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Uday Khambhammettu, Hyderabad, INDIA Research Upflow Filters Performance Evaluation for treating stormwater. Professional Working as Engineer with Metcalf and Eddy | AECOM, San Diego, CA. Major job responsibilities include designing stormwater BMPs, water and wastewater treatment plants. Interests Traveling, books, music (any kind from rock to Indian classical) and learning new languages. M.S. Environmental Engineering The University of Alabama, 2006 Education B.E. Environmental Engineering V T University, Mysore, India 2002 Graduate Research Assistant for Dr. Pitt (Jan, 04 Jan, 06)

Uday Khambhammettu, Hyderabad, INDIAunix.eng.ua.edu/~rpitt/Presentations/Urban_water... · Uday Khambhammettu, Hyderabad, INDIA Research • Upflow Filters Performance Evaluation

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Uday Khambhammettu, Hyderabad, INDIA

Research

• Upflow Filters Performance Evaluation for treating stormwater.

Professional

• Working as Engineer with Metcalf and Eddy | AECOM, San Diego, CA. Major job

responsibilities include designing stormwater BMPs, water and wastewater

treatment plants.

Interests

• Traveling, books, music (any kind from rock to Indian classical) and learning

new languages.

M.S. Environmental Engineering

The University of Alabama, 2006

Education

B.E. Environmental Engineering

V T University, Mysore, India 2002

Graduate Research Assistant for

Dr. Pitt (Jan, 04 – Jan, 06)

Upflow Filtration for the

Treatment of Stormwater at

Critical Source Areas

Uday Khambhammettu

Metcalf and Eddy, San Diego, CA

Robert Pitt

University of Alabama, Tuscaloosa, AL

Development of Stormwater

Control Devices using Media • Media filtration has been used for many years for the

treatment of stormwater (Maryland, Florida, Texas, etc.)

• EPA-funded research in the 1990s at the University of Alabama at Birmingham examined different media, and multiple treatment processes. Multiple treatment processes can be incorporated into stormwater treatment units to provide:

– Gross solids and floatables control (screening)

– Capture of fine solids (settling or filtration)

– Control of targeted dissolved pollutants (sorption/ion exchange)

WERF-funded project on Metals Removal from

Stormwater to the University of Alabama

Main Project Goals:

• Contribute to the understanding of metals’ capture from urban runoff by filter media and grass swales.

• Provide guidelines to enhance the design of filters and swales for metals’ capture from urban runoff.

Media Filtration Goals:

• Characterize physical properties • Assess and quantify ability of media to capture metals

• Rank media and select media for in-depth study

• Evaluate effect of varying conditions on rate and extent of capture

• Laboratory- and pilot-scale studies of pollutant removal

• Disposal issues of used media (using TCLP)

Clogging Problems Originally Addressed by Pre-

Treatment. What about Upflow Filtration?

Expected Advantages:

• Reduced Clogging: Sump collects large fraction of sediment load.

• Prolonged Life: Particles trapped on the surface of the media will fall into the sump during quiescent periods.

• High Flow Rates: Since large and heavy solids will be removed by way of settling in the sump prior to encountering the filter, the filters can be operated at higher flow rates.

No sump

With sump

Upflow Filter Design with Sump

Pressure

gage

•Sump

• Particulate Solids: Good removal (>90%) for all media for all runs.

• Particulate Metals: Generally 80-100% removal for Pb, Zn, Cd, and Fe and 60-95% removal for Cu and Cr.

• Peat had the best removal rates for particulate bound metals. Removal rates of compost and zeolite were about the same.

