Emission and Morphological Characteristics and Elemental

Article pubs.acs.org/EF

Emission and Morphological Characteristics and Elemental Compositions of Fine Particulate Matter from an Industrial Pulverized Coal Boiler Equipped with a Fabric Filter in China Guangbo Zhao,† Zhifeng Zhao,† Xin Guo,† Qian Du,*,† Jianmin Gao,† Heming Dong,† Yang Cao,‡ Qiang Han,§ and Lipeng Su† †

School of Energy Science and Engineering, Harbin Institute of Technology, 92 Xidazhi Street, Harbin 150001, People’s Republic of China ‡ State Grid Northeast Electric Power Science and Research Institute, 15 Guangrong Street, Shenyang 110000, People’s Republic of China § Huadian Electric Power Research Institute, 10 Xiyuanyi Street, Hangzhou 310030, People’s Republic of China ABSTRACT: In this research, the emission characteristics, morphological characteristics and size-classified elemental compositions of PM2.5 are determined experimentally before and after a fabric filter (FF) at an industrial pulverized coal boiler. Sampling and measurement of PM2.5 in situ were taken with an ELPI with a two-stage dilution sampling system. The morphological characteristics were analyzed by scanning electron microscopy. The size-classified elemental compositions were analyzed by energy-dispersive X-ray analysis and inductively coupled plasma−atomic emission spectrometry. The number size distribution of PM2.5 before the FF displays a unimodal distribution. The mass distribution of PM2.5 before the FF displays a unimodal distribution with the peak near 0.1 μm, but the mass distribution of PM2.5 after the FF shows no peak. The pulse back blowing of the FF exerts significant influence on PM2.5 number and mass concentrations after the FF, especially on the number and mass concentrations of PM0.007−0.029. There appears a penetration window in nearly 0.1−1 μm; however, the removal efficiency of PM0.007−0.029 is lowest. The pulse back blowing of the FF can reduce the removal efficiency of PM0.007−0.029 from 99.37% to 97.80%. The microstructures of super-micrometer and sub-micrometer particles are different before and after the FF; however, the ultrafine particles in 0.007−0.029 μm are nearly the same before and after the FF. The fractional mass distributions of silicon, aluminum, iron, calcium, and magnesium vary little with variation of the particle size. Cadmium, arsenic, and selenium are enriched with the particle size decreasing.

1. INTRODUCTION Coal-fired emission is a significant source of fine particulate matter (PM2.5; PM2.5 are aerosols with aerodynamic diameters of less than 2.5 μm) in ambient air in China.1−4 In China, approximately 84% of coal consumption is used for direct combustion,5 and a large proportion of the direct-combusted coal consumption is for coal combustion of coal-fired utility and industrial boilers.6 Therefore, the effective control of emission quantity of PM2.5 generated from the utility and industrial boilers is indispensable in reducing PM2.5 concentration in the environmental atmosphere in China. In China, pulverized coal boilers are extensively applied into coal-fired power plants, and grated-fired boilers are widely used as a main type of industrial coal-fired boilers. Recently, in China, some small-capacity pulverized coal (SCPC) boilers were built as industrial coal-fired boilers for high burnoff rates. Because the small-capacity industrial pulverized coal (SCIPC) boilers are not widely used, research reports on their PM2.5 generation and emission characteristics are very few. Fabric filters (FFs) are extensively equipped with coal-fired utility boilers and industrial boilers in Australia, the USA, and South Africa, etc.7 Recently, in China, FFs were applied to remove the coal fly ash generated from several coal-fired utility boilers and industrial boilers to be up to more strict environmental protection standards.8 © XXXX American Chemical Society

Relational research has been launched on coal-fired PM2.5 generated from utility and industrial boilers. Nielson et al.9 researched the combustion particle generation and emission from two full-scale coal-fired power plants; the results showed that the size of the 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 flue-gas particles were in the range of PM2.5. Fisher et al.10 found the different proportions of nonopaque solid sphere and cenosphere in fine particles (87% and 7.9%) and coarse particles (26% and 41%). Goodarzi11 researched the morphology of fine particulate matter emitted from a Canadian coal-fired power plant. The microstructural results showed that PM>10 emitted from a stack that 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 particle size distribution for most elements before the baghouse was bimodal, with the larger mode near 4−10 μm and the smaller mode 0.08 μm or less. Gieré et al.13 researched the chemical and structural Received: January 11, 2016 Revised: April 13, 2016

