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Laser-Induced Breakdown Spectroscopy for Determination of the Organic Oxygen Content in Anthracite Coal Under Atmospheric Conditions LEI ZHANG, LEI DONG, HAIPENG DOU, WANGBAO YIN,* and SUOTANG JIA State Key Laboratory of Quantum Optics and Quantum Optics Devices, College of Physics and Electronics Engineering, Shanxi University, Taiyuan 030006, P.R. China

Laser-induced breakdown spectroscopy has been used to measure the organic oxygen content in pulverized anthracite coal under atmospheric conditions. Special spectral processing including the optimal O( I ) emission-line selection by comparing the spectral correlation coefficients with the N( I ) line, internal normalization with the N( I ) line, and temperature correction are proposed and employed to satisfy the multiline analysis method and yield the most accurate quantitative results. The calibration method for determining the organic oxygen content of coal is presented, with an accuracy of 1.15–1.37% and an average relative error of 19.39% being evaluated through an experiment performed on six anthracite coal samples. The relative measurement error distribution has also been studied. Index Headings: Laser-induced breakdown spectroscopy; LIBS; Organic oxygen; Coal; Multi-line analysis method; Relation coefficient; Temperature correction.

INTRODUCTION Oxygen in dry coal exists in both organic (oxygencontaining groups, such as –COOH, –OH, ¼CO, –OCH3, etc.) and inorganic (oxides dominating the majority) forms,1 where the former is one of the most abundant substances in coal and is crucial for real-time monitoring to obtain the optimum oxygen/coal mixing ratios for combustion in boilers of coal-fired power plants.2 Other than the outdated and errorprone oxygen-by-difference calculation, Hannan et al.3 have measured the total oxygen content of Nigerian coal samples, crude oils, bitumen extracts, and tar sand samples directly using instrumental fast neutron activation analysis (FNAA) under an He atmosphere; Brown et al.4 have introduced inductively coupled plasma (ICP) combined with gas sampling loop injections to determine the oxygen content in permanent gases and volatile organic liquids in Ar gas by analyzing the near-infrared atomic oxygen emissions; and Tran et al.5 have developed a new approach for the determination of the major elemental ratios (C:H:N:O) in solid organic powders under an Ar gas environment, and linear responses were obtained from these elements with precision and an accuracy of 2–3%. However, the use of an inert gas environment to eliminate interference from air is unlikely to be implemented in power plants. Lo et al.,6 Koban et al.,7 and Roy et al.8 have employed charge-coupled device (CCD) cameras to obtain the oxygen distribution of the measured areas by constructing fluorescence lifetime maps by virtue of well-defined Stern–Volmer equations, where materials (such as phosphor, toluene, 3-pentanone, and pyrene butyric acid) are required for oxygen-dependent collisional quenching. Received 30 October 2007; accepted 10 January 2008. * Author to whom correspondence should be sent. E-mail: ywb65@sxu. edu.cn.

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Volume 62, Number 4, 2008

Recently, significant applications have been reported on laser-induced breakdown spectroscopy (LIBS) by using the oxygen emission line under oxygen-containing environments. Salle´ et al.9 have performed the multi-matrix calibration curves for oxygen and other elements in rocks by LIBS in a simulated Martian atmosphere (9 mbar CO2); Itoh et al.10 have applied LIBS to multi-element analysis of hydrogen and oxygen found in a hydrogen–air diffusion flame by ratioing the atomic intensities to those of nitrogen, and the results were in fairly good agreement with those obtained by the numerical simulation; Ferioli et al.11 have applied LIBS to measure the equivalence ratio of a spark-ignited engine using ratios of C/O and C/N atomic peaks derived from the averaged spectra in a laboratory setting; Moreno et al.12 have applied a stand-off LIBS system to identify samples (including organic explosives, organic non-explosives, and non-organic non-explosives) in air by comparing the O/N intensity ratios and other parameters, and 13 successes out of 15 samples are reached in a 30 m distance known-sample test. However, to the best of our knowledge, at the present time, there is no report on the application of LIBS to the quantitative analysis of organic oxygen in mixed organic–inorganic compounds under atmospheric conditions. Our objective in this investigation is to determine the organic oxygen content of anthracite coal under atmospheric conditions. With the special spectra processing, a calibration formula for organic oxygen has been built and evaluated through a number of representative anthracite coal samples. The approaches for accuracy improvement have been proposed by analyzing the relative error distribution of the measurements.

