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Jun 23, 2014 - Fine Particle Emission from an Industrial Coal-Fired Circulating. Fluidized-Bed Boiler Equipped with a Fabric Filter in China. Zhifeng ...
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Fine Particle Emission from an Industrial Coal-Fired Circulating Fluidized-Bed Boiler Equipped with a Fabric Filter in China Zhifeng Zhao,* Qian Du, Guangbo Zhao, Jianmin Gao, Heming Dong, Yang Cao, Qiang Han, Pengfei Yuan, and Lipeng Su School of Energy Science and Engineering, Harbin Institute of Technology, 92, Xidazhi Street, Harbin 150001, People’s Republic of China ABSTRACT: In this work, the PM2.5 emission characteristics, the comparison of the morphological characteristics, and the sizeclassified elemental composition of PM2.5 are determined experimentally before and after the fabric filter at an industrial circulating fluidized-bed boiler. Measurement in situ was taken with an electrical low-pressure impactor equipped with a two-stage dilution sampling system. The morphological characteristics and size-classified elemental composition were performed by scanning electron microscopy and energy-dispersive X-ray analysis. The size distribution was measured in the range from 0.029 to 2.38 μm. Before and after the fabric filter, the number size distribution displays a bimodal distribution. The fabric filter total removal efficiency of PM2.5 without pulse back blowing cleaning is 99.449%, and that with pulse back blowing cleaning can reach 99.029%. The minimum size-classified removal efficiencies appear in the particle size range from 0.1 to 1 μm. In this size range, the fabric filter size-classified removal efficiencies are 99.15−99.59%, and the pulse back blowing cleaning can result in the lowest value of 98.46%. The morphological characteristics before and after the fabric filter are nearly the same, except channels 3−5. Sodium, potassium, and zinc show enrichment with decreasing particle size; calcium and titanium show clear enrichment with increasing particle size; however, silicon, aluminum, magnesium, iron, and manganese show no enrichment with particle size variation. results,3 PM2.5 generated and emitted from coal-fired boilers is often rich in toxic compositions. In China, a grate-fired boiler is the most extensively used type of coal combustion industrial boilers, but more industrial circulating fluidized-bed (CFB) boilers are applied, because the CFB boiler can reduce NOx and SOx emissions. CFB combustion is different from grate combustion. In the process of fluidized-bed combustion, the particle temperature is lower and heat transfers more efficiently,4,5 which will result in its PM2.5 generation characteristics being quite different from those of grate combustion. Fabric filters (FFs) are widely equipped with utility boilers and industrial boilers in Australia, the U.S.A., South Africa, etc.6 Recently, in China, FFs were applied to remove particulate matter generated from some of the coal-fired utility boilers and industrial boilers to meet more strict requirements of environmental protection.7 McElroy et al.8 measured the particle size distribution (PSD) after six coal-fired utility boilers; a peak was shown at a particle diameter of about 0.1 μm. The existing sub-micrometer mode seemed to be a general character of coal combustion that derived from the vaporization−condensation process in the furnace. Nielson et al.9 researched on the combustion particle generation and emission from two full-scale coal-fired power plants; the results showed that the size of particles extends from 20 nm to 200 μm, with the largest mass contained in particles in the size range of 10−100 μm, and 50−80% of the stack fluegas particles are in the range of PM2.5. Fisher et al.10 found

1. INTRODUCTION Fine particles are the main environmental atmospheric pollutant in China. A fine particle is a particle with an aerodynamic diameter of less than 2.5 μm, namely, PM2.5, which can enter the respiratory tract through the mouth and nose into the alveolus region of the lungs. As a major type of environmental pollutant in China, PM2.5 is becoming a significant research topic.1,2 At present, the government of China has promulgated ambient air quality standards (GB3095-2012), which will be implemented in the year of 2016 and in which the upper limits of PM2.5 in the environmental atmosphere have been regulated, as shown in Table 1. Table 1. Upper Limits of PM2.5 and PM10 in Ambient Air Quality Standards upper limitsa serial number

pollutant

average time

first stage

second stage

unit

1

PM10 PM2.5

40 50 15 35

70 150 35 75

μg/m3

2

annual daily annual daily

a The first stage is implemented in natural conservation areas, landscape and famous scenery areas, and other special-protected areas, and the second stage is implemented in residential zones, zones of commerce and traffic mixed with residences, cultural zones, industrial zones, and rural zones.

