PhD CARLOS SANCHEZ RODRIGUEZ (Version sin articulos ...

Development of new methodologies based on

ICP techniques for the elemental and isotopic

analysis of bioethanol and related samples

Carlos Sánchez Rodríguez

https://www.ua.es/

http://www.eltallerdigital.com/es/index.html

DEPARTAMENTO DE QUÍMICA ANALÍTICA, NUTRICIÓN Y BROMATOLOGÍA

FACULTAD DE CIENCIAS

UNIVERSIDAD DE ALICANTE

DEVELOPMENT OF NEW METHODOLOGIES BASED ON ICP TECHNIQUES FOR THE ELEMENTAL AND

ISOTOPIC ANALYSIS OF BIOETHANOL AND RELATED SAMPLES

CARLOS SÁNCHEZ RODRÍGUEZ

Tesis presentada para aspirar al grado de

DOCTOR POR LA UNIVERSIDAD DE ALICANTE

MENCIÓN DE DOCTOR INTERNACIONAL

PD CIENCIAS EXPERIMENTALES Y BIOSANITARIAS

Dirigida por:

Prof. Dr. JOSÉ LUIS TODOLÍ TORRÓ

Dr. CHARLES PHILIPPE LIENEMANN

La presente Tesis Doctoral ha sido financiada por el centro de investigación IFP Energies Nouvelles (Lyon, France) y una ayuda para la Formación del Profesorado Universitario

(FPU13/01438) concedida por el Ministerio de Educación, Cultura y Deporte.

Dra. DOÑA MARÍA SOLEDAD PRATS MOYA, directora del Departamento de

Química Analítica, Nutrición y Bromatología de la Facultad de Ciencias de la

Universidad de Alicante

Certifica que,

D. CARLOS SÁNCHEZ RODRÍGUEZ ha realizado, bajo la dirección del profesor

Dr. D. JOSÉ LUIS TODOLÍ TORRÓ (Departamento de Química Analítica,

Nutrición y Bromatología. Universidad de Alicante, Alicante, España) y del Dr.

D. CHARLES PHILIPPE LIENEMANN (IFP Energies Nouvelles, Lyon, Francia), el

trabajo correspondiente a la obtención del Grado de Doctor en Ciencias

Experimentales y Biosanitarias (Mención de Doctor Internacional) titulado

DEVELOPMENT OF NEW METHODOLOGIES BASED ON ICP TECHNIQUES FOR

THE ELEMENTAL AND ISOTOPIC ANALYSIS OF BIOETHANOL AND RELATED

SAMPLES

Alicante, marzo de 2018

Fdo. Dra. María Soledad Prats Moya

El profesor Dr. D. JOSÉ LUIS TODOLÍ TORRÓ (Departamento de Química

Analítica, Nutrición y Bromatología. Universidad de Alicante, Alicante,

España) y el Dr. D. CHARLES PHILIPPE LIENEMANN (IFP Energies Nouvelles,

Lyon, Francia), en calidad de directores de la Tesis Doctoral presentada por

D. CARLOS SÁNCHEZ RODRÍGUEZ, conducente a la obtención del Grado de

Doctor en Ciencias Experimentales y Biosanitarias (Mención de Doctor

I te a io al titulada: DEVELOPMENT OF NEW METHODOLOGIES BASED

ON ICP TECHNIQUES FOR THE ELEMENTAL AND ISOTOPIC ANALYSIS OF

BIOETHANOL AND RELATED SAMPLES

Certifican que,

la citada Tesis Doctoral se ha realizado en los laboratorios del Departamento

de Química Analítica, Nutrición y Bromatología de la Universidad de Alicante,

del centro de investigación IFP Energies Nouvelles y del Departamento de

Química de la Universidad de Gante, y que, a su juicio, reúne los requisitos

necesarios y exigidos en este tipo de trabajos.

Alicante, marzo de 2018

Fdo. Prof. Dr. José Luis Todolí Torró

Fdo. Dr. Charles Philippe Lienemann

A mi familia

AGRADECIMIENTOS /

ACKNOWLEDGEMENTS

El simple hecho de estar escribiendo estas palabras indica que mi Tesis Doctoral está

llegando a su fin, o visto de otro modo, que comienzo una nueva etapa como Doctor que

afronto con tanta ilusión como esta que está a punto de acabar. Este es uno de esos

momentos en los que uno no tiene claro si sentirse feliz, por estar cerca de conseguir algo

por lo que tanto ha trabajado, o triste, porque esta fascinante etapa de mi vida se acaba.

Sin embargo, por encima esa dualidad felicidad-tristeza, destaca otro sentimiento del que

no tengo la menor duda: el agradecimiento. Durante este largo e intenso viaje, he tenido

la suerte de conocer muchas personas sin las que esto no habría sido posible, además de

aquellas que ya conocía mucho antes de encontrarme con la investigación, y que son las

responsables de que hoy esté escribiendo estas palabras. Tengo muy claro que unas

cuantas frases no son suficientes para agradecer tantas cosas como me gustaría y estas

personas merecen, pero permitidme intentarlo.

Me gustaría empezar recordando ese momento, ahora ya lejano, en el que todo comenzó.

Siempre recordaré el día en que un profesor del Departamento de Química Analítica me

preguntó si me interesaba empezar a colaborar en tareas de investigación en mis ratos

li es, pa a e si e at aía este u do . Ese p ofeso , u os años ás ta de, se o i tió

en mi Director de Tesis, al que hoy debo todo lo que se sobre investigación. Muchas

gracias José Luis, no solo por tu constante ayuda, tu inestimable apoyo y tus consejos, sino

por darme la oportunidad de descubrir la investigación. Sin embargo, no solo quisiera

darte las gracias por ser un gran Director de Tesis, sino también por ser un gran

compañero, por haber sido capaz de formarme como científico sin renunciar a pasarlo

bien y reírnos juntos. De ti me llevo un mentor y un amigo, ¡gracias!

During this period, I have also been fortunate to work with Charles Philippe Lienemann.

Thank you, Charles Philippe, for your contribution to this PhD, for transferring me your

knowledge and also for the amazing scientific discussions that we have enjoyed. But I

do ’t a t to a k o ledge o ly fo you a ade i help, si e afte so e of y Tha ks,

Cha les Philippe you told e it’s y o k, I’ just doi g y o k . Ho e e , it as ot

your work our bike rides, badminton matches and other nice moments that we have

shared. Thanks for being, in addition to a great PhD advisor, a great colleague.

I would like to express again my gratitude to my supervisors. José Luis and Charles

Philippe, thank you for giving me the opportunity to be part of this wonderful team where

I always felt that I was one more. For me, you will always be a model to follow to become

a great researcher. It has been a pleasure working with you and I hope to continue doing

it in the future.

Gracias a todos los profesores y profesoras del Departamento de Química Analítica,

Nutrición y Bromatología de la Universidad de Alicante, especialmente a Sole, Raquel y

Salva por vuestro apoyo y por compartir esos cafés y comidas que dan fuerza para

continuar el día. Muchas gracias a todos mis compañeros y compañeras del departamento

con las que he compartido tantas cosas estos años. Gracias también a todos los

estudiantes que de un modo u otro me habéis enseñado cosas y especialmente, Sergio,

Borja, Paula y Claudia, con quien he tenido el placer de trabajar más de cerca.

Me gustaría dar las gracias especialmente a aquellas personas que, además de

compañeros y compañeras de trabajo, se han convertido en amigos y amigas. Phanie,

Águeda, Ángela (y Vicen), Juan Pedro (y Sara), Silvia (y Josemi), gracias por aguantarme

día a día, con lo complicado que eso puede resultar en ciertas ocasiones.

Gracias al resto de amigos y amigas dispersos por el resto de departamentos de Química,

especialmente a Manu, con quien tengo la suerte de compartir vivencias y cafés desde

hace unos 15 años, y a los que me habéis sacado del laboratorio para llevarme de cena,

comida o a una pista de pádel o futbol sala. Gracias también a Mayte y Clemente, por

ayudarme en el ICP-MS y el ICP-OES siempre que lo he necesitado y por permitir que los

Agradecimientos/Acknowledgements

SSTTI sean mi segunda casa. Gracias a Diego por el placer de compartir contigo congresos

y otras experiencias, espero que sean los primeros de muchos.

Y finalmente, para acabar con los amigos que la (bio)Química me ha dado, muchas gracias

a Boby y Aída por esas cenas, que se pasan volando hablando de todo y riéndonos de

todos. Parece ser que las próximas cenas serán en Umeå, pero podéis contar conmigo.

Thanks also to the research center IFPEN. First, for the financial support; and, second,

because during my stays in its laboratories I met amazing people. Thanks to all the

technician of the Physics and Analysis Division for helping me. I would like to thank also

Sylvain Carbonneaux for his support and Fabien Chainet for a lot of good times that we

enjoyed together and your help in Lyon.

I would like to thank also Prof. Frank Vanhaecke and the A&MS research group (Ghent

University) for allowing me to discover other labs, other ways of working and doing

science and for giving me the opportunity of discovering the wonderful world of isotopic

analysis, particularly my office mates (Sara and Lieve) and the Spanish team. Charo, Marta,

Ana y Edu, muchas gracias por la ayuda que, desde el primer día, me brindasteis. Gracias

por la compañía en las largas noches de Neptune, los cafés en el S12 y los grandes ratos

fue a de él. “ois g a des i estigado es, pe o toda ía sois ejo es a igos… y yo te go la

suerte de conocer ambas cosas.

Pero si estoy cerca de ser doctor, no se debe únicamente a los últimos años. Es por ello,

que quiero agradecer a mi familia la inestimable ayuda que me han dado en estos 28 años.

Aunque lo he pensado mucho últimamente, no sé si seré capaz de plasmar en unas

simples palabras todo lo que tengo que agradecer a mis padres, Herminio y Juana. Muchas

gracias a los dos por darme todo sin pedir nada a cambio, por apoyarme en todas mis

decisiones sin cuestionarlas en ningún momento y por haberme formado como persona.

Gracias a mis hermanos, Hermi y Javi, y cuñadas, Mari Carmen y Mayte, por estar siempre

a mi lado disfrutando de los buenos momentos y, sobre todo, pasando los no tan buenos,

por escucharme cuando lo he necesitado. Gracias a todos y todas, simplemente por ser

mi familia. Dicen que la familia no se escoge; y yo digo que, si pudiera escogerla, escogería

exactamente la que tengo.

Puede parecer que me olvido de parte de mi familia, pero en realidad quería guardarles

un párrafo propio. Gracias a mis sobrinos y sobrinas, Javier, Jaime, Carla y Natalia. Sin

saberlo, habéis sido un pilar fundamental de esta Tesis. Gracias a los cuatro por hacerme

sonreír en los malos momentos, por darme esa alegría que lleváis dentro. Vuestras

llamadas por Skype y esos audios de WhatsApp durante las estancias dan ilusión y fuerzas

para seguir adelante.

Y mención especial, y por eso le he reservado el último agradecimiento de mi Tesis,

merece una persona con la que me siento formando un tándem perfecto y me

comprende, en ocasiones sin que diga ni una sola palabra. Gracias Ainhoa, por tu apoyo

incondicional, por apoyarme en todas las decisiones que he tomado durante esta Tesis,

incluso cuando algunas implican estar lejos de ti mucho tiempo. Simplemente, gracias por

estar conmigo siempre. Como tú bien sabes, todo llega.

Por todos estos motivos, y aunque sé que estas palabras no son suficientes para expresar

lo ue ha éis o t i uido a esta Tesis… GRACIAS

For all these reasons, although I know that these words are not enough to express your

o t i utio to this PhD…THANK“

List of contents

i

List of contents

List of acronyms and abbreviatures ................................................................................... vii

List of bioethanol samples ................................................................................................ xiii

List of figures ...................................................................................................................... xv

List of tables ....................................................................................................................... xix

RESUMEN ............................................................................................................................. 1

ABSTRACT ........................................................................................................................... 15

1 Inductively coupled plasma instrumentation ............................................................. 27

1.1 Sample introduction systems .............................................................................. 29

1.1.1 Nebulizers .................................................................................................... 29

1.1.2 Spray chambers ............................................................................................ 32

1.1.3 Special sample introduction systems .......................................................... 36

1.2 Plasma source...................................................................................................... 39

1.3 ICP-OES Perkin Elmer Optima 4300DV. ............................................................... 41

1.3.1 Transfer optics ............................................................................................. 42

1.3.2 Wavelength dispersive device ..................................................................... 43

1.3.3 Detector ....................................................................................................... 44

1.4 ICP-mass spectrometry (ICP-MS). General points............................................... 45

1.4.1 Interface ....................................................................................................... 46

1.4.2 Ion focusing system ..................................................................................... 46

1.4.3 Mass spectrometer ...................................................................................... 47

1.5 ICP-QMS Agilent 7700x ....................................................................................... 48

1.5.1 Collision cell. ................................................................................................ 50

1.5.2 Quadrupole filter ......................................................................................... 53

1.5.3 Detector ....................................................................................................... 55

ii

1.6 MC-ICP-MS Thermo Neptune. ............................................................................. 56

1.6.1 Double-focusing mass spectrometer ........................................................... 57

1.6.2 Detector ....................................................................................................... 60

1.6.3 Removal of interferences in MC-ICP-MS ..................................................... 60

1.6.4 Correction for instrumental mass discrimination ........................................ 61

1.7 References ........................................................................................................... 64

PUBLISHED WORKS / TRABAJOS PUBLICADOS .................................................................. 73

2 Metal and metalloids determination in biodiesel and bioethanol ............................ 75

2.1 Abstract ............................................................................................................... 79

2.2 General Introduction ........................................................................................... 80

2.3 Fundamental studies ........................................................................................... 83

2.3.1 Aerosol generation ...................................................................................... 83

2.3.2 Aerosol transport ......................................................................................... 86

2.3.3 Plasma effects. ............................................................................................. 88

2.3.4 Spectral interferences .................................................................................. 91

2.4 Biodiesel .............................................................................................................. 93

2.4.1 Synthesis and presence of metals. Importance of their determination. .... 94

2.4.2 Analysis by ICP techniques ........................................................................... 96

2.4.3 Analysis by additional techniques .............................................................. 103

2.4.4 Comparison among techniques ................................................................. 121

2.4.5 Standards for the analysis of biodiesel ...................................................... 124

2.5 Bioethanol ......................................................................................................... 126

2.5.1 Synthesis and presence of metals. Importance of their determination. .. 126

2.5.2 Analysis by ICP techniques ......................................................................... 128

2.5.3 Analysis by other techniques ..................................................................... 133

2.5.4 Speciation ................................................................................................... 135

List of contents

iii

2.5.5 Comparison among techniques. ................................................................ 150

2.5.6 Standards for the analysis of bioethanol ................................................... 151

2.6 Conclusions........................................................................................................ 154

2.7 Acknowledgements ........................................................................................... 156

2.8 References ......................................................................................................... 157

3 Metal and metalloid determination in bioethanol through inductively coupled

plasma-optical emission spectroscopy ............................................................................ 183

3.1 Abstract ............................................................................................................. 187

3.2 Introduction....................................................................................................... 188

3.3 Experimental ..................................................................................................... 189

3.3.1 Solutions and samples ............................................................................... 189

3.3.2 Instrumentation ......................................................................................... 191

3.4 Results and discussion ....................................................................................... 192

3.4.1 Drop size distribution ................................................................................. 192

3.4.2 Effect of the sample pre-treatment ........................................................... 193

3.4.3 Effect of hTISIS temperature on sensitivity and matrix effects in segmented

flow injection ............................................................................................................ 194

3.4.4 Effect of hTISIS temperature on sensitivity and matrix effects in continuous

aspiration mode ........................................................................................................ 199

3.4.5 Limits of detection ..................................................................................... 199

3.5 Recovery tests ................................................................................................... 201

3.6 Analysis of real samples .................................................................................... 201

3.6.1 hTISIS-ICP-OES-segmented injection ......................................................... 201

3.6.2 hTISIS-ICP-OES-continuous injection ......................................................... 203

3.6.3 Comparison between continuous and segmented flow injection............. 203

3.7 Conclusions........................................................................................................ 206

iv


3.9 References ......................................................................................................... 208

4 Analysis of bioethanol samples through Inductively Coupled Plasma-Mass

Spectrometry with a total sample consumption system ................................................. 213

4.1 Abstract ............................................................................................................. 217

4.2 Introduction....................................................................................................... 218

4.3 Experimental ..................................................................................................... 219

4.3.1 Solutions and samples ............................................................................... 219

4.3.2 Instrumentation ......................................................................................... 220

4.4 Results and Discussion ...................................................................................... 222

4.4.1 Analyte transport efficiency....................................................................... 222

4.4.2 Analytical figures of merit .......................................................................... 224

4.4.3 Matrix effects caused by ethanol .............................................................. 228

4.4.4 Recovery tests ............................................................................................ 236

4.4.5 Analysis of bioethanol real samples .......................................................... 239

4.5 Conclusions........................................................................................................ 242


4.7 References ......................................................................................................... 243

5 Evolution of the metal and metalloid content along the bioethanol production

process ............................................................................................................................. 247

5.1 Abstract ............................................................................................................. 251

5.2 Introduction....................................................................................................... 252

5.3 Experimental ..................................................................................................... 254

5.3.1 Reagents and standards ............................................................................. 254

5.3.2 Bioethanol production process and samples ............................................ 255

5.3.3 Samples preparation. ................................................................................. 256

List of contents

v

5.3.4 Instrumentation. ........................................................................................ 257

5.3.5 Method validation and samples analysis. .................................................. 259

5.4 Results and discussion. ...................................................................................... 259

5.4.1 Evaluation of the four sample preparation methods. ............................... 259

5.4.2 Analytical figures of merit. ......................................................................... 263

5.4.3 Recovery test. ............................................................................................ 264

5.4.4 Analysis of real samples. Fate of metals and metalloids along the production

process. .................................................................................................................... 265

5.5 Conclusions........................................................................................................ 274


5.7 References ......................................................................................................... 275

6 Direct lead isotopic analysis of bioethanol by means of multi-collector ICP-mass

spectrometry with a total consumption sample introduction system ............................ 279

6.1 Abstract ............................................................................................................. 283

6.2 Introduction....................................................................................................... 285

6.3 Experimental ..................................................................................................... 287

6.3.1 Aqueous standards and certified reference materials .............................. 287

6.3.2 Ethanol-water standards and bioethanol samples .................................... 288

6.3.3 Instrumentation and measurements ......................................................... 289

6.4 Results and discussion ....................................................................................... 292

6.4.1 Effect of sample introduction system and skimmer type on the sensitivity ...

.................................................................................................................... 292

6.4.2 Effect of sample introduction system and skimmer type on the isotope ratio

precision and accuracy ............................................................................................. 294

6.4.3 Effect of sample introduction system and skimmer type on the mass bias

correction. ................................................................................................................ 297

6.4.4 Effect of hTISIS temperature on the mass bias correction ........................ 300

vi

6.4.5 Robustness of the method to real matrices .............................................. 302

6.4.6 Lead isotope ratios in bioethanol .............................................................. 303

6.5 Conclusions........................................................................................................ 305


6.7 References ......................................................................................................... 307

UNPUBLISHED WORKS / TRABAJOS NO PUBLICADOS ..................................................... 313

7 Determination of volatile organic compounds in bioethanol by means of GC-FID and

GC-MS .............................................................................................................................. 315

7.1 Introduction....................................................................................................... 317

7.2 Experimental ..................................................................................................... 319

7.2.1 Gas Chromatography-Flame Ionization Detector (GC-FID) ....................... 319

7.2.2 Gas Chromatography-Mass Spectrometry (GC-MS) .................................. 319

7.2.3 Standards and samples. ............................................................................. 320

7.3 Results ............................................................................................................... 321

7.3.1 Quantification of major volatile compounds in bioethanol real samples by

means of GC-FID ....................................................................................................... 321

7.3.2 Semi-quantitative determination of major, minor and trace volatile

compounds by means of GC-MS .............................................................................. 330

7.4 Conclusions........................................................................................................ 350

7.5 References ......................................................................................................... 352

GENERAL CONCLUSIONS .................................................................................................. 355

CONCLUSIONES GENERALES ............................................................................................ 361

FUTURE STUDIES .............................................................................................................. 367

SCIENTIFIC IMPACT .......................................................................................................... 371

List of acronyms and abbreviatures

vii

List of a ro y s a d a re iatures

α Significance level

AC Alternating current

ASI Air - segmented injection

AAS Atomic absorption spectrometry

AFE Anhydrous fuel ethanol

ANP National Agency of Petroleum

ASTM American Society for Testing and Materials

ASV Anodic stripping voltammetry

BEC Background equivalent concentration

b.p. Boiling point

BTEX Benzene, toluene, ethylbenzene and xylene

CCD Charge - coupled device

CDA Chelidamic acid

CID Charge - injection device

CRI Collision - reaction interface

CRC Collision - reaction cell

CRM Certified reference material

CSA Continuous sample aspiration

CTD Charge - transfer device

CV-AFS Cold vapor - atomic fluorescence spectroscopy

viii

ETAAS Electrothermal atomic absorption spectroscopy

D3,2 Sauter mean diameter

D50 Median of aerosol volume drop size distribution

DC Direct current

DCC Dynamic collision cell

DPA Diphenylamine

DRC Dynamic reaction cell

εn Analyte transport efficiency

Ei First ionization energy

ETAAS Electrothermal atomic absorption spectroscopy

EtOH Ethanol

ETV Electrothermal vaporization

FAAS Flame atomic absorption spectrometry

FAEE Fatty acid ethyl esters

FAES Flame atomic emission spectrometry

FAME Fatty acid methyl esters

GC Gas chromatography

GC-FID Gas chromatography - flame ionization detector

GC-MS Gas chromatography - mass spectrometry

GHG Greenhouse gas

HDPE High-density polyethylene

HFE Hydrated fuel ethanol

HMI High matrix introduction system/device


ix

HPLC High - performance liquid chromatography

HR High resolution

HR-CS-AAS High resolution continuum source graphite furnace atomic

absorption spectrometry

hTISIS High temperature torch integrated sample introduction system

IC Ion chromatography

ICP Inductively coupled plasma

ICP-MS Inductively coupled plasma - mass spectrometry

ICP-MS/MS Inductively coupled plasma - tandem mass spectrometry

ICP-OES Inductively coupled plasma - optical emission spectroscopy

ICP-QMS Inductively coupled plasma - quadrupole mass spectrometry

ICP-QQQ Inductively coupled plasma - triple quadrupole

ICP-SFMS Inductively coupled plasma - sector field mass spectrometry

ICP-TOF-MS Inductively coupled plasma - time of flight - mass spectrometry

ID Isotope dilution

IFPEN Institute Français du Pétrole Energies Nouvelles

IH In - house standard

Ir or Irel Relative intensity

KED Kinetic energy discrimination

LA Laser ablation

LHR Solid lignin hydrolysate residue

LOD Limit of detection

LOQ Limit of quantification

x

LR Low resolution

m/z Mass to charge ratio

MC-IPC-MS Multi-collector - inductively coupled plasma - mass spectrometry

MCN Microconcentric nebulizer

MDL Method detection limit

MIP-OES Microwave induced plasma - optical emission spectroscopy

MR Medium resolution

MTEB Methyl tert-butyl ether

MW Microwave

N or n Number of replicants

ne Electron number density

NAZ Normal analytical zone

NIST National institute for standards and technology

ORS Octopole reaction system

PAR 4-(2-pyridazo)resorcinol

PDA Photodiode array

PFA Perfluoroalkoxy

PP Polypropilene

Ppb Parts per billion

ppm Parts per million

PPN Parallel - path nebulizer

PTFE Polytetrafluoroethylene

QC Quality control


xi

Qg Nebulizer gas flow rate

R Resistivity

R Resolution

Rexp Measured isotope ratio

Rtrue True isotope ratio

RF Radio – frequency

RSD Relative standard deviation

RT Room temperature

Sb or sb Blank standard deviation

SD or s Standard deviation

SF-ICP-MS Sector field - inductively coupled plasma - mass spectrometry

SSB Sample - standard bracketing approach

SSF Simultaneous saccharification and fermentation

T Temperature

TEA Triethylamine

THGA Transversely heated graphite atomizer

TIC Total ions current

TIMS Thermal ionization mass spectrometry

TMAH Tetramethylammonium hydroxide

UNGDA Union Nationale de Groupements de Distillateurs d'Alcool

USN Ultrasonic nebulizer

USN-MD-ICPOES Ultrasonic nebulizer and membrane desolvator inductively

coupled plasma optical emission

xii

v/v volume/volume dilution

VOCs Volatile organic compounds

w/w weight/weight dilution

w/v Weight/volume dilution

Wtot Mass of analyte transported

WCAES Tungsten coil atomic emission spectrometry

List of bioethanol samples

xiii

List of ioetha ol sa ples

Code Sample Description

B1 Wheat Bioethanol from wheat, non-hydrated

B2 Wheat 90% Bioethanol from wheat using Tereos process, 10% water

B3 Additivated Bioethanol additivated, non-hydrated

B4 Sugar cane 1 Bioethanol from sugar cane, hydrated

B5 Wheat 70% Bioethanol from wheat using Tereos process, 30% water

B6 Wheat 96% Bioethanol from wheat, 4% water

B7 Wheat + Beet Bioethanol from mixture of wheat and beet, non-hydrated

B8 Sugar cane 2 Bioethanol from sugar cane, 40% water

B9 Fraction 1 Fraction of distillation 1, sample B29








B17 Wheat 1 Bioethanol non-hydrated from wheat

B18 Wine residue 2 Bioethanol from winemaking residues

B19 Beet 3 Bioethanol from beet 3



xiv

Code Sample Description



B24 Unknown Not available



B27 Sugar cane 3 Bioethanol from sugar cane

B28 Second generation Lignocellulosic bioethanol (2nd generation)

B29 Distilled sample Sample resulting from distillation (B9-B16)

