Modeling Mercury Capture in Coal-Fired Power Plant Flue Gas

Elemental mercury vapor capture by powdered activated carbon in a fluidized bed reactor. Fabrizio Scala , Riccardo Chirone , Amedeo Lancia. Fuel 2011 ...
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Ind. Eng. Chem. Res. 2004, 43, 2575-2589

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Modeling Mercury Capture in Coal-Fired Power Plant Flue Gas Fabrizio Scala* Istituto di Ricerche sulla Combustione, CNR, P.le Tecchio 80, 80125 Napoli, Italy

Mercury capture from coal-fired power plant flue gas in the ductwork and on the fabric filter by powdered activated carbon injection was simulated by means of a detailed adsorption model. The model is based on material balances in both gaseous and adsorbed phases along the duct/ filter length and inside the activated carbon particles. The growing filter cake moving boundary problem was solved with a double orthogonal collocation technique after a suitable immobilization of the moving front. Model results indicated that high mercury removal efficiencies in the duct are only obtained with the use of large sorbent loadings, because of the short gas/sorbent contact time. On the contrary, effective gas/sorbent contact in the fabric filter leads to high removal efficiencies with moderate sorbent consumption. In both cases, the sorbent feed rate can be lowered by selecting a reactive sorbent and by decreasing the sorbent average particle size or the operating temperature. Model results for in-duct mercury capture are validated against a bench scale experimental set of data recently reported in the literature. Further comparison of model predictions with available pilot- and full-scale data suggests that simulation of mercury capture in real power plants will require taking into account the additional mercury removal by deposited activated carbon on the duct walls. Introduction In the past decade public concern has risen over the potential risk of toxic elements emitted from anthropogenic sources. The U.S. 1990 Clean Air Act Amendments listed 189 hazardous air pollutants, 11 of which are metallic elements present in coal. Among these, mercury has drawn special attention, because of the high volatility of this element and the increasing level of bioaccumulation in the environment and in the food chain, with potential risks for human health. In 1997 the U.S. Environmental Protection Agency (EPA) completed a comprehensive Mercury Study Report to Congress,1 identifying mercury as the hazardous air pollutant of greatest potential public health concern. Although mercury emissions occur naturally, major pollution is caused by human activities.1-6 Recent studies recognized that about 70-85% of the total anthropogenic mercury emissions are caused by combustion sources, mainly coal-fired utilities and waste incinerators.1,5 Even if mercury emissions from coalfired plants are very low on a local scale, the large amounts of coal burned worldwide make this source of mercury pollution significant on a global scale. Reported values of mercury concentration in coal (present mainly as sulfide) range approximately from 0.01 to 10 ppm.6-11 At the typical combustion temperatures all the mercury, regardless of its initial chemical form, is readily vaporized as elemental mercury (Hg0) and exits the combustion chamber with the flue gas.2,6-8,12-17 Upon cooling, mercury partly remains in the metallic form and partly is transformed into oxidized mercury species, the proportion being a complex function of the excess air, the presence of sulfur dioxide and/ or chlorinated compounds in the flue gas, the gas cooling rate, the residence time in the system, and the contact * To whom correspondence should be addressed. Tel.: +39 081 7682969. Fax: +39 081 5936936. E-mail: scala@ irc.na.cnr.it.

with fly ash and/or other sorbent particles which may exhibit catalytic activity.6,8,15-24 It is important to distinguish between elemental and oxidized forms of mercury, the latter being more reactive and water soluble and in turn more effectively captured by wet or dry pollution control devices.6,17,20 Thermodynamic equilibrium calculations combined with oxidation rate evaluations11,17,19-21,25-28 as well as experimental measurements20,29 in coal combustor flue gases showed that a large fraction of emitted mercury is likely to be Hg0. Contrary to other trace metals, this volatile compound does not undergo condensation and passes through traditional air pollution control systems with very low capture efficiencies and is eventually emitted in the atmosphere.6,7,9,12,14,16,29-34 It has been shown that mercury in flue gases can be partly captured by adsorption on the unburned carbon in fly ash;2,10,18,35-38 welldesigned coal combustors, however, have little unburned carbon in fly ash so that this capture mechanism is often negligible. Elemental mercury emitted in the atmosphere is slowly oxidized and then solubilized in cloudwater and rainwater and transported to soil, rivers, and lakes, where it is transformed into more toxic organic species (for example, methyl mercury) and assimilated by animals and plants.2,6 The long lifetime in the atmosphere (on the order of 1 year) makes possible the transportation of mercury even at long distances from the source of emission.6,39 In the last few years industrialized countries have been setting progressively tighter limits for mercury emissions from waste incinerator facilities, where relatively high local mercury gas concentrations are generated. Due to increasing concern for mercury emissions from coal-fired power plants, stringent emission limits are under consideration in many countries also for these facilities. Regulations concerning mercury have been agreed upon within the United Nations Economic Commission for Europe in 1998. In December 2000 the U.S. EPA announced that emissions of mercury from coal-

10.1021/ie034143g CCC: $27.50 © 2004 American Chemical Society Published on Web 04/01/2004

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fired power plants will be regulated by December 2004, while compliance is expected to be required by December 2007. To meet future emission limits, specific technologies for mercury capture will have to be applied to power plants.40 Following extensive bench-scale,11,38,41-54 pilotscale,1,55-65 and full-scale57,65-67 experimental research carried out in the past decade, powdered activated carbon injection in flue gas upstream of a particulate matter control device (PMCD) has been indicated as the most mature technology for mercury capture in coal combustor flue gas.1 Both virgin and chemically impregnated activated carbons may be used; the latter ones have been reported to provide better mercury capture efficiencies, but are more expensive. The powdered activated injection technology offers a number of advantages over other possible technologies, such as relatively high mercury capture efficiency, production of a nonhazardous and noncorrosive solid byproduct (possibly regenerable), limited fire or explosion hazards, simple and low-cost process design, operation, and maintenance, and the possibility of retrofitting existing plants. This technology could be particularly costeffective when the flue gas treatment system employs dry sorbent injection for acid gas control; in this case activated carbon can be simply mixed with the sorbent and injected in the duct upstream of the PMCD. Most power plants are equipped with electrostatic precipitators (ESPs) or fabric filters (FFs) as PMCDs. The efficiency of the mercury capture by activated carbon injection has been reported to be largely influenced by the type of PMCD.1,60,63,65,68 In particular, the amount of carbon needed to achieve a specific level of mercury removal in facilities equipped with ESPs is substantially larger than that needed when an FF is the relevant PMCD. This is because of the much larger sorbent residence time in the system and the additional gas/sorbent contact provided on the bags of the FF where the injected sorbent accumulates as a cake. As a consequence, a larger carbon utilization leading to reduced operating costs is anticipated for FF-equipped facilities. It has been suggested that ESP-equipped power plants could be retrofitted with an additional high air-to-cloth ratio fabric filter to increase the overall mercury removal efficiency of the PMCD and to separate effectively the ESP-collected fly ash from the FFcollected sorbent.60,64,65,69 Despite the considerable experimental research carried out to date, however, few models for mercury adsorption by activated carbon injection in power plant flue gas have been proposed.70-72 The scope of the present work was to apply a detailed predictive tool for this process taking into account all relevant mechanisms and evaluating parameters from available literature data. The starting point was a recently presented model for the in-duct/fabric filter mercury capture in incinerator flue gas by powdered activated carbon injection.73,74 In this work the model was employed for the simulation of mercury capture in conditions typical of coal-fired power plants. Results obtained in this paper are relevant to plants where the PMCD is either an electrostatic precipitator or a fabric filter. Theory The proposed model is based on the following simplifying assumptions.