EXPERIMENTAL SETUP The measurements were performed using the experimental setup sketched in Fig. 1. A portable Nd:YAG laser operating at 1064 nm was employed as the ablation source, with a fixed energy of 120 mJ/pulse output. The ablation laser beam was focused on the coal sample (for clarity, the coal samples used in our experiment were air dried) by a 90-mm-diameter and 400-mm-focal-length quartz lens. The sample holder was driven by a stepping motor and rotated at a speed of 1 rev/min. The plasma plume emission was guided to a 2-channel spectrometer (AvaSpec-2048FT) equipped with two gratings (3600, 1200 grooves/mm) by means of a 2-m-long all-silica optical fiber bundle (numerical aperture of 0.22; core of 600 lm). In the front of the fiber bundle, a focusing system was located 240 mm from the laser focal point on the sample at an angle of 458 from normal. The spectrometer triggered by the function signal generator would simultaneously respond by putting a 10 Hz TTL output with a 10 ls width to trigger the

0003-7028/08/6204-0458$2.00/0 Ó 2008 Society for Applied Spectroscopy

APPLIED SPECTROSCOPY

FIG. 1. Schematic view of the LIBS experimental apparatus used in this work.

laser. Finally, the spectral signal was analyzed on a personal computer. In order to obtain an optimum signal-to-noise ratio, a time delay of 200 ns and a time gate width of 10 ms were used.

SPECTRAL ANALYSIS The typical averaged spectra of the anthracite coal obtained from the spectrometer are shown in Fig. 2, which reveal most of the principal components such as C, H, O, N, Si, Al, Mg, and Ca. In Fig. 2b, several oxygen- and nitrogen-related peaks from 710 nm to 930 nm are observed. In this work, a 746.8 nm nitrogen band is mostly used throughout the experiments for normalization. Here, we attempted to build the calibration formula for organic oxygen by subtracting the inorganic oxygen content from the total oxygen content of coal. Determination of Total Oxygen Content of Coal, (CO)t. Although the raw atomic emission has been used for the analysis of organics,13–16 the intensity ratio IO /IN (IO and IN are the emission intensities of oxygen and nitrogen, respectively), which is approximately proportional to the atom density ratio of NO/NN, was applied to yield better results.5,10–12,17–20 Here, the intensity ratio IO / IN can be obtained from the following equation according to Boltzmann’s law:21,22 NO gO AO kN IO =IN ¼ BðTÞ NN gN AN kO

ð1Þ

BðTÞ ¼ ½ZN ðTÞ=ZO ðTÞ exp½ðEO EN Þ=KB T

ð2Þ

where

is a function of plasma temperature T (in K); Z(T) is the partition function for the emitting species; A (in s1) is the transition probability for the given line; E (in eV) and g are the energies and degeneracies of the upper levels, respectively; KB is the Boltzmann constant; and A and k (in nm) are the Einstein coefficient and the wavelength, respectively. However, even though the laser beam has been focused to a sufficiently small spot to reduce the undesired air breakdown induced in the proximity of the sample, there still exists disturbance in the measurements, which makes it difficult to distinguish between the oxygen from the coal and that from the surrounding air.12 Hence, it must be stated that the observed oxygen emissions

