The Nature and Control of Urban Storm Water – A Physical ... · Slide 1 The Nature and Control of...

The Nature and Control of Urban Storm Water – A Physical-Chemical Perspective

John J. Sansalone, Ph.D., P.E.

Civil and Environmental EngineeringLouisiana State University

Baton Rouge, Louisiana USA

Slide 2

• Transport, fate and treatment of storm water are complexand requires knowledge of:

1. Sources of pollutants:• Mobile sources – traffic loadings, urban sources (VDS)• Fixed sources – infrastructure material and design• Maintenance sources – i.e. winter storm maintenance

2. Chemistry of aqueous solution:• f ( pH, redox, alkalinity, hardness, speciation, kinetics, I, Mex+ )

3. Depositional method, hydrology, fluxes, spatial location• f ( wet/dry deposition, IDF, unsteady flow regime, RTD, loadings)

4. Physical-chemical characteristics of solids/soils• f ( PSD, SSA, SA, pzc, amphoteric nature, charge, stability, Ksat)

Problem Statement

Objectives

1. Background of sources, loadings nature of storm water

2. Understanding the problem – a critical first step before treatment at any location in a watershed

3. Solving the problem – A continuum of treatment (unit operations/processes) urban storm water

Slide 4

Background

• Sources

• Deposition

• Atmospheric influences

• Partitioning

• Annual loadings

• Toxicity

Traffic-generated constituents in storm water

BRAKES- Cu, Pb

ENGINE- Zn, Cu, Cr, Mn- Oil, grease

BODY/FRAME- Zn , Cr, Fe, Al

TIRES- Zn ( 3.0 mg/vehicle-km)- Cd ( 0.02 mg/vehicle-km)- solids (mean dia. = 20µm)- solids (ρs = 1.6)

EXHAUST- particulates

FUEL SYSTEM- VOCs- petroleum

PAVEMENT- solids (1--10,000+ µm)

- PAHs (asphalt)- phenols (asphalt)- thermal (asphalt)

Slide 6

Sources of traffic-generatedparticulates (Cincinnati : 13,500 mg/m2-day @ ADT = 150,000)

engine/brake wear15%

settleable exhaust6%

background atmospheric deposition

3%

pavement wear44 - 49%

tire wear28 - 31%

Objectives – Understanding the Problem

1. Identify sources/quantities of loadings and examine partitioningof heavy metals

2. Examine temporal variation and equilibrium partitioning of heavy metals at location of interest in the watershed –implications for accurate assessment

3. These problems are unsteady and stochastic in nature so therefore we must examine the role of hydrology (rain or snow) on the fate and transport of constituents.

4. Examine distribution of heavy metal mass associated with the entrained particle gradation.

Slide 8

Toxicity

Zn7.6 +2

30 65.38

Cd8.7 +2

48 112.41

Pb7.3 +2

82 207.2

high toxicity for:• aquatic plants• invertebrates• fish(Cu2+) (CuOH+)(Cu2OH2

2+)

• substantial gill damage in fish

• increased toxicity for fish under high Temp. and low DO(Zn2+)

• cytotoxin • carcinogen• toxicity enhanced w/ Cu & Zn present(Cd2+)

• neurotoxin• hemoglogininhibitor for fish & humans (anemia)(Pb2+) (RnPb)

Cu6.7

29 63.55

+2

Urban road runoff vs.untreateddomestic wastewater

Urban Cincinnati data utilized:• 800,000 population (250-Lpd/capita)• 1050-mm mean annual rainfall (C = 0.7)• 40-km2 interstate & arterial road area

RUNOFF WASTEWATERFlow (M3) 3.1 x 109 5.3 x 109COD [mg/L] 350 400 TSS [mg/L] 2001 220ZnT [µg/L] 4500 (232.0 tonsm ) 75 (USEPA, 1993)CuT [µg/L] 150 ( 7.7 tonsm) 35PbT [µg/L] 90 ( 3.6 tonsm) 10CdT [µg/L] 12 ( 0.7 tonsm) 11 TSS: 180-mg/L(81 Urban commercial/residential areas, NURP,1983)

15%

40-km2 as a % of total pavement areafor urban Cincinnati

Slide 10

EMC and Partitioning Equations for Metals¾ EMC* = event mean concentration [M/L3]

¾ M = total mass of constituent [M]¾ V = total volume of flow [L3]¾ c(t) = incremental concentration [M/L3]¾ q(t) = incremental flow rate [L3/ T ]¾ fd = dissolved fraction (< 0.45-µm) [M/L3]¾ fp = particulate-bound fraction [M/L3]¾ m = total suspended solids [M/L3]¾ Kd = partition coefficient (101-106) [L3/M]

¾ Mex+ = metal (i.e. Pb, Cu, Zn, Cd)

¾ t = time [ T ]

0V

t

t0

EMC = M =

∫

c(t)q(t) dt∫q(t) dt

*Applied separately to dissolved and particulate-bound fractions

fd + fp = 1.0

fd = 11 + Kdm +

+

=xd

d Mem

MeK

xp

“First Flush” Concept• Traditional concept suggests treatment of initial

stages only.

