Impact of Bed Particle Size Distribution on the Distribution of...

IMPACT OF BED PARTICLE SIZE DISTRIBUTION ONTHE DISTRIBUTION OF HEAVY METAL DURINGDEFLUIDIZATION PROCESS IN FLUIDIZED BEDINCINERATOR

Min-Hao Wu,1 Kaimin Shih,2 and Chiou-Liang Lin11Department of Civil and Environmental Engineering, National University ofKaohsiung, Kaohsiung, Taiwan2Department of Civil Engineering, The University of Hong Kong, Hong Kong

In this study, artificial waste was used to investigate the impact of bed particle-size

distributions (narrow, flat, and Gaussian) on heavy-metal distributions in the particles in

the bottom ash during defluidization in a fluidized bed incinerator. When the particle size

was less than 0.500mm, the heavy-metal concentration within the particles tended to

increase, and when the particle size was greater than 0.850mm, the heavy-metal concen-

tration showed a substantial increase. With regard to heavy-metal capture, the formation

of the low-melting eutectic complexes was produced by the combination of heavy metals

with Na. The capturing effect of the liquid eutectic material may be a more important mech-

anism than adsorption. The comparison of heavy-metal concentrations at different

particle-size distributions showed that heavy-metal concentrations in large and small parti-

cles with narrow particle distributions and their total retention rates were higher than the

corresponding values in the case of flat and Gaussian particle distributions.

Keywords: Agglomeration; Bottom ash; Cadmium; Chromium; Lead

INTRODUCTION

Fluidized bed reactors are widely used for various purposes, such as for wasteincineration, gasification, pyrolysis, and biomass fuel combustion (Arena et al., 2010;Chen et al., 2007; Srinivasa Rao and Venkat Reddy, 2007). However, during theoperation of fluidized bed reactors using complex mixtures of feed materials, stickysubstances may accumulate. The gradual accumulation of these substances can causethe bed material to agglomerate into large blocks. Previous studies have demon-strated that many kinds of elements can cause stickiness, and the results of these stu-dies are summarized in Table 1. It was found that alkali group elements such as Naand K are among the major materials that cause agglomeration. The generation ofagglomerated materials can affect the operating conditions of the fluidized bed by

Received 6 July 2011; revised 22 February 2012; accepted 22 February 2012.

Address correspondence to Chiou-Liang Lin, Department of Civil and Environmental Engineering,

National University of Kaohsiung, 700, Kaohsiung University Rd., Nanzih District, 811, Kaohsiung,

Taiwan. E-mail: [email protected]

Combust. Sci. Technol., 184: 811–828, 2012

Copyright # Taylor & Francis Group, LLC

ISSN: 0010-2202 print=1563-521X online

DOI: 10.1080/00102202.2012.669802

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affecting parameters such as the minimum fluidization velocity, bubble size, bubblefrequency, and rise velocity (Tardos and Pfeffer, 1995). Agglomeration can evencause the bed to stop functioning properly as a result of defluidization. Therefore,agglomeration issues are among the most difficult and perplexing problems in theuse of fluidized bed reactors.

Many researchers have explored the causes of fluidized bed agglomeration.Skrifvars et al. (1992, 1994) pointed out that the phenomena of agglomerationand defluidization originate from the stickiness of bed materials, and that in additionto the properties of the particles, the most common reasons for stickiness include (1)the presence of sticky sintered plastic material and the production of vitrifiedmaterial and (2) the production of liquid substances by chemical reactions or bythe melting of materials. Therefore, alkali group elements, when present in waste,can react with the bed material or other elements in the waste to produce liquideutectic materials that adhere to the surface of the bed, causing the bed materialto become sticky and leading to agglomeration and defluidization (Lin and Wey,2004).

Additionally, operating parameters are also important factors in causingagglomeration and defluidization. Langston and Stephens (1960), Moseley andO’Brien (1993), and Wank et al. (2001) have pointed out that the surface area ofthe bed material; operating temperature; gas velocity; the density, size, surface area,particle-size distribution, etc., of the bed particles; and other parameters are allrelated to the occurrence of agglomeration and defluidization. Among these factors,particle-size distribution has a particularly high impact on bed fluidization qualityand the conversion rate of chemical reactions, and also indirectly affects bed agglom-eration and defluidization. Ray et al. (1987) and Pell (1990) have shown that thebed-material particle-size distribution affects the minimum fluidization velocity,terminal velocity, elutriation velocity, rates of chemical reactions, etc.; further,particle-size distribution also affects the dynamic properties of fluidized beds.Gauthier et al. (1999) indicated that a narrow range of particle diameters can beemployed to increase the operational stability of fluidized bed reactors by, forexample, reducing the occurrence of bed-material separation. A wide range of par-ticle diameters can increase parameters such as mobility and chemical conversionrates.

