in

4 1,2-benzopyrone

7 1,3-indene-dione

8 1,4-naphthoquinone

9 1-hydroxy-

10 1-naphthalenol

11 2-naphthalenol

12 1-hydroxy-

13 2,3-epoxy-

naphthalen-4-one

naphthoquinone

naphthalen-2-one

5 Phthalic anhydride O

6 Phthalide <sup>O</sup>

Table 1. The products of the OH radical reaction of Naphthalene with the OH radical are shown together with the retention times on each column.

The products determined for Acenaphthene and Phenanthrene may be found in other publications (Sauret-Szczepanski & Lane, 2004; Lee & Lane 2010).

#### **3.2 Challenges in relating TOFMS data to the NIST and Wiley databases**

We soon discovered that TOFMS mass spectral data differ significantly from those in the NIST or WILEY databases that were largely derived from quadrupole mass spectrometric data. This is because of the manner in which the mass scans are obtained. With quadrupole mass spectrometers, maximum practical scanning rates are about 300 daltons.sec-1, or about 1 to 1.5 full scans per second. This means that only about 3 scans can be taken across a single chromatographic peak. Because the mass of material being detected is constantly varying and because the scan takes about a second to be completed, the distribution of the peaks in a mass spectrum are biased high at the upper end of the spectrum as the peak is growing and are biased low at the upper end of the mass spectrum on the descending side of the peak. The reported mass spectra in the commercial databases are, of practical necessity, an average of the 3 or so peaks collected over one chromatographic peak. However, with TOFMS, full mass scans are taken at a rate of 200 per second. At such a rate, relative ion ratios are virtually constant at each point on a chromatographic peak. Approximately 600 spectra are taken over the width of a single chromatographic peak. It was for these reasons that chemical standards were obtained whenever possible and those standards used to generate an in-house library of TOFMS mass spectra. The agreement between samples and the in-house data were well above matches of 990 whereas the best matches with the NIST and WILEY libraries were on the order of 920-940. We had much greater confidence in the determinations of real world samples using our in-house library.

#### **3.3 Retention times and mass spectral identification of products**

Many of the products could be identified, although with lower match certainty than desired, through the use of the NIST and Wiley mass spectral databases, however, many more were not found in the databases and had to be determined by other means. For example, if standards or surrogate standards could be obtained mass spectra were obtained. It was also found useful to compare our spectra with mass spectral patterns published in the literature by other investigators. Their suggested identifications were of assistance in our own assignment of identities. Finally, when all else failed we identified the compounds through fundamental analysis of the mass spectra. To improve the match of environmental samples with the known products, we prepared an in-house database of the mass spectra of all reactants and for all products for which standards could be acquired. Thus matches between products in smog samples and database reference standards rose from about 650 to over 990 giving much greater confidence in the identity of the products.

#### **3.4 Analysis of smog samples**

A 3D image of the chromatograph of one of the Korean smog samples is shown below in Figure 3. From this sample, we successfully resolved almost 18,000 individual compounds. Many of the peaks could be identified by computer database searching. However, many were unidentified. This was partly due to the incompatibility of NIST and Wiley spectra with TOFMS data as outlined above and, more likely, because the compound in the air did not have a mass spectral signature in the databases.

The products determined for Acenaphthene and Phenanthrene may be found in other

We soon discovered that TOFMS mass spectral data differ significantly from those in the NIST or WILEY databases that were largely derived from quadrupole mass spectrometric data. This is because of the manner in which the mass scans are obtained. With quadrupole mass spectrometers, maximum practical scanning rates are about 300 daltons.sec-1, or about 1 to 1.5 full scans per second. This means that only about 3 scans can be taken across a single chromatographic peak. Because the mass of material being detected is constantly varying and because the scan takes about a second to be completed, the distribution of the peaks in a mass spectrum are biased high at the upper end of the spectrum as the peak is growing and are biased low at the upper end of the mass spectrum on the descending side of the peak. The reported mass spectra in the commercial databases are, of practical necessity, an average of the 3 or so peaks collected over one chromatographic peak. However, with TOFMS, full mass scans are taken at a rate of 200 per second. At such a rate, relative ion ratios are virtually constant at each point on a chromatographic peak. Approximately 600 spectra are taken over the width of a single chromatographic peak. It was for these reasons that chemical standards were obtained whenever possible and those standards used to generate an in-house library of TOFMS mass spectra. The agreement between samples and the in-house data were well above matches of 990 whereas the best matches with the NIST and WILEY libraries were on the order of 920-940. We had much greater confidence in the

Many of the products could be identified, although with lower match certainty than desired, through the use of the NIST and Wiley mass spectral databases, however, many more were not found in the databases and had to be determined by other means. For example, if standards or surrogate standards could be obtained mass spectra were obtained. It was also found useful to compare our spectra with mass spectral patterns published in the literature by other investigators. Their suggested identifications were of assistance in our own assignment of identities. Finally, when all else failed we identified the compounds through fundamental analysis of the mass spectra. To improve the match of environmental samples with the known products, we prepared an in-house database of the mass spectra of all reactants and for all products for which standards could be acquired. Thus matches between products in smog samples and database reference standards rose from about 650 to over 990

A 3D image of the chromatograph of one of the Korean smog samples is shown below in Figure 3. From this sample, we successfully resolved almost 18,000 individual compounds. Many of the peaks could be identified by computer database searching. However, many were unidentified. This was partly due to the incompatibility of NIST and Wiley spectra with TOFMS data as outlined above and, more likely, because the compound in the air did

publications (Sauret-Szczepanski & Lane, 2004; Lee & Lane 2010).

determinations of real world samples using our in-house library.

giving much greater confidence in the identity of the products.

not have a mass spectral signature in the databases.

**3.4 Analysis of smog samples** 

**3.3 Retention times and mass spectral identification of products** 

**3.2 Challenges in relating TOFMS data to the NIST and Wiley databases** 

Fig. 3. The GCxGC trace of a Korean smog sample. The first column dimension is the vapor pressure dimension and is governed by chromatography on the DB-5MS column. The second dimension is the polar dimension and is governed by the polar DB-17MS column. The height of the peaks is proportional to the mass of the compound present.

However, for other unknowns or possibly improperly identified peaks, it was clearly a case of the compound not existing in the databases. We succeeded in finding 13 of the photochemical decomposition products from the chamber experiments in the Korean smog samples. The compounds from the decomposition of naphthalene, acenaphthene and phenanthrene that were found in the smog sample are shown in Table 2.

The above compounds were found in the particulate matter collected on the filter of a filter pack from Seoul, Republic of Korea. Since these compounds were found on the filter it is important to note that a) they were in the particle phase, 2) they may have suffered some volatilization or blow-off from the filter, but the degree to which that affected an estimation of the total compound in the atmosphere cannot be determined, and 3) many of the compounds detected such as the quinones, nitro derivatives and the hydroxynitro derivatives are known to be hazardous chemicals (Arey et al., 1989; Atkinson and Arey, 1994; Reisen and Arey, 2005 ). As many of these compounds, for example 1,2 naphthalenedicarboxaldehyde and (E)-2-formylcinnamaldehyde (Lane & Lee, 2010), are not known to originate in emissions, they must have been the result of atmospheric oxidation and this clearly indicates the formation of secondary aerosol material. It is important to note that there are no known anthropogenic sources of these two compounds. Recently Kroll and Seinfeld (Kroll and Seinfeld, 2008) have demonstrated the importance of atmospheric reaction products in the formation of secondary organic aerosol (SOA) and in the adverse effect of SOA to climate change and visibility in the atmosphere. A recent study (Robinson et al., 2007) has reported that research to estimate the organic aerosol budget, underestimates the production of SOA in the atmosphere when compared to actual field measurements. They suggested that the underestimate was due to the non-inclusion of the SOA produced from atmospheric semivolatile organic compounds.


Table 2. Above are presented the products found in the smog chamber during the studies of the reactions of naphthalene, acenaphthene and phenanthrene that were also found in the smog samples.

#### **4. Conclusions**

416 Advanced Gas Chromatography – Progress in Agricultural, Biomedical and Industrial Applications

O

O

O

O

O

O

O

CHO

CHO

Parent Product Structure Naphthalene 1-naphthol OH

1,4-naphthalenedione O

(E)-2-formylcinnamaldehyde CHO

1,3-indandione O

Indan-1-one O

Acenaphthene 1,8-naphthalicanhydride O O O

Phenanthrene 9-fluorenone O

1,2-naphthalenedicarboxaldahyde CHO

Phthalic anhydride

Phthalide

In this chapter, we have demonstrated that GC×GC-TOFMS is an excellent technique to identify the oxidized products of the decomposition of PAH in reactions with the OH radical. When combined with thermal desorption, TD-GC×GC-TOFMS becomes a very powerful tool to examine air extracts for a very wide range of pollutant chemicals. This method provides greatly enhanced sensitivity to chemical components and permits the detection of many, otherwise impossible to detect, compounds. We have demonstrated unequivocally that PAH are oxidized in the atmosphere and form a plethora of oxidized, nitrated and ring-opened products. This lends strong support to the statements of Robinson et al. (Robinson et al., 2007) that the production of SOA is underrepresented in budgets of atmospheric aerosols. We have found known oxidation products, some known only as atmospheric oxidation products with no anthropogenic source, in smog samples. This alone has many implications for the effect of SOA on human health.

#### **5. References**

Arey, J., Atkinson, R., Zlelinska, B., and McElroy, P.A. (1989). Diurnal concentrations of volatile polycyclic aromatic hydrocarbons and nitroarenes during a photochemical air pollution episode in Glendora, California. *Environmental Science & Technology.*  23, 321-327.


Atkinson, R., Aschmann, S.M., and Pitts, J.N. Jr. (1984). Kinetics of the reactions of

Atkinson, R. (1988). Estimation of gas-phase hydroxyl radical rate constants for organic

Atkinson, R., and Arey, J. (1994). Atmospheric chemistry of gas-phase polycyclic aromatic

Banceu, C.E., Mihele, C.M., Lane, D.A., & Bunce, N.J. (2001). Reactions of Methylated

Bunce, N.J., Liu, L., Zhu, J., Lane, D.A., (1997). Reaction of naphthalene and its derivatives

Esteve, W., Budzinski, H., Villenave, E. (2003). Heterogeneous reactivity of OH radicals with

Falk, H.L., Markul, I., and Kotin, P. (1956). Aromatic hydrocarbons. IV. Their fate following

Falk, H.L., Kotin, P., and Miller, A. (1960). Aromatic polycyclic hydrocarbons in polluted air

Galarneau, E., Harner, T., Shoeib, M., Kozma, M., and Lane, D.A. (2006). A preliminary

Gundel, L.A., Lee, V.C., Mahanama, K.R.R., Stevens, R.K., and Daisey, J.M. (1995). Direct

Gundel, L.A., and Lane, D.A. (1999). Sorbent-coated diffusion denuders for direct

Johnson, N.D., Barton, S.C., Thomas, G.H.S., Lane, D.A., and W.H. Schroeder. 1985.

Kroll, J.H. and Seinfeld, J.H. (2008). Chemistry of secondary organic aerosol: formation and

phenanthrene. *Science of the Total Environment*. 148, 11-21.

*Environmental Science & Technology.* 18, 110-113.

*Polycyclic Aromatic Compounds*. 18, 415-425.

*Atmospheric Environment.* 40, 5734-5740.

Berkeley National Laboratory (USA).

85-81-1. June 12-21, Detroit, MI.

3593-3624.

*Perspectives.* 102, 117–126.

2252–2259.

chemicals. *Environmental Toxicology & Chemistry.* 7, 435-442.

phenanthrene. *Polycyclic Aromatic Compounds.* 23, 441-456.

synthetic smog. *A.M.A. Archives of Industrial Health* 13, 13-17.

Naphthalene and Biphenyl with OH radicals and with O3 at 294 ± 1 K.

hydrocarbons: formation of atmospheric mutagens. *Environmental Health* 

Naphthalenes with Hydroxyl Radicals Under Simulated Atmospheric Conditions.

with hydroxyl radicals in the gas phase. *Environmental Science and Technology.* 31,

emission into the atmosphere and experimental exposure to washed air and

as indicators of carcinogenic hazards. *International Journal of Air Pollution* 2, 201-209.

investigation of sorbent-impregnated filters (SIFs) as an alternative to polyurethane foam (PUF) for sampling gas-phase semivolatile organic compounds in air.

determination of the phase distributions of semi-volatile Polycyclic Aromatic Hydrocarbons using annular denuders. Atmospheric Environment. 29, 1719-1733. Gundel, L.A., and Herring, S.V. (1998). Absorbing filter media for denuder-filter sampling of

total organic carbon in airborne particles. Record of invention WIB 1457, Lawrence

measurement of gas/particle partitioning by semi-volatile organic compounds.. In: Lane, D.A. (Ed.), Gas and Particle Phase Measurements of Atmospheric Organic Compounds. Gordon and Breach Science Publishers, Philadelphia PA, chapter 11. Helmig, D., and Harger, W.P. (1994). OH radical-initiated gas-phase reaction products of

Development of a gas/particle fractionating sampler for chlorinated organics. In proceedings of the annual meeting of the Air Pollyution Control Association. Paper

evolution of low-volatility organics in the atmosphere. *Atmospheric Environment.* 42,


### **Inverse Gas Chromatography in Characterization of Composites Interaction**

Kasylda Milczewska and Adam Voelkel *Poznan University of Technology, Institute of Chemical Technology and Engineering, Poznan, Poland* 

#### **1. Introduction**

420 Advanced Gas Chromatography – Progress in Agricultural, Biomedical and Industrial Applications

Sasaki, J., Aschmann, S.M., Kwok, E.S.C., Atkinson, R., & Arey, J. (1997). Products of the gas-

Sauret-Szczepanski, N., & Lane, D.A. (2004). Smog chamber study of acenaphthene:

Wang, L., Atkinson, R., and Arey, J. (2007). Dicarbonyl products of the OH radical-initiated

*Science and Technology.* 31, 3173–3179.

*Science & Technology.* 41, 2803-2810.

OH radical. *Polycyclic Aromatic Compounds*. 24, 161–172.

phase OH and NO3 radical-initiated reactions of naphthalene. *Environmental* 

gas/particle partition measurements of the products formed by reaction with the

reactions of naphthalene and the C1- and C2-alkylnaphthalenes. *Environmental* 

Inverse gas chromatography is a useful and quite versatile technique for materials' characterization, because it can provide information on thermodynamic properties over a wide temperature range. The term "inverse" indicates that the stationary phase of the chromatographic column is of interest, in contrast to conventional gas chromatography. The chromatographic column contains the material under study. The method is simple, fast and efficient. It has been used for the characterization of hyperbranched polymers [Dritsas et al., 2008], block copolymers [Zou et al., 2006], polymer blends [Al-Ghamdi & Al-Saigh, 2000], nanocomposites [Boukerma et al., 2006], fillers [Milczewska & Voelkel, 2002], cement pastes [Oliva et al., 2002], fibers [van Asten et al., 2000] and crude oils [Mutelet et al., 2002].

Mixtures of different types of materials i.e. polymers, blends, modified fillers or compositions are utilized extensively to produce commercially useful materials having combinations of properties not revealed by a single component. Many of the properties and processing characteristics of those mixtures depend on whether they are miscible or not. Theory operates with parameters relating to the pure components [Voelkel et al., 2009 (a)]. The knowledge of the interaction parameters between polymers and solvents is very important in the study of their miscibility and thermodynamic properties of solutions [Huang, 2009].

