comprehensive two dimensional

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Comprehensive two-dimensional

gas chromatography for theanalysis of organohalogenatedmicro-contaminantsPeter Korytar, Peter Haglund, Jacob de Boer, Udo A.Th. Brinkman

We explain the principles of comprehensive two-dimensional gas chroma-

tography (GC GC), and discuss key instrumental aspects with emphasison column combinations and mass spectrometric detection. As the main item

of interest, we review the potential of GC GC for the analysis of organo-

halogenated micro-contaminants, and highlight its superiority over conven-

tional 1D-GC. We present results for 12 compound classes, including

polychlorinated biphenyls, dibenzo-p-dioxins and furans, and n-alkanes,

toxaphene and polybrominated diphenyl ethers. We draw attention to target

analysis as well as within-class and between-class separations.

2006 Elsevier Ltd. All rights reserved.

Keywords: Comprehensive two-dimensional gas chromatography; GC GC; Mass

spectrometry; Organohalogenated compound; Separation

1. Introduction

In 1966, the Swedish chemist Jensen [1]

announced that he had identified a group

of organochlorine compounds that was

accumulated to toxic concentrations in

nature. Unlike the closely related chlori-

nated pesticides, such as DDT and the

various drins which had, so far,

attracted most attention of environmental

chemists the newly detected compounds,

the polychlorinated biphenyls (PCBs), had

entered the environment essentially

unintentionally. Since that time, these twoclasses of persistent organic pollutants,

which shared high annual production,

widespread usage, long persistence and

serious toxic effects, have been the subject

of a rapidly increasing number of funda-

mental as well as applied studies. Over the

years, many related classes of compounds

have been added to the list; Table 1 gives

an overview, and also lists the number of

theoretically possible congeners, which

gives an impression of the degree of com-

plexity that can be expected in technical

mixtures and, thus, in environmental and

food samples. For the rest, we assume that

the general reader will be familiar with the

main characteristics and usage of the

various classes of organohalogens and, at

least in some cases, with the catastrophes

or otherwise, which led to their being

considered priority pollutants by many

governments and international (UN, EU)

bodies.

During the entire past half-century, gas

chromatography with electron-capture

Peter Korytar*

Netherlands Institute for Fisheries Research,

P.O. Box 68, NL-1970 AB IJmuiden,

The Netherlands

Free University, Department of Analytical Chemistry and Applied Spectroscopy,

de Boelelaan 1083, NL-1081 HV Amsterdam,

The Netherlands

Peter Haglund

Umea University, Department of Chemistry, Environmental Chemistry,

SE-901 87 Umea, Sweden

Jacob de BoerNetherlands Institute for Fisheries Research,

P.O. Box 68, NL-1970 AB IJmuiden,

The Netherlands

Udo A.Th. Brinkman

Free University, Department of Analytical Chemistry and Applied Spectroscopy,

de Boelelaan 1083, NL-1081 HV Amsterdam,

The Netherlands

*Corresponding author.

E-mail: [email protected]

Trends in Analytical Chemistry, Vol. 25, No. 4, 2006 Trends

0165-9936/$ - see front matter 2006 Elsevier Ltd. All rights reserved. doi:10.1016/j.trac.2005.12.003 3730165-9936/$ - see front matter 2006 Elsevier Ltd. All rights reserved. doi:10.1016/j.trac.2005.12.003 373
mailto:[email protected]:[email protected]


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detection (GCECD) was the predominant analytical

technique for selective and sensitive determination of

organohalogens. In the early part of that period, when

packed-column GC was the only means of separation

available, total-PCB determination (based on comparing

an environmental sample with a technical PCB mixture)

was all that could be achieved. The introduction of

(fused-silica) capillary columns was a real breakthrough,

which, all of a sudden, enabled congener-specific deter-

mination of the PCBs and, of course, also of the other

classes of organohalogens. However, it also became clear,

after this major step forward, that capillary GC was notthe solution for all, or even most, problems. Admittedly,

single-column (or one-dimensional, 1D) GC can provide

the required resolution when the number of target ana-

lytes is restricted (e.g., with the organochlorine pesticides

(OCPs) or polychlorinated naphthalenes (PCNs)).

However, even for the PCBs with their still moderate

number of 209 congeners, or for the about 140 CB

congeners present in a technical mixture, no satisfactory

1D-GC solution could be found. And, not surprisingly,

correspondingly more serious problems were encoun-

tered with complicated mixtures, such as toxaphene,

polychlorinated terphenyls (PCTs) and, specifically,

polychlorinated alkanes (PCAs); the PCAs typically show

up in 1D-GC as an essentially unresolved broad band

covering a major part of the baseline. The magnitude of

the problem becomes even clearer when one considers

that the present discussion is about within-class separa-

tions only: interferences caused by other organohalogens

and/or matrix constituents or problems due to widely

different concentrations of (partly) co-eluting congeners

have not been taken into account.

Over the years, several approaches have been used to

alleviate the problems. One of these was sample frac-

tionation (e.g., by size-exclusion or adsorption liquid

chromatography). Another was to filter out interferences

by selective mass spectrometric (MS) detection, which is

powerful but fails to resolve co-elutants with closely

similar mass spectra, as is often the case for congeners of

the same compound class, but also of different classes.

On the GC side, one way to go was the parallel use of

several stationary phases and the combination of infor-mation from the GC runs on different columns to solve

specific separation problems. It was a step further to

combine two different columns in a single set-up: in so-

called multi-dimensional GC (MDGC), selected fractions

from the first column are subjected to a second GC run

that uses a completely different separation mechanism.

Many successful applications have been reported, but one

should keep in mind that, in essentially all cases, they are

of a heart-cutting nature: only a single, or at best a few,

small fractions are transferred to the second column for

further separation. That is, it is an excellent solution

when information is required about a few target analytes,

but not about the entire sample. In the latter instance (i.e.with complex samples and/or when unknowns have to be

traced), MDGC becomes much too complicated and time-

consuming. It is in these situations and their number

can confidently be said to be increasing daily that a so-

called comprehensive approach is needed: MDGC, or GC

GC, is now replaced by GC GC, with which, instead of a

few selected fractions, the entire sample is subjected to

separation on two different columns. One immediate

advantage is that the information content is much

greater, and another is that the GC GC run is ready once

the first-dimension run is finished; that is, GC GC is

much more efficient than MDGC.It is the goal of this review briefly to explain the

principle of GC GC and to discuss key aspects, such as

column-to-column interfacing or modulation, detection

and detector requirements (including a comparison of

time-of-flight MS (TOF-MS) and fast-scanning quadru-

pole MS (qMS) instruments) and the selection of properly

matched column combinations.

We will devote most attention to applications in the field

of organohalogenated micro-contaminants, which will

also be used to highlight the added value of GC GC

compared with 1D-GC. Readers who are interested in a

more detailed review of the various aspects of GC GC and

in applications to compound classes other than organo-

halogens, should consult two extensive reviews [2,3].

2. GC GC: general principle

In GC GC, the entire sample is subjected to two GC

separations that are based on different separation

mechanisms. Fig. 1 shows a schematic of a GC GC

system. In most instances, the sample is first separated

on a high-resolution capillary GC column typically a

1530 0.250.32 mm ID, 0.11 lm df column

Table 1. Main classes of polyhalogenated micro-contaminants

Name Acronym Maximumnumber ofcongenersa

Polychlorinated biphenyls PCBs 209Polychlorinated dibenzo-p-dioxins PCDDs 75

Polychlorinated dibenzofurans PCDFs 135Toxaphene components Toxaphene 61 696

bornane congeners 16 640camphene congeners 12 288dihydrocamphene congeners 32 768

Organohalogenated pesticides OCPs ca. 300Polychlorinated terphenyls PCTs 8149Polychlorinated diphenylethers PCDEs 209Polychlorinated naphthalenes PCNs 75Polychlorinated alkanes PCAs Very highPolybrominated biphenyls PBBs 209Polybrominated diphenylethers PBDEs 209

aEnantiomers not included.

Trends Trends in Analytical Chemistry, Vol. 25, No. 4, 2006

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containing a non-polar stationary phase. As will be

explained in Section 3, an interface called a modulator is

used to separate the first-column eluate into a very large

number of adjacent small fractions. To maintain the

first-column separation, these fractions should be no

larger than one quarter of the peak width, or r, in that

dimension. In order to meet this so-called modulation

criterion, temperature programming in GC GC is

slower than in 1D-GC, and typically occurs at a rate of

13C/min. Each individual fraction is trapped, re-

focused and, next, launched into the second GC column,

which is much shorter and narrower than the first one

typical dimensions are 12 m 0.1 mm ID 0.1 lm df.

The second-column separation generally is of a polar

or shape-selective nature. That is, the separation

mechanisms are indeed different or, in other words,

orthogonal separation conditions have been created. The

separation in the second column is extremely fast and

usually takes only 28 s as against 45120 min for the

first-dimension separation. Consequently, it is performed

under essentially isothermal conditions. The fast sepa-

ration in the second dimension causes the analyte peaks

to be very narrow with widths of, typically, 100600 ms

at the baseline. These narrow peaks require fast detectors

with a small internal volume and a short rise time in

order to achieve a proper reconstruction of the (second-

dimension) chromatograms. In some systems, the second

column is housed in a separate oven to allow more

flexible, independent temperature programming.