Lab-Scale Tests, WERF Project

Upflow Filters for Metals

Removal

Removals of Stormwater Particulates by

Different Media (1 to 175 m)

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

80.0

90.0

100.0

0 2 4 6 8 10 12 14

Residence Time, minutes

% R

em

ova

l

Series1

Series2

Series3

Removal of dissolved zinc using

sand/peat media in upflow filter mode

Gill 2004

Media Quantity

tested (kg)

Stormwater

volume that can

be treated (to

meet Zn capacity)

Paved area that can

be treated per 1 m

rainfall

Activated carbon 18 kg 1 million L 1200 m2 (0.3 ac)

Carbon plus fine

sand

9.2 kg + 22 kg 530,000 L 620 m2 (0.15 ac)

Pelletized peat

plus fine sand

13 kg + 22 kg 310,000 L 365 m2 (0.1 ac)

Activated carbon,

pelletized peat

plus fine sand

6.1 kg + 8.8 kg

+ 15 kg

570,000 L 670 m2 (0.17 ac)

Results of Upflow Filter Flow and Capacity Tests

The UpFlow FilterTM uses

sedimentation (22), gross

solids and floatables

screening (28), moderate

to fine solids capture (34

and 24), and sorption/ion

exchange of targeted

pollutants (24 and 26). It

also incorporates high

bypass capacity to

eliminate inlet clogging.

Prototype upflow filter

insert for catchbasins

UpFlow FilterTM patented

Initial Phase 1

EPA/SBIR tests of

UpFlow Stormwater

FilterTM in 2003

Successful flow tests using prototype unit

and mixed media as part of EPA SBIR

phase 1 project. Phase 2 tests have just

been completed and ETV tests are now

starting.

15 to 20 gpm/ft2 obtained for most media tested

Pelletized Peat, Activated Carbon, and Fine

Sandy = 2.0238x0.8516

R2 = 0.9714

0

5

10

15

20

25

0 5 10 15 20

Headloss (inches)

Flo

w (

gp

m)

SBIR2 field test site, Tuscaloosa, AL, City

Hall and public works vehicle parking area,

0.9 acres.

Test area, new City

Hall, Tuscaloosa, AL

Initial inlet that was

modified for tests

Prototype UpFlowTM filter

tested during SBIR phase 2

tests in Tuscaloosa, AL

Media

support

material

Flow

diffuser

layer

Mixed

media

placed

in bags

Top of media

bag and top

flow diffuser

High flow (300 gal/min) bypass capacity tests

Date Media Flow Rate (GPM)

4-Apr-05 Zeo + Mix (dirty) 30

Mix+Mix (dirty) 15

Zeo + Zeo (clean) 35

10-Apr-05 Zeo + Zeo (dirty) 14

AC+AC (clean) 48

BC+BC (clean) 44

Zeo+Zeo (clean) 35

Flow Tests to Determine Maximum Flow

Capacity of Different Media

Media (each

bag)

Flow

(gpm)

Influent

SS Conc.

(mg/L)

Average

Effluent SS

Conc.

(mg/L)

% SS

reduc.

Zeo+ Zeo High (21) 480 75 84

Zeo+ Zeo Mid (10) 482 36 92

Zeo+ Zeo Low (6.3) 461 16 97

Mix + Mix High (27) 487 75 85

Mix + Mix Mid (15) 483 42 91

Mix + Mix Low (5.8) 482 20 96

Suspended Solids Removal Tests

Zeo: Manganese-coated zeolite

Mix: 45% Mn-Z, 45% bone char, 10% peat moss

Manganese-Coated Zeolite

y = 2.0866x - 25.517

R2 = 0.9947

0

5

10

15

20

25

30

0 5 10 15 20 25

Head (inches)

Flo

w (

gp

m)

Mixed Media (Mn-Z, Bone Char and Peat)

y = 2.6575x - 31.581

R2 = 0.9799

0

5

10

15

20

25

30

35

0 5 10 15 20 25

Head (in)

Flo

w (

gp

m)

EPA-funded SBIR2 Field Test Setup,

Tuscaloosa, AL

mg/L

Pe

rce

nt

806040200-20

99

95

90

80

70

60

50

40

30

20

10

5

1

Mean

0.011

1.259 0.3854 12 0.311 0.507

StDev N AD P

27.34 22.21 12 0.942

Variable

Influent (mg/L)_5

Effluent (mg/L)_5

Normal

Probability Plot of Concentration for Particle Range 30-60 um

mg

/L

Effluent (mg/L)Influent (mg/L)

40

30

20

10

0

Boxplot of Concentration for the Particle Range 3-12 um

Very high levels of

control, even for very

small particles.