The interactions between one probe and the polymer are usually characterized by the values of Flory–Huggins interaction parameter [Dritsas et al., 2009]. Only a few techniques can provide quantitative information about the change of free energy when mixing two components. The data from P-V-T experiments might be successfully used in the prediction of the miscibility of polyolefine blends [Han et al., 1999]. Interaction parameter for the components of polymer blends was also determined with the use of small angle x-ray scattering (SAXS) [de Gennes, 1979; Meoer & Strobl, 1987; Ying et al. 1993], thermal induced phase separation (TIPS) [Sun et al., 1999] and small angle neutron scattering (SANS) [Fernandez et al., 1995; Hindawi et al., 1990; Horst & Wolf, 1992; Mani et al., 1992; Schwann et al., 1996]. In last two decades, the Flory-Huggins interaction parameter was also determined using the melting point depression method for crystal-containing polymers by differential scanning calorimetry (DSC) [Lee et al., 1997]. It is worth to note the increasing role of inverse gas chromatography (IGC) [Voelkel et al., 2009 (a)], because of its simplicity, rapidity, and the general availability of GC equipment.

#### **2. Theory of interaction**

Inverse Gas Chromatography (IGC) is a gas-phase technique for characterizing surface and bulk properties of solid materials. The principles of IGC are very simple, being the reverse of a conventional gas chromatographic (GC) experiment.

While it is a dynamic method, it was shown many years ago that measurements recorded under the correct conditions could give accurate equilibrium thermodynamic information [Shillcock & Price, 2003]. The retention of a solvent or 'probe' molecule on the material is recorded and the measurement made effectively at infinite dilution of the probe. A range of thermodynamic parameters can then be calculated. One advantage of the method is that it is readily applied to mixtures of two or more polymers.

A cylindrical column is uniformly packed with the solid material of interest, typically a powder, fiber or film. A pulse or constant concentration of gas is then injected down the column at a fixed carrier gas flow rate, and the time taken for the pulse or concentration front to elute down the column is measured by a detector. A series of IGC measurements with different gas phase probe molecules then allows access to a wide range of physicochemical properties of the solid sample [SMS-*i*GC brochure 2002].

Fig. 1. Analytical vs. Inverse gas chromatography

When a liquid probe is injected into the column, the probe vaporizes and flows with the carrier gas, and a characteristic specific retention volume (Vg) can be measured:

$$V\_{\mathcal{S}} = \frac{3}{2} \cdot \frac{\stackrel{\cdot}{t\_R} \cdot \stackrel{\cdot}{j} \cdot F \cdot 273.15}{m\_w \cdot T} \tag{1}$$

where: ' *ttt RRM* , *tM* - gas hold-up time, calculated by Grobler–Balizs procedure [Grobler & Balizs, 1974], *j* – James-Martin's coefficient [James & Martin, 1952].

#### **3. Flory-Huggins parameters**

422 Advanced Gas Chromatography – Progress in Agricultural, Biomedical and Industrial Applications

determined using the melting point depression method for crystal-containing polymers by differential scanning calorimetry (DSC) [Lee et al., 1997]. It is worth to note the increasing role of inverse gas chromatography (IGC) [Voelkel et al., 2009 (a)], because of its simplicity,

Inverse Gas Chromatography (IGC) is a gas-phase technique for characterizing surface and bulk properties of solid materials. The principles of IGC are very simple, being the reverse

While it is a dynamic method, it was shown many years ago that measurements recorded under the correct conditions could give accurate equilibrium thermodynamic information [Shillcock & Price, 2003]. The retention of a solvent or 'probe' molecule on the material is recorded and the measurement made effectively at infinite dilution of the probe. A range of thermodynamic parameters can then be calculated. One advantage of the method is that it is

A cylindrical column is uniformly packed with the solid material of interest, typically a powder, fiber or film. A pulse or constant concentration of gas is then injected down the column at a fixed carrier gas flow rate, and the time taken for the pulse or concentration front to elute down the column is measured by a detector. A series of IGC measurements with different gas phase probe molecules then allows access to a wide range of physico-

When a liquid probe is injected into the column, the probe vaporizes and flows with the

3 273.15

*w*

*ttt RRM* , *tM* - gas hold-up time, calculated by Grobler–Balizs procedure [Grobler

*m T* (1)

 '

carrier gas, and a characteristic specific retention volume (Vg) can be measured:

2 *R*

*t jF <sup>V</sup>*

*g*

& Balizs, 1974], *j* – James-Martin's coefficient [James & Martin, 1952].

rapidity, and the general availability of GC equipment.

of a conventional gas chromatographic (GC) experiment.

readily applied to mixtures of two or more polymers.

Fig. 1. Analytical vs. Inverse gas chromatography

where: '

chemical properties of the solid sample [SMS-*i*GC brochure 2002].

**2. Theory of interaction** 

The properties of polymer blends are determined mainly by the miscibility of the components and structure. Usually thermodynamic miscibility and homogeneity can be attained when the free energy of mixing is negative. The classical thermodynamics of binary polymer–solvent systems was developed independently by P.J. Flory [Flory, 1942] and M.L. Huggins [Huggins, 1942]. It is based on the well-known lattice model qualitatively formulated by K.H. Meyer [Meyer, 1939], who pointed out the effect of the differences in molecular size of polymer and solvent molecules on the entropy of mixing. The quantitative calculation of the entropy of mixing led to the introduction of a dimensionless value, the socalled Flory-Huggins interaction parameter, for the thermodynamic description of polymer solutions [Gundert & Wolf, 1989]. Flory–Huggins interaction parameter () is an important factor of miscibility of polymer blends and solutions.

Using Flory–Huggins theory, the Flory–Huggins interaction parameter between a polymer and probe, can be related to the specific retention volume of probes, *Vg*, by the following equation [Milczewska & Voelkel, 2002 as cited in Barrales-Rienda, 1988; Voelkel et al., 2009 (b) as cited in Voelkel & Fall, 1995]:

$$\chi\_{12}^{\circ \circ} = \ln \left( \frac{273.15 \cdot R}{p\_1^{\circ} \cdot V\_{\mathcal{S}} \cdot M\_1} \right) - \frac{p\_1^{\circ}}{R \cdot T} \cdot \left( B\_{11} - V\_1^{\circ} \right) + \ln \left( \frac{\rho\_1}{\rho\_2} \right) - \left( 1 - \frac{V\_1^{\circ}}{V\_2^{\circ}} \right) \tag{2}$$

1 denotes the solute and 2 denotes examined material, M1 is the molecular weight of the solute, 1 *<sup>o</sup> p* is the saturated vapor pressure of the solute, B11 is the second virial coefficient of the solute, *<sup>o</sup> Vi* is the molar volume, i is the density, R is the gas constant.

This equation may be rearranged into form including weight fraction activity coefficient:

$$\ln \mathcal{Q}\_1^{\mathcal{O}} = \ln \left( \frac{a\_1}{w\_1} \right) = \ln \left( \frac{273.15 \cdot R}{p\_1^o \cdot V\_\mathcal{S} \cdot M\_1} \right) - \frac{p\_1^o}{R \cdot T} \cdot \left( B\_{11} - V\_1^o \right) \tag{3}$$

$$\chi\_{12}^{\circ \circ} = \ln \mathcal{Q}\_1^{\circ} + \ln \left(\frac{\rho\_1}{\rho\_2}\right) - \left(1 - \frac{V\_1^o}{V\_2^o}\right) \tag{4}$$

When the data of the density and the molecular mass of both the solute and the stationary phase (polymer) are inaccessible it is possible to determine the Flory-Huggins interaction parameter by simplifying Eq. (4):

$$\log\_{12}^{\phi} = \ln \mathcal{Q}\_1^{\phi} - 1 \tag{5}$$

i.e., under the assumption that 1 2 ln 0 *<sup>ρ</sup> ρ* which means that the densities of the solute and

the stationary phase are of similar order and <sup>1</sup> 2 0 *o o V V* (the molar volume of the stationary phase is much higher than that of the test solute) [Voelkel & Fall, 1997].

Etxabarren et al. [Etxabarren et al., 2002] described molecular mass, temperature and concentration dependences of the polymer-solvent interaction parameter. The concentration dependence has been reasonably explained after the consideration of the different compressibilities (or free volumes) of the components. A parabolic dependence of with temperature is necessary in order to explain the lower or upper critical solution temperatures characteristic of most of the polymer solutions. In fact, there are experimental evidences of such type of dependence although because of limitations imposed by the degradation of the polymer and the freezing point of the solvent, a limited temperature range can be studied and only a part of this parabolic curve is usually evidenced.

Molecular mass dependence of the interaction parameter has been a recurrent subject in the polymer literature, and Petri et al. [Petri et al., 1995] have reported new experimental results which seem to indicate that there is a real molecular mass dependence of , especially in the range of moderate concentrations [Schuld & Wolf, 2001].

Ovejero et al. [Ovejero et al., 2009] determined Flory-Huggins parameter 12 for SEBS triblock copolymer. They noticed that Flory-Huggins parameter was defined as independent of concentration, but the effect of concentration is not negligible. Authors tried to develop a thermodynamic tool to simulate a polymer - solvent separation. In their work they also paid attention to temperature dependence. A decrease of Flory-Huggins parameter while increasing temperature was suggested. However they have shown that this dependence is

not clear. For investigated rubber values of 12 increased slightly with temperature.

When mixture of components is used as a stationary phase in a chromatographic column, subscripts 2 and 3 are used to represent first and second mixtures' component, respectively [Voelkel et al., 2009 (b)]:

$$\chi\_{1m}^{o} = \ln\left(\frac{273.15 \cdot R}{p\_1^o \cdot V\_\mathcal{g} \cdot M\_1}\right) - \frac{p\_1^o}{R^\* \, T} \cdot \left(B\_{11} - V\_1^o\right) + \ln\left(\frac{\rho\_1}{\rho u}\right) - \left(1 - \frac{V\_1^o}{V\_2^o}\right) \cdot \rho\_2 - \left(1 - \frac{V\_1^o}{V\_3^o}\right) \cdot \rho\_3\tag{6}$$

where 2 and 3 are the volume fractions of components.

When <0.5, the probe liquid is generally characterized as a good solvent for the polymer, whereas >0.5 indicates a poor solvent which use may lead to phase separation. In the case of a polymer blend, the parameter can still be defined and the miscibility generally occurs when <0, because the high molar volume of both components diminishes the combinatorial entropy [Huang, 2009].

When a polymer blend is used the interaction between the two polymers is expressed in terms of ' 23 as an indicator of the miscibility of the components of the polymer blend. If the parameters 12 and 13 are known (from IGC experiment with appropriate component "2" or "3") the interaction parameter ' <sup>23</sup> may be calculated from equation [El-Hibri et al., 1989; Olabisi, 1975]:

$$\chi\_{23}^{'} = \frac{1}{\varphi\_2 \cdot \varphi\_3} \cdot \left( \chi\_{12}^{\;\;\phi} \cdot \varphi\_2 + \chi\_{13}^{\;\;\phi} \cdot \varphi\_3 - \chi\_{1m}^{\;\;\phi} \right) \tag{7}$$

Etxabarren et al. [Etxabarren et al., 2002] described molecular mass, temperature and concentration dependences of the polymer-solvent interaction parameter. The concentration dependence has been reasonably explained after the consideration of the different compressibilities (or free volumes) of the components. A parabolic dependence of with temperature is necessary in order to explain the lower or upper critical solution temperatures characteristic of most of the polymer solutions. In fact, there are experimental evidences of such type of dependence although because of limitations imposed by the degradation of the polymer and the freezing point of the solvent, a limited temperature

Molecular mass dependence of the interaction parameter has been a recurrent subject in the polymer literature, and Petri et al. [Petri et al., 1995] have reported new experimental results which seem to indicate that there is a real molecular mass dependence of , especially in the

triblock copolymer. They noticed that Flory-Huggins parameter was defined as independent of concentration, but the effect of concentration is not negligible. Authors tried to develop a thermodynamic tool to simulate a polymer - solvent separation. In their work they also paid attention to temperature dependence. A decrease of Flory-Huggins parameter while increasing temperature was suggested. However they have shown that this dependence is

3 are the volume fractions of components.

 

*'*1

2 3

When mixture of components is used as a stationary phase in a chromatographic column, subscripts 2 and 3 are used to represent first and second mixtures' component, respectively

273.15 ln ln 1 <sup>1</sup> *<sup>o</sup> o o <sup>o</sup> <sup>m</sup> <sup>o</sup> o o <sup>m</sup> <sup>g</sup>*

1 11 1 2 3 1 1 2 3

of a polymer blend, the parameter can still be defined and the miscibility generally occurs

When a polymer blend is used the interaction between the two polymers is expressed in

'

<sup>23</sup> 12 2 13 3 1

*pVM R\*T ρ V V*

<0.5, the probe liquid is generally characterized as a good solvent for the polymer,

<0, because the high molar volume of both components diminishes the combinatorial

>0.5 indicates a poor solvent which use may lead to phase separation. In the case

23 as an indicator of the miscibility of the components of the polymer blend. If the

13 are known (from IGC experiment with appropriate component

*χ (χχχ <sup>m</sup> )* (7)

 

1 1 1 1

*R p ρ V V*

12 increased slightly with temperature.

<sup>23</sup> may be calculated from equation

*V* (6)

12 for SEBS

range can be studied and only a part of this parabolic curve is usually evidenced.

Ovejero et al. [Ovejero et al., 2009] determined Flory-Huggins parameter

range of moderate concentrations [Schuld & Wolf, 2001].

not clear. For investigated rubber values of

*χ B*

"2" or "3") the interaction parameter

[El-Hibri et al., 1989; Olabisi, 1975]:

[Voelkel et al., 2009 (b)]:

where 2 and 

When 

when 

terms of

parameters

whereas

entropy [Huang, 2009].

 12 and

' Here, the second subscript of identifies the nature of the column.

The interaction between the two components of composition is expressed in terms of ' 23 may be also calculated from [Milczewska et al., 2001 as cited in Li (Pun Choi), 1996, Milczewska et al., 2003 as cited in Voelkel & Fall, 1997]:

$$\dot{\chi}\_{23}^{\cdot} = \frac{\chi\_{23}^{\otimes} \cdot V\_1}{V\_2} = \frac{1}{\rho\_2 \cdot \rho\_3} \cdot \left( \ln \frac{V\_{\text{g,m}}}{W\_2 \cdot \nu\_2 + W\_3 \cdot \nu\_3} - \rho\_2 \cdot \ln \frac{V\_{\text{g,2}}}{\nu\_2} - \rho\_3 \cdot \ln \frac{V\_{\text{g,3}}}{\nu\_3} \right) \tag{8}$$

Here, the second subscript of *Vg* identifies the nature of the column. From Eq. (8), ' 23 may be calculated even for probes for which the parameters 1 *<sup>o</sup> p* ,B11 and *<sup>o</sup> Vi* are not known or are known with insufficient accuracy [Al-Saigh & Munk, 1984].

To obtain ' 23 for a polymer blend or composition utilizing IGC, 12 values for all components have to be known. Therefore, three columns are usually prepared: two for single components and the third one for a composition of the two components used. A further three columns containing different compositions of components can also be prepared if the effect of the weight fraction of the mixture on the examined property needs to be explored. These columns should be studied under identical conditions of column temperature, carrier gas flow rate, inlet pressure of the carrier gas, and with the same test solutes [Al-Saigh, 1997].