(1) The relevant mercury species in the gas phase is elemental mercury (Hg0), and no other mercury species are present. This assumption is based on the consideration that elemental mercury is much more difficult to capture with respect to oxidized forms, so that considering only this species would set the most conservative conditions. Moreover, it must be pointed out that precise prediction of mercury speciation in the flue gases is still beyond the present modeling capabilities and that the influence of simultaneous adsorption of different mercury species on the same activated carbon has not been investigated yet. (2) The adsorption process is not dependent on the flue gas composition apart from mercury concentration. This point will be discussed later on. (3) Activated carbon particles are supposed to be spherical, all of the same size, and uniformly dispersed in the duct/filter cake. (4) Both the gas and solid flow rates are constant. (5) The temperature is constant and uniform through the system, and pressure losses are neglected, so that gas velocity is constant along the duct/filter cake. In addition, a constant porosity of the cake is considered. It is recognized, however, that a more realistic representation should take into account the change of both pressure and cake porosity with time. (6) Mercury adsorption on the duct walls and filter fabric is negligible; i.e., equilibrium conditions are reached between the gas phase and walls/fabric so that no net exchange of mercury is present. (7) Mercury adsorption heat effects are neglected due to the trace level concentrations. Analysis of Relevant Mass Transfer Mechanisms. The process of mercury vapor adsorption onto activated carbon can be schematized as a series of three steps:73 (1) mass transfer from the bulk gas to the external surface of the activated carbon particle through the gas boundary layer, (2) mass transfer from the external surface to the interior of the particle through the pore structure, and (3) surface adsorption on the internal surface area of the particle. The first step can be treated in the classical way by means of an external mass transfer coefficient whose calculation passes through the evaluation of the particle Sherwood number, as will be detailed later on. As regards the second step, pore diffusion can be caused by two distinct mechanisms: gaseous diffusion inside the pore network and surface diffusion along the pore walls. While the first mechanism is always present, the second one is only relevant at high adsorbate coverages, that is, when monolayer adsorption conditions are approached;75 in these conditions the mobility of the adsorbed phase is comparable to that of the gas phase. To check if these conditions can be reached during the mercury capture process, a calculation was carried out to find the maximum coverage possible for the activated carbons considered. To this end conservative conditions were used by considering the maximum uptake capacity (ωmax) of mercury (Table 1). Given the dimension of a single Hg0 molecule (3 Å) and the sorbent pore surface area data,45,76 for the virgin activated carbon (DARCO G60) a maximum coverage of about 0.03% can be anticipated, while for the sulfur-impregnated one (HGR) a value of 1% is obtained. Taking into account that, in practical conditions, due to the short contact times, the particle mercury uptake is always much lower than the maximum one, surface diffusion

Ind. Eng. Chem. Res., Vol. 43, No. 10, 2004 2577 Table 1. Adsorptive and Physical Properties of the Sorbents Considered sorbent HGR DARCO G60 Nixon fly ash Cherokee fly ash Clark fly ash a

T, °C 120 150 200 120 120 120 120

k1, m3/(kg s) 0.41 0.70 0.96 0.505 0.23 0.2 0.056

k2, 1/s

ωmax

10-4

FP, kg/m3

P

dpore, Å

990 990 990 750 1400a 1400a 1400a

0.5 0.5 0.5 0.65 0.4a 0.4a 0.4a

30 30 30 60 100a 100a 100a

10-2

7.06 × 1.66 × 10-3 4.78 × 10-3 7.56 × 10-4 3.45 × 10-4 1.25 × 10-4 8.55 × 10-5

8.4 × 2.2 × 10-2 1.1 × 10-2 1.91 × 10-4 6.95 × 10-5 1.31 × 10-4 7.51 × 10-4

Estimated.

can be assumed to be always negligible as compared to gaseous diffusion. Moreover, should the adsorption mechanism be of a chemical nature (chemisorption), the strong bonds that are established between the mercury molecules and the surface sites would prevent any mobility of the mercury on the pore walls. For these reasons the homogeneous surface diffusion model used in a previous work70 is considered to be unsuitable to represent the mercury in-pore transport process. Gaseous diffusion inside the pore network is typically treated73 by means of an effective pore diffusion coefficient (Deff), dependent on particle porosity (P) and on an average pore size (dpore). This treatment is based on the simplifying assumption of a single average pore diameter, although many activated carbons exhibit a bimodal pore size distribution. Concerning the third step, considerable uncertainty still exists on the mechanism of elemental mercury adsorption on virgin or impregnated activated carbon particles. Evidence has been reported that a physical adsorption mechanism should be relevant for virgin activated carbons, while both chemisorption and physical adsorption have been suggested for impregnated ones.11,38,41-51,53,76 A number of theoretical and empirical equations can be used to model both physical and chemical adsorption processes. In this work the Langmuir theory will be used for the following reasons. (1) Langmuir isotherms were successfully used to correlate experimental adsorption data.45,76 In this respect it must be noted that available data have been obtained with experiments carried out in a nitrogen stream. On the other hand, it has been reported that the flue gas composition exerts a considerable influence on the mercury uptake.47,48,50-52 Due to the lack of thermodynamic and kinetic adsorption data obtained under simulated flue gas conditions, however, data obtained under nitrogen stream have been considered for calculations. (2) The Langmuir theory allows the intrinsic rate of adsorption to be expressed in addition to the equilibrium isotherm. In this respect, considering the mercury adsorbed on the activated carbon surface to be always in equilibrium with the local gas mercury concentration, as was done in previous works,71,72 may lead to a considerable overestimation of the actual mercury capture rate. Model Equations Following the Langmuir theory, the net rate of mercury adsorption on the activated carbon particle internal surface can be written as the difference between the local adsorption rate and desorption rate:73

dω/dt ) k1(ωmax - ω)c - k2ω

(1)

where ω is the local mercury uptake on the sorbent (kg

of Hg/kg of sorbent), c is the local gas mercury concentration, and k1 and k2 are the adsorption and desorption kinetic constants, respectively. The mercury mass balance in the gas phase inside the particle pores (in radial coordinates) reads

P

(

)

∂c ∂2c 2 ∂c + FP[k1(ωmax - ω)c - k2ω] ) 0 - Deff 2 + ∂t r ∂r ∂r (2)

where FP and P are the sorbent particle density and porosity, respectively, and eq 1 was used. The in-duct and fabric filter mercury capture processes will be treated separately in the following sections. In-Duct Mercury Capture. The system is schematized as a straight duct of constant diameter starting from the activated carbon feeding point and ending at the PMCD (Figure 1).

Figure 1. Model schematization of in-duct and fabric filter sections.