Although Na metal in the waste can cause bed agglomeration and defluidiza-tion, at high combustion temperatures, other metals such as Cd, Pb, and Cr may

Table 1 Possible elements inducing agglomeration in the fluidized bed

Na K Mg Ca Si Cl S Fe V

Ghaly et al., 1993 .Conn, 1995 . . .Mikami et al., 1996 .Steenari et al., 1998 . . . . .Wang et al., 1999 . . .Lin et al., 2003 . . . . . .Atakul et al., 2005 . . .Lin et al., 2010a .

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evaporate and form metal vapor or particles, which may then be released into theenvironment along with the exhaust gas or may get attached to fly ash or bottomash. The transport behavior of different heavy metals varies depending on theirphysical properties and the forms of the compounds in which they are present. Ingeneral, heavy-metal compounds with high volatility are mainly found in fly ashor flue gases, while heavy-metal compounds with high boiling points are mainlyfound in bottom ash or in the large particles of fly ash. Studies by Fournier et al.(1991) and Reimann (1989) have also suggested that the distribution of heavy metalsduring combustion is related to heavy-metal compound properties and boilingpoints. Metals with high boiling points such as Cr are mainly found in bottomash, whereas volatile heavy metals such as Cd mainly form vapor and leave the incin-eration system with the exhaust gas.

Apart from the properties of the heavy metal, the operating conditions ofincinerators comprise another important set of factors that affect the distributionof heavy metals. Studies by Hiraoka and Takeda (1980) and Gerstle and Albrinck(1982) have indicated that combustion temperature can affect the heavy-metal distri-bution ratio in bottom ash. Increasing the temperature results in a reduction in thezinc, lead, and cadmium contents in bottom ash, while increasing the arsenic, cad-mium, mercury, zinc, and lead contents in the emitted exhaust gas. Wey et al.(1996) pointed out that the lead, chromium, and cadmium contents in fluidized sandbeds decreased in the order Pb>Cr>Cd. The distribution of various heavy-metalcompounds is related to the properties of the heavy metal; it is also strongly relatedto the combustion temperature, operating gas-flow rate, feed ingredient load, and thecompositions of other elements (such as oxygen, chlorine, and sulfur).

The emission of heavy-metal pollutants is related to the operating conditions.Furthermore, changes in the particle-size distribution of the fluidized bed materialaffect fluidization. Altered particle-size distributions may directly cause changes inthe fluidized bed operating parameters, while at the same time indirectly causingchanges to the heavy-metal pollutant distribution. Few previous studies on fluidizedbed incineration have reported the effects of bed particle-size distribution onagglomeration=defluidization and heavy-metal pollutant emission. Therefore, inthe current study, artificial waste with different compositions to mimic conditionsthat promote agglomeration is used to investigate the effects of three differentbed-material particle-size distributions (narrow, flat, and Gaussian) on the depo-sition of heavy metals in bottom ash during agglomeration and defluidization.Experimental conditions include the presence or absence of Na, changes in Naconcentration, and the addition of Ca and other elements. The results of this workcan be used as a reference for the operation of fluidized bed combustion reactors.

EXPERIMENTAL

Apparatus

Figure 1 depicts the laboratory-scale fluidized bed incinerator used in theseexperiments. The main furnace was a stainless steel pipe with a diameter of 0.09m(AISI 310) and a height of 1.2m. The bottom of the incinerator was a porous platemade of stainless steel, and the pore area was 15.2%. A temperature-feedback

HEAVY METAL DISTRIBUTION DURING DEFLUIDIZATION 813

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control system together with a thermocouple was used to control the system tem-perature. A cyclone dust collector was installed at the gas exhaust, which was con-nected to a bag-filter-type dust collector to control particulate pollutants.

