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AdOxTM

--a Kinetic Model for the Hydrogen Peroxide / UV Process

Ke Li

Shumin Hu

John C. Crittenden

David W. Hand

David R. Hokanson

Portions Presented at AOTs-6 The Sixth Annual Conference onAdvanced Oxidation Technologies for Water and Air Remediation

London, Ontario Canada, June 26-30, 2000

Copyright © 2000-2002. Michigan Technological University. All Rights Reserved.

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Outline

•AOP Mechanism Behind the Model•Model Validation

•Example Applications

•Some Important Features

•Conclusions

•Looking Forward ...

•Objectives of AdOxTM

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Objectives of AdOxTM

Understand the chemistry of AOP process Assess the preliminary design and feasibility of

using advanced oxidation processes Plan pilot plant studies and interpret the results Predict the effect of operational parameters and

provide key parameters for process design Trace the destruction of contaminants and the

formation of byproducts, provide valuable information for mechanism study of AOP

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Outline

•Model Validation

•Example Applications

•Some Important Features

•Conclusions

•Looking Forward ...

•Objectives of AdOxTM

•AOP Mechanism Behind the Model

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• Photolysis of H2O2:

–Initiation: H2O2 / HO2

- + hv 2HO

–Propagation:H2O2 / HO2

- + HO H2O / OH- + HO2

H2O2 + HO2 / O2

- HO + H2O / OH- + O2

–Termination:HO + HO H2O2

HO + HO2 / O2

- H2O / OH- + O2

HO2 + HO2

/ O2- H2O2 / HO2

- + O2

AOP Mechanism Behind The Model

The 44 reactions considered in the model include the most comprehensive mechanism:

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• Reactions of organic compound R:R + hv Products

R+ HO Products

• Inorganic Scavengers:HO + CO3

2- / HCO3- CO3

-+OH- / H2O

HO + HPO42- HPO4

- + OH-

• Direct photolysis of target compound– rUV, R1 = -R1I0 fR1(1-e-A)

–A=2.303b ( H2O2 CH2O2 + R1 CR1 + R2 CR2 + S CS + HO2- CHO2-)

– fR1 = 2.303 b R1 cR1 /A

AOP Mechanism Behind The Model

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• Pseudo-steady-state is not assumed

• pH variation is considered• The influence of Background Organic

Matter is considered:

– absorption of UV light (s) and its influence on the photolysis of target compound and H2O2

BOM + hv – scavenging of hydroxyl radicals

HO + BOM

AOP Mechanism Behind The Model

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Outline

•AOP Mechanism Behind the Model

•Example Applications

•Some Important Features

•Conclusions

•Looking Forward ...

•Objectives of AdOxTM

•Model Validation

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Model Validation

The model was validated by comparing model predictions to the following experiments:

• 1,2-dibromo-3-chloropropane (DBCP) in a complete mixed batch reactor (CMBR) (Glaze and Kang, 1989)

• 1-chlorobutane (BuCl) in complete mixed flow reactor (CMFR)

(Liao and Gurol, 1995)

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Model Validation - Relationship between [H2O2]0 and DBCP pseudo-first-order rate

constant in a CMBR, CT=4 mM, I0=1.04E-6 einsteins/L-s

120

0

20

40

60

80

100

0 1 2 3 4 5 6 7

[H 2O2]0, mM

k 0, D

BC

P, (

10-5

s-1

)

experimental resultAdOx prediction

Glaze et al.'s model prediction

11Fluka Humic Acid as DOC, mg/L

Norm

alized

Con

cen

trati

on

, C

e/C

o

0

0.2

0.4

0.6

0.8

1

0 2 4 6 8 10 12 14

H2O2 , experimental result

BuCl, experimental result

AdOx prediction

Liao et al. 's model prediction

Model Validation - Effect of Humic Acid on BuCl degradation in a CMFR ( [H2O2]0 = 284

mM, [BuCl]0 = 8 mM, t = 7.76 min, CT,CO3 = 4 mM,

pH=7.6, I0 = 2.46 10-4 einsteins/L-min

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Outline

•AOP Mechanism Behind the Model•Model Validation

•Example Applications

•Conclusions

•Looking Forward ...

