Development of a Novel Mass Spectrometric ... - Jacobs University

Development of a Novel Mass Spectrometric Methodology for
the Analysis of Hydrocarbon Content in Light Shredder Waste
by
Nadim Hourani
A thesis submitted in partial fullfilment
of the requirements for the degree of
Doctor of Philosophy
in Chemistry
Approved, Thesis Committee
Prof. Dr. Nikolai Kuhnert
Jacobs University Bremen
Prof. Dr.-Ing. Dieter Lompe
Hochschule Bremerhaven
Dr. Helge Weingart
Jacobs University Bremen
x
x
x
Date of Defence: 02.04.2012
x
School of Engineering and Science

“That what doesn't kill me makes me stronger”
Friedrich Nietzsche (German philosopher)

Declaration of Authorship
I ,Nadim Hourani, hereby declare that this thesis and the work presented in it is
entirely my own. Where I have consulted the work of others, this is always clearly
stated.
Signed: Nadim Hourani
Date: 10.April. 2012

Acknowledgements
First and farmost, thanks are to ‘God’ for my life through all tests in the past years.
You have made my life more bountiful. May your name be exalted, honoured, and
glorified.
My sincere gratitude goes to Prof. Dr. Nikolai Kuhnert for his continuous supervision,
advice, support and inspiration as well as for his confidence he gifted to work in
generous freedom. Thanks for being able to work with modern analytical techniques
and to attend interesting international conferences. I’m so glad to have come to know
him. I’d like to deeply thank the Fond für Angewandte Umweltforschung des Landes
Bremen and the Bremer Entsorgungsbetriebe (BEB Company) for the support given to
this project.
I would like to thank my dear wife Adal for support and love through out the study
years, my parents Mahmoud and Salwa Hourani, my brothers Wassim, Ibrahim and
Hamzi, and my sisters Fatemah and Kawkab, all my dear friends and in particular
Hany Nour. My sincere love and gratitude goes for Dr. Ursula Zimoch whose splendid
care and support were more than intriguing for me during my study. Needless to say
how much gratitude I owe to Prof. Dr. Angela Danil De Namor for continued support
and advice. Without her contribution this Ph.D study wouldn’t have been achieved.
I am tempted to individually thank all my colleagues in our laboratory in as much as
thanks to Mrs Anja Müller, for the technical support.

This work has been carried out under the supervision of Prof. Dr. Nikolai Kuhnert in
the analytical and organic laboratory of Chemistry Department at Jacobs University
Bremen in Germany.
Abstract
The lack of a routine characterization method for non-volatile hydrocarbons has been
an ongoing problem preventing mass spectrometry from the analysis of these
hydrocarbons within many sources. Non-polar hydrocarbons are still difficult to be
detected by mass spectrometry. Although several studies targeted this problem, lack of
self-ionization has been limiting the ability of mass spectrometry to examine these
hydrocarbons.
A novel identification method for saturated straight-chain hydrocarbons in light
shredder waste fraction under atmospheric pressure chemical ionization mass
spectrometry (APCI-MS) has been developed. Ionization of alkanes under nitrogen gas
source favoured hydrogen abstraction producing majorly (M-H) + ions which are
strictly corresponding to their respective series of n-alkanes between n-decane (C10)
and n-tetracontane (C40). The method is shown to produce intact gas phase ions of n-
alkane in both reference and real life waste samples. APCI-MS 2 fragmentation data
assisted in the structural verification of the n-alkanes investigated in both standard and
waste mixtures. Additionally the total chemical composition of the light shredder
waste fraction was translated by the same method. The mass spectrum displayed a
bimodal distribution of odd and even mass ions with a molecular weight distribution
range of m/z 200-900 Da. Molecular formulas for a 1000 unsaturated hydrocarbon
compounds suggested a dehydrogenation process. The molecular masses were plotted
on a Kendrick plot which was successfully employed for monitoring sample
degradation.
Another selection of high mass linear, branched and cyclic hydrocarbons, reported to
be notoriously difficult to ionize, were examined during this study. Using optimized
APCI conditions all of these analytes could be ionized without the use of an additional

ionization aid and without fragmentation. This finding represents a promising step
towards extending the applicability of mass spectrometry to complex non-polar
hydrocarbon analyses.

Contents
Contents
Declaration of Authorship................................................................................................ iii 4
Achnowledgement………………………………………………………………………………iv
Abstract………………………………………………………………………………..…..v
Contents ........................................................................................................................ vii
List of Figures ................................................................................................................ ix
List of Tables................................................................................................................ xiii
Publications, Manuscripts ............................................................................................. xiv
Abbreviations ................................................................................................................ xv
1 Introduction .................................................................................................................. 1
1.1 Complex Mixtures .......................................................................................................... 1
1.2 Presence and Fate of Hydrocarbons in Contaminated Sites .............................................. 4
1.3 Use of Mass Spectrometry for Hydrocarbon Analyses..................................................... 8
1.3.1 EI and CI.................................................................................................................11
1.3.2 ESI, DESI and MALDI ...........................................................................................11
1.3.3 FD and FI ................................................................................................................12
1.3.4 APPI .......................................................................................................................13
1.3.5 APLI .......................................................................................................................14
1.3.6 APCI, LIAD/CI and LIAD/APCI ............................................................................14
1.3.7 Summary.................................................................................................................17
1.3.8 Ionisation via APCI .................................................................................................20
1.3.9 Petroleomics ...........................................................................................................22
1.3.10 Kendrick plot ..........................................................................................................24
1.4 Light Shredder Waste in Bremen (Project Objectives)....................................................26
1.5 Scope and Significance of this Work..............................................................................30
2 Experimental .............................................................................................................. 31
2.1 Chemicals and Model Standards ....................................................................................31
2.2 Preparation of Samples ..................................................................................................32
2.2.1 Alkane Standards and Shredder Waste Samples Preparation ....................................32

Contents
2.2.2 Preparation of Oxidation Products from Shredder Extract ........................................34
2.3 MS Operating Conditions ..............................................................................................34
2.4 Graphical Presentation of the Used Instruments .............................................................36
3 Results and Discussion ............................................................................................... 37
3.1 APCI-TOF-MS of Standard n-Alkanes ..........................................................................37
3.2 APCI-TOF-MS of a Variety of Hydrocarbons ................................................................44
3.3 Pathway of Ionisation of Hydrocarbon Standards under APCI Conditions ......................49
3.4 Light shredder Waste Analysis ......................................................................................53
3.4.1 (+)APCI-TOF-MS of Waste Sample ........................................................................53
3.4.2 Calibration ..............................................................................................................57
3.4.3 Identification of Polychlorinated Biphenyls (PCBs) in (-) APCI-TOF-MS ...............63
3.4.4 Tandem MS Measurements .....................................................................................65
3.4.5 Tandem MS of Derivatised Compounds ..................................................................76
3.4.6 Tandem MS of PCBs ...............................................................................................77
3.4.7 Oxidative Degradation of Complex Mixture of Shredder Waste ...............................79
3.4.8 Quantification .........................................................................................................84
3.5 Application of the Methodology to Other Complex Mixtures .........................................88
3.5.1 Analysis of Solid Waste from Lebanon ....................................................................88
3.5.2 Analysis of Car Motor Oil .......................................................................................91
3.5.3 Analysis of Asphaltenes ..........................................................................................96
3.6 Kendrick Plot and Interpretation of Complex Data from Various Complex Mixtures ......98
3.6.1 Light Shredder Waste ..............................................................................................98
3.6.1.1 Kendrick Plot for PCBs ................................................................................... 106
3.6.1.2 Kendrick Plot for Oxidation Products .............................................................. 108
3.6.2 Lebanon Waste...................................................................................................... 109
3.6.3 Oil sample ............................................................................................................. 110
3.6.4 Asphaltenes ........................................................................................................... 112
Conclusions ................................................................................................................. 114
References ................................................................................................................... 116

List of Figures
List of Figures
Figure 1-1 Examples of aliphatic and aromatic hydrocarbons in crude oils.................................. 8
Figure 1-2 Range of ionisation techniques employed with different types of compounds ...........10
Figure 1-3 Matrix-assisted laser desorption/ionization (MALDI) ...............................................12
Figure 1-4 Complex data management ......................................................................................19
Figure 1-5 Schematic description of the atmospheric pressure chemical ionisation (APCI)
interface and the mechanism of ion formation in the corona discharge region .....................21
Figure 1-6 Kendrick mass defect vs nominal Kendrick mass for odd mass ions in crude oil
sample. Note the visual vertical separation of compound classes (O, O 2 , O 3 S) and types (e.g.,
compounds with different number of rings plus double bonds) based on mass defect and the
simultaneous visual horizontal distribution of number of CH 2 groups for a given compound
class and type. 105 ................................................................................................................26
Figure 1-7 Shredding Plant ........................................................................................................27
Figure 1-8 Light shredder waste fraction set for biological treatment in a prepared unit. ............28
Figure 1-9 UCM feature of hydrocarbon content of light shredder waste in GC .........................29
Figure 2-1 Instruments used in the study ..................................................................................36
Figure 3-1 APCI mass spectrum in positive ion mode of dodecane (C 12 H 26 ) showing (M-3) + H 2 O
ion as product ion at m/z 185.2 ...........................................................................................38
Figure 3-2 APCI mass spectrum in positive ion mode of tridecane (C 13 H 28 ) showing (M-3) + H 2 O
ion as product ion at m/z 199.2 ...........................................................................................38
Figure 3-3 APCI mass spectrum in positive ion mode of a mixture containing decanes (C 10 H 22 ),
dodecane (C 12 H 26 ), tridecane (C 13 H 28 ), tetradecane (C 14 H 30 ), pentadecane (C 15 H 32 ) and
hexadecane (C 16 H 34 ) showing (M-3) + H 2 O ions at m/z 157.2, 185.2, 199.2, 213.2, 227.2 and
241.3 respectively...............................................................................................................39
Figure 3-4 APCI mass spectrum in positive ion mode of hexatricontane (C 36 H 74 ) showing an (M-
1) + and (M-3) + H 2 O at m/z 505.6 and 521.6 respectively ......................................................39
Figure 3-5 APCI mass spectrum in positive ion mode of dotriacontane (C 32 H 64 ), hexatricontane
(C 36 H 74 ) and tetracontane (C 40 H 82 ).....................................................................................40
Figure 3-6 APCI mass spectrum of model mixture of n-alkanes injected using n-pentane ..........41
Figure 3-7 APCI-MS spectrum in positive ion mode of C7-C40 showing (M-1) + ions of n-alkanes
..........................................................................................................................................42
Figure 3-8 APCI mass spectrum of n-paraffin mixture ...............................................................43
Figure 3-9 APCI mass spectrum of C12-C60 .............................................................................43
Figure 3-10 Structures of various hydrocarbons investigated by APCI-TOF-MS ........................45

List of Figures
Figure 3-11 APCI spectrum of the eight Chiron hydrocarbon mixture (for structures see figure 3-
10) .....................................................................................................................................46
Figure 3-12 APCI mass spectrum of n-decyl benzene, phytane and 5-α-cholestane ....................48
Figure 3-13 APCI of high mass n-alkanes..................................................................................48
Figure 3-14 Total APCI mass spectrumin of the mixture of seventeen compounds (see table 3.2)
..........................................................................................................................................48
Figure 3-15 Suggested graphical scheme for ionisation mechanism of hydrocarbon upon APCI .50
Figure 3-16 APCI mass spectrum after the addition of D 2 O to C40 ...........................................52
Figure 3-17 APCI mass spectrum of deuterated tetracosane (D-C24) .........................................52
Figure 3-18 APCI-MS 2 spectrum of C32 showing (M-3) + fragment at m/z 447.4 from precursor
ion at m/z 465.8 corresponding to (M-3) + H 2 O .....................................................................53
Figure 3-19 APCI-MS 2 spectrum of C29 showing (M-1) + fragment at m/z 407.3 from precursor
ion at m/z 425.1 corresponding to (M-1) + H 2 O .....................................................................53
Figure 3-20 APCI (+) mass spectrum of waste sample extracted using n-heptane/Acetone ..........54
Figure 3-21 APCI mass spectrum of waste sample extracted using n-heptane only .....................55
Figure 3-22 Mass spectra of the waste sample purified by using 2 gs (a), 4 gs (b) and 6 gs (c) of
florisil during purification. ..................................................................................................56
Figure 3-23 Enlarged section of (+) MS showing bimodal distribution of odd and even mass ions
..........................................................................................................................................57
Figure 3-24 APCI/APPI standard recommended calibrant for APCI source ...............................58
Figure 3-25 APCI mass spectra in positive ion mode of C7-C40 calibrant ................................59
Figure 3-26 (-) APCI mass spectrum showing identified PCBs in waste sample .........................64
Figure 3-27 (-) APCI mass spectrum of PCBs Congener Mix ....................................................64
Figure 3-28 (-) APCI mass spectrum of decachlorobiphenyl standard (C 12 OCl 9 ) with simulated
isotope pattern as suggested by Bruker Software .................................................................64
Figure 3-29 APCI-ion trap mass spectrum of waste sample......................................................66
Figure 3-30 Low mass distribution in APCI-iontrap mass spectrum for waste sample ..............66
Figure 3-31 APCI-MS 2 of tetracosane with precursor ion at m/z 337 corresponding to (M-1) + ....66
Figure 3-32 APCI-MS 2 of pentacosane with precursor ion at m/z 351corresponding to (M-1) + ....67
Figure 3-33 APCI-MS 2 of nonacosane with precursor ion at m/z 407 corresponding to (M-1) + ....67
Figure 3-34 APCI-MS 2 of dotriacontane with precursor ion at m/z 449 correspon- ding to (M-1) +
..........................................................................................................................................67
Figure 3-35 APCI-MS 2 of molecular ion of tetracontane (C40) at m/z 562 .................................68
Figure 3-36 APCI-MS 2 of molecular ion of nonatriacontane (C39) at m/z 548 .............................68
Figure 3-37 APCI-MS 2 of molecular ion of octatriacontane (C38) at m/z 534 ............................68
Figure 3-38 APCI-MS 2 spectra of m/z 561, 547, 519 and 505 corresponding to (M-1) + ions of
C40, C39, C37 and C36 respectively within a waste extract ................................................69

List of Figures
Figure 3-39 MS 2 fragmentation spectra for nonacosane C 29 H + 59 within standard n-alkane mixture
(a) and within waste sample (b) ..........................................................................................71
Figure 3-40 APCI-MS 2 spectrum of squalene of m/z 411 ...........................................................72
Figure 3-41 APCI-MS 2 spectra of four selected ions within the waste sample of m/z 409,411,413
and 415 ..............................................................................................................................72
Figure 3-42 Fragmentation spectrum of 5-α-cholestane at m/z 371 C 27 H + 47 within standard 5-αcholestane
sample...............................................................................................................74
Figure 3-43 Fragmentation spectra for C 27 H + 47 ion at m/z 371 within waste sample ....................74
Figure 3-44 APCI mass spectrum in positive ion mode of waste sample deriva- tised with
Agtriflate ............................................................................................................................76
Figure 3-45 APCI-MS 2 of a silver adducted complex at m/z 328 ion ..........................................77
Figure 3-46 Fragmentation of selected PCBs at m/z 306, 340 and 374 from the PCBs Congener
Mix ....................................................................................................................................78
Figure 3-47 Fragmentation of selected PCBs at m/z 306, 340 and 374 from the waste sample ....78
Figure 3-48 Fragmentation of high mass chlorinated components within the waste extract .........79
Figure 3-49 Positive APCI mass spectrum of waste sample before oxidation ..............................80
Figure 3-50 Positive APCI mass spectrum of waste sample after oxidation ................................80
Figure 3-51 Positive ESI mass spectrum of complex waste mixture after oxidation ...................82
Figure 3-52 Negative ESI mass spectrum of complex waste mixture after oxidation ..................82
Figure 3-53 Negative ESI mass spectrum of model mixture of hydrocarbon after oxidation .......83
Figure 3-54 APCI mass spectrum of spiked waste mixture with high mass n-alkanes .................84
Figure 3-55 APCI mass spectrum of deuterated dotriacontane C 32 D 66 .......................................85
Figure 3-56 A plot between Concentration vs Intensity for C20 .................................................85
Figure 3-57 A plot between Concentration vs Intensity for C29 .................................................86
Figure 3-58 A plot between Concentration vs Intensity for C38 .................................................86
Figure 3-59 A plot between Concentration vs Intensity for C40 .................................................87
Figure 3-60 Positive APCI mass spectrum of Lebanese waste sample 1 .....................................90
Figure 3-61 Negative polarity APCI of Lebanese waste sample 1 ..............................................90
Figure 3-62 Positive APCI mass spectrum of Lebanese waste sample 2 .....................................91
Figure 3-63 Negative polarity APCI mass spectrum of Lebanese waste sample 2 .......................91
Figure 3-64 APCI mass spectrum of S1 .....................................................................................94
Figure 3-65 APCI mass spectrum of S2 .....................................................................................94
Figure 3-66 APCI mass spectrum of S3 .....................................................................................94
Figure 3-67 APCI mass spectrum of S4 .....................................................................................95
Figure 3-68 APCI mass spectrum of S6 .....................................................................................95
Figure 3-69 APCI mass spectrum of S7 .....................................................................................95
Figure 3-70 APCI mass spectrum of S9 (contaminated through usage oil) .................................96

List of Figures
Figure 3-71 ESI mass spectrum of bitumen 1 using DCM as mobile phase ................................97
Figure 3-72 APCI mass spectrum of bitumen 1 using DCM as mobile phase .............................98
Figure 3-73 APCI mass spectrum of bitumen 2 using DCM as mobile phase .............................98
Figure 3-74 Kendrick plot for the light shredder waste ..............................................................99
Figure 3-75 Plot of DBE vs measured mass (m/z) for the hydrocarbon compone- nts of waste . 100
Figure 3-76 Plot of H/C ratio vs DBE (degree of unsaturation) of a light shredder waste sample
........................................................................................................................................ 100
Figure 3-77 Kendrick plot overlap of untreated I2 and I3 waste samples .................................. 103
Figure 3-78 Kendrick plot overlap of I3 and treated sample on small scale .............................. 103
Figure 3-79 Kendrick plot overlap between 2009 and 2011 waste samples............................... 104
Figure 3-80 Radar plot of four parameters related to five shredder waste samples varying by
operation time .................................................................................................................. 106
Figure 3-81 Kendrick plot of (CH 2 ) for waste mixture upon (-) APCI-MS ............................... 107
Figure 3-82 Kendrick plot of (Cl) for waste mixture upon (-) APCI-MS .................................. 107
Figure 3-83 Kendrick plot of (Cl) for PCBs Congener Mix upon (-) APCI-MS ........................ 108
Figure 3-84 Kendrick plot overlap of I3, O2 and O3 ................................................................ 109
Figure 3-85 Kendrick plot overlap of Leb S1 and Leb S2 heterogeneous waste samples........... 110
Figure 3-86 Kendrick plot overlap of Calpam oil and light shredder waste ............................... 110
Figure 3-87 Kendrick plot overlap of Calpam motor oil and contaminated through usage motor
oil .................................................................................................................................... 111
Figure 3-88 Kendrick plot of bitumen 1 upon ESI-MS using DCM solvent .............................. 112
Figure 3-89 Kendrick plot of bitumen 1 upon APCI-MS using n-heptane solvent .................... 112
Figure 3-90 Kendrick plot overlap of bitumen 1 and bitumen 2 using DCM in APCI-MS ......... 113

List of Tables
List of Tables
Table 1.1 Reference studies targeting various hydrocarbons ......................................................19
Table 2.1 Different shredder waste samples treated under different conditions ...........................33
Table 3.1 Summary of APCI data of n-alkanes ..........................................................................41
Table 3.2 Ions produced of model hydrocarbon compounds.......................................................47
Table 3.3 Molecular formula list of n-alkanes in waste sample ..................................................59
Table 3.4 Molecular formula list of some analytes of hydrocarbons in waste sample..................61
Table 3.5 CID MS 2 -stage tandem mass spectra for some of the positive ions of tetracosane,
pentacosane and squalene. ..................................................................................................73
Table 3.6 Quantities of few selected n-alkanes in waste samples ................................................88
Table 3.7 A selection of different car oils from different companies ..........................................93
Table 3.8 Operating conditions of small scale treatment reactor of shredder waste ................... 102
Table 3.9 Acquisition of data points considered in 2009 and 2011 samples .............................. 104
Table 3.10 Extracted data from 5 measured light shredder waste samples ................................ 105

Publications, Manuscripts and Conferences
Publications, Manuscripts
• Hourani, N., Kuhnert, N, Development of a novel direct-infusion
atmospheric pressure chemical ionization mass spectrometry method for the
analysis of heavy hydrocarbons in light shredder waste, Anal. Methods,
2012, DOI 10.1039/ C2AY05249K
• Hourani, N., Kuhnert, N, Investigating non-polar hydrocarbons by
atmospheric pressure chemical ionisation (APCI) mass spectrometry, Rapid.
Commun. of Mass Spectrom., 2012 (submitted).
• Hourani, N., Kuhnert, N, Translation of the unresolved complex mixture of
hydrocarbons in light shredder Waste by APCI-MS, 2012 (manuscript).
Conferences
• GDCh Science Forum, Bremen, Sep. 2011, poster presented, Development
of a novel direct-infusion atmospheric pressure chemical ionization mass
spectrometry method for the analysis of heavy hydrocarbons in light
shredder waste.
• Analytical Research Forum (ARF 11), Manchester, Jul. 2011, presented
poster, Development of a novel direct-infusion atmospheric pressure
chemical ionization mass spectrometry method for the analysis of heavy
hydrocarbons in light shredder waste.
• International Mass Spectrometry conference, Bremen, Sep. 2009, presented
poster A New Mass Spectrometrical Method for the Analysis of
Complex Mixtures of Organic Compounds

Abbreviations
Abbreviations
APCI
APCI/CS 2
APLI
APPI
BEB
CrO 3
CI
CID
ClMn
Co(Cp) 2
DA-APPI
D 2 O
DCM
DESI
EI
ELV
EPA
ESI
FD
FD MS
FI
FI MS
FT ICR
Atmospheric pressure chemical ionisation
Atmospheric pressure chemical ionisation/ Carbon disulfide
Atmospheric pressure laser ionisation
Atmospheric pressure photoionization
Bremer Ensorgungsbetriebe
Chromium trioxide
Chemical ionisation
Collision induced dissociation
Manganese chloride
Cobalt cyclopentadienyl
Dopant assisted atmospheric pressure photoionization
Deuterium oxide
Dichloromethane
Desorption electrospray ionisation
Electron ionisation
End of life vehicle
Environmental protection agency
Electrospray ionisation
Field desorption
Field desorption mass spectrometry
Field ionisation
Field ionisation mass spectrometry
Fourier transform ion cyclotron resonance

Abbreviations
GC
HCs
HR MS
IUPAC
KMD
LC
LIAD
LQIT
MALDI
MS
MW
NKM
PAH
PAO
PASH
PCBs
PE
PIO
Q-TOF
RDB
S/N
Gas chromatography
Hydrocarbons
High resolution mass spectrometry
International union of pure and applied chemistry
Kendrick mass defect
Liquid chromatography
Laser induced acoustic desorption
Linear quadrupole ion trap
Matrix-assisted laser desorption ionisation
Mass spectrometry
Molecular weight
Nominal Kendrick Mass
Polyaromatic hydrocarbons
Polyalphaolefins
Polyaromatic sulfur heterocycles
Polychlorinated biphenyls
Polyethylene
Polyinternal olefins
Quadrupole time of flight
Ring double bond equivalence
Signal to noise ratio
CF 3 COOAg Trifluoroacetate
TOF
UCMs
Time of flight
Unresolved complex mixtures

Abbreviations
UV
VGOs
VOCs
VRs
ultraviolet
Vacuum gas oils
Volatile organic carbons
Vacuum residues