Artificial Wastes

Since most wastes contain alkali group elements (such as Na), which may causeagglomeration and defluidization during the fluidized bed combustion process,elemental Na was added to the artificial waste during experiments to formlow-melting-point eutectic materials. In addition, Ca was added in some experimentsto examine its effect on agglomeration and on the heavy-metal distribution. Theheavy metals added to the waste were primarily chromium, lead, and cadmium.The addition of these metals was accomplished by dissolving the metal nitrates indeionized water, which was then added to the artificial waste. The artificial wastecomprised primarily wood sawdust (1.6 g) and polypropylene (PP) (0.35 g). Thewood sawdust was willow that was obtained from a sawmill. To this material,1mL of the heavy-metal-nitrate aqueous solution was added, and the resulting mix-ture was wrapped in a polyethylene (PE) plastic bag (0.29 g). Each bag of artificialwaste had a final weight of 3.24 g. The artificial waste was enclosed in a PE bagand had a cylindrical shape with a diameter of 1.2 cm and a length of 3.0 cm. Theweight percentage of Pb, Cd, and Cr was 0.7% in each artificial waste bag (3.24 g).The elemental analysis of the sawdust, polypropylene, and polyethylene wasconducted using an elemental analyzer (EA), and the results are listed in Table 2.Table 3 shows the composition of the artificial waste and the experimentalconditions.

Figure 1 The bubbling fluidized bed reactor. (1) PID controller, (2) blower, (3) flow meter, (4) thermo-

couple, (5) pressure transducer, (6) electric resistance, (7) sand bed, (8) feeder, (9) cyclone, (10) filter,

and (11) induced fan.

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Bed Materials

The bed material used in the experiment was silica sand with a density of2,600 kg=m3. The height of the bed material was 18 cm, approximately twice thediameter of the incinerator (H=D¼ 2), and the silica sand was sieved according tothe method of Gauthier et al. (1999) with an ASTM standard sieve. Taking thedesired particle-diameter ratios into consideration, three different particle-size distri-butions (PSD) were prepared while maintaining dsv for each at about 0.725mm. Thevalue of dsv is calculated using the following equation, and Table 4 presents acomposite of the three PSD values.

dsv ¼1

P

i

xidpi

where xi is the ratio of weight (%) xi and dpi is the average diameter (mm).

Experimental Procedure

Before the experiment, the minimum fluidization velocity was measuredaccording to the method of Lin et al. (2002). According to the results, the minimum

Table 3 Operating conditions for each experiment

Temp.

(�C)Gas velocity

(m=s)

Na conc.

(%)

Ca conc.

(%)

Type of powderDefluidization

time (sec)Run Narrow Flat Gaussian

1 800 0.163 – – . —

2 800 0.163 – – . —

3 800 0.163 – – . —

4 800 0.163 0.7 – . 1,840

5 800 0.163 0.7 – . 1,300

6 800 0.163 0.7 – . 1,740

7 800 0.163 0.5 – . 2,840

8 800 0.163 0.5 – . 2,100

9 800 0.163 0.5 – . 2,500

10 800 0.163 0.9 – . 1,240

11 800 0.163 0.9 – . 1,040

12 800 0.163 0.9 – . 1,220

13 800 0.163 0.7 0.7 . 2,160

14 800 0.163 0.7 0.7 . 1,960

15 800 0.163 0.7 0.7 . 2,020

Table 2 Elemental analysis of different wastes by weight

Species C (%) H (%) N (%) O (%)

Sawdust 43.12 5.80 5.01 46.07

Polypropylene (PP) 86.16 12.20 1.12 0.52

Polyethylene (PE) 85.71 13.04 0.86 0.39


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fluidization velocities were different for different PSDs. The values of the minimumfluidization velocity for the three PSDs at 800�C were 0.125m=s (narrow), 0.126m=s(flat), and 0.113m=s (Gaussian). The excess air was approximately 40% (62L=min)during the combustion process, and the operating temperature was maintained at800�C. Operating conditions are shown in Table 3. When the sand bed was heatedto a stable preset temperature, the blower was turned on to establish airflow atthe desired rate. Air was preheated by passing it through a preheating chamber. Arti-ficial waste was delivered to the combustion chamber through the feed inlet at a feedrate of 3.24 g=(20 s). During experimental operation, in addition to the visual obser-vation of defluidization, the pressure change between the sand bed and the freeboardarea was monitored as an indicator of the occurrence of defluidization using twopressure probes connected to a pressure transmitter with a range of 0 to 1,000mmH2O. When defluidization occurred, the artificial waste feed was stopped andallowed to cool down. The bed material was removed and analyzed with anASTM standard sieve to measure changes in the bed material particle-size distribu-tion. The particle-size screening intervals were >1.180mm, 1.180–1.000mm, 1.000–0.850mm, 0.850–0.710mm, 0.710–0.600mm, 0.600–0.500mm, 0.500–0.355mm, and<0.355mm.