The flue gas is assumed to travel in plug flow along the duct. To establish if the slip velocity between the activated carbon particles and the gas is relevant, the terminal velocity of the particles was evaluated for the particle sizes of interest. To this end the Stokes regime assumption was made. Results indicated that terminal velocities are always more than 1 order of magnitude lower than typical flue gas velocities so that it is reasonable to assume that particles travel at the same velocity as the flue gas. The particle Reynolds number was always lower than 1, justifying the assumption of the Stokes regime. Keeping in mind this result, a reasonable assumption is that the particle Sherwood number is equal to the limiting theoretical value of 2 relative to the stagnant boundary layer condition. It was evaluated that this assumption would give negligible errors in the evaluation of Sh at most practical conditions and a maximum error on the order of 10% at the largest particle size considered (100 µm). Giving the plug flow and the no slip velocity assumptions, the mercury mass balance in the bulk gas phase reads

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|

dcB 3ΘACDeff ∂c )dt FPRP ∂r (RP,t)

(3)

where cB is the gas bulk mercury concentration, ΘAC the activated carbon loading per unit volume in the bulk gas, and RP the sorbent particle radius. This equation was derived using a Lagrangian approach, that is, following a small gas volume traveling along the duct together with the sorbent particles. In this way, the mercury uptake process is followed as a function of the gas/sorbent residence time in the duct, rather than of the axial position. The system of three coupled differential equations (eqs 1-3) has the following initial and boundary conditions:

ω(r,0) ) 0; c(r,0) ) 0; cB(0) ) cIN B

(4)

|

(5)

|

KG ∂c ∂c ) 0; ) [c (t) - c(RP,t)] ∂r (0,t) ∂r (RP,t) Deff B

where the boundary layer mass transfer coefficient is given by KG ) Dm(Sh)/2RP (Dm is the molecular diffusion coefficient). The average mercury uptake in the activated carbon particles at a certain residence time in the duct is simply given by

ω j (t) )

(cIN B

- cB)/ΘAC

(6)

To solve the system of eqs 1-3 and 6 (with the initial and boundary conditions given in eqs 4 and 5), they have been put in dimensionless form by means of suitable dimensionless variables.73 Fabric Filter Mercury Capture. The system is schematized as an activated carbon fixed bed (cake) of growing thickness (Figure 1). The flue gas is assumed to travel in plug flow along the filter cake, and axial dispersion is neglected.74 Typical superficial gas velocities through fabric filters (air-to-cloth ratio) are on the order of 0.005-0.05 m/s. In light of the very low gas/sorbent relative velocities, a reasonable assumption is that the particle Sherwood number is equal to the limiting theoretical value of 2bed relative to the stagnant boundary layer condition, where the bed (cake) porosity bed accounts for the reduced volume available for diffusion. It was evaluated that this assumption would give negligible errors in the evaluation of Sh at most practical conditions and a maximum error lower than 10% at the largest particle size considered (100 µm). Given the plug flow assumption with negligible axial dispersion, the mercury mass balance in the bulk gas phase in a filter cake section reads

bed

|

∂cB ∂cB 3FbedDeff ∂c +v )∂t ∂z FPRP ∂r (z,RP,t)

(7)

where v is the superficial gas velocity in the cake and Fbed ) FP(1 - bed) the cake density. Contrary to the induct section, eq 7 was derived using an Eulerian approach, that is, considering a reference system fixed with the filter. To set the initial conditions for the system of the three coupled differential equations (eqs 1, 2, and 7), it is assumed that at time t ) 0 the bulk and intraparticle

gas mercury concentrations as well as the sorbent mercury uptake are equal to those calculated at the end of the in-duct removal section, that is, at tD. Accordingly the initial and boundary conditions are

ω(z,r,0) ) ω(r,tD); c(z,r,0) ) c(r,tD); cB(z,0) ) cB(tD) (8)

|

|

KG ∂c ∂c ) 0; ) [c (z,t) - c(z,RP,t)]; ∂r (z,0,t) ∂r (z,RP,t) Deff B cB(0,t) ) cB(tD) (9) The last boundary condition implies that at any time at the bed inlet the bulk gas mercury concentration is equal to that calculated at the end of the in-duct removal section. The average mercury uptake in the whole filter cake is given by

ω j (t) ) ω j (tD) +

1 ΘACt

∫0t[cB(0,t) - cB(L,t)] dt

(10)

where L is the cake actual thickness. The actual cake thickness can be calculated as

L(t) ) vdt

(11)

where the sorbent deposition velocity on the filter is given by

vd ) ΘACv/Fbed

(12)

To solve the system of eqs 1, 2, and 7 (with the initial and boundary conditions given in eqs 8 and 9), they have been put in dimensionless form by means of suitable dimensionless variables.74 It is interesting to note that as the final cake thickness (LF) is proportional to the superficial gas velocity in the cake (see eqs 11 and 12) the system of eqs 1, 2, and 7 is independent of v. Solution Procedure. For the in-duct section, the boundary-value partial differential equation (eq 2) was reduced to a set of n initial-value ordinary differential equations in time using an orthogonal collocation technique.77 To this end, the solution was approximated by a linear combination of Lagrange polynomials, and the collocation points were chosen as the zeroes of a Legendre polynomial on the same order as the number of internal collocation points. The resulting system of 2n + 1 (2n + eq 3) ordinary differential equations was integrated using a fifth-order Runge-Kutta method with adaptive step-size control. The number of collocation points (n) and the Runge-Kutta step size were adjusted to give a total accuracy of 10-4 in the value of the output variables. Accordingly a value of n ) 5 was used for the calculations. For the fabric filter section, in the same way the boundary-value partial differential equation along the particles radius (eq 2) was reduced to a set of n initialvalue ordinary differential equations in time using an orthogonal collocation technique. To account for the moving boundary nature of the problem (growing thickness of the cake), a more powerful resolution technique than the finite-difference scheme used in a previous paper74 was implemented in this work. This technique, similar to that employed by Flora et al.,72 consists of a suitable change of variables to immobilize the moving front and adopts a set of transformation rules of the

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Figure 2. Gas bulk mercury concentration decrease (left) and average mercury uptake on the sorbent (right) as a function of particle 3 3 residence time in the duct for different particle sizes (sorbent HGR; T ) 150 °C; cIN B ) 5 µg/m ; ΘAC ) 10 g/m ).

partial derivatives to account for the displacement of the collocation points in the domain with time.78 After the above manipulations, fictitious partial derivatives along the dimensionless cake thickness are introduced in all the n + 2 (n + eqs 1 and 7) equations. Immobilization of the moving front with this technique allows the boundary-value partial differential problem along the cake thickness to be reduced to a set of m(n + 2) initial-value ordinary differential equations in time using again orthogonal collocation. The resulting system of equations was integrated using a fifth-order RungeKutta method with adaptive step-size control. The number of collocation points along the particle radius (n) and along the cake thickness (m) and the RungeKutta step size were adjusted to give a total accuracy of 10-4 in the value of the output variables. Accordingly values of n ) m ) 5 were used for the calculations. Parameter Estimation. The model was applied to one virgin activated carbon (DARCO G60) and one sulfur-impregnated carbon (HGR). For comparison also three fly ashes were considered. The fly ashes have been collected from full-scale coal-fired power plants and have an unburned carbon content of 2.0% (Nixon), 8.7% (Cherokee), and 32.7% (Clark) by weight.37 Adsorptive and physical properties of the sorbents considered were taken from the literature37,45,76 and are reported in Table 1. Molecular diffusivity of elemental mercury in the flue gas was estimated by means of the Chapman-Enskog theory and was calculated to be 0.21 × 10-4, 0.24 × 10-4, and 0.28 × 10-4 m2/s at 120, 150, and 200 °C, respectively. A bed porosity value bed ) 0.5 was used in the fabric filter model calculations. Results and Discussion The procedure followed to analyze model results was that of selecting a set of operating variables as a base case for computations and to assess the influence of the relevant input variables on the process by varying them one at a time. Tables 2 and 3 report the operating variables for the base case and the range of variation of each variable, for in-duct and fabric filter simulations, respectively. The values and range of the input variables