Introduction
1 Introduction
1.1 Complex Mixtures
Every human being is a complex mixture of around 100 000 different chemicals
and as humans we are surrounded by vast complex mixtures of additional millions
of chemical compounds affecting our daily lives. We define a complex mixture as
a mixture that contains too many individual compounds as to allow separation by
chromatographic methods (more than 1000 in gas chromatography (GC) and more
than 300 in liquid chromatography (LC)). Analysing such complex mixtures forms
the ultimate challenge of analytical chemistry and life sciences but the rewards will
be tremendous. Chemists have by tradition detested such mixture analysis and
reduced the world to the analysis of single purified and well defined compounds.
Many materials such as household and industrial wastes, plant and microbial
extracts and dietary materials can be considered as complex mixtures. These
mixtures may consist of tens, hundreds or thousands of organic compounds, which
exist in inexact proportions. 1 Moreover the composition of the aforementioned
complex mixtures is not fully known, either qualitatively or quantitatively and may
vary considerably. Many analytical approaches have targeted complex mixtures in
order to evaluate similarities and dissimilarities between different mixtures, source
identification, changes in mixture composition and assessment of toxicity. 2-9
Similarly environmental samples are extremely complex. They include oil spills,
atmospheric deposition, urban runoff and waste treatment plants. Many analytical
procedures introduced by legislative bodies tend to ignore this fact. Legal
concentration threshholds are only defined for well characterized single
compounds or groups of compounds. In many of these samples various types of
hydrocarbons are present such as in oil spills, industrial discharges and biofuels. 10-
12
The talk about complex mixture can’t be complete without mentioning
petroleum. The latter is the most precious mixture since it is the major source of
energy known to mankind. 13
1

Introduction
Analytical chemistry has been extensively dedicated to the investigation of
complex mixtures of petroleum for the last years. Petroleum and biodegraded or
hydrothermally altered hydrocarbon extracts are known to exhibit unresolved
complex mixtures (UCMs) in gas chromatograms (raised base line termed as
hump) where the exploration of the molecular composition of these mixtures
becomes limited. 14-17 Among these are the analysis of complex mixtures containing
various types of hydrocarbons present in waste or oil mixtures and the analysis of
high-boiling point distillates where adequate chromatographic separation is not yet
available. 10,18,19 Thus the hydrocarbons elsewhere in different mixtures are known
to possess a substantial proportion in which GC is unable to resolve and identify.
Therefore it is emphasized that the existing analytical technology can’t explore the
chemical composition of the sample in any other way. For example the large
magnitude of the unresolved complex oil components, containing an estimated
250,000 compounds, is not identified, 19 thus a great deal of compositional
knowledge remains poorly understood. Such a lack of knowledge limits, most
importantly, the assessment of effects of unresolved complex residues in the
environment. 20
Yet the study of complex mixtures has received recent attention since most of
these mixtures undergo compositional evolution due to some factors like
temperature, time, source, composition, water, and microbial activity. 10,14 It is well
pronounced that a minor change in the composition of a mixture can have a huge
effect on its characteristic properties such as flavour, reactivity and toxicity. Such
evolution yields derived products that could be sometimes described as
unrecognized toxins in, for example, marine environment, 8,21 mussel sediment, 22
and crude oil degradation. 23 As well weathering of oil spills requires full
understanding of the effects and fate of spilled products. 24-26 On the other hand,
chemical characterisation and identification of heavier components of crude oil can
guide refining and production processes necessary in oil industry. Hence the
analysis of complex mixture is very important to food chemistry, oil processing as
2

Introduction
well as to environmental concerns. 27,28 For instance; environmental chemists must
monitor the effects of various pollutants on human health and the eco-system.
As understood from the above, the rapidly expanding interest in characterization of
complex mixtures and their derivatives is driven by several objectives. The
identification and structural characterization of compounds, monitoring the
degradation processes of complex mixtures, evaluation of mixture reactivity
related to properties and the quantification of target molecules are the general aims
for research projects in this field. To achieve the above goals, researchers
abandoned traditional analytical methods of complex mixtures to meet
revolutionized methods implemented by mass spectrometry (MS). 29 Studies have
shown that the direct analysis of complex mixtures is one area of mass
spectrometry that has benefited from the evolution of the technology within mass
spectrometry. 7
Modern mass spectrometry, with its unsurpassed resolution allows, however, the
simultaneous analysis of tens of thousands of compounds in a single experiment,
which in chromatography are manifested as an unresolved complex hump. Yet the
application of novel measurement strategies allowed studying such complex
mixtures in food, biological system and environmental samples. With high
resolution MS studies and new data sorting strategies like Kendrick plots,
knowledge about the actual content of unknown complex mixture becomes more
accessible. 30 Although with complex mixtures a detailed and complete
characterization is still perhaps impossible, examinations of parts of these various
mixtures have recently become popular studies performed mainly due to the
aforementioned reasons. 13
3

Introduction
1.2 Presence and Fate of Hydrocarbons in Contaminated Sites
Petroleum samples involve many hydrocarbon mixtures like paraffins, cyclic
paraffins, condensed aromatics and various heteroatom hydrocarbons (mostly O, S
and N heterocycles). 31 The classification of hydrocarbons is shown below. Original
petroleum contains molecules of a wide boiling point range from highly volatile
C4 hydrocarbons to non-volatile asphaltenes. Generally petroleum mixtures are
common site contaminants and weathered petroleum residuals may stay bound to
soils or sediments for years. 32 In part due to their complexity, little is known about
detailed chemical composition and consequently their potential for health or
environmental impacts. Petroleum mixtures consist primarily of relatively
unreactive complex hydrocarbons covering a wide boiling point range. In many
mixtures, hydrocarbons range from volatile, short-chained organic compounds to
heavy, long-chained, branched compounds. The exact composition of petroleum
products varies depending upon the source, the modifiers or chemical processing.
In addition to that the chemical composition of the product can be further affected
by weathering and/or biological modification upon release to the environment. 33
On the other hand, the disposal of toxic industrial wastes through landfill,
incineration or other procedures is a controversial subject, as toxic chemicals or
their decomposition products may contaminate ground and drinking water or
escape into the atmosphere during the production, conservation and treatment of
the wastes. The lack of adequate regulation and official treatment and disposal
plants in many countries has led to the illegal collection, transportation and
dumping of wastes that, after the introduction of legislation designed to control the
problem, must be recovered, identified and properly disposed of. On the other hand
the analysis of the complex mixtures of industrial solvents that, being in liquid
form and often stored in metallic drums which are subject to corrosion, may
contaminate the landfill sites and could be leached by running water, or escape into
the atmosphere as a result of their appreciable vapor pressures.
Soil contamination has been a growing concern because it can be a source of
groundwater (drinking water) contamination. In addition to that contaminated soils
4

Introduction
can reduce the usability of land for development. Nowadays the major significant
source of contamination to land and marine environment remains to be oil spills.
Due to increased petroleum production and transportation activities, our world has
witnessed a lot of accidental oil spills in the recent years. 34 For example the Gulf
of Mexico was stricken by a British Petroleum oil spill which endangered the
whole wild life in that area. Rehabilitation of the area was launched instantly. As a
result to such accidents, the biodegradation of oil and its derived products have
been the focus of many studies. Nevertheless an important concern remains due to
the toxicity of these oil constituents. Despite hydrocarbons have low solubility in
water; they can accumulate in the fatty tissues of organisms. The long term toxicity
of n-hexane in humans is well known. Alkanes with more than 11 carbons are not
toxic most organisms due to their low solubility in water and low chemical
reactivity. However, aromatic hydrocarbons are problematic because of their
aqueous solubility and enhanced bioavailability. 35 Hereby studies have tried to
answer questions related to composition and persistence of potential complex
pollutants. In equal footing, studies have investigated the bioremediation process
of petroleum components in polluted areas. 36 While some types of hydrocarbons
are readily biodegraded in marine environment; others like multi-ring aromatics
are difficult to be biodegraded. These compounds resist microbial degradation
partly due to their structure. 37 The environmental impact of the unknown oil should
be assessed by the determination of individual petroleum hydrocarbons in a
complex mixture of compounds. However such mixtures are difficult to separate
by most analytical techniques.
Chromatography does not resolve (and thus identify) a substantial proportion of
complex hydrocarbon mixtures. These components are often referred to as the
unresolved complex mixture (UCM), or 'hump', (term UCM was introduced by
Gough and Rowland), which is especially pronounced for biodegraded
petroleum. 16 It is known that microorganisms metabolize various classes of
petroleum compounds which results in the reduction of dominant saturated
aliphatic hydrocarbons. UCM is believed to compose of branched and cyclic
5

Introduction
aliphatic hydrocarbons and aromatic hydrocarbons (see Figure 1-1), which usually
show the greatest resistance to biodegradation. 38,39 These compounds give rise to
UCM referred to as a hump by Gough and Rowland in 1990. UCM is used as an
indicator of petrogenic environmental input due to its persistence after accidental
or chronic oil spills. Historically, UCM has been considered non-toxic but more
recent studies suggest otherwise. 23 The chemical analysis of crude oils and related
samples are necessary for tracking compositional changes of products affected by
biodegradation or weathering 25 such as in oil spills or in complex mixtures
undergoing biological treatments like solid waste. Characterization of UCM has
been an important competition among researchers who applied different strategies
to guess the composition beyond the GC hump. Concerned with the toxic behavior
of the above reported hydrocarbon forms, other researchers have been looking for
improved methods of quantification. Therefore, development of informative
analytical methods that unambiguously reveal the quantity and identify
hydrocarbons found in different complex mixtures are highly required. Overall
environmental awareness demand the investigation of the presence and
concentration of primary contaminant classes such as polyaromatic hydrocarbons
(PAH), amines or polychlorinated biphenyls (PCBs) in water, soils or sands.
Regulatory bodies like Environmental Protection Agency (EPA, USA) are always
interested in assessing and minimizing the impact of chemical waste and in
detecting specific toxicants accidently released into the environment. 40
Classification of Hydrocarbons, HCs:
•Straight branched aliphatic, cycloaliphatic (Decane to Tetracontane)
•Polycyclic Aromatic Hydrocarbons, PAHs ( Naphthalene, Pyrene)
And the collection extends to others in terms of degradability, solubility
and volatility:
6

Introduction
•Polychlorinated Biphenyls, PCBs
•Chlorinated Hydrocarbons, CHC (chlorodecane, PVC)
• BTEX (Benzene, Toluene, Ethyl benzene and Xylene)
•Volatile organic carbon components, VOCs (Methane, Formaldehyde)
Aliphatic Hydrocarbons
Aromatic Hydrocarbons
7

Introduction
Figure 1-1 Examples of aliphatic and aromatic hydrocarbons in crude oils
1.3 Use of Mass Spectrometry for Hydrocarbon Analyses
New technology, advances in methodology and increase of computational power
have contributed massive generation of data in analytical chemistry. The evolution
of mass spectrometry has attracted interest into the world of complex mixture
analysis especially complex mixture of hydrocarbons.
Mass spectrometry has seen a dramatic development over the last ten to fifteen
years. Whereas in the 1990 MS was limited to the analysis of volatile stable
compounds by electron ionization (EI) or chemical ionization (CI) ionization
methods, the advent of soft ionization techniques such as electrospray ionization
(ESI), atmospheric pressure chemical ionization (APCI) or matrix-assisted laser
desorption/ionization (MALDI) has lead to a surge of technical developments. As
a direct consequence of soft ionization techniques nowadays almost any analyte
independent of its molecular weight and stability can be successfully ionized and
transferred into the gas phase for MS measurements.
Parallel to the development of these ionization techniques the invention of new
mass separating systems and their improvement and fine tuning has taken place
Most notable examples are the developments and commercialization of ion trap
8

Introduction
MS, time of flight (TOF)-MS and Fourier transform ion cyclotron resonance (FT
ICR)-MS instruments as well as hyphenated MS technologies such as quadruple
(Q)-TOF or TOF-TOF instruments.
Each development has resulted in a dramatic increase of the scope of MS and
resulted in a spectacular increase of instruments capabilities. TOF instruments for
example allow the determination of molecular weights up to the million Dalton
range with whole virus being examined in the gas phase. Ion trap instruments have
added powerful methodology for structure elucidation by using up to twelve
tandem MS stages. Both TOF and FT ICR MS instruments have allowed an
impressive improvement in sensitivity of the instrumentation leading to routine
limits of detection in the femto mole (fmol) region. Finally TOF and FT ICR
instruments allow an impressive resolution many orders of magnetic higher than
any chromatographic technique. The current world record for an FT ICR
measurement stands at the detection of 100,000 species in a crude oil sample in a
single spectrum set by the group of A. Marshall. 41 Especially by the pioneering
work of A. Marshall in the field of petroleomics has paved the way for complex
mixture analysis exploiting the impressive resolving capability of a high resolution
mass spectrometer. However these capabilities pose new challenges to the
analytical chemist. A modern mass spectrometer is certainly capable of obtaining
structural information at high sensitivity, specificity and speed for complex
mixture sample, but how can such data be interpreted in a meaningful way? How
can such information be used for reliable structure elucidation and quantification
of analytes?
The coupling of LC to MS has resulted in the development of so called multidimensional
techniques providing a separation step coupled detection steps using a
variety of spectroscopic methods such as UV coupled to MS. Multi dimensional
information refer to the possibility of combining retention time information with
UV and MS information. An overview of the range of applications of GC/MS (EI)
and LC/MS (ESI, APCI) over a range of polarity and relative molecular mass is
shown in Figure 1-2.
9

Introduction
Figure 1-2 Range of ionisation techniques employed with different types of
compounds
As explained earlier chromatography coupled to MS can solve analytical problems
of mixtures containing several dozens or hundreds analytes, however the study of
real complex mixture comprising thousands of analytes is still in an area of MS
only. MS can provide detailed molecular-level information for hydrocarbon
complex mixtures.
Therefore, better methods that characterise complex mixtures have been most
recently driven by the development of improved mass spectrometry methods. For
example the emerging field of Petroleomics has provided a series of novel data
interpretation strategies to extract chemical and other relevant information from
such enormously complex data. 42 Under this concept and with the help of
developed technological devices available for research groups, studies have
examined hydrocarbon complex mixtures and their model compounds by
revolutionised methodologies. These experiments argued ionisability and
volatility 43 of hydrocarbon molecules using a high resolution detector are to play
an important role in extending the applicability of MS for complex hydrocarbon
mixture analyses. Although such experiments are considered intriguing steps
towards hydrocarbon complex mixture, however they are not without problems. To
understand the problems and limitations of hydrocarbon analyses in MS, a critical
10

Introduction
review of the work done in this field will be reported. Research efforts have
investigated the potential of various ionisation methods to create intact product
ions representing the neutral composition of complex mixture. It follows that the
choice of ionisation method plays a key role towards a rational detailed analysis of
crude oil samples.
1.3.1 EI and CI
Traditionally low-energy EI and CI ionisation were used for petroleum analysis. 44-
48 EI (70 eV) produces extensive fragmentation of the ionised hydrocarbon
molecules. Nevertheless characteristic fragment ions of petroleum were developed
to provide valuable crude oil assay for light or medium hydrocarbons. However,
this method can’t be used to identify each type of hydrocarbons as well as it is not
accurate if sample contains olefins or heteroatom containing compounds. 49 The
obtained molecular weight information becomes rather complicated due to
fragmentation and difficulties in identifying molecular ions. Also since molecules
are brought to gas phase by thermal vaporisation that defines EI and CI methods,
high boiling point molecules of hydrocarbons can’t be detected thereby.
1.3.2 ESI, DESI and MALDI
Other soft ionisation techniques such as ESI, APCI, APPI and MALDI have also
taken part in the analysis of individual or complex mixtures of hydrocarbons. For
numerous applications in mass spectrometry ESI is widely used as an ionisation
method. It has been used to evaporate and ionise polar compounds of petroleum
containing functional groups with nitrogen or oxygen atom. 41,50-56 The technique
can successfully vaporise and ionise hydrocarbon analytes and produce
pseudomolecular ions without fragmentation. The molecules in positive molecular
ion formation are either protonated (basic compounds) or deprotonated (acidic
compounds). With ESI FT ICR combination allows a compact mass spectral
display for visual resolution of up to thousands of peaks. However polar
hydrocarbons are only a small portion of petroleum (10%). ESI is ‘blind’ to other
major nonpolar hydrocarbon fraction of petroleum especially saturate and aromatic
11

Introduction
fractions. 42 Another study employed discharge-induced oxidation in desorption
electrospray ionisation (DESI). 57 Ambient analysis of saturated hydrocarbons
(C 15 H 32 to C 30 H 62 ) using reactive DESI as an insitu derivatization method
generated a representative adduct ion for the examined model alkanes and the
vacuum gas oil saturate fraction.
As well other soft ionisation method were employed for petroleum
characterisation, such as MALDI (Figure 1-3). 58,59 A reactive MALDI MS method
could successfully ionise large alkanes and polyethylene producing cobalt
cyclopentadienyl alkane cation [Co(Cp) 2 (alkane+2H 2 )] +• . This organometallic gas
phase chemistry seems functional but nevertheless a selective approach. 60
Figure 1-3 Matrix-assisted laser desorption/ionization (MALDI)
1.3.3 FD and FI
Field desorption (FD) and field ionisation (FI) techniques are considered among
the most successful ionisation techniques for saturated hydrocarbons. 28 [M-2H] +
ions were reported to be abundantly yielded for saturated and aromatic various
saturated and aromatic compounds under conditions of field desorption mass
12

Introduction
spectrometry (FD-MS). 61 Combination of FI to GC and TOF HRMS (High
resolution mass spectrometry) generated intact molecular ions [M] +• for both
saturated and aromatic petroleum molecules. 62 Another study performed by Hsu et
al. using this time LC/FI-MS, produced as well molecular ions for investigated
paraffins and napthenes but fragment ions for isoparaffins like squalane. 63 FD-MS
was employed to analyse large multiply branched saturated hydrocarbons,
fragment ions were produced reflecting dehydrogenation, alkyl losses and alkene
losses. 64 Field desorption ionisation however can also produce ions from nonpolar
species but with less convenience at atmospheric pressure. 65,66
1.3.4 APPI
APCI and APPI are known to produce intact ions for polar hydrocarbons as [M-
H]ˉ, [M+H] + or [M] •+ but for saturated hydrocarbons the techniques have proven
limited. 67,68 APPI is also used to analyze fairly nonpolar molecules. The
illumination of the sample molecules by vacuum ultraviolet lamp produces radical
molecular ions by photoionisation. For example PAH were produced as protonated
upon APPI, but APPI can’t be used to ionise saturated paraffins. APPI, however,
was found to produce at the same time protonated, deprotonated and molecular ion
radicals of nonpolar aromatic compounds like polyaromatic sulfur heterocycles
(PASH). 30 This leads to complication in composition assignment of these
compounds in petroleum fractions. It was as well shown that the ionisation
efficiency of the parent radical ion is enhanced once a dopant is added. The APPI
ionisation technique becomes dopant-assisted (DA-APPI). For example toluene
works by enhancing proton transfer and charge exchange reactions. Simultaneous
production of protonated and radical molecular ions is observed. Overall APPI is
thought to possess a potential to cover a broader range of compounds of crude oil.
Particularly APPI was demonstrated to analyse asphaltene producing good
results. 69
13

Introduction
1.3.5 APLI
Other crude oil ionisation methods included atmospheric pressure laser ionisation
(APLI). This technique was introduced by Benter and colleagues. 70-73 Since APLI
is found sensitive for aromatic compounds, it is considered capable to reduce
complexity of crude oil. Shrader et al. demonstrated coupling of APLI with FT-
ICR MS as a suitable approach for the analysis of aromatic species in complex
crude oil fractions. 74 A more recent paper also investigated the potential of APLI to
complement the ionisation process of crude oil analytes compared to other
ionisation techniques like ESI and APPI. Results showed preference of APLI over
the other techniques in the analysis of crude oil fraction. 75
1.3.6 APCI, LIAD/CI and LIAD/APCI
Another more generally applicable ionisation technique is the atmospheric pressure
chemical ionisation (APCI). Introduced by Horning in 1970, APCI produced a
wide variety of different types of ions from a given analyte. An LC-APCI-MS was
used to identify classes of PAHs in mussels. A proton transfer ion (M+H) + and a
charge transfer radical ion (M) •+ were observed for the studied PAHs using
different mobile phases. 27 The latter ionisation patterns are produced
simultaneously in typical APCI processes. APCI has as well been used for
petroleomic analyses 62,76,77 where it was considered limited due to its low
sensitivity. Nevertheless, APCI, a popular ionization technique, has been
considerably used for detection of n-alkanes. 78-81 Alkanes are known to be used as
probes for APCI-MS ionization processes.
Karasek et al. analysed n-alkyl halides 82 and n-alkanes (C 5 H 12 -C 15 H 32 ). 83 For alkyl
halides (MX), (M-1) + ions were formed by hydrogen abstraction, while for n-
alkanes, formation of (MH) + and (MNO) + adduct ions was postulated. Bell et al. 78
investigated some n-alkanes in 1994. He found that n-alkanes were characterised
by composites of protonated and monohydrated species (M-H) + , (M-3H) + and (M-
3H) + H 2 O. These ions were generated by corona discharge and monitored by ion
mobility. A hydrogen abstraction was supposed for the formation of the above
14

Introduction
product ions. The peak assignment based on a comparison of ion mobility spectra
with spectra obtained by CI-MS whereas (M-3H) + and (M-3) + H 2 O were identified
by using APCI-MS with 63 Ni ionisation. A Recent study by Marotta and Paradisi
obtained an array of low boiling point linear and branched C 5 -C 8 alkane ions by
using air plasma fed APCI-MS. 79 Subsequent chemical ionisation (CI) studies
showed that intact high mass alkane ions could be generated in the gas phase by
using ligated-metal ion chemistry via cationization methods (silver cation Ag + ,
disilver-oxide cation Ag 2 O + ) or transition metals ( Fe,Co,Ni). 84-86 Moreover
organometallic cations were used by Byrd et al. 87 in particular cobalt cyclopentadienyl
cation (CpCo •+ ) to create intact gas phase species [(CpCo+alkane)-2H 2 ] •+ .
Some of these ions were used to determine the molecular weight (MW) of many
nonpolar hydrocarbons and polymers and were later incorporated into other
techniques for petroleum analysis.
However the most extensive work in the field of nonpolar hydrocarbon analysis
within model mixtures or real life complex mixtures is attributed to Kenttamaa
et.al. The group explored many revolutionised and efficient methodologies to
explain the complex compositions of crude oil, asphaltenes and lubricants. 28,88,89
An analytical summary assay of their work in the recent years will be portrayed.
The work of Kenttamaa’s group is described to be an intriguing contribution to this
field. They mainly adopted laser desorption/ionisation methods using laser induced
acoustic desorption. 90-92 This enabled them to desorp non-volatile and thermally
labile species as intact neutral species into the gas phase. Such an approach allows
independent control of desorption/ionisation processes. This forms a benefit which
is not feasible with other techniques. More recently this group has examined the
behaviour of hydrocarbon ions in different mass spectrometries using different
ionisation technologies. For example, Kenttamaa et al. utilized cyclopentadienyl
cobalt radical cation (CpCo •+ ) as an ionising agent for the analysis of various polar
and nonpolar components in petroleum distillates using laser-induced acoustic
desorption/fourier transform ion cyclotron resonance mass spectrometry (LIAD/FT
ICR-MS). 28,93 The neutral desorbed hydrocarbons were reacted with activated
CpCo •+ to produce stable addition products (adduct-H 2 , adduct-2H 2 , or both
15

Introduction
products). Other molecules reacted by loss of methyl radical and two hydrogen
molecules like 5-α-cholestane. This group applied the same LIAD/CpCo •+ CI
method in another study for polyethylene (PE) samples with low molecular weight
(200-655). 94 Later on Kenttamaa co-workers selected a less aggressive chemical
ionisation reagent, the water cluster of Manganese cation, [ClMn(H 2 O) + ],
combined with LIAD for examining a variety of hydrocarbons. 95 This ion was
useful to ionise all types of hydrocarbons forming only one product ion
[ClMn+M] + via water loss and without fragmentation. This latter method was
described to be an efficient mass spectrometric method for the analysis of
branched saturated hydrocarbons forming exclusively pseudomolecular ions
(adduct-H 2 O). Such ionisation was found better characterising than atmospheric
pressure chemical ionisation (APCI) and ESI of nonpolar lipids and steroids as
according to their observations. 96
Another LIAD/ClMn(H 2 O) + method was applied for the analysis of base oils
(major components of Lubricants). 88 The product ion [ClMn+M] + was the only ion
representing each components (M) within the complex mixture of the base oil as
shown in Scheme 1. The molecular weight distribution for base oil samples was
found in the range of 350-600 Da.
ClMn(H 2 O) + + M H
2
O
[ClMn+M] +
Scheme 1. Generation of adduct ions using LIAD/ClMn(H 2 O) +
Coupling LIAD to APCI by kenttamaa’s group enabled the evaporation and
ionisation of polar and nonpolar analytes yielding predominantly molecular ions
with minor fragmentation using carbon disulfide (CS 2 ) as a reagent. 97 Protonated
molecules (M+H) + were observed to be found in higher branching ratios when
benzene was used as APCI reagent. The investigated compounds were structurally
similar to those present in petroleum. Petroleum cuts were as a result analysed
upon LIAD/APCI using nitrogen gas as the reagent. Explanations were elaborated
according to the results of model mixture of the hydrocarbons. Just recently, an
APCI/CS 2 method utilized by the same group demonstrated the production of
abundant stable molecular ion (M +• ) for nonpolar aromatic, polar aromatic and
16

