Faculteit Bio-ingenieurswetenschappen
Academiejaar 2014 – 2015
Method development for determination of platinum group
metals using tandem ICP-mass spectrometry and
application to measure their dispersion in urban areas
Thibaut Van Acker
Promotors: Prof. dr. ir. Gijs Du Laing and Prof. dr. Frank Vanhaecke
Tutors: Karel Folens and Eduardo Bolea-Fernandez
Masterproef voorgedragen tot het behalen van de graad van
Master in de bio-ingenieurswetenschappen: Milieutechnologie
“De auteur en de promotoren geven de toelating deze scriptie voor consultatie beschikbaar te
stellen en delen ervan te kopiëren voor persoonlijk gebruik. Elk ander gebruik valt onder de
beperkingen van het auteursrecht, in het bijzonder met betrekking tot de verplichting de bron te
vermelden bij het aanhalen van resultaten uit deze masterproef.”
“The author and the promotors give permission to use this thesis for consultation and to copy parts
of it for personal use. Every other use is subject to the copyright laws, more specifically the source
must be extensively specified when using results from this thesis.”
Thibaut Van Acker
Prof. dr. ir. Gijs Du Laing
Prof dr. Frank Vanhaecke
06/2015, Ghent
I
Acknowledgements
First of all, I would like to thank my promotors Prof. dr. ir. Gijs Du Laing and Prof. dr. Frank Vanhaecke
for giving me the opportunity to perform this study and giving me good advice during the progress
of this work. I learned a lot and I really enjoyed working on this topic. I am also very thankful to my
tutors Karel Folens and Eduardo Bolea-Fernandez. Karel guided me through all the work from the
beginning to the end, as well as Eduardo with whom I worked at the Department of Analytical
chemistry. Eduardo explained me everything about the fundamentals of ICP-mass spectrometry and
learned me how to work with the Agilent 8800 ICP-QQQ. I really appreciate the work and effort they
have put in my master thesis.
The next person I would like to put in the spotlight is my wonderful girlfriend Joyca. She is always
there for me in good and bad moments and knows exactly how to motivate and support me and I am
looking forward to a great future with her. I also would like to thank my parents, who gave me the
opportunity to study in Ghent. They made sure I could grow up in a warm family and I am forever
grateful to them.
Last but not least, thanks to all my friends. During this five years of studying in Ghent, I met some
amazing people with whom I shared unforgettable moments. It was a pleasure to play for the UGent
Volleyball team with some of my best friends. We won the Flemish and Belgian University
Championship and we were crowned champions in an international tournament for universities in
Paris. This are all memories I will cherish for the rest of my life.
III
Table of Contents
1.
Introduction ................................................................................................................................................. 1
2.
Objectives...................................................................................................................................................... 3
3.
Literature study ........................................................................................................................................... 5
3.1.
Introduction to the platinum group metals ................................................................................... 5
3.2.
Global supply ....................................................................................................................................... 6
3.3.
Applications ......................................................................................................................................... 8
3.3.1.
PGMs demand in different application areas ........................................................................ 8
3.3.2.
Industrial catalysts .................................................................................................................... 9
3.3.3.
Fuel cell ...................................................................................................................................... 10
3.3.4.
Jewellery .................................................................................................................................... 11
3.3.5.
Dentistry .................................................................................................................................... 12
3.3.6.
Glass manufacture ................................................................................................................... 12
3.3.7.
Anticancer drugs ...................................................................................................................... 12
3.3.8.
Prosthetics ................................................................................................................................ 13
3.3.9.
Electronics................................................................................................................................. 13
3.4.
The development of the automotive catalytic converter .......................................................... 14
3.4.1.
Introduction .............................................................................................................................. 14
3.4.2.
The first emission control systems ....................................................................................... 15
3.4.3.
The catalytic approach............................................................................................................ 16
3.4.4.
Three-way catalyst .................................................................................................................. 18
3.5.
Possible PGMs scarcity problems ................................................................................................... 21
3.6.
Environmental problems related to the dispersion of PGMs .................................................... 25
3.6.1.
Sources of PGMs dispersion ................................................................................................... 25
3.6.2.
Soils and road dust ................................................................................................................... 25
3.6.3.
Aquatic ecosystems ................................................................................................................. 26
3.6.4.
Air ............................................................................................................................................... 27
3.6.5.
The effects on living organisms ............................................................................................. 27
V
4.
Materials and methods ............................................................................................................................. 31
4.1.
Chemicals and consumables............................................................................................................ 31
4.2.
Instruments........................................................................................................................................ 32
4.2.1.
Tandem ICP-mass spectrometry ............................................................................................ 32
4.2.2.
ICP-optical emission spectroscopy ........................................................................................ 37
4.2.3.
Microwave system.................................................................................................................... 37
4.2.4.
pH meter .................................................................................................................................... 38
4.3.
5.
Methods .............................................................................................................................................. 39
4.3.1.
Sampling procedure for urban samples (Ghent) ................................................................. 39
4.3.2.
Soil pH-analysis ........................................................................................................................ 47
4.3.3.
Sample preparation methods ................................................................................................. 47
Results and discussion .............................................................................................................................. 49
5.1.
Systematic study of the reactions between CH3F and the PGMs via tandem ICP-mass
spectrometry .................................................................................................................................................. 49
5.1.1.
Introduction .............................................................................................................................. 49
5.1.2.
Selection of the isotopes ......................................................................................................... 50
5.1.3.
Product ion scans ..................................................................................................................... 51
5.1.4.
Ramp cell gas tests ................................................................................................................... 54
5.1.5.
Calibration curves .................................................................................................................... 57
5.2.
VI
Interference experiments of platinum, palladium and rhodium.............................................. 59
5.2.1.
Introduction .............................................................................................................................. 59
5.2.2.
Platinum .................................................................................................................................... 59
5.2.3.
Palladium ................................................................................................................................... 61
5.2.4.
Rhodium..................................................................................................................................... 63
5.2.5.
Overall discussion .................................................................................................................... 64
5.3.
Method validation with CRM BCR-723 (road dust) ...................................................................... 65
5.4.
Application to urban samples ......................................................................................................... 66
5.4.1.
Platinum determination in road dust samples .................................................................... 66
5.4.2.
Platinum determination in soil samples .............................................................................. 67
5.5.
Characterisation of urban samples ................................................................................................ 71
6.
General conclusions .................................................................................................................................. 73
7.
Future research recommendations ........................................................................................................ 75
8.
Bibliography ............................................................................................................................................... 77
9.
Appendix ..................................................................................................................................................... 83
VII
List of Figures
Figure 1. World platinum supply over a period from 2004 to 2013 (Johnson Matthey Ltd., 2014) ......... 7
Figure 2. World palladium supply over a period from 2004 to 2013 (Johnson Matthey Ltd., 2014)........ 7
Figure 3. World rhodium supply over a period from 2004 to 2013 (Johnson Matthey Ltd., 2014) .......... 7
Figure 4. Gross demand in 2013 for platinum (left), palladium (middle) and rhodium (right) in the
various application areas and industries (Johnson Matthey Ltd., 2014) ..................................................... 9
Figure 5. Schematic representation of a hydrogen/oxygen proton exchange membrane fuel cell
(Carrette et al., 2001) ......................................................................................................................................... 10
Figure 6. Chemical structures of the platinum complexes cisplatin (left) and carboplatin (right)
(Hambley, 1997) .................................................................................................................................................. 13
Figure 7. The first three-wheeled car design from inventor Karl Benz (left) and the first four-wheeled
car design from inventor Gottlieb Daimler (right) (Dutton, 2006) ............................................................. 14
Figure 8. The Johnson Matthey design for 1976 model cars of the first automotive catalytic system
controlling CO, HC and NOx emissions by installing a reduction catalyst (NOx converter) downstream
the combustion engine and further downstream the injection point of the secondary air pump and
the oxidation catalyst (CO/HC converter) (Acres & Cooper, 1972) ............................................................ 18
Figure 9. Schematic representation of the TWC (left) and a picture of BASF’s TWC (right) (BASF Ltd.,
2015; Fornalczyk et al., 2014) ............................................................................................................................ 20
Figure 10. Annual gross demand of PGMs for automotive catalysts over a period of 10 years (20042013). In 2009, the overall PGM consumption dropped by 22 % due to the global financial crisis
(Johnson Matthey Ltd., 2014). .......................................................................................................................... 21
Figure 11. Dynamometer setup of a Marina test vehicle (Acres & Cooper, 1972) .................................... 23
Figure 12. Schematic representation of a plasma torch and RF coil (Thomas, 2001d) ........................... 32
Figure 13. Schematic representation of a pneumatic concentric nebuliser (left) and an ICP
introduction system with a plasma torch (Thomas, 2013) .......................................................................... 33
Figure 14. Schematic representation of the interface region with sampler and skimmer cones
(Thomas, 2001e).................................................................................................................................................. 34
Figure 15. Schematic representation of the quadrupole mass filter principles (Thomas, 2001g) ........ 35
Figure 16. Schematic representation of a discrete dynode electron multiplier (Thomas, 2001b) ........ 35
Figure 17. Real picture of the Agilent 8800 ICP-QQQ with autosampler (left) and a diagram with
internal parts of the Agilent 8800 ICP-QQQ (right) (Agilent Technologies Inc., 2015)............................ 36
Figure 18. Picture of the Orion Star A211 with pH electrode ...................................................................... 38
Figure 19. Map of Ghent with the 13 selected sample locations (Google Inc., 2015) ............................... 40
Figure 20. Tools for soil samples (shovel on the top) and road dust samples (brush on the bottom) . 41
IX
Figure 21. Pictures of the selected sampling locations: Location 1 (top left), location 10 (top right),
location 2 where distance to the road samples were taken (bottom left) and part of the depth profile
at location 6 (bottom right) .............................................................................................................................. 42
Figure 22. Selection of the main reaction product ions for Pt monitoring via product ion scanning
using CH3F/He as a reaction gas in tandem ICP-MS ..................................................................................... 51
Figure 23. Selection of the main reaction product ions for Pd monitoring via product ion scanning
using CH3F/He as a reaction gas in tandem ICP-MS ..................................................................................... 52
Figure 24. Selection of the main reaction product ions for Rh monitoring via product ion scanning
using CH3F/He as a reaction gas in tandem ICP-MS ..................................................................................... 52
Figure 25. Selection of the main reaction product ions for Ir monitoring via product ion scanning using
CH3F/He as a reaction gas in tandem ICP-MS ................................................................................................ 53
Figure 26. Selection of the main reaction product ions for Os monitoring via product ion scanning
using CH3F/He as a reaction gas in tandem ICP-MS ..................................................................................... 53
Figure 27. Selection of the main reaction product ions for Ru monitoring via product ion scanning
using CH3F/He as a reaction gas in tandem ICP-MS ..................................................................................... 54
Figure 28. Selection of the optimal CH3F/He flow rate for selected reaction product ions
193
195
PtCHF+,
IrCHF+ and 192OsCHF+ ....................................................................................................................................... 55
Figure 29. Selection of the better CH3F/He flow rate for the selected species 105PdCH3F+ and 105Pd(CH3F)2+
............................................................................................................................................................................... 56
Figure 30. Selection of the better CH3F/He flow rate for the selected species
103
RhCH3F+ and
103
Rh(CH3F)2+ ......................................................................................................................................................... 56
Figure 31. Selection of the better CH3F/He flow rate for the selected species 102RuCH3F+ and 102Ru(CH3F)2+
............................................................................................................................................................................... 56
Figure 32. Calibration curves for 195PtCHF+, 105PdCH3F+, 103RhCH3F+, 193IrCHF+, 192OsCHF+ and 102RuCH3F+57
Figure 33. Measured concentrations of 5 µg L-1 Pt solutions with Hf for 194PtCHF+ (left) and 195PtCHF+
(right) ................................................................................................................................................................... 60
Figure 34. Measured concentrations of 5 µg L-1 Pt solutions with Hf for 196PtCHF+ (left), Sm for 194PtCHF+
(right) ................................................................................................................................................................... 60
Figure 35. Measured concentrations of 5 µg L-1 Pt solutions with Gd for 194PtCHF+ (left) and 195PtCHF+
(right) ................................................................................................................................................................... 60
Figure 36. Measured concentrations of 5 µg L-1 Pt solutions with Gd for 196PtCHF+ (left), Hg for 196PtCHF+
(right) ................................................................................................................................................................... 60
Figure 37. Measured concentrations of 5 µg L-1 Pd solutions with Y for 105PdCH3F+ (left) and 105Pd(CH3F)2+
(right) ................................................................................................................................................................... 62
Figure 38. Measured concentrations of 5 µg L-1 Pd solutions with Y for 106PdCH3F+ (left) and 106Pd(CH3F)2+
(right) ................................................................................................................................................................... 62
X
Figure 39. Measured concentrations of 5 µg L-1 Pd solutions with Sr for 105PdCH3F+ (left) and 105Pd(CH3F)2+
(right) ................................................................................................................................................................... 62
Figure 40. Measured concentrations of 5 µg L-1 Pd solutions with Cd for
106
PdCH3F+ (left) and
106
Pd(CH3F)2+ (right) ............................................................................................................................................ 62
Figure 41. Measured concentrations of 5 µg L-1 Pd solutions with Cd for
108
108
PdCH3F+ (left) and
Pd(CH3F)2+ (right) ............................................................................................................................................. 63
Figure 42. Measured concentrations of 5 µg L-1 Rh solutions with Sr for
103
RhCH3F+ (left) and
103
Rh(CH3F)2+ (right) ............................................................................................................................................ 64
Figure 43. Platinum recoveries with corresponding standard deviations (5 replicates) for 5 digestions
of CRM BCR-723, measured as reaction product ions
194
PtCHF+ (blue),
195
PtCHF+ (red) and
196
PtCHF+
(green). The horizontal dotted lines give the platinum content uncertainty of the CRM BCR-723,
converted to recovery values. .......................................................................................................................... 66
Figure 44. Graphical representation of Pt content (x-axis) and soil depth (y-axis) for the depth profile
2 soil samples, including corresponding standard deviations (except for the high standard deviation
of sample S6G2 from depth profile 1) ............................................................................................................. 69
Figure 45. Two maps of Ghent with on the left, the Pt contents, represented as blue circles, of the road
dust samples at 9 different locations. On the right, the Pt contents, represented as red circles, of the
soil samples at 12 different locations instead of 13 (Pt content S1G13 < LOD). Circle sizes are in
proportion to the Pt contents and the scale values are indicated as µg kg-1 Pt. ...................................... 70
XI
List of Tables
Table 1. Average element concentrations in the continental crust (Wedepohl, 1995) ............................ 5
Table 2. Overview with some important application areas of the platinum group metals (Hagelüken,
2012) ....................................................................................................................................................................... 8
Table 3. PGM-based catalysts in the refining and petroleum industry (Marcilly, 2003) .......................... 9
Table 4. PGM contents in various plant species (Pawlak et al., 2014) ........................................................ 27
Table 5. PGM contents in various animal tissues (Pawlak et al., 2014) ...................................................... 28
Table 6. Toxicity to rats of different platinum compounds (Pawlak et al., 2014) .................................... 28
Table 7. Element concentration in calibration standard solutions and selected wavelength for ICP-OES
analyses................................................................................................................................................................ 37
Table 8. Overview of the 13 selected sample locations ................................................................................ 40
Table 9. Overview of the samples with parameters ...................................................................................... 43
Table 10. Closed microwave digestion program for soil and road dust samples using 4 mL HCl and 3
mL HNO3............................................................................................................................................................... 48
Table 11. Primary reaction product ions and corresponding reaction rate coefficients (T = 295 ± 2 K)
for PGMs with CH3F (Zhao et al., 2006)............................................................................................................ 49
Table 12. The selected isotopes of the PGMs with their corresponding relative abundances .............. 50
Table 13. Selected m/z ratio in the first and second quadrupole for ramp cell gas tests in tandem ICPMS ......................................................................................................................................................................... 55
Table 14. Overview of calibration data and instrumental limits of detection and limits of quantification
for all elements using CH3F/He in tandem ICP-MS....................................................................................... 58
Table 15. Possible polyatomic and isobaric interferences for 3 isotopes of Pt ........................................ 59
Table 16. Possible polyatomic and isobaric interferences for 3 isotopes of Pd ........................................ 61
Table 17. Possible polyatomic and isobaric interferences for Rh ............................................................... 63
Table 18. Platinum contents with corresponding standard deviations (5 replicates) for 5 digestions of
CRM BCR-723, measured as reaction product ions 194PtCHF+, 195PtCHF+ and 196PtCHF+ ............................ 65
Table 19. Average Pt contents with corresponding standard deviations (3 replicates) for digested road
dust samples, measured as reaction product ion 195PtCHF+ ......................................................................... 67
Table 20. Average Pt contents with corresponding instrumental standard deviations (5 replicates) for
digested road dust samples, measured as reaction product ion 195PtCHF+ ................................................ 67
Table 21. Average Pt contents with corresponding standard deviations (2 replicates) for digested soil
samples, measured as reaction product ion 195PtCHF+ .................................................................................. 68
Table 22. Average Pt contents with corresponding standard deviations (1 replicate for depth profile 2,
2 replicates for depth profiles 1 and 3) for digested soil samples of the depth profiles, measured as
reaction product ion 195PtCHF+ ......................................................................................................................... 68
XIII
Table 23. Average Pt contents with corresponding standard deviations (1 replicate for distance to the
road profile 1, 2 replicates for distance to the road profiles 2 and 3) for digested soil samples of the
distance to the road samples, measured as reaction product ion 195PtCHF+ ............................................. 69
Table 24. Overview of Pt contents in road dust and soil samples of other similar studies .................... 70
Table 25. Average soil samples contents for heavy metals Cd, Cr, Cu, Ni, Pb and Zn .............................. 71
Table 26. Pearson correlation coefficients between variables Pt, Al, Cd, Co, Cr, Cu, Fe, Mn, Ni, Pb and
Zn content in road dust samples (N=9) ........................................................................................................... 71
Table 27. Pearson correlation coefficients between variables Pt, Al, Cd, Co, Cr, Cu, Fe, Mn, Ni, Pb and
Zn content in soils samples (N=29). Soil samples with Pt content <LOD (S3G11, S4G11, S8G11 and S1G13)
are not included. ................................................................................................................................................. 72
XIV
List of Abbreviations
AFR
Air-fuel ratio
AFRs
Stoichiometric air-fuel ratio
ANOVA
Analysis of variance
CRM
Certified reference material
CTD
Charge transfer device
DCP
Direct current plasma
DM
Dry matter
EFI
Electronic fuel injection
EGR
Exhaust gas recycling
EPA
Environmental Protection Agency
EU
European Union
GD
Glow discharge
HC
Hydrocarbons
ICP-MS
Inductively coupled plasma-mass spectrometry
ICP-SIFT-MS
Inductively coupled plasma-selected ion flow tube mass spectrometry
LD50
Median lethal dose
LOD
Limit of detection
LOQ
Limit of quantification
m/z
Mass-to-charge
MID
Microwave-induced plasma
MLCC
Multi-layer ceramic capacitor
MSC
Metal substrate converter
NOx
Nitrogen oxides
OES
Optical emission spectroscopy
XV
ORS
Octopole reaction system
PEMFC
Proton exchange membrane fuel cell
PGM
Platinum group metal
PIS
Product ion scan
PM10
Particulate matter with aerodynamic diameter smaller than 10 µm
PM2.5
Particulate matter with aerodynamic diameter smaller than 2.5 µm
PRF
Primary reference fuels
Q1
First quadrupole mass filter
Q2
Second quadrupole mass filter
RF
Radio frequency
SCR
Selective catalytic reduction
SOx
Sulphur oxides
TWC
Three-way catalyst
UNEP
United Nation Environment Program
λ
Normalised air-fuel ratio
XVI
Summary
Automotive catalytic converters are one of the most important emission sources of platinum group
metals (PGMs) into the environment, resulting in elevated Pt, Pd and Rh levels in road dust and soils
in the vicinity of roads. In this work, road dust and soil samples were collected in the city of Ghent.
Multiple sample preparation steps were performed, including a closed-vessel microwave digestion
step with aqua regia. To determine the PGMs, new methods were developed via tandem inductively
coupled plasma (ICP) - mass spectrometry, using a highly reactive gas mixture of CH3F/He as a
reaction gas. A systematic study of the reactions between the PGMs and CH3F was performed and
demonstrated that the dominant reactions are dehydrogenation for Pt, Os and Ir and methyl fluoride
addition for Pd, Rh and Ru. Since Pt, Pd and Rh are most abundantly used in automotive catalytic
converters, interference experiments were performed on these elements. The Pd and Rh methods are
affected by some spectral interferences that could not be removed. Nevertheless, the Pt method is
able to remove all spectral interferences and therefore could be applied to determine Pt contents in
urban samples, after successful validation with certified reference material BCR-723 (road dust). In
soil and road dust samples, measured Pt content ranges are 1.3-57.9 and 7.5-134.8 µg kg-1, respectively.
With increasing distance to the road, Pt contents in soil samples decrease. Moreover, in the upper 10
cm of the soils, the highest Pt contents are measured, while underlying soil layers contain very low
amounts of Pt. Heavy metals were determined via ICP-optical emission spectroscopy and no
correlations are found between heavy metals and Pt, except for Mn in road dust samples.
XVII
Samenvatting
Autokatalysatoren zijn een van de belangrijkste emissiebronnen van platinumgroep metalen in het
milieu. Ze zorgen voor een verhoogd niveau van Pt, Pd en Rh in straatstof en bodems langs wegen. In
het kader van dit onderzoek werden bodem- en straatstofstalen genomen in de stad Gent. Meerdere
stappen werden uitgevoerd tijdens de staalvoorbereiding, waaronder een digestie in gesloten
microgolfrecipiënten met koningswater. Om de platinumgroep metalen nauwkeurig te bepalen,
werden nieuwe methodes ontwikkeld via tandem inductief gekoppeld plasma (ICP) massaspectrometrie waarbij een sterk reactief gasmengsel van CH3F/He werd gebruikt als reactiegas.
Uit de systematische studie van de reacties tussen de platinumgroep metalen en CH3F bleek dat de
dominante reacties de volgende zijn: dehydrogenatie voor Pt, Os en Ir en methylfluoride additie voor
Pd, Rh en Ru. Aangezien vooral Pt, Pd en Rh rijkelijk worden gebruikt in autokatalysatoren, werden
interferentie-experimenten uitgevoerd op deze elementen. De Pd- en Rh-methodes blijken beïnvloed
te zijn door enkele spectrale interferenties die niet konden worden weggewerkt. De Pt-methode is
echter wel vrij van spectrale interferenties en werd succesvol gevalideerd met het gecertifieerd
referentiemateriaal BCR-723 (straatstof). Bijgevolg kon de Pt-methode toegepast worden om de Ptgehaltes te bepalen in de stalen. In bodemstalen zijn Pt-gehaltes in het bereik van 1.3-57.9 µg kg-1
gemeten en in straatstofstalen betreft dit 7.5-134.8 µg kg-1. Naarmate de bodem zich verder van de
weg bevindt, zijn er steeds lagere Pt-gehaltes in de bodem aanwezig. Bovendien zijn de hoogste Ptgehaltes gemeten in de bovenste 10 cm van de bodem en bevatten de diepere bodemlagen zeer lage
Pt-gehaltes. Ten slotte werden in dit onderzoek ook zware metalen gemeten aan de hand van ICP optische emissie spectroscopie. Er is echter geen correlatie vastgesteld tussen zware metalen en Pt,
met uitzondering van Mn in straatstofstalen.
XIX
1.
Introduction
In recent years, people are becoming more aware of environmental and climate problems.
Accordingly, lots of new technologies are being developed within the context of sustainable
development, such as wind turbines, solar panels, electric cars and batteries, fuel cells, LED-lights,
catalytic converters in cars and many more. However, for their production, tons of rare earth
elements and precious metals are needed. The platinum group metals (PGMs) are an important group
of metals needed. This group includes 6 elements: platinum (Pt), rhodium (Rh), palladium (Pd),
iridium (Ir), osmium (Os) and ruthenium (Ru). Three of them are commonly used for catalytic
converters in cars (Pt, Pd and Rh). The metals catalyse the oxidation and reduction reactions that
convert the harmful compounds such as nitrogen oxides (NOx), carbon monoxide (CO) and unburnt
hydrocarbons (HC), coming from the engine, into less harmful compounds like nitrogen gas (N2),
carbon dioxide (CO2) and water (H20) (Ravindra et al., 2004). There is a growing concern about the fact
that small amounts of PGMs, in the range of ng km-1, are emitted into the environment via
deterioration and surface abrasion of the catalysts. These elements can potentially accumulate in
soils, plants and road dust (Puls et al., 2010; Ravindra et al., 2004). However, analysing them in
environmental samples is still a major challenge.