Table 2. Base Case Values and Range of Variation of the Operating Variables for In-Duct Model Computations

base case range

T, °C

dP, µm

3 cIN B , µg/m

tD, s

ΘAC, g/m3

150 120-200

20 5-100

5 1-10

10 1-10

10 0.01-100

Table 3. Base Case Values and Range of Variation of the Operating Variables for Fabric Filter Model Computations

base case range

T, °C

dP, µm

3 cIN B , µg/m

tF, min

ΘAC, g/m3

150 120-200

20 5-100

5 1-10

60 1-60

0.1 0.001-100

were chosen to simulate as closely as possible typical coal-fired power plant operating conditions. The sulfurimpregnated activated carbon (HGR) was selected for base case computations. This commercial sorbent, in fact, is extensively used in industrial practice, so that simulation results obtained with HGR have particular practical interest. In-Duct Mercury Capture. Figures 2 and 3 report the gas bulk mercury concentration decrease and the average mercury uptake on the sorbent as a function of residence time in the duct for different particle sizes (Figure 2) and different system temperatures (Figure 3) at a sorbent loading of 10 g/m3. The gas bulk mercury concentration was normalized with the inlet bulk concentration, while the sorbent mercury uptake was normalized with ωmax. Both figures show that, as expected, the longer the particle residence time in the duct the larger the mercury capture. Figure 2 clearly points out that small sorbent particles achieve larger mercury capture at all residence times, indicating that diffusional resistance might be relevant for the uptake process. Below a certain particle size, however, for this sorbent about 10 µm, there is not much effect in lowering the particle size. On the other hand, curves in Figure 3 show that a temperature decrease from 200 to 120 °C determines an increase of mercury capture from about 50% to about 80% after 10 s of residence time in the duct. This result suggests that the adsorption of mercury onto HGR carbon is likely to be of a physical nature. It must be recalled here, however, that available adsorption data have been obtained in a nitrogen

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Figure 3. Gas bulk mercury concentration decrease (left) and average mercury uptake on the sorbent (right) as a function of particle 3 3 residence time in the duct for different operating temperatures (sorbent HGR; dP ) 20 µm; cIN B ) 5 µg/m ; ΘAC ) 10 g/m ).

Figure 4. Gas mercury concentration profiles inside the sorbent particles at different particle sizes (left) and temperatures (right) (sorbent 3 3 HGR; cIN B ) 5 µg/m ; ΘAC ) 10 g/m ; tD ) 1.0 s).

stream, so that under real flue gas conditions the scenario might be somewhat different. In analyzing the uptake curves (on the right-hand side of the figures), it is interesting to observe that the mercury uptake values are several orders of magnitude lower than ωmax, indicating a very low sorbent utilization under all operating conditions. These low uptake values confirm the initial assumption that the surface diffusion mechanism in the sorbent pores is always negligible. Figure 4 reports the gas mercury concentration profiles inside the HGR sorbent particles after 1.0 s of residence time in the duct at different particle sizes (left) and temperatures (right). The mercury concentration was normalized with the bulk concentration at the same residence time. The curves show that for large particle sizes intraparticle diffusion resistance is largely controlling the mercury uptake rate, while for small particle sizes the rate is mostly under kinetic control. A decrease of the process temperature leads to an increase of the intraparticle diffusion resistance contribution due to the

augmented adsorption kinetic rate. It is interesting to note that, under the operating conditions explored in this work, intraparticle diffusion is practically dominated by Knudsen diffusivity (which was estimated to be on the order of 10-6-10-7 m2/s). Boundary layer (external) diffusion resistance, instead, is always very limited as demonstrated by the mercury concentration value at the particle surface (r/RP ) 1) being close to the bulk one. Figures 5 and 6 report the gas bulk mercury removal as a function of the sorbent loading in the duct at 10 s of residence time at different particle sizes (Figure 5) and temperatures (Figure 6). The curves show that, to obtain mercury removal efficiencies on the order of 9095%, large loadings on the order of 10-100 g/m3 have to be used with HGR. The best operating conditions are achieved with small particles (dP < 10 µm) and low temperatures (120 °C). The influence of the mercury gas inlet concentration was investigated in the range of values reported in Table 2. Similarly to results obtained under incinerator

Ind. Eng. Chem. Res., Vol. 43, No. 10, 2004 2581

Figure 5. Gas bulk mercury removal as a function of sorbent loading in the duct at different particle sizes (sorbent HGR; T ) 150 °C; 3 cIN B ) 5 µg/m ; tD ) 10 s).

Figure 6. Gas bulk mercury removal as a function of sorbent loading in the duct at different temperatures (sorbent HGR; dP ) 20 µm; 3 cIN B ) 5 µg/m ; tD ) 10 s).

flue gas conditions,73 no appreciable influence on the mercury removal results was observed at any operating condition. Figure 7 reports the gas bulk mercury removal as a function of the sorbent loading in the duct at 10 s of residence time for the different sorbents considered at T ) 120 °C. In the figure the external diffusion limit curve, corresponding to the ideal case of an infinitely fast adsorption kinetic rate, has been drawn for comparison. At any sorbent loading in the duct this curve represents the maximum theoretical mercury removal obtainable in these particular operating conditions. Comparison of the curves shows that the sulfurimpregnated carbon performs much better than the virgin one. At any operating condition investigated HGR removes about 2 orders of magnitude more mercury than DARCO G60. This result confirms the high affinity of sulfur with metallic mercury, leading to a considerable increase of both the adsorption kinetics and the maximum uptake capacity (Table 1). Once again, however, it must be highlighted that adsorption kinetic data

obtained under nitrogen gaseous streams may not be fully representative of real flue gas conditions. The fly ashes considered, instead, have a bad mercury capture behavior, slightly worse than that of DARCO G60. It is interesting to note that, in line with reported experimental data,10,37 the fly ash mercury removal performance increases with the unburned carbon content of the fly ash. Results show that a more reactive sorbent gives the possibility to considerably economize in the sorbent feed rate. It should be kept in mind, however, that, to achieve a determined mercury removal efficiency with the induct process, it is not possible to go beyond the external diffusion limit curve. For example, for the case reported in Figure 7 a 90% mercury reduction cannot be obtained with sorbent loadings lower than about 0.4 g/m3. It is worthy to note, moreover, that for reactive sorbents it is important to employ the smaller particle size possible to reduce diffusional resistances. On the whole model results indicate that for the induct mercury capture in coal-fired power plant flue gas

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Figure 7. Gas bulk mercury removal as a function of sorbent loading in the duct for different sorbents (T ) 120 °C; dP ) 20 µm; cIN B ) 5 µg/m3; tD ) 10 s).

Figure 8. Comparison between experimental50 (sorbent FGD; T ) 100 °C) and model (sorbent HGR; T ) 150 °C) in-duct mercury removal data at different particle sizes (tD ) 8.4 s).

it is crucial to operate with a reactive sorbent. Anyhow, a large loading of sorbent is always needed to obtain a high mercury removal efficiency, as a consequence of the short contact times provided in the duct. Under all operating conditions, very low utilization of the sorbents is predicted. Minimization of the sorbent feeding rate is achievable by lowering the operating temperature, by increasing the in-duct particle residence time, and especially by decreasing the sorbent particle size. In-Duct Capture Model Validation. To validate the model, the literature was searched for in-duct mercury capture experimental studies carried out under controlled conditions, possibly similar to those under which the adsorption kinetic data were collected. One such experimental work was recently published.54 In this work a quartz bench-scale entrained-flow reactor was used to study in-duct capture of elemental mercury by different commercial activated carbons. The experiments were conducted under isothermal conditions in a nitrogen stream, i.e., in the absence of gaseous (O2, SO2, HCl, etc.) and solid (fly ash) pollutants that could

influence the mercury speciation and uptake behavior. Moreover, care was taken to keep as clean as possible the reactor walls and the sampling filter to minimize additional mercury uptake besides the in-flight one. The overall trends of the model simulations compare favorably with reported experimental results. In particular, no significant influence of the inlet mercury concentration on the removal efficiency was found, while the mercury uptake increased by decreasing the temperature and the sorbent particle size, by increasing the activated carbon feed rate and the in-duct residence time, and especially by using a more reactive sorbent. Figure 8 reports a comparison between mercury removal experimental data with FGD (lignite-based) virgin activated carbon (at T ) 100 °C) and model data with HGR carbon (at T ) 150 °C) for different particle sizes. Curves in the figure show that the model catches very well the overall trends even if two different sorbents at two different temperatures were compared. With this respect it must be noted that kinetic and thermodynamic data for mercury adsorption on FGD carbon are

