method development for determination of platinum group ...€¦ · method development for...

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

I

“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

III

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.

V

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

VI

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. 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

5. 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. 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

VII

5.5. Characterisation of urban samples ................................................................................................ 71

6. General conclusions .................................................................................................................................. 73

7. Future research recommendations ........................................................................................................ 75

8. Bibliography ............................................................................................................................................... 77

9. Appendix ..................................................................................................................................................... 83

IX

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 (2004-

2013). 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

X

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


Figure 24. Selection of the main reaction product ions for Rh monitoring via product ion scanning


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


Figure 27. Selection of the main reaction product ions for Ru monitoring via product ion scanning


Figure 28. Selection of the optimal CH3F/He flow rate for selected reaction product ions 195PtCHF+,

193IrCHF+ 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 103RhCH3F+ and

103Rh(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


+

(right) ................................................................................................................................................................... 62

XI

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 106PdCH3F+ (left) and

106Pd(CH3F)2+ (right) ............................................................................................................................................ 62

Figure 41. Measured concentrations of 5 µg L-1 Pd solutions with Cd for 108PdCH3F+ (left) and

108Pd(CH3F)2+ (right) ............................................................................................................................................. 63

Figure 42. Measured concentrations of 5 µg L-1 Rh solutions with Sr for 103RhCH3F+ (left) and

103Rh(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 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. .......................................................................................................................... 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

XIII

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 ICP-

MS ......................................................................................................................................................................... 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

XIV

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

XV

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

XVI

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

XVII

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.

XIX

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 Pt-

gehaltes 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 Pt-

gehaltes 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.

1

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.

3

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.

5

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

6

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.

7

Figure 1. World platinum supply over a period from 2004 to 2013 (Johnson Matthey Ltd., 2014)

Figure 2. World palladium supply over a period from 2004 to 2013 (Johnson Matthey Ltd., 2014)

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.

0

50

100

150

200

250

2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

Pla

tin

um

su

pp

ly (

t)

South Africa Russia North America Zimbabwe Others

0

50

100

150

200

250

300

2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

Pal

lad

ium

su

pp

ly (

t)


0

5

10

15

20

25

30

2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

Rh

od

ium

su

pp

ly (

t)


8

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 Rhodium Iridium Ruthenium

Catalysts ✔ ✔ ✔ ✔ ✔

Electronics ✔ ✔ ✔ ✔

Fuel cells ✔ ✔ ✔ ✔

Glass, ceramics and pigments ✔ ✔

Medical/dental ✔ ✔ ✔

Pharmaceutical ✔ ✔ ✔

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.

9

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 (NH3) 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 (NO2).

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 Industrial use Monometallic Ru Selective hydrogenation, metathesis of olefins Pd Hydrocracking, selective hydrogenation Ir Dearomatisation Pt Reforming, C4-C6 isomerisation,

dehydrogenation, hydrogenation, isodewaxing Association of metals Pd with Ag or Au Selective hydrogenation Pt with Ge, Sn, Re or Ir Reforming Pt with Sn Dehydrogenation Pt-Pd Hydrogenation of aromatics in presence of

sulfur

Pt

AutocatalystChemicalElectricalGlassInvestmentJewelleryMedical & BiomedicalPetroleumOther

Autocatalyst

Chemical

Dental

Electrical

Investment

Jewellery

Other

Pd Rh

Autocatalyst

Chemical

Electrical

Glass

Other

10

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 + 12⁄ 𝑂2 → 𝐻2𝑂 ∆𝐺 = −237 𝑘𝐽 𝑚𝑜𝑙−1 (1)

11

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):

𝐶𝐻3𝑂𝐻 + 𝐻2𝑂 → 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 CO2-

emission 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).

12

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). Palladium-

silver, 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).

13

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 platinum-

iridium 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).

14

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

15

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 NOx

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 NOx 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):

16

𝜆 =𝐴𝐹𝑅

𝐴𝐹𝑅𝑠 (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)

𝐶𝑥𝐻𝑦 + (𝑥 + 14⁄ 𝑦)𝑂2 → 𝑥𝐶𝑂2 + 1

2⁄ 𝑦𝐻2𝑂 (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

17

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 NOx 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 → 𝐻2𝑂 (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).

18

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) :

Oxidation reactions 𝐶𝑂 + 1 2⁄ 𝑂2 → 𝐶𝑂2 (12)

𝐶𝑥𝐻𝑦 + (𝑥 + 14⁄ 𝑦)𝑂2 → 𝑥𝐶𝑂2 + 1

2⁄ 𝑦𝐻2𝑂 (13)

𝐻2 + 1 2⁄ 𝑂2 → 𝐻2𝑂 (14)

Steam-reforming reaction 𝐶𝑥𝐻𝑦 + 𝑥𝐻2𝑂 → 𝑥𝐶𝑂 + (𝑥 + 12⁄ 𝑦)𝐻2 (15)

NOx reduction 2𝐶𝑂 + 2𝑁𝑂 → 2𝐶𝑂2 + 𝑁2 (16)

𝐶𝑥𝐻𝑦 + (2𝑥 + 12⁄ 𝑦)𝑁𝑂 → 𝑥𝐶𝑂2 + 1

2⁄ 𝐻2𝑂 + (𝑥 + 14⁄ )𝑁2 (17)

𝐻2 + 𝑁𝑂 → 𝐻2𝑂 + 12⁄ 𝑁2 (18)

Water-gas shift 𝐶𝑂 + 𝐻2𝑂 → 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

19

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).

20

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 ’palladium-

only’ 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

21

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

Matthey Ltd., 2015c).

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

0

100

200

300

400

2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

Gro

ss d

em

and

(t)

Year

Rh

Pd

Pt

22

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 end-

of-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

23

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 (iii)

- 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

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

24

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 Li-

reserves 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

25

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.

26

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).

27

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 5.1-

32 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)

Type of plant material Content (ng g-1) Pt Pd Rh

Grass 8.98 3.20 0.68 Pine, birch 12.0 2.0 2.0 Tomato (without skin) 0.10 - - Carrot 0.31 - - Cabbage 1.1 - - Lettuce 2.1 - - Celery 1.3 - - Onion (without skin) 0.03 - - Dandelion 5.4-30 0.83-1.5 2.0-7.0 Greater plantain 3.6-10.1 0.45-2.1 1.1-3.4 Lichen 30.0 2.4 5.4 Rye grass 4.6-5.8 0.1 2.1-2.2

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.

28

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

Binomial name Content (ng g-1)

Pt Pd Rh Shellfish tissue Asellus aquaticus 0.04-12.4 - - Mussel tissue Dreissena polymorpha 0.1-0.5 1.0 - Eel liver Anguilla anguilla - 0.18 - Fish tissue Barbus barbus 0.1-0.4 0.3-7.0 0.1-2.0 Feathers Falco peregrinus 0.5 1.4 0.3 Blood Falco peregrinus 2.7 0.8 0.6 Eggs Falco peregrinus 0.4 0.5 0.3 Feces Falco peregrinus 0.2 - - Liver Falco peregrinus 0.2 0.7 0.3 Kidneys Falco peregrinus 0.2 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 Application method Toxicity LD50 (Pt mg kg-1) Cisplatin Intraperitoneally 7.4 Sodium tetrachloroplatinate(II) Orally 15-50 Hexachloroplatinic(IV) acid Intraperitoneally 15-19 Platinum(IV) chloride Intraperitoneally 22 Platinum(IV) chloride Orally 136 Potassium tetrachloroplatinate(II) Orally 23-94 Ammonium hexachloroplatinate(IV) Orally 88 Platinum(II) chloride Intraperitoneally 490 Platinum(II) chloride Orally >1400 Platinum(IV) oxide Orally >6900

The toxicity value reported is the median lethal dose (LD50), 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.

