ARTICLE IN PRESS

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doi:10.1016/j.bu

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Building and Environment 43 (2008) 246–252

www.elsevier.com/locate/buildenv

UV-PCO device for indoor VOCs removal: Investigation onmultiple compounds effect

Wenhao Chen�, Jianshun S. Zhang

Building Energy and Environmental Systems Laboratory1, Department of Mechanical and Aerospace Engineering,

Syracuse University, Syracuse, NY 13244, USA

Received 15 January 2006; received in revised form 13 March 2006; accepted 15 March 2006

Abstract

Current design models for ultraviolet photocatalytic oxidation (UV-PCO) devices often assume that the air contains only one volatile

organic compound (VOC) species or all the VOCs in the air can be treated on a non-interacting basis. However, trace-level multiple

VOCs co-exist in most indoor environments. This paper assesses the significance of interference effects among different VOCs for indoor

applications by full-scale ‘‘pull-down’’ experiments assisted with model simulations. Multiple versus single VOC tests were performed on

selected groups of compounds under low concentration levels. Removal efficiency for each compound was calculated. It was found that

the interference effect among test VOCs were generally small in the 2-VOC and 3-VOC mixture tests performed on toluene, ethylbenzene,

octane, decane and dodecane with initial concentration of approximate 1mg/m3 for each compound. However, in the 16 VOC mixture

test, the interference effect among different VOCs became quite obvious, and compounds with lower removal efficiency in the single

compound test appeared to also have relatively lower efficiency and more obvious delay period in the initial reaction. The L–H model

appears to be able to account for this effect if reaction rate constants can be accurately estimated. Results, although limited, indicate that

interference between multiple VOCs may not be neglected for the PCO reactor for indoor applications where the number of VOCs

species is large and the TVOC concentration is high.

r 2006 Elsevier Ltd. All rights reserved.

Keywords: Volatile organic compounds; Photocatalytic oxidation; Multiple components system

1. Introduction

Volatile organic compounds (VOCs) represent a majorgroup of indoor contaminants. They are possible causes ofsick building syndrome and may have adverse health effect.Application of ultraviolet photocatalytic oxidation (UV-PCO) for indoor VOCs removal has received growinginterests in recent years. Different types of models, fromsimple effectiveness-NTU (number of the mass transferunits) method [1,2] to 1-D lumped parameter model [3] andmore complex 3-D UV distribution and(/or) CFD model[4,5], have been developed for analyzing the removalperformance of PCO reactors. All these models assume

e front matter r 2006 Elsevier Ltd. All rights reserved.

ildenv.2006.03.024

ing author.

ess: wchen13@syr.edu (W. Chen).

BEESL.syr.

that the air contains only one VOC species or all the VOCsin the air can be treated on a non-interacting basis.However, experimental results have confirmed the inter-ference effect among different VOCs for the mixture,especially under high concentration levels. For example,Turchi et al. [6] tested a mixture of isopropanol, acetoneand methanol with a concentration of approximate100 ppmV per compound using an annular tube flowreactor. They found that the behavior of the mixture can bedescribed by a Langmuir–Hinshelwood (L–H) model withthe effect of competition between different VOCs for thesame type of adsorption sites considered in the denomi-nator. Lichtin et al. [7] tested 14 binary mixtures of VOCsover Degussa P-25 TiO2 with concentrations ranged from50 ppm to 1% using either a batch reactor or an annulartube flow reactor. Both promotion and inhibition ofremoval of one component by the other as well as absence

ARTICLE IN PRESSW. Chen, J.S. Zhang / Building and Environment 43 (2008) 246–252 247