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Figure 9. Mercury capture experimental data in pilot- and full-scale facilities.54-63 Lines represent the theoretical maximum in-duct mercury removal curves (diffusion limit curves) at different residence times (T ) 150 °C; dP ) 20 µm).

not available in the literature, thus avoiding the possibility of a comparison between experimental and model results using the same activated carbon. Experimental data obtained with two other activated carbons showed better mercury removal efficiencies than those relative to FGD, anyhow always significantly below the external diffusion limit curve. Comparison of In-Duct Capture Results with Available Pilot- and Full-Scale Data. In-duct mercury capture model results are relevant to power plants where the PMCD is an ESP. A number of pilot-scale experimental data under this PMCD configuration have been collected to date,57-65 most of them using slipstreams from full-scale power plants, to have flue gas conditions representative of real operation. In addition, two experimental campaigns of mercury capture with activated carbon in ESP-equipped full-scale power plants have been recently reported: the first was carried out on unit 5 (12 MW) of Abbott Power Plant, Illinois,66 and the second on unit 2 (using only one ESP, representing nominally 150 MW) of Pleasant Prairie Power Plant, Wisconsin.67 When comparing pilot- and full-scale experimental data with model predictions, one has to consider that under real operating conditions several factors, not taken into account in the model, may influence the mercury removal efficiency. On one side the presence of gaseous (especially SO2 and HCl) and solid (fly ash) pollutants influences both the mercury speciation and uptake; on the other side temperature gradients and sorbent/flue gas mixing limitations along the ducts, as well as the occurrence of sorbent deposition on the ducts and the ESP surfaces, influence the mercury removal efficiency. Anyhow, the present model computations qualitatively agree with experimental data. In particular, it was demonstrated that the lower the duct and the electrostatic precipitator temperatures the higher the mercury capture efficiency, while mercury gas concentration was not found to influence appreciably the capture efficiency. Few studies in which the sorbent particle size was varied59,66 showed that smaller sized sorbent performed better mercury uptake. The variable with the greatest influence on the mercury capture performance was found to be the carbon feed rate, that is, the sorbent loading in the duct. Figure 9 reports a collection of mercury removal experimental

data in pilot- and full-scale facilities, represented as shaded zones, plotted as a function of the sorbent loading. All data refer to mercury capture experiments carried out in the temperature range T ) 65-215 °C (most experiments at T ) 100-150 °C) at residence times shorter than 5 s and with sorbent sizes in the range 3-44 µm. Most experiments have been carried out using FGD activated carbon. It must be noted that some of the data were originally reported as mercury removal vs carbon-to-mercury injection ratio (C/Hg). As previously suggested,65 the injection ratio is a misleading variable as it is a function of the inlet mercury concentration. On the other hand, as also demonstrated in this paper, the carbon injection rate necessary for a determined mercury removal efficiency is independent of the inlet mercury concentration. For this reason, the above data have been transformed into mercury removal vs carbon loading for inclusion in Figure 9. In the same figure the theoretical maximum in-duct mercury removal curves (external diffusion limit curves) have also been reported for comparison for three different in-duct residence times (at T ) 150 °C and dP ) 20 µm). Comparison of experimental data with the external diffusion limit curves in the figure and with the previously reported model simulations (Figures 6-8) suggests some considerations. First, it can be clearly noted that mercury removal efficiencies under pilot- and fullscale conditions are much higher than predicted by the model. One possible explanation is that under real flue gas conditions the activated carbons used are much more reactive than under laboratory conditions. However, close examination of Figure 9 shows that a large set of experimental removal efficiency data are higher (sometimes much higher) than the theoretical maximum in-duct removal values. The only possible explanation for this apparent inconsistency is that some additional mercury capture mechanism be active at the same time. It has been suggested64,67 that mercury capture by sorbent particles deposited on the ducts and especially on the ESP surfaces may contribute to a significant fraction of the total removal efficiency. The finding (Figure 9) that in pilot-scale experiments, where higher surface areas exposed per unit volume of flue gas are present, mercury capture is more effective than under full-scale conditions is consistent with this mechanism.

2584 Ind. Eng. Chem. Res., Vol. 43, No. 10, 2004

Figure 10. Filter outlet gas bulk mercury concentration (left) and average mercury uptake on the sorbent (right) as a function of filtration 3 time for different sorbent loadings (sorbent HGR; T ) 150 °C; cIN B ) 5 µg/m ; dP ) 20 µm).

Figure 11. Filter outlet gas bulk mercury concentration (left) and average mercury uptake on the sorbent (right) as a function of filtration 3 3 time for different particle sizes (sorbent HGR; T ) 150 °C; cIN B ) 5 µg/m ; ΘAC ) 0.1 g/m ).

In particular, it can be seen that in ESP-equipped fullscale plants mercury capture efficiencies larger than 70% are seldom reached, compared to figures up to 95% in pilot plants. Furthermore, comparison between pilotscale data where mercury is removed only in the duct section and those where mercury is removed both in the duct and in the ESP shows that a large fraction of mercury is presumably captured on the ESP surfaces. These arguments suggest that a realistic simulation of mercury capture in full-scale ESP-equipped power plants will require taking into account the wall deposition of activated carbon (and possibly of fly ash) together with the additional mercury removal onto this deposited particle layer. Fabric Filter Mercury Capture. As reported in the Theory section, the bulk gas mercury concentration as well as the average sorbent mercury uptake at the filter inlet should be equal to those calculated at the end of the in-duct removal section. However, as the contribution to mercury removal of the in-duct section is always much lower than that obtained on the fabric filter,72,74

the former has been neglected in the present model calculations. Figures 10-13 report the filter outlet gas bulk mercury concentration and the mercury uptake on the sorbent (averaged over the entire cake) as a function of filtration time, parametric in the sorbent loading, in the sorbent particle size, in the filter temperature, and in the sorbent type, respectively. The outlet gas bulk mercury concentration has been normalized with the inlet one, while the sorbent mercury uptake has been normalized with ωmax . The outlet mercury concentration curves show that, contrary to typical fixed bed operation, the outlet mercury concentration decreases with filtration time until an asymptotic figure is approached.74 This behavior is the consequence of the growing thickness of the cake: fresh sorbent is continuously added on the filter, providing increased mercury adsorption. At long times, however, the ending zone of the cake, consisting of almost fully spent sorbent, gives a negligible contribution to the adsorption process so that asymptotic conditions are reached. The average sorbent

Ind. Eng. Chem. Res., Vol. 43, No. 10, 2004 2585

Figure 12. Filter outlet gas bulk mercury concentration (left) and average mercury uptake on the sorbent (right) as a function of filtration 3 3 time for different filter temperatures (sorbent HGR; cIN B ) 5 µg/m ; dP ) 20 µm; ΘAC ) 0.1 g/m ).