Introduction
alkene compounds under investigation. 43 On contrast the alkane derivatives like 5-
α-cholestane, squalane and hentriacontane studied under the same conditions
produced different product ions accompanied with notorious fragmentation. In
addition to that changing APCI reagent to MeOH/H 2 O, only few of the tested
analytes were detected where fragmentation was observed for most of them. It was
clear that this study facilitated to a certain extent the analysis of petroleum cuts
through understanding the behaviour of model compounds structurally similar to
those in petroleum.
Although the above reported APCI methodology has established a stable
corresponding ion for few hydrocarbon analytes, it failed to achieve a successful
ionisation of saturated aliphatic hydrocarbons. In fact another similar study
performed by the group of Kenttamaa didn’t even yield any detectable ions for
saturated cyclic hydrocarbon 5-α-cholestane under different APCI conditions. 96
1.3.7 Summary
In summary to this part, nonpolar hydrocarbons that form 90% of the petroleum
composition were examined by different mass spectrometries coupled to different
ionisation technologies mostly assisted by various chemical modification
processes.
EI and CI are not ideal for high MW hydrocarbon analysis because they produce
extensive fragmentation. 28 In the analysis of complex mixture, fragmentation is
deleterious, because the production of more than one signal per analyte
complicates an already crowded mass spectrum and thus makes it difficult to
identify parent ion. On the other hand ESI was found capable of ionising only
polar hydrocarbons. Further studies employing DESI, MALDI, APPI and APLI
were found rather selective for certain types of nonpolar hydrocarbons. Using FD
and FI suffers from low ionisation efficiency, varied response factors of
hydrocarbons of different types of MW (affecting quantification) and
fragmentation of molecular ions due to heating of analytes. 28
17

Introduction
Other studies performed using APCI have attributed hydrocarbon ionisation to the
chemistry of this methodology. 2 For example, failure to control ion generation in
APCI restricts the production of lone intact gas phase hydrocarbon ions in mass
spectrometry. Tuning APCI conditions can to some extent control gas phase
reactions. However, certain analytes still produce significant abundant ions or
fragments which can consequently complicate a real life sample containing
thousands of hydrocarbons. 43
Specifically, failure to produce intact, high mass alkane gas phase ions has been
preventing mass spectrometric analysis of saturated hydrocarbons as well limiting
its application towards petroleum industry. Furthermore all studies carried out
using APCI-MS focused on model system and pure reference compounds rather
than achieving any analysis of n-alkanes within real life samples of complex
mixtures. It is well demonstrated that the aforementioned studies have lacked a
“universal” soft ionisation method that simultaneously can ionise both saturate (i.e.
paraffins, cyclic paraffins) and aromatic petroleum molecules (alkylated benzenes,
alkylated polynuclear aromatics, alkylated thiophenoaromatics, etc). A summary of
most significant studies performed for model or complex hydrocarbon mixtures is
given in Table 1.
As understood from the above reporting, an ideal mass spectrometric method
capable of desorping intact hydrocarbons into the gas phase and ionising all
hydrocarbon analytes, including saturated and unsaturated analytes, to yield intact
molecular or pseudomolecular ions that are representative of neutral hydrocarbon
molecular weight (MW) without fragmentation and while avoiding any
derivatisation or adduct chemistry would be an intriguing novel approach. Such
approach should accordingly infer product ions can be subjected to controlled
fragmentation using tandem MS. Acquisition of qualitative and quantitative data
from complex hydrocarbon mixture can be then greatly facilitated as ionisation of
all components becomes uniform. In other words the first step in characterization
of organics in petroleum is to define the molecular mass distribution and proceed
with elemental composition assignment from efficiently accurate mass
18

Introduction
measurements. Next data interpretation skills are performed to visualise the
acquired data in its most informative form (Figure 1-4).
Figure 1-4 Complex data management
Table 1.1 Reference studies targeting various hydrocarbons
Methodology Tested Hydrocarbons Product Ions Drawback Ref.
DESI-Iontrap-MS
Alkanes (C 15 to C 30 )
Petroleum distillate
[M+2O+BA] +
Extensive dehydrogenation
species observed
57
MALDI-RTOF-260
High mass n-alkanes
Polyethylene
[Co(Cp) 2 (alkane-2H 2 )] +
Organometallic matrix
interactions
60
FD-MS
Saturated and aromatic HCs
Polywax
[M-2H] +
Low ionisation efficiency
of product ion
61
FD-MS
Large branched
hydrocarbons
Low abundance M •+ Extensive fragmentation 64
LC/FI-MS
Paraffins-Napthenes-
Isoparaffins
M •+
Fragment ions for
isoparaffins
63
n-paraffins
GC-FI-TOF-MS
VGO distillate(S
heterocycles)
M •+ Selective 62
APPI-FT ICR-MS
Naphtho[2,3-a]pyrene
Crude oil
[M+H] + , [M-H] ‾ , M •+
Complication of mass
spectra
30
19

Introduction
APLI-FT ICR-MS Crude oil M •+ Specific and sensitive for
aromatic hydrocarbons
74
APLI-FT ICR-MS
Non-polar aromatic in
heavy crude oil samples
M •+
Selective for aromatic
components
75
LC/APCI-MS PAH [M+H] + , M •+ Poor signal intensity of
PAH< 300 u
6
APCI-MS with 63 Ni
ionisation
n-alkanes
[M+H] + , [M-3H] + ,
[(M-3H)H 2 O] + Low mass alkanes 78
EI-FT ICR-MS n-alkanes (up to C 30 )
[CpCo+alkane-2H 2 ] •+
~80%
Formation of other product
ions, Limit C 30
87
LIAD/FT ICR-MS
Saturated, unsaturated
Hydrocarbons
Petroleum distillate
[M+CpCo-2H 2 ] •+
(Adduct), (Adduct-H 2 ) or
(Adduct-2H 2 -CH 3 ) may
form
28,93,
94
polyethylene
LIAD/ClMn(H 2 O) + /
FT- ICR MS
Various hydrocarbons
[(ClMn+M)-H 2 O] +
Adduct interaction may
result with complex
mixture
88,95
Base oil fractions
LIAD/APCI/LQIT Model hydrocarbons M •+ , [M+H] + generation and minor
No control of ion
fragmentation
APCI/CS 2 /LQIT Model hydrocarbons M •+ Significant failure with
saturated analytes
97
43
1.3.8 Ionisation via APCI
Since a significant portion of the studies employed for hydrocarbon analyses has
used APCI as an ionisation technique, I would like to give an insight about this
ionisation technique. APCI is an ionisation method used in mass spectrometry. It is
20

Introduction
an ionisation technique of choice for the analysis of medium to less polar, small
and thermally relative stable analytes. It is a form of CI which takes place at
atmospheric pressure. APCI was first introduced by Horning in 1973 for the
analysis of volatile compounds. 43 However APCI wasn’t spread until the
commercialisation of ESI after Fenn’s work in 1985. 98 Contrary to ESI, APCI has
the capability to vaporise higher boiling point analytes which resist volatilisation.
Figure 1-5 Schematic description of the atmospheric pressure chemical ionisation
(APCI) interface and the mechanism of ion formation in the corona discharge
region
Ionisation inside APCI is separated from solvent evaporation. After the mobile
phase is introduced into a pneumatic nebuliser, it is heated to high temperatures
(400-450 °C) inside a heated quartz tube and sprayed with high flow of nebulizer
gas (nitrogen gas). Ionisation occurs in gas phase, in contrast to ESI, by subjecting
the vaporised neutral analytes and reagent gas molecules (N 2 , H 2 O, O 2 ) to corona
discharge needle that creates the ions. It is emphasized that the corona discharge
needle is used as an electron source to ionise gas phase molecules such as
molecules of N 2 (commonly used as sheath gas) and molecules of the solvent
(commonly used methanol/water) forming radical cation in positive ion-mode.
These ions collide with the neutral analytes resulting in the creation of ions. The
high frequency of collisions results in high ionisation efficiency and thermalisation
of the analyte ions. These ions enter pumping and focusing stages within mass
21

Introduction
spectrometry in as much as with other ionisation techniques like ESI. The APCI
techniques generally produce pseudo-molecular ions depending on many factors
such as the chemical properties of the analytes, the polarity of electrospray voltage,
the nature of the matrix and the solvent composition. It is not always easy to
predict whether positive or negative ions will be preferentially produced. Overall
protonation of the analyte is usually observed in positive-mode APCI. Other
molecular ions and fragments like (M-H) + can also be formed. 76,99
Research efforts have focused to control ion generation in APCI by selecting a
convenient sheath gas or a proper solvent. Many types of ions are still produced for
each analyte. This phenomenon can complicate the analysis of complex mixtures.
This happens when solvent molecules engage in the generation of the radical
cations that collide with the neutral analytes ions.
Ionisation upon APCI with no liquid reagent can be most likely attributed to N 2
molecular ions N +• +•
2 . N 2 ions are thought to be responsible for production of
molecular ions by electron abstraction. The A significant advantage of APCI is
the ability to introduce nonpolar solvent instead of polar solvents and to handle
higher flow rate in the range of 1ml/min commonly applied in high performance
liquid chromatography (HPLC). This allows the analysis of nonpolar species
which otherwise can’t be analysed under ESI conditions. APCI is known to be a
less ‘soft’ ionisation technique than ESI by causing fragmentation compared to ESI
ionisation. A schematic description of an APCI-interface and the mechanism of
APCI is given in Figure 1-5.
1.3.9 Petroleomics
Global energy challenges have impelled chemical analysis towards better
understanding of petroleum composition. The chemical composition of crude oil is
so complex in terms of the number of chemically distinct constituents in an
abundance range 10 000-100 000. Petroleum distillates are complex mixture of
aliphatic, naphthenic and polaromatic hydrocarbons including various heteroatom
(e.g. N, O) hydrocarbons. Olefins are found in the cracked petroleum streams. 41
22

Introduction
Petroleomics is a field of chemical analysis concerned about the characterization of
all of the components of petroleum along with their interaction and reactivity.
Acquisition of this knowledge allows to differentiate petroleum samples or
distillates and can guide production and refining processes. Such molecular level
information on the types of chemical classes and presence of certain functional
groups are required by petroleum chemists. For example they can reduce refining
byproducts and waste, prevent pipe failures and predict production problems.
This need to obtain such detailed compositional information pushed the rapid
development of mass spectrometry technology. In 1960s the coupling of gas
chromatography to mass spectrometry was achieved. Although the growth
continued until 1990, mass spectrometry was limited to low-boiling nonpolar
species. After that GC/MS and LC/MS and tandem MS yielded impressive content
information of many petroleum distillates such as gasoline, diesel and gas oil.
However little was known about other polar species of heavy crude oils and heavy
petroleum distillate. Fenn suggested most polar species could be ionized by ESI
(Fenn received Noble Prize for ESI). The advent of ESI-FT ICR-MS facilitated the
analysis of polar fractions within complex crude oils. However little is known
about the compositional knowledge of saturates/olefins. Their tendency to
fragment and undergo gas phase reactions leaves them difficult to explore. To this
end, even at the expense of the mentioned MS limitations, it is still the cornerstone
of the emerging field of petroleomics.
Industrial laboratories and research groups have moved from physical (crude oil
assays of viscosity, density, etc.) or bulk chemical characterization (% of S
content, acid number, etc.) of petroleum into detailed characterization of petroleum
compositions. 42 The careful choice of base oil components and their concentration
leads to enhancing performance of lubricants. 88 Nowadays interest is even shifted
into heavier petroleum fractions as the lighter ones (low sulfur) are depleted. 74,100
High energy demand and rising energy prices have led to mold the attention
towards higher-boiling point fractions like vacuum gas oils (VGOs) and vacuum
residues (VRs) of crude oil. 13,101 These mixtures should undergo desulfurisation by
23

Introduction
catalytic processing to reduce their sulfur content. 102 Optimisation of catalytic
operations demands a structural information about components containing S like
PASH. 103 However while polar hydrocarbon constituents of petroleum (10%) are
readily detected under ESI FT-ICR MS conditions, nonpolar components (90%)
are especially problematic and challenging. Recent studies, reviewed in the ‘Use of
mass spectrometry for hydrocarbon analyses’ section, have shown a great promise
in achieving an efficient and rational analysis of such hydrocarbon mixtures. So
far molecular mass distribution, elemental composition assignment and
compositional sorting are elaborated for polar fractions within crude oil by virtue
of high resolution FT ICR. Up to thousands of different chemical elemental
compositions can be resolved in a single mass spectrum. 41,104,105 The resulting
compositional information may then be displayed in Kendrick plots for rapid
visual comparisons between samples.
To this end, energy research will last for the next two decades. Until alternative
sustainable energy sources are developed, fossil fuels will remain the major source
of energy. The advancements in petroleomics will guide how energy will be
processed in the future.
1.3.10 Kendrick plot
The advantages of high resolution analysis of crude oil extracts by ESI-FT MS
provided access to complex mixture data which were further interpreted in an
illustrative and informative way. Elemental composition of ionic species up to
~400 Da can be unambiguously assigned with the virtue of high mass accuracy
machines (FT-ICR-MS). 42 However the successfully assigned elemental
compositions for higher-mass ions require data reduction based on the Kendrick
mass scale. The method was originally introduced by Kendrick in 1963. 106
For ultrahigh-resolution measurements, it is useful to convert the measured mass to
the Kendrick mass which allows sorting compounds into homologous series
according to alkylation degree, classes (type of heteroatoms), and types (rings plus
double bonds). For example, the IUPAC mass of CH 2 , 14.0157 Da, becomes a
24

Introduction
Kendrick mass of 14.0000 Da. The ratio of nominal mass and accurate mass of
CH 2 is multiplied by the mass measured by MS to convert it into Kendrick mass.
Kendrick mass = IUPAC mass x (14/14.01565)
Compounds with the same (N, S and O) composition and the same number of
rings plus double bonds but different numbers of CH 2 units in alkyl side chains for
example will differ in Kendrick mass by integer multiples of 14.0000 Da. These
compounds are thus easily identified as members of a homologous series. Stated
another way, members of a homologous series will have the same Kendrick mass
defect (KMD), defined as:
KMD = [Kendrick nominal mass – Kendrick exact mass] x 1,000
This is unique to that series and will be plotted as a homologous series of
compounds on one horizontal line. The KMD value remains unique as long as the
class and type of compounds remain identical. The Kendrick formation has been
successfully applied to crude oil samples using the CH 2 mass increment. An
example of Kendrick is given in Figure 1-6 where part of elemental composition of
a crude oil has been sorted. Not only does 2-D Kendrick mass plots aid in the
assignment of unique elemental compositions but they also constitute a chemically
sorted display of thousands of mass spectral data points whose mass is higher than
~400 Da. In other words once a few related compounds are identified, extension of
that pattern to higher mass allows for confident elemental composition assignment
of ions whose mass is too high to allow a unique assignment based on the
measured mass. 105
25

Introduction
Figure 1-6 Kendrick mass defect vs nominal Kendrick mass for odd mass ions in
crude oil sample. Note the visual vertical separation of compound classes (O, O 2 ,
O 3 S) and types (e.g., compounds with different number of rings plus double bonds)
based on mass defect and the simultaneous visual horizontal distribution of number
of CH 2 groups for a given compound class and type. 105
In summary to this part this graphical display affords many advantages like
recognition of outlier data (data that fall outside the main pattern) and extension of
identified pattern to higher mass components. It can be as well an outstanding way
to monitor for example aromatic hydrocarbon content for different refinery process
streams. Biodegradation or weathering processes of various complex mixtures of
hydrocarbons are also easily tracked.
1.4 Light Shredder Waste in Bremen (Project Objectives)
Light shredder waste constitutes a waste fraction, which is obtained from industrial
waste originating from the end of life cars, white goods or other electrical
household and industrial items. The light shredder waste fraction is produced by
26

Introduction
mechanical shredding of the waste followed by sieving and finally removal of
magnetic metal contents using large scale magnet. The resulting light shredder
waste fraction was historically directly sent to landfill sites. It is estimated that in
UK around 850,000 t and in Germany around 2 Mt of light shredder waste are
generated annually. Due to End of Life Vehicle (ELV) and landfill directive, 107
political pressure has mounted to reduce the amount of light shredder waste to send
to landfill and develop alternative technologies resulting in the recycling or
reduction of light shredder waste.
Figure 1-7 Shredding Plant
The Bremer Entsorgungsbetriebe (BEB) Company has recently developed such an
innovative technology. In a pilot plant light shredder waste is treated biologically
resulting in a dramatic reduction of its weight and volume. The waste is sprayed
with water and naturally occurring microorganisms transform the waste at
operating temperatures around 90˚C for a period of two to four weeks. The
resulting product is designated for landfill sites. However, before final landfill is
approved the waste material needs to undergo a series of analytical investigations
27

Introduction
including determination of residual hydrocarbons (HCs), residual polyaromatic
hydrocarbons (PAHs), volatile organic compounds (VOC) and residual heavy
metal contamination. All these analytical quality control (QC) measures are legally
binding before approval for landfill given by the local authorities.
Figure 1-8 Light shredder waste fraction set for biological treatment in a prepared
unit.
For the BEB light shredder waste in particular hydrocarbons contamination is an
issue with large proportions of the waste exceeding the legal limit of 5 g
hydrocarbons per kg of waste. The legally binding analytical procedure for the
determination of HCs as defined by the German government is known as KW4
using DIN norm method DIN EN 14039. 108 This method specifies GC based
quantifications of HCs. While short and medium chain HCs can be readily
quantified, long chain derivatives result in a UCM in the gas chromatogram (as
shown in Fig.1-9). According to KW 4 the UCM hump is directly and uncritically
integrated and the resulting integral is used as a measure of the HC content. Within
the BEB treated light shredder fraction in particular this UCM results in the
deviation from the legal HC limit resulting in a lack of approval of landfilling.
28

Introduction
uV (x100,000)
Chromatogram
1.75
1.50
1.25
1.00
0.75
0.50
0.25
0.00
5.0 7.5 10.0 12.5 15.0 17.5 20.0 22.5 25.0 27.5 30.0 32.5 35.0 37.5 min
Figure 1-9 UCM feature of hydrocarbon content of light shredder waste in GC
The scientific question that needs to address urgently is about the composition of
the hump. Whether the hump contains only hydrocarbons has remained a matter of
speculation rather than experimental proof and no detailed information exists on
the actual composition, presumably varying dramatically between samples. If other
non HC components are present the KW 4 does not then determine HCs and
should not be used as legally binding procedure for measuring HC contamination.
The resulting challenge is to develop an alternative method to reliably measure
HCs in shredder waste or any other source of heavy long chain HCs.
Resulting from this problem the specific aim of the project is to establish the
chemical content of the UCM in light shredder waste and once adequately
characterized develop a reliable method for the determination and quantification of
HCs alternative to KW 4.As well the study aims at evaluating the extent of UCM
weathering or biodegradation of the waste. The project however seeks to devise
and develop an MS-based methodology capable of analysing and characterizing a
complex mixture of hydrocarbons within the light shredder waste.
29

Introduction
1.5 Scope and Significance of this Work
The aim of this work is to develop, adapt and evaluate a new MS-based methodology
for the analysis of hydrocarbons. Besides general method development and
validation, the following problems and applications should be addressed
At first task it should be investigated if model hydrocarbons compounds can be
analysed using mass spectrometry. The following step will involve applying the
developed method for the analysis of light shredder waste sample. The major goal
is to explore the chemical composition of shredder waste. The ability to provide a
quantitative figure about selected hydrocarbons needs to be devised. Validation of
the method requires testing similar complex hydrocarbon mixtures. The
possibilities to differentiate complex data from each other by using tools available
in literature need to be established. Finally the comparability of results obtained by
different spectrometries should be investigated as by their advantages and
limitations.
After this promising scope of this study, a general synopsis of the study
significance is illustrated in the following description. This thesis describes
investigations undertaken into the nature of the UCM of light shredder waste. The
results and discussion section comprises six parts. The first two parts involves the
ionisation of n-alkanes and other various branched and cyclic hydrocarbons by a
newly developed mass spectrometry method. In the third part the mechanism of the
ionisation was discussed. The fourth part comprises the analysis of the chemical
content of the light shredder waste. This included exploring the molecular level
details of the complex mixture. The fifth part investigates the application of the
developed methodology into other different complex mixture comprising similar
types of hydrocarbons. The final part explains the management of the complex
data. The utility of graphical tool to help simplify the spectral data was
demonstrated.
30

Experimental
2 Experimental
2.1 Chemicals and Model Standards
a) Standard low mass n-alkanes such as Octane, nonane, decane, undecane,
dodecane, tridecane, tetradecane, pentadecane and hexadecane were purchased
from Sigma Aldrich (Bremen, Germany). Higher mass n-alkanes like octadecane,
eicosane, henicosane, docosane, tricosane, tetracosane, pentacosane, hexacosane,
octacosane, dotricontane, hexatriacontane, tetracontane, dotetracontane,
tetratetracontane, octatetracontane, pentacontane, tetrapentacontane and
hexacontane all of analytical grade, were purchased from Sigma Aldrich.
b) Different model mixtures of n-alkanes were also purchased from the same
company.
i) C7-C40 Saturated Alkanes (1 mg/ml in hexane)
ii) C8-C40 Alkanes Calibration Standard (500 µg/ml in dichloromethane)
iii) C10, C20-C40 Alkane Standard Mixture (50 mg/l in n-heptane)
iv) C21-C40 Alkane Standard Solution (40 mh/l in toluene)
v) C12-C60 Quantitative Linearity Standard (0.01 % (w/w) in cyclohexane)
vi) n-Paraffin Mix C18, C20, C22, C24 Analytical Standard (2 % (w/w) in octane)
c) Other deuterated standards such as deuterated tetracosane [(D-24), (C 24 D 50 )] and
deuterated dotriacontane [(D-32), (C 32 D 66 )]
d) Other individual standards were purchased from Chiron Company (Chiron.no).
These standards were 2,6,10,14-tetramethyl nonadecane, 2,6,10,14,18-pentamethyl
heneicosane, n-tetradecyl cyclohexane, n-octadecyl cyclohexane, n-octyl benzene,
n-nonyl benzene, n-tetradecyl benzene, and n-octadecyl benzene, each in 1 mg/ml
isooctane solution. 5-α-Cholestane, squalane, squalene, phytane, and 1-phenyl
decane all of analytical grade were also purchased from Sigma Aldrich.
31

Experimental
e) Other model mixture purchased also from Aldrich Company is the
polychlorinated biphenyls (PCBs), PCB Congener Mix 1. Decachlorobiphenyl
(C 12 Cl 10 ) was purchased from the same company.
f) The list of solvents and derivatisation agents include n-pentane, n-heptane,
chloroform, isooctane, methanol, dichloromethane and toluene. Deuterium oxide
(D 2 O), silver trifluoroacetate (CF 3 COOAg) and chromium trioxide (CrO 3 ) were
also supplied. Last, the purification material florisil (100-200 mesh) was purchased
from Aldrich Company as well.
2.2 Preparation of Samples
2.2.1 Alkane Standards and Shredder Waste Samples Preparation
Preparation of model standards was done by dissolving or diluting a known
quantity of separate alkanes. The prepared solution was always diluted prior to
injection to meet the concentration needed for mass spectrometry around mM
concentration. Model mixtures of n-alkanes was prepared by mixing equimolar
ratios of the separate alkane standards. Standard model mixture purchased from
Sigma Aldrich company were diluted to mM concentration before measurement.
For example 20 µl were taken from C7-C40 alkane standard (1mg/l) and diluted
into a 1 ml of n-heptane solvent before injection.
Preparation of light shredder waste samples was achieved by few but important
steps. Most of the common analytical steps are related to the separation and
purification of analytes of interest from a sample matrix prior to their
measurement. After frequent treatments of huge amounts of upcoming light
shredder waste in the BEB Company, samples are cropped for analytical
investigation. Although the shredder waste itself is homogenous by nature,
samples are taken from different locations of the same treated shredder waste
portion. In our laboratory, the sample was dried and sieved by a normal sieve to
get rid of bulk pieces of plastic, small wires and others that are removed. Next the
sieved waste are grounded into fine particles (around µm) by a Fritsch Mill.
32