Performance Plot for Particle Size Distributions

0

10

20

30

40

50

60

70

80

90

100

0.1 1 10 100 1000 10000

Particle Size (um)

% F

iner

Influent PSD

50 mg/L High Flow

50 mg/L Mid Flow

50 mg/L Low Flow

100 mg/L High Flow

100 mg/L Mid Flow

100 mg/L Low Flow

250 mg/L High Flow

250 mg/L Mid Flow

250 mg/L Low Flow

500 mg/L High Flow

500 mg/L Mid Flow

500 mg/L Low Flow

Upflow Filter Mixed Media Tests (Mn-coated

Zeolite, Bone Char, Peat Moss)

0 to 0.45 µm (TDS)

concentration in

particle size range

(mg/L):

6 gpm/ft2 or

less)

13

gpm/ft2

20 gpm/ft2

(to overflow)

69 (and smaller) 0 0 0

70 0 0 0

80 0 0 0

93 (and larger) 0 0 0 0.45 to 3 µm

2.1 (and smaller) 0 0 0

4.2 0 0 0

10.4 80 42 26

20.8 (and larger) 80 62 34

3 to 12 µm

4 (and smaller) 6 0 0

8 22 22 22

20.1 80 36 35

40.2 (and larger) 80 67 35

12 to 30 µm

2.1 (and smaller) 35 0 0

4.2 35 0 0

10.6 80 42 17

21.2 (and larger) 80 68 31

30 to 60 µm

6.1 (and smaller) 86 86 86

12.2 90 90 90

30.4 96 96 95

60.8 (and larger) 98 98 97

60 to 120 µm

4.4 (and smaller) 95 95 95

8.9 97 97 97

22.2 98 97 97

44.4 (and larger) 98 98 98

120 to 240 µm

0.8 (and smaller) 100 100 100

1.6 100 100 100

4 100 100 100

8 (and larger) 100 100 100

>240 µm

25.2 (and smaller) 100 100 100

50.3 100 100 100

126 100 100 100

252 (and larger) 100 100 100

Scatterplot for 0 to 0.45 um Particles; Low Flow Rate

0

20

40

60

80

100

120

0 20 40 60 80 100 120

Influent (mg/L)

Eff

luen

t (m

g/L

)Scatterplot for 0.45 to 3 um Particles; Low Flow Rate

0

5

10

15

20

25

0 5 10 15 20 25

Influent (mg/L)

Eff

luen

t (m

g/L

)

Scatterplot for 3 to 12 um Particles; Low Flow Rate

0

5

10

15

20

25

30

35

40

45

50

0 10 20 30 40 50

Influent (mg/L)

Eff

luen

t (m

g/L

)

Scatterplot for 12 to 30 um Particles, Low Flow Rate

0

5

10

15

20

25

0 5 10 15 20 25

Influent (mg/L)

Eff

luen

t (m

g/L

)

Scatterplot for 30 to 60 um Particles; Low Flow Rate

0

10

20

30

40

50

60

70

0 10 20 30 40 50 60 70

Influent (mg/L)

Eff

luen

t (m

g/L

)

Scatterplot for 60 to 120 um Particles; Low Flow Rate

0

5

10

15

20

25

30

35

40

45

50

0 10 20 30 40 50

Influent (mg/L)

Eff

luen

t (m

g/L

)

Particle Removal under Low Flow Conditions

Scatterplot for 3 to 12 um Particles; Low Flow Rate

0

5

10

15

20

25

30

35

40

45

50

0 10 20 30 40 50

Influent (mg/L)