of significant effects have been observed. They suggestedthat the inhibition of removal could be a consequence ofcompetition between reactants for adsorption sites on thecatalyst, modification of the catalyst surface by adsorptionof or reaction with a reactant, or strong adsorption of anintermediate product from degradation of the otherreactant. As for the promotion of removal of some VOCsby trichloroethylene (TCE) and perchloroethylene (PCE),they attributed the promotion effect to the production of atransient product of decomposition of these reactantswhich can initiate or propagate chain oxidation andsuggested that atomic chlorine played an important role.No quantitative relationships were developed in this paper.Obee and Hay [8] tested the mixture of butanol andpropanal with various combinations of concentrations(0–2.7 ppm) using a glass-plate flow reactor. They foundthat small amount of butanol (i.e. 1.0 ppm) couldsignificantly reduce the oxidation of propanal, althoughthe oxidation rates for each individual compound lied inthe linear range at these low concentrations. However, thedecrease of butanol oxidation rate by the addition of smallamount of propanal was not significant. No quantitativerelationships were developed in this paper. Yang et al. [9]tested the single compound and binary mixture using aglass plate reactor in the concentration range of 4.48–27.4and 1.82–4.08mg/m3 for toluene and benzene, respectively.They found that the PCO of each individual VOC obeyedthe unimolecular L–H rate expression. As for the mixture,competitive adsorption phenomenon existed. The existenceof toluene depressed the PCO of benzene greatly and theeffect increased with increasing toluene concentration, butthis effect could not be described by unimolecular L–H rateform with competitive adsorption considered. The exis-tence of benzene only depressed the PCO of tolueneslightly, and the effect followed the unimolecular L–H rateform with competitive adsorption considered although thereaction coefficients obtained from single compound testcould not be used directly in the model.

Since most of IAQ applications involve multiple VOCspecies at low concentrations (typically in the order of1–100 ppb) [10–12], it is important to determine howsignificant the interference effects can be under indoorconcentration levels and to describe these effects quantita-tively in a model whenever possible. The purpose of thispaper is to access the significance of interference effectsamong different VOCs for indoor applications by full-scaleexperiments assisted with the model simulations. The full-scale ‘‘pull-down’’ test results of a UV-PCO reactor underlow concentration levels using single compounds, binaryVOC mixtures, a triple VOC mixture and a 16-VOCmixture are presented. No such data have been reportedpreviously in the literature. The simulation results from animproved 1-D engineering model are also briefly presented.This model calculates the UV irradiation field based onpublished models and considers the interaction amongmultiple VOCs, although tentatively, on the removalefficiency.

2. Experimental research method

2.1. PCO reactor for testing

The PCO reactor tested was a prototype structuredhoneycomb in-duct unit. It consists of two layers ofhoneycomb monoliths coated with TiO2-based catalyst anda bank of three 25W germicidal UV lamps centered inbetween.

2.2. Test procedures

All the tests were conducted in a 54.4m3 full-scalestainless steel chamber (4.88� 3.66� 3.05m3 or 16� 12�10 ft3) using a ‘‘pull-down’’ test procedure under acontrolled temperature of 2370.5 1C and relative humidityof 5075%. The chamber has a dedicated recirculation ductand HVAC system and there is a test box (0.6� 0.6�0.6m3 or 2� 2� 2 ft3) on the return duct specially designedfor testing in-duct air cleaners. The PCO reactor wasinstalled in the test box and the recirculation flow ratethrough the reactor was controlled at 1360m3/h (800CFM) for all the tests. Between each test, the PCO reactorwas flushed by humid clean air for at least overnight. Anempty chamber test was performed first to investigate thepossible effects of chamber characteristics (i.e. air tightnessand sink effect) on test results for the air cleaners. Detaileddescription of the ‘‘pull-down’’ test procedure and emptychamber test results can be found in Chen et al. [13]. Sinceempty chamber test results indicated good air tightness andonly small sink effects under experimental conditions, weneglect chamber air leakage rate and sink effect in thisresearch. The dynamic period was 1 h for all the tests,except for the 16-VOC mixture which was tested with 12-hdynamic period.

2.3. Test VOCs

Table 1 lists the tests performed during this study. Twoaromatic hydrocarbons (toluene and ethylbenzene) andthree alkanes (octane, decane and dodecane) were selectedfor single VOC, binary and triple VOC mixture tests. Amixture of 16 VOCs, which cover major chemicalcategories and a wide range of molecular weight andboiling point for VOCs commonly found indoors, was alsotested. Detailed information of the challenge VOC mixtureand their properties can be found in Chen et al. [13]. Thetarget initial concentration in experiments was 1mg/m3 foreach compound except formaldehyde and acetaldehyde inthe 16-VOC mixture test, which had a target initialconcentration of 2mg/m3 each.

