Development of a Novel Mass Spectrometric ... - Jacobs University
Development of a Novel Mass Spectrometric ... - Jacobs University
Development of a Novel Mass Spectrometric ... - Jacobs University
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<strong>Development</strong> <strong>of</strong> a <strong>Novel</strong> <strong>Mass</strong> <strong>Spectrometric</strong> Methodology for<br />
the Analysis <strong>of</strong> Hydrocarbon Content in Light Shredder Waste<br />
by<br />
Nadim Hourani<br />
A thesis submitted in partial fullfilment<br />
<strong>of</strong> the requirements for the degree <strong>of</strong><br />
Doctor <strong>of</strong> Philosophy<br />
in Chemistry<br />
Approved, Thesis Committee<br />
Pr<strong>of</strong>. Dr. Nikolai Kuhnert<br />
<strong>Jacobs</strong> <strong>University</strong> Bremen<br />
Pr<strong>of</strong>. Dr.-Ing. Dieter Lompe<br />
Hochschule Bremerhaven<br />
Dr. Helge Weingart<br />
<strong>Jacobs</strong> <strong>University</strong> Bremen<br />
x<br />
x<br />
x<br />
Date <strong>of</strong> Defence: 02.04.2012<br />
x<br />
School <strong>of</strong> Engineering and Science
“That what doesn't kill me makes me stronger”<br />
Friedrich Nietzsche (German philosopher)
Declaration <strong>of</strong> Authorship<br />
I ,Nadim Hourani, hereby declare that this thesis and the work presented in it is<br />
entirely my own. Where I have consulted the work <strong>of</strong> others, this is always clearly<br />
stated.<br />
Signed: Nadim Hourani<br />
Date: 10.April. 2012
Acknowledgements<br />
First and farmost, thanks are to ‘God’ for my life through all tests in the past years.<br />
You have made my life more bountiful. May your name be exalted, honoured, and<br />
glorified.<br />
My sincere gratitude goes to Pr<strong>of</strong>. Dr. Nikolai Kuhnert for his continuous supervision,<br />
advice, support and inspiration as well as for his confidence he gifted to work in<br />
generous freedom. Thanks for being able to work with modern analytical techniques<br />
and to attend interesting international conferences. I’m so glad to have come to know<br />
him. I’d like to deeply thank the Fond für Angewandte Umweltforschung des Landes<br />
Bremen and the Bremer Entsorgungsbetriebe (BEB Company) for the support given to<br />
this project.<br />
I would like to thank my dear wife Adal for support and love through out the study<br />
years, my parents Mahmoud and Salwa Hourani, my brothers Wassim, Ibrahim and<br />
Hamzi, and my sisters Fatemah and Kawkab, all my dear friends and in particular<br />
Hany Nour. My sincere love and gratitude goes for Dr. Ursula Zimoch whose splendid<br />
care and support were more than intriguing for me during my study. Needless to say<br />
how much gratitude I owe to Pr<strong>of</strong>. Dr. Angela Danil De Namor for continued support<br />
and advice. Without her contribution this Ph.D study wouldn’t have been achieved.<br />
I am tempted to individually thank all my colleagues in our laboratory in as much as<br />
thanks to Mrs Anja Müller, for the technical support.
This work has been carried out under the supervision <strong>of</strong> Pr<strong>of</strong>. Dr. Nikolai Kuhnert in<br />
the analytical and organic laboratory <strong>of</strong> Chemistry Department at <strong>Jacobs</strong> <strong>University</strong><br />
Bremen in Germany.<br />
Abstract<br />
The lack <strong>of</strong> a routine characterization method for non-volatile hydrocarbons has been<br />
an ongoing problem preventing mass spectrometry from the analysis <strong>of</strong> these<br />
hydrocarbons within many sources. Non-polar hydrocarbons are still difficult to be<br />
detected by mass spectrometry. Although several studies targeted this problem, lack <strong>of</strong><br />
self-ionization has been limiting the ability <strong>of</strong> mass spectrometry to examine these<br />
hydrocarbons.<br />
A novel identification method for saturated straight-chain hydrocarbons in light<br />
shredder waste fraction under atmospheric pressure chemical ionization mass<br />
spectrometry (APCI-MS) has been developed. Ionization <strong>of</strong> alkanes under nitrogen gas<br />
source favoured hydrogen abstraction producing majorly (M-H) + ions which are<br />
strictly corresponding to their respective series <strong>of</strong> n-alkanes between n-decane (C10)<br />
and n-tetracontane (C40). The method is shown to produce intact gas phase ions <strong>of</strong> n-<br />
alkane in both reference and real life waste samples. APCI-MS 2 fragmentation data<br />
assisted in the structural verification <strong>of</strong> the n-alkanes investigated in both standard and<br />
waste mixtures. Additionally the total chemical composition <strong>of</strong> the light shredder<br />
waste fraction was translated by the same method. The mass spectrum displayed a<br />
bimodal distribution <strong>of</strong> odd and even mass ions with a molecular weight distribution<br />
range <strong>of</strong> m/z 200-900 Da. Molecular formulas for a 1000 unsaturated hydrocarbon<br />
compounds suggested a dehydrogenation process. The molecular masses were plotted<br />
on a Kendrick plot which was successfully employed for monitoring sample<br />
degradation.<br />
Another selection <strong>of</strong> high mass linear, branched and cyclic hydrocarbons, reported to<br />
be notoriously difficult to ionize, were examined during this study. Using optimized<br />
APCI conditions all <strong>of</strong> these analytes could be ionized without the use <strong>of</strong> an additional
ionization aid and without fragmentation. This finding represents a promising step<br />
towards extending the applicability <strong>of</strong> mass spectrometry to complex non-polar<br />
hydrocarbon analyses.
Contents<br />
Contents<br />
Declaration <strong>of</strong> Authorship................................................................................................ iii 4<br />
Achnowledgement………………………………………………………………………………iv<br />
Abstract………………………………………………………………………………..…..v<br />
Contents ........................................................................................................................ vii<br />
List <strong>of</strong> Figures ................................................................................................................ ix<br />
List <strong>of</strong> Tables................................................................................................................ xiii<br />
Publications, Manuscripts ............................................................................................. xiv<br />
Abbreviations ................................................................................................................ xv<br />
1 Introduction .................................................................................................................. 1<br />
1.1 Complex Mixtures .......................................................................................................... 1<br />
1.2 Presence and Fate <strong>of</strong> Hydrocarbons in Contaminated Sites .............................................. 4<br />
1.3 Use <strong>of</strong> <strong>Mass</strong> Spectrometry for Hydrocarbon Analyses..................................................... 8<br />
1.3.1 EI and CI.................................................................................................................11<br />
1.3.2 ESI, DESI and MALDI ...........................................................................................11<br />
1.3.3 FD and FI ................................................................................................................12<br />
1.3.4 APPI .......................................................................................................................13<br />
1.3.5 APLI .......................................................................................................................14<br />
1.3.6 APCI, LIAD/CI and LIAD/APCI ............................................................................14<br />
1.3.7 Summary.................................................................................................................17<br />
1.3.8 Ionisation via APCI .................................................................................................20<br />
1.3.9 Petroleomics ...........................................................................................................22<br />
1.3.10 Kendrick plot ..........................................................................................................24<br />
1.4 Light Shredder Waste in Bremen (Project Objectives)....................................................26<br />
1.5 Scope and Significance <strong>of</strong> this Work..............................................................................30<br />
2 Experimental .............................................................................................................. 31<br />
2.1 Chemicals and Model Standards ....................................................................................31<br />
2.2 Preparation <strong>of</strong> Samples ..................................................................................................32<br />
2.2.1 Alkane Standards and Shredder Waste Samples Preparation ....................................32
Contents<br />
2.2.2 Preparation <strong>of</strong> Oxidation Products from Shredder Extract ........................................34<br />
2.3 MS Operating Conditions ..............................................................................................34<br />
2.4 Graphical Presentation <strong>of</strong> the Used Instruments .............................................................36<br />
3 Results and Discussion ............................................................................................... 37<br />
3.1 APCI-TOF-MS <strong>of</strong> Standard n-Alkanes ..........................................................................37<br />
3.2 APCI-TOF-MS <strong>of</strong> a Variety <strong>of</strong> Hydrocarbons ................................................................44<br />
3.3 Pathway <strong>of</strong> Ionisation <strong>of</strong> Hydrocarbon Standards under APCI Conditions ......................49<br />
3.4 Light shredder Waste Analysis ......................................................................................53<br />
3.4.1 (+)APCI-TOF-MS <strong>of</strong> Waste Sample ........................................................................53<br />
3.4.2 Calibration ..............................................................................................................57<br />
3.4.3 Identification <strong>of</strong> Polychlorinated Biphenyls (PCBs) in (-) APCI-TOF-MS ...............63<br />
3.4.4 Tandem MS Measurements .....................................................................................65<br />
3.4.5 Tandem MS <strong>of</strong> Derivatised Compounds ..................................................................76<br />
3.4.6 Tandem MS <strong>of</strong> PCBs ...............................................................................................77<br />
3.4.7 Oxidative Degradation <strong>of</strong> Complex Mixture <strong>of</strong> Shredder Waste ...............................79<br />
3.4.8 Quantification .........................................................................................................84<br />
3.5 Application <strong>of</strong> the Methodology to Other Complex Mixtures .........................................88<br />
3.5.1 Analysis <strong>of</strong> Solid Waste from Lebanon ....................................................................88<br />
3.5.2 Analysis <strong>of</strong> Car Motor Oil .......................................................................................91<br />
3.5.3 Analysis <strong>of</strong> Asphaltenes ..........................................................................................96<br />
3.6 Kendrick Plot and Interpretation <strong>of</strong> Complex Data from Various Complex Mixtures ......98<br />
3.6.1 Light Shredder Waste ..............................................................................................98<br />
3.6.1.1 Kendrick Plot for PCBs ................................................................................... 106<br />
3.6.1.2 Kendrick Plot for Oxidation Products .............................................................. 108<br />
3.6.2 Lebanon Waste...................................................................................................... 109<br />
3.6.3 Oil sample ............................................................................................................. 110<br />
3.6.4 Asphaltenes ........................................................................................................... 112<br />
Conclusions ................................................................................................................. 114<br />
References ................................................................................................................... 116
List <strong>of</strong> Figures<br />
List <strong>of</strong> Figures<br />
Figure 1-1 Examples <strong>of</strong> aliphatic and aromatic hydrocarbons in crude oils.................................. 8<br />
Figure 1-2 Range <strong>of</strong> ionisation techniques employed with different types <strong>of</strong> compounds ...........10<br />
Figure 1-3 Matrix-assisted laser desorption/ionization (MALDI) ...............................................12<br />
Figure 1-4 Complex data management ......................................................................................19<br />
Figure 1-5 Schematic description <strong>of</strong> the atmospheric pressure chemical ionisation (APCI)<br />
interface and the mechanism <strong>of</strong> ion formation in the corona discharge region .....................21<br />
Figure 1-6 Kendrick mass defect vs nominal Kendrick mass for odd mass ions in crude oil<br />
sample. Note the visual vertical separation <strong>of</strong> compound classes (O, O 2 , O 3 S) and types (e.g.,<br />
compounds with different number <strong>of</strong> rings plus double bonds) based on mass defect and the<br />
simultaneous visual horizontal distribution <strong>of</strong> number <strong>of</strong> CH 2 groups for a given compound<br />
class and type. 105 ................................................................................................................26<br />
Figure 1-7 Shredding Plant ........................................................................................................27<br />
Figure 1-8 Light shredder waste fraction set for biological treatment in a prepared unit. ............28<br />
Figure 1-9 UCM feature <strong>of</strong> hydrocarbon content <strong>of</strong> light shredder waste in GC .........................29<br />
Figure 2-1 Instruments used in the study ..................................................................................36<br />
Figure 3-1 APCI mass spectrum in positive ion mode <strong>of</strong> dodecane (C 12 H 26 ) showing (M-3) + H 2 O<br />
ion as product ion at m/z 185.2 ...........................................................................................38<br />
Figure 3-2 APCI mass spectrum in positive ion mode <strong>of</strong> tridecane (C 13 H 28 ) showing (M-3) + H 2 O<br />
ion as product ion at m/z 199.2 ...........................................................................................38<br />
Figure 3-3 APCI mass spectrum in positive ion mode <strong>of</strong> a mixture containing decanes (C 10 H 22 ),<br />
dodecane (C 12 H 26 ), tridecane (C 13 H 28 ), tetradecane (C 14 H 30 ), pentadecane (C 15 H 32 ) and<br />
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<br />
241.3 respectively...............................................................................................................39<br />
Figure 3-4 APCI mass spectrum in positive ion mode <strong>of</strong> hexatricontane (C 36 H 74 ) showing an (M-<br />
1) + and (M-3) + H 2 O at m/z 505.6 and 521.6 respectively ......................................................39<br />
Figure 3-5 APCI mass spectrum in positive ion mode <strong>of</strong> dotriacontane (C 32 H 64 ), hexatricontane<br />
(C 36 H 74 ) and tetracontane (C 40 H 82 ).....................................................................................40<br />
Figure 3-6 APCI mass spectrum <strong>of</strong> model mixture <strong>of</strong> n-alkanes injected using n-pentane ..........41<br />
Figure 3-7 APCI-MS spectrum in positive ion mode <strong>of</strong> C7-C40 showing (M-1) + ions <strong>of</strong> n-alkanes<br />
..........................................................................................................................................42<br />
Figure 3-8 APCI mass spectrum <strong>of</strong> n-paraffin mixture ...............................................................43<br />
Figure 3-9 APCI mass spectrum <strong>of</strong> C12-C60 .............................................................................43<br />
Figure 3-10 Structures <strong>of</strong> various hydrocarbons investigated by APCI-TOF-MS ........................45
List <strong>of</strong> Figures<br />
Figure 3-11 APCI spectrum <strong>of</strong> the eight Chiron hydrocarbon mixture (for structures see figure 3-<br />
10) .....................................................................................................................................46<br />
Figure 3-12 APCI mass spectrum <strong>of</strong> n-decyl benzene, phytane and 5-α-cholestane ....................48<br />
Figure 3-13 APCI <strong>of</strong> high mass n-alkanes..................................................................................48<br />
Figure 3-14 Total APCI mass spectrumin <strong>of</strong> the mixture <strong>of</strong> seventeen compounds (see table 3.2)<br />
..........................................................................................................................................48<br />
Figure 3-15 Suggested graphical scheme for ionisation mechanism <strong>of</strong> hydrocarbon upon APCI .50<br />
Figure 3-16 APCI mass spectrum after the addition <strong>of</strong> D 2 O to C40 ...........................................52<br />
Figure 3-17 APCI mass spectrum <strong>of</strong> deuterated tetracosane (D-C24) .........................................52<br />
Figure 3-18 APCI-MS 2 spectrum <strong>of</strong> C32 showing (M-3) + fragment at m/z 447.4 from precursor<br />
ion at m/z 465.8 corresponding to (M-3) + H 2 O .....................................................................53<br />
Figure 3-19 APCI-MS 2 spectrum <strong>of</strong> C29 showing (M-1) + fragment at m/z 407.3 from precursor<br />
ion at m/z 425.1 corresponding to (M-1) + H 2 O .....................................................................53<br />
Figure 3-20 APCI (+) mass spectrum <strong>of</strong> waste sample extracted using n-heptane/Acetone ..........54<br />
Figure 3-21 APCI mass spectrum <strong>of</strong> waste sample extracted using n-heptane only .....................55<br />
Figure 3-22 <strong>Mass</strong> spectra <strong>of</strong> the waste sample purified by using 2 gs (a), 4 gs (b) and 6 gs (c) <strong>of</strong><br />
florisil during purification. ..................................................................................................56<br />
Figure 3-23 Enlarged section <strong>of</strong> (+) MS showing bimodal distribution <strong>of</strong> odd and even mass ions<br />
..........................................................................................................................................57<br />
Figure 3-24 APCI/APPI standard recommended calibrant for APCI source ...............................58<br />
Figure 3-25 APCI mass spectra in positive ion mode <strong>of</strong> C7-C40 calibrant ................................59<br />
Figure 3-26 (-) APCI mass spectrum showing identified PCBs in waste sample .........................64<br />
Figure 3-27 (-) APCI mass spectrum <strong>of</strong> PCBs Congener Mix ....................................................64<br />
Figure 3-28 (-) APCI mass spectrum <strong>of</strong> decachlorobiphenyl standard (C 12 OCl 9 ) with simulated<br />
isotope pattern as suggested by Bruker S<strong>of</strong>tware .................................................................64<br />
Figure 3-29 APCI-ion trap mass spectrum <strong>of</strong> waste sample......................................................66<br />
Figure 3-30 Low mass distribution in APCI-iontrap mass spectrum for waste sample ..............66<br />
Figure 3-31 APCI-MS 2 <strong>of</strong> tetracosane with precursor ion at m/z 337 corresponding to (M-1) + ....66<br />
Figure 3-32 APCI-MS 2 <strong>of</strong> pentacosane with precursor ion at m/z 351corresponding to (M-1) + ....67<br />
Figure 3-33 APCI-MS 2 <strong>of</strong> nonacosane with precursor ion at m/z 407 corresponding to (M-1) + ....67<br />
Figure 3-34 APCI-MS 2 <strong>of</strong> dotriacontane with precursor ion at m/z 449 correspon- ding to (M-1) +<br />
..........................................................................................................................................67<br />
Figure 3-35 APCI-MS 2 <strong>of</strong> molecular ion <strong>of</strong> tetracontane (C40) at m/z 562 .................................68<br />
Figure 3-36 APCI-MS 2 <strong>of</strong> molecular ion <strong>of</strong> nonatriacontane (C39) at m/z 548 .............................68<br />
Figure 3-37 APCI-MS 2 <strong>of</strong> molecular ion <strong>of</strong> octatriacontane (C38) at m/z 534 ............................68<br />
Figure 3-38 APCI-MS 2 spectra <strong>of</strong> m/z 561, 547, 519 and 505 corresponding to (M-1) + ions <strong>of</strong><br />
C40, C39, C37 and C36 respectively within a waste extract ................................................69
List <strong>of</strong> Figures<br />
Figure 3-39 MS 2 fragmentation spectra for nonacosane C 29 H + 59 within standard n-alkane mixture<br />
(a) and within waste sample (b) ..........................................................................................71<br />
Figure 3-40 APCI-MS 2 spectrum <strong>of</strong> squalene <strong>of</strong> m/z 411 ...........................................................72<br />
Figure 3-41 APCI-MS 2 spectra <strong>of</strong> four selected ions within the waste sample <strong>of</strong> m/z 409,411,413<br />
and 415 ..............................................................................................................................72<br />
Figure 3-42 Fragmentation spectrum <strong>of</strong> 5-α-cholestane at m/z 371 C 27 H + 47 within standard 5-αcholestane<br />
sample...............................................................................................................74<br />
Figure 3-43 Fragmentation spectra for C 27 H + 47 ion at m/z 371 within waste sample ....................74<br />
Figure 3-44 APCI mass spectrum in positive ion mode <strong>of</strong> waste sample deriva- tised with<br />
Agtriflate ............................................................................................................................76<br />
Figure 3-45 APCI-MS 2 <strong>of</strong> a silver adducted complex at m/z 328 ion ..........................................77<br />
Figure 3-46 Fragmentation <strong>of</strong> selected PCBs at m/z 306, 340 and 374 from the PCBs Congener<br />
Mix ....................................................................................................................................78<br />
Figure 3-47 Fragmentation <strong>of</strong> selected PCBs at m/z 306, 340 and 374 from the waste sample ....78<br />
Figure 3-48 Fragmentation <strong>of</strong> high mass chlorinated components within the waste extract .........79<br />
Figure 3-49 Positive APCI mass spectrum <strong>of</strong> waste sample before oxidation ..............................80<br />
Figure 3-50 Positive APCI mass spectrum <strong>of</strong> waste sample after oxidation ................................80<br />
Figure 3-51 Positive ESI mass spectrum <strong>of</strong> complex waste mixture after oxidation ...................82<br />
Figure 3-52 Negative ESI mass spectrum <strong>of</strong> complex waste mixture after oxidation ..................82<br />
Figure 3-53 Negative ESI mass spectrum <strong>of</strong> model mixture <strong>of</strong> hydrocarbon after oxidation .......83<br />
Figure 3-54 APCI mass spectrum <strong>of</strong> spiked waste mixture with high mass n-alkanes .................84<br />
Figure 3-55 APCI mass spectrum <strong>of</strong> deuterated dotriacontane C 32 D 66 .......................................85<br />
Figure 3-56 A plot between Concentration vs Intensity for C20 .................................................85<br />
Figure 3-57 A plot between Concentration vs Intensity for C29 .................................................86<br />
Figure 3-58 A plot between Concentration vs Intensity for C38 .................................................86<br />
Figure 3-59 A plot between Concentration vs Intensity for C40 .................................................87<br />
Figure 3-60 Positive APCI mass spectrum <strong>of</strong> Lebanese waste sample 1 .....................................90<br />
Figure 3-61 Negative polarity APCI <strong>of</strong> Lebanese waste sample 1 ..............................................90<br />
Figure 3-62 Positive APCI mass spectrum <strong>of</strong> Lebanese waste sample 2 .....................................91<br />
Figure 3-63 Negative polarity APCI mass spectrum <strong>of</strong> Lebanese waste sample 2 .......................91<br />
Figure 3-64 APCI mass spectrum <strong>of</strong> S1 .....................................................................................94<br />
Figure 3-65 APCI mass spectrum <strong>of</strong> S2 .....................................................................................94<br />
Figure 3-66 APCI mass spectrum <strong>of</strong> S3 .....................................................................................94<br />
Figure 3-67 APCI mass spectrum <strong>of</strong> S4 .....................................................................................95<br />
Figure 3-68 APCI mass spectrum <strong>of</strong> S6 .....................................................................................95<br />
Figure 3-69 APCI mass spectrum <strong>of</strong> S7 .....................................................................................95<br />
Figure 3-70 APCI mass spectrum <strong>of</strong> S9 (contaminated through usage oil) .................................96
List <strong>of</strong> Figures<br />
Figure 3-71 ESI mass spectrum <strong>of</strong> bitumen 1 using DCM as mobile phase ................................97<br />
Figure 3-72 APCI mass spectrum <strong>of</strong> bitumen 1 using DCM as mobile phase .............................98<br />
Figure 3-73 APCI mass spectrum <strong>of</strong> bitumen 2 using DCM as mobile phase .............................98<br />
Figure 3-74 Kendrick plot for the light shredder waste ..............................................................99<br />
Figure 3-75 Plot <strong>of</strong> DBE vs measured mass (m/z) for the hydrocarbon compone- nts <strong>of</strong> waste . 100<br />
Figure 3-76 Plot <strong>of</strong> H/C ratio vs DBE (degree <strong>of</strong> unsaturation) <strong>of</strong> a light shredder waste sample<br />
........................................................................................................................................ 100<br />
Figure 3-77 Kendrick plot overlap <strong>of</strong> untreated I2 and I3 waste samples .................................. 103<br />
Figure 3-78 Kendrick plot overlap <strong>of</strong> I3 and treated sample on small scale .............................. 103<br />
Figure 3-79 Kendrick plot overlap between 2009 and 2011 waste samples............................... 104<br />
Figure 3-80 Radar plot <strong>of</strong> four parameters related to five shredder waste samples varying by<br />
operation time .................................................................................................................. 106<br />
Figure 3-81 Kendrick plot <strong>of</strong> (CH 2 ) for waste mixture upon (-) APCI-MS ............................... 107<br />
Figure 3-82 Kendrick plot <strong>of</strong> (Cl) for waste mixture upon (-) APCI-MS .................................. 107<br />
Figure 3-83 Kendrick plot <strong>of</strong> (Cl) for PCBs Congener Mix upon (-) APCI-MS ........................ 108<br />
Figure 3-84 Kendrick plot overlap <strong>of</strong> I3, O2 and O3 ................................................................ 109<br />
Figure 3-85 Kendrick plot overlap <strong>of</strong> Leb S1 and Leb S2 heterogeneous waste samples........... 110<br />
Figure 3-86 Kendrick plot overlap <strong>of</strong> Calpam oil and light shredder waste ............................... 110<br />
Figure 3-87 Kendrick plot overlap <strong>of</strong> Calpam motor oil and contaminated through usage motor<br />
oil .................................................................................................................................... 111<br />
Figure 3-88 Kendrick plot <strong>of</strong> bitumen 1 upon ESI-MS using DCM solvent .............................. 112<br />
Figure 3-89 Kendrick plot <strong>of</strong> bitumen 1 upon APCI-MS using n-heptane solvent .................... 112<br />
Figure 3-90 Kendrick plot overlap <strong>of</strong> bitumen 1 and bitumen 2 using DCM in APCI-MS ......... 113
List <strong>of</strong> Tables<br />
List <strong>of</strong> Tables<br />
Table 1.1 Reference studies targeting various hydrocarbons ......................................................19<br />
Table 2.1 Different shredder waste samples treated under different conditions ...........................33<br />
Table 3.1 Summary <strong>of</strong> APCI data <strong>of</strong> n-alkanes ..........................................................................41<br />
Table 3.2 Ions produced <strong>of</strong> model hydrocarbon compounds.......................................................47<br />
Table 3.3 Molecular formula list <strong>of</strong> n-alkanes in waste sample ..................................................59<br />