Eff

luen

t (m

g/L

)Scatterplot for 3 to 12 um Particles; Mid Flow Rate

0

5

10

15

20

25

30

35

40

45

0 5 10 15 20 25 30 35 40 45

Influent (mg/L)

Eff

luen

t (m

g/L

)

Scatterplot for 3 to 12 um Particles; High Flow Rates

0

5

10

15

20

25

30

35

40

45

0 5 10 15 20 25 30 35 40 45

Influent (mg/L)

Eff

luen

t (m

g/L

)

Scatterplot for 30 to 60 um Particles; Low Flow Rate

0

10

20

30

40

50

60

70

0 10 20 30 40 50 60 70

Influent (mg/L)

Eff

luen

t (m

g/L

)

Scatterplot for 30 to 60 um Particles; Mid Flow Rate

0

10

20

30

40

50

60

70

0 10 20 30 40 50 60 70

Influent (mg/L)

Eff

luen

t (m

g/L

)

Scatterplot for 30 to 60 um Particles; High Flow Rate

0

10

20

30

40

50

60

70

0 10 20 30 40 50 60 70

Influent (mg/L)E

fflu

en

t (m

g/L

)

Effects of Flow on 30 to 60 um Particle Removals

Effects of Flow on 3 to 12 um Particle Removals

Low Flow Medium Flow High Flow

Low Flow Rate (6 gpm/ft2 or less)

Size Range

(µm)

removal rate equation (y =

effluent concentration; x =

influent concentration, both in

mg/L of particulate solids in

designated size range)

Approx. irreducible

concentration

0.0 to 0.45

(TDS) y = x 0

0.45 to 3 y = 0.1088x + 2.3895 2.7

3 to 12 y = 0.1438x + 3.2771 3.8

12 to 30 y = 0.1345x + 1.6574 1.9

30 to 60 y = 0.0245x 0

60 to 120 y = 0.0217x 0

120 to 240 y = 0 0

>240 y = 0 0

mg/L

Pe

rce

nt

100806040200

99

95

90

80

70

60

50

40

30

20

10

5

1

Mean

0.771

84.17 10.81 12 0.402 0.302

StDev N AD P

78.25 13.71 12 0.224

Variable

Influent (mg/L)

Effluent (mg/L)