2.4. VOC sampling and analysis

For quantitation of individual VOC, air samples werecollected on the return duct of the chamber using sorbenttubes (Tenax TA, 0.2mg). These sample tubes were then

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Table 1

Summary of tests performed

Test compound Test date Note

Toluene 2/13/04

Toluene (II) 2/19/04 Repeat test

Ethylbenzene 2/20/04

Toluene+ethylbenzene 2/21/04

Octane 2/25/04

Decane 2/27/04

Decane (II) 5/13/04 Repeat test

Dodecane 5/10/04

Dodecane (II) 5/24/04 Repeat test

Dodecane (III) 5/25/04 Repeat test

Dodecane (IV) 5/26/04 Repeat test

Dodecane (V) 5/27/04 Repeat test

Octane+decane 2/26/04

Octane+decane+dodecane 5/14/0416 VOC mixture: toluene,

ethylbenzene, octane, decane,

dodecane, undecane, hexane,

dichloromethane,

tetrachloroethylene, 1,2-

dichlorobenzene, formaldehyde,

acetaldehyde, n-hexanal, 2-

butanone, cyclohexanone, and 2-

butanol

3/11/04

W. Chen, J.S. Zhang / Building and Environment 43 (2008) 246–252248

analyzed by either an automated thermal desorber–gaschromatograph/mass spectrometer (ATD–GC/MS) or GC/flame ionization detector (FID) system to determine theconcentration of each individual compound excludingformaldehyde and acetaldehyde. For formaldehyde andacetaldehyde, DNPH-Silica cartridges were used to collectsamples and then analyzed by a HPLC system. Themeasurement uncertainty for individual VOC was esti-mated to be 715%. A modern on-line GC/FID with pre-concentrator may be developed and used in the future toreduce the additional source of error due to air sampling bysorbent tubes.

3. 1-D engineering model development

In general, the design model for honeycomb PCOreactor consists of a UV-irradiation sub-model, a VOCreaction kinetics sub-model and a fluid and mass transfermodel.

3.1. UV irradiation field model

The models developed by Hall et al. [3] and Hossainet al. [5] analyzed UV intensity along the monolith channelusing the diffuse reflectance model assuming uniform anddiffuse intensity at the mouth of each channel. Theirmodels allowed the optimization of honeycomb design butcould not show lamp arrangement effects. The modelsdeveloped by Khalifa [4] provided the most detailed (3-D)and accurate light irradiation field, and it allowed theoptimization of design parameters related to lamp arrange-

ments (such as the lamp stand-off distance from thehoneycomb, the reflectivity of duct side-walls, lamp UVoutput and number of lamps). However, the lamp andmonolith channel position and dimensions as well asreaction rate expression were coupled together and itwould require great computational effort if multiple VOCspecies were included. From design point of view, a modelthat can separate the lamp design optimization from thehoneycomb monolith structure design optimization wouldbe simpler and is desired. Therefore, we integrated theexisting models as follows:

(1)

Calculate UV light intensity distribution on themonolith entrance face. This part of the model allowsthe optimization of lamp-related parameters to reachmore uniform and larger average light intensity on themonolith entrance face. Detailed theoretical basis canbe found in Khalifa [4].

(2)

Calculate the UV intensity within the monolith channelbut using the average light intensity on the monolithentrance face obtained from (1) and assuming it wasdiffuse. This part of the model allows the optimizationof monolith configurations (shape, channel aspectratio, etc.) to reach better light penetration inside thechannel. Detailed theoretical basis can be found inHossian et al. [5].

3.2. VOC reaction rate expressions

Considering the lack of experimental data, it is areasonable approach to tentatively define several mostpossible rate expressions for modeling purpose and theother forms of rate expressions can be easily incorporatedonce validated. Three types of rate expressions commonlyused for describing single compound kinetics have beenextended to include multiple VOCs in the current designmodel for the user to choose from:

�

First-order reaction assuming no competition betweenVOCs:

RRexpi¼ ki Csi

; ði ¼ 1; 2; . . . ; nÞ. (1)

�

Unimolecular L–H form with the effect of competitionbetween VOCs for the same type of adsorption sitesconsidered in the denominator:

RRexpi¼ ki �

KiCsi

1þPn

i¼1KiCsi

; ði ¼ 1; 2; . . . ; nÞ. (2)

�

Bimolecular L–H form considering the water vaporeffect and the effect of competition between VOCs forthe same type of adsorption sites:

RRexpi¼ ki �

ðKiCsiÞ � ðKwCwÞ

ð1þPn

i¼1KiCsiþ KwCwÞ

2; ði ¼ 1; 2; . . . ; nÞ,

(3)

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where Cs is the concentration of VOC species on catalystsurface (mg/m3 or ppm), CW the concentration of watervapor on the catalyst surface (mg/m3 or ppm), k thereaction rate constant of VOC species (mg/h-m2 ormmol/h-m2), K the adsorption equilibrium constant ofVOC species (m3/mg or 1/ppm), KW the adsorptionequilibrium constant of water vapor (m3/mg or 1/ppm),n the total number of VOC species, RRexp the reactionrate of VOC species under experimental UV lightintensity (mg/h-m2 or mmol/h-m2) and i is used assubscript to refer to the VOC species i in the mixture.

3.3. Flow and concentration field model

Assuming that the flow is steady and the reaction rateexpression has already been obtained (either from litera-tures or by experiments), the mass balance of VOC species i

can be written by

U fAcdCi

dx¼ �PcKmi

ðCi � CsiÞ or

U fVdCi

dx¼ �AsKmi

ðCi � CsiÞ, ð4Þ

KmiðCi � Csi

Þ ¼ RRi ¼I

I exp

� �p

RRexpi

¼I0FðxÞ

I exp

� �p

RRexpið5Þ

with the boundary conditions

Cijx¼0 ¼ C0i; ði ¼ 1; 2; . . . ; nÞ,

where Ac is the channel cross-section area (m2), As thecatalyst-coated surface area (m2), C the local concentrationof VOC species in bulk-air at location x inside monolithchannel (mg/m3 or ppm), C0 the concentration of VOCspecies at monolith inlet (mg/m3 or ppm), I the localUV light intensity at location x inside monolith channel(mW/cm2), I0 the average UV light intensity at themonolith entrance face (mW/cm2), Iexp the UV lightintensity at location x under which the reaction rateexpression (RRexp) was obtained (mW/cm2), Km the localmass transfer coefficient at location x inside monolithchannel (m/h) which is calculated according to thecorrelation of Hawthorn used in Hall et al. [3] and Khalifa[4], L the monolith channel length (m), p the exponent forreaction rate dependency on UV light (p ¼ 0.5), Pc theperimeter of channel cross section (m), RR the localreaction rate of VOC species at location x inside monolithchannel (mg/h-m2 or mmol/h-m2), Uf the average facevelocity at the inlet of monolith channel (m/h or m/s), V thevolume of the monolith channel (m3), x the axial distancealong the monolith channel (m), and F(x) the dimension-less UV light intensity on the wall along the channel length.

The above differential-algebraic equations (DAEs) canbe solved using the available DAE solver (DASSL,RADAU5, etc.) with a user subroutine. The single passremoval efficiency can then be obtained.

3.4. Modeling the application of UV-PCO device for indoor

VOC control

Modeling the application of UV-PCO device for indoorVOC control is based on the well-mixed single zoneassumption. To compare with full-scale ‘‘pull-down’’ testresults, the model only considers the VOC removal by UV-PCO device and does not include the ventilation and VOCsource term. Assuming perfect mixing in the chamber andneglecting sink effect and air leakage rate, the mass-balancefor a test VOC species under full-recirculation mode can bewritten as:

V rdCri

dt¼ �GCri

Zi ði ¼ 1; 2; � � � ; nÞ (6)

with the initial concentrations

Crijt¼0 ¼ Cinitiali ,

where Cr is the average concentration of VOC species inchamber during ‘‘pull-down’’ test (mg/m3 or ppm), Cinitial

the initial concentration of VOC species in chamber for‘‘pull-down’’ test (mg/m3 or ppm), G the flow rate passingthrough the UV-PCO device during ‘‘pull-down’’ test (m3/h),t the time from turning on the UV-PCO device during ‘‘pull-down’’ test (h), Vr the volume of test chamber (m3), and Z thesingle pass removal efficiency of VOC species.Eq. (6) is solved by explicit finite differential method and

can be easily extended to include the ventilation and VOCsource term.