•Objectives of AdOxTM

•Some Important Features

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Important Features of AdOxTM

1.0• Model Various Reactor Configurations:

– Completely Mixed Batch Reactor (CMBR)– Completely Mixed Flow Reactor (CMFR)

Completely Mixed Flow Reactor (CMFR)

Completely Mixed Batch Reactor (CMBR)

Q,

C in VR

C e

Q, C e

dCdt ao C a1a (C a r )

(Governing Equation)

V RC e

dC adt

ra (Governing Equation)

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Features of Current Version AdOxTM 1.0

–Tanks-In-Series (TIS or CMFRs)

– Plug Flow Reactor (PFR)

– Real Reactor (Describe non-ideal mixing with a tanks-in-series model.)

Q,

Cin

VR

Cn

VR

C1

Q,

C1

Q,

Cn-1

Q,

C nR

Cn-1

V

Q,

Cn-2

Q,

Cn-1

n-CMFR:

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Important Features of AdOxTM

1.0

• Dynamically model multi-component contaminant mixtures (up to 10).

• Model multi-chromatic light sources

(up to 100 wavelength)

• Determine Optimum Operational Parameters:

– Optimum H2O2 Dosage

– UV Light Intensity

– Hydraulic Retention Time

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Important Features of AdOxTM

1.0

• Determine the influence of water quality :– Alkalinity (Total Inorganic Carbon)– pH

• Includes a database of more than 600 compounds including second-order hydroxyl-radical rate constants

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Some Important Features• Modeling Different Reactor Configurations

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Some Important Features• Modeling Multi-chromatic (up to 100) Light Sources

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Some Important Features• Dye Study Analysis for Tanks-In-Series Model

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Some Important Features• Database of Second-Order Hydroxyl-Radical

Rate Constants

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Selection of Optimum [H2O2]0/[DBCP]0 as a function of

Water Quality Parameters

0

50

100

150

200

250

300

350

0 300 600 900 1200 1500[H2O2]0/[DBCP]0

k 0,

DB

CP,

(10-5

s-1)

Io=1.04e-6eins./l-s, TIC=0.01mM, pH7.64

Io=1.04e-6eins./l-s, TIC=0.1mM, pH8.1

Io=1.04e-6eins./l-s, TIC=4mM, pH6.4

Io=1.30e-6eins./l-s, TIC=4mM, pH8.4

Io=1.04e-6eins/l-s, TIC=4mM, pH8.4

Io=0.52e-6eins./l-s, TIC=4mM, pH8.4

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Influence of CT,CO3 on the pseudo-first-order rate

constant of DBCP and H2O2 ([H2O2]0=1.00 mM, I0

=1.04X10-6 eins./L.s,CTIC=4mM)

0

50

100

150

200

250

300

0 1 2 3 4CT,CO3, mM

k0, D

BCP, o

r k 0

, H

2O

2, (

10-5

s-1

) DBCP, experimental resultDBCP, AdOx prediction

H2O2, AdOx prediction

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Impact of CT,CO3 on EE/O for the Degradation of DBCP ([H2O2]0=1.00 mM, I0 =1.04X10-6 eins./L.s, CTIC=4mM,

pH=7~8.4)

0

1

2

3

4

5

0 1 2 3 4 5CT,CO3 (mM)

EE/O

(Kw

h/K

gal

lon-o

rder

)

EE/O, experiment results

EE/O, AdOx prediction

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Impact of pH on Degradation Rate of DBCP and H2O2 (I0 = 1.0410-6 eins./L-s;[H2O2]0 = 1.00mM; CTIC = 4

mM)

0

50

100

150

200

250

300

5 6 7 8 9 10 11pH

k0, D

BCP, o

r k

0, H

2O

2, (

10

-5 s

-1) DBCP, experimental result

DBCP, AdOx prediction

H2O2, AdOx prediction

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Impact of pH on EE/O for the DBCP Degradation (I0 = 1.0410-6 eins./L-s; [H2O2]0 = 1.00mM; CTIC = 4

mM)

0

2

4

6

8

10

12

14

16

18

5 6 7 8 9 10 11pH

EE

/O(K

wh/

Kga

llon-

orde

r)

EE/O, experiment results

EE/O, AdOx prediction

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Outline

•Background

•AOP Mechanism Behind the Model•Model Validation

•Example Applications

•Some Important Features

•Conclusions

•Looking Forward ...