A

DOI: 10.1021/acs.energyfuels.6b00060 Energy Fuels XXXX, XXX, XXX−XXX

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Energy & Fuels properties of PM2.5 emitted from cyclone-type mechanical collectors and ESPs of a utility boiler, which consumed two types of fuels (a type of coal and the same type of coal mixed with tire chips) in successive weeks; the results showed that the emitted PM2.5 contained amorphous selenium particles and three types of crystalline metal sulfates; PbSO4 was ubiquitous in the PM2.5 derived from both fuels; ZnSO4·H2O was a main existential form of Zn in the PM only generated from combusting the coal mixed with tire chips and KFe(SO4)2 existed only in the PM from the pure coal combustion. In China, relative researches on coal-fired particulate matter have started later since the 1980s. Yi et al.7 researched the size distributions of number and mass, microstructure, and trace elements size distribution of PM10 before and after the bag house. Zhang et al.14 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 elements percent concentrations of samples. Wen et al.15 sampled from the inlet and outlet of each dust collector of six coal-fired boilers, indicating the mass concentration distributions of PM2.5 before and after those dust collectors and the emission factors of the six boilers. Relational research on PM2.5 generation and emission characteristics generated from an industrial pulverized coal boiler are very few to date. Bonin and Queiroz16 sampled and analyzed the PSDs (1100 μm) of PM generated from a 80 MWe industrial pulverized coal boiler by PCSV-P (particle concentration size and velocimeter probe). Kang et al.17 analyzed the PSDs of TPM (total particulate matter) from a 1.6 MW industrial pulverized coal boiler and calculated the removal efficiency of TPM. Zhou18 sampled the PM from seven boilers by a WY-1 impact seven-stage classification dust sampler, and mainly researched the generation and emission mass concentrations of particles with Dp range from 1.3 to 14.1 μm generated from a 6 t/h industrial pulverized coal boiler. Most of the foreign and domestic research usually focuses on the coal fly ash and PM10 generation and emission characteristics of the coal-fired utility boilers equipped with the ESPs, investigates PM2.5 emission characteristics of the coal-fired industrial boilers equipped with the FFs are relatively less to date, especially that from SCIPC boilers. The research on PM generated from SCIPC boilers has often focused on PM>1 (particles with aerodynamic diameter of more than 1 μm), but involved no morphological characteristics and chemical constitutes. This work analyzed the PM2.5 generation and emission characteristics of a small-capacity industrial pulverized coal boiler equipped with a fabric filter in China, including PM2.5 generation and emission concentrations, particle size distributions, morphological characteristics, and chemical compositions, and mainly analyzed the particles with aerodynamic diameters of less than 1 μm in the PM2.5, especially of particles in 0.007−0.029 μm in the PM2.5.

Figure 1. Schematic of the industrial pulverized coal boiler. 2.2. Sampling and Analytical Methods. Sampling and analytical methods can find in the Experimental Section of Zhao et al.19 Besides, in this research, we analyzed the mass fraction concentrations of cadmium, arsenic, and selenium in PM2.5 with ICP-AES (inductively coupled plasma−atomic emission spectrometry). And individual-particle microstructures of PM2.5 on these substrates were analyzed with field emission scanning electron microscopy, and thermionic emission scanning electron microscopy was used to take the micrographs of the particles on channel 1 and other channels, respectively. The temperatures of stack flue gas before and after the fabric filter were approximately 121 and 92 °C. The temperatures of the secondstage dilution, the air filter, and the ELPI (electrical low pressure impactor) were the same as the environmental temperature, which was approximately 19 °C. The flow velocities of flue gas were 7.38 and 6.94 m/s.

3. RESULTS AND DISCUSSION 3.1. Size Distribution and Concentration of PM2.5. This research showed PM2.5 emission characteristics of a smallcapacity industrial pulverized coal boiler at the inlet and outlet of the fabric filter, which focused on the influence of the pulse back blowing of the FF on PM2.5 emission characteristics. The particle size ranges of 10 channels in the ELPI are shown in Table 4. Shown in Figure 2 are the current values of the 10 channels in the ELPI during the test after the FF, which correspond to size-classified PM2.5. In Figure 2, two current value peaks can be seen, which are caused by the pulse back blowing of the FF. The two peaks are nearly the same, so we choose the first peak to research the influence of the pulse back blowing process on PM2.5 emission characteristics. In this research, the current values after the FF are divided into three parts, as shown in Figure 2. Part (1) represents the average values of the total current values with and without the pulse back blowing; part (2) represents the current value peak caused by the pulse back blowing of the FF; part (3) represents the current value with no dust cleaning. The following studies are based on this division. Figures 3 and 4 show the number and mass concentration distributions before and after the FF. The number concentration distribution of PM2.5 before the FF displays a unimodal distribution, with a peak located between 0.07 and 0.12 μm. This characteristic number size distribution of PM2.5 is different from the bimodal number concentration distributions of PM2.5 generated from most other pulverized coal boilers of coal-fired power plants,6 which can be caused by relatively less residence times of pulverized coal particles in the furnace. The capacity of the boiler in this research is only 10 t/h; its scale is much less than those of the boilers (2202045 t/h) in the earlier research,6 so the residence times of pulverized coal particles in this pulverized