29

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).

31

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 real-

life 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.

32

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 high-

voltage 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)

33

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

34

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

35

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

36

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)

37

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 fine-

droplet 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 Blank (mg L-1)

Standard 1 (mg L-1)

Standard 2 (mg L-1)

Standard 3 (mg L-1)

Wavelength (nm)

Al 0 5 10 20 396.152 Cd 0 0.25 0.5 1 226.502 Co 0 0.25 0.5 1 238.892 Cr 0 0.5 1 2 267.716 Cu 0 1.25 2.5 5 327.395 Fe 0 5 10 20 238.204 Mn 0 2.5 5 10 257.610 Ni 0 1.25 2.5 5 231.604 Pb 0 1.25 2.5 5 220.353 Zn 0 5 10 20 213.857

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.

38

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

39

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.

40

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

Location description

1 B401 next to the Zuidparklaan and Gustaaf Callierlaan 2 UZ roundabout with the Corneel Heymanslaan 3 Deinsesteenweg near the end of the Watersportbaan 4 Roundabout Henri Dunantlaan and Constant Dosscheweg (near hospital Jan Palfijn) 5 Nieuwewandeling (Eethuis Volta) 6 N430 Opgeëistenlaan (Rabotpark) 7 Valentin Vaerwyckweg (near building P and sports hall HoGent) 8 R40 near De Bijloke 9 R4 Binnenring-Zwijnaarde

10 N60 Grotesteenweg-Noord (near Technologiepark-Zwijnaarde) 11 Sneppenbrugstraat at R4 Buitenring-Drongen 12 De Pintelaan near Campus De Sterre 13 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.

41

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

42

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)

43

Table 9. Overview of the samples with parameters

Code Position Description Date Distance to the

road (m)

Precipitation (mm)

3 days 7 days

Maximum

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




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


S1G4 N 51°03.086’ Soil sample 11/02/’15 3 0.10 2.90 30


S1G5 N 51°03.334’ Soil sample 11/02/’15 2 0.10 2.90 50

E003°42.431’

44

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

E 003°43.032

S1G9 N 51°00.859 Soil sample 11/02/’15 0.5 0.10 2.90 90

E 003°43.179’

S1G10 N 51°01.117’ Soil sample 11/02/’15 1 0.10 2.90 70

D1G10 E 003°42.578’ Road dust sample 11/02/’15 0.5 0.10 2.90 70

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



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



D1G11 Road dust sample 07/04/’15 0 0 9.75 90

S1G12 N 51°01.389’ Soil sample 07/04/’15 0.5 0 9.75 50

D1G12 E 003°42.750’ Road dust sample 07/04/’15 0 0 9.75 50

45

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



D1G13 Road dust sample 07/04/’15 0 0 9.75 50

47

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 HNO3 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.

48

Table 10. Closed microwave digestion program for soil and road dust samples using 4 mL HCl and 3 mL HNO3

Temperature (°C)

Ramping time (min)

Hold time (min)

Power (W)

Max. pressure (psi)

Step 1 20-90 10 5 600 300 Step 2 90-170 15 10 800 300 Step 3 170-200 10 50 1000 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 ICP-

MS 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.

49

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+ + 𝐶𝐻3𝐹 → 𝑀+𝐶𝐻3𝐹 (20)

→ 𝑀𝐹+ + 𝐶𝐻3 (21)

→ 𝑀𝐶𝐻2+ + 𝐻𝐹 (22)

→ 𝑀𝐶𝐻𝐹+ + 𝐻2 (23)

→ 𝐶𝐻2𝐹+ + 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+ 1.4 × 10-9 PtCHF+ Pd+ 5.1 × 10-12 PdCH3F

+ Rh+ 2.7 × 10-12 RhCH3F

+ Ir+ 6.6 × 10-10 IrCHF+ Os+ 1.8 × 10-10 OsCHF+ Ru+ 3.2 × 10-12 RuCH3F

+

50

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 Relative abundance (%)

Palladium isotopes Relative abundance (%)

194Pt 32.97 105Pd 22.33 195Pt 33.83 106Pd 27.33 196Pt 25.24 108Pd 26.46

Rhodium isotopes Relative abundance (%)

Iridium isotopes Relative abundance (%)

103Rh 100.00 191Ir 37.3 193Ir 62.7

Osmium isotopes Relative abundance (%)

Ruthenium isotopes Relative abundance (%)

188Os 13.24 99Ru 12.76 189Os 16.15 100Ru 12.60 190Os 26.26 101Ru 17.06 192Os 40.78 102Ru 31.55

104Ru 18.62

51

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 195PtCHF+. The

main reaction for 195Pt+ with reaction gas CH3F/He is the dehydrogenation reaction (25).

𝑃𝑡+ + 𝐶𝐻3𝐹 + 𝐻𝑒 → 𝑃𝑡𝐶𝐻𝐹+ + 𝐻2 + 𝐻𝑒 (25)

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

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+ + 𝐶𝐻3𝐹 + 𝐻𝑒 → 𝑃𝑑𝐶𝐻3𝐹+ + 𝐻𝑒 (26)

𝑃𝑑+ + 2 𝐶𝐻3𝐹 + 𝐻𝑒 → 𝑃𝑑(𝐶𝐻3𝐹)2+ + 𝐻𝑒 (27)

1

10

100

1000

10000

100000

1000000

190 195 200 205 210 215 220 225 230 235 240 245 250 255 260

Inte

nsi

ty (

cou

nts

s-1

)

Mass Q2 (amu)

195PtCHF

+ 195

Pt+

52

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

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 103RhCH3F+. The second highest intensity at m/z ratio 171 corresponds to

103Rh(CH3F)2+. The main reactions for 103Rh+ with reaction gas CH3F/He are mentioned below in

reactions (28) and (29).

𝑅ℎ+ + 𝐶𝐻3𝐹 + 𝐻𝑒 → 𝑅ℎ𝐶𝐻3𝐹+ + 𝐻𝑒 (28)

𝑅ℎ+ + 2 𝐶𝐻3𝐹 + 𝐻𝑒 → 𝑅ℎ(𝐶𝐻3𝐹)2+ + 𝐻𝑒 (29)

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

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 193IrCHF+. The main reaction for 193Ir+

with reaction gas CH3F/He is mentioned below in reaction (30).

1

10

100

1000

10000

100000

1000000

100 105 110 115 120 125 130 135 140 145 150 155 160 165 170 175 180

Inte

nsi

ty (

cou

nts

s-1

)

Mass Q2 (amu)

1

10

100

1000

10000

100000

1000000

100 105 110 115 120 125 130 135 140 145 150 155 160 165 170 175 180

Inte

nsi

ty (

cou

nts

s-1

)

Mass Q2 (amu)

105Pd(CH

3F)

2

+ 105

PdCH3F

+

105Pd

+

103Rh(CH

3F)

2

+

103Rh

+ 103

RhCH3F

+

53

𝐼𝑟+ + 𝐶𝐻3𝐹 + 𝐻𝑒 → 𝐼𝑟𝐶𝐻𝐹+ + 𝐻2 + 𝐻𝑒 (30)

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+ + 𝐶𝐻3𝐹 + 𝐻𝑒 → 𝑂𝑠𝐶𝐻𝐹+ + 𝐻2 + 𝐻𝑒 (31)

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

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

102Ru+ with reaction gas CH3F/He are mentioned below in reactions (32) and (33).