The outcome of a GC GC run is a large series of high-

speed, second-dimension chromatograms, which are

usually stacked side by side to form a two-dimensional

Figure 1. Schematic of a GC GC system with different modulator types.


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(2D) chromatogram with one dimension representing the

retention time on the first column and the other the

retention time on the second column. The most conve-

nient way to visualize these chromatograms is as contour

plots, where peaks are displayed as spots in a 2D plane

using colors and/or shading to indicate signal intensities.

Apex plots, which use specific symbols to indicate theposition of the peak apexes, are another frequently used

means to display GC GC chromatograms; the overall

presentation becomes much simpler, and that is espe-

cially advantageous when ordered structures are studied

(in this review, apex plots are used (e.g., Figs. 4 and 8)

and are combined with contour plots (e.g., Figs. 9 and

10); contour plots are also displayed (e.g., Figs. 2 and 5).

There is general agreement regarding the main

advantages of GC GC over 1D-GC. Most strikingly, the

peak capacity is much higher, and that yields a dramat-

ically improved separation of the analytes of interest from

each other but also and this is often even more impor-

tant from interfering matrix constituents. In addition, amain benefit of the trapping-plus-refocusing occurring

during modulation is, typically, a 310-fold improved

signal-to-noise ratio compared with 1D-GC. Finally,

compound identification is more reliable in GC GC be-

cause each substance now has two identifying retention

values rather than one. Specifically, when orthogonal

conditions are used, chemically related compounds show

up as so-called ordered structures (i.e. as clusters or

bands). This phenomenon greatly facilitates group-typeanalysis, fingerprinting studies and the provisional clas-

sification of unknowns. It is particularly important in the

study of classes of organohalogens, as will become clear

from most of the figures included in Sections 6 and 7.

In the following sections, we will discuss in some detail

three topics of general analytical interest: modulation;

detection and analytical performance; and, column

selection.

3. Modulation

The key component of a GC GC instrument is themodulator that joins the two columns. It serves three

main goals:

Figure 2. GC GClECD chromatograms of PCA-60 technical mixture on DB-1 in the first dimension and each of the six columns indicated inthe second dimension [24].




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(i) collecting and focusing of each of the fractions elut-

ing from the first-dimension column;

(ii) re-injecting/launching of each collected fraction

into the second-dimension column; and,

(iii) trapping of the next eluent fraction from the first

column during the launch of the preceding

fraction.Over the years, different ways of modulating the first-

column effluent have been reported (Fig. 1). Initially,

heating was preferred, with a rotating slotted heater, the

sweeper, rapidly moving over a thick-film modulation

capillary, heating it locally. Despite its frequent use in

the early years of GC GC, because of the vulnerability

of the set-up, the time-consuming optimization of the

multi-parameter design and the restricted application

range, the sweeper and related modulator types are

obsolete today.

The first major step forward was the introduction of

the longitudinally modulating cryogenic system (LMCS).

This modulator uses expanding CO2 (liquid) for trappingof the analytes at the top of the second-dimension col-

umn. By subsequently moving the trap rapidly to an

upstream position, the re-focused zone is exposed to the

GC oven air and instantaneously volatilized and laun-

ched. Today, jet-based modulators with no moving

parts at all with either CO2 or liquid N2 for cooling

are generally preferred. Single-, dual- and quad-jet

modulators have been introduced, and several of these

have been extensively compared in a recent study [4].

The main conclusion was that all cryogenic modulators,

if properly optimized, can satisfactorily be used for most

applications, and certainly for those in the field oforganohalogen analysis. One caveat should be added. In

order to ensure proper modulation of high-boiling com-

pounds (i.e. highly substituted congeners), cooling

should be just enough to trap the target compounds

safely. Cooling that is too strong can cause remobiliza-

tion to be inefficient and may lead to distorted and/or

tailing peaks [5]. In addition, severe cooling will lead to

more bleed from the first-dimension column being

accumulated and that, in turn, will yield noisier second-

dimension chromatograms. Some studies have indicated

that modulation of high-boiling compounds can easily be

achieved by air cooling [6]. If found to be true in further

studies, this will make GC GC of organohalogens less

expensive and simpler to operate.

4. Detection

As briefly mentioned in Section 2, detectors with a high

data-acquisition rate and a negligible internal volume

are required to describe properly the very narrow peaks

that are the outcome of a GC GC run. Flame ionization

detectors (FIDs) have data-acquisition rates up to 200 Hz

and dead volumes that are effectively zero. It does not

therefore come as a surprise that virtually all early

GC GC studies were carried out with an FID, including

those dealing with organohalogens [7]. However, as

soon as real-life studies and analyte detectability became

an issue of interest, it became clear that FID would have

to be replaced by ECD to obtain sufficient selectivity and

sensitivity. Conventional ECDs have data-acquisitionrates up to 50 Hz, but the main problem is their 1.5-ml

cell volume, which causes severe peak broadening [8].

Kristenson et al. [4] showed that, from amongst the

miniaturized ECDs marketed in recent years, only the

Agilent micro-ECD (lECD) with an internal volume of

150 ll gives acceptable peak widths. The best results

were obtained when working at the maximum flow of

make-up gas (150 ml/min) and at temperatures above

300C. However, as is to be expected, even under opti-

mum conditions, the lECD delivers about 2-fold broader

peaks than an FID [9]. All recent GC GClECD studies

use an Agilent detector.

The main problem of element-selective detection ingeneral and, therefore, also of ECD is that no struc-

tural information is provided. In other words, MS is

indispensable for identification/confirmation of the

numerous separated compounds, whether target ana-

lytes or unknowns. Today, the preferred choice is a TOF-

MS that can, typically, acquire up to 50500 mass

spectra per second (with unit mass resolution). The

coupling of GC GC separation and TOF-MS detection

presents no difficulties, and there is no additional peak

broadening. This is true for both conventional electron

impact (EI) ionization and the recently introduced elec-

tron-capture negative ionization (ECNI) mode. An addi-tional advantage of a TOF-MS is that the sensitivity is

higher than that of the full-scan mode of conventional

scanning MS detectors, while the high acquisition rate

prevents spectral skewing, and deconvolution conse-

quently becomes a very powerful tool.

Unfortunately, TOF-MS instruments are very expen-

sive. From the start therefore, the potential and limita-

tions of qMS instruments, which are available in

essentially all GC laboratories, were investigated by

several groups of workers [1013]. Briefly, the outcome

of these studies was that, for restricted mass ranges of

150200 Da, acquisition rates of 2030 Hz can be ob-

tained, and that tentative identification is then indeed

often possible, but that proper quantification cannot be

achieved on the basis of the 35 data points registered

across a peak. Recently, the situation has improved (i.e.

when two rapid-scanning qMSs were marketed, the

Shimadzu QP 2010 and the Perkin Elmer Clarus 500,

which allow scanning up to 10,000 Da/s [14,15]).

Table 2 provides an illustrative comparison of these two

instruments and a state-of-the-art conventional qMS. A

clear indication of the improved performance is that, if

the lower limit of the peak width at the baseline is set at

300 ms, the conventional qMS is restricted to a mass




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range of about 100 Da, whilst 23-fold larger ranges can

be handled by rapid scanning detectors. This is fullysatisfactory for many, and certainly for most, organo-

halogen applications. In the selected ion monitoring

(SIM) mode, acquisition rates of up to 90 Hz can be used

when only one ion is monitored (i.e. seven data points

can be collected even for peaks having a baseline width

of only 80 ms). While the present conclusions are grat-

ifying, they do not imply that rapid-scanning qMS

instruments can replace TOF-MS in all instances, as,

particularly when a wide mass range has to be covered

(e.g., in searching for unknowns), TOF-MS has to be

used.

4.1. Analytical performance data

Analyte detectability and linearity are influenced by

quite a number of parameters such as GC conditions

and set-up, and the number of modulations but the

key factor is the detector used. Table 3 shows instru-mental limits of detection (iLODs) and dynamic ranges

for various detectors and compound classes quantified

so far by GC GC. The data can be called fully

satisfactory, specifically the iLODs, which are 35-fold

lower than in 1D-GC due to peak re-focusing in the

modulator.

5. Columns and column combinations

To summarize, and simultaneously extend, what has so

far been said about columns or, more appropriatelycolumn combinations to be used in GC GC, in

essentially all early studies, a conventional 1530 m

non-polar first-dimension column was combined with a

Table 3. Analytical performance data for various detectors and classes of organohalogens

Detector (mode) Class/compound iLOD [pg] Linearity* Reference

Range [pg] R 2

lECD PCBs 0.010.07 1400 >0.999 [9,19,20]PCDD/Fs 0.040.15 0.1200 >0.998 [9,19]2,3,7,8-TCDD 0.09 0.140 >0.998 [9,19]

TOF-MS (EI) PCBs 0.110 0.51000 >0.993 [22,37]PCDD/Fs n.a. 0.2500 >0.996 [36,38]2,3,7,8-TCDD 0.20.5 0.5200 >0.996 [36,38,63]PBDEs 5 0.22000 >0.994 [37]OCPs 510 51000 >0.991 [37]

qMS (EI, scan 50 Da) PCBs 12 101000 >0.997 [15]

qMS (ECNI, SIM) PBDEs 1040 n.a. n.a. [14]PCDD/Fs 10710 n.a. n.a. [14]2,3,7,8-TCDD 710 n.a. n.a. [14]

*n.a., not available.

