Evaluation of Mathematical Algorithm for Solving of Fourier Transform

Ind. Eng. Chem. Res. 2008, 47, 8101–8106

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Evaluation of Mathematical Algorithm for Solving of Fourier Transform Infrared Spectroscopic and Mass Spectra Raimo A. Ketola,*,† Virpi Tarkiainen,‡ Jari Kiuru,‡ Pekka Savolahti,‡ Tapio Kotiaho,§ Jouni Juuja¨rvi,| Marianna Ridderstad,|,⊥ and Jukka Heikkonen| UniVersity of Helsinki, Centre for Drug Research (CDR) and DiVision of Pharmaceutical Chemistry, P.O. Box 56, FI-00014 UniVersity of Helsinki; VTT Technical Research Centre of Finland, P.O.Box 1000, FI-02044 VTT; UniVersity of Helsinki, Laboratory of Analytical Chemistry and DiVision of Pharmaceutical Chemistry, P.O. Box 55, FI-00014 UniVersity of Helsinki; Helsinki UniVersity of Technology, Laboratory of Computational Engineering, P.O.Box 9400, FI-02015 Helsinki UniVersity of Technology; and Helsinki UniVersity ObserVatory, P.O. Box 14, FI-00014 UniVersity of Helsinki, Finland

The aim of this study was to evaluate the benefits of the simultaneous use of two different analytical methods, namely Fourier transform infrared spectroscopy (FTIR) and mass spectrometry (MS), for online analysis of environmental and process samples. A mathematical method (NALMS) that identifies and quantifies all single components from a single multicomponent spectrum was previously developed for MS, and in this study, the same method, named as SPECTACS, was adopted for solving also an FTIR spectrum and a combined FTIRMS spectrum. The performance of SPECTACS was evaluated by analyzing various gaseous samples, as case studies, containing volatile organic compounds, and the performance was compared with other methods, which are used to identify and quantitate organic compounds from multicomponent spectra. The results obtained show that SPECTACS with optimized noise reduction and solving a combined FTIR-MS spectrum can increase the reliability of identifying components in a single spectrum and also the accuracy in quantitative measurements when compared to the analysis with one analytical technique alone. The reasons for this improvement is evaluated and discussed in detail. Introduction Contamination of the environment is still increasing, even though much work has been done to decrease environmental contamination. Numerous contaminated sites exist, which are caused by large cities, industry, traffic, energy production, accidents, leakages, and so forth. Because of these facts, new efficient online analytical methods are needed for rapid screening of contaminated sites. Contamination is often severe and complex (i.e., there are tens or hundreds of compounds in one sample); thus, simple sensors are not specific or selective enough. In industry, especially in process industry, a comprehensive management of production and quality control is essential to speed up production rate, to improve the quality of products, to minimize losses, and to avoid contamination of the environment. Specific online analytical methods are also needed for these applications. Mass spectrometry, especially membrane inlet mass spectrometry (MIMS), and Fourier transform infrared spectroscopy (FTIR) are both commonly used techniques for online, realtime measurement of volatile organic compounds (VOCs) from gaseous samples.1-3 The principle of MIMS is a selective pervaporation of molecules through a membrane that is mounted between the sample and the ion source of a mass spectrometer in vacuum. Molecules from a gaseous or aqueous sample are * To whom correspondence should be addressed. E-mail: [email protected]. Fax: +358 9 191 59556. † University of Helsinki, Centre for Drug Research (CDR) and Division of Pharmaceutical Chemistry. ‡ VTT Technical Research Centre of Finland. § University of Helsinki, Laboratory of Analytical Chemistry and Division of Pharmaceutical Chemistry. | Helsinki University of Technology, Laboratory of Computational Engineering. ⊥ Helsinki University Observatory.