Table 3.4 Molecular formula list <strong>of</strong> some analytes <strong>of</strong> hydrocarbons in waste sample..................61<br />
Table 3.5 CID MS 2 -stage tandem mass spectra for some <strong>of</strong> the positive ions <strong>of</strong> tetracosane,<br />
pentacosane and squalene. ..................................................................................................73<br />
Table 3.6 Quantities <strong>of</strong> few selected n-alkanes in waste samples ................................................88<br />
Table 3.7 A selection <strong>of</strong> different car oils from different companies ..........................................93<br />
Table 3.8 Operating conditions <strong>of</strong> small scale treatment reactor <strong>of</strong> shredder waste ................... 102<br />
Table 3.9 Acquisition <strong>of</strong> data points considered in 2009 and 2011 samples .............................. 104<br />
Table 3.10 Extracted data from 5 measured light shredder waste samples ................................ 105
Publications, Manuscripts and Conferences<br />
Publications, Manuscripts<br />
• Hourani, N., Kuhnert, N, <strong>Development</strong> <strong>of</strong> a novel direct-infusion<br />
atmospheric pressure chemical ionization mass spectrometry method for the<br />
analysis <strong>of</strong> heavy hydrocarbons in light shredder waste, Anal. Methods,<br />
2012, DOI 10.1039/ C2AY05249K<br />
• Hourani, N., Kuhnert, N, Investigating non-polar hydrocarbons by<br />
atmospheric pressure chemical ionisation (APCI) mass spectrometry, Rapid.<br />
Commun. <strong>of</strong> <strong>Mass</strong> Spectrom., 2012 (submitted).<br />
• Hourani, N., Kuhnert, N, Translation <strong>of</strong> the unresolved complex mixture <strong>of</strong><br />
hydrocarbons in light shredder Waste by APCI-MS, 2012 (manuscript).<br />
Conferences<br />
• GDCh Science Forum, Bremen, Sep. 2011, poster presented, <strong>Development</strong><br />
<strong>of</strong> a novel direct-infusion atmospheric pressure chemical ionization mass<br />
spectrometry method for the analysis <strong>of</strong> heavy hydrocarbons in light<br />
shredder waste.<br />
• Analytical Research Forum (ARF 11), Manchester, Jul. 2011, presented<br />
poster, <strong>Development</strong> <strong>of</strong> a novel direct-infusion atmospheric pressure<br />
chemical ionization mass spectrometry method for the analysis <strong>of</strong> heavy<br />
hydrocarbons in light shredder waste.<br />
• International <strong>Mass</strong> Spectrometry conference, Bremen, Sep. 2009, presented<br />
poster A New <strong>Mass</strong> <strong>Spectrometric</strong>al Method for the Analysis <strong>of</strong><br />
Complex Mixtures <strong>of</strong> Organic Compounds
Abbreviations<br />
Abbreviations<br />
APCI<br />
APCI/CS 2<br />
APLI<br />
APPI<br />
BEB<br />
CrO 3<br />
CI<br />
CID<br />
ClMn<br />
Co(Cp) 2<br />
DA-APPI<br />
D 2 O<br />
DCM<br />
DESI<br />
EI<br />
ELV<br />
EPA<br />
ESI<br />
FD<br />
FD MS<br />
FI<br />
FI MS<br />
FT ICR<br />
Atmospheric pressure chemical ionisation<br />
Atmospheric pressure chemical ionisation/ Carbon disulfide<br />
Atmospheric pressure laser ionisation<br />
Atmospheric pressure photoionization<br />
Bremer Ensorgungsbetriebe<br />
Chromium trioxide<br />
Chemical ionisation<br />
Collision induced dissociation<br />
Manganese chloride<br />
Cobalt cyclopentadienyl<br />
Dopant assisted atmospheric pressure photoionization<br />
Deuterium oxide<br />
Dichloromethane<br />
Desorption electrospray ionisation<br />
Electron ionisation<br />
End <strong>of</strong> life vehicle<br />
Environmental protection agency<br />
Electrospray ionisation<br />
Field desorption<br />
Field desorption mass spectrometry<br />
Field ionisation<br />
Field ionisation mass spectrometry<br />
Fourier transform ion cyclotron resonance
Abbreviations<br />
GC<br />
HCs<br />
HR MS<br />
IUPAC<br />
KMD<br />
LC<br />
LIAD<br />
LQIT<br />
MALDI<br />
MS<br />
MW<br />
NKM<br />
PAH<br />
PAO<br />
PASH<br />
PCBs<br />
PE<br />
PIO<br />
Q-TOF<br />
RDB<br />
S/N<br />
Gas chromatography<br />
Hydrocarbons<br />
High resolution mass spectrometry<br />
International union <strong>of</strong> pure and applied chemistry<br />
Kendrick mass defect<br />
Liquid chromatography<br />
Laser induced acoustic desorption<br />
Linear quadrupole ion trap<br />
Matrix-assisted laser desorption ionisation<br />
<strong>Mass</strong> spectrometry<br />
Molecular weight<br />
Nominal Kendrick <strong>Mass</strong><br />
Polyaromatic hydrocarbons<br />
Polyalphaolefins<br />
Polyaromatic sulfur heterocycles<br />
Polychlorinated biphenyls<br />
Polyethylene<br />
Polyinternal olefins<br />
Quadrupole time <strong>of</strong> flight<br />
Ring double bond equivalence<br />
Signal to noise ratio<br />
CF 3 COOAg Trifluoroacetate<br />
TOF<br />
UCMs<br />
Time <strong>of</strong> flight<br />
Unresolved complex mixtures
Abbreviations<br />
UV<br />
VGOs<br />
VOCs<br />
VRs<br />
ultraviolet<br />
Vacuum gas oils<br />
Volatile organic carbons<br />
Vacuum residues
Introduction<br />
1 Introduction<br />
1.1 Complex Mixtures<br />
Every human being is a complex mixture <strong>of</strong> around 100 000 different chemicals<br />
and as humans we are surrounded by vast complex mixtures <strong>of</strong> additional millions<br />
<strong>of</strong> chemical compounds affecting our daily lives. We define a complex mixture as<br />
a mixture that contains too many individual compounds as to allow separation by<br />
chromatographic methods (more than 1000 in gas chromatography (GC) and more<br />
than 300 in liquid chromatography (LC)). Analysing such complex mixtures forms<br />
the ultimate challenge <strong>of</strong> analytical chemistry and life sciences but the rewards will<br />
be tremendous. Chemists have by tradition detested such mixture analysis and<br />
reduced the world to the analysis <strong>of</strong> single purified and well defined compounds.<br />
Many materials such as household and industrial wastes, plant and microbial<br />
extracts and dietary materials can be considered as complex mixtures. These<br />
mixtures may consist <strong>of</strong> tens, hundreds or thousands <strong>of</strong> organic compounds, which<br />
exist in inexact proportions. 1 Moreover the composition <strong>of</strong> the aforementioned<br />
complex mixtures is not fully known, either qualitatively or quantitatively and may<br />
vary considerably. Many analytical approaches have targeted complex mixtures in<br />
order to evaluate similarities and dissimilarities between different mixtures, source<br />
identification, changes in mixture composition and assessment <strong>of</strong> toxicity. 2-9<br />
Similarly environmental samples are extremely complex. They include oil spills,<br />
atmospheric deposition, urban run<strong>of</strong>f and waste treatment plants. Many analytical<br />
procedures introduced by legislative bodies tend to ignore this fact. Legal<br />
concentration threshholds are only defined for well characterized single<br />
compounds or groups <strong>of</strong> compounds. In many <strong>of</strong> these samples various types <strong>of</strong><br />
hydrocarbons are present such as in oil spills, industrial discharges and bi<strong>of</strong>uels. 10-<br />
12<br />
The talk about complex mixture can’t be complete without mentioning<br />
petroleum. The latter is the most precious mixture since it is the major source <strong>of</strong><br />
energy known to mankind. 13<br />
1
Introduction<br />
Analytical chemistry has been extensively dedicated to the investigation <strong>of</strong><br />
complex mixtures <strong>of</strong> petroleum for the last years. Petroleum and biodegraded or<br />
hydrothermally altered hydrocarbon extracts are known to exhibit unresolved<br />
complex mixtures (UCMs) in gas chromatograms (raised base line termed as<br />
hump) where the exploration <strong>of</strong> the molecular composition <strong>of</strong> these mixtures<br />
becomes limited. 14-17 Among these are the analysis <strong>of</strong> complex mixtures containing<br />
various types <strong>of</strong> hydrocarbons present in waste or oil mixtures and the analysis <strong>of</strong><br />
high-boiling point distillates where adequate chromatographic separation is not yet<br />
available. 10,18,19 Thus the hydrocarbons elsewhere in different mixtures are known<br />
to possess a substantial proportion in which GC is unable to resolve and identify.<br />
Therefore it is emphasized that the existing analytical technology can’t explore the<br />
chemical composition <strong>of</strong> the sample in any other way. For example the large<br />
magnitude <strong>of</strong> the unresolved complex oil components, containing an estimated<br />
250,000 compounds, is not identified, 19 thus a great deal <strong>of</strong> compositional<br />
knowledge remains poorly understood. Such a lack <strong>of</strong> knowledge limits, most<br />
importantly, the assessment <strong>of</strong> effects <strong>of</strong> unresolved complex residues in the<br />
environment. 20<br />
Yet the study <strong>of</strong> complex mixtures has received recent attention since most <strong>of</strong><br />
these mixtures undergo compositional evolution due to some factors like<br />
temperature, time, source, composition, water, and microbial activity. 10,14 It is well<br />
pronounced that a minor change in the composition <strong>of</strong> a mixture can have a huge<br />
effect on its characteristic properties such as flavour, reactivity and toxicity. Such<br />
evolution yields derived products that could be sometimes described as<br />
unrecognized toxins in, for example, marine environment, 8,21 mussel sediment, 22<br />
and crude oil degradation. 23 As well weathering <strong>of</strong> oil spills requires full<br />
understanding <strong>of</strong> the effects and fate <strong>of</strong> spilled products. 24-26 On the other hand,<br />
chemical characterisation and identification <strong>of</strong> heavier components <strong>of</strong> crude oil can<br />
guide refining and production processes necessary in oil industry. Hence the<br />
analysis <strong>of</strong> complex mixture is very important to food chemistry, oil processing as<br />
2
Introduction<br />
well as to environmental concerns. 27,28 For instance; environmental chemists must<br />
monitor the effects <strong>of</strong> various pollutants on human health and the eco-system.<br />
As understood from the above, the rapidly expanding interest in characterization <strong>of</strong><br />
complex mixtures and their derivatives is driven by several objectives. The<br />
identification and structural characterization <strong>of</strong> compounds, monitoring the<br />
degradation processes <strong>of</strong> complex mixtures, evaluation <strong>of</strong> mixture reactivity<br />
related to properties and the quantification <strong>of</strong> target molecules are the general aims<br />
for research projects in this field. To achieve the above goals, researchers<br />
abandoned traditional analytical methods <strong>of</strong> complex mixtures to meet<br />
revolutionized methods implemented by mass spectrometry (MS). 29 Studies have<br />
shown that the direct analysis <strong>of</strong> complex mixtures is one area <strong>of</strong> mass<br />
spectrometry that has benefited from the evolution <strong>of</strong> the technology within mass<br />
spectrometry. 7<br />
Modern mass spectrometry, with its unsurpassed resolution allows, however, the<br />
simultaneous analysis <strong>of</strong> tens <strong>of</strong> thousands <strong>of</strong> compounds in a single experiment,<br />
which in chromatography are manifested as an unresolved complex hump. Yet the<br />
application <strong>of</strong> novel measurement strategies allowed studying such complex<br />
mixtures in food, biological system and environmental samples. With high<br />
resolution MS studies and new data sorting strategies like Kendrick plots,<br />
knowledge about the actual content <strong>of</strong> unknown complex mixture becomes more<br />
accessible. 30 Although with complex mixtures a detailed and complete<br />
characterization is still perhaps impossible, examinations <strong>of</strong> parts <strong>of</strong> these various<br />
mixtures have recently become popular studies performed mainly due to the<br />
aforementioned reasons. 13<br />
3
Introduction<br />
1.2 Presence and Fate <strong>of</strong> Hydrocarbons in Contaminated Sites<br />
Petroleum samples involve many hydrocarbon mixtures like paraffins, cyclic<br />
paraffins, condensed aromatics and various heteroatom hydrocarbons (mostly O, S<br />
and N heterocycles). 31 The classification <strong>of</strong> hydrocarbons is shown below. Original<br />
petroleum contains molecules <strong>of</strong> a wide boiling point range from highly volatile<br />
C4 hydrocarbons to non-volatile asphaltenes. Generally petroleum mixtures are<br />
common site contaminants and weathered petroleum residuals may stay bound to<br />
soils or sediments for years. 32 In part due to their complexity, little is known about<br />
detailed chemical composition and consequently their potential for health or<br />
environmental impacts. Petroleum mixtures consist primarily <strong>of</strong> relatively<br />
unreactive complex hydrocarbons covering a wide boiling point range. In many<br />
mixtures, hydrocarbons range from volatile, short-chained organic compounds to<br />
heavy, long-chained, branched compounds. The exact composition <strong>of</strong> petroleum<br />
products varies depending upon the source, the modifiers or chemical processing.<br />
In addition to that the chemical composition <strong>of</strong> the product can be further affected<br />
by weathering and/or biological modification upon release to the environment. 33<br />
On the other hand, the disposal <strong>of</strong> toxic industrial wastes through landfill,<br />
incineration or other procedures is a controversial subject, as toxic chemicals or<br />
their decomposition products may contaminate ground and drinking water or<br />
escape into the atmosphere during the production, conservation and treatment <strong>of</strong><br />
the wastes. The lack <strong>of</strong> adequate regulation and <strong>of</strong>ficial treatment and disposal<br />
plants in many countries has led to the illegal collection, transportation and<br />
dumping <strong>of</strong> wastes that, after the introduction <strong>of</strong> legislation designed to control the<br />
problem, must be recovered, identified and properly disposed <strong>of</strong>. On the other hand<br />
the analysis <strong>of</strong> the complex mixtures <strong>of</strong> industrial solvents that, being in liquid<br />
form and <strong>of</strong>ten stored in metallic drums which are subject to corrosion, may<br />
contaminate the landfill sites and could be leached by running water, or escape into<br />
the atmosphere as a result <strong>of</strong> their appreciable vapor pressures.<br />
Soil contamination has been a growing concern because it can be a source <strong>of</strong><br />
groundwater (drinking water) contamination. In addition to that contaminated soils<br />
4
Introduction<br />
can reduce the usability <strong>of</strong> land for development. Nowadays the major significant<br />
source <strong>of</strong> contamination to land and marine environment remains to be oil spills.<br />
Due to increased petroleum production and transportation activities, our world has<br />
witnessed a lot <strong>of</strong> accidental oil spills in the recent years. 34 For example the Gulf<br />
<strong>of</strong> Mexico was stricken by a British Petroleum oil spill which endangered the<br />
whole wild life in that area. Rehabilitation <strong>of</strong> the area was launched instantly. As a<br />
result to such accidents, the biodegradation <strong>of</strong> oil and its derived products have<br />
been the focus <strong>of</strong> many studies. Nevertheless an important concern remains due to<br />
the toxicity <strong>of</strong> these oil constituents. Despite hydrocarbons have low solubility in<br />
water; they can accumulate in the fatty tissues <strong>of</strong> organisms. The long term toxicity<br />
<strong>of</strong> n-hexane in humans is well known. Alkanes with more than 11 carbons are not<br />
toxic most organisms due to their low solubility in water and low chemical<br />
reactivity. However, aromatic hydrocarbons are problematic because <strong>of</strong> their<br />
aqueous solubility and enhanced bioavailability. 35 Hereby studies have tried to<br />
answer questions related to composition and persistence <strong>of</strong> potential complex<br />
pollutants. In equal footing, studies have investigated the bioremediation process<br />
<strong>of</strong> petroleum components in polluted areas. 36 While some types <strong>of</strong> hydrocarbons<br />
are readily biodegraded in marine environment; others like multi-ring aromatics<br />
are difficult to be biodegraded. These compounds resist microbial degradation<br />
partly due to their structure. 37 The environmental impact <strong>of</strong> the unknown oil should<br />
be assessed by the determination <strong>of</strong> individual petroleum hydrocarbons in a<br />
complex mixture <strong>of</strong> compounds. However such mixtures are difficult to separate<br />
by most analytical techniques.<br />
Chromatography does not resolve (and thus identify) a substantial proportion <strong>of</strong><br />
complex hydrocarbon mixtures. These components are <strong>of</strong>ten referred to as the<br />
unresolved complex mixture (UCM), or 'hump', (term UCM was introduced by<br />
Gough and Rowland), which is especially pronounced for biodegraded<br />
petroleum. 16 It is known that microorganisms metabolize various classes <strong>of</strong><br />
petroleum compounds which results in the reduction <strong>of</strong> dominant saturated<br />
aliphatic hydrocarbons. UCM is believed to compose <strong>of</strong> branched and cyclic<br />
5
Introduction<br />
aliphatic hydrocarbons and aromatic hydrocarbons (see Figure 1-1), which usually<br />
show the greatest resistance to biodegradation. 38,39 These compounds give rise to<br />
UCM referred to as a hump by Gough and Rowland in 1990. UCM is used as an<br />
indicator <strong>of</strong> petrogenic environmental input due to its persistence after accidental<br />
or chronic oil spills. Historically, UCM has been considered non-toxic but more<br />
recent studies suggest otherwise. 23 The chemical analysis <strong>of</strong> crude oils and related<br />
samples are necessary for tracking compositional changes <strong>of</strong> products affected by<br />
biodegradation or weathering 25 such as in oil spills or in complex mixtures<br />
undergoing biological treatments like solid waste. Characterization <strong>of</strong> UCM has<br />
been an important competition among researchers who applied different strategies<br />
to guess the composition beyond the GC hump. Concerned with the toxic behavior<br />
<strong>of</strong> the above reported hydrocarbon forms, other researchers have been looking for<br />
improved methods <strong>of</strong> quantification. Therefore, development <strong>of</strong> informative<br />
analytical methods that unambiguously reveal the quantity and identify<br />
hydrocarbons found in different complex mixtures are highly required. Overall<br />
environmental awareness demand the investigation <strong>of</strong> the presence and<br />
concentration <strong>of</strong> primary contaminant classes such as polyaromatic hydrocarbons<br />
(PAH), amines or polychlorinated biphenyls (PCBs) in water, soils or sands.<br />
Regulatory bodies like Environmental Protection Agency (EPA, USA) are always<br />
interested in assessing and minimizing the impact <strong>of</strong> chemical waste and in<br />
detecting specific toxicants accidently released into the environment. 40<br />
Classification <strong>of</strong> Hydrocarbons, HCs:<br />
•Straight branched aliphatic, cycloaliphatic (Decane to Tetracontane)<br />
•Polycyclic Aromatic Hydrocarbons, PAHs ( Naphthalene, Pyrene)<br />
And the collection extends to others in terms <strong>of</strong> degradability, solubility<br />
and volatility:<br />
6
Introduction<br />
•Polychlorinated Biphenyls, PCBs<br />
•Chlorinated Hydrocarbons, CHC (chlorodecane, PVC)<br />
• BTEX (Benzene, Toluene, Ethyl benzene and Xylene)<br />
•Volatile organic carbon components, VOCs (Methane, Formaldehyde)<br />
Aliphatic Hydrocarbons<br />
Aromatic Hydrocarbons<br />
7
Introduction<br />
Figure 1-1 Examples <strong>of</strong> aliphatic and aromatic hydrocarbons in crude oils<br />
1.3 Use <strong>of</strong> <strong>Mass</strong> Spectrometry for Hydrocarbon Analyses<br />
New technology, advances in methodology and increase <strong>of</strong> computational power<br />
have contributed massive generation <strong>of</strong> data in analytical chemistry. The evolution<br />
<strong>of</strong> mass spectrometry has attracted interest into the world <strong>of</strong> complex mixture<br />
analysis especially complex mixture <strong>of</strong> hydrocarbons.<br />
<strong>Mass</strong> spectrometry has seen a dramatic development over the last ten to fifteen<br />
years. Whereas in the 1990 MS was limited to the analysis <strong>of</strong> volatile stable<br />
compounds by electron ionization (EI) or chemical ionization (CI) ionization<br />
methods, the advent <strong>of</strong> s<strong>of</strong>t ionization techniques such as electrospray ionization<br />
(ESI), atmospheric pressure chemical ionization (APCI) or matrix-assisted laser<br />
desorption/ionization (MALDI) has lead to a surge <strong>of</strong> technical developments. As<br />
a direct consequence <strong>of</strong> s<strong>of</strong>t ionization techniques nowadays almost any analyte<br />
independent <strong>of</strong> its molecular weight and stability can be successfully ionized and<br />
transferred into the gas phase for MS measurements.<br />
Parallel to the development <strong>of</strong> these ionization techniques the invention <strong>of</strong> new<br />
mass separating systems and their improvement and fine tuning has taken place<br />
Most notable examples are the developments and commercialization <strong>of</strong> ion trap<br />
8
Introduction<br />
MS, time <strong>of</strong> flight (TOF)-MS and Fourier transform ion cyclotron resonance (FT<br />
ICR)-MS instruments as well as hyphenated MS technologies such as quadruple<br />
(Q)-TOF or TOF-TOF instruments.<br />
Each development has resulted in a dramatic increase <strong>of</strong> the scope <strong>of</strong> MS and<br />
resulted in a spectacular increase <strong>of</strong> instruments capabilities. TOF instruments for<br />
example allow the determination <strong>of</strong> molecular weights up to the million Dalton<br />
range with whole virus being examined in the gas phase. Ion trap instruments have<br />
added powerful methodology for structure elucidation by using up to twelve<br />
tandem MS stages. Both TOF and FT ICR MS instruments have allowed an<br />
impressive improvement in sensitivity <strong>of</strong> the instrumentation leading to routine<br />
limits <strong>of</strong> detection in the femto mole (fmol) region. Finally TOF and FT ICR<br />
instruments allow an impressive resolution many orders <strong>of</strong> magnetic higher than<br />
any chromatographic technique. The current world record for an FT ICR<br />
measurement stands at the detection <strong>of</strong> 100,000 species in a crude oil sample in a<br />
single spectrum set by the group <strong>of</strong> A. Marshall. 41 Especially by the pioneering<br />
work <strong>of</strong> A. Marshall in the field <strong>of</strong> petroleomics has paved the way for complex<br />
mixture analysis exploiting the impressive resolving capability <strong>of</strong> a high resolution<br />
mass spectrometer. However these capabilities pose new challenges to the<br />
analytical chemist. A modern mass spectrometer is certainly capable <strong>of</strong> obtaining<br />
structural information at high sensitivity, specificity and speed for complex<br />
mixture sample, but how can such data be interpreted in a meaningful way? How<br />
can such information be used for reliable structure elucidation and quantification<br />
<strong>of</strong> analytes?<br />
The coupling <strong>of</strong> LC to MS has resulted in the development <strong>of</strong> so called multidimensional<br />
techniques providing a separation step coupled detection steps using a<br />
variety <strong>of</strong> spectroscopic methods such as UV coupled to MS. Multi dimensional<br />
information refer to the possibility <strong>of</strong> combining retention time information with<br />
UV and MS information. An overview <strong>of</strong> the range <strong>of</strong> applications <strong>of</strong> GC/MS (EI)<br />
and LC/MS (ESI, APCI) over a range <strong>of</strong> polarity and relative molecular mass is<br />
shown in Figure 1-2.<br />
9
Introduction<br />
Figure 1-2 Range <strong>of</strong> ionisation techniques employed with different types <strong>of</strong><br />
compounds<br />
As explained earlier chromatography coupled to MS can solve analytical problems<br />
<strong>of</strong> mixtures containing several dozens or hundreds analytes, however the study <strong>of</strong><br />
real complex mixture comprising thousands <strong>of</strong> analytes is still in an area <strong>of</strong> MS<br />
only. MS can provide detailed molecular-level information for hydrocarbon<br />
complex mixtures.<br />
Therefore, better methods that characterise complex mixtures have been most<br />
recently driven by the development <strong>of</strong> improved mass spectrometry methods. For<br />
example the emerging field <strong>of</strong> Petroleomics has provided a series <strong>of</strong> novel data<br />
interpretation strategies to extract chemical and other relevant information from<br />
such enormously complex data. 42 Under this concept and with the help <strong>of</strong><br />
developed technological devices available for research groups, studies have<br />
examined hydrocarbon complex mixtures and their model compounds by<br />
revolutionised methodologies. These experiments argued ionisability and<br />
volatility 43 <strong>of</strong> hydrocarbon molecules using a high resolution detector are to play<br />
an important role in extending the applicability <strong>of</strong> MS for complex hydrocarbon<br />
mixture analyses. Although such experiments are considered intriguing steps<br />
towards hydrocarbon complex mixture, however they are not without problems. To<br />
understand the problems and limitations <strong>of</strong> hydrocarbon analyses in MS, a critical<br />
10
Introduction<br />
review <strong>of</strong> the work done in this field will be reported. Research efforts have<br />
investigated the potential <strong>of</strong> various ionisation methods to create intact product<br />
ions representing the neutral composition <strong>of</strong> complex mixture. It follows that the<br />
choice <strong>of</strong> ionisation method plays a key role towards a rational detailed analysis <strong>of</strong><br />
crude oil samples.<br />
1.3.1 EI and CI<br />
Traditionally low-energy EI and CI ionisation were used for petroleum analysis. 44-<br />
48 EI (70 eV) produces extensive fragmentation <strong>of</strong> the ionised hydrocarbon<br />
molecules. Nevertheless characteristic fragment ions <strong>of</strong> petroleum were developed<br />
to provide valuable crude oil assay for light or medium hydrocarbons. However,<br />
this method can’t be used to identify each type <strong>of</strong> hydrocarbons as well as it is not<br />
accurate if sample contains olefins or heteroatom containing compounds. 49 The<br />
obtained molecular weight information becomes rather complicated due to<br />
fragmentation and difficulties in identifying molecular ions. Also since molecules<br />
are brought to gas phase by thermal vaporisation that defines EI and CI methods,<br />
high boiling point molecules <strong>of</strong> hydrocarbons can’t be detected thereby.<br />
1.3.2 ESI, DESI and MALDI<br />
Other s<strong>of</strong>t ionisation techniques such as ESI, APCI, APPI and MALDI have also<br />
taken part in the analysis <strong>of</strong> individual or complex mixtures <strong>of</strong> hydrocarbons. For<br />
numerous applications in mass spectrometry ESI is widely used as an ionisation<br />
method. It has been used to evaporate and ionise polar compounds <strong>of</strong> petroleum<br />
containing functional groups with nitrogen or oxygen atom. 41,50-56 The technique<br />
can successfully vaporise and ionise hydrocarbon analytes and produce<br />
pseudomolecular ions without fragmentation. The molecules in positive molecular<br />
ion formation are either protonated (basic compounds) or deprotonated (acidic<br />
compounds). With ESI FT ICR combination allows a compact mass spectral<br />
display for visual resolution <strong>of</strong> up to thousands <strong>of</strong> peaks. However polar<br />
hydrocarbons are only a small portion <strong>of</strong> petroleum (10%). ESI is ‘blind’ to other<br />
major nonpolar hydrocarbon fraction <strong>of</strong> petroleum especially saturate and aromatic<br />
11
Introduction<br />
fractions. 42 Another study employed discharge-induced oxidation in desorption<br />
electrospray ionisation (DESI). 57 Ambient analysis <strong>of</strong> saturated hydrocarbons<br />
(C 15 H 32 to C 30 H 62 ) using reactive DESI as an insitu derivatization method<br />
generated a representative adduct ion for the examined model alkanes and the<br />
vacuum gas oil saturate fraction.<br />
As well other s<strong>of</strong>t ionisation method were employed for petroleum<br />
characterisation, such as MALDI (Figure 1-3). 58,59 A reactive MALDI MS method<br />
could successfully ionise large alkanes and polyethylene producing cobalt<br />
cyclopentadienyl alkane cation [Co(Cp) 2 (alkane+2H 2 )] +• . This organometallic gas<br />
phase chemistry seems functional but nevertheless a selective approach. 60<br />
Figure 1-3 Matrix-assisted laser desorption/ionization (MALDI)<br />
1.3.3 FD and FI<br />
Field desorption (FD) and field ionisation (FI) techniques are considered among<br />
the most successful ionisation techniques for saturated hydrocarbons. 28 [M-2H] +<br />
ions were reported to be abundantly yielded for saturated and aromatic various<br />
