Energy Fuels 2010, 24, 199–204 Published on Web 09/15/2009
: DOI:10.1021/ef900556s
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Evaluation of a Mg-Based Additive for Particulate Matter (PM)2.5 Reduction during Pulverized Coal Combustion† Yoshihiko Ninomiya,*,‡ Qunying Wang,‡ Shuyin Xu,‡ Tsuyoshi Teramae,§ and Isao Awaya
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‡ Department of Applied Chemistry, Chubu University, 1200 Matsumoto-cho, Kasugai, Aichi 487-8501, Japan, §Coal and Environment Research Laboratory, Idemitsu Kosan Company, Limited, 3-1 Nakasode, Sodegaura, Chiba 299-0267, Japan, and Research Laboratory, Taihokohzai Company, Limited, 9 Kirihara-cho, Fujisawa, Kanagawa 252-0811, Japan
Received May 30, 2009. Revised Manuscript Received August 24, 2009
This paper aims to evaluate the addition of a Mg-based additive to coal on the emission/reduction of particulate matter (PM) during coal combustion. Four pulverized coals with different mineralogical properties were investigated. Each of them was mixed with Mg-based additive and combusted at 1723 K in a lab-scale drop tube furnace (DTF). The results indicate that the Mg-based additive tested here has a pronounced impact on particle size distribution of PM and the morphologies of individual ash particles. For all of the coals tested here, the addition of the Mg-based additive increased the coarse ash fraction and substantially reduced the amount of ash particles smaller than 2.5 μm (PM2.5). This is because the Mgbased additive is able to reduce the ash melting point via the formation of low-melting eutectic compounds, which promote the coalescence among sub-micrometer mineral particles. The effect of the Mg-based additive on PM2.5 reduction also depends upon the properties of the original minerals present in the coal. The particle size distributions and concentrations of PM10 were also compared to that predicted by an advanced coalescence and fragmentation model developed here. The comparisons indicate that the model can satisfactorily predict ash formation and properties, taking into account both coalescence of included minerals and fragmentation of excluded minerals at high temperature.
altered.7-9 The agglomeration extent of small mineral particles can also be greatly affected by the presence of molten species among ash particles.10-12 Following this idea, it is inferable that the emission of PM2.5 could be changed/reduced by the addition of a suitable additive during coal combustion. Study on this issue is however very limited to date. Our previous studies have proven that Mg- or Ca-based additives are available to reduce PM2.5 emission during coal combustion. In particular, the Mg-based additive exhibits good performance compared to others.12 To further understand the interaction between Mg and inherent minerals during coal combustion, four coals bearing distinctively different mineralogical properties were further tested in this study. Each coal sample was mixed with a Mg-based chemical. The resulting mixtures were burnt in a lab-scale DTF at 1723 K. The effects of Mg addition on ash formation and properties are discussed. Changes in the emission of ash particles smaller than 1 μm (PM1) and 2.5 μm (PM2.5) are also investigated. Finally, an advanced coalescence and fragmentation model was developed to predict the PM10 formation upon the addition of Mg during coal combustion.