2. EXPERIMENTAL SECTION 2.1. Basic Information on the Industrial Pulverized Coal Boiler. Fuel coal produced from Shanxi province was consumed in a 10 t/h industrial vortex pulverized coal boiler equipped with a fabric filter, as shown in Figure 1. Proximate and ultimate analyses of the coal are given in Table 1. Ash analysis of the fuel coal is in Table 2. In the test period, the boiler was operating normally and the testing load was relatively stabilized, the furnace temperature was approximately 1340 °C, the combustion efficiency (burnoff rate) was 98.6%, and the concentrations of flue gas compositions are shown in Table 3. B


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Energy & Fuels Table 1. Proximate and Ultimate Analyses of the Fuel Coal proximate analysis (wt %)

heating value

Mar

Aar

Var

FCar

Qnet,ar (MJ/kg)

1.87

34.12

21.53

42.48

20.23

rank bitumite

ultimate analysis (wt %) Car

Har

Nar

Oar

Sar

51.71

4.61

1.29

6.73

0.43

Table 2. Ash Analysis of the Fuel Coal composition, wt % SiO2

Al2O3

FeO

CaO

MgO

SO3

TiO2

K2O

Na2O

P2O5

52.76

31.82

4.52

5.26

2.21

0.15

1.65

1.02

0.31

0.30

Table 3. Concentrations of Flue Gas Compositions flue gas composition

SO2 (mg/m3)

NOx (mg/m3)

CO (mg/m3)

O2 (%)

CO2 (%)

concentration

547

425

38

5.3

14.2

Table 4. Particle Size Ranges of the 10 Channels of ELPI particle size range channel no.

lower limit (μm)

upper limit (μm)

1 2 3 4 5 6 7 8 9 10

0.007 0.029 0.057 0.093 0.154 0.26 0.38 0.609 0.943 1.59

0.029 0.057 0.093 0.154 0.26 0.38 0.609 0.943 1.59 2.38

Figure 3. Number size distributions of PM2.5 before and after the FF. [The results given are at 10% dioxygen in the standard temperature and pressure.]

peak of PM2.5 in this research is generally higher than the earlier research result,6 because less residence times of pulverized coal particles tend to suppress the agglomeration and growth of the ultrafine particles generated from pulverized coal.24 The PM2.5 number distribution after the FF displays a bimodal distribution that is two sub-micrometer modes with peaks near 0.1 and 0.4− 0.5 μm. The mass concentration distribution of PM2.5 before the FF displays a unimodal distribution with the peak near 0.1 μm, but the mass concentration distribution of PM2.5 after the FF (after FF(3)) shows no peak. As shown in Figures 3 and 4, the shapes of PM2.5 number and mass distribution curves caused by the pulse back blowing of the FF are similar to the ones after the FF without the pulse back blowing. This result indicates that the pulse back blowing of the FF has no prominent influence on characteristics of PM2.5 number and mass distributions after the FF. However, PM2.5 number and mass concentrations vary from 42629 to 219950 cm−3 and from 0.28 to 3.46 mg/Nm3, and PM0.007−0.029 number and mass concentrations vary from 18365 to 64143 cm−3 and from 9.42 × 10−5 to 3.29 × 10−4 mg/Nm3. This result indicates that the pulse back blowing has significant influence on the PM2.5 and PM0.007−0.029 number and mass concentrations after the FF.

Figure 2. Current values of 10 channels in ELPI during the test after the FF.

coal boiler is less.20 Tangentially fired pulverized coal boilers with direct current burners are widely used in coal-fired power plants in China,21 and pulverized coal particles have less residence times in cyclone-fired pulverized coal boilers than those in tangentially fired pulverized coal boilers.22 Less residence times of pulverized coal particles in the furnace tend to suppress the thermal fragmentation of pulverized coal,23 which makes the generation concentration of coarse-mode particles decrease, so there is no peak of PM2.5 number concentration at approximately 1 μm, unlike an earlier research result on pulverized coal boilers of coalfired power plants.6 The sub-micrometer number concentration C


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Figure 5 and Table 5 show the Rosin−Rammler function fitting results of the mass size distributions of PM2.5 before and after the FF. D = 100[1 − exp( −bDpn)]

