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Quantitative analysis of Fe and detection of multiple elements in the coal ash by laser-induced breakdown spectroscopy
Optik - International Journal for Light and Electron Optics 169 (2018) 77–84
Contents lists available at ScienceDirect
Optik journal homepage: www.elsevier.com/locate/ijleo
Original research article
Quantitative analysis of Fe and detection of multiple elements in the coal ash by laser-induced breakdown spectroscopy
T
⁎
Ruosong Zhua,b, Yuzhu Liua,b, , Qihang Zhanga,b, Fengbin Zhoua,b, Feng Jinc, Wenyi Yina,b, Xinfeng Zhaoa a
Jiangsu Key Laboratory for Optoelectronic Detection of Atmosphere and Ocean, Nanjing University of Information Science & Technology, Nanjing 210044, PR China b Jiangsu Collaborative Innovation Center on Atmospheric Environment and Equipment Technology (CICAEET), Nanjing 210044, PR China c Advanced Technology Core, Baylor College of Medicine, Houston, TX 77030, USA
A R T IC LE I N F O
ABS TRA CT
Keywords: Laser-induced breakdown spectroscopy Coal ash Quantitative analysis Fe Aerosols Internal standard method
Sulfates produced by the reaction of metal oxides in coal ash with the acid gases in the atmosphere are the main causes of haze-fog formation. In this study, laser induced breakdown spectroscopy(LIBS) was used for elemental analysis in coal ash. A new method was adopted to conduct an accurate qualitative analysis of the four elements (Al, Ca, Cu and Fe) that easily form sulfates in coal ash. An internal standard method was used to quantitatively analyze the typical Fe element of the four elements with a calibration curve that had a linear correlation coefficient (R2) of 0.986. In order to test the accuracy of the curve, three kinds of coal ash with unknown composition were selected and analyzed by LIBS and X-ray fluorescence spectrometry (XRF). The relative differences of the two methods were around 7.42%, 3.37% and 4.34%, respectively, which are all in the acceptable range. The experimental results indicate that LIBS can be employed for the rapid detection and analysis of metal elements in coal ash and provide a new classification method for coal ash based on the content of Fe element.
1. Introduction Coal ash, as a mineral dust, is the main component of a variety of metal oxides. It is the product of the complete burning of coal. Since the Second Industrial Revolution, coal, as a significant energy material, were widely used in people's production and life. At the same time, a large amount of mineral dust (coal ash) from coal combustion were released into the atmosphere, reacting with the acid gases in the atmosphere to form sulfates [1], which forms a haze-fog in the atmosphere and brings great threat to human health, Several significant air pollution events happened due to coal ash, such as the Great Smog of London [2], the Yokkaichi asthma incident [3] and the Belgian Meuse Valley incident [4], and all caused a large number of fatalities. Till now, there are still a lot of developing countries in the world which have faced the similar environmental challenge such as China [5], India [6], Iran [7] and so on. Therefore, there is urgent need for developing sufficient tools to detect haze-fog so that timely actions may be taken to prevent more people from harms. We propose the rapid detection and analysis of sulfate-forming elements in coal ash, that is believed to be the main cause of haze-fog. Laser induced breakdown spectroscopy (LIBS) [9] is an element detection technique developing in recent years. Due to its advantages of real-time, fast, non-contact and simultaneous detection of multiple elements, LIBS has been widely applied on detection
⁎
Corresponding author. E-mail addresses: [email protected], [email protected] (Y. Liu).
https://doi.org/10.1016/j.ijleo.2018.05.035 Received 8 February 2018; Received in revised form 3 April 2018; Accepted 10 May 2018 0030-4026/ © 2018 Elsevier GmbH. All rights reserved.
Optik - International Journal for Light and Electron Optics 169 (2018) 77–84
R. Zhu et al.
Fig. 1. Schematic diagram of the LIBS setup.
and analysis of elements in soils [10–15], aerosols [16–20], liquid [21,22] and rocks [23]. It has become an important medium in the field of environmental monitoring. In this article, seven kinds of coal ash samples from a steel company were detected based on laser-induced breakdown spectroscopy. The qualitative analysis of four elements Al, Ca, Cu and Fe, which are easy to form sulfates, was carried out. The Fe content was chosen as an example for quantitatively analysis and a calibration curve was obtained. Three kinds of samples with unknown composition were selected to test the predictive ability of the curve. In addition, it is proposed that the content of Fe element in coal ash can be used to provide a new method for the classification of coal ash.