1. Introduction Particulate matter (PM) emission from coal combustion is a major source contributing to air pollution.1-4 The existing air control devices are not capable of efficiently capturing ash particles in a diameter range of 0.1-2 μm. Therefore, the emission of particles smaller than 2.5 μm (i.e., PM2.5) has been causing severe damage to the environment and human health, especially in the developing countries, such as China and India, where air control devices are insufficient in power generation plants.5,6 To effectively reduce coal-combustiondriven PM2.5 emission, further knowledge of mineral transformation at high temperatures must be attained. Both field and laboratory studies have found that, by adjusting the components in coal minerals, especially the contents of basic elements, including Ca, Fe, and K, the fouling and slagging properties of resulting ash can be greatly † Presented at the 2009 Sino-Australian Symposium on Advanced Coal and Biomass Utilisation Technologies. *To whom correspondence should be addressed. E-mail: ninomiya@ isc.chubu.ac.jp. (1) Sloss, L. L. IEA Clean Coal Centre, London, U.K., Oct 2004. (2) Sarofim, A. F.; Lighty, J. S.; Eddings, E. G. Prepr. Symp.-Am. Chem. Soc., Div. Fuel Chem. 2002, 47, 618–621. (3) Nelson, P. F. Energy Fuels 2007, 21, 477–484. (4) Lighty, J. S.; Veranth, J. M.; Sarofim, A. F. J. Air Waste Manage. Assoc. 2000, 50, 1565–1618. (5) Nalbanian, H. IEA Coal Research, London, U.K., Nov 2004. (6) Soud, H. N.; Mitchell, S. C. IEA Coal Research, London, U.K., July 1997. (7) Huggins, F. E.; Kosmak, D. A.; Huffman, G. P. Fuel 1981, 60, 577–584. (8) Huffman, G. P.; Huggins, F. E.; Dunmyre, G. R. Fuel 1981, 60, 585–597. (9) Gupta, S. K.; Wall, T. F.; Creelman, R. A.; Gupta, R. P. Fuel Process. Technol. 1998, 56, 33–43.
r 2009 American Chemical Society
2. Experimental Section 2.1. Sample Preparation and Analysis. Four bituminous coals collected from different countries and marked as A-D were tested here. They were pulverized and dried prior to use. The (10) Wang, Q.; Zhang, L.; Sato, A.; Ninomiya, Y.; Yamashita, T. Fuel 2008, 87, 2997–3005. (11) Wang, Q.; Zhang, L.; Sato, A.; Ninomiya, Y.; Yamashita, T. Fuel 2009, 88, 150–157. (12) Ninomiya, Y.; Wang, Q; Xu, S.; Mizuno, K.; Awaya, I. Energy Fuels 2009, 23, 3412–3417.
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: DOI:10.1021/ef900556s
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Table 1. Coal Proximate and Ultimate Properties (wt %) analysis
moisture ash volatile matter fixed carbon C H N S O
coal A
coal B
coal C
coal D
Proximate Analysis (Air Dried) 2.7 2.92 4.9 13.0 13.2 11.8 42.4 33.8 31.6 41.9 50.8 51.7
4.2 11.6 32.2 52.0
Ultimate Analysis (Dry Ash Free) 78.3 78.8 81.4 6.2 4.9 4.3 1.0 2.1 4.9 0.4 0.5 0.9 14.1 13.7 11.5
81.0 4.9 1.8 0.7 11.6
Figure 1. Cumulative particle size distribution of original minerals in raw coals, determined by CCSEM.
Table 2. Ash Compositions Analyzed by XRF (wt %) oxide
coal A
coal B
coal C
coal D
Table 3. Mineralogical Properties of Four Raw Coal Samples (wt %)
SiO2 Al2O3 Fe2O3 CaO MgO Na2O K2O TiO2 P2O5 SO3
66.59 25.15 1.94 2.44 0.90 0.74 0.17 1.74 0.04 1.25
52.96 22.83 11.43 2.6 2.07 0.35 0.58 1.17 0.65 2.58
46.21 39.31 3.54 3.34 0.31 0.15 0.74 1.44 0.43 1.52
45.08 19.70 4.96 16.27 0.87 0.09 0.37 1.43 0.38 5.00
categories
coal A
coal B
coal C
coal D
Si-Al Si-rich Ca-rich Ca-Al-Si Fe-rich Fe-S Fe-Al-Si Ca-Mg
68.5 23.5 0 2.3 0 0.8 1.4 1.5
62.5 10.0 2.5 1.7 2.6 5.2 4.0 2.8
76.2 7.0 4.1 1.8 0 4.5 1.0 0.9
47.0 13.0 25.4 4.7 1.1 3.8 1.4 1.6