B30 Wine residue Bioethanol from winemaking residues

B31 Cereal Bioethanol from cereal

B32 Beet Bioethanol from beet

B33 A-Glass Bioethanol sample A stored in glass

B34 A-Nalgene® Bioethanol sample A stored in Nalgene®

B35 A-HDPE Bioethanol sample A stored in HDPE

B36 A-PTFE Bioethanol sample A stored in PTFE

B37 B-Glass Bioethanol sample B stored in Glass

B38 B-Nalgene® Bioethanol sample B stored in Nalgene®

B39 B-HDPE Bioethanol sample B stored in HDPE

B40 B-PTFE Bioethanol sample B stored in PTFE

B41 Biobutanol Biobutanol sample



List of figures

xv

List of figures

Figure 1.1. Schemes of the most used pneumatic nebulization devices ........................... 30

Figure 1.2. Detailed scheme of a concentric nebulizer. .................................................... 31

Figure 1.3. Scheme of the aerosol transport phenomena in a sample introduction system

consisting of a concentric nebulizer in combination with a double-pass spray chamber

(Scott) ................................................................................................................................. 33

Figure 1.4.Conventional spray chamber designs ............................................................... 35

Figure 1.5. Schematic description of two commercially available desolvation systems ... 37

Figure 1.6. Scheme (a) and picture (b) of the hTISIS sample introduction system. .......... 38

Figure 1.7. (a) Scheme the of torch, coil and plasma and (b) picture of the plasma

generated in an ICP-MS Agilent 7700x spectrometer. ...................................................... 40

Figure 1.8. Scheme of the optic and detection systems of the ICP-OES Perkin Elmer

4300DV. .............................................................................................................................. 42

Figure 1.9. Plasma viewing modes. (a) Radial or side-on viewing and (b) axial or end-on

viewing. .............................................................................................................................. 43

Figure 1.10. Scheme of the operation principle of a CCD detector ................................... 44

Figure 1.11. General scheme of an ICP-MS instrument..................................................... 45

Figure 1.12. Sampler cone and skimmer ........................................................................... 46

Figure 1.13. Detailed scheme of the ICP-MS Agilent 7700x used in chapters 4 and 5 ...... 49

Figure 1.14. Collision-cell operation principle ................................................................... 53

Figure 1.15. Operation principle of a quadrupole mass filter ........................................... 53

Figure 1.16. The combination of the high-mass (a) and low mass (b) filters resulting the

bandpass filter (c) .............................................................................................................. 55

Figure 1.17. Scheme of the MC-ICP-MS Thermo Neptune used in chapter 6. .................. 57

Figure 1.18. Operation principle of magnetic (a) and electrostatic (b) sectors ................ 58

Figure 1.19. Nier-Johnson double-focusing setup ............................................................. 60

Figure 2.1. Sauter mean diameter (D3,2) for primary aerosols generated by a conventional

pneumatic concentric nebulizer working with 19 different bioethanol samples (A-S). .... 86

xvi

Figure 2.2. Spectral survey of the visible emission from de ICP loaded with methanol for

several observations heights. Cyanide radical (410-430 nm) and diatomic carbon (450-520

nm) ..................................................................................................................................... 92

Figure 2.3. Techniques employed for the determination of several metals in biodiesel

samples and number of studies dealing with the determination of each one of the

elements .......................................................................................................................... 123

Figure 2.4. General flow chart of bioethanol production process from lignocelulosic

biomass (second generation) ........................................................................................... 127

Figure 2.5. Techniques employed for the determination of several metals in bioethanol

samples and number of studies dealing with the determination of each one of the

elements .......................................................................................................................... 151

Figure 2.6. Main elements found in real biodiesel and ethanol fuel samples ................ 155

Figure 3.1. D50 of primary aerosols for solutions containing different percentage in

ethanol ............................................................................................................................. 193

Figure 3.2. Peaks for Mn 257.610 and Ar 420.069 and magnesium ratio in the maximum

of the peak for several water-ethanol mixtures at: (a) room temperature; (b) 200°C; (c)

350°C and (d) 400°C ......................................................................................................... 196

Figure 3.3. Relative intensity under discrete sample injection versus the hTISIS

temperature ..................................................................................................................... 198

Figure 4.1. Analyte mass leaving the spray chamber per unit of time (Wtot) normalized

with respect to that measured when the ethanol concentration is 50% versus hTISIS

temperature. .................................................................................................................... 223

Figure 4.2. Effect of the sample introduction system and hTISIS temperature on the signal.

(a) 55Mn; (b) 111Cd. ........................................................................................................... 225

Figure 4.3. Relative intensity variation (taking the 50% ethanol solution as reference)

versus the hTISIS temperature for two different matrices under the air-segmented

injection mode ................................................................................................................. 229

Figure 4.4. Doubly charged ion (a) and oxide ratios (b) for the two sample introduction

systems and several hTISIS temperatures. Air segmented mode. .................................. 230

Figure 4.5. Effect of the chamber walls temperature on the extent of matrix effects. .. 232

Figure 4.6. ICP-MS radial plasma profiles obtained for two different temperatures and

three different solutions .................................................................................................. 234

List of figures

xvii

Figure 4.7. ICP-MS axial plasma profiles obtained for two different temperatures and three

different solutions ............................................................................................................ 236

Figure 4.8. Recoveries found for four real bioetanol spiked samples ............................. 237

Figure 4.9. Elemental concentrations found for several bioethanol samples following five

different procedures ........................................................................................................ 238

Figure 5.1. Scheme of bioethanol production process studied in the present work. ..... 256

Figure 5.2. Recoveries obtained for twelve spiked samples ........................................... 264

Figure 5.3. Evolution of metals along bioethanol production process from the beginning

until the end of the sampling campaign. Sugar factory 1 ................................................ 268

Figure 5.4. Evolution of major metals along bioethanol production process from the

beginning until the end of the sampling campaign of Sugar factory 2............................ 272

Figure 5.5. Evolution of minor metals along bioethanol production process from the

beginning until the end of the sampling campaign of Sugar factory 2............................ 273

Figure 6.1. Effect of ICP-MS interface (a) and introduction system (b) on the sensitivity293

Figure 6.2. Effect of lead concentration on accuracy and precision (H-type skimmer) .. 296

Figure 6.3. Effect of the matrix composition on the effectiveness of mass bias correction

via a combination of internal correction (based on admixed Tl) and external correction

using a Pb standard solution in 75% ethanol for the different skimmer types and sample

introduction systems under optimum conditions ........................................................... 299

Figure 6.4. Effect of hTISIS temperature on the effectiveness of mass bias correction . 301

Figure 6.5. 208Pb/206Pb ratio obtained for spiked bioethanol and ethanol samples with 5

µg L-1 of IH-Pb ................................................................................................................... 303

Figure 6.6. Three-isotopes plot for bioethanol samples coming from different raw

materials .......................................................................................................................... 305

Figure 7.1. Chromatogram obtained under optimum conditions for the standard

containing 2,000 mg L-1 of ten analytes in ethanol ......................................................... 322

Figure 7.2. Recoveries for three samples spiked with 200 mg L-1 of each analyte ......... 324

Figure 7.3. Effect of the distillation step. Chromatograms obtained for the different

distillation fractions. ........................................................................................................ 327

Figure 7.4. Scheme of the samples analyzed and compounds identified by means of GC-

MS. ................................................................................................................................... 331

xviii

Figure 7.5. Reactions that take place in bioethanol. (a) generation of FAEE from TAG and

ethanol; (b) production of FAEE from fatty acids and ethanol; (c) generation of 1,1-

diethoxyethane from ethanol and acetaldehyde. ........................................................... 333

Figure 7.6. Frequency of identification of each analyte when n 3. ................................ 344

Figure 7.7. Number of compounds found in the samples by GC-MS. ............................. 347

Figure 7.8. Chromatograms obtained for distillation fractions ...................................... 348

Figure 7.9. Chromatograms obtained for different raw materials .................................. 349

Figure A.1. Scheme of future studies………………………………………………………………………….. 6

List of tables

xix

List of ta les

Table 1.1. Comparison of the three types of mass spectrometers used in ICP-MS .......... 48

Table 1.2. Examples of typical interferences in ICP-MS classified by categories.. ............ 51

Table 2.1. Standard specifications and maximum allowable levels of metals and

metalloids........................................................................................................................... 81

Table 2.2. Biodiesel and bioethanol based products CRMs. ............................................. 82

Table 2.3. Density, viscosity and surface tension at 20°C for the different samples. ....... 84

Table 2.4. Summary of the limits of detection and found concentrations obtained in

biodiesel samples by several authors. ............................................................................. 109

Table 2.5. List of standards for the elemental determination of biodiesel samples. ...... 125

Table 2.6. Summary of the limits of detection and found concentrations obtained in fuel

ethanol samples by several authors ................................................................................ 136

Table 2.7. Standards for the elemental determination in ethanol employed for fuel

applications. ..................................................................................................................... 152

Table 3.1. Physical properties for a series of samples with different ethanol content... 190

Table 3.2. ICP-OES operating conditions. ........................................................................ 192

Table 3.3. Limits of detection (ng mL-1) obtained in both Injection methodologies. ...... 200

Table 3.4. Found concentrations (in ng mL-1) in bioethanol real samples through hTISIS-

ICP-OES in segmented flow injection.. ............................................................................. 202

Table 3.5. Found concentrations (in ng mL-1) in bioethanol real samples through hTISIS-

ICP-OES in continuous injection. ...................................................................................... 204

Table 4.1. ICP-MS Agilent 7700x operating conditions. .................................................. 221

Table 4.2. Limits of detection for 50% ethanol/water mixtures and different sample

introduction systems in air-segmented injection mode. ................................................. 226

Table 4.3. Found concentrations (in ng mL-1) in real bioethanol samples by means of the

hTISIS-ICP-MS in continuous aspiration ........................................................................... 240

Table 5.1. ICP-MS operating conditions. .......................................................................... 258

Table 5.2. Main elements concentration (mg kg-1) determined for the CRM DC73349 by

using the four acid assisted digestion protocols evaluated ............................................ 261

xx

Table 5.3. Main elements concentration (mg kg-1) for the CRM SRM 1575a by using the

four acid assisted digestion protocols evaluated ............................................................ 262

Table 5.4. Limits of detection (in mg kg-1) obtained for real samples. ............................ 263

Table 6.1. Conditions used for isotope ratio measurements .......................................... 291

Table 6.2. Internal and external precision ....................................................................... 295

Table 7.1. GC-FID operating conditions and column characteristics. .............................. 319

Table 7.2. GC-MS operating conditions and column characteristics. .............................. 320

Table 7.3. Interday and intraday precisions for a multi-compound standard. ............... 323

Table 7.4. Summary of the analytes found in bioethanol real samples .......................... 325

Table 7.5. Concentrations (in mg L-1) of organic pollutants found in different distillation

fraction ............................................................................................................................. 326

Table 7.6. Concentrations (in mg L-1) of organic pollutants found in samples obtained from

different raw materials .................................................................................................... 329


different raw materials with different water content, second generation bioethanol and

biobutanol ........................................................................................................................ 330

Table 7.8. Alcohols found by GC-MS in the bioethanol samples. .................................... 335

Table 7.9. Aldehydes and ketones found by GC-MS in the bioethanol samples. ............ 336

Table 7.10. Esters found by GC-MS in the bioethanol samples. ...................................... 337

Table 7.11. Ethers found by GC-MS in the bioethanol samples. ..................................... 338

Table 7.12. Hydrocarbons found by GC-MS in the bioethanol samples. ......................... 339

Table 7.13. Aromatic hydrocarbons found by GC-MS in the bioethanol samples. ......... 340

Table 7.14. Nitrogen compounds found by GC-MS in the bioethanol samples. ............. 341

Table 7.15. Organic acids found by GC-MS in the bioethanol samples. .......................... 341

Table 7.16. Furane derivates found by GC-MS in the bioethanol samples. .................... 342

Table 7.17. Other organic compounds found by GC-MS in the bioethanol samples. ..... 342

RESUMEN

Resumen

3

La presente Tesis Doctoral, desarrollada en el Departamento de Química Analítica,

Nutrición y Bromatología de la Universidad de Alicante, en colaboración con el centro de

investigación francés IFP Energies Nouvelles (IFPEN), se centra en el desarrollo de nuevas

metodologías analíticas para el análisis elemental (cuantificación de metales) y el análisis

isotópico de muestras de bioetanol, así como de muestras relacionadas con la producción

y obtención de bioetanol.

Se conoce como bioetanol al etanol que ha sido obtenido a través de la fermentación de

azúcares extraídos de diversas fuentes vegetales mediante el uso de microorganismos.

Este bioetanol es empleado mayoritariamente como combustible, y se enmarcaría dentro

del grupo de fuentes de energía renovables. La fuente de dichos azúcares, empleados

para llevar a cabo la fermentación, puede ser muy variada. Existen dos generaciones de

bioetanol en función de la materia prima empleada. Para la producción de bioetanol de

primera generación, se emplean materias ricas en azúcares fácilmente extraíbles, como

cereales, remolacha, caña de azúcar, etc. Aunque el proceso industrial empleado para la

producción de este tipo de bioetanol es favorable, tanto energéticamente como

económicamente, el bioetanol de primera generación presenta un importante problema

relacionado con la competencia generada entre la producción de bioetanol y la

producción de alimentos para consumo humano. De hecho, algunos autores llegan a

cuestionar el bioetanol como fuente de energía renovable. Como consecuencia, surge el

bioetanol de segunda generación (también conocido como bioetanol lignocelulósico), que

emplea como materia prima residuos de alimentos o partes de vegetales no comestibles,

solucionando de este modo el problema previamente mencionado. Sin embargo, este

proceso proporciona un menor rendimiento, ya que requiere una hidrólisis química y/o

enzimática para transformar azúcares complejos en azúcares simples que puedan

transformarse en etanol durante la fermentación microbiana. Existe una tercera

generación de biocombustibles, que emplea como materia prima algas y otros residuos

del fondo marino. Sin embargo, se trata de una tecnología emergente en vías de

desarrollo que, todavía, no ha sido implementada a escala industrial y, por tanto, el

bioetanol de tercera generación no se encuentra comercialmente disponible.

4

El bioetanol puede ser empleado como combustible directamente (en motores FlexiFuel

modificados para tal fin) o mezclado con gasolina en diferentes proporciones. En este

último caso, el bioetanol se emplea como sustituto de otros compuestos químicos, más

tóxicos que el etanol (por ejemplo, sustituto del etil tert- util éte ETBE , e pleados

para aumentar el contenido en oxígeno de la gasolina y, de este modo, favorecer una

combustión de más eficiente. Cabe desatacar que un motor de combustión no modificado

puede usar hasta E15 (gasolina con un 15% de bioetanol), sin que ello suponga una

alteración de su funcionamiento.

Este biocombustible, junto a otras formas de energía renovables, es considerado un

potencial candidato para sustituir a los combustibles fósiles debido a que su uso conduce

a la emisión de una menor proporción de gases de efecto invernadero. Así, en el caso de

bioetanol de primera generación, se puede reducir dicha emisión hasta en un 66%. Por

tanto, el consumo de bioetanol puede dar solución a corto plazo a otros problemas

medioambientales y de salud, que podrían estar relacionados con el uso masivo de

combustibles derivados del petróleo. Estos motivos, junto a la disminución de reservas de

petróleo en el planeta (algunos estudios indican que las existencias de petróleo pueden

agotarse en un plazo de unos 50 años), han propiciado que el uso y producción de

bioetanol haya aumentado de forma muy notable durante los últimos 20 años, así como

el número de investigaciones dedicadas al desarrollo de métodos de producción de

bioetanol usando nuevas materias primas y/o nuevos microorganismos.

Obviamente, los desarrollos mencionados deben estar ligados al diseño e implementación

de nuevos métodos de análisis para llevar a cabo el control de calidad de estos

biocombustibles. Sin embargo, al contrario que en el caso de los combustibles fósiles, los

métodos de análisis oficiales recogidos en la legislación europea están limitados a la

evaluación de ciertos parámetros globales (por ejemplo, contenido en agua, pH, acidez

total o conductividad). No obstante, el bioetanol puede contener tanto compuestos

orgánicos como inorgánicos que alteren su calidad y, por tanto, su uso como combustible.

En el caso de contaminantes orgánicos, destacan los compuestos volátiles por su efecto

negativo en el medio ambiente cuando son emitidos a la atmósfera. Entre los compuestos

inorgánicos destacan metales y metaloides, que son de especial interés ya que algunos de

estos elementos pueden tener efectos perjudiciales para el medioambiente, así como la

Resumen

5

salud humana, incluso en muy bajas concentraciones (niveles inferiores a las partes por

billón). Además, algunos metales y metaloides pueden dañar los motores de combustión.

Adicionalmente, cabe destacar que el análisis isotópico de bioetanol podría proporcionar

información útil sobre el tipo de materia prima empleada para su producción, así como el

origen geográfico del mismo. Hasta el momento no se conoce ningún intento por efectuar

este tipo de análisis en bioetanol.

Por todos los motivos expuestos anteriormente, la presente Tesis Doctoral tiene como

principales objetivos los que se enumeran a continuación:

1. Desarrollo de nuevos métodos de análisis para la determinación de metales en

muestras de bioetanol mediante técnicas de plasma acoplado por inducción (ICP, del

inglés Inductively Coupled Plasma). Dichos métodos deben proporcionar menores

límites de detección que los métodos ya existentes y reducir los efectos de memoria.

Sin embargo, el aspecto más relevante es la obtención de resultados exactos para lo

cual se debe proceder a la eliminación de los efectos de matriz causados por

diferencias en la composición de muestras de bioetanol.

2. En el caso de que los metales de interés se encuentren en concentraciones

cuantificables (> LOQ), establecer la procedencia de dichos metales a través del

análisis de muestras tomadas a lo largo del proceso de producción de bioetanol.

3. Desarrollar un nuevo método analítico para llevar a cabo, por primera vez, la

determinación de relaciones isotópicas de plomo en bioetanol que proporcionen

información acerca del material de partida y origen geográfico de las muestras.

4. Adicionalmente, se establece como objetivo de esta Tesis Doctoral la identificación y

cuantificación de compuestos orgánicos volátiles mediante el uso de cromatografía de

gases acoplada a diferentes detectores. Por una parte, estos compuestos orgánicos

son contaminantes y, por otra, su presencia como parte de la matriz de la muestra

condiciona el desarrollo de métodos analíticos basados en ICP para el análisis

elemental e isotópico de muestras de bioetanol.

Todos estos objetivos, los métodos experimentales para llevarlos a cabo, así como los

resultados y conclusiones más relevantes derivados de cada uno de ellos, se presentan de

6

forma detallada en siete capítulos estrechamente relacionados. De estos siete capítulos,

los dos primeros consideran aspectos introductorios necesarios para la comprensión del

estado de la temática desde un punto de vista analítico, dejando entrever problemáticas

de tipo industrial y medioambiental. Los capítulos 3 y 4 se consagran a la consecución del

primero de los objetivos propuestos anteriormente. Los capítulos 5 y 6 centran su

atención en los objetivos 2 y 3, respectivamente. Finalmente, el cuarto y último objetivo

se desarrolla íntegramente en el capítulo 7. Los capítulos comprendidos desde el 2 al 6

han sido publicados en diferentes revistas indexadas en el JCR del primer cuartil del área,

mientras que los resultados presentados en el capítulo 7 serán próximamente enviados

para su publicación.

CAPÍTULO 1. Espectrometría de Plasma Acoplado por Inducción.

En el capítulo 1 se presenta la instrumentación que, en la actualidad, es frecuentemente

utilizada para llevar a cabo el análisis elemental e isotópico de un gran número de

muestras. A lo largo del mismo se detallan las diferentes partes de un equipo de

espectroscopía de emisión óptica con fuente de plasma acoplado inductivamente (ICP-

OES) y espectrometría de masas con fuente de plasma acoplado inductivamente (ICP-MS).

Dentro de este segundo grupo de instrumentos, se hace un análisis detallado de dos tipos

de ICP-MS. Estos equipos incorporan, como analizador de masas, un cuadrupolo (ICP-

QMS) y un analizador de doble enfoque (sector eléctrico-sector magnético) acoplado a un

detector múltiple y simultáneo (MC-ICP-MS).

En primer lugar, se discute de forma pormenorizada aquellos elementos que son comunes

a todos los instrumentos basados en ICP. En esta primera parte del capítulo, se hace una

revisión de los diferentes sistemas de introducción de muestras líquidas (nebulizador +

cámara de nebulización) comúnmente empleados para llevar la muestra líquida, a un

caudal constante, hasta el plasma en forma de aerosol fino y monodisperso. Asimismo, se

describen los fenómenos de transporte que tienen lugar en dichos sistemas de

introducción de muestras. Posteriormente, se detalla cómo se genera el plasma y los

procesos que sufre la muestra cuando se introduce en el mismo.

Resumen

7

En segundo lugar, se discuten los detalles de cada uno de los equipos empleados en cada

técnica de forma detallada (ICP-OES, ICP-QMS y MC-ICP-MS). En cada uno de estos

apartados se describen los elementos dedicados a separar la radiación (ICP-OES) o a

seleccionar las masas de interés (ICP-MS), así como los diferentes detectores utilizados en

cada uno de los instrumentos usados en la presente Tesis Doctoral.

CAPÍTULO 2. Determinación de metales y metaloides en bioetanol y biodiesel

El segundo capítulo tiene como principal objetivo hacer una revisión exhaustiva de los

métodos desarrollados para la determinación de metales y metaloides en

biocombustibles (bioetanol y biodiesel) previos a la presente Tesis Doctoral.

En una primera sección, cuyas conclusiones son aplicables para ambos biocombustibles,

se discuten los efectos que una matriz orgánica tiene sobre los fenómenos de transporte

que ocurren en el sistema de introducción de muestras y los efectos que la carga de

disolvente orgánico tiene sobre el plasma. Entre ellos, se pueden citar: (i) generación de

remolinos; (ii) modificaciones de la densidad de electrones, densidad de hidrógeno y

temperatura de excitación; (iii) cambios en la geometría del plasma; (iv) emisión

molecular de productos de pirólisis del disolvente; y, (v) formación de depósitos de

carbonilla en diferentes partes del espectrómetro (principalmente en el inyector, en ICP-

OES e ICP-MS, y en los conos de la interfaz, en el caso de ICP-MS). Además, las diferentes

interferencias espectrales que pueden ser ocasionadas por la introducción de muestras

orgánicas en el plasma son descritas en esta primera parte del capítulo.

Posteriormente, se tratan en detalle los diferentes métodos desarrollados para el análisis

de biodiesel y bioetanol. En ambos casos, se menciona la importancia de llevar a cabo la

determinación de metales y metaloides en biocombustibles, como parte del control de

calidad de los mismos y, a continuación, se hace una revisión exhaustiva de los métodos

de análisis existentes basados tanto en ICP como en otras técnicas analíticas, así como los

métodos de preparación de muestra y calibrado más empleados en dichas técnicas y

métodos.

8

Tal y como se ha comentado previamente, la determinación de metales y metaloides en

bioetanol es importante debido a los efectos negativos que estos pueden causar sobre la

salud, el medio ambiente y el funcionamiento de los motores de combustión. Sin

embargo, desde el punto de vista analítico, la determinación de metales y metaloides en

matrices orgánicas en general, y en bioetanol en particular, es un reto debido a: (i) los

efectos de matriz (interferencias no espectrales) causados por la introducción de matrices

orgánicas. Cabe remarcar que, contrariamente a lo que cabría esperar, el bioetanol puede

poseer una matriz compleja compuesta por diversos productos orgánicos, así como agua

en proporciones significativas; (ii) la introducción de matrices orgánicas puede deteriorar

la estabilidad del plasma; (iii) la concentración de algunos metales y metaloides en estos

productos puede ser muy baja (niveles del orden o inferiores a los ng mL-1). A pesar de

ello, esas concentraciones son suficientes para causar los efectos negativos previamente

descritos; (iv) no existen materiales de referencia con los que validar los métodos

desarrollados.

Por todos estos motivos, y tras una revisión de los métodos existentes, se concluye que

se requiere un trabajo importante en el desarrollo de nuevos métodos para el análisis

elemental de bioetanol, con el principal objetivo de eliminar o mitigar los efectos de

matriz y mejorar la sensibilidad de los métodos existentes, lo cual se traduciría en una

mejora de los límites de detección (LOD). En este sentido, el estudio de nuevos sistemas

de introducción de muestras en ICP se plantea como una opción interesante.

CAPÍTULO 3. Determinación de metales y metaloides en bioetanol mediante ICP-OES.

En el capítulo 3 de la presente Tesis Doctoral se presenta el desarrollo de un nuevo

método para llevar a cabo la determinación de metales en muestras de bioetanol

mediante el uso de un sistema de consumo total de muestra, llamado hTISIS (high

temperautre Torch Integrated Sample Introduction System), desarrollado en el grupo de

investigación donde se ha realizado la Tesis Doctoral, acoplado a ICP-OES. Este sistema,

que consiste en una cámara de paso simple calentada, se ha empleado en sus dos modos

de introducción de muestra: (i) aspiración continua a un caudal líquido de 25 µL min-1; y

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9

(ii) inyección segmentada de 5 µL de muestra (ambos descrito en el capítulo 1). Su uso a

400°C y 200°C en inyección segmentada y aspiración continua, respectivamente, permite

alcanzar una eficiencia de transporte de analito cercana al 100% para todas las matrices

objeto de estudio y, por tanto, eliminar las interferencias provocadas por diferencias de

composición de matrices formadas por mezclas de etanol y agua. La validación del método

se llevó a cabo mediante la obtención de la recuperación, a través del análisis de cuatro

muestras reales dopadas con los analitos de interés, obteniéndose en todos los casos

valores entre 80% y 120%. Además, se realizó la comparación de las concentraciones

obtenidas mediante este método frente a las obtenidas para las mismas muestras a través

de un método basado en la evaporación a sequedad de la muestra seguido de la

redisolución de residuo resultante en un pequeño volumen de agua. Ambos métodos

suministraron valores concordantes. Tras la optimización del método, se analizaron

mediante calibración externa 28 muestras reales de bioetanol con contenido en etanol

entre 55% y 100%. El método de cuantificación estuvo basado en el calibrado externo

empleando una serie de patrones multielementales preparados en una mezcla de etanol

y agua en igual proporción. Los límites de detección (LOD) obtenidos oscilaron entre 3 ng

mL-1 para Mn y 500 ng mL-1 para Ca. Por tanto, haciendo uso de este método pueden

cuantificarse, de manera exacta y precisa, aquellos elementos mayoritarios y minoritarios

presentes en muestras de bioetanol. Sin embargo, no es posible llevar a cabo la

cuantificación de aquellos metales y metaloides presentes en niveles traza. Por ese

motivo, se trató de extender el uso de este sistema de introducción de muestras

acoplándolo a ICP-MS, ya que es una técnica más sensible que ICP-OES.

