MULTIDIMENSIONAL CHROMATOGRAPHIC

TECHNIQUES FOR MONITORING AND CHARACTERIZATION OF ENVIRONMENTAL SAMPLES

E. Mateus1, A. Ribeiro1, M. da Silva2 & P. Marriott3

1CENSE, Universidade Nova de Lisboa-FCT/DCEA, Campus Caparica, Portugal 2REQUIMTE, Universidade Nova de Lisboa-FCT/DQ, Campus Caparica, Portugal

3Monash University, Centre for Green Chemistry, Melbourne, Australia

Limitation of conventional GC

•  Peak capacity

•  A 50 m column has a peak capacity of 250 peaks (R=1)

o Statistical theory of component overlap - STO

A sample with 100 components in order to separate 50

will need a column with a capacity to separate 290

analites

•  Peak capacity limited physically and statistically

•  Insufficient separation for complex samples in 1D-GC

In 1D co-elutions

occur

Analytes

Structural Similarities

Wide Concentration Ranges

Problems in separation,

detection and identification

Adittionally ...

1

2

3

Trace analytes undetectable

Often the trace compounds

are the more important

Analytical Strategies

ü Multidimensional techniques

–  Comprehensive two-dimensional gas

chromatography (GC×GC)

–  Heart cutting gas chromatography

…more accurate characterization of samples

Thermal Modulator

GC×GC: The system

The GC x GC System

2 capillary columns – different phases

2 independent separation mechanisms (boiling point vs polarity)

1 interface – modulator

Column 1: Boiling point separation (e.g. DB-5) Column 2: Polarity separation (e.g.DB-17 or DB-wax)

GCxGC-FID - Modulated

GC×GC modulation increases sensitivity

Classical 1D GC - Non Modulated

S/N Increases

GC×GC increases sensitivity

1D-GC

GCxGC-FID

100 Hz

Polluted Soil sample

Hydrocarbons Column bleeding

Nothing?

100 Hz

E. Mateus et al, J. Chrom A, 1217, 1845- 1855, 2010.

2 D r

eten

tio

n (s

)

1D retention (min)

GC×GC: Overview of the separation structured contour plot

Scale effect: separation

seems to form a diagonal

band

Section enlargement:

3D plot shows a good

resolution

Creosote Volatiles

from railway wood sleepers

The amount of

information

implies an identification

challenge….

GC×GC: increased peak capacity

1 2

4

3

TOF:

High spectral

acquisition rate

Skewed-free spectra

MS deconvolution

GC×GC - new information about composition especially for minor

compounds not revealed in 1D-GC analysis.

GC×GC/TOFMS vs 1D-GC/TOFMS

1

2 3

4

x 5

4 5

x

6

6

x 1) dichlorobenzene 2) 1,4 - cineol 3) α-terpinene 4) Unknown Mol. W. = 150?

4

1 2

3

4

GC×GC/TOFMS vs 1D-GC/TOFMS

4 = 4 + 5 + 6 6 in 1D-GC will be hard to find

1

2 3

4

x

5

4 5

x

6

6

x

1) diclorobenzene 2) 1,4-cineol

3) α-terpinene 4) Disulfite isopropil C6H14S2

5) o-cimene 6) trimethylbenzene (pseudocumene)

GC×GC/TOFMS

GC×GC/TOFMS vs 1D-GC/TOFMS

GCxGC/TOFMS: what does it give?

Compound separation “better” detection

“true” mass spectra “better” identification

More information

Creosote Volatiles

Anolythe

Catholyte

Monitorization of

Electrokinetic remediation

Remediation technique

that

uses a low-level dc

current

as the "cleaning agent".

GCxGC/TOFMS

Anolyte

Catholyte

ca. 500 compounds Phenols S-, O-heterocycles Less basic N-heterocycles (eg. nitrile compounds) PAHs

ca. 300 compounds Azaarene compounds (basic N-heterocycles)

76 common compounds due to diffusion

processes

after the electrokinetic process

GCxGC-­‐FID  

INJ FID

M  

GCxGC-FID

Column sets

Non Polar x Polar

Polar x nonPolar

Monitorization of

target compounds

in environmental

complex samples

LMCS

5 10 15 20 25 30 35 40

5

4

3

2

1

0

min

s

10 15 20 25 30 35 40 45 50

STTIRSO_2D_CSV_x

Column set:

Non polar x polar

GCxGC-FID

Particulate air pollution (PM10): Classical set

5 10 15 20 25 30 35 40

5

4

3

2

1

0

min

s

25 38 50 63 75 88 100

CLAT_2D_CSV_x_x

Parafins

Naphthenes mono aromatics

Di aromatics

Naphthene diaromatica

Tri aromatics

Column set :

mid polar x non polar

GCxGC-FID

Particulate air pollution (PM10): reverse set

alkanes alkenes cyclic aliphatics aromatics ketones/aldehydes alcohols acids

Remember that GCxGC provides a

Structured Retention in 2D Space?