1

10

100

1000

10000

100000

1000000

190 195 200 205 210 215 220 225 230 235 240 245 250 255 260

Inte

nsi

ty (

cou

nts

s-1

)

Mass Q2 (amu)

1

10

100

1000

10000

100000

1000000

190 195 200 205 210 215 220 225 230 235 240 245 250 255 260

Inte

nsi

ty (

cou

nts

s-1

)

Mass Q2 (amu)

193Ir

+ 193IrCHF

+

192OsCHF

+ 192

Os+

54

𝑅𝑢+ + 𝐶𝐻3𝐹 + 𝐻𝑒 → 𝑅𝑢𝐶𝐻3𝐹+ + 𝐻𝑒 (32)

𝑅𝑢+ + 2 𝐶𝐻3𝐹 + 𝐻𝑒 → 𝑅𝑢(𝐶𝐻3𝐹)2+ + 𝐻𝑒 (33)

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

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.

1

10

100

1000

10000

100000

1000000

100 105 110 115 120 125 130 135 140 145 150 155 160 165 170 175 180

Inte

nsi

ty (

cou

nts

s-1

)

Mass Q2 (amu)

102Ru

+

102RuCH

3F

+ 102Ru(CH

3F)

2

+

55

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 195 227 Pd 105 139 Pd 105 173 Rh 103 137 Rh 103 171 Ir 193 225 Os 192 224 Ru 102 136 Ru 102 170

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

determination of Pt, Ir and Os.

Figure 28. Selection of the optimal CH3F/He flow rate for selected reaction product ions 195PtCHF+, 193IrCHF+ and 192OsCHF+

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,

0

40000

80000

120000

160000

0.00 0.20 0.40 0.60 0.80 1.00

Inte

nsi

ty 1

95 P

tCH

F+(c

ps)

CH3F/He flow Rate (mL min-1)

0

50000

100000

150000

200000

250000

0.00 0.20 0.40 0.60 0.80 1.00

Inte

nsi

ty 1

93 I

rCH

F+(c

ps)


0

15000

30000

45000

60000

75000

0.00 0.20 0.40 0.60 0.80 1.00

Inte

nsi

ty 1

92O

sCH

F+(c

ps)


56

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

automatically optimized with the software of the instrument.

Figure 29. Selection of the better CH3F/He flow rate for the selected species 105PdCH3F+ and 105Pd(CH3F)2

+

Figure 30. Selection of the better CH3F/He flow rate for the selected species 103RhCH3F+ and 103Rh(CH3F)2

+

Figure 31. Selection of the better CH3F/He flow rate for the selected species 102RuCH3F+ and 102Ru(CH3F)2

+

0

500

1000

1500

2000

2500

3000

3500

0.00 0.20 0.40 0.60 0.80 1.00Inte

nsi

ty 1

05 P

dC

H3F

+(c

ps)


0

500

1000

1500

2000

2500

3000

0.00 0.20 0.40 0.60 0.80 1.00

Inte

nsi

ty 1

05 P

d(C

H3F)

2+(c

ps)


0

2000

4000

6000

8000

10000

12000

14000

0.00 0.20 0.40 0.60 0.80 1.00Inte

nsi

ty 1

03 R

hC

H3F

+(c

ps)


0

2000

4000

6000

8000

10000

0.00 0.20 0.40 0.60 0.80 1.00

Inte

nsi

ty 1

03 R

h(C

H3F

) 2+

(cp

s)


0

1000

2000

3000

4000

5000

6000

0.00 0.20 0.40 0.60 0.80 1.00Inte

nsi

ty 1

02 R

uC

H3F

+(c

ps)


0

1000

2000

3000

4000

5000

6000

0.00 0.20 0.40 0.60 0.80 1.00

Inte

nsi

ty 1

02 R

u(C

H3F)

2+

(cp

s)


57

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.

Figure 32. Calibration curves for 195PtCHF+, 105PdCH3F+, 103RhCH3F

+, 193IrCHF+, 192OsCHF+ and 102RuCH3F+

y = 25845x - 312.41R² = 0.9999

0

20000

40000

60000

80000

100000

120000

140000

0 1 2 3 4 5

Inte

nsi

ty 19

5 PtC

HF+

(cp

s)

Concentration (µg L-1)

y = 688.56x - 4.2945R² = 0.9996

0

500

1000

1500

2000

2500

3000

3500

4000

0 1 2 3 4 5

Inte

nsi

ty 1

05 P

dC

H3F

+(c

ps)


y = 2651.3x - 1.6031R² = 1

0

2000

4000

6000

8000

10000

12000

14000

0 1 2 3 4 5

Inte

nsi

ty 1

03 R

hC

H3F

+(c

ps)


y = 44543x - 140.92R² = 1

0

50000

100000

150000

200000

250000

0 1 2 3 4 5

Inte

nsi

ty 1

93 I

rCH

F+(c

ps)


y = 13898x + 319.66R² = 1

0

10000

20000

30000

40000

50000

60000

70000

80000

0 1 2 3 4 5

Inte

nsi

ty 1

92 O

sCH

F+(c

ps)


y = 1016.7x - 8.3398R² = 1

0

1000

2000

3000

4000

5000

6000

0 1 2 3 4 5

Inte

nsi

ty 1

02 R

uC

H3F

+(c

ps)


58

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

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) 99Ru 1.00 99RuCH3F

+ 99 133 381 ± 5 1.0000 0.005 0.018 99Ru 1.00 99Ru(CH3F)2

+ 99 167 440 ± 5 0.9998 0.008 0.026 100Ru 1.00 100RuCH3F

+ 100 134 384 ± 9 0.9998 0.011 0.036

100Ru 1.00 100Ru(CH3F)2+ 100 168 447 ± 13 0.9998 0.004 0.013

101Ru 1.00 101RuCH3F+ 101 135 526 ± 7 1.0000 0.003 0.009

101Ru 1.00 101Ru(CH3F)2+ 101 169 614 ± 13 0.9999 0.005 0.016

102Ru 1.00 102RuCH3F+ 102 136 1017 ± 17 1.0000 0.003 0.009

102Ru 1.00 102Ru(CH3F)2+ 102 170 1161 ± 17 0.9999 0.002 0.008

104Ru 1.00 104RuCH3F+ 104 138 805 ± 10 1.0000 0.005 0.017

104Ru 1.00 104Ru(CH3F)2+ 104 172 730 ± 10 0.9999 0.004 0.014

103Rh 1.00 103RhCH3F+ 103 137 2651 ± 30 1.0000 0.0005 0.002

103Rh 1.00 103Rh(CH3F)2+ 103 171 2198 ± 18 1.0000 0.001 0.003

105Pd 1.00 105PdCH3F+ 105 139 689 ± 15 0.9996 0.004 0.014

105Pd 1.00 105Pd(CH3F)2+ 105 173 680 ± 12 0.9995 0.003 0.011

106Pd 1.00 106PdCH3F+ 106 140 836 ± 11 0.9996 0.004 0.013

106Pd 1.00 106Pd(CH3F)2+ 106 174 837 ± 11 0.9992 0.003 0.010

108Pd 1.00 108PdCH3F+ 108 142 953 ± 13 0.9997 0.003 0.010

108Pd 1.00 108Pd(CH3F)2+ 108 176 849 ± 15 0.9997 0.003 0.011

188Os 0.80 188OsCHF+ 188 220 4504 ± 26 0.9999 0.005 0.018

189Os 0.80 189OsCHF+ 189 221 5449 ± 28 0.9999 0.005 0.017 190Os 0.80 190OsCHF+ 190 222 8798 ± 68 1.0000 0.005 0.018 191Ir 0.80 191IrCHF+ 191 223 25927 ± 172 1.0000 0.0008 0.003