Figure 13. Filter outlet gas bulk mercury concentration (left) and average mercury uptake on the sorbent (right) as a function of filtration 3 3 time for different sorbents (T ) 120 °C; cIN B ) 5 µg/m ; ΘAC ) 1.0 g/m ; dP ) 20 µm).

mercury uptake, instead, increases steadily with the filtration time, even at long filtration times. This is because the thickness of the spent zone of the cake increases with time, thus increasing the average mercury uptake of the cake. The effect of the sorbent loading on mercury capture (Figure 10) is straightforward: larger carbon loadings lead to much larger mercury captures on the filter, but, on the other hand, correspond to lower sorbent utilization degrees. The influence of the sorbent particle size (Figure 11) and that of the filter temperature (Figure 12) on the filter outlet mercury concentration are similar to those reported for the in-duct process: smaller sorbent particles achieve larger mercury capture at all residence times, as a consequence of the reduced intraparticle diffusion resistance, while a temperature decrease from 200 to 120 °C corresponds to a considerable increase of the mercury capture at all filtration times. Below a certain particle size, however, in this case about 10 µm, there is not much effect in lowering the particle size. The influence of the sorbent type on the filter outlet mercury concentration is reported in Figure 13. Com-

parison of the different curves shows that a dramatic difference exists between HGR carbon and the other sorbents, the former performing considerably better under the same operating conditions. However, care should be used in reading this result, as adsorption kinetic data used for calculations are taken from experiments where nitrogen was used as the gaseous stream. Under real flue gas conditions kinetic parameters of the sorbents may change significantly, possibly leading to different results. Further, as also noted by Serre and Silcox,37 the virgin activated carbon and the three fly ashes considered remove mercury to a comparable extent, while the fly ash mercury removal performance increases with the unburned carbon content of the fly ash. In analyzing the uptake curves in the figures, it should be noted that results have been normalized with ωmax, whose value changes with temperature and sorbent type. It is interesting to observe that the sorbent mercury uptake values are 2-3 orders of magnitude higher than those of the in-duct process, reaching values on the order of 0.5% of ωmax at long filtration times. This

2586 Ind. Eng. Chem. Res., Vol. 43, No. 10, 2004

Figure 14. Mean gas bulk mercury removal as a function of sorbent loading at different filter temperatures (reverse-flow baghouse) 3 (sorbent HGR; dP ) 20 µm; cIN B ) 5 µg/m ; tF ) 60 min).

Figure 15. Mean gas bulk mercury removal as a function of sorbent loading at different filter temperatures (pulse-jet baghouse) (sorbent 3 HGR; dP ) 20 µm; cIN B ) 5 µg/m ; tF ) 12 min).

finding is a clear indication that, due to the additional gas/sorbent contact time in the filter cake, mercury capture on the filter is far more effective than in the duct. The influence of the mercury gas inlet concentration was investigated in the range of values reported in Table 3. As for the in-duct process, limited influence of this variable on the mercury removal results was observed at any operating condition.74 Up to now the analysis has been restricted to the mercury capture behavior of a single fabric filter section. Typical full-scale baghouses consist of a number of compartments cleaned cyclically in a staggered way. It was noted by Scala74 that while the mean outlet mercury concentration does not vary with the number of compartments, a large number of compartments gives a smoother mercury removal operation, avoiding large concentration spikes at the baghouse outlet. In the following, the mean mercury removal (calculated from the mean outlet gas bulk mercury concentrations) will be considered to have curves independent of the number

of compartments. Further, it was noted74 that the mean mercury removal efficiency increases with the cleaning cycle time, even if at long times it approaches an asymptotic value. To simulate real full-scale baghouse performances, two cycle times typical of a reverse-flow baghouse (tF ) 60 min) and a pulse-jet baghouse (tF ) 12 min) have been chosen. Figures 14 and 15 report the mean gas bulk mercury removal as a function of the sorbent loading in the duct at different filter temperatures for the reverse-flow (Figure 14) and pulse-jet (Figure 15) baghouse configurations. The curves show that, to obtain mercury removal efficiencies on the order of 90-95%, loadings on the order of 1-10 g/m3 have to be used with the sorbent at hand. As expected, the most effective removal is achieved at the lower temperature (120 °C). Comparison of the two figures shows that reverse-flow baghouses can achieve larger mercury removal efficiencies than pulse-jet baghouses, under similar operating conditions. This result is based on the implicit modeling assumption of idealized baghouses. Should nonideal

Ind. Eng. Chem. Res., Vol. 43, No. 10, 2004 2587

Figure 16. Baghouse mercury capture experimental data in pilot- and full-scale facilities.58,60,63-65,68,69,79-82 Lines represent calculated mean gas bulk mercury removal curves taken from Figure 14.

phenomena, often observed during pulse-jet baghouse operation, such as patchy cleaning or ash re-entrainment after pulsing be relevant, the performance of this kind of baghouse might be more close to that of reverseflow ones. On the whole model results indicate that mercury capture in coal-fired power plant flue gas can be carried out on the fabric filter cake with high removal efficiencies and with only moderate sorbent consumption, as a consequence of the effective gas/sorbent contact on the filter. Satisfactory utilization of the sorbents is predicted, especially at long filtration times. Minimization of the sorbent feeding rate can be achieved by using a more reactive sorbent, by lowering the operating temperature, by decreasing the sorbent particle size, and by increasing the cleaning cycle time of the baghouse compartments. Reverse-flow baghouses showed a better performance than pulse-jet ones. Comparison of Fabric Filter Capture Results with Available Pilot- and Full-Scale Data. A number of pilot-scale experimental data under a fabric filter (baghouse) PMCD configuration have been collected to date,58,60,63-65,68,79-82 most of them using slipstreams from full-scale power plants, to have flue gas conditions representative of real operation. In addition, one experimental campaign of mercury capture with activated carbon in an FF-equipped full-scale power plant (unit 3 at Gaston Power Plant, Alabama, representing nominally 135 MW) has been recently reported.69 As highlighted before, comparison between model results and pilot- and full-scale experimental data must be considered with care, because under real operating conditions several factors (the presence of gaseous and solid pollutants, temperature gradients, sorbent/flue gas mixing limitations, and sorbent deposition), not taken into account in the model, may influence the mercury removal efficiency. Figure 16 shows a collection of mercury removal experimental data in FF-equipped pilot- and full-scale facilities, represented as shaded zones, plotted as a function of the sorbent loading. All data refer to mercury capture experiments carried out in the temperature range T ) 65-200 °C (most experiments at T ) 100150 °C) with sorbent sizes in the range 3-27 µm. Most experiments have been carried out using FGD activated carbon. Data originally reported as mercury removal vs

carbon-to-mercury injection ratio (C/Hg) have been transformed into mercury removal vs carbon loading for inclusion in Figure 16. No distinction between pilot- and full-scale data has been done in the figure: contrary to ESP-equipped plants, in fact, full-scale data follow both qualitatively and quantitatively the same trends as pilot-scale data.65 Experimental data show that, in accordance with model simulations, the primary variable affecting the mercury control efficiency is the activated carbon feed rate. Mercury capture efficiencies on the order of 8090% were obtained with carbon loadings in the duct on the order of 0.01-0.1 g/m3, lower than those necessary in ESP-equipped facilities. These values indicate that the activated carbons used in the experiments are more reactive than the sorbents considered for model calculations. As in ESP-equipped plants, the lower the baghouse temperature the higher the mercury capture efficiency, while mercury gas concentration was not found to influence appreciably the capture efficiency. Comparison between experimental and calculated data indicates that the model is able to satisfactorily catch the overall mercury removal trends as a function of temperature. For a quantitative point of view, however, the model underestimates the experimental baghouse mercury capture efficiencies, indicating that the adsorption parameters obtained under real flue gas conditions for the activated carbons used in the experiments are needed for a more realistic matching. Notation c ) local gas mercury concentration, kg/m3 cB ) gas bulk mercury concentration, kg/m3 3 cIN B ) inlet gas bulk mercury concentration, kg/m dP ) sorbent particle diameter, m dpore ) sorbent average pore size, Å Deff ) effective pore diffusion coefficient, m2/s Dm ) molecular diffusion coefficient, m2/s k1 ) adsorption kinetic constant, m3/(kg s) k2 ) desorption kinetic constant, s-1 KG ) boundary layer mass transfer coefficient, m/s L ) filter cake actual thickness, m LF ) filter cake final thickness, m r ) radial coordinate, m RP ) sorbent particle radius, m Sh ) Sherwood number t ) time, s tF ) filtration time, s tD ) in-duct residence time, s T ) temperature, K v ) superficial gas velocity in the filter cake, m/s vD ) sorbent deposition velocity on the filter, m/s z ) axial coordinate, m bed ) filter bed (cake) porosity P ) sorbent particle porosity ΘAC ) activated carbon loading per unit volume in the bulk gas, kg/m3 Fbed ) filter bed (cake) density, kg/m3 FP ) sorbent particle density, kg/m3 ω ) local mercury uptake on the sorbent ω j ) average mercury uptake on the sorbent ω j max ) maximum mercury uptake capacity on the sorbent