4. Results and discussions

4.1. Experimental data analysis and results

With the measured curve of VOC concentration decay(detection limit: 0.001mg/m3 under the experimentalsampling and analysis conditions) vs. time (Fig. 1), thesingle pass removal efficiency Z can be calculated fromEq. (6) for each compound tested. If Z does not changeduring the test period, an analytical solution can be obtained:

Cr ¼ Cinitiale�ðG=V rÞZt or ln

Cr

Cinitial

� �¼ �

G

V rZt. (7)

The lines appearing in Fig. 1 are for distinguishing thevarious sets of experimental data. If the measuredconcentrations followed the exponential decay perfectly(Eq. (7)), a straight line on Fig. 1 (semi-log plot) would beexpected. And the presence of curvature would beindicative of a deviation from such dependence. As shownin Fig. 1, the concentration decay followed the exponentialdecay well in all tests except for the results from 16 VOCmixture test. Therefore, the single-pass efficiency wascalculated by least-square fit of experimental data toEq. (7) for these tests and results are summarized inTable 2. For the 16 VOC mixture test, the removalcharacteristics was different for different VOCs and theinitial removal rate of each VOC was significantly reduced,

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0.001

0.01

0.1

1

10

0 2 4 6 8 1210

Time from turning on the UV light (hr)

0 2 4 6 8 1210

Time from turning on the UV light (hr)

0 2 4 6 8 1210

Time from turning on the UV light (hr)

0 2 4 6 8 1210

Time from turning on the UV light (hr)

Co

nce

ntr

atio

n (

mg

/m3)

0.001

0.01

0.1

1

10

Co

nce

ntr

atio

n (

mg

/m3)

0.001

0.01

0.1

1

10

Co

nce

ntr

atio

n (

mg

/m3)

0.001

0.01

0.1

1

10

Co

nce

ntr

atio

n (

mg

/m3)

dodecane

dodecane (II)

dodecane (III)

dodecane (IV)

dodecane (V)

dodecane in 3-VOC mixture

dodecane in 16-VOC mixture

decane

decane (II)

decane in 2-VOC mixture

decane in 3-VOC mixture

decane in 16-VOC mixture

octane

occane in2-VOC mixture

octane in 3-VOC mixture

occane in16-VOC mixture

toluene

toluene (II)toluenein 2-VOC mixture

toluene in 16-VOC mixtureethylbenzene

ethylbenzene in 2-VOC mixtureethylbenzene in 16-VOC mixture

a b

c d

Fig. 1. Experimental data: single compound vs. multiple compounds for (a) dodecane, (b) decane, (c) octane, and (d) toluene and ethylbenzene.

W. Chen, J.S. Zhang / Building and Environment 43 (2008) 246–252250

which made the direct fitting of all experimental data to Eq.(7) inappropriate. Therefore, the reported values in Table 2are 12-h average removal efficiency based on the time-averaged VOC concentration during the test period anddefined in Chen et al. [13].

For single VOC tests, results show a maximumdifference of 10% for all the repeat tests and suggest agood repeatability of the test method. The R2 values ofexponential fit were high, suggesting that the removalefficiency was near constant over the test concentrationrange and the chamber ‘‘pull-down’’ test method was agood way to characterize performance of UV-PCO aircleaner under low concentration levels. For the 2-VOC and3-VOC mixture tests, the addition of other compoundeither somewhat reduced the removal efficiency of thetarget VOC or had no significant effect. For example, theremoval efficiency of dodecane was almost the same inthe 3-VOC mixture test as that in single compound test,while the removal efficiency reduced by a factor of 2(largest in these tests) for octane in the 3-VOC mixture test.The decrease of removal efficiency was within a factorof 1.4 for most other compounds. Considering that thekinetic parameters can generally be determined only towithin a factor of two as stated in Hossain et al. [5],the results are meaningful and suggest that the inter-ference effects among test VOCs under the experimentalconcentration levels were generally small. As for the 16