192Os 0.80 192OsCHF+ 192 224 13898 ± 102 1.0000 0.004 0.013

193Ir 0.80 193IrCHF+ 193 225 44543 ± 355 1.0000 0.0005 0.002 194Pt 0.80 194PtCHF+ 194 226 24469 ± 102 0.9999 0.0006 0.002 195Pt 0.80 195PtCHF+ 195 227 25845 ± 115 0.9999 0.0007 0.002 196Pt 0.80 196PtCHF+ 196 228 18570 ± 63 0.9999 0.0008 0.003

59

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 Isobaric interferences

194Pt 32.97 178HfO+ 154SmAr+ 154GdAr+ /

195Pt 33.83 179HfO+ 155GdAr+ /

196Pt 25.24 180HfO+ 156GdAr+ 196Hg+

60

Figure 33. Measured concentrations of 5 µg L-1 Pt solutions with Hf for 194PtCHF+ (left) and 195PtCHF+ (right)

Figure 34. Measured concentrations of 5 µg L-1 Pt solutions with Hf for 196PtCHF+ (left), Sm for 194PtCHF+ (right)

Figure 35. Measured concentrations of 5 µg L-1 Pt solutions with Gd for 194PtCHF+ (left) and 195PtCHF+ (right)

Figure 36. Measured concentrations of 5 µg L-1 Pt solutions with Gd for 196PtCHF+ (left), Hg for 196PtCHF+ (right)

0

1

2

3

4

5

no Hf 10 ppb Hf 100 ppb Hf 1 ppm Hf

Co

nce

ntr

atio

n (

µg

L-1)

0

1

2

3

4

5


Co

nce

ntr

atio

n (

µg

L-1)

0

1

2

3

4

5


Co

nce

ntr

atio

n (

µg

L-1)

0

1

2

3

4

5

no Sm 10 ppb Sm 100 ppb Sm 1 ppm Sm

Co

nce

ntr

atio

n (

µg

L-1)

0

1

2

3

4

5

no Gd 10 ppb Gd 100 ppb Gd 1 ppm Gd

Co

nce

ntr

atio

n (

µg

L-1)

0

1

2

3

4

5


Co

nce

ntr

atio

n (

µg

L-1)

0

1

2

3

4

5


Co

nce

ntr

atio

n (

µg

L-1)

0

1

2

3

4

5

no Hg 5 ppb Hg 10 ppb Hg 100 ppb Hg

Co

nce

ntr

atio

n (

µg

L-1)

61

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 106Pd but not for 105Pd. 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

addition reaction with Cd inside the ORS results in the same reaction product ions 106CdCH3F+,

106Cd(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 105Pd(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



105Pd 22.33 89YO+ 88SrOH+ 65CuAr+ 70Zn35Cl+ 68Zn37Cl+

/

106Pd 27.33 89YOH+ 90ZrO+ 66ZnAr+ 106Cd+

108Pd 26.46 92ZrO+ 92MoO+ 68ZnAr+ 108Cd+

62


+ (right)


+ (right)

Figure 39. Measured concentrations of 5 µg L-1 Pd solutions with Sr for 105PdCH3F+ (left) and 105Pd(CH3F)2

+ (right)

Figure 40. Measured concentrations of 5 µg L-1 Pd solutions with Cd for 106PdCH3F+ (left) and 106Pd(CH3F)2

+ (right)

0

2

4

6

8

no Y 10 ppb Y 100 ppb Y 1 ppm Y

Co

nce

ntr

atio

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µg

L-1)

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0

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no Sr 10 ppb Sr 100 ppb Sr 1 ppm Sr

Co

nce

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atio

n (µ

g L-1

)

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3

4

5

6

7


Co

nce

ntr

atio

n (µ

g L-1

)

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no Cd 5 ppb Cd 10 ppb Cd 100 ppb Cd

Co

nce

ntr

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n (

µg

L-1)

0

2

4

6

8


Co

nce

ntr

atio

n (

µg

L-1)

29.075

25.683

63

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



103Rh 100.00 87SrO+ 87RbO+ 63CuAr+ 68Zn35Cl+ 66Zn37Cl+ 206Pb++

/

0

2

4

6

8


Co

nce

ntr

atio

n (

µg

L-1)

0

2

4

6

8


Co

nce

ntr

atio

n (

µg

L-1)

64

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 106,108Pd 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.

0

1

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4

5


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L-1)

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65

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+

(Average ± s)a 194PtCHF+ (µg kg-1 Pt) 195PtCHF+ (µg kg-1 Pt) 196PtCHF+ (µg kg-1 Pt)

1 81.88 ± 2.06 81.10 ± 0.61 81.82 ± 1.80 2 80.75 ± 2.45 80.96 ± 1.47 79.98 ± 1.21 3 81.57 ± 2.90 80.32 ± 1.53 81.54 ± 1.99 4 82.30 ± 2.00 80.78 ± 2.28 80.59 ± 0.77 5 81.76 ± 1.09 81.27 ± 0.87 80.07 ± 1.11

(Average ± s)b 81.65 ± 0.57 80.89 ± 0.36 80.80 ± 0.84 Certified reference material (µg kg-1 Pt) 81.3 ± 2.5

aAverage values and standard deviations are calculated based on 5 replicates. bAverage values and standard deviations are calculated based on the average values of 5 digestion replicates.

66

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 p-

values 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.

80

90

100

110

1 2 3 4 5

Re

cove

ry (

%)

Digestion

67

Table 19. Average Pt contents with corresponding standard deviations (3 replicates) for digested road dust samples, measured as reaction product ion 195PtCHF+

Sample Pt content (µg kg-1)

Standard deviation (µg kg -1)

Distance to the road (m)

D1G1 29.7 16.1 0 D1G2 134.8 130.5 0 D1G3 7.5 0.5 1 D1G4 18.4 5.7 0 D1G7 11.1 1.0 0 D1G10 7.6 0.9 0.5 D1G11 18.1 17.5 0 D1G12 16.8 5.3 0 D1G13 34.4 10.0 0 Averagea 30.9 40.0

aAverage 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+


Standard deviation (µg kg-1)

D1G1-1 25.2 0.3 D1G1-2 47.6 0.6 D1G1-3 16.4 0.8 D1G2-1 8.5 0.3 D1G2-2 269.1 3.7 D1G2-3 126.8 2.6 D1G11-1 7.8 0.4 D1G11-2 38.3 0.7 D1G11-3 8.3 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).