• Mathematical approach:

∫∫

t

0

t

0

m(t)Mt

dt

v(t)Vt

dt

> 1.0(

( ))

t = elapsed timem(t) = mass at time tMt = total mass for entire event

v(t) = volume at time tVt = total volume for entire event

Can be applied to dissolved orparticulate fraction separately

Slide 12

Power Law Model (sediments or suspended solids)

• General Form:

• “Signature of a site”• Coefficient (α):

– Index for particle number density

• Exponent (β):– Slope of log-

transformed data– Defines shape of

particle distribution

dNd(dp)

= α dp-β

dpi (µm)1 10 100

Surfa

ce A

rea

Frac

tion

0.00

0.02

0.04

0.06

0.08

0.10

0.12

0.14 β = 1β = 2β = 3β = 4 β = 5

Particle Gradation Indices

• Analyzer yields particle volume density– 32 particle size increments

• Particle number density (particle count)

• Number volume mean size (lnv)

Ni =Vi

C dpi3 Nt = Σ Ni

lnv =Σ Ni dpi

3

Σ Ni

1/3 Vt = C lnv3 Nt

Mt = ρs C lnv3 Nt

Slide 14

• Site Characteristics:• ADT = 150,000 (1997), RTD ranged from 15 to 45 minutes • Asphalt pavement• Mill Creek Expressway in operation since 1961

• Soils:• Clayey glacial till (primarily kaolinite & illite from XRD spectra)• Ksat. range at site: 1 x 10-5 – 1 x 10-7

• Soil SSA range: 10 – 128 m2/g

• Climate and Proximate Land Use Characteristics:• Annual rainfall = 1000 mm , Snow = 50 cm• Land Use = Urban Mixed Use (Before 1960 - Residential) • Rainfall pH: 3.5 to 4 redox : +265 to +455 mV • Runoff pH: 5.6 to 7 redox : +190 to +230 mV

Experimental Site (Urban Cincinnati – upper end of watershed)

Urban rainfall pH @ Cincinnati, OH (1995-96)

0

1

2

3

4

5

6

7

0 2 4 6 8 10 12 14

previous dry days (pdd)

pH

data (n=14)trendline CO2

SO2

acidfog

R 2= 0.80

Slide 16

Experimental site stormwater EMCs vs. EPA criteria(for discharges to modified warmwater surface waters)

dissolved EMC USEPA criterion total EMC OEPA criterion

93.4

17

147.4

180

50

100

150

51.582 89.6

147

0

50

100

150

3987

110

4481

1200

2500

50009.2

3.75.6

0

5

10

15

Cu

Znfd = 0.89

12 Cdfd = 0.77

fd = 0.63

Pbfd = 0.57

• Site EMC: TSS = 204-mg/L• n = 13 rain events • Site mean pH = 6.8

dissolved total dissolved total

EM

C [µ

g/L]

EM

C [µ

g/L]

Partitioning and Kinetics

Particulateform (fp)

Dissolvedform (fd)

De-sorption

Sorption

Kinetic rates, equilibrium are functions of:-pH, redox, sediments, TSS, salinity-RTD, mixing and flow regime-Heavy metal and competitive interactions

0varies

1.0

fd

Time0

50

100

150

200

250

300

0 4 8 12 16 20 24Time from sampling (hours)

Cu

[µg

/ L ]

dissolvedparticulate-bound

pH = 6.5Alkalinity = 30 mg/LTSS = 150 mg/L

fp

fd + fp = 1

fd

fp

Example: Copper

Equilibriumpartitioning

Slide 18

Example: 8 August 1996 - rainfall runoff event(single hydrograph, residence time t50 = 10 minutes)

0 10 20 30 40 500

200400600800

10001200

0.00.20.40.60.81.0

0 10 20 30 40 50020040060080010000

50100150200250

TSS

Elapsed Time (min)Elapsed Time (min)