Table 2. Comparison of performance of two rapid-scanning and a conventional qMS in GC GC [11,1315,62]

Mass range (Da) ornumber of ions monitored

Perkin Elmer Clarus 500 Shimadzu QP 2010 Agilent MSD HP 5973

maximumacquisition (Hz)

minimumpeak widtha (ms)


minimumpeak widtha(ms)


minimumpeak widtha(ms)

Full scan

400 17 410 20 350 12 540300 23 300 25 280 15 470200 31 230 33 210 20 350100 63 110 50 140 n.a. n.a.

SIM1 ion 91 80 n.a. 33 2102 ions 45 160 n.a. 18 3903 ions 30 230 n.a. 12 580

n.a., not available.aCalculated for seven points per peak from: minimum peak width = 7/maximum acquisition.




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much shorter, narrower (medium-)polar or shape-

selective second-dimension column. Using such a

non-polar more polar column set has three distinct

advantages:

A wealth of information on the 1D-GC separation of

the compound classes of interest is available in the

literature and can be used for the first-dimensionseparation.

The non-polar columnsalso have a high thermal stabil-

ity and, consequently, cause little bleeding. As was

shown in one study [19], use of some polar columns

in the first dimension (e.g., an LC-50or a DB-Dioxin sta-

tionary phase) can cause LODs to be 10 times higher.

While in the first dimension there is a truly volatility-

based boiling-point separation, for all other, more

selective columns, separation will indeed be mainly

governed by specific analyte/stationary phase interac-

tions with, however, also a volatility-based contribution.

Fortunately, the extremely rapid second-dimension

separation will be essentially isothermal. This impliesthat, for sample constituents present in each individual

first-dimension effluent fraction (which will have clo-

sely similar boiling points), there will be no volatility

contribution. In other words, the two separation

mechanisms are indeed independent, and the condi-

tions are orthogonal.

In the early literature on GC GC, most of the above

was already clearly understood and, possibly because of

this and also because of a rather limited availability of

short and narrow-bore second-dimension columns, not

too much attention was devoted to optimizing the

selection of column combinations. In recent years, this

attitude has changed and, today, several interesting

studies on, specifically, second-dimension column selec-

tion are available notably in the context of organo-halogen analysis [1923]. We include illustrative

examples in Sections 6 and 7 below. The present dis-

cussion is therefore limited to two comments:

(i) when aspects such as nature of substituents (Cl vs.

Br), molecular shape (planar vs. non-planar) or

parent-compound nature (aromatic vs. non-

aromatic) play a role, even a brief study of

second-column characteristics can be most reward-

ing; and,

(ii) the column combination providing the best struc-

tural ordering (often considered the Number

One criterion) does not always offer the best

overall resolution of a class of compounds (highlyrelevant when unraveling the composition of rela-

tively unknown mixtures such as toxaphene or

PCAs).

As an example, Fig. 2 shows what is found when a

non-polar DB-1 first-dimension column is combined with

six different second-dimension columns for the study of

PCAs [24]. In this case, using 007-65HT as the second

column yielded optimal structural ordering (less band

Table 4. First- and second-dimension columns used for GC GC of organohalogens

Code Phase References

First-dimension columnsDB-1, HP-1, VF-1ms 100% methylpolysiloxane [19,20,2224,33,35,37,54]Rtx-Dioxin 2 Proprietary [36]Rtx-500 Proprietary (carborane) [38]HT-5 5% phenyl-methylpolysiloxane (carborane) [19]HT-8 8% phenyl-methylpolysiloxane (carborane) [22]DB-XLB Proprietary [9,19,21,22]DB-Dioxin Proprietary (44% methyl, 28% phenyl, 20% cyanopropyl,

8% polyoxyethylene-polysiloxane)[19]

LC-50 50% liquid crystalline-methylpolysiloxane [7,19]Chirasil-Dex 2,3,6-tri-O-methyl-b-cyclodextrin [2527]BGB-172 25% 2,3,6-tert.-butyldimethylsilyl-b-cyclodextrin [28]BGB-176SE 20% 2,3-di-O-methyl-6-O-tert.-butyldimethyl-b-cyclodextrin [28]

Second-dimension columnsBPX-5 5% phenyl-methylsilphenylene [7]HT-8 8% phenyl-methylpolysiloxane (carborane) [19,20,2224,35,37,54]Rtx-500 Proprietary (carborane) [36]DB-17 50% phenyl-methylpolysiloxane [35]BPX-50 50% phenyl-methylpolysiloxane (silphenylene) [19,22,38]007-65HT 65% phenyl-methylpolysiloxane [19,23,24]OV 1701, DB-1701 14% cyanopropyl-phenyl-methylpolysiloxane [19,35]BPX-70 70% cyanopropyl polysilphenylene-siloxane [21]SP-2340 100% biscyanopropyl polysiloxane [21]VF-23ms Proprietary (7090% cyano-containing polymer) [19,23,24,26,27]007-210 50% trifluoropropyl-methylpolysiloxane [19,23,24]LC-50 50% liquid crystalline-methylpolysiloxane [9,19,21,2326]SupelcoWax-10, CP-WAX-52CB Polyethylene glycol [19,23,24,27,33,35]




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overlap than with SupelcoWax-10 and LC-50), but, with

VF-23ms, a much larger part of the 2D-separation space

was used and overall resolution was, consequently,

better.

The only exception to what was said above is in the

area of chiral separations. Since separations such as

those of the pairs of atropisomeric PCBs require longcolumns and long run times for these applications,

the more discriminating (i.e. in this case shape-selective)

column is used in the first dimension [2528]. As can be

seen in Table 4, substituted b-cyclodextrins were the

preferred stationary phases in these studies. Relevant

examples are included in Section 6 below.

6. Within-class separations

6.1. Polychlorinated biphenyls (PCBs)

PCBs are products of anthropogenic activity and com-

prise a class of chlorinated aromatic compounds with110 chlorine atoms attached to a biphenyl backbone.

In total, there are 209 CB congeners; the presence of

about 140 of these has been confirmed in technical

formulations, such as Aroclors and Clophens, and also in

environmental samples.

For regulatory and monitoring purposes, seven CBs

(CBs 28, 52, 101, 118, 138, 153 and 180) have been

selected because of their abundance in humans and in

foodstuff of animal origin, and they are often called the

EU indicator CBs.

In the past two decades, much attention has been paid

to the toxicology of PCBs, particularly to the congenersthat show the same type of toxicity as polychlorinated

dibenzo-p-dioxins and dibenzofurans (PCDD/Fs), the

so-called dioxin-like or WHO CBs. They include four

non-ortho (CBs 77, 81, 126 and 169) and eight mono-

ortho (CBs 105, 114, 118, 123, 156, 157, 167 and 189)

substituted CBs.

Due to restricted rotation around the central CC bond

of biphenyl, some CB congeners occur as enantiomers.

Separation of such enantiomer pairs is interesting, since

it enables the study of enantioselective bioaccumulation

and biodegradation. There are 19 such pairs (CBs 45,

84, 88, 91, 95, 131, 132, 135, 136, 139, 144, 149,

171, 174, 175, 176, 183, 196 and 197), which exist as

stable atropisomers at ambient or physiological temper-

atures.

The separation of any of the groups of CBs listed above

and, specifically, of all CB congeners from each other and

from the plethora of matrix constituents is a challenging

task. Even though 1D-GC (with ECD or MS detection)

can separate some 100150 CB congeners, there still is

no unambiguous chromatographic separation of the 12

WHO CBs, or even the seven EU indicator CBs, from the

209 congeners or, even, the 140 present in technical

formulations [29]. To achieve the intended goal, it is

necessary to use sample fractionation, multiple injec-

tions on different stationary phases, heart-cut multidi-

mensional GC or columns coupled in series. It should,

therefore, come as no surprise that, since the introduc-

tion of GC GC, there have been many attempts to use

this technique for improving separation of PCBs.

There are over 20 papers [4,5,79,15,1923,2528,3038] that discuss PCB separation by GC GC.

However, most of these use PCBs merely as test analytes

to optimize and/or demonstrate modulator tuning,

proper modulator or detector performance, and instru-

ment set-up. These studies have clearly contributed to

the development of robust GC GC procedures but

provide little information on the separation itself. The

present review therefore mainly discusses papers aimed

at improving separation and/or detection of CB cong-

eners [7,2022,32] and the atropisomeric CB pairs

[2528].

The first study on the GC GC separation of PCBs was

presented by Phillips and Xu [32], who used theretention database of all 209 CBs published for 20 sta-

tionary phases [39] to construct 2D gas chromatograms.

The authors did not discuss the separation of individual

congeners, but they predicted structured chromato-

grams for the non-polar semi-polar DB-1 CNBP

column combination. The CBs in the 2D plane were

grouped together according to the number of chlorine

substituents, and the position of the congeners within a

homologue group was determined by the number of

ortho chlorines, with the retention sequence being:

4 < 3 < 2 < 1 < 0.