Large positive values of ' 23 indicates the absence or negligible interactions between components, a low value indicates favorable interactions, while negative value indicates strong interactions (the pair of polymers is miscible).

Equations (7) or (8) were frequently used to study the interaction parameter between two stationary phases using the IGC method. In literature data, it was found that, in many miscible systems, ' 23 values were probe dependent. The values of ' 23 were positive when 12 and 13 were positive, and decreased when 12 and 13 decreased to negative. Some negative ' 23 values were generally observed for probes with low 12 and 13 [Huang, 2009].

Nesterov and Lipatov [Nesterov & Lipatov, 1999] studied thermodynamics of interactions in the ternary system: polymer A + polymer B + filler S. In their studies it was shown that the introduction of a third component into the binary immiscible mixture of two polymers, where the third component is miscible with each component of binary mixture, may lead full miscibility of the ternary system. For the immiscible mixtures of polyolefins with polyacrylates and polymethacrylates it was discovered that a mineral filler (e.g. silica) also may serve as compatibilizer.

The compatibilization effect of two immiscible polymers by adding the third polymer (or filler) my be described in the framework of the Flory-Huggins theory extended for describing ternary mixtures. For that mixtures Flory-Huggins parameter can be expressed as:

$$\mathcal{X}\_{A+B+\mathbb{C}} \cong \mathcal{X}\_{AB} \cdot \boldsymbol{\uprho}\_{A} \cdot \boldsymbol{\uprho}\_{B} + \mathcal{X}\_{A\mathbb{C}} \cdot \boldsymbol{\uprho}\_{A} \cdot \boldsymbol{\uprho}\_{\mathbb{C}} + \mathcal{X}\_{BC} \cdot \boldsymbol{\uprho}\_{\mathbb{B}} \cdot \boldsymbol{\uprho}\_{\mathbb{C}} \tag{9}$$

A positive value of the parameter *ABC* corresponds to an immiscible systems whereas a negative is an indicator of miscibility [Nesterov & Lipatov, 2001].

Values of Flory-Huggins ' 23 parameter depend on chemical structure of the solute and it is a common phenomenon, although not allowed by the theory [Fernandez-Sanchez et al., 1988]. It has been interpreted as a result of preferential interactions of the test solute with one of two components. This phenomenon for polymer blends was described independently by Fernandez-Sanchez et al. and Olabisi [Olabisi, 1975]. They attributed this to the nonrandom distribution of the solute in the stationary phase owing to its preferential affinity for one of the components. Selective solutes do not "sense" the three varieties of intramolecular contacts in the polymer mixture (A-A, A-B, B-B) in proportion to concentration. This modifies the retention volume (and ' <sup>23</sup> ) values relative to those which would be obtained by truly random mixing of the solute with the polymer. Less selective solvents, on the other hand, exhibit a more random 'sampling' of the molecular environment of the stationary phase owing to the equal affinities they have for both. It is therefore expected that a better measure of the polymer-polymer interaction will be likely with less selective solvents.

Olabisi [Olabisi, 1975] described a polyblend as micro heterogeneous, where the size of the different phases and their interpenetration being limited by a host of factors among which are the extents of mixing, compatibility, molecular weight, clustering behaviour of each polymer, rheological and surface and interfacial properties. He attributed Flory-Huggins parameter dependence on test solute to unequal distribution of the solute in the stationary phase, and to wide range of interactions (polar, nonpolar, hydrogen-bonding and also electronic and electrostatic interactions) [Li, 1996]. Olabisi proposed to use a set of solvents based on their type of interactions with probe: (i) proton accepting strength, probed with chloroform and ethanol; (ii) proton donor strength with methyl-ethyl ketone and pyridine; (iii) polar strength with acetonitrile and fluorobenzene; (iv) nonpolar strength with hexane and carbon tetrachloride.

Prolongo et al. proposed to calculate the polymer-polymer interaction parameter from measurements performed on ternary systems composed of the polymer pair plus a solvent or probe. They given the expressions needed to calculate the true polymer-polymer based on the equation-of-state theory and they compared that method for PS+PVME data obtained from vapor sorption (VP). The results show that the values obtained from IGC correlation and VP are nearly the same [Prolongo et al., 1989].

Many authors suggest that the ' 23 values are solvent (solute) independent for probes giving 12 13 [Su & Patterson, 1977; Lezcano et al., 1995]. If the difference between the interaction of the components (for blend ≡ polymers 2 and 3) with the solvent is negligible 12 13 0 interaction parameter ' 23 should be solvent independent. The equation above is often called "Δχ effect".

Horta's group [Prolongo et al., 1989] have proposed a method based on the equation-ofstate theory, which gives a polymer-polymer parameter 23 named 'true', because the assumption that the Gibbs mixing function for the ternary polymer-polymer-solvent system is additive with respect to the binary contributions is avoided. They suggested that it is necessary to substitute the volume fraction *<sup>i</sup>* in the Flory-Huggins theory by segment fractions *<sup>i</sup>* according to:

$$\phi\_i = \frac{w\_i \cdot \upsilon\_i^\*}{\sum w\_i \cdot \upsilon\_i^\*} \tag{10}$$

where \* *<sup>i</sup> v* and *wi* represent characteristic specific volume and the weight fraction of the *i*th component, respectively.

Shi and Shreiber [Shi & Shreiber, 1991] stated that the probe dependence of ' 23 is due to two major contributing factors. Firstly, the surface composition of a mixed stationary phase will rarely, if ever, correspond to the composition of the bulk. Thermodynamic requirements to minimize the surface free energy of the stationary phase will favor the preferential concentration, at the surface, of the component with the lower (lowest) surface free energy. Thus, the values of 2 and 3, as defined by the bulk composition of mixtures, are inapplicable to Eq. (7). Instead, a graphical method was proposed by Shi and Schreiber to evaluate the effective volume fraction and to correct the problem. Secondly, since 12 and 13 will not usually be equal, it follows that the volatile phase will partition preferentially to the component that has the lower pertinent <sup>1</sup>*m* value. Thus, the partitioning must vary with each probe, inevitably affecting the ' 23 datum.

Deshpande and Farooque were the first to suggest the use of IGC for studying polymer blends [Deshpandee et al., 1974]. Starting form the Flory-Huggins expression for the change of the free enthalpy in mixing, which was extended to three-component systems, they proposed a method of analysis of IGC measurements on polymer blends which yielded the polymer-polymer interaction parameter ' <sup>23</sup> . They also observed probe dependency and tried to develop a method to evaluate probe-independent interaction [Farooque et al., 1992].

Milczewska and Voelkel [Milczewska & Voelkel, 2006] mentioned some of that methods of evaluating probe-independent interaction parameter. One of the solution may be procedure proposed by Zhao and Choi [Zhao & Choi, 2001; Zhao & Choi, 2002]. Authors proposed to use 'common reference volume' which vanishes the problem. As the reference volume they used molar volume of the smallest repeated unit of polymer.

Flory-Huggins parameter for blends can be calculated from equations:

$$\mathcal{X}\_{1m} = \frac{V\_o}{V\_1} \cdot \left( \ln \frac{273.15 \cdot R}{M\_1 \cdot V\_g \cdot p\_1^o} - 1 + \left( 1 - \frac{V\_1}{V\_2} \right) \cdot \wp\_2 + \left( 1 - \frac{V\_1}{V\_3} \right) \cdot \wp\_3 - \left( \frac{B\_{11} - V\_1}{R \cdot T} \right) \cdot p\_1^o \right) \tag{11}$$

and

426 Advanced Gas Chromatography – Progress in Agricultural, Biomedical and Industrial Applications

*A B C AB A B AC A C BC B C*

a common phenomenon, although not allowed by the theory [Fernandez-Sanchez et al., 1988]. It has been interpreted as a result of preferential interactions of the test solute with one of two components. This phenomenon for polymer blends was described independently by Fernandez-Sanchez et al. and Olabisi [Olabisi, 1975]. They attributed this to the nonrandom distribution of the solute in the stationary phase owing to its preferential affinity for one of the components. Selective solutes do not "sense" the three varieties of intramolecular contacts in the polymer mixture (A-A, A-B, B-B) in proportion to concentration. This

by truly random mixing of the solute with the polymer. Less selective solvents, on the other hand, exhibit a more random 'sampling' of the molecular environment of the stationary phase owing to the equal affinities they have for both. It is therefore expected that a better measure of the polymer-polymer interaction will be likely with less selective solvents.

Olabisi [Olabisi, 1975] described a polyblend as micro heterogeneous, where the size of the different phases and their interpenetration being limited by a host of factors among which are the extents of mixing, compatibility, molecular weight, clustering behaviour of each polymer, rheological and surface and interfacial properties. He attributed Flory-Huggins parameter dependence on test solute to unequal distribution of the solute in the stationary phase, and to wide range of interactions (polar, nonpolar, hydrogen-bonding and also electronic and electrostatic interactions) [Li, 1996]. Olabisi proposed to use a set of solvents based on their type of interactions with probe: (i) proton accepting strength, probed with chloroform and ethanol; (ii) proton donor strength with methyl-ethyl ketone and pyridine; (iii) polar strength with acetonitrile and fluorobenzene; (iv) nonpolar strength with hexane

Prolongo et al. proposed to calculate the polymer-polymer interaction parameter from measurements performed on ternary systems composed of the polymer pair plus a solvent or probe. They given the expressions needed to calculate the true polymer-polymer based on the equation-of-state theory and they compared that method for PS+PVME data obtained from vapor sorption (VP). The results show that the values obtained from IGC correlation

12 13 [Su & Patterson, 1977; Lezcano et al., 1995]. If the difference between the

interaction of the components (for blend ≡ polymers 2 and 3) with the solvent is negligible

Horta's group [Prolongo et al., 1989] have proposed a method based on the equation-of-

'

 (9)

23 parameter depend on chemical structure of the solute and it is

*ABC* corresponds to an immiscible systems whereas a

<sup>23</sup> ) values relative to those which would be obtained

23 values are solvent (solute) independent for probes

23 should be solvent independent. The equation

23 named 'true', because the

'

A positive value of the parameter

modifies the retention volume (and

Values of Flory-Huggins

and carbon tetrachloride.

Many authors suggest that the

above is often called "Δχ effect".

> 

giving

 

and VP are nearly the same [Prolongo et al., 1989].

12 13 0 interaction parameter

'

state theory, which gives a polymer-polymer parameter

 

negative is an indicator of miscibility [Nesterov & Lipatov, 2001].

'

$$
\hat{\mathcal{L}}\boldsymbol{\chi}\_{1m} = \boldsymbol{\varphi}\_2 \cdot \boldsymbol{\chi}\_{12} + \boldsymbol{\varphi}\_3 \cdot \boldsymbol{\chi}\_{13} - \boldsymbol{\varphi}\_2 \cdot \boldsymbol{\varphi}\_3 \cdot \boldsymbol{\chi}\_{23} \tag{12}
$$

Equation (12) predicts that a plot of 1*m* versus ( 2 12 3 13 ) will give a straight line with a slope 1 and an intercept of - ' 2 3 23 .

Jan-Chan Huang [Huang, 2003] and with R. Deanin [Huang & Deanin, 2004] rearranged equation (12) into the following form:

$$\frac{\mathcal{X}\_{1m}}{V\_1} = \frac{\varrho\_2 \cdot \mathcal{X}\_{12} + \varrho\_3 \cdot \mathcal{X}\_{13}}{V\_1} - \frac{\varrho\_2 \cdot \varrho\_3 \cdot \dot{\mathcal{X}}\_{23}}{V\_2} \tag{13}$$

The polymer-polymer interaction term can be determined from the intercept at 2 12 3 13 1 0 *<sup>V</sup>* . This modification provided smaller standard deviations for the slope and the polymer-polymer interaction parameter.

Jan-Chan Huang [Huang, 2006] used also solubility parameter model to the study of the miscibility and thermodynamic properties of solutions by means of IGC. Because polymer– polymer mixtures have little entropy of mixing, the miscibility is largely decided by the sign of the heat of mixing. The determination of the heat of mixing becomes the key factor. The heat of vaporization is related to the solubility parameter, of the liquid by the relation:

$$
\delta \mathcal{S} = \left(\frac{\Delta E\_{vap}}{V}\right)^{1/2} \tag{14}
$$

where *Evap* is the energy of vaporization and *V* is the molar volume of the solvent.

The Flory–Huggins interaction parameter can be related to the solubility parameters of the two components by:

$$\mathcal{Z} = \left(\frac{V\_1}{RT}\right) \cdot \left(\delta\_1 - \delta\_2\right)^2 \tag{15}$$

where 1 and 2 are the solubility parameters of the solvent and polymer, respectively, and V1 is the volume of the solvent.

Guillet and co-workers [DiPaola-Baranyi & Guillet, 1978; Ito & Guillet 1979] have proposed IGC method for estimating of Flory–Huggins interaction parameter and solubility parameter for polymers by the modification of Eq. (15):

$$
\left(\frac{\delta\_1^2}{RT} - \frac{\mathcal{X}}{V\_1}\right) = \left(\frac{2\delta\_2}{RT}\right)\delta\_1 - \left(\frac{\delta\_2^2}{RT}\right) \tag{16}
$$

It is a straight line equation. The left-hand side contains the values of Flory–Huggins interaction parameter of test solute (see Eq. (2)), solubility parameter of test solute ()) and its molar volume. Plotting the left-hand side of such equation vs. solubility parameter of test solute () one obtains the slope (*a*=/*RT*) enabling the calculation of the solubility parameter of the examined material. This value should be equal to that found from the intercept and positive [Voelkel et al., 2009 (b)].

When a mixture is used as the stationary phase the solubility parameter of the mixture, m , can be compared with the prediction of the regular solution method, which gives m to be the volume average of the two components [Huang, 2006]:

$$
\delta\_m = \varphi\_A \cdot \delta\_A + \varphi\_B \cdot \delta\_B \tag{17}
$$

From this equation the formula of specific heat of mixing in the regular solution theory could be derived. A measurement of the solubility parameter of the polymer mixtures would then be a good indicator to predict their miscibility.

Huang [Huang, 2006] proposed a mechanism of probe dependency. When two polymers with specific interactions are brought together some functional groups interact with each other and are no longer available to the probes. Relative to the volume average of the pure components the probes will feel the mixture becomes lower in polar or hydrogen bonding interaction and more in nonpolar dispersive force. In other words, the mixture becomes more ''alkane-like''. The polar probes will be squeezed from the stationary phase and the specific retention volume decreased, which increases <sup>1</sup>*m* through Eq. (5) then decreases

' 23 through Eq. (13). Therefore, polar probes have lower retention volume and ' <sup>23</sup> , and for n-alkane probes the change is less. This difference between probes is exhibited as the probe dependency.

#### **4. Applications**

428 Advanced Gas Chromatography – Progress in Agricultural, Biomedical and Industrial Applications

Jan-Chan Huang [Huang, 2003] and with R. Deanin [Huang & Deanin, 2004] rearranged

1 2 12 3 13 2 3 23 11 2

The polymer-polymer interaction term can be determined from the intercept at

Jan-Chan Huang [Huang, 2006] used also solubility parameter model to the study of the miscibility and thermodynamic properties of solutions by means of IGC. Because polymer– polymer mixtures have little entropy of mixing, the miscibility is largely decided by the sign of the heat of mixing. The determination of the heat of mixing becomes the key factor. The

1/2 *Evap*

 

*Evap* is the energy of vaporization and *V* is the molar volume of the solvent.