Experimental
After that, 20 g of waste were extracted by 20 ml of n-heptane and 40 ml of
acetone inside an automatic soxhlet extractor for 6 hours. The resulting brown
solution then is washed with water (15 ml) to remove the acetone content. The n-
heptane solution is cleaned by a column (d=1cm) using florisil (2g) and sodium
sulfate (2g). The filtrate was dried using rota evaporation. Then 5 ml of n-heptane
was added to the extract. For injection into MS, 1 ml of the prepared heptane
solution is used. Sometimes diluted solutions were prepared before infusion.
Similarly this preparation method was applied to treated waste samples on small
scale reactor in Hochschule Bremerhaven. Our project partners probed aeration
and hydrothermal conditions as seen in Table 2.1 to optimize degradation process.
Table 2.1 Different shredder waste samples treated under different conditions
Sample
Date
Conditions
Temp. Air flow Input water
Operating time
I 1 2010-12-14
1.
R 1.1 2010-12-14 60 °C 1,5 L/h 120 mL/d 22 days
R 2.1 2010-12-14 60 °C 1,5 L/h 120 mL/d 22 days
I 2 2010-12-22
2.
R 1.2 2010-12-22 60 °C 1,5 L/h 120 mL/d 20 days
R 2.2 2010-12-22 60 °C 3,0 L/h 120 mL/d 20 days
R 3.2 2010-12-22 60 °C 3,0 L/h 120 mL/d 20 days
I 3 2011-04-02
3.
R 1.3 2011-03-16 60 °C 3,0 L/h 120 mL/d 31 days
R 2.3 2011-03-16 60 °C 3,0 L/h 120 mL/d 22 days
R 3.3 2011-03-16 60 °C 3,0 L/h 120 mL/d 14 days
I 4 2011-04-14
4.
R 1.4 2011-04-21 60 °C 3,0 L/h 120 mL/d 22 days
R 2.4 2011-04-21 60 °C 3,0L/h 120 mL/d 22 days
R 3.4 2011-04-21 60 °C 3,0 L/h 120 mL/d 22 days
I 3 2011-06-14
5.
R 1.3 2011-07-04 70 °C 3,0 L/h 120 mL/d 22 days
R 2.3 2011-07-04 70 °C 3,0 L/h 120 mL/d 22 days
R 3.3 2011-07-04 70 °C 3,0 L/h 120 mL/d 22 days
33

Experimental
2.2.2 Preparation of Oxidation Products from Shredder Extract
The waste extract was subjected to oxidative degradation using CrO 3 . Oxidation
of the waste complex mixture was performed at 70°C for 3 h in a CrO 3 /glacial
acetic acid mixture. Thus, waste extract (100-200 mg) was added to acetic acid (15
ml) in two-necked round bottom flask (25 ml) equipped with a reflux condenser.
The solution was heated to about 70°C with stirring (10 minutes) before adding the
oxidant (10:1 molar ratio, assuming 352 g mol -1 for waste extract). After 3 hours,
the solution is cooled, transferred into another flask where water (10 ml) and
dichloromethane (15 ml) were added. Extraction by similar volumes of DCM
again recovers the oxidized products. The extract was concentrated to dryness by
rota-evaporation.
2.3 MS Operating Conditions
The present study was carried out with a Bruker micrOTOF Focus MS and a
Bruker HCT ultra Iontrap MS instruments equipped with an electrospray ionisation
(ESI) source or with an atmospheric pressure chemical ionisation (APCI). In the
case of ESI source, ions were generated externally by a microelectrospray source
under positive or negative ion mode conditions and samples were delivered by a
direct infusion syringe pump. Calibration was achieved with 10 mL of 0.1 M
sodium formate Cluster solution. The infusion pump line was set at 180 µl/h
suitable for ESI source. The applied settings of the optimised methods varied
slightly but the general conditions are : nebuliser of 0.5 Bar, a dry gas of 5 L/min,
a dry heater of 180 ˚C, set target mass start at 50 m/z and set target mass end at
1000 m/z.
However the main technique in this study that has been hugely employed is the
APCI-TOF-MS. The ionisation technique has already been discussed in details in
the introduction. Mass spectra were acquired by a high resolution micrOTOF
Focus mass spectrometer equipped with APCI (Bruker Daltonics, Bremen,
Germany). Separate analytes were dissolved generally in n-heptane. Direct
infusion of the sample was assisted by an electric feeder supplying a convenient
34

Experimental
flow rate of 400-500 µl/hr. MS operating conditions were as follows: nebulizer
pressure of 1.6 Bar, a corona discharge of 6000 nA, a hexapole RF of 200 Vpp, a
dry gas of 6 L/min, a drying temperature of 200 ˚C and a vaporizer temperature of
450 ˚C. Calibration of APCI was achieved by the general APCI/APPI calibrant for
the desired mass range. However calibration was also achieved by C7-C40
standard as will be discussed in details later on.
Fragmentation patterns were obtained by an Ion trap mass spectrometer fitted with
the APCI source (Bruker Daltonics HCT Ultra, Bremen, Germany) operating in a
manual MS n mode to obtain as desired MS 2 and MS 3 fragmented ions. Alkane
method settings in Iontrap included nitrogen as source gas and helium as collision
gas with corona discharge of +4000 nA, a nebulizer gas of 30 Bar, a drying
temperature of 200 ˚C, a vaporizer temperature of 450 ˚C and a compound stability
of 100% within a mass range of m/z 50-1000. Few parameters like collision energy
amplitude and peak width were adjusted to enhance fragmentation spectra.
35

Experimental
2.4 Graphical Presentation of the Used Instruments
Light Shredder Waste
Fritsch Mill
BUCHI Soxhlet Extractor
MicrOTOF MS
Iontrap MS
Figure 2-1 Instruments used in the study
36

Results and Discussion
3 Results and Discussion
3.1 APCI-TOF-MS of Standard n-Alkanes
Given that the study of a complex hydrocarbon mixture should rely on the study of
separate hydrocarbon standards in a certain technique, the behaviour of different
standard n-alkanes under APCI-TOF-MS conditions in the positive ion mode was
examined. The analytes of a series of standard n-alkanes from dodecane (C 12 H 26 )
to tetracontane (C 40 H 82 ) were injected into the MS instrument as direct infusions in
n-heptane. Equimolar model mixtures of n-alkanes were also prepared and
analysed by an optimised APCI-TOF-MS methodology. The MS settings
especially the nitrogen flow rate (nebuliser pressure) and corona discharge were
probed to obtain a stable generation of ions within the APCI source. In addition to
that the flow rate of sample injection appeared to have a significant role in the
analysis. At first an external HPLC pump was used. However, the optimum flow
rate was found to be 400-500 µl/hr supplied by an electric feeder only. The best
concentration was found to be the more diluted. Generally a solution of 10 -3 to 10 -4
M was infused. After optimising concentration and MS conditions, measurements
of separate and mixtures was launched. It was noticed that a monohydrated (M-
3) + H 2 O ion, was the only intact ion corresponding to each individually injected n-
alkanes (up to C20). For example figures 3-1 and 3-2 show the ions at m/z 185 and
m/z 199 corresponding to dodecane (C12) and tridecane (C13) respectively. These
ions were produced as intact stable monohydrated ions under positive APCI
conditions using n-heptane as infusion solvent. Next a model mixture of six model
n-alkanes (all in equimolar ratios) was analysed by APCI-TOF-MS using n-
heptane. The mass spectrum in figure 3-3 shows monohydrated (M-3) + H 2 O ions
for all six analytes of C10, C12, C13, C14, C15 and C16 appearing with minor
fragmentation. While the relative abundances of these ions don’t exactly match the
relative molar concentrations, all analytes were successfully detected in a single
37

Results and Discussion
experiment. High mass n-alkanes in contrast (C20-C40) formed additionally M •+ ,
(M-1) + and other low intensity monohydrated species (M-1) + H 2 O. For the range of
(C32-C40) some low intensity species that are formed of a composition of (M-3) +
were observed (Table 3.1). Figure 3-4 shows the ionisation of hexatriacontane
(C36) where (M-3) + , (M-1) + and (M-3) + H 2 O appeared at m/z 503, m/z 505 and m/z
521 respectively. These monohydrated and composite ions were further
demonstrated in a model mixture of dotriacontane (C32), C36 and tetracontane
(C40) in figure 3-5.
Intens.
[%]
100
185.2
+MS
80
60
40
20
0
123.1 137.1 149.0
163.1
199.2
225.2
216.2
241.3
263.2
285.3 297.3
100 125 150 175 200 225 250 275 300 m/z
Figure 3-1 APCI mass spectrum in positive ion mode of dodecane (C 12 H 26 )
showing (M-3) + H 2 O ion as product ion at m/z 185.2
Intens.
[%]
100
199.2
+MS
80
60
40
20
0
123.1 137.1 149.1 185.2
163.1
213.2 227.2 241.3 257.3 285.3 297.3 311.3
100 125 150 175 200 225 250 275 300 m/z
Figure 3-2 APCI mass spectrum in positive ion mode of tridecane (C 13 H 28 )
showing (M-3) + H 2 O ion as product ion at m/z 199.2
38

Results and Discussion
Intens.
[%]
C15
227.2
+MS
80
60
40
20
0
C10
135.1 149.1 157.2 163.1 177.2
C12
185.2
191.2
C13
199.2
213.2
241.3
253.1 263.2
140 160 180 200 220 240 260 m/z
C14
C16
Figure 3-3 APCI mass spectrum in positive ion mode of a mixture containing
decanes (C 10 H 22 ), dodecane (C 12 H 26 ), tridecane (C 13 H 28 ), tetradecane (C 14 H 30 ),
pentadecane (C 15 H 32 ) and hexadecane (C 16 H 34 )
showing (M-3) + H 2 O ions at m/z
157.2, 185.2, 199.2, 213.2, 227.2 and 241.3 respectively.
Intens.
[%]
100
(M-1) +
505.6
+MS
80
60
(M-3) + H 2 O
521.6
40
20
0
257.2
285.3
409.4
309.3 353.4
(M-3) +
465.5
597.6
250 300 350 400 450 500 550 600 650 m/z
663.4
Figure 3-4 APCI mass spectrum in positive ion mode of hexatricontane (C 36 H 74 )
showing an (M-1) + and (M-3) + H 2 O at m/z 505.6 and 521.6 respectively
39

Results and Discussion
Intens.
[%]
50
505.6 521.6
+MS
40
30
20
449.5 465.5
561.6 577.6
10
0
535.5
479.5
407.4 421.4 435.5
493.3
549.6
591.6
617.7
425 450 475 500 525 550 575 600 m/z
Figure 3-5 APCI mass spectrum in positive ion mode of dotriacontane (C 32 H 64 ),
hexatricontane (C 36 H 74 ) and tetracontane (C 40 H 82 )
These reported measurement were my starting steps before I tried to optimise
solvent. These measurements were absolutely considered novel hits because it is
well known that n-alkanes are difficult to be ionised. As far as the effect of other
solvents over the ionisation process in APCI was concerned, two further
experiments were performed. Two solutions of model n-alkane mixture of the
higher mass range (C20 to C40) were prepared and injected as direct infusions in
n-pentane and chloroform as the APCI reagent. None of the two solvents afforded
better results compared to those with n-heptane. Figure 3-6 shows the mass spectra
of few analytes in the aforementioned range in n-pentane. n-Pentane was seen to
enhance fragmentation potential of alkanes by possibly increasing the efficiency of
collisions of reagent ions with the neutral n-alkane analytes inside the APCI
source. To this end, the appearance of such n-alkane species is in agreement with
the results summarized in the introduction in particular the study performed by
Bell et al.. 78 The latter’s study of a set of low mass n- alkanes produced (M-1) + ,
(M-3) + and (M-3) + H 2 O. The results of individual model n-alkanes were
summarised in table 3.1.
40

Results and Discussion
Intens.
[%]
100
80
60
40
20
0
+MS
449.5
561.6
491.6
243.0
313.3
281.3 341.3 365.4 577.6 603.7
250 300 350 400 450 500 550 600 m/z
Figure 3-6 APCI mass spectrum of model mixture of n-alkanes injected using n-
pentane
Table 3.1 Summary of APCI data of n-alkanes
Alkane M ∙+ (M-1) + (M-3) + (M-3) + H 2 O
C 12 N Y* N Y
C 13 N Y* N Y
C 14 N Y* N Y
C 15 N Y* N Y
C 16 N Y* N Y
C 18 N Y* N Y
C 20 Y Y N Y
C 21 Y Y N Y
C 22 Y Y N Y
C 23 Y Y* N Y
C 24 Y Y N Y
C 26 Y* Y N Y*
C 28 Y Y N Y*
C 32 Y Y Y* Y
C 36 Y Y Y* Y
C 40 Y Y Y* Y
*Species with low Intensity
Further direct infusion experiments were performed using standard mixtures of
alternative composition such as, C7-C40 and C8-C40,
C21-C40 n-alkane
standards using n-heptane as the APCI reagent. Such experiments yielded a
41

Results and Discussion
common feature regarding the n-alkanes’ detection. Each of these saturated n-
alkanes were depicted instantly as (M-1) + molecular species which was
accompanied by low intensity M •+ ions. Figure 3-7 shows an APCI-MS spectrum
of the C7-C40 standard. This clearly emphasized that each single (M-1) + was
strictly related to its corresponding n-alkane precursor within the standard mixture.
Although the relative product ion abundances do not exactly match the relative
molar concentration of each component in the C7-C40 mixture, they are still
remarkably close when considering the fact that the volatilities of the compounds
vary widely. Other n-paraffin mixtures were also tested by the same method.
Figure 3-8 shows the mass spectrum of n-paraffin mixture containing C18, C20,
C22 and C24 detected as m/z 269, m/z 297, m/z 325 and m/z 353 respectively. In all
cases the ideal behavior of these analytes is mostly attributed to the proper solvent
selection, purity of reference standards and careful tuning of the APCI method
settings. In fact ionization was achieved without the use of any additional additives
and without any fragmentation. The data demonstrates that molecules of various
volatilities (boiling points ranging from 174 °C of C10 to 525 °C of tetracontane)
can be efficiently ionised by APCI and accurately mass analysed by TOF MS.
Intens.
[%]
100
+MS
561.6
547.6
80
533.6
505.6
60
449.5
477.5
40
20
253.3 281.3 337.4
239.3
379.4
407.5
435.5
0
211.2
200 250 300 350 400 450 500 550 m/z
Figure 3-7 APCI-MS spectrum in positive ion mode of C7-C40 showing (M-1) +
ions of n-alkanes
42

Results and Discussion
Intens.
[%]
325.4
C22
+MS
80
60
40
20
0
C24
C18 C20
353.4
269.3
297.3
339.3 375.4
240 260 280 300 320 340 360 380 400 m/z
Figure 3-8 APCI mass spectrum of n-paraffin mixture
Overall the mass spectrum is considerably simpler than that provided by EI or CI.
The production of intact abundant stable n-alkane ions that are representative for
their n-alkane precursor neutral analytes is the utmost achievement in my study.
For many years, mass spectrometry was considered incapable to analyse alkane
species. By this careful ionisation study of n-alkanes, the analyses of the latters are
no more out of reach. This novel approach enabled to extend the applicability of
reactive APCI-MS towards n-alkanes. The next step was to apply this unique
methodology to other types of hydrocarbons whether separate or model mixtures.
The method was successfully applied to a wider range of n-alkanes such as for
C12-C60 n-alkane standard mixture as illustrated in Figure 3-9.
Intens.
[%]
100
617.7
701.8
+MS
80
60
505.6
561.6
663.4
40
20
0
242.9
219.2
449.5
338.3 421.5
283.3 309.3
365.4 393.4 523.6 543.6 599.6 647.5
487.5
579.6
633.7 717.8 739.8 841.9
200 300 400 500 600 700 800 m/z
Figure 3-9 APCI mass spectrum of C12-C60 alkane standard
43

Results and Discussion
3.2 APCI-TOF-MS of a Variety of Hydrocarbons
Encouraged by the success in controlling the ionisation process of n-alkanes upon
APCI, we have attempted to examine a wide variety of hydrocarbons. To probe the
APCI capability, different standards of non-polar hydrocarbons were investigated
under positive APCI-TOF-MS conditions. The compounds were chosen due to
previous literature reports stating that ionization using APCI in the absence of an
additive failed to produce molecular or pseudomolecular ions. Therefore these
compounds must be considered a benchmark for difficult analytes. The ionisation
of a whole set of model standards including various non-polar hydrocarbons was
studied. Model compounds were divided into three groups as considering solvent
requirements and molecular weight distributions. The first group involved the eight
Chiron standards which were diluted in isooctane before injection. Phytane, n-
decyl benzene and 5-α-cholestane were prepared in n-heptane and were also
injected together as a second model mixture. The last group consisted of the
remaining high molecular weight (MW) alkanes which were prepared in n-heptane
prior to infusion. All analytes in the three groups were easily evaporated by APCI
heating chamber which reached up to 450 ˚C.
Figure 3-11 shows the spectrum of the eight Chiron hydrocarbon mixture. All
analytes in the mixture are in equal molar ratios. Initial inspection of the spectrum
shows that each analyte was impressively ionized and detected as intact stable [M-
H] + ion with minor or no fragmentation as obvious in Figure 3-11. This ion was
shown to be accompanied by another radical molecular cation M •+ . The intensity of
this molecular ion appears to be directly related to the intensity of the major ion,
[M-H] + , regardless of the structure of the studied compounds. Figure 3-11 also
demonstrates that the relative abundances measured for the [M-H] + ions of these
compounds are close to each other except for n-octadecyl benzene (10). Despite
the fact that those eight analytes are different in terms of volatility, structure and
composition, their product ions have close relative abundances that match their
relative molar concentrations. N-decyl benzene, phytane and 5-α-cholestane were
measured together.
44

Results and Discussion
Figure 3-10 Structures of various hydrocarbons investigated by APCI-TOF-MS
45

Results and Discussion
These compounds tend to lose hydrogen producing m/z 217, m/z 281 and m/z 371
respectively as shown in figure 3-12. A molecular ion was as well formed in
addition to the dominant [M-H] + ion for each of the three hydrocarbons. 5-α-
Cholestane was previously measured by the group of kenttamaa where no ions
were detected under positive APCI conditions according to their experimental
results. 96
Intens.
[%]
100
10
329.3
+MS
80
60
40
20
0
6
7
203.2
273.3
189.2
279.3
323.4
295.3
225.3 242.9 257.2
315.3
183.2
9
4 5
2 3
180 200 220 240 260 280 300 320 340 360 m/z
335.4
345.3
365.4
Figure 3-11 APCI spectrum of the eight Chiron hydrocarbon mixture (for
structures see figure 3-10)
Overall it was observed that the relative product ion abundances of the analytes
(equimolar solution at 0.2 mM) were very close to each other. Further direct
infusion experiments were performed using a mixture of high MW n-alkanes (C50-
C60 mass range) that were dissolved in n-heptane. Examination of separate and
model mixture of these n-alkanes demonstrated that the same ionisation pattern
was shown. The APCI mass spectrum comprised [M-H] + ions that are shown in
figure 3-13. Each gas phase [M-H] + ion was, similar to the previous hydrocarbons
in the other groups, accompanied by its molecular ion M •+ . For example
pentacontane produced a stable m/z 701.8 as intact ion conforming to [C 50 H 101 ] +
ion, this ion was accompanied by a lower-intensity M •+ m/z 702.8 conforming to
[C 50 H 102 ] •+ . This pattern of ionisation produced for all of the examined high mass
n-alkanes wasn’t surprising as this is consistent with our previous investigation of
n-alkanes’ behaviour under APCI-TOF-MS.
46

Results and Discussion
Within all of the three mass spectra (Figures 3-11, 3-12 and 3-13), the major
product ion of each analyte was found characteristic for the original precursor
hydrocarbon within the three model mixtures. All yielded a unique [M-H] +
ionisation pattern. Also figure 3-14 demonstrates the production of the same
product ion when the three groups were added together.
Again the ideal behaviour of these analytes is mostly attributed to the optimised
APCI developed methodology. A minor change of any of the method parameters
can hugely affect the product ion generation process. The examined seventeen
compounds presented model compounds of linear, branched and cyclic
hydrocarbons. Table 3.2 presents all the hydrocarbons examined in this experiment
showing their unique product ion distribution. Some of these hydrocarbons are
representative or similar to components in real life complex mixtures such as
petroleum mixtures. Since n-alkanes in the previous section and the other
hydrocarbons in the current section have been ionised by a unique [M-H] +
ionisation, an insight about the mechanism for the formation of this major ion and
other ions will be discussed in the next section.
Table 3.2 Ions produced of model hydrocarbon compounds
# Analyte MW Product Ion
1 2,6,10,14-Tetramethyl hexadecane 282 M-H +
2 2,6,10,14-Tetramethyl nonadecane 324 M-H +
3 2,6,10,14,18-Pentamethyl heneicosane 366 M-H +
4 n-Tetradecyl cyclohexane 280 M-H +
5 n-Octadecyl cyclohexane 336 M-H +
6 n-Octyl benzene 190 M-H +
7 n-Nonyl benzene 204 M-H +
8 n-Decyl benzene 218 M-H +
9 n-Tetradecyl benzene 274 M-H +
10 n-Octadecyl benzene 330 M-H +
11 5-α-Cholestane 372 M-H +
12 Dotetracontane 590 M-H +
13 Tetratetracontane 618 M-H +
14 Octatetracontane 674 M-H +
15 Pentacontane 702 M-H +
16 Tetrapentacontane 758 M-H +
17 Hexacontane 842 M-H +
47

Results and Discussion
Intens.
[%]
100
+MS
80
60
40
8
1
217.2
281.3
20
183.2 197.2 225.3
239.3 261.3 295.3 310.3 329.3
0
175 200 225 250 275 300 325 350 375 400m/z
Figure 3-12 APCI mass spectrum of n-decyl benzene, phytane and 5-α-cholestane
11
371.4
Intens.
[%]
100
80
589.7
12
15
701.8
+MS
60
40
20
0
547.6
13
617.7 647.5
14
663.5
673.8
757.8
739.8
550 600 650 700 750 800 850 m/z
16
17
841.9
Figure 3-13 APCI of high mass n-alkanes
Intens.
[%]
100
411.4
663.5
+MS
80
329.3
60
40
189.2
217.2
273.3
371.4
449.4
520.9
589.7
701.8
20
0
551.5 617.7
757.8 841.9
200 300 400 500 600 700 800 m/z
Figure 3-14 Total APCI mass spectrum in of the mixture of seventeen compounds
(see table 3.2)
48

Results and Discussion
3.3 Pathway of Ionisation of Hydrocarbon Standards under APCI
Conditions
Representative alkanes and the other hydrocarbon standards produced
predominantly (M-1) + as shown within the previous results. The results include as
well (M-3) + and (M-3) + H 2 O to the extent that in many cases, these ions were seen
in greater abundances than the (M-1) + species. (M-1) + ions were reported to be
formed by the studies of Carroll 109 et al. and Bell et al. 78 The latter has also shown
the importance of (M-1) + , (M-3) + and (M-3) + H 2 O ions in the APCI mass spectra of
alkanes generated by a corona discharge and monitored by ion mobilities. 78 (M-1) +
is also a common feature of the APCI mass spectra in air plasma of
hydrocarbons. 79 (M-1) + is the characteristic product ion in chemical ionisation
experiments of alkanes run with interplay of reagent gases such as N 2 , O 2 and H 2 O.
However under the conditions of our experiment, atmospheric pressure nitrogen
plasma seems to be a focused complex environment using n-heptane as infusion
solvent. (Figure 3-15). With very low water content within the nitrogen reagent gas
stream, the radical cation of nitrogen (N •+ 2 ) is the major reagent ion available for
performing ionisation of evaporated analytes of alkanes or other hydrocarbons that
were tested in this study. Based on the experimental results obtained in this study
and on available literature, we suggested a general pathway that accounts for the
formation of (M-1) + and (M-3) + H 2 O ions. It is suggested that the route of
formation of ions observed within atmospheric pressure and generated by corona
discharge under nitrogen is shown in Scheme 2. A structural route of ionisation
mechanism is also provided by scheme 3. This proposed ionisation comprises
formal hydride abstraction particularly by N •+ 2 as the lone reactive species thought
to be responsible for the production of (M-1) + ions. The high frequency of collision
of N •+ 2 with the neutral hydrocarbon analytes resulted in enhanced ionisation and
thermalisation of the analyte ions. As far as the molecular ion generation is
concerned, a charge transfer reaction is most likely responsible in this case.
The suggestion is also corporated by data from Kolakowski where (M-1) + ions
were observed under chemical ionization (CI) experiments of alkanes. 89 (M-3) +
49