In 2001, Haglund et al. [7] analyzed PCBs in technicalClophen A50. The authors used a rather unconventional

column set-up, with a highly shape-selective liquid

crystal LC-50 (10 m 0.15 mm 0.1 lm) column in the

first dimension and a non-polar BPX-5 (0.25 m 0.1

mm 0.1 lm) column in the second dimension. The

non-ortho CBs were most strongly retained by the LC-50

column, followed by the mono-, di- and multi-ortho CBs.

As a consequence, the non- and mono-ortho congeners

eluted at the highest temperature within each homo-

logue group, and the toxic non-ortho CBs 77, 126 and

169 and the mono-ortho CBs 105, 118 and 156 all

showed up in the lower right-hand corner of the contour

plot. In order to achieve reasonable second-dimension

elution times (10C/min) had to be used.

Under these conditions, all six planar CBs quoted above

were successfully separated from other CBs present in

the mixture within a run time of only 17 min. In addi-

tion, the seven EU indicator CBs were also adequately

resolved. In our opinion, despite the excellent separation

of the non-ortho CBs from the other congeners, their

quantification may be problematic, because the excessive




9/24

bleed of the LC-50 phase at the elevated temperatures at

which non-ortho CBs elute will also be modulated and

dramatically increase the noise level and, thus, increase

the LODs. In addition, the column combination does not

allow the determination of the many other CBs, because,

due to the fast temperature programme required, the

separation power of the first-dimension column cannotbe used fully and many CBs co-elute.

In 2002, Korytar et al. [20] tested three column

combinations for the separation of 90 CBs with emphasis

on the separation of the 12 WHO CBs. They preferred

a classical set-up, with a non-polar HP-1 (30 m

0.25 mm 0.25 lm) separating solely on the basis of

volatility in the first dimension, and three more polar

phases, BPX-50, HT-8 and SupelcoWax-10 (all 1 m 0.1

mm 0.1 lm), in the second dimension. A complete

separation of the WHO CBs from each other and from the

other CBs was obtained with the latter two columns.

With HP-1

SupelcoWax-10, only six congeners wereinvolved in co-elutions, as against 12 congeners for

HP-1 HT-8. However, the latter combination provided

the highest information content, because structured

chromatograms were obtained. The CBs were found to

be grouped together according to the number of chlorine

Table 5. Co-eluting PCBs on six column combinations [21,22]*,**

DB-1 HT-8 HT-8 BPX-50 DB-XLB BPX-50 DB-XLB SP-2340 DB-XLB LC-50 DB-XLB BPX-70

Non-ortho CB congeners 77/144

Mono-ortho CB congeners 118/131a

Marker CB congeners 52/69 153/168 101/90 101/90 153/168138/163/164

Other CB congeners 23/54a 132/179a 38/47/62a 21/33 4/10 31/53a

16/32 160/175a 20/21/33 47/62/65 20 /33 47/62/6520/21/33 20/33 66/155 42/59 43/69 42/5943/49 47/48 84/89 37/40a 62/65 57 /94a

48/75 93/95/98 90 /101 57/94a 58/67 86/11242/59 112/119 107/123 58/67 63/76 106 /10741/64 97/117 63/76 88 /95 175/18261/70 108/107 86/125 84/8956/60 163/164 107/134a 83/119

98/102 182/187 160/163 86/12588/91 175/182 160 /16383/112 201/204 175/182a

115/116 196/203 201/204108/107 196/203139/149134/143146/165182/187196/203

No. of CBs resolved byGC GC

163 188 191 176 181 194

No. of CBs resolved byGC GCMS

165 192 192/194 184 183 198

Temperature ramp (C/min) 1 1 1 1.5 1.5 0.5

Modulation time (s) 3 3 3 4 5 5

Run time (min) 140 146 144est. 100est. 90 240

, all congeners separated.aResolved by MS.est.Run time not explicitly mentioned in paper; estimated from available information.*CB congener classification according to their presence in any of the Aroclors 1242, 1254 or 1260: Bold, >1.0 wt.%; Bold, 0.051.0 wt.%;italics, trace or undetected.**IUPAC numbering is used. Numbering of [21] was corrected accordingly.




10/24

substituents and, within a group, the number of ortho

chlorines. This is the structure predicted by Phillips and

Xu [32], but now verified experimentally. The ordered

structure is very useful because it helps to predict the

position of other CB congeners in the 2D plane. This

enabled the prediction, on the basis of published 1D-GC

retention data, that the WHO CBs will be separated fromall other congeners present in Aroclor mixtures. In

addition, a large number of unknown peaks detected in a

cod-liver extract could be provisionally identified as CB

congeners.

The effort to analyze PCBs by means of GC GC cul-

minated in two recent studies [21,22], in which attempts

were made to separate all 209 CBs. In these studies,

seven column combinations were evaluated. The sepa-

ration for six of these is visualized in Table 5. The

DB-XLB HT-8 set-up is not included because it pro-

vided a very limited improvement over 1D-GC due to the

very similar separation mechanisms applied in both

dimensions. When comparing the data of Table 5, oneshould keep in mind that the results also depend on run

time or, more precisely, the temperature ramp during

elution, and on modulation time. In general, slower

elution and a shorter modulation time yield more effi-

cient separation. Table 5 therefore includes these two

parameters. As for the DB-1 HT-8 column combina-

tion, the ordered structure quoted above has been con-

firmed for all CBs (Fig. 3). The separation of the

homologue groups was so clear cut that only one

co-elution of two congeners, CBs 23 and 54, was caused

by the overlapping of two (tri- and tetra-substituted)

homologue series. All other co-elutions occurred within

these series. For the rest, this column set performed

much poorer, in terms of number of congeners resolved,

than the other column combinations. Because most

co-eluting compounds have closely similar mass spectra,

additional separation by means of MS detection is pos-sible in a limited number of cases only such as here for

CBs 23 and 54.

As regards the other column sets, the best result was

found for DB-XLB BPX-70, which separated 198

congeners. However, the run time was as high as 4 h, or

almost double that of most other procedures and it is

questionable whether, in several instances, a limited

overall increase of resolution justifies such an excessive

demand of time. In other words, from a practical point of

view, HT-8 or DB-XLB combined with BPX-50 or

DB-XLB LC-50 are to be preferred with the first two

sets separating 192 congeners in 2.5 h, and the latter a

lower number (183) of analytes, but in a very short time(1.5 h). Two of these combinations separate all WHO

CBs and EU indicator CBs. The HT-8 BPX-50 set has

the added advantage of yielding structured chromato-

grams. For the penta-CBs, this is shown in the apex plot

of Fig. 4, which also clearly visualizes the non-ortho-

number-based sub-division.

One should consider that the above separations were

studied with the congener concentrations in the stan-

dard mixture being essentially the same and with

RS > 0.5 as the separation criterion. As is well known,

Figure 3. GC GCTOF-MS chromatogram of all CB congeners on DB-1 HT-8 column set [22].




11/24

this resolution will not be satisfactory for quantifying

partly co-eluting congeners with widely different con-

centrations, as is often true for PCBs and other classes oforganohalogens in real-life samples. Even if RS > 1, the

determination of the WHO CBs in one run together with

predominant congeners may be difficult.

Another problem was encountered when the target

analytes had to be determined in a seal-blubber sample

[21]. After the usual sample treatment, some of them

were found to be present in concentrations too low to be

detected by GC GClECD. One solution would be to

concentrate the extract. However, some of the major

congeners would then overload the second-dimension

column and, in addition, it would be difficult to keep all

congeners within the working range of the detector.Therefore, two separate injections will be required.

6.1.1. Chiral analysis. With atropisomeric CBs, the

preferred method is heart-cut MDGC [29]. Most

reported methods use two-oven systems and comprise

an achiral precolumn and a chiral main column. Heart

cuts (from the precolumn) containing the atropisomers

of interest and, inevitably, other PCBs or interferences

are directed towards the chiral column. With typical

precolumns, such as DB-5 or DB-XLB, three or four out

of the 11 atropisomeric pairs present in technical for-

mulations co-elute with some of the 140 CBs [29] and

must be separated in the second dimension. Chirasil-

Dex (permethylated 2,3,6-tri-O-methyl-b-cyclodextrin)

is the most commonly used chiral column that can

resolve nine out of the 19 stable, and seven out of the

11 interesting pairs of chiral congeners [29]. The

column sequence used in heart-cut MDGC has to be

changed for GC GC, because the second-dimension

column must be short and, if a short chiral column is

used, no separation of the enantiomers would be

achieved (i.e. the chiral column is used in the first

dimension, and a polar or shape-selective column in the

second dimension).

In all published papers [2528], Chirasil-Dex was used

as the first-dimension column; in one study [28],

BGB-172 (25% 2,3,6-tert.-butyldimethylsilyl-b-cyclo-dextrin) and BGB-176SE (20% 2,3-di-O-methyl-6-O-

tert.-butyldimethyl-b-cyclodextrin) were also evaluated.