2. Experimental 2.1. Experimental setup The schematic of the LIBS experiment is shown in Fig. 1. The laser used in the experiment was a Q-switched Nd-YAG laser, which was operated at a fundamental wavelength of 1064 nm. The maximum energy is 600 mJ in a single laser pulse, and the pulse energy for the employed laser beam in the current measurement is around 100 mJ per pulse with 10 ns duration at a frequency of 5 Hz. The laser beam was focused onto the sample surface using a focusing lens (f = 150 mm), of which the irradiation energy was collected with a fibre-optical probe. The emission signal from the plasma was transferred via a fiber to a spectrometer system. The spectrum was recorded on a personal computer, and the PLSUS software was utilized to identify emission lines and presented the possible elements according to the spectrum. The effective spectral resolution of this spectrometer system was around 0.03 nm, depending on the wavelength. In order to increase the stability and reduce the standard deviation of the spectral intensities, 10 measured spectra were averaged. The spectrometer and wavelength shift were calibrated via the pure metal sample.
2.2. Sample preparation In this experiment, seven kinds of coal ashes from a steel company were prepared as samples, which were labeled with Sample1#, Sample-2# to Sample-7#, respectively. The accurate elemental concentration was obtained by X-ray Fluorescence Spectrometry [24–26] (As shown in Table 1). Since the sample is powder, in order to obtain a better LIBS signal, the tablet machine was used to press the coal ash into coal lump of 10 mm in diameter and 5 mm in thickness.
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Table 1 Chemical composition of coal ash samples(Reproducibility Critical Difference < 0.80%). Mass%
Si
S
Al
P
Fe
Na
K
Mn
Mg
Cu
Ca
Ti
Sample-1# Sample-2# Sample-3# Sample-4# Sample-5# Sample-6# Sample-7#
20.923 21.329 23.284 22.454 21.903 21.445 19.341
0.807 0.618 0.060 0.205 0.336 0.480 1.085
14.430 13.345 16.370 16.725 17.195 14.662 14.296
0.297 0.340 0.269 0.229 0.317 0.341 0.274
4.511 2.598 8.320 6.867 7.788 3.224 4.218
1.009 1.112 0.446 0.430 0.367 1.025 0.890
1.211 1.259 0.767 0.807 0.509 1.206 1.222
0.056 0.036 0.110 0.113 0.136 0.043 0.050
1.052 1.059 0.533 0.614 0.487 0.934 1.469
0.014 0.013 0.016 0.018 0.021 0.014 0.015
3.684 2.916 1.794 2.037 1.837 2.767 4.458
0.754 0.711 0.875 0.930 0.975 0.832 0.905
3. Results and discussion 3.1. Qualitative analysis of coal ash Fig. 2 shows the LIBS spectral line of the wavelength range of 200nm∼800 nm for the sample. As shown in, the figure, all of the metal elements and some non-metallic elements have been detected by the LIBS experiment. S element was not detected because, the characteristic lines of S element are mainly concentrated in the infrared band and beyond the scope of this experiment. Due to the uncertainty of spectral analysis and wavelength shift phenomenon, it is difficult to qualitative analyze the element accurately. In order to solve this problem, four kinds of high-purity elemental Fe, Ca, Al and Cu were selected for the reference experiment from a chemical company. Under the same experimental conditions, the measured four kinds of single-line spectra were compared with the corresponding wavelengths in the NIST Atomic Spectral Database [8], and all the spectra in the experiment were corrected according to the error of the wavelength. At this point, the spectrum of pure sample can be aligned with the coal ash sample spectrum, and the element can be identified when the characteristic spectrum in the simple one is aligned with the spectrum in the sample. Fig. 3 shows the spectrum of sample-4# contrast to the pure Al, Ca, Cu and Fe, respectively. Characteristic peaks of Al at 308.2 nm, 309.21 nm, 394.418 nm and 396.152 nm in the reference experiment of Al sample were observed and were used to calibrate the wavelength shift for the observed peaks of coal ash sample-4#. Similarly, characteristic peaks at 442.748 nm, 443.778 nm and 445.495 were chosen for Ca; Cu has characteristic peaks at 393.377 nm and 396.845 nm and Fe has characteristic peaks at 610.269 nm, 612.278 nm, 614.258 nm, 616.238 nm and 714.816 nm.