dissolved into the membrane, diffuse through it due to a difference in partial pressures in the sample and the vacuum of the mass spectrometer, and finally evaporate into the ion source. The permeability of nonpolar volatile organic compounds through a silicone membrane is higher than that of atmospheric gases or water, and that is why a 10-100-fold concentration of VOCs compared to atmospheric gases is obtained. The MIMS method is sensitive as detection limits of below the microgram per cubic meter level can be reached. In FTIR spectroscopy, each compound gives a specific IR spectrum due to absorption of certain wavelengths in the range 500-4000 cm-1; thus, IR spectra can be used for the identification of compounds in the samples. But, quantitation of structurally similar compounds such as alkanes is difficult or even impossible from a multicomponent spectrum as it gets more difficult to find specific IR absorption bands for each individual compound. Both MIMS and FTIR methods are widely used for various industrial and environmental applications.2,4-11 Different approaches have been taken in order to differentiate between various samples or structurally similar compounds from IR data. For example, Elliott et al.12 used various chemometric approaches, such as principal component analysis (PCA), discriminant function analysis (DFA), and multiple linear regression (MLR) for differentiation of soil classes by their FTIR spectra. Similarly, Durand et al.13 used partial least-squares (PLS) regression and mutual information variable selection procedures in quantitative near-infrared analysis of cotton-viscose textiles. IR data with several functional algorithms have also been used for identification of similar compounds, such as benzodiazepines and β-lactam antibiotics.14 IR and MS spectral detection have also been used together in combination with gas chromatography for identification of unknown components in complex mixtures.15 The main advantages of these methods are the capability for online and in situ monitoring volatile organic compounds

10.1021/ie800851e CCC: $40.75  2008 American Chemical Society Published on Web 10/03/2008

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Figure 1. The concentrations of six components in two gaseous samples measured with MS and obtained with three calculations methods. The reference value is the actual concentration of each gas in the sample mixture obtained with the Environics S2000 gas mixer. The main differences between these samples were the relative concentrations of carbon monoxide and argon. For clarity reasons, the relative concentrations of carbon dioxide and water (a), and carbon dioxide, carbon monoxide, and water (b) are multiplied by a factor of 10.

and gases from various samples. However, sometimes when the samples are complex, identification of unknown compounds can be insufficient when only one analytical technique is used. One disadvantage of the methods is that all compounds are measured at the same time and the separation of isomers or compounds with similar spectra is difficult from a multicomponent spectrum. For identification and quantitation of unknown compounds from a single mass spectrum measured from gaseous samples,

a mathematical method, nonlinear asymmetric error functionbased least mean square (NALMS), has previously been developed.16,17 The algorithm fits the spectra of compounds from a spectral library to the measured multicomponent spectrum by minimizing the residual spectrum. In this way, it is possible to identify at least the major components of the sample. Mixture analysis of multicomponent mass spectra is typically based on a linear multicomponent mass spectrum model solved via a leastsquares (LS) technique. In LS solution, the compounds of the measured spectra to be solved are explicitly stated and hence assumed to be known before estimating their concentrations. In many cases, however, the measured spectrum may contain unknown compounds that are not explicitly known, and hence, the commonly used LS solution is in difficulty. Our recently proposed NALMS method, where also SPECTACS is based, overcomes this limitation of LS solution by modeling the effect of the unknown compound(s) to the error of the linear model. The experimental results have shown that the NALMS approach can separate more robustly the complex multicomponent mass spectra into their individual constituents compared to commonly used LS method.17 NALMS methods can also be applied for FTIR spectroscopy in order to identify and quantitate compounds in the sample from a single IR spectrum. But, it can also be applied for solving a combined spectrum that contains both FTIR and MS spectrum of the sample, measured either simultaneously or consequently. The resulting combined spectrum analysis approach was programmed by Matlab and named as SPECTACS program. In addition to NALMS methods, SPECTACS program is also able to produce LS solution. In this study, a few exemplary cases were selected where the use of SPECTACS was evaluated, using FTIR or MS alone or using a combined FTIR-MS spectrum. Experimental Section Reagents. The commercial reagents used were carbon dioxide (CO2, 99.995%), carbon monoxide (CO, 99.999%), nitrogen (N2, 99.999%), oxygen (O2, 99.999%), argon (Ar, 99.998%), and helium (He, 99.996%) from Oy AGA Ab (Riihima¨ki, Finland). Ammonia (NH3), nitrogen oxide (NO), and sulfur dioxide (SO2) were obtained from Oy Aga Ab (Finland). Methane and ethane were obtained from Messer (Sweden). A certified gas mixture containing CO, SO2, CO2, and NO was purchased from Aga, Sweden. Benzene (99.5%), cumyl alcohol (97%), toluene (99.5%), and o-xylene (99.8%) were from Merck KGA (Darmstadt, Germany); acetophenone (99%), m-xylene (99.5%),

Figure 2. Online FTIR measurement of concentrations of three gases calculated by SPECTACS and CALCMET. The actual concentrations produced with a gas mixer were 300 ppm for methane, 200 ppm for NH3, and 100 ppm for ethane. One spectrum was measured in 20 s.