Normal

Probability Plot of Concentration for Particle Range 0-0.45 um

mg/L

Pe

rce

nt

2520151050

99

95

90

80

70

60

50

40

30

20

10

5

1

Mean

0.011

5.215 3.384 12 0.500 0.167

StDev N AD P

9.36 7.604 12 0.942

Variable

Influent (mg/L)_1

Effluent (mg/L)_1

Normal

Probability Plot of Concentration for Particle Range 0.45-3 um

mg/L

Pe

rce

nt

6050403020100-10-20

99

95

90

80

70

60

50

40

30

20

10

5

1

Mean

0.011

9.079 6.691 12 0.693 0.052

StDev N AD P

18.07 14.68 12 0.942

Variable

Influent (mg/L)_2

Effluent (mg/L)_2

Normal

Probability Plot of Concentration for Particle Range 3-12 um

mg/L

Pe

rce

nt

302520151050

99

95

90

80

70

60

50

40

30

20

10

5

1

Mean

0.011

5.148 3.653 12 0.658 0.064

StDev N AD P

9.518 7.730 12 0.943

Variable

Influent (mg/L)_4

Effluent (mg/L)_4

Normal

Probability Plot of Concentration for Particle Range 12-30 um

mg/L

Pe

rce

nt

806040200-20

99

95

90

80

70

60

50

40

30

20

10

5

1

Mean

0.011

1.259 0.3854 12 0.311 0.507

StDev N AD P

27.34 22.21 12 0.942

Variable

Influent (mg/L)_5

Effluent (mg/L)_5

Normal

Probability Plot of Concentration for Particle Range 30-60 um

mg/L

Pe

rce

nt

100806040200-20

99.9999

99.99

99

95

80

50

20

5

1

Mean

0.011

0.6858 0.9493 12 1.699 <0.005

StDev N AD P

19.98 16.23 12 0.942

Variable

Influent (mg/L)_6

Effluent (mg/L)_6

Normal

Probability Plot of Concentration for Particle Range 60-120 um

mg/L

Pe

rce

nt

1086420-2-4

99

95

90

80

70

60

50

40

30

20

10

5

1

Mean

0.034

* * 10 *

StDev N AD P

3.44 2.721 10 0.747

Variable

Influent (mg/L)_7

Effluent (mg/L)_7

Normal

Probability Plot of Concentration for Particle Range 120-240 um

mg/L

Pe

rce

nt

3002001000-100

99

95

90

80

70

60

50

40

30

20

10

5

1

Mean

0.011

* * 12 *

StDev N AD P

113.2 91.94 12 0.942

Variable

Influent (mg/L)_8

Effluent (mg/L)_8

Normal

Probability Plot of Concentration for Particle Range >240 um

Commercial

UpFlo Filter™

Components:

1. Access Port

2. Filter Module Cap

3. Filter Module

4. Module Support

5. Coarse Screen

6. Outlet Module

7. Floatables

Baffle/Bypass

1

3

2

4 5

7

6

Hydro International, Ltd.

UpFlo FilterTM

Components

1. Module Cap/Media Restraint and Upper Flow Collection Chamber

2. Conveyance Slot

3. Flow-distributing Media

4. Filter Media

5. Coarse Screen

6. Filter Module

1

6

3

4

5

2

3

Hydro International, Ltd.

Hydraulic Characterization

Assembling UpFlo

FilterTM modules for

lab tests Initial CFD

Model

Results

High

flow

tests

Hydro International, Ltd.

Full-Size UpFloTM ETV Test Setup

(Hydro International, Ltd. and Penn State – Harrisburg)

Conclusions

• Setting the initial flow rate using the hydraulic residence time (HRT) predicted from batch studies is not accurate for long-term field applications. Particulate solids loading and clogging in traditional downflow filters will quickly control hydraulic residence times.

• Batch study predictions of rate constants and capacities unlikely to be valid in the field. Laboratory-scale breakthrough curve studies using multi-component and representative concentrations in actual stormwater provide better predictions of kinetics and capacity.

Conclusions (cont.)

• It is desirable to develop stormwater controls that provide treatment train approach. Available research reports describe stormwater characteristics for critical source areas and treatability requirements.

• Upflow filtration with a sump and interevent drainage provided the best combination of pre-treatment options and high flow capacity, along with sustained high contaminant removal rates.

Selected References • Johnson, P., R. Pitt, S. Clark, M. Urritta, and R. Durrans.

Innovative Metal Removal for Stormwater Treatment. Water Environment Research Foundation. 2003.

• Pitt, R., R. Raghavan, and Clark, S. Upflow Filters for the Rapid and Effective Treatment of Stormwater at Critical Source Areas. SBIR Phase 1 report. U.S. EPA, Edison, NJ. 2003.

• Pitt, R., R. Raghavan, S. Clark, M. Pratap, U. Khambhammettu. Upflow Filters for the Rapid and Effective Treatment of Stormwater at Critical Source Areas. SBIR Phase 2 report. U.S. EPA, Edison, NJ. 2005.

• Khambhammettu, U. Evaluation of Upflow Filtration for the Treatment of Stormwater at Critical Source Areas. MSCE thesis. Dept. of Civil and Envir. Eng., the University of Alabama. Tuscaloosa, AL 2006.

Acknowledgements

WERF Project 97-IRM-2

Project Manager: Jeff Moeller

U.S. EPA Small Business Innovative Research Program (SBIR)

Project Officer: Richard Field

Many graduate students at the University of Alabama and Penn State-Harrisburg

Industrial Partners: US Infrastructure and

Hydro International, Ltd.