The total weight of the bed material for each particle diameter was recorded,and samples were taken from each particle-size fraction to analyze the heavy-metalconcentrations. In order to analyze heavy-metal concentrations, solid samples werefirst treated using microwave digestion to completely release heavy metals from theparticulate material. For digestion, the bottom ash sample (0.5 g), 9mL concentratednitric acid, and 3mL concentrated hydrofluoric acid were added to the vessel. Theoven was set to reach a temperature of 180� 5�C over 10min and was then left at180� 5�C for a duration of 10min. The heavy-metal concentration of this digestedsample was then analyzed using an inductively coupled plasma spectrometer (ICP).In addition, the agglomerated material was analyzed using scanning electron micro-scopy=energy dispersive spectrometry (SEM=EDS) to examine the agglomerationstatus of the bed material particles.

Table 4 Particle size distributions of different powder types

Type of powder Weight (%) xi Sieves no. Sieves (mm) Average diameter di (mm)

Narrow 100 30–20 600–850 725.0

Gaussian 8 45–35 355–500 427.5

25 35–25 500–710 605.0

35 25–20 710–850 780.0

23 20–18 850–1000 925.0

9 18–16 1000–1180 1090.0

Flat 17 45–35 355–500 427.5

17 35–25 500–710 605.0

19 25–20 710–850 780.0

23 20–18 850–1000 925.0

24 18–16 1000–1180 1090.0

dsv¼ 725.0

�� The dsv calculation formula is: dsv ¼ 1P

i

xidpi

.

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RESULTS AND DISCUSSION

Changes in Bed Particle Distribution

During operation of the fluidized bed, collisions between bed particles and thefriction between the bed and the furnace wall cause a gradual decline in bed particlesize. Figure 2 shows the particle distribution after agglomeration=defluidization inthe presence of different additives. The figure shows that the distribution range ofbed particles widened. The widening was especially significant in the case of the nar-row distribution. In the absence of Na, there was a large increase in the number ofparticles smaller than 0.600mm, suggesting a gradual decrease in particle size causedby fluidization. Vaux and Fellers (1981) and Shamlou et al. (1990) have proposedthat thermal, chemical, static mechanical, and kinetic stresses during fluidizationall cause bed particle attrition, leading to a decrease in particle size. Moreover, theinside of a combustion chamber is a high-temperature environment, and thermalstress may therefore also have an impact on changes in particle size. Chirone et al.(1985) and Lin and Wey (2003) pointed out that the thermal shock generated inthe incineration process within the thermal fluidized bed also causes a decrease inparticle size. Hence, the bed particle size tends to decrease after thermal fluidization.

When agglomeration occurs within the reactor, the changes in particle size aremore complicated. From Figure 2, we see that in addition to the general tendencytowards a decline in particle sizes, some large particles have a tendency to increasein size. The resulting amount of large particles was greater when Na and Ca wereadded simultaneously than when only Na was added, but the amount of large par-ticles was higher in both these cases than when neither Na nor Ca were added. On

Figure 2 Particle size distribution after agglomeration=defluidization with the addition of different

additives.


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the basis of these results, we speculate that low-melting eutectic compoundsare formed from Na and the impurities in the silica sand during agglomeration=defluidization. These eutectic compounds have lower melting points and thereforebecome viscous molten substances that adhere to the bed particles. If the kineticenergy (separation force) of the bed particles themselves is not sufficient in orderto overcome the adherent forces of the liquid substance, the bed particles willagglomerate (Lin et al., 2010b). Subsequently, the diameter of bed particles willincrease.