where Dp is the aerodynamic diameter of particles, R represents the mass percentage of the particles with an aerodynamic diameter less 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 values of b after the FF are larger than those before the FF, which indicates that the average diameters of PM2.5 after the FF are smaller than that before the FF.25 The values of n after the FF are smaller than that before the FF, which indicates the particle size distributions of PM2.5 after the FF are more dispersive than that before the FF.25 The wt%(PM1.0/PM2.5), wt%(PM1.0−2.5/PM2.5), and wt %(PM0.007−0.029/PM2.5) represent the mass percentage concentrations of PM1.0, PM1.0−2.5, and PM0.007−0.029 in PM2.5. The values of wt%(PM1.0/PM2.5) after the FF are higher than those before the FF, and the values of wt%(PM1.0−2.5/PM2.5) after the FF are lower than those before the FF, which can indicate the FF has a higher removal efficiency on super-micrometer particles (Dp ≥ 1 μm) than on sub-micrometer particles (Dp < 1 μm). The values of wt%(PM0.007−0.029/PM2.5) after the FF are much higher than those before the FF, which can indicate that the FF removed the PM0.007−0.029 relatively less efficiently. The value of n after FF(2) is larger than that after FF(3), which indicates that the pulse back blowing of the FF made the particle size distributions of PM2.5 after the FF more centralized. The value of b after FF(2) is smaller than that after FF(3), which indicates that the pulse back blowing of the FF made the average diameters of PM2.5 after the FF coarser. The value of wt%(PM1.0/ PM2.5) after FF(2) is smaller than that after FF(3), and the value of wt%(PM1.0/PM2.5) after FF(2) is larger than that after FF(3), which can also indicate that the pulse back blowing of the FF made the PM2.5 coarser after the FF. That is because pulse back blowing of the FF reduced the thickness of the cake on the FF, therefore, lowering the effectiveness to capture the coarser particles until the cake was built again; meanwhile, reentrainment of dust caused by the pulse back blowing could also be a source of PM2.5, and the cake must contain coarser particles because the FF removed the coarser particles more efficiently. The value of wt%(PM0.007−0.029/PM2.5) after FF(2) is smaller than that after FF(3), which indicates that the pulse back blowing of the FF can make the concentration of PM0.007−0.029 in

Figure 4. Mass size distributions of PM2.5 before and after the FF. [The results given are at 10% dioxygen in the standard temperature and pressure.]

Figure 5. PSD experimental results and Rosin−Rammler fitting curves.

Table 5. PSD Rosin−Rammler Fitting Characteristic Numbers no.

D50 (μm)

after FF(1) after FF(2) after FF(3) before FF no.

1.384 1.394 1.241 1.624 wt%(PM1.0/PM2.5)

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

25.4343 24.7685 35.0446 11.0317

b 0.29349 0.2846 0.43147 0.11689 wt%(PM1.0−2.5/PM2.5) 74.5657 75.2315 64.9554 88.9683 D

γ2

n 2.6424 2.68042 2.19552 3.67185

0.99359 0.99364 0.99257 0.98179 wt%(PM0.007−0.029/PM2.5) 0.002539 0.002152 0.018153 0.000026 DOI: 10.1021/acs.energyfuels.6b00060 Energy Fuels XXXX, XXX, XXX−XXX

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Energy & Fuels

μm. The proportion of the particles in 0.007−0.029 μm in PM2.5 after FF(3) is 13.92% higher than those after FF(2), which indicates that pulse back blowing of the FF can have a significant effect on the proportion of the particles in 0.007−0.029 μm in PM2.5. The mass distribution is dominated by the particles in 0.943− 2.38 μm, which account for 84.67 and 71.12−77.01% of the PM2.5 total mass before and after the FF, respectively, which indicates 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 7.66−13.55% lower than that before the FF. 3.2. Fractional Collection Efficiencies of PM2.5 through the FF. The fractional collection efficiencies of PM2.5 through the FF are shown in Figure 8. Obviously, there appears a

PM2.5 higher, which is caused by the coarser particles generated by pulse back blowing of the FF joining into PM2.5 after the FF. In Figures 6 and 7, the number and mass cumulative distributions of PM2.5 before and after the FF are shown. As

Figure 6. Number cumulative distribution in PM2.5.

Figure 8. Fractional collection mass efficiencies of PM2.5 (%).

penetration window in nearly 0.1−1 μm. The removal efficiency of PM0.1−1 can reach 98.18−99.69%; the results are in accordance with theoretical analysis.26 The particles have various dynamic behaviors when they are influenced by different forces.27 The removal process of particulate matter would be influenced by several forces, such as inertial impaction, interception, diffusion collision, and gravity, etc., which vary with the sizes and types of particulate matter. According to the research results by Carr and Smith,26 the inertial impaction, interception, and diffusion collision are most influential on the removal efficiency of fine particles. According to Lee and Liu,28 Landahl and Herman,29 and Payet et al.,30 inertial impaction and interception forces acting on particles make the removal efficiencies of particles increase with their sizes, especially for the particles more than 1 μm, whereas the diffusion force decreases with the sizes, especially for the particles less than 0.1 μm. The result is that the removal efficiency is relatively lower in the range from 0.1 to 1 μm,26 because the influences of inertial impaction, interception, and diffusion are all weaker on these intermediate particles. Besides, particles can pass straight through the fabric filter, which is caused by a faster filtration velocity.31 The PM0.007−0.029 are finer particles with the stronger faculty of following the flue gas;

Figure 7. Mass cumulative distribution in PM2.5.