3.2. Quantitative analysis of Fe via internal standard method For the rapid detection of element of coal ash, quantitative analysis is also realized in the experiment. For these four interest elements, Fe content was chosen as the example for quantitatively analysis. The quantitative analysis formula of laser induced breakdown spectroscopy is Lomakin-Scheibe formula: I = aCb
(1)
where I is the observed intensity of the spectral line, a is the experiment constant, C is the concentration of the objective element, and b is the self-absorption coefficient. Since no visible self-absorption phenomenon can be found from the sample. The self-absorption coefficient can be ignored, b = 1. The corresponding equation is then: I = aC
(2)
In this experiment for quantitatively analysis of Fe, Al was selected as the internal standard element because of its high content and close to mass fraction in each sample. Several analytical lines such as Al I 308.2 nm, Al I 309.21 nm, Al I 394.418 nm and Al I 396.152 nm were selected. And the equation above was changed to: ∑(IFe/IAl) = aFeCFe/aAlCAl
(3)
Further, the Eq. (3) can be simplified to: I* = AC
(4)
*
Where I is the relative intensity of spectral lines of Fe, A is a constant which equals aFe/aAlCAl, and C is the concentration of Fe in the coal ash. As demonstrated in Eq. (4), the concentration of Fe is taken as the independent variable, and Σ (IFe / IAl) is used as the dependent variable while fitting a model to establish the calibration curve. As can be seen from the Fig. 4, linear correlation coefficients (R2) of the relative intensity versus the concentration of Fe is 0.986. It means that the intensity of Fe in the LIBS spectrum of coal ash is proportional to the concentration of the corresponding Fe in coal ash. Thus, we concluded that the Fe concentration of the coal ash can be determined by analyzing the spectral lines of Fe with LIBS. The possible saturation with increasing laser energy and an increasing elemental concentration is very important in the 79
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R. Zhu et al.
Fig. 2. LIBS spectrum of coal ash(sample-4#) ranged from 200 to 800 nm.
calibration process. For the present measurement, the laser power is kept the same for all the different concentration. And for the prepared concentration from 2.598% to 8.320% in the current measurement, no significant saturation effect is observed. The Fe element in the atmosphere is mainly discharged by the metallurgical enterprises. And there is the following reaction between Fe2O3 and the acid gas in the atmosphere[27–30]: Fe2O3 + H+ + H2O → Fe2+ + Fe3+
(5) 80
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Fig. 3. Spectral comparison of sample-4# (coal ash) and four elementary substances of (a) Al, (b) Ca, (c) Cu and (d) Fe at different range.
Therefore, the resulting iron ions combine with sulfate to form sulfates. The content of Fe element can also reflect part of the S content in the atmosphere. Through the real-time, accurate detection and treatment of Fe content in coal ash, the content of sulfate in the atmosphere can be effectively controlled, so that the occurrence of haze can be controlled. The same applies to other sulfate-forming elements. The coal ash used in this paper is the ash left after the complete combustion of the coking coal and the coal injection which are made by the modern coal blending process, and therefore they are uniformly mixed (Note: metallurgical coke is made by dry distillation of coking coal). In blast furnace ironmaking, the ash content of the coal injection should be as low as possible and is lower than the ash content in 81
Optik - International Journal for Light and Electron Optics 169 (2018) 77–84
R. Zhu et al.
Fig. 3. (continued)
the metallurgical coke. Ash content is directly related to the content of metal element. In Table 1, it also can be found that most relevant metals (such as Al, Fe, Mn, Cu and Ti) have a higher content in metallurgical coke than coal injection. In this article, Fe is used as an example for quantitative analysis. The results are shown in Fig. 4, the content of Fe is linear overall, which in coal ash made from coal injection is mainly concentrated in the dash circle and in metallurgical coke focus on the dash dot circle. Through this curve, coal ash can be sorted preliminarily and quickly.
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Fig. 4. Calibration curve for Fe in the coal ash (The error bars indicate the uncertainties of spectral calibration causes fluctuations in Fe elements during quantitative analysis).