Received: March 12, 2014 Revised: June 17, 2014 Published: June 23, 2014

Coal combustion is a significant source of PM2.5 in the environmental atmosphere. According to relational research © 2014 American Chemical Society

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operating normally and the testing load was relatively stabilized. Proximate and ultimate analyses of the fuel coal are in Table 2. Ash analysis of the fuel coal is given in Table 3. The samples were taken before and after the FF in situ, which represent PM2.5 generated from the ICFB boiler under non-controlled and controlled conditions, respectively. During the test, the bed temperature was approximately 870 °C. In comparison to earlier corresponding studies,14,15 the bed temperature (870 °C) is lower than the furnace box temperature (1127 °C) in the earlier corresponding studies. The boiler load and the gaseous pollutant emission concentrations were relatively stabilized, and the boiler combustion operation was not altered. The temperatures and speed samplings before and after FF were measured by a TH-880F computer-controlling multifunctional dustparallel-sampling device manufactured by Wuhan Tianhong Intelligent Meter Company. An electrical low-pressure impactor (ELPI) was used to measure the PM2.5 number and mass size distribution and take sizeclassified samples. The ELPI is able to monitor mass and number size distributions of aerosol particle sizes in the range from 30 nm to 10 μm,16,17 divided into 12 channels. For ELPI only, a single value of density was used, because the magnitude of density affects the mass concentrations by only a few percentage;18 therefore, the monitoring of the particle mass can be relatively accurate. Otherwise, the resolution time of ELPI is less than 5 s; therefore, it is able to measure the instantaneous volatilities of the PM concentration during the operations, such as the pulse back blowing of the FF. The particle size ranges of the first nine channels of ELPI have been shown in Table 4. As shown in Table 4, the measuring range of the nine channels of ELPI is from 0.029 to 2.38 μm; therefore, the results of the nine channels can represent PM2.5. A two-stage dilution system was used to decrease the PM concentrations and flue gas temperature from the boiler and in the stacks, of which the dilution ratio is approximately 1:90 in this test. The sampling system for PM2.5 is shown in Figure 2, which consists of an isokinetic sampling probe, a precut cyclone (it can cut off the particles more than 10 μm), the two-stage dilution, and two PM2.5 samplers. All of the pipelines in the sampling system were as short as possible to prevent particles from losing in the sampling process. In the process of measuring in situ, the pipe between the gas stack and the cyclone, the cyclone, the first-stage dilution, and the pipe between the cyclone and the first-stage dilution were heated by controllingtemperature heater layers to keep their temperatures consistent with the temperature of the flue gas in the stack, and the temperatures of stack gas before and after the FF were approximately 113 and 97 °C, respectively. The temperatures of the second-stage dilution, the air filter, and the ELPI are the environmental temperature, which was approximately 14 °C. Different sampling substrates were chosen on the basis of different analytical purposes. Clean non-porous polycarbonate substrates (radius of 25 mm) were for taking the size-classified samples to obtain the data of the PM2.5 number and mass size distributions; meanwhile, the samples would be used for energy-dispersive x-ray (EDX) analysis. Microstructure and trace element samples were taken on polycarbonate and Teflon substrates (radius of 47 mm), respectively. The fuel coal was taken regularly in the testing process. 2.2. Analytical Methods. A fraction of each polycarbonate substrate in ELPI 12 channels with PM2.5 size-classified samples was fixed onto aluminum stubs. The substrates were sprayed with 25 nm Au. The percent concentrations of elements (Si, Al, Mg, Ca, K, Na, Fe, Mn, Zn, and Ti) were measured with EDX microanalysis. Individual particle microstructures of PM2.5 on these substrates were analyzed with field emission scanning electron microscopy (FESEM) and thermionic emission scanning electron microscopy (TESEM), which were applied to take the micrographs of channels 1 and 2 before the FF and other channels, respectively.