As second-dimension columns, Bordajandi et al. tested

HT-8, VF-23ms and SupelcoWax-10 for 65 [28] or 90

[27] CBs, whilst Harju et al. [25,26] used VF-23ms and

LC-50 for all 140 Aroclor CBs. The results of the latter,

more comprehensive study are displayed in Table 6. It

shows that all nine atropisomeric pairs, which are

resolved on Chirasil-Dex, partly or completely co-elute

with one or more CBs in 1D-GC, while all but two or

three of the co-elutions are resolved in the second

dimension. As an application, grey-seal tissue was ana-lyzed on both column combinations. Seven out of the

nine atropisomeric pairs were detected, and enantio-

meric fractions could be determined for six of these (CBs

91, 95, 132, 135, 149 and 174) by using lECD and/or

TOF-MS detection; the second eluting enantiomer of CB

84 co-eluted with CB 56. The most abundant

Table 6. Co-elutions for nine atropisomeric CB pairs in 1D-GCand GC GC with 140 Aroclor CBs [26]*

Atropisomeric

CBs

Co-elutants on

Chirasil-Dex (CD) CD VF-23ms CD LC-50

84 56, 90, 99, 101 56 9991 63 95 93 93

132 176, 141 141 141 (0.7)a

135 110, 82 136 115 149 77, 124 174 202 176 132, 141

aRS in second dimension.*For classification code, see Table 5.

0.7

1

1.3

1.6

1.9

4200 4700 5200 5700 6200 67001tR (s)

2tR

(s)

103 100

94102

88

91

84

89989593

127

126

104

96

111 120

124

105

122114

106118

123

108

107

121

92

90

113

99

101

112,119

10983

12587

8611085

115116

97,117

82

0 50 50 5

989593

1098386116

Figure 4. GC GCTOF-MS apexplotof thepenta-CBson HT-8 BPX-50columnset. Pink, tetra-orthoCBs; green, tri-orthoCBs;red,di-orthoCBs;light blue, mono-orthoCBs; dark blue, non-orthoCBs. Boxes represent co-eluting congeners [22].




12/24

atropisomers, CBs 135, 149 and 174, had enantiomeric

fractions (EFs) close to the racemic value, while the EFs

for CBs 91, 95 and 132 invariably deviated significantly

from that value.

6.2. Polychlorinated dibenzo-p-dioxins/furans

(PCDD/Fs)PCDD/Fs are highly toxic compounds formed as

by-products during a variety of chemical and combus-

tion processes [40]. Notorious examples are their (trace-

level) presence in technical PCB mixtures, chlorinated

phenoxyalkanoic acid pesticides and fly ash. The number

of chlorine substituents can vary from one to eight to

produce up to 75 CDD and 135 CDF positional isomers.

There is a pronounced difference in toxic and biological

effects amongst these CDD/F congeners and toxicities

vary 1,00010,000-fold. Seven 2,3,7,8-substituted

CDDs and 10 CDFs are generally considered the most

toxic, since they have toxic properties similar to 2,3,7,8-

tetrachlorodibenzo-p-dioxin (2,3,7,8-TCDD), which isthe most toxic congener of the group. Consequently, the

analytical challenge is to detect, and quantify, these 17

priority congeners and, also, the 12 WHO CBs discussed

above (which also show a dioxin-like effect). Such ultra-

trace analyses are expensive, both because of the time-

consuming pre-treatment and clean-up, and the need to

use GChigh-resolution MS (GCHRMS) with its unri-

valled sensitivity and selectivity [18]. In other words,

sample throughput is low and cost is high. Not surpris-

ingly, therefore, the potential of GC GC with its

improved selectivity is eagerly explored to find less

demanding but equally rewarding analytical ap-proaches.

The first attempt to analyze dioxins and dioxin-like

CBs by GC GC was made by Grainger et al. [16,17].

They used an early sweeper for modulation and HRMS

(resolution power 3000) for detection of a 24-compound

mixture containing the non-ortho CBs 77, 81, 126 and

169 and a suite of PCDD/Fs. Rather unconventional

column dimensions were used: a very short first-

dimension DB-5 column (2 m 0.25 mm 0.25 lm)

and a rather long second-dimension OV-1701 column (3

m 0.1 mm 0.05 lm). With this set-up, the separation

took only 18 min, with an impressive iLOD of 335 attog

(S/N 9) for 2,3,7,8-TCDD. Unfortunately, no further

information was provided.

As a part of their PCB study quoted above, Korytar

et al. [20] tried to separate the priority CDD/Fs and WHO

CBs from each other and the bulk of 90 CBs on

HP-1 HT-8. The outcome was successful for all except

one pair of target analytes, 1,2,3,7,8-PeCDD/CB 169.

This stimulated a further search for a column combi-

nation that would separate all target compounds from

each other and, as importantly, from matrix

co-extractants. In a subsequent study [19], therefore,

seven first-dimension and eight second-dimension

columns were tested. With a 100% methylpolysiloxane

stationary phase (DB-1) in the first dimension to create

orthogonal conditions, all congeners with different toxic

equivalency factor (TEF) values could be separated if

VF-23ms or LC-50 were used in the second dimension.

When other types of first-dimension column were used

(and orthogonality was partly sacrificed), a DB-XLBcolumn combined with 007-65HT, VF-23ms or LC-50

gave a complete separation of all 29 priority congeners.

With a spiked, fractionated milk extract, DB-XLB LC-

50 was found to be the most powerful column combi-

nation, because of the good separation of all priority

congeners from each other as well as matrix constitu-

ents. Analytical performance was satisfactory with a

close to 3-order linearity, and iLODs of 30150 fg

injected mass.

Two of the quoted column sets the preferred

DB-XLB LC-50 and also VF-1 LC-50 were used by

Danielsson et al. [9,41], who studied the quantification

of dioxins and dioxin-like CBs by GC GClECD. Fish oilfrom herring, spiked cows milk, vegetable oil and an eel

extract were analyzed by two GC GC and four

GCHRMS laboratories, with the latter serving as refer-

ences. Fig. 5 shows typical GC GClECD chromato-

grams of the mono-ortho-CB, and non-ortho-CB and

CDD/F fraction of herring oil on DB-XLB LC-50, and

clearly demonstrates the efficiency of the LC-50 phase to

separate the target analytes from matrix co-extractants.

The quantification data for WHO CBs obtained on both

GC GClECD systems were closely similar and agreed

very well with the GCHRMS data. As for the dioxins,

data produced on DB-XLB LC-50 also showed goodagreement, but this was not true for VF-1 LC-50 due to

interferences co-eluting with some congeners. For the

rest, the CVs were somewhat higher for GC GC than for

HRMS (540% vs. 227%). The total toxic equivalent

(TEQ) data obtained on the preferred GC GC system

compared well with those obtained by GCHRMS, with

CVs for both techniques being below 10%. These results

show that the proposed method meets the EC require-

ments for a WHO CDD/F-plus-CB screening method,

which should have a false negative rate of less than 1%

and a TEQ CV of less than 30%. However, more samples

need to be analyzed to confirm fully the criterion for the

false negative rate. For the rest, as Danielsson et al. noted

[9,41], before GC GClECD can be considered a con-

firmatory method, the EC Directives will have to be

revised; currently, MS is the only mode of detection

allowed for this purpose.

Focant et al. [36,38] devoted two studies to GC GC

TOF-MS. In their first report [36], Rtx-Dioxin 2 was

employed as the first-dimension column because it is

known for its excellent separation of the priority CDD/Fs

from each other and also from non-2,3,7,8-substituted

congeners. For the second dimension, they selected a

relatively non-polar Rtx-500 column (similar to HT-8),




13/24

because they expected the second dimension to bringmore in terms of signal enhancement after modulation

than added resolution retention on that column

should, consequently, be rather weak. An iLOD of 0.5 pg

was obtained for 2,3,7,8-TCDD. As for the separation of

the 17 CDD/Fs and the four non-ortho CBs analyzed, one

co-elution persisted in both dimensions (viz between CB

126 and 2,3,7,8-TCDD). This co-elution is especially

problematic because CB 126 is usually present in con-

centrations one or two orders of magnitude higher than

2,3,7,8-TCDD, causing a serious over-estimation of the

sample TEQ due to the much higher toxicity of 2,3,7,8-

TCDD. The problem was solved by deconvoluting the

masses involved. The congener-specific data found by

GC GCTOF-MS and GCHRMS for various environ-

mental (sediment, fly ash) and biological (vegetation,

fish) samples showed good agreement for 2,3,7,8-TCDD

and most other congeners.

However, in their next study [38], the authors used

another column combination, Rtx-500 BPX-50. All

priority CDD/Fs and four non-ortho CBs were then

separated and, in a next run, all EU indicator and

mono-ortho CBs were also separated from each other

and other CBs. The iLOD of 2,3,7,8-TCDD improved to

an impressive 0.2 pg. The system was used to analyze

fish, pork, and milk samples and the results werecompared with conventional GCHRMS. Not unex-

pectedly, the earlier conclusions on CBs were con-

firmed. For the CDD/Fs, the results were strongly

concentration dependent. When the average congener

concentrations were rather high (above 0.4 pg/g fat

weight, which corresponds to 1.1 pg of compound in-

jected), as for fish, and a large sample intake was used

(15 g), the two techniques showed good agreement.

But, again, the CVs for GCHRMS were 714%, as

against 1060% for GC GCTOF-MS. With pork and

milk, for which the CDD/F concentrations were much

lower (above 0.030.1 pg/g fat weight), there were

many over-estimations with CVs up to 90%. However,

the congener distribution was still well defined in all

instances and can be used (e.g., for tracking sources of

contamination). Despite the problems, the TEQ results

for the CDD/Fs and CBs compared favorably with those

of GCHRMS because a rather good description of the

main TEQ contributors (2,3,7,8-TCDD, 1,2,3,7,8-

PeCDD and 2,3,4,7,8-PeCDF) was achieved.