" 2D location is function of analyte chemical property

– e.g.. boiling point and polarity

" .. and we can “see” the 2D space as a ‘chemical

property MAP’

5 10 15 20 25 30 35

6

5

4

3

2

1

0

min

s

25 38 50 63 75 88 100

HC2D2d_CSV_x_x

Standard solution with

n-hydrocarbons C9 – C30

Standard injection

GCxGC-FID

Particulate air pollution (PM10) - Standards

Column set :

mid polar x non polar

5 10 15 20 25 30 35 40

6

5

4

3

2

1

0

min

s

25 38 50 63 75 88 100

PAHS2D2D_CSV_x_x

Standard injection

GCxGC-FID

Particulate air pollution (PM10) - Standards

Standard solution with

16 PAHs mix

Column set :

mid polar x non polar

5 10 15 20 25 30 35 40

5

4

3

2

1

0

min

s

25 38 50 63 75 88 100

CLAT_2D_CSV_x_x

GCxGC-FID

Particulate air pollution (PM10) - Sample

Column set :

mid polar x non polar Standard solutions

hydrocarbons + PAHs

naphthalene  

B(a)P  

B(b)F  B(k)F  

B(a)A  Chrysene  

Acenaphthylene  acenaphthene  

Fluorene  

Phenanthrene  anthracene  

Fluoranthrne  pyrene  

GCxGC-FID

Particulate air pollution (PM10) – PAHs mix

B(a)P  

naphthalene  

B(a)P  

B(b)F  B(k)F  

B(a)A  Chrysene  

Acenaphthylene  acenaphthene  

Fluorene  

Phenanthrene  anthracene  

Fluoranthrne  pyrene  

GCxGC-FID

Particulate air pollution (PM10) – sample

30 32 34 36 38 40

5

4

3

2

1

0

min

s

25 38 50 63 75 88 100

CLAT_2D_CSV_x_x_x_x

Benzo[a]pyrene zone

GCxGC-FID

Particulate air pollution (PM10)

30.625 30.750 30.875 31.000 31.125 31.250 31.375 31.500

5

4

3

2

1

0

min

s

15 20 25 30 35 40 45 50 55

CLAT_2D_CSV_x_x_x_x_x_x_x

Benzo[a]pyrene

GCxGC-FID

5 10 15 20 25 30 35

6

5

4

3

2

1

0

min

s

25 38 50 63 75 88 100

SOILGALP2D_CSV_x_x

Polluted Soil

GCxGC-FID

5 10 15 20 25 30 35 40

5

4

3

2

1

min

s

25 38 50 63 75 88

MR4_2D2D_CSV_x_x_x

Surface water

GCxGC-FID

5 10 15 20 25 30 35

6

5

4

3

2

1

0

min

s

25 38 50 63 75 88 100

SOILGALP2D_CSV_x_x

5 10 15 20 25 30 35 40

5

4

3

2

1

min

s

25 38 50 63 75 88

MR4_2D2D_CSV_x_x_x

5 10 15 20 25 30 35 40

5

4

3

2

1

0

min

s

25 38 50 63 75 88 100

CLAT_2D_CSV_x_x

Air particles

Surface water

Soil

Different Matrices different chromatographic “Maps”

GCxGC-FID

MDGC-FID: Heart-Cut with Dean Switch

MD-GC / DS/CT

DS  

INJ DET  2   EPC

M  

2  

1  

       DET  1  

Monitorization of

target compounds

in environmental

complex samples LMCS

Dean Switch

Target Analysis MDGC – Dean switch OFF

B(a)P

B(a)P

B(a)P

Target Analysis MDGC – Dean switch ON

MDGC – Cryotrap HC vs classical HC

B(a)P without Cryotrap

B(a)P with Cryotrap Ø Improved peak symmetry

Ø Higher S/N (x 4.5)

Heart cut – No Cryotrap vs Cryotrap

No Cryotrap

Cryotrap

Confirmation by

Standard injection

MDGC-FID: Heart-Cut with Dean Switch

MDGC - Particulate air pollution (PM10)

