A Dynamic Model of Biofiltration for Odor Control

Hebi Li, Ron W. Martin Jr., John C. Crittenden, James R. Mihelcic

Department of Civil and Environmental Engineering Michigan Technological University

Based on Material Presented to Central States Water Environment Association (CSWEA) Conference, May 14, 2001

Copyright © 2001-2002. Michigan Technological University. All Rights Reserved.

OutlineOutline

Introduction Motivation and Objectives Model Development Model Calibration and Verification Model Applications

IntroductionIntroduction Odor Sources

Wastewater collection and treatment, petrochemical, paper, agricultural, et. al.

Odor-causing chemicals: Ammonia, VOCs, reduced sulfur compounds Hydrogen Sulfide (H2S)

– Low Odor Threshold: 8.5-1,000 ppbv

– Toxicity– Corrosive

Introduction Introduction (continued)(continued)

Odor Control Technologies Physicochemical: scrubbing, adsorption,

incineration, oxidation, masking.–Disadvantage: high operational cost

Biofiltration–Advantages:

• requires no chemical addition • can be operated at room temperature• low operational cost

Why a Biofiltration Model?Why a Biofiltration Model?

Design and operation of biofilters for control of odor-causing air emissions is not well developed (Hautakangas et al., 1999).

A good mathematical model is useful to aid in biofilter design and operation.

No model had been available for design and optimization of biofilters used for odor control (Card, 1999).

Study ObjectivesStudy Objectives Develop a mathematical model that simulates

the processes occurring in a biofilter used for odor control

Calibrate and verify the model using full-scale and pilot-scale data

Evaluate the usefulness of the model as a tool for biofilter design and operation

Schematics of a BiofilterSchematics of a Biofilter

Air with H2S

Clean air

Packing Material Supporting Biofilm

Biological Reaction

Water with nutrients

Water with oxidation products

Schematics of a BiofilterSchematics of a Biofilter

GasLiquidmassfluxFH IK

FHG

IKJK

C

HCL

gl

massfluxFH IK K C C xf l b 0b g

BiofilmSupport

massfluxFH IK

DC

xbb

consumptionrate

FH IK r x z tsub , ,b g

Mechanisms Used in ModelMechanisms Used in Model

Advective flow in gas- and liquid-phases

Mass transfer at the gas-liquid and liquid-biofilm interfaces

Internal diffusion in the biofilm Active biomass growth and decay and

biological reaction in the biofilm

Plant Layout - Cedar Rapids (Iowa) Plant Layout - Cedar Rapids (Iowa) WPCFWPCF

2 Full-Scale Biofilters in 2 Full-Scale Biofilters in ParallelParallel

Surface Area = 2,556 ftSurface Area = 2,556 ft22 each each

Packing Medium - Lava Packing Medium - Lava RockRock

(Average ~1 inch Diameter)(Average ~1 inch Diameter)

Interior of Cedar Rapids Biofilter

6 ft. media depth

Cross Section of Lava RockCross Section of Lava RockShowing Porous StructureShowing Porous Structure

Intermittent Rinse Water Intermittent Rinse Water Feed Feed

(Secondary Effluent 5 minutes per (Secondary Effluent 5 minutes per hour)hour)

Pilot-Scale Pilot-Scale BiofilterBiofilter

Lava Rock Lava Rock 3.1 ft 3.1 ft22 Area Area

byby6 ft. Depth6 ft. Depth

Model Calibration and VerificationModel Calibration and Verification

Using H2S data from Cedar Rapids

Calibration– pilot data: 03/07/00~03/14/00

Verification– pilot-scale data: 01/17/00~01/28/00– full-scale data: 10/09/98 - 11/03/98

Minimize Objective Function:2

data,i model,i

1 data,i

1OF

1

n

i

C C

n C

Model Calibration with Pilot-scale Model Calibration with Pilot-scale Data from Cedar Rapids (20°C)Data from Cedar Rapids (20°C)

(Air residence time 6.5 sec)

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3/7/00 3/8/00 3/9/00 3/10/00 3/11/00 3/12/00 3/13/00 3/14/00 3/15/00

Eff

lue

nt

H 2S

Co

nc

en

tra

tio

n (

pp

m v)