6.3. Toxaphene

Toxaphene is an organochlorine pesticide mixture of

complex composition. The major constituents are

Figure 5. GC GClECD of the (A) mono-ortho-CB and (B) non-ortho-CB and CDD/F fractions of a fish oil on DB-XLB LC-50. Assignment for(B): 1, CB 77; 2, CB 126; 3, CB 169; IS1, 1,2,3,4-TCDD; 4F1, 2,3,7,8-TCDF; 4D1, 2,3,7,8-TCDD; 5F1, 1,2,3,7,8-PeCDF; 5F2, 2,3,4,7,8-PeCDF;5D1, 1,2,3,7,8-PeCDD; 6D3, 1,2,3,7,8,9-HxCDD; IS2, 1,2,3,4,6,7,9-HpCDD; 7D1, 1,2,3,4,6,7,8-HpCDD; 8D1, OCDD [9].




14/24

chlorobornanes (ca. 75 wt.%), with chlorocamphenes

in second place, while chlorodihydrocamphenes are

present as minor components [42]. Individual members

of these compound classes have been isolated from the

technical mixture, and they are likely products of

synthesis. The presence of chlorobornenes, which has

also been reported [42] as a possible class of constitu-ents, is discussed at the end of this section. The number

of congeners that can be found theoretically exceeds

60,000 (cf. Table 1). 1D-GC, which is the method of

choice to study the composition of technical toxaphene,

cannot create a satisfactory separation. Typically, about

100 peaks show up in a GCECD chromatogram. Better

results were obtained by combining GC with other

separation techniques, such as adsorption chromatog-

raphy on silica [43] or active carbon [44], normal-

phase LC [45], or heart-cut MDGC [46]. With these

techniques, the number of compounds in technical

toxaphene was estimated to be at least 177 [43], 246

[45], 300 [46], and 675 [44]; all quoted methods werevery time-consuming (e.g., the 675-peak experiment

required pre-fractionation into no less than 160 frac-

tions with a subsequent 30-min GC analysis of each

fraction). In the environment and particularly in higher

organisms, many toxaphene constituents are degraded,

and only a few are bio-accumulated. This leads to a

significantly simpler toxaphene-residue pattern com-

pared to the technical mixture. One problem with the

quantification of individual congeners is the limited

availability of the standards. Today, only 23 standards

are commercially available (Table 7). Since various

nomenclature rules were proposed for the toxaphene

components [4753], each congener in Table 7 has

several names.

In view of the separation problems outlined above,

expectations were high when GC GC became available

as a tool to unravel the composition of complex mixtures

[54]. Indeed, the use of an HP-1

HT-8 column com-bination yielded highly structured chromatograms and

easily revealed a complex mixture of over 1000 com-

pounds in a run of less than 3 h. Subsequent analysis of

the 23-standard mixture and EI-TOF-MS evaluation of

technical toxaphene showed that the 2D chromatogram

is structured according to the number of chlorine sub-

stituents in a molecule (see Fig. 6), with little, if any,

dependence on the class of compounds (bornanes or

camphenes). The range of chlorination found with

GC GCEI-TOF-MS was 511 substituents per mole-

cule. Using home-made software to calculate the total

area for each iso-substitution band, hexa- to nona-

chlorinated compounds were found to be the majorcomponents of toxaphene and represented some 97% of

the total toxaphene mass.

In a more recent study [23], six column combina-

tions were tested for the separation of 12 classes of

organohalogenated compounds (see Section 7); one

of these was technical toxaphene. Ordered structures

were then also found for DB-1 combined with 007-210,

007-65HT or LC-50. Somewhat surprisingly, another

column combination, DB-1 VF-23ms, did not deliver

ordered structures but offered the best overall separa-

tion; the entire GC GC plane was used and visual

Table 7. List of 23 commercially available standards for toxaphene and their various codes

IUPAC name Parlar[47,48]

Nikiforov[49]

Wester et al.[50,51]

AV-code[52]

OK-code[53]

2,2,3-exo,8,9,10-hexachlorocamphene 11 C[032001]-(11)2-exo,3-endo,8,8,9,10-hexachlorocamphene 12 C[021001]-(21)2-exo,3-endo,7,8,9,10-hexachlorocamphene 15 C[021011]-(11)2,2,5,5,9,10,10-heptachlorobornane 21 HpCB-6533 B[30030]-(012) B7-499 99-0132,2,3-exo,8,8,9,10-heptachlorocamphene 25 C[032001]-(21)2-endo,3-exo,5-endo,6-exo,8,8,10,10-octachlorobornane 26 OCB-4921 B[12012]-(202) B8-1413 198-3032,2,3-exo,8,8,9,9,10-octachlorocamphene 31 C[032001]-(22)2,2,5-endo,6-exo,8,9,10-heptachlorobornane 32 HpCB-6452 B[30012]-(111) B 7-515 195-1112,2,5,5,9,9,10,10-octachlorobornane 38 OCB-6535 B[30030]-(022) B8-789 99-033

2,2,3-exo,5-endo,6-exo,8,9,10-octachlorobornane 39 OCB-6964 B[32012]-(111) B8-531 199-1112-endo,3-exo,5-endo,6-exo,8,9,10,10-octachlorobornane 40 OCB-4917 B[12012]-(112) B8-1414 198-1132-exo,3-endo,5-exo,8,9,9,10,10-octachlorobornane 41 OCB-3223 B[21020]-(122) B8-1945 41-1332,2,5-endo,6-exo,8,8,9,10- octachlorobornane 42a OCB-6460 B[30012]-(211) B8-806 195-3112,2,5-endo,6-exo,8,9,9,10-octachlorobornane 42b OCB-6454 B[30012]-(121) B8-809 195-1312-exo,5,5,8,9,9,10,10-octachlorobornane 44 OCB-2455 B[20030]-(122) B8-2229 97-0332-endo,3-exo,5-endo,6-exo,8,8,9,10,10-nonachlorobornane 50 NCB-4925 B[12012]-(212) B9-1679 198-3132,2,5,5,8,9,10,10-octachlorobornane 51 OCB-6549 B[30030]-(112) B8-786 99-1132,2,5-endo,6-exo,8,8,9,10,10-nonachlorobornane 56 NCB-6461 B[30012]-(212) B9-1046 195-3132,2,3-exo,5,5,8,9,10,10-nonachlorobornane 58 NCB-7061 B[32030]-(112) B9-715 103-1132,2,5-endo,6-exo,8,9,9,10,10-nonachlorobornane 59 NCB-6455 B[30012]-(122) B9-1049 195-1332,2,5,5,8,9,9,10,10-nonachlorobornane 62 NCB-6551 B[30030]-(122) B9-1025 99-0332-exo,3-endo,5-exo,6-exo,8,8,9,10,10-nonachlorobornane 63 NCB-3261 B[21022]-(212) B9-2206 169-3132,2,5,5,6-exo,8,9,9,10,10-decachlorobornane 69 DCB-6583 B[30032]-(122) B10-1110 227-133




15/24

inspection showed that, here, the highest number of

congeners was observed. The column sets that yielded

ordered structures indicated the presence of a cluster of

unknown compounds (Fig. 6). This group of com-

pounds was not observed in the earlier study [54],

because the temperature programme then used was

much slower. This caused much more spreading of the

toxaphene congeners in the 2D plane; wrap-around

occurred and led to co-elution with the unknown

compounds. Combined information on the peak shapes

and the ECNI-TOF mass spectra added as inserts dem-

onstrated that the unknowns were decomposition

products formed during the first-dimension GC run (i.e.

chlorinated bornenes, probably formed by HCl elimi-

nation). So far, not a single polychlorinated bornene

has been isolated from technical mixtures and the

assumption about their presence was based only on

GCMS and GCFTIR data [42]. The observations cited

created serious doubts about the presence of bornenes

in technical toxaphene.

6.4. Polychlorinated alkanes (PCAs)

PCAs are complex mixtures with a degree of chlorina-

tion of 3070 wt.%, and carbon chain lengths of

C10C13 (short-chain PCAs), C14C17 (medium-chain

PCAs) or >C17 (long-chain PCAs). They are used as

extreme-pressure additives in industrial cutting fluids,

plasticizers and flame retardants for polyvinyl chloride

(PVC) and other plastics and rubbers, and as additives

in paints and sealants. PCAs are persistent and non-

biodegradable, and they accumulate in the food chain.

The global production of PCAs has been reduced since

the early 1980s [55], but is still in the range of

380,000 tons [56]. Short-chain PCAs cause particular

concern due to the high amounts released into the

environment, and their toxicity, which is higher than

that of other PCAs.

Analysis of PCAs is difficult because of the extreme

complexity of the mixtures and the lack of quantification

standards, and semi-quantification is all that can be

achieved. In many environmental studies dealing with

Figure 6. Total-ion GC GCECNI-TOF-MS chromatogram of technical toxaphene on DB-1 HT-8, with the mass spectra of two peaks asindicated. Lines indicate position of iso-substitution bands [23].