Results and Discussion
Ions were proposed by Bell to form when alkane cations spontaneously lose H 2 to
form ions of an allyl cation structure (M (M-1) + H 2 elimination). Alternatively
a hydrogen abstraction by any reactive nitrogen species present after discharge to
produce (NH) 2 species can be envisaged. The allyl cations, as highly reactive
electrophiles, can add water present in the gas flow to produce protonated allylic
alcohol ions.
Figure 3-15 Suggested graphical scheme for ionisation mechanism of hydrocarbon
upon APCI
Scheme 2. Suggested routes for the formation of (M-H) + and (M-3H) + H 2 O in
APCI-MS.
In an attempt to support the hypothesis of intermolecular water addition to allyl
cations in the gas phase, deuterium oxide was added to individual alkanes for
example, tetracontane (C40). As expected the resulting ions could be characterised
as deuterated species (M-3) + D 2 O using the same MS conditions. Figure 3-16
shows the mass spectrum after addition of D 2 O to n-tetracontane. Also we have
also measured deuterated standards of n-alkane.
50

Results and Discussion
Scheme 3. Suggested structural route for the formation of (M-H) +
3H) + H 2 O in APCI-MS.
and (M-
The results for deuterated compounds paralleled those obtained for nondeuterated
equivalents. Figure 3-17 shows the mass spectrum of deuterated tetracosane.
Deuterated tetracosane D-C24 (C 24 D 50 ) produced primarily (M-D) + and (M-
3D) + H 2 O. These findings confirm that (M-1) + and (M-3) + ions initially observed
were geniune species.
51

Results and Discussion
Intens.
[%]
(M-1) +
561.6
+MS
60
(M-3) + D 2 O
580.6
40
20
0
507.5 523.4 537.5 551.5
591.4 599.6 608.4
617.7
520 540 560 580 600 620 m/z
Figure 3-16 APCI mass spectrum after the addition of D 2 O to C40
Intens.
[%]
100
80
(M-D) +
386.7
(M-3D) + H 2 O
401.7
+MS
60
40
20
0
285.3
369.3
306.5 331.3
429.4
447.4 467.4 481.5
280 300 320 340 360 380 400 420 440 460 m/z
Figure 3-17 APCI mass spectrum of deuterated tetracosane (D-C24)
Another verification of (M-3) + H 2 O as water adduct species was accomplished by
isolating the monohydrated ion of dotriacontane (C32) and subjecting it to
collision induced dissociation (CID). A high mass fragment ion was recorded at
m/z 447, corresponding to (M-3) + , assuming the loss of water as shown in figure 3-
18. A similar water loss was identified from hydrated clusters of the (M-1) + of
C29. Figure 3-19 illustrates the loss of water from m/z 425 (M-1) + H 2 O to give m/z
407 (M-1) + . These results combined with findings from APCI-MS of deuterated
species prove confidence with the authenticity of (M-1) + and (M-3) + species.
52

Results and Discussion
Intens.
[%]
100
(M-3) +
+MS 2 (465.8)
447.4
80
409.4
60
40
167.0
181.0
353.4 381.4
367.4
395.4
(M-3) + H 2 O
465.8
20
0
100 150 200 250 300 350 400 450 m/z
Figure 3-18 APCI-MS 2 spectrum of C32 showing (M-3) + fragment at m/z 447.4
from precursor ion at m/z 465.8 corresponding to (M-3) + H 2 O
Intens.
+MS 2 (425)
[%]
100
(M-1) +
(M-1) + H 2 O
425.1
407.3
158.9
369.1
50
0
188.9
215.0 271.0
313.1
299.1
351.1
381.1
150 200 250 300 350 400 450 m/z
Figure 3-19 APCI-MS 2 spectrum of C29 showing (M-1) + fragment at m/z 407.3
from precursor ion at m/z 425.1 corresponding to (M-1) + H 2 O
3.4 Light shredder Waste Analysis
3.4.1 (+)APCI-TOF-MS of Waste Sample
After the detailed and necessary groundwork knowledge about the ionisation of the
standard hydrocarbons in the previous section was attained, I have moved into the
analysis of hydrocarbon content within the complex mixture of light shredder
waste. Concerning the waste sample I have employed an optimised extraction
53

Results and Discussion
procedure based on the KW 04 method. 108,110 I found that addition of acetone
during extraction, enhanced the penetration of n-heptane (main solvent). Using an
automatic Soxhlet extraction, it was found that six hours were the optimum
extraction time needed for hydrocarbon intake. Next, the extracted waste samples
were measured as direct infusions in n-heptane using the APCI-TOF MS method
similar to the one used for the analysis of reference standards. Figure 3-20 shows a
mass spectrum of light shredder waste sample initially extracted with
Heptane/Acetone. Figure 3-21 shows a waste sample which was extracted with n-
heptane only. The former spectrum reflected a higher degree of complexity which
was characterised by a large number of significant peaks compared to the sample
of figure 3-21. By similar mass spectra comparisons, I was also able to screen the
effectivity of florisil in purifying the heptane extract from polar species. Mass
spectra (a), (b) and (c) in Figure 3-22 shows that when more grams of florisil are
used during purification course, the sample is better cleaned.
Intens.
[%]
100
80
369.4
411.4
397.4
425.4
453.4
+MS
60
40
273.3
315.3
467.5
481.5
495.5
509.5
551.5
20
701.8
0
200 250 300 350 400 450 500 550 600 650 m/z
Figure 3-20 APCI (+) mass spectrum of waste sample extracted using n-
heptane/Acetone
54

Results and Discussion
Intens.
[%]
100
80
60
40
20
397.4
411.4
425.4
257.2
285.3
305.3
449.5
505.6
541.6 561.6 663.5
+MS
0
200 250 300 350 400 450 500 550 600 650 m/z
Figure 3-21 APCI mass spectrum of waste sample extracted using n-heptane only
Intens.
[%]
60
40
347.3
(a)
349.3
351.3
352.3
353.3
355.3
357.3
359.3
361.3
363.3
+MS
365.3
20
348.3
350.3
354.3
356.4
358.2
360.3
362.3
364.3
0
348 350 352 354 356 358 360 362 364 m/z
Intens.
[%]
40
(b)
+MS
355.3
357.4
30
353.3
365.3
351.3
359.3
363.3
349.3
20
347.3
361.3
356.3
358.4
10
354.3
352.3
350.3
360.3
364.3
348.3
362.3
0
348 350 352 354 356 358 360 362 364 m/z
55

Results and Discussion
Intens.
[%]
50
(c)
357.4
+MS
40
355.3
359.4
30
20
10
0
C 26 H 39 C 25 H 52
353.3
347.4
C 26 H 39 C 25 H 52
361.4
358.4
365.3
349.4
351.3
356.3
360.4 363.4
348.4
354.3
362.4
352.3
350.4
364.4
348 350 352 354 356 358 360 362 364 m/z
Figure 3-22 Mass spectra of the waste sample purified by using 2 gs (a), 4 gs (b)
and 6 gs (c) of florisil during purification.
The altered light shredder waste fraction (hydrothermally treated) was analysed by
APCI using N 2 gas as reagent. The mass spectrum in figure 3-20 shows ions for all
components within the solid waste sample. The bulk of the sample, assuming
ionisation without fragmentation as shown earlier, consists of hydrocarbons
between 18 and 34 carbon atoms per molecule resulting in a mass envelope with
almost Gaussian distribution centered around m/z 400. Examination of the waste
spectrum reveals a MW distribution that spans over a mass range of m/z 200-700
Da. This could define a typical MW distribution of solid waste hydrocarbon
content. Although the waste spectrum demonstrates a relatively low mass
distribution range, it reflects a high degree of complexity characterized by the huge
number of peaks found in the spectrum. Around 4000 resolved signals were
observed by direct infusion using a (+) APCI-TOF/MS method.
The enlarged mass spectrum in figure 3-23 exhibits two contrasting modes of
ionisation for each analyte. Low intensity even mass ions accompany their
respective high intensity odd mass ions. Even mass ions are most likely
hydrocarbon molecular ions (or isotope peaks 2 H, 13 C) formed by a loss of an
electron due to the role played by N 2 gas while odd mass ions are the significant
ions corresponding to (M-1) + ions of hydrocarbons within the waste mixture.
56

Results and Discussion
Intens.
[%]
100
80
60
40
20
393.3
394.3
395.4
396.4
397.4
398.4
399.4
400.4
401.4
405.3
403.4
402.4
404.4 406.4
407.4
408.4
409.4
410.4
411.4
412.4
413.4
+MS
414.4
0
392.5 395.0 397.5 400.0 402.5 405.0 407.5 410.0 412.5 m/z
Figure 3-23 Enlarged section of (+) MS showing bimodal distribution of odd and
even mass ions
The latter interpreted ionisation behavior of hydrocarbon ions in solid waste was
anticipated from our previous results of ionisation behavior of n-alkanes and other
hydrocarbon model standards upon APCI. These model standards produced also
stable (M-1) + ions with neighboring molecular ions M •+ without any fragmentation
under similar APCI conditions. This indicated that the stable ions appearing in the
positive mass spectrum (+MS) are intact ions expressing their hydrocarbons that
exist in the waste sample.
3.4.2 Calibration
After this fundamental description of the explored chemical content of the waste, a
molecular formula assignment was required for all compounds present in the waste
spectrum. However before identifying n-alkanes ,that are expected to be found
within the waste chemical content, the obvious obstacle was to find suitable
calibrant for the APCI-MS high resolution mass measurements. The generally used
commercial APCI/APPI acetonitrile calibrant was not really effective towards a
low-mass error assignment of waste sample components of n-alkanes and others.
This is due to the fact that the calibrant’s range, shown in figure 3-24, did not fully
cover the alkane mass range of interest (m/z 200-600) in these experiments. To
overcome this problem, I have employed the C7-C40 n-alkane standard (figure 3-
25) mixture to be used for m/z calibration using an enhanced quadratic calibration
57

Results and Discussion
to produce mass errors around 3 ppm. An enhanced quadratic fit provides the best
relative standard deviation (RSD) around 1 of the analytes of the calibrant
compared to linear or quadratic fits. For the calibration curve all (M-1) + ions of n-
alkanes were used as reference masses, serving as an external calibrant for the
waste analysis. The speciation of most of the components including n-alkanes
within the waste sample was made possible by this intriguing employment of the
C7-C40 calibrant standard. The combination of the calibration method
establishment with the preceded thorough understanding of the ionisation of
hydrocarbons provided a rational elemental assignment of the molecular
composition of the waste complex mixture. Table 3.3 shows the molecular formula
list of n-alkanes obtained from a shredder waste sample under investigation.
Intens.
[%]
100
80
622.0
922.0
+MS
60
40
20
322.0
1522.0
0
663.4 850.0
200 400 600 800 1000 1200 1400 m/z
Figure 3-24 APCI/APPI standard recommended calibrant for APCI source
With this result we could tentatively identify all n-alkanes (C13-C40) by their
apparent (M-1) + representative ions in a real life complex waste sample displaying
a UCM hump in a gas chromatogram. However the identified series of n-alkanes is
only a significant part of the chemical content of the waste. The determination of
the other components within the waste spectrum will lead to clarify the chemical
content of the unresolved complex mixture.
58

Results and Discussion
Intens.
[%]
100
+MS
561.6
547.6
80
533.6
505.6
60
449.5
477.5
40
20
253.3
239.3
281.3 337.4
379.4
407.5
435.5
0
211.2
200 250 300 350 400 450 500 550 m/z
Figure 3-25 APCI mass spectra in positive ion mode of C7-C40 calibrant
Table 3.3 Molecular formula list of n-alkanes in waste sample
m/z Meas. m/z Molecular Formula Error [ppm]
183.2107 183.211 C 13 H 28 -1.5
197.2264 197.2266 C 14 H 30 -1.3
211.242 211.2421 C 15 H 32 -0.4
225.2577 225.2579 C 16 H 34 -0.8
239.2733 239.2724 C 17 H 36 4.1
253.289 253.2888 C 18 H 38 0.6
267.3052 267.3044 C 19 H 40 3
281.3203 281.3209 C 20 H 42 -2.1
295.3359 295.3364 C 21 H 44 -1.7
309.3516 309.3516 C 22 H 46 -0.1
337.3829 337.3823 C 24 H 50 1.8
351.3985 351.3981 C 25 H 52 1.3
365.4142 365.4131 C 26 H 54 3
379.4298 379.4284 C 27 H 56 3.8
393.4455 393.4457 C 28 H 58 -0.5
421.4768 421.4775 C 30 H 62 -1.7
435.493 435.4938 C 31 H 64 -1.9
449.5081 449.5075 C 32 H 66 1.4
463.5237 463.522 C 33 H 68 3.8
477.5394 477.5386 C 34 H 70 1.6
491.555 491.5538 C 35 H 72 2.5
505.5707 505.5695 C 36 H 74 2.4
59

Results and Discussion
519.5863 519.5838 C 37 H 76 4.9
533.602 533.5975 C 38 H 78 1.3
547.6182 547.6176 C 39 H 80 1.1
561.6333 561.6306 C 40 H 82 4.8
Table 3.4 shows the molecular formula list of some of the compounds found in the
waste spectrum. The molecular formulas of n-alkanes within the list are obviously
characterized by their (M-1) + ion formula. The content is already known to
comprise a series of n-alkanes ranging from decane (C10) till tetracontane (C40).
The remaining compounds are assigned as unsaturated and/or cyclic hydrocarbons
depending on their molecular formulas. Underneath each saturated n-alkane a
series of dehydrogenated derivatives was observed. The molecular formulas
suggested that waste components could be assigned as alkenes or cycloalkanes
varying by their unsaturation degree or variation of doubly bond equivalents. The
molecular formulas for these compounds also suggested degradation that happened
to the hydrocarbons in the waste sample during microbial processing, since they
were found to be absent in untreated waste. Apparently each compound differs by
a mass increment of two m/z units between every two consecutive compounds,
thus suggesting a dehydrogenation process. An enlarged part of the waste sample’s
mass spectrum is shown in figure 3-22 (c) showing that peaks corresponding to the
saturated alkanes along with peaks corresponding to compounds with increased
double bond equivalents formally obtained through a dehydrogenation. All waste
samples were measured in triplicates and were found to be reproducible.
60

Results and Discussion
Table 3.4 Molecular formula list of some analytes of hydrocarbons in waste
sample
Meas. m/z Mol.Formula m/z Error [ppm]
189.163 C 14 H 21 189.1638 4.2
191.1789 C 14 H 23 191.1794 2.6
193.1941 C 14 H 25 193.1947 3.1
195.2105 C 14 H 27 195.2107 1
197.2259 C 14 H 29 197.2264 2.5
199.1477 C 15 H 19 199.1481 2
201.164 C 15 H 21 201.1638 -1
203.1796 C 15 H 23 203.1794 -1
205.1954 C 15 H 25 205.1951 -1.5
207.211 C 15 H 27 207.2107 -1.5
209.2266 C 15 H 29 209.2264 -1
211.2422 C 15 H 31 211.242 -1
213.1647 C 16 H 21 213.1638 -4.2
215.1804 C 16 H 23 215.1794 -4.6
217.1956 C 16 H 25 217.1951 -2.3
219.2109 C 16 H 27 219.2107 -0.9
221.2274 C 16 H 29 221.2264 -4.5
223.2427 C 16 H 31 223.242 -3
225.2586 C 16 H 33 225.2577 -4
231.212 C 17 H 27 231.211 -4.3
233.2273 C 17 H 29 233.2264 -3.8
235.2429 C 17 H 31 235.242 -3.8
237.258 C 17 H 33 237.2577 -1.3
245.2276 C 18 H 29 245.2264 -4.9
247.2432 C 18 H 31 247.242 -4.8
249.2591 C 18 H 33 249.2583 -3.2
251.274 C 18 H 35 251.2733 -2.8
253.2904 C 18 H 37 253.291 2.4
261.2592 C 19 H 33 261.2599 2.6
263.2747 C 19 H 35 263.2752 1.8
265.2884 C 19 H 37 265.289 2.3
267.3051 C 19 H 39 267.3046 -1.9
279.3057 C 20 H 39 279.3046 -4
61

Results and Discussion
Higher mass range
281.3214 C 20 H 41 281.3203 -3.9
289.2906 C 21 H 37 289.291 1.4
291.306 C 21 H 39 291.312 2
293.3212 C 21 H 41 293.3222 3.4
295.3374 C 21 H 43 295.3384 3.4
303.3062 C 22 H 39 303.3076 4.6
305.3215 C 22 H 41 305.3203 -4
307.3367 C 22 H 43 307.3359 -2.6
309.3522 C 22 H 45 309.3516 -2
317.3219 C 23 H 41 317.3228 2.8
319.3375 C 23 H 43 319.3381 -4.8
321.3515 C 23 H 45 321.3516 0.3
323.3685 C 23 H 47 323.3672 -4
327.3065 C 24 H 39 327.3071 1.8
331.3377 C 24 H 43 331.3387 3
333.3529 C 24 H 45 333.3516 -3.9
337.3836 C 24 H 49 337.3829 -2
343.3378 C 24 H 43 343.3389 3.2
345.3532 C 24 H 45 345.3516 -4.7
347.3684 C 24 H 47 347.3672 -3.4
351.3986 C 25 H 51 351.3985 -0.2
357.3535 C 26 H 45 357.3549 3.9
359.3686 C 26 H 47 359.3672 -3.8
361.3841 C 26 H 49 361.3829 -3.4
365.4155 C 26 H 53 365.4142 -3.6
371.3694 C 27 H 47 371.3704 2.7
373.384 C 27 H 49 373.3829 -2.9
379.4303 C 27 H 55 379.4298 -1.3
383.3692 C 28 H 47 383.3705 3.4
385.3851 C 28 H 49 385.387 5
387.3994 C 28 H 51 387.3985 -2.4
389.4144 C 28 H 53 389.4142 -0.6
391.3359 C 29 H 43 391.3356 -0.7
393.445 C 28 H 57 393.4455 1.2
395.3694 C 29 H 47 395.368 -3.5
399.4009 C 29 H 51 399.3999 -2.5
401.4146 C 29 H 53 401.4142 -1
407.4588 C 29 H 59 407.4599 2.7
62

Results and Discussion
After identifying the chemical content in the positive ion mode of APCI-TOF-MS
method, I shifted the method to the negative polarity to explore any potential
compounds preferably ionised under negative APCI-TOF-MS
3.4.3 Identification of Polychlorinated Biphenyls (PCBs) in (-) APCI-TOF-
MS
The waste mixture was measured again by direct injection using this time negative
(-) APCI-TOF-MS method. The mass spectrum observed in figure 3-26 revealed a
class of polychlorinated compounds which demonstrated chlorine isotope patterns.
Tetrachlorobiphenyl (1) at m/z 272.9, pentachlorobiphenyl (2) at m/z 306.9,
hexachlorobiphenyl (3) at m/z 340.9, heptachlorobiphenyl (4) at m/z 374.8 and
octachlorobiphenyl (5) at m/z 408.8 were identified by the (-) APCI method. This
identification was based on a rational study of a PCB Congener Mix under the
same (-) APCI conditions. The PCBs components within the standard mix
produced (M-Cl+O) – ions as shown in figure 3-27. This finding wasn’t surprising
as PCBs have been previously reported to ionize with the same fashion under
APCI conditions. 111,112 The selectivity of ionisation is actually the significant
observation. We tested the highest chlorinated PCB, decachlorobiphenyl (M=
498.66 g/mole) which was found to produce an (M-Cl+O) – ion at m/z 478.7 as
shown in figure 3-28. A simulated isotope pattern for decachlorobiphenyl which is
embedded in figure 3-28 was provided by Bruker Software. The latter figure shows
that the measured and simulated isotope patterns are identical. However the (-)
mass spectrum of the waste extract comprises also high mass chlorinated
compounds. These compounds could be assigned as chlorinated alkanes or
chlorinated aromatic hydrocarbons. Nevertheless the Bruker software of the TOF-
MS suggested a chlorine content of these compounds according to their isotope
patterns shown in figure 3-26. Small PCBs containing capacitors in household
appliances and PCB-containing sealants for buildings within light shredder waste
fraction would be the sources of these PCBs.
63

Results and Discussion
Intens.
[%]
100
2
306.9
3
340.9
Cl 6
450.9
-MS
80
60
40
20
0
Cl 7
484.8
283.3
4
1
374.8 420.8 473.3
Cl 6
270.9
5
Cl 5 Cl8
576.6
435.8
520.8
Cl 8
Cl 7
658.5
Cl 10
736.4
632.7
300 350 400 450 500 550 600 650 700 m/z
Figure 3-26 (-) APCI mass spectrum showing identified PCBs in waste sample
Intens.
[%]
100
C 12 H 6 OCl 4
C 12 H 5 OCl 5
306.9
340.9
-MS
80
60
40
283.3
C 12 H 4 OCl 6
374.8
C 12 H 3 OCl 7
408.8 473.3
20
0
321.9
355.9
275 300 325 350 375 400 425 450 475 500 m/z
Figure 3-27 (-) APCI mass spectrum of PCBs Congener Mix
Intens.
[%]
100
478.7
-MS
80
60
476.7
480.7
40
20
474.7
482.7
484.7
0
455 460 465 470 475 480 485 490 495 500 m/z
Figure 3-28 (-) APCI mass spectrum of decachlorobiphenyl standard (C 12 OCl 9 )
with simulated isotope pattern as suggested by Bruker Software
64

Results and Discussion
After the confident identification of few PCBs within the waste extract, we
employed tandem-MS in order to obtain further structural information on the
components.
3.4.4 Tandem MS Measurements
Tandem MS measurements were carried out as direct infusion experiments in n-
heptane in the positive ion mode using an ion trap mass spectrometer with APCIionisation.
After injecting the waste sample into the iontrap, the lower mass
distribution of the sample, shown in figure 3-29, had ions with mostly odd mass
values (see figure 3-30). This indicated that the lower mass distribution mostly
consists of fragment ions formed from the molecular ions. This is as expected
because ionisation occurred via the high-energy process of electron abstraction by
N +• 2 . At first task (M-1) + series of standard n-alkanes ions were selected and
isolated with an isolation width of 1 Da and each n-alkane subjected to Collision
Induced Dissociation (CID). The (M-1) + ions of few analytes of n-alkanes within
the C7-C40 standard were fragmented as shown in figures 3-31 to 3-34. The
fragmentation pattern (MS 2 spectrum) seems to decrease by an increment of 14 Da
which reflects the CH 2 group that forms the structure of n-alkanes. This is further
emphasized in scheme 4 where a fragmentation route for pentacosane (C25) is
provided. Isolation of the molecular ions of the higher n-alkanes within the
standard C7-C40 like tetracosane (C40) was made possible. Figure 3-35 shows the
MS 2 spectrum of m/z 562, the molecular ion of C40. The advantage here is that this
ion could independantly evaporate into the gas phase, get ionised and further
isolated to be subjected to CID in Iontrap-MS. Further isolation of similar
molecular ions are demonstrated in figures 3-36 and 3-37. Access to fragmentation
patterns of molecular ions can make use of the GC library accummulated for many
years.
65