saturated and aromatic compounds under conditions <strong>of</strong> field desorption mass<br />
12
Introduction<br />
spectrometry (FD-MS). 61 Combination <strong>of</strong> FI to GC and TOF HRMS (High<br />
resolution mass spectrometry) generated intact molecular ions [M] +• for both<br />
saturated and aromatic petroleum molecules. 62 Another study performed by Hsu et<br />
al. using this time LC/FI-MS, produced as well molecular ions for investigated<br />
paraffins and napthenes but fragment ions for isoparaffins like squalane. 63 FD-MS<br />
was employed to analyse large multiply branched saturated hydrocarbons,<br />
fragment ions were produced reflecting dehydrogenation, alkyl losses and alkene<br />
losses. 64 Field desorption ionisation however can also produce ions from nonpolar<br />
species but with less convenience at atmospheric pressure. 65,66<br />
1.3.4 APPI<br />
APCI and APPI are known to produce intact ions for polar hydrocarbons as [M-<br />
H]ˉ, [M+H] + or [M] •+ but for saturated hydrocarbons the techniques have proven<br />
limited. 67,68 APPI is also used to analyze fairly nonpolar molecules. The<br />
illumination <strong>of</strong> the sample molecules by vacuum ultraviolet lamp produces radical<br />
molecular ions by photoionisation. For example PAH were produced as protonated<br />
upon APPI, but APPI can’t be used to ionise saturated paraffins. APPI, however,<br />
was found to produce at the same time protonated, deprotonated and molecular ion<br />
radicals <strong>of</strong> nonpolar aromatic compounds like polyaromatic sulfur heterocycles<br />
(PASH). 30 This leads to complication in composition assignment <strong>of</strong> these<br />
compounds in petroleum fractions. It was as well shown that the ionisation<br />
efficiency <strong>of</strong> the parent radical ion is enhanced once a dopant is added. The APPI<br />
ionisation technique becomes dopant-assisted (DA-APPI). For example toluene<br />
works by enhancing proton transfer and charge exchange reactions. Simultaneous<br />
production <strong>of</strong> protonated and radical molecular ions is observed. Overall APPI is<br />
thought to possess a potential to cover a broader range <strong>of</strong> compounds <strong>of</strong> crude oil.<br />
Particularly APPI was demonstrated to analyse asphaltene producing good<br />
results. 69<br />
13
Introduction<br />
1.3.5 APLI<br />
Other crude oil ionisation methods included atmospheric pressure laser ionisation<br />
(APLI). This technique was introduced by Benter and colleagues. 70-73 Since APLI<br />
is found sensitive for aromatic compounds, it is considered capable to reduce<br />
complexity <strong>of</strong> crude oil. Shrader et al. demonstrated coupling <strong>of</strong> APLI with FT-<br />
ICR MS as a suitable approach for the analysis <strong>of</strong> aromatic species in complex<br />
crude oil fractions. 74 A more recent paper also investigated the potential <strong>of</strong> APLI to<br />
complement the ionisation process <strong>of</strong> crude oil analytes compared to other<br />
ionisation techniques like ESI and APPI. Results showed preference <strong>of</strong> APLI over<br />
the other techniques in the analysis <strong>of</strong> crude oil fraction. 75<br />
1.3.6 APCI, LIAD/CI and LIAD/APCI<br />
Another more generally applicable ionisation technique is the atmospheric pressure<br />
chemical ionisation (APCI). Introduced by Horning in 1970, APCI produced a<br />
wide variety <strong>of</strong> different types <strong>of</strong> ions from a given analyte. An LC-APCI-MS was<br />
used to identify classes <strong>of</strong> PAHs in mussels. A proton transfer ion (M+H) + and a<br />
charge transfer radical ion (M) •+ were observed for the studied PAHs using<br />
different mobile phases. 27 The latter ionisation patterns are produced<br />
simultaneously in typical APCI processes. APCI has as well been used for<br />
petroleomic analyses 62,76,77 where it was considered limited due to its low<br />
sensitivity. Nevertheless, APCI, a popular ionization technique, has been<br />
considerably used for detection <strong>of</strong> n-alkanes. 78-81 Alkanes are known to be used as<br />
probes for APCI-MS ionization processes.<br />
Karasek et al. analysed n-alkyl halides 82 and n-alkanes (C 5 H 12 -C 15 H 32 ). 83 For alkyl<br />
halides (MX), (M-1) + ions were formed by hydrogen abstraction, while for n-<br />
alkanes, formation <strong>of</strong> (MH) + and (MNO) + adduct ions was postulated. Bell et al. 78<br />
investigated some n-alkanes in 1994. He found that n-alkanes were characterised<br />
by composites <strong>of</strong> protonated and monohydrated species (M-H) + , (M-3H) + and (M-<br />
3H) + H 2 O. These ions were generated by corona discharge and monitored by ion<br />
mobility. A hydrogen abstraction was supposed for the formation <strong>of</strong> the above<br />
14
Introduction<br />
product ions. The peak assignment based on a comparison <strong>of</strong> ion mobility spectra<br />
with spectra obtained by CI-MS whereas (M-3H) + and (M-3) + H 2 O were identified<br />
by using APCI-MS with 63 Ni ionisation. A Recent study by Marotta and Paradisi<br />
obtained an array <strong>of</strong> low boiling point linear and branched C 5 -C 8 alkane ions by<br />
using air plasma fed APCI-MS. 79 Subsequent chemical ionisation (CI) studies<br />
showed that intact high mass alkane ions could be generated in the gas phase by<br />
using ligated-metal ion chemistry via cationization methods (silver cation Ag + ,<br />
disilver-oxide cation Ag 2 O + ) or transition metals ( Fe,Co,Ni). 84-86 Moreover<br />
organometallic cations were used by Byrd et al. 87 in particular cobalt cyclopentadienyl<br />
cation (CpCo •+ ) to create intact gas phase species [(CpCo+alkane)-2H 2 ] •+ .<br />
Some <strong>of</strong> these ions were used to determine the molecular weight (MW) <strong>of</strong> many<br />
nonpolar hydrocarbons and polymers and were later incorporated into other<br />
techniques for petroleum analysis.<br />
However the most extensive work in the field <strong>of</strong> nonpolar hydrocarbon analysis<br />
within model mixtures or real life complex mixtures is attributed to Kenttamaa<br />
et.al. The group explored many revolutionised and efficient methodologies to<br />
explain the complex compositions <strong>of</strong> crude oil, asphaltenes and lubricants. 28,88,89<br />
An analytical summary assay <strong>of</strong> their work in the recent years will be portrayed.<br />
The work <strong>of</strong> Kenttamaa’s group is described to be an intriguing contribution to this<br />
field. They mainly adopted laser desorption/ionisation methods using laser induced<br />
acoustic desorption. 90-92 This enabled them to desorp non-volatile and thermally<br />
labile species as intact neutral species into the gas phase. Such an approach allows<br />
independent control <strong>of</strong> desorption/ionisation processes. This forms a benefit which<br />
is not feasible with other techniques. More recently this group has examined the<br />
behaviour <strong>of</strong> hydrocarbon ions in different mass spectrometries using different<br />
ionisation technologies. For example, Kenttamaa et al. utilized cyclopentadienyl<br />
cobalt radical cation (CpCo •+ ) as an ionising agent for the analysis <strong>of</strong> various polar<br />
and nonpolar components in petroleum distillates using laser-induced acoustic<br />
desorption/fourier transform ion cyclotron resonance mass spectrometry (LIAD/FT<br />
ICR-MS). 28,93 The neutral desorbed hydrocarbons were reacted with activated<br />
CpCo •+ to produce stable addition products (adduct-H 2 , adduct-2H 2 , or both<br />
15
Introduction<br />
products). Other molecules reacted by loss <strong>of</strong> methyl radical and two hydrogen<br />
molecules like 5-α-cholestane. This group applied the same LIAD/CpCo •+ CI<br />
method in another study for polyethylene (PE) samples with low molecular weight<br />
(200-655). 94 Later on Kenttamaa co-workers selected a less aggressive chemical<br />
ionisation reagent, the water cluster <strong>of</strong> Manganese cation, [ClMn(H 2 O) + ],<br />
combined with LIAD for examining a variety <strong>of</strong> hydrocarbons. 95 This ion was<br />
useful to ionise all types <strong>of</strong> hydrocarbons forming only one product ion<br />
[ClMn+M] + via water loss and without fragmentation. This latter method was<br />
described to be an efficient mass spectrometric method for the analysis <strong>of</strong><br />
branched saturated hydrocarbons forming exclusively pseudomolecular ions<br />
(adduct-H 2 O). Such ionisation was found better characterising than atmospheric<br />
pressure chemical ionisation (APCI) and ESI <strong>of</strong> nonpolar lipids and steroids as<br />
according to their observations. 96<br />
Another LIAD/ClMn(H 2 O) + method was applied for the analysis <strong>of</strong> base oils<br />
(major components <strong>of</strong> Lubricants). 88 The product ion [ClMn+M] + was the only ion<br />
representing each components (M) within the complex mixture <strong>of</strong> the base oil as<br />
shown in Scheme 1. The molecular weight distribution for base oil samples was<br />
found in the range <strong>of</strong> 350-600 Da.<br />
ClMn(H 2 O) + + M H<br />
2<br />
<br />
O<br />
<br />
[ClMn+M] +<br />
Scheme 1. Generation <strong>of</strong> adduct ions using LIAD/ClMn(H 2 O) +<br />
Coupling LIAD to APCI by kenttamaa’s group enabled the evaporation and<br />
ionisation <strong>of</strong> polar and nonpolar analytes yielding predominantly molecular ions<br />
with minor fragmentation using carbon disulfide (CS 2 ) as a reagent. 97 Protonated<br />
molecules (M+H) + were observed to be found in higher branching ratios when<br />
benzene was used as APCI reagent. The investigated compounds were structurally<br />
similar to those present in petroleum. Petroleum cuts were as a result analysed<br />
upon LIAD/APCI using nitrogen gas as the reagent. Explanations were elaborated<br />
according to the results <strong>of</strong> model mixture <strong>of</strong> the hydrocarbons. Just recently, an<br />
APCI/CS 2 method utilized by the same group demonstrated the production <strong>of</strong><br />
abundant stable molecular ion (M +• ) for nonpolar aromatic, polar aromatic and<br />
16
Introduction<br />
alkene compounds under investigation. 43 On contrast the alkane derivatives like 5-<br />
α-cholestane, squalane and hentriacontane studied under the same conditions<br />
produced different product ions accompanied with notorious fragmentation. In<br />
addition to that changing APCI reagent to MeOH/H 2 O, only few <strong>of</strong> the tested<br />
analytes were detected where fragmentation was observed for most <strong>of</strong> them. It was<br />
clear that this study facilitated to a certain extent the analysis <strong>of</strong> petroleum cuts<br />
through understanding the behaviour <strong>of</strong> model compounds structurally similar to<br />
those in petroleum.<br />
Although the above reported APCI methodology has established a stable<br />
corresponding ion for few hydrocarbon analytes, it failed to achieve a successful<br />
ionisation <strong>of</strong> saturated aliphatic hydrocarbons. In fact another similar study<br />
performed by the group <strong>of</strong> Kenttamaa didn’t even yield any detectable ions for<br />
saturated cyclic hydrocarbon 5-α-cholestane under different APCI conditions. 96<br />
1.3.7 Summary<br />
In summary to this part, nonpolar hydrocarbons that form 90% <strong>of</strong> the petroleum<br />
composition were examined by different mass spectrometries coupled to different<br />
ionisation technologies mostly assisted by various chemical modification<br />
processes.<br />
EI and CI are not ideal for high MW hydrocarbon analysis because they produce<br />
extensive fragmentation. 28 In the analysis <strong>of</strong> complex mixture, fragmentation is<br />
deleterious, because the production <strong>of</strong> more than one signal per analyte<br />
complicates an already crowded mass spectrum and thus makes it difficult to<br />
identify parent ion. On the other hand ESI was found capable <strong>of</strong> ionising only<br />
polar hydrocarbons. Further studies employing DESI, MALDI, APPI and APLI<br />
were found rather selective for certain types <strong>of</strong> nonpolar hydrocarbons. Using FD<br />
and FI suffers from low ionisation efficiency, varied response factors <strong>of</strong><br />
hydrocarbons <strong>of</strong> different types <strong>of</strong> MW (affecting quantification) and<br />
fragmentation <strong>of</strong> molecular ions due to heating <strong>of</strong> analytes. 28<br />
17
Introduction<br />
Other studies performed using APCI have attributed hydrocarbon ionisation to the<br />
chemistry <strong>of</strong> this methodology. 2 For example, failure to control ion generation in<br />
APCI restricts the production <strong>of</strong> lone intact gas phase hydrocarbon ions in mass<br />
spectrometry. Tuning APCI conditions can to some extent control gas phase<br />
reactions. However, certain analytes still produce significant abundant ions or<br />
fragments which can consequently complicate a real life sample containing<br />
thousands <strong>of</strong> hydrocarbons. 43<br />
Specifically, failure to produce intact, high mass alkane gas phase ions has been<br />
preventing mass spectrometric analysis <strong>of</strong> saturated hydrocarbons as well limiting<br />
its application towards petroleum industry. Furthermore all studies carried out<br />
using APCI-MS focused on model system and pure reference compounds rather<br />
than achieving any analysis <strong>of</strong> n-alkanes within real life samples <strong>of</strong> complex<br />
mixtures. It is well demonstrated that the aforementioned studies have lacked a<br />
“universal” s<strong>of</strong>t ionisation method that simultaneously can ionise both saturate (i.e.<br />
paraffins, cyclic paraffins) and aromatic petroleum molecules (alkylated benzenes,<br />
alkylated polynuclear aromatics, alkylated thiophenoaromatics, etc). A summary <strong>of</strong><br />
most significant studies performed for model or complex hydrocarbon mixtures is<br />
given in Table 1.<br />
As understood from the above reporting, an ideal mass spectrometric method<br />
capable <strong>of</strong> desorping intact hydrocarbons into the gas phase and ionising all<br />
hydrocarbon analytes, including saturated and unsaturated analytes, to yield intact<br />
molecular or pseudomolecular ions that are representative <strong>of</strong> neutral hydrocarbon<br />
molecular weight (MW) without fragmentation and while avoiding any<br />
derivatisation or adduct chemistry would be an intriguing novel approach. Such<br />
approach should accordingly infer product ions can be subjected to controlled<br />
fragmentation using tandem MS. Acquisition <strong>of</strong> qualitative and quantitative data<br />
from complex hydrocarbon mixture can be then greatly facilitated as ionisation <strong>of</strong><br />
all components becomes uniform. In other words the first step in characterization<br />
<strong>of</strong> organics in petroleum is to define the molecular mass distribution and proceed<br />
with elemental composition assignment from efficiently accurate mass<br />
18
Introduction<br />
measurements. Next data interpretation skills are performed to visualise the<br />
acquired data in its most informative form (Figure 1-4).<br />
Figure 1-4 Complex data management<br />
Table 1.1 Reference studies targeting various hydrocarbons<br />
Methodology Tested Hydrocarbons Product Ions Drawback Ref.<br />
DESI-Iontrap-MS<br />
Alkanes (C 15 to C 30 )<br />
Petroleum distillate<br />
[M+2O+BA] +<br />
Extensive dehydrogenation<br />
species observed<br />
57<br />
MALDI-RTOF-260<br />
High mass n-alkanes<br />
Polyethylene<br />
[Co(Cp) 2 (alkane-2H 2 )] +<br />
Organometallic matrix<br />
interactions<br />
60<br />
FD-MS<br />
Saturated and aromatic HCs<br />
Polywax<br />
[M-2H] +<br />
Low ionisation efficiency<br />
<strong>of</strong> product ion<br />
61<br />
FD-MS<br />
Large branched<br />
hydrocarbons<br />
Low abundance M •+ Extensive fragmentation 64<br />
LC/FI-MS<br />
Paraffins-Napthenes-<br />
Isoparaffins<br />
M •+<br />
Fragment ions for<br />
isoparaffins<br />
63<br />
n-paraffins<br />
GC-FI-TOF-MS<br />
VGO distillate(S<br />
heterocycles)<br />
M •+ Selective 62<br />
APPI-FT ICR-MS<br />
Naphtho[2,3-a]pyrene<br />
Crude oil<br />
[M+H] + , [M-H] ‾ , M •+<br />
Complication <strong>of</strong> mass<br />
spectra<br />
30<br />
19
Introduction<br />
APLI-FT ICR-MS Crude oil M •+ Specific and sensitive for<br />
aromatic hydrocarbons<br />
74<br />
APLI-FT ICR-MS<br />
Non-polar aromatic in<br />
heavy crude oil samples<br />
M •+<br />
Selective for aromatic<br />
components<br />
75<br />
LC/APCI-MS PAH [M+H] + , M •+ Poor signal intensity <strong>of</strong><br />
PAH< 300 u<br />
6<br />
APCI-MS with 63 Ni<br />
ionisation<br />
n-alkanes<br />
[M+H] + , [M-3H] + ,<br />
[(M-3H)H 2 O] + Low mass alkanes 78<br />
EI-FT ICR-MS n-alkanes (up to C 30 )<br />
[CpCo+alkane-2H 2 ] •+<br />
~80%<br />
Formation <strong>of</strong> other product<br />
ions, Limit C 30<br />
87<br />
LIAD/FT ICR-MS<br />
Saturated, unsaturated<br />
Hydrocarbons<br />
Petroleum distillate<br />
[M+CpCo-2H 2 ] •+<br />
(Adduct), (Adduct-H 2 ) or<br />
(Adduct-2H 2 -CH 3 ) may<br />
form<br />
28,93,<br />
94<br />
polyethylene<br />
LIAD/ClMn(H 2 O) + /<br />
FT- ICR MS<br />
Various hydrocarbons<br />
[(ClMn+M)-H 2 O] +<br />
Adduct interaction may<br />
result with complex<br />
mixture<br />
88,95<br />
Base oil fractions<br />
LIAD/APCI/LQIT Model hydrocarbons M •+ , [M+H] + generation and minor<br />
No control <strong>of</strong> ion<br />
fragmentation<br />
APCI/CS 2 /LQIT Model hydrocarbons M •+ Significant failure with<br />
saturated analytes<br />
97<br />
43<br />
1.3.8 Ionisation via APCI<br />
Since a significant portion <strong>of</strong> the studies employed for hydrocarbon analyses has<br />
used APCI as an ionisation technique, I would like to give an insight about this<br />
ionisation technique. APCI is an ionisation method used in mass spectrometry. It is<br />
20
Introduction<br />
an ionisation technique <strong>of</strong> choice for the analysis <strong>of</strong> medium to less polar, small<br />
and thermally relative stable analytes. It is a form <strong>of</strong> CI which takes place at<br />
atmospheric pressure. APCI was first introduced by Horning in 1973 for the<br />
analysis <strong>of</strong> volatile compounds. 43 However APCI wasn’t spread until the<br />
commercialisation <strong>of</strong> ESI after Fenn’s work in 1985. 98 Contrary to ESI, APCI has<br />
the capability to vaporise higher boiling point analytes which resist volatilisation.<br />
Figure 1-5 Schematic description <strong>of</strong> the atmospheric pressure chemical ionisation<br />
(APCI) interface and the mechanism <strong>of</strong> ion formation in the corona discharge<br />
region<br />
Ionisation inside APCI is separated from solvent evaporation. After the mobile<br />
phase is introduced into a pneumatic nebuliser, it is heated to high temperatures<br />
(400-450 °C) inside a heated quartz tube and sprayed with high flow <strong>of</strong> nebulizer<br />
gas (nitrogen gas). Ionisation occurs in gas phase, in contrast to ESI, by subjecting<br />
the vaporised neutral analytes and reagent gas molecules (N 2 , H 2 O, O 2 ) to corona<br />
discharge needle that creates the ions. It is emphasized that the corona discharge<br />
needle is used as an electron source to ionise gas phase molecules such as<br />
molecules <strong>of</strong> N 2 (commonly used as sheath gas) and molecules <strong>of</strong> the solvent<br />
(commonly used methanol/water) forming radical cation in positive ion-mode.<br />
These ions collide with the neutral analytes resulting in the creation <strong>of</strong> ions. The<br />
high frequency <strong>of</strong> collisions results in high ionisation efficiency and thermalisation<br />
<strong>of</strong> the analyte ions. These ions enter pumping and focusing stages within mass<br />
21
Introduction<br />
spectrometry in as much as with other ionisation techniques like ESI. The APCI<br />
techniques generally produce pseudo-molecular ions depending on many factors<br />
such as the chemical properties <strong>of</strong> the analytes, the polarity <strong>of</strong> electrospray voltage,<br />
the nature <strong>of</strong> the matrix and the solvent composition. It is not always easy to<br />
predict whether positive or negative ions will be preferentially produced. Overall<br />
protonation <strong>of</strong> the analyte is usually observed in positive-mode APCI. Other<br />
molecular ions and fragments like (M-H) + can also be formed. 76,99<br />
Research efforts have focused to control ion generation in APCI by selecting a<br />
convenient sheath gas or a proper solvent. Many types <strong>of</strong> ions are still produced for<br />
each analyte. This phenomenon can complicate the analysis <strong>of</strong> complex mixtures.<br />
This happens when solvent molecules engage in the generation <strong>of</strong> the radical<br />
cations that collide with the neutral analytes ions.<br />
Ionisation upon APCI with no liquid reagent can be most likely attributed to N 2<br />
molecular ions N +• +•<br />
2 . N 2 ions are thought to be responsible for production <strong>of</strong><br />
molecular ions by electron abstraction. The A significant advantage <strong>of</strong> APCI is<br />
the ability to introduce nonpolar solvent instead <strong>of</strong> polar solvents and to handle<br />
higher flow rate in the range <strong>of</strong> 1ml/min commonly applied in high performance<br />
liquid chromatography (HPLC). This allows the analysis <strong>of</strong> nonpolar species<br />
which otherwise can’t be analysed under ESI conditions. APCI is known to be a<br />
less ‘s<strong>of</strong>t’ ionisation technique than ESI by causing fragmentation compared to ESI<br />
ionisation. A schematic description <strong>of</strong> an APCI-interface and the mechanism <strong>of</strong><br />
APCI is given in Figure 1-5.<br />
1.3.9 Petroleomics<br />
Global energy challenges have impelled chemical analysis towards better<br />
understanding <strong>of</strong> petroleum composition. The chemical composition <strong>of</strong> crude oil is<br />
so complex in terms <strong>of</strong> the number <strong>of</strong> chemically distinct constituents in an<br />
abundance range 10 000-100 000. Petroleum distillates are complex mixture <strong>of</strong><br />
aliphatic, naphthenic and polaromatic hydrocarbons including various heteroatom<br />
(e.g. N, O) hydrocarbons. Olefins are found in the cracked petroleum streams. 41<br />
22
Introduction<br />
Petroleomics is a field <strong>of</strong> chemical analysis concerned about the characterization <strong>of</strong><br />
all <strong>of</strong> the components <strong>of</strong> petroleum along with their interaction and reactivity.<br />
Acquisition <strong>of</strong> this knowledge allows to differentiate petroleum samples or<br />
distillates and can guide production and refining processes. Such molecular level<br />
information on the types <strong>of</strong> chemical classes and presence <strong>of</strong> certain functional<br />
groups are required by petroleum chemists. For example they can reduce refining<br />
byproducts and waste, prevent pipe failures and predict production problems.<br />
This need to obtain such detailed compositional information pushed the rapid<br />
development <strong>of</strong> mass spectrometry technology. In 1960s the coupling <strong>of</strong> gas<br />
chromatography to mass spectrometry was achieved. Although the growth<br />
continued until 1990, mass spectrometry was limited to low-boiling nonpolar<br />
species. After that GC/MS and LC/MS and tandem MS yielded impressive content<br />
information <strong>of</strong> many petroleum distillates such as gasoline, diesel and gas oil.<br />
However little was known about other polar species <strong>of</strong> heavy crude oils and heavy<br />
petroleum distillate. Fenn suggested most polar species could be ionized by ESI<br />
(Fenn received Noble Prize for ESI). The advent <strong>of</strong> ESI-FT ICR-MS facilitated the<br />
analysis <strong>of</strong> polar fractions within complex crude oils. However little is known<br />
about the compositional knowledge <strong>of</strong> saturates/olefins. Their tendency to<br />
fragment and undergo gas phase reactions leaves them difficult to explore. To this<br />
end, even at the expense <strong>of</strong> the mentioned MS limitations, it is still the cornerstone<br />
<strong>of</strong> the emerging field <strong>of</strong> petroleomics.<br />
Industrial laboratories and research groups have moved from physical (crude oil<br />
assays <strong>of</strong> viscosity, density, etc.) or bulk chemical characterization (% <strong>of</strong> S<br />
content, acid number, etc.) <strong>of</strong> petroleum into detailed characterization <strong>of</strong> petroleum<br />
compositions. 42 The careful choice <strong>of</strong> base oil components and their concentration<br />
leads to enhancing performance <strong>of</strong> lubricants. 88 Nowadays interest is even shifted<br />
into heavier petroleum fractions as the lighter ones (low sulfur) are depleted. 74,100<br />
High energy demand and rising energy prices have led to mold the attention<br />
towards higher-boiling point fractions like vacuum gas oils (VGOs) and vacuum<br />
residues (VRs) <strong>of</strong> crude oil. 13,101 These mixtures should undergo desulfurisation by<br />
23
Introduction<br />
catalytic processing to reduce their sulfur content. 102 Optimisation <strong>of</strong> catalytic<br />
operations demands a structural information about components containing S like<br />
PASH. 103 However while polar hydrocarbon constituents <strong>of</strong> petroleum (10%) are<br />
readily detected under ESI FT-ICR MS conditions, nonpolar components (90%)<br />
are especially problematic and challenging. Recent studies, reviewed in the ‘Use <strong>of</strong><br />
mass spectrometry for hydrocarbon analyses’ section, have shown a great promise<br />
in achieving an efficient and rational analysis <strong>of</strong> such hydrocarbon mixtures. So<br />
far molecular mass distribution, elemental composition assignment and<br />
compositional sorting are elaborated for polar fractions within crude oil by virtue<br />
<strong>of</strong> high resolution FT ICR. Up to thousands <strong>of</strong> different chemical elemental<br />
compositions can be resolved in a single mass spectrum. 41,104,105 The resulting<br />
compositional information may then be displayed in Kendrick plots for rapid<br />
visual comparisons between samples.<br />
To this end, energy research will last for the next two decades. Until alternative<br />
sustainable energy sources are developed, fossil fuels will remain the major source<br />
<strong>of</strong> energy. The advancements in petroleomics will guide how energy will be<br />
processed in the future.<br />
1.3.10 Kendrick plot<br />
The advantages <strong>of</strong> high resolution analysis <strong>of</strong> crude oil extracts by ESI-FT MS<br />
provided access to complex mixture data which were further interpreted in an<br />
illustrative and informative way. Elemental composition <strong>of</strong> ionic species up to<br />
~400 Da can be unambiguously assigned with the virtue <strong>of</strong> high mass accuracy<br />
machines (FT-ICR-MS). 42 However the successfully assigned elemental<br />
compositions for higher-mass ions require data reduction based on the Kendrick<br />
mass scale. The method was originally introduced by Kendrick in 1963. 106<br />
For ultrahigh-resolution measurements, it is useful to convert the measured mass to<br />
the Kendrick mass which allows sorting compounds into homologous series<br />
according to alkylation degree, classes (type <strong>of</strong> heteroatoms), and types (rings plus<br />
double bonds). For example, the IUPAC mass <strong>of</strong> CH 2 , 14.0157 Da, becomes a<br />
24
Introduction<br />
Kendrick mass <strong>of</strong> 14.0000 Da. The ratio <strong>of</strong> nominal mass and accurate mass <strong>of</strong><br />
CH 2 is multiplied by the mass measured by MS to convert it into Kendrick mass.<br />
Kendrick mass = IUPAC mass x (14/14.01565)<br />
Compounds with the same (N, S and O) composition and the same number <strong>of</strong><br />
rings plus double bonds but different numbers <strong>of</strong> CH 2 units in alkyl side chains for<br />
example will differ in Kendrick mass by integer multiples <strong>of</strong> 14.0000 Da. These<br />
compounds are thus easily identified as members <strong>of</strong> a homologous series. Stated<br />
another way, members <strong>of</strong> a homologous series will have the same Kendrick mass<br />
defect (KMD), defined as:<br />
KMD = [Kendrick nominal mass – Kendrick exact mass] x 1,000<br />
This is unique to that series and will be plotted as a homologous series <strong>of</strong><br />
compounds on one horizontal line. The KMD value remains unique as long as the<br />
class and type <strong>of</strong> compounds remain identical. The Kendrick formation has been<br />
successfully applied to crude oil samples using the CH 2 mass increment. An<br />
example <strong>of</strong> Kendrick is given in Figure 1-6 where part <strong>of</strong> elemental composition <strong>of</strong><br />
a crude oil has been sorted. Not only does 2-D Kendrick mass plots aid in the<br />
assignment <strong>of</strong> unique elemental compositions but they also constitute a chemically<br />
sorted display <strong>of</strong> thousands <strong>of</strong> mass spectral data points whose mass is higher than<br />
~400 Da. In other words once a few related compounds are identified, extension <strong>of</strong><br />
that pattern to higher mass allows for confident elemental composition assignment<br />
<strong>of</strong> ions whose mass is too high to allow a unique assignment based on the<br />
measured mass. 105<br />
25
Introduction<br />
Figure 1-6 Kendrick mass defect vs nominal Kendrick mass for odd mass ions in<br />
crude oil sample. Note the visual vertical separation <strong>of</strong> compound classes (O, O 2 ,<br />
O 3 S) and types (e.g., compounds with different number <strong>of</strong> rings plus double bonds)<br />