The main analytical technique used, to analyse concentrations of PGMs present in soils, plant
material, road dust and airborne particulate matter is inductively coupled plasma-mass spectrometry
(ICP-MS) (Leśniewska et al., 2004; Morton-Bermea et al., 2014; Spaziani et al., 2008). ICP-MS is known
for its high sensitivity and multi-element capability and is the number one choice for trace element
analysis. Nevertheless, the technique has also a few disadvantages including spectral interferences.
Analysing the PGMs in environmental samples via ICP-MS entails several complex interferences. To
deal with these interferences, various techniques may be used, e.g., mathematical correction
procedures, operating the ICP-MS in high resolution mode, cool plasma technology and matrix
separation. A quite recent approach to resolve the interferences is the introduction of a
collision/reaction cell in which interferences can be removed by pressurising the cell with a
collision/reaction gas (Vanhaecke, 2015). In this work, a new tandem ICP-mass spectrometer is used
which relies on collision/reaction cell technology.
1
2.
Objectives
This work includes two general objectives. Firstly, the aim was to develop interference-free methods
for the determination of PGMs via a new tandem ICP-mass spectrometer, equipped with an octopole
reaction cell in between two quadrupoles, by pressurising this reaction cell with a highly reactive gas
mixture of methyl fluoride/helium (10 % CH3F/90 % He). Herewith specific objectives are:

study the reactions between the PGMs and CH3F. This includes the performance of product
ion scans, ramp cell gas tests and calibration curves.

check if the developed methods are able to remove all spectral interferences by performing
interference experiments on Pt, Pd and Rh, which are the most relevant PGMs in this study.

validate the interference-free methods by analysing a certified reference material.
The second general objective is to determine ultra-trace levels of PGMs in samples of road dust and
urban soils by applying the developed methods. Therefore, soil and road dust samples are collected
on various locations in the vicinity of some heavy traffic roads in the city of Ghent, at different
distances to the road and at different soil depths. These samples are analysed using the developed
methods. In this way, the dispersion of the PGMs via the car exhaust fumes can be mapped for the city
of Ghent, additionally the influence of the distance to the road and soil depth can be evaluated.
Furthermore, other heavy metals are determined in the collected soils to find correlations between
these heavy metals and PGM contents.
3
3.
Literature study
3.1. Introduction to the platinum group metals
The platinum group metals (PGMs) include six elements: platinum (Pt), palladium (Pd), rhodium (Rh),
ruthenium (Ru), iridium (Ir) and osmium (Os). Together with the elements gold (Au) and silver (Ag),
they form the group of noble metals (Glaister & Mudd, 2010). Platinum, palladium and rhodium are
the three PGMs with the greatest economic importance. The discovery of the PGMs dates from a few
centuries ago. In 1750, Dr. William Brownrigg and William Watson discovered the element platinum
in samples from the Colombian Choco district. There, the population already used the metal to make
jewellery, fishing hooks, etc. Since the Spanish term platina means “little silver”, the element was
given the name platinum (Brenan, 2008; Reith et al., 2014). Years later in 1804, iridium and osmium
were discovered by Smithson Tennant. The name iridium comes from the Greek word iris which
means rainbow, Tennant gave this name because he observed many different colours when he
dissolved the metal in hydrochloric acid (HCl). The metal osmium owes its name to the smell of
osmium tetroxide which is toxic and volatile. The Greek word osme means smell (Brenan, 2008).
William Wollaston, a colleague of Tennant announced three days after the discovery of iridium and
osmium, the identification of a new element rhodium. The solution which contained rhodium had a
pink colour and the element its name comes from the Greek word for pink, rhodon. One year later, in
1805, Wollaston announced another new element palladium. He named the element after the Pallas
asteroid that was discovered back then (Brenan, 2008). Ultimately in 1844, the element ruthenium
was discovered by the chemist Karl Klaus in platinum ore found in the Ural mountains, Russia. The
name of the element comes from the Latin word ruthenia, meaning Russia (Brenan, 2008). The PGMs
possess one of a kind chemical and physical properties that make them useful for a variety of
applications which will be discussed further (Reith et al., 2014). The elements are very rare in the
Earth’s crust. The average elemental concentrations in the continental crust of the PGMs are given in
Table 1. The concentrations stated in Table 1 are very low and there are limited places on Earth where
the PGMs are present in concentrations that are high enough to mine them in an economically
feasible way.
Table 1. Average element concentrations in the continental crust (Wedepohl, 1995)
Element
Average element
concentration (µg kg-1)
Element
Average element
concentration (µg kg-1)
Pt
0.4
Ru
0.1
Pd
0.4
Ir
0.05
Rh
0.06
Os
0.05
5
3.2. Global supply
The world supply of PGMs is dominated by the Bushveld complex, South Africa (Mudd, 2012). The
Bushveld complex is situated in the north-east of South Africa. It is the largest layered igneous
intrusion in the world, formed by slow cooling of a huge volume of magma (1 million km³) coming
from deep inside the Earth. The maximum layer thickness is approximately 8 kilometers and the area
covers around 250 km north-south and 450 km east-west (Cawthorn, 2010; Mudd, 2012; Schouwstra &
Kinloch, 2000). Globally, PGMs resources are estimated at approximately 90,700 t, in the Bushveld
Complex the PGMs resources are estimated at about 63,261 t. This means that the Bushveld complex
contains approximately 70 % of the global PGMs resources. The concentration of PGMs in the ores
varies around 3-23 g t-1 PGMs (Mudd, 2012). When comparing the average elemental concentration of
0.4 mg t-1 Pt with, for example, an ore grade of 5 g t-1 Pt, the platinum concentration in the ores is
more than 10,000 times higher than the average concentration. This makes it possible to mine the
PGMs in an economically feasible way.
Other major countries that play a key role in the supply of PGMs are Zimbabwe, Canada, Russia and
the USA (Glaister & Mudd, 2010). In Russia, it is especially the Noril’sk-Talnakh field that contains high
amounts of PGMs (Mudd, 2012). In order to give an overview of the contribution of each geographical
region to the global PGMs supply, data from the British multinational Johnson Matthey are used.
World supply graphs over a period of 2004 to 2013 are presented in Figure 1, 2 and 3 for platinum,
palladium and rhodium respectively. The conclusions that can be drawn from the graphs are as
follows, over this period of time Russia is the main producer of palladium, but the Russian palladium
supply is decreasing from approximately 150 tonnes per year in 2004 to 80 tonnes per year in 2013.
On the other hand, South Africa is by far the main supplier of platinum and rhodium. In comparison
with South Africa, the PGMs supply of Canada, Zimbabwe and the USA is a lot less, but the importance
of these countries should not be underestimated (Johnson Matthey Ltd., 2014).
With the rising PGMs demand in recent years, the mining activities will grow and the reserves will be
depleted faster. Furthermore, the required energy to mine PGMs will increase, since the depletion
results in lower PGMs ore grades. If the production costs keep on rising, the extraction processes will
not be economically feasible anymore and the prices of the PGMs will be higher than ever before
(Bardi & Caporali, 2014). To give an example, the price of platinum nowadays is nearly a factor 3
higher than the price in 1992 (32,392 € kg-1 on the 1st of May 2015 vs. 12,507 € kg-1 on the 1st of July
1992) (Johnson Matthey Ltd., 2015c). If the price becomes too high, the metals may be too expensive
to be used in some applications.
6
Platinum supply (t)
250
200
150
100
50
0
2004
2005
2006
South Africa
2007
Russia
2008
2009
North America
2010
2011
Zimbabwe
2012
2013
Others
Palladium supply (t)
Figure 1. World platinum supply over a period from 2004 to 2013 (Johnson Matthey Ltd., 2014)
300
250
200
150
100
50
0
2004
2005
2006
South Africa
2007
Russia
2008
2009
North America
2010
Zimbabwe
2011
2012
2013
Others
Figure 2. World palladium supply over a period from 2004 to 2013 (Johnson Matthey Ltd., 2014)
Rhodium supply (t)
30
25
20
15
10
5
0
2004
2005
2006
South Africa
2007
Russia
2008
2009
2010
North America
Zimbabwe
2011
Others
2012
2013
Figure 3. World rhodium supply over a period from 2004 to 2013 (Johnson Matthey Ltd., 2014)
Multiple information sources mention the possible future scarcity of the PGMs (Alonso et al., 2008;
Bardi & Caporali, 2014; Glaister & Mudd, 2010). In 2007, the U.S. National Research Council evaluated
the scarcity risk and classified PGMs as critical (Saurat & Bringezu, 2008). Further in this work
(Chapter 3.5), the possible future PGMs depletion problem will come back.
7
3.3. Applications
3.3.1. PGMs demand in different application areas
In this chapter, the demand for the PGMs in the different industries and application areas is discussed.
The PGMs have exceptional chemical and physical properties. They have overall good ductility, high
mechanical strength and melting point and they are resistant to corrosion even at high temperatures.
Additionally to this, they possess outstanding catalytic properties (Ravindra et al., 2004). Therefore,
the metals are used in industrial and automotive catalysts, fuel cells, the manufacture of jewellery,
the production of glass, alloys for dentistry, thermocouples, anticancer drugs, prosthetics, etc.
(Ravindra et al., 2004; Reith et al., 2014). An overview with some applications of the PGMs is given in
Table 2. Because of the limited applications, osmium is not mentioned in Table 2.
Table 2. Overview with some important application areas of the platinum group metals (Hagelüken, 2012)
Application area
Platinum Palladium
Catalysts
✔
✔
Electronics
✔
✔
Fuel cells
✔
✔
Glass, ceramics and pigments
✔
Medical/dental
✔
✔
Pharmaceutical
✔
✔
Rhodium
Iridium
Ruthenium
✔
✔
✔
✔
✔
✔
✔
✔
✔
✔
Photovoltaics
✔
Superalloys
✔
The platinum, palladium and rhodium demands for the different application areas in 2013 are given
in Figure 4. The most demanding industries for platinum are the automotive catalytic industry and
the jewellery industry, followed by the sector of the investment and the chemical industry. The
greatest demand for palladium and rhodium is for the automotive catalytic industry. To give an idea
about the total demand in mass units, the demands for the automotive catalytic industry are
calculated for the three PGMs. Around 37 % of the total demand of 262 t Pt, 72 % of the total demand
of 300 t Pd and 79 % of the total demand of 32 t Rh is used in the automotive catalytic industry. These
percentages correspond to approximately 97 t Pt, 216 t Pd and 25 t Rh (Johnson Matthey Ltd., 2014).
It is clear that the main application of the PGMs is the automotive catalyst. Further in this work, the
automotive catalyst will be discussed in detail (Chapter 3.4) because of its importance in controlling
vehicle exhaust emissions.
8
Pt
Pd
Autocatalyst
Chemical
Electrical
Glass
Investment
Jewellery
Medical & Biomedical
Petroleum
Other
Rh
Autocatalyst
Chemical
Autocatalyst
Dental
Chemical
Electrical
Electrical
Investment
Jewellery
Other
Glass
Other
Figure 4. Gross demand in 2013 for platinum (left), palladium (middle) and rhodium (right) in the various
application areas and industries (Johnson Matthey Ltd., 2014)
3.3.2. Industrial catalysts
Platinum group metal-based catalysts are commonly used in all kinds of industrial processes. The
production of nitric acid via ammonium oxidation for instance can be catalysed by platinum-rhodium
catalysts. The synthesis process happens in three main steps. Firstly, ammonia gas (NH 3) is oxidised
with air, forming nitric oxide (NO). This step is usually performed over a Pt-Rh catalyst under
pressure. Secondly, cooling and further oxidation of NO is required to obtain nitrogen dioxide (NO 2).
Finally, nitric acid is produced by absorption of NO2 in water. Subsequently, nitric acid can be
processed to e.g., nitrogen fertilizers (Bell, 1960; Johnson Matthey Ltd., 2015b; Reith et al., 2014). In
the refining and petroleum industry, PGM-based catalysts are used in multiple processes. An overview
of the different applications is given in Table 3.
Table 3. PGM-based catalysts in the refining and petroleum industry (Marcilly, 2003)
Catalyst
Metals
Monometallic
Ru
Pd
Ir
Pt
Association of metals
Pd with Ag or Au
Pt with Ge, Sn, Re or Ir
Pt with Sn
Pt-Pd
Industrial use
Selective hydrogenation, metathesis of olefins
Hydrocracking, selective hydrogenation
Dearomatisation
Reforming, C4-C6 isomerisation,
dehydrogenation, hydrogenation, isodewaxing
Selective hydrogenation
Reforming
Dehydrogenation
Hydrogenation of aromatics in presence of
sulfur
9
Platinum-iridium or platinum-rhenium catalysts are commonly used in reforming processes to raise
the octane number of a fuel (Brenan, 2008). The octane rating or octane number is an important
characteristic for fuels. For internal combustion engines with spark-ignition, it is a measure to
evaluate the resistance of the fuel to autoignition (McAllister et al., 2011). In these engines, fuels with
high tendencies to autoignition are disadvantageous. The octane rating is determined by comparing
the knock resistance of the fuel to a mixture of the easy to combust normal heptane (n-heptane) and
the hard to combust isooctane (2,2,4-trimethylpentane). The components normal heptane and
isooctane are called the primary reference fuels (PRF). Octane ratings for n-heptane and isooctane are
0 and 100, respectively. For purposes of illustration, gasoline with an octane rating of 80 has a similar
anti-knocking capacity as a fuel mixture with 80 vol % isooctane and 20 vol % n-heptane (McAllister
et al., 2011). Well-known processes in the petroleum industry to improve the octane number are e.g.,
n-heptane dehydrogenation to toluene and C4-C6 alkanes isomerisation (Brenan, 2008).
3.3.3. Fuel cell
Fuel cells are able to transform the free energy coming from chemical reactions, into electrical energy
and they are in fact galvanic cells. Basic fuel cells comprise two electrodes linked by an external circuit
and isolated from each other by an electrolyte. The electrodes are supplied with a fuel and oxidant
and are porous in order to be permeable for gases or liquids. Hydrogen gas and methanol are
dominant fuels used for oxidation at the anode (Carrette et al., 2001). Moreover, ethanol is a promising
alternative for methanol in fuel cells because of its higher energy density (Bergamaski et al., 2008).
The cathodic reaction is the reduction of oxygen, present in air (Carrette et al., 2001). Figure 5 shows
an example of a hydrogen/oxygen fuel cell in which the electrons flow in an external circuit.
Figure 5. Schematic representation of a hydrogen/oxygen proton exchange membrane fuel cell (Carrette et al.,
2001)
The overall reaction (1) of the proton exchange membrane fuel cell (PEMFC) is (Carrette et al., 2001) :
𝐻2 + 1⁄2 𝑂2 → 𝐻2 𝑂
10
∆𝐺 = −237 𝑘𝐽 𝑚𝑜𝑙 −1
(1)
From all PGMs, especially platinum has an important function in fuel cells. Pt-based catalysts are used
for the oxidation reactions. The active catalyst surface is able to adsorb hydrogen gas molecules and
dissociate them subsequently. The reactions at the anode (2), (3) and overall oxidation reaction (4)
are stated below (Carrette et al., 2001) :
2 𝑃𝑡(𝑠) + 𝐻2 → 2 𝑃𝑡 − 𝐻𝑎𝑑𝑠
(2)
𝑃𝑡 − 𝐻𝑎𝑑𝑠 → 𝐻 + + 𝑃𝑡(𝑠) + 𝑒 −
(3)
𝐻2 → 2 𝐻 + + 2 𝑒 −
(4)
In the case of methanol oxidation at the anode, Pt-based catalysts are used as well. The overall
oxidation reaction (5) for the oxidation of methanol is (Carrette et al., 2001):
𝐶𝐻3 𝑂𝐻 + 𝐻2 𝑂 → 𝐶𝑂2 + 6𝐻 + + 6𝑒 −
(5)
The active surface of the catalyst adsorbs the methanol molecules and deprotonates the molecules in
several steps. During these steps CO is formed, which blocks active surface sites. By adding co-metals,
the formation of CO can be reduced (Carrette et al., 2001). Co-metals like ruthenium, osmium, iridium,
tin, rhenium and bismuth are investigated for use in the methanol oxidation catalysts and show
enhanced activity (Gurau et al., 1998; Hampson et al., 1979; Morimoto & Yeager, 1998; Watanabe &
Motoo, 1975).
Actually, fuel cells date back to the mid-1800s but there was not that much interest because of the use
of fossil fuels to produce electricity. In the last decades, there is more attention for fuel cells. One of
the main reasons for this increasing interest is the environmental concern (Carrette et al., 2001). The
production of electricity, based on fossil fuels, has a big influence on the environment. The CO 2emission caused by the combustion of fossil fuels is enormous. In contrast to this, hydrogen/oxygen
fuel cells emit H2O instead of CO2. Furthermore, the electrical efficiency of fuel cells is very much
higher than the efficiency of a combustion engine (Carrette et al., 2001). Nowadays, fuel cells are used
for stationary power generation and in cars, but also in some smaller applications such as the
Dynario™ direct methanol fuel cell from Toshiba Inc. This is a small portable fuel cell which delivers
energy to power electronic mobile devices (Carrette et al., 2001; Toshiba Inc., 2009).
3.3.4. Jewellery
The most important PGM in the jewellery manufacture is platinum. Usually, the jewellery consists of
85 percent platinum. Alloying metals are added, to obtain the required wear and working
characteristics. Frequently used alloying metals are ruthenium, palladium, iridium, cobalt and
copper. Platinum jewellery is known for its high strength and its permanent retention of shapes,
which make it highly suitable for the setting of diamonds in all kinds of design (Johnson Matthey Ltd.,
2015a).
11
3.3.5. Dentistry
To restore a decayed tooth, dentists often use crowns or in the case of multiple decayed teeth, they
use bridges. These structures are commonly made out of Pd-based alloys (Rushforth, 2004). Palladiumsilver, palladium-gold-silver and palladium-copper alloys are the most important ones (Böck, 2006).
Sometimes platinum is used as alloying metal but palladium is preferred because it has similar
physical and chemical properties as platinum (superior oral environment biocompatibility and
corrosion resistance) and palladium is less expensive and has a lower specific gravity (Rushforth,
2004).
3.3.6. Glass manufacture
Especially platinum, iridium and platinum-rhodium alloys are of great importance in the glass
manufacture, since PGMs are known for their resistance to corrosion and high melting point. These
metals are used in separate parts (stirrers, tubes, etc.) or as coatings on ceramic substrates. They
protect ceramic substrates and components (thermocouples, furnace walls and forehearth parts)
from corrosive vapours and molten glass erosion (Couderc, 2010). The addition of rhodium in Pt-Rh
alloys improves the mechanical strength and to obtain even higher durability and mechanical
strength, zirconium can be added (Couderc, 2010). Iridium is a promising alternative for platinum and
platinum-rhodium alloys, it has similar properties and it is less expensive than platinum and rhodium.
The price of iridium is about half the price of platinum and rhodium (Couderc, 2010; Johnson Matthey
Ltd., 2015c). The use of PGMs in the glass making industry not only extends the furnace lifetime, but
it also provides better glass quality because of less contamination by dissolution of ceramic materials
(Couderc, 2010).
3.3.7. Anticancer drugs
Studies showed that platinum complexes possess effective anticancer activity and that platinum
complex (NH4)2[PtCl6] is able to inhibit the growth of Escherichia coli cultures (Pawlak et al., 2014). In
the past three decades, many platinum complexes have been tested to cure different kinds of tumors.
Some of them have been used with great success in the chemotherapy of human cancers. Carboplatin
and cisplatin are the two main platinum complexes utilised in chemotherapy (Pawlak et al., 2014).
The chemical structures of the anti-cancer drugs cisplatin (cis-[Pt(NH3)2Cl2]) and carboplatin (cis[Pt(NH3)2CBCDA], CBCDA = 1,1-cyclobutanedicarboxylic acid) are represented in Figure 6 (Hambley,
1997).
12
Figure 6. Chemical structures of the platinum complexes cisplatin (left) and carboplatin (right) (Hambley, 1997)
3.3.8. Prosthetics
Prosthetics are artificial body parts which substitute the natural missing body parts, lost due to
disease or trauma. The first artificial body parts date back to the ancient Egyptians (1500 B.C.), they
are considered as the masterminds of prosthetics. Scientists discovered the first functional prosthetic
toe, made of fibers, on the foot of an Egyptian mummy (Norton, 2007). Nowadays, prosthetics can be
equipped with computer chips and microprocessors, which make it possible to perform natural
movements with robotic arms, legs and other body parts (Norton, 2007). Prosthetics are sometimes
made of platinum. Platinum femoral components of a knee prosthesis are commonly used (Shur,
2010). The surface of a metallic bone joint prosthesis can be coated with a layer of ruthenium, iridium,
platinum or alloy of these metals, to improve the prosthesis resistance to synovial fluid corrosion
(Notton, 1981). In prosthesis fasteners for heart valves, biocompatible materials such as platinumiridium alloys can be applied (Buchanan & Anderson, 2000).
3.3.9. Electronics
Due to their exceptional chemical and physical properties, PGMs also have applications in the
electronic industry. Platinum, ruthenium, palladium and rhodium are applied as coatings, to protect
base metal materials from corrosion. Moreover, connectors are frequently electroplated with a Pd/Ni
coating. The main application of palladium in the electronic industry is the multi-layer ceramic
capacitor (MLCC) (Böck, 2006). The function of a capacitor is to temporarily store and release electrical
energy (Bird, 2010). The MLCC consist of multiple ceramic sheets with internal electrodes (Masuda,
2001). In between the electrodes, a conductive paste is present. This conductive paste contains a
powder with palladium, nickel, copper and silver (Ferrier et al., 1985; Masuda, 2001). Next to these
applications, PGMs are applied in hard disks and in smaller amounts in cell phones (Alonso et al.,
2008).
13
3.4. The development of the automotive catalytic converter
3.4.1. Introduction
The automotive catalytic industry is responsible for the greatest amounts of PGMs usage, globally
about 338 t PGMs is used in this industry each year. By comparing this value to the global total PGMs
demand, estimated at approximately 626 t PGMs (osmium not included), the automotive catalytic
industry is responsible for 54 % of the total PGMs usage (Johnson Matthey Ltd., 2014). The next
chapters will describe the history of the catalytic converter in cars, the structure and design of recent
automotive catalytic converters and environmental problems linked to the application of PGMs in the
catalytic converters.
The invention of the first car is not clearly stated in its history, Isaac Newton and Leonardo Da Vinci
already made plans to build motor vehicles hundreds of years ago but they were not able to convert
their ideas into reality because of the less developed state of technology in that time (Dutton, 2006).
In 1885, a mechanical engineer from Germany, named Karl Benz, designed and built the first ever
practical car, driven by an internal combustion engine, in the world. One year later in 1886, he
obtained the first patent for a three-wheeled car fuelled by gas and a few months later Gottlieb
Daimler designed the first car with four wheels (Dutton, 2006), pictures of the first cars are shown in
Figure 7. Since that time, the development of cars gained momentum. In the USA, commercial cars
powered by gasoline were developed and more and more cars became available on the market
(Dutton, 2006).
Figure 7. The first three-wheeled car design from inventor Karl Benz (left) and the first four-wheeled car design
from inventor Gottlieb Daimler (right) (Dutton, 2006)
In the beginning of the 1940s, the awareness of the environmental pollution related to the emissions
of gasoline engines, started to increase in the USA and around Tokyo (Acres & Cooper, 1972; Morgan,
2014). This was a result of the photochemical smog in Los Angeles. Photochemical smog is an
atmospheric phenomenon and occurs when NOx and unburnt HC react and form noxious compounds.
Due to an inversion of temperature in the upper air layers, these compounds did not dissipate in the
higher atmosphere and they were accumulated at the surface layer in the city of Los Angeles. As a
consequence, the residents experienced an irritating feeling in their eyes (Acres & Cooper, 1972). This
14
attracted the attention of the United States. Soon, it was clear that the main reason for the smog was
the internal combustion engine. The emissions of the engines contain high amounts of unburnt HC,
NOx, CO and lower quantities of particulates, Pb and sulphur oxides (SOx) (Acres & Cooper, 1972).
Subsequently in 1970, the USA introduced stricter standards for CO, HC and NOx emissions by signing
the Clean Air Act. Emissions from model year 1970 levels required a 90 % decrease of HC and CO by
1975 and emissions from model year 1971 levels required a 90 % NOx decrease by 1976 (Twigg, 2011).
In order to meet the new standards, different methods to control the automotive emissions were
developed. In the next chapter, the development of certain emission control systems will be
discussed.
3.4.2. The first emission control systems
The methods are categorised into two groups: preventive and destructive methods. The first
destructive methods are (a) manifold air oxidation, (b) thermal reactors and (c) catalytic reactors
(Acres & Cooper, 1972) :
(a)
Manifold air oxidation: oxidation of CO and HC in the hot exhaust manifold by injecting
air into the manifold.
(b)
Thermal reactor: high-volume chamber that is thermally isolated and placed downstream
the combustion chamber, in which air is injected and the pollutants react (less CO and
unburnt HC).