different proportions of non-opaque solid sphere and cenosphere in fine particles (87 and 7.9%) and coarse particles (26 and 41%). Goodarzi11 researched that morphology of fine particulate matter emitted from a Canadian coal-fired power plant. The microstructural results showed that PM>10 emitted from the stack mainly contained fragments of char, small plerosphere, feldspar particles, and angular quartz, PM10 contained spheres and cenospheres, gypsum needles, and char particles, and PM2.5 were mostly composed of spherical aluminosilicates enriched on the surface with Ba, Ca, and Fe. Shendrikar et al.12 found that the PSD for most elements before the baghouse was bimodal, with the larger mode near 4−10 μm and the smaller mode near 0.08 μm or less. Nielson et al.9 found that the ashcontained elements were volatilized in the furnace and condense onto the surface of smaller particles in the process of chilling of the flue gas; these elements tend to have a high concentration in emitted particles because of the lower removal efficiencies of the smaller particles through the filter and scrubber. In China, relative studies on coal-fired particulate matter have started later since the 1980s. Yi et al.6 researched the size distributions of the number and mass, microstructure, and trace element size distribution of PM10 before and after the baghouse. Zhang et al.13 sampled from the dust hopper of the electric fields of the electrostatic precipitator (ESP), cyclone of the CFB boiler, and inlet of the desulfurization scrubber, indicating the size distribution, morphological characteristics, and element percent concentrations of samples. Obviously, most foreign and domestic studies are usually on the fly ash and PM10 generation and emission characteristics from the utility boiler; however, investigations on the PM2.5 generation and emission characteristics from an industrial boiler are relatively less to date, especially that from industrial circulating fluidized-bed (ICFB) boilers. This paper analyzes the PM2.5 generation and emission characteristics from a coalfired CFB boiler equipped with a FF in China, including PSDs, morphological characteristics, and chemical constitutes.

2. EXPERIMENTAL SECTION 2.1. Sampling Methods. Fuel coal from Heilongjiang province was combusted in a 40 ton/h industrial CFB boiler equipped with a FF, as shown in Figure 1. During the test period, the boiler was

Figure 1. Schematic of the ICFB boiler. 4770

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Table 2. Proximate and Ultimate Analyses of the Fuel Coal proximate analysis (wt %)

ultimate analysis (wt %)

Mar

Aar

Var

FCar

heating value, Qnet,ar (MJ/kg)

rank

Car

Har

Nar

Oar

Sar

6.90

49.36

23.48

20.26

12.48

bitumite

35.51

3.43

1.07

6.91

0.24

Table 3. Ash Analysis of the Fuel Coal composition

SiO2

Al2O3

Fe2O3

CaO

MgO

SO3

TiO2

K2O

Na2O

P2O5

wt %

53.57

37.98

5.17

0.11

0.22

0.13

1.47

0.46

0.22

0.31

Table 4. Particle Size Range of the Nine Channels of ELPI particle size range channel number

lower limit (μm)

upper limit (μm)

1 2 3 4 5 6 7 8 9

0.029 0.057 0.093 0.154 0.26 0.38 0.609 0.943 1.59

0.057 0.093 0.154 0.26 0.38 0.609 0.943 1.59 2.38

Figure 3. Current values of nine channels in ELPI during the test after the FF.

Figure 2. Sampling system for PM2.5.

Figure 4. Number size distribution of PM2.5 before and after the FF: (1) no dust cleaning, (2) dust cleaning maximum peak value, (3) dust cleaning general peak value, and (4) average. The results given are at 10% dioxygen in the standard temperature and pressure.

3. RESULTS AND DISCUSSION 3.1. Size Distribution and Concentration of PM2.5. PM2.5 emissions from an industrial circulating bed boiler were characterized before and after the FF in this research. Especially, it is focused on the influence of the pulse back blowing of the FF on PM2.5 emission characteristics. Figure 3 shows the current values of nine channels in the ELPI during the test after the FF. The levels of granulometries of nine channels in the ELPI are shown in Table 4. In Figure 3, there are seven current value peaks that are caused by the pulse back blowing of the FF. In this research, the current values are divided into several parts, as shown in Figure 3. Part 1

represents the no dust cleaning, which means there is no pulse back blowing of the FF. Part 2 represents the dust cleaning maximum peak value. Part 3 represents the dust cleaning general peak value. Part 4 represents the average values of the total current values in this research. The following studies are based on this division. Figures 4 and 5 show the number and mass concentration distributions at the inlet and outlet of the FF. The number size distribution of PM2.5 before and after FF displays a bimodal distribution that is two sub-micrometer modes with peaks near 4771

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Figure 7. Number cumulative distribution in PM2.5.

Figure 5. Mass size distribution of PM2.5 before and after the FF.