According to the literature, the presence of Ca generates high-melting-pointcompounds and therefore increases the melting point of the overall resultant com-pounds and mixtures (Atakul et al., 2005). Lin and Wey (2004) and Lin et al.(2009) reported a delayed effect of defluidization under different operating con-ditions with the addition of Ca. Therefore, the bed material remains fluidized fora long time and contributes to an increased ratio of small particles owing to attrition.However, Figure 2 shows that with the addition of Ca, the concentration of smallparticles became lower than that corresponding to the other two operating con-ditions, whereas the ratio of large particles was higher than that found without Caaddition. This suggests that in spite of the attrition effect, the bed particles do nottend to decrease in particle size due to agglomeration.

Heavy-Metal Distribution in Bed Particles Under Different OperatingConditions

In order to understand the rates of heavy-metal retention corresponding to dif-ferent bed-particle sizes in the experiment, we collected bed particles after agglomer-ation=defluidization and analyzed them. We divided these particles into eight sizeranges and analyzed the concentrations of three heavy metals. Figure 3 shows theheavy-metal concentration distributions for different particle-size fractions in thebottom ash under different additive conditions. Figure 4 shows the heavy-metal con-centration distributions for the different particle sizes in the bottom ash for differentNa concentrations. From the results shown in Figures 3 and 4, we find that heavy-metal concentrations were highest in the largest and smallest particle-size fractionsmeasured. In general, when the particle size was smaller than 0.500mm, theheavy-metal concentration tended to increase, and when the particle size was largerthan 0.850mm, the heavy-metal concentration also increased substantially.

Small particles are primarily generated from attrition during fluidized bedoperation. Small particles have a high relative surface area and thus readily adsorbheavy metals. Therefore, the smaller the bed particles become, the greater the tend-ency for heavy metals to adsorb onto them, and thus the heavy-metal concentrationin the bed particles increases. However, the generation of large particles is caused bylow-melting-point eutectic compounds forming molten liquid materials duringhigh-temperature operation. The viscosity of this liquid material causes agglomer-ation of bed particles and therefore increases the bed particle size. Although thesurface area of these large bed particles is rather small, the heavy-metal concen-tration is still fairly high, suggesting that adsorption may not be the only mechanismof heavy-metal capture by bed particles. Another possibility is that heavy metalsand Na may combine to form low-melting eutectic compounds. Alternatively,

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incoming heavy metals may come into contact with and stick to or cover molten Na-containing eutectic compounds formed under thermal melting conditions, andthereby increase the heavy-metal concentrations in bed particles. Figure 5 shows aSEM=EDS analysis of the surface properties of agglomerated bed particles. Theresults show that in addition to Na, heavy metals (Cd, Pb, and Cr) also exist inthe agglomerate. This finding suggests that heavy metals may form eutectic

Figure 3 Heavy metal concentration distribution with the addition of different additives.


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compounds with Na, or may stick to or cover the Na-containing liquid eutecticmaterial, thereby causing heavy-metal retention. Furthermore, a comparison ofthe different additive conditions (Figure 3) shows that the heavy metal concentra-tions within small bed particles did not differ significantly between the no-additives,Na-addition, and Na þCa-addition conditions. Thus, the adsorption ability ofsmall bed particles was not significantly different in the presence or absence of

Figure 4 Heavy metal concentration distribution with the addition of different Na concentrations.

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Na. However, for large bed particles, heavy-metal concentrations under the Na orNa þCa addition conditions were much greater than the concentrations in theabsence of Na. This suggests that adsorption is not the main mechanism ofheavy-metal capture for large bed particles, but that the formation of low-melting-point eutectic heavy-metal=Na compounds or the capturing effect of liquid eutecticmaterials may be more important mechanisms.

Figures 3 and 4 show that the heavy-metal concentration in bed particles isgenerally lowest when no Na is added. After Na is added, heavy-metal concentra-tions in different-sized particles tend to increase. Although adding Na-containingeutectic materials during the fluidization process produces particle agglomerationand therefore increases the risk of defluidization, the increased heavy-metal concen-tration within bed particles (caused by the formation of low-melting eutectic com-pounds by heavy metals and Na, or by the adherence on contact of heavy metalsto molten Na-containing eutectic compounds liquefied under thermal meltingconditions) decreases the heavy-metal emission volume. Therefore, the large agglom-erated bed particles have high heavy-metal concentrations.

Figure 5 FE-SEM=EDS analysis results of agglomerated material. (Figure is provided in color online.)