(c)
Catalytic reactor: catalytic chamber, placed downstream the combustion chamber, in
which active materials are applied to catalyse oxidation and reduction reactions. An
oxidation catalyst oxidises CO and HC, a reduction catalyst is able to reduce the NO x
emissions.
Examples of the first preventive methods are exhaust gas recycling (EGR) and the use of leaner
gasoline mixtures. Exhaust gas recycling gives the opportunity to control the NO x emissions by
recirculating part of the exhaust gas again to the combustion chamber. The use of leaner gasoline
mixtures with a higher air-fuel ratio (AFR) provide less CO and unburnt HC in the exhaust fumes
(Acres & Cooper, 1972). A combustible mixture can be characterised by the air-fuel ratio and the
equation (i) for the AFR is stated below (McAllister et al., 2011):
𝐴𝐹𝑅 =
𝑚𝑎𝑖𝑟
𝑚𝑓𝑢𝑒𝑙
(i)
The mass of air and fuel are represented by mair and mfuel. The stoichiometric AFR (AFRs) is the
theoretical AFR so that the combustible mixture comprises the precise quantity of air and fuel for the
total combustion of the fuel. The typical AFRs for gasoline is approximately 14.7. Another variable
based on the AFR is the normalised air-fuel ratio (λ), see equation (ii) below (McAllister et al., 2011):
15
𝐴𝐹𝑅
𝜆 = 𝐴𝐹𝑅
𝑠
(ii)
The normalized air-fuel ratio is used to characterise mixtures as rich, lean or stoichiometric. If λ = 1,
the mixture is stoichiometric. If λ > 1, the mixture is lean and if λ < 1, the mixture is rich. This means
that for lean mixtures, an excess of air is used to combust the fuel. To reduce the amount of HC and
CO emissions, lean air-fuel mixtures can be used. Due to the excess air, there will be less unburnt HC
and less CO in the exhaust gasses, as mentioned above (McAllister et al., 2011).
3.4.3. The catalytic approach
The destructive catalytic approach was an interesting option to deal with the reduction targets for
the automotive emissions since not a lot of adjustments are needed for the installation of the catalysts
and since the efficiency stays high, even at lower temperatures. The only problem was the
composition of the fuel (gasoline), containing phosphorus (pre-ignition control) and lead (anti-knock)
(Acres & Cooper, 1972). Lead and phosphorus are compounds that are poisonous for the catalysts, so
there was a need for fuel that is high in octane, phosphorus-free and lead-free (Acres & Cooper, 1972).
The Environmental Protection Agency (EPA) demanded to make changes in the chemical composition
of fuels, related to these compounds, in this way the catalytic reactors could be developed and
introduced into the automobile industry (Acres & Cooper, 1972). In 1975, the first cars equipped with
an oxidation catalyst were manufactured in the USA, for Europe this was the case in 1986 (Palacios et
al., 2000).
The first automotive catalyst installed was an oxidation catalyst, downstream the engine, with an
additional air pump so that the exhaust mixture was certainly lean enough for the reactions, inside
the oxidation catalyst. The main reactions (6) and (7) are stated below (Twigg, 2011):
𝐶𝑂 + 1⁄2 𝑂2 → 𝐶𝑂2
(6)
𝐶𝑥 𝐻𝑦 + (𝑥 + 1⁄4 𝑦)𝑂2 → 𝑥𝐶𝑂2 + 1⁄2 𝑦𝐻2 𝑂
(7)
The oxidation catalyst contained a stainless steel can with inside a monolithic ceramic honeycomb
structure, the channels of the structure were coated with a washcoat, mostly alumina (Al2O3),
containing metals that act as catalysts for the oxidation reactions. Base metals were tested as coating
metals but their performance, poison resistance and durability were not good enough. Pt-based
catalysts perform significantly better and their long-term activity is much better, resulting into the
production of Pt-based oxidation catalysts on an industrial scale (Twigg, 2011).
From this point on, the research for better and better emission control systems developed further. To
obtain enhanced durability, a second PGM addition becomes a possibility. Palladium or rhodium can
be added as a second PGM in the oxidation catalyst. However, large vehicle catalytic manufacturers,
such as Johnson Matthey, preferred only little amounts of valuable rhodium in their oxidation
16
catalysts. The control of the gasoline engine emissions with only an oxidation catalyst was not of long
duration since NOx emissions are not controlled with this type of catalyst. More complicated systems
had to be developed (Twigg, 2011).
Exhaust gas recycling ensures less NOx formation during the combustion. As mentioned above, this is
achieved by recirculating part of the exhaust gas back to the combustion engine. EGR provides a
reduction in NOx emissions but there was still room for improvement. Therefore, it was essential to
find a way to transform NOx to N2, which is an inert gas (Twigg, 2011). A huge amount of tests and
studies were performed to get insight into the processes of the reduction of NO x on catalysts. It
became clear that under lean conditions, the reduction of NOx was not possible. The catalytic reactions
for the example of NO are stated below (Twigg, 2011):
2 𝑁𝑂 → 2 𝑁𝑎𝑑𝑠 + 2 𝑂𝑎𝑑𝑠
(8)
2 𝑁𝑎𝑑𝑠 → 𝑁2
(9)
𝑂𝑎𝑑𝑠 + 𝐻2 → 𝐻2 𝑂
(10)
𝑂𝑎𝑑𝑠 + 𝐶𝑂 → 𝐶𝑂2
(11)
Equation (8) represents the NO dissociative adsorption and equation (9) is the N2 fast desorption. The
problem here is that the active surface of the catalyst powerfully adsorbs the oxygen atoms, these
atoms reduce the amount of active sites on the catalyst surface available for NO dissociation. The only
option to displace the oxygen atoms from the active surface places, is via reaction with a reducing
agent (H2 or CO stated in equations (10) and (11), respectively) (Twigg, 2011). From all this, it is clear
that the reduction catalysts should be used under rich conditions and not under lean conditions. The
most suitable metals to act as catalysts for this process, are the PGMs ruthenium and rhodium (Twigg,
2011). Rhodium was preferred over ruthenium for this application. Further in this chapter the main
reason for this choice will be explained.
In 1976, the first system in cars that considerably reduced the emissions of the three pollutants (CO,
HC and NOx) coming from gasoline engines, was implemented and consisted of two individual
catalysts, both containing PGMs (Twigg, 2011). Figure 8 shows a schematic drawing of the Johnson
Matthey emission control system design for 1976 model cars, drawn in 1972 (Acres & Cooper, 1972).
This system is called a dual-bed catalytic converter (Morgan, 2014). Firstly, the reduction catalyst
(mostly Rh-based) works in a reducing atmosphere and reduces NOx to N2. Secondly, an oxidation
catalyst (mostly Pt-based) works under lean conditions by the presence of a secondary air pump and
oxidises unburnt HC and CO. This first system works effectively, but a major disadvantage is the high
production cost (Twigg, 2011).
17
Figure 8. The Johnson Matthey design for 1976 model cars of the first automotive catalytic system controlling
CO, HC and NOx emissions by installing a reduction catalyst (NOx converter) downstream the combustion engine
and further downstream the injection point of the secondary air pump and the oxidation catalyst (CO/HC
converter) (Acres & Cooper, 1972)
3.4.4. Three-way catalyst
After several years of research, an even more efficient and more economically interesting automotive
catalytic system was developed, the three-way catalyst (TWC). The first three-way catalyst is a single
platinum-rhodium catalyst that is able to remove CO, HC and NOx at the same time. The most
important reactions for TWCs are stated below (Palacios et al., 2000; Twigg, 2011) :
(12)
Steam-reforming reaction
𝐶𝑂 + 1⁄2 𝑂2 → 𝐶𝑂2
𝐶𝑥 𝐻𝑦 + (𝑥 + 1⁄4 𝑦)𝑂2 → 𝑥𝐶𝑂2 + 1⁄2 𝑦𝐻2 𝑂
𝐻2 + 1⁄2 𝑂2 → 𝐻2 𝑂
𝐶𝑥 𝐻𝑦 + 𝑥𝐻2 𝑂 → 𝑥𝐶𝑂 + (𝑥 + 1⁄2 𝑦)𝐻2
NOx reduction
2𝐶𝑂 + 2𝑁𝑂 → 2𝐶𝑂2 + 𝑁2
(16)
Oxidation reactions
(13)
(14)
(15)
𝐶𝑥 𝐻𝑦 + (2𝑥 + 1⁄2 𝑦)𝑁𝑂 → 𝑥𝐶𝑂2 + 1⁄2 𝐻2 𝑂 + (𝑥 + 1⁄4)𝑁2 (17)
Water-gas shift
𝐻2 + 𝑁𝑂 → 𝐻2 𝑂 + 1⁄2 𝑁2
(18)
𝐶𝑂 + 𝐻2 𝑂 → 𝐶𝑂2 + 𝐻2
(19)
When comparing reactions (13) and (17) regarding thermodynamics and kinetics, the most favourable
reaction is (13), the hydrocarbon oxidation with oxygen. An effective working catalyst should be able
to promote reaction (17), the hydrocarbon oxidation by NO. Such a reaction is a selective catalytic
reduction (SCR) reaction (Palacios et al., 2000). In order to obtain optimal conversion efficiencies for
CO, NOx and HC, the structure and type of the catalyst is very important. Next to this, the operating
AFR in the gasoline engines has to be kept around the AFRs (Palacios et al., 2000; Twigg, 2011).
Therefore, new technologies are required to control the engine operation. An oxygen sensor has to
be installed to analyse the exhaust gas, whether the mixture is rich or lean. The lambda-sensor is an
18
example of an oxygen sensor where the lambda refers to the normalized air-fuel ratio λ, which has to
be kept at around 1 in order to run the engine around the stoichiometric point (Eschnauer, 2000). In
order to add correct quantities of fuel, to keep stoichiometric conditions, an electronic fuel injection
system (EFI) is installed. Furthermore, for the overall control, the system is equipped with a
microprocessor. The industrial production of the TWCs started in the beginning of the 1980s and the
TWCs became the number one choice for the emission control in the automotive industry (Twigg,
2011).
The structure of the oxidation catalyst is already shortly explained above. In this part, the structure
of the TWC will be explained further in detail. As for the oxidation catalyst, the TWC consist of a metal
can in which a monolithic ceramic honeycomb structure or a metal substrate converter is present,
see Figure 9 (Fornalczyk et al., 2014). Metal substrate converters (MSCs) are very reliable under
constant high temperatures and loads. They provide minimal back pressure and they are initially
created for racing cars. Due to the high costs of the MSCs, their application in normal passenger
vehicles is limited (Fornalczyk et al., 2014). Ceramic honeycomb structures are chosen above the
MSCs. They typically consist of alumina or cordierite (Mg2Al4Si5O18) (Ravindra et al., 2004). The cell
density of cordierite catalysts is higher than for standard alumina based catalysts (140 cells cm-2 vs. 64
cells cm-2), resulting in more surface contact. Other important advantages of the cordierite catalysts
are their resistance to thermal shock abrasion and their flexibility to extrusion processes (Palacios et
al., 2000). The walls of the honeycomb-type structures are coated with high-surface active alumina,
this layer is called a washcoat. Almost 90% of the washcoat is γ-Al2O3, the rest of the layer is a mixture
of metal oxides (La2O3, ZrO2, CeO2…), alkaline earth metals and/or rare-earth metals and the catalytic
active PGMs (Palacios et al., 2000; Ravindra et al., 2004). The method used for the catalyst preparation
is mainly washcoating. The catalyst substrate (honeycomb-type structure) is immersed into an
aqueous suspension which comprises oxides (La, Ba, Zr, Ce, etc.) and alumina. The rest of the
suspension is blown out of the channels of the substrate which is subsequently calcinated for a few
hours (700 °C). Next to this, for the PGM surface, co-impregnation of the corresponding precursor
salts is generally used. For Pt, Rh and Pd, the precursor salts are H2PtCl6 · 6H2O, RhCl3 and PdCl2
respectively. Finally, a hydrogen reduction process at approximately 500 °C is applied to reduce the
PGMs (present in the surface layer) to obtain the metallic form of the PGMs (Palacios et al., 2000). The
PGMs are present in little quantities in standard TWCs (0.10-0.15 % w/w). Nevertheless, they are
crucial for proper functioning. Platinum mainly promotes reaction (19), the water-shift equilibrium
and this results in the removal of CO. Rhodium is known for its promotion of reaction (17), the
reduction of NOx by HC. Moreover, rhodium promotes reaction (15), the steam-reforming reaction.
Palladium mainly promotes reactions (12) and (13), resulting in lower CO and HC levels (Palacios et
al., 2000).
19
Figure 9. Schematic representation of the TWC (left) and a picture of BASF’s TWC (right) (BASF Ltd., 2015;
Fornalczyk et al., 2014)
The multiple reasons why Al2O3 is preferred, are the low costs, the possibility to easily shape the
material with excellent porosity control and the possibility to electrically charge (+ or -) the surface
so that selective ion absorption can take place (Palacios et al., 2000). The addition of base metal oxides
has several important functions. Firstly, the alumina washcoat is stabilised. Secondly, better thermal
resistance is obtained and finally, the dispersion of the PGMs over the washcoat is more
homogeneous. This results in an enhanced activity of the catalyst (Palacios et al., 2000). As stated
above, the platinum-rhodium based TWCs are effective in reducing CO, HC and NOx. Rhodium is
mainly used in the catalysts to lower NOx emissions although ruthenium is a viable alternative because
of the lower price of ruthenium. The main reason why rhodium is chosen instead of ruthenium is that
ruthenium suffers from metal loss. Due to the high temperatures inside the TWC, higher ruthenium
oxidation state oxides can be formed, such as RuO4 which is a very volatile compound (Perry, 2011;
Twigg, 2011).
Another cost-efficient alternative element to apply in the TWC, is palladium. Until the early 1990s,
palladium could not be used for the autocatalyst application because the precious metal is very prone
to sulphur and lead poisoning (Twigg, 2011). Platinum on the contrary is more noble in that way than
palladium (Gandhi et al., 2003). With the introduction of lower sulphur levels in gasoline, the
application of palladium in the TWC became an interesting option. Three-way catalysts containing
platinum, rhodium and palladium are named ‘trimetal’ TWCs (Twigg, 2011) and from there on, further
developments in the PGM composition of TWCs were made. Palladium-rhodium catalysts have been
developed without the more expensive platinum. The development of thermally stable ’palladiumonly’ catalysts, that were able to control CO, HC and NOx effectively, is realised in the mid-1990s. In
result of the constantly rising demand for palladium, the price also went up. Stricter standards on NOx
emissions, together with the increased prices of palladium, resulted in a comeback of rhodium and
platinum into TWCs (Twigg, 2011). In Figure 10, the evolution of the PGMs demand for the automotive
catalyst application is represented over a period of 2004 until 2013. The palladium demand in 2013 is
approximately doubled in comparison with the palladium demand in 2004. The platinum demand is
decreasing slowly and the rhodium demand is nearly constant during this period. Due to the 2008
20
global financial crisis, there is a sharp drop (22 %) in the demand in the following year. To conclude,
it is likely that in coming years again more and more palladium will be used in automotive catalytic
converters. The main reason for this evolution is the price of the metals. Nowadays, palladium is
cheaper than platinum (22,150 € kg-1 Pd vs 32,392 € kg-1 Pt on the 1st of May 2015) and is able to catalyse
the oxidation reactions inside the catalytic converter with similar efficiency. By using less platinum,
the overall price of catalytic converters lowered as a consequence (Bardi & Caporali, 2014; Johnson
Gross demand (t)
Matthey Ltd., 2015c).
400
300
200
Rh
100
Pd
0
2004
Pt
2005
2006
2007
2008
2009
2010
2011
2012
2013
Year
Figure 10. Annual gross demand of PGMs for automotive catalysts over a period of 10 years (2004-2013). In 2009,
the overall PGM consumption dropped by 22 % due to the global financial crisis (Johnson Matthey Ltd., 2014).
3.5. Possible PGMs scarcity problems
As stated in the previous chapter, the catalytic converters are fully dependent on the PGMs (Pt, Pd
and Rh). Without these elements, the three way catalytic converters do not function. Chapter 3.2
mentioned that economically exploitable ores of the PGMs are very rare. This combination can lead
to a serious problem in assuring the supply. When mankind is further depleting these precious metals,
both the prices of the metals and the prices of the catalytic converters will rise (Bardi & Caporali,
2014). Moreover, since 1993, the catalytic converters in cars are mandatory in the European Union
(EU) according to the EURO 1 standards (Departement Leefmilieu Natuur en Energie, 2015). Therefore,
sustainable management of the PGMs is extremely important to keep the price of the catalytic
converters acceptable.
Efforts were made to find other materials substituting PGMs, which are able to catalyse the reactions
of the three-way catalyst equally but until now, there is no alternative. PGMs have unique properties
and are stable under long periods of high temperature (Bardi & Caporali, 2014). Apart from this, there
are two main options to deal with the increasing PGMs scarcity. The first option is to reduce the
quantity of PGMs in the automotive catalytic converters. This option is practically limited because
the removal efficiency of the catalytic converter has to stay as high as possible. Nevertheless, it is
realistic to reduce the amount of PGMs a little. The reduction can be realised by just adding lower
quantities of PGMs to catalytic converters (Bardi & Caporali, 2014). Alternatively, adding more but
smaller particles (higher surface/volume ratio), can provide the same total contact surface with the
21
exhaust fumes, but lowers the required total volume and mass of PGMs. Nevertheless, particles should
not be too small to prevent them to be unstable, otherwise the particles end up in the environment
with the car exhaust fumes (Bardi & Caporali, 2014).
The second option is the efficient recycling of PGMs. End-of-life products should not be considered as
waste but should be used as a source of elements for other products (Bardi & Caporali, 2014). Urban
areas incorporate enormous material stocks, for example buildings, roads, cars, etc. These huge stocks
are utilisable for reuse at end-of-life. The reuse of materials from urban areas is known as urban
mining (Brunner, 2011). It is interesting and energy saving to use the catalytic converters from endof-life vehicles as a source of PGMs. According to a report from the United Nations Environment
Program (UNEP), an automotive catalytic unit contains around 2-5 g PGMs. This corresponds with a
PGM concentration that is higher than 1,000 g t-1 (Buchert et al., 2009). Hagelüken (2012) even
mentions concentrations up to 2,000 g PGMs per ton ceramic catalyst substrate. By comparing these
values with 10 g PGMs per ton primary ore, this is more than a factor 100 higher (Hagelüken, 2012).
Less energy and costs are required to extract the PGMs from the catalytic converter in comparison
with primary ores (Buchert et al., 2009). Consequently, recycling is attractive from an economical and
environmental point of view (Hagelüken, 2012). Umicore (Hoboken, Belgium) practices secondary
refining of PGMs and the practice shows that the environmental pressure caused by secondary mining
is considerably lower than the environmental pressure caused by primary mining (Saurat & Bringezu,
2008). PGMs have a great technical recyclability, around 95 % recovery is possible if the scrap arrives
at a modern secondary refining facility (Hagelüken, 2012). Nevertheless, the actual recycling rates at
end-of-life of platinum are much lower (Bardi & Caporali, 2014). In the USA, recycling rates for
platinum in 1993 are around 38 % (Sibley & Butterman, 1995). Nowadays the recycling rates for
platinum and other precious metals are higher and vary around 60 % (Reck & Graedel, 2012). Platinum
recycling rates from automotive catalytic converters are in the same range of 50-60 % (Bardi &
Caporali, 2014).
The high temperatures and strong vibrations inside the automotive catalytic converter, while driving
a car, cause deterioration and surface abrasion of the washcoat layer. Little particles, of a size ranging
from a few micrometers (PM10: aerodynamic diameter < 10 µm and PM2.5: aerodynamic diameter < 2.5
µm) to sub-micrometers, break off the washcoat and they are emitted into the atmosphere through
the exhaust (Puls et al., 2010). This results in a loss of elements that are available for recycling (Bardi
& Caporali, 2014). In chapter 3.6, the environmental problems linked to these emissions will be
discussed. To estimate the amount of PGMs that is emitted by vehicles, dynamometer tests measuring
the vehicle emissions during standardised driving cycles can be performed. The vehicle is set on a
roller system during the driving cycles and via constant volume sampling, the exhaust is captured
(Limbeck & Puls, 2010). The tests do not fully imitate real-life conditions since the results of laboratory
studies differ significantly from results of studies under real driving conditions. However, the
22
dynamometer tests are most frequently used (Limbeck & Puls, 2010). A picture from 1972 of a
dynamometer test setup is shown in Figure 11.
Figure 11. Dynamometer setup of a Marina test vehicle (Acres & Cooper, 1972)
Cheaper, less complex and more representative tests than the dynamometer tests are the tunnel
studies (Jamriska et al., 2004). Tunnel studies are based on real-world driving conditions and give a
better estimation of the average emission of vehicles. The pollutant concentrations are measured at
the same time, at the beginning and at the end of the tunnel. In addition to these measurements,
temperature, pressure, traffic density, vehicle velocity and wind velocity have to be measured
(Limbeck & Puls, 2010). By combining the various measurements and the method of Pierson, the
vehicle emission factor can be calculated as the mass of the total emission of a certain pollutant per
vehicle per kilometer. The method of Pierson uses the following formula to calculate the emission
factor (Limbeck & Puls, 2010):
𝐸𝐹𝑣𝑒ℎ =
(𝑐𝑜𝑢𝑡 −𝑐𝑖𝑛 ).𝐴.𝑈.𝑡
𝑁.𝑙
-
EFveh [mg veh-1 km-1] : average vehicle emission factor
-
Cout [mg m-³] : mass concentration of pollutant at the end of the tunnel
-
Cin [mg m-³] : mass concentration of pollutant at the beginning of the tunnel
-
A [m²] : cross section area of the tunnel
-
U [m s-1] : wind velocity
-
t [s] : sampling duration
-
N [veh] : total traffic during sampling
-
l [km] : distance between entrance and exit of the tunnel
(iii)
Some results of tunnel studies for Pt and Pd emissions in PM10 are summarised by Limbeck and Puls
(2010). The emissions vary around 25-200 ng vehicle-1 km-1 Pt and around 9.7-370 ng vehicle-1 km-1 Pd.
The emissions may seem very low, but taking into account the enormous amount of vehicles on Earth
23
and the distances that are covered with these vehicles, the total emission of PGMs may not be
underestimated. The PGMs emitted to the environment via the exhaust fumes are dispersed over big
areas in very low concentrations, resulting in the loss of elements forever for any future application
(Bardi & Caporali, 2014).
A second reason for the low recycling rates of platinum from automotive catalytic converters is the
collection problem. To obtain efficient recycling, efficient collection of the end-of-life products is
essential. Nowadays, there are not a lot of recycling facilities for the automotive catalytic converters,
so cars that end up in areas without such recycling facilities are not recycled (Bardi & Caporali, 2014).
To conclude the option of recycling, Bardi and Caporali (2014) state that recycling alone is not enough
to deal with the scarcity problem.
Apart from the two main options mentioned above, there are several alternatives to possibly solve
the PGMs scarcity problem (Bardi & Caporali, 2014).

The use of alternative fuels (H2 and NH3 ) in combustion engines. Particulates, unburnt HC and
CO will not be present in the exhaust fumes. Possibly NOx can be present but this can be solved
by using catalysts in which no PGMs are present (Bardi & Caporali, 2014). There is the
possibility to install hydrogen fuels cells in vehicles. Sadly enough, the fuel cells require PGMs
for the electrodes (Bardi & Caporali, 2014). In 2005, the catalyst specific power of a fuel cell
was approximately 0.9 kW g-1 PGMs. Thanks to new developments during the last decade this
value is improved to about 6.3 kW g-1 PGMs in 2014 (U.S. Department of Energy, 2015). The
average power of a fuel cell powered car is approximately 60 kW, requiring about 9.5 g PGMs
(von Helmolt & Eberle, 2007). This is significantly more than for exhaust catalysts. Changing
all vehicles on the world to electric vehicles is impossible with the platinum reserves that are
available nowadays (Bardi & Caporali, 2014; Bossel, 2006). Another main problem with shifting
to alternative fuels is the need of totally different pumping stations and transportation for
these alternative fuels (Bardi & Caporali, 2014).

The use of electric motors would be a more drastic approach to deal with the depletion
problem. The electric motors have multiple advantages. First of all, they emit no harmful
substances. Furthermore, they are lighter and they have a higher efficiency and durability.
Nowadays, there are electric vehicles on the market, but the main drawback of these vehicles
is the rather bad performance of the Pb-based batteries. The energy per unit mass that can be
stored is limited, resulting in a limited driving range (Bardi & Caporali, 2014).

The use of Li-based batteries in electric vehicles seems promising because of the lighter
weight of the batteries and the very high recycling rates of these batteries. The known Lireserves are higher than for the PGMs (Bardi & Caporali, 2014). Assuming a constant global
demand of 626 t PGMs (Chapter 3.4) and total resource of 90,700 t PGMs worldwide (Chapter
24
3.2), the PGMs reserves can be estimated around 145 years (Mudd, 2012). For a constant
lithium demand, the reserves are estimated around 350 years (Bardi & Caporali, 2014; U.S.