68

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 7.8 0.8 2 S1G2 4.3 1.5 0.5 S1G3 12.8 3.4 2 S1G4 2.9 0.7 3 S1G5 5.2 1.4 2 S1G6 57.9 1.0a 1 S1G7 2.3 0.6 0.5 S1G8 1.3 0.7 1 S1G9 10.8 1.3 0.5 S1G10 15.8 15.9 1 S1G11 1.4 0.1 1 S1G12 4.4 0.3 0.5 S1G13 < LODc - 0.5 Averageb 10.6 15.6

aStandard deviation given, is the instrumental standard deviation since only 1 digestion replicate is analysed. bAverage Pt content is calculated based on the average Pt contents of 13 soil samples. cLOD = 0.175 µg kg-1 Pt (in case of 0.200 g sample)

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 Pt content (µg kg-1)

Standard deviation (µg kg-1)

Soil depth (cm)

1 S5G2 2.0 1.8 0-3 S6G2 84.2 106.5 3-10 S7G2 1.0 0.5 10-20 S8G2 0.8 0.02 20-30

2 S1G6 57.9 1.0a 0-3 S2G6 29.1 0.6a 3-10 S3G6 2.0 1.2a 10-20 S4G6 1.2 0.5a 20-30

3 S1G11 1.4 0.1 0-3 S2G11 1.5 0.5 3-10 S3G11 < LODb - 10-20 S4G11 < LODb - 20-30

aStandard deviation given, is the instrumental standard deviation since only 1 digestion replicate is analysed. bLOD = 0.175 µg kg-1 Pt (in case of 0.200 g sample)

69

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 Pt content (µg kg-1) Standard deviation Distance to the road (m)

1 S1G2 4.3 1.5 0.5 S2G2 2.2 0.8 1 S3G2 3.7 2.6 2 S4G2 2.0 0.1 3

2 S5G11 131.3 180.4 0.5 S6G11 0.9 0.1 1 S7G11 0.1 0.3 2 S8G11 < LODb - 3

3 S1G13 < LODb - 0.5 S2G13 21.1 0.4a 1 S3G13 8.5 0.7a 2 S4G13 1.3 0.5a 3

aStandard deviation given, is the instrumental standard deviation since only 1 digestion replicate is analysed. bLOD = 0.175 µg kg-1 (in case of 0.200 g sample)

0 10 20 30 40 50 60 70 80 90

-30

-25

-20

-15

-10

-5

0

Pt content (µg kg-1)

Soil

de

pth

(cm

)

Depthprofile 1

Depthprofile 2

Depthprofile 3

70

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.

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) 3.7-91.4 13.9-153.2 (Whiteley, 2005) Ioannina (Greece) 3.2-306.4 2.8-225.1 (Tsogas et al., 2008) Madrid (Spain) 31-2,252 - (B. Gómez et al., 2001) Italy 26-1177 1.0-11.5 (Spaziani et al., 2008) Bialystok (Poland) 34.2-110.9 - (Leśniewska et al., 2004) Honolulu (USA) 15-160 2-160 (Sutherland, 2003) Germany - 1.3-261 (Wichmann et al., 2007) Ghent (Belgium) 7.5-134.8 1.3-57.9 This study

< 2.5

2.5-8

8.1-15

15.1-25

25.1-50

50.1-100

>100

71

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 9,643.2 2,015.6 Cd 1.4 0.7 Co 1.8 1.9 Cr 42.5 56.0 Cu 42.5 49.3 Fe 12,198.6 4,484.2 Mn 245.3 105.08 Ni 16.4 27.6 Pb 79.6 75.8 Zn 140.4 248.8

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 1 -0.264 -0.465 0.017 0.166 -0.245 -0.312 -0.740* -0.494 -0.279 -0.485

Al - 1 0.902** 0.467 0.111 0.056 0.926** 0.259 0.069 0.679* 0.415

Cd - - 1 0.363 0.267 0.222 0.953** 0.419 0.419 0.741* 0.444

Co - - - 1 -0.211 0.055 0.416 -0.260 0.157 0.703* -0.200

Cr - - - - 1 0.751* 0.410 0.119 0.503 0.248 0.341

Cu - - - - - 1 0.374 0.278 0.756* 0.361 0.351

Fe - - - - - - 1 0.315 0.389 0.753* 0.436

Mn - - - - - - - 1 0.307 0.351 0.826**

Ni - - - - - - - - 1 0.433 0.162

Pb - - - - - - - - - 1 0.412

Zn - - - - - - - - - - 1

*Correlation is significant at the 0.05 level (two-sided). **Correlation is significant at the 0.01 level (two-sided).

72

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 Pt 1 -0.116 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

Cr - - - - 1 0.321 0.382* 0.415* 0.979** 0.206 0.093

Cu - - - - - 1 0.453* 0.325 0.434* 0.639** 0.223

Fe - - - - - - 1 0.264 0.433* 0.664** 0.140

Mn - - - - - - - 1 0.453* 0.513** 0.398*

Ni - - - - - - - - 1 0.291 0.080

Pb - - - - - - - - - 1 0.134

Zn - - - - - - - - - - 1

*Correlation is significant at the 0.05 level (two-sided). **Correlation is significant at the 0.01 level (two-sided).

73

6. General conclusions

Results obtained when studying the reactions between the PGMs and CH3F occurring in tandem ICP-

mass 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.

75

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

105Pd(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.

77

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Alt, F., Eschnauer, H. R., Mergler, B., Messerschmidt, J., & Tölg, G. (1997). A contribution to the ecology and enology of platinum. Fresenius’ Journal of Analytical Chemistry, 357(8), 1013–1019.

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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 µg kg-1 81.3 2.5 Pd µg kg-1 6.1 1.9 Rh µg kg-1 12.8 1.3 Al % 3.75 0.22 Ba g kg-1 0.46 0.04 Cd mg kg-1 2.5 0.4 Co mg kg-1 29.8 1.6 Cr mg kg-1 440 18 Fe % 3.29 0.20 Hf mg kg-1 2.2 0.7 Mn g kg-1 1.28 0.04 Mo mg kg-1 40.0 0.6 Ni mg kg-1 171 3 Pb mg kg-1 866 16 Rb mg kg-1 75 5 Sb mg kg-1 28.2 2.3 Sr mg kg-1 254 19 Ti g kg-1 2.58 0.13 Th mg kg-1 4.8 0.5 V mg kg-1 74.9 1.9 Y mg kg-1 12.5 1.8

Zn g kg-1 1.66 0.10

Figure A. 1. Calibration curves obtained for two platinum isotopes as PtCHF+

y = 24469x - 268.66R² = 0.9999

0

20000

40000

60000

80000

100000

120000

140000

0 1 2 3 4 5

Inte

nsi

ty 19

4P

tCH

F+(c

ou

nts

s-1

)


y = 18570x - 251.03R² = 0.9999

0

20000

40000

60000

80000

100000

0 1 2 3 4 5

Inte

nsi

ty 19

6P

tCH

F+(c

ou

nts

s-1

)


84

Figure A. 2. Calibration curves obtained for three different palladium isotopes as PdCH3F+ and Pd(CH3F)2

+

y = 679.67x - 11.241R² = 0.9995

0

500

1000

1500

2000

2500

3000

3500

4000

0 1 2 3 4 5Inte

nsi

ty 1

05P

d(C

H3F)

2+

(co

un

ts s

-1)


y = 835.83x + 4.1699R² = 0.9996

0

500

1000

1500

2000

2500

3000

3500

4000

4500

0 1 2 3 4 5

Inte

nsi

ty 1

06P

dC

H3F+

(co

un

ts s

-1)


y = 837.08x - 6.3921R² = 0.9992

0

500

1000

1500

2000

2500

3000

3500

4000

4500

0 1 2 3 4 5Inte

nsi

ty 1

06P

d(C

H3F)

2+

(co

un

ts s

-1)


y = 953.28x + 9.0866R² = 0.9997

0

1000

2000

3000

4000

5000

6000

0 1 2 3 4 5Inte

nsi

ty 1

08P

dC

H3F

+(c

ou

nts

s-1

)


y = 849.41x - 9.8566R² = 0.9997

0

500

1000

1500

2000

2500

3000

3500

4000

4500

0 1 2 3 4 5Inte

nsi

ty 1

08P

d(C

H3F)

2+

(co

un

ts s

-1)