Subsequently, the ash particles were size-segregated by a cyclone and a 13-stage low-pressure impactor (LPI) in sequence. The poly Teflon filters (PTFs) were used as substrates for particle deposition in each stage of the LPI.15 The bulk elemental composition of particles collected on an LPI stage was quantified using XRF. SEM (JEOL JSM-5600) with energy-dispersive X-ray spectroscopy (EDAX) was used to observe particle morphology and quantify the elemental composition of individual particles larger than 2.5 μm. In addition, computer-controlled SEM (CCSEM, JEM5600) was used for chemical speciation of the ash particles deposited on a LPI stage through analyzing more than 1000 individual particles. The compound classification categories are the same as those developed elsewhere.16 2.3. Prediction on Liquidus Formation during Coal Combustion. The commercial thermodynamic equilibrium software package, FactSage 5.2, was used to theoretically estimate the liquidus formation during coal combustion, especially in the case when additives are mixed with coal. The database used for calculation includes real gas, non-ideal liquid, and solid solutions. Coal properties (C, H, and O contents) and its original mineral matter composition in terms of oxides were used together as solid input. An oxidizing gas atmosphere with an air/fuel ratio of 1.35 at 1 atm was used as the gas input. As stated above, the added Mg-based additive was assumed to be a solid species embedded/included in the char rather than remaining separately as excluded particles from the coal matrix. Calculations were carried out at 1723 K.10,11,15,17
proximate and ultimate properties of the raw coals are shown in Table 1. Elemental compositions of the low-temperature ashes (LTAs) of four raw coals generated at around 150 °C in a plasma reactor were determined by X-ray fluorescence spectrometry (XRF), as summarized in Table 2. As can be seen, both coals A and C are rich in SiO2 and Al2O3, whereas CaO and Fe2O3 are rather low in these two coals. The interaction between added Mg and inherent Ca, Fe, Al, and Si in coal may occur during coal combustion. A Mg-based additive was mixed with coal at a mass fraction of 5.0 wt % on a total mineral basis for PM reduction. It is watersoluble and, hence, was loaded on coal through impregnation rather than physically mixing. Coal was initially soaked in the aqueous solution of Mg at a volume ratio of 1:3 of coal to solution. Subsequently, the resulting slurry was slowly evaporated at 20 °C under vacuum in a rotary evaporator for around 2 h. Eventually, the residue was dried at 60 °C for around 4 h with N2 purge. Scanning electron microscopy (SEM) observation indicated an extremely high dispersion of Mg on the impregnated coal surface, possessing the chemical form of MgO and an average particle size in the sub-micrometer range or less. Because of the intimate contact between Mg and the coal particle, the Mgbased additive in the impregnated coal was considered as an included species rather than excluded grains that have poor contact with the coal particle because of the physical mixing.13 2.2. Combustion Condition, Ash Particle Sampling, and Characterization. Coal combustion was performed in a lab-scale DTF of 50 mm in inner diameter and 2000 mm in length, the schematic of which has been described in detail elsewhere.14 All of the coal samples were combusted at 1723 K in air. The feed rate was about 15 g/h. The residence time of coal particles in the combustion zone is estimated to be about 2.5 s.15 Each run was carried out around 3 times, and the average result was discussed throughout this paper. An iso-kinetic sampling system was applied for ash collection. A water-cooled nitrogen-quenched probe was adopted to isokinetically suck a portion of ash particles in the furnace.
3. Results and Discussion 3.1. Mineralogical Properties of Raw Coals. The mineralogical properties of four raw coals were determined by CCSEM. The particle size distributions of the original minerals are plotted in Figure 1. As can be seen, coal A is rich in fine mineral particles, which partition comparably between included and excluded fractions. On the other hand, coal D is rich in coarse mineral particles, which are mostly
(13) Zhang, L.; Sato, A.; Ninomiya, Y.; Sasaoka, E. Fuel 2003, 82, 255–266. (14) Zhang, L.; Sato, A.; Ninomiya, Y. Fuel 2002, 80, 1499–1508. (15) Wang, Q.; Zhang, L.; Sato, A.; Ninomiya, Y. Proc. Combust. Inst. 2009, 32, 2701–2708.