Geological Survey, 2012).
3.6. Environmental problems related to the dispersion of PGMs
3.6.1. Sources of PGMs dispersion
As mentioned earlier in chapter 3.5, the PGMs end up in the environment due to catalyst deterioration
and mechanical surface abrasion (Pawlak et al., 2014). Particles of micrometer and submicrometer
size from the catalyst washcoat, which hold the PGMs, are emitted through the exhaust (Puls et al.,
2010). Although the catalytic converters decreased the impact of the harmful exhaust gasses on the
environment drastically, they now contribute to another environmental problem, the emission of
PGMs into the environment (Pawlak et al., 2014). The main source of PGMs emissions is the
automotive catalytic converter, other minor sources are jewellery and dissipation of anticancer drugs.
Over the last decades, the accumulation of PGMs in different compartments of the environment (road
dust, soils, rivers, airborne particulate matter, vegetation, etc.) has increased (Ravindra et al., 2004).
In general, the PGMs are emitted through the exhaust pipe in their metallic form and, less commonly,
as an oxide (Pawlak et al., 2014). The metallic form is considered as inert and immobile (Pawlak et al.,
2014; Ravindra et al., 2004). However, when the metals end up in the environment, they can become
mobile and bioavailable. This leads to bioaccumulation in living organisms and subsequently the entry
inside the food chain. Up until now, little is known about the effects of chronic exposure to low
concentrations of PGMs on the human health (Pawlak et al., 2014; Ravindra et al., 2004). In the
following parts, the mobilisation of PGMs in the various environmental compartments is explained
together with a few concentration data. More platinum content data for soils and road dust samples
will be given in chapter 5.4, in which the results of this research will be compared with other similar
studies. Furthermore, the studied effects on living organisms are discussed.
3.6.2. Soils and road dust
Multiple studies have shown elevated PGM contents in soils in the vicinity of roads (Pawlak et al.,
2014; Ravindra et al., 2004). Average contents from research give platinum contents of 0.14 µg kg-1,
1.12 µg kg-1 and 20.9 µg kg-1 in respectively intact soils, agricultural soils and soils next to roads (Alt et
al., 1997; Pawlak et al., 2014; Zereini et al., 1997). The contents are dependent on several factors like
the weather conditions, traffic, distance to the road, sampling depth, etc. Generally, the further from
the road, the lower the content of Pt, Pd and Rh. Another trend that has been observed is with
increasing sampling depth, the PGM content decreases (Pawlak et al., 2014; Schäfer & Puchelt, 1998).
In chapter 5.4, more attention will be paid to these factors.
25
The conversion in soils of the emitted PGMs into organic or chloro complexes, which are bioavailable
forms, happens due to the presence of some complexing ligands in soils. Organic substances play a
key role in mobilisation and immobilisation processes (Pawlak et al., 2014; Šebek et al., 2011). They
have the ability to mobilise the PGMs by creating soluble complexes. On the other hand, they can
immobilise the PGMs via precipitation, reduction of metal ions and adsorption (Pawlak et al., 2014;
Šebek et al., 2011; Wood, 1996). Humic acid is found to immobilise Pt salts as nearly insoluble organic
complexes (Pawlak et al., 2014). Examples of PGM complexing ligands are (Pawlak et al., 2014; Šebek
et al., 2011):

Fulvic acid: product of the natural microbial degradation processes of lignin and cellulose

Phosphates (PO43-): naturally present and present due to application of fertilizers

Citrates (C3H5O(COO)33-): plant roots secretion

Sodium chloride (NaCl): application of salt to prevent icy roads
Apart from the complexing ligands in soils, mechanisms such as bacterial biochemical reactions and
chemical oxidation reactions can lead to the transformation of PGMs into bioavailable forms. Other
important factors that affect the mobilisation of PGMs are the redox potential, pH and salinity of the
soil (Pawlak et al., 2014).
Even higher contents than in soils are reported for road dust samples. The PGMs can directly
accumulate on the roads where they are deposited. Some examples of road dust PGM contents in
urban areas are 31-2,252 µg kg-1 Pt, 39-191 µg kg-1 Pd and 11-182 µg kg-1 Rh in Madrid, Spain (B. Gómez
et al., 2001; Ravindra et al., 2004) and 101.3 µg kg-1 Pt, 21.3 µg kg-1 Pd and 18.7 µg kg-1 Rh in Karlsruhe,
Germany (Ravindra et al., 2004; Sures et al., 2001).
3.6.3. Aquatic ecosystems
Aquatic ecosystems consist of rivers, oceans, groundwater, rainwater, river sediments, drinking
water, etc. The last decades, increased PGM concentrations in these environmental compartments
have been reported. Mainly, the PGMs end up in the aquatic ecosystems via run-off from roads and
via direct emissions into surface waters in the vicinity of roads (Pawlak et al., 2014). The highest total
PGM content in surface water sediments next to roads is reported around 50 µg kg -1, normally the
total PGM content in river sediments ranges from 0.4 to 10.8 µg kg-1 (Pawlak et al., 2014; Ravindra et
al., 2004). Reported concentrations for river water are 0.4 ng L-1 Pd and 0.22-0.64 ng L-1 Pt (Ravindra et
al., 2004). Although the PGMs are present in very low concentrations, they can have considerable
effects on the aquatic animals because of the ability to bioaccumulate (Pawlak et al., 2014).
26
3.6.4. Air
Initially, the PGMs are emitted into the air via the exhaust fumes. The particles are transferred from
the air to other matrices by deposition, either wet or dry. The deposition due to gravitational force is
referred as dry deposition. Wet deposition is caused by rainfall. The finest particles, which are able to
reside longer in the atmosphere, can be deposited hundreds of kilometers further (Pawlak et al., 2014).
Airborne PGM contents reported for PM10 are 0.9-19 pg m-3 Pt, 0.3-4 pg m-3 Rh and 0.1-10 pg m-3 Pd in
Göteborg, Sweden (Rauch et al., 2001; Ravindra et al., 2004), 15-19 pg m-3 Pt, 9.1-27 pg m-3 Rh and 5.132 pg m-3 Pd in Madrid, Spain (Gómez et al., 2003; Ravindra et al., 2004) and 4.3 pg m-3 Pt, 0.4 pg m-3 Rh
and 2.6 pg m-3 Pd in Vienna, Austria (Ravindra et al., 2004).
3.6.5. The effects on living organisms
3.6.5.1. Plants
Plants are primary producers and therefore occur at the beginning of the food chain. The absorption
by plants of PGMs from soils is considered as a danger for the human health. The roots of the plant
are the most important vegetative parts in the PGM accumulation, followed by the stem and the
leaves. Mainly palladium is absorbed and accumulated in plants since it is the most mobile and
bioavailable metal of Pt, Pd and Rh (Pawlak et al., 2014). When comparing the metals in terms of
mobility and uptake by plants, the following order is generally accepted: Pd > Pt > Rh (Puls et al., 2010).
The uptake of PGMs differs largely between the various plant species, in general, dicotyledonous
plants have the ability to take up and accumulate more PGMs than monocotyledonous plants (Pawlak
et al., 2014). Table 4 gives an overview of PGM contents in some plant species.
Table 4. PGM contents in various plant species (Pawlak et al., 2014)
Pt
Content (ng g-1)
Pd
Rh
8.98
12.0
0.10
0.31
1.1
2.1
1.3
0.03
5.4-30
3.6-10.1
30.0
4.6-5.8
3.20
2.0
0.83-1.5
0.45-2.1
2.4
0.1
0.68
2.0
2.0-7.0
1.1-3.4
5.4
2.1-2.2
Type of plant material
Grass
Pine, birch
Tomato (without skin)
Carrot
Cabbage
Lettuce
Celery
Onion (without skin)
Dandelion
Greater plantain
Lichen
Rye grass
From Table 4, it can be concluded that the highest contents are reported for platinum although
palladium has the highest bioavailability. This can be explained by the possible higher platinum
contents present in the soils on which the plants grow.
27
3.6.5.2. Animals
Table 5 gives an overview of PGM contents in animal tissues. Aquatic and terrestrial organisms are
able to bioaccumulate the PGMs. The contents are very low but when the bioaccumulation increases
in the lower food chain levels, higher level organisms can be endangered (Pawlak et al., 2014).
Table 5. PGM contents in various animal tissues (Pawlak et al., 2014)
Type of animal
material
Shellfish tissue
Mussel tissue
Eel liver
Fish tissue
Feathers
Blood
Eggs
Feces
Liver
Kidneys
Content (ng g-1)
Binomial name
Asellus aquaticus
Dreissena polymorpha
Anguilla anguilla
Barbus barbus
Falco peregrinus
Falco peregrinus
Falco peregrinus
Falco peregrinus
Falco peregrinus
Falco peregrinus
Pt
Pd
Rh
0.04-12.4
0.1-0.5
0.1-0.4
0.5
2.7
0.4
0.2
0.2
0.2
1.0
0.18
0.3-7.0
1.4
0.8
0.5
0.7
0.3
0.1-2.0
0.3
0.6
0.3
0.3
0.3
The mobility and chemical form in which the PGMs appear, are important factors for the toxicity. Up
until now little data are available regarding the toxicity of the elements to animals. Mostly, the
toxicity is investigated under laboratory conditions and not under real-life conditions. To estimate
the risk to the human health of the PGM emissions in the environment, the toxicity has to be well
understood. In general, the most toxic are the most soluble forms (Pawlak et al., 2014). Table 6 lists
different platinum compounds and their toxicity in lab experiments with rats.
Table 6. Toxicity to rats of different platinum compounds (Pawlak et al., 2014)
Platinum compounds
Cisplatin
Sodium tetrachloroplatinate(II)
Hexachloroplatinic(IV) acid
Platinum(IV) chloride
Platinum(IV) chloride
Potassium tetrachloroplatinate(II)
Ammonium hexachloroplatinate(IV)
Platinum(II) chloride
Platinum(II) chloride
Platinum(IV) oxide
Application method
Toxicity LD50 (Pt mg kg-1)
Intraperitoneally
Orally
Intraperitoneally
Intraperitoneally
Orally
Orally
Orally
Intraperitoneally
Orally
Orally
7.4
15-50
15-19
22
136
23-94
88
490
>1400
>6900
The toxicity value reported is the median lethal dose (LD 50), the amount of platinum compound
expressed as mg kg-1 body weight that kills half of the population during the experiment (Pawlak et
al., 2014). The lower the LD50, the more toxic the platinum compound.
28
3.6.5.3. Humans
The exposure routes to humans for PGMs are via food intake, dermal contact and inhalation of
airborne particles (Ek et al., 2004). The inhalation of PM2.5 particles containing PGMs is a considerable
route of exposure, since PM2.5 is the alveolar fraction and enters deeper inside the lungs (Puls et al.,
2010). Dermal contact with platinum salts can cause skin irritation (Ek et al., 2004). A study in Australia
estimated the daily food consumption of platinum and reported an average value of 1.4 µg day-1 Pt
(Vaughan & Florence, 1992). This is a quite high value and there are some doubts about the
correctness of the daily intake (Ek et al., 2004). Several symptoms can be linked with PGMs present in
human bodies: skin diseases, asthma, allergies, loss of hair, miscarriage, etc. (Pawlak et al., 2014).
Although multiple studies report elevated PGM concentrations in various environmental
compartments, it can be considered that, if the PGM emissions stay at the levels of today, there is no
danger to humans. Still, attention must be given to the better understanding of the toxicity and the
bioaccumulation of PGMs in living organisms since higher accumulated concentrations can
potentially be dangerous (Pawlak et al., 2014).
29
4.
Materials and methods
4.1. Chemicals and consumables
Throughout the experiments, all standard solutions were prepared in plastic, sterile, metal free,
centrifugal tubes of 15 or 50 mL (VWR®, USA) with following pipettes: 0.5-5 mL Eppendorf Research®
Plus pipette (Eppendorf, Germany), 100-1000 µL Thermo Scientific Finnpipette® F3 pipette (Thermo
Scientific, Finland) and 10-100 µL Thermo Scientific Finnpipette® F3 pipette (Thermo Scientific,
Finland). A Direct-Q® UV3 Ultrapure water system (Merck Millipore, Germany) provided the purified
water (resistivity at 25°C, 18.2 MΩ cm), needed for the experiments. The acids of pro analysis purity
level, 12 M HCL and 14 M HNO3 (Chem Lab, Belgium) were subjected to an additional purification step
of sub-boiling distillation in a class-10 clean lab. All experiments were carried out using external
calibration. The following calibration standard concentrations 0, 0.5, 1, 2.5 and 5 µg L-1 were applied
for the study of the reactions and for method development. Calibration standard concentrations 0, 1,
2.5, 5 and 10 µg L-1 were used for interference experiments. For the analyses of the samples, calibration
standard concentrations 0, 0.1, 0.5, 1 and 5 µg L-1 were used.
For the study of the reactions and for method development of the PGMs, single element stock
solutions of Ir, Os, Pd, Pt, Rh and Ru (1 g L-1 Instrument Solutions, The Netherlands) were used and
single element stock solutions of Au, Tl and In (1 g L-1 Instrument Solutions, The Netherlands) were
applied as internal standards. In the experiments related to interferences, single element stock
solutions of Cd, Cu, Gd, Hf, Hg, Mo, Pb, Rb, Sm, Sr, Y and Zn (1 g L -1 Instrument Solutions, The
Netherlands) were applied. Standard solutions were prepared by dilution of the stock solutions with
0.24 M HCl.
For the validation of the developed method, a certified reference material (CRM) of road dust
containing PGMs was used, named BCR®-723 (road dust). In Appendix, Table A. 1 gives an overview of
some elemental mass fractions. During the analyses of the certified reference material and the reallife road dust and soil samples, standard solutions for the external calibration were prepared by the
use of a slightly acid mixture solution of 0.24 M HCl and 0.14 M HNO3.
31
4.2. Instruments
4.2.1. Tandem ICP-mass spectrometry
Before going more in detail on tandem ICP-mass spectrometry, the basic principles of inductively
coupled plasma and mass spectrometry will be explained. The principle of ICP-MS is based on the
generation of positively charged ions, subsequently the transportation of these ions through the
different parts of the instrument and finally the detection. In order to generate the ions, an ion source
is needed which contains enough energy to ionise the atoms. Ionisation is the process of generating
an ion by eliminating an electron from its orbital by using a high energy source (Thomas, 2001c). A
plasma is very energetic and is mainly used as an ion source. There, positively charged ions, neutral
species and electrons occur simultaneously in a small bounded space. The plasma is generated by a
plasma source and the most common plasma source is inductively coupled plasma, furthermore
others exist such as direct current plasma (DCP), glow discharge (GD) and microwave-induced plasma
(MID) (Du Laing, 2012). The inductively coupled plasma is formed in a plasma torch. Figure 12 shows
a plasma torch with a radio frequency (RF) copper coil. The three concentric tubes, commonly made
of quartz, form the plasma torch. The outer and middle tube have a tangential gas inlet. Between the
outer and the middle tube, a plasma gas (~12-17 L min-1 Ar) is flowing. Between the middle and the
inner tube, an auxiliary gas (~1 L min-1 Ar) is flowing which can be used to slightly alter the position
of the plasma. In the inner sample injector tube, the nebuliser gas (~1 L min-1 Ar), carrying the sample
aerosol, is flowing (Thomas, 2001d). The fine sample aerosol is formed in the introduction system
which will be explained further in this chapter. The process of initiating the plasma, is done in
multiple steps. The tangential plasma gas starts flowing first, secondly the RF coil is loaded with RF
power, resulting in a strong electromagnetic field. Thirdly, free electrons are generated by a highvoltage spark and in the electromagnetic field, they are accelerated. The electrons collide with the
argon gas and they ionise it. Finally, the fine-droplet aerosol is introduced via the inner tube and the
ICP is produced (Thomas, 2001d).
Figure 12. Schematic representation of a plasma torch and RF coil (Thomas, 2001d)
32
In the ICP, the fine-droplet aerosol undergoes several steps. Firstly, the liquid aerosol undergoes a
drying/desolvation step which converts it into a solid form. Secondly, the solid form is converted into
a gas form by vaporisation. Thirdly, this gas form is atomised and subsequently the atoms are ionised
(Thomas, 2001c, 2001d).
The formation of the fine-droplet aerosol happens in the sample introduction system (Figure 13). This
introduction system consists of three major parts, namely the peristaltic pump, nebuliser and spray
chamber. The peristaltic pump consists of little rollers that turn at the same speed. A flexible plastic
tube is pushed against these turning rollers and is put in the sample solution at one end. In this way
the pump is able to suck up the sample solution at a constant flow rate. The sample solution is pushed
towards the nebuliser (Du Laing, 2012). In the nebuliser, the liquid solution is converted into an
aerosol. Mostly pneumatic concentric nebulisers, made of quartz, are used (Figure 13). A gas flow,
mostly Ar, is introduced via the sidearm and creates a low pressure zone at the tip of the nebuliser.
The liquid solution flows in the capillary tube and breaks up at the end and forms an aerosol because
of the low pressure and the high speed gas flow (Du Laing, 2012; Thomas, 2001a). This aerosol has to
pass the spray chamber before entering the plasma torch. Since large droplets can lower the
temperature of the plasma or even extinguish the plasma. The main function of the spray chamber is
to select the finest aerosol droplets and transport them to the plasma torch. One of the most common
is the double pass spray chamber (Du Laing, 2012; Thomas, 2001a).
Figure 13. Schematic representation of a pneumatic concentric nebuliser (left) and an ICP introduction system
with a plasma torch (Thomas, 2013)
After passing the plasma torch, the ions enter the interface region (Figure 14). In this interface region,
ions are transported effectively from the plasma, under atmospheric pressure (760 Torr), to the mass
separation device, under vacuum conditions (10-6 Torr). This region comprises two metallic cones, the
sampler and skimmer cone. They both have a very small hole in the middle through which the ions
can pass. Typical opening diameters for sampler and skimmers cones are 0.8-1.2 mm and 0.4-0.8 mm
respectively (Thomas, 2001e). The pressure in between the sampler and skimmer cone is
33
approximately 3-4 Torr, this pressure is obtained by the use of a mechanical pump. After the ion beam
passes through the opening of the first cone, expansion occurs. Subsequently, the ion beam, that
passes through the skimmer cone, expands in the zone of the ion optics (10-3-10-4 Torr). Turbo
molecular pumps provide these low pressures (Thomas, 2001e). The ion focusing system is essential
to focus the expanded ion beam before entering the mass separation device. This is realised by
steering the ions electrostatically with various lens components. The ion lens components are not
real lenses like in standard optics, but they consist of little metallic cylinders, plates and barrels under
voltage (Thomas, 2001f). Next to the focusing function of the ion optics, this system is able to remove
photons, neutral species and particulates before entering the mass analyser. This is important
because these species give rise to higher background levels and signal instability. This can be realised
by the positioning of the mass analyser. By slightly putting the mass separation device off-axis, it is
possible to electrostatically steer the ions into the entrance of the mass separation device and remove
all other species from the ion beam (Thomas, 2001f).
Figure 14. Schematic representation of the interface region with sampler and skimmer cones (Thomas, 2001e)
The zone of the mass analyser/mass separation device is kept under high vacuum conditions (10-6
Torr) by another turbo molecular pump. The mass analyser works as a filter, only the ions with a
selected mass-to-charge (m/z) ratio are able to pass and reach the detector. For ICP-MS, one of the
most common mass analysers is the quadrupole mass filter (Figure 15), others such as time-of-flight,
ion-trap and double focusing magnetic sector are also on the market (Du Laing, 2012; Thomas, 2001g).
A quadrupole is made out of two pairs of metallic rods, which are hyperbolic or cylindrical shaped.
All four rods have the same dimensions (diameter and length). In ICP-MS, typical lengths of
quadrupoles are 15-20 cm and the diameter is circa 1 cm (Thomas, 2001g). A direct current is put on
the four rods. Two opposite rods have the same electric potential and the two other rods are under
the opposite electric potential. On top of this direct current, a radio frequency voltage is
superimposed, resulting in an oscillating field (Du Laing, 2012). The speed at which an ion enters the
quadrupole will determine its trajectory. Ions are repelled or attracted by the quadrupole rods and
their trajectory is never a straight line. By proper selecting the radio frequency and direct current,
only the ions with a specific m/z ratio can pass the quadrupole and reach the detector. This can be
seen in Figure 15, the black ion is the analyte ion which passes the quadrupole. All other coloured ions
34
are caught by the rods and neutralised. Subsequently, they are removed by the turbo molecular pump
(Du Laing, 2012; Thomas, 2001g).
Figure 15. Schematic representation of the quadrupole mass filter principles (Thomas, 2001g)
The detector counts the amount of ions coming from the mass analyser by transforming them into
electrical pulses. An integrated system counts these pulses and by using calibration standards, the ion
signal of the sample is compared with the signal of the calibration standards. In this way, the analyte
concentration in the sample can be derived (Thomas, 2001b). One of the most commonly used
detectors in ICP-MS systems, is the discrete dynode electron multiplier (Figure 16). In general, the
detector is placed slightly off-axis to lower the background levels. When the first dynode is hit by an
ion, secondary electrons are set free. These electrons are accelerated and will strike the second
dynode, producing even more electrons which will strike the next dynode and the same happens at
every other dynode. In the end, the electrons are caught by the anode or multiplier collector (Thomas,
2001b).
Figure 16. Schematic representation of a discrete dynode electron multiplier (Thomas, 2001b)
In ICP-MS, interferences in all kind of forms can be problematic for trace analysis. Generally, there
are two groups of interferences, spectral and non-spectral interferences. Spectral interferences
comprise double charged ions, polyatomic and isobaric interferences (Du Laing, 2012). Polyatomic
interferences, also called molecular interferences, can be formed when atomic ions react and combine
to molecular species. Usually, this happens in the plasma with argon, oxygen and nitrogen (present
in the air). Moreover, other elements present in the sample solution such as acids or matrix elements
35
can form different species (e.g., oxides, chlorides, hydrides and hydroxides) in the plasma, which are
all polyatomic interferences (Du Laing, 2012; Thomas, 2002). Isobaric interferences occur due to the
fact that approximately 75% of the periodic table elements have multiple isotopes (Du Laing, 2012).
When elements present in the sample solution have isotopes with masses, equal to the mass of the
analyte, they can cause spectral overlap. Usually, this can be solved by selecting and analysing
another isotope of the analyte without isobaric interferences, if possible (Du Laing, 2012; Thomas,
2002). Under the group of non-spectral interferences, the matrix-induced interferences are
important. The complex matrix of a sample solution can affect and lower the sensitivity. Various
techniques can be used to correct for matrix interferences, such as internal standards, standard
addition, isotope dilution, chromatographic separation, desolvation systems, etc. (Du Laing, 2012).
Tandem ICP-mass spectrometry offers many opportunities to deal with spectral interferences. The
instrument used during this work is the Agilent® 8800 ICP-QQQ from Agilent Technologies Inc. (Figure
17). An autosampler is coupled to the instrument, in order to automatically switch between different
samples. Tandem ICP-mass spectrometers contain multiple quadrupoles in series. In the Agilent 8800
ICP-QQQ, there are two quadrupole mass filters and in between them, there is a collision/reaction
cell. This cell is not a quadrupole but an octopole and is called the octopole reaction system (ORS).
Collision-reaction gases can be applied to pressurise the ORS (Agilent Technologies Inc., 2015).
Throughout this work, the highly reactive mixture methyl fluoride/helium (10 % CH3F/90 % He) was
evaluated. By using the instrument in MS/MS mode, the first quadrupole mass filter (Q1) is selected
at a specific m/z ratio, for which only those ions with the same m/z ratio can pass Q1 and reach the
ORS. In this way, all other matrix ions with a different m/z ratio are removed. The only ions present
in the ORS, are the target analyte ions and possible interferences with equal m/z ratio. Subsequently,
the analyte ions react with the mixture CH3F/He in the ORS, forming specific reaction product ions.
By selecting the m/z ratio of a reaction product ion of the analyte in the second quadrupole mass
filter (Q2), only this reaction product ion can pass and the interferences from the ORS will be removed
by Q2 (Agilent Technologies Inc., 2015).
Figure 17. Real picture of the Agilent 8800 ICP-QQQ with autosampler (left) and a diagram with internal parts of
the Agilent 8800 ICP-QQQ (right) (Agilent Technologies Inc., 2015)
36
4.2.2. ICP-optical emission spectroscopy
It is possible to couple the inductively coupled plasma to an optical emission spectrometer (OES).
Here, the plasma acts as an emission source instead of an ion source. When introducing the finedroplet aerosol to the plasma torch, ionisation occurs and the plasma emits light at various
wavelengths. The wavelengths are separated from each other by the use of a diffraction grate. The
spectral information from the different wavelengths is quantified by a detector, usually a charge
transfer device (CTD). When this detector is exposed to light, a charge is accumulated (Du Laing, 2012).