based on mass defect and the simultaneous visual horizontal distribution <strong>of</strong> number<br />
<strong>of</strong> CH 2 groups for a given compound class and type. 105<br />
In summary to this part this graphical display affords many advantages like<br />
recognition <strong>of</strong> outlier data (data that fall outside the main pattern) and extension <strong>of</strong><br />
identified pattern to higher mass components. It can be as well an outstanding way<br />
to monitor for example aromatic hydrocarbon content for different refinery process<br />
streams. Biodegradation or weathering processes <strong>of</strong> various complex mixtures <strong>of</strong><br />
hydrocarbons are also easily tracked.<br />
1.4 Light Shredder Waste in Bremen (Project Objectives)<br />
Light shredder waste constitutes a waste fraction, which is obtained from industrial<br />
waste originating from the end <strong>of</strong> life cars, white goods or other electrical<br />
household and industrial items. The light shredder waste fraction is produced by<br />
26
Introduction<br />
mechanical shredding <strong>of</strong> the waste followed by sieving and finally removal <strong>of</strong><br />
magnetic metal contents using large scale magnet. The resulting light shredder<br />
waste fraction was historically directly sent to landfill sites. It is estimated that in<br />
UK around 850,000 t and in Germany around 2 Mt <strong>of</strong> light shredder waste are<br />
generated annually. Due to End <strong>of</strong> Life Vehicle (ELV) and landfill directive, 107<br />
political pressure has mounted to reduce the amount <strong>of</strong> light shredder waste to send<br />
to landfill and develop alternative technologies resulting in the recycling or<br />
reduction <strong>of</strong> light shredder waste.<br />
Figure 1-7 Shredding Plant<br />
The Bremer Entsorgungsbetriebe (BEB) Company has recently developed such an<br />
innovative technology. In a pilot plant light shredder waste is treated biologically<br />
resulting in a dramatic reduction <strong>of</strong> its weight and volume. The waste is sprayed<br />
with water and naturally occurring microorganisms transform the waste at<br />
operating temperatures around 90˚C for a period <strong>of</strong> two to four weeks. The<br />
resulting product is designated for landfill sites. However, before final landfill is<br />
approved the waste material needs to undergo a series <strong>of</strong> analytical investigations<br />
27
Introduction<br />
including determination <strong>of</strong> residual hydrocarbons (HCs), residual polyaromatic<br />
hydrocarbons (PAHs), volatile organic compounds (VOC) and residual heavy<br />
metal contamination. All these analytical quality control (QC) measures are legally<br />
binding before approval for landfill given by the local authorities.<br />
Figure 1-8 Light shredder waste fraction set for biological treatment in a prepared<br />
unit.<br />
For the BEB light shredder waste in particular hydrocarbons contamination is an<br />
issue with large proportions <strong>of</strong> the waste exceeding the legal limit <strong>of</strong> 5 g<br />
hydrocarbons per kg <strong>of</strong> waste. The legally binding analytical procedure for the<br />
determination <strong>of</strong> HCs as defined by the German government is known as KW4<br />
using DIN norm method DIN EN 14039. 108 This method specifies GC based<br />
quantifications <strong>of</strong> HCs. While short and medium chain HCs can be readily<br />
quantified, long chain derivatives result in a UCM in the gas chromatogram (as<br />
shown in Fig.1-9). According to KW 4 the UCM hump is directly and uncritically<br />
integrated and the resulting integral is used as a measure <strong>of</strong> the HC content. Within<br />
the BEB treated light shredder fraction in particular this UCM results in the<br />
deviation from the legal HC limit resulting in a lack <strong>of</strong> approval <strong>of</strong> landfilling.<br />
28
Introduction<br />
uV (x100,000)<br />
Chromatogram<br />
1.75<br />
1.50<br />
1.25<br />
1.00<br />
0.75<br />
0.50<br />
0.25<br />
0.00<br />
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<br />
Figure 1-9 UCM feature <strong>of</strong> hydrocarbon content <strong>of</strong> light shredder waste in GC<br />
The scientific question that needs to address urgently is about the composition <strong>of</strong><br />
the hump. Whether the hump contains only hydrocarbons has remained a matter <strong>of</strong><br />
speculation rather than experimental pro<strong>of</strong> and no detailed information exists on<br />
the actual composition, presumably varying dramatically between samples. If other<br />
non HC components are present the KW 4 does not then determine HCs and<br />
should not be used as legally binding procedure for measuring HC contamination.<br />
The resulting challenge is to develop an alternative method to reliably measure<br />
HCs in shredder waste or any other source <strong>of</strong> heavy long chain HCs.<br />
Resulting from this problem the specific aim <strong>of</strong> the project is to establish the<br />
chemical content <strong>of</strong> the UCM in light shredder waste and once adequately<br />
characterized develop a reliable method for the determination and quantification <strong>of</strong><br />
HCs alternative to KW 4.As well the study aims at evaluating the extent <strong>of</strong> UCM<br />
weathering or biodegradation <strong>of</strong> the waste. The project however seeks to devise<br />
and develop an MS-based methodology capable <strong>of</strong> analysing and characterizing a<br />
complex mixture <strong>of</strong> hydrocarbons within the light shredder waste.<br />
29
Introduction<br />
1.5 Scope and Significance <strong>of</strong> this Work<br />
The aim <strong>of</strong> this work is to develop, adapt and evaluate a new MS-based methodology<br />
for the analysis <strong>of</strong> hydrocarbons. Besides general method development and<br />
validation, the following problems and applications should be addressed<br />
At first task it should be investigated if model hydrocarbons compounds can be<br />
analysed using mass spectrometry. The following step will involve applying the<br />
developed method for the analysis <strong>of</strong> light shredder waste sample. The major goal<br />
is to explore the chemical composition <strong>of</strong> shredder waste. The ability to provide a<br />
quantitative figure about selected hydrocarbons needs to be devised. Validation <strong>of</strong><br />
the method requires testing similar complex hydrocarbon mixtures. The<br />
possibilities to differentiate complex data from each other by using tools available<br />
in literature need to be established. Finally the comparability <strong>of</strong> results obtained by<br />
different spectrometries should be investigated as by their advantages and<br />
limitations.<br />
After this promising scope <strong>of</strong> this study, a general synopsis <strong>of</strong> the study<br />
significance is illustrated in the following description. This thesis describes<br />
investigations undertaken into the nature <strong>of</strong> the UCM <strong>of</strong> light shredder waste. The<br />
results and discussion section comprises six parts. The first two parts involves the<br />
ionisation <strong>of</strong> n-alkanes and other various branched and cyclic hydrocarbons by a<br />
newly developed mass spectrometry method. In the third part the mechanism <strong>of</strong> the<br />
ionisation was discussed. The fourth part comprises the analysis <strong>of</strong> the chemical<br />
content <strong>of</strong> the light shredder waste. This included exploring the molecular level<br />
details <strong>of</strong> the complex mixture. The fifth part investigates the application <strong>of</strong> the<br />
developed methodology into other different complex mixture comprising similar<br />
types <strong>of</strong> hydrocarbons. The final part explains the management <strong>of</strong> the complex<br />
data. The utility <strong>of</strong> graphical tool to help simplify the spectral data was<br />
demonstrated.<br />
30
Experimental<br />
2 Experimental<br />
2.1 Chemicals and Model Standards<br />
a) Standard low mass n-alkanes such as Octane, nonane, decane, undecane,<br />
dodecane, tridecane, tetradecane, pentadecane and hexadecane were purchased<br />
from Sigma Aldrich (Bremen, Germany). Higher mass n-alkanes like octadecane,<br />
eicosane, henicosane, docosane, tricosane, tetracosane, pentacosane, hexacosane,<br />
octacosane, dotricontane, hexatriacontane, tetracontane, dotetracontane,<br />
tetratetracontane, octatetracontane, pentacontane, tetrapentacontane and<br />
hexacontane all <strong>of</strong> analytical grade, were purchased from Sigma Aldrich.<br />
b) Different model mixtures <strong>of</strong> n-alkanes were also purchased from the same<br />
company.<br />
i) C7-C40 Saturated Alkanes (1 mg/ml in hexane)<br />
ii) C8-C40 Alkanes Calibration Standard (500 µg/ml in dichloromethane)<br />
iii) C10, C20-C40 Alkane Standard Mixture (50 mg/l in n-heptane)<br />
iv) C21-C40 Alkane Standard Solution (40 mh/l in toluene)<br />
v) C12-C60 Quantitative Linearity Standard (0.01 % (w/w) in cyclohexane)<br />
vi) n-Paraffin Mix C18, C20, C22, C24 Analytical Standard (2 % (w/w) in octane)<br />
c) Other deuterated standards such as deuterated tetracosane [(D-24), (C 24 D 50 )] and<br />
deuterated dotriacontane [(D-32), (C 32 D 66 )]<br />
d) Other individual standards were purchased from Chiron Company (Chiron.no).<br />
These standards were 2,6,10,14-tetramethyl nonadecane, 2,6,10,14,18-pentamethyl<br />
heneicosane, n-tetradecyl cyclohexane, n-octadecyl cyclohexane, n-octyl benzene,<br />
n-nonyl benzene, n-tetradecyl benzene, and n-octadecyl benzene, each in 1 mg/ml<br />
isooctane solution. 5-α-Cholestane, squalane, squalene, phytane, and 1-phenyl<br />
decane all <strong>of</strong> analytical grade were also purchased from Sigma Aldrich.<br />
31
Experimental<br />
e) Other model mixture purchased also from Aldrich Company is the<br />
polychlorinated biphenyls (PCBs), PCB Congener Mix 1. Decachlorobiphenyl<br />
(C 12 Cl 10 ) was purchased from the same company.<br />
f) The list <strong>of</strong> solvents and derivatisation agents include n-pentane, n-heptane,<br />
chlor<strong>of</strong>orm, isooctane, methanol, dichloromethane and toluene. Deuterium oxide<br />
(D 2 O), silver trifluoroacetate (CF 3 COOAg) and chromium trioxide (CrO 3 ) were<br />
also supplied. Last, the purification material florisil (100-200 mesh) was purchased<br />
from Aldrich Company as well.<br />
2.2 Preparation <strong>of</strong> Samples<br />
2.2.1 Alkane Standards and Shredder Waste Samples Preparation<br />
Preparation <strong>of</strong> model standards was done by dissolving or diluting a known<br />
quantity <strong>of</strong> separate alkanes. The prepared solution was always diluted prior to<br />
injection to meet the concentration needed for mass spectrometry around mM<br />
concentration. Model mixtures <strong>of</strong> n-alkanes was prepared by mixing equimolar<br />
ratios <strong>of</strong> the separate alkane standards. Standard model mixture purchased from<br />
Sigma Aldrich company were diluted to mM concentration before measurement.<br />
For example 20 µl were taken from C7-C40 alkane standard (1mg/l) and diluted<br />
into a 1 ml <strong>of</strong> n-heptane solvent before injection.<br />
Preparation <strong>of</strong> light shredder waste samples was achieved by few but important<br />
steps. Most <strong>of</strong> the common analytical steps are related to the separation and<br />
purification <strong>of</strong> analytes <strong>of</strong> interest from a sample matrix prior to their<br />
measurement. After frequent treatments <strong>of</strong> huge amounts <strong>of</strong> upcoming light<br />
shredder waste in the BEB Company, samples are cropped for analytical<br />
investigation. Although the shredder waste itself is homogenous by nature,<br />
samples are taken from different locations <strong>of</strong> the same treated shredder waste<br />
portion. In our laboratory, the sample was dried and sieved by a normal sieve to<br />
get rid <strong>of</strong> bulk pieces <strong>of</strong> plastic, small wires and others that are removed. Next the<br />
sieved waste are grounded into fine particles (around µm) by a Fritsch Mill.<br />
32
Experimental<br />
After that, 20 g <strong>of</strong> waste were extracted by 20 ml <strong>of</strong> n-heptane and 40 ml <strong>of</strong><br />
acetone inside an automatic soxhlet extractor for 6 hours. The resulting brown<br />
solution then is washed with water (15 ml) to remove the acetone content. The n-<br />
heptane solution is cleaned by a column (d=1cm) using florisil (2g) and sodium<br />
sulfate (2g). The filtrate was dried using rota evaporation. Then 5 ml <strong>of</strong> n-heptane<br />
was added to the extract. For injection into MS, 1 ml <strong>of</strong> the prepared heptane<br />
solution is used. Sometimes diluted solutions were prepared before infusion.<br />
Similarly this preparation method was applied to treated waste samples on small<br />
scale reactor in Hochschule Bremerhaven. Our project partners probed aeration<br />
and hydrothermal conditions as seen in Table 2.1 to optimize degradation process.<br />
Table 2.1 Different shredder waste samples treated under different conditions<br />
Sample<br />
Date<br />
Conditions<br />
Temp. Air flow Input water<br />
Operating time<br />
I 1 2010-12-14<br />
1.<br />
R 1.1 2010-12-14 60 °C 1,5 L/h 120 mL/d 22 days<br />
R 2.1 2010-12-14 60 °C 1,5 L/h 120 mL/d 22 days<br />
I 2 2010-12-22<br />
2.<br />
R 1.2 2010-12-22 60 °C 1,5 L/h 120 mL/d 20 days<br />
R 2.2 2010-12-22 60 °C 3,0 L/h 120 mL/d 20 days<br />
R 3.2 2010-12-22 60 °C 3,0 L/h 120 mL/d 20 days<br />
I 3 2011-04-02<br />
3.<br />
R 1.3 2011-03-16 60 °C 3,0 L/h 120 mL/d 31 days<br />
R 2.3 2011-03-16 60 °C 3,0 L/h 120 mL/d 22 days<br />
R 3.3 2011-03-16 60 °C 3,0 L/h 120 mL/d 14 days<br />
I 4 2011-04-14<br />
4.<br />
R 1.4 2011-04-21 60 °C 3,0 L/h 120 mL/d 22 days<br />
R 2.4 2011-04-21 60 °C 3,0L/h 120 mL/d 22 days<br />
R 3.4 2011-04-21 60 °C 3,0 L/h 120 mL/d 22 days<br />
I 3 2011-06-14<br />
5.<br />
R 1.3 2011-07-04 70 °C 3,0 L/h 120 mL/d 22 days<br />
R 2.3 2011-07-04 70 °C 3,0 L/h 120 mL/d 22 days<br />
R 3.3 2011-07-04 70 °C 3,0 L/h 120 mL/d 22 days<br />
33
Experimental<br />
2.2.2 Preparation <strong>of</strong> Oxidation Products from Shredder Extract<br />
The waste extract was subjected to oxidative degradation using CrO 3 . Oxidation<br />
<strong>of</strong> the waste complex mixture was performed at 70°C for 3 h in a CrO 3 /glacial<br />
acetic acid mixture. Thus, waste extract (100-200 mg) was added to acetic acid (15<br />
ml) in two-necked round bottom flask (25 ml) equipped with a reflux condenser.<br />
The solution was heated to about 70°C with stirring (10 minutes) before adding the<br />
oxidant (10:1 molar ratio, assuming 352 g mol -1 for waste extract). After 3 hours,<br />
the solution is cooled, transferred into another flask where water (10 ml) and<br />
dichloromethane (15 ml) were added. Extraction by similar volumes <strong>of</strong> DCM<br />
again recovers the oxidized products. The extract was concentrated to dryness by<br />
rota-evaporation.<br />
2.3 MS Operating Conditions<br />
The present study was carried out with a Bruker micrOTOF Focus MS and a<br />
Bruker HCT ultra Iontrap MS instruments equipped with an electrospray ionisation<br />
(ESI) source or with an atmospheric pressure chemical ionisation (APCI). In the<br />
case <strong>of</strong> ESI source, ions were generated externally by a microelectrospray source<br />
under positive or negative ion mode conditions and samples were delivered by a<br />
direct infusion syringe pump. Calibration was achieved with 10 mL <strong>of</strong> 0.1 M<br />
sodium formate Cluster solution. The infusion pump line was set at 180 µl/h<br />
suitable for ESI source. The applied settings <strong>of</strong> the optimised methods varied<br />
slightly but the general conditions are : nebuliser <strong>of</strong> 0.5 Bar, a dry gas <strong>of</strong> 5 L/min,<br />
a dry heater <strong>of</strong> 180 ˚C, set target mass start at 50 m/z and set target mass end at<br />
1000 m/z.<br />
However the main technique in this study that has been hugely employed is the<br />
APCI-TOF-MS. The ionisation technique has already been discussed in details in<br />
the introduction. <strong>Mass</strong> spectra were acquired by a high resolution micrOTOF<br />
Focus mass spectrometer equipped with APCI (Bruker Daltonics, Bremen,<br />
Germany). Separate analytes were dissolved generally in n-heptane. Direct<br />
infusion <strong>of</strong> the sample was assisted by an electric feeder supplying a convenient<br />
34
Experimental<br />
flow rate <strong>of</strong> 400-500 µl/hr. MS operating conditions were as follows: nebulizer<br />
pressure <strong>of</strong> 1.6 Bar, a corona discharge <strong>of</strong> 6000 nA, a hexapole RF <strong>of</strong> 200 Vpp, a<br />
dry gas <strong>of</strong> 6 L/min, a drying temperature <strong>of</strong> 200 ˚C and a vaporizer temperature <strong>of</strong><br />
450 ˚C. Calibration <strong>of</strong> APCI was achieved by the general APCI/APPI calibrant for<br />
the desired mass range. However calibration was also achieved by C7-C40<br />
standard as will be discussed in details later on.<br />
Fragmentation patterns were obtained by an Ion trap mass spectrometer fitted with<br />
the APCI source (Bruker Daltonics HCT Ultra, Bremen, Germany) operating in a<br />
manual MS n mode to obtain as desired MS 2 and MS 3 fragmented ions. Alkane<br />
method settings in Iontrap included nitrogen as source gas and helium as collision<br />
gas with corona discharge <strong>of</strong> +4000 nA, a nebulizer gas <strong>of</strong> 30 Bar, a drying<br />
temperature <strong>of</strong> 200 ˚C, a vaporizer temperature <strong>of</strong> 450 ˚C and a compound stability<br />
<strong>of</strong> 100% within a mass range <strong>of</strong> m/z 50-1000. Few parameters like collision energy<br />
amplitude and peak width were adjusted to enhance fragmentation spectra.<br />
35
Experimental<br />
2.4 Graphical Presentation <strong>of</strong> the Used Instruments<br />
Light Shredder Waste<br />
Fritsch Mill<br />
BUCHI Soxhlet Extractor<br />
MicrOTOF MS<br />
Iontrap MS<br />
Figure 2-1 Instruments used in the study<br />
36
Results and Discussion<br />
3 Results and Discussion<br />
3.1 APCI-TOF-MS <strong>of</strong> Standard n-Alkanes<br />
Given that the study <strong>of</strong> a complex hydrocarbon mixture should rely on the study <strong>of</strong><br />
separate hydrocarbon standards in a certain technique, the behaviour <strong>of</strong> different<br />
standard n-alkanes under APCI-TOF-MS conditions in the positive ion mode was<br />
examined. The analytes <strong>of</strong> a series <strong>of</strong> standard n-alkanes from dodecane (C 12 H 26 )<br />
to tetracontane (C 40 H 82 ) were injected into the MS instrument as direct infusions in<br />
n-heptane. Equimolar model mixtures <strong>of</strong> n-alkanes were also prepared and<br />
analysed by an optimised APCI-TOF-MS methodology. The MS settings<br />
especially the nitrogen flow rate (nebuliser pressure) and corona discharge were<br />
probed to obtain a stable generation <strong>of</strong> ions within the APCI source. In addition to<br />
that the flow rate <strong>of</strong> sample injection appeared to have a significant role in the<br />
analysis. At first an external HPLC pump was used. However, the optimum flow<br />
rate was found to be 400-500 µl/hr supplied by an electric feeder only. The best<br />
concentration was found to be the more diluted. Generally a solution <strong>of</strong> 10 -3 to 10 -4<br />
M was infused. After optimising concentration and MS conditions, measurements<br />
<strong>of</strong> separate and mixtures was launched. It was noticed that a monohydrated (M-<br />
3) + H 2 O ion, was the only intact ion corresponding to each individually injected n-<br />
alkanes (up to C20). For example figures 3-1 and 3-2 show the ions at m/z 185 and<br />
m/z 199 corresponding to dodecane (C12) and tridecane (C13) respectively. These<br />
ions were produced as intact stable monohydrated ions under positive APCI<br />
conditions using n-heptane as infusion solvent. Next a model mixture <strong>of</strong> six model<br />
n-alkanes (all in equimolar ratios) was analysed by APCI-TOF-MS using n-<br />
heptane. The mass spectrum in figure 3-3 shows monohydrated (M-3) + H 2 O ions<br />
for all six analytes <strong>of</strong> C10, C12, C13, C14, C15 and C16 appearing with minor<br />
fragmentation. While the relative abundances <strong>of</strong> these ions don’t exactly match the<br />
relative molar concentrations, all analytes were successfully detected in a single<br />
37
Results and Discussion<br />
experiment. High mass n-alkanes in contrast (C20-C40) formed additionally M •+ ,<br />
(M-1) + and other low intensity monohydrated species (M-1) + H 2 O. For the range <strong>of</strong><br />
(C32-C40) some low intensity species that are formed <strong>of</strong> a composition <strong>of</strong> (M-3) +<br />
were observed (Table 3.1). Figure 3-4 shows the ionisation <strong>of</strong> hexatriacontane<br />
(C36) where (M-3) + , (M-1) + and (M-3) + H 2 O appeared at m/z 503, m/z 505 and m/z<br />
521 respectively. These monohydrated and composite ions were further<br />
demonstrated in a model mixture <strong>of</strong> dotriacontane (C32), C36 and tetracontane<br />
(C40) in figure 3-5.<br />
Intens.<br />
[%]<br />
100<br />
185.2<br />
+MS<br />
80<br />
60<br />
40<br />
20<br />
0<br />
123.1 137.1 149.0<br />
163.1<br />
199.2<br />
225.2<br />
216.2<br />
241.3<br />
263.2<br />
285.3 297.3<br />
100 125 150 175 200 225 250 275 300 m/z<br />
Figure 3-1 APCI mass spectrum in positive ion mode <strong>of</strong> dodecane (C 12 H 26 )<br />
showing (M-3) + H 2 O ion as product ion at m/z 185.2<br />
Intens.<br />
[%]<br />
100<br />
199.2<br />
+MS<br />
80<br />
60<br />
40<br />
20<br />
0<br />
123.1 137.1 149.1 185.2<br />
163.1<br />
213.2 227.2 241.3 257.3 285.3 297.3 311.3<br />
100 125 150 175 200 225 250 275 300 m/z<br />
Figure 3-2 APCI mass spectrum in positive ion mode <strong>of</strong> tridecane (C 13 H 28 )<br />
showing (M-3) + H 2 O ion as product ion at m/z 199.2<br />
38
Results and Discussion<br />
Intens.<br />
[%]<br />
C15<br />
227.2<br />
+MS<br />
80<br />
60<br />
40<br />
20<br />
0<br />
C10<br />
135.1 149.1 157.2 163.1 177.2<br />
C12<br />
185.2<br />
191.2<br />
C13<br />
199.2<br />
213.2<br />
241.3<br />
253.1 263.2<br />
140 160 180 200 220 240 260 m/z<br />
C14<br />
C16<br />
Figure 3-3 APCI mass spectrum in positive ion mode <strong>of</strong> a mixture containing<br />
decanes (C 10 H 22 ), dodecane (C 12 H 26 ), tridecane (C 13 H 28 ), tetradecane (C 14 H 30 ),<br />
pentadecane (C 15 H 32 ) and hexadecane (C 16 H 34 )<br />
showing (M-3) + H 2 O ions at m/z<br />
157.2, 185.2, 199.2, 213.2, 227.2 and 241.3 respectively.<br />
Intens.<br />
[%]<br />
100<br />
(M-1) +<br />
505.6<br />
+MS<br />
80<br />
60<br />
(M-3) + H 2 O<br />
521.6<br />
40<br />
20<br />
0<br />
257.2<br />
285.3<br />
409.4<br />
309.3 353.4<br />
(M-3) +<br />
465.5<br />
597.6<br />
250 300 350 400 450 500 550 600 650 m/z<br />
663.4<br />
Figure 3-4 APCI mass spectrum in positive ion mode <strong>of</strong> hexatricontane (C 36 H 74 )<br />
showing an (M-1) + and (M-3) + H 2 O at m/z 505.6 and 521.6 respectively<br />
39
Results and Discussion<br />
Intens.<br />
[%]<br />
50<br />
505.6 521.6<br />
+MS<br />
40<br />
30<br />
20<br />
449.5 465.5<br />
561.6 577.6<br />
10<br />
0<br />
535.5<br />
479.5<br />
407.4 421.4 435.5<br />
493.3<br />
549.6<br />
591.6<br />
617.7<br />
425 450 475 500 525 550 575 600 m/z<br />
Figure 3-5 APCI mass spectrum in positive ion mode <strong>of</strong> dotriacontane (C 32 H 64 ),<br />
hexatricontane (C 36 H 74 ) and tetracontane (C 40 H 82 )<br />
These reported measurement were my starting steps before I tried to optimise<br />
solvent. These measurements were absolutely considered novel hits because it is<br />
well known that n-alkanes are difficult to be ionised. As far as the effect <strong>of</strong> other<br />
solvents over the ionisation process in APCI was concerned, two further<br />
experiments were performed. Two solutions <strong>of</strong> model n-alkane mixture <strong>of</strong> the<br />
higher mass range (C20 to C40) were prepared and injected as direct infusions in<br />
n-pentane and chlor<strong>of</strong>orm as the APCI reagent. None <strong>of</strong> the two solvents afforded<br />
better results compared to those with n-heptane. Figure 3-6 shows the mass spectra<br />
<strong>of</strong> few analytes in the aforementioned range in n-pentane. n-Pentane was seen to<br />
enhance fragmentation potential <strong>of</strong> alkanes by possibly increasing the efficiency <strong>of</strong><br />
collisions <strong>of</strong> reagent ions with the neutral n-alkane analytes inside the APCI<br />
source. To this end, the appearance <strong>of</strong> such n-alkane species is in agreement with<br />
the results summarized in the introduction in particular the study performed by<br />
Bell et al.. 78 The latter’s study <strong>of</strong> a set <strong>of</strong> low mass n- alkanes produced (M-1) + ,<br />
(M-3) + and (M-3) + H 2 O. The results <strong>of</strong> individual model n-alkanes were<br />
summarised in table 3.1.<br />
40
Results and Discussion<br />
Intens.<br />
[%]<br />
100<br />
80<br />
60<br />
40<br />
20<br />
0<br />
+MS<br />
449.5<br />
561.6<br />
491.6<br />
243.0<br />
313.3<br />
281.3 341.3 365.4 577.6 603.7<br />
250 300 350 400 450 500 550 600 m/z<br />
Figure 3-6 APCI mass spectrum <strong>of</strong> model mixture <strong>of</strong> n-alkanes injected using n-<br />
pentane<br />
Table 3.1 Summary <strong>of</strong> APCI data <strong>of</strong> n-alkanes<br />
Alkane M ∙+ (M-1) + (M-3) + (M-3) + H 2 O<br />
C 12 N Y* N Y<br />
C 13 N Y* N Y<br />
C 14 N Y* N Y<br />
C 15 N Y* N Y<br />
C 16 N Y* N Y<br />
C 18 N Y* N Y<br />
C 20 Y Y N Y<br />
C 21 Y Y N Y<br />
C 22 Y Y N Y<br />
C 23 Y Y* N Y<br />
C 24 Y Y N Y<br />
C 26 Y* Y N Y*<br />
C 28 Y Y N Y*<br />
C 32 Y Y Y* Y<br />
C 36 Y Y Y* Y<br />
C 40 Y Y Y* Y<br />
*Species with low Intensity<br />
Further direct infusion experiments were performed using standard mixtures <strong>of</strong><br />
alternative composition such as, C7-C40 and C8-C40,<br />
C21-C40 n-alkane<br />
standards using n-heptane as the APCI reagent. Such experiments yielded a<br />
41
Results and Discussion<br />
common feature regarding the n-alkanes’ detection. Each <strong>of</strong> these saturated n-<br />
alkanes were depicted instantly as (M-1) + molecular species which was<br />
accompanied by low intensity M •+ ions. Figure 3-7 shows an APCI-MS spectrum<br />
<strong>of</strong> the C7-C40 standard. This clearly emphasized that each single (M-1) + was<br />
strictly related to its corresponding n-alkane precursor within the standard mixture.<br />
Although the relative product ion abundances do not exactly match the relative<br />
molar concentration <strong>of</strong> each component in the C7-C40 mixture, they are still<br />
remarkably close when considering the fact that the volatilities <strong>of</strong> the compounds<br />
vary widely. Other n-paraffin mixtures were also tested by the same method.<br />
Figure 3-8 shows the mass spectrum <strong>of</strong> n-paraffin mixture containing C18, C20,<br />
C22 and C24 detected as m/z 269, m/z 297, m/z 325 and m/z 353 respectively. In all<br />
cases the ideal behavior <strong>of</strong> these analytes is mostly attributed to the proper solvent<br />
selection, purity <strong>of</strong> reference standards and careful tuning <strong>of</strong> the APCI method<br />
settings. In fact ionization was achieved without the use <strong>of</strong> any additional additives<br />
and without any fragmentation. The data demonstrates that molecules <strong>of</strong> various<br />
volatilities (boiling points ranging from 174 °C <strong>of</strong> C10 to 525 °C <strong>of</strong> tetracontane)<br />
can be efficiently ionised by APCI and accurately mass analysed by TOF MS.<br />
Intens.<br />
[%]<br />
100<br />
+MS<br />
561.6<br />
547.6<br />
80<br />
533.6<br />
505.6<br />
60<br />
449.5<br />
477.5<br />
40<br />
20<br />
253.3 281.3 337.4<br />
239.3<br />
379.4<br />
407.5<br />
435.5<br />
0<br />
211.2<br />
200 250 300 350 400 450 500 550 m/z<br />
Figure 3-7 APCI-MS spectrum in positive ion mode <strong>of</strong> C7-C40 showing (M-1) +<br />
ions <strong>of</strong> n-alkanes<br />
42
Results and Discussion<br />
Intens.<br />
[%]<br />
325.4<br />
C22<br />
+MS<br />
80<br />
60<br />
40<br />
20<br />
0<br />
C24<br />
C18 C20<br />
353.4<br />
269.3<br />
297.3<br />
339.3 375.4<br />
240 260 280 300 320 340 360 380 400 m/z<br />
Figure 3-8 APCI mass spectrum <strong>of</strong> n-paraffin mixture<br />
Overall the mass spectrum is considerably simpler than that provided by EI or CI.<br />
The production <strong>of</strong> intact abundant stable n-alkane ions that are representative for<br />
their n-alkane precursor neutral analytes is the utmost achievement in my study.<br />
For many years, mass spectrometry was considered incapable to analyse alkane<br />
species. By this careful ionisation study <strong>of</strong> n-alkanes, the analyses <strong>of</strong> the latters are<br />
no more out <strong>of</strong> reach. This novel approach enabled to extend the applicability <strong>of</strong><br />
reactive APCI-MS towards n-alkanes. The next step was to apply this unique<br />
methodology to other types <strong>of</strong> hydrocarbons whether separate or model mixtures.<br />
The method was successfully applied to a wider range <strong>of</strong> n-alkanes such as for<br />
C12-C60 n-alkane standard mixture as illustrated in Figure 3-9.<br />
Intens.<br />
[%]<br />
100<br />
617.7<br />
701.8<br />
+MS<br />
80<br />
60<br />
505.6<br />
561.6<br />
663.4<br />
40<br />
20<br />
0<br />
242.9<br />
219.2<br />
449.5<br />
338.3 421.5<br />
283.3 309.3<br />
365.4 393.4 523.6 543.6 599.6 647.5<br />
487.5<br />
579.6<br />
633.7 717.8 739.8 841.9<br />
200 300 400 500 600 700 800 m/z<br />
Figure 3-9 APCI mass spectrum <strong>of</strong> C12-C60 alkane standard<br />
43
Results and Discussion<br />