shown in Figures 6 and 7, the number and mass cumulative distributions before the FF are different from the ones after the FF, which indicates that the dust-removal process of the FF exerted an influence on the PM2.5 distribution. The number distribution is dominated by particles in 0.007− 0.154 μm, which account for 93.99 and 92.04−93.53% 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 ultrafine particles. The proportion of the particles in 0.007−0.154 μm in PM2.5 before the FF is 0.46−1.95% higher than those after the FF, which indicates that the dust-removal process of the FF has few effects on the proportion of particles in 0.007−0.154 μm in PM2.5. The particles in 0.007−0.029 μm in PM2.5 account for 14.15 and 29.16−43.08% of the PM2.5 total number before and after the FF, respectively. The proportion of the particles in 0.007−0.029 μm in the PM2.5 total number before the FF is 15.02−28.94% lower than those after the FF, which indicates that the FF has relatively weak faculty to remove the particles in 0.007−0.029 E


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flue gas stack before the FF. The surface of the sub-micrometer particle after the FF is rougher than that before the FF. That is because the surface of the sub-micrometer particle would adsorb more ultrafine particles and gaseous composition when the submicrometer particle passed through the FF. Panels C and c of Figure 9 show that the ultrafine particle before the FF is nearly the same as the one after the FF, because this ultrafine particle is too small to be the adsorbing target of other smaller existing ultrafine particles in flue gas. However, this ultrafine particle would adsorb gaseous composition onto its surface, which cannot be observed by the microstructure of ultrafine particles. 3.5. Chemical Composition of PM2.5. Elemental fractional mass distributions in PM2.5 were obtained by analyzing the sizeclassified particles on 10 channels of ELPI with EDX and ICPAES. The elemental fractional mass distributions can indicate the proportion of the mass of each element in the total mass of the particles on each channel. Figure 10 shows the elemental fractional mass distributions in PM2.5 before and after the FF. As shown in Figure 10, elements can be classified into three groups according to the elemental fractional mass distributions in PM2.5 before the FF. The fractional mass distributions of silicon and aluminum increase with the particle size increasing. The fractional mass distributions of calcium, cadmium, arsenic, and selenium increase with the particle size decreasing, which should be caused by volatilization of these elements and then surface condensation and chemical reaction on existing particles or homogeneous nucleation of these elements.33 The fractional mass distributions of iron and magnesium vary little with variation of the particle size, which indicates that no noticeable amount of these elements was condensed heterogeneously or reacted on the existing particle surfaces during combustion. The fractional mass distributions of all elements before and after the FF are similar except cadmium, arsenic, and selenium. The percentage contents of these elements in correspondingsized particles after the FF are higher than those before the FF. That is because cadmium, arsenic, and selenium are volatile elements;34 these elements could still exist in gaseous form in the flue gas of the FF, and then these gaseous elements condensed on the surface of pre-existing particles or reacted on the pre-existing particles in the FF. The filtration velocity of the fabric filter is often much less than the flow velocities in the flue gas stack before and after the FF; the relatively low filtration velocity can lead to partial higher pressure near the surface of the filter bags, and the partial higher pressure will make the solubility of gaseous cadmium, arsenic, and selenium in flue gas decrease, which can intensify the surface condensation of these three elements on pre-existing particles or homogeneous nucleation of these three elements. Meanwhile, the relatively low filtration velocity of the FF will supply relatively long residence time for these gaseous elements in the flue gas to condense or react on the pre-existing particles or form new particles by homogeneous nucleation. This can be a probable approach of gaseous cadmium, arsenic, and selenium in flue gas transforming into the PM2.5 or a part of the PM2.5 after the FF, which makes the fractional mass distributions of these three elements after the FF higher than those before the FF. The relative enrichment factor is introduced to indicate the mass fraction size characteristics. The relative enrichment factor is expressed with Rij,35 and its definition is as follows

these particles can more easily pass straight through the fabric filter, so the removal efficiency of PM0.007−0.029 is lowest. As shown in Figure 8, the fractional collection efficiency after FF(2) is higher than that after FF(3), which indicates that the pulse back blowing of the FF has a significant influence on the fractional collection efficiency of PM2.5, especially on PM0.1−1 and PM0.007−0.029. The fractional collection efficiency of these particles can reach the lowest values, which are 98.18% and 97.80%. The reasons are the pulse back blowing of the FF reduced the thickness of the cake on the FF, hence, diminishing the effectiveness of the FF and the particle re-entrainment caused by the pulse back blowing that make the fractional collection efficiency of the FF lower. 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 Table 6. Total Removal Efficiency of Different Particles Dp

PM2.5

PM1

PM1−2.5

PM0.007−0.029

after FF(1) after FF(2) after FF(3)