Results and Discussion
Intens.
[%]
100
80
60 97.1
577.5
40
633.5
20
0
100 200 300 400 500 600 700 800 900 m/z
Figure 3-29 APCI-ion trap mass spectrum of waste sample
Intens.
+MS
[%]
80
60
97.1
40
111.0
124.9
20
0
60 80 100 120 m/z
Figure 3-30 Low mass distribution in APCI-iontrap mass spectrum for waste
sample
Intens.
+MS 2 (337)
[%]
239.0
100
225.1
197.0
253.1
80
183.0
267.1
60
154.9
338.3
281.1
40
113.0
303.3
20
0
100 150 200 250 300 350 400 m/z
Figure 3-31 APCI-MS 2 of tetracosane with precursor ion at m/z 337 corresponding
to (M-1) +
150.9 190.9 409.3
467.4
509.5
+MS
66

Results and Discussion
Intens.
[%]
100
80
60
40
20
0
113.0
169.0
141.0
154.9
211.0
239.1 267.1
281.2
295.2
309.3 333.3 351.3
+MS 2 (351)
100 150 200 250 300 350 400 450 m/z
Figure 3-32 APCI-MS 2 of pentacosane with precursor ion at m/z 351corresponding
to (M-1) +
Intens.
[%]
100
80
154.9
168.9
182.9
197.0
225.0
239.1
295.2
281.1
309.3 323.3
+MS 2 (407)
60
40
20
127.0
337.3
351.3
365.3
389.4
405.2
0
100 150 200 250 300 350 400 m/z
Figure 3-33 APCI-MS 2 of nonacosane with precursor ion at m/z 407 corresponding
to (M-1) +
Intens.
[%]
100
80
60
40
20
0
132.9
144.8
186.9
172.9 198.8
269.0
283.1
297.1
325.2
311.1
337.2
351.2
365.2
379.3
393.3
407.3
421.2
433.2
449.3
+MS 2 (449)
150 200 250 300 350 400 450 500 m/z
Figure 3-34 APCI-MS 2 of dotriacontane with precursor ion at m/z 449 correspon-
ding to (M-1) +
67

Results and Discussion
Intens.
[%]
100
562.6
+MS 2 (562)
80
60
295.3 351.4 379.4 407.4
197.1 225.1 253.1 323.3 449.5
463.5
183.0
477.5
40
169.0
491.5
20
0
505.5
150 200 250 300 350 400 450 500 550 600 m/z
519.5
Figure 3-35 APCI-MS 2 of molecular ion of tetracontane (C40) at m/z 562
Intens.
[%]
100
80
60
40
20
0
155.0
211.0
197.0
182.9
168.9
295.2
281.2
239.1 267.1
309.3
407.4 435.4
421.4
323.3 449.4
351.4
463.5
477.5
491.5
505.5
529.6
548.7
+MS 2 (548)
150 200 250 300 350 400 450 500 550 m/z
Figure 3-36 APCI-MS 2 of molecular ion of nonatriacontane (C39) at m/z 548
Intens.
[%]
100
80
60
295.2
225.0 267.1
211.0 253.1
337.3 365.3
351.3
421.4
379.4 407.4 435.4
449.5
+MS 2 (534)
40
20
0
168.9
463.5 515.5
155.0
534.6
491.4
150 200 250 300 350 400 450 500 550 m/z
Figure 3-37 APCI-MS 2 of molecular ion of octatriacontane (C38) at m/z 534
68

Results and Discussion
Similar results were obtained for (M-1) + for n-alkanes within waste samples. In
contrast higher mass n-alkane species in some waste samples exhibited low
relative abundances. This leads to make them difficult to isolate and thus fragment.
It happens that the isolated low abundance alkane ion is not steady enough to give
a fragmentation pattern similar to the one isolated from the standard C7-C40
alkane mixture.
Intens.
[%]
100
75
50
25
[%]
0
100
75
50
25
[%] 0
172.8 252.9 325.1 379.2
181.8216.9 276.0
349.0 406.3436.1
561.5
504.4
547.5
517.4
100
75
50
25
[%] 0
172.8 267.0 377.2407.2
461.4
517.4
100
75
50
25
0
503.4
447.3
184.8 255.0 298.9 379.2
100 200 300 400 500 600 700 m/z
Figure 3-38 APCI-MS 2 spectra of m/z 561, 547, 519 and 505 corresponding to
(M-1) + ions of C40, C39, C37 and C36 respectively within a waste extract
Figure 3-38 shows the MS 2 pattern of m/z 561, 547,519 and 505 (M-1) + ions within
a waste extract. After acquiring the Tandem MS data for the n-alkanes within the
C7-C40 standard as well as those within the waste extract, a comparison was
necessary to prove structural identity of the ions. The comparison of the
fragmentation patterns of the standard n-alkanes was found similar, but not
identical, to that of the ions of identical m/z values found within the waste sample.
Figure 3-39 shows an MS 2 tandem spectrum for nonacosane (C 29 H + 59 ) at m/z 407
69

Results and Discussion
isolated from n-alkane standard (a) and a tandem MS spectrum of an ion of m/z
407 from waste extract (b). The partial identity of the spectra, with all fragment
ions observed in the reference sample as well observed in the actual waste sample,
serves as a structural evidence for the presence of n-alkanes in the complex
mixture of the light shredder waste. These data suggest as well that the positive
reactant ion and alkane molecules undergo ion-molecule reaction at the
atmospheric pressure conditions to produce molecular type and alkyl fragment
ions. The production of this (M-1) + series of fragments is in agreement with
electron impact and chemical ionisation of one n-alkane reported previously. 113
The differences in the two experimental tandem MS spectra can be rationalised by
assuming that in addition to n- alkanes as well other isomeric branched alkanes are
present in the actual waste sample giving rise to variations in the intensities of the
fragment ions.
Scheme 4. Fragmentation scheme of (M-1) + of pentacosane (C25) at m/z 351
Although the utility of chemical standards is impractical for such incredibly large
number of derivatives, we have used few specific standards to map the structure of
the detected unsaturated compounds in the waste spectrum. Tandem MS
experiments were performed using similar APCI conditions interfaced to an
Iontrap-MS. With a low isolation width (1Da), groups the unsaturated compounds
were selected and fragmented using CID available in Iontrap/MS.
70

Results and Discussion
The fragmentation patterns of the waste components were found similar to each
other. While fragmenting few hydrocarbon standards we have seen a significant
similarity between the MS 2 patterns of waste components and that of squalene.
Figure 3-40 shows the MS 2 spectrum for squalene and figure 3-41 shows the MS 2
spectra that belong to four selected ions from the waste, m/z 409, m/z 411, m/z 413
and m/z 415. While the m/z 411 ions within the waste extract and that of squalene
have the same molecular formula (C 30 H 51 ) + , they are not structurally identical.
There is partial resemblance between the MS 2 spectra of the two compounds.
Similarly the other selected ions have matching fragments with those obtained
from squalene.
Figure 3-39 MS 2 fragmentation spectra for nonacosane C 29 H 59 + within standard n-
alkane mixture (a) and within waste sample (b)
71

Results and Discussion
Intens.
[%]
100
80
60
40
20
120.9
134.9
162.9
176.9 202.9
230.9
245.0
259.1
287.1
301.1
315.2
329.2
355.3
341.3 369.3
412.3
+MS 2 (411.0)
0
100 150 200 250 300 350 400 450m/z
Figure 3-40 APCI-MS 2 spectrum of squalene of m/z 411
Intens
[%]
100
75
50
25
[%]
0
100
75
50
25
[%]
0
100
75
50
25
[%]
0
100
75
50
25
0
130.8
144.8
160.7
172.8
174.8
160.7 188.8
202.7
162.8
176.7
162.7 190.8
148.7
198.7 212.8 254.9
226.8
240.8
216.9
228.9
242.9
218.7232.9
244.8
259.0
260.9
271.0
274.9
339.1
311.0
283.0 297.0 325.1
100 150 200 250 300 350 400 450m/z
287.0
299.0
315.0
317.0
367.1
394.1
411.3
327.1 341.1 355.1369.1 396.1
343.1
345.1
357.1
359.1
373.1
385.2
419.2
MS 2 (409)
MS 2 (411)
MS 2 (413)
MS 2 (415)
Figure 3-41 APCI-MS 2 spectra of four selected ions within the waste sample of
m/z 409,411,413 and 415
The similarity between the unsaturated compounds in the waste and squalene is
demonstrated in their fragmentation pattern that are underlined in figure 3-41.
This suggests degraded compounds could be structurally similar but not identical
to squalene. Addition experiments involved the analysis of other standards of
hydrocarbon. For example 5-α-cholestane was depicted as (M-1) + ions first time
reported to produce under APCI conditions. Interestingly MS 2 tandem spectrum
for 5-α-cholestane standard (see figure 3-42) at m/z 371 (C 27 H 47 ) + was found
72

Results and Discussion
identical to MS 2 tandem spectrum of m/z 371 isolated from the waste mixture
shown in figure 3-43. Further MS 3 spectra were acquired for the significant m/z
355 fragment ion from both the standard and waste sample. The resulting spectra
were also found identical. Another interpretation of the MS 2 fragmentation spectra
is provided in table 3.5. The fragments of tetracosane, pentacosane and squalene
are assigned.
Table 3.5
CID MS 2 -stage tandem mass spectra for some of the positive ions of
tetracosane, pentacosane and squalene.
Compound (m/z)
MS 2 fragmentations
(Product ions m/z)
(281) C 20 H 41 (183) C 13 H 27
(267) C 19 H 39 (169) C 12 H 25
Tetracosane (337)
(253) C 18 H 37 (155) C 11 H 23
(239) C 17 H 35 (141) C 10 H 21
(225) C 16 H 33 (127) C 9 H 19
(211) C 15 H 31 (113) C 8 H 17
(197) C 14 H 29
(295) C 21 H 43 (197) C 14 H 29
(281) C 20 H 41 (183) C 13 H 27
Pentacosane (351)
(267) C 19 H 39 (169) C 12 H 25
(253) C 18 H 37 (155) C 11 H 23
(239) C 17 H 35 (141) C 10 H 21
(225) C 16 H 33 (127) C 9 H 19
(211) C 15 H 31 (113) C 8 H 17
(369) C 27 H 45 (231) C 17 H 27
(355) C 26 H 43 (217) C 16 H 25
(341) C 25 H 41 (203) C 15 H 23
(329) C 24 H 41 (189) C 14 H 21
Squalene (411)
(315) C 23 H 39 (177) C 13 H 19
(301) C 22 H 37 (163) C 12 H 17
(287) C 21 H 35 (149) C 11 H 15
(273) C 20 H 33 (135) C 10 H 13
(259) C 19 H 31 (121) C 9 H 11
(245) C 18 H 29
73

Results and Discussion
Intens.
[%]
100
354.9
+MS 2 (371)
75
50
25
[%]
0
148.9
188.9
261.0
315.1
371.3
+MS 3 (371->355)
100
268.7
75
50
284.8
354.9
25
0
338.9
50 100 150 200 250 300 350 400 450 m/z
Figure 3-42 Fragmentation spectrum of 5-α-cholestane at m/z 371 C 27 H 47 + within
standard 5-α-cholestane sample
Intens.
[%]
100
373.3
+MS 2 (371.0)
75
50
25
119.1 145.0 174.9 230.0 258.1 300.2
355.1
[%]
0
100
355.1
+MS 3 (371.0->355.0)
75
50
25
0
268.9
284.9
50 100 150 200 250 300 350 400 450 m/z
Figure 3-43 Fragmentation spectra for C 27 H 47 + ion at m/z 371 within waste sample
A fragmentation scheme for 5-α-cholestane at m/z 371 is demonstrated in scheme
5. The fragmentation appears to start in the alkyl group of 5-α-cholestane.
Subsequent losses of a methyl with a neighboring hydrogen and an isopentyl group
is proposed to explain part of the fragmentation spectrum of 5-α-cholestane.
74

Results and Discussion
Scheme 5. Fragmentation scheme of (M-1) + of 5-α-cholestane at m/z 371
75

Results and Discussion
3.4.5 Tandem MS of Derivatised Compounds
Furthermore, Tandem MS has been used to explore derivatised waste sample. In a
separate experiment, silver triflate was added to the waste extract. Figure 3-44
shows the mass spectrum after addition of silver triflate. Isotope patterns indicating
the presence of Ag were observed. This shows that the silver complexed to few
components within the waste and the resultant masses dominated the waste spectra
as shown in figure 3-44. The idea here was to employ Tandem MS to inquire about
the structural identity of these new product ions. MS 2 spectrum of selected m/z 328
ion was acquired as shown in figure 3-45. The fragmentation shows the typical
isotope pattern of the detached silver at m/z 107 and m/z 109 in figure 3-45.
However the fragmentation spectrum didn’t provide additional knowledge about
the structure of the compound that complexed with Ag. This leads to conclude that
derivatisation with silver has led to enhance few compounds that may have been of
low abundance within the waste extract. However derivatisation in this case
doesn’t seem to aid in providing structural information about the compounds found
in the waste sample.
Intens.
[%]
100
328.8
+MS
80
60
411.4 423.4
40
303.2
20
337.3 351.3 365.3 379.3
397.4
439.4
457.4 471.4 485.4 499.4 513.5 527.5
0
300 325 350 375 400 425 450 475 500 525m/z
Figure 3-44 APCI mass spectrum in positive ion mode of waste sample deriva-
tised with Agtriflate
76

Results and Discussion
Intens.
[%]
100
327.0
+MS 2 (328)
80
60
Ag
106.8
40
20
0
346.7
126.9
242.9 271.0 299.1
158.8 188.9 214.8 364.7
50 100 150 200 250 300 350 400 450 500 m/z
Figure 3-45 APCI-MS 2 of a silver adducted complex at m/z 328 ion
3.4.6 Tandem MS of PCBs
Tandem MS experiments were performed for the PCBs that appeared in the
negative mode mass spectrum of the waste sample. Similarly, in advance, PCBs
from the Congener standard mix were fragmented. (M-Cl+O) – ions from the two
aforementioned sources were selected and isolated with an isolation width of 0.5
Da and each PCB was subjected to Collision Induced Dissociation (CID). All ions
of different PCBs from both samples suggested a loss of chlorine upon
fragmentation (see figure 3-46 and 3-47). It was noticed that the PCBs are less
liable to fragment. This is also reported for the fragmentation of PCBs. 111,112 In all
cases the MS 2 of the selected PCBs within the standard mix were found identical
to those native in waste sample. Similar to the high mass n-alkane species in some
waste samples, high mass chlorinated compounds demonstrated the production of
very weak or no fragments upon fragmentation. Figure 3-48 shows the MS 2 spectra
of the high mass chlorinated components. This can be attributed to the low
abundance of these components as well as their insufficiency to provide a detailed
fragmentation pattern.
77

Results and Discussion
Intens.
[%]
100
75
50
25
0
[%]
100
75
50
25
[%]
0
100
75
50
25
270.6
304.7
304.6
338.7
338.6
374.6
-MS 2 (306)
-MS 2 (340)
-MS 2 (374)
0
100 150 200 250 300 350 400 450 500 m/z
Figure 3-46 Fragmentation of selected PCBs at m/z 306, 340 and 374 from the
PCBs Congener Mix
Intens.
[%]
100
75
50
25
0
[%]
270.7
304.8
-MS 2 (306)
-MS 2 (340)
100
338.7
75
50
25
304.7
0
[%]
-MS 2 (374)
100
372.7
75
50
338.8
25
0
100 150 200 250 300 350 400 450 500 m/z
Figure 3-47 Fragmentation of selected PCBs at m/z 306, 340 and 374 from the
waste sample
78

Results and Discussion
Intens.
[%]
100
50
[%] 0
100
50
[%] 0
100
50
[%] 0
100
50
[%] 0
100
50
[%] 0
100
50
0
414.9
380.9
448.8
414.8
474.3
358.1
498.6
527.5
230.9
576.5
200 300 400 500 600 700 800 m/z
Figure 3-48 Fragmentation of high mass chlorinated components within the waste
extract
3.4.7 Oxidative Degradation of Complex Mixture of Shredder Waste
In an attempt to further achieve an insight about the structure composition of the
unsaturated hydrocarbons within the content of the light shredder waste, oxidation
of these hydrocarbon components within the waste sample was performed. This
method was introduced in the literature in order to explore the composition of the
UCM by changing the hydrocarbons to functionalized compounds described to be
easily resolved and identified. Gough and Rowland used this oxidative degradation
over UCM of hydrocarbons from lubricating oil feed stocks to characterize
them. 17 After reacting the light shredder waste extract with chromium trioxide in
acetic acid for six hours, the functionalised products were measured by mass
spectrometry. This time ESI was also employed because the products of oxidative
degradation were expected to be polar compounds such as carboxylic acids,
ketones and lactones. The products of oxidation from the waste sample were
79

Results and Discussion
injected into an APCI-MS as well as into the ESI-MS. Spectra of waste extract
before and after oxidation were recorded. Figures 3-49 and 3-50 show the positive
APCI mass spectra of the waste before and after oxidation respectively.
Intens.
[%]
100
411.4
+MS
80
60
329.3
561.6
40
663.5
20
0
250 300 350 400 450 500 550 600 650 m/z
Figure 3-49 Positive APCI mass spectrum of waste sample before oxidation
Intens.
[%]
100
295.2
391.3
+MS
80
337.3
419.3
60
353.3
40
20
447.4
481.4
509.5 565.5
591.6
647.6
663.5
681.5
0
250 300 350 400 450 500 550 600 650 m/z
Figure 3-50 Positive APCI mass spectrum of waste sample after oxidation
80

Results and Discussion
Instant inspection of the figures confirms oxidation yield is very high and this is
supported by the huge shift in the mass distribution in the positive APCI-MS
spectrum of the waste sample after oxidation. Also positive and negative ion mode
ESI-TOF-MS spectra were acquired for the oxidation products as shown in figures
3-51 and 3-52. This suggested that other nonreacted products can be differentiated
from those in APCI-MS because nonreacted species can only ionise upon APCI
source. Next, molecular assignment for oxidation product in both ESI and APCI
spectra was performed. The molecular formulas suggest carboxylic and ketone
groups are present. However, this oxidation process alone can not give that insight
about the source of these products. A model hydrocarbon complex mixture was
designed and prepared. The model mixture consisted of linear alkanes such as C20,
C21, C23, C26, C32, C36 and C40 as well as from few other standards 5-αcholestane,
squalane and squalene. These compounds were subjected to oxidation
with chromium trioxide using the same procedure performed for the complex
mixture of the waste extract. The products of this model complex mixture were
measured by ESI-TOF-MS in both positive and negative modes. Figure 3-53
shows the negative ESI MS spectrum of model mixture of hydrocarbons.
Comparing the latter spectrum to the negative ESI mass spectrum of oxidation
products of the waste sample mixture demonstrated a dramatic resemblance. It was
clearly observed that products of the model mixture are among the products of the
complex mixture of the waste sample. This suggested that the complex mixture
composition is composed or at least contains compounds similar to the ones within
the model mixture. This was emphasized from the oxidation of representative
hydrocarbons which supported these suggestions. Oxidative degradation does
provide some useful additional information about the complex mixture
composition. After direct and indirect exploring of the complex hydrocarbon
mixture within the light shredder waste fraction, a quantitative figure is discussed
in the following section.
81

Results and Discussion
Intens.
[%]
100
349.2
393.2
+MS
80
305.2
377.2
437.2
60
265.2
323.2
421.2
481.3
40
465.2
525.3
20
569.3
613.3
0
200 250 300 350 400 450 500 550 600 650 m/z
Figure 3-51 Positive ESI mass spectrum of complex waste mixture after oxidation
Intens.
[%]
100
215.6
-MS
80
60
171.5
40
20
0
150 200 250 300 350 400 450 500 550 m/z
Figure 3-52 Negative ESI mass spectrum of complex waste mixture after
oxidation
82

Results and Discussion
Intens.
[%]
100
80
60
143.1
171.1
201.1
215.1
229.1
243.1
257.1
-MS
40
20
129.1
313.1
411.1
115.0
483.4
0
100 150 200 250 300 350 400 450 500 m/z
Figure 3-53 Negative ESI mass spectrum of model mixture of hydrocarbon after
oxidation
83

Results and Discussion
3.4.8 Quantification
Through out the whole waste spectrum, it was noticed that nearly all of the n-
alkanes identified had low intensities compared to other compounds in the sample.
In an attempt to know whether the low n-alkane’s intensities found in waste
spectrum are attributed to ion-suppression or not, I spiked the waste matrix with
some high mass n-alkanes like C26, C32, C36 and C40 as shown in figure 3-54.
These compounds enhanced their corresponding (M-1) + ions that are originally
found within the waste sample without any significant ion suppression observed.
Intens.
[%]
100
C36
505.6
+MS
80
60
C26
399.4
C32
449.5
40
20
315.3
481.5
C40
561.6
663.5
0
200 250 300 350 400 450 500 550 600 650 m/z
Figure 3-54 APCI mass spectrum of spiked waste mixture with high mass n-
alkanes
This concludes that the n-alkanes in the waste are initially having low quantities
within the waste fraction. This would be indicative for the extent of biodegradation
of the waste as linear alkanes are the first to degrade among other hydrocarbons.
Another indirect experiment was performed to assess the possibility to quantify n-
alkanes within the applied APCI-TOF-MS methodology. Using an isotope dilution
experiment with a selected polydeuterated n-alkane C 32 D 66 (figure 3-55), a linear
response was found which allowed to show that in this complex mixture no ion
suppression effects were operating allowing adequate quantification of single n-
alkanes or groups of n-alkanes. For quantification, different concentrations of C7-
C40 standard mixture (0.2, 1, 4, 6, 10, 15, 20, 25, 35, 45 and 50 µg/ml) were
prepared by dilution and were injected afterwards to establish calibration curves.
84

Results and Discussion
Using model mixture C7-C40, calibration curves for all the analytes were
established. A linear response between concentration (ranging from 0.2 to 50
µg/ml) and the intensity recorded in the positive mass spectrum under APCI-MS
was observed. The linearity graphs for few analytes like C20, C29, C38 and C40
are shown in figures 3-56 to 3-59.
Intens.
[%]
100
80
60
40
20
0
343.3 369.3 395.4 413.4 482.9
499.9 519.9 537.9
+MS
350 400 450 500 550 600 m/z
Figure 3-55 APCI mass spectrum of deuterated dotriacontane C 32 D 66
14
12
10
Int.
8
x 10000
C20
6
4
y = 2995.5x + 11159
R² = 0.99
2
0
0 10 20 30 40 50
ppm
Figure 3-56 A plot between Concentration vs Intensity for C20
85

Results and Discussion
Int.
x 10000
25
20
15
C29
10
y = 4768.8x + 6714.8
R² = 0.9967
5
0
0 10 20 30 40 50
ppm
Figure 3-57 A plot between Concentration vs Intensity for C29
Int.
60
x 10000
50
C38
40
30
20
10
0
y = 11840x + 9931.1
R² = 0.9958
0 10 20 30 40 50
ppm
Figure 3-58 A plot between Concentration vs Intensity for C38
86

Results and Discussion
Int.
70
60
50
x 10000
C40
40
30
20
y = 14165x + 4479.9
R² = 0.9961
10
0
0 10 20 30 40 50
ppm
Figure 3-59 A plot between Concentration vs Intensity for C40
Using these linearity graphs, a quantitative figure of few n-alkanes was deduced.
Table 3.6 presents the quantities of C20, C23, C32, C36 and C40 present in a 1 ml
waste extract. Next a standard addition experiment was conducted for C36. The
addition of a known quantity of C36 into the native quantity of C36 within the the
same 1 ml of waste sample was monitored. The addition of 40 µl of a 1 mg/ml
prepared standard of C36, that individually provoked 3 µg/ml, to the same 1 ml
solution of the waste extract produced a total of 17 µg/ml. According to table 3.6,
the latter value was found cumulative for native and spiked quantities of C36. This
demonstrated success of not just quantitating a native amount of a single n-alkane
(C36) but as well reflecting a promising response that C36 exhibited when a little
quantity was added. This is an advantage for monitoring the quantities of certain n-
alkane analytes within the waste sample subjected to biological degradation or
other weathering conditions. Addition experiments were tested for C40 where
similar results were attained. However it is important to mention that the addition
method wasn’t applicable when low n-alkane’s quantities were spiked to the waste
matrix. This can be attributed to the limit of detection of these n-alkanes under
APCI-TOF-MS method. As well few n-alkanes were seen not to respond
efficiently with such addition experiments upon the applied methodology.
87