CAPÍTULO 4. Análisis de muestras de bioetanol mediante ICP-MS usando un sistema de

consumo total de muestra.

Como se ha anticipado, en el capítulo 4, se acopló el sistema de introducción de muestras

hTISIS a un ICP-MS para la cuantificación de metales y metaloides en bioetanol,

focalizándose el estudio sobre los elementos traza. De igual modo que en el capítulo 3, el

primer objetivo era la optimización del método en términos de exactitud y sensibilidad.

Por lo tanto, se buscó eliminar los efectos de matriz causados por la presencia de etanol

10

consiguiendo, al mismo tiempo, la mayor sensibilidad posible. En el caso de ICP-MS, las

concentraciones de etanol varían desde 0% al 50%, ya que concentraciones de etanol

superiores causan la formación de depósitos de carbonilla en los conos de la interfaz. Bajo

estas condiciones, se estudió el efecto de la temperatura del sistema hTISIS sobre la

sensibilidad y los efectos de matriz, tanto en modo de aspiración continua de la muestra

como en modo discontinuo. Se obtuvo un máximo de sensibilidad entre 100°C y 200°C,

dependiendo de la matriz. Sin embargo, al contrario de lo observado en ICP-OES, un

aumento de la temperatura no fue suficiente para eliminar los efectos de matriz causados

por el etanol. Este efecto extra no estuvo ligado a modificaciones en los fenómenos de

transporte de aerosol en la cámara, puesto que la eficiencia de transporte de analito fue

independiente de la composición de la matriz para temperaturas 300°C. Por contra, se

demostró que se producía un cambio de la distribución de iones en el plasma en función

de la matriz y la temperatura de la cámara. Por tanto, usando el sistema hTISIS a 300°C,

fue necesario modificar en 1 mm la posición relativa de la antorcha con respecto al cono

de muestreo de iones (sampling cone) del acoplamiento para eliminar totalmente los

efectos de matriz. Bajo estas condiciones, todas las matrices estudiadas proporcionaron

la misma sensibilidad. De manera análoga al procedimiento empleado en el capítulo 3, la

validación del método se llevó a cabo mediante la obtención de recuperaciones en

muestras reales dopadas. Finalmente, utilizando el método de análisis directo optimizado,

se analizaron 28 muestras reales de bioetanol tras realizar una dilución 1:1, usando

patrones preparados en un 50% de etanol. Los LODs obtenidos oscilaron entre 0.014 ng

mL-1 para Co y 5 ng mL-1 para Na. Estos LODs mejoraron los obtenidos mediante ICP-OES

en un factor promedio próximo a los dos órdenes de magnitud, siendo posible la

cuantificación de los metales traza presentes en las muestras.

En los capítulos 3 y 4 se ha llevado a cabo la determinación de metales y metaloides en

muestras reales de bioetanol y ha sido posible la cuantificación de 16 elementos en

diferentes muestras, en concentraciones entre 1 ng mL-1 y 2 µg mL-1. Sin embargo, no

existen datos sobre el origen de estos metales. Como posibles fuentes destacan la materia

prima, el proceso de producción de bioetanol, así como su almacenamiento y/o

transporte.

Resumen

11

CAPÍTULO 5. Evolución del contenido en metales y metaloides a lo largo del proceso de

obtención de bioetanol.

En el capítulo 5 de la presente Tesis Doctoral, se ha llevado a cabo la determinación de

metales y metaloides, mediante ICP-MS, en: muestras de bioetanol, los materiales de

partida empleados para su obtención y muestras tomadas en diferentes puntos críticos a

lo largo del proceso de producción. De este modo, se ha estudiado la evolución del

contenido en metales y metaloides a lo largo del proceso de obtención de bioetanol,

siendo posible establecer el origen de los elementos cuantificados en el producto final.

Además, se han identificado claramente las etapas del proceso donde estos metales y

metaloides son eliminados o incorporados/acumulados en el biocombustible.

Para llevar a cabo este estudio se han comparado 4 tratamientos de muestra diferentes,

para lo que se han empleado dos materiales de referencia certificados. Los resultados

mostraron que el tratamiento más adecuado es la digestión asistida por microondas

usando ácido nítrico ultrapuro. Bajo estas condiciones, las recuperaciones variaron entre

el 90% y el 110%. Además, los bajos LODs obtenidos permitieron cuantificar los elementos

de interés con una buena precisión tanto a corto como a largo plazo.

Se han estudiado dos líneas de producción diferentes basadas en el empleo de dos

materiales de partida provenientes de dos regiones diferentes de la geografía francesa.

Los resultados muestran que hay ligeras diferencias en las concentraciones de elementos

minoritarios en función de la biomasa empleada en ambas líneas de producción. Por otra

parte, las concentraciones de elementos mayoritarios no difieren significativamente para

las dos fuentes de bioetanol. El material de partida, del cual se extraen los azúcares, ha

sido identificado como la fuente más importante de metales en el producto final. La etapa

de destilación provoca una disminución de entre 1000 y 10000 veces en el contenido de

metales y metaloides en el bioetanol final, por lo que la concentración de estos metales

es menor del 0.01% de las concentraciones presentes en la biomasa empleada para su

producción.

12

CAPÍTULO 6. Determinación directa de la relación isotópica de plomo en bioetanol

mediante MC-ICP-MS utilizando un sistema de consumo total de muestra.

De acuerdo con los resultados obtenidos en el capítulo 5, la principal fuente de metales

presentes en bioetanol es el material empleado para su obtención. Por tanto, el análisis

isotópico de metales en muestras de bioetanol puede resultar de especial interés para

obtener información sobre el material de partida. Los elementos a considerar son aquellos

susceptibles de sufrir fraccionamiento ya que alguno de sus isótopos es radiogénico (por

ejemplo, Sr o Pb). Así, este procedimiento puede resultar de gran utilidad para la

discriminación entre bioetanol de primera y segunda generación o con objeto de obtener

información sobre la localización geográfica de dicho material.

En el capítulo 6 se desarrolla un método para el análisis isotópico de plomo de forma

directa, sin preparación previa de la muestra y sin separación del analito y la matriz, en

muestras de bioetanol usando el sistema de consumo total de muestra hTISIS acoplado a

MC-ICP-MS. Los estudios se han llevado a cabo en el grupo Atomic & Mass Spectrometry

de la Universidad de Gante en colaboración con el Profesor Frank Vanhaecke, durante una

estancia de 7 meses. Los resultados obtenidos con el sistema hTISIS se compararon con

los obtenidos con un sistema de introducción de muestras convencional. Además, se han

evaluado dos conos del acoplamiento ICP-MS diferentes: un skimmer tipo H y un skimmer

tipo X. La sensibilidad alcanzada por el sistema hTISIS fue entre 3 y 7.5 veces superior a la

obtenida con el sistema convencional, mientras que el skimmer tipo X proporcionó los

mejores resultados. La combinación hTISIS + skimmer tipo X permitió llevar a cabo la

determinación de relaciones de intensidades para los pares de isótopos 208Pb/207Pb y

208Pb/206Pb en concentraciones de hasta 2 ng mL-1 sin degradar la precisión (0.007% -

0.008% para ambas relaciones isotópicas).

El efecto del contenido en etanol y la temperatura del sistema hTISIS en la discriminación

en masa ha sido evaluado para las cuatro combinaciones, sistema de introducción de

muestra + skimmer, posibles. Para la corrección de la discriminación en masa, se empleó

la corrección interna usando un patrón certificado en la composición isotópica de Tl (NIST

997) seguida de la corrección mediante sample-standard bracketing (SSB) con otro patrón

certificado en la composición isotópica de Pb (NIST 981) preparado en una matriz

Resumen

13

previamente fijada conteniendo un 75% de etanol. En el método de corrección SSB, se

mide una secuencia patrón - muestra - patrón, donde la muestra se corrige con el patrón

anterior y posterior, para corregir una posible deriva instrumental. A pesar de que las

muestras de bioetanol poseían diferente concentración de agua, el método descrito fue

adecuado para la corrección de la discriminación en masa para matrices con un contenido

en agua de entre un 0% y 40%. Por lo tanto, también fue apta para el análisis isotópico de

muestras de bioetanol. Estos estudios se efectuaron empleando el sistema de

introducción de muestras hTISIS a 125°C y un skimmer tipo X.

La robustez del método frente a cambios en la matriz fue comprobada mediante el análisis

isotópico de muestras de bioetanol dopadas con un patrón de plomo isotópicamente

caracterizado. Finalmente, se analizaron 6 muestras reales de bioetanol de diferente

procedencia y se obtuvieron diferencias significativas en las relaciones isotópicas de

plomo, abriendo una puerta al análisis isotópico directo de muestras de biocombustibles

y otras matrices orgánicas.

CAPÍTULO 7. Determinación de compuestos orgánicos en muestras de bioetanol

mediante GC-FID y GC-MS.

Como se ha indicado a lo largo del presente resumen, la presente Tesis Doctoral se

consagra, principalmente, al análisis elemental e isotópico de muestras de bioetanol y

muestras tomadas a lo largo del proceso de producción de bioetanol. Sin embargo, como

objetivo paralelo se establece la determinación de compuestos orgánicos volátiles con

dos fines: (i) enumerar los compuestos orgánicos presentes en las muestras, que pueden

ser contaminantes; y (ii) conocer en detalle las matrices de las muestras de bioetanol, ya

que estos componentes orgánicos que forman parte de la matriz pueden tener un efecto

en los métodos desarrollados en ICP.

Para llevar a cabo esta determinación se han optimizado dos métodos basados en el uso

de cromatografía de gases con detector de ionización en llama (GC-FID) para la

identificación de los componentes mayoritarios y acoplamiento GC – espectrometría de

masas (GC-MS) para la determinación de componentes minoritarios y trazas. Se han

14

identificado un total de 130 compuestos orgánicos diferentes en 41 muestras de bioetanol

en concentraciones que varían desde pocos µg L-1 hasta más de 10 g L-1.

Además, se ha estudiado el efecto de la etapa de destilación, el material de almacenado

y el tipo de biomasa empleada para la producción y la generación de combustible sobre

el perfil de contaminantes orgánicos de las muestras.

Estos siete capítulos suponen una actualización de los métodos de análisis de bioetanol y

muestras relacionadas, especialmente de aquellos métodos para el análisis elemental e

isotópico de este tipo de muestras. Además, se ha llevado a cabo una caracterización

exhaustiva de diversas muestras de bioetanol haciendo uso de los métodos desarrollados

y optimizados previamente, que hasta la fecha no habían recibido especial atención, a

pesar de estar comercialmente disponibles y encontrarse su uso en pleno auge.

ABSTRACT

Abstract

17

The present PhD, carried out at the Department of Analytical Chemistry, Nutrition and

Food Sciences at University of Alicante, in collaboration with the French research center

IFP Energies Nouvelles (IFPEN), is focused on the development of new analytical methods

for the elemental analysis, as well as the isotopic analysis of bioethanol and samples

related with its production.

Bioethanol corresponds to ethanol obtained through microorganism-based fermentation

of sugars extracted from diverse sources. This product is mainly used as a fuel and it is

considered as a renewable energy source. There are two generations of bioethanol,

depending on the type of raw material: First-generation bioethanol is obtained from foods

such as cereals, beet and sugar cane that contain high concentrations of easily extractable

sugars. Although the industrial process used for producing first-generation bioethanol is

efficient, both economically and energetically, fuel-food competition phenomenon has

been claimed to be a drawback of this product. The second-generation bioethanol (also

called lignocellulosic bioethanol), produced using biomass corresponding to non-edible

food crop production, appears to overcome the fuel-food competition problem. However,

its synthesis involves previous chemical and/or enzymatic hydrolysis steps in order to

transform complex sugars into mono and disaccharides. There also exists a third

generation of biofuels, based on the use of algae as raw material. However, this is still an

emerging technology that has not been industrially implemented yet.

Bioethanol can be used in its pure form within modified spark-ignition (Flex-Fuel) engines

or blended with petroleum distillates at different ratios. Indeed, it acts as an efficient

octane-boosting agent, thereby replacing chemical additives such as methyl tert-butyl

ether (MTBE). It should be noted that current non-modified engines are compatible with

up to E15 (gasoline containing 15% of ethanol).

This biofuel is considered to be a good candidate to replace the fossil fuels because its

combustion lowers the amount of greenhouse gas (GHG) emissions. In the case of first-

generation bioethanol, the emission of GHG can be reduced up to a 66% as compared to

fossil fuels. Therefore, bioethanol would mitigate some environmental and health

problems that can be related with the widespread use of petroleum derivates. These

reasons, combined with the fact that, according to some studies, petroleum stocks will be

18

depleted in about 50 years, have led to a significant growing of the bioethanol use and

production during the last decades. As a result, the number of studies focused on the

development of new production processes, using new raw materials and/or new

microorganisms, have also increased considerably.

Obviously, the growing demand for bioethanol and emerging production technologies

should be linked to the development and implementation of new analytical methods to

control the quality of these biofuels. However, the official methods of bioethanol analysis

incorporated in the current European legislation are limited to some global parameters

(e.g., water content, pH, total acidity or conductivity). It is interesting to mention that

bioethanol may contain additional organic as well as inorganic compounds, leading to a

deterioration of its quality. Regarding organic pollutants, volatile organic compounds

(VOCs) should be monitored, among others, due to the negative impact caused by their

emission into the atmosphere. Among the inorganic pollutants, metals and metalloids are

of particular interest because some of them cause environmental pollution and risks to

the human health, even at very low concentrations (levels below ng mL-1). Moreover,

some metals and metalloids may cause engine damages.

Additionally, isotopic analysis of bioethanol could provide valuable information about the

kind and the provenance of the raw materials used for its production. It should be noted

that studies related with isotope ratios determination in bioethanol have not been

reported to date.

For all the reasons mentioned above, the present PhD has four main objectives:

1. Development of new analytical methods to perform the determination of metals in

bioethanol samples through Inductively Coupled Plasma (ICP) techniques. The novel

methods should provide lower limits of detection and higher sample throughputs than

the existing ones. More importantly, accurate results must be obtained. For this

purpose, the removal of matrix effects caused by the different composition of

bioethanol samples is of capital importance.

Abstract

19

2. In the case of the metals found at measurable levels (>LOQ), the second objective

would be to establish the origin of these metals by means of the analysis of samples

taken throughout the bioethanol production process.

3. Development of a new analytical method to carry out, for the first time, the

determination of lead isotope ratios in bioethanol with the goal of providing

information about the raw material and the geographical provenance of the samples.

4. Identification and quantification of volatile organic compounds in bioethanol through

gas chromatography. This study is of great importance because of two main reasons:

(i) there is a need for characterizing the organic pollutants in bioethanol; and, (ii) their

presence as constituents of the sample matrix may induce ICP interferences leading

to a degradation in the accuracy of the methods for metals determination.

The experimental methods, as well as the results and main conclusions drawn are deeply

discussed in seven chapters closely interrelated. The first two chapters focus on the state

of the art of analytical methods for the elemental analysis of biofuels. Chapters 3 and 4

report on the development of novel ICP based methods for bioethanol elemental analysis

(objective 1). Chapter 5 deals with the link between elemental content and bioethanol

production process (objective 2). The development and implementation of a new method

for bioethanol isotope ratios measurement is described in chapter 6 (goal 3). Finally,

chapter 7 considers the determination of organic pollutants in bioethanol (objective 4).

Chapters 2 - 6 have been published in Q1 JCR indexed journals, whereas the results

reported in chapter 7 will be submitted, in the near future, for publication.

CHAPTER 1. Inductively Coupled Plasma Instrumentation.

Chapter 1 gives an overview of the instrumentation typically used to carry out the

elemental and isotopic analysis of a wide variety of samples. Along this chapter, the

different components of Inductively Coupled Plasma-Optical Emission Spectroscopy (ICP-

OES) and Inductively Coupled Plasma-Mass Spectrometry (ICP-MS) spectrometers are

presented. Within the latest group, a description of two types of ICP-MS instruments is

done. These instruments incorporate as mass analyzer: (i) a quadrupole (ICP-QMS); and,

20

(ii) a double-focusing mass spectrometer (sector field-magnetic sector) coupled to a

multiple collector (MC-ICP-MS).

Firstly, a description of common liquid sample introduction systems (nebulizer + spray

chamber) frequently used to deliver the sample to the plasma is done. Transport

phenomena taking place in the introduction system as well as processes occurring within

the plasma are also detailed.

Secondly, the ICP-OES, ICP-QMS and MC-ICP-MS spectrometers used in the present work

are described. Attention is paid to the optical components (ICP-OES) as well as the mass

analyzers (ICP-MS). Finally, the typical detectors used in each specific instrument are

briefly addressed.

CHAPTER 2. Determination of metals and metalloids in bioethanol and biodiesel.

The second chapter corresponds to a critical review of the existing methods dedicated to

the determination of metals and metalloids in biofuels (bioethanol and biodiesel).

In a first section, the effects of an organic matrix on transport phenomena, taking place in

the sample introduction system, and the plasma thermal characteristics are deeply

discussed. The following plasma related effects can be highlighted: (i) vortex generation;

(ii) changes in electron number density, hydrogen density and excitation temperature; (iii)

modifications on the plasma geometry, (iv) molecular emission of solvent pyrolysis

products; and, (v) formation of carbon or soot deposits somewhere in the spectrometer

(mainly in the injector, in ICP-OES, and the interface cones, in ICP-MS). Moreover, the

spectral interferences caused by organic samples are described in this first part of the

chapter.

The different methods developed for the analysis of biodiesel and bioethanol are

described in detail pointing out the importance of the determination of metals and

metalloids in biofuels, as a part of their quality control. After that, an exhaustive review

of the sample preparation and calibration methods for biofuel ICP elemental analysis is

done.

Abstract

21

As it has been previously mentioned, the determination of metals and metalloids in

bioethanol is important due to the adverse effects that they may cause, even at low

concentrations, on the human health, the environment and the engine performance.

Nevertheless, from an analytical point of view, the determination of metals and metalloids

in bioethanol is still a challenge due to: (i) the matrix effects (non-spectral interferences).

It should be noted that, in contrast to what could be expected, bioethanol has a complex

matrix composed by diverse organic compounds and significant concentrations of water;

(ii) the plasma degradation caused by the presence of organic species; (iii) the low

concentrations of some metals and metalloids in these products (< ng mL-1); and, (iv) the

lack of certified reference materials (CRMs) to validate the methods developed.

After critically reviewing the exiting methods, it was concluded that the development of

accurate and sensitive methods for the elemental analysis of bioethanol is still needed.

The main goals are, therefore, the removal or mitigation of matrix effects and the

enhancement of the sensitivity, with the subsequent lowering of limits of detection (LOD).

In this sense, the application of efficient sample introduction systems in ICP appears to be

a key issue.

CHAPTER 3. Metal and metalloid determination in bioethanol through inductively

coupled plasma-optical emission spectroscopy.

A new method to carry out the determination of metals in bioethanol samples has been

developed using a total sample consumption system developed by our research group, so

called hTISIS (high temperature Torch Integrated Sample Introduction System), coupled

to ICP-OES.

This sample introduction system, which consists in a heated single pass spray chamber,

has been used under two different injection modes; (i) continuous sample aspiration (CSA)

at 25 µL min-1; and, (ii) air-segmented flow injection (ASI) analysis of 5 µL of sample. The

use of the hTISIS at 400°C and 200°C in air-segmented flow injection and continuous

sample aspiration, respectively, provides an analyte transport efficiency of virtually 100%

regardless the sample matrix. Therefore, this system is able to remove the interferences

22

caused by changes in the ethanol content. The method validation was performed by

measuring the recoveries obtained for four spiked bioethanol real samples. The obtained

values went from 80% to 120% in all the cases. Moreover, the measured elemental

concentrations were compared to those encountered with a method based on the total

evaporation of the sample and the redissolution of the resulting residue in a lower volume

of water. The concentrations provided by both methods did not differed significantly.

After the method optimization, twenty-eight bioethanol real samples with ethanol

content between 55% and 100% were analyzed by means of external calibration. The

calibration method was relied on the use of standards containing ethanol and water (1:1).

Limits of detection ranged from 3 ng mL-1 for Mn to about 500 ng mL-1 for Ca. Therefore,

major and minor elements present in bioethanol samples were accurately and precisely

determined using the hTISIS with external calibration. However, it was not possible to

carry out the quantification of trace elements. For this reason, the next step was to extend

the use of the hTISIS to ICP-MS, since this technique provides lower LODs than ICP-OES.

CHAPTER 4. Analysis of bioethanol samples through Inductively Coupled Plasma Mass

Spectrometry with a total sample consumption system.

The hTISIS has been coupled to ICP-MS for the quantification of metals and metalloids in

bioethanol. The first objective was the optimization of the method in terms of accuracy

and sensitivity. In the case of ICP-MS, the ethanol concentration ranged from 0% to 50%

because higher concentrations caused soot deposits in the spectrometer interface cones.

Under these conditions, the effect of the hTISIS temperature on the sensitivity and the

extent of matrix effects was studied under both CSA and ASI introduction modes. A

maximum of sensitivity was reached between 100°C and 200°C, depending on the matrix.

However, in contrast to the results observed in ICP-OES, increasing the temperature did

not completely remove the ICP-MS matrix effects caused by ethanol. This residual

interference was plasma – related, since the analyte transport efficiency was not

dependent on the matrix composition when using the hTISIS above 300°C. A modification

in the spatial ions distribution within the plasma depending on the matrix and the spray

chamber temperature was then verified. Therefore, it was necessary to sample ions 1 mm

Abstract

23

off plasma axis for fully removing the matrix effects. Under these conditions, all the

matrices studied provided the same sensitivity. As in chapter 3, the method validation was

performed by determination of the recoveries for spiked real samples. Finally, using the

optimized method, 28 bioethanol real samples were (1:1) diluted with ultrapure water

and further analyzed using standards prepared in 50% of ethanol. The LODs obtained

ranged from 0.014 ng mL-1, for Co, to 5 ng mL-1, for Na. These LODs were roughly two

orders of magnitude lower than those calculated in ICP-OES. Thus, being possible the

quantification of trace metals in bioethanol samples using a straightforward sample

preparation method (i.e., dilution).

In chapters 3 and 4 the determination of metals in bioethanol samples has been carried

out, being possible the quantification of 16 elements in different samples, in

concentrations ranging from 1 ng mL-1 to 2 µg mL-1. Nevertheless, information about the

origin of these metals has not been reported. These metals could be extracted from the

raw material used as source of sugars, or they could be incorporated along the bioethanol

production process, as well as during the storage and/or transportation.

CHAPTER 5. Evolution of the metal and metalloid content along the bioethanol

production process.

ICP-MS has been applied for the quantification of metals and metalloids in bioethanol

samples, raw materials used to obtain this biofuel and samples taken from different

critical points of the production process. In this way, it has been possible to establish the

origin of the elements encountered in the final bioethanol. Moreover, the steps of the

production process where they were either removed from the biomass or accumulated in

the biofuel were successfully identified.

To carry out the analysis of solid samples and slurries, four different protocols based on

acid assisted sample digestions were compared by means of the analysis of two biomass

certified reference materials. The results revealed that the most suitable treatment was

the acid assisted MW digestion with nitric acid. Under these conditions, the recoveries

24

ranged from 90% to 110%. Furthermore, low enough LODs and good short-term and long-

term precision were obtained.

Two different production lines were studied. Each one corresponded to two raw materials

grew in two different French regions. The results show that there existed slight differences

in terms of minor elements contents between the biomass used in each production line,

whereas significant differences were not observed in terms of major elements

concentrations. The most important source of metals and metalloids in the whole process

was attributed to the raw material. Meanwhile the distillation step caused 1000 to 10000

times decrease in metals and metalloids concentration in the final bioethanol with respect

to the biomass used for its production.

CHAPTER 6. Direct lead isotopic analysis of bioethanol by means of multi-collector ICP-

mass spectrometry with a total consumption sample introduction system.

According to the results obtained in chapter 5, the main source of metals found in

bioethanol samples was the raw material. Therefore, the isotopic analysis of metals in

bioethanol samples may be of special interest for obtaining information about the

material used for its production. The elements to consider are those that can suffer

fractionation because any of their isotopes are radiogenic (e.g., Sr or Pb). Therefore, this

procedure can be useful to distinguish between first- and second-generation bioethanol

as well as to get information about the provenance of the raw material.

In chapter 6, a method for the direct lead isotopic analysis of bioethanol samples has been

developed using the hTISIS coupled to a MC-ICP-MS. The method involves neither sample

pre-treatment nor isolation of the target analyte from the sample matrix. These studies

have been carried out in the Atomic & Mass Spectrometry research unit, at Ghent

University, in collaboration with Prof. Dr. Frank Vanhaecke, during a stay of 7 months. The

results obtained using the hTISIS were compared to those found with a conventional

sample introduction system. Moreover, two different plasma interfaces were evaluated:

H-type or X-type skimmer cone. The sensitivity achieved with the hTISIS was between 3-

and 7.5-fold higher than that obtained with the conventional sample introduction system,

Abstract

25

whereas the X-type skimmer provided better sensitivity than the H-type skimmer. The

combination hTISIS + X-type skimmer allowed to carry out the 207Pb/206Pb and 208Pb/206Pb

isotope ratios determination for lead concentrations up to 2 ng mL-1 without degrading

the precision (0.007% and 0.008%, for both isotope ratios, respectively).