85

Figure A. 3. Calibration curve obtained for mono-isotopic Rh as Rh(CH3F)2+

Figure A. 4. Calibration curve obtained for iridium isotope 191 as IrCHF+

Figure A. 5. Calibration curves obtained for osmium isotope 188 as OsCHF+

y = 2197.7x + 10.333R² = 1

0

2000

4000

6000

8000

10000

12000

0 1 2 3 4 5Inte

nsi

ty 1

03R

h(C

H3F)

2+

(co

un

ts s

-1)


y = 25927x - 122.17R² = 1

0

20000

40000

60000

80000

100000

120000

140000

0 1 2 3 4 5

Inte

nsi

ty 1

91 I

rCH

F+(c

ou

nts

s-1

)


y = 4504.4x + 127R² = 0.9999

0

5000

10000

15000

20000

25000

0 1 2 3 4 5

Inte

nsi

ty 1

88 O

sCH

F+(c

ou

nts

s-1

)


86

Figure A. 6. Calibration curves obtained for osmium isotopes 189 and 190 as OsCHF+

Figure A. 7. Calibration curves obtained for ruthenium isotopes 99 and 100 as RuCH3F+ and Ru(CH3F)2

+

y = 5449.3x + 159.58R² = 0.9999

0

5000

10000

15000

20000

25000

30000

0 1 2 3 4 5

Inte

nsi

ty 1

89 O

sCH

F+(c

ou

nts

s-1

)


y = 8797.5x + 221.15R² = 1

0

10000

20000

30000

40000

50000

0 1 2 3 4 5

Inte

nsi

ty 1

90 O

sCH

F+(c

ou

nts

s-1

)


y = 381.04x - 5.4274R² = 1

0

500

1000

1500

2000

0 1 2 3 4 5

Inte

nsi

ty 9

9 Ru

CH

3F+

(co

un

ts s

-1)


y = 440.42x - 11.003R² = 0.9998

0

500

1000

1500

2000

2500

0 1 2 3 4 5Inte

nsi

ty 9

9R

u(C

H3F)

2+

(co

un

ts s

-1)


y = 384.46x - 7.6903R² = 0.9998

0

500

1000

1500

2000

0 1 2 3 4 5Inte

nsi

ty 1

00 R

uC

H3F

+(c

ou

nts

s-1

)


y = 447.8x - 13.28R² = 0.9998

0

500

1000

1500

2000

2500

0 1 2 3 4 5Inte

nsi

ty 1

00R

u(C

H3F)

2+

(co

un

ts s

-1)


87

Figure A. 8. Calibration curves obtained for ruthenium isotopes 101, 102 and 104 as RuCH3F+ and Ru(CH3F)2

+

y = 525.66x - 3.6476R² = 1

0

500

1000

1500

2000

2500

3000

0 1 2 3 4 5Inte

nsi

ty 1

01R

uC

H3F

+(c

ou

nts

s-1

)


y = 613.89x - 11.972R² = 0.9999

0

500

1000

1500

2000

2500

3000

3500

0 1 2 3 4 5Inte

nsi

ty 1

01R

u(C

H3F)

2+

(co

un

ts s

-1)


y = 1161x - 31.987R² = 0.9999

0

1000

2000

3000

4000

5000

6000

0 1 2 3 4 5Inte

nsi

ty 1

02R

u(C

H3F)

2+

(co

un

ts s

-1)


y = 805.23x - 11.707R² = 1

0

1000

2000

3000

4000

5000

0 1 2 3 4 5Inte

nsi

ty 1

04 R

uC

H3F+

(co

un

ts s

-1)


y = 730.04x - 18.087R² = 0.9999

0

1000

2000

3000

4000

0 1 2 3 4 5Inte

nsi

ty 1

04R

u(C

H3F)

2+

(co

un

ts s

-1)


88

Figure A. 9. Measured concentrations of 5 µg L-1 Pd solutions with Mo for 108PdCH3F+ (left) and 108Pd(CH3F)2

+ (right)

Figure A. 10. Measured concentrations of 5 µg L-1 Pd solutions with Zn for 105PdCH3F+ (left) and 105Pd(CH3F)2

+ (right)


+ (right)


+ (right)

0

1

2

3

4

5

no Mo 10 ppb Mo 100 ppb Mo 1 ppm Mo

Co

nce

ntr

atio

n (

µg

L-1)

0

1

2

3

4

5

no Mo 10 ppb Mo 100 ppb Mo 1 ppm Mo

Co

nce

ntr

atio

n (

µg

L-1)

0

1

2

3

4

5

no Zn 10 ppb Zn 100 ppb Zn 1 ppm Zn

Co

nce

ntr

atio

n (

µg

L-1)

0

1

2

3

4

5


Co

nce

ntr

atio

n (

µg

L-1)

0

1

2

3

4

5


Co

nce

ntr

atio

n (

µg

L-1)

0

1

2

3

4

5


Co

nce

ntr

atio

n (

µg

L-1)

0

1

2

3

4

5


Co

nce

ntr

atio

n (

µg

L-1)

0

1

2

3

4

5


Co

nce

ntr

atio

n (

µg

L-1)

89

Figure A. 13. Measured concentrations of 5 µg L-1 Pd solutions with Cu for 105PdCH3F+ (left) and 105Pd(CH3F)2

+ (right)

Figure A. 14. Measured concentrations of 5 µg L-1 Rh solutions with Rb for 103RhCH3F+ (left) and 103Rh(CH3F)2

+

(right)

Figure A. 15. Measured concentrations of 5 µg L-1 Rh solutions with Cu for 103RhCH3F+ (left) and 103Rh(CH3F)2

+

(right)

Figure A. 16. Measured concentrations of 5 µg L-1 Rh solutions with Zn for 103RhCH3F+ (left) and 103Rh(CH3F)2

+

(right)

0

1

2

3

4

5

no Cu 10 ppb Cu 100 ppb Cu 1 ppm Cu

Co

nce

ntr

atio

n (

µg

L-1)

0

1

2

3

4

5


Co

nce

ntr

atio

n (

µg

L-1)

0

1

2

3

4

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no Rb 10 ppb Rb 100 ppb Rb 1 ppm Rb

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90

Figure A. 17. Measured concentrations of 5 µg L-1 Rh solutions with Pb for 103RhCH3F+ (left) and 103Rh(CH3F)2

+

(right)

Table A. 2. Tandem ICP-MS instrumental parameters of the platinum method

Plasma parameters Lens parameters Parameter Unit Value Parameter Unit Value RF power W 1550 Q1 entrance V 3 Carrier gas L min-1 1.14 Q1 exit V 1 Sampling depth mm 5.5 Cell entrance V -50 Nebuliser pump rps 0.1 Cell exit V -52 Spray chamber T °C 2 Deflect V 4.6 Plate bias V -60

Cell parameters Parameter Unit Value CH3F/He gas flow rate mL min-1 0.8 Octopole bias V -4.1 Energy discrimination V -8.4

0

1

2

3

4

5

no Pb 10 ppb Pb 100 ppb Pb 1 ppm Pb

Co

nce

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no Pb 10 ppb Pb 100 ppb Pb 1 ppm Pb

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91

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.