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Figure 3. Online FTIR measurement of concentrations of four gases calculated by SPECTACS and CALCMET. The actual concentrations in the certified gas mixture were 50 ppm, 39 ppm, 8.1%, and 78 ppm for CO, SO2, CO2, and NO, respectively. One spectrum was measured in either 20 or 60 s.

p-xylene (99.5%), ethylbenzene (99.5%), 1,3,5-trimethylbenzene (99.8%), methyl-2-methyl-2-butyl ether (TAME) (97%), methyltert-butyl ether (MTBE) (99.5%), hexane (99.5%), and heptane (99.5%) were from Fluka Chemie AG (Buchs, Switzerland). Water was purified with a Milli-Q purification system (Millipore, Molsheim, France). Mass Spectrometric Conditions. The mass spectrometer used was a Balzers Omnistar quadrupole mass spectrometer with a mass range m/z 1-300 and equipped with a modified open cross-beam electron impact (70 eV) ion source (Balzers Aktiengesellschaft, Balzers, Liechtenstein). Either a custom-made sheet membrane inlet (MIMS-inlet)11 or a direct steel capillary inlet was used in the experiments. The MS-inlet temperature was set to 120 °C. A polydimethylsiloxane membrane (SSPM100, Specialty Silicone Products Inc., Ballston Spa, NY) with thickness of 25 µm and contact area of 8 mm2 was used in the MIMS inlet. Mass spectrometric data were collected either by scanning full mass spectra (typical mass range m/z 0-50 for atmospheric gases and m/z 46-200 for volatile organic compounds) or by using MCD-mode (multiple concentration detection) of the Balzers QUADSTAR 422 measurement-program. Quantitation of measured compounds was made either using the MCD-mode of commercial Balzers QUADSTAR 422 Measurement-program or using SPECTACS program based on NALMS method.17 FTIR Conditions. The Fourier transform infrared spectroscopic instrument used was a GASMET with CALCMETmeasurement program (GASMET Technologies Ltd., Helsinki, Finland) with the volume of the sample cell of 200 mL, the length of the optical path of 2.0 m, and the temperature of the sample cell of 100 °C. The IR spectrometer used in steel plant measurements was T14 (Hartmann & Brown, Germany). Calibration. Gas specific calibration of MS and IR instruments was made using Environics series S2000 computerized multicomponent gas mixer (Environics, Inc., Tolland, CT). Gaseous standards of volatile organic compounds were prepared by diluting methanolic solutions of organic compounds with a Harvard Apparatus 11 syringe pump (Harvard Apparatus, Kent, England) into the mixed gas stream. Water was added to the mixed gas stream with GasmetCalibrator (Gasmet Technologies Oy, Helsinki, Finland). HPLC Analysis. Samples from a cellular plastics plant were collected (adsorbed) onto XAD-2 resin tubes (Amberlite, 20-60 mesh, 5 g per tube, Supelco, Bellefonte, PA). Analytes were extracted from the resin with methanol and subsequently analyzed with a liquid chromatograph (HP1100, Agilent Tech-

