
reduced with stirring, this may be due to the stirring speed causing the transfer of
styrene from water to headspace faster than that of the mass transfer from headspace
to fiber coating, and thus a stirring speed increase does not improve the HS-SPME
kinetics for the analyte.
Competition among the different analytes for fiber
absorption during stirring may also cause the decrease in extraction efficiency for
styrene. Based on these results, the stirring speed of 800 rpm was selected for further
experiments.
90
90000
80000
Peak area (µV)
70000
60000
50000
40000
30000
20000
10000
0
0
200
400
600
800
1000
1200
Stirring rate (rpm)
toluene
ethylbenzene
n-propylbenzene
styrene
iso-propylbenzene
Fig. 5.7: Effect of sample agitation rate on the extraction efficiency of analytes
5.3.8
Addition of Salt
The extraction efficiency may also be improved by adding soluble salts to the
sample. In principle, supersaturation of the sample with salts is most effective for
the extraction of analytes onto the fiber due to the salting-out effect. The addition of
salt usually increases the ionic strength of the sample. This reduces the solubility of
analytes which are more easily retained and the partition coefficients can be several
times higher.
The influence of salt addition in HS-SPME procedure was investigated by
comparing the extraction efficiency of samples with addition of 30% KCl and
without addition of KCl. The addition of 30% KCl yielded a saturated solution and
this resulted in increased in the peak area of the analytes, from 6% (isoPropylbenzene) to 41% (styrene) enhancement (Fig. 5.8).
The reason was
considered to be the increase of ionic strength in aqueous samples by adding salt, and
the decrease in solubility of analytes and therefore, more analyte was released into
91
the headspace. Thus, saturation with salt additives was shown to be an effective
method to lower the LOQ, and it could also normalize the influence of a random salt
concentration in sample matrix to improve reproducibility.
80000
Peak area ( µV)
70000
60000
50000
40000
30000
20000
10000
0
Styrene
Toluene
Ethylbenzene
without KCl
iso-Propylbenzene
n-Propylbenzene
with KCl
Fig. 5.8: Salting out effect on the five analytes
5.4 Performance of the Method
The method was validated in terms of LOD, LOQ, linearity, precision and
accuracy by using the experimental setting providing the optimized conditions. A
blank sample was prepared using purified deionized water. Calibration curve was
prepared by spiking blank sample with different level of standard mixtures. Using
the chosen HS-SPME conditions for water sample spiked with standard mixture at
different levels, the performance characteristics of the method were evaluated for
each analyte using the developed method.
5.4.1
LOD and LOQ
Detection and quantification limits were estimated following the signal-tonoise approach as mentioned in the material test (section 3.8.2.1). These parameters
92
were calculated as the minimum concentration that generated a peak signal at least
three times higher (LOD) and ten times higher (LOQ) than the signal from adjacent
noise. Determination was made by calculating the average signal-to-noise ratio
(S/N) from ten replicate runs of a blank sample on different day together with a
standard mixture of low concentration. Based on the results, it was found that the
calculated LOQ for all the analytes were far beyond the ability to differentiate a peak
from random noise. Therefore, the ratio for LOQ was adjusted to five times higher
than the signal. The LOD and LOQ values were converted into concentration unit by
analyzing mixture of standard solution and the results are presented in Table 5.1. In
general, most analytes are readily detected at less than 1ppb except for toluene with
LOD of 2.66 ppb. n-Propylbenzene has lowest LOD and LOQ and toluene has the
highest LOD and LOQ values. Excellent results were obtained for LOD and LOQ for
all the target analytes, thus, proving the potential of the method for the determination
of the five analytes at trace levels, which is very suitable for migration testing of
packaging.
Table 5.1: Data obtained for each test compound based on signal-to-noise approach
Compound
Mean (peak height values), p = 10
Blank
% RSD
S/N=3
S/N=5
311
LOD
(ng/mL)
0.58
LOQ
(ng/mL)
0.97
Styrene
62
40
186
Toluene
61
24
182
304
2.66
4.43
Ethylbenzene
59
23
176
294
0.78
1.63
iso-Propylbenzene
56
26
168
281
0.40
0.67
n-Propylbenzene
64
20
193
321
0.28
0.47
In the experiment, variation of the blank signal from day-to-day basis as
indicated by the % RSD in Table 5.1 was similar to the results obtained using the
material test. This is because the same GC-FID was used for both material test and
migration test, and the variation of blank signal was mainly due to instrument factor.