FIG. 2. (a) Averaged spectra of the anthracite coal obtained from channel 1 of the spectrometer. Specific lines emitted by C, Mg, Si, Al, Ti, and Ca atoms are marked. (b) Averaged spectra of the anthracite coal obtained from channel 2 of the spectrometer. Specific lines emitted by O, N, H, Si, Li, and K atoms are marked. Moreover, the averaged spectral correlation between the spectrum of channel 2 and the N( I ) line intensity at 746.8 nm (without background subtracted) is shown.

under atmospheric conditions are a result of both coal and air contents in this element. Provided that the small amount of nitrogen content ((NN)coal 1%) in typical anthracite coal samples can be neglected as compared to that in the background air ((NN)air), and provided that the induced amounts of nitrogen and oxygen originating from the air are fixed ((NN)air and (NO)air are constants) under normal and certain experimental conditions, then the total oxygen content of coal ((CO)t) can be deduced as IO NO ðNO Þair þ ðNO Þcoal ðNO Þair } ¼ ’ IN NN ðNN Þair þ ðNN Þcoal ðNN Þair ðNO Þcoal ðNO Þcoal þ } }ðNO Þcoal }ðCO Þt ðNN Þair ðNN Þair

ð3Þ

This expression shows that the intensity ratio IO / IN varies linearly with the corresponding total oxygen content (CO)t of coal. To reduce the stochastic measurement errors that depend on the undesired air breakdown, laser energy, spatial mode


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FIG. 3. Typical Boltzmann plots obtained from the analysis of an anthracite coal sample.

variations, or irregular surface conditions of the sample, the multi-line analysis method, which employs several O( I ) lines, was proposed and employed to enhance the sensitivity and reliability. As shown in Fig. 2b, the four O( I) lines at 715.7, 777.3, 844.6, and 926.6 nm were labeled as O0, O1, O2, and O3, respectively. To choose the optimal analytical O( I) lines for calculation of the IO /IN ratios, the averaged spectral correlation between the spectrum of channel 2 and the N(I ) line at 746.8 nm was studied (see Fig. 2b). For each pixel of channel 2, the correlation value was obtained by averaging the computed linear correlation coefficients (or product-moment coefficient) between the corresponding signal intensity and the N( I ) line intensity (without background subtracted) through 1500 groups of plasma spectra (processed by a procedure compiled in Labview). It is obvious that the peak correlation coefficients at the location of O1, O2, and O3 are larger than 0.95, while that at the location of O0 is 0.87. This is probably due to the fact that the O0 emission line lies on an obscure background. Accordingly, the O1, O2, and O3 lines were selected. The weak correlations between the N( I) line and emission lines such as Si( I), Li( I), and K( I) are mainly due to the large differences between the upper energy states of their transitions, in which case the temperature effect of the Boltzmann factor is serious.23 The optimization process, which was based on the correlation method, was proposed firstly to yield more accurate IO /IN ratios. Moreover, it can be seen that the intensity ratios IO /IN in Eq. 1 are related to the difference between the upper energy levels of the lines and also are proportional to the ratio of Boltzmann factors, becoming independent of the ablated mass.24 Thus, it is expected to yield lower relative standard deviation (RSD) by proper temperature correction. From Eq. 1, we obtain ðIOi =IN Þ 0 ¼

ðIOi =IN Þ NO gOi AOi kN ¼ ; BðTÞ NN gN AN kOi

ði ¼ 1; 2; 3Þ


plots, using the total intensities of the four nitrogen lines at 746.8, 821.6, 868.3, and 904.6 nm and the three oxygen lines at 777.3, 844.6, and 926.6 nm. As an example, the Boltzmann plots obtained from the analysis of an anthracite coal sample are reported in Fig. 3. The slopes of the two solid lines for nitrogen and oxygen yield an average temperature T of 25 533 K. Once the T is obtained, the function B( T ) in Eq. 4 can be calculated using a six-order polynomial with the partition function Z( T ) being provided by NIST27 (see Fig. 4). A typical comparison between the original IO1/ IN values and the corresponding temperature-corrected (IO1/IN) 0 values is shown in Fig. 5, where the relative standard deviation (RSD) has decreased from 8.33% to 5.98%, indicating the necessity for temperature correction. We can finally obtain the required expression ðCO Þt ¼ aRbi ðIOi =IN Þ 0 þ c