In this work, the ICP-OES was only used for the characterisation of the soil and road dust samples. The
determination of following 10 elements was performed: Al, Cd, Co, Cr, Cu, Fe, Mn, Ni, Pb and Zn. The
instrument used, was a Vista MPX™ simultaneous ICP-OES from Varian Inc. The calibration standards
solutions used were multi element solutions (Al, Cd, Co, Cr, Cu, Fe, Mn, Ni, Pb and Zn) in a similar
diluted aqua regia matrix as the digested samples (Table 7). Moreover, the selected wavelengths for
the elements are given in Table 7.
Table 7. Element concentration in calibration standard solutions and selected wavelength for ICP-OES analyses
Element
Al
Cd
Co
Cr
Cu
Fe
Mn
Ni
Pb
Zn
Blank
(mg L-1)
Standard 1
(mg L-1)
Standard 2
(mg L-1)
Standard 3
(mg L-1)
Wavelength
(nm)
0
0
0
0
0
0
0
0
0
0
5
0.25
0.25
0.5
1.25
5
2.5
1.25
1.25
5
10
0.5
0.5
1
2.5
10
5
2.5
2.5
10
20
1
1
2
5
20
10
5
5
20
396.152
226.502
238.892
267.716
327.395
238.204
257.610
231.604
220.353
213.857
4.2.3. Microwave system
The closed microwave digestions were performed in the MARS™ 6 One Touch™ Technology microwave
system (CEM Corporation, USA). The maximum microwave power is 1800 W. The digestions were
performed in Teflon® vessels, which were put in protective sleeves. The vessels were closed and locked
in XP-1500 Plus™ Microwave high-pressure vessels (CEM Corporation, USA) to withstand the pressure
inside the Teflon vessels during the digestions. The temperature and pressure were controlled in one
reference vessel, of the maximum 12 vessels during one run, by the installation of a CEM® RTP-300
Plus™ Direct fiber optic temperature sensor (CEM Corporation, USA) and a CEM® ESP-1500 Plus™
Pressure sensor (CEM Corporation, USA). A safety ring was placed on top of the 12 vessels and the
whole was loaded onto the turntable of the instrument. The rotation inside the microwave system
ensures more effective microwave energy absorption by the vessels and more uniform temperatures
inside the vessels.
37
4.2.4. pH meter
The pH meter is a Orion Star™ A211 with a glass-body pH electrode (Thermo Scientific™, USA). It was
calibrated before the analysis, with buffer solutions of pH 4, 7 and 10 (Bernd Kraft, Germany). Figure
18 shows the pH meter used for analysis.
Figure 18. Picture of the Orion Star A211 with pH electrode
38
4.3. Methods
4.3.1. Sampling procedure for urban samples (Ghent)
4.3.1.1. Locations
In order to apply the developed methods for the determination of PGMs, urban samples are taken in
the city of Ghent, Belgium. In this study, the urban samples are soil and road dust samples. Since
automotive catalytic converters are the main sources of PGM emissions, the location of the urban
samples are chosen in the vicinity of roads. In the city of Ghent, 13 different places were selected for
sampling (Figure 19, Table 8). The selected places include a variety of expressways and motorways.
Sampling place 1 is located at the B401. It’s a shorter motorway connecting the E17/A14 with the
centre of Ghent. Place 2 is located at the traffic roundabout near the University Hospital (UZ
Universitair Ziekenhuis). Due to road works last summer at the E17 exit Ghent-Centre, the E17 exit UZ
Ghent was used much more often and therefore much more cars drove on the traffic roundabout.
Place 3 is situated towards the Watersportbaan at the Deinsesteenweg. Place 4 is chosen near the hospital
Jan Palfijn, namely at the roundabout that connects the Henri Dunantlaan and the Constant Dosscheweg.
Place 5 is located at the Nieuwewandeling, next to Eethuis Volta. Traffic lights are present and they
provide more start/stop traffic. Place 6 is chosen near the park Rabotpark at the N430 Opgeëistelaan.
Place 7 is nearby the building P and the sports hall of HoGent. Place 8 is located at the R40 near De
Bijloke, traffic lights are present, providing more start/stop traffic. Place 9 is situated at the R4
Binnenring-Zwijnaarde and is near the E17/E40. Place 10 is at the N60 Grotesteenweg-Noord. This place is
situated at the Technologiepark-Zwijnaarde. At the R4 Buitenring-Drongen, place 11 is located. Place 12 is
at De Pintelaan near Campus De Sterre. Finally, place 13 is situated near the Citadelpark in the Charles De
Kerchovelaan.
39
Figure 19. Map of Ghent with the 13 selected sample locations (Google Inc., 2015)
Table 8. Overview of the 13 selected sample locations
Location
number
1
2
3
4
5
6
7
8
9
10
11
12
13
Location description
B401 next to the Zuidparklaan and Gustaaf Callierlaan
UZ roundabout with the Corneel Heymanslaan
Deinsesteenweg near the end of the Watersportbaan
Roundabout Henri Dunantlaan and Constant Dosscheweg (near hospital Jan Palfijn)
Nieuwewandeling (Eethuis Volta)
N430 Opgeëistenlaan (Rabotpark)
Valentin Vaerwyckweg (near building P and sports hall HoGent)
R40 near De Bijloke
R4 Binnenring-Zwijnaarde
N60 Grotesteenweg-Noord (near Technologiepark-Zwijnaarde)
Sneppenbrugstraat at R4 Buitenring-Drongen
De Pintelaan near Campus De Sterre
Charles De Kerchovelaan near Citadelpark
4.3.1.2. Procedure
For the sampling it was important to know when the samples should be taken. From the literature, it
is clear that sampling after several days without precipitation is the best option (Tsogas et al., 2008).
In this way, the particles containing PGMs can accumulate on roads when there is no precipitation,
otherwise the rain washes the particles off the road into the sewer system. The purpose was to take
soil and road dust samples next to the roads at the selected sample places in Ghent.
40
4.3.1.2.1.
Soil samples
Soil samples were taken with a shovel over a surface of 20 cm by 10 cm, up to a soil depth of 3 cm. The
samples were stored in plastic bags. Since it seems interesting to take into account the parameter
“distance to the road”, samples were taken at different distances to the road at three specific places
(location 2, 11 and 13). The distance to the road is defined as the distance between the white line of
the lane and the soil sample. The chosen distances are 0.5 m – 1 m – 2 m – 3 m. Supplementary to these
samples, depth samples were taken at three places (location 2, 6 and 11). By taking a depth sample, it
is possible to make a depth profile of the soil for the PGMs. For this, samples were taken with a soil
auger. The depth intervals are [0-3 cm], [3-10 cm], [10-20 cm] and [20-30 cm]. The total amount of soil
samples is 33 at 13 locations.
4.3.1.2.2.
Road dust samples
Road dust samples were taken by rubbing the fine dust of the asphalt in a plastic jar with a brush. The
samples were taken as close as possible to the white line of the road otherwise the road dust was taken
from the roadside gutter or from the cycle path next to the road. Figure 20 shows the tools used during
the sampling of soils and road dust. In total, 9 road dust samples were collected at 9 locations.
Figure 20. Tools for soil samples (shovel on the top) and road dust samples (brush on the bottom)
4.3.1.3. Parameters urban samples
Table 9 gives an overview of the parameters, noted during the field sampling. The code of the sample
was written in the first column. The first letter indicates the sample type. There are soil samples (S)
and road dust samples (D). Next is a number, which differs if there are samples from the same type
and the same place. To define the city where the sample is taken, a letter is used, for Ghent the letter
(G). Finally, there is another number and this number indicates the sampling location number, see
Figure 19 and Table 8. For example, (S2G4), the sample type is soil (S) with number 2. The sample was
taken in Ghent (G) at place 4, which is located at the roundabout of the Henri Dunantlaan and the
Constant Dosscheweg. The GPS-coordinates of the sampling places were defined with a hand-GPS
(Garmin Etrex 10). The coordinates were noted in the column position. The sample description and
date were noted in the following columns. In the column precipitation, the rainfall data (3 and 7 days
prior to the sampling) were noted, based on data of the website of the Flemish Hydrological
41
Information Center (Flemish Hydrological Information Center, 2015). The parameter maximum speed
can be an important parameter that influences the emission of the PGMs via the exhaust fumes of cars
and is noted in the last column. During sampling next to the roads, safety was important and a fluo
safety vest was used. Some pictures, which were taken during the sampling days, are given in Figure
21.
Figure 21. Pictures of the selected sampling locations: Location 1 (top left), location 10 (top right), location 2
where distance to the road samples were taken (bottom left) and part of the depth profile at location 6
(bottom right)
42
Table 9. Overview of the samples with parameters
Code
Position
Description
Date
Distance to the
Precipitation (mm)
Maximum
road (m)
3 days
7 days
Speed (km h-1)
S1G1
N 51°02.557’
Soil sample
11/02/’15
2
0.10
2.90
50
D1G1
E 003°44.015’
Road dust sample
11/02/’15
0
0.10
2.90
50
S1G2
N 51°01.371’
Distance to the road soil sample
11/02/’15
0.5
0.10
2.90
70
S2G2
E 003°43.910’
Distance to the road soil sample
11/02/’15
1
0.10
2.90
70
S3G2
Distance to the road soil sample
11/02/’15
2
0.10
2.90
70
S4G2
Distance to the road soil sample
11/02/’15
3
0.10
2.90
70
S5G2
Depth profile soil sample (0-3 cm)
07/04/’15
1
0
9.75
70
S6G2
Depth profile soil sample (3-10 cm)
07/04/’15
1
0
9.75
70
S7G2
Depth profile soil sample (10-20 cm)
07/04/’15
1
0
9.75
70
S8G2
Depth profile soil sample (20-30 cm)
07/04/’15
1
0
9.75
70
D1G2
Road dust sample
11/02/’15
0
0.10
2.90
70
S1G3
N 51° 03.217’
Soil sample
11/02/’15
2
0.10
2.90
70
D1G3
E 003°40.566’
Road dust sample
11/02/’15
1
0.10
2.90
70
S1G4
N 51°03.086’
Soil sample
11/02/’15
3
0.10
2.90
30
D1G4
E 003°41.917’
Road dust sample
11/02/’15
0
0.10
2.90
30
S1G5
N 51°03.334’
Soil sample
11/02/’15
2
0.10
2.90
50
E003°42.431’
43
S1G6
N 51°03.583’
Depth profile soil sample (0-3 cm)
11/02/’15
1
0.10
2.90
50
S2G6
E 003°42.727’
Depth profile soil sample (3-10 cm)
11/02/’15
1
0.10
2.90
50
S3G6
Depth profile soil sample (10-20 cm)
11/02/’15
1
0.10
2.90
50
S4G6
Depth profile soil sample (20-30 cm)
11/02/’15
1
0.10
2.90
50
S1G7
N 51°02.144’
Soil sample
11/02/’15
0.5
0.10
2.90
50
D1G7
E 003°42.227
Road dust sample
11/02/’15
0
0.10
2.90
50
S1G8
N 51°02.581’
Soil sample
11/02/’15
1
0.10
2.90
50
Soil sample
11/02/’15
0.5
0.10
2.90
90
Soil sample
11/02/’15
1
0.10
2.90
70
Road dust sample
11/02/’15
0.5
0.10
2.90
70
E 003°43.032
S1G9
N 51°00.859
E 003°43.179’
S1G10
N 51°01.117’
D1G10 E 003°42.578’
S1G11
N 51°02.380’
Depth profile soil sample (0-3 cm)
07/04/’15
1
0
9.75
90
S2G11
E 003°40.855’
Depth profile soil sample (3-10 cm)
07/04/’15
1
0
9.75
90
S3G11
Depth profile soil sample (10-20 cm)
07/04/’15
1
0
9.75
90
S4G11
Depth profile soil sample (20-30 cm)
07/04/’15
1
0
9.75
90
S5G11
Distance to the road soil sample
07/04/’15
0.5
0
9.75
90
S6G11
Distance to the road soil sample
07/04/’15
1
0
9.75
90
S7G11
Distance to the road soil sample
07/04/’15
2
0
9.75
90
S8G11
Distance to the road soil sample
07/04/’15
3
0
9.75
90
D1G11
Road dust sample
07/04/’15
0
0
9.75
90
Soil sample
07/04/’15
0.5
0
9.75
50
Road dust sample
07/04/’15
0
0
9.75
50
S1G12
N 51°01.389’
D1G12 E 003°42.750’
44
S1G13
N 51°02.354’
Distance to the road soil sample
07/04/’15
0.5
0
9.75
50
S2G13
E 003°43.453’
Distance to the road soil sample
07/04/’15
1
0
9.75
50
S3G13
Distance to the road soil sample
07/04/’15
2
0
9.75
50
S4G13
Distance to the road soil sample
07/04/’15
3
0
9.75
50
D1G13
Road dust sample
07/04/’15
0
0
9.75
50
45
46
4.3.2. Soil pH-analysis
A small quantity of the soil samples was dried to the air to perform the soil pH-analyses.
Approximately 10 g of air-dried soil was mixed in a 50 mL Duran® beaker (Schott, Germany) with 25
mL of a 1 M KCl solution, made from KCl-powder (Chem Lab, Belgium) and milli-Q water. The soil
suspensions, in total 33, were stirred and allowed to equilibrate for 10 minutes. The pH-KCl (total or
potential acidity) was measured with the pH-meter. In between different soil suspensions, the pH
electrode was rinsed with milli-Q water and carefully dried with absorbing paper.
4.3.3. Sample preparation methods
4.3.3.1. Oven drying and dry matter determination
In order to analyse the urban samples, some sample preparation steps had to be performed. The first
step was the drying of the soil samples. The soils were put in an aluminum tray or a self-made paper
tray and weighted on a Miras 2 balance (max 15 kg, d = 0.001 kg, Sartorius, Germany). Soil samples
were dried in the oven (Memmert, Germany) at 105 °C for 72 hours. Road dust samples and BCR-723
were not dried since they were completely dry. After oven-drying, the soil samples were weighted on
the balance in order to determine the dry matter (DM) content.
4.3.3.2. Closed microwave digestion
The next step in the sample preparation is the closed microwave digestion. After the oven-drying of
the soils, soil samples were finely crushed in a mortar and sieved over a 1 mm stainless steel sieve.
Road dust samples were sieved over a 0.15 mm stainless steel sieve to remove all little stones present
in the samples. These size-reducing steps for the samples were necessary to improve homogeneity of
the material and the digestion efficiency. Smaller particles have a higher surface area-to-volume
ratio, resulting in more contact surface for the acids to interact with the particles. The reference
material was not sieved and crushed in a mortar since the material is already homogeneous.
Subsequently, about 200 mg of the samples was weighted on a type BP 221 S balance (max 220 g, d =
0.1 mg, Sartorius, Germany) in Teflon vessels. Thereafter, 4 mL HCl and 3 mL HNO 3 was added to the
Teflon vessels. During each microwave digestion run of maximum 12 vessels, one or two blanks were
incorporated. The vessels were placed in an Sonorex™ Super RK103 ultrasonic bath (Bandelin,
Germany) for 10 minutes, in order to remove all air bubbles present in the sample-acid suspensions
which could potentially give rise to little explosions during the microwave digestion. Then, the vessels
were closed and locked and subsequently loaded into the microwave system. The choice of the acids
and the microwave program for the digestion was mainly based on a paper (Kowalska et al., 2014), but
small modifications were made in the microwave program, stated below in Table 10. At the end of the
microwave program, a cooling step of 20 minutes was automatically added to cool the vessels. After
each digestion run, the Teflon vessels were cleaned during a cleaning run in the microwave with 10
mL HNO3.
47
Table 10. Closed microwave digestion program for soil and road dust samples using 4 mL HCl and 3 mL HNO 3
Step 1
Step 2
Step 3
Temperature
(°C)
Ramping time
(min)
Hold time
(min)
Power
(W)
Max. pressure
(psi)
20-90
90-170
170-200
10
15
10
5
10
50
600
800
1000
300
300
300
4.3.3.3. Hot plate evaporation and centrifugation
The following step in the sample preparation is a hot plate evaporation step. There are two main
reasons why an evaporation step is included in the sample preparation. Firstly, to analyse the digested
samples, the acid concentration should not be too high. By evaporating the samples until
approximately 1 mL, a large volume of concentrated acids is removed from the samples. Secondly, the
easiest option would be to just dilute the digested samples until an acceptable acid concentration
level. This option is practically not possible because the PGMs are present in very low concentrations
and dilution steps should be avoided as much as possible because every dilution step lowers the PGMs
concentration in the samples, resulting in concentrations closer or below the limits of detection.
So after the digestion, the content of the Teflon vessels was transferred to 100 mL Duran beakers
(Schott, Germany) and the vessels were rinsed with a few mL of a 0.24 M HCl solution so that no
solution remains in the vessels. Thereafter, the beakers were placed on a hot plate at 150 °C until
approximately 1 mL solution was left. Then, 4 mL of a 0.24 M HCl solution was added to each beaker
to rinse the beaker walls. The content of the beakers was transferred via small funnels to 10 mL
Blaubrand® volumetric flasks (Brand®, Germany). Subsequently, the beakers were rinsed two times
with 1-2 mL of a 0.24 M HCl solution. The flasks were added up to the 10 mL calibration mark with a
0.24 M HCl solution. The borosilicate beakers, volumetric flasks and funnels were cleaned before use
with 10 mL 1.4 M HNO3 and milli-Q water.
Since the digested solutions still contained solid particles, the content of the volumetric flasks was
transferred to 15 mL centrifugal tubes. In order to prepare the solutions for ICP-OES and tandem ICPMS analyses, the sample tubes were centrifuged in an Eppendorf™ 5702 centrifuge (Eppendorf,
Germany) at 4300 rounds per minute (rpm) for 10 minutes. Finally, 2 mL clear solution of the
centrifuged sample tubes was transferred to 15 mL centrifugal tubes. For the ICP-OES analyses, 8 mL
of milli-Q water was added, resulting in a total volume of 10 mL. For the tandem ICP-MS analyses, 7.9
mL of milli-Q water was added together with 100 µL of a 500 µg L-1 internal standard Au solution (in a
slightly acid mixture of 0.24 M HCl/0.14 M HNO3), resulting in a total volume of 10 mL and final
internal standard concentration of 5 µg L-1.
48
5.
Results and discussion
5.1. Systematic study of the reactions between CH3F and the PGMs
via tandem ICP-mass spectrometry
5.1.1. Introduction
Tandem ICP-MS can be used as an universal tool for the systematic study of the reactions taking place
in the reaction cell. In this work, the reactions between the platinum group metals and methyl
fluoride (10 % CH3F/90 % He) were evaluated for the elemental determination of ultra-trace
concentrations of PGMs. The possible reactions between a target analyte (M+) and CH3F are (20)
molecular addition, (21) F atom transfer, (22) HF elimination, (23) dehydrogenation and (24) hydride
transfer, mentioned below (Zhao et al., 2006):
𝑀+ + 𝐶𝐻3 𝐹 → 𝑀+ 𝐶𝐻3 𝐹
(20)
→ 𝑀𝐹 + + 𝐶𝐻3
(21)
→ 𝑀𝐶𝐻2+ + 𝐻𝐹
(22)
→ 𝑀𝐶𝐻𝐹 + + 𝐻2
(23)
→ 𝐶𝐻2 𝐹 + + 𝑀𝐻
(24)
Moreover, Zhao et al. (2006) demonstrates the primary reaction product ions of the PGMs with CH3F
and the corresponding reaction rate coefficients (Table 11). From the table, it is clear that the reaction
rate coefficients of palladium, rhodium and ruthenium (molecular addition) are lower than the ones
for platinum, iridium and osmium (dehydrogenation). The first objective of this work is evaluating
whether the expected reactions from previous works, using inductively coupled plasma-selected ion
flow tube mass spectrometry (ICP-SIFT-MS), can be extrapolated to the complex chemistry produced
in the reaction cells, via the use of the improved capabilities offered by tandem ICP-MS.
Table 11. Primary reaction product ions and corresponding reaction rate coefficients (T = 295 ± 2 K) for PGMs
with CH3F (Zhao et al., 2006)
M+
Reaction rate coefficient
(cm³ molecule-1 s-1)
Primary product
Pt+
Pd+
Rh+
Ir+
Os+
Ru+
1.4 × 10-9
5.1 × 10-12
2.7 × 10-12
6.6 × 10-10
1.8 × 10-10
3.2 × 10-12
PtCHF+
PdCH3F+
RhCH3F+
IrCHF+
OsCHF+
RuCH3F+
49
For that purpose, different steps were performed for each metal, starting with the selection of the
most relevant isotopes. Secondly, product ion scans were performed for all metals separately, in order
to study the reaction products. Thirdly, ramp cell gas tests were performed to investigate which
reaction gas flow rate gives the highest intensities for the selected reaction product ions of each
element. Finally, the instrumental parameters were optimised via the instrument software and the
instrumental limits of detection (LODs) and limits of quantification (LOQs) were calculated from the
corresponding calibration curves.
Thereafter, interference experiments were performed, in order to investigate whether the developed
methods are free of spectral interferences. These experiments were carried out only for platinum,
palladium and rhodium, since these are the most abundant PGMs used in automotive catalytic
converters. Possible polyatomic and isobaric interfering elements were found in literature (May &
Wiedmeyer, 1998; Sugiyama, 2015). The validation of the method was done by using the certified
reference material BCR-723. Finally, the interference-free method developed for Pt was used for the
determination of this analyte in urban samples.
5.1.2. Selection of the isotopes
The selected isotopes for this work are stated in Table 12. Multiple isotopes were selected for all metals
except for rhodium, since rhodium is mono-isotopic.
Table 12. The selected isotopes of the PGMs with their corresponding relative abundances
Platinum isotopes
194
Relative abundance
(%)
Pt
195
Pt
196
Pt
32.97
33.83
25.24
Rhodium isotopes
Relative abundance
(%)
103
Rh
100.00
Palladium isotopes
105
Pd
Pd
108
Pd
22.33
27.33
26.46
Iridium isotopes
Relative abundance
(%)
106
191
193
Osmium isotopes
188
Os
Os
190
Os
192
Os
189
50
Relative abundance
(%)
13.24
16.15
26.26
40.78
Relative abundance
(%)
Ir
Ir
Ruthenium isotopes
99
Ru
Ru
101
Ru
102
Ru
104
Ru
100
37.3
62.7
Relative abundance
(%)
12.76
12.60
17.06
31.55
18.62
5.1.3. Product ion scans
5.1.3.1. Introduction
After the isotopes of interest were chosen, the possible reactions of the PGMs with the reaction gas
mixture CH3F/He had to be determined. All the metals were studied separately by preparing single
element standard solutions of 5 µg L-1 Pt, Pd, Rh, Ir, Os and Ru. The six product ion scans (PIS) were
performed with the Agilent 8800 in MS/MS mode. The first quadrupole was selected at m/z ratio 195,
105, 103, 193, 192 and 102 for Pt, Pd, Rh, Ir, Os and Ru, respectively. The second quadrupole was
selected in the range of m/z ratio 2-260. Although a complete range of gas flow rates was evaluated
(0-1 mL min-1), only the product ion scans obtained for 1 mL min-1 are indicated below.
5.1.3.2. Platinum
The PIS of 195Pt is displayed for the range of m/z ratio 190-260 in Figure 22. It is clear that the highest
intensity can be seen at m/z ratio 227, this corresponds to the reaction product ion
195
PtCHF+. The
main reaction for 195Pt+ with reaction gas CH3F/He is the dehydrogenation reaction (25).
𝑃𝑡 + + 𝐶𝐻3 𝐹 + 𝐻𝑒 → 𝑃𝑡𝐶𝐻𝐹 + + 𝐻2 + 𝐻𝑒
1000000
195
Intensity (counts s-1)
195
(25)
+
PtCHF
+
Pt
100000
10000
1000
100
10
1
190
195
200
205
210
215
220
225
230
235
240
245
250
255
260
Mass Q2 (amu)
Figure 22. Selection of the main reaction product ions for Pt monitoring via product ion scanning using CH 3F/He
as a reaction gas in tandem ICP-MS
5.1.3.3. Palladium
The PIS of 105Pd is displayed for the range of m/z ratio 100-180 in Figure 23. The highest intensity at
m/z ratio 139, corresponds to 105PdCH3F+. The second highest intensity at m/z ratio 173 corresponds
to the reaction product ion 105Pd(CH3F)2+. The main reactions for 105Pd+ with reaction gas CH3F/He are
mentioned below in reactions (26) and (27). The reaction (26) corresponds to the methyl fluoride
addition and the reaction (27) corresponds to the double methyl fluoride addition.