Al content (%)

Cd content (mg kg-1)

Co content (mg kg-1)

Cr content (mg kg-1)

Cu content (mg kg-1)

D1G1 29.7 ± 16.1 0.92 ± 0.03 2.80 ± 0.09 2.09 ± 0.33 58.8 ± 2.1 121.4 ± 4.5

D1G2 134.8 ± 130.5 0.70 ± 0.03 1.36 ± 0.13 0.85 ± 0.49 59.5 ± 11.7 87.6 ± 15.7

D1G3 7.5 ± 0.5 0.65 ± 0.03 1.94 ± 0.21 0.08 ± 0.12 47.4 ± 5.6 84.7 ± 10.7

D1G4 18.4 ± 5.7 0.70 ± 0.03 1.70 ± 0.05 1.32 ± 0.57 46.7 ± 9.0 105.6 ± 13.6

D1G7 11.1 ± 1.0 0.92 ± 0.03 2.16 ± 0.22 1.21 ± 0.51 57.4 ± 5.7 138.8 ± 33.5

D1G10 7.6 ± 0.9 0.83 ± 0.06 2.27 ± 0.33 0.51 ± 0.64 53.7 ± 3.8 104.7 ± 18.4

D1G11 18.1 ± 17.5 0.91 ± 0.02 2.47 ± 0.23 0.74 ± 0.47 64.1 ± 3.3 113.2 ± 10.3

D1G12 16.8 ± 5.3 1.40 ± 0.08 3.71 ± 0.08 1.37 ± 1.36 61.0 ± 8.3 103.0 ± 4.8

D1G13 34.5 ± 10.0 0.74 ± 0.01 2.38 ± 0.19 0.25 ± 0.26 87.3 ± 9.2 160.9 ± 9.1


Fe content (%)

Mn content (mg kg-1)

Ni content (mg kg-1)

Pb content (mg kg-1)

Zn content (mg kg-1)

D1G1 29.7 ± 16.1 1.60 ± 0.06 347.2 ± 11.0 28.9 ± 5.4 92.8 ± 7.1 199.9 ± 15.0

D1G2 134.8 ± 130.5 1.15 ± 0.02 246.7 ± 6.6 11.5 ± 2.1 47.5 ± 20.4 173.0 ± 7.6

D1G3 7.5 ± 0.5 1.13 ± 0.04 386.1 ± 17.6 21.1 ± 10.8 39.7 ± 1.9 238.6 ± 9.6

D1G4 18.4 ± 5.7 1.18 ± 0.05 300.9 ± 4.3 19.5 ± 7.2 57.1 ± 7.7 208.2 ± 9.9

D1G7 11.1 ± 1.0 1.50 ± 0.04 405.2 ± 9.0 22.5 ± 3.7 67.1 ± 5.7 301.9 ± 0.6

D1G10 7.6 ± 0.9 1.40 ± 0.12 415.4 ± 34.3 18.4 ± 2.2 59.9 ± 7.3 240.4 ± 23.7

D1G11 18.1 ± 17.5 1.47 ± 0.02 465.0 ± 8.7 19.5 ± 0.7 82.4 ± 3.7 391.0 ± 13.9

D1G12 16.8 ± 5.3 2.02 ± 0.08 366.3 ± 15.2 20.0 ± 3.8 81.2 ± 8.8 295.0 ± 14.8

D1G13 34.5 ± 10.0 1.55 ± 0.03 367.3 ± 13.1 30.1 ± 6.6 61.2 ± 4.8 278.5 ± 9.4

92

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.


Al content (%)





S1G1 7.8 ± 0.8 1.12 ± 0.04 2.50 ± 0.16 2.50 ± 0.04 31.2 ± 0.6 57.4 ± 8.1

S1G2 4.28 ± 1.5 0.92 ± 0.02 1.67 ± 0.30 0.76 ± 0.77 30.1 ± 3.3 21.0 ± 6.0

S2G2 2.25 ± 0.8 1.00 ± 0.03 1.26 ± 0.13 0.59 ± 0.56 32.1 ± 5.6 7.3 ± 3.0

S3G2 3.71 ± 2.6 0.89 ± 0.01 1.26 ± 0.12 0.51 ± 0.07 25.4 ± 4.9 5.9 ± 1.1

S4G2 2.05 ± 0.1 0.95 ± 0.03 1.39 ± 0.05 1.14 ± 0.55 26.2 ± 1.8 9.1 ± 0.6

S5G2 2.0 ± 1.8 0.77 ± 0.02 0.83 ± 0.08 0.31 ± 0.05 18.4 ± 1.0 7.4 ± 0.2

S6G2 84.2 ± 106.5 0.97 ± 0.08 1.29 ± 0.04 0.94 ± 0.91 27.8 ± 0.6 6.1 ± 0.3

S7G2 1.0 ± 0.5 1.00 ± 0.05 1.58 ± 0.03 1.23 ± 0.24 26.3 ± 0.8 14.3 ± 1.5

S8G2 0.8 ± 0.02 0.86 ± 0.04 0.06 ± 0.09 0.25 ± 0.26 18.3 ± 0.9 < LOD

S1G3 12.8 ± 3.4 0.59 ± 0.08 1.81 ± 0.16 0.93 ± 0.19 36.1 ± 4.3 70.5 ± 5.2

S1G4 2.9 ± 0.7 1.08 ± 0.01 1.04 ± 0.14 1.28 ± 0.14 28.3 ± 0.7 15.7 ± 0.2


Fe content (%)





S1G1 7.8 ± 0.8 1.52 ± 0.26 622.2 ± 526.5 12.1 ± 3.0 336.1 ± 38.6 153.1 ± 4.5

S1G2 4.28 ± 1.5 1.17 ± 0.12 305.4 ± 147.0 4.2 ± 1.7 21.7 ± 4.2 172.2 ± 2.4

S2G2 2.25 ± 0.8 1.30 ± 0.10 168.7 ± 8.1 5.0 ± 0.9 21.9 ± 1.2 43.9 ± 3.7

S3G2 3.71 ± 2.6 1.03 ± 0.04 156.6 ± 5.6 3.5 ± 1.2 12.2 ± 1.2 38.4 ± 2.1

S4G2 2.05 ± 0.1 1.09 ± 0.05 165.3 ± 5.1 3.2 ± 0.9 26.7 ± 5.8 54.0 ± 2.3

S5G2 2.0 ± 1.8 0.77 ± 0.01 200.6 ± 5.0 1.2 ± 0.4 7.0 ± 1.4 56.6 ± 1.0

S6G2 84.2 ± 106.5 1.17 ± 0.02 180.8 ± 8.8 3.9 ± 0.8 17.3 ± 0.3 42.0 ± 1.6

S7G2 1.0 ± 0.5 1.13 ± 0.01 187.5 ± 0.5 3.0 ± 1.1 29.8 ± 4.0 58.5 ± 5.4

S8G2 0.8 ± 0.02 0.70 ± 0.02 237.9 ± 6.2 5.6 ± 2.1 6.7 ± 3.2 29.8 ± 2.1

S1G3 12.8 ± 3.4 1.01 ± 0.01 318.7 ± 21.9 7.0 ± 1.4 67.5 ± 47.7 281.4 ± 2.5

S1G4 2.9 ± 0.7 1.35 ± 0.07 362.8 ± 27.3 11.3 ± 2.4 60.2 ± 2.6 93.6 ± 18.5

93

Table A. 4. (Continued)


Al content (%)