The effects of ethanol content and the hTISIS temperature on the extent of mass bias were

evaluated for the four instrument setups (sample introduction system/skimmer cone type

combinations). The use of internal correction using Tl standard NIST SRM 997 followed by

the external correction, in a sample-standard bracketing approach (SSB), using Pb

standard NIST SRM 981, prepared in 75% ethanol was used for mass bias correction. In

the SSB approach, a sequence standard – sample – standard was measured and each

sample was corrected for with the preceding and following standard, to compensate for

possible signal drifts. Although bioethanol samples contained different amounts of water,

the correction described above enabled to properly amend the mass bias in ethanol-water

matrices with a water content from 0 to 40%. Thus, the method was also adequate for

actual bioethanol samples. These studies were performed using the hTISIS operated at

125°C and an X-type skimmer cone.

The robustness of the method to real matrices has been assessed by means of lead

isotopic analysis of bioethanol samples spiked with a lead standard previously

characterized isotopically. Finally, six bioethanol samples, obtained from different raw

materials, have been analyzed and significant differences in the lead isotope ratios have

been observed. This study may open new research lines focused on the direct isotopic

analysis of biofuel samples and other organic matrices.

CHAPTER 7. Determination of volatile organic compounds in bioethanol by means of GC-

FID and GC-MS.

As it has been indicated along the present abstract, this PhD focus, mainly, on the

elemental and isotopic analysis of bioethanol samples and samples taken along the

bioethanol production process. However, a parallel objective was the determination of

volatile organic compounds (VOCs) with two goals: (i) identify the organic compounds

26

present in the samples, that can be pollutants; and, (ii) to get more insight into the matrix

composition of the bioethanol samples, since these organic components of the matrix can

play an important effect on the methods developed in ICP techniques.

Two methods based on gas chromatography have been optimized to carry out these

determinations. Gas chromatography-flame ionization detector (GC-FID) has been used

for the quantification of major organic compounds whereas the coupling gas

chromatography-mass spectrometry (GC-MS) has been used for the determination of

minor and trace VOCs. A total of 130 organic compounds have been identified in 41

different bioethanol samples, in concentrations ranging from few µg L-1 to more than 10

g L-1.

Moreover, the effects of the distillation step, the storage material, the type of biomass

used for the bioethanol production and the effect of the generation of bioethanol on the

organic compounds profiles have been studied.

These seven chapters involve a significant update of the methods for the analysis of

bioethanol and related samples, specially, those methods for the elemental and isotopic

analysis of this type of samples. Moreover, an exhaustive characterization of diverse

bioethanol samples has been carried out. These products had not received special

attention in spite of their extended use.

CHAPTER 1

1 I du ti ely oupled

plas a i stru e tatio

Inductively coupled plasma instrumentation

29

The main objective of this chapter is to address essential or basic aspects as well as the

main instrumental components of Inductively Coupled Plasma (ICP) techniques with

special focus on the spectrometers used for obtaining the results presented in the present

PhD.

ICP techniques including ICP-Optical Emission Spectroscopy (ICP-OES) and ICP-Mass

Spectrometry (ICP-MS), are widely used as powerful techniques for the determination of

major, minor (ICP-OES) and trace (ICP-MS) elements in a large variety of applications.

Furthermore, isotopic analysis can be carried out by means of multi-collector MC-ICP-MS

instruments. The first ICP-OES was commercially introduced in 1974 [1] and a decade

later, ICP-MS was introduced into the market [2].

An ICP spectrometer consists of four essential parts: The sample introduction system, the

excitation/ionization source, the optical dispersive system (ICP-OES) or mass analyzer

(ICP-MS), and the detection system. Additionally, in the case of ICP-MS and MC-ICP-MS,

the ICP is operated at atmospheric pressure whereas the mass spectrometer works at high

vacuum. An interface is thus needed to bridge the big difference in pressure between the

atmospheric ICP and the mass spectrometer.

1.1 Sample introduction systems

The objective of the sample introduction system is to transfer a representative fraction of

the sample to the plasma. Although solid samples can be directly introduced into the ICP

(without sample digestion) by using laser ablation (LA) or electrothermal vaporization

(ETV) [3], these systems are not commonly used for biofuel liquid sample introduction. In

the case of liquids, the sample introduction device often has two main constituents: the

nebulizer and the spray chamber [4,5].

1.1.1 Nebulizers

The nebulizer is responsible for the formation of the so called primary aerosol. In a

pneumatic nebulizer (most used nebulizers) this aerosol is generated as a result of the

Chapter 1

30

interaction of a high velocity gas stream, usually Ar, with the liquid sample, which is

aspirated through a capillary.

Pneumatic nebulizers can be classified according to the tip geometry (Figure 1.1) as: (i)

concentric nebulizers either made of glass or an alternative material (PFA, PP and PTFE);

(ii) cross-flow nebulizers that can be fixed or with adjustable tips; (iii) high-solids

nebulizers, used for samples containing high salt contents or suspended particles; (iv)

parallel path pneumatic nebulizers; and, (v) high-pressure pneumatic nebulizers [6–8].

Figure 1.1. Schemes of the most used pneumatic nebulization devices. (a) Concentric, (b) high-

solids nebulizer (Babington type), (c) cross-flow nebulizer, and (d) parallel-path nebulizer.

Adapted from [9].

It should be noted that the most used design is the concentric nebulizer (Figure 1.2). In

this design the sample and gas capillary are co-axially positioned, with the sample capillary

surrounded by the main nebulizer body. The nebulizer is constricted at the end, thus

causing the acceleration of the Ar stream. This acceleration causes a pressure drop at the

end of the sample capillary, thus aspirating the liquid spontaneously through the Venturi

effect. However, a peristaltic pump is frequently operated for providing a constant liquid


31

flow rate that is not subjected to possible differences between samples and standards in

terms of physical properties, i.e., viscosity and surface tension [6,10].

Figure 1.2. Detailed scheme of a concentric nebulizer.

The high-solids nebulizer, developed by Babington in 1969 [6,11,12], is extensively

exploited for the analysis of high salt content solutions (e.g., up to 20% of total dissolved

solids) and slurries. In this nebulizer (Figure 1.1.b), the aerosol is generated when the

liquid sample reaches the orifice for the gas stream. Several modifications of the initially

described design, have been reported [13,14].

Another type of nebulizer widely used is the cross-flow design (Figure 1.1.c). In this

nebulizer, the liquid sample and the Ar stream flow perpendicularly and the nozzles of

both exits are mounted in a polymer body (typically PFA or PTFE) [6,15]. Cross-flow

nebulizers may contain either fixed or adjustable tips [6] and do not tend to aspirate the

solution. Therefore, a peristaltic pump should be used in order to deliver the sample to

the nebulizer. Unlike concentric designs, cross flow nebulizers are tip blocking resistant.

It should be noted that, for a given spray chamber, the transport efficiency reached with

cross flow nebulizers is, typically, half that obtained with a concentric nebulizer.

In the parallel-path nebulizer (PPN), introduced in 1995 (Figure 1.1.d), the gas and liquid

interaction takes place when the former stream interacts tangentially with the latter one

[6,16]. Both streams are aligned close enough to create instabilities on the solution, thus

Chapter 1

32

forming the aerosol. The liquid exit is not constrained, being possible the use of larger

orifices than in the nebulizers previously mentioned. As a result, with the PPN, solutions

containing particles and dissolved salts can be easily analyzed. In fact, some of these

nebulizers are provided with liquid capillaries that allow the introduction of slurries

containing particles with diameters of up to about 100 µm.

In the present PhD, concentric and microconcentric nebulizers made in glass and PFA,

respectively, have been used in combination with different spray chambers (see sections

1.1.2 and 1.1.3). Three concentric nebulizers have been used: (i) a nebulizer Meinhard®

type C-0.5 made in glass (Meinhard, Santa Ana, CA, USA) in combination with a total

sample consumption system so-called hTISIS (see section 1.1.3.2) were used in chapters

3 and 4 for the elemental analysis of bioethanol; (ii) a micronebulizer MicroMist® (Glass

Expansion, Melbourne, Australia) coupled to a double pass spray chamber was used for

the analysis of samples coming from different points of the bioethanol production

process, described in chapter 5; and (iii) a PFA-ST micronebulizer (Elemental Scientific,

Omaha, NE, USA) was used in combination with the hTISIS to perform the isotopic analysis

of bioethanol samples (chapter 6).

1.1.2 Spray chambers

Aerosols generated by the nebulizer have characteristics and properties that make

impossible their direct introduction into the plasma. In general terms, the aerosol droplets

reaching the plasma should be small enough (diameter 10 µm) to enable the efficient

desolvation, atomization and ionization of the analytes. Unfortunately, primary aerosols

are normally polydisperse and coarse (with droplets whose diameters range from tens of

nanometers to 100 µm). Therefore, an extra component for adapting the aerosol

properties to the plasma requirements is needed. For this purpose, the nebulizer is,

typically, fitted to a spray chamber. As a result, the aerosol that reaches the plasma

(tertiary aerosol) is monodisperse and fine (see Figure 1.3). Unfortunately, most of the

droplets generated by the nebulizer do not reach the plasma. In fact, for conventional

flow rates (i.e., order of 1 mL min-1) around 95-99.5% of the solution mass aspirated by

the nebulizer is lost in the spray chamber. The main aerosol transport phenomena that


33

take place in a spray chamber are evaporation, coagulation and droplets impacts caused

by inertia, gravitational settling and turbulences [6].

Figure 1.3. Scheme of the aerosol transport phenomena in a sample introduction system

consisting of a concentric nebulizer in combination with a double-pass spray chamber (Scott).

Adapted from [6].

Different designs of spray chambers have been developed, being the most popular: (i)

double-pass spray chamber or Scott-type (Figure 1.4.a); (ii) single pass spray chamber

(Figure 1.4.b); (iii) cyclonic spray chamber (Figure 1.4.c) ; (iv) baffled cyclonic spray

chamber (Figure 1.4.d); (v) single pass spray chamber with impact surface or conical

(Figure 1.4.e); and (vi) tandem or dual spray chambers (Figure 1.4.f).

A double-pass spray chamber (Figure 1.4.a) is composed of two concentric tubes. The

nebulizer is directly introduced in the central tube, which promotes the elimination of the

droplets by means of impacts. This tube also reduces the extent of the turbulences

associated to the nebulization as well as the pulses caused by the peristaltic pump. The

Chapter 1

34

inner tube also isolates the aerosol passing through the volume left between the internal

and external tubes from the turbulences generated in the nebulization process [6].

Single pass spray chamber (Figure 1.4.b) is a simple device where the nebulizer is coupled

to a single tube or a conical conduction and the aerosol describes a direct trajectory to

the ICP. This design provides the highest transport efficiency, but the median diameter of

the tertiary aerosol is also higher than that obtained with other spray chambers. This

chamber configuration is often used in combination with high efficiency nebulizers or

ultrasonic nebulizers (USN). Single pass spray chambers can be equipped with an impact

surface (Figure 1.4.c) in order to remove the coarsest aerosol droplets [6,17]. As a result,

the aerosol leaving this system is less dispersed and finer than the obtained with no

impact surface, although a higher fraction of the solution is lost and does not escape the

chamber.

Cyclonic spray chambers used in ICP have two main configurations: (i) single-pass cyclonic

spray chamber (Figure 1.4.d) and double-pass cyclonic spray chamber (baffled cyclonic

spray chamber) (Figure 1.4.e). The nebulizer is introduced into the spray chamber

tangentially to the cylindrical body and the tertiary aerosol leaves the chamber through a

tube at the top of the chamber, whereas drains leave the chamber at the bottom.

Therefore, the aerosol first impacts against the chamber walls to be subsequently

transported towards the injector [6].

Additionally, in the last two decades, low inner volume spray chambers have appeared in

order to perform the analysis of microsamples or to improve the transport efficiency for

specific applications. Generally, these chambers are used in combination with a

micronebulizer. The most commonly used low inner volume spray chambers are the

cyclonic (cinnabar) and single-pass designs.

The combination of two spray chambers placed in series has been evaluated for its

application in ICP-MS and MC-ICP-MS. Figure 1.4.f shows a scheme of the most used dual

spray chamber. It contains a cyclonic spray chamber coupled to a double-pass one

[6,18,19]. In this design, the aerosol leaving the cyclonic spray chamber is driven to the

double-pass spray chamber, also called homogenization chamber, before reaching the

plasma. A sensitivity enhancement has been reported when using the dual spray chamber


35

over a single one, that has been attributed to the generation of a monodispersed aerosol.

However, the long-term stability is jeopardized because the solution can be accumulated

in the connection between the two spray chambers.

Figure 1.4.Conventional spray chamber designs. Double-pass or Scott-type (a), Single-pass (b),

cyclonic single-pass (c), cyclonic double-pass (d), single-pass with impact surface or conical (e),

and tandem or dual spray chamber (f). Adapted from [6,20].

In the present thesis, the most used spray chamber is the single pass design, contained in

the hTISIS (see section 1.1.3.2). This device has been used for the direct elemental analysis

of bioethanol samples through ICP-OES (Chapter 3) and ICP-MS (Chapter 4) as well as their

isotopic analysis via MC-ICP-MS (Chapter 6). Cyclonic and double-pass spray chambers

Chapter 1

36

have been used as reference sample introduction systems in the cited chapters. The

double-pass spray chamber has also been applied to the analysis of samples taken along

the bioethanol production process, from the raw material to the final product (Chapter

5). Finally, the dual spray chamber has been used for the lead isotopic characterization of

in-house standards by means of MC-ICP-MS (Chapter 6).

1.1.3 Special sample introduction systems

1.1.3.1 Desolvation systems

The use of desolvation systems has been widely explored due to: (i) the low tolerance of

the plasma to solvent load (especially organic solvents), and (ii) the growing interest of

removing the interferences caused by the solvent. Lowering of the solvent plasma load

can be achieved by working at low liquid flow rates thus reducing the total amount of

aerosol, on the one hand, or removing a significant part of the solvent after the aerosol

formation, on the other hand.

A desolvation system consists of an aerosol heating unit to promote the evaporation of

the solvent contained in the primary aerosol followed by either a condenser or a

membrane (or both) to remove the generated solvent vapor. Under these conditions, the

solvent plasma load decreases and the analyte mass transport rate increases over a

conventional spray chamber thus leading to a sensitivity enhancement.

Figure 1.5. shows a schematic description of two desolvation systems used in ICP-MS and

MC-ICP-MS. The so-called Aridus II (Teledyne Cetac Technologies, NE, USA), Figure 1.5.a,

is equipped with a fluoropolymer evaporation chamber generally used at 110°C and a

membrane, also made in fluoropolymer, operated at 160°C. Figure 1.5.b. shows an outline

of the APEX IR (Elemental Scientific, NE, USA). This desolvation system combines a heated

cyclonic spray chamber (100°C or 140°C) with a multi-pass condenser (-5°C or 2°C). It

should be noted that, if required, a membrane could be adapted to the APEX IR system.


37

Figure 1.5. Schematic description of two commercially available desolvation systems. (a) Aridus

II (Teledyne Cetac technologies, NE, USA) and (b) APEX IR (Elemental Scientific, NE, USA)

1.1.3.2 High-temperature Torch Integrated Sample Introduction System (hTISIS)

To enhance the analytical performance of ICP spectrometers, efficient nebulizers and/or

spray chambers can be used for improving the transport efficiency. In this sense, a total

sample consumption device so-called High-temperature Torch Integrated Sample

Introduction System (hTISIS) has been applied in the present PhD to perform the analysis

of organic samples. This device, developed by Todolí and Mermet in 2003 [21], is

composed by a micronebulizer inserted in a single-pass spray chamber that is heated by

means of a copper coil. A temperature controller equipped with a thermocouple is

adapted to set the spray chamber temperature (see Figure 1.6).

Chapter 1

38

Figure 1.6. Scheme (a) and picture (b) of the hTISIS sample introduction system.

As a result of the heating of the primary aerosol, the analyte transport efficiency (εn) is

higher than that typically obtained with conventional sample introduction systems

described before. Under optimum temperature conditions, if the primary aerosol is fine

enough and the liquid to gas volume ratio at the nebulizer tip low enough, the totality of

the solvent contained in the aerosol is evaporated before reaching the chamber walls and

the transport efficiency is about 100%. In this case, the spray chamber acts as evaporation

cavity and drains exit is not necessary. Under these conditions, the transport efficiency is

not matrix-dependent, and the matrix effects caused by mismatching between the

physical properties of the samples and those of the standards are mitigated or even

completely removed. The hTISIS has been reported to be able to remove matrix effects

for organic [22,23] as well as aqueous complex matrices [24,25]. This introduction system


39

can be operated in two different flow regimes: (i) continuous sample aspiration mode

(CSA-hTISIS), with liquid flow rates about 30 µL min-1; and (ii) air-segmented injection (ASI-

hTISIS) in which discrete volumes (typically 5 µL) are aspirated using air as carrier. This

second injection mode appeared to solve problems related to the plasma thermal

degradation and the formation of carbon deposits in the ICP-MS interface cones when

organic matrices are introduced into the plasma without using an extra stream of O2.

Additionally, the hTISIS provides other advantages over default setups such as: (i)

sensitivity improvement close to one order of magnitude; (ii) 4- to 5- fold decrease in

limits of detection; (iii) 30-fold shortening of wash-out time because the spray chamber

walls remain dry [6]; (iv) suitability for the analysis of clinical [26,27] or environmental

microsamples [28,29].

In a recent study, the analytical performances obtained with the hTISIS were compared

against those found with an APEX desolvation system, both coupled to ICP-MS. Similar

detection limits and sensitivities were obtained in CSA mode for the APEX and hTISIS

whereas the LODs were about 12 times lower for the latter system in the ASI mode.

Additionally, the matrix effects for aqueous and hydro-organic matrices were less severe

when the hTISIS was operated than when an APEX was used [30].

In the present PhD, the hTISIS has been applied to the direct elemental analysis

(determination of metals) of bioethanol samples in ICP-OES (Chapter 3) and ICP-MS

(Chapter 4) as well as the direct (without sample preparation and/or analyte isolation) Pb

isotopic analysis of bioethanol samples by means of MC-ICP-MS (Chapter 6).

1.2 Plasma source

A plasma is defined as a gas at high temperature that contains molecules, atoms, ions and

electrons. The plasma is generated at the top of a torch normally made in quartz,

consisting of three separated concentric tubes (Figure 1.7). The tertiary aerosol flows

through the central tube or injector. This Ar flow (central flow) ranges from 0.1 to 2 L min-

1. An auxiliary argon stream flows through the space left between the two innermost

tubes. This stream (< 2 L min–1) is used to control the plasma vertical position. Finally, an

Chapter 1

40

argon stream (up to 18-20 L min-1) flowing between the two outermost tubes maintains

the plasma and acts as a thermal barrier between the plasma and the quartz torch, thus

preventing its melting as a consequence of the high temperatures reached. Note that the

maximum plasma temperature is close to 10,000 K.

Figure 1.7. (a) Scheme the of torch, coil and plasma (Adapted from [31]) and (b) picture of the

plasma generated in an ICP-MS Agilent 7700x spectrometer.

A water cooled copper coil located at the top of the torch (Figure 1.7.a) is connected to a

radio frequency (RF) generator, that produces an intense time-variable magnetic field.

The ignition of the plasma begins when a high-voltage spark or tesla discharge is applied

to the neutral argon gas. The oscillating field accelerates the charged particles that collide

with the Ar atoms thus yielding argon ions (Equation 1.1). More electrons are generated

and a chain reaction is established in which Ar is continuously ionized [1,32,33]. The

resulting ions and electrons diffuse to the end of the torch thus giving rise to the plasma

tear-like geometry (see Figure 1.7.b).

+ − → + + − 1.1

At the same time, excited argon atoms are formed:

+ − → ∗ 1.2

The ICP is mainly operated at an RF power above 1,200 W and a plasma ionization

temperature in the plasma central channel of about 8,000 K. Under these conditions, the


41

tertiary aerosol leaving the introduction system (see section 1.1) reaches the plasma and

droplets are desolvated, the resulting solid particle is vaporized and the analyte is

successively atomized and excited according to [32]:

� + − → �∗ + − 1.3

After the atomization/excitation process, the ionization takes place by means of: (i)

electron impact (equation 1.4); (ii) charge transfer reactions between ions and atoms

(equation 1.5); and, (iii) penning ionization, caused by collision between atoms and

excited Ar atoms (equation 1.6) [32].

� + − → �+ + − 1.4

� + + → �+ + 1.5

� + ∗ → �+ + + − 1.6

The analyte ionization efficiency α depends on its first ionization potential (Ei). Under the

ICP operating conditions, the ionization efficiency is about 100% for elements with Ei

below 8 eV, between 30 and 80% for metalloids, and from 1 to 30% for non-metals [33].

In addition, excited ions are formed (equations 1.7 - 1.8) [32].

� + ∗ → �+∗ + + − 1.7

� + + → �+∗ + 1.8

Excited analyte atoms can also be generated from ions (Equation 1.9)

�+ + − → �∗ 1.9

1.3 ICP-OES Perkin Elmer Optima 4300DV.

In order to obtain the ICP-OES analytical signal, the radiation emitted from an element at

a given wavelength is isolated from that emitted by other elements or molecules and its

intensity is finally detected [34–36].

An ICP-OES PerkinElmer Optima 4300DV (PerkinElmer, Uberlingen, Germany) instrument

(Figure 1.8) has been used in the present PhD (Chapter 3). The conventional introduction

Chapter 1

42

system consists of a pneumatic concentric nebulizer inserted into a glass made cyclonic

spray chamber. Moreover, the hTISIS sample introduction system (see section 1.1.3.2) has

been coupled to this instrument.

Figure 1.8. Scheme of the optic and detection systems of the ICP-OES Perkin Elmer 4300DV.

1.3.1 Transfer optics

The radiation of analytical interest is that emitted from the region of the plasma known

as the normal analytical zone (NAZ). The plasma can be viewed in both radial or side-on

(Figure 1.9.a) and axial or end-on viewing (Figure 1.9.b). Recently, instruments that

combine both radial and axial viewing, called dual view, are also available. In any case, the

radiation emitted from the plasma is transferred to the optical system by means of an

appropriate focusing component.


43

Figure 1.9. Plasma viewing modes. (a) Radial or side-on viewing and (b) axial or end-on viewing.

Taken from [35].

The radiation is collected by a toroidal mirror and image of the plasma is focused onto the

entrance slit of the wavelength dispersing device or spectrometer [35]. The ICP-OES Perkin

Elmer Optima 4300DV instrument incorporates the dual viewing mode (see Figure 1.8).

However, it should be noted that radial and axial intensities are not simultaneously taken

as a single dispersive system is used (Figure 1.8). In the present PhD, the intensities were

axially taken for the analysis of bioethanol samples.

1.3.2 Wavelength dispersive device

The next step is the separation of the radiation emitted by a given analyte from that

emitted by the remaining ones as well as the plasma species. This discrimination is

performed by means of a diffraction grating. A reflection diffraction grating is simply a

mirror with closely spaced lines ruled or etched into its surface (density ≈ 600 to 4200

lines mm-1). When light strikes such a grating, it is diffracted at an angle that is dependent

on the light wavelength and on the grating line density. In general terms, the longer the

wavelength and the higher the line density, the higher the light diffraction angle.

An additional dispersing device used in this instrument is a prism. This device disperses

polychromatic radiation in its characteristic wavelengths. The combination of an echelle

Chapter 1

44

diffraction grating with a prism has been found to provide excellent optical resolution and

it is widely used in modern ICP-OES instruments.

1.3.3 Detector

In the first generation of ICP-OES instruments, a photomultiplier tube was widely used

[38]. However, in the 1960s, solid-state devices were introduced into the electronics

industry. These devices, such as transistors and diodes, were based on the properties of

silicon. It was also discovered that silicon-based sensors responded to light and were

quickly integrated into linear and two-dimensional arrays called solid-state imagers or

detectors. Consequently, three generic, advanced solid-state detectors with high

sensitivity and resolution for spectroscopic applications were developed, among them,

the photodiode array (PDA), the charge-injection device (CID) and the charge-coupled

device (CCD). The CID and CCD devices, or charge-transfer devices (CTD), are based on the

light-sensitive properties of solid-state silicon (Figure 1.10.b) [35,36].

Figure 1.10. Scheme of the operation principle of a CCD detector. Taken from [39].


45

The spectrometer tested in the present work incorporates two different CCD detectors

used to measure intensities in the UV and visible wavelength regions, as both types of

wavelengths are separated in the dispersive system.

1.4 ICP-mass spectrometry (ICP-MS). General points.

When an ICP-MS instrument is used, once the elements that are present in the sample

are ionized in the ICP, they are led to the mass spectrometer. The spectrometer can be

divided in four parts depending on their role: (i) the interface, used to transfer the

generated ions from the plasma (atmospheric pressure) to the mass spectrometer (high

vacuum); (ii) the ion focusing beam, which selects the positive ions; (iii) the mass

spectrometer, that separates the ions according to their mass-to-charge ratio (m/z); and,

(iv) the detector, which is responsible of the signal registration. A general scheme of an

ICP-MS instrument is shown in Figure 1.11

Figure 1.11. General scheme of an ICP-MS instrument. Adapted from [40].

Chapter 1

46

1.4.1 Interface

The ionization process takes place in the plasma at atmospheric pressure whereas the

mass spectrometer operates under high vacuum conditions. For this reason, the interface

plays an important role as the ions need to be efficiently transferred from the plasma to

the mass spectrometer [1]. This interface is generally composed by two co-axial metal

cones with a small central orifice. The first cone is called sampler whereas the second one

is called skimmer (Figure 1.12). These cones are manufactured of an acid-resistant

material with high thermal conductivity, typically Ni or Pt. The latter one, which presents

better properties, is normally used when organic matrices are introduced into the

instrument in combination with an extra oxygen stream.

After the sampler cone, the beam composed by ions, electrons and neutral species

(resulting from the plasma), expands supersonically because of the pressure drop. The

major part of this expanded gas is pumped away by the vacuum pumps. The central part

of the beam is extracted once again by the skimmer.

Figure 1.12. Sampler cone and skimmer. Taken from [41].

1.4.2 Ion focusing system

After the skimmer, the extraction lenses are positioned to select the ions positively

charged, and them are introduced into the ion focusing optics. This part of the instrument

is formed by electrostatic lenses. The ion focusing system can be very simple, being

formed by only one lens, or it can be more complicated combining several lenses.