𝑃𝑑+ + 𝐶𝐻3 𝐹 + 𝐻𝑒 → 𝑃𝑑𝐶𝐻3 𝐹 + + 𝐻𝑒
(26)
𝑃𝑑+ + 2 𝐶𝐻3 𝐹 + 𝐻𝑒 → 𝑃𝑑(𝐶𝐻3 𝐹)+
2 + 𝐻𝑒
(27)
51
105
Intensity (counts s-1)
1000000
+
Pd
100000
105
+
PdCH3F
10000
105
+
Pd(CH3F)2
1000
100
10
1
100 105 110 115 120 125 130 135 140 145 150 155 160 165 170 175 180
Mass Q2 (amu)
Figure 23. Selection of the main reaction product ions for Pd monitoring via product ion scanning using CH 3F/He
as a reaction gas in tandem ICP-MS
5.1.3.4. Rhodium
Figure 24 shows the PIS of 103Rh for the range of m/z ratio 100-180. The highest intensity at m/z ratio
137, corresponds to
103
RhCH3F+. The second highest intensity at m/z ratio 171 corresponds to
103
Rh(CH3F)2+. The main reactions for
103
Rh+ with reaction gas CH3F/He are mentioned below in
reactions (28) and (29).
Intensity (counts s-1)
1000000
100000
103
𝑅ℎ+ + 𝐶𝐻3 𝐹 + 𝐻𝑒 → 𝑅ℎ𝐶𝐻3 𝐹 + + 𝐻𝑒
(28)
𝑅ℎ+ + 2 𝐶𝐻3 𝐹 + 𝐻𝑒 → 𝑅ℎ(𝐶𝐻3 𝐹)+
2 + 𝐻𝑒
(29)
+
Rh
103
+
RhCH3F
103
+
Rh(CH3F)2
10000
1000
100
10
1
100 105 110 115 120 125 130 135 140 145 150 155 160 165 170 175 180
Mass Q2 (amu)
Figure 24. Selection of the main reaction product ions for Rh monitoring via product ion scanning using CH 3F/He
as a reaction gas in tandem ICP-MS
5.1.3.5. Iridium
Figure 25 displays the PIS of 193Ir for the range of m/z ratio 190-260. The highest intensity can be seen
at m/z ratio 225, this corresponds to the reaction product ion
with reaction gas CH3F/He is mentioned below in reaction (30).
52
193
IrCHF+. The main reaction for 193Ir+
𝐼𝑟 + + 𝐶𝐻3 𝐹 + 𝐻𝑒 → 𝐼𝑟𝐶𝐻𝐹 + + 𝐻2 + 𝐻𝑒
193 +
Intensity (counts s-1)
1000000
193
Ir
(30)
+
IrCHF
100000
10000
1000
100
10
1
190
195
200
205
210
215
220
225
230
235
240
245
250
255
260
Mass Q2 (amu)
Figure 25. Selection of the main reaction product ions for Ir monitoring via product ion scanning using CH3F/He
as a reaction gas in tandem ICP-MS
5.1.3.6. Osmium
Figure 26 displays the PIS of 192Os for the range of m/z ratio 190-260. The highest intensity can be seen
at m/z ratio 224, this corresponds to the reaction product ion 192OsCHF+. The main reaction for 192Os+
with reaction gas CH3F/He is mentioned below in reaction (31).
𝑂𝑠 + + 𝐶𝐻3 𝐹 + 𝐻𝑒 → 𝑂𝑠𝐶𝐻𝐹 + + 𝐻2 + 𝐻𝑒
192
Intensity (counts s-1)
1000000
Os
+
192
(31)
+
OsCHF
100000
10000
1000
100
10
1
190
195
200
205
210
215
220
225
230
235
240
245
250
255
260
Mass Q2 (amu)
Figure 26. Selection of the main reaction product ions for Os monitoring via product ion scanning using CH 3F/He
as a reaction gas in tandem ICP-MS
5.1.3.7. Ruthenium
In the PIS of 102Ru (Figure 27), the two highest intensities can be seen at m/z ratio 136 and 170, these
correspond to reaction product ions 102RuCH3F+ and 102Ru(CH3F)2+, respectively. The main reactions for
102
Ru+ with reaction gas CH3F/He are mentioned below in reactions (32) and (33).
53
102
Intensity (counts s-1)
1000000
𝑅𝑢+ + 𝐶𝐻3 𝐹 + 𝐻𝑒 → 𝑅𝑢𝐶𝐻3 𝐹 + + 𝐻𝑒
(32)
𝑅𝑢+ + 2 𝐶𝐻3 𝐹 + 𝐻𝑒 → 𝑅𝑢(𝐶𝐻3 𝐹)+
2 + 𝐻𝑒
(33)
+
Ru
100000
102
+
RuCH3F
10000
102
+
Ru(CH3F)2
1000
100
10
1
100 105 110 115 120 125 130 135 140 145 150 155 160 165 170 175 180
Mass Q2 (amu)
Figure 27. Selection of the main reaction product ions for Ru monitoring via product ion scanning using CH 3F/He
as a reaction gas in tandem ICP-MS
5.1.3.8. Discussion of the reactions
After comparison of the main reactions of all PGMs, the main reaction with CH3F for Pt, Ir and Os is
the same, a dehydrogenation reaction. This reaction is less likely to occur with Pd, Rh and Ru, since
for these PGMs the methyl fluoride addition reaction is dominant. Thus, it can be concluded that a
similar trend has been observed for the results obtained in this work and those reported in literature
via ICP-SIFT-MS. This further demonstrates the potential of tandem ICP-MS for the study of the
reactions, taking place in the reaction cell, in a very straightforward way.
5.1.4. Ramp cell gas tests
5.1.4.1. Introduction
An important parameter in the method development is the reaction gas flow rate. By measuring the
intensities of the reaction product ions with reaction gas flow rates, varying from 0 to 1 mL min-1, the
optimal reaction gas flow rate can be selected for the highest intensity. The solutions used for the
analyses were diluted from single element standard solutions of 5 µg L-1 Pt, Pd, Rh, Ir, Os and Ru. Table
13 gives an overview of the selected m/z ratios in Q1 and Q2 for the ramp cell gas tests.
54
Table 13. Selected m/z ratio in the first and second quadrupole for ramp cell gas tests in tandem ICP-MS
Element
Q1 (m/z)
Q2 (m/z)
Pt
Pd
Pd
Rh
Rh
Ir
Os
Ru
Ru
195
105
105
103
103
193
192
102
102
227
139
173
137
171
225
224
136
170
5.1.4.2. Platinum, iridium and osmium
In Figure 28, similar graphs for Pt, Ir and Os can be seen. The intensities reach a maximum for a
reaction gas flow rate of 0.8 mL min-1. This flow rate can be used to obtain the best results for the
160000
Intensity 193IrCHF+ (cps)
Intensity 195PtCHF+ (cps)
determination of Pt, Ir and Os.
120000
80000
40000
0
0.00
0.20
0.40
0.60
0.80
Intensity 192OsCHF+ (cps)
CH3F/He flow Rate (mL
250000
200000
150000
100000
50000
1.00
0
0.00
min-1)
0.20
0.40
0.60
0.80
CH3F/He flow Rate (mL
1.00
min-1)
75000
60000
45000
30000
15000
0
0.00
0.20
0.40
0.60
0.80
1.00
CH3F/He flow Rate (mL min-1)
Figure 28. Selection of the optimal CH3F/He flow rate for selected reaction product ions 195PtCHF+, 193IrCHF+ and
192
OsCHF+
5.1.4.3. Palladium, rhodium and ruthenium
The ramp cell gas test results for Pd, Rh and Ru are given in Figure 29, 30 and 31. In contrast to Pt, Ir
and Os, no maximum is reached for the intensities. The reaction gas flow rate is limited to 1 mL min-1
in the instrument, so it is not possible to determine the real optimal reaction gas flow rate. Probably,
55
this instrumental limitation can be overcome by the use of another CH3F/He mixture or with another
flow controller. In this work, the best possible flow rate to determine Pd, Rh and Ru is 1 mL min-1. Next
to this, the remaining parameters of the six analytical methods (Pt, Pd, Rh, Ir, Os and Ru) were
3500
3000
2500
2000
1500
1000
500
0
0.00
0.20
0.40
0.60
CH3F/He flow Rate (mL
0.80
1.00
Intensity 105Pd(CH3F)2+ (cps)
Intensity 105PdCH3F+ (cps)
automatically optimized with the software of the instrument.
3000
2500
2000
1500
1000
500
0
0.00
min-1)
0.20
0.40
0.60
CH3F/He flow Rate (mL
0.80
1.00
min-1)
14000
12000
10000
8000
6000
4000
2000
0
0.00
0.20
0.40
0.60
0.80
CH3F/He flow Rate (mL
1.00
Intensity 103Rh(CH3F)2+ (cps)
Intensity 103RhCH3F+ (cps)
Figure 29. Selection of the better CH3F/He flow rate for the selected species 105PdCH3F+ and 105Pd(CH3F)2+
10000
8000
6000
4000
2000
0
0.00
min-1)
0.20
0.40
0.60
0.80
CH3F/He flow Rate (mL
1.00
min-1)
6000
5000
4000
3000
2000
1000
0
0.00
0.20
0.40
0.60
CH3F/He flow Rate (mL
0.80
min-1)
1.00
Intensity 102Ru(CH3F)2+ (cps)
Intensity 102RuCH3F+ (cps)
Figure 30. Selection of the better CH3F/He flow rate for the selected species 103RhCH3F+ and 103Rh(CH3F)2+
6000
5000
4000
3000
2000
1000
0
0.00
0.20
0.40
0.60
CH3F/He flow Rate (mL
0.80
1.00
min-1)
Figure 31. Selection of the better CH3F/He flow rate for the selected species 102RuCH3F+ and 102Ru(CH3F)2+
56
5.1.5. Calibration curves
Thereafter, single element standard solutions (0, 0.5, 1, 2.5 and 5 µg L-1 Pt, Pd, Rh, Ir, Os and Ru) were
made for the calibration curves with the aim to evaluate the sensitivity, the limits of detection and
quantification and thus, the capability of the developed methods for the determination of ultra-trace
concentrations of PGMs. Figure 32 shows calibration curves for the six PGMs, all other calibration
curves are included in Appendix (Figure A. 1-8). Table 14 gives an overview of all calibration results.
140000
Intensity 105PdCH3F+ (cps)
120000
Intensity 195PtCHF+ (cps)
4000
y = 25845x - 312.41
R² = 0.9999
100000
80000
60000
40000
20000
y = 688.56x - 4.2945
R² = 0.9996
3500
3000
2500
2000
1500
1000
500
0
0
0
1
2
3
4
0
5
1
Concentration (µg L-1)
4
5
250000
y = 2651.3x - 1.6031
R² = 1
12000
Intensity 193IrCHF+ (cps)
Intensity 103RhCH3F+ (cps)
3
Concentration (µg L-1)
14000
10000
8000
6000
4000
2000
y = 44543x - 140.92
R² = 1
200000
150000
100000
50000
0
0
0
1
2
3
4
0
5
1
Concentration (µg L-1)
Intensity 102RuCH3F+ (cps)
6000
y = 13898x + 319.66
R² = 1
70000
60000
2
3
4
5
Concentration (µg L-1)
80000
Intensity 192OsCHF+ (cps)
2
50000
40000
30000
20000
10000
0
y = 1016.7x - 8.3398
R² = 1
5000
4000
3000
2000
1000
0
0
1
2
3
4
Concentration (µg L-1)
5
0
1
2
3
4
5
Concentration (µg L-1)
Figure 32. Calibration curves for 195PtCHF+, 105PdCH3F+, 103RhCH3F+, 193IrCHF+, 192OsCHF+ and 102RuCH3F+
57
Table 14. Overview of calibration data and instrumental limits of detection and limits of quantification for all elements using CH 3F/He in tandem ICP-MS
Isotope
CH3F/He flow rate (mL min-1)
Reaction Product Ion Q1 (amu) Q2 (amu)
Sensitivity (L µg-1)
R²
LOD (µg L-1)
LOQ (µg L-1)
99
Ru
99
Ru
100
Ru
100
Ru
101
Ru
101
Ru
102
Ru
102
Ru
1.00
1.00
1.00
1.00
1.00
1.00
1.00
104
Ru
1.00
104
Ru
1.00
103
Rh
103
Rh
105
105
106
106
108
108
Pd
Pd
Pd
Pd
Pd
Pd
188
189
190
Os
Os
Os
191
Ir
192
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
99
RuCH3F+
99
133
381 ± 5
1.0000
0.005
0.018
+
2
99
167
440 ± 5
0.9998
0.008
0.026
+
100
134
384 ± 9
0.9998
0.011
0.036
+
2
100
168
447 ± 13
0.9998
0.004
0.013
+
101
135
526 ± 7
1.0000
0.003
0.009
+
2
101
169
614 ± 13
0.9999
0.005
0.016
+
102
136
1017 ± 17
1.0000
0.003
0.009
+
2
99
Ru(CH3F)
100
RuCH3F
100
Ru(CH3F)
101
RuCH3F
101
Ru(CH3F)
102
RuCH3F
102
Ru(CH3F)
102
170
1161 ± 17
0.9999
0.002
0.008
RuCH3F+
104
138
805 ± 10
1.0000
0.005
0.017
Ru(CH3F)2+
104
172
730 ± 10
0.9999
0.004
0.014
103
137
2651 ± 30
1.0000
0.0005
0.002
104
104
103
RhCH3F
+
103
Rh(CH3F)
105
105
171
2198 ± 18
1.0000
0.001
0.003
105
139
689 ± 15
0.9996
0.004
0.014
+
2
105
173
680 ± 12
0.9995
0.003
0.011
+
PdCH3F
106
140
836 ± 11
0.9996
0.004
0.013
+
2
106
174
837 ± 11
0.9992
0.003
0.010
+
108
142
953 ± 13
0.9997
0.003
0.010
+
2
Pd(CH3F)
108
108
103
+
Pd(CH3F)
106
106
PdCH3F
+
2
PdCH3F
108
176
849 ± 15
0.9997
0.003
0.011
0.80
188
Pd(CH3F)
+
188
220
4504 ± 26
0.9999
0.005
0.018
0.80
189
+
189
221
5449 ± 28
0.9999
0.005
0.017
0.80
190
+
190
222
8798 ± 68
1.0000
0.005
0.018
0.80
191
+
191
223
25927 ± 172
1.0000
0.0008
0.003
OsCHF
OsCHF
OsCHF
IrCHF
0.80
192
192
224
13898 ± 102
1.0000
0.004
0.013
193
Ir
0.80
193
IrCHF+
193
225
44543 ± 355
1.0000
0.0005
0.002
194
Pt
0.80
194
PtCHF+
194
226
24469 ± 102
0.9999
0.0006
0.002
195
Pt
0.80
195
PtCHF+
195
227
25845 ± 115
0.9999
0.0007
0.002
0.80
196
PtCHF+
196
228
18570 ± 63
0.9999
0.0008
0.003
Os
196
58
1.00
Pt
OsCHF+
5.2. Interference experiments of platinum, palladium and rhodium
5.2.1. Introduction
Platinum, palladium and rhodium are the most relevant PGMs for this work, due to their presence in
the samples of interest. Thus, after the reaction study, the focus throughout further work will be on
these three analytes. In urban samples, these metals are present in very low concentrations together
with various other elements which are present in much higher concentrations. Some of these
elements can cause severe spectral overlap. The purpose of the interference experiments is to identify
possible interferences for Pt, Pd and Rh, and investigate whether the developed methods are able to
obtain interference-free conditions, allowing reliable ultra-trace elemental determination by using
CH3F in tandem ICP-mass spectrometry.
5.2.2. Platinum
The possible interferences for the selected Pt isotopes are listed in Table 15. Calibration standard
solutions of 0, 1, 2.5, 5 and 10 µg L-1 Pt were prepared. Subsequently, 5 µg L-1 Pt standard solutions
were spiked separately with the interfering elements Hf, Sm, Gd and Hg. For each interfering element,
three different concentrations (10, 100 and 1000 µg L-1) were prepared, except for Hg, for which other
concentrations were used (5, 10 and 100 µg L-1). Lower concentrations of Hg were chosen because
when introducing Hg, the instrument lines have to be cleaned much more than for other elements, in
order to avoid memory effects. By using the developed method for the determination of Pt, it is
possible to see whether the interfering elements cause higher signals intensities for the reaction
product ion of Pt or not. After evaluation of three internal standards (Au, Tl and In), 5 µg L-1 Au was
used as internal standard concentration throughout the whole work. The results are displayed in
Figure 33-36. It is clear that none of the possible interfering elements have an influence on the
measured concentration, which means that the developed method is able to remove all possible
interferences in the case of Pt. The final instrumental parameters for selected Pt method are shown
in Appendix (Table A. 2).
Table 15. Possible polyatomic and isobaric interferences for 3 isotopes of Pt
Isotope
Relative isotopic
abundance (%)
Polyatomic interferences
194
32.97
195
33.83
179
196
25.24
180
Pt
Pt
Pt
178
HfO+
154
SmAr+
HfO+
HfO+
Isobaric interferences
154
GdAr+
/
155
GdAr+
156
GdAr+
/
196
Hg+
59
Concentration (µg L-1)
Concentration (µg L-1)
5
4
3
2
1
5
4
3
2
1
0
0
no Hf
10 ppb Hf
100 ppb Hf
no Hf
1 ppm Hf
10 ppb Hf
100 ppb Hf
1 ppm Hf
5
Concentration (µg L-1)
Concentration (µg L-1)
Figure 33. Measured concentrations of 5 µg L-1 Pt solutions with Hf for 194PtCHF+ (left) and 195PtCHF+ (right)
4
3
2
1
0
5
4
3
2
1
0
no Hf
10 ppb Hf
100 ppb Hf
1 ppm Hf
no Sm
10 ppb Sm 100 ppb Sm 1 ppm Sm
5
Concentration (µg L-1)
Concentration (µg L-1)
Figure 34. Measured concentrations of 5 µg L-1 Pt solutions with Hf for 196PtCHF+ (left), Sm for 194PtCHF+ (right)
4
3
2
1
0
5
4
3
2
1
0
no Gd
10 ppb Gd 100 ppb Gd 1 ppm Gd
no Gd
10 ppb Gd 100 ppb Gd 1 ppm Gd
5
Concentration (µg L-1)
Concentration (µg L-1)
Figure 35. Measured concentrations of 5 µg L-1 Pt solutions with Gd for 194PtCHF+ (left) and 195PtCHF+ (right)
4
3
2
1
0
5
4
3
2
1
0
no Gd
10 ppb Gd 100 ppb Gd 1 ppm Gd
no Hg
5 ppb Hg
10 ppb Hg 100 ppb Hg
Figure 36. Measured concentrations of 5 µg L-1 Pt solutions with Gd for 196PtCHF+ (left), Hg for 196PtCHF+ (right)
60
5.2.3. Palladium
The Pd interference experiments are similar to those for Pt. Table 16 gives the possible polyatomic
and isobaric interferences. Cd is an isobaric interference and this can be a serious problem for 106, 108Pd.
Since the Pt method was able to remove all polyatomic interferences, the effect of possible
interferences in the case of Pd also have to be evaluated. The same calibration standard solutions were
prepared for Pd and standard solutions of 5 µg L-1 Pd were spiked separately with interfering elements:
Cu, Mo, Sr, Y and Zn (10, 100 and 1000 µg L-1) or Cd (5, 10 and 100 µg L-1) were prepared. Au was used
as an internal standard at the concentration of 5 µg L-1, as explained above. The experiment results of
Y, Sr and Cd co-presence are shown in Figure 37-41. All other results for Mo, Cu and Zn are given in
Appendix (Figure A. 9-13). It can be concluded that the Pd method is able to remove the polyatomic
interferences arising from co-presence of Mo, Cu and Zn. This is not the case for Y, Sr and Cd, thus the
Pd method is not able to remove all spectral interferences. The polyatomic interferences caused by Y
can be removed for
106
Pd but not for
105
Pd. Higher signal intensities for both reaction product ions
were measured. Moreover, for 105Pd, the polyatomic interferences caused by Sr cannot be removed.
Furthermore, the isobaric interference of Cd cannot be solved by the method, because the CH3F
106
CdCH3F+,
addition reaction with Cd inside the ORS results in the same reaction product ions
106
Cd(CH3F)2+, 108CdCH3F+ and 108Cd(CH3F)2+ as for Pd. These ions are able to pass the second quadrupole
and reach the detector. Additional experiments were performed in order to investigate which
reaction product ions were formed with Sr. Via precursor ion scans and product ion scans the Sr
interference was identified as 86Sr18OH+ (m/z ratio 105). This ion passes the first quadrupole (set at
m/z ratio 105) and reacts with CH3F to form 86SrFCH3F+ (m/z ratio 139). Subsequently, this ion passes
the second quadrupole (set at m/z ratio 139), resulting in higher signal intensities for 105PdCH3F+ (m/z
ratio 139). Moreover, higher signal intensities were measured for
105
Pd(CH3F)2+ (m/z ratio 173),
suggesting the formation of 86SrF(CH3F)2+ (m/z ratio 173).
Table 16. Possible polyatomic and isobaric interferences for 3 isotopes of Pd
Isotope
Relative isotopic
abundance (%)
105
22.33
106
27.33
Pd
Pd
108
Pd
26.46
Polyatomic interferences
YO+ 88SrOH+ 65CuAr+
70
Zn35Cl+ 68Zn37Cl+
89
YOH+ 90ZrO+ 66ZnAr+
Isobaric interferences
89
92
ZrO+ 92MoO+ 68ZnAr+
/
106
Cd+
108
Cd+
61
29.07
5
6
4
2
8
Concentration (µg L-1)
Concentration (µg L-1)
8
0
25.68
3
6
4
2
0
no Y
10 ppb Y
100 ppb Y
1 ppm Y
no Y
10 ppb Y
100 ppb Y
1 ppm Y
5
Concentration (µg L-1)
Concentration (µg L-1)
Figure 37. Measured concentrations of 5 µg L-1 Pd solutions with Y for 105PdCH3F+ (left) and 105Pd(CH3F)2+ (right)
4
3
2
1
0
5
4
3
2
1
0
no Y
10 ppb Y
100 ppb Y
1 ppm Y
no Y
10 ppb Y
100 ppb Y
1 ppm Y
Figure 38. Measured concentrations of 5 µg L-1 Pd solutions with Y for 106PdCH3F+ (left) and 106Pd(CH3F)2+ (right)
Concentration (µg L-1)
Concentration (µg L-1)
7
6
5
4
3
2
1
0
7
6
5
4
3
2
1
0
no Sr
10 ppb Sr
100 ppb Sr
1 ppm Sr
no Sr
10 ppb Sr
100 ppb Sr
1 ppm Sr
Figure 39. Measured concentrations of 5 µg L-1 Pd solutions with Sr for 105PdCH3F+ (left) and 105Pd(CH3F)2+ (right)
8
Concentration (µg L-1)
Concentration (µg L-1)
8
6
4
2
0
6
4
2
0
no Cd
5 ppb Cd
10 ppb Cd 100 ppb Cd
no Cd
5 ppb Cd
10 ppb Cd 100 ppb Cd
Figure 40. Measured concentrations of 5 µg L-1 Pd solutions with Cd for 106PdCH3F+ (left) and 106Pd(CH3F)2+ (right)
62
8
Concentration (µg L-1)
Concentration (µg L-1)
8
6
4
2
0
6
4
2
0
no Cd
5 ppb Cd
10 ppb Cd 100 ppb Cd
no Cd
5 ppb Cd
10 ppb Cd 100 ppb Cd
Figure 41. Measured concentrations of 5 µg L-1 Pd solutions with Cd for 108PdCH3F+ (left) and 108Pd(CH3F)2+ (right)
5.2.4. Rhodium
Furthermore, interference experiments for Rh were performed. The possible polyatomic and isobaric
interferences are listed in Table 17. Similar to the other interference experiments, calibration
standard solutions were prepared and 5 µg L-1 Rh standard solutions were spiked separately with
interfering elements Cu, Pb, Rb, Sr and Zn (10, 100 and 1000 µg L-1), using gold as an internal standard
(5 µg L-1). The results for Sr are shown in Figure 42. All other results for Cu, Pb, Rb and Zn are given in
Appendix (Figure A. 14-17). From the results, it is clear that the Rh method is able to remove the
polyatomic interferences caused by Cu, Pb, Rb and Zn, while it is not able to remove the Sr
interferences as explained below. Since Sr caused interference problems for the Pd method, more
attention was paid to the interpretation of Figure 42. At first sight, there are no obvious differences
in measured concentrations, even in the case of 1000 µg L-1 Sr. Further experiments were carried out
by spiking higher Sr concentrations and apparently for 100 mg L-1 Sr, higher signal intensities were
measured for 103RhCH3F+ and 103Rh(CH3F)2+. This suggests the polyatomic interference of 84Sr18OH+ (m/z
ratio 103) which reacts with CH3F forming 84SrFCH3F+ (m/z ratio 137) and 84SrF(CH3F)2+ (m/z ratio 171).
Consequently, the Rh method is not capable of removing all spectral interferences.