3.3. Calibration curve testing In order to test the accuracy of the calibration curve, three kinds of samples with unknown composition were prepared as unknown samples from the Steel Company, which were labeled with Unknow-a, Unknow-b and Unknow-c, respectively, and tested under the same experimental conditions. After the LIBS detection is completed, the samples are detected for the exact concentration by XRF for reference. According to the comparison, the relative differences were calculated and listed in Table 2. The contents of Fe measured by XRF were 4.04%, 5.93% and 5.30%. The Fe contents measured by LIBS were 3.74%, 6.13% and 5.53%. The relative differences of the two methods were 7.42%, 3.37% and 4.34%, respectively. The causes of the differences are: the lack of resolution of the spectrometer, the instability of the laser, and the impact of background noise. Compared with well-established technique XRF, LIBS can detect rapidly for the applied laser with 10 times average, the detection time is around 2 s for one spectrum 2 s resolution. And in the case of the sample does not require pretreatment, to obtain more accurate experimental results. 4. Conclusion Almost elements such as Si, Al, P, Fe, Na, K, Mn, Mg, Cu, Ca and Ti were found in coal ash by LIBS. Among them, four characteristic elements Al, Cu, Fe and Ca, were further accurately analyzed qualitatively. The internal standard calibration method was used to quantitatively analyze the Fe content in different samples. The linear correlation coefficient between relative intensity and Fe concentration was 0.986. In addition, three unknown samples were selected to test the accuracy of the resulting calibration curve. The relative difference between the predicted value of the curve and the accurate value measured by X-ray fluorescence spectrometry were within the acceptable range. The experimental results show that the content of Fe in different kinds of coal ash is distinguished, and the distribution of Fe is linear. The calibration curve can be a preliminary classification of coal ash and accurate detection of Fe element content. Thus, LIBS Table 2 Measurement of Fe Element Content in Unknown Samples by Two Methods. MASS%
Element
LIBS experimental value
XRF experimental value
Relative difference
Unknow-a Unknow-b Unknow-c
Fe Fe Fe
3.74% 6.13% 5.53%
4.04% 5.93% 5.30%
7.42% 3.37% 4.34%
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can be used to quickly detect the discharge of coal ash containing and track its origin via the content of Fe element. For others it is easy to form sulfates metal elements, this method can also be used in the establishment of the calibration curve of the element after its quantitative analysis. Acknowledgments This work was supported by the National Key R&D Program of China (2017YFC0212700), “Six Talent Peaks” project in Jiangsu Province (Grant No. 2015-JNHB-011) and the Innovation practice training plan for college students of Hefei Institute of Physical Science, Chinese Academy of Sciences (201717001061). References [1] Biwu Chu, Jiming Hao, Hideto Takekawa, Junhua Li, Kun Wang, Jingkun Jiang, The remarkable effect of FeSO4 seed aerosols on secondary organic aerosol formation from photooxidation of a-pinene/NOx and toluene/NOx, Atmos. Environ. 55 (2012) 26–34. [2] https://en.wikipedia.org/wiki/Great_Smog_of_London. [3] https://en.wikipedia.org/wiki/1930_Meuse_Valley_fog. [4] https://en.wikipedia.org/wiki/Yokkaichi_asthma. [5] X.Y. Zhang, Y.Q. Wang, T. Niu, X.C. Zhang, S.L. Gong, Y.M. Zhang, J.Y. Sun, Atmospheric aerosol compositions in China: spatial/temporal variability, chemical signature, regional haze distribution and comparisons with global aerosols, Atmos. Chem. Phys. 12 (2012) 779–799. [6] S. Tiwari a, A.K. Srivastava, D.S. Bisht a, P. Parmita, Manoj K. Srivastava, S.D. Attri, Diurnal and seasonal variations of black carbon and PM2.5 over New Delhi, India: influence of meteorology, Atmospheric Res. (125–126) (2013) 50–62. [7] Heidar Maleki, Armin Sorooshian, Gholamreza Goudarzi, Amirhossein Nikfal, Mohammad Mehdi Baneshi, Temporal profile of PM10 and associated health effects in one of the most polluted cities of the world (Ahvaz, Iran) between 2009 and 2014, Aeolian Res. 22 (2016) 135–140. [8] NIST Atomic Spectra Database, http://physics.nist.gov/PhysRefData/ASD/lines_form.html. [9] Hahn D.W, Omenetto.N., Laser-Induced Breakdown Spectroscopy (LIBS), Part II: Review of Instrumental and Methodological Approaches to Material Analysis and Applications to Different Fields. [10] V.S. Burakov, N.V. Tarasenko, M.I. Nedelko, V.A. Kononov, N.N. Vasilev, S.N. Isakov, Analysis of lead and sulfur in environmental samples by double pulse laser induced breakdown spectroscopy, Spectrochim. Acta Part B 64 (2009) 141–146. [11] Yeqiu Li, Rina Wu, Qin Dai, Tianyu Li, Nan Gong, Chenglin Sun, Zhiwei Men, Spectroscopic study on the time evolution behaviors of the double laser-induced breakdown of Al plasma, Optik 147 (2017) 32–38. [12] Peng Xiong Wan, Wang, Analysis of heavy metals in organisms based on an optimized quantitative LIBS, Optik 126 (9) (2015) 1930–1934. [13] Jae-Jun Choi, Soo-Jin Choi, J. Jack, Yoh. Standoff, Detection of geological samples of metal, rock, and soil at low pressures using laser-induced breakdown spectroscopy, Appl. Spectrosc. 