93
5.4.2
Linearity
Using a range of spiking concentrations of standard solution in deionized
water, the linear dynamic range was determined for each analyte. Each solution was
subjected to the HS-SPME analysis three times. The linear regression values for
styrene, toluene, ethylbenzene, iso-propylbenzene and n-propylbenzene were
obtained.
By visual inspection of residual plot (Fig. 5.9), the outlier data was
rejected and applying regression model test (Freg) and lack of fit test (Flof) to test the
linearity (Table 5.2). The linearity range varied among the different analytes by
using SPME extraction. The results shows that good linearity was demonstrated for
each analyte in the range tested (Table 5.3).
(a)
0.4000
0.3000
y-residual
0.2000
0.1000
0.0000
0.0000
-0.1000
0.0100
0.0200
0.0300
0.0400
0.0500
0.0600
0.0700
0.0800
0.0900
-0.2000
-0.3000
Conc. (mg/L)
(b)
0.2500
0.2000
0.1500
y-residual
0.1000
0.0500
0.0000
0.0000
-0.0500
0.0100
0.0200
-0.1000
-0.1500
-0.2000
Conc. (mg/L)
0.0300
94
(c)
0.1500
0.1000
Y-residual
0.0500
0.0000
0.0000
-0.0500
0.0050
0.0100
-0.1000
-0.1500
Conc (mg/L)
(d)
0.1000
Y-residual
0.0500
0.0000
0.0000
0.0050
0.0100
-0.0500
-0.1000
Conc (mg/L)
(e)
0.2000
0.1500
y-residual
0.1000
0.0500
0.0000
0.0000
-0.0500
0.0100
0.0200
-0.1000
-0.1500
-0.2000
Conc. (mg/L)
Fig. 5.9: Residual plot of the targeted analytes (a) Toluene; (b) Ethylbenzene;
(c) iso-Propylbenzene; (d) n-Propylbenzene; and (e) Styrene with limits ± t(0.05,
np-2).Sres
95
Table 5.2: Results for regression test and lack-of-fit test
Analyte
Regression test
Freg[1, n(p-1), 5%]
Fcal
Fcrit
Lack-of-fit test
Flof[n-2, n(p-1), 5%)
Fcal
Fcrit
Styrene
1260.42
8.29
3.53
4.58
Toluene
2112.17
8.53
4.33
4.77
Ethylbenzene
2755.06
8.40
2.46
4.67
iso-Propylbenzene
3883.79
8.40
3.87
4.67
n-Propylbenzene
1260.42
8.29
3.53
4.58
Table 5.3: Summary of findings for linearity testing using HS-SPME
Analyte
Linearity Least square linear
range
regression equation
(ng/mL)
Correlation
coefficient,
r
Styrene
1 - 20
y=66.590x+0.0613
0.9883
y-intercept
passes
through
origin
yes
Toluene
4.5 - 90
y=26.3901x+0.0654
0.9937
yes
Ethylbenzene
1.5 - 30
y=63.0701x+0.0681
0.9957
yes
iso-Propylbenzene
0.5 - 10
y=110.5050x+0.0212
0.9974
yes
n-Propylbenzene
0.5 - 10
y=131.6803x+0.0393
0.9971
yes
5.4.3
Precision
The method precision was evaluated by testing three concentration levels, i.e.
low, medium and high levels within the linearity range in aqueous solution (Table
5.4).
Table 5.4: Three different concentration levels applied for precision testing
Level
Concentration, ng/mL
Styrene
Toluene
Ethylbenzene
iso-Propylbenzene
n-Propylbenzene
Low
1
4.5
1.5
0.5
0.5
Median
10
45
15
5
5
high
20
90
30
10
10
96
Based on the results in Table 5.5, the RSD values for intra-day repeatability
were smaller than the inter-day precision as expected except for ethylbenzene at the
median concentration level.
The precision varied at different concentration levels,
and generally the RSD values were higher at the lower concentration level for interday precision. For intra-day repeatability, there was no specific trend observed
among the RSD values at different concentration levels.