Figure 8. Mass cumulative distribution in PM2.5.

Figure 6. PSD experimental results and Rosin−Rammler fitting curves.

0.1−0.2 and 0.3 μm. The mass size distribution of PM2.5 before and after the FF shows no peak. The results are different from the earlier research results about the pulverized coal boiler, probably because of the different combustion method and the different combustion temperature.19 The combustion temperatures of pulverized coal boilers and CFB boilers are approximately 1250−1500 and 800−900 °C, respectively. Lower temperatures tend to suppress the volatilization of elements in coal, which makes the generation concentration of sub-micrometer particles decrease. Otherwise, various low NOx burners are extensively applied in pulverized coal boilers, which

Figure 9. Size-classified mass removal efficiency of PM2.5.

lead to the formation of a partial reducing atmosphere in pulverized coal boilers, and the reducing atmosphere makes the

Table 5. PSD Rosin−Rammler Fitting Characteristic Numbers number

D50 (μm)

b

n

γ2

w(PM0.38)/w(PM2.5) (%)

w(PM1)/w(PM2.5) (%)

before FF after FF(1) after FF(2) after FF(3) after FF(4)

1.672 1.539 1.524 1.534 1.542

0.09769 0.18748 0.1976 0.19185 0.18573

3.81391 3.03127 2.97721 3.004 3.04262

0.99317 0.99378 0.99409 0.99372 0.99375

0.2538 1.0444 1.1587 1.0973 1.0233

9.6952 17.9776 18.8465 18.3633 17.8220

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Figure 10. continued

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Figure 10. continued

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Figure 10. Microstructures of size-classified PM2.5 before and after the FF.

the multiple cleaning pulses reduced the thickness of the cake on FF and, hence, diminished the effectiveness to capture the finer particles until the cake was built again. Number and mass cumulative distributions of PM2.5 are shown in Figures 7 and 8. Figures 7 and 8 show that the number and mass distributions of PM2.5 before and after the FF are not similar, which indicates that the FF has effects on PM2.5 distribution. The number distribution is dominated by particles that are 0.26−0.943 μm, which account for 45.96 and 54.21−60.12% of the PM2.5 total number before and after the FF, respectively, which indicates that the number concentrations of PM2.5 before and after the FF are determined by sub-micrometer particles. The proportions of the particles in 0.26−0.943 μm in PM2.5 after the FF are 8.25−14.16% higher than that before the FF, which indicates that the FF has relatively weak faculty to remove the particles in 0.26−0.943 μm. The mass distribution is dominated by particles in 0.943− 2.38 μm, which account for 87.21 and 80.97−81.65% of PM2.5 total mass before and after the FF, respectively, which indicates that the mass concentrations of PM2.5 before and after the FF are determined by super-micrometer particles. The proportions of the particles in 0.943−2.38 μm after the FF are 5.56−6.24% lower than that before the FF. Especially, the proportions of the particles in 1.59−2.38 μm (channel 9) after the FF are approximately 10% lower than that before the FF, which indicates that the FF has higher mass size-classified collection efficiencies for the particles in 0.943−2.38 μm. 3.2. Size-Classified Collection Efficiencies of PM2.5 through the FF. The temperatures of stack gas before and after the FF were about 113 and 97 °C. The speeds of stack flue gas were 7.54 and 6.28 m/s before and after the FF. The size-classified removal efficiency of PM2.5 through the FF is shown in Figure 9. The lowest removal efficiency appears in the range from nearly 0.1 to 1 μm. The removal efficiency of PM0.1−1 can reach 99.15−99.59%; the result is in accordance with theoretical analysis.20 The particulates have various dynamic behaviors when they are influenced by different forces. The removal process of particulate matter would be influenced by several forces, such as inertial impaction, interception, diffusion collision, gravity, etc., which are various for sizes and types of particulate matter. According to the research results by Carr et al.,20 the inertial impaction, interception, and diffusion collision forces are most influential on removal efficiencies of fine particulates. According to Landahl et al.,21 Payet et al.,22 and Lee et al.,23 inertial impaction and interception forces acting on particulates make the removal efficiencies of particulates increase with their sizes, especially for the particles more than 1 μm,

Table 6. Total Removal Efficiency of Different Particle Sizes (%) Dp CFB CFB CFB CFB

boiler, boiler, boiler, boiler,

FF(1) FF(2) FF(3) FF(4)