(16) Wang, Q.; Zhang, L.; Sato, A.; Ninomiya, Y.; Yamashita, T. Energy Fuels 2007, 21, 756–765. (17) Zhang, L.; Ninomiya, Y.; Yamashita, T. Fuel 2006, 85, 194–203.
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Figure 2. Effects of Mg addition on the particle size distribution of PM.
excluded from the coal matrix. The minerals in coals B and C are rather similar in terms of the particle size distribution of the included minerals. The main mineral species in the four coals are listed in Table 3. Clearly, the refractory elements including Si and Al are mainly present in Si-Al and Si-rich, irrespective of the coal name. The amounts of Fe and Ca are low in coal A. Fe is mainly present as Fe-S and Fe-rich in coal B and Fe-S in coals C and D. Ca is mainly present as Ca-rich in coal D. 3.2. Effect of Mg Addition on PM Emissions. Figure 2 illustrates the influence of Mg addition on the particle size distribution of PM emitted from four coals. As can be seen, the Mg-based additive tested here noticeably affected ash particle size distribution. Its effect however varies with coal. For coals A and B, particles smaller than 7 μm in size were transferred into coarse particles upon addition of the Mgbased additive. The emission of both PM1 and PM2.5 was thus reduced. In the case of coal C, the releases of particles smaller than 1 μm were reduced, while the amounts of those ranging from 1 to 3 μm were however not changed. In the case of coal D, the added Mg additive reduced PM2.5 emission, while it had little effect on the reduction of PM1. These variations with coal are mainly caused by the difference in the amounts of original fine included minerals and excluded Ca-rich species in the four coals,16,17 as shown in Figure 1 and Table 3. The effect of Mg addition on the emission of fine PM is to a certain extent determined by the properties of the original minerals, including size and chemical form. Comparisons of PM1 and PM2.5 amounts emitted from combustion of raw coal and coal mixed with Mg additive are further summarized in Figure 3. Clearly, the Mg-based additive tested reduced emissions of PM1 and PM2.5. This is because the content of liquidus formed during combustion was changed, which is one of the key factors controlling mineral particle agglomeration at high temperatures.10-12 The liquidus amount in each case, as predicted by FactSage in Table 4, supports this hypothesis. The addition of Mgbased additive to coal evidently increases the liquidus amount. As a result, all of the PM emissions, except PM1 from coal D, were inhibited. The little change in PM1
Figure 3. Comparison of PM1 and PM2.5 emissions from combustion of coal added with and without Mg-based additive. Table 4. Liquidus Amount Predicted by FactSage (wt % on the Total Ash Basis) without Mg addition with Mg addition
coal A
coal B
coal C
coal D
72.1 95.8
48.9 66.4
41.9 62.2
68.9 85.6
emission from coal D implies that the liquidus formation may not be the only factor affecting the formation of the smallest ash fraction. PM1 emission is very complicated, because it is mainly influenced by vaporization rather than coalescence/fragmentation of minerals. Morphologies of ash particles collected from the combustion of four coals mixed with Mg are shown in Figure 4. Irrespective of the coal name, combustion of a coal with added Mg resulted in the formation of a large amount of aggregates when compared to the combustion of raw coal alone. A portion of fine ash particles on the sub-micrometer scale obviously adhered to the surface of coarse particles. As a result, the overall ash size was increased. However, in the case of coal C mixed with Mg additive, the fly ash particles are not fully molten and, hence, less aggregate was formed. 3.3. Model Simulation. According to the SEM observations in Figure 4, the Mg-based additive tested here is 201
Energy Fuels 2010, 24, 199–204
: DOI:10.1021/ef900556s
Ninomiya et al.