47

1.4.3 Mass spectrometer

Once the positive ions are selected in the ion focusing system, they reach the mass

spectrometer. This part of the instrument leads to the separation of the positive ions

based on their mass-to-charge ratio (m/z). Mass spectrometers operate under high

vacuum to avoid collisions between the ions and gas molecules, which would disturb the

ion beam. The characteristics of a mass spectrometer that affect the analytical figures of

merit are resolution, abundance sensitivity and scan speed [8,33].

The mass resolution is defined as the ability of the mass spectrometer to separate two

neighbouring spectral peaks (isotopes). Mass resolution is expressed according to

equation 1.10.

= � 1.10

Where R is the resolution, m the analyte mass and Δm the peak width at 5% of the peak

height corresponding to a given isotope. The resolution necessary to resolve two adjacent

isotope masses can also be calculated by means of equation 1.11:

= +− 1.11

Where m2 and m1 are the masses of both isotopes. In this case, two isotope peaks are

considered to be separated when the valley between the peaks does not exceed 10% of

the peak maximum.

The abundance sensitivity [42] is a parameter that measures the contribution of the tail

of an adjacent peak to the intensity of the analyte. This parameter is calculated as the

ratio between the intensity of the tail at the mass of the analyte and the intensity of the

analyte itself. The abundance sensitivity can be obtained using the peak height or area.

The scan speed is the speed at which the mass spectrometer can scan the spectrum

and/or switch from one mass to another. This characteristic is especially important when

working with either transient signals or isotope ratios.

Chapter 1

48

There are three types of mass spectrometers commercially available: (i) Quadrupole filter

(ICP-QMS), (ii) double-focusing sector field (ICP-SFMS) and (iii) time of flight (ICP-TOF-MS),

that report different resolution and scanning speed (see Table 1.1).

Table 1.1. Comparison of the three types of mass spectrometers used in ICP-MS. Taken from

[33].*

Type of mass

spectrometer Mass resolution

Scanning speed

Speed / u s-1 Full spectrum / ms

Quadrupole filter Unit mass resolution R ≈ 300 2500 100

Sector field Rmax ≈ ,000 1500 150

Time-of-flight Unit mass resolution R ≈ 7500000 0.003

* The operation principle of a quadrupole filter is explained in detail when ICP-QMS is

presented (see section 1.5.2), whereas the double-focusing sector field is explained in the

section where the MC-ICP-MS instrument is described (see section 1.6.1)

1.5 ICP-QMS Agilent 7700x

In the present PhD, most of the experiments carried out in ICP-MS have been performed

by means of an Agilent 7700x instrument (Agilent, Santa Clara, CA, USA). Figure 1.13

shows a detailed scheme of this instrument.

The conventional sample introduction system consists of a micronebulizer micromist®

(Glass Expansion, Melbourne, Australia) inserted in a double pass spray chamber (Scott-

type) made of glass. The hTISIS introduction system (see section 1.1.3.2) has also been

coupled to this instrument for carrying out the quantification of metals in bioethanol

samples (chapter 4). The conventional sample introduction system has been used as a

reference setup to compare the results obtained with the hTISIS and for the elemental

analysis of samples taken in different points of the bioethanol production process

(chapter 5).


49

Figure 1.13. Detailed scheme of the ICP-MS Agilent 7700x used in chapters 4 and 5. Adapted

from [43].

Chapter 1

50

The ICP-MS Agilent 7700x is equipped with the high matrix introduction (HMI) system.

This device dilutes the tertiary aerosol formed in the spray chamber with an extra argon

stream and it allows the introduction of high salt content and/or hydro-organic matrices

avoiding the formation of deposits of salts and/or carbon in the injector and interface

cones. Obviously, the maximum concentration of organic solvent that can be introduced

into the system depends on the sample flow rate and the ratio nebulizer/HMI gas flows.

The plasma is generated by a frequency-matching 27 MHz generator with 1,600 W

maximum power. The standard interface is composed by Ni-made sampler and skimmer

cones, with orifices of 1.0 mm and 0.4 mm, respectively. The extraction system contains

four different lenses: (i) extraction lens 1, (ii) extraction lens 2, (iii) omega lens, and (iv)

omega bias. Once the ion beam is focused, it reaches the octopole reaction cell (ORC), in

this case designed to be operated in collision mode (KED) using He (described in section

1.5.1) and, after that, the masses are filtered in the quadrupole (section 1.5.2). Finally, the

ions reach the detector, an electron multiplier (section 1.5.3), and the registered signal is

transformed and transferred to the software.

1.5.1 Collision cell.

Spectral interferences are generally classified into three major groups (Table 1.2): isobaric,

multiply (mostly doubly) charged ions, or polyatomic (molecular). Isobaric interferences

occur when nuclides from different elements have the same nominal mass. Doubly

charged ions are formed when an ion is generated with a double positive charge and

produces a spectral peak at half its mass (e.g., 88Sr2+ and 44Ca+). The level of doubly

charged species depends on the ionization conditions that in turn are related with the

nebulizer gas flow, RF power, and torch position [1]. Polyatomic or molecular ions consist

of two or more atoms and typically contain Ar, and/or elements from the sample matrix,

the solvent and/or the surrounding air. Moreover, intense signals of neighbouring ions,

for instance derived from the matrix elements, may overlap with the signal of the target

element.


51

Table 1.2. Examples of typical interferences in ICP-MS classified by categories. Adapted from

[33].

Type of interfering ion Interfering ion/Analyte nuclide affected

Isobaric interference

40Ar+/40Ca+

58Ni+/58Fe+

87Rb+/87Sr+

204Hg+/204Pb+

Polyatomic ions

(Ar-containing)

40Ar12C+/52Cr+

40Ar16O+/56Fe+

40Ar23Na+/63Cu+

40Ar35Cl+/75As+

40Ar2+/80Se+

Polyatomic ions

(oxide and hydroxide ions)

12C16O+/28Si+

12C16O1H+/29Si+

32S16O+/48Ti+

35Cl16O+/51V+

Polyatomic ions

(others)

14N2+/28Si+

28Si35Cl+/63Cu+

23Na23Na16O+/62Ni+

Doubly charged ions

48Ca2+/24Mg+

86Sr2+/43Ca+

88Sr2+/44Ca+

Chapter 1

52

Several strategies have been proposed to overcome spectral interferences, such as

increasing the mass resolution in sector-field instruments, chemical or energy resolution

using a reaction/collision cell (CRC), cold plasma conditions, mathematical corrections,

and chemical separation of the target analyte from the sample matrix [44]. In the present

section, only the use of a CRC is discussed in detail.

The CRC is a universal and flexible strategy to reduce the extent of spectral interferences

in ICP-MS equipped with a quadrupole mass spectrometer. The cell, containing a

multipole under a radio frequency potential, is positioned between the interface and the

mass analyzer and filled with an appropriate gas. The analyte ion can be separated via

selective ion-chemical reactions of the interfering ion with the reaction gas in the cell with

subsequent neutralization or change in its m/z ratio. Newly formed species, as a result of

the reactions, can be eliminated by kinetic energy discrimination using a deceleration

voltage. Alternatively, the target ion can be involved in a selective reaction and measured

as a reaction product ion. Another approach is based on the use of an inert collision gas

(He or H2) in combination with energy discrimination (KED). As a result, a decelerating

voltage may be applied to discriminate selectively against the polyatomic ions [33,45]. The

ICP-QMS used in the present PhD incorporates a collision cell, where He is introduced as

collision gas. As the cross section of the polyatomic ions (interfering ions) is larger than

that for the analyte, the loss of kinetic energy suffered by the polyatomic species is higher

than that suffered by the analyte and, thus, the KED mode is used for discriminating

selectively the ions (Figure 1.14).


53

Figure 1.14. Collision-cell operation principle. Adapted from [46].

1.5.2 Quadrupole filter

A quadrupole filter [5,33] consists of four parallel cylindrical or hyperbolic rods with a

direct current (DC) and an alternating current (AC) voltages applied to them. The

diagonally opposed rods are electrically connected, forming two electrode pairs. The

voltages applied on both pairs, have the same magnitude but show an opposite charge.

Figure 1.15 shows the operation principle of the quadrupole filter.

Figure 1.15. Operation principle of a quadrupole mass filter. Taken from [47].

Chapter 1

54

The focused ion beam coming from the ion optics is directed into the quadrupole central

channel. The positive DC component (+U) forces the ions to move towards the axis of the

od a d the AC o po e t Vsi ωt fo uses the io s to the e te du i g the fi st half

period and defocuses the ions from the center in the direction of the rods during the

second half period. Heavy ions are focused on the central axis and lighter ions are

sufficiently accelerated towards the quadrupole rods and removed from the ion beam.

The average potential is positive and this pair of the electrodes acts as a high-mass filter.

The voltage applied to the other pair of electrodes shows the same magnitude with

opposite sign. In this case, the pair of electrodes consist of a DC component (-U) and an

AC component, which shows a phase difference of 180° Vsi ωt + π)). The average

potential is negative and thus, this pair of electrodes acts as a low-mass filter. In this way,

the heavier ions are defocused and removed from the ion beam, while the lighter ions are

focused on the central axis. Thus, the combination of the two electrode pairs results in a

bandpass filter (see Figure 1.16). The DC and AC voltages are selected in such a way that

only the ions within a selected narrow mass-to-charge ratio range can pass through the

quadrupole filter. The dynamic selection of masses passing the filter is accomplished by

changing the DC and AC voltages in such a way that the ratio of their magnitudes remains

constant [32,33,48]. The most notable advantages of the quadrupole mass analyzer are

its technical simplicity with rapid scanning, larger tolerance towards the spread of the

kinetic energies of ions entering the filter, possibility to operate at higher pressure and,

consequently, relatively low cost. The major disadvantage of the quadrupole mass

spectrometer is the low ass esolutio /Δ ≈ .


55

Figure 1.16. The combination of the high-mass (a) and low mass (b) filters resulting the bandpass

filter (c). Adapted from [49].

1.5.3 Detector

The final part of an ICP-MS unit is the ion detection system. The ions leaving the mass

analyzer are detected and transformed into a suitable signal, proportional to the

abundance of nuclides. Nowadays, two types of detectors are commonly used: the

electron multiplier and the Faraday cup. The Agilent 7700x instruments incorporates an

electron multiplier. The operating principle of this detector is based on avalanche

multiplication of electrons formed when an ion strikes the conversion electrode of a

discrete dynode electrode. The electrons thus formed are accelerated towards the back

end of the detector due to the potential difference over the detector (negatively charged

front end and grounded back end of detector, each subsequent dynode is at a higher

potential). This acceleration leads to multiple collisions with subsequent dynodes and

he e e a ele t o ollides ith a dy ode’s su fa e, o e ele t o s a e set f ee. As a

result of this multiplication effect, an ion arriving at the detector finally leads to

Chapter 1

56

approximately 107–108 electrons. Each ion is individually detected in pulse counting mode

[33,50].

1.6 MC-ICP-MS Thermo Neptune.

High-precision isotopic analysis via multi-collector inductively coupled plasma-mass

spectrometry (MC-ICP-MS) instrument is widely used to perform the isotopic analysis of

several types of samples. Modern MC-ICP-MS provide similar precisions to those provided

by thermal ionization mass spectrometry (TIMS) instruments (RSD about 0.002%, under

ideal conditions) [51,52] but with higher sample throughput. Moreover, the ICP is capable

of ionizing elements with high ionization energies as Cu, Fe, W, B, Sb or Hg at atmospheric

pressure.

A MC-ICP-MS Thermo Neptune (Thermo, Bremen, Germany) instrument has been used in

the present PhD, for the determination of lead isotope ratios in bioethanol samples

(chapter 6).

The conventional sample introduction system of this instrument is a PFA micronebulizer

(Elemental Scientific, Omaha, NE, USA) coupled to a dual spray chamber (see section 1.1).

However, the hTISIS sample introduction system (see section 1.1.3.2) as well as a cyclonic

spray chamber, both equipped with an extra gas stream for the addition of oxygen, have

also been adapted to this instrument.

The instrument is equipped with a 130 m3 h-1 dry interface pump and two different types

of interface can be set-up: (i) standard interface and (ii) jet interface. In both cases, the

orifices of both sampler and skimmer are 0.8 mm id. However, the jet interface enhances

the sensitivity from 4 to 50 times due to the differences in terms of geometry between

both interfaces that provide a significantly higher ion extraction efficiency from the

plasma [53,54]. In the work carried out as part of the present PhD, a conventional Pt

sampler cone was combined with two Pt skimmer cones: (i) jet or X-type skimmer, and (ii)

standard skimmer or H-type skimmer.


57

After the ion extraction and focusing system, the ions are directed to a double-focusing

mass spectrometer with a Nier-Johnson geometry (see section1.6.1) and finally, they

reach the detector (nine faraday cups in static-mode) (see section 1.6.2).

Figure 1.17. Scheme of the MC-ICP-MS Thermo Neptune used in chapter 6. Adapted from [51].

1.6.1 Double-focusing mass spectrometer

The sector-field mass spectrometer consists of a combination of a magnetic (Figure

1.18.a) and an electrostatic sector (Figure 1.18.b). The ion beam is first accelerated over

a potential difference V and subsequently introduced into a magnetic field whose

direction is perpendicular to the plane of the ions flow. As a consequence, the ions move

according to a circular path (Figure 1.18.a). The centripetal force needed to move along a

circular path is provided by the Lorentz force (equation 1.12) exerted by the magnetic

field on the ion:

= = 1.12

Where F is the force exerted on the ion, v its velocity, m its mass, r the radius of the circular

path and z is the charge of the given ion. The resulting radius of the circular path r of the

Chapter 1

58

ion depends on its mass-to-charge ratio (m/z) at a constant acceleration voltage V and

constant magnetic field B (equation 1.13).

= √ �√ 1.13

The radius of the trajectory of the nuclide of interest needs to be altered to allow it to

reach the detector. When a single detector is used, the mass-to-charge ratio of the ion

can be selected by either adapting the magnetic field strength B (magnetic scanning or B-

scanning) or the acceleration voltage V (electric scanning or E-scanning) [33].

Figure 1.18. Operation principle of magnetic (a) and electrostatic (b) sectors. Adapted from [33].

The electrostatic sector (Figure 1.18.b) provides energy focusing to improve the mass

resolution. An electrostatic sector with strength E consists of two bent electrode plates,


59

to which potentials equal in magnitude but opposite in charge are applied. The ions,

moving between the positively and negatively charged bent plate, are forced to move

along a circular path. The centripetal force required to move ions along a circular path, is

provided by the electrostatic force (equation 1.14) [33].

= = 1.14

As a result, the radius of the circular path of an ion depends on its kinetic energy (equation

1.15).

= = 1.15

The combination of magnetic and electrostatic sectors radically improves the mass

resolution, but lowers the transmission efficiency as less ions eventually reach the

detector [32,33,48]. In a double-focusing setup, the electrostatic and magnetic sectors are

combined. Although three different double-focusing geometries (Mattauch-Herzog, Nier-

Johnson and reversed Nier-Johnson geometry) have been reported [33], only the Nier-

Johnson geometry is described in this chapter, since it is the setup incorporated by the

Thermo Neptune MC-ICP-MS instrument. In this geometry (Figure 1.19), the electrostatic

sector is followed by the magnetic sector (both at 90°). Double-focusing is not

simultaneously applied to all the ions, but present-day MC-ICP-MS instruments show a

mass range from m up to 1.3m wherein the ion signals can be monitored under static

conditions (constant magnetic field and acceleration voltage) [33]. Sector-field mass

analyzers are characterized by a high mass resolution (up to 10,000), low abundance

sensitivity, high ion transmission efficiency, and flat-topped peaks with a trapezoidal

shape [33,48].

Chapter 1

60

Figure 1.19. Nier-Johnson double-focusing setup. Adapted from [33].

1.6.2 Detector

In a Faraday cup, the ion beam coming from the mass analyzer is directed into a metallic

cup, when the ions reach the wall of the cup, they are neutralized by accepting electrons.

This leads to a current through the resistor, which is further amplified and detected. This

type of detector consists of a thin and deep bucket (cup). In a multi-collector setup,

several Faraday cups are fitted onto movable stages. The large depth of the cup helps to

ensure that any secondary electron produced by energetic incident ions cannot escape

the detector. The cups are connected to current amplifiers with high-ohmic feedback

resistors (modern systems have amplifiers of 1010, 1011,1012, and 1013 Ω . Fa aday up

detection is the most robust, linear, and accurate technology for the measurement of ion

currents. However, the main disadvantages of this detector are the low sensitivity, which

is limited by the noise of the amplifiers, and the long response time [33].

1.6.3 Removal of interferences in MC-ICP-MS

The mass resolution of a sector field mass spectrometer can be enhanced by narrowing

down the entrance and exit slits of the mass spectrometer. In this way, signals that overlap

at low resolution can be resolved. However, the higher resolution comes with a lower

transmission efficiency causing the signal intensity to go down. With present-day


61

instruments, a mass resolution of 10,000 can be achieved. But for some interferences

even this high mass resolution is not enough to separate the overlapping signals (e.g., 87Sr

and 87Rb).

The Thermo Neptune, used in this work, has three predefined resolution settings: low

esolutio LR, R ≈ , ediu esolutio MR, R ≈ ,000) a d high HR, R ≈ ,000).

When changing from low resolution (LR) to medium resolution (MR) or from medium

resolution to high resolution (HR), the signal intensity goes down by a factor of 10 and 4,

respectively.

Another way to eliminate interferences is the isolation of the target element from the

sample matrix prior the isotopic analysis via MC-ICP-MS. For this purpose, ion exchange

chromatography (off-line with cartridges or columns and on-line chromatographic

methods) is typically used. It should be noted that the isolation can induce mass-

dependent isotope fractionation, but this effect can be avoided if the recovery is

quantitative [55]. Otherwise, the double spike approach is recommended. Another

disadvantage of this methodology is that the chemical separation can generate an

important amount of waste.

1.6.4 Correction for instrumental mass discrimination

Isotope ratio measurements by MC-ICP-MS are affected by instrumental mass

discrimination, principally due to a more efficient transmission of the heavier isotopes of

the target analyte. This phenomenon is mainly associated with the supersonic expansion

of the ion beam in the interface and the space-charge effects (heavy ions having higher

kinetic energy than light ones are preferentially located at the beam centre, because the

electrostatic repulsion causes defocusing of light ions) [56–60]. Therefore, this effect must

be carefully corrected for in order to obtain precise and accurate isotope ratios [51].

Different approaches have been proposed for mass bias correction based on: (i) external

correction using a certified isotopic reference material (certified isotopic composition); (ii)

an internal correction using an internal standard (intra- or inter-elemental); and (iii) a

combination of both external and internal approaches. The external correction is typically

Chapter 1

62

carried out in a sample-standard bracketing (SSB) approach, where the isotope ratio data

obtained for a sample is referred to the ratio obtained for an isotopic standard measured

before and after the sample. The SSB approach has two major assumptions: (i) the mass

discrimination is supposed to be relatively stable as a function of time; and, (ii) the

external standard and samples show an identical mass discrimination behaviour.

Therefore, matrix matching of the samples and standards should be carried out [51],

which in practice is not always possible (e.g., in the case of bioethanol samples, the sample

matrix is unknown) [33]. Internal standardization using a second isotope pair of the same

element (considered invariant in nature, e.g., 88Sr/86Sr) can be used to correct the target

isotope ratio for instrumental mass discrimination (intra-element internal

standardization) [51,61]. This model not only corrects for instrumental mass

discrimination, but also for any natural mass-dependent isotope fractionation of the

target isotope ratio. However, the main limitation of intra-elemental internal

standardization is the number of isotopes required and the limited applicability. Another

approach is based on using an additional element, admixed to the sample as an internal

standard (IS).

Different models overcoming instrumental mass discrimination have been proposed over

the years [42,51,62–64]. The difference between the measured (Rexp) and the true (Rtrue)

isotope ratios is usually expressed by the mass bias correction coefficient, Kij, according

to equation 1.16

= ∙ � 1.16

The mass-bias correction model, firstly described by Russell et al. (equation 1.17) [65] is

the most used model:

= 1.17

where mi and mj are the nuclide masses, and f is fractionation function.

In general, mass-bias correction models express the mass-bias relation between various

isotope pairs of the same (intra-elemental internal standard) or differing (inter-elemental


63

internal standard) elements. Thus, the two mass-bias correction factors are assumed to

be proportional to the mass ratio of the nuclides, according to equation 1.18.

,� = ( )( ) 1.18

Woodhead suggested to use the best-fitting straight line through data for the target

isotope ratio (fsample) plotted against those for an IS (fIS), calculated according to equation

1.18, to deduce the correction factor [63]. This model was further revised by Baxter et al.

[64] using a linear regression line between ln(Rsample) and ln(RIS) to establish the correlation

between the correction factors for the analyte and the internal standard. Recently,

Devulder et al. proposed a modification of this method (CAIS) [66]. All these methods

provide similar results.

Instrumental mass discrimination can also be corrected for by using the double spike

approach, where a spike enriched in two isotopes and with known isotopic composition

of the target element is added to the sample [33,67]. Therefore, the target element needs

to have at least four isotopes. This method provides accurate and precise isotope ratio

data and allows to correct for sample loss in any sample preparation step, which can lead

to artificial isotope fractionation. However, besides the number of isotopes required, the

double spike technique also has other disadvantages such as the high cost of high-purity

isotopically enriched materials, lack of sensitivity for some isotopes, potential memory

effects and lower sample throughput.

In the chapter 6 of the present PhD, lead (NIST SRM 981) and thallium (NIST SRM 997)

isotopic reference materials from the National Institute for Standards and Technology

(NIST, Gaithersburg, MD, USA), are used for mass bias correction purposes. Sample-

standard bracketing solution prepared in 75% ethanol has been applied for the mass bias

correction of any ethanol : water matrix ranging from 60 to 100% of ethanol without

matrix matching methodology.

Chapter 1

64

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sensitivities and non-linear mass dependent fractionation of Nd isotopes, J. Anal.

At. Spectrom. 27 (2012) 63–70.

[55] C. Maréchal, F. Albarède, Ion-exchange fractionation of copper and zinc isotopes,

Geochim. Cosmochim. Acta. 66 (2002) 1499–1509.

[56] M. Rehkämper, M. Schönbächler, C.H. Stirling, Multiple collector ICP-MS:

Introduction to instrumentation, measurement techniques and analytical

capabilities, Geostand. Newsl. 25 (2001) 23–40.

[57] C.N. Maréchal, P. Télouk, F. Albarède, Precise analysis of copper and zinc isotopic

compositions by plasma-source mass spectrometry, Chem. Geol. 156 (1999) 251–

273.

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[58] C.P. Ingle, B.L. Sharp, M.S.A. Horstwood, R.R. Parrish, D.J. Lewis, Instrument

response functions, mass bias and matrix effects in isotope ratio measurements

and semi-quantitative analysis by single and multi-collector ICP-MS, J. Anal. At.

Spectrom. 18 (2003) 219–229.

[59] H. Andrén, I. Rodushkin, A. Stenberg, D. Malinovsky, D.C. Baxter, Sources of mass

bias and isotope ratio variation in multi-collector ICP-MS: optimization of

instrumental parameters based on experimental observations, J. Anal. At.

Spectrom. 19 (2004) 1217–1224.

[60] N. Kivel, I. Günther-Leopold, F. Vanhaecke, D. Günther, Isotope fractionation during

ion beam formation in multi-collector inductively coupled plasma mass

spectrometry, Spectrochim. Acta - Part B At. Spectrosc. 76 (2012) 126–132.

[61] M. Horsky, J. Irrgeher, T. Prohaska, Evaluation strategies and uncertainty

calculation of isotope amount ratios measured by MC ICP-MS on the example of Sr,

Anal. Bioanal. Chem. 408 (2016) 351–367.

[62] J. Meija, L. Yang, R. Sturgeon, Z. Mester, Mass bias fractionation laws for multi-

collector ICPMS: Assumptions and their experimental verification, Anal. Chem. 81

(2009) 6774–6778.

[63] J. Woodhead, A simple method for obtaining highly accurate Pb isotope data by

MC-ICP-MS, J. Anal. At. Spectrom. 17 (2002) 1381–1385.

[64] D.C. Baxter, I. Rodushkin, E. Engström, D. Malinovsky, Revised exponential model

for mass bias correction using an internal standard for isotope abundance ratio

measurements by multi-collector inductively coupled plasma mass spectrometry,

J. Anal. At. Spectrom. 21 (2006) 427–430.

[65] W.A. Russell, D.A. Papanastassiou, T.A. Tombrello, Ca isotope fractionation on the

Earth and other solar system materials, Geochim. Cosmochim. Acta. 42 (1978)

1075–1090.

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[67] S.J.G. Galer, Optimal double and triple spiking for high precision lead isotopic

measurement, Chem. Geol. 157 (1999) 255–274.