ð5Þ

for the total oxygen content (CO)t determination in anthracite coal based on the multi-line analysis method. Here, a and c are the coefficients previously determined from the relative

ð4Þ

That means that when the plasma temperature T is obtained by determining the slope of the Boltzmann plot,25,26 we can arbitrarily obtain the corrected value (IOi/IN) 0 , which eliminates the negative effect caused by B(T). In this work, the plasma temperature T was determined by constructing Boltzmann

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FIG. 4. Simulation of the function B(T) of O1, O2, and O3 at different plasma temperatures.

FIG. 5. Intensity ratios without (IO1/IN) and with ((IO1/IN) 0 ) temperature correction for 100 laser shots.

FIG. 6. Calibration curve created for total oxygen content in our certified anthracite coal samples.

calibration curve, and bi is the normalization coefficient, which could be calculated from the actual intensity ratio IO1/IOi. Here, b1 ¼ 1, b2 ¼ 2.96, and b3 ¼ 1.19 are obtained in our experiment. The calibration curve of the total oxygen content (CO)t versus the Rbi(IOi/IN) 0 values measured on eight reference anthracite coal samples with values certified by ICC (Institute of Coal Chemistry, China) is plotted in Fig. 6. It can be seen that although the curve does not intercept the 0 point, there is a linear relationship (with the correlation coefficient R larger than 0.98) between the Rbi(IOi/ IN) 0 values and the actual (CO)t values. This non-zero intercept is due to the atmospheric oxygen breakdown induced on the sample proximity. From this linear plot, the coefficients a and c in Eq. 5 are determined to be 54.78 and 204.29, respectively. Determination of the Inorganic Oxygen Content of Coal, (CO)i. Provided that the temperature of the resulting plasma is high enough to dissociate molecules into their constituent atoms, the atomic oxygen emissions of the coal are derived both from the organic and inorganic substances. For the representative anthracite coal in China, the main inorganic

FIG. 8. A comparison between the measured organic oxygen contents and the actual organic oxygen contents through six certified anthracite coal samples. Each sample has been analyzed by 300 successive laser shots for five times.

components are silicon dioxide (SiO2) and aluminum trioxide (Al2O3), which together account for 80 to 90% of the total inorganic components in coal by weight. As a result, in principle, the other trace-element oxides (iron trioxide (Fe2O3), phosphorus pentoxide (P2O5), calcium oxide (CaO), magnesium oxide (MgO), titanium dioxide (TiO2), etc.) can be neglected here. Namely, if the contents of Si and Al (CSi and CAl) were known, the (CO)i value could be estimated by summing up the corresponding inorganic oxygen contents in these oxides. By using the pulse-to-pulse intensity normalization method,28 the calibration curves of Si (288.2 nm) and Al (309.3 nm) were obtained, as shown in Fig. 7. Then the inorganic oxygen content of coal can be expressed as ðCO Þi ¼ 1:14CSi þ 0:89CAl ¼ 1:14 3ð3926:69ISi þ 0:40Þ þ 0:89 3ð4265:33IAl 0:72Þ

ð6Þ

where the coefficients of 1.14 and 0.89 were obtained from the atomic weight ratios 2O/Si and 3O/2Al, respectively; ISi and IAl are the normalized peak intensities for Si and Al, respectively. Finally, by combining Eq. 5 and Eq. 6, the calibration formula for organic oxygen (CO)o was written in the form ðCO Þo ¼ ðCO Þt ðCO Þi ¼ ðCO Þt ð1:14CSi þ 0:89CAl Þ ¼ 54:78 3½ðIO1 =IN Þ 0 þ 2:96 3ðIO2 =IN Þ 0 þ 1:19 3ðIO3 =IN Þ 0 204:29 ½1:14 3ð3926:69ISi þ 0:40Þ þ 0:89 3ð4265:33IAl 0:72Þ ð7Þ

RESULTS AND DISCUSSION

FIG. 7. Calibration curves created for Si and Al in our certified anthracite coal samples.