The Flory–Huggins interaction parameter can be related to the solubility parameters of the

 

Guillet and co-workers [DiPaola-Baranyi & Guillet, 1978; Ito & Guillet 1979] have proposed IGC method for estimating of Flory–Huggins interaction parameter and solubility

> 

 2 2 1 22

2

It is a straight line equation. The left-hand side contains the values of Flory–Huggins

its molar volume. Plotting the left-hand side of such equation vs. solubility parameter of test

parameter of the examined material. This value should be equal to that found from the

1

1 2 1 2

2 are the solubility parameters of the solvent and polymer, respectively, and

 

*RT V RT RT* (16)

/*RT*) enabling the calculation of the solubility

)) and

1

interaction parameter of test solute (see Eq. (2)), solubility parameter of test solute (

*V*

*<sup>V</sup>* . This modification provided smaller standard deviations for the

   

> 

'

*VV V* (13)

2 12 3 13 ) will give a straight line

of the liquid by the relation:

*V* (14)

*RT* (15)

1*m* versus (

 ' 2 3 23 .

slope and the polymer-polymer interaction parameter.

heat of vaporization is related to the solubility parameter,

parameter for polymers by the modification of Eq. (15):

) one obtains the slope (*a*=

intercept and positive [Voelkel et al., 2009 (b)].

*m*

Equation (12) predicts that a plot of

equation (12) into the following form:

0

 2 12 3 13 1

where

where 1 and 

solute (

two components by:

V1 is the volume of the solvent.

with a slope 1 and an intercept of -

Authors examined many polymeric materials filled with modified silica or other inorganic fillers. Our measurements were carried out with the use of Chrom5 (Kovo, Prague, Czech.Rep.) gas chromatograph equipped with a flame ionisation detector. Some of the results were presented here.

#### **4.1 Flory-Huggins parameters for polylactic acid compositions**

For composition of polylactic acid (P, M=55000), containing different amount (5, 10, 15% wt) of modified silica (B2 and B5) [Jesionowski, 1999] or modified carbonate-silicate fillers (N1 and N2) [Grodzka 2004] we calculated Flory-Huggins parameters 12 and ' <sup>23</sup> . The influence of the temperature and the amount and type of filler was examined. To eliminate the solvent dependence of ' 23 values (from basic Eq. 8) experimental data were recalculated according to Zhao-Choi procedure.

Small volumes (0.L) of vapour of the probes were injected manually to achieve the infinite dilution conditions. These were: n-pentane (C5), n-hexane (C6), n-heptane (C7), n-octane (C8), n-nonane (C9), dichloromethane (CH2Cl2), chloroform (CHCl3), carbon tetrachloride (CCl4), 1,2-dichloroethane (Ethyl. Chl.) (all from POCH, Gliwice, Poland).

Values of 12 parameter for P-15N1 (it denotes the composition of polylactic acid with 15% of N1 filler) composition we presented in Figure 2. We obtained almost the same values of 12 parameter for other investigated compositions.

Fig. 2. Values of Flory-Huggins 12 parameter for P-15N1 composition

The lowest values of 12 parameter were obtained for dichloromethane (MeCl) and chloroform (CHCl3) as the test solute. Values calculated for compositions were almost always lower than those found for pure components, i.e. polymer and/or filler separately. The increase of temperature decreased values of 12 only for P-5B5 system, indicating the increase of interactions between composition and test solute. For the other compositions the increase of temperature increased values of 12 parameter.

The influence of the amount and type of filler was also examined. The change of these two factors also lead to the changes in the solute-composition interactions (Fig. 3). The influence of the amount of the filler is different for various compositions. For composition with N1 filler (carbonate-silicate filler modified with N-2-aminoethyl-3-aminopropyltrimethoxysilane) the strongest interaction with solvent was found for the composition containing 5% of the filler. However, for P-N2 the most active is the composition with 15% addition of N2 (carbonate-silicate filler modified with n-octyltriethoxysilane).

Fig. 3. The influence of the type and the amount of the filler [% wt.] on 12 parameters at 403K

363 K 383 K 403 K

C5 C6 C7 C8 C9 C10 MeCl CHCl3 CCl4 DiClEtETHER **Test solute**

chloroform (CHCl3) as the test solute. Values calculated for compositions were almost always lower than those found for pure components, i.e. polymer and/or filler separately.

increase of interactions between composition and test solute. For the other compositions the

The influence of the amount and type of filler was also examined. The change of these two factors also lead to the changes in the solute-composition interactions (Fig. 3). The influence of the amount of the filler is different for various compositions. For composition with N1 filler (carbonate-silicate filler modified with N-2-aminoethyl-3-aminopropyltrimethoxysilane) the strongest interaction with solvent was found for the composition containing 5% of the filler. However, for P-N2 the most active is the composition with 15%

addition of N2 (carbonate-silicate filler modified with n-octyltriethoxysilane).

Fig. 3. The influence of the type and the amount of the filler [% wt.] on

12 parameter for P-15N1 composition

12 parameter.

12 parameter were obtained for dichloromethane (MeCl) and

12 only for P-5B5 system, indicating the

12 parameters

0.0

Fig. 2. Values of Flory-Huggins

The lowest values of

at 403K

The increase of temperature decreased values of

increase of temperature increased values of

12 

0.5

1.0

1.5

 12 2.0

2.5

Determined values of ' 23 depend on the type of the test solute used in IGC experiment (Fig. 4). Influence of the amount of the filler on the Flory-Huggins parameter ' 23 was examined and some results are presented in Figure 4. It is depended on test solute used in our study. For C5-C7 and CHCl3 and CCl4 we obtained the lowest values for 5% of N1 filler. For the other solutes – the strongest interaction are observed between polymer and 15% of the filler. Generally, the strongest interaction between components were observed for compositions with 5% of the filler.

Fig. 4. Values of Flory-Huggins ' 23 parameter for compositions with 5%, 10% or 15% of filler

To eliminate the solvent dependence of ' 23 values (from basic equation) experimental data were recalculated according to Zhao-Choi procedure (Eq. 12). Values of ' *ZC* 23 parameter are presented in Figure 5. In all cases only one value for each composition was obtained. All ' *ZC* 23 values indicated the presence of strong or medium interaction between the modified filler and polymer matrix. This observation is consistent with that formulated after analysis of ' 23 data found for most of test solutes in the classic procedure.

Fig. 5. Values of Flory-Huggins ' *ZC* 23 parameter for all compositions calculated according to Zhao-Choi procedure

It is worth to note that the increase of the filler content does not enhance the magnitude of interactions. Most often limited (rather negligible) decrease of polymer-filler interactions was observed.

#### **4.2 Chemometric evaluation of IGC data**

Principal Component Analysis (PCA) became a popular technique in data analysis for classification for pattern recognition and dimension reduction. It can reveal several underlying components, which explain the vast majority of variance in the data [Héberger, 1999; Malinowski, 1991; Héberger et al., 2001]. The principle is to characterize each object (rows in the input matrix) not by analyzing every variable (columns of the input matrix) but projecting the data in a much smaller subset of new variables (or principal component scores). PCA should facilitate the overcoming of the problem connected with the solute dependence of ' 23 parameter.

Values of Flory–Huggins ' 23 parameter expressing the magnitude of interactions between the polymer matrix and filler strongly depend on the type of test solute being used in IGC experiment (see Fig. 4). It causes the difficulties in the analysis of the influence of the type and amount of the filler onto the magnitude of these interactions. Such analysis is possible with the help of PCA technique [Voelkel et al., 2006] as presented in Fig. 6 for systems of polyurethane (PU) with modified silica fillers (B2). Materials used in experiments were described elsewhere [Milczewska & Voelkel 2002; Milczewska, 2001]. The magnitude of interactions is similar (the corresponding points belong to one – large cluster) for most of samples. Outside this large cluster the points correspond mainly to the compositions with 5 or 20% of the filler.

Fig. 6. Scatterplot for Polyurethane (PU) systems [Reprinted from Voelkel et al., 2006 with permission from Elsevier]

It is worth to note that the increase of the filler content does not enhance the magnitude of interactions. Most often limited (rather negligible) decrease of polymer-filler interactions

Principal Component Analysis (PCA) became a popular technique in data analysis for classification for pattern recognition and dimension reduction. It can reveal several underlying components, which explain the vast majority of variance in the data [Héberger, 1999; Malinowski, 1991; Héberger et al., 2001]. The principle is to characterize each object (rows in the input matrix) not by analyzing every variable (columns of the input matrix) but projecting the data in a much smaller subset of new variables (or principal component scores). PCA should facilitate the overcoming of the problem connected with the solute

the polymer matrix and filler strongly depend on the type of test solute being used in IGC experiment (see Fig. 4). It causes the difficulties in the analysis of the influence of the type and amount of the filler onto the magnitude of these interactions. Such analysis is possible with the help of PCA technique [Voelkel et al., 2006] as presented in Fig. 6 for systems of polyurethane (PU) with modified silica fillers (B2). Materials used in experiments were described elsewhere [Milczewska & Voelkel 2002; Milczewska, 2001]. The magnitude of interactions is similar (the corresponding points belong to one – large cluster) for most of samples. Outside this large cluster the points correspond mainly to the compositions with 5

Fig. 6. Scatterplot for Polyurethane (PU) systems [Reprinted from Voelkel et al., 2006 with

23 parameter expressing the magnitude of interactions between

was observed.

dependence of

or 20% of the filler.

permission from Elsevier]

'

Values of Flory–Huggins

23 parameter.

'

**4.2 Chemometric evaluation of IGC data** 

IGC procedures discussed earlier allow eliminating the test solutes dependence of ' 23 values. However, very often the relatively significant error of the determination was reported.

Values of ' 23 parameter calculated according to Zhao–Choi procedure for the examined polymeric composition are presented in Table 1. All values are negative and close to zero. It indicates the existence of polymer–filler interaction although their strength is limited.


Table 1. Values of ' 23 parameter calculated by Zhao-Choi method for B2-PU compositions [Reprinted from Voelkel et al., 2006 with permission from Elsevier]

The differences of the magnitude of polymer–filler interactions are significant as the error of determination is equal to approximately 2.5\*10−7, i.e. it is at least two orders lower than the determined ' 23 values. However, collection of retention data for all test solutes is somewhat time-consuming. It would be useful to select the test solutes carrying the statistically valid information, applied these species in IGC experiments and further use their retention data in calculations of ' 23 from Zhao–Choi procedure. The problem was: how the reduction of the number of test solutes will influence the ' 23 values as well as error of their determination.

For all PU compositions PCA made possible using three - four test solutes (C6, C8, MeCl and CCl4) for determination of interaction parameters. Recalculating of ' 23 from Zhao– Choi procedure for selected test solutes gave values presented in Table 2.

Comparison of values of ' 23 calculated by Zhao-Choi method before and after PCA selection of solutes is presented on Figure 7. Corrected values are lower or higher than these found for all test solutes, but they indicate the presence or absence of interaction.


Table 2. Values of ' 23 parameter for B2-PU compositions calculated by Zhao-Choi method after PCA selection of solutes [Reprinted from Voelkel et al., 2006 with permission from Elsevier]

Fig. 7. Comparison of ' <sup>23</sup> calculated by Zhao–Choi procedure before and after PCA selection of test solutes for PU [Reprinted from Voelkel et al., 2006 with permission from Elsevier]

PCA enabled the significant reduction of the number of test solutes required for the proper determination of Flory–Huggins parameter and further the reduction of time required for proper characterization of examined material.

#### **5. Summary**

Inverse gas chromatography method has been found to be an effective tool for measurement of the magnitude of interaction ( 12 interaction material – test solute) in polymers at different temperatures. From technological point of view ' <sup>23</sup> is more interesting. This parameter can be used as indicator of the miscibility of the polymer blend.

Drawback of ' 23 estimated by classical procedure is the test solute dependence. The procedure of its elimination proposed by Zhao-Choi seems to be most appropriate. It leads to realistic values of ' <sup>23</sup> with low error of determination. The full procedure of ' <sup>23</sup> .with the use of large series of the test solutes might be time-consuming. The use of chemometric analysis enabled the reduction of the number of the test solutes without loss of information. One may expect further application of IGC in examination of polymer materials.

#### **6. References**

Al-Ghamdi A., Al-Saigh Z.Y. (2000) *J. Polym. Sci., Part B: Polym. Phys*. Vol. 38 pp. 1155-1166.

Al-Saigh Z., Munk P. (1984) *Macromolecules* Vol. 17 pp. 803-809.

Al-Saigh Z.Y. (1997) *TRIP* Vol. 5 pp. 97-101.


<sup>23</sup> calculated by Zhao–Choi procedure before and after PCA

23 estimated by classical procedure is the test solute dependence. The

<sup>23</sup> with low error of determination. The full procedure of

12 interaction material – test solute) in polymers at

<sup>23</sup> is more interesting. This

'

<sup>23</sup> .with the

'

selection of test solutes for PU [Reprinted from Voelkel et al., 2006 with permission from

PCA enabled the significant reduction of the number of test solutes required for the proper determination of Flory–Huggins parameter and further the reduction of time required for

Inverse gas chromatography method has been found to be an effective tool for measurement

procedure of its elimination proposed by Zhao-Choi seems to be most appropriate. It leads

use of large series of the test solutes might be time-consuming. The use of chemometric analysis enabled the reduction of the number of the test solutes without loss of information.

Al-Ghamdi A., Al-Saigh Z.Y. (2000) *J. Polym. Sci., Part B: Polym. Phys*. Vol. 38 pp. 1155-1166.

Boukerma K., Piquemal J.Y., Chehimi M.M., Mravcakova M., Omastova M., Beaunier P.

de Gennes P.G. (1979) *Scaling Concepts in Polymer Physics*, Cornell University Press, Ithaca,

parameter can be used as indicator of the miscibility of the polymer blend.

One may expect further application of IGC in examination of polymer materials.

different temperatures. From technological point of view

Al-Saigh Z., Munk P. (1984) *Macromolecules* Vol. 17 pp. 803-809.

Fig. 7. Comparison of

Elsevier]

**5. Summary** 

Drawback of

to realistic values of

**6. References** 

NY.

'

proper characterization of examined material.

of the magnitude of interaction (

'

> '

Al-Saigh Z.Y. (1997) *TRIP* Vol. 5 pp. 97-101.

(2006) *Polymer* Vol. 47 pp. 569-576.


### **Recent Applications of Comprehensive Two-Dimensional Gas Chromatography to Environmental Matrices**

Cardinaël Pascal1, Bruchet Auguste2 and Peulon-Agasse Valérie1 *1SMS, Université de Rouen, 2CIRSEE (Centre International de Recherche Sur l'Eau et l'Environnement), France* 

#### **1. Introduction**

436 Advanced Gas Chromatography – Progress in Agricultural, Biomedical and Industrial Applications

Oliva V., Mrabet B., Neves M.I.B., Chehimi M.M., Benzarti K. (2002) *J. Chromatogr. A* Vol. 969

Schwann D., Frielinghaus H., Mortensen K., Almdal K. (1996) *Phys. Rev. Lett*. Vol. 77 pp.