Table 17. Possible polyatomic and isobaric interferences for Rh
Isotope
103
Rh
Relative isotopic
abundance (%)
Polyatomic interferences
87
100.00
68
SrO+ 87RbO+ 63CuAr+
Zn35Cl+ 66Zn37Cl+ 206Pb++
Isobaric interferences
/
63
Concentration (µg L-1)
Concentration (µg L-1)
5
4
3
2
1
0
5
4
3
2
1
0
no Sr
10 ppb Sr
100 ppb Sr
1 ppm Sr
no Sr
10 ppb Sr
100 ppb Sr
1 ppm Sr
Figure 42. Measured concentrations of 5 µg L-1 Rh solutions with Sr for 103RhCH3F+ (left) and 103Rh(CH3F)2+ (right)
5.2.5. Overall discussion
As previously demonstrated, the Pt method is the only method of the three that is able to remove all
spectral interferences. Pd and Rh are affected by some spectral overlap, coming from Sr, Y and Cd.
Unfortunately, in the samples of interest, these elements are present in high concentrations, which
means that both methods are not suitable for the purpose of this work. Although, in less complex
matrices, the methods could be successfully applied. If the Pd and Rh methods want to be used, there
are different options to solve these interferences. For instance, since the polyatomic interferences for
the Pd method (86Sr18OH+ and 89Y16O+) and Rh method (84Sr18OH+) are oxides and hydroxides, the use of
a desolvation unit can be an option. These units are separate introduction systems that reduce the
formation of oxides and hydroxides, which are entering the plasma. Another option is to pressurise
the cell with a different reaction gas (e.g., NH3) and select the better reaction product ions.
Furthermore, the problematic isobaric interference of Cd for
106,108
Pd can possibly be solved via
mathematical corrections. However, these options were not tested during this work, as they were out
of scope for this work. Further focus is on the validation and application of the Pt method.
64
5.3. Method validation with CRM BCR-723 (road dust)
As previously mentioned, the validation of the Pt method was carried out using the certified reference
material BCR-723. Masses varying between 0.2028-0.2270 g were weighed and five digestion replicates
were analysed, aiming to evaluate the capabilities of the developed method. The results, after
correction with Au as an internal standard, are given in Table 18. Statistical two-sample t-tests
(assuming unequal variances) are used to compare the average results of the digestion replicates with
the certified reference value, for each of the selected isotopes. For the 95 % confidence level, there
are no significant differences between the measured results and the certified reference value, since
two-sided p-values range between 0.77 and 0.81. One-way analysis of variance (ANOVA) is used to
investigate the reproducibility of the method, including all sample preparation steps, by comparing
the five replicates of all digestion replicates with each other, for each of the selected isotopes. The
three F-values are lower than the critical F-value (0.31-1.70 < 2.87) at the 95 % level of significance,
resulting in no significant differences between the five digestion replicates. This clearly shows the
reproducibility of the method, including all sample preparation steps. Furthermore, one-way ANOVA
is applied to check if there are significant differences between the three platinum isotopes for all five
replicates of each digestion replicate separately. Since at the 95 % confidence level, all five F-values
are lower that the critical F-value (0.36-3.57 < 3.88), no significant differences are found between
isotopes. This enables the use of isotope dilution for calibration, if necessary.
Figure 43 displays the Pt recovery results with corresponding standard deviation error bars. All
results lie within the acceptable recovery ranges. Once more, this shows the potential of the Pt
method, to accurately and precisely determine the Pt content, even in complex matrices such as the
BCR-723, avoiding the problem of spectral overlap.
Table 18. Platinum contents with corresponding standard deviations (5 replicates) for 5 digestions of CRM
BCR-723, measured as reaction product ions 194PtCHF+, 195PtCHF+ and 196PtCHF+
194
1
2
3
4
5
(Average ± s)b
a
PtCHF+ (µg kg-1 Pt)
81.88 ± 2.06
80.75 ± 2.45
81.57 ± 2.90
82.30 ± 2.00
81.76 ± 1.09
81.65 ± 0.57
(Average ± s)a
195
PtCHF+ (µg kg-1 Pt)
196
PtCHF+ (µg kg-1 Pt)
81.10 ± 0.61
80.96 ± 1.47
80.32 ± 1.53
80.78 ± 2.28
81.27 ± 0.87
80.89 ± 0.36
Certified reference material (µg kg-1 Pt)
81.3 ± 2.5
81.82 ± 1.80
79.98 ± 1.21
81.54 ± 1.99
80.59 ± 0.77
80.07 ± 1.11
80.80 ± 0.84
Average values and standard deviations are calculated based on 5 replicates.
Average values and standard deviations are calculated based on the average values of 5 digestion replicates.
b
65
110
Recovery (%)
100
90
80
1
2
3
Digestion
4
5
Figure 43. Platinum recoveries with corresponding standard deviations (5 replicates) for 5 digestions of CRM
BCR-723, measured as reaction product ions 194PtCHF+ (blue), 195PtCHF+ (red) and 196PtCHF+ (green). The horizontal
dotted lines give the platinum content uncertainty of the CRM BCR-723, converted to recovery values.
5.4. Application to urban samples
5.4.1. Platinum determination in road dust samples
Since the Pt method is validated successfully, it can be applied to determine Pt in urban samples.
Starting with the road dust samples, results are given in Table 19. Considerable amounts of Pt are
present in the samples, in a range of 7.5-134.8 µg kg-1 Pt. One-way ANOVA test is applied to check if
there are significant differences in average Pt content of road dust samples between the different
locations. At the 95 % confidence level, no significant differences are found in average Pt content
between locations, since the p-value is equal to 0.06 (p > 0.05). The two lowest Pt contents are found
in samples D1G3 and D1G10, which are taken further from the road than all other samples. Two
statistical two-sample t-tests (assuming unequal variances) are performed to compare the average
platinum content in samples D1G3 and D1G10 with the average Pt content of all other samples.
Significant differences are found in both cases, at the 95 % confidence level, since the two-sided pvalues are lower than 0.05. In both cases, p-values are 0.03. For the samples D1G1, D1G2 and D1G11,
the variability expressed by standard deviations is quite high. This is due to the heterogeneity of the
sample material. As stated in the chapter 3, Pt is emitted into the environment via small demolished
particles of the catalyst washcoat (Puls et al., 2010). These particles can contain considerable amounts
of Pt and one particle as such can have a large influence in the total sample analysis, resulting in large
differences between three replicates. Table 20 shows the instrumental standard deviations for three
replicates of road dust samples D1G1, D1G2 and D1G11. Since the instrumental standard deviations
are considerably lower, the problem lies not in the Pt method, but in the heterogeneity of these
samples.
66
Table 19. Average Pt contents with corresponding standard deviations (3 replicates) for digested road dust
samples, measured as reaction product ion 195PtCHF+
a
Sample
Pt content
(µg kg-1)
Standard deviation
(µg kg -1)
Distance to the road
(m)
D1G1
D1G2
D1G3
D1G4
D1G7
D1G10
D1G11
D1G12
D1G13
Averagea
29.7
134.8
7.5
18.4
11.1
7.6
18.1
16.8
34.4
30.9
16.1
130.5
0.5
5.7
1.0
0.9
17.5
5.3
10.0
40.0
0
0
1
0
0
0.5
0
0
0
Average Pt content is calculated based on the average platinum contents of 9 road dust samples.
Table 20. Average Pt contents with corresponding instrumental standard deviations (5 replicates) for digested
road dust samples, measured as reaction product ion 195PtCHF+
Sample
Pt content
(µg kg-1)
Standard deviation
(µg kg-1)
D1G1-1
D1G1-2
D1G1-3
D1G2-1
D1G2-2
D1G2-3
D1G11-1
D1G11-2
D1G11-3
25.2
47.6
16.4
8.5
269.1
126.8
7.8
38.3
8.3
0.3
0.6
0.8
0.3
3.7
2.6
0.4
0.7
0.3
5.4.2. Platinum determination in soil samples
After the analyses of the road dust samples, the Pt method is used to analyse the soil samples. The
results of thirteen soil samples at all different locations are given in Table 21. A two-sample t-test
(assuming unequal variances) is performed to see if there is a significant difference in average Pt
content between road dust and soils. A two-sided p-value of 0.18 is obtained, at the 95 % confidence
level, meaning there is no significant difference in average Pt content, between road dust and soils.
Average Pt contents, with corresponding standard deviations, in road dust and soils are 30.9 ± 40.0
and 10.6 ± 15.6 µg kg-1, respectively. The variability expressed by standard deviations seems lower for
the soils, suggesting that Pt is distributed more homogeneously in soils than in road dust. To
investigate if there are significant differences in average Pt content between the different locations,
one-way ANOVA is used. The 95 % confidence level gives no significant differences in average Pt
content between the different locations (p-value 0.15 > 0.05).
67
Table 21. Average Pt contents with corresponding standard deviations (2 replicates) for digested soil samples,
measured as reaction product ion 195PtCHF+
Sample
Pt content (µg kg-1)
Standard deviation (µg kg-1)
Distance to road (m)
S1G1
S1G2
S1G3
S1G4
S1G5
S1G6
S1G7
S1G8
S1G9
S1G10
S1G11
S1G12
S1G13
Averageb
7.8
4.3
12.8
2.9
5.2
57.9
2.3
1.3
10.8
15.8
1.4
4.4
< LODc
10.6
0.8
1.5
3.4
0.7
1.4
1.0a
0.6
0.7
1.3
15.9
0.1
0.3
15.6
2
0.5
2
3
2
1
0.5
1
0.5
1
1
0.5
0.5
a
Standard deviation given, is the instrumental standard deviation since only 1 digestion replicate is analysed.
Average Pt content is calculated based on the average Pt contents of 13 soil samples.
c
LOD = 0.175 µg kg-1 Pt (in case of 0.200 g sample)
b
The Pt contents within the three depth profiles are given in Table 22. The highest content for depth
profile 1 and 3 is found in soil depth interval 3-10 cm, for depth profile 2 in interval 0-3 cm. In general,
the Pt contents in soil depth intervals 10-20 cm and 20-30 cm are very low in comparison with the
overlying layers. Rainfall and leaching can be small contributing factors to the migration of Pt from
the surface layer to the 3-10 cm interval. Additionally, possible explanations for the high Pt content
in interval 3-10 cm (depth profile 1) are, for instance, vegetation changes which alter the distribution
of Pt in the soil, ploughing of the soil which results in an easier Pt migration to deeper soil layers or
substitution of the soil surface layer with fresh uncontaminated soil. Figure 44 gives a graphical
representation of all three depth profiles.
Table 22. Average Pt contents with corresponding standard deviations (1 replicate for depth profile 2, 2
replicates for depth profiles 1 and 3) for digested soil samples of the depth profiles, measured as reaction
product ion 195PtCHF+
Profile Sample
1
2
3
a
S5G2
S6G2
S7G2
S8G2
S1G6
S2G6
S3G6
S4G6
S1G11
S2G11
S3G11
S4G11
Pt content
(µg kg-1)
Standard deviation
(µg kg-1)
Soil depth
(cm)
2.0
84.2
1.0
0.8
57.9
29.1
2.0
1.2
1.4
1.5
< LODb
< LODb
1.8
106.5
0.5
0.02
1.0a
0.6a
1.2a
0.5a
0.1
0.5
-
0-3
3-10
10-20
20-30
0-3
3-10
10-20
20-30
0-3
3-10
10-20
20-30
Standard deviation given, is the instrumental standard deviation since only 1 digestion replicate is analysed.
LOD = 0.175 µg kg-1 Pt (in case of 0.200 g sample)
b
68
Pt content (µg kg-1)
0
10
20
30
40
50
60
70
80
90
0
Soil depth (cm)
-5
-10
Depth
profile 1
-15
Depth
profile 2
-20
Depth
profile 3
-25
-30
Figure 44. Graphical representation of Pt content (x-axis) and soil depth (y-axis) for the depth profile 2 soil
samples, including corresponding standard deviations (except for the high standard deviation of sample S6G2
from depth profile 1)
Pt contents as function of the distance to the road are shown in Table 23. In all three profiles, a
decreasing trend in Pt content can be seen, as the distance to the road increases. For sample S5G11,
sample heterogeneity is observed again, as was the case for some road dust samples. In the first sample
of profile 3 (S1G13), the Pt content cannot be determined, since the Pt concentration in the digested
solution is below the instrumental limit of detection. This is rather unexpected because in the other
profiles, the highest Pt contents are found in the samples closest to the road. At the location where
this first sample is taken, many trees and bushes are planted by the city green services. It is possible
that fresh soil (uncontaminated with Pt) was used during planting recently, resulting in an extremely
low Pt content.
Table 23. Average Pt contents with corresponding standard deviations (1 replicate for distance to the road
profile 1, 2 replicates for distance to the road profiles 2 and 3) for digested soil samples of the distance to the
road samples, measured as reaction product ion 195PtCHF+
Profile Sample
1
2
3
a
S1G2
S2G2
S3G2
S4G2
S5G11
S6G11
S7G11
S8G11
S1G13
S2G13
S3G13
S4G13
Pt content (µg kg-1)
Standard deviation
Distance to the road
(m)
4.3
2.2
3.7
2.0
131.3
0.9
0.1
< LODb
< LODb
21.1
8.5
1.3
1.5
0.8
2.6
0.1
180.4
0.1
0.3
0.4a
0.7a
0.5a
0.5
1
2
3
0.5
1
2
3
0.5
1
2
3
Standard deviation given, is the instrumental standard deviation since only 1 digestion replicate is analysed.
LOD = 0.175 µg kg-1 (in case of 0.200 g sample)
b
69
Thereafter, the results represented in Table 19 and Table 21, are used together with the GPS
coordinates of the locations, to create two maps of Ghent (Figure 45) with the Esri maps software
(Microsoft Office add-in of ArcGIS). The maps contain information on the Pt content in road dust (blue
circles) and in soils (red circles). As stated earlier, there are no significant differences (95 % confidence
level) in average Pt content between road dust and soils, mainly because of the heterogeneity of some
samples.
< 2.5
2.5-8
8.115
15.125
25.150
50.1100
>100
Figure 45. Two maps of Ghent with on the left, the Pt contents, represented as blue circles, of the road dust
samples at 9 different locations. On the right, the Pt contents, represented as red circles, of the soil samples at
12 different locations instead of 13 (Pt content S1G13 < LOD). Circle sizes are in proportion to the Pt contents
and the scale values are indicated as µg kg-1 Pt.
Table 24 gives a comparison of the Pt contents measured in our study, with those reported in other
studies. In Madrid, the capital of Spain with more than 3 million citizens, contents up to 2,252 µg kg-1
are measured in road dust.
Table 24. Overview of Pt contents in road dust and soil samples of other similar studies
Location
Pt content in road dust
(µg kg-1)
Pt content in soils
(µg kg-1)
References
Perth (Australia)
Ioannina (Greece)
Madrid (Spain)
Italy
Bialystok (Poland)
Honolulu (USA)
Germany
Ghent (Belgium)
3.7-91.4
3.2-306.4
31-2,252
26-1177
34.2-110.9
15-160
7.5-134.8
13.9-153.2
2.8-225.1
1.0-11.5
2-160
1.3-261
1.3-57.9
(Whiteley, 2005)
(Tsogas et al., 2008)
(B. Gómez et al., 2001)
(Spaziani et al., 2008)
(Leśniewska et al., 2004)
(Sutherland, 2003)
(Wichmann et al., 2007)
This study
70
5.5. Characterisation of urban samples
In urban samples, also the heavy metals Al, Cd, Co, Cr, Cu, Fe, Mn, Ni, Pb and Zn were determined via
ICP-OES. The main purpose of these analyses was to investigate whether their contents can be
correlated to the Pt contents. Results of the heavy metal contents in road dust and soil samples are
given in Appendix (Table A. 3-4), with Pt contents also being included again in these tables. Average
soil sample heavy metal contents are in Table 25. Pearson correlation coefficients are calculated based
on the data in Table A. 3 and Table A. 4., results are shown in Table 26 and Table 27. There are no
significant correlations between Pt contents and heavy metal contents in road dust or soil samples,
at 95 % and 99 % confidence level, except for the correlation between the Mn and Pt content in road
dust, which is significant at the 95 % confidence level. Other significant correlations between heavy
metals are marked in the tables below. Further characterisation of the soils was carried out by
analysing the pH and dry matter content. Results of these analyses are shown in Appendix (Table A.
5). The range for DM content is 70.2–90.6 % and the range for pH is 3.72-8.81. The low pH values of
samples S1G13, S2G13, S3G13 and S4G13 can be explained because these samples are taken in the
vicinity of a conifer, with samples being located closer to the tree having a lower pH.
Table 25. Average soil samples contents for heavy metals Cd, Cr, Cu, Ni, Pb and Zn
Element
Average sample content (mg kg-1)
Standard deviation (mg kg-1)
Al
Cd
Co
Cr
Cu
Fe
Mn
Ni
Pb
Zn
9,643.2
1.4
1.8
42.5
42.5
12,198.6
245.3
16.4
79.6
140.4
2,015.6
0.7
1.9
56.0
49.3
4,484.2
105.08
27.6
75.8
248.8
Table 26. Pearson correlation coefficients between variables Pt, Al, Cd, Co, Cr, Cu, Fe, Mn, Ni, Pb and Zn
content in road dust samples (N=9)
Pt
Al
Cd
Co
Cr
Cu
Fe
Mn
Ni
Pb
Zn
Pt
Al
Cd
Co
Cr
Cu
Fe
Mn
Ni
Pb
Zn
1 -0.264
-0.465 0.017 0.166 -0.245
-0.312 -0.740* -0.494
-0.279
-0.485
1 0.902** 0.467 0.111
0.056 0.926**
0.259
0.069
0.679*
0.415
1 0.363 0.267
0.222 0.953**
0.419
0.419
0.741*
0.444
1 -0.211
0.055
0.416
-0.260
0.157
0.703*
-0.200
1 0.751*
0.410
0.119
0.503
0.248
0.341
1
0.374
0.278 0.756*
0.361
0.351
1
0.315
0.389
0.753*
0.436
1
0.307
0.351 0.826**
1
0.433
0.162
1
0.412
1
*Correlation is significant at the 0.05 level (two-sided). **Correlation is significant at the 0.01 level (two-sided).
71
Table 27. Pearson correlation coefficients between variables Pt, Al, Cd, Co, Cr, Cu, Fe, Mn, Ni, Pb and Zn
content in soils samples (N=29). Soil samples with Pt content <LOD (S3G11, S4G11, S8G11 and S1G13) are not
included.
Pt
Al
Cd
Co
Cr
Cu
Fe
Mn
Ni
Pb
Zn
1 -0.116
Pt
0.028
0.012
0.295
-0.006
-0.059
0.087
0.262
-0.085
0.010
Al
1 0.593** 0.770**
0.238
0.421* 0.830**
0.224
0.335 0.599** -0.019
Cd
1 0.598**
0.327
0.383* 0.791**
0.354
0.328 0.647**
0.252
Co
1 0.424* 0.641** 0.731** 0.396* 0.556** 0.573**
0.205
1
Cr
0.321
0.382* 0.415* 0.979**
0.206
0.093
1
Cu
0.453*
0.325
0.434* 0.639**
0.223
1
Fe
0.264
0.433* 0.664**
0.140
1
Mn
0.453* 0.513** 0.398*
1
Ni
0.291
0.080
1
0.134
Pb
1
Zn
*Correlation is significant at the 0.05 level (two-sided). **Correlation is significant at the 0.01 level (two-sided).
72
6.
General conclusions
Results obtained when studying the reactions between the PGMs and CH3F occurring in tandem ICPmass spectrometry are in agreement with those reported in literature for ICP-SIFT-MS.
Dehydrogenation is the dominant reaction for Pt, Os and Ir, whereas methyl fluoride addition is
dominant for Pd, Rh and Ru. Herewith, the optimal reaction gas flow rate for Pt, Os and Ir is 0.8 mL
min-1 and because of instrumental limitations, the highest gas flow rate of 1 mL min-1 was considered
most suitable for Pd, Rh and Ru. The interference experiments conducted for Pt demonstrate that the
Pt method is able to remove all spectral interferences. In the case of Pd and Rh, the methods are not
able to remove all spectral interferences (Sr, Y and Cd), therefore they cannot be applied to analyse
the samples of interest with high concentrations of Sr, Y and Cd. However, the developed Pd and Rh
methods can be applied to analyse samples with low concentrations of these interfering elements.
The Pt method validation with the certified reference material BCR-723 proves that the method is
able to accurately and precisely determine the Pt content in road dust. Subsequently, the Pt method
is successfully applied to analyse urban samples collected in Ghent. Considerable amounts of Pt are
found in soil and road dust samples with Pt contents ranging from 1.3 to 57.9 and from 7.5 to 134.8 µg
kg-1, respectively. A decreasing trend in Pt content was observed with increasing distance to the road.
Moreover, the highest Pt contents are observed in the upper 10 cm of soils, since in underlying soil
layers very low Pt contents are measured. Furthermore, analyses of heavy metal contents in soil
samples show no significant correlations between Pt and heavy metals (95 % significance level),
except for Mn.
73
7.
Future research recommendations
A first recommendation is to investigate the polyatomic interference of 89Y16O+ for 105Pd. The reaction
between 105Pd+ and CH3F results in two main reaction product ions i.e. 105PdCH3F+ (m/z ratio 139) and
105
Pd(CH3F)2+ (m/z ratio 173). Both ions are affected by Y species, which can be identified in further
research. Additionally, a desolvation system can be applied to reduce the amount of oxides and
hydroxides formed, since the Pd and Rh methods are not able to remove all spectral interferences. In
this way, possibly the Pd and Rh methods can be applied to determine PGMs even in heavy matrices
such as the samples of interest in this study.
Secondly, the potential of using NH3 as a reaction gas instead of CH3F/He for the determination of
PGMs via tandem ICP-mass spectrometry can be evaluated. Since CH3F reaction rate coefficients of Pd
and Rh are lower than the one for Pt, the use of NH3 can be an alternative for these elements.
Thirdly, more studies can be performed to better understand the migration processes of PGMs in soils,
to what extent the precipitation and presence of vegetation affects the migration and distribution of
these elements.
75
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82
9.