VOC mixture test, the interference effect among differentVOCs became quite obvious. The reactions of somecompounds (i.e. octane, toluene) on the catalyst surfaceseemed to be prohibited by the coexistence of other VOCsat relatively high concentration levels at the beginning,which was most possibly due to the competition of theavailable adsorption sites. Once the other more reactiveVOCs have been decomposed, the reactions for thesecompounds became faster. The 12-h average efficiency foreach compound in the 16 VOC mixture test was signi-ficantly smaller than that obtained from single compoundtest, suggesting that the interference effect became strongeras more VOCs were added into the mixture and the TVOCconcentration went up. In addition, compounds with lowerremoval efficiency in the single compound test appeared toalso have relatively lower efficiency and more obviousdelay period in the initial reaction during the 16 VOCmixture test.

4.2. Pilot model investigation and parameter analysis

Without experimentally validated reaction rate expres-sions for each group of test compounds, it is difficult tomodel the above mixture experimental results quantita-tively. However, the design model can still provide manyuseful hints into the multi-VOC adsorption process, andassist with the trend-line analysis.

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Table 2

Summary of calculated single-pass efficiency for each test compound

Test VOC compound Fit by regression Single-

pass

efficiency

Z (%)

Relative

effectivenessa

Slope

(GZ/Vr)

R2

Toluene 1.698 0.997 6.8 1.00

Toluene (II) 1.673 0.998 6.7 0.99

Toluene in 2-VOC 1.042 0.995 4.2 0.61

Toluene in 16-VOC 1.8b 0.27

Ethylbenzene 1.936 0.998 7.7 1.00

Ethylbenzene in 2-VOC 1.413 0.997 5.7 0.73

Ethylbenzene in 16-

VOC

2.6b 0.34

Octane 1.609 0.999 6.4 1.00

Octane in 2-VOC 1.304 0.994 5.2 0.81

Octane in 3-VOC 0.801 0.998 3.2 0.50

Octane in 16-VOC 1.1b 0.17

Decane 2.142 0.999 8.6 1.00

Decane (II) 1.938 0.999 7.8 0.90

Decane in 2-VOC 2.095 0.997 8.4 0.98

Decane in 3-VOC 1.504 0.999 6.0 0.70

Decane in 16-VOC 2.5b 0.29

Dodecane 2.204 0.998 8.8 1.00

Dodecane (II) 2.320 0.999 9.3 1.05

Dodecane (III) 2.376 0.998 9.5 1.08

Dodecane (IV) 2.373 0.998 9.5 1.08

Dodecane (V) 2.365 0.997 9.5 1.07

Dodecane in 3-VOC 2.105 1.000 8.4 0.96

Dodecane in 16-VOC 4.0b 0.45

aRelative effectiveness was calculated as the ratio of single-pass

efficiency of a compound in mixture to that of a compound as a single

test VOC.b12-h average removal efficiency.

0.01

0.1

1

10

0 654321

Time from turning on the UV light (hr)

Co

nce

ntr

atio

n (

mg

/m3)

toluene, experiment

toluene in 2-VOC mixture, experiment

toluene in 16-VOC mixture, experiment

toluene, trial modeling

toluen in 2-VOC mixture, trial modeling

toluen in 16-VOC mixture,trial modeling

Fig. 2. Modeling vs. experimental results for toluene tests.

Table 3

Bimolecular L–H model and coefficients for toluene from Obee [14]

Gas k (mmol/h-cm2) K (1/ppmV) Kw (1/ppmV)

Toluene 0.34 1.93 0.00036

RRexp ¼ kðKCsÞðKwCwÞ

ð1þKCs þ KwCwÞ2.