3.2 APCI-TOF-MS <strong>of</strong> a Variety <strong>of</strong> Hydrocarbons<br />
Encouraged by the success in controlling the ionisation process <strong>of</strong> n-alkanes upon<br />
APCI, we have attempted to examine a wide variety <strong>of</strong> hydrocarbons. To probe the<br />
APCI capability, different standards <strong>of</strong> non-polar hydrocarbons were investigated<br />
under positive APCI-TOF-MS conditions. The compounds were chosen due to<br />
previous literature reports stating that ionization using APCI in the absence <strong>of</strong> an<br />
additive failed to produce molecular or pseudomolecular ions. Therefore these<br />
compounds must be considered a benchmark for difficult analytes. The ionisation<br />
<strong>of</strong> a whole set <strong>of</strong> model standards including various non-polar hydrocarbons was<br />
studied. Model compounds were divided into three groups as considering solvent<br />
requirements and molecular weight distributions. The first group involved the eight<br />
Chiron standards which were diluted in isooctane before injection. Phytane, n-<br />
decyl benzene and 5-α-cholestane were prepared in n-heptane and were also<br />
injected together as a second model mixture. The last group consisted <strong>of</strong> the<br />
remaining high molecular weight (MW) alkanes which were prepared in n-heptane<br />
prior to infusion. All analytes in the three groups were easily evaporated by APCI<br />
heating chamber which reached up to 450 ˚C.<br />
Figure 3-11 shows the spectrum <strong>of</strong> the eight Chiron hydrocarbon mixture. All<br />
analytes in the mixture are in equal molar ratios. Initial inspection <strong>of</strong> the spectrum<br />
shows that each analyte was impressively ionized and detected as intact stable [M-<br />
H] + ion with minor or no fragmentation as obvious in Figure 3-11. This ion was<br />
shown to be accompanied by another radical molecular cation M •+ . The intensity <strong>of</strong><br />
this molecular ion appears to be directly related to the intensity <strong>of</strong> the major ion,<br />
[M-H] + , regardless <strong>of</strong> the structure <strong>of</strong> the studied compounds. Figure 3-11 also<br />
demonstrates that the relative abundances measured for the [M-H] + ions <strong>of</strong> these<br />
compounds are close to each other except for n-octadecyl benzene (10). Despite<br />
the fact that those eight analytes are different in terms <strong>of</strong> volatility, structure and<br />
composition, their product ions have close relative abundances that match their<br />
relative molar concentrations. N-decyl benzene, phytane and 5-α-cholestane were<br />
measured together.<br />
44
Results and Discussion<br />
Figure 3-10 Structures <strong>of</strong> various hydrocarbons investigated by APCI-TOF-MS<br />
45
Results and Discussion<br />
These compounds tend to lose hydrogen producing m/z 217, m/z 281 and m/z 371<br />
respectively as shown in figure 3-12. A molecular ion was as well formed in<br />
addition to the dominant [M-H] + ion for each <strong>of</strong> the three hydrocarbons. 5-α-<br />
Cholestane was previously measured by the group <strong>of</strong> kenttamaa where no ions<br />
were detected under positive APCI conditions according to their experimental<br />
results. 96<br />
Intens.<br />
[%]<br />
100<br />
10<br />
329.3<br />
+MS<br />
80<br />
60<br />
40<br />
20<br />
0<br />
6<br />
7<br />
203.2<br />
273.3<br />
189.2<br />
279.3<br />
323.4<br />
295.3<br />
225.3 242.9 257.2<br />
315.3<br />
183.2<br />
9<br />
4 5<br />
2 3<br />
180 200 220 240 260 280 300 320 340 360 m/z<br />
335.4<br />
345.3<br />
365.4<br />
Figure 3-11 APCI spectrum <strong>of</strong> the eight Chiron hydrocarbon mixture (for<br />
structures see figure 3-10)<br />
Overall it was observed that the relative product ion abundances <strong>of</strong> the analytes<br />
(equimolar solution at 0.2 mM) were very close to each other. Further direct<br />
infusion experiments were performed using a mixture <strong>of</strong> high MW n-alkanes (C50-<br />
C60 mass range) that were dissolved in n-heptane. Examination <strong>of</strong> separate and<br />
model mixture <strong>of</strong> these n-alkanes demonstrated that the same ionisation pattern<br />
was shown. The APCI mass spectrum comprised [M-H] + ions that are shown in<br />
figure 3-13. Each gas phase [M-H] + ion was, similar to the previous hydrocarbons<br />
in the other groups, accompanied by its molecular ion M •+ . For example<br />
pentacontane produced a stable m/z 701.8 as intact ion conforming to [C 50 H 101 ] +<br />
ion, this ion was accompanied by a lower-intensity M •+ m/z 702.8 conforming to<br />
[C 50 H 102 ] •+ . This pattern <strong>of</strong> ionisation produced for all <strong>of</strong> the examined high mass<br />
n-alkanes wasn’t surprising as this is consistent with our previous investigation <strong>of</strong><br />
n-alkanes’ behaviour under APCI-TOF-MS.<br />
46
Results and Discussion<br />
Within all <strong>of</strong> the three mass spectra (Figures 3-11, 3-12 and 3-13), the major<br />
product ion <strong>of</strong> each analyte was found characteristic for the original precursor<br />
hydrocarbon within the three model mixtures. All yielded a unique [M-H] +<br />
ionisation pattern. Also figure 3-14 demonstrates the production <strong>of</strong> the same<br />
product ion when the three groups were added together.<br />
Again the ideal behaviour <strong>of</strong> these analytes is mostly attributed to the optimised<br />
APCI developed methodology. A minor change <strong>of</strong> any <strong>of</strong> the method parameters<br />
can hugely affect the product ion generation process. The examined seventeen<br />
compounds presented model compounds <strong>of</strong> linear, branched and cyclic<br />
hydrocarbons. Table 3.2 presents all the hydrocarbons examined in this experiment<br />
showing their unique product ion distribution. Some <strong>of</strong> these hydrocarbons are<br />
representative or similar to components in real life complex mixtures such as<br />
petroleum mixtures. Since n-alkanes in the previous section and the other<br />
hydrocarbons in the current section have been ionised by a unique [M-H] +<br />
ionisation, an insight about the mechanism for the formation <strong>of</strong> this major ion and<br />
other ions will be discussed in the next section.<br />
Table 3.2 Ions produced <strong>of</strong> model hydrocarbon compounds<br />
# Analyte MW Product Ion<br />
1 2,6,10,14-Tetramethyl hexadecane 282 M-H +<br />
2 2,6,10,14-Tetramethyl nonadecane 324 M-H +<br />
3 2,6,10,14,18-Pentamethyl heneicosane 366 M-H +<br />
4 n-Tetradecyl cyclohexane 280 M-H +<br />
5 n-Octadecyl cyclohexane 336 M-H +<br />
6 n-Octyl benzene 190 M-H +<br />
7 n-Nonyl benzene 204 M-H +<br />
8 n-Decyl benzene 218 M-H +<br />
9 n-Tetradecyl benzene 274 M-H +<br />
10 n-Octadecyl benzene 330 M-H +<br />
11 5-α-Cholestane 372 M-H +<br />
12 Dotetracontane 590 M-H +<br />
13 Tetratetracontane 618 M-H +<br />
14 Octatetracontane 674 M-H +<br />
15 Pentacontane 702 M-H +<br />
16 Tetrapentacontane 758 M-H +<br />
17 Hexacontane 842 M-H +<br />
47
Results and Discussion<br />
Intens.<br />
[%]<br />
100<br />
+MS<br />
80<br />
60<br />
40<br />
8<br />
1<br />
217.2<br />
281.3<br />
20<br />
183.2 197.2 225.3<br />
239.3 261.3 295.3 310.3 329.3<br />
0<br />
175 200 225 250 275 300 325 350 375 400m/z<br />
Figure 3-12 APCI mass spectrum <strong>of</strong> n-decyl benzene, phytane and 5-α-cholestane<br />
11<br />
371.4<br />
Intens.<br />
[%]<br />
100<br />
80<br />
589.7<br />
12<br />
15<br />
701.8<br />
+MS<br />
60<br />
40<br />
20<br />
0<br />
547.6<br />
13<br />
617.7 647.5<br />
14<br />
663.5<br />
673.8<br />
757.8<br />
739.8<br />
550 600 650 700 750 800 850 m/z<br />
16<br />
17<br />
841.9<br />
Figure 3-13 APCI <strong>of</strong> high mass n-alkanes<br />
Intens.<br />
[%]<br />
100<br />
411.4<br />
663.5<br />
+MS<br />
80<br />
329.3<br />
60<br />
40<br />
189.2<br />
217.2<br />
273.3<br />
371.4<br />
449.4<br />
520.9<br />
589.7<br />
701.8<br />
20<br />
0<br />
551.5 617.7<br />
757.8 841.9<br />
200 300 400 500 600 700 800 m/z<br />
Figure 3-14 Total APCI mass spectrum in <strong>of</strong> the mixture <strong>of</strong> seventeen compounds<br />
(see table 3.2)<br />
48
Results and Discussion<br />
3.3 Pathway <strong>of</strong> Ionisation <strong>of</strong> Hydrocarbon Standards under APCI<br />
Conditions<br />
Representative alkanes and the other hydrocarbon standards produced<br />
predominantly (M-1) + as shown within the previous results. The results include as<br />
well (M-3) + and (M-3) + H 2 O to the extent that in many cases, these ions were seen<br />
in greater abundances than the (M-1) + species. (M-1) + ions were reported to be<br />
formed by the studies <strong>of</strong> Carroll 109 et al. and Bell et al. 78 The latter has also shown<br />
the importance <strong>of</strong> (M-1) + , (M-3) + and (M-3) + H 2 O ions in the APCI mass spectra <strong>of</strong><br />
alkanes generated by a corona discharge and monitored by ion mobilities. 78 (M-1) +<br />
is also a common feature <strong>of</strong> the APCI mass spectra in air plasma <strong>of</strong><br />
hydrocarbons. 79 (M-1) + is the characteristic product ion in chemical ionisation<br />
experiments <strong>of</strong> alkanes run with interplay <strong>of</strong> reagent gases such as N 2 , O 2 and H 2 O.<br />
However under the conditions <strong>of</strong> our experiment, atmospheric pressure nitrogen<br />
plasma seems to be a focused complex environment using n-heptane as infusion<br />
solvent. (Figure 3-15). With very low water content within the nitrogen reagent gas<br />
stream, the radical cation <strong>of</strong> nitrogen (N •+ 2 ) is the major reagent ion available for<br />
performing ionisation <strong>of</strong> evaporated analytes <strong>of</strong> alkanes or other hydrocarbons that<br />
were tested in this study. Based on the experimental results obtained in this study<br />
and on available literature, we suggested a general pathway that accounts for the<br />
formation <strong>of</strong> (M-1) + and (M-3) + H 2 O ions. It is suggested that the route <strong>of</strong><br />
formation <strong>of</strong> ions observed within atmospheric pressure and generated by corona<br />
discharge under nitrogen is shown in Scheme 2. A structural route <strong>of</strong> ionisation<br />
mechanism is also provided by scheme 3. This proposed ionisation comprises<br />
formal hydride abstraction particularly by N •+ 2 as the lone reactive species thought<br />
to be responsible for the production <strong>of</strong> (M-1) + ions. The high frequency <strong>of</strong> collision<br />
<strong>of</strong> N •+ 2 with the neutral hydrocarbon analytes resulted in enhanced ionisation and<br />
thermalisation <strong>of</strong> the analyte ions. As far as the molecular ion generation is<br />
concerned, a charge transfer reaction is most likely responsible in this case.<br />
The suggestion is also corporated by data from Kolakowski where (M-1) + ions<br />
were observed under chemical ionization (CI) experiments <strong>of</strong> alkanes. 89 (M-3) +<br />
49
Results and Discussion<br />
Ions were proposed by Bell to form when alkane cations spontaneously lose H 2 to<br />
form ions <strong>of</strong> an allyl cation structure (M (M-1) + H 2 elimination). Alternatively<br />
a hydrogen abstraction by any reactive nitrogen species present after discharge to<br />
produce (NH) 2 species can be envisaged. The allyl cations, as highly reactive<br />
electrophiles, can add water present in the gas flow to produce protonated allylic<br />
alcohol ions.<br />
Figure 3-15 Suggested graphical scheme for ionisation mechanism <strong>of</strong> hydrocarbon<br />
upon APCI<br />
Scheme 2. Suggested routes for the formation <strong>of</strong> (M-H) + and (M-3H) + H 2 O in<br />
APCI-MS.<br />
In an attempt to support the hypothesis <strong>of</strong> intermolecular water addition to allyl<br />
cations in the gas phase, deuterium oxide was added to individual alkanes for<br />
example, tetracontane (C40). As expected the resulting ions could be characterised<br />
as deuterated species (M-3) + D 2 O using the same MS conditions. Figure 3-16<br />
shows the mass spectrum after addition <strong>of</strong> D 2 O to n-tetracontane. Also we have<br />
also measured deuterated standards <strong>of</strong> n-alkane.<br />
50
Results and Discussion<br />
Scheme 3. Suggested structural route for the formation <strong>of</strong> (M-H) +<br />
3H) + H 2 O in APCI-MS.<br />
and (M-<br />
The results for deuterated compounds paralleled those obtained for nondeuterated<br />
equivalents. Figure 3-17 shows the mass spectrum <strong>of</strong> deuterated tetracosane.<br />
Deuterated tetracosane D-C24 (C 24 D 50 ) produced primarily (M-D) + and (M-<br />
3D) + H 2 O. These findings confirm that (M-1) + and (M-3) + ions initially observed<br />
were geniune species.<br />
51
Results and Discussion<br />
Intens.<br />
[%]<br />
(M-1) +<br />
561.6<br />
+MS<br />
60<br />
(M-3) + D 2 O<br />
580.6<br />
40<br />
20<br />
0<br />
507.5 523.4 537.5 551.5<br />
591.4 599.6 608.4<br />
617.7<br />
520 540 560 580 600 620 m/z<br />
Figure 3-16 APCI mass spectrum after the addition <strong>of</strong> D 2 O to C40<br />
Intens.<br />
[%]<br />
100<br />
80<br />
(M-D) +<br />
386.7<br />
(M-3D) + H 2 O<br />
401.7<br />
+MS<br />
60<br />
40<br />
20<br />
0<br />
285.3<br />
369.3<br />
306.5 331.3<br />
429.4<br />
447.4 467.4 481.5<br />
280 300 320 340 360 380 400 420 440 460 m/z<br />
Figure 3-17 APCI mass spectrum <strong>of</strong> deuterated tetracosane (D-C24)<br />
Another verification <strong>of</strong> (M-3) + H 2 O as water adduct species was accomplished by<br />
isolating the monohydrated ion <strong>of</strong> dotriacontane (C32) and subjecting it to<br />
collision induced dissociation (CID). A high mass fragment ion was recorded at<br />
m/z 447, corresponding to (M-3) + , assuming the loss <strong>of</strong> water as shown in figure 3-<br />
18. A similar water loss was identified from hydrated clusters <strong>of</strong> the (M-1) + <strong>of</strong><br />
C29. Figure 3-19 illustrates the loss <strong>of</strong> water from m/z 425 (M-1) + H 2 O to give m/z<br />
407 (M-1) + . These results combined with findings from APCI-MS <strong>of</strong> deuterated<br />
species prove confidence with the authenticity <strong>of</strong> (M-1) + and (M-3) + species.<br />
52
Results and Discussion<br />
Intens.<br />
[%]<br />
100<br />
(M-3) +<br />
+MS 2 (465.8)<br />
447.4<br />
80<br />
409.4<br />
60<br />
40<br />
167.0<br />
181.0<br />
353.4 381.4<br />
367.4<br />
395.4<br />
(M-3) + H 2 O<br />
465.8<br />
20<br />
0<br />
100 150 200 250 300 350 400 450 m/z<br />
Figure 3-18 APCI-MS 2 spectrum <strong>of</strong> C32 showing (M-3) + fragment at m/z 447.4<br />
from precursor ion at m/z 465.8 corresponding to (M-3) + H 2 O<br />
Intens.<br />
+MS 2 (425)<br />
[%]<br />
100<br />
(M-1) +<br />
(M-1) + H 2 O<br />
425.1<br />
407.3<br />
158.9<br />
369.1<br />
50<br />
0<br />
188.9<br />
215.0 271.0<br />
313.1<br />
299.1<br />
351.1<br />
381.1<br />
150 200 250 300 350 400 450 m/z<br />
Figure 3-19 APCI-MS 2 spectrum <strong>of</strong> C29 showing (M-1) + fragment at m/z 407.3<br />
from precursor ion at m/z 425.1 corresponding to (M-1) + H 2 O<br />
3.4 Light shredder Waste Analysis<br />
3.4.1 (+)APCI-TOF-MS <strong>of</strong> Waste Sample<br />
After the detailed and necessary groundwork knowledge about the ionisation <strong>of</strong> the<br />
standard hydrocarbons in the previous section was attained, I have moved into the<br />
analysis <strong>of</strong> hydrocarbon content within the complex mixture <strong>of</strong> light shredder<br />
waste. Concerning the waste sample I have employed an optimised extraction<br />
53
Results and Discussion<br />
procedure based on the KW 04 method. 108,110 I found that addition <strong>of</strong> acetone<br />
during extraction, enhanced the penetration <strong>of</strong> n-heptane (main solvent). Using an<br />
automatic Soxhlet extraction, it was found that six hours were the optimum<br />
extraction time needed for hydrocarbon intake. Next, the extracted waste samples<br />
were measured as direct infusions in n-heptane using the APCI-TOF MS method<br />
similar to the one used for the analysis <strong>of</strong> reference standards. Figure 3-20 shows a<br />
mass spectrum <strong>of</strong> light shredder waste sample initially extracted with<br />
Heptane/Acetone. Figure 3-21 shows a waste sample which was extracted with n-<br />
heptane only. The former spectrum reflected a higher degree <strong>of</strong> complexity which<br />
was characterised by a large number <strong>of</strong> significant peaks compared to the sample<br />
<strong>of</strong> figure 3-21. By similar mass spectra comparisons, I was also able to screen the<br />
effectivity <strong>of</strong> florisil in purifying the heptane extract from polar species. <strong>Mass</strong><br />
spectra (a), (b) and (c) in Figure 3-22 shows that when more grams <strong>of</strong> florisil are<br />
used during purification course, the sample is better cleaned.<br />
Intens.<br />
[%]<br />
100<br />
80<br />
369.4<br />
411.4<br />
397.4<br />
425.4<br />
453.4<br />
+MS<br />
60<br />
40<br />
273.3<br />
315.3<br />
467.5<br />
481.5<br />
495.5<br />
509.5<br />
551.5<br />
20<br />
701.8<br />
0<br />
200 250 300 350 400 450 500 550 600 650 m/z<br />
Figure 3-20 APCI (+) mass spectrum <strong>of</strong> waste sample extracted using n-<br />
heptane/Acetone<br />
54
Results and Discussion<br />
Intens.<br />
[%]<br />
100<br />
80<br />
60<br />
40<br />
20<br />
397.4<br />
411.4<br />
425.4<br />
257.2<br />
285.3<br />
305.3<br />
449.5<br />
505.6<br />
541.6 561.6 663.5<br />
+MS<br />
0<br />
200 250 300 350 400 450 500 550 600 650 m/z<br />
Figure 3-21 APCI mass spectrum <strong>of</strong> waste sample extracted using n-heptane only<br />
Intens.<br />
[%]<br />
60<br />
40<br />
347.3<br />
(a)<br />
349.3<br />
351.3<br />
352.3<br />
353.3<br />
355.3<br />
357.3<br />
359.3<br />
361.3<br />
363.3<br />
+MS<br />
365.3<br />
20<br />
348.3<br />
350.3<br />
354.3<br />
356.4<br />
358.2<br />
360.3<br />
362.3<br />
364.3<br />
0<br />
348 350 352 354 356 358 360 362 364 m/z<br />
Intens.<br />
[%]<br />
40<br />
(b)<br />
+MS<br />
355.3<br />
357.4<br />
30<br />
353.3<br />
365.3<br />
351.3<br />
359.3<br />
363.3<br />
349.3<br />
20<br />
347.3<br />
361.3<br />
356.3<br />
358.4<br />
10<br />
354.3<br />
352.3<br />
350.3<br />
360.3<br />
364.3<br />
348.3<br />
362.3<br />
0<br />
348 350 352 354 356 358 360 362 364 m/z<br />
55
Results and Discussion<br />
Intens.<br />
[%]<br />
50<br />
(c)<br />
357.4<br />
+MS<br />
40<br />
355.3<br />
359.4<br />
30<br />
20<br />
10<br />
0<br />
C 26 H 39 C 25 H 52<br />
353.3<br />
347.4<br />
C 26 H 39 C 25 H 52<br />
361.4<br />
358.4<br />
365.3<br />
349.4<br />
351.3<br />
356.3<br />
360.4 363.4<br />
348.4<br />
354.3<br />
362.4<br />
352.3<br />
350.4<br />
364.4<br />
348 350 352 354 356 358 360 362 364 m/z<br />
Figure 3-22 <strong>Mass</strong> spectra <strong>of</strong> the waste sample purified by using 2 gs (a), 4 gs (b)<br />
and 6 gs (c) <strong>of</strong> florisil during purification.<br />
The altered light shredder waste fraction (hydrothermally treated) was analysed by<br />
APCI using N 2 gas as reagent. The mass spectrum in figure 3-20 shows ions for all<br />
components within the solid waste sample. The bulk <strong>of</strong> the sample, assuming<br />
ionisation without fragmentation as shown earlier, consists <strong>of</strong> hydrocarbons<br />
between 18 and 34 carbon atoms per molecule resulting in a mass envelope with<br />
almost Gaussian distribution centered around m/z 400. Examination <strong>of</strong> the waste<br />
spectrum reveals a MW distribution that spans over a mass range <strong>of</strong> m/z 200-700<br />
Da. This could define a typical MW distribution <strong>of</strong> solid waste hydrocarbon<br />
content. Although the waste spectrum demonstrates a relatively low mass<br />
distribution range, it reflects a high degree <strong>of</strong> complexity characterized by the huge<br />
number <strong>of</strong> peaks found in the spectrum. Around 4000 resolved signals were<br />
observed by direct infusion using a (+) APCI-TOF/MS method.<br />
The enlarged mass spectrum in figure 3-23 exhibits two contrasting modes <strong>of</strong><br />
ionisation for each analyte. Low intensity even mass ions accompany their<br />
respective high intensity odd mass ions. Even mass ions are most likely<br />
hydrocarbon molecular ions (or isotope peaks 2 H, 13 C) formed by a loss <strong>of</strong> an<br />
electron due to the role played by N 2 gas while odd mass ions are the significant<br />
ions corresponding to (M-1) + ions <strong>of</strong> hydrocarbons within the waste mixture.<br />
56
Results and Discussion<br />
Intens.<br />
[%]<br />
100<br />
80<br />
60<br />
40<br />
20<br />
393.3<br />
394.3<br />
395.4<br />
396.4<br />
397.4<br />
398.4<br />
399.4<br />
400.4<br />
401.4<br />
405.3<br />
403.4<br />
402.4<br />
404.4 406.4<br />
407.4<br />
408.4<br />
409.4<br />
410.4<br />
411.4<br />
412.4<br />
413.4<br />
+MS<br />
414.4<br />
0<br />
392.5 395.0 397.5 400.0 402.5 405.0 407.5 410.0 412.5 m/z<br />
Figure 3-23 Enlarged section <strong>of</strong> (+) MS showing bimodal distribution <strong>of</strong> odd and<br />
even mass ions<br />
The latter interpreted ionisation behavior <strong>of</strong> hydrocarbon ions in solid waste was<br />
anticipated from our previous results <strong>of</strong> ionisation behavior <strong>of</strong> n-alkanes and other<br />
hydrocarbon model standards upon APCI. These model standards produced also<br />
stable (M-1) + ions with neighboring molecular ions M •+ without any fragmentation<br />
under similar APCI conditions. This indicated that the stable ions appearing in the<br />
positive mass spectrum (+MS) are intact ions expressing their hydrocarbons that<br />
exist in the waste sample.<br />
3.4.2 Calibration<br />
After this fundamental description <strong>of</strong> the explored chemical content <strong>of</strong> the waste, a<br />
molecular formula assignment was required for all compounds present in the waste<br />
spectrum. However before identifying n-alkanes ,that are expected to be found<br />
within the waste chemical content, the obvious obstacle was to find suitable<br />
calibrant for the APCI-MS high resolution mass measurements. The generally used<br />
commercial APCI/APPI acetonitrile calibrant was not really effective towards a<br />
low-mass error assignment <strong>of</strong> waste sample components <strong>of</strong> n-alkanes and others.<br />
This is due to the fact that the calibrant’s range, shown in figure 3-24, did not fully<br />
cover the alkane mass range <strong>of</strong> interest (m/z 200-600) in these experiments. To<br />
overcome this problem, I have employed the C7-C40 n-alkane standard (figure 3-<br />
25) mixture to be used for m/z calibration using an enhanced quadratic calibration<br />
57
Results and Discussion<br />
to produce mass errors around 3 ppm. An enhanced quadratic fit provides the best<br />
relative standard deviation (RSD) around 1 <strong>of</strong> the analytes <strong>of</strong> the calibrant<br />
compared to linear or quadratic fits. For the calibration curve all (M-1) + ions <strong>of</strong> n-<br />
alkanes were used as reference masses, serving as an external calibrant for the<br />
waste analysis. The speciation <strong>of</strong> most <strong>of</strong> the components including n-alkanes<br />
within the waste sample was made possible by this intriguing employment <strong>of</strong> the<br />
C7-C40 calibrant standard. The combination <strong>of</strong> the calibration method<br />
establishment with the preceded thorough understanding <strong>of</strong> the ionisation <strong>of</strong><br />
hydrocarbons provided a rational elemental assignment <strong>of</strong> the molecular<br />
composition <strong>of</strong> the waste complex mixture. Table 3.3 shows the molecular formula<br />
list <strong>of</strong> n-alkanes obtained from a shredder waste sample under investigation.<br />
Intens.<br />
[%]<br />
100<br />
80<br />
622.0<br />
922.0<br />
+MS<br />
60<br />
40<br />
20<br />
322.0<br />
1522.0<br />
0<br />
663.4 850.0<br />
200 400 600 800 1000 1200 1400 m/z<br />
Figure 3-24 APCI/APPI standard recommended calibrant for APCI source<br />
With this result we could tentatively identify all n-alkanes (C13-C40) by their<br />
apparent (M-1) + representative ions in a real life complex waste sample displaying<br />
a UCM hump in a gas chromatogram. However the identified series <strong>of</strong> n-alkanes is<br />
only a significant part <strong>of</strong> the chemical content <strong>of</strong> the waste. The determination <strong>of</strong><br />
the other components within the waste spectrum will lead to clarify the chemical<br />
content <strong>of</strong> the unresolved complex mixture.<br />
58
Results and Discussion<br />
Intens.<br />
[%]<br />
100<br />
+MS<br />
561.6<br />
547.6<br />
80<br />
533.6<br />
505.6<br />
60<br />
449.5<br />
477.5<br />
40<br />
20<br />
253.3<br />
239.3<br />
281.3 337.4<br />
379.4<br />
407.5<br />
435.5<br />
0<br />
211.2<br />
200 250 300 350 400 450 500 550 m/z<br />
Figure 3-25 APCI mass spectra in positive ion mode <strong>of</strong> C7-C40 calibrant<br />
Table 3.3 Molecular formula list <strong>of</strong> n-alkanes in waste sample<br />
m/z Meas. m/z Molecular Formula Error [ppm]<br />
183.2107 183.211 C 13 H 28 -1.5<br />
197.2264 197.2266 C 14 H 30 -1.3<br />
211.242 211.2421 C 15 H 32 -0.4<br />
225.2577 225.2579 C 16 H 34 -0.8<br />
239.2733 239.2724 C 17 H 36 4.1<br />
253.289 253.2888 C 18 H 38 0.6<br />
267.3052 267.3044 C 19 H 40 3<br />
281.3203 281.3209 C 20 H 42 -2.1<br />
295.3359 295.3364 C 21 H 44 -1.7<br />
309.3516 309.3516 C 22 H 46 -0.1<br />
337.3829 337.3823 C 24 H 50 1.8<br />
351.3985 351.3981 C 25 H 52 1.3<br />
365.4142 365.4131 C 26 H 54 3<br />
379.4298 379.4284 C 27 H 56 3.8<br />
393.4455 393.4457 C 28 H 58 -0.5<br />
421.4768 421.4775 C 30 H 62 -1.7<br />
435.493 435.4938 C 31 H 64 -1.9<br />
449.5081 449.5075 C 32 H 66 1.4<br />
463.5237 463.522 C 33 H 68 3.8<br />
477.5394 477.5386 C 34 H 70 1.6<br />
491.555 491.5538 C 35 H 72 2.5<br />
505.5707 505.5695 C 36 H 74 2.4<br />
59
Results and Discussion<br />
519.5863 519.5838 C 37 H 76 4.9<br />
533.602 533.5975 C 38 H 78 1.3<br />
547.6182 547.6176 C 39 H 80 1.1<br />
561.6333 561.6306 C 40 H 82 4.8<br />
Table 3.4 shows the molecular formula list <strong>of</strong> some <strong>of</strong> the compounds found in the<br />
waste spectrum. The molecular formulas <strong>of</strong> n-alkanes within the list are obviously<br />
characterized by their (M-1) + ion formula. The content is already known to<br />
comprise a series <strong>of</strong> n-alkanes ranging from decane (C10) till tetracontane (C40).<br />
The remaining compounds are assigned as unsaturated and/or cyclic hydrocarbons<br />
depending on their molecular formulas. Underneath each saturated n-alkane a<br />
series <strong>of</strong> dehydrogenated derivatives was observed. The molecular formulas<br />
suggested that waste components could be assigned as alkenes or cycloalkanes<br />
varying by their unsaturation degree or variation <strong>of</strong> doubly bond equivalents. The<br />
molecular formulas for these compounds also suggested degradation that happened<br />
to the hydrocarbons in the waste sample during microbial processing, since they<br />
were found to be absent in untreated waste. Apparently each compound differs by<br />
a mass increment <strong>of</strong> two m/z units between every two consecutive compounds,<br />
thus suggesting a dehydrogenation process. An enlarged part <strong>of</strong> the waste sample’s<br />
mass spectrum is shown in figure 3-22 (c) showing that peaks corresponding to the<br />
saturated alkanes along with peaks corresponding to compounds with increased<br />
double bond equivalents formally obtained through a dehydrogenation. All waste<br />
samples were measured in triplicates and were found to be reproducible.<br />
60
Results and Discussion<br />
Table 3.4 Molecular formula list <strong>of</strong> some analytes <strong>of</strong> hydrocarbons in waste<br />
sample<br />
Meas. m/z Mol.Formula m/z Error [ppm]<br />
189.163 C 14 H 21 189.1638 4.2<br />
191.1789 C 14 H 23 191.1794 2.6<br />
193.1941 C 14 H 25 193.1947 3.1<br />
195.2105 C 14 H 27 195.2107 1<br />
197.2259 C 14 H 29 197.2264 2.5<br />
199.1477 C 15 H 19 199.1481 2<br />
201.164 C 15 H 21 201.1638 -1<br />
203.1796 C 15 H 23 203.1794 -1<br />
205.1954 C 15 H 25 205.1951 -1.5<br />
207.211 C 15 H 27 207.2107 -1.5<br />
209.2266 C 15 H 29 209.2264 -1<br />
211.2422 C 15 H 31 211.242 -1<br />
213.1647 C 16 H 21 213.1638 -4.2<br />
215.1804 C 16 H 23 215.1794 -4.6<br />
217.1956 C 16 H 25 217.1951 -2.3<br />
219.2109 C 16 H 27 219.2107 -0.9<br />
221.2274 C 16 H 29 221.2264 -4.5<br />
223.2427 C 16 H 31 223.242 -3<br />
225.2586 C 16 H 33 225.2577 -4<br />
231.212 C 17 H 27 231.211 -4.3<br />
233.2273 C 17 H 29 233.2264 -3.8<br />
235.2429 C 17 H 31 235.242 -3.8<br />
237.258 C 17 H 33 237.2577 -1.3<br />
245.2276 C 18 H 29 245.2264 -4.9<br />
247.2432 C 18 H 31 247.242 -4.8<br />
249.2591 C 18 H 33 249.2583 -3.2<br />
251.274 C 18 H 35 251.2733 -2.8<br />
253.2904 C 18 H 37 253.291 2.4<br />
261.2592 C 19 H 33 261.2599 2.6<br />
263.2747 C 19 H 35 263.2752 1.8<br />
265.2884 C 19 H 37 265.289 2.3<br />
267.3051 C 19 H 39 267.3046 -1.9<br />
279.3057 C 20 H 39 279.3046 -4<br />
61
Results and Discussion<br />
Higher mass range<br />
281.3214 C 20 H 41 281.3203 -3.9<br />
289.2906 C 21 H 37 289.291 1.4<br />
291.306 C 21 H 39 291.312 2<br />
293.3212 C 21 H 41 293.3222 3.4<br />
295.3374 C 21 H 43 295.3384 3.4<br />
303.3062 C 22 H 39 303.3076 4.6<br />
305.3215 C 22 H 41 305.3203 -4<br />
307.3367 C 22 H 43 307.3359 -2.6<br />
309.3522 C 22 H 45 309.3516 -2<br />
317.3219 C 23 H 41 317.3228 2.8<br />
319.3375 C 23 H 43 319.3381 -4.8<br />
321.3515 C 23 H 45 321.3516 0.3<br />
323.3685 C 23 H 47 323.3672 -4<br />
327.3065 C 24 H 39 327.3071 1.8<br />
331.3377 C 24 H 43 331.3387 3<br />
333.3529 C 24 H 45 333.3516 -3.9<br />
337.3836 C 24 H 49 337.3829 -2<br />
343.3378 C 24 H 43 343.3389 3.2<br />
345.3532 C 24 H 45 345.3516 -4.7<br />
347.3684 C 24 H 47 347.3672 -3.4<br />