TS

S [m

g/L]

1e+01e+11e+21e+31e+41e+5

Pb Cu Cd Zn

Kd

[L/k

g]

f d

Flo

w (

L/m

in)

Inte

nsity

(m

m/h

r)

General characteristics of transported sediments

01020304050

4000 15

SS

A (

m 2

/ g )

Particle diameter (µm)

( measured SSAi ) data

0

10

20

30

4000 15mas

s fr

actio

n (%

)

300

SA

i( m

2 )

15Particle diameter (µm)

0

2000

4000

6000

4000

i1

in

i1 in

(measured mi ) data from PSD

calculated (SAi ) results from

discrete P of SSAi with miΣ{(SSAi)(mi)}SAi = SAi : Incremental particle

surface area (m2 ) SSAi : Incremental specific

surface area (m2/g )mi : Incremental particle

mass (g)

Slide 20

40

10000 850 250 106 63 45 15

Zn massR2 = 0.94

Particle diameter (µm)

Cu massR2 = 0.81

SSA SA

Cd massR2 = 0.90

10000 850 250 106 63 45 15Particle diameter (µm)

Pb massR2 = 0.97

SS

A (

m 2

/g )

SA

(m

2 )

Zn

( m

g )

0

9000

0240

0

2.0

0

Cd

( m

g )

60

Cu

( m

g )

0

40

Pb

( m

g )

0

Distribution of heavy metal mass across sediment gradation

Site Characteristics – Baton Rouge

• I-10 City Park Lake overpass

• 270-m span, concrete pavement

• ADT 87,000 east-bound

• 400,000 metro population

• Direct runoff discharge to City Park Lake

• Designated NPDES Phase II area

• 1460 mm rainfall/year

Slide 22

Plan View Of Baton Rouge I-10 Site

Flo

w (

L/m

in)

0

100

200

300

400

Tra

ffic Cou

nt

0100200300400500600700

Elapsed Time (min)0 15 30 45 60 75

Mas

s (g

)

0

50

100

150

200

250

300TSS1 VSS2

Turbid

ity (NT

U)300

600

900

1200

1500

1800Turbidity


CO

D M

ass (g)

0

20

40

60

80

100

120Particulate1 Dissolved2

Flow (v=3176-L)Traffic

1EMC = 225.8-mg/L2EMC = 100.0-mg/L

µ = 0.36

1EMC = 84.4-mg/L2EMC = 69.9-mg/L

EMC = 101.5-NTU

pdh = 70

fd = 0.45

Results for 10 August 2000 Event

Slide 24

Results for 10 August 2000 Event (cont.)


pH (

s.u

.)

6.2

6.4

6.6

6.8

7.0

Redo

x (+m

V)

455460465470475480485490

Flo

w (

L/m

in)

0

100

200

300

400

Tra

ffic Co

unt

0100200300400500600700

1 10 100

dN/d(d

p ) (cm-3 µ

m-1)1e-3

1e-1

1e+1

1e+3

1e+5

1e+7


Mas

s (g

)

0

35

70

105

140TDS

dp (µm)3.4

pH Redox


EMC = 102.4-mg/L

pHMean = 6.6

Redoxmean = 474.4-mV

Results for 10 August 2001 Event (cont.)

Flo

w (

L/m

in)

0

100

200

300

400

Traffic C

ount

0100200300400500600700


Nt (

coun

t)

0.0

3.0e+11

6.0e+11

9.0e+11

1.2e+12

1.5e+12

lnv (µm

)

1

2

3

4

5

Elapsed Time (min)

0 15 30 45 60 75

β

3

4

5

6

7

8

9β1β2


Nt lnv

Nt EMC = 1.1x106-cm-3

lnvmean = 3.1-µm

β1 mean = 6.1

β2 mean = 4.0

dNd(dp)

= α dp-β

Power Law Function:

Slide 26

Particulate First Flush

Normalized Time

0.00 0.25 0.50 0.75 1.00

No

rma

lize

d V

olu

me

0.00

0.25

0.50

0.75

1.00Volume1-µm10-µm50-µm100-µm

Normalized Time

0.00 0.25 0.50 0.75 1.00

No

rma

lized C

ount

0.00

0.25

0.50

0.75

1.00

No

rma

lize

d V

olu

me

0.00

0.25

0.50

0.75

1.00

VolumeNt

TSS

No

rma

lized M

ass

and C

oun

t

0.00

0.25

0.50

0.75

1.007 August 10 August

Process Selection Diagram

• Initial screening of potential solid-liquid separation processes

• Delineated regions representing process alternatives

• Plot of log-Nt vs lnv indicates the most appropriate process for a given size distribution.