PUBLISHED WORKS /

TRABAJOS PUBLICADOS

CHAPTER 2

2 Metal a d etalloids deter i atio

i iodiesel a d ioetha ol

Metal and metalloid determination in biodiesel and bioethanol

79

R. Sánchez, C. Sánchez, C.P. Lienemann, J.L. Todolí, Metal and metalloid determination in

biodiesel and bioethanol, J. Anal. At. Spectrom. 30 (2015) 64–101.

doi:10.1039/C4JA00202D

Abstract

Biofuels quality control involves the determination of metal and metalloid content. These

species play a very important role because they may modify the efficiency of the biofuel

production as well as the stability of these products. Furthermore, some metals are toxic

and generate environmental concerns whereas others are used as additives. Normally,

products such as biodiesel and bioethanol are mixed with fossil conventional fuels (diesel

and gasoline, respectively). Therefore, metals come from the raw product employed for

iofuel p odu tio seeds, suga s… as ell as from the production and storage process

or even from the added fuels. The determination of the final metal and metalloid

concentration in biofuels is a challenging subject because of several reasons. On the one

hand, their content is usually low (i.e., f o se e al μg L-1 to mg L-1) and, hence, sensitive

techniques should be used. Besides all this, calibration with organic complex matrices

becomes more difficult and degrades the accuracy of the determination. Several

approaches have been evaluated to carry out this kind of analysis going from

spectrochemical to electroanalytical techniques. Within the first group, Inductively

Coupled Plasma Optical Emission Spectroscopy (ICP-OES) and Mass Spectrometry (ICP-

MS) are often employed together with Atomic Absorption methods. The different

procedures applied will be discussed in the present review emphasizing the most widely

employed ones. On this subject, fundamental as well as applied studies related with the

biofuels analysis through ICP-OES and ICP-MS will be shown to illustrate the current

difficulties associated to these determinations. Comments regarding to the possible

solutions proposed to overcome the drawbacks encountered will be made.

http://pubs.rsc.org/en/content/articlelanding/2015/ja/c4ja00202d#!divAbstract

CHAPTER 3

3 Metal a d etalloid deter i atio i

ioetha ol through i du ti ely

oupled plas a-opti al e issio

spe tros opy

Metal and metalloid determination in bioethanol through ICP-OES

187

C. Sánchez, C.P. Lienemann, J.L. Todolí, Metal and metalloid determination in bioethanol

through inductively coupled plasma-optical emission spectroscopy, Spectrochim. Acta

Part B At. Spectrosc. 115 (2016) 16–22.

doi:10.1016/j.sab.2015.10.011

Abstract

A new method to carry out the elemental determination of metals in bioethanol through

ICP-OES has been developed. The procedure is based on the use of a heated Torch

Integrated Sample Introduction System (hTISIS) to directly introduce the vaporized sample

into the plasma. Two injection modes, continuous sample aspiration (CSA) and air-

segmented flow injection analysis (ASI), have been evaluated. In a first step, the matrix

effects caused by several ethanol-water mixtures were removed by operating the hTISIS

at 400°C in air-segmented injection. Meanwhile, the results also proved that the system

could be operated in continuous mode at 200°C with the complete interferences removal.

Finally, twenty-eight real samples with bioethanol contents between 55% and 100% were

analyzed with the methods previously developed. Regarding validation, recoveries from

80% to 120% were obtained for 18 analytes and the concentrations found with the

proposed method were in agreement with those encountered with a preconcentration

method, taken as a reference procedure. Limits of detection went from 3 ng mL-1 for

manganese to about 500 ng mL-1 for calcium. This allowed to quantify Cr, Fe, Mg, Mn and

Zn in segmented flow injection and Al, Cd, Cr, Cu, K, Mg, Mn, Na and Zn in continuous

sample aspiration mode in bioethanol samples.

https://www.sciencedirect.com/science/article/pii/S0584854715002633?via%3Dihub

.

CHAPTER 4

4 A alysis of ioetha ol sa ples

through I du ti ely Coupled Plas a-

Mass Spe tro etry ith a total

sa ple o su ptio syste

Analysis of bioethanol samples through ICP-MS using the hTISIS

217

C. Sánchez, C.P. Lienemann, J.L. Todolí, Analysis of bioethanol samples through Inductively

Coupled Plasma Mass Spectrometry with a total sample consumption system,

Spectrochim. Acta - Part B At. Spectrosc. 124 (2016) 99-108.

doi:10.1016/j.sab.2016.08.018.

Abstract

Bioethanol real samples have been directly analyzed through ICP-MS by means of the so

called High Temperature Torch Integrated Sample Introduction System (hTISIS). Because

bioethanol samples may contain water, experiments have been carried out in order to

determine the effect of ethanol concentration on the ICP-MS response. The ethanol

content studied went from 0 to 50%, because higher alcohol concentrations led to carbon

deposits on the ICP-MS interface. The spectrometer default spray chamber (double pass)

equipped with a glass concentric pneumatic micronebulizer has been taken as the

reference system. Two flow regimes have been evaluated: continuous sample aspiration

at 25 L min-1 and 5 L air-segmented sample injection. hTISIS temperature has been

shown to be critical, in fact ICP-MS sensitivity increased with this variable up to 100 – 200

°C depending on the solution tested. Higher chamber temperatures led to either a drop

in signal or a plateau. Compared with the reference system, the hTISIS improved the

sensitivities by a factor included within the 4 to 8 range while average detection limits

were 6 times lower for the latter device. Regarding the influence of the ethanol

concentration on sensitivity, it has been observed that an increase in the temperature was

not enough to eliminate the interferences. It was also necessary to modify the torch

position with respect to the ICP-MS interface to overcome them. This fact was likely due

to the different extent of ion plasma radial diffusion encountered as a function of the

matrix when working at high chamber temperatures. When the torch was moved 1 mm

plasma down axis, ethanolic and aqueous solutions provided statistically equal

sensitivities. A preconcentration procedure has been applied in order to validate the

methodology. It has been found that, under optimum conditions from the point of view

of matrix effects, recoveries for spiked samples were close to 100%. Furthermore,

analytical concentrations for real samples following the preconcentration method and the


Chapter 4

218

direct determination were not significantly different. The quantification method was

finally based on external calibration with standards containing 50% (v/v) ethanol content.

CHAPTER 5

5 E olutio of the etal a d etalloid

o te t alo g the ioetha ol

produ tio pro ess

Evolution of the metal and metalloid content along the bioethanol production process

251

C. Sánchez, J.P. Vidal, C.P. Lienemann, J.L. Todolí, Evolution of the metal and metalloid

content along the bioethanol production process, Fuel Process. Technol. 173 (2018) 1–10.

doi:10.1016/j.fuproc.2018.01.001.

Abstract

Metal and metalloid concentration has been determined through inductively coupled

plasma - mass spectrometry (ICP-MS) in bioethanol samples, raw materials employed to

obtain this biofuel and samples taken from different critical points of the manufacture

method. In this way, it was possible to study the evolution of the metal and metalloid

content all along the bioethanol production process, allowing to establish the origin of the

elements determined in the final samples. Moreover, the steps of the production process

where they were either removed from the biomass or accumulated in the biofuel were

successfully identified.

Four different acid assisted protocols were compared through the analysis of two biomass

certified reference materials (CRMs). The results revealed that, for the most suitable

method (nitric acid assisted MW digestion), recoveries for the analytes of interest went

from 90% to 110%. Furthermore, good short-term and long-term precision and acceptable

limits of detection (LODs) were obtained.

Two different production lines were studied, and our results show that slight differences

in terms of the minor elements concentration (Cd, Co, Sb, Pb and V) were identified. The

most important source of metals and metalloids in the whole process can be attributed

to the raw material. Meanwhile the distillation step caused 1000 to 10000 times decrease

in elemental concentration in the final bioethanol as compared to the initial biomass.


Chapter 5

252

CHAPTER 6

6 Dire t lead isotopi a alysis of

ioetha ol y ea s of ulti-

olle tor ICP- ass spe tro etry ith

a total o su ptio sa ple

i trodu tio syste

Direct lead isotopic analysis of bioethanol by means of hTISIS-MC-ICP-MS

283

C. Sánchez, E. Bolea-Fernandez, M. Costas-Rodríguez, C.P. Lienemann, J.L. Todolí, F.

Vanhaecke, Direct lead isotopic analysis of bioethanol by means of multi-collector ICP-

mass spectrometry with a total consumption sample introduction system, J. Anal. At.

Spectrom. 33 (2018) 481–490.

doi:10.1039/C8JA00020D

Abstract

A method has been developed for the direct (no sample pre-treatment and/or isolation

of the target analyte from the sample matrix) lead isotopic analysis of bioethanol samples

via multi-collector inductively coupled plasma-mass spectrometry (MC-ICP-MS). A total

consumption sample introduction system, the so-called high-temperature Torch-

Integrated Sample Introduction System (hTISIS), equipped with a PFA micro-nebulizer and

a heated small-volume spray chamber, has been used for (i) reducing the analyte

concentration required for obtaining accurate and precise lead isotope ratio results; and

(ii) mitigating the effect of the ethanol-water ratio on the extent of mass bias.

The results obtained when using the hTISIS have been compared to those obtained with

a more conventional sample introduction system, i.e. a micro-nebulizer mounted onto a

cyclonic spray chamber at room temperature. The performance of both introduction

systems has been assessed for two different plasma interfaces. The Pt standard sampling

cone has been combined with an X-type or H-type skimmer cone, respectively. The

sensitivity achieved with the hTISIS was between 3- and 7.5-fold higher, depending on the

ethanol-water ratio, than that with the conventional sample introduction system, thus

permitting accurate lead isotope ratios to be obtained at lower concentration levels

without degradation of the precision. The external precisions, reported as twice the

relative standard deviation (2RSD), for 207Pb/206Pb and 208Pb/206Pb were 0.007% and

0.008%, respectively, whereas the internal precision was 0.007% (2RSD) for both isotope

ratios.

The effects of ethanol content and the hTISIS temperature on the extent of mass bias have

been evaluated for the four instrument setups (different sample introduction

system/skimmer cone type combinations). The combination of (i) internal correction

http://pubs.rsc.org/en/content/articlelanding/2018/ja/c8ja00020d#!divAbstract

Chapter 6

284

using NIST SRM 997 – thalliu as a i te al sta da d elyi g o Russell’s la ; and (ii)

external correction using NIST SRM 981 – lead, prepared in 75% ethanol, in a sample-

standard bracketing (SSB) approach was used for mass bias correction. Although

bioethanol samples may contain different amounts of water, the correction described

above enabled adequate correction for mass bias in ethanol-water matrices with a water

content of 0 to 40% and thus, also for actual bioethanol samples, when using the hTISIS

operated at 125°C and an X-type skimmer cone.

The robustness of the method to real matrices has been assessed by means of lead

isotopic analysis of bioethanol samples spiked with a lead standard previously

characterized isotopically. Finally, as a proof of concept, actual bioethanol samples have

been analyzed and significant differences in the lead isotope ratios have been observed.

UNPUBLISHED WORKS /

TRABAJOS NO PUBLICADOS

CHAPTER 7

7 Deter i atio of olatile orga i

o pou ds i ioetha ol y ea s

of GC-FID a d GC-MS

Determination of VOCs in bioethanol by means of GC-FID and GC-MS

317

7.1 Introduction

In the last decades, biofuels are considered as an effective alternative energy source for

mitigating the health and environmental problems caused by fossil fuels. In addition, the

increasing demands for energy and the depletion of petroleum in the near future have led

to an increase of the interest on these products [1–4].

Bioethanol is one of the most promising biofuel, likely because its use can reduce up to

75% the emission of greenhouse gases compared with fossil fuels [1–6]. As a result, its

production and consumption have grown exponentially during the last two decades

[4,7,8]. This biofuel can be directly used, in its pure form, within modified spark-ignition

engines or it can be blended with gasoline or diesel fuels [8]. One liter of ethanol contains

66% of the energy provided by a liter of petrol but it is used in the blend as a very efficient

octane-boosting agent, thereby substituting for chemical additives such as methyl tert-

butyl ether (MTBE) or tetraethyl lead, in leaded gasolines [1,3,4,9,10].

There are two main sources of bioethanol. The so-called first-generation bioethanol is the

alcoholic product generated from simple sugars (sugar cane, sugar beet, etc.), seeds or

starch (potato, corn, wheat, etc.) using diverse types of microorganisms. Generally, the

yeasts convert sugars into ethanol by fermentation. Afterward, the resulting product is

distilled and dehydrated [9]. The conversion of starch and sugars into ethanol is relatively

simple and efficient, in terms of energy consumption. Nevertheless, only a limited fraction

of the raw material is actually used to obtain bioethanol. This causes the main problem of

first-generation bioethanol; namely the fuel-food competition [1,9,11]. The second-

generation bioethanol appeared some years ago with the objective of overcoming this

problem and its production is carried out using agricultural non-edible lignocellulosic

biomass issued from food crop production or whole plants biomass. An additional

advantage of the second generation is the low cost of the raw material, which corresponds

to wastes of the food processing industry [2,9,12]. However, the use of these raw

materials involves a previous enzymatic hydrolysis, thus the equipment needed to obtain

this type of bioethanol becomes more sophisticated and affords lower bioethanol yields

than in the case of first-generation processes [9]. Finally, a third generation of biofuels is

Chapter 7

318

being implemented quickly in the case of biodiesel [13], although this emerging

technology is still not widely implemented for bioethanol production.

At the end of the production process, bioethanol may contain inorganic pollutants [14–

17] as well as organic [14,18,19] compounds whose presence may negatively affect its

quality in different ways: (i) they may degrade the combustion efficiency; (ii) the catalyst

and/or engines performance may also be worsened; and (iii) the gaseous emissions

produced may be an important source of harmful volatile organic compounds (VOCs).

Although there exists a lack of legislation regarding the quality control of bioethanol, some

methods have been developed for carrying out the determination of metals and

metalloids in this kind of fuels [5,15,20]. However, to the best of our knowledge, a limited

number of articles related with the determination on organic compounds in bioethanol

have been published [14,19]. These studies are focused on the major organic pollutants

and a short list of compounds are quantified.

The objective of this chapter is to develop a method based on gas chromatography (GC)

for the identification and quantification of volatile organic compounds in bioethanol

samples. A flame ionization detector (GC-FID) has been used for the determination of

major compounds whereas a mass spectrometer (GC-MS) has been selected for major,

minor and trace organic components. The analysis of 41 bioethanol real samples has been

performed, with particular focus on: (i) the effect of the use of different raw materials; (ii)

the effect of the number of distillation steps applied; (iii) first versus second-generation

bioethanol; and (iv) bioethanol versus biobutanol.


319

7.2 Experimental

7.2.1 Gas Chromatography-Flame Ionization Detector (GC-FID)

A GC-FID Shimadzu GC-2014 (Shimadzu corp., Kyoto, Japan) was used to carry out the

quantification of volatile compounds. The selected column was a TRB-624 (Teknokroma,

Barcelona, Spain). The experimental conditions are gathered in Table 7.1.

Table 7.1. GC-FID operating conditions and column characteristics.

Column characteristics

Model

Stationary phase

Inner diameter

Length

Film thickness

TRB-624 Teknokroma

6% Cyanopropyl-phenyl – 94% dimethylpolysiloxane cross-linked

0.25 mm

60 m

1.4 µm

Chromatographic conditions

Temperature T1 [time]

Temperature ramp [T1 - T2]


Injector temperature

Split

Detector temperature

Carrier gas

Flow rate mobile phase

40°C [12 min]

10°C min-1 [40°C - 100°C]

100°C [12 min]

250°C

1:100

250°C

He

1.3 mL min-1

7.2.2 Gas Chromatography-Mass Spectrometry (GC-MS)

A gas chromatography system Agilent 6890N (Agilent, Santa Clara, USA) coupled to a mass

spectrometer Agilent 5973N (Agilent, Santa Clara, USA), with electron impact as a source

of ions, was used to carry out the identification of volatile compounds in bioethanol

samples. The column chosen was a DB-624 (Agilent, Santa Clara, USA). The characteristics

of the column and operating conditions are gathered in Table 7.2.

Chapter 7

320

Table 7.2. GC-MS operating conditions and column characteristics.

Column characteristics

Model

Stationary phase

Inner diameter

Length

Film thickness

DB624 J&W Scientific (Agilent)

6% Cyanopropyl-phenyl – 94% dimethylpolysiloxane cross-linked

0.25 mm

30 m

1.4 µm

Chromatographic conditions


Temperature ramp 1 [T1 - T2]

Temperature ramp 2 [T2 - T3]


Injector temperature

Split

Detector temperature

Carrier gas

Carrier flow rate

35°C [10 min]

10°C min-1 [35°C - 100°C]

20°C min-1 [100°C - 225°C]

225°C [10 min]

250°C

1:10

250°C

He

1.3 mL min-1

7.2.3 Standards and samples.

In order to optimize the separation, a multi-compound standard was prepared. This

standard contained 2,000 mg L-1 of methanol (Sigma Aldrich, Sant Louis, USA), 1- propanol

(Sigma Aldrich, Sant Louis, USA), 2-propanol (Sigma Aldrich, Sant Louis, USA), 1-butanol

(Merck, Darmstadt, Germany), 2-butanol (Merck, Darmstadt, Germany), i-butanol (Sigma

Aldrich, Sant Louis, USA), isoamyl alcohol (Merck, Darmstadt, Germany), acetone (Sigma

Aldrich, Sant Louis, USA), acetaldehyde (Merck, Darmstadt, Germany) and 1,1-

diethoxyethane (Sigma Aldrich, Sant Louis, USA). The chemicals were of analytical or GC-

MS grade, ensuring that the standard was not polluted with other compounds. The

calibration standards used in GC-FID were prepared by dilution of this multi-compound

standard with ethanol (Panreac, Barcelona, Spain). The analytes concentrations ranged

from 20 to 2,000 mg L-1.

Forty-one bioethanol real samples coming from different geographical origin, raw

material and treatment were analyzed (see list of bioethanol samples). The samples were


321

grouped in five categories: (i) ten fractions of the distillation of the same bioethanol

sample; (ii) two second-generation bioethanol samples; (iii) one sample of biobutanol (the

main component of the matrix being iso-butanol); (iv) two samples stored in several

materials (glass, Nalgene®, PTFE, HDPE); (v) three samples coming from different raw

materials (winemaking residues, cereal, sugar beet) that have been produced by means

of the same process.

7.3 Results

7.3.1 Quantification of major volatile compounds in bioethanol real samples

by means of GC-FID

7.3.1.1 Method optimization

In a first place, an isothermal program at 65°C was tested for the separation of the 10

compounds present in the multi-compound standard. Under these conditions, the peaks

for some compounds overlapped with the ethanol peak at the beginning of the

chromatogram whereas other compounds were detected at retention times above 50

min. To overcome the peak overlapping simultaneously shortening the analysis time, a

gradient program was set with a 40°C initial temperature for 12 min followed by a

temperature ramp at 5°C min-1 up to 100°C and a third step in which the temperature was

kept at 100°C until the last compound reached the detector. Under these conditions, the

analytes were successfully separated and the analysis time was around 45 min. Finally,

the conditions shown in Table 7.1 were selected as the analysis time of a sample was 30

minutes with good resolution and signal-to-noise ratio. The chromatogram obtained

under these conditions is shown in Figure 7.1. In general terms, the retention time

increased with the boiling point, for a given group of compounds. It is important to remark

that the chromatogram obtained showed an unexpected peak that corresponded to

ethenol originated from the auto-tautomerization of acetaldehyde [21].

Chapter 7

322

Figure 7.1. Chromatogram obtained under optimum conditions for the standard containing

2,000 mg L-1 of ten analytes in ethanol. (1) Acetaldehyde, (2) methanol, (3) Acetone, (4) 2-

propanol, (5) 1-propanol, (6) 2-butanol, (7) i-butanol, (8) 1-butanol, (9) 1,1-diethoxyethano, and

(10) Isoamyl alcohol. *Peak (11) corresponds to ethenol from enolic equilibrium of

acetaldehyde.


323

7.3.1.2 Method validation

The inter- and intra-day precision of the method, in terms of retention time and area, was

evaluated. The precision obtained for the analytes when five chromatograms were

obtained in the same day (intra-day) and five different days (inter-day) are shown in Table

7.3. In all the cases, the area RSD was lower than 7% and 9% for intraday and interday

runs, respectively. In terms of retention time, the variability was much lower than that

observed in terms of peak area, being the RSD lower than 0.14% and 0.3% for intraday

and interday assays, respectively.

Table 7.3. Interday and intraday precisions for a multi-compound standard (n=5).

Intraday Retention time RSD 0.05 – 0.14%

Area RSD 4 – 7%

Interday Retention time RSD 0.09 – 0.30%

Area RSD 7 – 9%

Additionally, the recoveries were obtained by means of the analysis of three real samples

spiked with 200 mg L-1 of the analytes of interest. The recoveries for acetone, 2-propanol,

1-propanol, 2-butanol, 1-butanol, 1,1-diethoxyethane and isoamyl alcohol were not

statistically different from 100% (Figure 7.2). However, the recoveries for acetaldehyde

were slightly lower than the target value. This may be caused by the loses of acetaldehyde

in the auto-tautomeric equilibrium [21]. Furthermore, the recovery for methanol in

sample 1 was around 10%. This result could be due to the fact that the concentration of

methanol in this sample (B30) was actually high (10.4 g methanol L-1). Note that the spiked

concentration was 200 mg methanol L-1. Considering that the confidence levels obtained

for the real samples was between 5% and 10%, the total methanol concentrations in the

spiked and non-spiked samples were not significantly different. Therefore, it could be

concluded that the method was validated for almost all the analytes, but special attention

might be paid to the quantification of acetaldehyde.

Chapter 7

324

Figure 7.2. Recoveries for three samples spiked with 200 mg L-1 of each analyte (n=3, α=0.05).

7.3.1.3 Analysis of real samples

Table 7.4 shows a summary of the analytes identified in each sample as well as their

concentration range. For the sake of clarity, the samples have been classified in different

groups according to their type. In general terms, it can be observed that acetaldehyde,

methanol, 1-propanol and 1,1-diethoxyethane were present in almost all the samples.

Isoamyl alcohol, in turn, was present in a lower number of samples than the previous

compounds but its concentration was, typically, higher than 500 mg L-1. Finally, it is

noteworthy that the most abundant compound was methanol whose content was above

10 g L-1 in sample B30.

Table 7.4. Summary of the analytes found in bioethanol real samples. Samples not presented in the table contain concentrations < LOD for all the analytes.*

Sam

ple

B1

(W

hea

t)

B2

(W

hea

t 10

% w

ate

r)

B4

(su

gar

can

e)

B5

(w

hea

t 30

% w

ate

r)

B7

(w

hea

t +

bee

t)

B8

(su

gar

can

e)

B9

(Fr

acti

on

1)

B10

(Fr

acti

on

2)

B11

(Fr

acti

on

3)

B12

(Fr

acti

on

4)

B13

(Fr

acti

on

5)

B14

(Fr

acti

on

6)

B15

(Fr

acti

on

7)

B16

(Fr

acti

on

8)

B43

(Fr

acti

on

9)

B42

(Fr

acti

on

10

)

B18

(W

ine

res.

2)

B19

(B

eet

3)

B20

(B

eet

4)

B21

(B

eet

5)

B22

(B

eet

6)

B23

(B

eet

7)

B25

(1

302

50)

B27

(G

uar

ani)

B28

(Li

gno

cellu

losi

c)

B30

(W

ine

res.

)

B31

(C

erea

l)

B32

(B

eet)

B33

(A

-Gla

ss)

B34

(A

-Nal

gen

e)

B35

(A

-HD

PE)

B36

(A

-PTF

E)

B41

(b

iob

uta

no

l)

Analyte

1

2

3

4

5

6

7

8

9

10

> 500 mg L-1 100 mg L-1 – 500 mg L-1 < 100 mg L-1

*(1) Acetaldehyde, (2) methanol, (3) Acetone, (4) 2-propanol, (5) 1-propanol, (6) 2-butanol, (7) i-butanol, (8) 1-butanol, (9) 1,1-diethoxyethano, (10) Isoamyl

alcohol.

Chapter 7

326

Effect of distillation step. The samples Fraction 1 to Fraction 10 were taken from different

steps/points of the same distillation process, where Fraction 1 is the lightest fraction and

Fraction 10 the heaviest one. Figure 7.3 shows that peaks for acetaldehyde, methanol and

1,1-diethoxyethane appeared in the lightest fraction gradually disappeared from fraction

2 to fraction 10. In contrast, unidentified compounds, not present in the lightest fractions,

appeared in the heavy ones. Found concentrations of acetaldehyde, methanol and 1,1-

diethoxyethane were higher than 500 mg L-1 in the lightest fraction (Table 7.5).

Table 7.5. Concentrations (in mg L-1) of organic pollutants found in different distillation

fractions.*

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1 864 160 282

2 684 315 398 374 186 188

3

4

5 183

6

7 431

8

9 742 325 273

10

*(1) Acetaldehyde, (2) methanol, (3) Acetone, (4) 2-propanol, (5) 1-propanol, (6) 2-butanol, (7) i-

butanol, (8) 1-butanol, (9) 1,1-diethoxyethano, (10) Isoamyl alcohol. Confidence levels < 10%.


327

Figure 7.3. Effect of the distillation step. Chromatograms obtained for the different distillation

fractions.

Chapter 7

328

Effect of storage material. The influence of the material of the container on the

concentration of volatile organic compounds was evaluated. For this purpose, the samples

S8311 and S7875 stored in glass, Nalgene, HDPE and PTFE were analyzed. It was observed

that the storage material did not have any effect on the content of volatile organic

compounds.

Bioethanol samples obtained from different raw materials. Table 7.6 shows the found

concentrations for first generation bioethanol samples obtained using wheat, winemaking

residues, beetroot, cereals and sugar cane as raw materials. It can be observed that

bioethanol produced from winemaking residues (B30) provided the highest contents of

organic pollutants (> 10 g L-1 of methanol, 2.5 g L-1 of 1-propanol and about 2 g L-1 of

butanol isomers). Other samples as B32, B18, B19 or B22 also contained high

concentrations of compounds, such as 1-propanol, 1,1-diethoxyethane and i-butanol.

However, it was not easy to establish a direct link between the raw material and the

pollutants present in the resulting bioethanol. Note that the number of samples produced

from each type of raw material was rather limited.

It should be highlighted that the standard EN15376, which establishes the requirements

for ethanol used as a blending component for automotive fuels [22], reports the

maximum concentrations of methanol allowable at 0.5% and other higher alcohols (C3-

C5) at 2%. Nevertheless, it can be observed that sample B30 contains around 1% of

methanol, which correspond to twice the maximum concentration specified in the

mentioned standard. Some samples also contain significant concentrations of other

alcohols, but they are below the maximum concentration allowable in all the samples

analyzed.


329


different raw materials.*

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1 834 276 422 510 442 1049 920 281 504

2 176 181 10398

3

4

5 777 1659 295 473 875 297 2498 355 583 627

6 801

7 367 838 314 445 673 327 507 323

8

9 737 342 905 638

10 715

* (1) Acetaldehyde, (2) methanol, (3) Acetone, (4) 2-propanol, (5) 1-propanol, (6) 2-butanol, (7) i-


Hydrated samples, second generation bioethanol and biobutanol. This group considers

bioethanol obtained by means of different processes, samples with different water

contents, second generation bioethanol (B28) and a biobutanol sample (B41). It is

important to remark that the biobutanol sample contains 4 g L-1 of 1-propanol and more

than 1.5 g L-1 of isoamyl alcohol.