W. Chen, J.S. Zhang / Building and Environment 43 (2008) 246–252 251

Assuming that the interference effects are only due to thecompetition between test VOCs for the same type ofadsorption sites and the overall competition effects of allother VOCs on toluene can be described by the bimolecularL–H rate expression using an imaginary species B, the‘‘properties’’ of species B that will determine its inter-ference effect on toluene include: the initial concentrationof species B in chamber, the diffusion coefficient, theadsorption strength (adsorption equilibrium constant) andreaction rate constant of species B. Fig. 2 shows modelingresults for toluene, assuming species B has the samediffusion coefficient, adsorption strength and reaction rateconstant as toluene. For single toluene test, the bimolecularL–H rate expressions (Table 3) developed by Obee [14]were first used in simulation. However, it was found thatthe reaction rate constant had to be adjusted to 1.5 timesliterature value to fit the experimental data. Consideringthat the kinetic parameters can generally be determinedonly to within a factor of two and the catalyst propertiesmay not be totally identical, the adjustment factoremployed is judged as reasonable and used in 2-VOC and16-VOC mixture simulation. Fig. 3 analyzes the sensitivityof toluene concentration decay to the adsorption strengthand reaction rate constant of species B.

The general trend is comparable with experimentalresults. The competition effect of species B is insignificantwhen initial concentration of species B in chamber is low(i.e. 1mg/m3), and it remains so if the adsorption strengthand reaction rate constant of species B are within a factorof 0.5–2 compared with toluene. Therefore, neglecting theinterference effect among different VOCs may be accep-table when the TVOC concentration level is low (i.e.o2mg/m3). However, the competition effect of species Bbecomes quite obvious when its initial concentration inchamber is high (i.e. 17mg/m3), and change of its proper-ties (adsorption equilibrium constant and reaction rateconstant) will greatly change its effect on toluene removal.For example, the initial removal of toluene will be moreretarded by the stronger adsorption of species B on catalystsites.Since the catalytic reaction rates and interferences might

be different for different sets of VOC species and over 300VOCs have been found indoors, it is very difficult todetermine for the general case a TVOC level below whichinterference effects are not important. However, thecurrent research provided some ideas regarding the orderof magnitude of interference effects, especially for aro-matics and alkanes. Brown [10] reported that the maximummean TVOC concentration in established dwellings wasonly 0.32mg/m3, in which neglecting the interference effectmay be acceptable. However, in new dwellings and officesafter renovation, the TVOC concentration could reach ashigh as 11mg/m3 [10]. Treating the VOCs on a non-interacting basis may significantly overestimate the perfor-mance of PCO reactor for this situation.

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0.01

0.1

1

10

0 54321 6

Time from turning on the UV light (hr)

0 54321 6

Time from turning on the UV light (hr)

Tolu

en

e C

on

ce

ntr

atio

n (

mg

/m3)

0.01

0.1

1

10

Tolu

en

e C

on

ce

ntr

atio

n (

mg

/m3)

K_B = K_tol k_B = k_tol

a b

Fig. 3. Modeling investigation: effect of (a) reaction rate constant k and (b) adsorption equilibrium constant K of species B on toluene removal.

W. Chen, J.S. Zhang / Building and Environment 43 (2008) 246–252252

5. Conclusions and implications

A full-scale PCO reactor was tested on selected VOC andmixtures to evaluate the effect of interference betweenmultiple VOCs on removal efficiency for indoor applica-tions. An improved 1-D engineering model capable ofhandling multiple VOCs was also developed, and used forthe trend-line analysis. Results show that:

(1)

Whether the interference effect for multiple VOCsystem has to be considered depends on the numberof coexisting VOC species, their properties as well asTVOC concentration. In the 2-VOC and 3-VOCmixture tests performed on toluene, ethylbenzene,octane, decane and dodecane, the removal efficiencywas nearly constant and the interference effect amongtest VOCs were generally small within the testedconcentration range. However, in the 16 VOC mixturetest, the interference effect became quite obvious andthe affinity of a compound for the adsorption sites onthe catalyst surface might have played an importantrole on its relative faster removal from the mixture.

(2)

The L–H model appears to be able to account for thisinterference effect if reaction rate constants can beaccurately estimated. More systematic research isneeded to provide the reaction rate constants forindividual and mixture VOCs and determine whetherthe mixture performance can be predicted based on thesingle VOC test data under the concentration levelstypically found in indoor environments.

Acknowledgement

The authors are grateful for the financial support fromNew York State Energy Research and DevelopmentAuthority (NYSERDA), Niagara Mohawk, Xerox Cor-poration and Syracuse Center of Excellence in Energy andEnvironmental Systems.

References

[1] Zhang YP, Yang R, Zhao RY. A model for analyzing the

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