70 (9) (2016) 1411–1419. [14] D.M. Dong, C.J. Zhao, W.G. Zheng, X.D. Zhao, L.Z. Jiao, Spectral characterization of nitrogen in farmland soil by laser-induced breakdown spectroscopy, Spectrosc. Lett. 46 (6) (2013) 421–426. [15] Ji-hyun Kwak, Christoph Lenth, Christian Salb, Eun-Joung Ko, Kyoung-Woong Kim, Kihong Park, Quantitative analysis of arsenic in mine tailing soils using double pulse-laser induced breakdown spectroscopy, Spectrochimica Acta Part. B. 64 (2009) 1105–1110. [16] Gibaek Kim, Young-Jun Yoon, Hyun-A. Kim, Hee-joo Cho, Kihong Park, Elemental composition of arctic soils and aerosols in Ny-Ålesund measured using laserinduced breakdown spectroscopy, Spectrochim. Acta Part B 134 (2017) 17–24. [17] Erin S. Simpson, Gregg A. Lithgow, Steven G. Buckley, Three-dimensional distribution of signal from single monodisperse aerosol particles in a laser induced plasma: initial measurements, Spectrochimica Acta Part. B. 62 (2007) 1460–1465. [18] Ammon N. 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Taschuk, Robert Tsui, Fedosejevs, Detection of lead in water using laser-induced breakdown spectroscopy and laser-induced fluorescence, Anal. Chem. 80 (2008) 1995–2000. [23] Kheireddine Rifai, Marcel Laflamme, Marc Constantin, François Vidal, Mohamad Sabsabi, Alain Blouin, Paul Bouchard, Konstantinos Fytas, Maryline Castello, Blandine Nguegang Kamwa, Analysis of gold in rock samples using laser-induced breakdown spectroscopy: matrix and heterogeneity effects, Spectrochimica Acta Part. B. 134 (2017) 33–41. [24] S. Kapishnikov, D. Grolimund, G. Schneider, E. Pereiro, J.G. McNally, J. Als-Nielsen, L. Leiserowitz, Unraveling heme detoxification in the malaria parasite by in situ correlative X-ray fluorescence microscopy and soft X-ray tomography, Sci. Rep. 7 (2017) 7610. [25] A. Maruccu, W. Stankiewicz, Development of an XRF spectroscopy analytical method for determination in gold jewelry alloys, Gold. Technol. 24 (1998) 14–22. [26] V. Honkimaki, K. Hämäläinen, S. Manninen, Quantitative X-ray fluorescence ¨ analysis using fundamental parameters: application to gold jewelry, X-Ray Spectrom. 25 (1996) 215–220. [27] Biwu Chu, Jiming Hao, Hideto Takekawa, Junhua Li, Kun Wang, Jingkun Jiang, The remarkable effect of FeSO4 seed aerosols on secondary organic aerosol formation from photooxidation of alpha-pinene/NOx and toluene/NOx, Atmos. Environ. 55 (2012) 26–34. [28] Qi Fan, Jing Lan, Yiming Liu, Xuemei Wang, Pakwai Chan, Shaojia Fan, Yingying Hong, Yexin Liu, Yanjun Zeng, Guixiong Liang, Yerong Feng, Diagnostic analysis of the sulfate aerosol pollution in Spring over Pearl River delta, China, Aerosol Air Quality Res. 15 (1) (2015) 46–57. [29] Haihan Chen, Alexander Laskin, Jonas Baltrusaitis, Christopher A. Gorski, Michelle M. Scherer, Coal fly ash as a source of iron in atmospheric dust, Environ. Sci. Technol. 46 (2012) 2112–2120. [30] Yong Peng Tong, Ai Guo Li, C.A.I. YingWen, Xin Bo Ni, Yuan Xun Zhang, Ji Qui Wang, Pan Ling Guo, Xiao Lin Li, Gui Lin Zhang, Mossbauer study of atmospheric aerosols of Shanghai, Environ. Sci. Technol. 35 (2001) 1432–1436.
84
Contents lists available at ScienceDirect
Optik journal homepage: www.elsevier.com/locate/ijleo
Original research article
Quantitative analysis of Fe and detection of multiple elements in the coal ash by laser-induced breakdown spectroscopy
T
⁎
Ruosong Zhua,b, Yuzhu Liua,b, , Qihang Zhanga,b, Fengbin Zhoua,b, Feng Jinc, Wenyi Yina,b, Xinfeng Zhaoa a
Jiangsu Key Laboratory for Optoelectronic Detection of Atmosphere and Ocean, Nanjing University of Information Science & Technology, Nanjing 210044, PR China b Jiangsu Collaborative Innovation Center on Atmospheric Environment and Equipment Technology (CICAEET), Nanjing 210044, PR China c Advanced Technology Core, Baylor College of Medicine, Houston, TX 77030, USA
A R T IC LE I N F O
ABS TRA CT
Keywords: Laser-induced breakdown spectroscopy Coal ash Quantitative analysis Fe Aerosols Internal standard method
Sulfates produced by the reaction of metal oxides in coal ash with the acid gases in the atmosphere are the main causes of haze-fog formation. In this study, laser induced breakdown spectroscopy(LIBS) was used for elemental analysis in coal ash. A new method was adopted to conduct an accurate qualitative analysis of the four elements (Al, Ca, Cu and Fe) that easily form sulfates in coal ash. An internal standard method was used to quantitatively analyze the typical Fe element of the four elements with a calibration curve that had a linear correlation coefficient (R2) of 0.986. In order to test the accuracy of the curve, three kinds of coal ash with unknown composition were selected and analyzed by LIBS and X-ray fluorescence spectrometry (XRF). The relative differences of the two methods were around 7.42%, 3.37% and 4.34%, respectively, which are all in the acceptable range. The experimental results indicate that LIBS can be employed for the rapid detection and analysis of metal elements in coal ash and provide a new classification method for coal ash based on the content of Fe element.