351.3986 C 25 H 51 351.3985 -0.2<br />
357.3535 C 26 H 45 357.3549 3.9<br />
359.3686 C 26 H 47 359.3672 -3.8<br />
361.3841 C 26 H 49 361.3829 -3.4<br />
365.4155 C 26 H 53 365.4142 -3.6<br />
371.3694 C 27 H 47 371.3704 2.7<br />
373.384 C 27 H 49 373.3829 -2.9<br />
379.4303 C 27 H 55 379.4298 -1.3<br />
383.3692 C 28 H 47 383.3705 3.4<br />
385.3851 C 28 H 49 385.387 5<br />
387.3994 C 28 H 51 387.3985 -2.4<br />
389.4144 C 28 H 53 389.4142 -0.6<br />
391.3359 C 29 H 43 391.3356 -0.7<br />
393.445 C 28 H 57 393.4455 1.2<br />
395.3694 C 29 H 47 395.368 -3.5<br />
399.4009 C 29 H 51 399.3999 -2.5<br />
401.4146 C 29 H 53 401.4142 -1<br />
407.4588 C 29 H 59 407.4599 2.7<br />
62
Results and Discussion<br />
After identifying the chemical content in the positive ion mode <strong>of</strong> APCI-TOF-MS<br />
method, I shifted the method to the negative polarity to explore any potential<br />
compounds preferably ionised under negative APCI-TOF-MS<br />
3.4.3 Identification <strong>of</strong> Polychlorinated Biphenyls (PCBs) in (-) APCI-TOF-<br />
MS<br />
The waste mixture was measured again by direct injection using this time negative<br />
(-) APCI-TOF-MS method. The mass spectrum observed in figure 3-26 revealed a<br />
class <strong>of</strong> polychlorinated compounds which demonstrated chlorine isotope patterns.<br />
Tetrachlorobiphenyl (1) at m/z 272.9, pentachlorobiphenyl (2) at m/z 306.9,<br />
hexachlorobiphenyl (3) at m/z 340.9, heptachlorobiphenyl (4) at m/z 374.8 and<br />
octachlorobiphenyl (5) at m/z 408.8 were identified by the (-) APCI method. This<br />
identification was based on a rational study <strong>of</strong> a PCB Congener Mix under the<br />
same (-) APCI conditions. The PCBs components within the standard mix<br />
produced (M-Cl+O) – ions as shown in figure 3-27. This finding wasn’t surprising<br />
as PCBs have been previously reported to ionize with the same fashion under<br />
APCI conditions. 111,112 The selectivity <strong>of</strong> ionisation is actually the significant<br />
observation. We tested the highest chlorinated PCB, decachlorobiphenyl (M=<br />
498.66 g/mole) which was found to produce an (M-Cl+O) – ion at m/z 478.7 as<br />
shown in figure 3-28. A simulated isotope pattern for decachlorobiphenyl which is<br />
embedded in figure 3-28 was provided by Bruker S<strong>of</strong>tware. The latter figure shows<br />
that the measured and simulated isotope patterns are identical. However the (-)<br />
mass spectrum <strong>of</strong> the waste extract comprises also high mass chlorinated<br />
compounds. These compounds could be assigned as chlorinated alkanes or<br />
chlorinated aromatic hydrocarbons. Nevertheless the Bruker s<strong>of</strong>tware <strong>of</strong> the TOF-<br />
MS suggested a chlorine content <strong>of</strong> these compounds according to their isotope<br />
patterns shown in figure 3-26. Small PCBs containing capacitors in household<br />
appliances and PCB-containing sealants for buildings within light shredder waste<br />
fraction would be the sources <strong>of</strong> these PCBs.<br />
63
Results and Discussion<br />
Intens.<br />
[%]<br />
100<br />
2<br />
306.9<br />
3<br />
340.9<br />
Cl 6<br />
450.9<br />
-MS<br />
80<br />
60<br />
40<br />
20<br />
0<br />
Cl 7<br />
484.8<br />
283.3<br />
4<br />
1<br />
374.8 420.8 473.3<br />
Cl 6<br />
270.9<br />
5<br />
Cl 5 Cl8<br />
576.6<br />
435.8<br />
520.8<br />
Cl 8<br />
Cl 7<br />
658.5<br />
Cl 10<br />
736.4<br />
632.7<br />
300 350 400 450 500 550 600 650 700 m/z<br />
Figure 3-26 (-) APCI mass spectrum showing identified PCBs in waste sample<br />
Intens.<br />
[%]<br />
100<br />
C 12 H 6 OCl 4<br />
C 12 H 5 OCl 5<br />
306.9<br />
340.9<br />
-MS<br />
80<br />
60<br />
40<br />
283.3<br />
C 12 H 4 OCl 6<br />
374.8<br />
C 12 H 3 OCl 7<br />
408.8 473.3<br />
20<br />
0<br />
321.9<br />
355.9<br />
275 300 325 350 375 400 425 450 475 500 m/z<br />
Figure 3-27 (-) APCI mass spectrum <strong>of</strong> PCBs Congener Mix<br />
Intens.<br />
[%]<br />
100<br />
478.7<br />
-MS<br />
80<br />
60<br />
476.7<br />
480.7<br />
40<br />
20<br />
474.7<br />
482.7<br />
484.7<br />
0<br />
455 460 465 470 475 480 485 490 495 500 m/z<br />
Figure 3-28 (-) APCI mass spectrum <strong>of</strong> decachlorobiphenyl standard (C 12 OCl 9 )<br />
with simulated isotope pattern as suggested by Bruker S<strong>of</strong>tware<br />
64
Results and Discussion<br />
After the confident identification <strong>of</strong> few PCBs within the waste extract, we<br />
employed tandem-MS in order to obtain further structural information on the<br />
components.<br />
3.4.4 Tandem MS Measurements<br />
Tandem MS measurements were carried out as direct infusion experiments in n-<br />
heptane in the positive ion mode using an ion trap mass spectrometer with APCIionisation.<br />
After injecting the waste sample into the iontrap, the lower mass<br />
distribution <strong>of</strong> the sample, shown in figure 3-29, had ions with mostly odd mass<br />
values (see figure 3-30). This indicated that the lower mass distribution mostly<br />
consists <strong>of</strong> fragment ions formed from the molecular ions. This is as expected<br />
because ionisation occurred via the high-energy process <strong>of</strong> electron abstraction by<br />
N +• 2 . At first task (M-1) + series <strong>of</strong> standard n-alkanes ions were selected and<br />
isolated with an isolation width <strong>of</strong> 1 Da and each n-alkane subjected to Collision<br />
Induced Dissociation (CID). The (M-1) + ions <strong>of</strong> few analytes <strong>of</strong> n-alkanes within<br />
the C7-C40 standard were fragmented as shown in figures 3-31 to 3-34. The<br />
fragmentation pattern (MS 2 spectrum) seems to decrease by an increment <strong>of</strong> 14 Da<br />
which reflects the CH 2 group that forms the structure <strong>of</strong> n-alkanes. This is further<br />
emphasized in scheme 4 where a fragmentation route for pentacosane (C25) is<br />
provided. Isolation <strong>of</strong> the molecular ions <strong>of</strong> the higher n-alkanes within the<br />
standard C7-C40 like tetracosane (C40) was made possible. Figure 3-35 shows the<br />
MS 2 spectrum <strong>of</strong> m/z 562, the molecular ion <strong>of</strong> C40. The advantage here is that this<br />
ion could independantly evaporate into the gas phase, get ionised and further<br />
isolated to be subjected to CID in Iontrap-MS. Further isolation <strong>of</strong> similar<br />
molecular ions are demonstrated in figures 3-36 and 3-37. Access to fragmentation<br />
patterns <strong>of</strong> molecular ions can make use <strong>of</strong> the GC library accummulated for many<br />
years.<br />
65
Results and Discussion<br />
Intens.<br />
[%]<br />
100<br />
80<br />
60 97.1<br />
577.5<br />
40<br />
633.5<br />
20<br />
0<br />
100 200 300 400 500 600 700 800 900 m/z<br />
Figure 3-29 APCI-ion trap mass spectrum <strong>of</strong> waste sample<br />
Intens.<br />
+MS<br />
[%]<br />
80<br />
60<br />
97.1<br />
40<br />
111.0<br />
124.9<br />
20<br />
0<br />
60 80 100 120 m/z<br />
Figure 3-30 Low mass distribution in APCI-iontrap mass spectrum for waste<br />
sample<br />
Intens.<br />
+MS 2 (337)<br />
[%]<br />
239.0<br />
100<br />
225.1<br />
197.0<br />
253.1<br />
80<br />
183.0<br />
267.1<br />
60<br />
154.9<br />
338.3<br />
281.1<br />
40<br />
113.0<br />
303.3<br />
20<br />
0<br />
100 150 200 250 300 350 400 m/z<br />
Figure 3-31 APCI-MS 2 <strong>of</strong> tetracosane with precursor ion at m/z 337 corresponding<br />
to (M-1) +<br />
150.9 190.9 409.3<br />
467.4<br />
509.5<br />
+MS<br />
66
Results and Discussion<br />
Intens.<br />
[%]<br />
100<br />
80<br />
60<br />
40<br />
20<br />
0<br />
113.0<br />
169.0<br />
141.0<br />
154.9<br />
211.0<br />
239.1 267.1<br />
281.2<br />
295.2<br />
309.3 333.3 351.3<br />
+MS 2 (351)<br />
100 150 200 250 300 350 400 450 m/z<br />
Figure 3-32 APCI-MS 2 <strong>of</strong> pentacosane with precursor ion at m/z 351corresponding<br />
to (M-1) +<br />
Intens.<br />
[%]<br />
100<br />
80<br />
154.9<br />
168.9<br />
182.9<br />
197.0<br />
225.0<br />
239.1<br />
295.2<br />
281.1<br />
309.3 323.3<br />
+MS 2 (407)<br />
60<br />
40<br />
20<br />
127.0<br />
337.3<br />
351.3<br />
365.3<br />
389.4<br />
405.2<br />
0<br />
100 150 200 250 300 350 400 m/z<br />
Figure 3-33 APCI-MS 2 <strong>of</strong> nonacosane with precursor ion at m/z 407 corresponding<br />
to (M-1) +<br />
Intens.<br />
[%]<br />
100<br />
80<br />
60<br />
40<br />
20<br />
0<br />
132.9<br />
144.8<br />
186.9<br />
172.9 198.8<br />
269.0<br />
283.1<br />
297.1<br />
325.2<br />
311.1<br />
337.2<br />
351.2<br />
365.2<br />
379.3<br />
393.3<br />
407.3<br />
421.2<br />
433.2<br />
449.3<br />
+MS 2 (449)<br />
150 200 250 300 350 400 450 500 m/z<br />
Figure 3-34 APCI-MS 2 <strong>of</strong> dotriacontane with precursor ion at m/z 449 correspon-<br />
ding to (M-1) +<br />
67
Results and Discussion<br />
Intens.<br />
[%]<br />
100<br />
562.6<br />
+MS 2 (562)<br />
80<br />
60<br />
295.3 351.4 379.4 407.4<br />
197.1 225.1 253.1 323.3 449.5<br />
463.5<br />
183.0<br />
477.5<br />
40<br />
169.0<br />
491.5<br />
20<br />
0<br />
505.5<br />
150 200 250 300 350 400 450 500 550 600 m/z<br />
519.5<br />
Figure 3-35 APCI-MS 2 <strong>of</strong> molecular ion <strong>of</strong> tetracontane (C40) at m/z 562<br />
Intens.<br />
[%]<br />
100<br />
80<br />
60<br />
40<br />
20<br />
0<br />
155.0<br />
211.0<br />
197.0<br />
182.9<br />
168.9<br />
295.2<br />
281.2<br />
239.1 267.1<br />
309.3<br />
407.4 435.4<br />
421.4<br />
323.3 449.4<br />
351.4<br />
463.5<br />
477.5<br />
491.5<br />
505.5<br />
529.6<br />
548.7<br />
+MS 2 (548)<br />
150 200 250 300 350 400 450 500 550 m/z<br />
Figure 3-36 APCI-MS 2 <strong>of</strong> molecular ion <strong>of</strong> nonatriacontane (C39) at m/z 548<br />
Intens.<br />
[%]<br />
100<br />
80<br />
60<br />
295.2<br />
225.0 267.1<br />
211.0 253.1<br />
337.3 365.3<br />
351.3<br />
421.4<br />
379.4 407.4 435.4<br />
449.5<br />
+MS 2 (534)<br />
40<br />
20<br />
0<br />
168.9<br />
463.5 515.5<br />
155.0<br />
534.6<br />
491.4<br />
150 200 250 300 350 400 450 500 550 m/z<br />
Figure 3-37 APCI-MS 2 <strong>of</strong> molecular ion <strong>of</strong> octatriacontane (C38) at m/z 534<br />
68
Results and Discussion<br />
Similar results were obtained for (M-1) + for n-alkanes within waste samples. In<br />
contrast higher mass n-alkane species in some waste samples exhibited low<br />
relative abundances. This leads to make them difficult to isolate and thus fragment.<br />
It happens that the isolated low abundance alkane ion is not steady enough to give<br />
a fragmentation pattern similar to the one isolated from the standard C7-C40<br />
alkane mixture.<br />
Intens.<br />
[%]<br />
100<br />
75<br />
50<br />
25<br />
[%]<br />
0<br />
100<br />
75<br />
50<br />
25<br />
[%] 0<br />
172.8 252.9 325.1 379.2<br />
181.8216.9 276.0<br />
349.0 406.3436.1<br />
561.5<br />
504.4<br />
547.5<br />
517.4<br />
100<br />
75<br />
50<br />
25<br />
[%] 0<br />
172.8 267.0 377.2407.2<br />
461.4<br />
517.4<br />
100<br />
75<br />
50<br />
25<br />
0<br />
503.4<br />
447.3<br />
184.8 255.0 298.9 379.2<br />
100 200 300 400 500 600 700 m/z<br />
Figure 3-38 APCI-MS 2 spectra <strong>of</strong> m/z 561, 547, 519 and 505 corresponding to<br />
(M-1) + ions <strong>of</strong> C40, C39, C37 and C36 respectively within a waste extract<br />
Figure 3-38 shows the MS 2 pattern <strong>of</strong> m/z 561, 547,519 and 505 (M-1) + ions within<br />
a waste extract. After acquiring the Tandem MS data for the n-alkanes within the<br />
C7-C40 standard as well as those within the waste extract, a comparison was<br />
necessary to prove structural identity <strong>of</strong> the ions. The comparison <strong>of</strong> the<br />
fragmentation patterns <strong>of</strong> the standard n-alkanes was found similar, but not<br />
identical, to that <strong>of</strong> the ions <strong>of</strong> identical m/z values found within the waste sample.<br />
Figure 3-39 shows an MS 2 tandem spectrum for nonacosane (C 29 H + 59 ) at m/z 407<br />
69
Results and Discussion<br />
isolated from n-alkane standard (a) and a tandem MS spectrum <strong>of</strong> an ion <strong>of</strong> m/z<br />
407 from waste extract (b). The partial identity <strong>of</strong> the spectra, with all fragment<br />
ions observed in the reference sample as well observed in the actual waste sample,<br />
serves as a structural evidence for the presence <strong>of</strong> n-alkanes in the complex<br />
mixture <strong>of</strong> the light shredder waste. These data suggest as well that the positive<br />
reactant ion and alkane molecules undergo ion-molecule reaction at the<br />
atmospheric pressure conditions to produce molecular type and alkyl fragment<br />
ions. The production <strong>of</strong> this (M-1) + series <strong>of</strong> fragments is in agreement with<br />
electron impact and chemical ionisation <strong>of</strong> one n-alkane reported previously. 113<br />
The differences in the two experimental tandem MS spectra can be rationalised by<br />
assuming that in addition to n- alkanes as well other isomeric branched alkanes are<br />
present in the actual waste sample giving rise to variations in the intensities <strong>of</strong> the<br />
fragment ions.<br />
Scheme 4. Fragmentation scheme <strong>of</strong> (M-1) + <strong>of</strong> pentacosane (C25) at m/z 351<br />
Although the utility <strong>of</strong> chemical standards is impractical for such incredibly large<br />
number <strong>of</strong> derivatives, we have used few specific standards to map the structure <strong>of</strong><br />
the detected unsaturated compounds in the waste spectrum. Tandem MS<br />
experiments were performed using similar APCI conditions interfaced to an<br />
Iontrap-MS. With a low isolation width (1Da), groups the unsaturated compounds<br />
were selected and fragmented using CID available in Iontrap/MS.<br />
70
Results and Discussion<br />
The fragmentation patterns <strong>of</strong> the waste components were found similar to each<br />
other. While fragmenting few hydrocarbon standards we have seen a significant<br />
similarity between the MS 2 patterns <strong>of</strong> waste components and that <strong>of</strong> squalene.<br />
Figure 3-40 shows the MS 2 spectrum for squalene and figure 3-41 shows the MS 2<br />
spectra that belong to four selected ions from the waste, m/z 409, m/z 411, m/z 413<br />
and m/z 415. While the m/z 411 ions within the waste extract and that <strong>of</strong> squalene<br />
have the same molecular formula (C 30 H 51 ) + , they are not structurally identical.<br />
There is partial resemblance between the MS 2 spectra <strong>of</strong> the two compounds.<br />
Similarly the other selected ions have matching fragments with those obtained<br />
from squalene.<br />
Figure 3-39 MS 2 fragmentation spectra for nonacosane C 29 H 59 + within standard n-<br />
alkane mixture (a) and within waste sample (b)<br />
71
Results and Discussion<br />
Intens.<br />
[%]<br />
100<br />
80<br />
60<br />
40<br />
20<br />
120.9<br />
134.9<br />
162.9<br />
176.9 202.9<br />
230.9<br />
245.0<br />
259.1<br />
287.1<br />
301.1<br />
315.2<br />
329.2<br />
355.3<br />
341.3 369.3<br />
412.3<br />
+MS 2 (411.0)<br />
0<br />
100 150 200 250 300 350 400 450m/z<br />
Figure 3-40 APCI-MS 2 spectrum <strong>of</strong> squalene <strong>of</strong> m/z 411<br />
Intens<br />
[%]<br />
100<br />
75<br />
50<br />
25<br />
[%]<br />
0<br />
100<br />
75<br />
50<br />
25<br />
[%]<br />
0<br />
100<br />
75<br />
50<br />
25<br />
[%]<br />
0<br />
100<br />
75<br />
50<br />
25<br />
0<br />
130.8<br />
144.8<br />
160.7<br />
172.8<br />
174.8<br />
160.7 188.8<br />
202.7<br />
162.8<br />
176.7<br />
162.7 190.8<br />
148.7<br />
198.7 212.8 254.9<br />
226.8<br />
240.8<br />
216.9<br />
228.9<br />
242.9<br />
218.7232.9<br />
244.8<br />
259.0<br />
260.9<br />
271.0<br />
274.9<br />
339.1<br />
311.0<br />
283.0 297.0 325.1<br />
100 150 200 250 300 350 400 450m/z<br />
287.0<br />
299.0<br />
315.0<br />
317.0<br />
367.1<br />
394.1<br />
411.3<br />
327.1 341.1 355.1369.1 396.1<br />
343.1<br />
345.1<br />
357.1<br />
359.1<br />
373.1<br />
385.2<br />
419.2<br />
MS 2 (409)<br />
MS 2 (411)<br />
MS 2 (413)<br />
MS 2 (415)<br />
Figure 3-41 APCI-MS 2 spectra <strong>of</strong> four selected ions within the waste sample <strong>of</strong><br />
m/z 409,411,413 and 415<br />
The similarity between the unsaturated compounds in the waste and squalene is<br />
demonstrated in their fragmentation pattern that are underlined in figure 3-41.<br />
This suggests degraded compounds could be structurally similar but not identical<br />
to squalene. Addition experiments involved the analysis <strong>of</strong> other standards <strong>of</strong><br />
hydrocarbon. For example 5-α-cholestane was depicted as (M-1) + ions first time<br />
reported to produce under APCI conditions. Interestingly MS 2 tandem spectrum<br />
for 5-α-cholestane standard (see figure 3-42) at m/z 371 (C 27 H 47 ) + was found<br />
72
Results and Discussion<br />
identical to MS 2 tandem spectrum <strong>of</strong> m/z 371 isolated from the waste mixture<br />
shown in figure 3-43. Further MS 3 spectra were acquired for the significant m/z<br />
355 fragment ion from both the standard and waste sample. The resulting spectra<br />
were also found identical. Another interpretation <strong>of</strong> the MS 2 fragmentation spectra<br />
is provided in table 3.5. The fragments <strong>of</strong> tetracosane, pentacosane and squalene<br />
are assigned.<br />
Table 3.5<br />
CID MS 2 -stage tandem mass spectra for some <strong>of</strong> the positive ions <strong>of</strong><br />
tetracosane, pentacosane and squalene.<br />
Compound (m/z)<br />
MS 2 fragmentations<br />
(Product ions m/z)<br />
(281) C 20 H 41 (183) C 13 H 27<br />
(267) C 19 H 39 (169) C 12 H 25<br />
Tetracosane (337)<br />
(253) C 18 H 37 (155) C 11 H 23<br />
(239) C 17 H 35 (141) C 10 H 21<br />
(225) C 16 H 33 (127) C 9 H 19<br />
(211) C 15 H 31 (113) C 8 H 17<br />
(197) C 14 H 29<br />
(295) C 21 H 43 (197) C 14 H 29<br />
(281) C 20 H 41 (183) C 13 H 27<br />
Pentacosane (351)<br />
(267) C 19 H 39 (169) C 12 H 25<br />
(253) C 18 H 37 (155) C 11 H 23<br />
(239) C 17 H 35 (141) C 10 H 21<br />
(225) C 16 H 33 (127) C 9 H 19<br />
(211) C 15 H 31 (113) C 8 H 17<br />
(369) C 27 H 45 (231) C 17 H 27<br />
(355) C 26 H 43 (217) C 16 H 25<br />
(341) C 25 H 41 (203) C 15 H 23<br />
(329) C 24 H 41 (189) C 14 H 21<br />
Squalene (411)<br />
(315) C 23 H 39 (177) C 13 H 19<br />
(301) C 22 H 37 (163) C 12 H 17<br />
(287) C 21 H 35 (149) C 11 H 15<br />
(273) C 20 H 33 (135) C 10 H 13<br />
(259) C 19 H 31 (121) C 9 H 11<br />
(245) C 18 H 29<br />
73
Results and Discussion<br />
Intens.<br />
[%]<br />
100<br />
354.9<br />
+MS 2 (371)<br />
75<br />
50<br />
25<br />
[%]<br />
0<br />
148.9<br />
188.9<br />
261.0<br />
315.1<br />
371.3<br />
+MS 3 (371->355)<br />
100<br />
268.7<br />
75<br />
50<br />
284.8<br />
354.9<br />
25<br />
0<br />
338.9<br />
50 100 150 200 250 300 350 400 450 m/z<br />
Figure 3-42 Fragmentation spectrum <strong>of</strong> 5-α-cholestane at m/z 371 C 27 H 47 + within<br />
standard 5-α-cholestane sample<br />
Intens.<br />
[%]<br />
100<br />
373.3<br />
+MS 2 (371.0)<br />
75<br />
50<br />
25<br />
119.1 145.0 174.9 230.0 258.1 300.2<br />
355.1<br />
[%]<br />
0<br />
100<br />
355.1<br />
+MS 3 (371.0->355.0)<br />
75<br />
50<br />
25<br />
0<br />
268.9<br />
284.9<br />
50 100 150 200 250 300 350 400 450 m/z<br />
Figure 3-43 Fragmentation spectra for C 27 H 47 + ion at m/z 371 within waste sample<br />
A fragmentation scheme for 5-α-cholestane at m/z 371 is demonstrated in scheme<br />
5. The fragmentation appears to start in the alkyl group <strong>of</strong> 5-α-cholestane.<br />
Subsequent losses <strong>of</strong> a methyl with a neighboring hydrogen and an isopentyl group<br />
is proposed to explain part <strong>of</strong> the fragmentation spectrum <strong>of</strong> 5-α-cholestane.<br />
74
Results and Discussion<br />
Scheme 5. Fragmentation scheme <strong>of</strong> (M-1) + <strong>of</strong> 5-α-cholestane at m/z 371<br />
75
Results and Discussion<br />
3.4.5 Tandem MS <strong>of</strong> Derivatised Compounds<br />
Furthermore, Tandem MS has been used to explore derivatised waste sample. In a<br />
separate experiment, silver triflate was added to the waste extract. Figure 3-44<br />
shows the mass spectrum after addition <strong>of</strong> silver triflate. Isotope patterns indicating<br />
the presence <strong>of</strong> Ag were observed. This shows that the silver complexed to few<br />
components within the waste and the resultant masses dominated the waste spectra<br />
as shown in figure 3-44. The idea here was to employ Tandem MS to inquire about<br />
the structural identity <strong>of</strong> these new product ions. MS 2 spectrum <strong>of</strong> selected m/z 328<br />
ion was acquired as shown in figure 3-45. The fragmentation shows the typical<br />
isotope pattern <strong>of</strong> the detached silver at m/z 107 and m/z 109 in figure 3-45.<br />
However the fragmentation spectrum didn’t provide additional knowledge about<br />
the structure <strong>of</strong> the compound that complexed with Ag. This leads to conclude that<br />
derivatisation with silver has led to enhance few compounds that may have been <strong>of</strong><br />
low abundance within the waste extract. However derivatisation in this case<br />
doesn’t seem to aid in providing structural information about the compounds found<br />
in the waste sample.<br />
Intens.<br />
[%]<br />
100<br />
328.8<br />
+MS<br />
80<br />
60<br />
411.4 423.4<br />
40<br />
303.2<br />
20<br />
337.3 351.3 365.3 379.3<br />
397.4<br />
439.4<br />
457.4 471.4 485.4 499.4 513.5 527.5<br />
0<br />
300 325 350 375 400 425 450 475 500 525m/z<br />
Figure 3-44 APCI mass spectrum in positive ion mode <strong>of</strong> waste sample deriva-<br />
tised with Agtriflate<br />
76
Results and Discussion<br />
Intens.<br />
[%]<br />
100<br />
327.0<br />
+MS 2 (328)<br />
80<br />
60<br />
Ag<br />
106.8<br />
40<br />
20<br />
0<br />
346.7<br />
126.9<br />
242.9 271.0 299.1<br />
158.8 188.9 214.8 364.7<br />
50 100 150 200 250 300 350 400 450 500 m/z<br />
Figure 3-45 APCI-MS 2 <strong>of</strong> a silver adducted complex at m/z 328 ion<br />
3.4.6 Tandem MS <strong>of</strong> PCBs<br />
Tandem MS experiments were performed for the PCBs that appeared in the<br />
negative mode mass spectrum <strong>of</strong> the waste sample. Similarly, in advance, PCBs<br />
from the Congener standard mix were fragmented. (M-Cl+O) – ions from the two<br />
aforementioned sources were selected and isolated with an isolation width <strong>of</strong> 0.5<br />
Da and each PCB was subjected to Collision Induced Dissociation (CID). All ions<br />
<strong>of</strong> different PCBs from both samples suggested a loss <strong>of</strong> chlorine upon<br />
fragmentation (see figure 3-46 and 3-47). It was noticed that the PCBs are less<br />
liable to fragment. This is also reported for the fragmentation <strong>of</strong> PCBs. 111,112 In all<br />
cases the MS 2 <strong>of</strong> the selected PCBs within the standard mix were found identical<br />
to those native in waste sample. Similar to the high mass n-alkane species in some<br />
waste samples, high mass chlorinated compounds demonstrated the production <strong>of</strong><br />
very weak or no fragments upon fragmentation. Figure 3-48 shows the MS 2 spectra<br />
<strong>of</strong> the high mass chlorinated components. This can be attributed to the low<br />
abundance <strong>of</strong> these components as well as their insufficiency to provide a detailed<br />
fragmentation pattern.<br />
77
Results and Discussion<br />
Intens.<br />
[%]<br />
100<br />
75<br />
50<br />
25<br />
0<br />
[%]<br />
100<br />
75<br />
50<br />
25<br />
[%]<br />
0<br />
100<br />
75<br />
50<br />
25<br />
270.6<br />
304.7<br />
304.6<br />
338.7<br />
338.6<br />
374.6<br />
-MS 2 (306)<br />
-MS 2 (340)<br />
-MS 2 (374)<br />
0<br />
100 150 200 250 300 350 400 450 500 m/z<br />
Figure 3-46 Fragmentation <strong>of</strong> selected PCBs at m/z 306, 340 and 374 from the<br />
PCBs Congener Mix<br />
Intens.<br />
[%]<br />
100<br />
75<br />
50<br />
25<br />
0<br />
[%]<br />
270.7<br />
304.8<br />
-MS 2 (306)<br />
-MS 2 (340)<br />
100<br />
338.7<br />
75<br />
50<br />
25<br />
304.7<br />
0<br />
[%]<br />
-MS 2 (374)<br />
100<br />
372.7<br />
75<br />
50<br />
338.8<br />
25<br />
0<br />
100 150 200 250 300 350 400 450 500 m/z<br />
Figure 3-47 Fragmentation <strong>of</strong> selected PCBs at m/z 306, 340 and 374 from the<br />
waste sample<br />
78
Results and Discussion<br />
Intens.<br />
[%]<br />
100<br />
50<br />
[%] 0<br />
100<br />
50<br />
[%] 0<br />
100<br />
50<br />
[%] 0<br />
100<br />
50<br />
[%] 0<br />
100<br />
50<br />
[%] 0<br />
100<br />
50<br />
0<br />
414.9<br />
380.9<br />
448.8<br />
414.8<br />
474.3<br />
358.1<br />
498.6<br />
527.5<br />
230.9<br />
576.5<br />
200 300 400 500 600 700 800 m/z<br />
Figure 3-48 Fragmentation <strong>of</strong> high mass chlorinated components within the waste<br />
extract<br />
3.4.7 Oxidative Degradation <strong>of</strong> Complex Mixture <strong>of</strong> Shredder Waste<br />
In an attempt to further achieve an insight about the structure composition <strong>of</strong> the<br />
unsaturated hydrocarbons within the content <strong>of</strong> the light shredder waste, oxidation<br />
<strong>of</strong> these hydrocarbon components within the waste sample was performed. This<br />
method was introduced in the literature in order to explore the composition <strong>of</strong> the<br />
UCM by changing the hydrocarbons to functionalized compounds described to be<br />
easily resolved and identified. Gough and Rowland used this oxidative degradation<br />
over UCM <strong>of</strong> hydrocarbons from lubricating oil feed stocks to characterize<br />
them. 17 After reacting the light shredder waste extract with chromium trioxide in<br />
acetic acid for six hours, the functionalised products were measured by mass<br />
spectrometry. This time ESI was also employed because the products <strong>of</strong> oxidative<br />
degradation were expected to be polar compounds such as carboxylic acids,<br />
ketones and lactones. The products <strong>of</strong> oxidation from the waste sample were<br />
79
Results and Discussion<br />
injected into an APCI-MS as well as into the ESI-MS. Spectra <strong>of</strong> waste extract<br />
before and after oxidation were recorded. Figures 3-49 and 3-50 show the positive<br />
APCI mass spectra <strong>of</strong> the waste before and after oxidation respectively.<br />
Intens.<br />
[%]<br />
100<br />
411.4<br />
+MS<br />
80<br />
60<br />
329.3<br />
561.6<br />
40<br />
663.5<br />
20<br />
0<br />
250 300 350 400 450 500 550 600 650 m/z<br />
Figure 3-49 Positive APCI mass spectrum <strong>of</strong> waste sample before oxidation<br />
Intens.<br />
[%]<br />
100<br />
295.2<br />
391.3<br />
+MS<br />
80<br />
337.3<br />
419.3<br />
60<br />
353.3<br />
40<br />
20<br />
447.4<br />
481.4<br />
509.5 565.5<br />
591.6<br />
647.6<br />
663.5<br />
681.5<br />
0<br />
250 300 350 400 450 500 550 600 650 m/z<br />
Figure 3-50 Positive APCI mass spectrum <strong>of</strong> waste sample after oxidation<br />
80
Results and Discussion<br />
Instant inspection <strong>of</strong> the figures confirms oxidation yield is very high and this is<br />
supported by the huge shift in the mass distribution in the positive APCI-MS<br />
spectrum <strong>of</strong> the waste sample after oxidation. Also positive and negative ion mode<br />
ESI-TOF-MS spectra were acquired for the oxidation products as shown in figures<br />
3-51 and 3-52. This suggested that other nonreacted products can be differentiated<br />
from those in APCI-MS because nonreacted species can only ionise upon APCI<br />
source. Next, molecular assignment for oxidation product in both ESI and APCI<br />
spectra was performed. The molecular formulas suggest carboxylic and ketone<br />
groups are present. However, this oxidation process alone can not give that insight<br />
about the source <strong>of</strong> these products. A model hydrocarbon complex mixture was<br />
designed and prepared. The model mixture consisted <strong>of</strong> linear alkanes such as C20,<br />
C21, C23, C26, C32, C36 and C40 as well as from few other standards 5-αcholestane,<br />
squalane and squalene. These compounds were subjected to oxidation<br />
with chromium trioxide using the same procedure performed for the complex<br />
mixture <strong>of</strong> the waste extract. The products <strong>of</strong> this model complex mixture were<br />
measured by ESI-TOF-MS in both positive and negative modes. Figure 3-53<br />
shows the negative ESI MS spectrum <strong>of</strong> model mixture <strong>of</strong> hydrocarbons.<br />
Comparing the latter spectrum to the negative ESI mass spectrum <strong>of</strong> oxidation<br />
products <strong>of</strong> the waste sample mixture demonstrated a dramatic resemblance. It was<br />
clearly observed that products <strong>of</strong> the model mixture are among the products <strong>of</strong> the<br />
complex mixture <strong>of</strong> the waste sample. This suggested that the complex mixture<br />
composition is composed or at least contains compounds similar to the ones within<br />
the model mixture. This was emphasized from the oxidation <strong>of</strong> representative<br />
hydrocarbons which supported these suggestions. Oxidative degradation does<br />
provide some useful additional information about the complex mixture<br />
composition. After direct and indirect exploring <strong>of</strong> the complex hydrocarbon<br />
mixture within the light shredder waste fraction, a quantitative figure is discussed<br />
in the following section.<br />
81
Results and Discussion<br />
Intens.<br />
[%]<br />
100<br />
349.2<br />
393.2<br />
+MS<br />
80<br />
305.2<br />
377.2<br />
437.2<br />
60<br />
265.2<br />
323.2<br />
421.2<br />
481.3<br />
40<br />
465.2<br />
525.3<br />
20<br />
569.3<br />
613.3<br />
0<br />
200 250 300 350 400 450 500 550 600 650 m/z<br />
Figure 3-51 Positive ESI mass spectrum <strong>of</strong> complex waste mixture after oxidation<br />
Intens.<br />
[%]<br />
100<br />
215.6<br />
-MS<br />
80<br />
60<br />
171.5<br />
40<br />
20<br />
0<br />