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Heavy-Metal Retention Rate of Bed Particles Under DifferentOperating Conditions

Figures 6 and 7 show heavy-metal retention rates corresponding to bed parti-cles of different sizes under different operating conditions. These rates were calcu-lated by dividing the total heavy-metal quantities retained by each particle-sizefraction by the total incoming metal quantity. These results show that in spite of

Figure 6 Heavy metal retention rate distribution with the addition of different additives.

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the high heavy-metal concentrations in the larger bed particles, the total quantities ofheavy metals they retained were lower than those of other particles owing to the lowabundance of large particles in the reactor bed. Meanwhile, mid-sized particles (ran-ging from 0.500–0.850mm) retained more heavy metals owing to their higher abun-dance, although these particles had relatively low heavy-metal concentrations. Theabundance of small particles was lower than that of mid-sized particles but higherthan that of large particles, and small particles had high heavy-metal concentrations.

Figure 7 Heavy metal retention rate distribution with the addition of different Na concentrations.


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Therefore, the total amount of heavy metals retained by small particles wasrelatively high.

Figures 8 and 9 show the ratio of total heavy-metal content in bed particlesto the total incoming heavy-metal content under different operating conditions.The differences between the defluidization times in different experimental trialsindirectly causes differences between the total incoming amounts of heavy metals

Figure 9 Heavy metal retention rate with the addition of different Na concentrations.

Figure 8 Heavy metal retention rate with the addition of different additives.

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corresponding to these trials. If we compare the total heavy-metal retention in thesilica sand with the total amount of incoming heavy metals, Cr generally has thehighest retention rate, followed by Pb and Cd. The three heavy metals Cd, Pb,and Cr have high, intermediate, and low volatilities, respectively. Hence, Cr is theheavy metal with the highest boiling point, and it also had the highest concentrationwithin the bed particles. According to Chen et al. (1997), when silica sand is used asthe bed, it adsorbs large amounts of heavy metals during operation. The adsorptionefficiencies observed in that study were in the order Cr>Pb>Cd, which followed theorder of the boiling points of the metals. Therefore, on the basis of both literaturestudies and our current experiments, the relative rates of heavy-metal adsorptiononto sand are suggested to correspond to the relative boiling points of the heavymetals.

Heavy-Metal Distribution Within Bed Particle-Size Distributions

Figures 3 and 4 show heavy-metal concentration distributions for the three dif-ferent particle-size fractions considered. In general, under the condition of a narrowparticle-size distribution, the heavy-metal concentrations for both large particles andsmall particles were higher than those for particles under the flat or Gaussian distri-bution conditions, immediately followed by the Gaussian distribution with inter-mediate concentrations. The comparison of heavy-metal retention rates in bedparticles in Figures 8 and 9 shows that, under most conditions, heavy-metal retentionrates were higher for the narrow particle-size distribution than for the other two dis-tributions studied, with the results of the Gaussian distribution being the secondhighest. Gauthier et al. (1999) indicated that separation behavior generally occurredin flat distribution fluidization. The proportion of main particles was greater thanthat of extreme particles for the Gaussian distribution, such that the influence ofthe extreme particles was not significant. Therefore, the Gaussian distribution beha-vior was similar to and tended to co-occur with the narrow distribution. Narrow andGaussian distributions showed better mixing results, and problems such as unevenmixing or bed particle detention were less likely to occur in the case of these distribu-tions; consequently, particle agglomeration was less probable in the case of these dis-tributions. Meanwhile, the degree of mixing in the case of narrow and Gaussiandistributions was higher than that in case of flat distribution. Therefore, in the incin-eration process, bed particles with narrow and Gaussian distributions were morelikely to come into contact with the waste than particles with the flat distribution,and this increased contact corresponds to increasing adsorption rates.

However, in some of the tests, the differences between the adsorption rates forthe three bed-particle distributions were not obvious. In the case of the flat distri-bution, since there were no significant differences in the amounts of differently sizedparticles, the proportion of small particles was higher than that in the narrow andGaussian distributions. Although the fraction of small particles in the narrow andGaussian distributions showed a tendency to increase after the fluidization process,the amount of small bed particles was still lower under these conditions than in theflat distribution. The higher concentration of small bed particles in the flat distri-bution greatly enhanced the rate of heavy-metal adsorption. Therefore, despite thelowest degree of bed fluidization and a decreased degree of contact between bed


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particles and waste for the flat distribution, the increase in adsorption by small par-ticles led to heavy-metal retention rates for this particle distribution that were notsignificantly different from the other two distributions in some tests.