Ovejero G., Pérez P., Romero M.D., Díaz I., Díez E. (2009) *Eur. Polym. J.* Vol.45 pp. 590-594.

Prolongo M.G., Masegosa R.M., Horta A. (1989) *Macromolecules* Vol. 22 pp. 4346-4351. Schuld N., Wolf B.A. (2001) *J. Polym. Sci.: Part B: Polym. Phys.* Vol. 39 pp. 651-662.

Sun H., Rhee K.B., Kitano T., Mah S.I. (1999) *J. Appl. Polym. Sci.* Vol. 73 pp. 2135-2142. van Asten A., van Veenendaal N., Koster S. (2000) *J. Chromatogr. A* Vol. 888 pp. 175-196.

Voelkel A., Milczewska K., Héberger K. (2006) *Analytica Chimica Acta* Vol. 559 pp. 221-226. Voelkel A., Strzemiecka B., Adamska K., Milczewska K. (2009) *J. Chromatogr. A* Vol. 1216 pp.

Voelkel A., Strzemiecka B., Adamska K., Milczewska K., Batko K. (2009) Surface and bulk

Ying Q., Chu B., Wu G., Linliu K., Gao T., Nose T., Okada M. (1993). *Macromolecules* Vol. 26

Zou Q.C., Zhang S.L., Wang S.M., Wu L.M. (2006) *J. Chromatogr. A* Vol. 1129 pp. 255-261.

characteristics of polymers by means of inverse gas chromatography *in* A. Nastasovic, S. Jovanovic (eds.) *Polymeric materials*, Research Signpost, pp. 71-102. (a)

Nesterov A.E., Lipatov Y.S., Ignatova T.D. (2001) *Eur. Polym. J.* Vol. 37 pp. 281-285.

Petri H.M., Schuld N., Wolf B.A. (1995) *Macromolecules* Vol. 28 pp. 4975-4980.

Shi Z.H., Schreiber H.P. (1991) *Macromolecules* Vol. 24 pp. 3522–3527. Shillcock I.M., Price G.J. (2003) *Polymer* Vol. 44 pp. 1027-1034.

Su C.S., Patterson D. (1977) *Macromolecules* Vol. 10 pp. 708-710.

Voelkel A., Fall J. (1997) *Chromatographia* Vol. 44 pp. 197-204.

Zhao L., Choi P. (2001) *Polymer* Vol. 42 pp. 1075-1081. Zhao L., Choi P. (2002) *Polymer* Vol. 43 pp. 6677-6681.

Olabisi O. (1975) *Macromolecules* Vol. 8 pp. 316-322.

pp. 261-272.

3153-3156.

1551-1566 (b)

pp. 5890-5896.

SMS-*i*GC brochure 2002

Anthropological pressure on environment combined with continuous progress of analytical techniques allows the detection of more micro-pollutants in environmental matrices. Analysis of Persistent Organic Pollutants (POPs) remains a real challenge due to the large number of compounds and the complexity of environmental matrices. Conventional Gas Chromatography (GC) coupled with mass spectrometry (MS) is the reference technique for the analysis and the quantification of volatile and semi-volatile pollutants. Comprehensive two-dimensional gas chromatography (GC×GC) is a relatively new technique, developed in 1991 by Liu and Phillips (Liu & Phillips, 1991). This technique provides high separation power and sensitivity. The principles of multidimensional chromatography were described by Giddings (Giddings, 1984). When a fraction or few fractions of the effluent from a first column, is subsequently injected into a second column with a different selectivity, the multidimensional chromatographic separation techniques are called 'heart cutting'. These methods have proved to be very effective only in target compounds analysis. A twodimensional separation can be called comprehensive if the three following conditions are established (Schoenmakers et al., 2003). First, every part of the sample is subjected to two different separations. Secondly, equal percentages (either 100% or lower) of all sample components pass through both columns and eventually reach the detector. Finally, the separation (resolution) obtained in the first dimension is essentially maintained. This latter point could be reached if the transfer of the effluent from the first column to the second one was successfully performed by a modulator or column interface. So, the modulator could be considered as the 'heart' of the system and is currently in development. A maximum of retention space could be used especially if compounds are subjected to two independent separations. Orthogonal separation occurs when the two columns use different separation mechanisms, operating independently in the two dimensions. In practice, columns containing chemically different stationary phases are chosen. In normal orthogonality, the first apolar column is coupled to a column containing a stationary phase of equivalent or higher polarity. For reversed orthogonality, the more polar stationary phase is used in first dimension and a less polar one in second dimension. Due to the low peak width, some constraints are imposed for the choice of detector. An ideal data acquisition rate for GC×GC detector is equal or more than 100 Hz to maintain its large separation power. Numerous detectors, conventionally used in GC like Flame Ionization Detector (FID), Electron Capture Detector (ECD) and microECD (µECD), have been widely employed. Concerning the MS, the high speed time-of-flight (TOFMS) with a unit-mass resolution has proved to be the best candidate for GC×GC. Moderate acquisition rate instruments, such as quadrupole mass spectrometer qMS (e.g. 20 Hz) were also used with a limited mass range. Several GC×GC instruments with various modulators have been developed (Semard et al., 2009) and are now commercially available. GC×GC has now demonstrated its capacity of resolution in the field of complex matrices like petroleum products, fragrance (Dallüge et al., 2003). GC×GC is currently one of the most effective techniques for the separation and analysis of environmental samples, offering significantly greater peak capacities than conventional chromatographic methods. GC×GC provides three major benefits, namely, enhanced chromatographic separation, improved sensitivity by effect of cryofocusing with the thermal modulator, and chemical class ordering in the contour plot (Ballesteros-Gomez & Rubio, 2011). Research in GC×GC has recently shifted from instrumental development to application to real samples over the last four years especially with the coupling to MS. Nearly 83% of the over 110 research articles published (specify the type or classification of articles) in 2010 were devoted to applications of GC×GC (Edwards et al., 2011). Moreover, some software improvements have also facilitated GC×GC quantitative analyses.

A few reviews were already published about applications of comprehensive GC in relation to environmental analyses. The most recent review was proposed by Wang et al. (Wang et al., 2010) that covered the works published between 2007 and the beginning of 2009. This chapter focuses on the most important developments in environmental applications of GC×GC, salient advances in GC×GC instrumentation and theoretical aspects reported over the period 2009 to July 2011. Recent applications using GC×GC methods for analysis of environmental toxicants such as PolyChlorinatedDibenzo-p-Dioxins (PCDDs), PolyChlorinatedDibenzoFurans(PCDFs), PolyChlorinatedBiphenyls (PCBs), Polycyclic Aromatic Hydrocarbons (PAHs), pesticides, alkylphenols *etc*… are reviewed. Moreover, this technique appeared especially suitable for the development of multiresidue analytical methods which was the most important trend in GC×GC-MS environmental analysis over the last period. The recent works demonstrated that this technique provides interesting alternative methods in terms of sensitivity and mapping of pollutants and minimizes sample preparation steps. A part of this chapter will be dedicated to the recent screening of emerging contaminants such as pharmaceuticals, plasticizers, personal care products, ... Various matrices (water, soils and sediments) will be considered including river and wastewater. Analysis of air sample were not reported according to the publication of recent reviews dealing with the analysis of Volatile and semivolatile Organic Compounds (VOCs) found in the atmosphere (Arsene et al., 2011; Hamilton, 2010). All aspects of GC×GC will be presented including instrumentation, theoretical considerations and applications. Moreover, novel tools used for optimization of retention space or orthogonality estimation will be discussed.

#### **2. GC×GC and environmental analysis reviews**

A non exhaustive review (Ballesteros-Gomez & Rubio, 2011) was focused on main developments and advances in environmental analysis reported over the period 2009-2010. Numerous aspects of environmental analysis, based on more than 200 articles, were reported including sampling, sample preparation, separation and detection … Emerging contaminants and atomic spectrometry for the determination of trace metals and metalloids topics were excluded due to the publication of other reviews. Few applications of GC×GC were shortly reported (Eganhouse et al., 2009; Matamoros et al., 2010a; Hilton et al., 2010) and will be discussed in the present chapter. Recently, GC×GC applications devoted to measurement of volatile and semivolatile organic compounds in air and aerosol were reviewed and discussed (Arsene et al., 2011, Hamilton, 2010).

Wang *et al.* (Wang et al., 2010) have reviewed technological advances and applications of GC×GC between 2007 and July 2009. For example, separations of eight persistent organohalogenated classes of pollutants including OrganoChlorinatedPesticides (OCPs), PCBs, PolyBrominatedDiphenylEthers (PBDEs), PolyChlorinatedNaphthalenes (PCNs), PCDDs, PCDFs, PolyChlorinatedTerphenyls (PCTs), and toxaphene (CTT) in environmental samples were reported by Bordajandi *et al.* (Bordajandi et al., 2008). Nine column combinations in normal and reversed orthogonality (ZB-5, HT-8, DB-17 and BP-10, as first dimension column and HT-8, BPX-50 and Carbowax as second dimension one) were tested. The feasibility of the proposed approach for the fast screening of the target classes of pollutants was illustrated by the analysis of food and marine fat samples. A method of quantification of PAHs in air particulates based on a GC×GC isotope dilution mass spectrometry method was also reported by Amador-Munoz *et al.* (Amador-Munoz et al., 2009) with favorable resolution and sensitivity over conventional one dimensional GC. GC×GC-TOFMS method was successfully developed by Skoczynska *et al.* (Skoczynska et al., 2008) to identify 400 compounds in highly polluted sediment sample from the River Elbe (Czech Republic). Several older reviews dealing with the development of GC×GC and its applications including environmental matrices could be mentioned (Ramos et al., 2009; Cortes et al., 2009*;* Adahchour et al., 2006; Adahchour et al., 2008; Pani & Gorecki., 2006).

#### **3. PCBs**

438 Advanced Gas Chromatography – Progress in Agricultural, Biomedical and Industrial Applications

detector is equal or more than 100 Hz to maintain its large separation power. Numerous detectors, conventionally used in GC like Flame Ionization Detector (FID), Electron Capture Detector (ECD) and microECD (µECD), have been widely employed. Concerning the MS, the high speed time-of-flight (TOFMS) with a unit-mass resolution has proved to be the best candidate for GC×GC. Moderate acquisition rate instruments, such as quadrupole mass spectrometer qMS (e.g. 20 Hz) were also used with a limited mass range. Several GC×GC instruments with various modulators have been developed (Semard et al., 2009) and are now commercially available. GC×GC has now demonstrated its capacity of resolution in the field of complex matrices like petroleum products, fragrance (Dallüge et al., 2003). GC×GC is currently one of the most effective techniques for the separation and analysis of environmental samples, offering significantly greater peak capacities than conventional chromatographic methods. GC×GC provides three major benefits, namely, enhanced chromatographic separation, improved sensitivity by effect of cryofocusing with the thermal modulator, and chemical class ordering in the contour plot (Ballesteros-Gomez & Rubio, 2011). Research in GC×GC has recently shifted from instrumental development to application to real samples over the last four years especially with the coupling to MS. Nearly 83% of the over 110 research articles published (specify the type or classification of articles) in 2010 were devoted to applications of GC×GC (Edwards et al., 2011). Moreover,

some software improvements have also facilitated GC×GC quantitative analyses.

discussed.

**2. GC×GC and environmental analysis reviews** 

A few reviews were already published about applications of comprehensive GC in relation to environmental analyses. The most recent review was proposed by Wang et al. (Wang et al., 2010) that covered the works published between 2007 and the beginning of 2009. This chapter focuses on the most important developments in environmental applications of GC×GC, salient advances in GC×GC instrumentation and theoretical aspects reported over the period 2009 to July 2011. Recent applications using GC×GC methods for analysis of environmental toxicants such as PolyChlorinatedDibenzo-p-Dioxins (PCDDs), PolyChlorinatedDibenzoFurans(PCDFs), PolyChlorinatedBiphenyls (PCBs), Polycyclic Aromatic Hydrocarbons (PAHs), pesticides, alkylphenols *etc*… are reviewed. Moreover, this technique appeared especially suitable for the development of multiresidue analytical methods which was the most important trend in GC×GC-MS environmental analysis over the last period. The recent works demonstrated that this technique provides interesting alternative methods in terms of sensitivity and mapping of pollutants and minimizes sample preparation steps. A part of this chapter will be dedicated to the recent screening of emerging contaminants such as pharmaceuticals, plasticizers, personal care products, ... Various matrices (water, soils and sediments) will be considered including river and wastewater. Analysis of air sample were not reported according to the publication of recent reviews dealing with the analysis of Volatile and semivolatile Organic Compounds (VOCs) found in the atmosphere (Arsene et al., 2011; Hamilton, 2010). All aspects of GC×GC will be presented including instrumentation, theoretical considerations and applications. Moreover, novel tools used for optimization of retention space or orthogonality estimation will be

A non exhaustive review (Ballesteros-Gomez & Rubio, 2011) was focused on main developments and advances in environmental analysis reported over the period 2009-2010. PCBs are composed of 209 distinct congeners and are found in complex mixtures (Aroclors).They were commercially used in a variety of applications, including heat transfer and hydraulic fluids, dielectric fluids for capacitors, and as additives in pesticides, sealants, and plastics (Osemwengie & Sovocool, 2011). The World Health Organization (WHO) has designated twelve PCBs as "dioxin-like", coplanar PCB congeners that exhibited high toxicity.

Recently, a routine accredited method (Muscalu et al., 2011) was presented for analysis of PCBs, chlorobenzenes and other halogenated compounds in soil, sediment and sludge by GC×GC-µECD. A column combination DB1×Rtx-PCB was used to minimize coelution of analytes. The method was developed to analyze these pollutants in a single analytical run and no fractionation of sample extracts prior to instrument analysis, with enhanced selectivity and sensitivity over one dimensional GC method. The method can also be used to perform analytical triage to screen for additional compounds, for additional extract processing and testing or for identification and monitoring of new and emerging halogenated compounds present in sample extracts and to screen other halogenated organics. The optimized method provided quantification of Aroclors and Aroclors mixtures to within 15% of targets values and sub-nanograms per gram detection limits. The authors claimed that GC×GC requires minimal additional training to be used as a routine analytical method for the analysis of halogenated compounds.

Separation of 209 PCB congeners, using a sequence of 1D and 2D chromatographic modes was evaluated (Osemwengie et al., 2011). The authors used a RTX-PCB column as the first column and a DB-17 as the second one. In two consecutive chromatographic runs, 196 PCB congeners were distinguished, including 43 of the 46 pentachlorobiphenyl isomers. PCBs congeners that were not resolved chromatographically were resolved with the deconvolution program (ChromaTOFSoftware). Nevertheless, the 209 congeners have not been successfully separated.

New capillary columns coated with Ionic Liquids (ILs) were used as second columns for the separation of 209 PCBs congeners (Zapadlo et al., 2010; Zapadlo et al., 2011). In the first paper (Zapadlo et al., 2010), the orthogonality of three columns coupled in two series was studied. A non-polar capillary column coated with poly(5%-phenyl–95%-methyl)siloxane was used as the rst column in both series. A polar capillary column coated with 70% cyanopropyl-polysilphenylene-siloxane or a capillary column coated with the ionic liquid 1,12-di(tripropylphosphonium)-dodecanebis(triuoromethanesulfonyl)imide (IL36) was used as the second columns. The authors concluded that column coated with IL was more polar and more selective for the separation of PCBs than BPX-70 column (Figure 1).