Results and Discussion
Table 3.6 Quantities of few selected n-alkanes in waste samples
APCI-TOF-MS
Alkane
Extract Spiked C36 Extract + C36
(µg/ml) (µg/ml) (µg/ml)
C20 34 – –
C23 45 – –
C32 28 – –
C36 14 3 17
C40 10 – –
3.5 Application of the Methodology to Other Complex Mixtures
3.5.1 Analysis of Solid Waste from Lebanon
With more than 4200 tons of solid waste produced daily out of household,
industrial and medical sources, Lebanon suffers from uncontrolled garbage
mountains randomly distributed all over its area. The accumulation of such
heterogeneous waste is considered one of the chronic environmental problems in
this country. Daily waste deposition contains 60% organic material, 15%, cartoon,
5% plastic and others. Unfortunately only 10% of the waste is recycled daily, the
rest is sent to readily over-load random dumps or landfills known as well as
“Garbage Mountains”. Unfortunately there is a continuous leakage of liquids rich
in heavy metals and toxic chemicals towards the sea. Even parts of the
accumulated waste fall directly to the sea as in famous ‘Saida Garbage Mountain’
(30 km from Capital). ‘Ras El-Ein Garbage Dump’ (80 km from Capital),
permanently closed recently, is still an unclear threaten for the groundwater source
just few meters away from the dump. On the other side accumulation of these
massive waste mixtures subjected to weathering conditions, periodic incineration
activities and bacterial degradation arouse an alarming pollution affecting the
health of the surrounding people and the environment. Unfortunately, to the best of
88

Results and Discussion
my knowledge, no analyses or other kinds of monitoring activities have
specifically utilized a precise analytical method to determine accurate data
concerning the composition of the existing solid waste in uncontrolled dumps.
Since these dumps are thought to be sources of hazardous complex mixtures and
are hitherto unknown which components are present in these mixtures, I suggested
to apply our current light shredder waste analytical methodology to such complex
mixture of mixed solid waste in Lebanon. Samples were brought from ‘Garbage
Mountain’ in the city of Saida. Two samples were taken from the garbage
mountain at different intervals of time in May 2011 and July 2011. The samples
were extracted, purified and measured in a similar fashion to the light shredder
waste in Bremen. Sample 1 appears as in figure 3-60 to have a relatively higher
mass distribution (m/z 200 to 800), but similar collection of signals compared to
light shredder waste. The negative MS spectrum of the first sample was as well
obtained.
The mass spectrum observed in figure 3-61 demonstrated the presence of few
polychlorinated biphenyls compounds. It included hexachlorobiphenyl at m/z
340.9, heptachlorobiphenyl at m/z 374.8 and octachlorobiphenyl at m/z 408.8 that
were identified by the (-) APCI method. This shows that even with the different
nature and source of the solid waste in Lebanon, the method can be beneficial in
identifying PCBs elsewhere. The low relative abundance of the PCBs is related to
the fact that the sample belongs to a heterogeneous and untreated waste dump.
This finding gives an indication that the remaining series of PCBs can be present.
Knowing that there is a wide range of toxic substances (e.g. tannery waste and
paints) that arrive at the waste site on a daily basis, this can be the source of toxic
PCBs pollutants.
Regarding the second sample, the positive mass spectrum shown in figure 3-62,
appears to have also an equal number of compounds as compared to light shredder
waste. However the negative mass spectrum of this sample doesn’t contain any
PCBs as far as shown in figure 3-63. The work done with waste samples from
Lebanon is considered a remarkable groundwork study towards a critical
89

Results and Discussion
assessment of the chemical content of the random solid waste dumps in Lebanon.
This should raise the interest for alleviating waste problems by enhanced
management supported by analytical research.
Intens.
[%]
100
307.2
397.4
369.3
+MS
80
60
257.2 285.3
453.4
481.5509.5537.5
663.5
40
20
729.8
771.8
0
200 300 400 500 600 700 800m/z
Figure 3-60 Positive APCI mass spectrum of Lebanese waste sample 1
Intens.
[%]
100
473.3
-MS
80
489.2
60
40
20
0
255.2
283.3
205.1
220.1
C 12 H 5 OCl 5
C12 H 4 OCl 6
314.1 340.8
408.3
374.8
423.3 456.3
200 250 300 350 400 450 500 m/z
529.4
Figure 3-61 Negative polarity APCI of Lebanese waste sample 1
90

Results and Discussion
Intens.
[%]
100
80
60
40
20
257.2 287.3
397.4
453.4 497.4 525.5
+MS
0
300 400 500 600 700 800 900 m/z
Figure 3-62 Positive APCI mass spectrum of Lebanese waste sample 2
Intens.
[%]
100
80
60
40
20
0
-MS
255.2
473.3
283.3
264.8
409.3
230.9
243.1 333.1
423.4
445.1
298.1 322.2
367.3 381.3 459.4
507.5
250 300 350 400 450 500m/z
Figure 3-63 Negative polarity APCI mass spectrum of Lebanese waste sample 2
3.5.2 Analysis of Car Motor Oil
Companies of car motor oil has been simultaneously competing and advertising for
the best blend that can perform as car motor oil enduring thermal and other drastic
conditions inside the engine. Composition of car oil engine is considered a heavily
guarded trade secret that varies greatly from conventional to synthetic oils. In
recent decades, synthetic motor oil has become a common option for cars. This is
because synthetic motor oil is slower to decompose chemically. The composition
of synthetic motor oil is also superior to that of traditional motor oil. Motor oils are
derived from petroleum-based and non-petroleum-synthesized chemical
compounds. Motor oils today are mainly blended by using base oils composed of
91

Results and Discussion
hydrocarbons, polyalphaolefins (PAO), and polyinternal olefins (PIO), thus
organic compounds consisting entirely of carbon and hydrogen. The bulk of
typical motor oil consists of hydrocarbons with between 18 and 34 carbon atoms
per molecule that is why we see peak shape spectrum.
Car oil technology is complex in many factors in terms of viscosity, additives
effect and corrosion inhibition. The oil in a motor oil product does not break down
or burn as it is used in an engine, it simply gets contaminated with particles and
chemicals that make it a less effective lubricant. Re-refining cleans the
contaminants and used additives out of the dirty oil. But what makes the car motor
oil slower to decompose chemically or less susceptible to evaporation over time is
indeed a question about the oil’s composition.
From this background, I considered the analysis of a selection of car motor oil
from different companies in Germany. The selection of oils is shown in table 3.7.
Some of these oils are for other specific uses such as transmission fluid. A dirty car
oil from an unknown car is present within the list. The samples were diluted in n-
heptane before direct infusion into the APCI. The mass distribution and
composition of each sample are well defined in their mass spectra. For example S1
comprises a dominant odd mass distribution with an exception of one compound
having an m/z 422 as shown in figure 3-64. In contrast the mass spectrum of S2,
presented in figure 3-65, is very simple comprising a series of n-alkanes up to
pentacosane (C50) at m/z 701. The molecular composition was identified using the
same calibrated APCI method that allows elemental assignment. While S3 looks
similar to S2 as revealed from figure 3-66, S4 reflects a very complex composition
over a high mass range m/z 400 to 1000 demonstrated in figure 3-67. This is
attributed to the presence of longer hydrocarbon isomers contributing to the
viscous nature of the oil. The bulk of S4 mass spectrum is concentrated at m/z
range 600-800 suggesting that the present hydrocarbons are in the range C40 to
C60. The elemental composition suggests that the components are series of high
mass unsaturated compounds. This oil thus has a different usability. The mass
spectra presented in figure 3-68 of transmission oil of Liqui Moly Company was
92

Results and Discussion
found to comprise an m/z 422 which was observed earlier in S1. This looks like the
secret even mass additive inserted to the regular components. Similar to S4, the
grease sample S7 in figure 3-69 covers a wide mass range (m/z 200 to m/z 700).
The contaminated through usage car motor oil (S9) appears to comprise additional
components not generally observed in other car motor oil samples within the
chosen list. The mass spectrum appears to have a depleted composition as shown
in figure 3-70.
Table 3.7 A selection of different car oils from different companies
Sample Trade Name Specification
S1 Calpam Mineral öl Motorenöl 10-40 W
S2 LIQUI MOLY GmbH 5 W - 30 HC Synthese
S3 Mitan Mineraöl GmbH SAE 15 W-40
S4 Castrol Epx 90 Viscous
S5 Pentosin For central Hydraluc system
S6 LIQUI MOLY GmbH Transmission fluid
S7 Grease CRC MoS2
S8 Ford 75-90 BO (Transmission Öl)
S9 Dirty Oil from unknown car Used
S10 Aral Motoröl (Old Auto) 15W-40
S11 Alpine TS 10W-40 (Semi synthetic)
93

Results and Discussion
Intens.
[%]
100
422.4
+MS
80
397.4
60
369.3
40
257.2
285.3
355.3
439.4
20
245.2
561.6
0
200 250 300 350 400 450 500 550 600 m/z
Figure 3-64 APCI mass spectrum of S1
Intens.
[%]
100
421.5
+MS
80
561.6
60
40
20
0
239.3 267.3 295.3 323.4
391.3
449.5
464.5
200 300 400 500 600 700m/z
599.6
701.7
Figure 3-65 APCI mass spectrum of S2
Intens.
[%]
100
397.4
+MS
80
425.4
60
439.4
40
242.9
355.3
20
257.2 301.3
0
200 250 300 350 400 450 500 550 600 m/z
Figure 3-66 APCI mass spectrum of S3
94

Results and Discussion
Intens.
[%]
100
+MS
80
647.6 687.6
743.7
759.7
60
40
20
993.9
0
500 600 700 800 900 1000 m/z
Figure 3-67 APCI mass spectrum of S4
Intens.
[%]
100
80
60
40
20
0
147.0
181.0
197.0 296.2
337.2
379.3
422.3
447.3
547.3 579.5
+MS
100 150 200 250 300 350 400 450 500 550 600m/z
Figure 3-68 APCI mass spectrum of S6
Intens.
[%]
100
80
60
40
213.2
255.2 283.2 411.4
+MS
20
0
200 300 400 500 600 700 m/z
Figure 3-69 APCI mass spectrum of S7
95

Results and Discussion
Intens.
[%]
100
379.3
422.3
511.4
+MS
80
60
40
147.0
207.1
296.2
20
0
663.4
200 300 400 500 600 m/z
Figure 3-70 APCI mass spectrum of S9 (contaminated through usage oil)
3.5.3 Analysis of Asphaltenes
The analysis of asphaltenes has been reviewed in many studies. Asphaltenes are
described as fractions that are insoluble in n-heptane. Such fractions comprise a
high degree of aromaticity and can contain nitrogen, oxygen and sulphur
atoms.The mass distribution of asphaltenes had been a controversial topic as
well. 89 The analysis of asphaltenes is considered a challenging field due to
complexity, high boiling points, solubility and tendency to aggregate. While my
contribution aims at examining the volatility and ionisation of complex
hydrocarbon mixtures, I investigated some bitumen samples by looking at their
mass distribution and ionisation behaviour. Due to limited resources, I only had to
look at asphalt samples that are already mixed with other solid particles. Samples
from two companies were diluted in different solvents and measured under the
same methodology. Bitumen 1 from Bay-systems and Bitumen 2 from Deuter
Lindenhagen were chosen for this investigation experiment. The solvents that were
used to extract hydrocarbons from these samples were dichloromethane (DCM), n-
heptane and toluene. Sample 1 was measured by ESI-MS and by APCI using DCM
as shown in figures 3-71 and 3-72. By visual scanning of each spectrum, it appears
that the composition vary widely between ESI and APCI. ESI comprised high
mass hydrocarbons that are not observed in the APCI spectrum. The APCI
96

Results and Discussion
spectrum appears to comprise less number of analytes than that of ESI.
Nevertheless the components of Bitumen 1 are successfully ionised without any
recorded fragmentation. Since such asphaltene fractions has been mainly
measured by ESI or other revolutionised methodologies, 89,100 the acquisition of
such data under APCI conditions proves the importance of the methodology to
attain a deeper understanding of asphaltenes. Regarding Bitumen 2, the sample
was dissolved in DCM and injected into the APCI source. The mass spectra of this
sample shown in figure 3-73 suggests a huge similarity to bitumen 1 however the
matching components differ with their relative abundances in both samples. This
would suggest that the two samples revert to two different sources of original
asphaltenes. In both samples there had been many analytes that appeared with low
abundance. Some of them were even hardly resolved with the TOF-MS. In my
opinion the interface of APCI to high resolution MS should be established to
effectively then analyse full compositions of complex mixtures.
Intens.
[%]
100
80
60
40
20
0
+MS
555.4
511.4
274.2
599.4 659.4
703.5
467.4
747.5
236.1
372.2 441.3
190.1
791.5
835.5 879.6
200 300 400 500 600 700 800 900 m/z
Figure 3-71 ESI mass spectrum of bitumen 1 using DCM as mobile phase
97

Results and Discussion
Intens.
[%]
100
297.2
+MS
80
403.3
60
40
241.2
319.1
347.2
467.1
541.4
20
663.4
0
200 300 400 500 600 700 800 900 m/z
741.2
Figure 3-72 APCI mass spectrum of bitumen 1 using DCM as mobile phase
Intens.
[%]
100
80
242.9
257.2
+MS
60
285.3
383.2
40
218.8
316.7
20
0
347.2 403.3 467.1
190.8
507.5 541.4 639.6663.5
200 250 300 350 400 450 500 550 600 650 m/z
Figure 3-73 APCI mass spectrum of bitumen 2 using DCM as mobile phase
3.6 Kendrick Plot and Interpretation of Complex Data from Various
Complex Mixtures
3.6.1 Light Shredder Waste
The externally calibrated masses of the waste sample were converted to Kendrick
masses and sorted into groups according to common Kendrick mass defect. The
compositional analysis is then displayed in the Kendrick plot represented in figure
3-74. This is of course inspired from the employment of such plots to display
chemical contents of complex mixtures in other sources measured by the group of
Marshall extensively discussed earlier. The chemically sorted display shows other
98

Results and Discussion
members of a homologous alkylation series. For example alkanes are sorted
horizontally to the value of KMD=1 separated by number of alkyl (CH 2 ) groups
whereas the other degraded compounds are appearing in a vertical arrangement
according to their degrees of unsaturation (number of double bonds). Around 800
elemental compositions in a single waste extract in positive ion mass spectrum
were rapidly distinguised in the plot. To the best of our knowledge this is the first
time Kendrick plot is employed to display a nonpolar hydrocarbon content of a
certain complex mixture. This 2D chemical sorting allowed tracing the
biodegradation of the n-alkanes. The reduction in the number and amount of n-
alkanes is greatly desired before the waste would be approved for final landfill.
KMD
1.0
0.8
0.6
100 200 300 400 500 600 700 800
NKM
Figure 3-74 Kendrick plot for the light shredder waste
It is emphasized from the above graph that 90% of the components are
hydrocarbons having a KMD around 1. The majority of the content appears as
explained earlier to be degraded compounds varying by their doubly bond
equivalents as their unsaturation degrees. The horizontal lines having different
KMD values suggest a dehydrogenation process taking place during microbial
processing. (M-1) + ions of n-alkanes are aligned horizontally at KMD = 0. (M-1) +
ions of n-alkanes aligned at KMD=0, a line which is not shown in the plot because
y-axis is enlarged for better screening of the set of data points. Molecular ions, M •+
99

Results and Discussion
of n-alkanes are aligned at KMD=0. Figure 3-75 shows a plot of measured mass
of hydrocarbon components against double bond equivalence (DBE; degree of
unsaturation). The graph clearly shows, similar to Kendrick plot, a pattern showing
parallel horizontal lines expressing different degrees of unsaturation within the
degraded hydrocarbons constituting the chemical content of the waste.
15
DBE
RDB
10
5
0
200 300 400 500 600 700
Measured m/z
Figure 3-75 Plot of DBE vs measured mass (m/z) for the hydrocarbon compone-
nts of waste
H/C
2.5
2
1.5
1
0.5
0
0 5 10 15 20
DBE
Figure 3-76 Plot of H/C ratio vs DBE of a light shredder waste sample
100

Results and Discussion
Another graphical compositional image is a typical plot of H/C ratio vs. DBE
(degree of unsaturation). Figure 3-76 shows such a plot for a measured light
shredder waste sample. The H/C ratio was calculated from the molecular formulas
of the waste components whereas the DBE values were obtained from the Data
analysis program of the Bruker software. From the graph it can be noticed that the
majority of compounds within the waste extract are those having a DBE range of
4-8. n-Alkanes, that are found in the chemical content of the waste sample, are
aligned at H/C value of 2 and DBE of 0.5. The latter value of DBE for n-alkanes
results from their ionisation as (M-1) + . The DBE values of all the analytes of the
waste are not adjusted against ionisation. The rule that lower H/C ratio corresponds
to higher DBE is demonstrated in this plot. Of course the graph reflects a
preferential dehydrogenation process arising from the high number of unsaturated
compounds.
Other effects like treatment of shredder waste on a small scale reactor and
weathering of deposited shredder waste were frequently tracked by Kendrick plots.
Our Project partners studied the effect of hydrothermal and aeration conditions
over the waste in a small scale reactor in terms of time. Table 3.8 shows examples
of treated samples on small scale under different conditions. Using the developed
methodology, the samples were extracted and analysed accordingly. For example
comparison of two different waste samples was performed by overlapping their
two Kendrick plots. Figure 3-77 shows the Kendrick plot for initial sample I2 and
I3 (Initial untreated samples) which were cropped at different times. I2 and I3 well
overlap in the m/z 200 to 500 but differ significantly in the range m/z 500 to 1000.
This shows that although these samples are similarly treated and their sources are
roughly the same, they still vary according to Kendrick plot. The Kendrick plot
here proves to be a magnificent chemical display to detect differences among
samples. After that each sample on separate was treated under certain conditions in
a small scale reactor. For example I1 (Initial sample cropped on 14.12.2010) was
treated in duplicate under defined conditions as shown in table 3.8. The treatment
was probed by subjecting the initial samples to different conditions such as air
101

Results and Discussion
flow (in I2) and varying operating time (in I3). Treated samples of I1 and I2 were
established to be as pilot tests for the validity of I3. In Figure 3-78, the differences
in Kendrick plots between I3 and its three treated samples, R1.3, R2.3 and R3.3,
with different operating times are tracked. By a critic look, sample R3.3 (14 days)
was found to show some evolution in composition compared to initial I3. Many I3
components are not present in the treated R3.3. The change within samples R2.2
(22 days) was similar to that of R3.3, however more compounds disappeared in the
high range (m/z 500-900). The largest difference of KMD values, however, is
between the set of data points of R1.3 (31 days) and I3. It can be concluded that
the increase of operating time in this case enhanced the degradation process of
shredder waste.
Table 3.8 Operating conditions of small scale treatment reactor of shredder waste
Sample
Date
Conditions
Temperature Air flow Input water
Operating
Time
1
I 1 12/14/2010
R 1.1 12/14/2010 60 °C 1,5 L/h 120 mL/d 22 days
R 2.1 12/14/2010 60 °C 1,5 L/h 120 mL/d 22 days
2
I 2 12/22/2010
R 1.2 12/22/2010 60 °C 1,5 L/h 120 mL/d 20 days
R 2.2 12/22/2010 60 °C 3,0 L/h 120 mL/d 20 days
R 3.2 12/22/2010 60 °C 3,0 L/h 120 mL/d 20 days
3
I 3 04/02/2011
R 1.3 3/16/2011 60 °C 3,0 L/h 120 mL/d 31 days
R 2.3 3/16/2011 60 °C 3,0 L/h 120 mL/d 22 days
R 3.3 3/16/2011 60 °C 3,0 L/h 120 mL/d 14 days
102

Results and Discussion
KMD
1.1
1
I2
0.9
I3
0.8
0.7
0.6
0 200 400 600 800 1000 1200
NKM
Figure 3-77 Kendrick plot overlap of untreated I2 and I3 waste samples
1.05
KMD
1
I3
0.95
R1.3
0.9
R2.3
0.85
R3.3
0.8
0.75
100 200 300 400 500 600 700 800 900 1000 1100
NKM
Figure 3-78 Kendrick plot overlap of I3 and treated sample on small scale
103

Results and Discussion
Other interesting comparison involved overlapping the Kendrick plots of waste
sample, which was preserved from 2009, with another freshly treated one from
2011. However to attain a confident figure of this comparison, some few
parameters of data analysis were considered according to table 3.9. After
establishing their Kendrick plot, the display quickly discriminates between the two
waste samples. Degradation seems more evincive with 2009 sample according to
figure 3-79. This is attributed to persistent compositional evolution as time elapses.
Hydrocarbons within sample 2009 are expected to be comprising higher
unsaturation degrees than those in 2011 sample. This is parallel to reduced values
of KMD of the hydrocarbons in sample 2009 compared to those of 2011 sample.
Table 3.9 Acquisition of data points considered in 2009 and 2011 samples
# Sample taken Total Signals S/N Filter Signals
Waste (2009) 3/11/2009 1065 50 820
Waste (2011) 4/2/2011 1200 30 800
1.1
KMD
1
W (2009)
0.9
0.8
W (2011)
0.7
0.6
0.5
0 100 200 300 400 500 600 700 800 900 1000
NKM
Figure 3-79 Kendrick plot overlap between 2009 and 2011 waste samples
104

Results and Discussion
Another graphical representation was performed for a set of 5 light shredder waste
samples. These initially identical samples were subjected to similar aeration and
hydrothermal conditions by our project partners upon their small scale reactor
mentioned earlier. Small quantities were cropped from each sample at different
days for analysis. The aim then was to investigate the effect of time against the
presence and abundance of the components within the waste. After the samples
were measured few important parameters were extracted like the number of
saturated and unsaturated and their sum of intensities as shown in table 3.10.
A radar plot in figure 3-80 was established for the parameters which were
extracted from the data analysis program of the Bruker software. From the data for
example it can be seen that the count of saturated compounds remains rather
similar (~34) over all varieties.
The plot showed that sample 2 (4 days) had the highest count of unsaturated and
consequently the highest sum of intensities of these compounds. Excluding sample
1, it was noticed that increasing operating time resulted in a drop of the intensities
of both saturated and unsaturated compounds in the waste samples. Moreover a
reduction of the count of unsaturated compounds was recorded. This reduction is
attributed to the operating time of treatment of those samples on a small scale
reactor. Such a plot provides a detailed information about the changeability of
samples.
Table 3.10 Extracted data from 5 measured light shredder waste samples
#
Operating Count Count
Time Saturated Unsaturated
∑ Int. Sat. (x10 3 ) ∑ Int. Unsat. (x10 4 )
1 2 Days 33 489 557 730
2 4 Days 34 731 1131 1860
3 10 Days 34 666 757 1045
4 14 Days 34 622 508 793
5 16 Days 36 592 512 759
105

Results and Discussion
Figure 3-80 Radar plot of four parameters related to five shredder waste samples
varying by operation time
3.6.1.1 Kendrick Plot for PCBs
Kendrick plot was also used to sort chemical composition that appears in the
negative APCI-TOF-MS. The PCBs were firstly displayed on a CH 2 -increment
Kendrick plot. Figure 3-81 shows the PCBs showing an inclined decreasing
fashion. This confirms that PCBs are not CH 2 homologues and thus the plot should
be modified. A rescale of Kendrick plot from CH 2 to Chlorine (Cl) as the new
increment is performed for the components in the negative mass spectrum of the
waste sample. Rescaling the data points to Cl occurs by multiplying the measured
mass by the ratio of nominal mass and accurate mass of Cl (35/34.9683). The
KMD is deduced by subtracting the calculated Kendrick mass (KM) of the
analytes from their nominal Kendrick mass (NKM). Thus the chlorine Kendrick
plot for the (-MS) spectrum for the chlorinated components is shown in figure 3-
82. Now the components are horizontally sorted because they are homologues of
Cl. The five identified PCBs are aligned at KMD = 1.18. This is consistent with
106

Results and Discussion
the data obtained from the Kendrick plot of the PCBs standard in figure 3-83. The
other classes of chlorinated compounds are as well observed in the Kendrick plot
at KMD = 1.3 and KMD = 2.1 which reflect the presence of high mass chlorinated
compounds within light shredder waste fraction. Similarly this Kendrick plot was
used to identify and track the chlorinated components among different samples.
KMD
1.0
Kendrick plot (CH 2 ) for (-MS) spectrum of waste sample
0.8
0.6
0.4
0.2
0.0
200 300 400 500 600 700 800 900
NKM
Figure 3-81 Kendrick plot of (CH 2 ) for waste mixture upon (-) APCI-MS
2.4
Kendrick plot (Cl) for (-MS) spectrum for waste sample
KMD
2.2
2.0
1.8
1.6
1.4
1.2
1.0
200 300 400 500 600 700 800 900
NKM
Figure 3-82 Kendrick plot of (Cl) for waste mixture upon (-) APCI-MS
107