CONCLUSIONS

In this study, we used simulated waste with different compositions toinvestigate the impact of three different particle-size distributions (narrow, flat,and Gaussian) on the heavy-metal distribution in bottom ash during defluidization.The results showed that when no Na was added, the particle size graduallydecreased, owing to bed-material attrition and thermal shock during the incinerationprocess. However, when Na was added, low-melting eutectic compounds would forma molten liquid material that then became sticky and caused bed agglomeration,thereby increasing particle size.

Additionally, the large and small particles had the highest concentrations ofheavy metals. Generally, heavy-metal concentrations increased with decreasing sizewhen the particle size was less than 0.500mm, and heavy-metal concentrations alsoshowed a dramatic increase when the particle size was greater than 0.850mm. In thelarge particle bed, the elevated heavy-metal concentrations resulting from Na or NaþCa addition were much higher than those observed when no Na was added. Theseresults suggest that the capturing effects of the low-melting eutectic compounds gen-erated from heavy metals and Na, or by the liquid eutectic material, are likely to be amore important mechanism. The heavy-metal concentrations within large and smallparticles and their total retention rates were higher for the narrow particle distri-bution than for the flat or Gaussian particle distributions, with the Gaussian distri-bution having the second highest retention rates. Since mixing effects were greaterwith narrow and Gaussian distributions, the opportunity for bed-waste contact dur-ing the incineration process was greater for the narrow and Gaussian distributionsthan for the flat distribution, and therefore resulted in increased retention rates.

REFERENCES

Arena, U., Zaccariello, L., and Mastellone, M.L. 2010. Gasification of natural and wastebiomass in a pilot scale fluidized bed reactor. Combust. Sci. Technol., 182, 625–639.

Atakul, H., Hilmioglu, B., and Ekinci, E. 2005. The relationship between the tendency oflignites to agglomerate and their fusion characteristics in a fluidized bed combustor. FuelProcess. Technol., 86, 1369–1383.

Chen, J.C., Wey, M.Y., and Wu, H.Y. 2007. Emission characteristics of chlorobenzenes,chlorophenols and dioxins during waste incineration with different additives. Combust.Sci. Technol., 179, 1039–1058.

Chen, J.C., Wey, M.Y., and Yan, M.H. 1997. Theoretical and experimental study of metalcapture during incineration process. J. Environ. Eng., 123, 1100–1106.

Chirone, R., D’Amore, M., Massimilla, L., and Mazza, A. 1985. Char attrition during thebatch fluidized bed combustion of coal. AIChE J., 31, 812–820.

Conn, R.E. 1995. Laboratory techniques for evaluating ash agglomeration potential inpetroleum coke fired circulating fluidized bed combustors. Fuel Process. Technol., 44,95–103.

826 M.-H. WU ET AL.

Dow

nloa

ded

by [

Chi

ou-L

iang

Lin

] at

18:

59 1

4 M

ay 2

012

Fournier, D.J., Whitworth, W.E., Lee, J.W., and Waterland, L.R. 1991. The fate of tracemetals in a rotary kiln incinerator with a venturi=packed column scrubber, EPA=600=S2–90=043 Feb, National Technical Information Service, Springfield, VA.

Gauthier, D., Zerguerras, S., and Flamant, G. 1999. Influence of the particle size distributionof powders on the velocities of minimum and complete fluidization. Chem. Eng. J., 74,181–196.

Gerstle, R.W., and Albrinck, D.N. 1982. Atmospheric emissions of metals from sewage sludgeincineration. Journal of Air Pollution Control Association, 32, 1113–1123.

Ghaly, A.E., Ergudenler, A., and Laufer, E. 1993. Agglomeration characteristics of aluminasand-straw ash mixtures at elevated temperatures. Biomass Bioenergy, 5, 467–480.

Hiraoka, M., and Takeda, N. 1980. Behavior of hazardous substances in stabilization and sol-idification processes of industrial wastes. In R.B. Pojasek (Ed.) Toxic and HazardousWaste Disposal, vol. 3, Ann Arbor Science, Ann Arbor, MI, pp. 107–124.

Langston, B.G., and Stephens, F.M. 1960. Self agglomerating fluidized bed reduction.J. Metals, 12, 312–316.