PM2.5

PM1−2.5

PM1

PM0.38−1

PM0.38

99.449 99.029 99.333 99.433

99.485 99.099 99.379 99.469

99.206 98.555 99.021 99.187

99.204 98.555 99.019 99.185

99.237 98.551 99.043 99.213

generation concentration of sub-micrometer particles increase. As a consequence, there is always a highest peak near 0.1 μm in the number concentration distribution generated by pulverized coal boilers, but there is no peak or a subordinate peak near 0.1 μm in the number and mass concentration distributions generated by CFB boilers. The PM2.5 number and mass emission caused by the pulse back blowing of the FF are of particles in the range from 0.029 to 2.38 μm, with a similar increase in all of the particles, and the total PM2.5 number and mass concentration varied from 5.6 × 1011 to 7.8 × 1011 N m−3 and from 158 to 231 mg Nm−3 with the FF cleaning pulsing, respectively. The results indicate that the pulse back blowing of the FF has no significant influence on the PM2.5 number and mass size distribution; however, it has a significant influence on the total PM2.5 number and mass concentration after the FF. Figure 6 and Table 5 show the Rosin−Rammler function fitting results of the mass size distribution of PM2.5 before and after the FF R = 100 exp( −bDpn)

where Dp is the aerodynamic diameter of particles, R represents the mass percentage of the particles with an aerodynamic diameter more than Dp in the mass of PM2.5, and b and n are the size distribution factor and size distribution index, respectively. Rosin−Rammler function fitting D50 represents the mass medium diameter of PM2.5. The value of D50 before the FF is larger than those after the FF, which indicates that the FF removed the coarser particles more efficiently. The w(PM0.38)/ w(PM2.5) and w(PM1)/w(PM2.5) represent the mass percentage concentration of PM0.38 and PM1 in PM2.5. The values of w(PM0.38)/w(PM2.5) and w(PM1)/w(PM2.5) before the FF are lower than those after the FF, which can indicate that FFs have a higher removal efficiency on coarser particles. The value of D50 after FF(2) is larger than that after FF(3), which indicates that the first-time pulse back blowing of the FF would result in the finer particles being emitted after the FF. That is because 4775

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Figure 11. Mass fraction size distributions of elements in PM2.5.

Figure 9 shows that the curve of after FF(1) is higher than the curves of after FF(2) and after FF(3), which indicates that the pulse back blowing of the FF has a significant influence on the size-classified removal efficiency of PM2.5, especially on the range from 0.1 to 1 μm. In the range, the size-classified removal

whereas the diffusion force decreases with the size, especially for the particles less than 0.1 μm. The result is that the particle removal efficiency is the lowest in the range from 0.1 to 1 μm,20 because the influences of inertial impaction, interception, and diffusion are all weakest on these intermediate particles. 4776

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According to the informed research results,24 the unfused particle must be quartz in panel 9-i of Figure 10. 3.5. Chemical Composition of PM2.5. Elemental mass fraction size distributions in PM2.5 were obtained by analyzing the impacting particles on the nine channels of ELPI with EDX. The elemental mass fraction size distributions indicate the proportion of the mass of each element in the total mass of the particles on each channel. As shown in Figure 11, elements can be classified into three groups, in line with the mass fraction size distributions of elements in PM2.5 before and after the FF. Sodium and potassium are clearly enriched with the particle size decreasing; otherwise, zinc is slightly enriched with the particle size decreasing, which should be caused by volatilization of elements and then surface condensation and chemical reaction on pre-existing particles or homogeneous nucleation of the elements.25 However, as shown in Panels 1-i/1-o−9-i/9-o of Figure 10, there are very few spherical particles, which indicates that homogeneous nucleation of sodium, potassium, and zinc was very weak. Calcium and titanium are enriched with the particle size increasing because of the large amount of coarse sorbent limestone particles,25 which may include the mineral compounds enriched with titanium. The mass fraction size distributions of silicon, aluminum, magnesium, iron, and manganese vary little with the variation of the particle size, which indicates that no noticeable amount of these elements was condensed heterogeneously or reacted on the existing particle surfaces after combustion, whereas minor amounts of these elements may have been volatilized via combustion and condensed after combustion.25 To indicate the elemental size distribution characteristics, the relative enrichment factor (that is Rij)26 is introduced and its definition is as follows