1. Introduction Coal ash, as a mineral dust, is the main component of a variety of metal oxides. It is the product of the complete burning of coal. Since the Second Industrial Revolution, coal, as a significant energy material, were widely used in people's production and life. At the same time, a large amount of mineral dust (coal ash) from coal combustion were released into the atmosphere, reacting with the acid gases in the atmosphere to form sulfates [1], which forms a haze-fog in the atmosphere and brings great threat to human health, Several significant air pollution events happened due to coal ash, such as the Great Smog of London [2], the Yokkaichi asthma incident [3] and the Belgian Meuse Valley incident [4], and all caused a large number of fatalities. Till now, there are still a lot of developing countries in the world which have faced the similar environmental challenge such as China [5], India [6], Iran [7] and so on. Therefore, there is urgent need for developing sufficient tools to detect haze-fog so that timely actions may be taken to prevent more people from harms. We propose the rapid detection and analysis of sulfate-forming elements in coal ash, that is believed to be the main cause of haze-fog. Laser induced breakdown spectroscopy (LIBS) [9] is an element detection technique developing in recent years. Due to its advantages of real-time, fast, non-contact and simultaneous detection of multiple elements, LIBS has been widely applied on detection
⁎
Corresponding author. E-mail addresses: [email protected], [email protected] (Y. Liu).
https://doi.org/10.1016/j.ijleo.2018.05.035 Received 8 February 2018; Received in revised form 3 April 2018; Accepted 10 May 2018 0030-4026/ © 2018 Elsevier GmbH. All rights reserved.
Optik - International Journal for Light and Electron Optics 169 (2018) 77–84
R. Zhu et al.
Fig. 1. Schematic diagram of the LIBS setup.
and analysis of elements in soils [10–15], aerosols [16–20], liquid [21,22] and rocks [23]. It has become an important medium in the field of environmental monitoring. In this article, seven kinds of coal ash samples from a steel company were detected based on laser-induced breakdown spectroscopy. The qualitative analysis of four elements Al, Ca, Cu and Fe, which are easy to form sulfates, was carried out. The Fe content was chosen as an example for quantitatively analysis and a calibration curve was obtained. Three kinds of samples with unknown composition were selected to test the predictive ability of the curve. In addition, it is proposed that the content of Fe element in coal ash can be used to provide a new method for the classification of coal ash.
2. Experimental 2.1. Experimental setup The schematic of the LIBS experiment is shown in Fig. 1. The laser used in the experiment was a Q-switched Nd-YAG laser, which was operated at a fundamental wavelength of 1064 nm. The maximum energy is 600 mJ in a single laser pulse, and the pulse energy for the employed laser beam in the current measurement is around 100 mJ per pulse with 10 ns duration at a frequency of 5 Hz. The laser beam was focused onto the sample surface using a focusing lens (f = 150 mm), of which the irradiation energy was collected with a fibre-optical probe. The emission signal from the plasma was transferred via a fiber to a spectrometer system. The spectrum was recorded on a personal computer, and the PLSUS software was utilized to identify emission lines and presented the possible elements according to the spectrum. The effective spectral resolution of this spectrometer system was around 0.03 nm, depending on the wavelength. In order to increase the stability and reduce the standard deviation of the spectral intensities, 10 measured spectra were averaged. The spectrometer and wavelength shift were calibrated via the pure metal sample.
2.2. Sample preparation In this experiment, seven kinds of coal ashes from a steel company were prepared as samples, which were labeled with Sample1#, Sample-2# to Sample-7#, respectively. The accurate elemental concentration was obtained by X-ray Fluorescence Spectrometry [24–26] (As shown in Table 1). Since the sample is powder, in order to obtain a better LIBS signal, the tablet machine was used to press the coal ash into coal lump of 10 mm in diameter and 5 mm in thickness.