To validate the feasibility of the calibration formula for organic oxygen, six standard pulverized anthracite coal samples (marked from #1 to #6) were analyzed, with each one being analyzed by 300 successive laser shots for five times. Comparisons of the measured and the actual organic oxygen contents are shown by solid circles and hollow circles in Fig. 8. Obviously, employing our spectra processing, the LIBS system


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FIG. 9. The relative error distribution functions for the three terms in Eq. 7 by analyzing six anthracite coal samples. Each of the samples has been analyzed five times in our experiment.

was able to distinguish the #1, #2/#3/#4, #5, and #6 samples, where the minimum organic oxygen content difference is 1.37%. However, for the #2, #3, and #4 samples with the maximum organic oxygen content difference of 1.15%, the data points are largely overlapped with each other. Therefore, the accuracy for absolute organic oxygen content determination in pulverized anthracite coal in this experiment was considered simply in the range of 1.15–1.37%. The relative error distribution functions for (CO)o determination are shown in Fig. 9. The bars show the error distribution of the LIBS measured values of the three terms of Eq. 7 in comparison to the ‘‘real’’ values provided by ICC. The calculated Lorentz distributions (dotted lines) feature the shift of maximum to positive values. The average absolute relative error is calculated to be 19.39%. It can also be seen that the measurement errors from terms such as (CO)t and 1.14CSi are the potential dominant error sources in the measurement task, while those of the term 0.89CAl are negligible. Therefore, the measurement accuracy of (CO)o could be further improved by obtaining more accurate CSi values. Approaches including selection of a proper reference line for internal normalization and temperature correction are considered to be the shortcuts. Note that the C( I) (247.8 nm) line rather than the N(I) (746.8 nm) line should be selected as the reference line for internal normalization for our case, because the Si( I ) (288.2 nm) and N( I ) (746.8 nm) lines lay in different channels of our current spectrometer, which will bring additional errors into the measuring process referring to the different spectral responses of the CCD and optical transmission efficiencies.

CONCLUSION In the present study, an effort was made to develop the feasible data processing for organic oxygen determination in anthracite coal under atmospheric conditions, which has not been reported previously. The processes proposed in the investigation are concentrated on measuring the total oxygen content (CO)t and the inorganic oxygen content (CO)i. For the former, methods of optimal analytical line selection, multi-line analysis, internal normalization, and temperature correction are