efficiency can reach the lowest value, which is 98.46%. The reasons are that the pulse back blowing of the FF reduced the thickness of the cake on the FF and, hence, diminished the effectiveness of the FF and the particle re-entrainment caused by the pulse back blowing that makes the removal efficiency of the FF low. 3.3. Total Removal Efficiencies of PM2.5 through the FF. The total removal efficiency of different particle sizes is shown in Table 6. As shown in Table 6, the FF has very high removal efficiencies for PM2.5, PM1, and PM0.38, which are 99.029−99.449, 98.551−99.237, and 98.555−99.206%. As shown in Table 6, the removal efficiencies of PM1−2.5 and PM0.38 are higher than those of PM0.38−1, which indicates that the FF removed the coarser particles (PM1−2.5) and ultrafine particles (PM0.38) more efficiently than the intermediate particles (PM0.38−1). The removal efficiency of PM1−2.5 is higher than the removal efficiency of PM0.38, which indicates that the influences of inertial impaction and interception on PM2.5 are more important than the influence of diffusion on PM2.5 in this case. 3.4. Morphological Characteristics of Size-Classified PM2.5. The size-classified PM2.5 was impacted to form several cumulative sample spots on each polycarbonate filter, except channels 1 and 2. Through observations with SEM, there is no obvious cumulative sampling spot on channels 1 and 2; there is only somewhere dark on the positions of sampling spots. The significant reason is that the particles on these two channels are too small, and the other reason is that the number of particles on these two channels is not dominant. Some micrographs of channels 3−9 showed that the particle concentration in the middle of the spots was higher than at the edge of the spots. Figure 10 shows the micrographs of channels 1−9 in the ELPI, which represent size-classified PM2.5, respectively. As shown in Figure 10, morphological characteristics of the particles on the corresponding channels are different before and after the FF. The particles before and after the FF are almost irregular in shape, but there are still a small number of spherical and elliptical particles via vaporization−condensation and partial fusion of mineral matter (panel 3-i of Figure 10), respectively. Panels 1-i/1-o and 2-i/2-o of Figure 10 are the closeups of typical ultrafine particles on the channels 1 and 2 before and after the FF. The particles on the two channels have not impact to form cumulative sample spots. Particles in the two channels are irregular in shape, which are agglomerates consisting of unburnt carbon.6 Panels 3-i/3-o−7-i/7-o of Figure 10 are the micrographs of sub-micrometer particles on the channels 3−7. The particles on these channels are almost irregular. These particles were formed via breakage fusion/partial fusion of mineral matter in coal. As shown in panels 3-i/3-o−5-i/5-o of Figure 10, the morphological characteristics after the FF are different from the morphological characteristics before the FF. The particles formed by agglomeration can be seen on channels 3−5 after the FF compared to before the FF, which may have resulted from the long residence time caused by the low filter speed (1−2 m/min) of the filter bags, and this long residence time allows for the particles in channels 3−5 to adsorb smaller particles on them. In panels 6-i/ 6-o and 7-i/7-o of Figure 10, there is no obvious agglomeration after the FF compared to before the FF, which may be caused by the larger particles in channels 6 and 7 with the lower surface adsorption force compared to the particles in channels 3−5. Panels 8-i/8-o and 9-i/9-o of Figure 10 are the micrographs of super-micrometer particles on channels 8 and 9. The particles in shape are similar to the particles on channels 3−7, indicating that channels 3−9 formed via the same mechanisms.

R ij = Cij/Ci9 where Cij is the mass fraction size distribution of element i in PM2.5 on the channel j of the ELPI and Ci9 is the mass fraction

Figure 12. Relative enrichment factor of PM2.5 before the FF.

Figure 13. Relative enrichment factor of PM2.5 after the FF. 4777

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Figure 14. Elemental size distribution in PM2.5 before and after the FF.