Literature Cited (1) EPA. Mercury Study Report to Congress; Report EPA-452/ R-97-003; EPA: Washington, DC, 1997. (2) Lindqvist, O. Waste Manage. Res. 1986, 4, 35. (3) Nriagu, J. O.; Pacyna, J. M. Nature 1988, 333, 134.

2588 Ind. Eng. Chem. Res., Vol. 43, No. 10, 2004 (4) Nriagu, J. O. Nature 1989, 338, 47. (5) Pacyna, J. M.; Munch, J. Water, Air, Soil Pollut. 1991, 5, 51. (6) Carpi, A. Water, Air, Soil Pollut. 1997, 98, 241. (7) Billings, C. E.; Sacco, A. M.; Matson, W. R.; Griffin, R. M.; Coniglio, W. R.; Harley, R. A. J. Air Pollut. Control Assoc. 1973, 23, 773. (8) Hall, B.; Schager, P.; Lindqvist, O. Water, Air, Soil Pollut. 1991, 56, 3. (9) Sandelin, K.; Backman, R. Environ. Sci. Technol. 1999, 33, 4508. (10) Gibb, W. H.; Clarke, F.; Mehta, A. K. Fuel Process. Technol. 2000, 65-66, 365. (11) Huang, H. S.; Wu, J. M.; Livengood, C. D. Hazard. Waste Hazard. Mater. 1996, 13, 107. (12) Klein, D. H.; Andren, A. W.; Carter, J. A.; Emery, J. F.; Feldman, C.; Fulkerson, W.; Lyon, W. S.; Ogle, J. C.; Talmi, Y.; Van Hook, R. I.; Bolton, N. Environ. Sci. Technol. 1975, 9, 973. (13) Otani, Y.; Emi, H.; Kanaoka, C.; Matsui, S. Environ. Sci. Technol. 1984, 18, 793. (14) Germani, M. S.; Zoller, W. H. Environ. Sci. Technol. 1988, 22, 1079. (15) Hall, B.; Lindqvist, O.; Ljungstrom, E. Environ. Sci. Technol. 1990, 24, 108. (16) Meij, R. Water, Air, Soil Pollut. 1991, 56, 21. (17) Senior, C. L.; Helble, J. J.; Sarofim, A. F. Fuel Process. Technol. 2000, 65-66, 65. (18) Hall, B.; Schager, P.; Weesma, J. Chemosphere 1995, 30, 611. (19) Bool, L. E., III; Helble, J. J. Energy Fuels 1995, 9, 880. (20) Galbreath, K. C.; Zygarlicke, C. J. Environ. Sci. Technol. 1996, 30, 2421. (21) Senior, C. L.; Sarofim, A. F.; Zeng, T.; Helble, J. J.; Mamani-Paco, R. Fuel Process. Technol. 2000, 63, 197. (22) Laudal, D. L.; Brown, T. D.; Nott, B. R. Fuel Process. Technol. 2000, 65-66, 157. (23) Galbreath, K. C.; Zygarlicke, C. J. Fuel Process. Technol. 2000, 65-66, 289. (24) Sliger, R. N.; Kramlich, J. C.; Marinov, N. M. Fuel Process. Technol. 2000, 65-66, 423. (25) Frandsen, F. J.; Dam-Johansen, K.; Rasmussen, P. Prog. Energy Combust. Sci. 1994, 20, 115. (26) Furimsky, E. Fuel Process. Technol. 2000, 63, 29. (27) Yan, R.; Gauthier, D.; Flamant, G. Combust. Flame 2001, 125, 942. (28) Edwards, J. R.; Srivastava, R. K.; Kilgroe, J. D. J. Air Waste Manage. Assoc. 2001, 51, 869. (29) Laudal, D. L.; Pavlish, J. H.; Graves, J.; Stockdill, D. J. Air Waste Manage. Assoc. 2000, 50, 1798. (30) Chu, P.; Porcella, D. B. Water, Air, Soil Pollut. 1995, 80, 135. (31) Fahlke, J.; Bursik, A. Water, Air, Soil Pollut. 1995, 80, 209. (32) Clemens, A. H.; Damiano, L. F.; Gong, D.; Matheson, T. W. Fuel 1999, 78, 1379. (33) Nodelman, I. G.; Pisupati, S. V.; Miller, S. F.; Scaroni, A. W. J. Hazard. Mater. 2000, 74, 47. (34) Klika, Z.; Bartonova, L.; Spears, D. A. Fuel 2001, 80, 907. (35) Hassett, D. J.; Eylands, K. E. Fuel 1999, 78, 243. (36) Sakulpitakphon, T.; Hower, J. C.; Trimble, A. S.; Schram, W. H.; Thomas, G. A. Energy Fuels 2000, 14, 727. (37) Serre, S. D.; Silcox, G. D. Ind. Eng. Chem. Res. 2000, 39, 1723. (38) Otani, Y.; Kanaoka, C.; Usui, C.; Matsui, S.; Emi, H. Environ. Sci. Technol. 1986, 20, 735. (39) Pai, P.; Niemi, D.; Powers, B. Fuel Process. Technol. 2000, 65-66, 101. (40) Brown, T. D.; Smith, D. N.; Hargis, R. A., Jr.; O’Dowd, W. J. J. Air Waste Manage. Assoc. 1999, 49, 628. (41) Matsumura, Y. Atmos. Environ. 1974, 8, 1321. (42) Otani, Y.; Emi, H.; Kanaoka, C.; Uchijima, I.; Nishino, H. Environ. Sci. Technol. 1988, 22, 708. (43) Henning, K. D.; Keldenich, K.; Knoblauch, K.; Degel, J. Gas Sep. Purif. 1988, 2, 20. (44) Krishnan, S. V.; Gullett, B. K.; Jozewicz, W. Environ. Sci. Technol. 1994, 28, 1506. (45) Karatza, D.; Lancia, A.; Musmarra, D.; Pepe, F. Proc. Combust. Inst. 1996, 26, 2439. (46) Vidic, R. D.; McLaughlin, J. B. J. Air Waste Manage. Assoc. 1996, 46, 241.