B(a)P interferences

Surface water

not detected

Soil

Huge

interference detected

Now… Methylquinoline (MQ) in creosote samples

(m a in lib )  Q u in o lin e ,  2 -­‐m e th yl-­‐1 0 2 0 3 0 4 0 5 0 6 0 7 0 8 0 9 0 1 0 0 1 1 0 1 2 0 1 3 0 1 4 0 1 5 0

0

5 0

1 0 0

2 73 9 5 1

5 8 6 3 7 1 7 5 8 9 1 0 1

1 1 5 1 2 8

1 4 3

N

(m a in lib )  Q u in o lin e ,  3 -­‐m e th yl-­‐5 0 6 0 7 0 8 0 9 0 1 0 0 1 1 0 1 2 0 1 3 0 1 4 0 1 5 0

0

5 0

1 0 0

5 1 5 7 6 37 0 7 5 8 7

8 9

1 0 1

1 1 5

1 2 8 1 4 0

1 4 3

N

(m a in lib )  Q u in o lin e ,  4 -­‐m e th yl-­‐2 0 3 0 4 0 5 0 6 0 7 0 8 0 9 0 1 0 0 1 1 0 1 2 0 1 3 0 1 4 0 1 5 0

0

5 0

1 0 0

3 9 5 1 5 7 6 3 7 1 7 7 8 9 1 0 4

1 1 5

1 2 8

1 4 3

N

(m a in lib )  Q u in o lin e ,  5 -­‐m e th yl-­‐2 0 3 0 4 0 5 0 6 0 7 0 8 0 9 0 1 0 0 1 1 0 1 2 0 1 3 0 1 4 0 1 5 0

0

5 0

1 0 0

2 7

3 9

4 1

5 1

5 7

6 3

6 5 7 5 8 78 9

1 0 1

1 1 5

1 2 8

1 4 3

N

(m a in lib )  Q u in o lin e ,  6 -­‐m e th yl-­‐2 0 3 0 4 0 5 0 6 0 7 0 8 0 9 0 1 0 0 1 1 0 1 2 0 1 3 0 1 4 0 1 5 0

0

5 0

1 0 0

3 9 5 1 5 8 6 3 7 1 7 58 9

1 1 5

1 4 3

N

(m a in lib )  Q u in o lin e ,  7 -­‐m e th yl-­‐2 0 3 0 4 0 5 0 6 0 7 0 8 0 9 0 1 0 0 1 1 0 1 2 0 1 3 0 1 4 0 1 5 0

0

5 0

1 0 0

2 73 9 5 1 5 8 6 3

7 1 7 58 9

1 1 5

1 4 3

N

(m a in lib )  Q u in o lin e ,  8 -­‐m e th yl-­‐2 0 3 0 4 0 5 0 6 0 7 0 8 0 9 0 1 0 0 1 1 0 1 2 0 1 3 0 1 4 0 1 5 0

0

5 0

1 0 0

3 9 5 1 5 8 6 3 7 07 5

8 9

1 1 5

1 4 3

N

MS Differences…???

Output from Mass spectra database for

Methylquinoline

shows…..

2MQ

7MQ 3MQ

6MQ 4MQ

8MQ

x-MIsoQ y-MIsoQ

(262°C)

(258°C) (252°C)

(258°C)

(248°C) (248°C)

91%

94%

92%

67%

93%

94%

6MQ

8MQ

7MQ

8MQ

6MQ

63% 7MQ

5MQ

…that frequently more

information is needed

e.g. physical properties

E. P. Mateus et al, J. Chrom. A. 1178, 215-222, 2008.

91%

94%

92%

67%

93%

94%

6MQ

8MQ

7MQ

8MQ

6MQ

63% 7MQ

5MQ

Methylquinoline

Boiling point separation, BPX5 column (non polar)

Polarity separation, BPX50 column (polar)

Human factor very

important and does

the difference!!!

Zhang Blagjo ST

Kae

Grace

Sunny

Phil Marriott

Lucy

ACKNOWLEDGEMENTS

•  Project ELECTROACROSS - Electrokinetics across disciplines and continents: an integrated approach to finding new strategies for sustainable development

(FP7-PEOPLE-2010-IRSES/MC-IRSES-269289).

All the people

from Phillip Marriott Lab

at Monash University,

Australia

Dr. Rui Rocha, Dr. Jitka Zrostlíková from LECO Corp.

Thank  you  very  much    

for  your  a@enAon  

C3 Naphtalenes C2 Naphtalenes

C12

C13 C15

C16