99.37 98.94 99.91

99.04 98.42 99.84

99.43 99.04 99.93

98.49 97.80 99.37

efficiencies for PM2.5, PM1, PM1−2.5, and PM0.007−0.029 of 98.94− 99.91%, 98.42−99.84%, 99.04−99.93%, and 97.80−99.37%. The removal efficiency of PM1−2.5 is higher than that of PM1, which indicates that the influences of inertial impaction and interception on PM2.5 are more important than that of diffusion on PM2.5 in this case. The removal efficiencies of PM2.5, PM1, PM1−2.5, and PM0.007−0.029 after FF(2) are lower than those after FF(3), which indicates that the pulse back blowing of the FF made the emissions of PM2.5, PM1, PM1−2.5, and PM0.007−0.029 increase. 3.4. Morphological Characteristics of PM2.5. The objects of earlier research on morphological characteristics of particles were coal fly ash or dust-collector bottom ash, and these research reports and these researchers focused on morphological characteristics of particle swarms.14,32 In addition, the morphological characteristics of particle swarms analyzed by SEM are always the ones of the coarser particles; microstructures of the ultrafine particles are not easy to analyze, and accumulation of particles on filter membranes can break the microstructures of some particles.6 In this research, we analyze the microstructures of the individual particles on different channels by SEM to research typical individual-particle morphological characteristics of the ultrafine, sub-micrometer and super-micrometer particles in PM2.5 before and after the FF. As shown in Figure 9, the particles before the FF are spherical, which were formed by surface tension of fused mineral substance at the high furnace temperature. Panels A and a of Figure 9 show that the supe-rmicrometer particle before the FF is different from the one after the FF; the super-micrometer particle is relatively smooth-surfaced before the FF, but there are many ultrafine particles on the surface of super-micrometer particles after the FF. These ultrafine particles were formed by condensation of gaseous mineral composition in the flue gas when the flue gas passed through the flue gas stack and the FF; then they were adsorbed onto the super-micrometer particles. Panels B and b of Figure 9 show that the sub-micrometer particle before the FF is relatively rough-surfaced; the particle was formed by adsorption of ultrafine particles and growth of these ultrafine particles on the sub-micrometer particle when the flue gas passed through the

R ij = Cij/Ci10 where Cij is the fractional mass distribution of element i in PM2.5 on channel j of the ELPI and Ci10 is the fractional mass F


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Figure 9. Microstructures of sized-classified PM2.5 before and after the FF: Representative microstructure of ultrafine PM2.5 (A) before and (a) after the FF (channel 10); representative microstructure of sub-micrometer PM2.5 (B) before and (b) after the FF (channel 7); representative microstructure of super-micrometer PM2.5 (C) before and (c) after the FF (channel 1).

distribution of element i in PM2.5 on channel 10 of the ELPI. Rij can indicate the variation tendency of the enrichment degrees of elements along with the PSDs 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. As shown in Figures 11 and 12, Rij values of silicon, aluminum, iron, and magnesium are similar and near 1 before and after the FF, which indicates that these elements were not enriched in PM2.5; even the Rij values of silicon in channels 1−5 and the Rij values of aluminum in channels 1−8 are all less than 1, which indicates that silicon and aluminum in these channels have relatively lower abundances. Rij values of cadmium, arsenic, and selenium before the FF are greater than 1 in channels 19, which indicates that these three elements were enriched on particles in channels 19. The Rij values of cadmium, arsenic, and selenium after the FF are greater than those before the FF, which indicates that these three elements were enriched on pre-existing particles in the process of flue gas passing through the FF. The Rij values of cadmium, arsenic, and selenium before and after the FF increase with the particle size decreasing, especially in channels 13, and the Rij

values of these elements in channel 1 are maximum values. That is because the particles with smaller sizes have more relative surface areas and the three gaseous elements in flue gas are easy to enrich on them. Size-classified distributions of elements in PM2.5 were calculated by the elemental fractional mass distributions in PM2.5 and the mass concentration distributions of PM2.5, and the results are shown in Figure 13. As shown in Figure 13, the sizeclassified distribution curves of all tested elements are nearly in line with the mass concentration distribution curves of PM2.5, which indicates that the elemental size-classified distributions are mainly determined by mass concentrations distributions of PM2.5 and have only a weak correlation with elemental fractional mass distributions. Figure 13 shows that the trends of the size-classified distributions of all elements before and after the FF are different, which indicates that these elements were re-distributed in the process of dust collection of the FF. The size-classified distribution curves of all elements after FF(2) are obviously above those after FF(3), which indicates that the pulse back blowing of the FF has significant influence on elemental sizeG


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Figure 10. Elemental fractional mass distributions in PM2.5 before and after the FF. “(1)” represents elemental fractional mass distributions in PM2.5 before the FF, and “(2)” represents after.