Lin, C.L., Chang, S.H., and Peng, T.H. 2010b. Investigation on the emission of heavy metalsin fluidized bed incineration during agglomeration=defluidization process. Energy Fuels,24, 2910–2917.

Lin, C.L., Kuo, J.H., Wey, M.Y., Chang, S.H., and Wang, K.S. 2009. Inhibition and pro-motion: The effect of earth alkali metals and operating temperature on particle agglom-eration=defluidization during incineration in fluidized bed. Powder Technol., 189, 57–63.

Lin, C.L., Tsai, M.C., and Chang, C.H. 2010a. The effects of agglomeration=defluidization onemission of heavy metals for various fluidized parameters in fluidized-bed incineration.Fuel Process. Technol., 91, 52–61.

Lin, C.L., and Wey, M.Y. 2003. Effects of high temperature and combustion on fluidizedmaterials attrition in fluidized bed. Korean J. Chem. Eng., 20, 1123–1130.

Lin, C.L., andWey, M.Y. 2004. The effect of mineral compositions of waste and operating con-ditions on particle agglomeration=defluidization during incineration. Fuel, 83, 2335–5343.

Lin, C.L., Wey, M.Y., and You, S.D. 2002. The effect of particle size distribution on minimumfluidization velocity at high temperature. Powder Technol., 126, 297–301.

Lin, W., Johansen, K.D., and Frandsen, F. 2003. Agglomeration in bio-fuel fired fluidized bedcombustors. Chem. Eng. J., 96, 171–185.

Mikami, T., Kamiya, H., and Horio, M. 1996. The mechanism of defluidization of ironparticles in a fluidized bed. Powder Technol., 89, 231–238.

Moseley, J.L., and O’Brien, T.J. 1993. A model for agglomeration in a fluidized bed. Chem.Eng. Sci., 48, 3043–3050.

Pell, M. 1990. Gas fluidization. In J.C. Williams and T. Allen (Eds.), Handbook of PowderTechnology, vol. 8, Elsevier, Amsterdam, pp. 9–19.

Ray, Y.C., Jiang, T.S., and Wen, C.Y. 1987. Particle attrition phenomena in a fluidized bed.Powder Technol., 49, 193–206.

Reimann, D.O. 1989. Heavy metals in domestic refuse and their distribution in incinerationresidues. Waste Manage. Res., 7, 57–62.

Shamlou, P.A., Liu, Z., and Yates, J.G. 1990. Hydrodynamic influences on particle breakagein fluidized beds. Chem. Eng. Sci., 45, 809–817.

Skrifvars, B.J., Hupa, M., Backman, R., and Hiltunen, M. 1994. Sintering mechanisms ofFBC ashes. Fuel, 73, 171–176.

Skrifvars, B.J., Hupa, M., and Hiltunen, M. 1992. Sintering of ash during fluidized bed com-bustion. Ind. Eng. Chem. Res., 31, 1026–1030.

Srinivasa Rao, K.V.N., and Venkat Reddy, G. 2007. Effect of distributor design on tempera-ture profiles in fluidized bed during the combustion of rice husk. Combust. Sci. Technol.,179, 1589–1603.


Dow

nloa

ded

by [

Chi

ou-L

iang

Lin

] at

18:

59 1

4 M

ay 2

012

Steenari, B.M., Lindqvist, O., and Langer, V. 1998. Ash sintering and deposit formation inPFBC. Fuel, 77, 407–417.

Tardos, G., and Pfeffer, R. 1995. Chemical reaction induced agglomeration and defluidizationof fluidized beds. Powder Technol., 85, 29–35.

Vaux, W.G., and Fellers, A.W. 1981. Measurement of attrition tendency in fluidization.AIChE Symp. Ser., 77, 107–115.

Wang, K.S., Chiang, K.Y., Lin, S.M., Tsai, C.C., and Sun, C.J. 1999. Effects of chlorides onemissions of toxic compounds in waste incineration: Study on partitioning characteristicsof heavy metal. Chemosphere, 38, 1833–1849.

Wank, J.R., George, S.M., and Weimer, A.W. 2001. Vibro-fluidization of fine boron nitridepowder at low pressure. Powder Technol., 121, 195–204.

Wey, M.Y., Huang, J.H., and Chen, J.C. 1996. The behavior of heavy metal Cr, Pb and Cdduring waste incineration in fluidized bed under various chlorine additives. J. Chem. Eng.Jpn., 29, 743–752.

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