• Boundaries determined based on criterion of 90% removal by mass within 1-hour

Slide 28

Process Selection for Suspended Fraction

lnv (µm)0.1 1 10 100 1000

log

Nt (

cm-3

)

0

2

4

6

8

10

12

0.01-mg/L as TSS

10 6-mg/L as TSS

BrownianCoagulation

Direct Filtration

Shear Coagulation

Sedimentationρs = 2.6-gm/cm3Site data

50-mg/L as TSS

lnv (µm)1 10

log

Nt (

cm-3

)

5

6

7

8

9

10

lnv (µm)1 10

log

Nt (cm

-3)

5

6

7

8

9

10

Shear Coagulation

Shear CoagulationDirect Filtration

Direct Filtration

7 August 10 August10 6-mg/L as TSS

10 6-mg/L as TSS

Straining

Conclusions1. Hydrology (quantity and quality parameters) have a direct impact on

transport/partitioning of heavy metals and particulate matter.

2. For low pH rainfall, low residence time and poorly-buffered urban storm water, at the upper end of the urban watershed, partitioning to the dissolved fraction can be important.

3. Heavy metal mass distribution across particulate bound gradation is primarily to mid-range to coarse fraction.

4. Results indicate that in-situ treatment BMP will require particle separation operations in combined or separate units for treatment. At the very upper end of the urban watershed, in-situ treatment will require a combination of adsorption/separation.

5. A “traditional” first-flush does not exist when mass is used as a basis for transport. Mass is driven by hydrology as should treatment.

Slide 30

Unit Operations and Processes for Storm Water (BMPs)

THE BMP CONTINUUM

Technologyexamples

BMP Type

Control

Classification

Technology&

CapitolIntensity

P SourceControl

In -SituControl

End -Of - PipeControl

CentralizedTreatment

3

unleadedfuels

porouspavement

PER,Infiltration

Solids Separation,Detention, Retention

WWTP

High Tech.

High Cost

Low Cost

High Tech.

LOCATION IN WATERSHEDCONTROLS

TREATMENTCONTROLS

SOURCE

Slide 32

Filtration Systems

• Structural BMPs include Filtration systems, Infiltration systems, Detention systems, Retention systems, Constructed wetland systems, Vegetated systems etc.

• Filtration systems are devices that utilize a media such as sand, gravel, engineered media, peat or compost to remove a fraction of the constituents found in storm water.

• Limited abilities of most typical current filter media to remove dissolved heavy metals; according 2001 National Storm water BMP Database (USEPA 2001)

Sorptive Systems

• Engineered sorptive mediaare needed in order to combine unit operations of filtration and unit processes of adsorption;

� Mechanism of heavy metal removalcan range from ion exchange, surface complexation, and precipitation.

Slide 34

Application of Media to Urban Hydrologic Treatment System (Cincinnati, OH)

Lateral sheet flow (Qsf)Infiltration

Pavement

Surroundingsoil

H

W

Shoulder

Qe

Capacity is a function of• Qsf characteristics (EBCT = 15+ min)(volume, peak, duration)

• Mass loading• Media physical & chemical properties• Engineered design of PER(H ~ varies, W ~ varies)

System Benefits•Water quality enhancement•Multi-purpose infrastructure•Water quantity attenuation•Passive (but requires maintenance)

Underdrain

Subgrade

(KCPP = 10-2 cm/s)(f `c = 27,000 kPa)

Surrounding soil(clayey glacial till)

Ksoil = 10-6 cm/sQU

Qe

PER(Sorptive filtration media)

Kmedia

(10-2 cm/s)

Traveled pavement

PER hydraulics ( 12 June 97 runoff event )

0

20

40

60

80

0 10 20 30 40 50 60

Time (min)

Flo

w r

ate

( L/

min

)

inflow hydrograph (Qsf)outflow hydrographvariably saturated flow model

τi = 15 min.

τm = 14 min. ε = 0.40

K s (soil) = 5 x 10 -6 cm /s.

K s (media) = 2 x 10 -2 cm /s.

Slide 36

Freundlich isotherm model

n

eFe CKQ =

Qe: adsorption capacity (mg/g);

Ce: equilibrium concentration of adsorbate (mg/L);

KF: empirical constant, an indication of adsorption affinity;

n: empirical constant, reflects steepness of curve (nonlinearity).