classified distribution in PM2.5 after the FF. The size-classified distributions of all elements are calculated by mass concentration distributions of PM2.5 and elemental fractional mass concentrations after the FF. The mass concentration distribution curves of PM2.5 after FF(2) are above those after FF(3), and the fractional mass concentrations of each element after FF(2) and FF(3) are the same; therefore, the reason why the size-classified distributions of all elements after FF(2) are above those after FF(3) is that the mass concentrations distribution of PM2.5 after FF(2) is above that after FF(3). Elemental fractional mass collection efficiencies of PM2.5 through the FF are calculated by the size-classified distributions of elements in PM2.5 before and after the FF, which are shown in Figure 14. As shown in Figure 14, the fractional mass collection efficiencies of silicon, aluminum, iron, calcium, and magnesium in PM2.5 are similar to the fractional collection mass efficiencies of PM2.5, which is because fractional mass distributions of these elements in all corresponding channels in PM2.5 before and after the FF are nearly the same in Figure 10. However, the fractional mass collection efficiencies of cadmium, arsenic, and selenium in PM2.5 are all lower than the fractional collection mass efficiencies of PM2.5, which is due to the increasing mass of cadmium, arsenic, and selenium caused by these gaseous elements in flue gas depositing onto pre-existing particles via surface condensation and reaction, or forming new particles by homogeneous nucleation. Figure 14 shows that the pulse back blowing of the FF can obviously reduce the elemental fractional mass collection efficiencies of PM2.5, which is due to the relatively lower fractional collection efficiencies of PM2.5 caused by the pulse back blowing. And the pulse back blowing of the FF can even make the fractional mass collection efficiencies of cadmium, arsenic, and selenium in the particles in 0.007−0.029 μm (channel 1) reduce

Figure 11. Relative enrichment factor of PM2.5 before the FF.

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

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Figure 13. Elemental size distribution in PM2.5 before and after the FF.

4. CONCLUSION

2.48, 5.55 and 6.77%, which are higher than those on other channels. That is because the particulates in 0.007−0.029 μm have relatively more surface areas and gaseous cadmium, arsenic, and selenium in flue gas are easy to enrich on them. Besides, the pulse back blowing of the FF can cause the higher partial concentration of particulates nearby the filter bags, which can increase the probability of the particulates meeting these three gaseous elements in the partial higher pressure near the surface of the filter bags, and many of these particulates measured by number concentration would be in the range 0.007−0.029 μm.

In this work, the generation and emission characteristics, morphological characteristics, and size-classified elemental compositions of PM2.5 are researched experimentally before and after a fabric filter (FF) at an industrial pulverized coal boiler. Sampling and measurement of PM2.5 in situ were taken with ELPI with a two-stage dilution sampling system. The morphological characteristics were analyzed by SEM. The sizeclassified elemental compositions were analyzed by EDX and I


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Figure 14. Elemental mass collection efficiency of PM2.5.

ICP-AES. Results are shown as follows: (1) The PM2.5 number size distribution before the FF displays a unimodal distribution, with a peak located between 0.07 and 0.12 μm. The PM2.5 number size distribution after the FF (after FF(3)) displays a bimodal distribution that is two sub-micrometer modes with peaks near 0.1 μm and 0.4−0.5 μm. The PM2.5 mass size distribution before the FF displays a unimodal distribution with the peak near 0.1 μm, but the mass size distribution of PM2.5 after

the FF (after FF(3)) shows no peak. The results in this work are not in accordance with the earlier research results, which is caused by different residence times of pulverized coal particles in the furnace. (2) The pulse back blowing of the FF has no prominent influence on characteristics of PM2.5 number and mass size distributions after the FF; however, the pulse back blowing of the FF exerts significant influence on PM2.5 number and mass concentrations after the FF, especially on the number J


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(5) Zhou, K. The Properties and Control of Fine Particulates Generated from Coal Combustion. Doctoral Academic Dissertation, Huazhong University of Science and Technology. 2011. (6) Hao, J.; Duan, L.; Yi, H.; Li, X.; Hu, J. The Physical and Chemical Characteristics of Inhalable Particulate Matter Generated from Combustion Sources; Science Press: Beijing, 2008 (Monograph). (7) Yi, H.; Hao, J.; Duan, L.; Tang, X.; Ning, P.; Li, X. Fuel 2008, 87, 2050−2057. (8) Ji, J.; Chen, A. Arrester Dedusting Technology in Boiler Flue Gas; China Electric Power Press: Beijing, 2006. (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) Gieré, R.; Blackford, M.; Smith, K. Environ. Sci. Technol. 2006, 40, 6235−6240. (14) Zhang, C.; Yao, Q.; Sun, J. Fuel Process. Technol. 2005, 86, 757− 768. (15) Wen, P.; Song, F.; Cheng, N.; Mu, L. J. Taiyuan Univ. Technol. 2014, 45, 712−717. (16) Bonin, M. P.; Queiroz, M. A. Fuel 1996, 75, 195−206. (17) Kang, Y. S.; Kim, S. S.; Hong, S. C. J. Ind. Eng. Chem. 2015, 30, 197−203. (18) Zhou, X. Shanxi Archit. 2011, 37, 195−196. (19) Zhao, Z.; Du, Q.; Zhao, G.; Gao, J.; Dong, H.; Cao, Y.; Han, Q.; Yuan, P.; Su, L. Energy Fuels 2014, 28, 4769−4780. (20) Lv, J.; Feng, J. Boiler Technol. 2005, 36, 21−24. (21) Zhang, H.; Lv, J.; Xu, X.; Zeng, R.; Yue, G. Chin. J. Power Eng. 2005, 25, 125−130. (22) Guo, X.; Hao, J.; Duan, L.; Yi, H.; Li, X. J. Tsinghua Univ., Sci. Technol. 2006, 46, 1991−1994. (23) Xu, M.; Yu, D.; Liu, X. Formation and Emission of Inhalable Particulate Matter Generated by Coal Combustion; Science Press: Beijing, 2009 (Monograph). (24) Zhuang, Y.; Biswas, P. Energy Fuels 2001, 15, 510−516. (25) Zhang, G. Aerosol Mechanics; China Environmental Science Press: Beijing, 1987 (Monograph). (26) Carr, R. C.; Smith, W. B. J. Air Pollut. Control Assoc. 1984, 34, 399−413. (27) Yi, H.; Guo, X.; Hao, J.; Duan, L.; Li, X. J. Air Waste Manage. Assoc. 2006, 56, 1243−1251. (28) Lee, W. K.; Liu, B. Y. Aerosol Sci. Technol. 1982, 1, 147−161. (29) Landahl, H. D.; Herrmann, R. G. J. Colloid Sci. 1949, 4, 103−136. (30) Payet, S.; Boulaud, D.; Madelaine, G.; Renoux, A. J. Aerosol Sci. 1992, 23, 723−735. (31) Yang, J.; Zhang, D. Design Guide of Fabric Filter; China Press: Beijing, 2012 (Monograph). (32) Booher, H. B.; Martello, D. V.; Tamilia, J. P.; Irdi, G. A. Fuel 1994, 73, 205−213. (33) Linak, W. P.; Wendt, J. O. L. Prog. Energy Combust. Sci. 1993, 19, 145−185. (34) Ratafia-Brown, J. A. Fuel Process. Technol. 1994, 39, 139−157. (35) Yu, D.; Xu, M.; Yao, H.; Liu, X.; Zhou, K. Chin. Sci. Bull. 2008, 53, 1593−1602.