Figure 4. SEM images of PM generated by combustion of coal added with and without Mg-based additive.
capable of adhering to refractory mineral particles to promote their agglomeration. This concept is further depicted in Figure 5. Mineral agglomeration extent directly determines the particle size distribution of ash. The coalescence/fragmentation model developed by us previously was used to predict the particle size distribution of PM10 during the combustion of coal added with and without Mg. The transformation of included and excluded mineral fractions was considered separately in this model. Note that vaporization and condensation of organically bound metals are not considered here because of their relatively low amounts in high-rank coals.11
A Poisson distribution in eq 1 is introduced to describe the random coalescence and fragmentation among inherent mineral species Pðk; λÞ ¼
e -λ λk ðk ¼ 0, 1, 2, 3:::Þ k!
ð1Þ
where λ refers to an average coalescence number of included mineral particles or an average fragmentation number of excluded mineral particles. The k denotes the average number of occurrences of coalescence or fragmentation of mineral particles. The average fragmentation number of excluded minerals (λEX) is estimated from the experiments 202
Energy Fuels 2010, 24, 199–204
: DOI:10.1021/ef900556s
Ninomiya et al.
Figure 5. Agglomeration modes of the included minerals under the effect of Mg addition.
Figure 6. Comparison of particle size distribution of PM10 determined by the experiment to that of the model prediction. The symbols denote those determined by experiments, while the curves refer to modeling prediction.
of corresponding pure mineral species. For example, the excluded Si-rich and Si-Al species possess a fragmentation number of 1.18 The excluded Ca- and Fe-rich fraction numbers are however 3.19,20 On the basis of the curve-fitting results, the average fragmentation number of excluded minerals here is set as 2. The average coalescence number of included minerals (λIN) is also determined by curve fitting. Figure 6 depicts the particle size distributions of PM10 observed during combustion of coals A and D and their comparison to those predicted by the model. Clearly, the model developed is capable of predicting ash formation, especially for the particles smaller than 10 μm. Both coalescence of included minerals and fragmentation of excluded minerals govern PM emission. The relationship between the liquidus amount
Figure 7. Relationship between the predicted liquidus content in ash and the average coalescence number of included minerals in four coals used at 1723 K.
(18) Zhang, L.; Wang, Q.; Sato, A.; Ninomiya, Y.; Yamashita, T. Energy Fuels 2007, 21, 766–777. (19) Yan, L; Gupta, R. P.; Wall, T. F. Fuel 2002, 81, 337–344. (20) Yan, L; Gupta, R. P.; Wall, T. F. Energy Fuels 2001, 15, 389–394.
and average coalescence number of included minerals is further plotted in Figure 7. With the liquidus amount increasing, the average coalescence number of minerals in 203
Energy Fuels 2010, 24, 199–204
: DOI:10.1021/ef900556s
Ninomiya et al.
4. Conclusions The Mg-based additive tested in this study is a promising promoter of ash agglomeration and, therefore, has the potential to significantly reduce PM emissions from coal combustion. In particular, emissions of PM1 and PM2.5 can be greatly reduced because of the formation of liquidus and promotion of ash particle coalescence upon Mg addition. The coalescence/fragmentation model developed in this study can reliably predict the PM2.5 emissions during combustion of coal added with and without Mg. When the elemental compositions of the original minerals are only taken into account, the average coalescence number can be attained from FactSage prediction of the liquidus amount.
Figure 8. Comparison of the experimentally determined PM2.5 reduction rate to that predicted by the model.
Acknowledgment. This work was partially supported by New Energy and Industrial Technology Development Organization (NEDO), Japan for “Leading Study on Environmental Pollutant Control Technology, Study on reduction of PM2.5 generated during the pulverized coal combustion” (2009), the grants for scientific research on priority areas (B) 20310048 from the Ministry of Education, Science, Sports and Technology, and the Steel Industry Foundation for the Advancement of Environmental Protection Technology in Japan.
both raw coal and coal mixed with Mg increases linearly. Figure 8 illustrates the comparison between the PM2.5 reduction extent observed experimentally and that predicted by modeling. Clearly, both experiments and simulation in this study prove that the Mg-based additive tested here is capable of improving the liquidus formation in ash and thus promoting coalescence among included mineral particles.
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