Freundlich isotherm for MOPM (good fit)

CCee (mg/L)(mg/L)00 11 22 33 44 55

0.00.0

0.20.20.40.4

0.60.60.80.8

1.01.0

ZnZnCuCu

Cu: Cu: QQee =0.429=0.429CCee0.4440.444

Zn: Zn: QQee =0.276=0.276CCee0.3510.351

CC00 = 5 mg/L= 5 mg/LpH = 7.0pH = 7.00.0

0.10.20.30.40.50.6

pH 6pH 5

pH 5: Qe=0.217Ce0.253

pH 6: Qe = 0.223Ce0.493

Pb C0 = 5 mg/L

Ce (mg/L)0 1 2 3 4 5

0123456

pH 7

pH 7: Qe = 1.358Ce0.789

Pb C0 = 5 mg/L

neFCKeQ =Freundlich Equation:

pHi pHe Metal KF n r2

7 6.63-5.71 Pb 1.358 0.789 0.9596 5.81-5.36 Pb 0.223 0.493 0.8785 5.07-4.96 Pb 0.217 0.253 0.8357 6.87-6.15 Zn 0.276 0.351 0.9567 6.74-6.03 Cu 0.419 0.444 0.892

eQ

Slide 38

Breakthrough Curve (BTC) for Silica Sand, IOCS and MOCS

00.20.40.60.8

1

0 20 40 60BV

C/C

0

Silica sand

BV0 100 200 300

IOCS

00.20.40.60.8

1

0 200 400 600BV

C/C

0

MOCS

ZnCdPbCu

C0 = 5 mg/ L for each of Zn, Cd, Pb and Cu.

10% breakthrough BV.

Zn Cd Pb Cu

Silica sand 0 0 0 0

IOCS 10 10 80 10

MOCS 10 10 100 100

ZnCdPbCu

ZnCdPbCu

BTC for GAC and BSPER

0

20

40

60

80

100

5 6 7 8 9 10pH

% p

reci

pita

te

ZnCdPbCu

pH

00.20.4

0.6

0.81

0 100 200 300 400 500BV

C/C

0GAC

0 200 400 600BV

5

6

7

8

9

10

Eff

lue

nt p

H

BSPET

C0 = 5 mg/ L for each of Zn, Cd, Pb and Cu.

Influent pH = 6.5

10% breakthrough BV.

Zn Cd Pb Cu

GAC 45 15 120 350

BSPET 80 70 420 >600

ZnCdPbCu

Slide 40

Example of Media Capacity for an Engineered Design (Application of PER in Cincinnati, OH)

PER Loading Inputs• Drainage Area (15 x 20 m) = 300 m2

• Cvolumetric = 0.5• Annual rain fall depth = 1000 mm• EMCs for (Me2+)aq [mg/L] :

– Zn = 1000 – Pb, Cu = 100– Cd = 10

• Annual linear Qsf : = 20,000 L/m

PER System Design• ksat(media) = 10-2 cm/sec

• ksoil = 10-6 cm/sec• Width of PER = 30 cm• Depth of PER = 90 cm

• Media: η = 0.40

• Media: ρs = 2.7

PER System Capacity (Qsf or years) (based on q at C/C0 = 0.10)

• Plain filter sand (typical media) = 30 L(0.00015 year) [q = 0.0001 mg/g]• IOCS (BSPET: 33,000 L) = 6,600 L (0.33 yrs) [q = 0.013 mg/g]

• GAC (ρs = 1.8) = 57,000 L (2.85 yrs) [q = 0.19 mg/g] • MOPM = 138,000 L (6.9 yrs) [q = 0.46 mg/g]• MOCM = 762,000 L (38.1 yrs) [q = 2.54 mg/g]

Application of Media to Engineered Urban Hydrology Treatment System (Baton Rouge, LA)

Qsf

Influent

Sludge collection chamber

Media (BV = 14L)

Effluent

Effluent siphon line

Elevated Transportation Infrastructure

SBMC: Sorptive Media Clarifier

Qsf: Pavement Sheetflow

SBMC

Slide 42

Treatment Operational Specifications

Flow Rate (L/min)

Surface Loading Rate (L/m2 min)

Pumping Time (min)

Backwash Prior to Event

Additional solids loadings (kg)

8/4/00 8/16/0010/5/00 2/6/01

3.75 3.75 3.75 3.75

207 207 207 207

300 390 360 360

yes yes yes no

0 0 4 10

Event Date

Treatment Event Protocol

• Four treatment events examined• Samples collected from three sample locations

– Influent to system– Influent to filter– Effluent from system

• Removal Efficiency

• Unit process evaluation as a function of particle size– Sedimentation theory– Filter evaluation

Min - Meff

Min

x 100E =

Slide 44

Sedimentation Theory• Terminal Settling Velocity

– Newton’s equation

• Overflow rate theory– Ideal or quiescent settling

• Hazen’s Theory– Non-ideal basin conditions– N is number of hypothetical

compartments ranging from 1 to ?