nologies, Bo¨blingen, Germany) equipped with an DAD detector and a C18 column (Symmetry Shield, 4.6 mm × 150 mm, 5 µm particles, Waters, Milford, MA) using an isocratic elution with water/acetonitrile (50:50 v/v) with 0.1% formic acid. Results and Discussion The performance of SPECTACS program was evaluated, using various synthetic and authentic gaseous samples analyzed with either FTIR or MS, or with both techniques at the same time. If possible, the results obtained were compared with true values or results acquired with other measurement techniques or calculation programs. Use of SPECTACS with Either MS or IR. Analysis of Gases by MS. The performances of LS and NALMS modes of SPECTACS calculation program and of the MCD mode of Balzers Quadstar 422 Measurement program were tested by calculating concentrations for different gas mixtures containing CO, CO2, N2, O2, Ar, and water using the measured mass spectra. The results obtained by these three calculation methods were compared with the actual concentrations given by the Environics S2000 gas mixer. The concentrations obtained with different calculation methods for two samples with varying relative concentrations for each gas are presented in Figure 1. As can be seen from this figure, the results obtained with LS, NALMS, and MCD methods were very similar to each other. The LS method was performing best, but the measurement of CO at low concentration level is difficult with all methods due to overlapping peaks with nitrogen. All components of the analyzed gas mixtures were known, and therefore, it was not surprising that LS method gave the best results. When one or more components were missing from the calculations then the NALMS method worked a little better than the other methods (data not shown). The situation was the same when the component library used was large; that is, the methods calculated concentrations for tens of compounds even though only six of them were actually present in the samples. Linearity of the measured signal was studied for CO2, N2, O2, Ar, and He and also for various combinations of these gases. It was observed that the signals of these atmospheric gases were linear only in concentrations below 30% (v/v). It was also observed that all components present in the gas mixture, not only the monitored ones, had an effect on the MS signal of monitored components. The most nonlinear signal was obtained for the mixture of CO2 and He; it was nonlinear in the whole 0-100% concentration range (v/v), though the deviations of

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Figure 4. (a) Concentrations of CO and CO2 during one blasting in a steel plant measured by IR and MS (MCD mode). (b) Normalized MS results with MCD for five gases from the same blasting as in Figure 4a. (c) Online measurement of CO and CO2 during one blasting measured with IR and with MS using SPECTACS with NALMS and baseline correction.

the calibration curves from a linear slope were mostly below 10% (absolute values) in the whole concentration range. On the basis of these results, it is obvious that thorough calibration is of outmost importance in order to get accurate results for atmospheric gas measurements. If only high gas concentrations are measured, the samples should be diluted before the analysis in order to measure the concentrations in the linear range and to maximize accuracy. Analysis of Gases with FTIR. The performance of SPECTACS in the analysis of gas mixtures with FTIR was tested using two separate mixtures. The mixture 1, containing ammonia (NH3), methane, and ethane, was made from commercial gaseous standards by the Environics S2000 gas mixer. The mixture 2 was a certified gas standard, containing CO, SO2, CO2, and NO. The signal of each gas (reference standard) was

separately calibrated using a pure compound in nitrogen at concentration levels of 100-300 ppm. Figure 2 shows the online measurement of concentrations of NH3, methane, and ethane in the mixture 1, obtained by CALCMET and SPECTACS, while the reference concentrations were 200, 300, and 100 ppm, respectively. The measurement lasted for 10 minutes, and one FTIR spectrum was measured in 20 s. As can be seen from Figure 2, the results are in a good agreement with each other, but the concentrations calculated by SPECTACS are a little closer to the predicted concentrations than those obtained by CALCMET. Similar tendency can be seen also in Figure 3, in which the concentrations of CO, SO2, CO2, and NO in the mixture 2 have been calculated by both methods (the certified concentrations were 50 ppm, 39 ppm, 8.1%, and 78 ppm, respectively). The largest deviation is seen in the case of NO in which CALCMET produced slightly higher concentrations than SPECTACS, probably because the IR spectrum of NO is rather simple and the main absorption bands might overlap with those of other components in the sample. Steel Plant Measurements with MS and IR. Gas samples taken from the converter of a steel plant were analyzed online with IR and MS during the combustion of steel; thus, the real concentrations were unknown. The IR results were calculated directly from the specific absorbance bands for both CO and CO2, and the MS results were calculated with either MCD mode on-site, or afterward with SPECTACS from the measured mass spectra. The IR and MS (MCD mode) results of carbon monoxide and carbon dioxide formed during one blasting correlated very well with each other (Figure 4a). The calibration of IR and MS instruments were made separately with different gas mixtures at different time in different conditions (temperature and humidity), and therefore, the agreement of the results was surprisingly good. The benefits of combining IR and MS methods were that the analytical results could be confirmed by using two separate methods, and with MS, it was possible to analyze also concentrations of oxygen and nitrogen which cannot be analyzed with IR. Figure 4b shows the normalized (the total sum of concentrations is 100%) concentrations of the main five gases of gaseous samples during the same blasting measured by MS using MCD mode. It shows the advantage of the MS method for the capability of the measurement of the whole composition of a gaseous sample online. Interestingly, also the concentrations of CO and N2 were analyzed accurately with MS despite the fact that they have equal molecular masses. This might be due to the fact that the concentration of CO is very high compared to that in normal atmosphere; thus, the ion at m/z 28 relates mostly to CO, and the concentration of N2 can be calculated from the intensity of the ion at m/z 14. Full scan mass spectra from another blasting were measured, the concentrations of the gases were calculated by SPECTACS using NALMS method with baseline correction, and the comparison of results obtained by IR and MS with SPECTACS is presented in Figure 4c. The results agree well with each other, even though the correlation is not as good as shown in Figure 4a using MCD mode with MS, but because of the mass spectrometer characteristics, the scanning time was very long (almost 50 s) compared to one cycle time in SIM measurements with MCD mode (about 17 s) or in IR measurements (3 s). As a consequence of this, rapid fluctuations in concentrations could not be observed in the full scan mode, and the concentrations are only averages of a long time span. To obtain more accurate results, faster scanning instruments should be used. Cellular Plastics Plant Measurements with MS and FTIR. Atmospheric emissions of acetophenone and R-cumyl