Additionally, some low intensity peaks were not identified. In order to be able to identify

and quantify these compounds, the study was extended to GC-MS.

Chapter 7

330


different raw materials with different water content, second generation bioethanol and

biobutanol.*

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4

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B2

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(2n

d G

en.)

.

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1 640 541 322 175 419 810 442

2 820

3

4 117

5 433 407 268 366 589 211 3901

6 80

7 233 376 342 309 >>

8

9 156 365

10 361 712 523 305 1536

* (1) Acetaldehyde, (2) methanol, (3) Acetone, (4) 2-propanol, (5) 1-propanol, (6) 2-butanol, (7) i-


7.3.2 Semi-quantitative determination of major, minor and trace volatile

compounds by means of GC-MS

7.3.2.1 Method optimization

As a first approach, the method optimized in GC-FID was taken as a reference, because

the column characteristics were similar for both instruments. However, in the case of the

GC-MS instrument, the length of the column was 30 m instead of 60 m and the resolution

for low molecular mass compounds when using 40°C as initial temperature was lower

than that obtained in the case of GC-FID. Moreover, the retention time of some minor and

trace non-polar compounds with high molecular weight at 100°C was longer than 1 hour.

The chromatographic method was optimized for overcoming these problems, the initial

temperature was set at 35°C during 10 min, followed by two temperature ramps from


331

35°C to 100°C at 10°C min-1 and from 100°C to 225°C at 20°C min-1, respectively. Finally,

the temperature remained at 225°C for 10 min to elute all the compounds present in the

samples.

7.3.2.2 Analysis of bioethanol real samples

Forty-one bioethanol real samples were analyzed by means of GC-MS and 130 different

volatile compounds were found. Figure 7.4 shows a scheme of the samples analyzed and

the groups of compounds identified.

Figure 7.4. Scheme of the samples analyzed and compounds identified by means of GC-MS.

The analytes encountered have been divided in eight categories according to their main

functional group. The results and conclusions for each group are described below and the

compounds found in each sample are summarized from Table 7.8 to Table 7.17. The

compounds highlighted in blue in these tables were found in, at least, one sample at high

abundances (relative area of peak) indicating that they were major pollutants in

bioethanol samples.

Alcohols. It should be noted that methanol could not be identified by means of this

method because it eluted together with dissolved air and water present in the samples.

However, this analyte was easily identified and quantified by GC-FID. A total of 23

Chapter 7

332

additional alcohols such as 1-propanol, 2-butanol, i-butanol, 1- butanol, isoamyl alcohol

and amyl alcohol were present in the samples at relatively high levels (Table 7.8). All these

alcohols were expectedly originated as by-products of the alcoholic fermentation. Some

samples contained heavier alcohols as undecanol or tetradecanol, but their low relative

areas suggested that they were present at trace levels. By means of this analysis, it was

also determined that the main component present in sample B41 (bio-butanol) was i-

butanol instead n-butanol, appearing 1- butanol and 2-butanol as fermentation by-

products.

Aldehydes and ketones. Fifteen analytes containing one of these functional groups were

found in the samples (Table 7.9). The major analyte in this group was acetaldehyde, which

appeared in several samples with a high relative peak area. Most of the analytes of this

group could appear as a consequence of the incomplete fermentation process,

nevertheless, compounds such as acetaldehyde or formaldehyde could be added to water

during the sugars extraction process, to avoid the growth of bacteria, thus remaining in

the final biofuel after the distillation process [23].

Esters. Twenty-four mainly fatty acid ethyl esters (FAEE) were found in the samples (Table

7.10). They were likely the product of the reaction of the organic acids or triacylglicerides,

present in the samples as by-products of the production process, with ethanol at a slightly

acid pH (3.5 < pH < 5.5) (Figure 7.5.a and Figure 7.5.b). The most abundant analytes in this

group were ethyl acetate, ethyl propionate, ethyl butyrate, isoamyl acetate, ethyl valerate

and ethyl caproate. Other esters with higher number of carbon atoms were found but the

areas of the peaks they generated were much lower than those for the previously

mentioned compounds, suggesting that they were present at trace levels. It is noteworthy

that, for sample B41 (bio-butanol), a specific ester profile was found. In this product, some

of the FAEEs found in bioethanol were not present but peaks assigned to fatty acid

isobutyl esters were detected. This fact suggested that fatty acids reacted with iso-

butanol.


333

Figure 7.5. Reactions that take place in bioethanol. (a) generation of FAEE from TAG and ethanol;

(b) production of FAEE from fatty acids and ethanol; (c) generation of 1,1-diethoxyethane from

ethanol and acetaldehyde.

Ethers. Seventeen ethers have been identified in the samples (Table 7.11) 1,1-

diethoxyethane being present in virtually all the biofuels. This compound has been

reported to be the product of the reaction between ethanol and acetaldehyde (Figure

7.5.c) [24]. The extent of this reaction depends on the pH of the sample and, for this

reason, acetaldehyde was not found in some samples.

Hydrocarbons. Table 7.12 shows the list of seventeen hydrocarbons found in the biofuel

samples. According to their relative peak area they did not represent a significant fraction

of the total content of pollutants. The major analyte, within this group, was n-hexane. It

is noteworthy that bicycle [2.2.1] hepta-2,5-diene also appeared in the fractions of the

distillation process (Fraction 1 to Fraction 8). The origin of these compounds is not clearly

established in the literature, but they could be extracted from the raw material and would

Chapter 7

334

remain in the sample after distillation. Another hypothesis is that, some of them, could

be a by-product of the fermentation process or even formed during the fuel storage.

Aromatic hydrocarbons. Twelve aromatic hydrocarbons were detected at moderate

contents (relative areas) in the bioethanol samples (Table 7.13). Toluene and the three

isomers of xylene (m-xylene and p-xylene appeared at the same retention time, whereas

o-xylene eluted at longer times) prevailed over the remaining analytes of this group.

Aromatic hydrocarbons could be probably extracted from the raw material in the first

steps of the bioethanol production process.

Nitrogen compounds. Ten nitrogen compounds were identified in the samples (Table

7.14) but none of them was present under relevant concentrations (relative areas were

very low). The possible origin of the nitrogen compounds was the raw material.

Organic acids. Only two organic acids remained in the samples (Table 7.15), probably

because they were converted into FAEEs at the pH of the samples. These two acids were

acetic acid in a great number of samples and isobutyric acid in the case of sample B41

(bio-butanol) where isobutanol was the main component of the matrix. Organic acids

could appear as a result of the ethanol or isobutanol oxidation during the fermentation

step.

Furane derivates. Sample B28 (lignocellulosic bioethanol) contained eight different

furane derivates (Table 7.16). It should be noted that this sample is a second-generation

bioethanol and the presence of furane and related compounds has been reported to be a

consequence of non-complete fermentations of lignocellulosic ethanol [25].

Additional organic compounds. Six additional compounds were found in the samples that

fell out of the previous groups (Table 7.17). Limonene appeared in a remarkable number

of samples (i.e., fourteen). This compound could be easily extracted from the raw

materials used in the bioethanol production.

Table 7.8. Alcohols found by GC-MS in the bioethanol samples.

ALCOHOLS

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n 4

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n 5

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tio

n 6

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n 7

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0

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B2

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5

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6

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2-propanol X X X X X X X

2-propen-1-ol X

1-propanol X X X X X X X X X X X X X X X X X X X X X

2-Butanol X X X X X X X X

Isobutanol X X X X X X X X X X X X X X X X X

1-Butanol X X X X X X X X X X X

2-methyl-2-propen-1-ol X

2-Pentanol X X X X

Isoamyl alcohol X X X X X X X X X X X X X X X X X X X

Amyl alcohol X X X X X X X X X X X X X X X X X X X

2-hexanol X

Diethylenglicol X

1,3-butanediol X

2,3-butanediol X X

3-ethoxy-1-propanol X

1-hexanol X X X X

Cyclohexanol X

2-Furanmethanol X X

Guaiacol X

benzene etanol X X X X

1-undecanol X

Tetradecanol X

3,5-dimethyladamantan-1-ol X

Table 7.9. Aldehydes and ketones found by GC-MS in the bioethanol samples.

ALDEHYDES AND

KETONES Wh

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Acetaldehide X X X X X X X X X X X X

Isobutanal X X X

Methyl ethyl ketone X X

3-methylbutanal X

2-methylbutanal X

2-pentanone X

Hexanal X X

Cyclopentanone X

2-methylcyclopentanone X

Furfural / 2-Furaldehide X X

3,3-diethoxy-2-butanone X

trimethyl-2-ciclohexen-1-one X

1-(2-furyl)-3-butanone X

Megastigmatrienone 4 X

2,3-dihydro-3,3,5,6-tetramethyl-

1H-inden-1-one X

Table 7.10. Esters found by GC-MS in the bioethanol samples.

ESTERS

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Ethyl acetate X X X X X X X X X X X X X X X X X X X X X X X X

Ethyl propionate X X X X X X X X X X X X X X X X X X X X

n-Propyl acetate X

Ethyl isobutirate X

Isobutyl acetate X X

Isoamyl formate X

Ethyl butirate X X X X X X X X X X X X X X X X X X X X X X X X X X

Ethyl (S)-(-)-lactate X X X X

ethyl 3-methylbutanoate X X

Isobutyl propionate X

isoamyl acetate X X X X X X X X X X X X X X X X X X

amyl acetate X

2-methylbutyl acetate X X

Ethyl valerate X X X X X X X X X X

isobutyl isobutyrate X

Methyl caproate X

Ethyl caproate X X X X X X X X X X X X

Methyl furoate X

isobutyl isopentanoic acid ester X

Ethyl heptanoate X X

Ethyl caprylate X X X X X

ethyl nonanoate X

Phenylethyl acetate X X

Ethyl caprate X X X X X

Table 7.11. Ethers found by GC-MS in the bioethanol samples.

ETHERS

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2-ethoxy-2-metylpropane X

1-ethoxy-1-methoxyethane X

1,1-dimethoxyethane X

1,1-diethoxyethane X X X X X X X X X X X X X X X X X X X X X X X X X X X X X

2,4,5-trimethyl-1,3-dioxolane X

2,2-diethoxypropane X X

3,3-diethoxy-1-propene X

1-ethoxy-1-propoxyethane X X

1,1-diethoxy-2-methylpropane X X X X X X X X X X X X X X X X

1,1-diethoxybutane X X X X

1,1-diethoxy isopentane X X

1,1-diethoxy-3-methylbutane X X X

1-ethoxy-1-pentoxyethane X X

Diisobutylacetal X

1,1,3-triethoxypropane X

1,1-diethoxyhexane X

Table 7.12. Hydrocarbons found by GC-MS in the bioethanol samples.

HYDROCARBONS

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n-pentane

n-hexane X X X X X X X X X X X

Cyclohexane X X X X X X

1,3-dimethylciclopentane X

1,2-dimethylciclopentane X

n-heptane X X X X

Bicycle (2.2.1) hepta-2,5-diene X X X X X X X X

Methylciclohexane X

Ethylcyclopentane X

Ethylcyclohexane

1,1,cis 3,5-tetramethylciclohexane

X

1-Dodecene X X

Tridecane X

Butylcyclohexane X

Cyclododecane X

1-tetradecene X X X

11-tricosene X

Table 7.13. Aromatic hydrocarbons found by GC-MS in the bioethanol samples.

AROMATIC HYDROCARBONS W

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Toluene X X X X X X X X X X X X X X X

Ethylbenzene X X X

p-xylene X X X X X X X X X X X X X X X X X X

m-xylene X X X X X X X X X X X X X X X X

Stirene X X X X X X X

o-xylene X X

o-methyltoluene X

1,2,3-trymethylbenzene X X

1,2,4-trymethylbenzene X X

1,3,5-trimethylbenzene X X

1,2,3,4-tetrahydro-1,1,6-trimethyl-1-napthalene

X

1,2-dihydro-1,1,6-trimethylnapthalene

X

Table 7.14. Nitrogen compounds found by GC-MS in the bioethanol samples.

NITROGEN COMPOUNDS W

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N-ethyl-1,3-dithioisoindoline X X X X

2-methylazetidine X

2-Methylpyridine X

Methylpyrazine X

2,4,5-trimethyloxazole X

2,5-dimethylpirazine X

2,3,5-trimethylpirazine X

tetramethylpyrazine X

Pyrazole X

Tributylamine X X X X X X X X

Table 7.15. Organic acids found by GC-MS in the bioethanol samples.

ORGANIC ACIDS

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Acetic acid X X X

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Table 7.16. Furane derivates found by GC-MS in the bioethanol samples.

FURANE DERIVATES W

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Furfural X X

Furylcarbinol X X

Acetylfurane X

2-pentylfurane X

Ethylfurane carbonate X

Methyl furoate X

2-acetyl-5-methylfurane X

1-(2-furyl)-3-butanone X

Table 7.17. Other organic compounds found by GC-MS in the bioethanol samples.

OTHER COMPOUNDS W

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Chloroform X

Dimethoxydimethylsilane X

Hexamethyl-cyclotrisiloxane X X X X X X X

Myrcene X

Limonene X X X X X X X X X X X X X X

alpha ionene X


343

Additionally, Figure 7.6 shows the number of samples in which each analyte was

identified. The number of pollutants that was found in the samples was very high (130

organic compounds in 41 samples). However, none of them was present in every sample.

These two facts, revealed that bioethanol production is complex and slight modifications

in this process as well as in the raw material used as source of sugars, may cause an

alteration of the organic pollutants contained in the final bioethanol. In addition, the

storage and transport conditions (i.e., temperature, pH, humidity, hydration grade of

bioethanol, etc.) could strongly affect the organic fraction of the bioethanol samples, since

some of the pollutants were products resulting from post-production chemical reactions.

It should also be noted that alcohols and esters, generated by reaction of organic acids

and alcohols, appeared as the predominant groups of pollutants in bioethanol samples in

terms of both, total number of compounds and concentration. Surprisingly, the most

frequent pollutant was an ether (1,1-diethoxyethane) that was present in 35 products

(85% of the samples).

Other groups of compounds, such as hydrocarbons, aromatic hydrocarbons and

heterocycles, have been found at minor or trace levels in a considerable number of

samples. However, it should be taken into account that these compounds (VOCs) can

severely affect the environment quality and the human health [26,27] even at very low

concentrations. Some aromatic hydrocarbons identified in the samples, such as benzene,

toluene, ethylbenzene and xylene (BTEX), have been widely recognized as human

carcinogens whereas others also possess high toxicity, especially to central nervous

system in humans [26]. Moreover, acetaldehyde was also present in a significant number

of bioethanol samples. This fact could explain the data reported by Niven [10] related with

an increase of acetaldehyde emissions when 10% ethanol was added to gasoline (E10).

Nevertheless, in the same study, it was reported that the addition of ethanol to gasoline

lowered, compared with pure gasoline, the emission of other VOCs, such as xylene or

toluene [10].

Chapter 7

344

Figure 7.6. Frequency of identification of each analyte when n≥3.


345

Regarding the number of pollutants found in the analyzed biofuels, sample B30 (i.e., a

bioethanol originated from winemaking wastes), yielded the highest number of peaks. A

total of 37 compounds (together with methanol that could not be identified in the present

work by GC-MS) were identified in this sample (Figure 7.7). Additional samples, as

biobutanol (B41) or the second-generation bioethanol (B28) also contained a high number

of organic compounds in their matrices. Each one of these samples showed more than 30

peaks in GC-MS. Finally, around 25 organic pollutants were detected in samples such as

B1, B5, B27, and the set from B33 to B36, whereas the rest of the samples contained less

than 25 organic compounds (Figure 7.7).

In the present study, some samples were selected to evaluate the effect of different

variables on the number of organic compounds in the samples and their concentrations.

Distillation fractions (Fraction 1 to Fraction 8) were considered (Figure 7.8). As it was

established in GC-FID for major pollutants, it can be clearly observed that some volatile

organic compounds were more concentrated in the lightest fraction and their

concentration decreased in heavier fractions. It can be clearly observed in the cases of:

acetaldehyde (Figure 7.8.b), ethyl acetate (Figure 7.8.c), bicycle [2.2.1] hepta-2,5-diene

and 1,1-diethoxyethane and toluene (Figure 7.8.d). There is a direct relation between the

boiling point and the fractions where these analytes were present. Acetaldehyde, whose

boiling point is 20.2°C, was only detected in the initial fractions (1 and 2). Ethyl acetate,

with a boiling point of 77°C appeared in fractions from 1 to 3. However, bicycle [2.2.1]

hepta-2,5-diene (b.p.:89°C), 1,1-diethoxyethane (b.p.:102°C) and toluene (b.p.:111°C)

were present in all the fractions, except the heaviest one (fraction 10) under different

concentrations.

Several samples provided by the company UNGDA coming from several raw materials

have also been studied in detail (Figure 7.9). These samples are B30, obtained from wine

by-products, B31, obtained using cereals as raw material and B32, generated using sugars

extracted from beetroot. The sample B30 contained 37 different organic compounds

whereas the samples coming from cereals and beetroot were cleaner with 14 and 18

volatile organic compounds, respectively.

Chapter 7

346

Regarding the effect of the storage material, as it was observed for major pollutants, the

profile of minor and trace organic compounds was not affected by the storage material.

The comparison between first-generation and second-generation bioethanol was also

very interesting. The second-generation sample (B28) contained a large number of

organic compounds within its matrix (33 compounds), typically higher than the average

number of organic pollutants in the first-generation samples. Unfortunately, only one

representative sample originated from lignocellulosic material (second-generation) was

available in this study. However, other samples (e.g., B30, obtained from winemaking sub-

products, with 37 compounds present in its matrix) were more polluted than B28. This

topic could be source of further discussion, since some authors consider bioethanol

obtained from sub-products of other process as second-generation despite they are not

obtained from lignocellulosic material. Therefore, if sample B30 is considered as second-

generation bioethanol, it could be concluded that second-generation samples presented

higher number of organic pollutants than first-generation bioethanol.

The estimated total concentration of VOCs in sample B30, the most polluted one, was

about 25 g of VOCs L-1. This content corresponded to a 2.5% of the sample, revealing the

significant contribution of this kind of organic compounds to the composition of some

bioethanol samples. It should also be noted that the concentration of VOCs found in

sample B30 is higher than that established as the maximum allowable in the standard

EN15376 [22].


347

Figure 7.7. Number of compounds found in the samples by GC-MS.

Chapter 7

348

Figure 7.8. Chromatograms obtained for distillation fractions. (a) complete; (b) 2 to 2.5 min;

(c) 8.5 to 9.5 min; (d) 13 to 16.5 min.


349

Figure 7.9. Chromatograms obtained for different raw materials. Blue: Winemaking residues;

Orange: Cereal; Grey: Beetroot.

Chapter 7

350

7.4 Conclusions.

More than 130 different VOCs were identified in bioethanol samples. Some of these

pollutants can be directly extracted from the raw material, such as limonene, organic acids

and aromatic hydrocarbons. Nevertheless, other VOCs, such as alcohols or acetaldehyde,

appear as by-products of the fermentation process. Finally, other group of organic

compounds can be generated in the samples after their production by means of reactions

favored by slightly acid conditions. Among these compounds esters (especially FAEEs) and

1,1-diethoxyethane, present in almost all the samples, are found. These results indicate

that bioethanol samples have a complex matrix, with variable water content and VOCs in

concentrations in the order of tens of g L-1 (the total amount of VOCs in bioethanol

samples was up to 2.5%). These results highlight the difficulty in removing matrix effects

in ICP techniques when analyzing bioethanol samples. Likewise, systems such as the

hTISIS, overcoming these interferences are needed to achieve accurate results.

It has been demonstrated that the material in which the sample is stored does not have

any effect in the organic compounds profile of the sample. Additionally, it has been

reported that those organic compounds with low boiling point (lower or similar that

ethanol b.p.) appear in the bioethanol samples because the distillation is not effective for

their removal. Moreover, second generation sample and bioethanol coming from

winemaking residues presented the highest number of organic compounds in their

matrices. When simple sugars sources as cereals, wheat or beetroot are selected to

produce the bioethanol, less organic pollutants are identified. These results can be

associated with a simple fermentation and it is, consequently, reflected in the lower

number of by-products resulting from this process. Finally, i-butanol was identified as

major component of the matrix of a biobutanol sample. The number of organic

compounds was also higher than the average in the rest of the samples. This fact could

also be associated with the production process, which is more complex than in the case

of first-generation bioethanol.

Alcohols and esters were the most important contributors to the total VOCs in the

bioethanol samples analyzed. However, it is also necessary to carefully monitor other

minor and trace VOCs that have been identified in bioethanol samples, such as benzene,


351

toluene, ethylbenzene or xylene (BTEX), since they can cause drastic damages to the

human health when they are emitted to the atmosphere, even in very low concentrations.

All these observations revealed the importance of carrying out the production of

bioethanol under controlled conditions, since slight changes in any of the steps may

modify the profile of organic compounds present in the final product. Additionally, the

conditions of transportation and storage of this biofuel should also be controlled, because

some of the organic products are produced as post-production reactions and changes of

pH, humidity or temperature could modify the concentration of VOCs, and therefore, the

quality of the bioethanol can be altered. On this subject, the metal determination

(chapters 3 and 4) is extremely important as some of them play an active role in terms of

side reactions production. Thus, for instance copper may catalyze ethanol oxidation

reactions thus promoting the appearance of additional organic pollutants.

Chapter 7

352

7.5 References

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28.

[2] M. Köpke, P. Dürre, Biochemical production of bioethanol., in: Handb. Biofuels

Prod. Process. Technol., Woodhead Publishing Limited, 2011: pp. 221–257.

[3] G.M. Walker, Bioethanol: Science and technology of fuel alcohol, Ventus Publishing

ApS, 2010.

[4] E. Wheals, L.C. Basso, D.M. Alves, H. V Amorim, Fuel ethanol after 25 years., Trends

Biotechnol. 17 (1999) 482–487

[5] R. Sánchez, C. Sánchez, C.P. Lienemann, J.L. Todolí, Metal and metalloid

determination in biodiesel and bioethanol, J. Anal. At. Spectrom. 30 (2015) 64–101.

[6] F. Monot, A. Margeot, B. Hahn-Hägerdal, J. Lindstedt, R. Slade, The NILE Project —

Advances in the Conversion of Lignocellulosic Materials into Ethanol, Oil Gas Sci.

Technol. – Re . d’IFP E e gies Nou . 6 693–705.

[7] P. Le os, F.C. Mes uita, Futu e of Glo al Bioetha ol : A App aisal of Results , Risk

and Uncertainties, in: Glob. Bioethanol, Elsevier Inc., 2016: pp. 221–237.

[8] M. Balat, H. Balat, Recent trends in global production and utilization of bio-ethanol

fuel, Appl. Energy. 86 (2009) 2273–2282.

[9] P.S. Nigam, A. Singh, Production of liquid biofuels from renewable resources, Prog.

Energy Combust. Sci. 37 (2011) 52–68.

[10] R.K. Niven, Ethanol in gasoline: Environmental impacts and sustainability review

article, Renew. Sustain. Energy Rev. 9 (2005) 535–555.

[11] J. Fargione, J. Hill, D. Tilman, S. Polasky, P. Hawthorne, Land Clearing and the Biofuel

Carbon Debt, Science. 319 (2008) 1235–1238.

[12] D.P. Ho, H.H. Ngo, W. Guo, A mini review on renewable sources for biofuel,


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Bioresour. Technol. 169 (2014) 742–749.

[13] V. Patil, K.Q. Tran, H.R. Giselrød, Towards sustainable production of biofuels from

microalgae, Int. J. Mol. Sci. 9 (2008) 1188–1195.

[14] H. Habe, T. Shinbo, T. Yamamoto, S. Sato, H. Shimada, K. Sakaki, Chemical Analysis

of Impurities in Diverse Bioethanol Samples, J. Japan Pet. Inst. 56 (2013) 414–422.

[15] C. Sánchez, C.P. Lienemann, J.L. Todolí, Analysis of bioethanol samples through

Inductively Coupled Plasma Mass Spectrometry with a total sample consumption

system, Spectrochim. Acta Part B At. Spectrosc. 124 (2016) 99–108.

[16] C. Sánchez, C.P. Lienemann, J.L. Todolí, Metal and metalloid determination in

bioethanol through inductively coupled plasma-optical emission spectroscopy,

Spectrochim. Acta Part B At. Spectrosc. 115 (2016) 16–22.

[17] D. Chiche, C. Diverchy, A.C. Lucquin, F. Porcheron, F. Defoort, Synthesis Gas

Purification, Oil Gas Sci. Technol. – Re . d’IFP E e gies Nou . 68 (2013) 707–723.

[18] L.G. Anderson, Ethanol fuel use in Brazil: air quality impacts, Energy Environ. Sci. 2

(2009) 1015–1037.

[19] D. Styarini, Y. Aristiawan, F. Aulia, H. Abimanyu, Y. Sudiyani, Determination of

organic impurities in lignocellulosic bioethanol product by GC-FID, Energy Procedia.

32 (2013) 153–159.

[20] C. Sánchez, C.P. Lienemann, J.L. Todolí, Metal and metalloid determination in


Spectrochim. Acta - Part B At. Spectrosc. 115 (2016).

[21] B. Sulzberger, D. Postma, R. Jakobsen, S.G. Benner, S. Fendorf, O. Larsen, K.M.

Rosso, M. Dupuis, a Hoel, G. a Niklasson, C.G. Granqvist, N.F. Mott, M.J. Apted, M.

Chergui, D.E. Janney, R.C. Gerkin, P.R. Buseck, D.B. Liston, J. a Lovejoy, H. Deng, J.Z.