As shown in Figures 12 and 13, the Rij values of the elements are similar before and after the FF, which indicates that the FF had few effects on the elemental size distribution. Rij values of sodium, potassium, and zinc are obviously greater than 1 in channels 1−5; Rij values of calcium and titanium in channels

size distribution of element i in PM2.5 on channel 9 of the ELPI. Rij represents the variation tendency of the enrichment degrees of the elements along with the PSD in PM2.5. Rij > 1 indicates that element i is enriched in channel j, and Rij < 1 indicates that there is no enrichment tendency in channel j. 4778

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1−3 are less than 1; and Rij values of silicon, aluminum, magnesium, iron, and manganese are about 1, which represent sodium, potassium, and zinc being enriched in particles with an aerodynamic diameter of less than 0.1 μm; however, calcium, titanium, silicon, aluminum, magnesium, iron, and manganese are not enriched in the particles with aerodynamic diameter less than 0.1 μm. According to Finkelman,27 sodium, potassium, and zinc may exist in the organic combination state in coal, which are easy to volatilize in the combustion, and then condense on the pre-existing particles. The particles with a smaller size have more relative surface areas; therefore, the volatile elements are easy to enrich on them. The size-classified distributions of elements in PM2.5 were calculated by the mass PSDs of PM2.5 and the mass fraction size distributions of elements in PM2.5. The results are shown in Figure 14. As shown in Figure 14, the size-classified distributions of most of the elements in PM2.5, except calcium and titanium, are in accordance with the mass PSDs of PM2.5, with the difference of size-classified distributions of calcium and titanium resulting from foreign materials, such as coarse sorbent limestone particles. In Figure 14, the trends of the elemental size-classified distributions before and after the FF are similar, which indicates that the elements in PM2.5 were not redistributed in the process of collection dust. The elemental size-classified distributions are nearly the same, which indicates that the pulse back blowing of the FF has few effects on the elemental size-classified distributions in PM2.5.

Morphological characteristics of the PM2.5 size-classified distribution before and after the FF are nearly the same, except the particles in channels 3−5, because of the obvious agglomeration of the particles in channels 3−5 after the FF compared to before the FF. (9) The elements can be classified into three groups, in line with the mass fraction size distributions of elements in PM2.5 before and after the FF. Group 1 includes sodium, potassium, and zinc, which are enriched with the particle size decreasing. Group 2 includes calcium and titanium, which are enriched with the particle size increasing because of the large amount of coarse sorbent limestone particles, including the mineral compounds containing titanium. Group 3 includes silicon, aluminum, magnesium, iron, and manganese, which are not enriched with the variation of the particle size. (10) The size-classified distributions of most of the elements in PM2.5 are in accordance with the mass PSDs of PM2.5; otherwise, the difference of size-classified distributions of calcium and titanium may result from foreign materials, which are coarse sorbent limestone particles containing titanium.

4. CONCLUSION In this work, the PM2.5 emission characteristics, the comparison of the morphological characteristics, and the size-classified elemental composition of PM2.5 are determined experimentally before and after the FF at an industrial CFB boiler. Measurement in situ was taken with an ELPI with a two-stage dilution sampling system. The morphological characteristics and size-classified elemental composition were performed by SEM and EDX. Results shown are as follows: (1) The number size distribution of PM2.5 before and after FF displays a bimodal distribution that is two sub-micrometer modes with peaks near 0.1−0.2 and 0.3 μm. The mass size distribution of PM2.5 before and after the FF shows no peak. The results are different from the earlier research results about the pulverized coal boiler, probably because of the different combustion methods and different combustion temperatures. (2) The pulse back blowing of the FF has no significant influence on the PM2.5 number and mass size distribution; however, it has significant influence on the total PM2.5 number and mass concentration after the FF. (3) The first-time pulse back blowing of the FF would result in the finer particles being emitted after the FF. The reason is that the multiple cleaning pulses reduced the thickness of the cake on FF and, hence, diminished the effectiveness to capture the finer particles until the cake was built again. (4) The size-classified removal efficiency of PM2.5 through the FF shows the lowest removal efficiency appearing at the PSD range from nearly 0.1 to 1 μm. (5) The pulse back blowing of the FF can reduce the thickness of the cake on the FF and, hence, diminish the effectiveness of the FF and the particle re-entrainment caused by the pulse back blowing that made the removal efficiency of the FF low. (6) The FF removed the coarser particles (PM1−2.5) and ultrafine particles (PM0.38) more efficiently than the intermediate particles (PM0.38−1). (7) The influence of inertial impaction and interception on PM2.5 is more important than the influence of diffusion on PM2.5 in this test. (8)

ACKNOWLEDGMENTS This work was financially supported by the project supported by the Special Fund for the National Environmental Protection Public Welfare Industries of China (201009006).