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Figure 5. The variation of concentrations of (a) acetophenone and (b) R-cumyl alcohol in a cellular plastics plant measured online with FTIR (with CALCMET) and MS (with SPECTACS).

alcohol from a cellular plastics plant were monitored online with FTIR using CALCMET software and with MS using SPECTACS with NALMS. The concentrations monitored during one measurement cycle are presented in Figure 5 for (a) acetophenone and (b) R-cumyl alcohol. The FTIR and MS results correlate rather well with each, and the fluctuations of acetophenone and R-cumyl alcohol releases during the process could be seen with both online methods. The concentrations of studied compounds measured with MS, especially that of acetophenone, were slightly lower than those measured with FTIR, due to the calibration of both instruments, which was done in conditions that differed a little from those of actual measurements (for practical reasons the calibration of the instruments was made beforehand in the laboratory, not on-site). On the other hand, the bulk concentrations of the compounds during the measurement period were also measured using another off-line method (adsorption with XAD-2 resin and subsequent analysis by liquid chromatography), and the concentrations of acetophenone and R-cumyl alcohol obtained with this method were 23 and 17 mg

m , respectively. Thus, for acetophenone, the FTIR results were closer to the average values, but for R-cumyl alcohol, the MS results were closer, and it is difficult to judge which method was better for the measurement. However, the advantage of online measurements compared to off-line measurements can clearly be seen from Figure 5, as with online measurement methods the variations in monitored concentrations during the measurement cycle can be observed whereas the off-line method gives only an average concentration of the whole measurement period. Use of SPECTACS with Combined FTIR-MS Spectrum. Petroleum Measurements. A mixture containing 11 organic compounds present in petroleum was analyzed simultaneously with FTIR and MS. The quantitative results from the measurement were calculated separately from FTIR and MS spectra, as well as from combined FTIR-MS spectra, with SPECTACS calculation program and the results obtained are presented in Table 1. The mixture made of major petroleum compounds is a difficult sample for both analytical methods, since many compounds are structurally very similar to each other and therefore hard to separate from one spectrum alone without any chromatographic separation. For example, different isomers of xylenes have almost identical mass spectra and many bands in the FTIR spectra of hexane and heptane are heavily overlapped. As can be seen from Table 1, errors of individual compounds measured with either FTIR or MS can be quite large, the average error of MS results was 65% and average error of FTIR results 38%. When the results were calculated for combined FTIRMS spectra, the average error was reduced to 24%. The accuracy of the analysis can be further improved by selecting the best method of analysis for each individual compound; for example, the isomers of xylene are analyzed with IR rather than with MS or FTIR-MS and this way the average error of analysis was decreased to 14%. Noise Reduction: Gases and Volatile Organic Compounds. The algorithm for solving the combined FTIR-MS spectrum was further improved by modeling the average noise at baseline in both spectra by using a third-degree polynomial and subtracting that model function from sample spectra. In Table 2 are presented the results of analysis of one gaseous sample, which contained eleven components. Both FTIR and MS spectra were measured from the sample simultaneously, and the spectra obtained were combined and processed using SPECTACS with LS or NALMS and noise reduction. The calibration of the instruments was made with the same compounds separately (i.e., each compound as its own gaseous standard diluted in nitrogen). The results in Table 2, compared with the results in Table 1, clearly show the benefit of noise