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employed to enhance the reliability; and for the latter, we have assumed that the inorganic oxygen of the anthracite coal totally exists in the oxides of silicon and aluminum. However, the validity of this assumption is restricted to the cases where the coal is the representative anthracite coal of China; for other coal types, it should be properly modified according to the practical chemical properties. For our LIBS system, the O1, O2, and O3 lines (with correlation coefficients larger than 0.95), excepting the O0 line (with a correlation coefficient of 0.87), are chosen to be the optimal O( I) lines. From the quantitative results, the measurement accuracy is estimated to be in the range of 1.15–1.37% while the average absolute relative error is 19.39%. The major measurement errors of the calibration formula are considered to have arisen from the term 1.14CSi in the calibration formula, and a better accuracy is expected after the present experiment upon employing several of the proposed approaches. In any case, this investigation has provided an approach for overcoming the limitation that has been up to now the major obstacle to practical LIBS applications to quantitative analysis of organic oxygen in coal under atmospheric conditions, and it serves as a first step toward the use of LIBS for in situ monitoring in coal-fired power plants. ACKNOWLEDGMENTS This work was supported by 973 Program (Grant. No. 2006CB921603), National Natural Science Foundation of China (Grant No. 10574084 and 60678003), Science and Technology Project of Taiyuan (Grant. No. 07010715), and Shanxi Province Foundation for Returned Overseas Scholars. The authors are grateful to Haitong Automation Technique Ltd. and Institute of Coal Chemistry (ICC) for their financial and technical support. 1. G. Takeya, Pure Appl. Chem. 50, 1099 (1978). 2. Y. Tan, E. Croisetb, M. A. Douglasa, and K. V. Thambimuthu, Fuel 85, 507 (2006). 3. M. A. Hannan, A. F. Oluwole, L. O. Kehinde, and A. B. Borisade, J. Radioanal. Nucl. Chem. 256, 61 (2003). 4. R. M. Brown, Jr. and R. C. Fry, Anal. Chem. 53, 532 (1981). 5. M. Tran, Q. Sun, B. W. Smith, and J. D. Winefordner, J. Anal. At. Spectrom. 16, 628 (2001). 6. L. W. Lo, S. H. Y. Huang, C. H. Chang, W. Y. Chen, P. J. Tsai, and C. S. Yang, J. Med. Biol. Eng. 23, 19 (2003). 7. W. Koban, J. Schorr, and C. Schulz, Appl. Phys. B 74, 111 (2002). 8. S. Roy and S. R. Duke, Exp. Fluid. 36, 654 (2004). 9. B. Salle´, J. L. Lacour, P. Mauchien, P. Fichet, S. Maurice, and G. Manhe`s, Spectrochim. Acta, Part B 61, 301 (2006). 10. S. Itoh, M. Shinoda, K. Kitagawa, N. Arai, Y. I. Lee, D. Zhao, and H. Yamashita, Microchim. J. 70, 143 (2001). 11. F. Ferioli, P. V. Puzinauskas, and S. G. Buckley, Appl. Spectrosc. 57, 1183 (2003). 12. C. L. Moreno, S. Palanco, J. J. Laserna, F. DeLucia, Jr., A. W. Miziolek, J. Rose, R. A. Walters, and A. I. Whitehouse, J. Anal. At. Spectrom. 21, 55 (2006). 13. L. Barrette and S. Turmel, Spectrochim. Acta, Part B 56, 715 (2001). 14. O. Samek, D. C. S. Beddows, H. H. Telle, J. Kaiser, M. Lisˇka, and J. O. Caćeres, Spectrochim. Acta, Part B 56, 865 (2001). 15. R. Barbini, F. Colao, R. Fantoni, A. Palucci, S. Ribezzo, H. J. L. van der Steen, and M. Angelone, Appl. Phys. B 65, 101 (1997). 16. P. Lucena, L. M. Cabalıń, E. Pardo, F. Martıń, L. J. Alemany, and J. J. Laserna, Talanta 47, 143 (1998). 17. R. Sattmann, I. Mo¨nch, H. Krause, R. Noll, S. Couris, A. Hatziapostolou, A. Mavromanolakis, C. Fotakis, E. Larrauri, and R. Miguel, Appl. Spectrosc. 52, 456 (1998). 18. L. St-Onge, E. Kwong, M. Sabsabi, and E. B. Vadas, Spectrochim. Acta, Part B 57, 1131 (2002). 19. S. Kaski, H. Ha¨kka¨nen, and J. Korppi-Tommola, J. Anal. At. Spectrom. 19, 474 (2004). 20. D. Mukherjee, A. Rai, and M. R. Zachariah, J. Aerosol Sci. 37, 677 (2006). 21. I. Bassiotis, A. Diamantopoulou, A. Giannoudakos, F. Roubani-Kalantzopoulou, and M. Kompitsas, Spectrochim. Acta, Part B 56, 671 (2001).

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