Fig. 1. 2D images for the separation of toxic, dioxin-like PCBs 81 and 105 on DB-5×BPX-70 and DB-5×IL-36 column series. Reprinted from Journal of Chromatography, A, (Zapadlo et al., 2010). Copyright (2010), with permission from Elsevier.

All "dioxin-like" PCBs, with the exception of PCB 118 and PCB 106, were resolved by this set of columns. In the second study (Zapadlo et al., 2011), the separation of 209 PCBs congeners was investigated using GC×GC–TOF-MS with a non-polar/IL column series consisting of poly(50%-n-octyl-50%-methyl)siloxane and (1,12-di(tripropylphosphonium) dodecanebis(triuoromethansulfonyl)amide) (SLB-IL59) in the rst and second dimensions, respectively. A total of 196 out of 209 PCBs congeners were resolved by separation and/or mass spectral deconvolution using the ChromaTOF software. All "dioxin-like" congeners were separated with no interferences from any PCB congener. The 109 PCBs present in Aroclor 1242 and the 82 PCBs present in Aroclor 1260 were resolved on this column set.

A Quantitative Structure–Retention Relationship (QSRR) method (D'Archivio et al., 2011) was applied to predict the retention times of 209 PCBs in GC×GC. Predicted data were compared to GC×GC retention data taken from the literature. Authors demonstrated that the experimental GC×GC chromatogram of PCBs can be accurately predicted using a QSRR model calibrated with retention data of about 1/3 of the congeners collected under the same separation conditions. The effect of structure on retention time in both dimensions can be successfully encoded by theoretical molecular descriptors quickly available by means of various computational methods.

### **4. PCDDs and PCDFs**

440 Advanced Gas Chromatography – Progress in Agricultural, Biomedical and Industrial Applications

claimed that GC×GC requires minimal additional training to be used as a routine analytical

Separation of 209 PCB congeners, using a sequence of 1D and 2D chromatographic modes was evaluated (Osemwengie et al., 2011). The authors used a RTX-PCB column as the first column and a DB-17 as the second one. In two consecutive chromatographic runs, 196 PCB congeners were distinguished, including 43 of the 46 pentachlorobiphenyl isomers. PCBs congeners that were not resolved chromatographically were resolved with the deconvolution program (ChromaTOFSoftware). Nevertheless, the 209 congeners have not

New capillary columns coated with Ionic Liquids (ILs) were used as second columns for the separation of 209 PCBs congeners (Zapadlo et al., 2010; Zapadlo et al., 2011). In the first paper (Zapadlo et al., 2010), the orthogonality of three columns coupled in two series was studied. A non-polar capillary column coated with poly(5%-phenyl–95%-methyl)siloxane was used as the rst column in both series. A polar capillary column coated with 70% cyanopropyl-polysilphenylene-siloxane or a capillary column coated with the ionic liquid 1,12-di(tripropylphosphonium)-dodecanebis(triuoromethanesulfonyl)imide (IL36) was used as the second columns. The authors concluded that column coated with IL was more

polar and more selective for the separation of PCBs than BPX-70 column (Figure 1).

Fig. 1. 2D images for the separation of toxic, dioxin-like PCBs 81 and 105 on DB-5×BPX-70 and DB-5×IL-36 column series. Reprinted from Journal of Chromatography, A, (Zapadlo et

al., 2010). Copyright (2010), with permission from Elsevier.

method for the analysis of halogenated compounds.

been successfully separated.

PCDDs and PCDFs constitute two classes of structurally related chlorinated aromatic hydrocarbons that are both highly toxic and produced as by-products during a variety of chemical and combustion processes. Due to their hydrophobic character and resistance to metabolic degradation, these substances exist as complex congener mixtures in the environment and are considered as POPs.

De Vos *et al.* (de Vos et al., 2011a) developed an alternative method of GC coupled with High Resolution Mass Spectrometry (HRMS) for analysis of PCDDs and PCDFs using GC×GC-TOFMS in different matrices. Three GC column combinations (Rtx-Dioxin 2Rtx-PCB, Rxi-5 SilMSRtx-200 and Rxi-XLBRtx-200) were evaluated to quantify PCDDs and PCDFs in numerous soil and sediment samples taken from various strategic sites in South Africa with a highest result obtained of 76 ng Toxic Equivalent Quantity/kg. Results were also compared with those obtained using GC–HRMS and a good agreement was observed. The limit of detection (LOD) for the method (300 fg on column for spiked soil samples) was determined using the combination Rxi-XLB×Rtx-200 which provided excellent separation of the compounds mandated for analysis by United States Environmental Protection Agency (US EPA) Method (Figure 2).

Using a multi-step temperature program, all seventeen PCDDs and PCDFs components mandated by EPA Method 1613 were separated. GC×GC–TOFMS appeared to be a viable tool for dioxin screening and quantitation, especially in cases where PCDDs/PCDFs levels are greater than 1 ng.kg−1. The technique proved to be ideal for application in developing countries where GC–HRMS is not available, and can be used to minimize costs by selecting only positive samples for further analysis by GC–HRMS. GC×GC–TOFMS additionally provides full range mass spectra for all sample components, thus allowing for identification of non-target analytes e.g. the brominated dioxins.

Fig. 2. 2D selected ion contour plot for the 17 priority PCDD/Fs using the Rxi-XLB/Rtx-200 column combination. The PCDD/Fs are again well resolved, especially the 1,2,3,4,7,8- HxCDD and 1,2,3,6,7,8-HxCDD isomers. Reprinted from Journal of Chromatography, A, (de Vos, 2011a). Copyright (2011), with permission from Elsevier.

GC×GC–TOFMS was also applied to investigate (de Vos et al., 2011b) toxic waste. This technique has allowed both comprehensive screening of samples obtained from a hazardous waste treatment facility for numerous classes of POPs and also quantitative analysis for the individual compounds. Various column combinations have been investigated for handling very complex waste samples. The close correlation between values obtained using the GC×GC-TOFMS approach and the GC-HRMS method has confirmed the validity of this technique to quantify PCDDs, PCDFs and four dioxin-like non-ortho substituted PCBs at levels required by regulatory bodies. The authors have obtained consistently higher values with the GC×GC–TOFMS method than those obtained with GC-HRMS. Nevertheless, they considered that the differences were certainly within permissible levels considering that the analyses have been performed in different laboratories.

An original application of the high sensitivity obtained using cryogenic zone compression (CZC) has been described by Patterson *et al.* (Patterson et al., 2011). The use of a GC×GC cryogenic loop modulator to perform CZC-GC coupled with Isotopic Dilution (ID) HRMS has been shown to be the most sensitive method available for the measurement of 2,3,7,8 tetrachlorodibenzo-p-dioxin (2,3,7,8-TCDD) (less than approximately 586,000 2,3,7,8-TCDD molecules) in human samples.

#### **5. PAHs and hydrocarbons**

PAHs are organic pollutants generated during the incomplete combustion of different natural and anthropogenic sources. They could enter the environment via

Fig. 2. 2D selected ion contour plot for the 17 priority PCDD/Fs using the Rxi-XLB/Rtx-200 column combination. The PCDD/Fs are again well resolved, especially the 1,2,3,4,7,8- HxCDD and 1,2,3,6,7,8-HxCDD isomers. Reprinted from Journal of Chromatography, A, (de

GC×GC–TOFMS was also applied to investigate (de Vos et al., 2011b) toxic waste. This technique has allowed both comprehensive screening of samples obtained from a hazardous waste treatment facility for numerous classes of POPs and also quantitative analysis for the individual compounds. Various column combinations have been investigated for handling very complex waste samples. The close correlation between values obtained using the GC×GC-TOFMS approach and the GC-HRMS method has confirmed the validity of this technique to quantify PCDDs, PCDFs and four dioxin-like non-ortho substituted PCBs at levels required by regulatory bodies. The authors have obtained consistently higher values with the GC×GC–TOFMS method than those obtained with GC-HRMS. Nevertheless, they considered that the differences were certainly within permissible levels considering that the

An original application of the high sensitivity obtained using cryogenic zone compression (CZC) has been described by Patterson *et al.* (Patterson et al., 2011). The use of a GC×GC cryogenic loop modulator to perform CZC-GC coupled with Isotopic Dilution (ID) HRMS has been shown to be the most sensitive method available for the measurement of 2,3,7,8 tetrachlorodibenzo-p-dioxin (2,3,7,8-TCDD) (less than approximately 586,000 2,3,7,8-TCDD

PAHs are organic pollutants generated during the incomplete combustion of different natural and anthropogenic sources. They could enter the environment via

Vos, 2011a). Copyright (2011), with permission from Elsevier.

analyses have been performed in different laboratories.

molecules) in human samples.

**5. PAHs and hydrocarbons** 

municipal/industrial effluents. Exposure to PAHs represents a risk for human health due to their genotoxic and carcinogenic effects. The International Agency for Research on Cancer has classified them as possible and probable carcinogens for humans. The US EPA has included sixteen of them in the list of priority pollutants and establishes a maximum contaminant level for benzo[a]pyrene in drinking water at 0.2 µg.L−1. In the European Union (EU), eight PAHs have been identied as priority hazardous substances in the eld of water policy.

Chlorinated or brominated PAHs (Cl-PAHs and Br-PAHs) have been already detected in environmental samples such as fly ash (Horii et al., 2008) and sediment (Ishaq et al., 2003; Horii et al. 2009). Moreover, toxicities of Cl-PAHs have been investigated and reported (Horii et al., 2009). A method (Ieda et al. 2011) using GC×GC coupled with HRTOFMS was developed for the analysis of Cl-PAHs and Br-PAHs congeners in environmental samples. The GC×GC-HRTOFMS method allowed highly selective group type analysis with a very narrow mass window (e.g. 0.02 Da), accurate mass measurements for the full mass range (m/z 35–600) in GC×GC mode, and the calculation of the elemental composition for the detected congeners in the real-world sample. The authors reported, for the first time, the detection of highly chlorinated PAHs, such as C14H3Cl7 and C16H3Cl7, and ClBr-PAHs, such as C14H7Cl2Br and C16H8ClBr in the environmental samples (Figure 3).

Fig. 3. The difference of isotope patterns between two peaks in the soil extract; (a)-1 C14H6Cl4 and (b)-1 C16H8ClBr and GC×GC–HR TOFMS 2D exact mass chromatogram of a 0.02 Da wide windows (a)-2 C14H6Cl4; m/z 337.9224 and (b)-2 C16H8ClBr; m/z 313.9498. Reprinted from Publication, Journal of Chromatography, A, (Ieda et al., 2011). Copyright (2011), with permission from Elsevier.

Other organohalogen compounds; e.g. PCBs, PCNs, and PCDFs were also detected. This technique provided exhaustive analysis and powerful identification for the unknown and unconfirmed Cl-/Br-PAH congeners in environmental samples.

GC×GC-FID and GC×GC-TOFMS methods (Wardlaw et al., 2011) were used to study the biodegradation of alkylated naphthalenes and benzothiophenes isomers in marine sediment contaminated with crude oil. Their power resolution enabled separation and quantication of multiple structural isomers to determine their rst order rate constants for aerobic biodegradation. Rate constants were used as proxies for microbial preference. A strong isomeric biodegradation preference was noted within each of these compound classes, with rate constants varying as much as a factor of 2 for structural isomers of the same compound class.

HPLC-GC×GC-FID and GC×GC-TOFMS were used to study the biodegradation of petroleum hydrocarbons in soil microcosms during 20 weeks (Mao et al., 2009). Aromatic hydrocarbons and n-alkanes were better biodegradable (>60% degraded) than iso-alkanes and cycloalkanes (<40%). GC×GC chromatograms showed that more polar and heavier compounds were formed as biodegradation proceeded.

#### **6. Alkyl phenol isomers**

AlkylPhenol EthOxylates (APEOs) are surfactants that have been widely used as detergents, emulsifier and dispersing agents in industrial or household cleaning products including laundry detergents. These compounds are degraded in wastewater treatment plants (WWTPs) in more toxic compounds, such as nonylphenols (NPs) and octylphenols (OPs). NPs and OPs, used for industrial production of APEOs surfactants, are complex mixtures of C3-10-phenols where the main isomers are para-substituted. The interest in NPs and OPs analysis has increased during the last decades due to their capacity to disrupt the endocrine system which varies according to the structure of the branched alkyl group. They have been included in the water framework directive (WFD) as priority hazardous substances.

GCGC was applied by Eganhouse *et al.* (Eganhouse et al., 2009) to enhance the chromatographic resolution of highly similar compounds such as 4-nonylphenol isomers and facilitate identification of a number of previously unrecognized components. Among the 153-204 peaks attributed to alkylphenol, 59-664-NPs were identified (Figure 4). Seven technical NPs products were analyzed using eight synthetic 4-NP isomers, with significant differences among the products and between two samples from a single supplier. This technique was also applied to environmental samples (wastewater, contaminated groundwater and municipal wastewater). The authors demonstrated that alteration of NPs composition through degradation results in enrichment of the more persistent isomers and removal or reduction of less persistent isomers. So, the estrogenicity may be increased or decreased depending on which 4-NP isomers are removed most rapidly.

The optimization of the separation of complex NPs technical mixtures (Vallejo et al., 2011) has been performed by means of experimental designs using GC×GC–FID and GC×GC– qMS equipped with valve-based modulator. Up to 79 OPs and NPs isomers have been separated using the FID detector and 39 have been undoubtedly identified using the mass spectra obtained from the qMS detector. The 22 OP, 33 OP, 363 NP and 22 NP isomers have been synthesized and quantified in two different technical mixtures from Fluka and Aldrich.

Other organohalogen compounds; e.g. PCBs, PCNs, and PCDFs were also detected. This technique provided exhaustive analysis and powerful identification for the unknown and

GC×GC-FID and GC×GC-TOFMS methods (Wardlaw et al., 2011) were used to study the biodegradation of alkylated naphthalenes and benzothiophenes isomers in marine sediment contaminated with crude oil. Their power resolution enabled separation and quantication of multiple structural isomers to determine their rst order rate constants for aerobic biodegradation. Rate constants were used as proxies for microbial preference. A strong isomeric biodegradation preference was noted within each of these compound classes, with rate constants varying as much as a factor of 2 for structural isomers of the same compound

HPLC-GC×GC-FID and GC×GC-TOFMS were used to study the biodegradation of petroleum hydrocarbons in soil microcosms during 20 weeks (Mao et al., 2009). Aromatic hydrocarbons and n-alkanes were better biodegradable (>60% degraded) than iso-alkanes and cycloalkanes (<40%). GC×GC chromatograms showed that more polar and heavier

AlkylPhenol EthOxylates (APEOs) are surfactants that have been widely used as detergents, emulsifier and dispersing agents in industrial or household cleaning products including laundry detergents. These compounds are degraded in wastewater treatment plants (WWTPs) in more toxic compounds, such as nonylphenols (NPs) and octylphenols (OPs). NPs and OPs, used for industrial production of APEOs surfactants, are complex mixtures of C3-10-phenols where the main isomers are para-substituted. The interest in NPs and OPs analysis has increased during the last decades due to their capacity to disrupt the endocrine system which varies according to the structure of the branched alkyl group. They have been

included in the water framework directive (WFD) as priority hazardous substances.

decreased depending on which 4-NP isomers are removed most rapidly.