78
Optik - International Journal for Light and Electron Optics 169 (2018) 77–84
R. Zhu et al.
Table 1 Chemical composition of coal ash samples(Reproducibility Critical Difference < 0.80%). Mass%
Si
S
Al
P
Fe
Na
K
Mn
Mg
Cu
Ca
Ti
Sample-1# Sample-2# Sample-3# Sample-4# Sample-5# Sample-6# Sample-7#
20.923 21.329 23.284 22.454 21.903 21.445 19.341
0.807 0.618 0.060 0.205 0.336 0.480 1.085
14.430 13.345 16.370 16.725 17.195 14.662 14.296
0.297 0.340 0.269 0.229 0.317 0.341 0.274
4.511 2.598 8.320 6.867 7.788 3.224 4.218
1.009 1.112 0.446 0.430 0.367 1.025 0.890
1.211 1.259 0.767 0.807 0.509 1.206 1.222
0.056 0.036 0.110 0.113 0.136 0.043 0.050
1.052 1.059 0.533 0.614 0.487 0.934 1.469
0.014 0.013 0.016 0.018 0.021 0.014 0.015
3.684 2.916 1.794 2.037 1.837 2.767 4.458
0.754 0.711 0.875 0.930 0.975 0.832 0.905
3. Results and discussion 3.1. Qualitative analysis of coal ash Fig. 2 shows the LIBS spectral line of the wavelength range of 200nm∼800 nm for the sample. As shown in, the figure, all of the metal elements and some non-metallic elements have been detected by the LIBS experiment. S element was not detected because, the characteristic lines of S element are mainly concentrated in the infrared band and beyond the scope of this experiment. Due to the uncertainty of spectral analysis and wavelength shift phenomenon, it is difficult to qualitative analyze the element accurately. In order to solve this problem, four kinds of high-purity elemental Fe, Ca, Al and Cu were selected for the reference experiment from a chemical company. Under the same experimental conditions, the measured four kinds of single-line spectra were compared with the corresponding wavelengths in the NIST Atomic Spectral Database [8], and all the spectra in the experiment were corrected according to the error of the wavelength. At this point, the spectrum of pure sample can be aligned with the coal ash sample spectrum, and the element can be identified when the characteristic spectrum in the simple one is aligned with the spectrum in the sample. Fig. 3 shows the spectrum of sample-4# contrast to the pure Al, Ca, Cu and Fe, respectively. Characteristic peaks of Al at 308.2 nm, 309.21 nm, 394.418 nm and 396.152 nm in the reference experiment of Al sample were observed and were used to calibrate the wavelength shift for the observed peaks of coal ash sample-4#. Similarly, characteristic peaks at 442.748 nm, 443.778 nm and 445.495 were chosen for Ca; Cu has characteristic peaks at 393.377 nm and 396.845 nm and Fe has characteristic peaks at 610.269 nm, 612.278 nm, 614.258 nm, 616.238 nm and 714.816 nm.
3.2. Quantitative analysis of Fe via internal standard method For the rapid detection of element of coal ash, quantitative analysis is also realized in the experiment. For these four interest elements, Fe content was chosen as the example for quantitatively analysis. The quantitative analysis formula of laser induced breakdown spectroscopy is Lomakin-Scheibe formula: I = aCb
(1)
where I is the observed intensity of the spectral line, a is the experiment constant, C is the concentration of the objective element, and b is the self-absorption coefficient. Since no visible self-absorption phenomenon can be found from the sample. The self-absorption coefficient can be ignored, b = 1. The corresponding equation is then: I = aC
(2)
In this experiment for quantitatively analysis of Fe, Al was selected as the internal standard element because of its high content and close to mass fraction in each sample. Several analytical lines such as Al I 308.2 nm, Al I 309.21 nm, Al I 394.418 nm and Al I 396.152 nm were selected. And the equation above was changed to: ∑(IFe/IAl) = aFeCFe/aAlCAl
(3)
Further, the Eq. (3) can be simplified to: I* = AC
(4)
*
Where I is the relative intensity of spectral lines of Fe, A is a constant which equals aFe/aAlCAl, and C is the concentration of Fe in the coal ash. As demonstrated in Eq. (4), the concentration of Fe is taken as the independent variable, and Σ (IFe / IAl) is used as the dependent variable while fitting a model to establish the calibration curve. As can be seen from the Fig. 4, linear correlation coefficients (R2) of the relative intensity versus the concentration of Fe is 0.986. It means that the intensity of Fe in the LIBS spectrum of coal ash is proportional to the concentration of the corresponding Fe in coal ash. Thus, we concluded that the Fe concentration of the coal ash can be determined by analyzing the spectral lines of Fe with LIBS. The possible saturation with increasing laser energy and an increasing elemental concentration is very important in the 79
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Fig. 2. LIBS spectrum of coal ash(sample-4#) ranged from 200 to 800 nm.
calibration process. For the present measurement, the laser power is kept the same for all the different concentration. And for the prepared concentration from 2.598% to 8.320% in the current measurement, no significant saturation effect is observed. The Fe element in the atmosphere is mainly discharged by the metallurgical enterprises. And there is the following reaction between Fe2O3 and the acid gas in the atmosphere[27–30]: Fe2O3 + H+ + H2O → Fe2+ + Fe3+
(5) 80
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Fig. 3. Spectral comparison of sample-4# (coal ash) and four elementary substances of (a) Al, (b) Ca, (c) Cu and (d) Fe at different range.