S1G5 5.2 ± 1.4 1.20 ± 0.09 2.39 ± 0.08 5.43 ± 0.12 33.9 ± 0.3 42.0 ± 7.1

S1G6 57.9 ± 1.0a 0.94b 1.99b 3.23b 297.5b 98.0b

S2G6 29.7 ± 0.6a 1.32b 1.80b 6.48b 207.0b 98.5b

S3G6 2.0 ± 1.2a 1.37b 1.45b 7.17b 32.8b 153.4b

S4G6 1.2 ± 0.5a 1.08b 1.25b 3.33b 24.2b 49.4b

S1G7 2.3 ± 0.6 1.06 ± 0.09 0.90 ± 0.18 1.89 ± 0.41 27.4 ± 2.4 20.1 ± 1.5

S1G8 1.3 ± 0.7 1.05 ± 0.02 1.09 ± 0.29 1.51 ± 0.21 29.0 ± 1.0 23.5 ± 0.1

S1G9 10.8 ± 1.3 0.94 ± 0.01 1.95 ± 0.12 3.39 ± 0.36 40.4 ± 3.1 81.3 ± 2.5

S1G10 15.8 ± 16.0 0.64 ± 0.01 0.73 ± 0.10 0.64 ± 0.04 27.6 ± 0.9 48.1 ± 0.5

S1G11 1.4 ± 0.1 0.70 ± 0.01 0.36 ± 0.08 0.88 ± 1.01 19.2 ± 2.7 20.9 ± 4.1

S2G11 1.5 ± 0.5 0.71 ± 0.01 0.70 ± 0.32 < LOD 18.5 ± 1.3 20.7 ± 2.6


Fe content (%)





S1G5 5.2 ± 1.4 1.26 ± 0.01 246.1 ± 4.9 22.3 ± 4.5 88.9 ± 13.8 118.8 ± 9.1

S1G6 57.9 ± 1.0a 1.66b 431.5b 137.1b 118.0b 205.6b

S2G6 29.7 ± 0.6a 1.67b 391.9b 99.2b 133.5b 188.6b

S3G6 2.0 ± 1.2a 1.93b 339.7b 31.1b 127.4b 82.4b

S4G6 1.2 ± 0.5a 1.67b 225.1b 17.7b 171.7b 64.5b

S1G7 2.3 ± 0.6 1.12 ± 0.05 253.9 ± 7.3 8.5 ± 4.4 73.5 ± 28.2 143.0 ± 14.5

S1G8 1.3 ± 0.7 1.33 ± 0.05 160.6 ± 18.5 12.5 ± 0.4 112.7 ± 0.2 115.4 ± 1.4

S1G9 10.8 ± 1.3 1.43 ± 0.09 415.0 ± 104.0 13.4 ± 3.0 108.1 ± 25.1 1488.8 ± 43.0

S1G10 15.8 ± 16.0 0.85 ± 0.02 185.3 ± 5.1 8.3 ± 4.0 23.8 ± 8.1 150.6 ± 1.4

S1G11 1.4 ± 0.1 0.67 ± 0.01 175.9 ± 12.9 3.1 ± 1.7 31.6 ± 10.7 72.3 ± 0.9

S2G11 1.5 ± 0.5 0.70 ± 0.01 203.8 ± 42.1 3.0 ± 0.3 39.2 ± 8.8 66.4 ± 3.6 aStandard deviation given, is the instrumental standard deviation since only 1 digestion replicate is analysed. bOnly 1 digestion replicate is analysed.

94

Table A. 4. (Continued)


Al content (%)





S3G11 < LODc 0.88 ± 0.02 0.71 ± 0.10 0.11 ± 0.24 18.4 ± 0.7 12.1 ± 0.2

S4G11 < LODc 1.01 ± 0.02 1.03 ± 0.03 1.72 ± 0.38 22.4 ± 0.6 8.2 ± 0.2

S5G11 131.3 ± 180.4 0.78 ± 0.06 0.93 ± 0.02 1.05 ± 0.34 26.1 ± 2.9 24.9 ± 4.6

S6G11 0.9 ± 0.1 0.74 ± 0.04 0.77 ± 0.08 0.27 ± 0.45 20.8 ± 0.2 19.6 ± 0.7

S7G11 0.1 ± 0.3 0.72 ± 0.04 0.55 ± 0.31 0.02 ± 0.10 19.6 ± 3.7 13.9 ± 1.1

S8G11 < LODc 0.79 ± 0.01 0.49 ± 0.04 0.22 ± 0.38 17.9 ± 0.5 12.2 ± 0.5

S1G12 4.4 ± 0.3 1.13 ± 0.01 1.59 ± 0.10 3.14 ± 1.38 31.2 ± 0.1 241.7 ± 286.3

S1G13 < LODc 1.07b 1.93b < LOD 39.3b 35.3b

S2G13 21.1 ± 0.4a 1.04b 2.54b 4.20b 46.0b 59.6b

S3G13 8.5 ± 0.7a 1.04b 2.25b 2.61b 52.5b 49.7b

S4G13 1.3 ± 0.5a 1.42b 2.72b 2.99b 52.4b 56.2b


Fe content (%)





S3G11 < LODc 0.80 ± 0.05 230.5 ± 1.2 6.2 ± 1.1 36.4 ± 5.2 47.0 ± 13.5

S4G11 < LODc 1.04 ± 0.04 279.3 ± 3.5 10.1 ± 4.7 34.2 ± 9.7 44.8 ± 11.4

S5G11 131.3 ± 180.4 0.74 ± 0.08 222.9 ± 21.0 7.3 ± 1.0 42.4 ± 3.8 107.1 ± 47.3

S6G11 0.9 ± 0.1 0.66 ± 0.04 177.8 ± 1.4 5.3 ± 0.5 41.4 ± 3.6 60.7 ± 0.2

S7G11 0.1 ± 0.3 0.63 ± 0.03 179.5 ± 23.1 3.9 ± 1.6 30.5 ± 5.8 54.4 ± 15.5

S8G11 < LODc 0.68 ± 0.07 212.7 ± 6.9 2.9 ± 1.3 25.3 ± 1.4 43.7 ± 2.7

S1G12 4.4 ± 0.3 1.29 ± 0.06 216.7 ± 8.4 20.3 ± 5.8 247.2 ± 270.5 134.2 ± 4.4

S1G13 < LODc 1.92b 141.8b 16.5b 59.0b 81.9b

S2G13 21.1 ± 0.4a 1.82b 221.2b 18.3b 158.9b 140.9b

S3G13 8.5 ± 0.7a 1.81b 145.0b 17.2b 114.2b 115.1b

S4G13 1.3 ± 0.5a 2.34b 126.6b 16.3b 199.0b 84.7b aStandard deviation given, is the instrumental standard deviation since only 1 digestion replicate is analysed. bOnly 1 digestion replicate is analysed

cLOD = 0.175 µg kg-1 Pt (in case of 0.200 g sample)

95

Table A. 5. Overview dry matter content and pH of soil samples

Sample DM (%) pH Sample DM (%) pH S1G1 84.6 7.39 S1G8 85.2 7.48 S1G2 84.3 7.56 S1G9 83.2 7.13 S2G2 86.0 7.36 S1G10 81.7 6.97 S3G2 86.5 7.74 S1G11 83.0 7.12 S4G2 81.0 7.73 S2G11 81.6 7.10 S5G2 88.1 7.89 S3G11 87.6 7.73 S6G2 87.8 7.84 S4G11 87.1 8.11 S7G2 87.7 8.13 S5G11 83.6 7.30 S8G2 90.6 8.81 S6G11 87.5 7.10 S1G3 75.7 7.30 S7G11 85.2 6.92 S1G4 81.8 7.18 S8G11 85.9 7.09 S1G5 77.7 6.74 S1G12 62.1 6.61 S1G6 70.2 6.67 S1G13 86.6 6.85 S2G6 78.2 6.61 S2G13 80.7 5.68 S3G6 88.8 7.64 S3G13 80.6 4.89 S4G6 89.4 7.87 S4G13 88.3 3.72 S1G7 75.2 7.07

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