•Objectives of AdOxTM

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Electrical Energy per Order (EE/O)– The electrical energy (in kilowatt hours)

required to reduce the concentration of a pollutant by one order of magnitude for 1000 U.S. gallons of water. For a CMBR:

EE / OP (t / 3600) 3785

V log(C / C )

2.42P

VkKwh / Kgallon order

0 e

0

( )

Example Applications

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3

0

0.5

1

1.5

2

2.5

0 5 10 15 20[H2O2]0, (mg/L)

•[H3C2Cl]0=10g/L=1.610-7M=0.16M•TOC = 5 mg/L •TIC = 8.0 mM•pH 7.0•I0 = 1.010-6 eins./L-s•Optical length L = 7.5 cm•K HO and NOM = 2.0104 (mg/L)-1s-1

•The UV-light absorption and direct photolysis of vinyl chloride are ignored

Example Application I - Predicted Energy Requirement for an Influent Vinyl Chloride

Concentration of 10 g/L(Treatment Objective=2g/L)

EE/O

(Kw

-hou

r/K

gal-

Ord

er)

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EE/O

(Kw

-hou

r/K

gal-

Ord

er)

0

3

6

9

0 20 40 60 80

[H2O2]0, (mg/L)

•[TCE]0=200g/L=1.52M=1.5210-6 M•TOC = 5 mg/L•TIC = 8.0 mM•pH 7.0•I0 = 1.010-6 eins./L-s•Optical length L = 7.5 cm•K HO and NOM = 2.0104 (mg/L)-1s-1

TCE=10M-1 cm-1, the direct photolysis of TCE is ignored.

Example Application II - Predicted Energy Requirement for an Influent TCE Concentration

of 200 g/L (Treatment Objective=5g/L)

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Example Application III - Relationship between EE/O and [H2O2]0/[DBCP]0

-- Impact of operational parameters on process efficiency

Molar Ratio: [H2O2]0/[DBCP] 0

EE/O

, (K

wh

/Kg

al-

Ord

er)

0.0

1.0

2.0

3.0

4.0

5.0

0 300 600 900 1200 1500

Io=1.04e-6eins./L-s, Carbonate=0.01mM, pH7.64

Io=1.04e-6eins./L-s, Carbonate=0.1mM, pH8.1

Io=1.04e-6eins./L-s, Carbonate=4mM, pH6.4

Io=1.30e-6eins./L-s, Carbonate=4mM, pH8.4

Io=1.04e-6eins/L-s, Carbonate=4mM, pH8.4

Io=0.52e-6eins./L-s, Carbonate=4mM, pH8.4

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Outline

•AOP Mechanism Behind the Model•Model Validation

•Example Applications

•Some Important Features

•Conclusions•Looking Forward ...

•Objectives of AdOxTM

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CONCLUSIONS• AdOxTM is an easy-to-use tool for the

design and mechanistic study of the

H2O2/UV process.

• AdOxTM can evaluate the impact of process variables on process performance.

• AdOxTM is capable of simulating the

dynamic behavior of the H2O2/UV process

for several reactor configurations.

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CONCLUSIONS

• AdOxTM is user-friendly with its database, archiving ability and Visual Basic front-end.

• AdOxTM is a practical model and considers the impact of background components in the water matrix, non-ideal mixing, and multi-chromatic light sources.

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Looking Forward...

• More processes options– Models of other AOP technologies

such as the H2O2/O3 and UV/O3

• Byproduct prediction– Generate the reaction pathway and

predict the fate of possible byproducts

• More informative database– More compounds – photochemical properties

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Further Reading

Crittenden, J.C., Hu, Sh., Hand D.W., and Green S.A., "A Kinetic Model for H2O2/UV

Process in a Completely Mixed Batch Reactor," Water Research, 33(10), 2315-2328 (1999).

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Contact us...

Prof. John C. Crittenden, CenCITT, Michigan Tech, (906)487-2798, E-mail: jcritt@mtu.edu

Prof. David W. Hand, CenCITT, Michigan Tech, (906)487-2777, E-mail: dwhand@mtu.edu

Ke Li, CenCITT, Michigan Tech, (906)487-3583, E-mail: keli@mtu.edu