Results and Discussion
KMD
2.4
2.2
2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
Kendrick plot (Cl) for (-MS) spectrum of PCBs Congener Mix
200 250 300 350 400 450 500
NKM
Figure 3-83 Kendrick plot of (Cl) for PCBs Congener Mix upon (-) APCI-MS
3.6.1.2 Kendrick Plot for Oxidation Products
Another employment of Kendrick plot was for screening the change in chemical
composition of the complex mixture of light shredder waste upon oxidation
process. The Kendrick plot of three samples was established from their respective
positive APCI mass spectra. The samples are described in figure 3-84 as I3, O2
and O3. I3 is the initial waste complex before oxidation. O2 represents the
oxidation products that were dissolved in MeOH before injection into the APCI-
MS. O3 is the sample containing also the same oxidation products but they were
dissolved and directly infused using n-heptane. Visual scanning of the graphs
reveals that the yield of oxidation is about 90%. This is due to the disappearance of
initial components of I3 sample in the Kendrick plots of oxidation products
injected in methanol or in n-heptane as in O2 and O3 respectively. The spread of
Kendrick plots of oxidation products of sample O2 was different from that
obtained by O3. This is because methanol retains polar oxidised products where as
n-heptane retains the nonpolar decomposed products in addition to initial
unreacted compounds.
108

Results and Discussion
1.2
KMD
1.1
I3 O2.Methanol O3.Heptane
1
0.9
0.8
0.7
0.6
0 100 200 300 400 500 600 700 800 900 1000
NKM
Figure 3-84 Kendrick plot overlap of I3, O2 and O3
3.6.2 Lebanon Waste
Kendrick plot has been employed as well for screening the chemical composition
of Lebanon waste. The graphs of the two analysed samples in figure 3-85 shows
that the two samples are very heterogeneous in nature. Their composition varies
markedly as demonstrated by their Kendrick plot overlap in figure 3-85 especially
in the high mass ranges. Leb S2 appears to have components with increased double
bond equivalents compared to Leb S1 waste sample. This significant difference in
chemical composition is certainly a proof to the heterogeneity of the waste source.
Nevertheless identification of harmful compounds allows estimating the impact of
such dumps over the environment. In all cases, this preliminary study forms a
promising step towards exploring the chemical composition necessary to solve
currently thousands of tons stored in the nasty dumps. In all cases, it is the scope of
the study that will recommend treatment strategies which eventually solve the
problem. Such a study can be a good reference for screening the waste residues or
treated waste (e.g. composted, biologically treated) before final landfilling.
109

Results and Discussion
KMD
1.1
1
Leb.S1
Leb.S2
0.9
0.8
0.7
0.6
100 300 500 700 900 1100
NKM
Figure 3-85 Kendrick plot overlap of Leb S1 and Leb S2 waste samples
3.6.3 Oil sample
Since the mass spectra of some car motor oil resembled that of light shredder
waste, an attempt to attain a better and detailed insight via overlapping their
Kendrick plots was performed. In fact the graphs in figure 3-86 show a close
similarity between the Calpam oil and the light shredder waste fraction. Although
they are not overlapping, however the compounds seem structurally similar.
1.1
KMD
1
Calpam Oil
Light shredder Waste
0.9
0.8
0.7
0.6
100 200 300 400 500 600 700 800
NKM
Figure 3-86 Kendrick plot overlap of Calpam oil and light shredder waste
110

Results and Discussion
As far as comparing dirty oil to unused one is concerned, Kendrick plot allowed
giving an insightful idea about what happens to the composition of oil engine upon
mileage. Figure 3-87 shows a Kendrick plot of general standard car oil from
Calpam Company overlapped to a contaminated-through-usage oil from an
unknown car. Assuming that this Calpam oil or a similar one has been used in a
new car and changed after a certain interval of time to give the contaminated one,
the plot shows a depletion of the oil structural composition. It seems that the
components have been degraded by observing the shift of KMD value of the
contaminated through usage oil components compared with those of Calpam oil.
As well decomposition of the oil is significant in plot. A large number of
decomposed compounds appear in low mass range of m/z 100-250. These
compounds are not found within the Calpam sample. To this end, this approach
can be employed to understand compositional evolution of car motor oils after they
are used. Understanding such changes in composition can guide car oil companies
in developing better car oil that can serve for prolonged period before service is
needed.
KMD
1.1
Calpam Motor Oil
Dirty Motor Oil
1
0.9
0.8
0.7
0.6
0.5
0.4
0 100 200 300 400 500 600 700 800
NKM
Figure 3-87 Kendrick plot overlap of Calpam motor oil and contaminated through
usage motor oil
111

Results and Discussion
3.6.4 Asphaltenes
The complex mixture within Asphaltenes was displayed by Kendrick plot. Figure
3-88 shows the compositional display of one sample of bitumen that was dissolved
in DCM under positive ESI conditions. This choice of DCM enabled to look at a
wide range of components because the plot demonstrates a wide KMD range.
KMD
1.2
Bitumen 1 (DCM-ESI)
1
0.8
0.6
0.4
0.2
0
0 200 400 600 800 1000
NKM
Figure 3-88 Kendrick plot of bitumen 1 upon ESI-MS using DCM solvent
KMD
1.4
Bitumen 1 (Heptane-APCI)
1.2
1
0.8
0.6
0.4
0.2
0
0 200 400 600 800
NKM
Figure 3-89 Kendrick plot of bitumen 1 upon APCI-MS using n-heptane solvent
112

Results and Discussion
In contrast the Kendrick plot of n-heptane sample under positive APCI-MS
conditions showed only few compounds from the bitumen sample. An example is
given by figure 3-89. This is not surprising because asphaltenes are fraction
defined to be insoluble in n-heptane. Next the two bitumen samples were plotted
together. Kendrick plot in figure 3-90 reflects the content of bitumen 1 and
bitumen 2 using DCM as a reagent under an applied positive APCI-MS method.
The two samples look very similar in terms of molecular composition.
KMD
1.2
Bitumen 1 Bitumen 2
1
0.8
0.6
0.4
0.2
0
100 200 300 400 500 600 700 800
NKM
Figure 3-90 Kendrick plot overlap of bitumen 1 and bitumen 2 using DCM in
APCI-MS
At last comparison of Kendrick plots, bitumen 1 under DCM/(+)APCI-MS
conditions and under DCM/(+)ESI-MS indicate the significant difference in
molecular composition. The same solvent was used however distinct Kendrick
plots were found under different ionisation techniques. The development of this
APCI methodology allowed including additional compounds that are not explored
by ESI technique. The necessity of molecular level details to complement the
developed methodology would then be paramount.
113

Conclusions
In conclusion we could show that using APCI-MS n-alkanes can be investigated not
only in model systems but as well in real life complex samples. Using [M-H] + ions of
n-alkanes in reference mixtures as external calibrant, close to 1000 molecular
formulas can be obtained from an APCI-MS spectrum in a light shredder waste
sample. The results demonstrated that a dehydrogenation process is releasing an
array of unsaturated olefins believed to make up the GC hump. The presence of few
harmful PCBs was explored using negative APCI-MS. This method could show a
typical chemical content for the light shredder waste complex mixture.
Further tandem MS experiments could confirm the identity of the compounds within
the waste sample. The n-alkanes showed a linear response in calibration curves
allowing the acquisition of a quantification figure of selected hydrocarbons in waste
sample. The method developed here is certainly not applicable for a routine analysis
of waste samples due to high instrument investment costs. However, the method
developed, allows a clear identification of hydrocarbons in complex waste samples
and a spot check screening of waste samples, very heterogeneous by nature, for the
presence of alkanes. Furthermore the techniques allow a critical re-evaluation of
legally binding analytical methods for the determination of hydrocarbons in
unresolved complex mixtures, by identification of the actual components of such
samples. The extent of biodegradation and weathering conditions over the complex
mixture of light shredder waste was monitored successfully by the employment of
Kendrick plot. This innovative methodology yielded important fundamental and
compositional information of the waste mixture.
Another intriguing aspect of this study is the success of the APCI methodology in
examining various hydrocarbon analytes previously considered as difficult to ionize.
The applicability of APCI-MS method was successfully extended for the
examination of various model non-polar hydrocarbons like high mass linear,
branched and cyclic hydrocarbons. This was demonstrated by the production of
intact abundant stable [M-H] + ion observed for each hydrocarbon within a large
114

selection. In all cases ionization was achieved without the use of any additional
additives and without significant fragmentations. In all cases tandem MS spectra
could be acquired from the intact precursor ions. The methodology demonstrated the
power of APCI-MS to analyse components of other kinds of complex hydrocarbon
mixtures that usually fall out of the ability of other techniques, such as car motor oil
and asphaltenes.
Hence such APCI method provides an excellent groundwork for the analysis of nonvolatile
hydrocarbons in complex mixtures containing similar compounds. Therefore
the application of this method should lead for better understanding of the chemical
composition of such mixtures.
115

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125

Appendix
Light shredder waste
Meas. m/z Mol.Formula m/z
error
[ppm]
189.163 C 14 H 21 189.1638 4.2
191.1789 C 14 H 23 191.1794 2.6
193.1941 C 14 H 25 193.1947 3.1
195.2105 C 14 H 27 195.2107 1
197.2259 C 14 H 29 197.2264 2.5
199.1477 C 15 H 19 199.1481 2
201.164 C 15 H 21 201.1638 -1
203.1796 C 15 H 23 203.1794 -1
205.1954 C 15 H 25 205.1951 -1.5
207.211 C 15 H 27 207.2107 -1.5
209.2266 C 15 H 29 209.2264 -1
211.2422 C 15 H 31 211.242 -1
213.1647 C 16 H 21 213.1638 -4.2
215.1804 C 16 H 23 215.1794 -4.6
217.1956 C 16 H 25 217.1951 -2.3
219.2109 C 16 H 27 219.2107 -0.9
221.2274 C 16 H 29 221.2264 -4.5
223.2427 C 16 H 31 223.242 -3
225.2586 C 16 H 33 225.2577 -4
231.212 C 17 H 27 231.211 -4.3
233.2273 C 17 H 29 233.2264 -3.8
235.2429 C 17 H 31 235.242 -3.8
237.258 C 17 H 33 237.2577 -1.3
239.274 C 17 H 35 239.2733 -3
241.1965 C 18 H 25 241.1958 -2.9
245.2276 C 18 H 29 245.2264 -4.9
247.2432 C 18 H 31 247.242 -4.8
249.2591 C 18 H 33 249.2583 -3.2
251.274 C 18 H 35 251.2733 -2.8
253.2904 C 18 H 37 253.291 2.4
261.2592 C 19 H 33 261.2599 2.6
263.2747 C 19 H 35 263.2752 1.8
265.2884 C 19 H 37 265.289 2.3
267.3051 C 19 H 39 267.3046 -1.9
279.3057 C 20 H 39 279.3046 -4
281.3214 C 20 H 41 281.3203 -3.9
126

289.2906 C 21 H 37 289.291 1.4
291.306 C 21 H 39 291.312 2
293.3212 C 21 H 41 293.3222 3.4
295.3374 C 21 H 43 295.3384 3.4
303.3062 C 22 H 39 303.3076 4.6
305.3215 C 22 H 41 305.3203 -4
307.3367 C 22 H 43 307.3359 -2.6
309.3522 C 22 H 45 309.3516 -2
317.3219 C 23 H 41 317.3228 2.8
319.3375 C 23 H 43 319.3381 -4.8
321.3515 C 23 H 45 321.3516 0.3
323.3685 C 23 H 47 323.3672 -4
327.3065 C 24 H 39 327.3071 1.8
331.3377 C 24 H 43 331.3387 3
333.3529 C 24 H 45 333.3516 -3.9
337.3836 C 24 H 49 337.3829 -2
343.3378 C 24 H 43 343.3389 3.2
345.3532 C 24 H 45 345.3516 -4.7
347.3684 C 24 H 47 347.3672 -3.4
351.3986 C 25 H 51 351.3985 -0.2
357.3535 C 26 H 45 357.3549 3.9
359.3686 C 26 H 47 359.3672 -3.8
361.3841 C 26 H 49 361.3829 -3.4
365.4155 C 26 H 53 365.4142 -3.6
371.3694 C 27 H 47 371.3704 2.7
373.384 C 27 H 49 373.3829 -2.9
379.4303 C 27 H 55 379.4298 -1.3
383.3692 C 28 H 47 383.3705 3.4
385.3851 C 28 H 49 385.387 5
387.3994 C 28 H 51 387.3985 -2.4
389.4144 C 28 H 53 389.4142 -0.6
391.3359 C 29 H 43 391.3356 -0.7
393.445 C 28 H 57 393.4455 1.2
395.3694 C 29 H 47 395.368 -3.5
399.4009 C 29 H 51 399.3999 -2.5
401.4146 C 29 H 53 401.4142 -1
407.4588 C 29 H 59 407.4599 2.7
409.3848 C 30 H 49 409.3829 -4.6
411.4002 C 30 H 51 411.3985 -4
413.4155 C 30 H 53 413.4142 -3.2
415.4304 C 30 H 55 415.4298 -1.5
417.445 C 30 H 57 417.4455 1.1
127

419.4592 C 30 H 59 419.4611 4.6
421.4766 C 30 H 61 421.4768 0.3
423.4002 C 31 H 51 423.3985 -3.9
425.4158 C 31 H 53 425.4142 -3.8
427.4309 C 31 H 55 427.4298 -2.6
429.4455 C 31 H 57 429.4455 -0.1
437.4161 C 32 H 53 437.4142 -4.3
439.4313 C 32 H 55 439.4298 -3.3
441.446 C 32 H 57 441.4455 -1.2
443.461 C 32 H 59 443.4611 0.4
449.5096 C 32 H 65 449.5081 -3.4
451.4318 C 33 H 55 451.4298 -4.3
453.4464 C 33 H 57 453.4455 -2.1
455.4614 C 33 H 59 455.4611 -0.7
457.4766 C 33 H 61 457.4768 0.3
463.432 C 34 H 55 463.4298 -4.7
465.4466 C 34 H 57 465.4455 -2.4
467.4617 C 34 H 59 467.4611 -1.2
469.4766 C 34 H 61 469.4768 0.3
471.4913 C 34 H 63 471.4924 2.4
477.4479 C 35 H 57 477.4455 -5
479.4621 C 35 H 59 479.4611 -1.9
481.4772 C 35 H 61 481.4768 -0.9
483.492 C 35 H 63 483.4924 0.9
485.5068 C 35 H 65 485.5081 2.7
491.463 C 36 H 59 491.4611 -3.8
493.477 C 36 H 61 493.4768 -0.5
495.492 C 36 H 63 495.4924 0.8
497.5075 C 36 H 65 497.5081 1.2
499.5218 C 36 H 67 499.5237 3.9
505.5718 C 36 H 73 505.5707 -2.2
507.495 C 37 H 63 507.4924 -5.3
509.5068 C 37 H 65 509.5081 2
511.5224 C 37 H 67 511.5237 2.5
521.5068 C 38 H 65 521.5081 2.4
523.5231 C 38 H 67 523.5237 1.1
525.5378 C 38 H 69 525.5394 3
535.5223 C 39 H 67 535.5237 2.6
537.5381 C 39 H 69 537.5394 2.3
539.5524 C 39 H 71 539.555 4.8
541.4785 C 40 H 61 541.4768 -3.2
543.4901 C 40 H 63 543.4924 4.3
128

545.5053 C 40 H 65 545.5081 5.1
547.5221 C 40 H 67 547.5237 2.9
549.5376 C 40 H 69 549.5394 3.2
551.5529 C 40 H 71 551.555 3.8
553.4754 C 41 H 61 553.4768 2.5
553.5721 C 40 H 73 553.5707 -2.5
555.4922 C 41 H 63 555.4924 0.4
557.5054 C 41 H 65 557.5081 4.8
559.5218 C 41 H 67 559.5237 3.4
561.5376 C 41 H 69 561.5394 3.2
563.553 C 41 H 71 563.555 3.5
565.5717 C 41 H 73 565.5707 -1.7
569.5075 C 42 H 65 569.5081 1
571.5247 C 42 H 67 571.5237 -1.7
573.5371 C 42 H 69 573.5394 4
575.5543 C 42 H 71 575.555 1.2
577.5695 C 42 H 73 577.5707 2
581.511 C 43 H 65 581.5081 -5
583.5244 C 43 H 67 583.5237 -1.2
585.5361 C 43 H 69 585.5394 5.6
587.5523 C 43 H 71 587.555 4.6
589.5701 C 43 H 73 589.5707 1
591.5995 C 43 H 75 591.5863 -2.2
597.5399 C 44 H 69 597.5394 -0.8
599.553 C 44 H 71 599.555 3.3
601.5699 C 44 H 73 601.5707 1.3
603.5848 C 44 H 75 603.5863 2.4
611.5556 C 45 H 71 611.555 -1
613.5693 C 45 H 73 613.5707 2.2
615.5842 C 45 H 75 615.5863 3.4
625.5717 C 46 H 73 625.5707 -1.6
627.5858 C 46 H 75 627.5863 0.8
629.594 C 46 H 77 629.602 1.2
639.585 C 47 H 75 639.5863 2.1
641.599 C 47 H 77 641.602 4.6
647.4623 C 49 H 59 647.4611 -1.8
653.622 C 48 H 77 653.602 -3
655.6155 C 48 H 79 655.6176 3.2
129

Liqui Moly car motor oil
Meas. m/z Mol.Formula m/z error [ppm]
183.2109 C 13 H 27 183.2107 -1
197.2269 C 14 H 29 197.2264 -2.5
211.2416 C 15 H 31 211.242 1.9
225.257 C 16 H 33 225.2577 3.1
253.2886 C 18 H 37 253.289 1.5
267.3036 C 19 H 39 267.3046 3.7
281.3199 C 20 H 41 281.3203 1.4
295.3355 C 21 H 43 295.3359 1.3
309.3511 C 22 H 45 309.3516 1.6
323.3666 C 23 H 47 323.3672 1.8
337.3812 C 24 H 49 337.3829 5
351.3971 C 25 H 51 351.3985 4
365.4126 C 26 H 53 365.4142 4.4
379.4283 C 27 H 55 379.4298 4
393.4438 C 28 H 57 393.4455 4.3
407.46 C 29 H 59 407.4611 2.7
421.4765 C 30 H 61 421.4768 0.7
449.5067 C 32 H 62 449.5081 3.1
561.6322 C 40 H 81 561.6333 2
701.791 C 50 H 101 701.7898 -1.7
739.8029 C 53 H 103 739.8054 3.3
841.9416 C 60 H 121 841.9463 5.5
Contaminated-by-usage car motor oil
Meas. m/z Mol. Formula m/z err [ppm]
175.1484 C 13 H 19 175.1481 -1.5
177.1645 C 13 H 21 177.1638 -4.3
179.18 C 13 H 23 179.1794 -3.3
181.1944 C 13 H 25 181.1951 3.9
183.2108 C 13 H 27 183.2107 -0.5
185.1318 C 14 H 17 185.1325 3.8
187.1476 C 14 H 19 187.1481 3.1
189.1629 C 14 H 21 189.1638 4.8
191.1786 C 14 H 23 191.1794 4.2
130

193.1951 C 14 H 25 193.1951 0
195.2101 C 14 H 27 195.2107 3
197.1318 C 15 H 17 197.1325 3.5
197.2256 C 14 H 29 197.2264 4
199.1478 C 15 H 19 199.1481 1.8
201.1645 C 15 H 21 201.1638 -3.4
207.1166 C 16 H 15 207.1168 0.9
207.2097 C 15 H 27 207.2107 4.8
213.1642 C 16 H 21 213.1638 -1.9
215.1784 C 16 H 23 215.1794 4.6
217.1939 C 16 H 25 217.1951 5
221.2253 C 16 H 29 221.2264 5
225.2567 C 16 H 33 225.2577 4.4
227.1782 C 17 H 23 227.1794 5
229.1949 C 17 H 25 229.1951 0.8
231.2117 C 17 H 27 231.2107 -4.3
241.1962 C 18 H 25 241.1951 -4.7
245.2254 C 18 H 29 245.2264 4
247.2412 C 18 H 31 247.242 3.2
255.2121 C 19 H 27 255.2107 -5.4
259.2428 C 19 H 31 259.242 -3
269.2257 C 20 H 29 269.2264 2.6
271.241 C 20 H 31 271.242 3.6
273.2564 C 20 H 33 273.2577 4.7
283.2418 C 21 H 31 283.242 0.8
293.2253 C 22 H 29 293.2264 3.8
295.2415 C 22 H 31 295.242 1.6
297.2585 C 22 H 33 297.2577 -2.9
299.2719 C 22 H 35 299.2733 4.7
301.2894 C 22 H 37 301.289 -1.3
307.2407 C 23 H 31 307.242 4.2
309.2561 C 23 H 33 309.2577 5
311.2721 C 23 H 35 311.2733 3.8
321.2576 C 24 H 33 321.2577 0.2
323.2719 C 24 H 35 323.2733 4.3
325.2889 C 24 H 37 325.289 0.3
327.3041 C 24 H 39 327.3046 1.5
335.2715 C 25 H 35 335.2733 5.5
337.2899 C 25 H 37 337.289 -2.7
339.3033 C 25 H 39 339.3046 3.8
341.3199 C 25 H 41 341.3203 1.2
343.3347 C 25 H 43 343.3359 3.4
131

345.3511 C 25 H 45 345.3516 1.5
349.2884 C 26 H 37 349.289 1.7
351.3034 C 26 H 39 351.3046 3.4
353.3199 C 26 H 41 353.3203 1.2
355.3341 C 26 H 43 355.3359 5
357.3504 C 26 H 45 357.3516 3.4
359.3669 C 26 H 47 359.3672 0.8
363.3033 C 26 H 49 363.3046 3.5
365.3184 C 27 H 41 365.3203 5.1
367.3344 C 27 H 43 367.3359 4
369.3502 C 27 H 45 369.3516 3.8
371.3659 C 27 H 47 371.3672 3.5
377.3202 C 28 H 41 377.3203 0.2
379.3348 C 28 H 43 379.3359 2.9
381.3529 C 28 H 45 381.3516 -3.4
385.3809 C 28 H 49 385.3829 5
391.3345 C 29 H 43 391.3359 3.6
393.3504 C 29 H 45 393.3516 2.9
395.3665 C 29 H 47 395.3672 1.8
397.3809 C 29 H 49 397.3829 5
399.3975 C 29 H 51 399.3985 2.5
405.3514 C 30 H 45 405.3516 0.4
407.3664 C 30 H 47 407.3672 2
409.3807 C 30 H 49 409.3829 5.3
411.3977 C 30 H 51 411.3985 1.9
419.3669 C 31 H 47 419.3672 0.8
421.383 C 31 H 49 421.3829 -0.3
423.3973 C 31 H 51 423.3985 2.8
433.383 C 32 H 49 433.3829 -0.2
435.4004 C 32 H 51 435.3985 -4.2
437.4136 C 32 H 53 437.4142 1.2
439.4282 C 32 H 55 439.4298 3.6
447.3989 C 33 H 51 447.3985 -0.7
449.4134 C 33 H 53 449.4142 1.7
451.4299 C 33 H 55 451.4298 -0.2
463.4311 C 34 H 55 463.4298 -2.7
465.4443 C 34 H 57 465.4455 2.6
475.4313 C 35 H 55 475.4298 -3
477.4475 C 35 H 57 477.4455 -4.2
479.4599 C 35 H 59 479.4611 2.5
489.4467 C 36 H 57 489.4455 -2.4
491.4614 C 36 H 59 491.4611 -0.6
132

493.4754 C 36 H 61 493.4768 2.8
507.4903 C 37 H 63 507.4924 4.1
519.4937 C 38 H 63 519.4924 -2.5
521.5073 C 38 H 65 521.5081 1.5
531.4935 C 39 H 63 531.4924 -2
547.5221 C 40 H 67 547.5237 2.9
133