and mass concentrations of PM0.007−0.029. (3) There appears a penetration window in nearly 0.1−1 μm; however, the removal efficiency of PM0.007−0.029 is lowest. (4) The pulse back blowing of the FF can reduce the removal efficiency of PM0.007−0.029 from 99.37% to 97.80%. (5) The microstructures of super-micrometer and sub-micrometer particles are different before and after the FF, but the ultrafine particles in 0.007−0.029 μm are nearly the same before and after the FF. (6) The elements can be classified into three groups according to the elemental fractional mass distributions in PM2.5 before the FF. Group 1 includes silicon and aluminum, which are enriched with the particle size increasing. Group 2 includes calcium, cadmium, arsenic, and selenium, which are enriched with the particle size decreasing. Group 3 includes iron and magnesium, of which elemental fractional mass distributions in PM2.5 vary little with variation of the particle size. (7) The lower filtration velocity of fabric filter and longer residence time near the filter bags can lead that gaseous cadmium, arsenic, and selenium in flue gas transforming into the PM2.5 or a part of the PM2.5 after the FF. This can be a probable approach of gaseous cadmium, arsenic, and selenium in flue gas transforming into the PM2.5 or a part of the PM2.5 after the FF, which makes the fractional mass distribution curves of these three elements after the FF higher than those after the FF. (8) The pulse back blowing of the FF has significant influence on elemental size-classified distribution in PM2.5 after the FF. (9) The fractional mass collection efficiencies of cadmium, arsenic, and selenium in the particles in 0.007−0.029 μm are relatively lower than other PM2.5, which is caused by their relatively greater surface areas and gaseous cadmium, arsenic, and selenium in flue gas are easy to enrich on them. Besides, the pulse back blowing of the FF can cause the higher partial concentration of particulates nearby the filter bags, which can increase the probability of the particulates meeting these three gaseous elements in the partial higher pressure near the surface of the filter bags, and many of these particulates measured by number concentration would be in 0.007−0.029 μm.

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AUTHOR INFORMATION

Corresponding Author

*E-mail: [email protected]. Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS This work was financially supported by the project supported by the Special Fund for the National Environmental Protection Public Welfare Industries of China (Grant 201009006), the National Science and Technology Support Project (2014BAA07B03) and the Science Foundation for Innovative Research Groups (51421063).

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REFERENCES

(1) Zhu, X.; Zhang, Y.; Zeng, L.; Wang, W. Res. Environ. Sci. 2006, 18, 1−5. (2) Dai, L.; Xue, Y.; Feng, Y.; Wu, J. Study on Source Apportionment of Particulate Matter in Ambient Air in Chengdu. Chinese Society for Environmental Sciences Academic Conference, 2009. (3) Xiao, Z.; Bi, X.; Feng, Y.; Wang, Y.; Zhou, J.; Fu, X.; Weng, Y. Res. Environ. Sci. 2012, 25, 549−555. (4) Yan, X. The Character and Source Apportionment of Fine Particles PM2.5 in Baoshan District, Shanghai. Master’s Academic Dissertation, East China University of Science and Technology: Shanghai, China, 2011. K


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