GCGC was applied by Eganhouse *et al.* (Eganhouse et al., 2009) to enhance the chromatographic resolution of highly similar compounds such as 4-nonylphenol isomers and facilitate identification of a number of previously unrecognized components. Among the 153-204 peaks attributed to alkylphenol, 59-664-NPs were identified (Figure 4). Seven technical NPs products were analyzed using eight synthetic 4-NP isomers, with significant differences among the products and between two samples from a single supplier. This technique was also applied to environmental samples (wastewater, contaminated groundwater and municipal wastewater). The authors demonstrated that alteration of NPs composition through degradation results in enrichment of the more persistent isomers and removal or reduction of less persistent isomers. So, the estrogenicity may be increased or

The optimization of the separation of complex NPs technical mixtures (Vallejo et al., 2011) has been performed by means of experimental designs using GC×GC–FID and GC×GC– qMS equipped with valve-based modulator. Up to 79 OPs and NPs isomers have been separated using the FID detector and 39 have been undoubtedly identified using the mass spectra obtained from the qMS detector. The 22 OP, 33 OP, 363 NP and 22 NP isomers have been synthesized and quantified in two different technical mixtures from Fluka and Aldrich.

unconfirmed Cl-/Br-PAH congeners in environmental samples.

compounds were formed as biodegradation proceeded.

**6. Alkyl phenol isomers** 

class.

The values obtained for NP isomers were in good agreement with the literature and the values calculated for OP were for the first time reported.

Fig. 4. Total ion chromatograms of technical NP (Fluka) showing (a) reconstructed 1 dimensional plot, and (b) 2-dimensional plot with alkylphenol regions indicated. Cx ) CxH2x+1, OPs ) octylphenols, DPs ) decylphenols. x-axis represents the separation in the column with the nonpolar stationary phase (DB-5 ms), whereas the y-axis represents the separation in the column with the polar stationary phase (Supelcowax 10); retention time is given in seconds. Reprinted with permission from Environmental Science & Technology (Eganhouse et al., 2009). Copyright 2011 American Chemical Society.

#### **7. Pesticides**

Recently, a study (Macedo da Silva et al., 2011) demonstrated the potential of the application of GC×GC-µECD to the analysis of seven pesticide residues (propanil, fipronil, propiconazole, trifloxystrobin, permethrin, difenoconazole and azoxystrobin) in sediments. GC×GC-ECD method improved the separation between analytes and matrix interferences, minimizing the possibility of co-elutions. Its resolution capacity allowed the use of a selective detector instead of the use of a more expensive mass spectrometry detector. Best results were obtained with the set of columns DB-5×DB-17ms. The LODs for GC×GC method were about 36% lower than those obtained for the one dimensional GC method (in the range from 0.08 to 1.07 g.L−1). Accuracy also indicated better results for GC×GC, possibly due to its higher sensitivity and lower contribution of co-eluting matrix components, which was minimized by increased peak capacity.

A GC×GC-qMS method (Purcaro et al., 2011) was developed for the multiresidue analysis of 28 pesticides contained in water. Pesticides extraction was performed by using direct Solid-Phase MicroExtraction (SPME). The rapid-scanning (20 000 amu/s) qMS system was operated using a rather wide *m/z* 50–450 mass range and a 33 Hz spectral production rate. The qMS performances were evaluated in terms of number of data points per peak, mass spectral quality, extent of peak skewing, and consistency of retention times.

A method for the determination of ultra-trace amounts of OCPs in river water was developed by Ochiai *et al.* using GC×GC–HR TOFMS (Ochiai & Sasamoto, 2011). Stir Bar Sorptive Extraction (SBSE) followed by thermal desorption (TD) was used for sample preparation. SBSE conditions including extraction time proles, phase ratio (sample volume/PolyDiMethylSiloxane (PDMS) volume), and modier addition were studied. The SBSE–TD–GC×GC–HR TOFMS method was solvent-free and highly selective and sensitive (LOD: 10–44 pg.L−1). The method was successfully applied to the determination of 16 OCPs in river water sample. Authors showed that the results for 8 OCPs were in good accordance with the values obtained by a conventional Liquid–Liquid Extraction (LLE)–GC–HRMS (Selected Ion Monitoring) SIM method. The method also allowed the identification of 20 non-target compounds, e.g. pesticides and their degradation products, PAHs, PCBs and pharmaceuticals and personal care products and metabolites in the same river water sample, by using full spectrum acquisition.

A review dedicated to determination of pyrethroid insecticides in environmental samples was recently published by Feo *et al.* (Feo et al., 2010). The authors discussed the advantages and the disadvantages of the different instrumental techniques including GC×GC.

#### **8. VOCs and other compounds**

Benzothiazoles, benzotriazoles and benzosulfonamides are high-production-volume chemicals that are used in industrial and household applications. These compounds were detected in various environmental aqueous samples and were usually quantified by LC-MS/MS. Jover *et al.* (Jover et al., 2009) developed a Solid Phase Extraction (SPE)-GC×GC– TOFMS method for the characterization of benzothiazoles, benzotriazoles and benzosulfonamides in aqueous matrices. Columns combination was optimized to ensure a good separation between target analytes and interfering compounds of the matrix. 12 target analytes were characterized in river water and in wastewater from both the influent and the effluent of a WWTP. Similar method (Matamoros et al., 2010b) was used to study the benzothiazoles and benzotriazoles removal efficiencies of four WWTPs.

The methods for the determination of polycyclic and nitro-aromatic musk compounds as well as those for the respective metabolites are reviewed by Bester (Bester, 2009).The power of GC×GC approaches was demonstrated considering the various production impurities (isomers) of the two polycyclic musks with the highest usage rates.

A methodology to characterize VOCs and semi-volatile compounds from marine salt using HeadSpace (HS)-SPME and GC×GC-TOFMS was developed by Silva *et al.* (Silva et al., 2010). 157 VOCs distributed over the chemical groups of hydrocarbons, aldehydes, esters, furans, haloalkanes, ketones, ethers, alcohols, terpenoids, C13 norisoprenoids, and lactones were detected. Furans, haloalkanes and ethers were identified for the first time in marine salt. Contour plot analysis revealed the complexity of marine salt volatile composition and confirmed the importance of a high resolution, sensitive analytical procedure (GC×GC-TOFMS) for this type of analysis. The structured 2D chromatographic profile arising from 1D volatility and 2D polarity was demonstrated, allowing more reliable identifications. Results obtained for analysis of salt from two diverse locations and harvests over three years have suggested loss of volatile compounds according to storage duration of the salt, with environmental factors surrounding the saltpans influencing the volatile composition of the salt. At present the relative contributions of these factors have not been quantified. Origins of newly identified compounds in marine salt were in accordance with previous propositions, with algae, surrounding bacterial community, and environmental pollution being obvious sources.

#### **9. Screening**

446 Advanced Gas Chromatography – Progress in Agricultural, Biomedical and Industrial Applications

Recently, a study (Macedo da Silva et al., 2011) demonstrated the potential of the application of GC×GC-µECD to the analysis of seven pesticide residues (propanil, fipronil, propiconazole, trifloxystrobin, permethrin, difenoconazole and azoxystrobin) in sediments. GC×GC-ECD method improved the separation between analytes and matrix interferences, minimizing the possibility of co-elutions. Its resolution capacity allowed the use of a selective detector instead of the use of a more expensive mass spectrometry detector. Best results were obtained with the set of columns DB-5×DB-17ms. The LODs for GC×GC method were about 36% lower than those obtained for the one dimensional GC method (in the range from 0.08 to 1.07 g.L−1). Accuracy also indicated better results for GC×GC, possibly due to its higher sensitivity and lower contribution of co-eluting matrix

A GC×GC-qMS method (Purcaro et al., 2011) was developed for the multiresidue analysis of 28 pesticides contained in water. Pesticides extraction was performed by using direct Solid-Phase MicroExtraction (SPME). The rapid-scanning (20 000 amu/s) qMS system was operated using a rather wide *m/z* 50–450 mass range and a 33 Hz spectral production rate. The qMS performances were evaluated in terms of number of data points per peak, mass

A method for the determination of ultra-trace amounts of OCPs in river water was developed by Ochiai *et al.* using GC×GC–HR TOFMS (Ochiai & Sasamoto, 2011). Stir Bar Sorptive Extraction (SBSE) followed by thermal desorption (TD) was used for sample preparation. SBSE conditions including extraction time proles, phase ratio (sample volume/PolyDiMethylSiloxane (PDMS) volume), and modier addition were studied. The SBSE–TD–GC×GC–HR TOFMS method was solvent-free and highly selective and sensitive (LOD: 10–44 pg.L−1). The method was successfully applied to the determination of 16 OCPs in river water sample. Authors showed that the results for 8 OCPs were in good accordance with the values obtained by a conventional Liquid–Liquid Extraction (LLE)–GC–HRMS (Selected Ion Monitoring) SIM method. The method also allowed the identification of 20 non-target compounds, e.g. pesticides and their degradation products, PAHs, PCBs and pharmaceuticals and personal care products and metabolites in the same river water

A review dedicated to determination of pyrethroid insecticides in environmental samples was recently published by Feo *et al.* (Feo et al., 2010). The authors discussed the advantages

Benzothiazoles, benzotriazoles and benzosulfonamides are high-production-volume chemicals that are used in industrial and household applications. These compounds were detected in various environmental aqueous samples and were usually quantified by LC-MS/MS. Jover *et al.* (Jover et al., 2009) developed a Solid Phase Extraction (SPE)-GC×GC– TOFMS method for the characterization of benzothiazoles, benzotriazoles and benzosulfonamides in aqueous matrices. Columns combination was optimized to ensure a good separation between target analytes and interfering compounds of the matrix. 12 target analytes were characterized in river water and in wastewater from both the influent and the

and the disadvantages of the different instrumental techniques including GC×GC.

components, which was minimized by increased peak capacity.

sample, by using full spectrum acquisition.

**8. VOCs and other compounds** 

spectral quality, extent of peak skewing, and consistency of retention times.

**7. Pesticides** 

In environmental monitoring, pollutants lists are periodically updated by regulatory agencies. Both the European Union (EU) and US EPA issued dangerous and hazardous contaminant lists, the so-called priority substances, whose concentration and occurrence in waters were strictly regulated (Directive 2000/60/EC; Decision No.2455/2001/EC and Clean Water Act) (Matamoros et al., 2010a). As the number of environmental regulated pollutants increases, it is necessary to develop global detection methods which can be used to screen a large number of substances simultaneously. This kind of method could reduce cost and time necessary for their detection and quantification. Moreover, there is a diverse group of unregulated pollutants called "emerging" contaminants, including pharmaceuticals and personal care products which were interesting to identify and monitor due to their high mass discharge into the environment. Some emerging contaminants have been recently included in candidate contaminant lists either from US EPA and the EU commission.

Semard *et al.* (Semard et al., 2008a; Semard et al., 2008b) reported a GC×GC-TOFMS method to search 58 target compounds and screen hazardous contaminants including PBDEs, PAHs and pesticides in urban wastewater. A variety of drugs (antidepressants, antibiotics, anticoagulants, *etc*…), personal care products (sunscreens, antiseptics, cosmetics etc.) and carcinogenic compounds, pesticides and compounds toxic for reproduction were identified in the raw wastewater. Most of these compounds were removed or decreased by the WWTP. Four priority substances (1,2,3-trichlorobenzene, 4-tert-butylphenol, benzothiazole and naphthalene) were present with concentrations in the range of 0.05 to 1.5 mg.L-1 in the raw wastewater and 0.01 to 0.1 mg.L-1 in the treated wastewater.

Household dusts were investigated using GC×GC-TOFMS as efficient screening method (Hilton et al., 2010). PAHs, phthalates, and compounds containing chlorine, bromine, or nitro groups were located on the chromatogram. Household dust (SRM-2585) was extracted with hexane using accelerated solvent extraction (ASE). Large molecules, such as triglycerides and fatty acids were removed with gel permeation chromatography. The resulting peak table was automatically filtered to identify compound classes such as phthalates, PAHs (Figure 5) and their heterocyclic analogs, PCBs, PBDEs, chloroalkyl phosphates, pesticides, and pesticides degradation products… By comparison with concentrations determined by National Institute of Standards and Technology, the technique was able to identify analytes at concentrations as low as 10–20 ng.g-1 dust for compounds quantified by NIST (National Institute of Standards and Technology).

Fig. 5. Location of peaks matching the PAH spectral pattern with those identified by library searching. PAHs can be expected to fall into a band, shown starting at about 2 seconds in the second dimension and, as the chromatogram proceeds, falling later in the second dimension. Reprinted from Journal of Chromatography, A, (Hilton et al., 2010). Copyright (2010), with permission from Elsevier.

A SPE-GC×GC-TOFMS screening method for 97 priority and emerging contaminants in river was developed by Matamoros *et al.* (Matamoros et al., 2010a). The SPE was followed by in GC-port methylation using trimethylsulfonium hydroxide. The target analytes included 13 pharmaceuticals, 18 plasticizers, 8 personal care products, 9 acid herbicides, 8 triazines, 10 organophosphorous compounds, 5 phenylureas, 12 organochlorine biocides, 9

and naphthalene) were present with concentrations in the range of 0.05 to 1.5 mg.L-1 in the

Household dusts were investigated using GC×GC-TOFMS as efficient screening method (Hilton et al., 2010). PAHs, phthalates, and compounds containing chlorine, bromine, or nitro groups were located on the chromatogram. Household dust (SRM-2585) was extracted with hexane using accelerated solvent extraction (ASE). Large molecules, such as triglycerides and fatty acids were removed with gel permeation chromatography. The resulting peak table was automatically filtered to identify compound classes such as phthalates, PAHs (Figure 5) and their heterocyclic analogs, PCBs, PBDEs, chloroalkyl phosphates, pesticides, and pesticides degradation products… By comparison with concentrations determined by National Institute of Standards and Technology, the technique was able to identify analytes at concentrations as low as 10–20 ng.g-1 dust for

compounds quantified by NIST (National Institute of Standards and Technology).

Fig. 5. Location of peaks matching the PAH spectral pattern with those identified by library searching. PAHs can be expected to fall into a band, shown starting at about 2 seconds in the second dimension and, as the chromatogram proceeds, falling later in the second dimension. Reprinted from Journal of Chromatography, A, (Hilton et al., 2010). Copyright (2010), with

A SPE-GC×GC-TOFMS screening method for 97 priority and emerging contaminants in river was developed by Matamoros *et al.* (Matamoros et al., 2010a). The SPE was followed by in GC-port methylation using trimethylsulfonium hydroxide. The target analytes included 13 pharmaceuticals, 18 plasticizers, 8 personal care products, 9 acid herbicides, 8 triazines, 10 organophosphorous compounds, 5 phenylureas, 12 organochlorine biocides, 9

permission from Elsevier.

raw wastewater and 0.01 to 0.1 mg.L-1 in the treated wastewater.

PAHs, 5 benzothiazoles and benzotriazoles. Best resolution between matrix constituents and target analytes was observed with TRB-5MS×TRB-50HT (apolar – polar) columns combination. Moreover, using polar-nonpolar columns combination, a strong correlation between the second dimension retention time and log Kow for the target compounds was observed and was proposed as an additional identification criterion. The method was successfully applied to the analysis of four river water samples with LOD ranging from 0.5 to 100 ng.L-1 (Figure 6). Plasticizers (e.g., phthalates and bisphenol A), pharmaceuticals (e.g., naproxen, ibuprofen), and personal care products (e.g., tonalide and methyl dihydrojasmonate) were the most abundant in concentration and detection frequency.