150 200 250 300 350 400 450 500 550 m/z<br />
Figure 3-52 Negative ESI mass spectrum <strong>of</strong> complex waste mixture after<br />
oxidation<br />
82
Results and Discussion<br />
Intens.<br />
[%]<br />
100<br />
80<br />
60<br />
143.1<br />
171.1<br />
201.1<br />
215.1<br />
229.1<br />
243.1<br />
257.1<br />
-MS<br />
40<br />
20<br />
129.1<br />
313.1<br />
411.1<br />
115.0<br />
483.4<br />
0<br />
100 150 200 250 300 350 400 450 500 m/z<br />
Figure 3-53 Negative ESI mass spectrum <strong>of</strong> model mixture <strong>of</strong> hydrocarbon after<br />
oxidation<br />
83
Results and Discussion<br />
3.4.8 Quantification<br />
Through out the whole waste spectrum, it was noticed that nearly all <strong>of</strong> the n-<br />
alkanes identified had low intensities compared to other compounds in the sample.<br />
In an attempt to know whether the low n-alkane’s intensities found in waste<br />
spectrum are attributed to ion-suppression or not, I spiked the waste matrix with<br />
some high mass n-alkanes like C26, C32, C36 and C40 as shown in figure 3-54.<br />
These compounds enhanced their corresponding (M-1) + ions that are originally<br />
found within the waste sample without any significant ion suppression observed.<br />
Intens.<br />
[%]<br />
100<br />
C36<br />
505.6<br />
+MS<br />
80<br />
60<br />
C26<br />
399.4<br />
C32<br />
449.5<br />
40<br />
20<br />
315.3<br />
481.5<br />
C40<br />
561.6<br />
663.5<br />
0<br />
200 250 300 350 400 450 500 550 600 650 m/z<br />
Figure 3-54 APCI mass spectrum <strong>of</strong> spiked waste mixture with high mass n-<br />
alkanes<br />
This concludes that the n-alkanes in the waste are initially having low quantities<br />
within the waste fraction. This would be indicative for the extent <strong>of</strong> biodegradation<br />
<strong>of</strong> the waste as linear alkanes are the first to degrade among other hydrocarbons.<br />
Another indirect experiment was performed to assess the possibility to quantify n-<br />
alkanes within the applied APCI-TOF-MS methodology. Using an isotope dilution<br />
experiment with a selected polydeuterated n-alkane C 32 D 66 (figure 3-55), a linear<br />
response was found which allowed to show that in this complex mixture no ion<br />
suppression effects were operating allowing adequate quantification <strong>of</strong> single n-<br />
alkanes or groups <strong>of</strong> n-alkanes. For quantification, different concentrations <strong>of</strong> C7-<br />
C40 standard mixture (0.2, 1, 4, 6, 10, 15, 20, 25, 35, 45 and 50 µg/ml) were<br />
prepared by dilution and were injected afterwards to establish calibration curves.<br />
84
Results and Discussion<br />
Using model mixture C7-C40, calibration curves for all the analytes were<br />
established. A linear response between concentration (ranging from 0.2 to 50<br />
µg/ml) and the intensity recorded in the positive mass spectrum under APCI-MS<br />
was observed. The linearity graphs for few analytes like C20, C29, C38 and C40<br />
are shown in figures 3-56 to 3-59.<br />
Intens.<br />
[%]<br />
100<br />
80<br />
60<br />
40<br />
20<br />
0<br />
343.3 369.3 395.4 413.4 482.9<br />
499.9 519.9 537.9<br />
+MS<br />
350 400 450 500 550 600 m/z<br />
Figure 3-55 APCI mass spectrum <strong>of</strong> deuterated dotriacontane C 32 D 66<br />
14<br />
12<br />
10<br />
Int.<br />
8<br />
x 10000<br />
C20<br />
6<br />
4<br />
y = 2995.5x + 11159<br />
R² = 0.99<br />
2<br />
0<br />
0 10 20 30 40 50<br />
ppm<br />
Figure 3-56 A plot between Concentration vs Intensity for C20<br />
85
Results and Discussion<br />
Int.<br />
x 10000<br />
25<br />
20<br />
15<br />
C29<br />
10<br />
y = 4768.8x + 6714.8<br />
R² = 0.9967<br />
5<br />
0<br />
0 10 20 30 40 50<br />
ppm<br />
Figure 3-57 A plot between Concentration vs Intensity for C29<br />
Int.<br />
60<br />
x 10000<br />
50<br />
C38<br />
40<br />
30<br />
20<br />
10<br />
0<br />
y = 11840x + 9931.1<br />
R² = 0.9958<br />
0 10 20 30 40 50<br />
ppm<br />
Figure 3-58 A plot between Concentration vs Intensity for C38<br />
86
Results and Discussion<br />
Int.<br />
70<br />
60<br />
50<br />
x 10000<br />
C40<br />
40<br />
30<br />
20<br />
y = 14165x + 4479.9<br />
R² = 0.9961<br />
10<br />
0<br />
0 10 20 30 40 50<br />
ppm<br />
Figure 3-59 A plot between Concentration vs Intensity for C40<br />
Using these linearity graphs, a quantitative figure <strong>of</strong> few n-alkanes was deduced.<br />
Table 3.6 presents the quantities <strong>of</strong> C20, C23, C32, C36 and C40 present in a 1 ml<br />
waste extract. Next a standard addition experiment was conducted for C36. The<br />
addition <strong>of</strong> a known quantity <strong>of</strong> C36 into the native quantity <strong>of</strong> C36 within the the<br />
same 1 ml <strong>of</strong> waste sample was monitored. The addition <strong>of</strong> 40 µl <strong>of</strong> a 1 mg/ml<br />
prepared standard <strong>of</strong> C36, that individually provoked 3 µg/ml, to the same 1 ml<br />
solution <strong>of</strong> the waste extract produced a total <strong>of</strong> 17 µg/ml. According to table 3.6,<br />
the latter value was found cumulative for native and spiked quantities <strong>of</strong> C36. This<br />
demonstrated success <strong>of</strong> not just quantitating a native amount <strong>of</strong> a single n-alkane<br />
(C36) but as well reflecting a promising response that C36 exhibited when a little<br />
quantity was added. This is an advantage for monitoring the quantities <strong>of</strong> certain n-<br />
alkane analytes within the waste sample subjected to biological degradation or<br />
other weathering conditions. Addition experiments were tested for C40 where<br />
similar results were attained. However it is important to mention that the addition<br />
method wasn’t applicable when low n-alkane’s quantities were spiked to the waste<br />
matrix. This can be attributed to the limit <strong>of</strong> detection <strong>of</strong> these n-alkanes under<br />
APCI-TOF-MS method. As well few n-alkanes were seen not to respond<br />
efficiently with such addition experiments upon the applied methodology.<br />
87
Results and Discussion<br />
Table 3.6 Quantities <strong>of</strong> few selected n-alkanes in waste samples<br />
APCI-TOF-MS<br />
Alkane<br />
Extract Spiked C36 Extract + C36<br />
(µg/ml) (µg/ml) (µg/ml)<br />
C20 34 – –<br />
C23 45 – –<br />
C32 28 – –<br />
C36 14 3 17<br />
C40 10 – –<br />
3.5 Application <strong>of</strong> the Methodology to Other Complex Mixtures<br />
3.5.1 Analysis <strong>of</strong> Solid Waste from Lebanon<br />
With more than 4200 tons <strong>of</strong> solid waste produced daily out <strong>of</strong> household,<br />
industrial and medical sources, Lebanon suffers from uncontrolled garbage<br />
mountains randomly distributed all over its area. The accumulation <strong>of</strong> such<br />
heterogeneous waste is considered one <strong>of</strong> the chronic environmental problems in<br />
this country. Daily waste deposition contains 60% organic material, 15%, cartoon,<br />
5% plastic and others. Unfortunately only 10% <strong>of</strong> the waste is recycled daily, the<br />
rest is sent to readily over-load random dumps or landfills known as well as<br />
“Garbage Mountains”. Unfortunately there is a continuous leakage <strong>of</strong> liquids rich<br />
in heavy metals and toxic chemicals towards the sea. Even parts <strong>of</strong> the<br />
accumulated waste fall directly to the sea as in famous ‘Saida Garbage Mountain’<br />
(30 km from Capital). ‘Ras El-Ein Garbage Dump’ (80 km from Capital),<br />
permanently closed recently, is still an unclear threaten for the groundwater source<br />
just few meters away from the dump. On the other side accumulation <strong>of</strong> these<br />
massive waste mixtures subjected to weathering conditions, periodic incineration<br />
activities and bacterial degradation arouse an alarming pollution affecting the<br />
health <strong>of</strong> the surrounding people and the environment. Unfortunately, to the best <strong>of</strong><br />
88
Results and Discussion<br />
my knowledge, no analyses or other kinds <strong>of</strong> monitoring activities have<br />
specifically utilized a precise analytical method to determine accurate data<br />
concerning the composition <strong>of</strong> the existing solid waste in uncontrolled dumps.<br />
Since these dumps are thought to be sources <strong>of</strong> hazardous complex mixtures and<br />
are hitherto unknown which components are present in these mixtures, I suggested<br />
to apply our current light shredder waste analytical methodology to such complex<br />
mixture <strong>of</strong> mixed solid waste in Lebanon. Samples were brought from ‘Garbage<br />
Mountain’ in the city <strong>of</strong> Saida. Two samples were taken from the garbage<br />
mountain at different intervals <strong>of</strong> time in May 2011 and July 2011. The samples<br />
were extracted, purified and measured in a similar fashion to the light shredder<br />
waste in Bremen. Sample 1 appears as in figure 3-60 to have a relatively higher<br />
mass distribution (m/z 200 to 800), but similar collection <strong>of</strong> signals compared to<br />
light shredder waste. The negative MS spectrum <strong>of</strong> the first sample was as well<br />
obtained.<br />
The mass spectrum observed in figure 3-61 demonstrated the presence <strong>of</strong> few<br />
polychlorinated biphenyls compounds. It included hexachlorobiphenyl at m/z<br />
340.9, heptachlorobiphenyl at m/z 374.8 and octachlorobiphenyl at m/z 408.8 that<br />
were identified by the (-) APCI method. This shows that even with the different<br />
nature and source <strong>of</strong> the solid waste in Lebanon, the method can be beneficial in<br />
identifying PCBs elsewhere. The low relative abundance <strong>of</strong> the PCBs is related to<br />
the fact that the sample belongs to a heterogeneous and untreated waste dump.<br />
This finding gives an indication that the remaining series <strong>of</strong> PCBs can be present.<br />
Knowing that there is a wide range <strong>of</strong> toxic substances (e.g. tannery waste and<br />
paints) that arrive at the waste site on a daily basis, this can be the source <strong>of</strong> toxic<br />
PCBs pollutants.<br />
Regarding the second sample, the positive mass spectrum shown in figure 3-62,<br />
appears to have also an equal number <strong>of</strong> compounds as compared to light shredder<br />
waste. However the negative mass spectrum <strong>of</strong> this sample doesn’t contain any<br />
PCBs as far as shown in figure 3-63. The work done with waste samples from<br />
Lebanon is considered a remarkable groundwork study towards a critical<br />
89
Results and Discussion<br />
assessment <strong>of</strong> the chemical content <strong>of</strong> the random solid waste dumps in Lebanon.<br />
This should raise the interest for alleviating waste problems by enhanced<br />
management supported by analytical research.<br />
Intens.<br />
[%]<br />
100<br />
307.2<br />
397.4<br />
369.3<br />
+MS<br />
80<br />
60<br />
257.2 285.3<br />
453.4<br />
481.5509.5537.5<br />
663.5<br />
40<br />
20<br />
729.8<br />
771.8<br />
0<br />
200 300 400 500 600 700 800m/z<br />
Figure 3-60 Positive APCI mass spectrum <strong>of</strong> Lebanese waste sample 1<br />
Intens.<br />
[%]<br />
100<br />
473.3<br />
-MS<br />
80<br />
489.2<br />
60<br />
40<br />
20<br />
0<br />
255.2<br />
283.3<br />
205.1<br />
220.1<br />
C 12 H 5 OCl 5<br />
C12 H 4 OCl 6<br />
314.1 340.8<br />
408.3<br />
374.8<br />
423.3 456.3<br />
200 250 300 350 400 450 500 m/z<br />
529.4<br />
Figure 3-61 Negative polarity APCI <strong>of</strong> Lebanese waste sample 1<br />
90
Results and Discussion<br />
Intens.<br />
[%]<br />
100<br />
80<br />
60<br />
40<br />
20<br />
257.2 287.3<br />
397.4<br />
453.4 497.4 525.5<br />
+MS<br />
0<br />
300 400 500 600 700 800 900 m/z<br />
Figure 3-62 Positive APCI mass spectrum <strong>of</strong> Lebanese waste sample 2<br />
Intens.<br />
[%]<br />
100<br />
80<br />
60<br />
40<br />
20<br />
0<br />
-MS<br />
255.2<br />
473.3<br />
283.3<br />
264.8<br />
409.3<br />
230.9<br />
243.1 333.1<br />
423.4<br />
445.1<br />
298.1 322.2<br />
367.3 381.3 459.4<br />
507.5<br />
250 300 350 400 450 500m/z<br />
Figure 3-63 Negative polarity APCI mass spectrum <strong>of</strong> Lebanese waste sample 2<br />
3.5.2 Analysis <strong>of</strong> Car Motor Oil<br />
Companies <strong>of</strong> car motor oil has been simultaneously competing and advertising for<br />
the best blend that can perform as car motor oil enduring thermal and other drastic<br />
conditions inside the engine. Composition <strong>of</strong> car oil engine is considered a heavily<br />
guarded trade secret that varies greatly from conventional to synthetic oils. In<br />
recent decades, synthetic motor oil has become a common option for cars. This is<br />
because synthetic motor oil is slower to decompose chemically. The composition<br />
<strong>of</strong> synthetic motor oil is also superior to that <strong>of</strong> traditional motor oil. Motor oils are<br />
derived from petroleum-based and non-petroleum-synthesized chemical<br />
compounds. Motor oils today are mainly blended by using base oils composed <strong>of</strong><br />
91
Results and Discussion<br />
hydrocarbons, polyalphaolefins (PAO), and polyinternal olefins (PIO), thus<br />
organic compounds consisting entirely <strong>of</strong> carbon and hydrogen. The bulk <strong>of</strong><br />
typical motor oil consists <strong>of</strong> hydrocarbons with between 18 and 34 carbon atoms<br />
per molecule that is why we see peak shape spectrum.<br />
Car oil technology is complex in many factors in terms <strong>of</strong> viscosity, additives<br />
effect and corrosion inhibition. The oil in a motor oil product does not break down<br />
or burn as it is used in an engine, it simply gets contaminated with particles and<br />
chemicals that make it a less effective lubricant. Re-refining cleans the<br />
contaminants and used additives out <strong>of</strong> the dirty oil. But what makes the car motor<br />
oil slower to decompose chemically or less susceptible to evaporation over time is<br />
indeed a question about the oil’s composition.<br />
From this background, I considered the analysis <strong>of</strong> a selection <strong>of</strong> car motor oil<br />
from different companies in Germany. The selection <strong>of</strong> oils is shown in table 3.7.<br />
Some <strong>of</strong> these oils are for other specific uses such as transmission fluid. A dirty car<br />
oil from an unknown car is present within the list. The samples were diluted in n-<br />
heptane before direct infusion into the APCI. The mass distribution and<br />
composition <strong>of</strong> each sample are well defined in their mass spectra. For example S1<br />
comprises a dominant odd mass distribution with an exception <strong>of</strong> one compound<br />
having an m/z 422 as shown in figure 3-64. In contrast the mass spectrum <strong>of</strong> S2,<br />
presented in figure 3-65, is very simple comprising a series <strong>of</strong> n-alkanes up to<br />
pentacosane (C50) at m/z 701. The molecular composition was identified using the<br />
same calibrated APCI method that allows elemental assignment. While S3 looks<br />
similar to S2 as revealed from figure 3-66, S4 reflects a very complex composition<br />
over a high mass range m/z 400 to 1000 demonstrated in figure 3-67. This is<br />
attributed to the presence <strong>of</strong> longer hydrocarbon isomers contributing to the<br />
viscous nature <strong>of</strong> the oil. The bulk <strong>of</strong> S4 mass spectrum is concentrated at m/z<br />
range 600-800 suggesting that the present hydrocarbons are in the range C40 to<br />
C60. The elemental composition suggests that the components are series <strong>of</strong> high<br />
mass unsaturated compounds. This oil thus has a different usability. The mass<br />
spectra presented in figure 3-68 <strong>of</strong> transmission oil <strong>of</strong> Liqui Moly Company was<br />
92
Results and Discussion<br />
found to comprise an m/z 422 which was observed earlier in S1. This looks like the<br />
secret even mass additive inserted to the regular components. Similar to S4, the<br />
grease sample S7 in figure 3-69 covers a wide mass range (m/z 200 to m/z 700).<br />
The contaminated through usage car motor oil (S9) appears to comprise additional<br />
components not generally observed in other car motor oil samples within the<br />
chosen list. The mass spectrum appears to have a depleted composition as shown<br />
in figure 3-70.<br />
Table 3.7 A selection <strong>of</strong> different car oils from different companies<br />
Sample Trade Name Specification<br />
S1 Calpam Mineral öl Motorenöl 10-40 W<br />
S2 LIQUI MOLY GmbH 5 W - 30 HC Synthese<br />
S3 Mitan Mineraöl GmbH SAE 15 W-40<br />
S4 Castrol Epx 90 Viscous<br />
S5 Pentosin For central Hydraluc system<br />
S6 LIQUI MOLY GmbH Transmission fluid<br />
S7 Grease CRC MoS2<br />
S8 Ford 75-90 BO (Transmission Öl)<br />
S9 Dirty Oil from unknown car Used<br />
S10 Aral Motoröl (Old Auto) 15W-40<br />
S11 Alpine TS 10W-40 (Semi synthetic)<br />
93
Results and Discussion<br />
Intens.<br />
[%]<br />
100<br />
422.4<br />
+MS<br />
80<br />
397.4<br />
60<br />
369.3<br />
40<br />
257.2<br />
285.3<br />
355.3<br />
439.4<br />
20<br />
245.2<br />
561.6<br />
0<br />
200 250 300 350 400 450 500 550 600 m/z<br />
Figure 3-64 APCI mass spectrum <strong>of</strong> S1<br />
Intens.<br />
[%]<br />
100<br />
421.5<br />
+MS<br />
80<br />
561.6<br />
60<br />
40<br />
20<br />
0<br />
239.3 267.3 295.3 323.4<br />
391.3<br />
449.5<br />
464.5<br />
200 300 400 500 600 700m/z<br />
599.6<br />
701.7<br />
Figure 3-65 APCI mass spectrum <strong>of</strong> S2<br />
Intens.<br />
[%]<br />
100<br />
397.4<br />
+MS<br />
80<br />
425.4<br />
60<br />
439.4<br />
40<br />
242.9<br />
355.3<br />
20<br />
257.2 301.3<br />
0<br />
200 250 300 350 400 450 500 550 600 m/z<br />
Figure 3-66 APCI mass spectrum <strong>of</strong> S3<br />
94
Results and Discussion<br />
Intens.<br />
[%]<br />
100<br />
+MS<br />
80<br />
647.6 687.6<br />
743.7<br />
759.7<br />
60<br />
40<br />
20<br />
993.9<br />
0<br />
500 600 700 800 900 1000 m/z<br />
Figure 3-67 APCI mass spectrum <strong>of</strong> S4<br />
Intens.<br />
[%]<br />
100<br />
80<br />
60<br />
40<br />
20<br />
0<br />
147.0<br />
181.0<br />
197.0 296.2<br />
337.2<br />
379.3<br />
422.3<br />
447.3<br />
547.3 579.5<br />
+MS<br />
100 150 200 250 300 350 400 450 500 550 600m/z<br />
Figure 3-68 APCI mass spectrum <strong>of</strong> S6<br />
Intens.<br />
[%]<br />
100<br />
80<br />
60<br />
40<br />
213.2<br />
255.2 283.2 411.4<br />
+MS<br />
20<br />
0<br />
200 300 400 500 600 700 m/z<br />
Figure 3-69 APCI mass spectrum <strong>of</strong> S7<br />
95
Results and Discussion<br />
Intens.<br />
[%]<br />
100<br />
379.3<br />
422.3<br />
511.4<br />
+MS<br />
80<br />
60<br />
40<br />
147.0<br />
207.1<br />
296.2<br />
20<br />
0<br />
663.4<br />
200 300 400 500 600 m/z<br />
Figure 3-70 APCI mass spectrum <strong>of</strong> S9 (contaminated through usage oil)<br />
3.5.3 Analysis <strong>of</strong> Asphaltenes<br />
The analysis <strong>of</strong> asphaltenes has been reviewed in many studies. Asphaltenes are<br />
described as fractions that are insoluble in n-heptane. Such fractions comprise a<br />
high degree <strong>of</strong> aromaticity and can contain nitrogen, oxygen and sulphur<br />
atoms.The mass distribution <strong>of</strong> asphaltenes had been a controversial topic as<br />
well. 89 The analysis <strong>of</strong> asphaltenes is considered a challenging field due to<br />
complexity, high boiling points, solubility and tendency to aggregate. While my<br />
contribution aims at examining the volatility and ionisation <strong>of</strong> complex<br />
hydrocarbon mixtures, I investigated some bitumen samples by looking at their<br />
mass distribution and ionisation behaviour. Due to limited resources, I only had to<br />
look at asphalt samples that are already mixed with other solid particles. Samples<br />
from two companies were diluted in different solvents and measured under the<br />
same methodology. Bitumen 1 from Bay-systems and Bitumen 2 from Deuter<br />
Lindenhagen were chosen for this investigation experiment. The solvents that were<br />
used to extract hydrocarbons from these samples were dichloromethane (DCM), n-<br />
heptane and toluene. Sample 1 was measured by ESI-MS and by APCI using DCM<br />
as shown in figures 3-71 and 3-72. By visual scanning <strong>of</strong> each spectrum, it appears<br />
that the composition vary widely between ESI and APCI. ESI comprised high<br />
mass hydrocarbons that are not observed in the APCI spectrum. The APCI<br />
96
Results and Discussion<br />
spectrum appears to comprise less number <strong>of</strong> analytes than that <strong>of</strong> ESI.<br />
Nevertheless the components <strong>of</strong> Bitumen 1 are successfully ionised without any<br />
recorded fragmentation. Since such asphaltene fractions has been mainly<br />
measured by ESI or other revolutionised methodologies, 89,100 the acquisition <strong>of</strong><br />
such data under APCI conditions proves the importance <strong>of</strong> the methodology to<br />
attain a deeper understanding <strong>of</strong> asphaltenes. Regarding Bitumen 2, the sample<br />
was dissolved in DCM and injected into the APCI source. The mass spectra <strong>of</strong> this<br />
sample shown in figure 3-73 suggests a huge similarity to bitumen 1 however the<br />
matching components differ with their relative abundances in both samples. This<br />
would suggest that the two samples revert to two different sources <strong>of</strong> original<br />
asphaltenes. In both samples there had been many analytes that appeared with low<br />
abundance. Some <strong>of</strong> them were even hardly resolved with the TOF-MS. In my<br />
opinion the interface <strong>of</strong> APCI to high resolution MS should be established to<br />
effectively then analyse full compositions <strong>of</strong> complex mixtures.<br />
Intens.<br />
[%]<br />
100<br />
80<br />
60<br />
40<br />
20<br />
0<br />
+MS<br />
555.4<br />
511.4<br />
274.2<br />
599.4 659.4<br />
703.5<br />
467.4<br />
747.5<br />
236.1<br />
372.2 441.3<br />
190.1<br />
791.5<br />
835.5 879.6<br />
200 300 400 500 600 700 800 900 m/z<br />
Figure 3-71 ESI mass spectrum <strong>of</strong> bitumen 1 using DCM as mobile phase<br />
97
Results and Discussion<br />
Intens.<br />
[%]<br />
100<br />
297.2<br />
+MS<br />
80<br />
403.3<br />
60<br />
40<br />
241.2<br />
319.1<br />
347.2<br />
467.1<br />
541.4<br />
20<br />
663.4<br />
0<br />
200 300 400 500 600 700 800 900 m/z<br />
741.2<br />
Figure 3-72 APCI mass spectrum <strong>of</strong> bitumen 1 using DCM as mobile phase<br />
Intens.<br />
[%]<br />
100<br />
80<br />
242.9<br />
257.2<br />
+MS<br />
60<br />
285.3<br />
383.2<br />
40<br />
218.8<br />
316.7<br />
20<br />
0<br />
347.2 403.3 467.1<br />
190.8<br />
507.5 541.4 639.6663.5<br />
200 250 300 350 400 450 500 550 600 650 m/z<br />
Figure 3-73 APCI mass spectrum <strong>of</strong> bitumen 2 using DCM as mobile phase<br />
3.6 Kendrick Plot and Interpretation <strong>of</strong> Complex Data from Various<br />
Complex Mixtures<br />
3.6.1 Light Shredder Waste<br />
The externally calibrated masses <strong>of</strong> the waste sample were converted to Kendrick<br />
masses and sorted into groups according to common Kendrick mass defect. The<br />
compositional analysis is then displayed in the Kendrick plot represented in figure<br />
3-74. This is <strong>of</strong> course inspired from the employment <strong>of</strong> such plots to display<br />
chemical contents <strong>of</strong> complex mixtures in other sources measured by the group <strong>of</strong><br />
Marshall extensively discussed earlier. The chemically sorted display shows other<br />
98
Results and Discussion<br />
members <strong>of</strong> a homologous alkylation series. For example alkanes are sorted<br />
horizontally to the value <strong>of</strong> KMD=1 separated by number <strong>of</strong> alkyl (CH 2 ) groups<br />
whereas the other degraded compounds are appearing in a vertical arrangement<br />
according to their degrees <strong>of</strong> unsaturation (number <strong>of</strong> double bonds). Around 800<br />
elemental compositions in a single waste extract in positive ion mass spectrum<br />
were rapidly distinguised in the plot. To the best <strong>of</strong> our knowledge this is the first<br />
time Kendrick plot is employed to display a nonpolar hydrocarbon content <strong>of</strong> a<br />
certain complex mixture. This 2D chemical sorting allowed tracing the<br />
biodegradation <strong>of</strong> the n-alkanes. The reduction in the number and amount <strong>of</strong> n-<br />
alkanes is greatly desired before the waste would be approved for final landfill.<br />
KMD<br />
1.0<br />
0.8<br />
0.6<br />
100 200 300 400 500 600 700 800<br />
NKM<br />
Figure 3-74 Kendrick plot for the light shredder waste<br />
It is emphasized from the above graph that 90% <strong>of</strong> the components are<br />
hydrocarbons having a KMD around 1. The majority <strong>of</strong> the content appears as<br />
explained earlier to be degraded compounds varying by their doubly bond<br />
equivalents as their unsaturation degrees. The horizontal lines having different<br />
KMD values suggest a dehydrogenation process taking place during microbial<br />
processing. (M-1) + ions <strong>of</strong> n-alkanes are aligned horizontally at KMD = 0. (M-1) +<br />
ions <strong>of</strong> n-alkanes aligned at KMD=0, a line which is not shown in the plot because<br />
y-axis is enlarged for better screening <strong>of</strong> the set <strong>of</strong> data points. Molecular ions, M •+<br />
99
Results and Discussion<br />
<strong>of</strong> n-alkanes are aligned at KMD=0. Figure 3-75 shows a plot <strong>of</strong> measured mass<br />
<strong>of</strong> hydrocarbon components against double bond equivalence (DBE; degree <strong>of</strong><br />
unsaturation). The graph clearly shows, similar to Kendrick plot, a pattern showing<br />
parallel horizontal lines expressing different degrees <strong>of</strong> unsaturation within the<br />
degraded hydrocarbons constituting the chemical content <strong>of</strong> the waste.<br />
15<br />
DBE<br />
RDB<br />
10<br />
5<br />
0<br />
200 300 400 500 600 700<br />
Measured m/z<br />
Figure 3-75 Plot <strong>of</strong> DBE vs measured mass (m/z) for the hydrocarbon compone-<br />
nts <strong>of</strong> waste<br />
H/C<br />
2.5<br />
2<br />
1.5<br />
1<br />
0.5<br />
0<br />
0 5 10 15 20<br />
DBE<br />
Figure 3-76 Plot <strong>of</strong> H/C ratio vs DBE <strong>of</strong> a light shredder waste sample<br />
100
Results and Discussion<br />
Another graphical compositional image is a typical plot <strong>of</strong> H/C ratio vs. DBE<br />
(degree <strong>of</strong> unsaturation). Figure 3-76 shows such a plot for a measured light<br />
shredder waste sample. The H/C ratio was calculated from the molecular formulas<br />
<strong>of</strong> the waste components whereas the DBE values were obtained from the Data<br />
analysis program <strong>of</strong> the Bruker s<strong>of</strong>tware. From the graph it can be noticed that the<br />
majority <strong>of</strong> compounds within the waste extract are those having a DBE range <strong>of</strong><br />
4-8. n-Alkanes, that are found in the chemical content <strong>of</strong> the waste sample, are<br />
aligned at H/C value <strong>of</strong> 2 and DBE <strong>of</strong> 0.5. The latter value <strong>of</strong> DBE for n-alkanes<br />
results from their ionisation as (M-1) + . The DBE values <strong>of</strong> all the analytes <strong>of</strong> the<br />
waste are not adjusted against ionisation. The rule that lower H/C ratio corresponds<br />
to higher DBE is demonstrated in this plot. Of course the graph reflects a<br />
preferential dehydrogenation process arising from the high number <strong>of</strong> unsaturated<br />
compounds.<br />
Other effects like treatment <strong>of</strong> shredder waste on a small scale reactor and<br />
weathering <strong>of</strong> deposited shredder waste were frequently tracked by Kendrick plots.<br />
Our Project partners studied the effect <strong>of</strong> hydrothermal and aeration conditions<br />
over the waste in a small scale reactor in terms <strong>of</strong> time. Table 3.8 shows examples<br />
<strong>of</strong> treated samples on small scale under different conditions. Using the developed<br />
methodology, the samples were extracted and analysed accordingly. For example<br />
comparison <strong>of</strong> two different waste samples was performed by overlapping their<br />
two Kendrick plots. Figure 3-77 shows the Kendrick plot for initial sample I2 and<br />
I3 (Initial untreated samples) which were cropped at different times. I2 and I3 well<br />
overlap in the m/z 200 to 500 but differ significantly in the range m/z 500 to 1000.<br />
This shows that although these samples are similarly treated and their sources are<br />
roughly the same, they still vary according to Kendrick plot. The Kendrick plot<br />
here proves to be a magnificent chemical display to detect differences among<br />
samples. After that each sample on separate was treated under certain conditions in<br />
a small scale reactor. For example I1 (Initial sample cropped on 14.12.2010) was<br />
treated in duplicate under defined conditions as shown in table 3.8. The treatment<br />
was probed by subjecting the initial samples to different conditions such as air<br />
101
Results and Discussion<br />
flow (in I2) and varying operating time (in I3). Treated samples <strong>of</strong> I1 and I2 were<br />
established to be as pilot tests for the validity <strong>of</strong> I3. In Figure 3-78, the differences<br />
in Kendrick plots between I3 and its three treated samples, R1.3, R2.3 and R3.3,<br />
with different operating times are tracked. By a critic look, sample R3.3 (14 days)<br />
was found to show some evolution in composition compared to initial I3. Many I3<br />
components are not present in the treated R3.3. The change within samples R2.2<br />
(22 days) was similar to that <strong>of</strong> R3.3, however more compounds disappeared in the<br />
high range (m/z 500-900). The largest difference <strong>of</strong> KMD values, however, is<br />