(47) Ghorishi, B.; Gullett, B. K. Waste Manage. Res. 1998, 16, 582. (48) Carey, T. R.; Hargrove, O. W., Jr.; Richardson, C. F.; Chang, R.; Meserole, F. B. J. Air Waste Manage. Assoc. 1998, 48, 1166. (49) Huggins, F. E.; Huffman, G. P.; Dunham, G. E.; Senior, C. L. Energy Fuels 1999, 13, 114. (50) Olson, E. S.; Miller, S. J.; Sharma, R. K.; Dunham, G. E.; Benson, S. A. J. Hazard. Mater. 2000, 74, 61. (51) Liu, W.; Vidic, R. D.; Brown, T. D. Environ. Sci. Technol. 2000, 34, 154. (52) Miller, S. J.; Dunham, G. E.; Olson, E. S.; Brown, T. D. Fuel Process. Technol. 2000, 65-66, 343. (53) Wu, B.; Peterson, T. W.; Shadman, F.; Senior, C. L.; Morency, J. R.; Huggins, F. E.; Huffman, G. P. Fuel Process. Technol. 2000, 63, 93. (54) Serre, S. D.; Gullett, B. K.; Ghorishi, S. B. J. Air Waste Manage. Assoc. 2001, 51, 733. (55) Schager, P. The Behaviour of Mercury in Flue Gases. Ph.D. Dissertation, Chalmers University of Technology, Go¨teborg, Sweden, 1990. (56) Chang, R.; Offen, G. R. Power Eng. 1995, 5, 51. (57) Felsvang, K.; Gleiser, R.; Juip, G.; Nielsen, K. K. Fuel Process. Technol. 1994, 39, 417. (58) Stouffer, M. R.; Rosenhoover, W. A.; Burke, F. Proceedings of the 89th Annual Meeting of the Air & Waste Management Association, Nashville, TN, 1996; Air & Waste Management Association: Pittsburgh, PA, 1996; Paper WP64B.06. (59) Sjostrom, S.; Smith, J.; Hunt, T.; Chang, R.; Brown, T. D. Proceedings of the 90th Annual Meeting of the Air & Waste Management Association, Toronto, Canada, 1997; Air & Waste Management Association: Pittsburgh, PA, 1997; Paper WA72A.07. (60) Waugh, E. G.; Jensen, B. K.; Lapatnick, L. N.; Gibbons, F. X.; Sjostrom, S.; Ruhl, J.; Slye, R.; Chang, R. Proceedings of the 1st EPRI-DOE-EPA Combined Utility Air Pollution Control Symposium, Washington, DC, 1997. (61) Broderick, T.; Haythornthwaite, S.; Bell, W.; Selegue, T.; Perry, M. Proceedings of the 91st Annual Meeting of the Air & Waste Management Association, San Diego, CA, 1998; Air & Waste Management Association: Pittsburgh, PA, 1998; Paper WP79A.09. (62) Pease, B.; Srinivasachar, S.; Porle, K.; Haythornthwaite, S.; Ruhl, J. Proceedings of the Conference on Advanced Coal-based Power & Environmental Systems, Morgantown, WV, 1998. (63) Haythornthwaite, S.; Smith, J.; Anderson, G.; Hunt, T.; Fox, M.; Chang, R.; Brown, T. Proceedings of the 92nd Annual Meeting of the Air & Waste Management Association, St. Louis, MO, 1999; Air & Waste Management Association: Pittsburgh, PA, 1999; Paper 524, pp 2395-2410. (64) Sjostrom, S.; Ebner, T.; Ley, T.; Slye, R.; Richardson, C.; Machalek, T.; Richardson, M.; Chang, R.; Meserole, F. Proceedings of the 3rd EPRI-DOE-EPA Combined Utility Air Pollution Control Symposium, Chicago, IL, 2001. (65) Sjostrom, S.; Ebner, T.; Harrington, P.; Slye, R.; Chang, R. Proceedings of the 95th Annual Meeting of the Air & Waste Management Association, Baltimore, MD, 2002; Air & Waste Management Association: Pittsburgh, PA, 2002. (66) Rostam-Abadi, M.; Chang, R.; Chen, S.; Lizzio, T.; Richardson, C.; Sjostrom, S. Demonstration of Sorbent Injection Process for Illinois Coal Mercury Control; Final Technical Report, ICCI Project 00-1/2.2D-1; 2001. (67) Starns, T.; Bustard, J.; Durham, M.; Lindsay, C.; Martin, C.; Schlager, R.; Donnelly, B.; Sjostrom, S.; Harrington, P.; Haythornthwaite, S.; Johnson, R.; Morris, E.; Chang, R.; Renninger, S. Proceedings of the 95th Annual Meeting of the Air & Waste Management Association, Baltimore, MD, 2002; Air & Waste Management Association: Pittsburgh, PA, 2002. (68) Carey, T. R.; Hargrove, O. W., Jr.; Richardson, C. F.; Chang, R.; Meserole, F. B. Proceedings of the 90th Annual Meeting of the Air & Waste Management Association, Toronto, Canada, 1997; Air & Waste Management Association: Pittsburgh, PA, 1997; Paper WA72A.05. (69) Bustard, C. J.; Durham, M.; Lindsey, C.; Starns, T.; Baldrey, K.; Martin, C.; Schlager, R.; Sjostrom, S.; Slye, R.; Renninger, S.; Monroe, L.; Miller, R.; Chang, R. Proceedings of the 3rd EPRI-DOE-EPA Combined Utility Air Pollution Control Symposium, Chicago, IL, 2001. (70) Flora, J. R. V.; Vidic, R. D.; Liu, W.; Thurnau, R. C. J. Air Waste Manage. Assoc. 1998, 48, 1051.

Ind. Eng. Chem. Res., Vol. 43, No. 10, 2004 2589 (71) Meserole, F. B.; Chang, R.; Carey, T. D.; Machac, J.; Richardson, C. F. J. Air Waste Manage. Assoc. 1999, 49, 694. (72) Flora, J. R. V.; Hargis, R. A.; O’Dowd, W. J.; Pennline, H. W.; Vidic, R. D. J. Air Waste Manage. Assoc. 2003, 53, 478. (73) Scala, F. Environ. Sci. Technol. 2001, 35, 4367. (74) Scala, F. Environ. Sci. Technol. 2001, 35, 4373. (75) Ruthven, D. M. Principles of Adsorption & Adsorption Processes; Wiley: New York, 1984. (76) Karatza, D.; Lancia, A.; Musmarra, D.; Russo, S. Capture of Elemental Mercury Vapors by Sulfur Impregnated Activated Carbon; submitted for publication. (77) Villadsen, J.; Michelsen, M. L. Solution of Differential Equation Models by Polynomial Approximation; Prentice Hall: Englewood Cliffs, NJ, 1978. (78) Dudukovic, M. P.; Lambda, H. S. Chem. Eng. Sci. 1978, 33, 303. (79) Chang, R.; Bustard, C. J.; Schott, G.; Hunt, T.; Noble, H.; Cooper, J. Proceedings of the 2nd International Conference on Managing Hazardous Pollutants, Washington, DC, 1993.

(80) Miller, S. J.; Laudal, D. L.; Dunham, G. E.; Chang, R.; Bergman, P. D. Proceedings of the EPRI/DOE International Conference on Managing Hazardous and Particulate Air Pollutants, Toronto, Canada, 1995. (81) Haythornthwaite, S.; Sjostrom, S.; Ebner, T.; Ruhl, J.; Slye, R.; Smith J.; Hunt, T.; Chang, R.; Brown, T. D. Proceedings of the 1st EPRI-DOE-EPA Combined Utility Air Pollution Control Symposium, Washington, DC, 1997. (82) Hargis, R. A.; O’Dowd, W. J.; Pennline, H. W. Proceedings of the 93rd Annual Meeting of the Air & Waste Management Association, Salt Lake City, UT, 2000; Air & Waste Management Association: Pittsburgh, PA, 2000; pp 1834-1848.

Received for review September 23, 2003 Revised manuscript received February 17, 2004 Accepted February 27, 2004 IE034143G