4 dp(ρs – ρl)g

3 fd ρl

Vt2 =

Vc =QA f =

VtVc

Q = flow rateA = basin surface areaVc = critical settling velocity

ρs = particle densityρl = fluid densityfd = drag coefficient

)(f = 1+Vt

N(Q/A)-N

1-

f = fractionremoved (0-1)

Filter Evaluation• Filter coefficient (λ)

• Media diameter/Particle diameter ratio (dm/dp)– dm and dp each represented by d50

– < 10 – surficial straining– 10-20 – deep bed filtration– > 20 – physical-chemical mechanisms

• Head loss (H)– Kozeny-Carmen equation:

dCdz = - λ C λ =

1z

lnCin

Ceff( )

H =cf

φ1-θθ3

zdm

Vs2

gcf = friction factorφ = media shape factor

Slide 46

TSS Removal Efficiency

TS

S R

emov

ed (

%)

0

20

40

60

80

100

Pore Volumes Treated0 400 800 1200

TS

S R

emov

ed (

%)

0

20

40

60

80

100 Pore Volumes Treated0 400 800 1200

TS

S R

emoved (%

)

0

20

40

60

80

100

8/4/00 8/16/00 10/5/00 2/7/01

CONTROLTYPE I

TYPE II

Control vs Type IControl vs Type IIType I vs Type II

0.330.380.88

p-values (<0.05 indicatesstatistical significance)

Turbidity Removal Efficiency

NT

U R

em

oved

(%

)0

20

40

60

80

100


NT

U R

em

oved

(%

)

0

20

40

60

80

100 Pore Volumes Treated0 400 800 1200

NT

U R

em

oved (%

)0

20

40

60

80

100

8/4/00 8/16/00 10/5/00 2/7/01

CONTROL

TYPE I

TYPE II

Control v Type IControl v Type IIType I v Type II

0.220.850.38


Slide 48

Ni R

em

oved

(%

)

0

20

40

60

80

100

dpi (µm)1 10 100

Ni R

em

oved

(%

)

0

20

40

60

80

100

dpi (µm)1 10 100

% N

i Re

mov

ed

0

20

40

60

80

100

OverallFiltrationSedimentation

Control Type I

Type II

Ni removal as a f (particle diameter)


0.140.030.19

p-values (Nt) (<0.05 indicatesstatistical significance)

16 August Event

dpi (µm)1 10 100

Ni R

em

ove

d (%

)0

20

40

60

80

100

dpi (µm)1 10 100

Ni R

em

ove

d (

%)

0

20

40

60

80

100

Ni R

em

ove

d (

%)

0

20

40

60

80

100

4 August

6 February

16 AugustDataOverflowHazen

Sedimentation as a f (particle diameter)

Overflow:

Hazen’s:

Vc =QA

Q = 3.75-L/min A = 182.4-cm2

)(f = 1+ VtN(Q/A)

-N1-

f = Vt

Vc

T = 20oC N = ?

(N = ? )

Slide 50

Head loss


8.52x10-8

2.09x10-4

3.73x10-5


Hea

d lo

ss (

mm

H2O

)

200

400

600

800

1000


Hea

d lo

ss (

mm

H2O

)

200

400

600

800

1000

8/4/00 8/16/00 10/5/00 2/7/01

φ = 0.75

Control Type I

Type II Pore Volumes Treated0 400 800 1200

Head loss (m

m H

2 O)

200

400

600

800

1000Predicted φ = media shape factor

Vs = 0.34-cm/s

θ = 0.35

cf = 12.8

dm = 3.44-mm

z = 0.78-m

Conclusions

• Effective treatment requires of:• Understanding of physical and chemical nature of

aqueous and solid phases in storm water,• Understanding of rainfall or snowfall hydrology,• The role and kinetics of partitioning,• The distribution of heavy metals across the particle

gradation,• Location in watershed,• Knowledge of unit operations and processes, • Site, soil and loading constraints,• A suite of unit operations and processes will be

required.

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