between the set <strong>of</strong> data points <strong>of</strong> R1.3 (31 days) and I3. It can be concluded that<br />
the increase <strong>of</strong> operating time in this case enhanced the degradation process <strong>of</strong><br />
shredder waste.<br />
Table 3.8 Operating conditions <strong>of</strong> small scale treatment reactor <strong>of</strong> shredder waste<br />
Sample<br />
Date<br />
Conditions<br />
Temperature Air flow Input water<br />
Operating<br />
Time<br />
1<br />
I 1 12/14/2010<br />
R 1.1 12/14/2010 60 °C 1,5 L/h 120 mL/d 22 days<br />
R 2.1 12/14/2010 60 °C 1,5 L/h 120 mL/d 22 days<br />
2<br />
I 2 12/22/2010<br />
R 1.2 12/22/2010 60 °C 1,5 L/h 120 mL/d 20 days<br />
R 2.2 12/22/2010 60 °C 3,0 L/h 120 mL/d 20 days<br />
R 3.2 12/22/2010 60 °C 3,0 L/h 120 mL/d 20 days<br />
3<br />
I 3 04/02/2011<br />
R 1.3 3/16/2011 60 °C 3,0 L/h 120 mL/d 31 days<br />
R 2.3 3/16/2011 60 °C 3,0 L/h 120 mL/d 22 days<br />
R 3.3 3/16/2011 60 °C 3,0 L/h 120 mL/d 14 days<br />
102
Results and Discussion<br />
KMD<br />
1.1<br />
1<br />
I2<br />
0.9<br />
I3<br />
0.8<br />
0.7<br />
0.6<br />
0 200 400 600 800 1000 1200<br />
NKM<br />
Figure 3-77 Kendrick plot overlap <strong>of</strong> untreated I2 and I3 waste samples<br />
1.05<br />
KMD<br />
1<br />
I3<br />
0.95<br />
R1.3<br />
0.9<br />
R2.3<br />
0.85<br />
R3.3<br />
0.8<br />
0.75<br />
100 200 300 400 500 600 700 800 900 1000 1100<br />
NKM<br />
Figure 3-78 Kendrick plot overlap <strong>of</strong> I3 and treated sample on small scale<br />
103
Results and Discussion<br />
Other interesting comparison involved overlapping the Kendrick plots <strong>of</strong> waste<br />
sample, which was preserved from 2009, with another freshly treated one from<br />
2011. However to attain a confident figure <strong>of</strong> this comparison, some few<br />
parameters <strong>of</strong> data analysis were considered according to table 3.9. After<br />
establishing their Kendrick plot, the display quickly discriminates between the two<br />
waste samples. Degradation seems more evincive with 2009 sample according to<br />
figure 3-79. This is attributed to persistent compositional evolution as time elapses.<br />
Hydrocarbons within sample 2009 are expected to be comprising higher<br />
unsaturation degrees than those in 2011 sample. This is parallel to reduced values<br />
<strong>of</strong> KMD <strong>of</strong> the hydrocarbons in sample 2009 compared to those <strong>of</strong> 2011 sample.<br />
Table 3.9 Acquisition <strong>of</strong> data points considered in 2009 and 2011 samples<br />
# Sample taken Total Signals S/N Filter Signals<br />
Waste (2009) 3/11/2009 1065 50 820<br />
Waste (2011) 4/2/2011 1200 30 800<br />
1.1<br />
KMD<br />
1<br />
W (2009)<br />
0.9<br />
0.8<br />
W (2011)<br />
0.7<br />
0.6<br />
0.5<br />
0 100 200 300 400 500 600 700 800 900 1000<br />
NKM<br />
Figure 3-79 Kendrick plot overlap between 2009 and 2011 waste samples<br />
104
Results and Discussion<br />
Another graphical representation was performed for a set <strong>of</strong> 5 light shredder waste<br />
samples. These initially identical samples were subjected to similar aeration and<br />
hydrothermal conditions by our project partners upon their small scale reactor<br />
mentioned earlier. Small quantities were cropped from each sample at different<br />
days for analysis. The aim then was to investigate the effect <strong>of</strong> time against the<br />
presence and abundance <strong>of</strong> the components within the waste. After the samples<br />
were measured few important parameters were extracted like the number <strong>of</strong><br />
saturated and unsaturated and their sum <strong>of</strong> intensities as shown in table 3.10.<br />
A radar plot in figure 3-80 was established for the parameters which were<br />
extracted from the data analysis program <strong>of</strong> the Bruker s<strong>of</strong>tware. From the data for<br />
example it can be seen that the count <strong>of</strong> saturated compounds remains rather<br />
similar (~34) over all varieties.<br />
The plot showed that sample 2 (4 days) had the highest count <strong>of</strong> unsaturated and<br />
consequently the highest sum <strong>of</strong> intensities <strong>of</strong> these compounds. Excluding sample<br />
1, it was noticed that increasing operating time resulted in a drop <strong>of</strong> the intensities<br />
<strong>of</strong> both saturated and unsaturated compounds in the waste samples. Moreover a<br />
reduction <strong>of</strong> the count <strong>of</strong> unsaturated compounds was recorded. This reduction is<br />
attributed to the operating time <strong>of</strong> treatment <strong>of</strong> those samples on a small scale<br />
reactor. Such a plot provides a detailed information about the changeability <strong>of</strong><br />
samples.<br />
Table 3.10 Extracted data from 5 measured light shredder waste samples<br />
#<br />
Operating Count Count<br />
Time Saturated Unsaturated<br />
∑ Int. Sat. (x10 3 ) ∑ Int. Unsat. (x10 4 )<br />
1 2 Days 33 489 557 730<br />
2 4 Days 34 731 1131 1860<br />
3 10 Days 34 666 757 1045<br />
4 14 Days 34 622 508 793<br />
5 16 Days 36 592 512 759<br />
105
Results and Discussion<br />
Figure 3-80 Radar plot <strong>of</strong> four parameters related to five shredder waste samples<br />
varying by operation time<br />
3.6.1.1 Kendrick Plot for PCBs<br />
Kendrick plot was also used to sort chemical composition that appears in the<br />
negative APCI-TOF-MS. The PCBs were firstly displayed on a CH 2 -increment<br />
Kendrick plot. Figure 3-81 shows the PCBs showing an inclined decreasing<br />
fashion. This confirms that PCBs are not CH 2 homologues and thus the plot should<br />
be modified. A rescale <strong>of</strong> Kendrick plot from CH 2 to Chlorine (Cl) as the new<br />
increment is performed for the components in the negative mass spectrum <strong>of</strong> the<br />
waste sample. Rescaling the data points to Cl occurs by multiplying the measured<br />
mass by the ratio <strong>of</strong> nominal mass and accurate mass <strong>of</strong> Cl (35/34.9683). The<br />
KMD is deduced by subtracting the calculated Kendrick mass (KM) <strong>of</strong> the<br />
analytes from their nominal Kendrick mass (NKM). Thus the chlorine Kendrick<br />
plot for the (-MS) spectrum for the chlorinated components is shown in figure 3-<br />
82. Now the components are horizontally sorted because they are homologues <strong>of</strong><br />
Cl. The five identified PCBs are aligned at KMD = 1.18. This is consistent with<br />
106
Results and Discussion<br />
the data obtained from the Kendrick plot <strong>of</strong> the PCBs standard in figure 3-83. The<br />
other classes <strong>of</strong> chlorinated compounds are as well observed in the Kendrick plot<br />
at KMD = 1.3 and KMD = 2.1 which reflect the presence <strong>of</strong> high mass chlorinated<br />
compounds within light shredder waste fraction. Similarly this Kendrick plot was<br />
used to identify and track the chlorinated components among different samples.<br />
KMD<br />
1.0<br />
Kendrick plot (CH 2 ) for (-MS) spectrum <strong>of</strong> waste sample<br />
0.8<br />
0.6<br />
0.4<br />
0.2<br />
0.0<br />
200 300 400 500 600 700 800 900<br />
NKM<br />
Figure 3-81 Kendrick plot <strong>of</strong> (CH 2 ) for waste mixture upon (-) APCI-MS<br />
2.4<br />
Kendrick plot (Cl) for (-MS) spectrum for waste sample<br />
KMD<br />
2.2<br />
2.0<br />
1.8<br />
1.6<br />
1.4<br />
1.2<br />
1.0<br />
200 300 400 500 600 700 800 900<br />
NKM<br />
Figure 3-82 Kendrick plot <strong>of</strong> (Cl) for waste mixture upon (-) APCI-MS<br />
107
Results and Discussion<br />
KMD<br />
2.4<br />
2.2<br />
2.0<br />
1.8<br />
1.6<br />
1.4<br />
1.2<br />
1.0<br />
0.8<br />
0.6<br />
Kendrick plot (Cl) for (-MS) spectrum <strong>of</strong> PCBs Congener Mix<br />
200 250 300 350 400 450 500<br />
NKM<br />
Figure 3-83 Kendrick plot <strong>of</strong> (Cl) for PCBs Congener Mix upon (-) APCI-MS<br />
3.6.1.2 Kendrick Plot for Oxidation Products<br />
Another employment <strong>of</strong> Kendrick plot was for screening the change in chemical<br />
composition <strong>of</strong> the complex mixture <strong>of</strong> light shredder waste upon oxidation<br />
process. The Kendrick plot <strong>of</strong> three samples was established from their respective<br />
positive APCI mass spectra. The samples are described in figure 3-84 as I3, O2<br />
and O3. I3 is the initial waste complex before oxidation. O2 represents the<br />
oxidation products that were dissolved in MeOH before injection into the APCI-<br />
MS. O3 is the sample containing also the same oxidation products but they were<br />
dissolved and directly infused using n-heptane. Visual scanning <strong>of</strong> the graphs<br />
reveals that the yield <strong>of</strong> oxidation is about 90%. This is due to the disappearance <strong>of</strong><br />
initial components <strong>of</strong> I3 sample in the Kendrick plots <strong>of</strong> oxidation products<br />
injected in methanol or in n-heptane as in O2 and O3 respectively. The spread <strong>of</strong><br />
Kendrick plots <strong>of</strong> oxidation products <strong>of</strong> sample O2 was different from that<br />
obtained by O3. This is because methanol retains polar oxidised products where as<br />
n-heptane retains the nonpolar decomposed products in addition to initial<br />
unreacted compounds.<br />
108
Results and Discussion<br />
1.2<br />
KMD<br />
1.1<br />
I3 O2.Methanol O3.Heptane<br />
1<br />
0.9<br />
0.8<br />
0.7<br />
0.6<br />
0 100 200 300 400 500 600 700 800 900 1000<br />
NKM<br />
Figure 3-84 Kendrick plot overlap <strong>of</strong> I3, O2 and O3<br />
3.6.2 Lebanon Waste<br />
Kendrick plot has been employed as well for screening the chemical composition<br />
<strong>of</strong> Lebanon waste. The graphs <strong>of</strong> the two analysed samples in figure 3-85 shows<br />
that the two samples are very heterogeneous in nature. Their composition varies<br />
markedly as demonstrated by their Kendrick plot overlap in figure 3-85 especially<br />
in the high mass ranges. Leb S2 appears to have components with increased double<br />
bond equivalents compared to Leb S1 waste sample. This significant difference in<br />
chemical composition is certainly a pro<strong>of</strong> to the heterogeneity <strong>of</strong> the waste source.<br />
Nevertheless identification <strong>of</strong> harmful compounds allows estimating the impact <strong>of</strong><br />
such dumps over the environment. In all cases, this preliminary study forms a<br />
promising step towards exploring the chemical composition necessary to solve<br />
currently thousands <strong>of</strong> tons stored in the nasty dumps. In all cases, it is the scope <strong>of</strong><br />
the study that will recommend treatment strategies which eventually solve the<br />
problem. Such a study can be a good reference for screening the waste residues or<br />
treated waste (e.g. composted, biologically treated) before final landfilling.<br />
109
Results and Discussion<br />
KMD<br />
1.1<br />
1<br />
Leb.S1<br />
Leb.S2<br />
0.9<br />
0.8<br />
0.7<br />
0.6<br />
100 300 500 700 900 1100<br />
NKM<br />
Figure 3-85 Kendrick plot overlap <strong>of</strong> Leb S1 and Leb S2 waste samples<br />
3.6.3 Oil sample<br />
Since the mass spectra <strong>of</strong> some car motor oil resembled that <strong>of</strong> light shredder<br />
waste, an attempt to attain a better and detailed insight via overlapping their<br />
Kendrick plots was performed. In fact the graphs in figure 3-86 show a close<br />
similarity between the Calpam oil and the light shredder waste fraction. Although<br />
they are not overlapping, however the compounds seem structurally similar.<br />
1.1<br />
KMD<br />
1<br />
Calpam Oil<br />
Light shredder Waste<br />
0.9<br />
0.8<br />
0.7<br />
0.6<br />
100 200 300 400 500 600 700 800<br />
NKM<br />
Figure 3-86 Kendrick plot overlap <strong>of</strong> Calpam oil and light shredder waste<br />
110
Results and Discussion<br />
As far as comparing dirty oil to unused one is concerned, Kendrick plot allowed<br />
giving an insightful idea about what happens to the composition <strong>of</strong> oil engine upon<br />
mileage. Figure 3-87 shows a Kendrick plot <strong>of</strong> general standard car oil from<br />
Calpam Company overlapped to a contaminated-through-usage oil from an<br />
unknown car. Assuming that this Calpam oil or a similar one has been used in a<br />
new car and changed after a certain interval <strong>of</strong> time to give the contaminated one,<br />
the plot shows a depletion <strong>of</strong> the oil structural composition. It seems that the<br />
components have been degraded by observing the shift <strong>of</strong> KMD value <strong>of</strong> the<br />
contaminated through usage oil components compared with those <strong>of</strong> Calpam oil.<br />
As well decomposition <strong>of</strong> the oil is significant in plot. A large number <strong>of</strong><br />
decomposed compounds appear in low mass range <strong>of</strong> m/z 100-250. These<br />
compounds are not found within the Calpam sample. To this end, this approach<br />
can be employed to understand compositional evolution <strong>of</strong> car motor oils after they<br />
are used. Understanding such changes in composition can guide car oil companies<br />
in developing better car oil that can serve for prolonged period before service is<br />
needed.<br />
KMD<br />
1.1<br />
Calpam Motor Oil<br />
Dirty Motor Oil<br />
1<br />
0.9<br />
0.8<br />
0.7<br />
0.6<br />
0.5<br />
0.4<br />
0 100 200 300 400 500 600 700 800<br />
NKM<br />
Figure 3-87 Kendrick plot overlap <strong>of</strong> Calpam motor oil and contaminated through<br />
usage motor oil<br />
111
Results and Discussion<br />
3.6.4 Asphaltenes<br />
The complex mixture within Asphaltenes was displayed by Kendrick plot. Figure<br />
3-88 shows the compositional display <strong>of</strong> one sample <strong>of</strong> bitumen that was dissolved<br />
in DCM under positive ESI conditions. This choice <strong>of</strong> DCM enabled to look at a<br />
wide range <strong>of</strong> components because the plot demonstrates a wide KMD range.<br />
KMD<br />
1.2<br />
Bitumen 1 (DCM-ESI)<br />
1<br />
0.8<br />
0.6<br />
0.4<br />
0.2<br />
0<br />
0 200 400 600 800 1000<br />
NKM<br />
Figure 3-88 Kendrick plot <strong>of</strong> bitumen 1 upon ESI-MS using DCM solvent<br />
KMD<br />
1.4<br />
Bitumen 1 (Heptane-APCI)<br />
1.2<br />
1<br />
0.8<br />
0.6<br />
0.4<br />
0.2<br />
0<br />
0 200 400 600 800<br />
NKM<br />
Figure 3-89 Kendrick plot <strong>of</strong> bitumen 1 upon APCI-MS using n-heptane solvent<br />
112
Results and Discussion<br />
In contrast the Kendrick plot <strong>of</strong> n-heptane sample under positive APCI-MS<br />
conditions showed only few compounds from the bitumen sample. An example is<br />
given by figure 3-89. This is not surprising because asphaltenes are fraction<br />
defined to be insoluble in n-heptane. Next the two bitumen samples were plotted<br />
together. Kendrick plot in figure 3-90 reflects the content <strong>of</strong> bitumen 1 and<br />
bitumen 2 using DCM as a reagent under an applied positive APCI-MS method.<br />
The two samples look very similar in terms <strong>of</strong> molecular composition.<br />
KMD<br />
1.2<br />
Bitumen 1 Bitumen 2<br />
1<br />
0.8<br />
0.6<br />
0.4<br />
0.2<br />
0<br />
100 200 300 400 500 600 700 800<br />
NKM<br />
Figure 3-90 Kendrick plot overlap <strong>of</strong> bitumen 1 and bitumen 2 using DCM in<br />
APCI-MS<br />
At last comparison <strong>of</strong> Kendrick plots, bitumen 1 under DCM/(+)APCI-MS<br />
conditions and under DCM/(+)ESI-MS indicate the significant difference in<br />
molecular composition. The same solvent was used however distinct Kendrick<br />
plots were found under different ionisation techniques. The development <strong>of</strong> this<br />
APCI methodology allowed including additional compounds that are not explored<br />
by ESI technique. The necessity <strong>of</strong> molecular level details to complement the<br />
developed methodology would then be paramount.<br />
113
Conclusions<br />
In conclusion we could show that using APCI-MS n-alkanes can be investigated not<br />
only in model systems but as well in real life complex samples. Using [M-H] + ions <strong>of</strong><br />
n-alkanes in reference mixtures as external calibrant, close to 1000 molecular<br />
formulas can be obtained from an APCI-MS spectrum in a light shredder waste<br />
sample. The results demonstrated that a dehydrogenation process is releasing an<br />
array <strong>of</strong> unsaturated olefins believed to make up the GC hump. The presence <strong>of</strong> few<br />
harmful PCBs was explored using negative APCI-MS. This method could show a<br />
typical chemical content for the light shredder waste complex mixture.<br />
Further tandem MS experiments could confirm the identity <strong>of</strong> the compounds within<br />
the waste sample. The n-alkanes showed a linear response in calibration curves<br />
allowing the acquisition <strong>of</strong> a quantification figure <strong>of</strong> selected hydrocarbons in waste<br />
sample. The method developed here is certainly not applicable for a routine analysis<br />
<strong>of</strong> waste samples due to high instrument investment costs. However, the method<br />
developed, allows a clear identification <strong>of</strong> hydrocarbons in complex waste samples<br />
and a spot check screening <strong>of</strong> waste samples, very heterogeneous by nature, for the<br />
presence <strong>of</strong> alkanes. Furthermore the techniques allow a critical re-evaluation <strong>of</strong><br />
legally binding analytical methods for the determination <strong>of</strong> hydrocarbons in<br />
unresolved complex mixtures, by identification <strong>of</strong> the actual components <strong>of</strong> such<br />
samples. The extent <strong>of</strong> biodegradation and weathering conditions over the complex<br />
mixture <strong>of</strong> light shredder waste was monitored successfully by the employment <strong>of</strong><br />
Kendrick plot. This innovative methodology yielded important fundamental and<br />
compositional information <strong>of</strong> the waste mixture.<br />
Another intriguing aspect <strong>of</strong> this study is the success <strong>of</strong> the APCI methodology in<br />
examining various hydrocarbon analytes previously considered as difficult to ionize.<br />
The applicability <strong>of</strong> APCI-MS method was successfully extended for the<br />
examination <strong>of</strong> various model non-polar hydrocarbons like high mass linear,<br />
branched and cyclic hydrocarbons. This was demonstrated by the production <strong>of</strong><br />
intact abundant stable [M-H] + ion observed for each hydrocarbon within a large<br />
114
selection. In all cases ionization was achieved without the use <strong>of</strong> any additional<br />
additives and without significant fragmentations. In all cases tandem MS spectra<br />
could be acquired from the intact precursor ions. The methodology demonstrated the<br />
power <strong>of</strong> APCI-MS to analyse components <strong>of</strong> other kinds <strong>of</strong> complex hydrocarbon<br />
mixtures that usually fall out <strong>of</strong> the ability <strong>of</strong> other techniques, such as car motor oil<br />
and asphaltenes.<br />
Hence such APCI method provides an excellent groundwork for the analysis <strong>of</strong> nonvolatile<br />
hydrocarbons in complex mixtures containing similar compounds. Therefore<br />
the application <strong>of</strong> this method should lead for better understanding <strong>of</strong> the chemical<br />
composition <strong>of</strong> such mixtures.<br />
115
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125
Appendix<br />
Light shredder waste<br />
Meas. m/z Mol.Formula m/z<br />
error<br />
[ppm]<br />
189.163 C 14 H 21 189.1638 4.2<br />
191.1789 C 14 H 23 191.1794 2.6<br />
193.1941 C 14 H 25 193.1947 3.1<br />
195.2105 C 14 H 27 195.2107 1<br />
197.2259 C 14 H 29 197.2264 2.5<br />
199.1477 C 15 H 19 199.1481 2<br />
201.164 C 15 H 21 201.1638 -1<br />
203.1796 C 15 H 23 203.1794 -1<br />
205.1954 C 15 H 25 205.1951 -1.5<br />
207.211 C 15 H 27 207.2107 -1.5<br />
209.2266 C 15 H 29 209.2264 -1<br />
211.2422 C 15 H 31 211.242 -1<br />
213.1647 C 16 H 21 213.1638 -4.2<br />
215.1804 C 16 H 23 215.1794 -4.6<br />
217.1956 C 16 H 25 217.1951 -2.3<br />
219.2109 C 16 H 27 219.2107 -0.9<br />
221.2274 C 16 H 29 221.2264 -4.5<br />
223.2427 C 16 H 31 223.242 -3<br />
225.2586 C 16 H 33 225.2577 -4<br />
231.212 C 17 H 27 231.211 -4.3<br />
233.2273 C 17 H 29 233.2264 -3.8<br />
235.2429 C 17 H 31 235.242 -3.8<br />
237.258 C 17 H 33 237.2577 -1.3<br />
239.274 C 17 H 35 239.2733 -3<br />
241.1965 C 18 H 25 241.1958 -2.9<br />
245.2276 C 18 H 29 245.2264 -4.9<br />
247.2432 C 18 H 31 247.242 -4.8<br />
249.2591 C 18 H 33 249.2583 -3.2<br />
251.274 C 18 H 35 251.2733 -2.8<br />
253.2904 C 18 H 37 253.291 2.4<br />
261.2592 C 19 H 33 261.2599 2.6<br />
263.2747 C 19 H 35 263.2752 1.8<br />
265.2884 C 19 H 37 265.289 2.3<br />
267.3051 C 19 H 39 267.3046 -1.9<br />
279.3057 C 20 H 39 279.3046 -4<br />
281.3214 C 20 H 41 281.3203 -3.9<br />
126
289.2906 C 21 H 37 289.291 1.4<br />
291.306 C 21 H 39 291.312 2<br />
293.3212 C 21 H 41 293.3222 3.4<br />
295.3374 C 21 H 43 295.3384 3.4<br />
303.3062 C 22 H 39 303.3076 4.6<br />
305.3215 C 22 H 41 305.3203 -4<br />
307.3367 C 22 H 43 307.3359 -2.6<br />
309.3522 C 22 H 45 309.3516 -2<br />
317.3219 C 23 H 41 317.3228 2.8<br />
319.3375 C 23 H 43 319.3381 -4.8<br />
321.3515 C 23 H 45 321.3516 0.3<br />
323.3685 C 23 H 47 323.3672 -4<br />
327.3065 C 24 H 39 327.3071 1.8<br />
331.3377 C 24 H 43 331.3387 3<br />
333.3529 C 24 H 45 333.3516 -3.9<br />
337.3836 C 24 H 49 337.3829 -2<br />
343.3378 C 24 H 43 343.3389 3.2<br />
345.3532 C 24 H 45 345.3516 -4.7<br />
347.3684 C 24 H 47 347.3672 -3.4<br />
351.3986 C 25 H 51 351.3985 -0.2<br />
357.3535 C 26 H 45 357.3549 3.9<br />
359.3686 C 26 H 47 359.3672 -3.8<br />
361.3841 C 26 H 49 361.3829 -3.4<br />
365.4155 C 26 H 53 365.4142 -3.6<br />
371.3694 C 27 H 47 371.3704 2.7<br />
373.384 C 27 H 49 373.3829 -2.9<br />
379.4303 C 27 H 55 379.4298 -1.3<br />
383.3692 C 28 H 47 383.3705 3.4<br />
385.3851 C 28 H 49 385.387 5<br />
387.3994 C 28 H 51 387.3985 -2.4<br />
389.4144 C 28 H 53 389.4142 -0.6<br />
391.3359 C 29 H 43 391.3356 -0.7<br />
393.445 C 28 H 57 393.4455 1.2<br />
395.3694 C 29 H 47 395.368 -3.5<br />
399.4009 C 29 H 51 399.3999 -2.5<br />
401.4146 C 29 H 53 401.4142 -1<br />
407.4588 C 29 H 59 407.4599 2.7<br />
409.3848 C 30 H 49 409.3829 -4.6<br />
411.4002 C 30 H 51 411.3985 -4<br />
413.4155 C 30 H 53 413.4142 -3.2<br />
415.4304 C 30 H 55 415.4298 -1.5<br />
417.445 C 30 H 57 417.4455 1.1<br />
127
419.4592 C 30 H 59 419.4611 4.6<br />
421.4766 C 30 H 61 421.4768 0.3<br />
423.4002 C 31 H 51 423.3985 -3.9<br />
425.4158 C 31 H 53 425.4142 -3.8<br />
427.4309 C 31 H 55 427.4298 -2.6<br />
429.4455 C 31 H 57 429.4455 -0.1<br />
437.4161 C 32 H 53 437.4142 -4.3<br />
439.4313 C 32 H 55 439.4298 -3.3<br />
441.446 C 32 H 57 441.4455 -1.2<br />
443.461 C 32 H 59 443.4611 0.4<br />
449.5096 C 32 H 65 449.5081 -3.4<br />
451.4318 C 33 H 55 451.4298 -4.3<br />
453.4464 C 33 H 57 453.4455 -2.1<br />
455.4614 C 33 H 59 455.4611 -0.7<br />
457.4766 C 33 H 61 457.4768 0.3<br />
463.432 C 34 H 55 463.4298 -4.7<br />
465.4466 C 34 H 57 465.4455 -2.4<br />
467.4617 C 34 H 59 467.4611 -1.2<br />
469.4766 C 34 H 61 469.4768 0.3<br />
471.4913 C 34 H 63 471.4924 2.4<br />
477.4479 C 35 H 57 477.4455 -5<br />
479.4621 C 35 H 59 479.4611 -1.9<br />
481.4772 C 35 H 61 481.4768 -0.9<br />
483.492 C 35 H 63 483.4924 0.9<br />
485.5068 C 35 H 65 485.5081 2.7<br />
491.463 C 36 H 59 491.4611 -3.8<br />
493.477 C 36 H 61 493.4768 -0.5<br />
495.492 C 36 H 63 495.4924 0.8<br />
497.5075 C 36 H 65 497.5081 1.2<br />
499.5218 C 36 H 67 499.5237 3.9<br />
505.5718 C 36 H 73 505.5707 -2.2<br />
507.495 C 37 H 63 507.4924 -5.3<br />
509.5068 C 37 H 65 509.5081 2<br />
511.5224 C 37 H 67 511.5237 2.5<br />
521.5068 C 38 H 65 521.5081 2.4<br />
523.5231 C 38 H 67 523.5237 1.1<br />
525.5378 C 38 H 69 525.5394 3<br />
535.5223 C 39 H 67 535.5237 2.6<br />
537.5381 C 39 H 69 537.5394 2.3<br />
539.5524 C 39 H 71 539.555 4.8<br />
541.4785 C 40 H 61 541.4768 -3.2<br />
543.4901 C 40 H 63 543.4924 4.3<br />
128
545.5053 C 40 H 65 545.5081 5.1<br />
547.5221 C 40 H 67 547.5237 2.9<br />
549.5376 C 40 H 69 549.5394 3.2<br />
551.5529 C 40 H 71 551.555 3.8<br />
553.4754 C 41 H 61 553.4768 2.5<br />
553.5721 C 40 H 73 553.5707 -2.5<br />
555.4922 C 41 H 63 555.4924 0.4<br />
557.5054 C 41 H 65 557.5081 4.8<br />
559.5218 C 41 H 67 559.5237 3.4<br />
561.5376 C 41 H 69 561.5394 3.2<br />
563.553 C 41 H 71 563.555 3.5<br />
565.5717 C 41 H 73 565.5707 -1.7<br />
569.5075 C 42 H 65 569.5081 1<br />
571.5247 C 42 H 67 571.5237 -1.7<br />
573.5371 C 42 H 69 573.5394 4<br />
575.5543 C 42 H 71 575.555 1.2<br />
577.5695 C 42 H 73 577.5707 2<br />
581.511 C 43 H 65 581.5081 -5<br />
583.5244 C 43 H 67 583.5237 -1.2<br />
585.5361 C 43 H 69 585.5394 5.6<br />
587.5523 C 43 H 71 587.555 4.6<br />
589.5701 C 43 H 73 589.5707 1<br />
591.5995 C 43 H 75 591.5863 -2.2<br />
597.5399 C 44 H 69 597.5394 -0.8<br />
599.553 C 44 H 71 599.555 3.3<br />
601.5699 C 44 H 73 601.5707 1.3<br />
603.5848 C 44 H 75 603.5863 2.4<br />
611.5556 C 45 H 71 611.555 -1<br />
613.5693 C 45 H 73 613.5707 2.2<br />
615.5842 C 45 H 75 615.5863 3.4<br />
625.5717 C 46 H 73 625.5707 -1.6<br />
627.5858 C 46 H 75 627.5863 0.8<br />
629.594 C 46 H 77 629.602 1.2<br />
639.585 C 47 H 75 639.5863 2.1<br />
641.599 C 47 H 77 641.602 4.6<br />
647.4623 C 49 H 59 647.4611 -1.8<br />
653.622 C 48 H 77 653.602 -3<br />
655.6155 C 48 H 79 655.6176 3.2<br />
129
Liqui Moly car motor oil<br />
Meas. m/z Mol.Formula m/z error [ppm]<br />
183.2109 C 13 H 27 183.2107 -1<br />
197.2269 C 14 H 29 197.2264 -2.5<br />
211.2416 C 15 H 31 211.242 1.9<br />
225.257 C 16 H 33 225.2577 3.1<br />
253.2886 C 18 H 37 253.289 1.5<br />
267.3036 C 19 H 39 267.3046 3.7<br />
281.3199 C 20 H 41 281.3203 1.4<br />
295.3355 C 21 H 43 295.3359 1.3<br />
309.3511 C 22 H 45 309.3516 1.6<br />
323.3666 C 23 H 47 323.3672 1.8<br />
337.3812 C 24 H 49 337.3829 5<br />
351.3971 C 25 H 51 351.3985 4<br />
365.4126 C 26 H 53 365.4142 4.4<br />
379.4283 C 27 H 55 379.4298 4<br />
393.4438 C 28 H 57 393.4455 4.3<br />
407.46 C 29 H 59 407.4611 2.7<br />
421.4765 C 30 H 61 421.4768 0.7<br />
449.5067 C 32 H 62 449.5081 3.1<br />
561.6322 C 40 H 81 561.6333 2<br />
701.791 C 50 H 101 701.7898 -1.7<br />
739.8029 C 53 H 103 739.8054 3.3<br />
841.9416 C 60 H 121 841.9463 5.5<br />
Contaminated-by-usage car motor oil<br />
Meas. m/z Mol. Formula m/z err [ppm]<br />
175.1484 C 13 H 19 175.1481 -1.5<br />
177.1645 C 13 H 21 177.1638 -4.3<br />
179.18 C 13 H 23 179.1794 -3.3<br />
181.1944 C 13 H 25 181.1951 3.9<br />
183.2108 C 13 H 27 183.2107 -0.5<br />
185.1318 C 14 H 17 185.1325 3.8<br />
187.1476 C 14 H 19 187.1481 3.1<br />
189.1629 C 14 H 21 189.1638 4.8<br />
191.1786 C 14 H 23 191.1794 4.2<br />
130
193.1951 C 14 H 25 193.1951 0<br />
195.2101 C 14 H 27 195.2107 3<br />
197.1318 C 15 H 17 197.1325 3.5<br />
197.2256 C 14 H 29 197.2264 4<br />
199.1478 C 15 H 19 199.1481 1.8<br />
201.1645 C 15 H 21 201.1638 -3.4<br />
207.1166 C 16 H 15 207.1168 0.9<br />
207.2097 C 15 H 27 207.2107 4.8<br />
213.1642 C 16 H 21 213.1638 -1.9<br />
215.1784 C 16 H 23 215.1794 4.6<br />
217.1939 C 16 H 25 217.1951 5<br />
221.2253 C 16 H 29 221.2264 5<br />
225.2567 C 16 H 33 225.2577 4.4<br />
227.1782 C 17 H 23 227.1794 5<br />
229.1949 C 17 H 25 229.1951 0.8<br />
231.2117 C 17 H 27 231.2107 -4.3<br />
241.1962 C 18 H 25 241.1951 -4.7<br />
245.2254 C 18 H 29 245.2264 4<br />
247.2412 C 18 H 31 247.242 3.2<br />
255.2121 C 19 H 27 255.2107 -5.4<br />
259.2428 C 19 H 31 259.242 -3<br />
269.2257 C 20 H 29 269.2264 2.6<br />
271.241 C 20 H 31 271.242 3.6<br />
273.2564 C 20 H 33 273.2577 4.7<br />
283.2418 C 21 H 31 283.242 0.8<br />
293.2253 C 22 H 29 293.2264 3.8<br />
295.2415 C 22 H 31 295.242 1.6<br />
297.2585 C 22 H 33 297.2577 -2.9<br />
299.2719 C 22 H 35 299.2733 4.7<br />
301.2894 C 22 H 37 301.289 -1.3<br />
307.2407 C 23 H 31 307.242 4.2<br />
309.2561 C 23 H 33 309.2577 5<br />
311.2721 C 23 H 35 311.2733 3.8<br />
321.2576 C 24 H 33 321.2577 0.2<br />
323.2719 C 24 H 35 323.2733 4.3<br />
325.2889 C 24 H 37 325.289 0.3<br />
327.3041 C 24 H 39 327.3046 1.5<br />
335.2715 C 25 H 35 335.2733 5.5<br />
337.2899 C 25 H 37 337.289 -2.7<br />
339.3033 C 25 H 39 339.3046 3.8<br />
341.3199 C 25 H 41 341.3203 1.2<br />
343.3347 C 25 H 43 343.3359 3.4<br />
131
345.3511 C 25 H 45 345.3516 1.5<br />
349.2884 C 26 H 37 349.289 1.7<br />
351.3034 C 26 H 39 351.3046 3.4<br />
353.3199 C 26 H 41 353.3203 1.2<br />
355.3341 C 26 H 43 355.3359 5<br />
357.3504 C 26 H 45 357.3516 3.4<br />
359.3669 C 26 H 47 359.3672 0.8<br />
363.3033 C 26 H 49 363.3046 3.5<br />
365.3184 C 27 H 41 365.3203 5.1<br />
367.3344 C 27 H 43 367.3359 4<br />
369.3502 C 27 H 45 369.3516 3.8<br />
371.3659 C 27 H 47 371.3672 3.5<br />
377.3202 C 28 H 41 377.3203 0.2<br />
379.3348 C 28 H 43 379.3359 2.9<br />
381.3529 C 28 H 45 381.3516 -3.4<br />
385.3809 C 28 H 49 385.3829 5<br />
391.3345 C 29 H 43 391.3359 3.6<br />
393.3504 C 29 H 45 393.3516 2.9<br />
395.3665 C 29 H 47 395.3672 1.8<br />
397.3809 C 29 H 49 397.3829 5<br />
399.3975 C 29 H 51 399.3985 2.5<br />
405.3514 C 30 H 45 405.3516 0.4<br />
407.3664 C 30 H 47 407.3672 2<br />
409.3807 C 30 H 49 409.3829 5.3<br />
411.3977 C 30 H 51 411.3985 1.9<br />
419.3669 C 31 H 47 419.3672 0.8<br />
421.383 C 31 H 49 421.3829 -0.3<br />
423.3973 C 31 H 51 423.3985 2.8<br />
433.383 C 32 H 49 433.3829 -0.2<br />
435.4004 C 32 H 51 435.3985 -4.2<br />
437.4136 C 32 H 53 437.4142 1.2<br />
439.4282 C 32 H 55 439.4298 3.6<br />
447.3989 C 33 H 51 447.3985 -0.7<br />
449.4134 C 33 H 53 449.4142 1.7<br />
451.4299 C 33 H 55 451.4298 -0.2<br />
463.4311 C 34 H 55 463.4298 -2.7<br />
465.4443 C 34 H 57 465.4455 2.6<br />
475.4313 C 35 H 55 475.4298 -3<br />
477.4475 C 35 H 57 477.4455 -4.2<br />
479.4599 C 35 H 59 479.4611 2.5<br />
489.4467 C 36 H 57 489.4455 -2.4<br />
491.4614 C 36 H 59 491.4611 -0.6<br />
132
493.4754 C 36 H 61 493.4768 2.8<br />
507.4903 C 37 H 63 507.4924 4.1<br />
519.4937 C 38 H 63 519.4924 -2.5<br />
521.5073 C 38 H 65 521.5081 1.5<br />
531.4935 C 39 H 63 531.4924 -2<br />
547.5221 C 40 H 67 547.5237 2.9<br />
133