Appendix
Table A. 1. Mass fractions based on dry mass and uncertainties of elements present in CRM BCR-723 (road
dust) (Institute for Reference Materials and Measurements (IRMM), 2011)
Element
Unit
Certified value
Uncertainty
Pt
Pd
Rh
Al
Ba
Cd
Co
Cr
Fe
Hf
Mn
Mo
Ni
Pb
Rb
Sb
Sr
Ti
Th
V
Y
Zn
µg kg-1
µg kg-1
µg kg-1
%
g kg-1
mg kg-1
mg kg-1
mg kg-1
%
mg kg-1
g kg-1
mg kg-1
mg kg-1
mg kg-1
mg kg-1
mg kg-1
mg kg-1
g kg-1
mg kg-1
mg kg-1
mg kg-1
g kg-1
81.3
6.1
12.8
3.75
0.46
2.5
29.8
440
3.29
2.2
1.28
40.0
171
866
75
28.2
254
2.58
4.8
74.9
12.5
1.66
2.5
1.9
1.3
0.22
0.04
0.4
1.6
18
0.20
0.7
0.04
0.6
3
16
5
2.3
19
0.13
0.5
1.9
1.8
0.10
100000
y = 24469x - 268.66
R² = 0.9999
120000
Intensity 196PtCHF+ (counts s-1)
Intensity 194PtCHF+ (counts s-1)
140000
100000
80000
60000
40000
20000
0
y = 18570x - 251.03
R² = 0.9999
80000
60000
40000
20000
0
0
1
2
3
Concentration (µg
4
L-1)
5
0
1
2
3
Concentration (µg
4
5
L-1)
Figure A. 1. Calibration curves obtained for two platinum isotopes as PtCHF +
83
Intensity 105Pd(CH3F)2+ (counts s-1)
4000
y = 679.67x - 11.241
R² = 0.9995
3500
3000
2500
2000
1500
1000
500
0
0
1
2
3
4
5
4500
4000
3500
3000
2500
2000
1500
1000
500
0
y = 835.83x + 4.1699
R² = 0.9996
0
1
2
3
4
5
Intensity 106Pd(CH3F)2+ (counts s-1)
Intensity 106PdCH3F+ (counts s-1)
Concentration (µg L-1)
4500
4000
3500
3000
2500
2000
1500
1000
500
0
y = 837.08x - 6.3921
R² = 0.9992
0
1
6000
y = 953.28x + 9.0866
R² = 0.9997
5000
4000
3000
2000
1000
0
0
1
2
3
4
Concentration (µg L-1)
3
4
5
Concentration (µg L-1)
5
Intensity 108Pd(CH3F)2+ (counts s-1)
Intensity 108PdCH3F+ (counts s-1)
Concentration (µg L-1)
2
4500
4000
3500
3000
2500
2000
1500
1000
500
0
y = 849.41x - 9.8566
R² = 0.9997
0
1
2
3
4
5
Concentration (µg L-1)
Figure A. 2. Calibration curves obtained for three different palladium isotopes as PdCH3F+ and Pd(CH3F)2+
84
Intensity 103Rh(CH3F)2+ (counts s-1)
12000
y = 2197.7x + 10.333
R² = 1
10000
8000
6000
4000
2000
0
0
1
2
3
4
5
Concentration (µg L-1)
Intensity 191IrCHF+ (counts s-1)
Figure A. 3. Calibration curve obtained for mono-isotopic Rh as Rh(CH3F)2+
140000
y = 25927x - 122.17
R² = 1
120000
100000
80000
60000
40000
20000
0
0
1
2
3
4
5
Concentration (µg L-1)
Intensity 188OsCHF+ (counts s-1)
Figure A. 4. Calibration curve obtained for iridium isotope 191 as IrCHF+
25000
y = 4504.4x + 127
R² = 0.9999
20000
15000
10000
5000
0
0
1
2
3
4
5
Concentration (µg L-1)
Figure A. 5. Calibration curves obtained for osmium isotope 188 as OsCHF+
85
Intensity 190OsCHF+ (counts s-1)
Intensity 189OsCHF+ (counts s-1)
30000
y = 5449.3x + 159.58
R² = 0.9999
25000
20000
15000
10000
5000
0
0
1
2
3
4
5
50000
y = 8797.5x + 221.15
R² = 1
40000
30000
20000
10000
0
0
1
Concentration (µg L-1)
2
3
4
5
Concentration (µg L-1)
2000
y = 381.04x - 5.4274
R² = 1
1500
1000
500
0
0
1
2
3
4
5
Intensity 99Ru(CH3F)2+ (counts s-1)
Intensity 99RuCH3F+ (counts s-1)
Figure A. 6. Calibration curves obtained for osmium isotopes 189 and 190 as OsCHF+
2500
y = 440.42x - 11.003
R² = 0.9998
2000
1500
1000
500
0
0
1
2000
y = 384.46x - 7.6903
R² = 0.9998
1500
1000
500
0
0
1
2
3
4
Concentration (µg L-1)
3
4
5
Concentration (µg L-1)
5
Intensity 100Ru(CH3F)2+ (counts s-1)
Intensity 100RuCH3F+ (counts s-1)
Concentration (µg L-1)
2
2500
y = 447.8x - 13.28
R² = 0.9998
2000
1500
1000
500
0
0
1
2
3
4
5
Concentration (µg L-1)
Figure A. 7. Calibration curves obtained for ruthenium isotopes 99 and 100 as RuCH 3F+ and Ru(CH3F)2+
86
Intensity 101Ru(CH3F)2+ (counts s-1)
Intensity 101RuCH3F+ (counts s-1)
3000
y = 525.66x - 3.6476
R² = 1
2500
2000
1500
1000
500
0
0
1
2
3
4
5
3500
y = 613.89x - 11.972
R² = 0.9999
3000
2500
2000
1500
1000
500
0
0
1
Intensity 102Ru(CH3F)2+ (counts s-1)
Concentration (µg L-1)
2
3
4
5
Concentration (µg L-1)
6000
y = 1161x - 31.987
R² = 0.9999
5000
4000
3000
2000
1000
0
0
1
2
3
4
5
5000
y = 805.23x - 11.707
R² = 1
4000
3000
2000
1000
0
0
1
2
3
4
Concentration (µg L-1)
5
Intensity 104Ru(CH3F)2+ (counts s-1)
Intensity 104RuCH3F+ (counts s-1)
Concentration (µg L-1)
4000
y = 730.04x - 18.087
R² = 0.9999
3000
2000
1000
0
0
1
2
3
4
5
Concentration (µg L-1)
Figure A. 8. Calibration curves obtained for ruthenium isotopes 101, 102 and 104 as RuCH 3F+ and Ru(CH3F)2+
87
Concentration (µg L-1)
Concentration (µg L-1)
5
4
3
2
1
0
5
4
3
2
1
0
no Mo
10 ppb Mo 100 ppb Mo 1 ppm Mo
no Mo
10 ppb Mo 100 ppb Mo 1 ppm Mo
5
Concentration (µg L-1)
Concentration (µg L-1)
Figure A. 9. Measured concentrations of 5 µg L-1 Pd solutions with Mo for 108PdCH3F+ (left) and 108Pd(CH3F)2+ (right)
4
3
2
1
0
5
4
3
2
1
0
no Zn
10 ppb Zn 100 ppb Zn
1 ppm Zn
no Zn
10 ppb Zn 100 ppb Zn
1 ppm Zn
5
Concentration (µg L-1)
Concentration (µg L-1)
Figure A. 10. Measured concentrations of 5 µg L-1 Pd solutions with Zn for 105PdCH3F+ (left) and 105Pd(CH3F)2+ (right)
4
3
2
1
0
5
4
3
2
1
0
no Zn
10 ppb Zn 100 ppb Zn
1 ppm Zn
no Zn
10 ppb Zn 100 ppb Zn 1 ppm Zn
Figure A. 11. Measured concentrations of 5 µg L-1 Pd solutions with Zn for 106PdCH3F+ (left) and 106Pd(CH3F)2+ (right)
Concentration (µg L-1)
Concentration (µg L-1)
5
4
3
2
1
0
5
4
3
2
1
0
no Zn
10 ppb Zn 100 ppb Zn 1 ppm Zn
no Zn
10 ppb Zn 100 ppb Zn
1 ppm Zn
Figure A. 12. Measured concentrations of 5 µg L-1 Pd solutions with Zn for 108PdCH3F+ (left) and 108Pd(CH3F)2+ (right)
88
Concentration (µg L-1)
Concentration (µg L-1)
5
4
3
2
1
0
5
4
3
2
1
0
no Cu
10 ppb Cu 100 ppb Cu 1 ppm Cu
no Cu
10 ppb Cu 100 ppb Cu 1 ppm Cu
5
Concentration (µg L-1)
Concentration (µg L-1)
Figure A. 13. Measured concentrations of 5 µg L-1 Pd solutions with Cu for 105PdCH3F+ (left) and 105Pd(CH3F)2+ (right)
4
3
2
1
0
5
4
3
2
1
0
no Rb
10 ppb Rb 100 ppb Rb 1 ppm Rb
no Rb
10 ppb Rb 100 ppb Rb 1 ppm Rb
5
Concentration (µg L-1)
Concentration (µg L-1)
Figure A. 14. Measured concentrations of 5 µg L-1 Rh solutions with Rb for
(right)
4
3
2
1
0
RhCH3F+ (left) and
103
Rh(CH3F)2+
5
4
3
2
1
0
no Cu
10 ppb Cu 100 ppb Cu 1 ppm Cu
no Cu
10 ppb Cu 100 ppb Cu 1 ppm Cu
Figure A. 15. Measured concentrations of 5 µg L-1 Rh solutions with Cu for
(right)
5
Concentration (µg L-1)
Concentration (µg L-1)
103
4
3
2
1
0
103
RhCH3F+ (left) and
103
Rh(CH3F)2+
5
4
3
2
1
0
no Zn
10 ppb Zn 100 ppb Zn 1 ppm Zn
no Zn
10 ppb Zn 100 ppb Zn
Figure A. 16. Measured concentrations of 5 µg L-1 Rh solutions with Zn for
(right)
103
RhCH3F+ (left) and
1 ppm Zn
103
Rh(CH3F)2+
89
Concentration (µg L-1)
Concentration (µg L-1)
5
4
3
2
1
0
5
4
3
2
1
0
no Pb
10 ppb Pb 100 ppb Pb 1 ppm Pb
no Pb
10 ppb Pb 100 ppb Pb 1 ppm Pb
Figure A. 17. Measured concentrations of 5 µg L-1 Rh solutions with Pb for
(right)
103
RhCH3F+ (left) and
103
Rh(CH3F)2+
Table A. 2. Tandem ICP-MS instrumental parameters of the platinum method
Plasma parameters
Parameter
RF power
Carrier gas
Sampling depth
Nebuliser pump
Spray chamber T
Unit
W
L min-1
mm
rps
°C
Cell parameters
Parameter
Unit
CH3F/He gas flow rate
mL min-1
Octopole bias
V
Energy discrimination
V
90
Lens parameters
Value
1550
1.14
5.5
0.1
2
Value
0.8
-4.1
-8.4
Parameter
Q1 entrance
Q1 exit
Cell entrance
Cell exit
Deflect
Plate bias
Unit
V
V
V
V
V
V
Value
3
1
-50
-52
4.6
-60
Table A. 3. Overview of heavy metal contents and Pt content, with corresponding standard deviations, in road dust samples. Average values and standard deviations are
calculated based on 3 replicates.
Sample
Pt content
(µg kg-1)
Al content
(%)
Cd content
(mg kg-1)
Co content
(mg kg-1)
Cr content
(mg kg-1)
Cu content
(mg kg-1)
D1G1
D1G2
D1G3
D1G4
D1G7
D1G10
D1G11
D1G12
D1G13
29.7 ± 16.1
134.8 ± 130.5
7.5 ± 0.5
18.4 ± 5.7
11.1 ± 1.0
7.6 ± 0.9
18.1 ± 17.5
16.8 ± 5.3
34.5 ± 10.0
0.92 ± 0.03
0.70 ± 0.03
0.65 ± 0.03
0.70 ± 0.03
0.92 ± 0.03
0.83 ± 0.06
0.91 ± 0.02
1.40 ± 0.08
0.74 ± 0.01
2.80 ± 0.09
1.36 ± 0.13
1.94 ± 0.21
1.70 ± 0.05
2.16 ± 0.22
2.27 ± 0.33
2.47 ± 0.23
3.71 ± 0.08
2.38 ± 0.19
2.09 ± 0.33
0.85 ± 0.49
0.08 ± 0.12
1.32 ± 0.57
1.21 ± 0.51
0.51 ± 0.64
0.74 ± 0.47
1.37 ± 1.36
0.25 ± 0.26
58.8 ± 2.1
59.5 ± 11.7
47.4 ± 5.6
46.7 ± 9.0
57.4 ± 5.7
53.7 ± 3.8
64.1 ± 3.3
61.0 ± 8.3
87.3 ± 9.2
121.4 ± 4.5
87.6 ± 15.7
84.7 ± 10.7
105.6 ± 13.6
138.8 ± 33.5
104.7 ± 18.4
113.2 ± 10.3
103.0 ± 4.8
160.9 ± 9.1
Sample
Pt content
(µg kg-1)
Fe content
(%)
Mn content
(mg kg-1)
Ni content
(mg kg-1)
Pb content
(mg kg-1)
Zn content
(mg kg-1)
D1G1
D1G2
D1G3
D1G4
D1G7
D1G10
D1G11
D1G12
D1G13
29.7 ± 16.1
134.8 ± 130.5
7.5 ± 0.5
18.4 ± 5.7
11.1 ± 1.0
7.6 ± 0.9
18.1 ± 17.5
16.8 ± 5.3
34.5 ± 10.0
1.60 ± 0.06
1.15 ± 0.02
1.13 ± 0.04
1.18 ± 0.05
1.50 ± 0.04
1.40 ± 0.12
1.47 ± 0.02
2.02 ± 0.08
1.55 ± 0.03
347.2 ± 11.0
246.7 ± 6.6
386.1 ± 17.6
300.9 ± 4.3
405.2 ± 9.0
415.4 ± 34.3
465.0 ± 8.7
366.3 ± 15.2
367.3 ± 13.1
28.9 ± 5.4
11.5 ± 2.1
21.1 ± 10.8
19.5 ± 7.2
22.5 ± 3.7
18.4 ± 2.2
19.5 ± 0.7
20.0 ± 3.8
30.1 ± 6.6
92.8 ± 7.1
47.5 ± 20.4
39.7 ± 1.9
57.1 ± 7.7
67.1 ± 5.7
59.9 ± 7.3
82.4 ± 3.7
81.2 ± 8.8
61.2 ± 4.8
199.9 ± 15.0
173.0 ± 7.6
238.6 ± 9.6
208.2 ± 9.9
301.9 ± 0.6
240.4 ± 23.7
391.0 ± 13.9
295.0 ± 14.8
278.5 ± 9.4
91
Table A. 4. Overview of heavy metal contents and Pt content, with corresponding standard deviations, in soil samples. Average values and standard deviations are
calculated based on 2 replicates.
92
Sample
Pt content
(µg kg-1)
Al content
(%)
Cd content
(mg kg-1)
Co content
(mg kg-1)
Cr content
(mg kg-1)
Cu content
(mg kg-1)
S1G1
S1G2
S2G2
S3G2
S4G2
S5G2
S6G2
S7G2
S8G2
S1G3
S1G4
7.8 ± 0.8
4.28 ± 1.5
2.25 ± 0.8
3.71 ± 2.6
2.05 ± 0.1
2.0 ± 1.8
84.2 ± 106.5
1.0 ± 0.5
0.8 ± 0.02
12.8 ± 3.4
2.9 ± 0.7
1.12 ± 0.04
0.92 ± 0.02
1.00 ± 0.03
0.89 ± 0.01
0.95 ± 0.03
0.77 ± 0.02
0.97 ± 0.08
1.00 ± 0.05
0.86 ± 0.04
0.59 ± 0.08
1.08 ± 0.01
2.50 ± 0.16
1.67 ± 0.30
1.26 ± 0.13
1.26 ± 0.12
1.39 ± 0.05
0.83 ± 0.08
1.29 ± 0.04
1.58 ± 0.03
0.06 ± 0.09
1.81 ± 0.16
1.04 ± 0.14
2.50 ± 0.04
0.76 ± 0.77
0.59 ± 0.56
0.51 ± 0.07
1.14 ± 0.55
0.31 ± 0.05
0.94 ± 0.91
1.23 ± 0.24
0.25 ± 0.26
0.93 ± 0.19
1.28 ± 0.14
31.2 ± 0.6
30.1 ± 3.3
32.1 ± 5.6
25.4 ± 4.9
26.2 ± 1.8
18.4 ± 1.0
27.8 ± 0.6
26.3 ± 0.8
18.3 ± 0.9
36.1 ± 4.3
28.3 ± 0.7
57.4 ± 8.1
21.0 ± 6.0
7.3 ± 3.0
5.9 ± 1.1
9.1 ± 0.6
7.4 ± 0.2
6.1 ± 0.3
14.3 ± 1.5
< LOD
70.5 ± 5.2
15.7 ± 0.2
Sample
Pt content
(µg kg-1)
Fe content
(%)
Mn content
(mg kg-1)
Ni content
(mg kg-1)
Pb content
(mg kg-1)
Zn content
(mg kg-1)
S1G1
S1G2
S2G2
S3G2
S4G2
S5G2
S6G2
S7G2
S8G2
S1G3
S1G4
7.8 ± 0.8
4.28 ± 1.5
2.25 ± 0.8
3.71 ± 2.6
2.05 ± 0.1
2.0 ± 1.8
84.2 ± 106.5
1.0 ± 0.5
0.8 ± 0.02
12.8 ± 3.4
2.9 ± 0.7
1.52 ± 0.26
1.17 ± 0.12
1.30 ± 0.10
1.03 ± 0.04
1.09 ± 0.05
0.77 ± 0.01
1.17 ± 0.02
1.13 ± 0.01
0.70 ± 0.02
1.01 ± 0.01
1.35 ± 0.07
622.2 ± 526.5
305.4 ± 147.0
168.7 ± 8.1
156.6 ± 5.6
165.3 ± 5.1
200.6 ± 5.0
180.8 ± 8.8
187.5 ± 0.5
237.9 ± 6.2
318.7 ± 21.9
362.8 ± 27.3
12.1 ± 3.0
4.2 ± 1.7
5.0 ± 0.9
3.5 ± 1.2
3.2 ± 0.9
1.2 ± 0.4
3.9 ± 0.8
3.0 ± 1.1
5.6 ± 2.1
7.0 ± 1.4
11.3 ± 2.4
336.1 ± 38.6
21.7 ± 4.2
21.9 ± 1.2
12.2 ± 1.2
26.7 ± 5.8
7.0 ± 1.4
17.3 ± 0.3
29.8 ± 4.0
6.7 ± 3.2
67.5 ± 47.7
60.2 ± 2.6
153.1 ± 4.5
172.2 ± 2.4
43.9 ± 3.7
38.4 ± 2.1
54.0 ± 2.3
56.6 ± 1.0
42.0 ± 1.6
58.5 ± 5.4
29.8 ± 2.1
281.4 ± 2.5
93.6 ± 18.5
Table A. 4. (Continued)
a
Sample
Pt content
(µg kg-1)
Al content
(%)
Cd content
(mg kg-1)
Co content
(mg kg-1)
Cr content
(mg kg-1)
Cu content
(mg kg-1)
S1G5
S1G6
S2G6
S3G6
S4G6
S1G7
S1G8
S1G9
S1G10
S1G11
S2G11
5.2 ± 1.4
57.9 ± 1.0a
29.7 ± 0.6a
2.0 ± 1.2a
1.2 ± 0.5a
2.3 ± 0.6
1.3 ± 0.7
10.8 ± 1.3
15.8 ± 16.0
1.4 ± 0.1
1.5 ± 0.5
1.20 ± 0.09
0.94b
1.32b
1.37b
1.08b
1.06 ± 0.09
1.05 ± 0.02
0.94 ± 0.01
0.64 ± 0.01
0.70 ± 0.01
0.71 ± 0.01
2.39 ± 0.08
1.99b
1.80b
1.45b
1.25b
0.90 ± 0.18
1.09 ± 0.29
1.95 ± 0.12
0.73 ± 0.10
0.36 ± 0.08
0.70 ± 0.32
5.43 ± 0.12
3.23b
6.48b
7.17b
3.33b
1.89 ± 0.41
1.51 ± 0.21
3.39 ± 0.36
0.64 ± 0.04
0.88 ± 1.01
< LOD
33.9 ± 0.3
297.5b
207.0b
32.8b
24.2b
27.4 ± 2.4
29.0 ± 1.0
40.4 ± 3.1
27.6 ± 0.9
19.2 ± 2.7
18.5 ± 1.3
42.0 ± 7.1
98.0b
98.5b
153.4b
49.4b
20.1 ± 1.5
23.5 ± 0.1
81.3 ± 2.5
48.1 ± 0.5
20.9 ± 4.1
20.7 ± 2.6
Sample
Pt content
(µg kg-1)
Fe content
(%)
Mn content
(mg kg-1)
Ni content
(mg kg-1)
Pb content
(mg kg-1)
Zn content
(mg kg-1)
S1G5
S1G6
S2G6
S3G6
S4G6
S1G7
S1G8
S1G9
S1G10
S1G11
S2G11
5.2 ± 1.4
57.9 ± 1.0a
29.7 ± 0.6a
2.0 ± 1.2a
1.2 ± 0.5a
2.3 ± 0.6
1.3 ± 0.7
10.8 ± 1.3
15.8 ± 16.0
1.4 ± 0.1
1.5 ± 0.5
1.26 ± 0.01
1.66b
1.67b
1.93b
1.67b
1.12 ± 0.05
1.33 ± 0.05
1.43 ± 0.09
0.85 ± 0.02
0.67 ± 0.01
0.70 ± 0.01
246.1 ± 4.9
431.5b
391.9b
339.7b
225.1b
253.9 ± 7.3
160.6 ± 18.5
415.0 ± 104.0
185.3 ± 5.1
175.9 ± 12.9
203.8 ± 42.1
22.3 ± 4.5
137.1b
99.2b
31.1b
17.7b
8.5 ± 4.4
12.5 ± 0.4
13.4 ± 3.0
8.3 ± 4.0
3.1 ± 1.7
3.0 ± 0.3
88.9 ± 13.8
118.0b
133.5b
127.4b
171.7b
73.5 ± 28.2
112.7 ± 0.2
108.1 ± 25.1
23.8 ± 8.1
31.6 ± 10.7
39.2 ± 8.8
118.8 ± 9.1
205.6b
188.6b
82.4b
64.5b
143.0 ± 14.5
115.4 ± 1.4
1488.8 ± 43.0
150.6 ± 1.4
72.3 ± 0.9
66.4 ± 3.6
Standard deviation given, is the instrumental standard deviation since only 1 digestion replicate is analysed. bOnly 1 digestion replicate is analysed.
93
Table A. 4. (Continued)
a
94
Sample
Pt content
(µg kg-1)
Al content
(%)
Cd content
(mg kg-1)
Co content
(mg kg-1)
Cr content
(mg kg-1)
Cu content
(mg kg-1)
S3G11
S4G11
S5G11
S6G11
S7G11
S8G11
S1G12
S1G13
S2G13
S3G13
S4G13
< LODc
< LODc
131.3 ± 180.4
0.9 ± 0.1
0.1 ± 0.3
< LODc
4.4 ± 0.3
< LODc
21.1 ± 0.4a
8.5 ± 0.7a
1.3 ± 0.5a
0.88 ± 0.02
1.01 ± 0.02
0.78 ± 0.06
0.74 ± 0.04
0.72 ± 0.04
0.79 ± 0.01
1.13 ± 0.01
1.07b
1.04b
1.04b
1.42b
0.71 ± 0.10
1.03 ± 0.03
0.93 ± 0.02
0.77 ± 0.08
0.55 ± 0.31
0.49 ± 0.04
1.59 ± 0.10
1.93b
2.54b
2.25b
2.72b
0.11 ± 0.24
1.72 ± 0.38
1.05 ± 0.34
0.27 ± 0.45
0.02 ± 0.10
0.22 ± 0.38
3.14 ± 1.38
< LOD
4.20b
2.61b
2.99b
18.4 ± 0.7
22.4 ± 0.6
26.1 ± 2.9
20.8 ± 0.2
19.6 ± 3.7
17.9 ± 0.5
31.2 ± 0.1
39.3b
46.0b
52.5b
52.4b
12.1 ± 0.2
8.2 ± 0.2
24.9 ± 4.6
19.6 ± 0.7
13.9 ± 1.1
12.2 ± 0.5
241.7 ± 286.3
35.3b
59.6b
49.7b
56.2b
Sample
Pt content
(µg kg-1)
Fe content
(%)
Mn content
(mg kg-1)
Ni content
(mg kg-1)
Pb content
(mg kg-1)
Zn content
(mg kg-1)
S3G11
S4G11
S5G11
S6G11
S7G11
S8G11
S1G12
S1G13
S2G13
S3G13
S4G13
< LODc
< LODc
131.3 ± 180.4
0.9 ± 0.1
0.1 ± 0.3
< LODc
4.4 ± 0.3
< LODc
21.1 ± 0.4a
8.5 ± 0.7a
1.3 ± 0.5a
0.80 ± 0.05
1.04 ± 0.04
0.74 ± 0.08
0.66 ± 0.04
0.63 ± 0.03
0.68 ± 0.07
1.29 ± 0.06
1.92b
1.82b
1.81b
2.34b
230.5 ± 1.2
279.3 ± 3.5
222.9 ± 21.0
177.8 ± 1.4
179.5 ± 23.1
212.7 ± 6.9
216.7 ± 8.4
141.8b
221.2b
145.0b
126.6b
6.2 ± 1.1
10.1 ± 4.7
7.3 ± 1.0
5.3 ± 0.5
3.9 ± 1.6
2.9 ± 1.3
20.3 ± 5.8
16.5b
18.3b
17.2b
16.3b
36.4 ± 5.2
34.2 ± 9.7
42.4 ± 3.8
41.4 ± 3.6
30.5 ± 5.8
25.3 ± 1.4
247.2 ± 270.5
59.0b
158.9b
114.2b
199.0b
47.0 ± 13.5
44.8 ± 11.4
107.1 ± 47.3
60.7 ± 0.2
54.4 ± 15.5
43.7 ± 2.7
134.2 ± 4.4
81.9b
140.9b
115.1b
84.7b
Standard deviation given, is the instrumental standard deviation since only 1 digestion replicate is analysed. bOnly 1 digestion replicate is analysed
c
LOD = 0.175 µg kg-1 Pt (in case of 0.200 g sample)
Table A. 5. Overview dry matter content and pH of soil samples
Sample
DM (%)
pH
Sample
DM (%)
pH
S1G1
S1G2
S2G2
S3G2
S4G2
S5G2
S6G2
S7G2
S8G2
S1G3
S1G4
S1G5
S1G6
S2G6
S3G6
S4G6
S1G7
84.6
84.3
86.0
86.5
81.0
88.1
87.8
87.7
90.6
75.7
81.8
77.7
70.2
78.2
88.8
89.4
75.2
7.39
7.56
7.36
7.74
7.73
7.89
7.84
8.13
8.81
7.30
7.18
6.74
6.67
6.61
7.64
7.87
7.07
S1G8
S1G9
S1G10
S1G11
S2G11
S3G11
S4G11
S5G11
S6G11
S7G11
S8G11
S1G12
S1G13
S2G13
S3G13
S4G13
85.2
83.2
81.7
83.0
81.6
87.6
87.1
83.6
87.5
85.2
85.9
62.1
86.6
80.7
80.6
88.3
7.48
7.13
6.97
7.12
7.10
7.73
8.11
7.30
7.10
6.92
7.09
6.61
6.85
5.68
4.89
3.72
95