0

50

100

150

200

250

300

Infl

ue

nt

H 2S

Co

nc

en

tra

tio

n (

pp

m v)

Model Output

Measured Effluent

Measured Influent

Model Verification with Pilot-scale Model Verification with Pilot-scale Data from Cedar RapidsData from Cedar Rapids (11.5°C)(11.5°C)

(Air residence time 7.7 sec)

0

10

20

30

40

50

60

70

80

1/17/00 1/19/00 1/21/00 1/23/00 1/25/00 1/27/00 1/29/00

Eff

luen

t H 2

S C

on

cen

trati

on

(p

pm v

) Model Output

Measured Effluent

Model Verification with Full-scale Model Verification with Full-scale Data from Cedar Rapids (25°C)Data from Cedar Rapids (25°C)

(Air residence time 8.4 sec)

0.0

0.5

1.0

1.5

2.0

2.5

3.0

10/9/98 10/13/98 10/17/98 10/21/98 10/25/98 10/29/98 11/2/98

Eff

luen

t H

2S C

on

cen

trat

ion

(p

pm

v) Measured Effluent

Model Output

OutlineOutline

Introduction Motivation and Objectives Model Development Model Calibration and Verification Model Applications

Model Application:Model Application:Effect of Residence TimeEffect of Residence Time

0

0.2

0.4

0.6

0.8

1

3 4 5 6 7 8 9Residence Time (sec)

Eff

lue

nt

H2S

Co

nc

en

tra

tio

n (

pp

mv)

Influent Concentration = 100 ppmv @ 25 C

Model Application:Model Application: Effect of Influent Conc./Temperature Effect of Influent Conc./Temperature

0

5

10

15

20

0 100 200 300 400

Influent H2S Concentration (ppmv)

Req

uir

ed R

esid

ence

Tim

e (s

ec) 15C

20C

25C

9

Model Application:Model Application:Effect of Variable Influent Conc.Effect of Variable Influent Conc.

0.0

0.2

0.4

0.6

0.8

1.0

7 8 9 10 11 12 13 14

Elapsed Time (days) (@ 25 C)

Eff

luen

t H

2S C

on

c. (

pp

mv)

0

20

40

60

80

100

120

140

160

Infl

uen

t H

2S

Co

nc.

(p

pm

v)

Conclusions from ModelingConclusions from Modeling The lava rock-based biofilter is efficient

for treating odorous H2S.

The biofiltration model, which has been incorporated into a friendly software (BiofilterTM), is capable of predicting the biofilter removal performance of H2S.

The model is a useful tool for biofilter design and operation.

Further ReadingFurther ReadingLi, Hebi, John C. Crittenden, James R. Mihelcic, H. Hautakangas,

“Optimization of Biofiltration for Odor Control: Model Development and Parameter Sensitivity," Water Environment Research, 74(1):5-16, 2002.

Martin, Ron W., Hebi Li., James R. Mihelcic, John C. Crittenden, Donald R. Lueking, Chris R. Hatch, Pat Ball, “Optimization of Biofiltration for Odor Control: Model Verification and Applications," Water Environment Research, 74(1):17-27, 2002.

Li, Hebi, James R. Mihelcic, John C. Crittenden, Keith Anderson, “Application of a Dynamic Biofiltration Model to a Two-Stage Biofilter that treats Hydrogen Sulfide and Organic Sulfur Compounds,” Proceedings of the 75nd Annual Water Environment Federation Conference & Exposition, September 28-October 2, 2002.

Hautakangas, Hannu, James R. Mihelcic, John C. Crittenden, Eric J. Oman, Optimization and Modeling of Biofiltration for Odor Control, Proceedings of the 72nd Annual Water Environment Federation Conference & Exposition, October 10-13, 1999.

AcknowledgementsAcknowledgements Project Support:

– Prof. Donald Lueking (MTU)– Christopher R. Hatch (Cedar Rapids WPCF)– Patrick Ball (Cedar Rapids WPCF)

Financial Support:– Cedar Rapids Water Pollution Control Facility– National Center for Clean Industrial and

Treatment Technologies– US Department of Education GAANN Program