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AUTHOR INFORMATION

Corresponding Author

*Telephone: +86-13946060313. E-mail: zhaozhifeng198211@ 163.com. Notes

The authors declare no competing financial interest.

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REFERENCES

(1) Wang, W.; Tang, D.; Liu, H.; Yue, X.; Pan, Z.; Ding, Y. Res. Environ. Sci. 2000, 13, 1−5. (2) Wei, F.; Teng, E.; Wu, G.; Hu, W.; Wilson, W. E.; Chapman, R. S. Environ. Monitor. China 2001, 17, 1−6. (3) Siegmann, K. J. Aerosol Sci. 2000, 31, 217−218. (4) Sarofim, A. F.; Beér, J. M. Symp. (Int.) Combust., [Proc.] 1979, 17, 189−204. (5) Hernberg, R.; Stenberg, J.; Zethræus, B. Combust. Flame 1993, 95, 191−205. (6) Yi, H.; Hao, J.; Duan, L.; Tang, X.; Ning, P.; Li, X. Fuel 2008, 87, 2050−2057. (7) Ji, J.; Chen, A. Arrester Dedusting Technology in Boiler Flue Gas; China Electric Power Press: Beijing, China, 2006. (8) McElroy, M. W.; Carr, R. C.; Ensor, D. S.; Markowski, G. R. Science 1982, 215, 13−19. (9) Nielsen, M. T.; Livbjerg, H.; Fogh, C. L.; Jensen, J. N.; Simonsen, P.; Lund, C.; Poulsen, K.; Sander, B. Combust. Sci. Technol. 2002, 174, 79−113. (10) Fisher, G. L.; Prentice, B. A.; Silberman, D.; Ondov, J. M.; Biermann, A. H.; Ragaini, R. C.; McFarland, A. R. Environ. Sci. Technol. 1978, 12, 447−451. (11) Goodarzi, F. Fuel 2006, 85, 273−280. (12) Shendrikar, A. D.; Ensor, D. S.; Cowen, S. J.; Woffinden, G. J.; McElroy, M. W. Atmos. Environ. 1983, 17, 1411−1421. (13) Zhang, C.; Yao, Q.; Sun, J. Fuel Proc. Technol. 2005, 86, 757− 768. (14) Kazanc, F.; Levendis, Y. A. Energy Fuels 2012, 26, 7127−7139. (15) Ruscio, A.; Kazanc, F.; Levendis, Y. A. Energy Fuels 2014, 28, 685−696. (16) Moisio, M.; Laitinen, A.; Hautanen, J.; Keskinen, J. J. Aerosol Sci. 1998, 29, S459−S460. 4779

dx.doi.org/10.1021/ef500558g | Energy Fuels 2014, 28, 4769−4780

Energy & Fuels

Article

(17) Lind, T.; Hokkinen, J.; Jokiniemi, J. K.; Saarikoski, S.; Hillamo, R. Environ. Sci. Technol. 2003, 37, 2842−2846. (18) Saarikoski, S.; Makela, T.; Hillamo, R.; Aalto, P. P. Boreal Environ. Res. 2005, 10, 385−400. (19) Yi, H.; Guo, X.; Hao, J.; Duan, L.; Li, X. J. Air Waste Manage. Assoc. 2006, 56, 1243−1251. (20) Carr, R. C.; Smith, W. B. J. Air Pollut. Control Assoc. 1984, 31, 399−413. (21) Landahl, H. D.; Herman, R. G. J. Colloid Sci. 1949, 4, 103−136. (22) Payet, S.; Boulaud, D.; Madelaine, G.; Renoux, A. J. Aerosol Sci. 1992, 23, 723−735. (23) Lee, W. K.; Liu, B. Y. Aerosol Sci. Technol. 1982, 1, 147−161. (24) Koukouzas, N.; Ketikidis, C.; Itskos, G. Fuel Process. Technol. 2011, 92, 441−446. (25) Linak, W. P.; Wendt, J. O. L. Prog. Energy Combust. Sci. 1993, 19, 145−185. (26) Yu, D.; Xu, M.; Yao, H.; Liu, X.; Zhou, K. Chin. Sci. Bull. 2008, 53, 1593−1602. (27) Finkelman, R. B. Fuel Process. Technol. 1994, 39, 21−34.

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