Table 5.5: Intra-day and inter-day precision for migration test method
Conc.
level
RSD (%)
Intra-day (p = 3)
Inter-day (p = 4)
Styrene
Toluene
EB
IPB
NPB
Styrene
Toluene
EB
IPB
NPB
Low
2.98
3.37
3.53
6.09
1.88
15.23
7.29
10.25
13.13
8.07
Median
6.63
4.57
7.65
0.55
0.23
16.98
10.30
6.41
3.97
3.04
High
1.72
0.77
4.32
0.97
4.83
3.55
3.83
4.48
7.72
3.13
EB = ethylbenzene, IPB = iso-Propylbenzene, NPB = n-Propylbenzene
5.4.4
Accuracy
Extraction recoveries for the five analytes were calculated respectively by
addition of standard mixture to blank samples. Good recoveries were obtained at
median and high spiking levels whereas for low spiking levels, the recovery was in
the range of 60% to 78% (Table 5.6). The precision improved as the concentration
level increased for styrene, toluene and ethylbenzene. The RSD values were about
15% and lower with the exception of n-propylbenzene of 20.08% at low spiking
level. In general, these results show good efficiency of the developed method in
term of extraction recovery as well as of precision.
97
Table 5.6: Evaluation of method accuracy by extraction recovery, p = 3
Analyte
Styrene
Toluene
Ethylbenzene
iso-Propylbenzene
n-Propylbenzene
5.5
Spiked level
(ng/mL)
1
% Recovery
% RSD
74
15.01
5
115
9.55
15
100
2.51
4.5
78
12.45
22.5
116
7.69
67.5
102
1.39
1.5
61
11.63
15
101
9.56
30
89
2.42
0.5
62
6.45
5
105
11.20
10
84
13.59
0.5
71
20.08
2.5
107
2.16
7.5
100
7.31
Application of the Method
The amount of absorption of the analytes on the fiber depends strongly on the
extraction temperature (refer Section 5.3.4), therefore, samples which have been
heated up during migration studies should be allowed to cool down, and standard
solution stored in the refrigerator should be allowed to warm up to a constant
temperature (i.e. room temperature) before SPME analysis. In each batch of sample,
a blank GC run was introduced with a fiber between sampling to eliminate the
memory effect of the fiber.
98
1,4-diethylbenzene was used as internal standard as it was not present in the
PS food packaging and water solution. The internal standard showed similar effect
as the targeted analyte when variation of SPME parameters was studied.
The applicability of the validated method for the determination of VOCs in
PS food packaging samples was demonstrated (Fig. 5.10).
2
3
1
0
2.5
5
7.5
Time (minutes)
10
12.5
Fig. 5.10: GC chromatogram showing the analytes migrated from a polystyrene cup.
Peaks: 1 = Ethylbenzene; 2 = Styrene; and 3 = 1,4-Diethylbenzene (ISTD)
Three types of commercially available disposable polystyrene cup and bowl
were purchased for analysis and data obtained are reported in Table 5.7. Prior to
performing the migration test, the levels of residual VOCs in packaging materials
were determined using the material test method developed. The concentrations were
calculated by interpolation of the total area values obtained for the samples in the
linear graphs obtained for standards in aqueous solution.
Toluene, iso-
propylbenzene and n-propylbenzene were not detected in the selected samples under
the studied conditions.
99
Table 5.7: Mean concentration of analytes migrated from samples into water
solution.
Sample type/capacity
(material test results,
mg/kg)
Leaching
solution
Leaching
condition
Mean analyte conc.
(ng/mL)
Styrene Ethylbenzene
PS bowl /500mL
Water
(80°C)
Water
(60°C)
Water
(24°C)
80°C/30 min
24°C/30 min
60°C/30 min
24°C/30 min
24°C/30 min
86
50
<LOQ
ND
ND
ND
ND
ND
ND
ND
Water
(80°C)
Water
(60°C)
Water
(24°C)
80°C/30 min
24°C/30 min
60°C/30 min
24°C/30 min
24°C/30 min
97
45
<LOQ
ND
ND
<LOQ
ND
ND
ND
ND
Water
(80°C)
Water
(60°C)
Water
(24°C)
80°C/30 min
24°C/30 min
60°C/30 min
24°C/30 min
24°C/30 min
293
224
126
48
<LOQ
64
50
<LOQ
ND
ND
(Styrene: 657 ,
Ethylbenzene: 134)
PS bowl /400 mL
(Styrene: 250,
Ethylbenzene: 32)
PS cup /200 mL
(Styrene :593,
Ethylbenzene: 243)
ND – not detected
As shown in table 5.7, styrene and ethylbenzene were detected and
quantitated at different concentration levels depending on the types of samples and
leaching conditions. Styrene and ethylbenzene were below LOQ levels by using
leaching solution of room temperature (24°C).