Table 1. FTIR, MS, and Combined FTIR-MS Results for Petrol Measurements Made Simultaneously with FTIR and MS conc, ppm compd

target value

MS

errora, %

FTIR

errora, %

FTIR-MS

errora, %

best method

errora, %

1,3,5-trimethylbenzene benzene ethylbenzene hexane heptane m-xylene o-xylene p-xylene toluene MTBE TAME average error

18.5 49.1 27.4 8.7 5.6 7.3 10.0 21.9 45.2 24.3 10.4

25.1 47.6 15.7 8.9 7.4 33.2 22.7 2.4 44.3 27.5 8.6

358 32 426 18 323 3548 1273 893 19 131 170 654

11.5 44.2 27.9 0 11.6 14.1 9.6 21.6 44.8 22.1 16.1

381 101 18 1000 1079 929 45 16 10 91 544 383

15.9 47.4 23.2 7.6 5.7 16.4 13.3 17.1 41.7 24.3 12.8

142 34 152 129 16 1249 332 220 78 01 232 235

15.9 47.4 27.9 8.9 5.7 14.1 9.6 21.6 44.8 24.3 12.8

142 34 18 18 16 929 45 16 10 01 232 143

a

The error is defined as an absolute deviation from the target value as percentage.

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Lassila and Lauri Holappa (Helsinki University of Technology) are acknowledged for their cooperation.

Table 2. Analysis of Combined FTIR-MS Spectra Using SPECTACS conc, ppm b

compd

calibration

target

LS

NALMS

benzene o-xylene m-xylene p-xylene 1,3,5-trimethylbenzene TAME hexane heptane methane oxygena hydrogena

100 100 100 100 100 100 100 100 70 30 50

100 5 10 15 95 8 4 50 70 30 50

106.0 -1.6 11.6 15.6 95.7 8.4 11.0 44.6 69.2 30 50

102.9 0.0 11.8 14.8 95.4 7.8 5.0 49.8 67.8 30 50

a Measured only with MS, concentrations in vol %. tration that was used for the calibration.

b

The concen-

reduction, since the concentrations obtained are closer to the target values. The major problem is still the isomers, such as those of xylene, but the total concentration of xylene isomers is rather close to the target value with both methods (25.6 and 26.6 ppm with LS and NALMS, respectively, compared with the target value of 30 ppm). When the total concentration of xylene isomers is taken into account, the absolute average deviation of concentrations of nine compounds from their target values is 24% for LS and 5.1% for NALMS thus showing that the accuracy can be improved with this noise reduction function. Conclusions The performance of a mathematical algorithm, SPECTACS, was evaluated for solving either a MS, an FTIR spectrum, or a combined FTIR-MS spectrum into its individual components (compounds in the original sample measured with the techniques). The SPECTACS method can identify and quantitate the major components in the samples thus enabling online measurement using both FTIR and MS full scan spectra. This method can improve the quantitative accuracy compared to the results obtained with one analytical technique alone, especially when the quantitative results are calculated from the combined FTIR-MS spectrum. The method was proven to work well with both volatile organic compounds and atmospheric gases. The new noise reduction function further improved the quantitative accuracy. Furthermore, in cases where the other technique can be considered more accurate than the other one, for example FTIR in the case where MS produce only a few nonspecific fragment ions or MS in case of atmospheric gases, the quantitative results can be taken only from the spectra of that instrument. Acknowledgment Financial support of Finnish Funding Agency for Technology and Innovation (TEKES), Borealis Polymers Oy, Ekogastek Oy, Laatukattila Oy, Fortum Oyj, Gasmet Technologies, and Kemira Fine Chemicals Oy is appreciated. Ismo Mattila, Kauko Tormonen, Jaakko Ra¨sa¨nen, and Jukka Lehtoma¨ki (VTT), and Ilkka

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ReceiVed for reView May 28, 2008 ReVised manuscript receiVed August 19, 2008 Accepted August 20, 2008 IE800851E