Zhang, M. Hilgendorff, a P. Yartsev, F. Farges, F. Martin, G. Fagheraz, F. Gazzarrini,

G. Lanzavecchia, G. Sironi, P. Belleville, J.P. Jolivet, J. Livage, M. Myers, K. a Bosnik,

L.E. Brus, B. Ravel, J.J. Rehr, S.D. Conradson, J.F. Meunier, M. Instrumentation, G.

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Jennings, Photo-Tautomerization of Acetaldehyde, 337 (2012) 1203–1206.

[22] European Committee for Standardization, EN 15376:2014: Automotive Fuels -

Ethanol as a blending component for automotive fuels - Requirements and test

methods, 2014.

[23] C. Sánchez, J.P. Vidal, C.P. Lienemann, J.L. Todolí, Evolution of the metal and

metalloid content along the bioethanol production process, Fuel Process. Technol.

173 (2018) 1–10.

[24] M.F. Gomez, L.A. Arrúa, M.C. Abello, Synthesis of 1,1-diethoxyethane from

bioethanol. Influence of catalyst acidity, React. Kinet. Catal. Lett. 73 (2001) 143–

149.

[25] G.J. Shin, S.Y. Jeong, J.W. Lee, Evaluation of antioxidant activity of the residues

generated from ethanol concentration of lignocellulosic biomass using

pervaporation, J. Ind. Eng. Chem. 52 (2017) 51–58.

[26] X. Han, L.P. Naeher, A review of traffic-related air pollution exposure assessment

studies in the developing world, Environ. Int. 32 (2006) 106–120.

[27] K. Zhang, S. Batterman, Air pollution and health risks due to vehicle traffic, Sci. Total

Environ. 450–451 (2013) 307–316.

GENERAL CONCLUSIONS

General conclusions

357

From the present PhD, several conclusions can be drawn:

▪ The quantification of metals in bioethanol is a complex task due to the appearance

of matrix effects caused by varying the matrix composition of this kind of samples.

Indeed, the content, of water, organic compounds and inorganic species may

change significantly among samples. These matrix effects are mainly related with

the diffe e es of a alyte t a spo t effi ie y εn) induced by modifications in the

physical properties of the samples.

▪ The use of the high temperature Torch Integrated Sample Introduction System

(hTISIS) operated in both injection modes (continuous sample aspiration at 25-30

µL min-1 or air-segmented injection of 5 µL of sample), coupled to ICP techniques

provides a significant enhancement of sensitivity and a reduction in the extent of

memory effects, in comparison with a conventional sample introduction system.

▪ Heating the hTISIS single pass spray chamber above 300°C makes the analyte

transport efficiency to be virtually 100% regardless the ethanol content.

▪ The hTISIS, operated under optimum temperature conditions, removes the ICP-

OES matrix effects for ethanol-water mixtures. Therefore, this device makes it

possible to perform the direct analysis of bioethanol samples through external

calibration using multielemental standards whose matrix contains ethanol and

water in a 1:1 ratio.

▪ The hTISIS does not remove the ICP-MS ethanol matrix effects. This fact is caused

by the different spatial distribution of the ions in the plasma depending on the

sample ethanol concentration. Therefore, a modification of the relative position

between the torch and the interface (sampling zone) is needed. In conclusion, the

accurate ICP-MS analysis of bioethanol involves moving the plasma torch 1 mm

down plasma axis, using the hTISIS at temperatures above 300°C, diluting the

samples with ultrapure water in a 1:1 proportion and using 1:1 water : ethanol

multielemental standards.

▪ Using the hTISIS, sixteen metals have been quantified in concentrations ranging

from 1 ng mL-1 to 2 µg mL-1 in bioethanol samples. Aluminum, cadmium, calcium,

chromium, copper, iron, magnesium, manganese, potassium, sodium, nickel and

zinc were quantified through ICP-OES, whereas, cobalt, copper, indium, iron,

358

magnesium, manganese, nickel, silver, sodium, strontium and zinc were

encountered in ICP-MS in concentrations above the LOQ. There has not been a

direct link between the type of bioethanol and the number of metals contained

and/or their concentrations.

▪ Among the different possible sources of metals, the raw material has been

identified as the main responsible of the presence of metals in the final product

(bioethanol).

▪ Carbonation and liming steps are applied in the bioethanol production process

prior to fermentation. These processes are efficient for the removal of major

divalent and trivalent cations. However, minor metals and monovalent cations

remain after these procedures. The distillation, carried out after fermentation, is,

in turn, responsible for the removal of more than 99.9% of the metals content.

Note that these species are present in bioethanol in concentrations below 2 mg L-

1 whereas the biomass used for its production contains metals at levels higher than

1 g kg-1.

▪ The use of the hTISIS at 125°C coupled to MC-ICP-MS, using an X-type skimmer,

provides precise and accurate lead isotope ratios in bioethanol samples. This

method affords direct isotopic analysis of this kind of samples without any prior

analyte and sample matrix separation step. Moreover, procedures such as matrix-

matching are not required for the correction of the mass bias. In fact, a standard

prepared in 75% of ethanol successfully performs the mass bias correction in the

60% to 100% ethanol concentration range.

▪ The isotopic analysis of lead in bioethanol samples provides useful information

about the type of biomass used for its production and helps to discern whether a

given sample belongs to first or second bioethanol generation.

▪ Besides water and ethanol, bioethanol contains a wide variety of organic

compounds. The type and concentration of organic compounds in bioethanol

depend on the biomass used for its production and the process applied to convert

this biomass into fuel. Around 130 volatile organic compounds have been

identified in bioethanol samples. This fact shows the importance of developing

new methods free of matrix effects, for the determination of metals in bioethanol.

General conclusions

359

▪ In summary, the present research incorporates new methods for the analysis of

bioethanol. In particular, new methodologies for the quantification of metals

(major, minor and traces) as well as for the lead isotopic analysis of this type of

samples have been developed. These methods provide significant improvements

over the existing ones, in terms of limits of detection and matrix effects. Moreover,

this work has provided new data about the composition of bioethanol regarding

the metals and organic compounds present together with their concentrations as

well as the origin of the formers in this type of samples.

CONCLUSIONES GENERALES

Conclusiones generales

363

A continuación, se detallan las principales conclusiones derivadas de la investigación

realizada en la presente Tesis Doctoral:

▪ La determinación de metales en bioetanol es una tarea compleja debido a los

efectos de matriz causados por la naturaleza variable de la matriz de las muestras

englobadas bajo la denominación de bioetanol. Este hecho se debe a que el

contenido en agua y otros componentes, tanto inorgánicos como orgánicos puede

cambiar de una muestra a otra. Dichos efectos de matriz están relacionados,

principalmente, con las diferencias en eficiencia de transporte de analito (εn) que

se originan como consecuencia de las diferentes propiedades físicas que confieren

a las muestras de bioetanol sus distintas matrices.

▪ El empleo del sistema de consumo total de muestra hTISIS (high temperature

Torch Integrated Sample Introduction System), en ambos modos de introducción

de muestras (aspiración continua a 25-30 µL min-1 o inyección segmentada de 5 µL

de muestra), acoplado a técnicas basadas en ICP proporciona una mejora notable

en sensibilidad y efectos de memoria, en comparación con un sistema de

introducción de muestras convencional.

▪ Cuando la cámara de nebulización de paso simple, que forma parte del sistema

hTISIS, es calentada a temperaturas iguales o superiores a 300°C, la eficiencia de

transporte de analito para cualquier mezcla etanol-agua y, por tanto, muestras de

bioetanol, es la misma y, prácticamente, del 100%.

▪ El uso del sistema de introducción de muestras hTISIS, en condiciones óptimas de

temperatura, acoplado a ICP-OES es capaz de eliminar los efectos de matriz para

cualquier mezcla etanol-agua y, por tanto, muestras de bioetanol. En

consecuencia, este dispositivo posibilita llevar a cabo el análisis de este tipo de

muestras, de forma directa, mediante calibrado externo con patrones que

contienen etanol y agua en una proporción 1:1.

▪ El sistema hTISIS a elevadas temperaturas no elimina los efectos de matriz

causados por el etanol en ICP-MS. El motivo de esta observación radica en que

existe una diferente distribución espacial de los iones en el seno del plasma en

función de la concentración de etanol en la muestra. Por lo tanto, es necesario

modificar la posición relativa de la antorcha con respecto a la interfaz (zona de

364

muestreo) para eliminar los efectos de matriz provocados por el etanol. Bajo estas

condiciones, se puede llevar a cabo el análisis de muestras de bioetanol realizando

una dilución 1:1 de las mismas con agua ultrapura mediante calibrado externo

empleando patrones que contienen agua y etanol en la misma proporción.

▪ Empleando el hTISIS acoplado a ICP-OES e ICP-MS, Se han cuantificado un total de

16 metales en muestras diferentes de bioetanol, en concentraciones que varían

desde el orden de 1 ng mL-1 hasta 2 µg mL-1. En ICP-OES, se han cuantificado

aluminio, cadmio, calcio, cromo, cobre, hierro, magnesio, manganeso, potasio,

sodio, níquel y zinc, mientras que en ICP-MS, se han encontrado cobalto, cobre,

indio, hierro, magnesio, manganeso, níquel, plata, sodio, estroncio y zinc en

concentraciones superiores al LOQ. No se ha encontrado una relación directa

entre el tipo de muestra y el número de metales presentes en las mismas y/o sus

concentraciones.

▪ De entre las diferentes posibilidades, el material de partida ha sido identificado

como el principal factor responsable de la presencia de metales en el producto

final (bioetanol).

▪ Las etapas de eliminación de metales previas a la fermentación empleada en el

proceso de producción de bioetanol, tales como la carbonatación y el encalado,

resultan eficientes para llevar a cabo la eliminación de cationes divalentes y

trivalentes mayoritarios. Sin embargo, no son capaces de extraer metales

minoritarios ni cationes monovalentes. No obstante, la destilación, realizada tras

la fermentación, reduce el contenido en metales en más de un 99.9%,

encontrándose estos en concentraciones inferiores a 2 mg L-1 en bioetanol,

mientras que en la biomasa están presentes en concentraciones superiores a 1 g

Kg-1.

▪ El uso del sistema de introducción de muestras hTISIS a 125°C acoplado a MC-ICP-

MS, empleando un skimmer tipo X, proporciona relaciones isotópicas de plomo

precisas y exactas en muestras de bioetanol. Mediante este método se puede

llevar a cabo el análisis isotópico directo de este tipo de muestras sin separación

previa del analito y la matriz. Además, con objeto de corregir la discriminación en

masa, no es necesario llevar a cabo la igualación exhaustiva de la matriz del patrón

empleado a las de las muestras. De hecho, un patrón preparado en 75% de etanol

Conclusiones generales

365

es capaz de corregir la discriminación en masa en un intervalo de concentraciones

de etanol entre el 60% y el 100%.

▪ El análisis isotópico de plomo en muestras de bioetanol proporciona información

útil sobre el tipo de biomasa empleada para su producción y, por tanto, sobre la

generación a la que pertenece el bioetanol que se está analizando.

▪ La técnica de cromatografía de gases, utilizando un detector de ionización en llama

o un espectrómetro de masas, puede ser empleada para identificar y cuantificar la

mayor parte de compuestos orgánicos volátiles presentes en muestras de

bioetanol.

▪ A pesar de que una matriz de bioetanol tiene como componentes mayoritarios

etanol y agua, se ha demostrado que las muestras de bioetanol presentan una

amplia variedad de compuestos orgánicos. La concentración y tipo de los mismos

depende de la biomasa empleada para su producción y del proceso que haya

sufrido la biomasa para ser convertida en bioetanol. Se han identificado alrededor

de 130 compuestos orgánicos en muestras de bioetanol. Este hecho pone de

manifiesto la importancia que posee el desarrollo de métodos libres de efectos de

matriz para la determinación de metales en bioetanol.

▪ En términos generales, el presente trabajo de investigación aporta nuevos

métodos de análisis de bioetanol. Más concretamente, se han desarrollado

métodos para la cuantificación de metales (mayoritarios, minoritarios y traza) así

como el análisis isotópico de plomo en este tipo de muestras. Estos métodos

proporcionan mejoras notables, frente a los existentes hasta la fecha, en términos

de límites de detección y efectos de matriz. Además, este trabajo ha aportado

nuevos datos sobre la composición del bioetanol, específicamente en términos de

metales y compuestos orgánicos presentes en bioetanol y su concentración, así

como el origen de los primeros en este tipo de muestras.

FUTURE STUDIES

Future studies

369

The present PhD has reported new analytical methods to perform: (i) the quantification

of metals in bioethanol samples as well as samples taken along the bioethanol production

process; (ii) lead isotopic analysis of bioethanol; and, (iii) determination of VOCs in this

kind of samples.

The conclusions drawn from the obtained results allow to propose future studies aimed

and enlarge the degree of understanding and applicability of ICP-MS and the hTISIS to the

analysis of organic samples. Figure A.1 advances future trends that include instrumental

developments (1 and 4) as well as fundamental studies: (2 and 6) and the application of

the findings to the analysis of real samples (3 and 7) that will improve the degree of

knowledge of their composition (5).

Figure A.1. Scheme of future studies.

Although not concluding results have been obtained, preliminary data demonstrate the

feasibility of the points 1-6. They will be the subject of further research and will give more

insight in the analysis of organic samples through ICP techniques.

SCIENTIFIC IMPACT

Scientific impact

373

Peer-reviewed publications

1. C. Sánchez, E. Bolea-Fernandez, M. Costas-Rodríguez, C.P. Lienemann, J.L. Todolí, F.

Vanhaecke, Direct lead isotopic analysis of bioethanol by means of multi-collector ICP-

mass spectrometry with a total consumption sample introduction system, J. Anal. At.

Spectrom. 33 (2018) 481–490. doi:10.1039/C8JA00020D.

2. C. Sánchez, J.P. Vidal, C.P. Lienemann, J.L. Todolí, Evolution of the metal and metalloid

content along the bioethanol production process, Fuel Process. Technol. 173 (2018)

1–10. doi:10.1016/j.fuproc.2018.01.001.

3. B. Klencsár, C. Sánchez, L. Balcaen, J.L. Todolí, F. Lynen, F. Vanhaecke, Comparative

evaluation of ICP sample introduction systems to be used in the metabolite profiling

of chlorine-containing pharmaceuticals via HPLC-ICP-MS, J. Pharm. Biomed. Anal. 153

(2018) 135–144. doi:10.1016/j.jpba.2018.02.031.

4. C. Sánchez, C.P. Lienemann, J.L. Todolí, Metal and metalloid determination in


Spectrochim. Acta Part B At. Spectrosc. 115 (2016) 16–22.

doi:10.1016/j.sab.2015.10.011.

5. C. Sánchez, C.P. Lienemann, J.L. Todolí, Analysis of bioethanol samples through

Inductively Coupled Plasma Mass Spectrometry with a total sample consumption

system, Spectrochim. Acta - Part B At. Spectrosc. 124 (2016) 99-108.

doi:10.1016/j.sab.2016.08.018.

6. R. Sánchez, C. Sánchez, C.P. Lienemann, J.L. Todolí, Metal and metalloid determination

in biodiesel and bioethanol, J. Anal. At. Spectrom. 30 (2015) 64–101.

doi:10.1039/C4JA00202D.

7. C. Sánchez, S.E. Maestre, M.S. Prats, J.L. Todolí, Ion balance in waters through

inductively coupled plasma optical emission spectrometry, Int. J. Environ. Anal. Chem.

94 (2014) 427-440. doi:10.1080/03067319.2013.853762.

8. R. Sánchez, C. Sánchez, J.L. Todolí, C.P. Lienemann, J.M. Mermet, Quantification of

nickel, vanadium and manganese in petroleum products and biofuels through

inductively coupled plasma mass spectrometry equipped with a high temperature

single pass spray chamber, J. Anal. At. Spectrom. 29 (2014) 242-248.

doi:10.1039/c3ja50146a.

374

Patents

1. Carlos Sánchez Rodríguez; José Luis Todolí Torró; Sistema para la determinación

simultánea de cationes y aniones en muestras acuosas mediante ICP-AES. Entity

holder of rights: Universidad de Alicante Country of inscription: Spain Date of register:

18/02/2013

Conference contributions

1. C. Sánchez; C.P. Lienemann; J.L. Todolí. Development of Analytical Methodologies

Based in ICP for Bioethanol Elemental Analysis and Related Samples. 2018 Winter

Conference on Plasma Spectrochemistry (poster). Amelia Island, United States of

America, January 2018. Poster award

2. C. Sánchez; E. Bolea-Fernández; M. Costas-Rodríguez; C.P. Lienemann; J.L. Todolí; F.

Vanhaecke. Direct Isotope Analysis in Bioethanol Samples Using a Total Sample

Consumption System Coupled to a Multi-Collector ICP-MS Unit. 2018 Winter

Conference on Plasma Spectrochemistry (oral communication). Amelia Island, United

States of America, January 2018. Participation granted with a travel student award

3. C. Sánchez; C.P. Lienemann; F. Vanhaecke; J.L. Todolí. Determination of metals and

metalloids in bioethanol samples using a total sample consumption system coupled to

ICP techniques. Colloquium Spectroscopicum Internationale XL (oral communication).

Pisa, Italy, June 2017.

4. C. Sánchez; F. Chainet; C.P. Lienemann; J.L. Todolí. Removing interferences in organic

solvents and petroleum products by hTISIS-ICP MS/MS. Colloquium Spectroscopicum

Internationale XL (poster). Pisa, Italy, June 2017. Poster award

5. J.L. Todolí; R. Sánchez; C. Sánchez; F. Chainet; C.P. Lienemann. Elemental analysis of

petroleum products and biofuels through ICP techniques. Total sample consumption

and universal calibration. Rio Symposium on Atomic Spectrometry (invited/keynote

talk), Vitoria (Espiritu Santo), Brazil, April 2017.

6. C.P. Lienemann; C. Sánchez; F. Chainet; M. Milliand; L. Ayouni; S. Carboneux; J.L.

Todolí; A. Desprez. Recent improvements of the ICP/MS capabilities of the 8800 for

the petroleum industry. American Chemical Society National Meeting & Exposition

(oral communication). San Francisco, United States of America, April 2017.

Scientific impact

375

7. C. Sánchez; C.P. Lienemann; F. Chainet; M.L. Milliand; L. Ayouni; S. Carbonneaux; J.L.

Todolí; A. Desprez. Study of various contaminants in the refining industry using the

8800 Triple quadrupole ICP/MS Agilent. Rio Symposium on Atomic Spectrometry (oral

communication). Vitoria (Espiritu Santo), Brazil, April 2017.

8. C.Sánchez, C.P. Lienemann, J.L. Todolí. Development of methodologies for the

quantification of metals and metalloids in bioethanol. RSC Twitter Poster Conference

2017. March 2017.

9. C. Sánchez; C.P. Lienemann; J.L. Todolí. Fundamental studies on the ions distribution

in ICP-MS for ethanol-water matrices and its application to the determination of

metals in bioethanol. European Winter Conference on Plasma Spectrochemistry (oral

communication). Sankt Anton am Arlberg, Austria, February 2017. Participation

granted with a Young Scientist Award

10. J.L. Todolí; C. Sánchez; C.P. Lienemann. Improving ICP accuracy for the analysis of

bioethanol samples by applying a new total consumption sample introduction device.

8th Nordic Conference on Plasma Spectrochemistry (invited/keynote talk). Loen,

Norway, June 2016.

11. C. Sánchez; C.P. Lienemann; J.L. Todolí. Détermination de métaux dans le bioéthanol

par ICP/MS et l'utilisation d'une chambre à consommation totale. Spectr'atom 2016

(poster). Pau, Midi-Pyrénées, France, May 2016.

12. J.L. Todolí, C. Sánchez, C.P. Lienemann. Bioethanol analysis through ICP-MS using a

total sample consumption system. Winter Conference on Plasma Spectrochemistry

(poster). Tucson, Arizona, United States of America, January 2016,

13. J.L. Todolí; A. Cañabate; C. Sánchez. Evaluation and characterization of commercial

micronebulizers. Winter Conference on Plasma Spectrochemistry (poster). Tucson,

Arizona, United States of America, January 2016.

14. J.L. Todolí; C. Sánchez; C.P. Lienemann. Monitoring metals and metalloids during the

bioethanol manufacturing process. Winter Conference on Plasma Spectrochemistry

(poster). Tucson, Arizona, United States of America, January 2016.

15. A. Cañabate; C. Sánchez; E. García; C. Flórez; M. Aramendia; M. Resano; J.L. Todolí.

Analysis of whole blood with a total sample consumption system coupled to ICP-MS.

Euroanalysis. European Conference on Analytical Chemistry (poster). Bordeaux,

France, September 2015.

376

16. S. Carballo Marrero; C. Sánchez; S. E. Maestre; S. Prats; J.L. Todolí. Assessment of the

application of the novel MW-HPLC technique for triglycerides characterization on

vegetable oils. Euroanalysis. European Conference on Analytical Chemistry (poster).

Bordeaux, France, September 2015.

17. C. Sánchez; C.P. Lienemann; J.L. Todolí. Determination of trace metals in bioethanol

through a simple and accurate preconcentration method in ICP techniques.

Euroanalysis. European Conference on Analytical Chemistry (poster). Bordeaux,

France, September 2015.

18. C. Sánchez; C.P. Lienemann; J.L. Todolí. Universal calibration for ICP techniques for

direct quantification in bioethanol and other water-ethanol mixtures. Euroanalysis.

European Conference on Analytical Chemistry (poster). Bordeaux, France, September

2015.

19. C. Sánchez; C.P. Lienemann; J.L Todolí. Development of analytical methodologies for

the determination of metals and metalloids in bioethanol samples. Primeras Jornadas

de Investigadores Noveles (poster). La Nucia, Spain, September 2015.

20. C. Sánchez; C.P. Lienemann, J.L. Todolí. Le dosage de metaux dans les bio ethanols par

les techniques a plasma par couplage inductif. Spectr’atom 2015 (invited/keynote

talk). Halifax, Canada, May 2015.

21. C. Sánchez; C.P. Lienemann; J.L. Todolí. Determination of metals and metalloids in

bioethanol through ICP techniques. European Winter Conference on plasma

Spectrochemistry 2015 (oral communication). Münster, Germany, February 2015.

22. C. Sánchez; A. Cañabate; A. Villaseñor; C.P. Lienemann; J. L Todolí. Biofuel

Characterization: new method for metal and metalloid analysis by ICP-MS. Jornadas

de Investigación Departamental San Alberto Magno 2014 (poster). Alicante, Spain,

November 2014.

23. R. Sánchez; C. Sánchez; C.P. Lienemann; J.L. Todolí. Analysis of Petroleum Products

Through ICP-MS. 2014 Winter Conference on Plasma Spectrochemistry (poster).

Amelia Island, Florida, United States of America, January 2014.

24. C. Sánchez; C.P. Lienemann; J.L. Todolí. Analysis of bioethanol through ICP-MS. 2014

Winter Conference on Plasma Spectrochemistry (poster). Amelia Island, Florida,

United States of America, January 2014.

Scientific impact

377

25. C. Sánchez; R. Sánchez; C.P. Lienemann; J.L. Todolí. Determination of heavy metals in

fuels through ICP-AES and ICP-MS. XVI Jornadas de Investigación Departamental "San

Alberto Magno" (poster). Alicante, November 2012.

26. J.L. Todolí; R. Sánchez; C. Sánchez; F. Ardini; M. Grotti; C.P. Lienemann; J.M. Mermet.

ICP Organic and Inorganic sample analysis with a high temperature micro sample

introduction system. The Great Scientific Exchange (SCIX) (invited/keynote talk).

Kansas City, United States of America, September 2012.

27. J.L. Todolí; D. Veracruz; R. Sánchez; C. Sánchez; S. Prats; S. Maestre; A. Carrasco.

Microwave digestion pretreatment for the determination of metals impurities in

pharmaceuticals through ICP-MS. Winter Conference on Plasma Spectrochemistry

(poster). Tucson (Arizona), United States of America, January 2012.

28. D. Veracruz; R. Sánchez; C. Sánchez; S. Prats; S.E. Maestre; A. Carrasco; J.L. Todolí.

Determination of Heavy Metals in pharmaceuticals through inductively coupled

plasma mass spectrometry. 2011 European Winter Conference on Plasma

Spectrochemistry (poster). Zaragoza, Aragon, Spain. January 2011.

29. J.L. Todolí; S. Maestre; C. Sánchez. Ionic Balance in Mineral Waters Through the

simultaneous determination of anions and cations through ICP-AES. Winter

Conference on Plasma Spectrochemistry (poster). Fort Myers (Florida), United States

of America, January 2010.

30. C. Sánchez; J.L. Todolí. Simultaneous determination of anions and cations in mineral

waters through ICP-AES. International Conference on Biodegradable Polymers and

sustainable Composites (Biopol 2009) (poster). Alicante, Spain, September 2009.

Research stays

1. Entity: Ghent University, Faculty of Sciences, Department of Chemistry. Ghent,

Belgium. Start-End date: 29/05/2017 - 22/12/2017 Duration: 7 months

Tasks: Isotopic analysis of bioethanol samples by means of MC-ICP-MS.

2. Entity: Institute Français du Pétrole Energies Nouvelles (IFPEN). Lyon, Rhône-Alpes,

France. Start-End date: 26/09/2016 - 14/10/2016 Duration: 3 weeks

Tasks: Analysis of biofuels and petroleum products by means of hTISIS-ICP-MS/MS.

378

3. Entity: Institute Français du Pétrole Energies Nouvelles (IFPEN) and Institute des

Sciences Analytiques (ISA). Lyon, Rhône-Alpes, France. Start-End date: 16/11/2015 -

04/12/2015 Duration: 3 weeks.

Tasks: Evaluation and validation of the system hTISIS for the analysis of biofuels

through ICP-OES and ICP-MS/MS.


France. Start-End date: 20/09/2014 - 03/10/2014 Duration: 2 weeks.

Tasks: Implementation of hTISIS-ICP-OES in the laboratories of IFPEN.


France. Start-End date: 02/09/2013 - 29/11/2013 Duration: 3 months.

Tasks: Validation of the universal injector (hTISIS) for introduction of petroleum

products in optical ICP.

PhD CARLOS SANCHEZ RODRIGUEZ (Version sin articulos ...

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