When the samples were in contact
with water of higher temperature (60°C), styrene (126 ng/mL and 48 ng/mL) was
detected in the leaching solution of polystyrene cup samples, and all the samples
detected with styrene in leaching solution of highest temperature (80°C).
Ethylbenzene was below LOQ levels for samples that were exposed to leaching
solution of 60°C and 80°C, except for polystyrene cup in which ethylbenzene at the
levels of 64 ng/mL and 50 ng/mL was detected at the two different leaching
conditions.
This shows that migration of analytes increased when leaching solution
of higher temperature was used. The results also showed that the amount of analytes
migrated were increased when the temperature of the leaching solution was kept
100
constant in comparison with the leaching condition of room temperature for 30 min.
This could be due to the migration of analytes was slow down as the leaching
solution began to cool down at room temperature condition.
Even though the number of samples considered does not make possible a
definitive conclusion, this behavior could be ascribed to the temperature effect of the
migration. Under higher temperature, the analyte, being extremely volatile can be
more easily released from the matrix. Based on the results obtained for the samples
of different capacities, higher levels of styrene were generally found for container of
small size (polystyrene cup, capacity of 200 mL), this is in good agreement with the
findings reported by MAFF [30], in which higher levels of styrene were found in
food products packed in small containers.
101
CHAPTER 6
CONCLUSIONS AND SUGGESTIONS FOR FURTHER STUDIES
6.1
Conclusions
Material test and migration test for residual styrene monomer, toluene,
ethylbenzene, iso-propylbenzene, n-propylbenzene in polystyrene food packaging
have been successfully developed and validated. These analytes could be determined
in a satisfactory manner by gas chromatography using a flame ionization detector.
This study demonstrates the feasibility of using the dissolution technique with
direct injection for the analysis of residual styrene monomer and other VOCs in
polystyrene food packaging.
efficiency
for
styrene,
The dissolution technique assures a good extraction
toluene,
ethylbenzene,
iso-propylbenzene
and
n-
propylbenzene in polystyrene matrices and overcome the lost of analytes during
precipitation by using dissolution-precipitation technique.
The developed material test method is simple, less tedious extraction
procedures and has good linearity in a wide range of concentrations (0.4 – 80
µg/mL), with good recovery and precision.
This technique possesses the advantage
of speed, as it does not require an equilibrated step as compared to headspace
method. However, the direct injection lacks sensitivity, with LOQ found to be 8
mg/kg.
Nevertheless, as the maximum levels of these compounds allowed in
polystyrene food packaging (based on Japan Food Standard) are high, this technique
is suitable for material testing of food packaging.
The validated method enables
successful quantification of the five analytes in various kinds of polystyrene food
packaging. Thus, this simple method can be applied to measure and screen styrene
102
monomer and VOCs in the polystyrene food packaging, although it has the limitation
of low sensitivity and requires relatively large volumes of organic solvent.
SPME technique helps to overcome the problem of sensitivity and use of
hazardous organic solvent used in the dissolution technique. In this study, HS-SPME
was successfully developed for testing of migration of styrene monomer and other
VOCs from food packaging into water as food simulant. Based on the investigation,
it was found that the sample volume, elutropic strength, extraction temperature and
time, sample agitation and salt addition influenced the amount of analytes extracted.
Therefore, optimization of SPME parameters is important to ensure the maximum
extraction of the analytes by SMPE technique.
The ability of the PDMS fiber to adsorb and concentrate the analyte of
interest enabled the analysis of the test compound at low levels (ppb and sub-ppb
levels) suitable for VOCs migration study. The linearity range varied depending on
the test compound whereas the precision and accuracy were comparable to the
dissolution technique. The HS-SPME-GC-FID method developed is suitable for
identifying and quantifying VOCs particularly styrene, toluene, ethylbenzene, isopropylbenzene and n-propylbenzene that migrate through polystyrene packaging
material.