Fig. 6. 3D contour plots of four rivers sampled in this study in which the total ion chromatogram is shown: Ebro (A), Llobregat (B), Ter (C), and Beso`s (D). Reprinted with permission from Analytical Chemistry, *(*Matamoros et al., 2010a). Copyright 2011 American Chemical Society.

Gomez *et al.* (Gomez et al., 2011) developed a GC×GC–TOFMS method for the automatic searching and evaluation of nonpolar or semipolar contaminants (13 personal care products, 15 PAHs and 27 pesticides) in wastewater and river water. SBSE was selected for sample preparation step. Good results have been obtained in terms of separation efficiency and detection limits at or below 1 ng.L-1 for most of the compounds in the MS full scan mode, using only 100 mL of river water sample and 25 mL of wastewater effluent sample. The authors mentioned the possibility to screen for non-target compounds or unknowns. New contaminants have been identified in the wastewater effluents and river water samples, such as cholesterol and its degradation products, pharmaceuticals, illegal drugs, industrial products as well as other pesticides and personal care products. Moreover, GC×GC features were proposed to compare the fingerprinting of different water samples giving valuable information about the contamination status of rivers and wastewaters (Figure 7).

Fig. 7. Contamination status. Automatic searching of temporal and spatial contamination variation of organic contaminants. Reprinted with permission from Analytical Chemistry, (Gómez et al., 2011). Copyright 2011 American Chemical Society.

The most frequently detected contaminants and the contaminants detected at higher concentrations were the personal care products (musk fragrances galaxolide and tonalide). The pesticides and PAHs were detected at much lower concentration.

Halogenated compounds were successfully detected (Hashimoto et al., 2011) from several kinds of environmental samples by using a GC×GC chromatograph coupled with a tandem mass spectrometer (GC×GC–MS/MS). The global and selective detection of halogenated compounds was achieved by neutral loss scans of chlorine, bromine and/or fluorine using an MS/MS which was especially effective for compounds with more than two halogen substituents (Figure 8).

Screening and identification of pollutants was performed with GCGC–HRTOFMS under the same conditions as those used for GC×GC–MS/MS. A lot of dioxins and PCBs congeners and many other compounds were identified in fly ash extract without any cleanup process and in sediment samples. In the future, the authors expect to achieve the complete global detection of any compound in one measurement of a crude sample simply with a GC×GC-HRTOFMS if it becomes possible to extract the desired information from the GC×GC-HR TOFMS data.

products as well as other pesticides and personal care products. Moreover, GC×GC features were proposed to compare the fingerprinting of different water samples giving valuable

Fig. 7. Contamination status. Automatic searching of temporal and spatial contamination variation of organic contaminants. Reprinted with permission from Analytical Chemistry,

The most frequently detected contaminants and the contaminants detected at higher concentrations were the personal care products (musk fragrances galaxolide and tonalide).

Halogenated compounds were successfully detected (Hashimoto et al., 2011) from several kinds of environmental samples by using a GC×GC chromatograph coupled with a tandem mass spectrometer (GC×GC–MS/MS). The global and selective detection of halogenated compounds was achieved by neutral loss scans of chlorine, bromine and/or fluorine using an MS/MS which was especially effective for compounds with more than two halogen

Screening and identification of pollutants was performed with GCGC–HRTOFMS under the same conditions as those used for GC×GC–MS/MS. A lot of dioxins and PCBs congeners and many other compounds were identified in fly ash extract without any cleanup process and in sediment samples. In the future, the authors expect to achieve the complete global detection of any compound in one measurement of a crude sample simply with a GC×GC-HRTOFMS if it becomes possible to extract the desired information from the GC×GC-HR

(Gómez et al., 2011). Copyright 2011 American Chemical Society.

substituents (Figure 8).

TOFMS data.

The pesticides and PAHs were detected at much lower concentration.

information about the contamination status of rivers and wastewaters (Figure 7).

Fig. 8. Two-dimensional TICs of fly ash extract (NIES CRM17) measured with a 35Cl-NLS (upper) and a conventional scan (lower) obtained with the GCGC–MS/MS. The red translucent shape in the upper chromatogram shows the area where organohalogens are expected to appear. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of the article.). Reprinted from Journal of Chromatography, A, (Hashimoto et al., 2011). Copyright (2011), with permission from Elsevier.

#### **10. GCGC instrumentation and optimization of operating conditions**

Publications and reviews were dedicated to specific aspect of GC×GC. Major innovations in GC×GC modulator development were recently reviewed (Edwards et al., 2011). Cryogenic modulators remain very popular because of their ability to produce very small peak widths at half height and minimize breakthrough. Their commercial availability from several suppliers, has also contributed to their popularity. The use of valve-based modulators is increasing because of their less operating cost and easier maintenance than cryogenic modulator. Nevertheless, their coupling to MS remains problematic due to the large carrier gas flows in the second column and these modulators are not able to produce peaks of the same quality. Thermal modulation with the use of thermoelectric cooling could be a promising alternative if temperatures can be lowered enough to trap VOCs. Tranchida *et al.* (Tranchida et al., 2011a) have also published a review focused on the history (1991–2010) and present trends and future prospects for GC×GC modulation. Authors provided detailed descriptions and discussed the advantages and the disadvantages of the most significant thermal and pneumatic modulators. The authors have concluded that if at the moment, dual stage liquid N2 systems can still be considered as the most effective modulators, in the next 10 years, the popularity of pneumatic modulators will gradually increase. The authors have included the description of their simple flow modulator, a seven port metallic disc published in 2011 (Tranchida et al., 2011b). A rotary and diaphragm 6-port 2-position valves have been also evaluated as modulators for GC×GC (Lidster et al., 2011).

Fig. 9. Chromatogram illustrating the retention space used (white) and the space used calculated with Delaunay's triangulation algorithms (yellow) obtained on HP5-Mega225. Reprinted from Journal of Chromatography, A, (Semard et al., 2010). Copyright (2010), with permission from Elsevier.

In 2011, Panic *et al.* (Panic et al., 2011) developed a new consumable-free thermal modulator for GC×GC. The modulator was constructed from a trapping capillary, installed outside the GC oven, and coated inside with PDMS stationary phase. Dual-stage modulation was accomplished by resistively heating alternate segments of the trap with a custom-designed

suppliers, has also contributed to their popularity. The use of valve-based modulators is increasing because of their less operating cost and easier maintenance than cryogenic modulator. Nevertheless, their coupling to MS remains problematic due to the large carrier gas flows in the second column and these modulators are not able to produce peaks of the same quality. Thermal modulation with the use of thermoelectric cooling could be a promising alternative if temperatures can be lowered enough to trap VOCs. Tranchida *et al.* (Tranchida et al., 2011a) have also published a review focused on the history (1991–2010) and present trends and future prospects for GC×GC modulation. Authors provided detailed descriptions and discussed the advantages and the disadvantages of the most significant thermal and pneumatic modulators. The authors have concluded that if at the moment, dual stage liquid N2 systems can still be considered as the most effective modulators, in the next 10 years, the popularity of pneumatic modulators will gradually increase. The authors have included the description of their simple flow modulator, a seven port metallic disc published in 2011 (Tranchida et al., 2011b). A rotary and diaphragm 6-port 2-position valves

have been also evaluated as modulators for GC×GC (Lidster et al., 2011).

Fig. 9. Chromatogram illustrating the retention space used (white) and the space used calculated with Delaunay's triangulation algorithms (yellow) obtained on HP5-Mega225. Reprinted from Journal of Chromatography, A, (Semard et al., 2010). Copyright (2010), with

In 2011, Panic *et al.* (Panic et al., 2011) developed a new consumable-free thermal modulator for GC×GC. The modulator was constructed from a trapping capillary, installed outside the GC oven, and coated inside with PDMS stationary phase. Dual-stage modulation was accomplished by resistively heating alternate segments of the trap with a custom-designed

permission from Elsevier.

capacitive discharge power supply. The two unique inventions presented, flattening of the trap and selective removal of the stationary phase, have successfully eliminated the traditional drawbacks of resistively heated modulators.

The identification of compounds by using GC is based on peak retention times and mass spectra which generates uncertainty for the analyst for complex samples containing isomeric species. Retention index procedures were introduced to minimize misidentification of compounds in conventional chromatography. Various approaches to use of the retention index in GC×GC were reviewed and discussed (von Muhlen & Marriott**,** 2011).

A new method for the calculation of the percentage of separation space used was developed by Semard *et al.* (Semard et al., 2010) using Delaunay's triangulation algorithms (convex hull).

This approach was compared with an existing method and showed better precision and accuracy. It was successfully applied to the selection of the most convenient column set (HP5-Mega225) for the analysis of 49 target compounds including pesticides, HAPs, PCBs, PBDE *etc*… in wastewater. The diameter and length of the second column were optimized to improve the percentage of separation space used up to 40%.

Recently, Omais *et al.* (Omais et al., 2011) have shown that the general notion of orthogonality combining retention mechanisms independence and two dimensional space occupation must be decoupled. They have demonstrated that a non-orthogonal system can offer a good separation and a great space occupation. Moreover, orthogonality is intimately linked to the sample properties and cannot be considered as a sine qua none condition to achieve a good separation.

Table 1 summarizes the acronyms used in this review.



Table 1. List of acronyms

#### **11. Conclusion**

This work reviews about 40 publications over the period 2009-2011 dealing with GCGC and more especially on environmental applications. This technique coupled to mass spectrometry is an excellent choice for analyzing complex environmental samples and is suitable for multiresidue and non target analyses. As the number of environmental regulated pollutants increases, GCGC appears ideal for the development of global detection method which can be used to screen a large number of compounds simultaneously. This kind of method could reduce cost and time necessary for their detection and quantification. GCGC provides the analytical chemist with a new tool for a better separations of organohalogen congeners and, potentially, for more accurate human and environmental exposure data for risk assessments. Moreover, the authors highlighted the improved resolution and sensitivity offered by GCGC over conventional one dimensional GC. The high selectivity of GCGC-TOFMS has also facilitated the development of a wide range of analytical methods with minimal sample preparation and allowed the screening of emerging contaminants. Table 2 summarizes the main technical characteristics of methods applied to the various classes of pollutants reviewed in this chapter.

#### Recent Applications of Comprehensive Two-Dimensional Gas Chromatography to Environmental Matrices 455

454 Advanced Gas Chromatography – Progress in Agricultural, Biomedical and Industrial Applications

**OCPs** OrganoChlorinated Pesticides

**PAHs** Polycyclic Aromatic Hydrocarbons

**PBDEs** PolyBrominated DiphenylEthers **PCBs** PolyChlorinated Biphenyls

**SBSE** Stir Bar Sorptive Extraction **SIM** Selected Ion Monitoring **SPE** Solid Phase Extraction **SPME** Solid Phase MicroExtraction **2,3,7,8-TCDD** 2,3,7,8-tetrachlorodibenzo-p-dioxin

**TEQ/kg** Toxic Equivalent Quantity/kg

**VOCs** Volatile Organic Compounds **WFD** Water Framework Directive **WHO** World Health Organization **WWTPs** WasteWater Treatment Plants

**TD** Thermal Desorption

**TOF** Time-Of-Flight

Table 1. List of acronyms

**11. Conclusion** 

in this chapter.

**PCDDs** PolyChlorinated Dibenzo-p-Dioxins **PCDFs** PolyChlorinated DibenzoFurans **PCNs** PolyChlorinated Naphthalenes **PCTs** PolyChlorinated Terphenyls **PDMS** PolyDiMethylSiloxane **POPs** Persistent Organic Pollutants **qMS** Quadrupole Mass Spectrometer

**Br-PAHs** Brominated Polycyclic aromatic hydrocarbon **Cl-PAHs** Chlorinated polycyclic aromatic hydrocarbon

**QSRR** Quantitative Structure–Retention Relationship

**US EPA** United States Environmental Protection Agency

This work reviews about 40 publications over the period 2009-2011 dealing with GCGC and more especially on environmental applications. This technique coupled to mass spectrometry is an excellent choice for analyzing complex environmental samples and is suitable for multiresidue and non target analyses. As the number of environmental regulated pollutants increases, GCGC appears ideal for the development of global detection method which can be used to screen a large number of compounds simultaneously. This kind of method could reduce cost and time necessary for their detection and quantification. GCGC provides the analytical chemist with a new tool for a better separations of organohalogen congeners and, potentially, for more accurate human and environmental exposure data for risk assessments. Moreover, the authors highlighted the improved resolution and sensitivity offered by GCGC over conventional one dimensional GC. The high selectivity of GCGC-TOFMS has also facilitated the development of a wide range of analytical methods with minimal sample preparation and allowed the screening of emerging contaminants. Table 2 summarizes the main technical characteristics of methods applied to the various classes of pollutants reviewed

**OPs** OctylPhenols


Table 2. characteristics of methods applied to the various classes of pollutants based on compounds, sample preparation techniques, GC×GC method andset of columns used.

#### **12. References**


Adahchour, M.; Beens, J.; Vreuls, R. J. J. & Brinkman, U. A. T. (2006). Recent developments

*Chemistry*, Vol.25, No.7, (July-August 2006), pp. 726-741, ISSN 0165-9936 Adahchour, M.; Beens, J. & Brinkman, U. A .T. (2008). Recent developments in the

Arsene, C.; Vione, D.; Grinberg, N. & Olariu, R.I. (2011). GCGC-MS hyphenated techniques

Ballesteros-Gomez, A. & Rubio, S. (2011). Recent Advances in Environmental Analysis. *Analytical Chemistry*, Vol.83, No.12, (April 2011), pp. 4579-4613, ISSN 0003-2700 Bester, K. (2009). Analysis of musk fragrances in environmental samples. *Journal of Chromatography, A*, Vol.1216, No.3, (January 2009), pp. 470-480, ISSN 0021-9673 Bordajandi, L. R.; Ramos, J. J.; Sanz, J.; Gonzalez, M. J. & Ramos, L. (2008). Comprehensive

Cortes, H. J.; Winniford, B.; Luong, J. & Pursch, M. Comprehensive two dimensional gas

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### *Edited by Mustafa Ali Mohd*

Progress in agricultural, biomedical and industrial applications' is a compilation of recent advances and developments in gas chromatography and its applications. The chapters cover various aspects of applications ranging from basic biological, biomedical applications to industrial applications. Book chapters analyze new developments in chromatographic columns, microextraction techniques, derivatisation techniques and pyrolysis techniques. The book also includes several aspects of basic chromatography techniques and is suitable for both young and advanced chromatographers. It includes some new developments in chromatography such as multidimensional chromatography, inverse chromatography and some discussions on two-dimensional chromatography. The topics covered include analysis of volatiles, toxicants, indoor air, petroleum hydrocarbons, organometallic compounds and natural products. The chapters were written by experts from various fields and clearly assisted by simple diagrams and tables. This book is highly recommended for chemists as well as non-chemists working in gas chromatography.

Photo by StationaryTraveller / iStock

Advanced Gas Chromatography -

Progress in Agricultural, Biomedical and Industrial Applications

Advanced Gas

Chromatography

Progress in Agricultural, Biomedical and

Industrial Applications

*Edited by Mustafa Ali Mohd*