16/24

halogenated micro-contaminants, an essentially

unresolved band covering a large part of the GC baseline

is all that indicates the presence of PCAs. Currently,

some 40 individual standards are available, but most of

them, as will be demonstrated below, are not present in

the technical mixtures. Mixtures of PCAs, with various

chlorine contents and carbon-chain lengths, are used as

reference standards for semi-quantification. Analysis is

usually carried out by GC coupled to HRMS in ECNI

mode. The method is based on monitoring [MCl] ions

to determine the concentrations of individual classes (i.e.

congeners with the same number of carbon and chlorine

atoms). HRMS is highly selective and eliminates inter-

ferences caused by other polychlorinated pollutants and

Figure 7. (A) GC GCECNI-TOF-MS extracted ion chromatogram (m/z 7073) of polychlorinated decanes with 55 wt.% Cl.(B) GC GCECNI-TOF-MS chromatograms of C10C13 technical mixture with 55 wt.% Cl. Colored lines indicate the position of apices withinthe band of polychlorinated (red) decanes, (green) undecanes, (blue) dodecanes and (black) tridecanes. (C) Overlay of GC GCECNI-TOF-MSchromatograms of (red) short-, (green) medium- and (blue) long-chain PCA mixtures with different Cl content. White numbers indicate number of(carbon + chlorine) atoms of the compounds present in the bands [24].




17/24

PCAs with the same nominal mass. However, this

detection method is not available in many laboratories

and is too expensive for routine analysis, so low-resolution

MS (LRMS) is also used for quantification. An interna-

tional inter-comparison study for short-chain PCAs has

shown that the two techniques can give comparable

quantitative results (e.g., in biota [57,58]). Nevertheless,because of the increased risk of interferences, improved

sample clean-up and/or the use of GC GC instead of

1D-GC is urgently required.

The potential of GC GC was investigated in a recent

paper in which six column combinations were tested

[24]. The highest number of separated congeners was

found with the DB-1 VF-23ms combination, but, for

characterization and quantification, DB-1 007-65HT

was preferred because this set provided more informa-

tion in terms of ordered structures (i.e. group and sub-

group separation). As demonstrated for polychlorinated

decanes in Fig. 7A, the separation of PCA congeners

with the same chain length is based on the number ofchlorine substituents. The authors added that the

number of congeners in the technical mixtures (formed

by uncontrolled synthesis) was relatively rather limited.

If a larger number were present, the iso-substitution

bands would become broader and neighboring bands

would start to overlap. This is demonstrated in Fig. 7A

by the outlying positions of several individual congen-

ers, which should be considered unlikely products of

uncontrolled synthesis. With mixtures of PCAs of

varying chain length, the ordered structures comprise

compounds having the same number of carbon-plus-

chlorine atoms for example, C10Cl8 is on the samediagonal line as C11Cl7, C12Cl6 and C13Cl5. This is

elegantly visualized in Fig. 7B. The position of the

various compounds in each diagonal band depends on

the number of carbon atoms: compounds with longer

carbon chains have lower second-dimension retention

times. This carbon-chain-length selectivity creates a

distinct separation of compounds that differ by at least

three carbons; C10 and C13 compounds show no over-

lap in Fig. 7B. For a mixture of short-, medium- and

long-chain PCAs, the (carbon+chlorine)-based ordering

is seen to hold over a summed-number range of at least

14 to 26. In addition, the carbon-chain-length selec-

tivity creates a partial separation of the three PCA

groups (Fig. 7C). Obviously, using GC GC is a major

step forward in PCA analysis, although, simulta-

neously, it is also clear that additional separation power

possibly provided by LC-based sample fractionation

will be needed for a satisfactory overall unraveling of

the composition of PCA mixtures.

Two relevant examples of the added value of GC GC

compared to 1D-GC are as follows. In the quoted study

[24], two dust samples were analyzed, and significantly

different GC GClECD patterns of the short- and med-

ium-chain PCAs were easily observed. Visual evaluation

of the chromatograms showed that one sample con-

tained more medium- than short-chain PCAs and that

these medium-chain PCAs had a relatively low degree of

chlorination, while the other sample contained more

short- than medium-chain PCAs, with the short-chain

PCAs having a higher degree of chlorination. In other

words, pattern recognition based on the visual evalua-tion allowed provisional identification of sample com-

position.

Another advantage of GC GC is the elimination of

LRMS interferences amongst the PCAs. Recently, Reth

and Oehme [56] discussed three critical limitations of

LRMS for the analysis of short- and medium-chain PCAs.

[MCl] ions of a specific PCA (e.g., [MCl + 2] of

C11H17Cl7 with m/z 360.9) interfere with:

(i) the [MCl] ions of a PCA with five carbon atoms

more and two chlorine atoms less (i.e. [MCl]

(m/z 361.1) of C16H29Cl5);

(ii) the [MCl] ions of a PCA with two carbon atoms

more and one chlorine atom less (i.e. [MCl + 8](m/z 361.0) of C13H22Cl6); and,

(iii) with [M + Cl] ions of a PCA with the same number

of carbon atoms and two chlorine atoms less (i.e.

[M + Cl] (m/z 360.9) of C11H19Cl5).

GC GC solves these three problems due to the

enhanced chromatographic resolution.

6.5. Polybrominated diphenylethers (PBDEs)

PBDEs are widely used as flame retardants (e.g., in

polymers, textiles, electronic boards) and, similar to the

PCBs, there are 209 BDE congeners. However, with only

some 2025 congeners, the composition of the technicalPBDE mixtures is rather simple. Most environmental

monitoring programmes focus on the analysis of seven

congeners (BDEs 28, 47, 99, 100, 153, 154 and 209),

which are most abundant in technical mixtures and are

conventionally considered a type of reference set, similar

to the seven EU indicator CBs. However, in environ-

mental and biota samples, many other BDEs are found

than the 2025 technical congeners because of their

photolytic and biological debromination and metabolism

in higher animals.

The analysis of PBDEs is carried out by GCECD or

GCMS (EI or ECNI mode) [59]. Today, 125 BDE cong-

eners are commercially available and their retentioncharacteristics on seven stationary phases have been

reported [60]. No stationary phase separates all cong-

eners and not even the seven reference BDEs from all

others. The best separation was achieved on a DB-XLB

column with which 70 congeners were separated, while

55 congeners were involved in 22 co-elutions. In real-life

samples, the situation is even worse because other bro-

minated compounds (e.g., polybrominated biphenyls

(PBBs), hexabromocyclododecane (HBCD), tetrabromo-

bisphenol-A (TBBP-A) or dimethyl-tetrabromobisphenol-

A (me-TBBP-A)) may be present in the sample extract




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and cause further interferences, which, often, cannot be

solved by means of MS.

GC GC of BDEs is challenging because of the high

boiling points and thermal instability of the higher bro-

minated congeners. In a study to be discussed in more

detail in Section 7, Focant et al. [35,37] found that the

higher brominated congeners were retained too stronglyin the second dimension, with the limited thermal sta-

bility of most stationary phases not allowing a suffi-

ciently high temperature to speed up the separation. In

the end, an HT-8 column was used; it was stable up to

360C. However, even with a DB-1 HT-8 column set,

hepta-BDE 183 and deca-BDE could not be included

because retention was still too great.

Korytar et al. [61] used GC GClECD to separate the

125 BDEs recently marketed. For the first dimension,

DB-XLB was not a good choice because nona- and deca-

substituted congeners were decomposed completely on

this phase and partial decomposition was observed down

to hexa-BDEs. Fortunately, on DB-1, decomposition ofnona-BDEs was negligible and only slight decomposition

of deca-BDE was observed. As for the second dimension,

from amongst six columns tested, 007-65HT was found

to add most to the selectivity of the first-dimension sep-

aration. In contrast with the findings quoted above, no

extreme peak broadening or trapping was observed for

the nona-BDEs 206, 207 and 208, and deca-BDE 209.

Possibly, the band broadening in [35] was caused by a

low temperature of the MS transfer line, which houses a

significant part of the second-dimension column or by

too low a temperature of the cooling gas used for

modulation.Fig. 8 shows the considerably improved separation on

the DB-1 007-65HT column set, with only 17

co-eluting pairs involving 35 congeners. In addition, the

seven reference BDEs were separated from all other BDEs.

When a dust extract was analyzed (insert in Fig. 8), 18

BDE congeners were identified.

Various other brominated flame retardants and a

number of BDE metabolites were all found to elute within

the BDE band, and that caused several more co-elutions

(Fig. 8). Of course, some separations were improved,

notably that of TBBP-A and BDE 153; the latter analyte

can now be quantified even if a high concentration of

TBBP-A is present, as was true for the dust sample.Finally, Fig. 8 shows that second-dimension separation

facilitates the use of fluorinated BDEs as internal stan-

dards, because all F-BDEs that co-elute with the parent

compound in the first dimension are separated in the

second dimension, appearing just below that parent.

Figure 8. GC GClECDof ( ) BDEs,( ) fluorinated BDEs,( ) otherbrominated flame retardants and( ) BDE metabolites on DB-1 007-65HT.Insert: GC GClECD contour plot of dust extract [61].




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7. Between-class separations

For obvious reasons, the common denominator of nearly

all papers devoted to GC GC analysis of organohalo-

gens is the (much) improved within-class resolution that

can be achieved, with the joint addressing of the priority

CDD/Fs and CBs as the only, and logical, exception.Because of the marked successes so obtained, we now see

a gradual shift of interest to the more intriguing

between-class separations [23,35,37].