Based on this migration study in polystyrene bowls and cups, styrene and
ethylbenzene are prompted to more intense migration through the packaging material
into water at elevated temperature. The storage temperature plays an important factor
that contributes to the amount of VOCs that migrate. This study shows that the
amount of VOCs that migrated is proportional to the storage temperature. The
highest amount of VOCs was found at the highest temperature tested (80°C).
In summary, HS-SPME is very effective as a sample preparation technique
for studying the migration of VOCs from polystyrene packaging material.
SPME
provides simple, rapid and solvent-free technique, and offers a dramatic sensitivity
enhancement as compared to the conventional sample preparation techniques. The
optimized HS-SPME procedure can be proposed as a fast monitoring method for the
analysis of migration of VOCs from polystyrene and other food packaging material.
103
6.2
Suggestions for Further Studies
This work has successfully developed the material test based on dissolution
sample preparation technique and GC-FID for detection and quantification of five
test compounds namely styrene, toluene, ethylbenzene, iso-propylbenzene and npropylbenzene for polystyrene food packaging. Further work is necessary to expand
the list of test compounds and samples to be tested. The investigations can look into
other VOCs and other types of packaging such as polycarbonate, PE, PP etc. which
are commonly available as food packaging materials.
GC-MS analysis is
recommended for future investigations for the improved VOCs characterization of
food packaging and to identify the unknown compounds present in the packaging
material.
This study proved that HS-SPME is a powerful tool for trace level analysis.
It is applicable to study migration of residual chemicals from food packaging into
food simulant or food-in-contact using HS-SPME technique. The performance
characteristics of the method can be improved by automation of SPME devices with
GC-FID. This will help to reduce errors that attributed to the manual handling of
SPME as in this study. Additional work should continue to explore the usefulness of
SPME coupled with GC-MS to provide near real-time screening and identification of
unknown analytes. Further investigation should include other food simulants to
cover the rest of the food groups such as oily, acidic and alcoholic products. It is
better still if the migration test can be directly performed on the food that is incontact with the packaging material, as using food stimulant may underestimate or
overestimate of the migration of the compounds.
In addition, further studies are needed to investigate other factors that may
influence the migration such as chemical and physical properties of food, and
polymer. This will help to a better understanding of the migration process, to predict
potential exposure of consumers to the VOCs from packaging materials, and control
measures to be taken to reduce the migration of chemicals from food packaging into
food-in-contact.
104
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APPENDIX A
Presentations and Publications
Parts of this work have been presented at the following symposia:
1.
Susie Lu Ling, Mohd Marsin Sanagi, Wan Aini Wan Ibrahim, Ahmedy Abu
Naim and Zalilah Nasir “Comparison of Different Methods for Estimating
Detection and Quantification Limits of Volatile Organic Compounds by Gas
Chromatography”. Oral presentation at the 19th Malaysian Analytical
Chemistry Symposium (SKAM 19) and 2nd Malaysian Conference on
Catalysis (MyCat 2), Melaka, Malaysia, 22 – 24 August 2006.
2.
Mohd Marsin Sanagi, Susie Lu Ling, Zalilah Nasir, Wan Aini Wan Ibrahim
and Ahmedy Abu Naim “Determination of Residual Styrene Monomer and
Other Volatile Organic Compounds in Polystyrene Food Packaging by Gas
Chromatography”. Poster presentation at the National Conference on Food
Science and Nutrition 2006, Sabah, Malaysia, 13 – 14 December, 2006.
3.
Mohd Marsin Sanagi, Susie Lu Ling, Zalilah Nasir, Wan Aini Wan Ibrahim
and Ahmedy Abu Naim
“Determination of Residual Volatile Organic
Compounds Migrated from Polystyrene Food Packaging into Food Simulant
by
Headspace-
Solid
Phase
Microextraction-Gas
Chromatography”
Presented at the 12th Asian Chemical Congress (12ACC), Putra World Trade
Centre (PWTC), Kuala Lumpur, Malaysia, 23-25 August 2007.