Therefore, the resulting iron ions combine with sulfate to form sulfates. The content of Fe element can also reflect part of the S content in the atmosphere. Through the real-time, accurate detection and treatment of Fe content in coal ash, the content of sulfate in the atmosphere can be effectively controlled, so that the occurrence of haze can be controlled. The same applies to other sulfate-forming elements. The coal ash used in this paper is the ash left after the complete combustion of the coking coal and the coal injection which are made by the modern coal blending process, and therefore they are uniformly mixed (Note: metallurgical coke is made by dry distillation of coking coal). In blast furnace ironmaking, the ash content of the coal injection should be as low as possible and is lower than the ash content in 81
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Fig. 3. (continued)
the metallurgical coke. Ash content is directly related to the content of metal element. In Table 1, it also can be found that most relevant metals (such as Al, Fe, Mn, Cu and Ti) have a higher content in metallurgical coke than coal injection. In this article, Fe is used as an example for quantitative analysis. The results are shown in Fig. 4, the content of Fe is linear overall, which in coal ash made from coal injection is mainly concentrated in the dash circle and in metallurgical coke focus on the dash dot circle. Through this curve, coal ash can be sorted preliminarily and quickly.
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Fig. 4. Calibration curve for Fe in the coal ash (The error bars indicate the uncertainties of spectral calibration causes fluctuations in Fe elements during quantitative analysis).
3.3. Calibration curve testing In order to test the accuracy of the calibration curve, three kinds of samples with unknown composition were prepared as unknown samples from the Steel Company, which were labeled with Unknow-a, Unknow-b and Unknow-c, respectively, and tested under the same experimental conditions. After the LIBS detection is completed, the samples are detected for the exact concentration by XRF for reference. According to the comparison, the relative differences were calculated and listed in Table 2. The contents of Fe measured by XRF were 4.04%, 5.93% and 5.30%. The Fe contents measured by LIBS were 3.74%, 6.13% and 5.53%. The relative differences of the two methods were 7.42%, 3.37% and 4.34%, respectively. The causes of the differences are: the lack of resolution of the spectrometer, the instability of the laser, and the impact of background noise. Compared with well-established technique XRF, LIBS can detect rapidly for the applied laser with 10 times average, the detection time is around 2 s for one spectrum 2 s resolution. And in the case of the sample does not require pretreatment, to obtain more accurate experimental results. 4. Conclusion Almost elements such as Si, Al, P, Fe, Na, K, Mn, Mg, Cu, Ca and Ti were found in coal ash by LIBS. Among them, four characteristic elements Al, Cu, Fe and Ca, were further accurately analyzed qualitatively. The internal standard calibration method was used to quantitatively analyze the Fe content in different samples. The linear correlation coefficient between relative intensity and Fe concentration was 0.986. In addition, three unknown samples were selected to test the accuracy of the resulting calibration curve. The relative difference between the predicted value of the curve and the accurate value measured by X-ray fluorescence spectrometry were within the acceptable range. The experimental results show that the content of Fe in different kinds of coal ash is distinguished, and the distribution of Fe is linear. The calibration curve can be a preliminary classification of coal ash and accurate detection of Fe element content. Thus, LIBS Table 2 Measurement of Fe Element Content in Unknown Samples by Two Methods. MASS%
Element
LIBS experimental value
XRF experimental value
Relative difference
Unknow-a Unknow-b Unknow-c
Fe Fe Fe
3.74% 6.13% 5.53%
4.04% 5.93% 5.30%
7.42% 3.37% 4.34%
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can be used to quickly detect the discharge of coal ash containing and track its origin via the content of Fe element. For others it is easy to form sulfates metal elements, this method can also be used in the establishment of the calibration curve of the element after its quantitative analysis. Acknowledgments This work was supported by the National Key R&D Program of China (2017YFC0212700), “Six Talent Peaks” project in Jiangsu Province (Grant No. 2015-JNHB-011) and the Innovation practice training plan for college students of Hefei Institute of Physical Science, Chinese Academy of Sciences (201717001061). References [1] Biwu Chu, Jiming Hao, Hideto Takekawa, Junhua Li, Kun Wang, Jingkun Jiang, The remarkable effect of FeSO4 seed aerosols on secondary organic aerosol formation from photooxidation of a-pinene/NOx and toluene/NOx, Atmos. Environ. 55 (2012) 26–34. [2] https://en.wikipedia.org/wiki/Great_Smog_of_London. [3] https://en.wikipedia.org/wiki/1930_Meuse_Valley_fog. 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