As a first attempt, Focant et al. [35] used GC GC

TOF-MS for the simultaneous determination of 38

predominant CBs, 11 persistent halogenated pesticides

(OCPs), one PBB and eight PBDEs. With the DB-1 HT-8

column combination selected, of 58 test compounds,

only one pair of CBs was not resolved.

In their next study [37], the authors determined the

priority compounds in serum and milk. Single-injection

GC

GC was compared with a validated GCHRMSprocedure, which required three separate injections with

three different temperature programmes and was, of

course, much more time-consuming. The data shown for

human serum corresponded very well between the two

techniques. For the milk sample and the more abundant

Figure 9. GC GClECD on DB-1 LC-50 of: (A) PCBs, PBBs, PCDEs, PBDEs, PCDTs,h PCNs, PCDD/Fs, OCPs, individualtoxaphene standards; (B) PCAs (PCA-60) as color contour plot and other classes as black dots; (C) PCTs (Aroclors 5442 + 5460) as color contourplot and dioxin-like CBs (black dots) and planar PCTs (white arrows); (D) PCDD/F fraction of a sediment extract [23].




20/24

congeners (>1 ng/g of lipid), per-cent deviations between

the two methods were below 20%, which is acceptable.

However, for some less-abundant congeners (


21/24

separations were found to strongly depend on the

column combination used.

We summarize a few relevant conclusions here:

On DB-1 HT-8, congener separation on the basis of

the number of halogen substituents, well-known for

PCBs and toxaphene, was also observed for PCTs

and PBDEs. However, there was no group-typeseparation (i.e. although the DB-1 HT-8 set can be

successfully used for within-class separation, there is

a high risk of interferences if congeners from other

compound classes are present).

Group separation based on planarity was obtained

with the DB-1 LC-50 column set. Fig. 9AC shows

that three groups of analytes could be distinguished.

Three-ring planar compounds, such as PCDD/Fs,

PCDTs and planar PCTs, were most strongly retained.

Next in line were two-ring planar compounds, such as

PCNs and planar PCBs. Non-planar analytes showed

least retention and did not interfere with the planar

compounds. The practicability of this column set isdemonstrated in Fig. 9D, which shows a chromato-

gram of the PCDD/F fraction of a sediment sample

after fractionation on a carbon column. Obviously, a

properly tuned GC GC system could accommodate

a very high number of compounds in the 2D plane,

and could separate dioxins (indicated by black acro-

nyms) from co-extractants (white-yellow band along

first-dimension axis).

Group-type separation was also delivered by

DB-1 007-65HT (Fig. 10A-B). Here, the PBDEs were

the strongest retained compounds in the second

dimension and the PCAs are the least retainedorganohalogens. This is a rewarding result because

PCAs and PBDEs are usually present in the same frac-

tion after clean-up. As an example, the analysis of a

dust sample is shown in Fig. 10C: the group separa-

tion is clear-cut. Finally, Fig. 10B displays the overlay

of three mixtures toxaphene, PCA-60 and Aroclors

5442 plus 5460. What shows up in the 2D plane

can be interpreted in two rather different ways:

one is to emphasize that the presence of these three

types of mixtures in any real-life sample will virtu-

ally obscure all other classes of organohalogens,

even in GC GC; but,

it is as interesting to note that there is a striking

separation of the three compound classes of

interest.

In addition, clearly ordered structures are observed for

toxaphene and PCAs.

The last column combination tested, DB-1 VF-

23ms, yielded excellent within-class separation, espe-

cially of non-aromatic compounds OCPs, toxaphene

and PCAs but there was no group separation. This

column set should, therefore, be preferred when

unraveling the composition of, specifically, toxaphene

and the PCAs, is the main aim of a study.

8. Conclusions and perspectives

Accurate, precise congener-specific analysis of organo-

halogenated compounds has been a main goal of ana-

lytical research since the early days of OCP and PCB

determination in environmental samples in the 1960s.

Three areas of interest can be recognized, viz. to ensure/improve:

(i) the separation of the analytes of interest from other

constituents present in a sample to enable their

quantification;

(ii) the sensitivity of the selected procedures and

achieve the required LODs; and,

(iii) the reliability of the identification/confirmation of

the target analytes and/or unknowns.

The common denominator of well-known milestones

of analytical chemistry, such as the introduction of

capillary GC columns, the coupling of GC with selec-

tive detectors, such as the ECD and low- or high-

resolution MS, and the introduction of heart-cut MDGC,is that they all simultaneously improved these three

aspects.

The present review shows that GC GC is effecting a

considerable further improvement and that this tech-

nique will no doubt become another milestone in

improving the analysis of the various classes of

organohalogenated compounds of interest at present. It

is worthwhile adding that the relatively brief introduc-

tory sections on instrumental aspects show that GC GC

can be considered a mature technique (with the excep-

tion of sufficiently rapid and (semi-)automated data

handling and interpretation) and that proper instru-mentation is commercially available.

The degree to which the overall resolution of

organohalogens can be improved by means of GC GC

depends on differences in the physicochemical properties

of the target analytes but, of course, also on the (non)-

complexity of the technical mixtures. The best results for

within-class separations were observed for very complex

mixtures, such as toxaphene, PCAs and PCTs, for which

about 10 times as many peaks can easily be identified.

For less complex mixtures, such as PCBs and PBDEs, the

gain is self-evidently more modest, but still some 50%

more congeners were resolved than by 1D-GC. For the

class of PCNs, with only 75 congeners, the improve-

ment was limited, irrespective of the stationary phase

used. However, one should always consider that the

separation of the target analytes from matrix constitu-

ents is another key issue and, here, GC GC contributes

to a satisfactory overall improvement also in the case of

limited numbers of congeners. Between-class separations

of the various groups of organohalogens come in more

or less the same category, and improvement is pro-

nounced because of the larger differences in physico-

chemical properties between classes than amongst

congeners of the same class. A striking example is the




22/24

essentially complete separation of the technical mixtures

of toxaphene, short-chain PCAs and PCTs in one

GC GC run.

The selection of a suitable column combination is

essential to achieve the desired separation. Certainly for

the fairly hydrophobic and essentially non-polar

organohalogens, the best option is to use a non-polarstationary phase in the first dimension, because then a

truly orthogonal system can be set up. Pure dimethyl-

polysiloxane phases containing 08% diphenyl groups or

those stabilized with polycarborane are preferred and are

easily available from various producers. The separation

mechanism in the second dimension should differ as

much as possible from that in the first dimension. Today,

commercial columns with geometry suitable for use in

the second dimension are coated with one of the fol-

lowing stationary phases polyethylene glycol or dim-

ethylpolysiloxane with up to 70% diphenyl groups, up to

100% cyanopropyl groups, up to 50% trifluoropropyl

groups or up to 50% liquid crystals. Detailed experi-mental work has shown that all of these, except the

trifluoropropyl phase, effect a significantly improved

separation of the organohalogens.

One problem common to all second-dimension sta-

tionary phases, except the phenyl phase, is their low

temperature stability. Further attention needs to be paid

urgently to the production of low-bleeding polar/shape-

selective phases that are stable up to 300C. Another

challenge for the manufacturers is to produce columns

containing two different stationary phases, with a

discrete in-between border. Coupling columns by means

of press-fits, which is a rather laborious and delicate job,will then become superfluous.

A notable exception to the (non-polar) (polar/shape-

selective) set-up is encountered in the analysis of enan-

tiomers such as the 19 pairs of atropisomeric CBs. The

shape-selective (i.e. chiral) column now has to be used in

the first dimension, because the rather marginal sepa-

ration usually obtained on such phases, makes it abso-

lutely necessary to use a long column of, typically,

2060 m: the 12 m length of a second-dimension

column would have little effect.

Analyte detectability can also be affected by the

column combination selected. Low-bleeding columns

should be used in the first dimension to keep noise as low

as possible. This is another reason why non-polar sta-

tionary phases are preferred in the first dimension. In

addition, the second-dimension separation is performed

under isothermal conditions. Consequently, if a study

mainly aims to improve LODs, phases that hardly, or do

not at all, retain the target analytes are preferred in the

second dimension, in order to generate very narrow and,

thus, very high peaks. In this way, an impressive iLOD of

0.2 pg was obtained for 2,3,7,8-TCDD with TOF-MS

detection. However, we would agree that the key aspect

of the analytical approach is now lost it is essentially a

1D-GC operation and there is no or very limited

improvement of the separation.

As regards the detection of organohalogens, today the

lECD is the most sensitive detector available for these

compounds with iLODs typically down to 10 fg. The

data-acquisition rate of 50 Hz is satisfactory for nearly

all applications, but there is considerable peak broad-ening due to the relatively large volume of the detector

cell (150 ll). In other words, the development of a

lECD with a 3050 ll cell volume would be a distinct

bonus.

For the rest, whatever the merits of lECD detection

(and these are significant), for analyte identification/

confirmation, one has to use a mass spectrometer.

Today, the work-horse is the Leco TOF-MS, which can

acquire up to 500 spectra per second over the entire

mass range and is described in the literature for a wide

variety of analytes and sample types. With this instru-

ment, excellent deconvolution of mass spectra can be

obtained. As can be seen from the present review, this isalso true for most organohalogen analyses.

However, it is also clear that, for ultra-trace studies,

satisfactory results cannot always be obtained. In such

instances, the

comprehensive two dimensional

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