introduction and perspective - deohs home

Opportunities for Bringing Rapidly Emerging

Technologies to Revolutionize Modeling of

Chemical Contaminants of Coastal Waters

Dr. Joel Baker

Director, UW Puget Sound Institute

University of Washington Tacoma

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Introduction and Perspective

May, 1982: Duluth, Minnesota

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Introduction and Perspective

October, 2012: Tacoma, WA

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The Information Technology Revolution

NJTechReviews6


2010 Map of the Global Internet by Cisco Systems

7

Map data © 2012 Googl e -

To see all the details that are visible on the

screen, use the "Print" link next to the map.

seattle traffic report - Google Maps http://maps.google.com/maps?oe=utf-8&rls=org.mozilla:en-US:...The Information Technology Revolution

8

Modeling Chemical Contaminants in

Aquatic Ecosystems:

Seminal Papers in PCB Modeling

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Aquatic Ecosystems: Karickhoff et al. 1979

10


Aquatic Ecosystems: Karickhoff et al. 1979

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Modeling Chemical Contaminants in Aquatic

Ecosystems: Thomann and DiToro, 1983

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Ecosystems: Mackay, 1989

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Ecosystems: Mackay, 1989

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Ecosystems: Gobas and Mackay, 1988

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Ecosystems: Gobas and Mackay, 1988

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Ecosystems: Current Models

R.A. Park et al., 201017


Ecosystems: NY/NJ Harbor CARP Model

Management Question

�Which sources of contaminants need to be reduced or

eliminated to render future dredged material clean?

Management Question

�Which sources of contaminants need to be reduced or

eliminated to render future dredged material clean?

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Ecosystems: NY/NJ Harbor CARP Model

19 20

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Summary of 2,3,7,8-TCDD

interim ““““clean bed”””” analysis

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NJTechReviews

?

CARP

23

Premise of Today’s Talk

Tools to model contaminant behavior and effects in

aquatic ecosystems have not kept up with the

information technology revolution

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Corollaries

1. We assume that technology is frozen in time

to what tools we had available in grad school

(computers, IT, and analytical chemistry)

2. Innovation and experimentation may be seen

at odds with stability and confidence

25

Wait!

Is this really a problem?

What are we missing with current models?

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27

Non-Spherical Cows

1. Phase partitioning in the water column

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• Use PCB and PAH distribution coefficients

measured in the Chesapeake Bay to explore the

mechanism driving observed variability

– three-phase partitioning?

– slow sorption kinetics?

– highly sorbent particles?

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Log KOW

3 4 5 6 7 8 9

Lo

g K

d

1

2

3

4

5

6

7

8

9

PAHsPCBs

[Mass on Filter/Volume Filtered]

Kd= -----------------------------------------------

[Mass on XAD/Volume Processed][TSS]

Log

Kd

30

Log Kd

3.84 3.97 4.11 4.24 4.37 4.50 4.64 4.77 4.90 5.03 5.17 5.30

Fre

quency

0

5

10

15

20 Pyrene

N = 119

Baltimore Harbor

Surface Waters

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Percent Dissolved

1 6 11 16 21 26 31 36 41 46 51 56 61 66 71 76 81 86 91 96

Fre

quency

0

2

4

6

8

10

12

14

16Pyrene Fraction DissolvedN = 119Baltimore Harbor Surface Waters

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CHARM Water PCBs

Log Kow

5 6 7 8

Measu

red

-Mo

dele

d(n

g/g

-dry

)

-300

-200

-100

0

100

200

(11 points offscale)

Investigating the sources of variability in partitioning

Re

sid

ua

l so

lid

ph

ase

co

nce

ntr

ati

on

(n

g/g

-dry

)

33

KDOC = 0.08Kow

High variation due to:

the nature of DOC

the methods used

Environmental Science and Technology, 2000, 34, 4663-4668

1. The presence of colloids


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Baltimore HarborDissolved Organic Carbon

DO

C, m

g/L

4

6

8

Total Suspended Solids (mg/L)

20 40 60 80


1. The presence of colloids

70% between 3.5 and 5.5 mg/L

DO

C (

mg

/L)

35


2. Kinetics of Partitioning

C-18 or PUF Sorbent

Water Saturator

5 µm Impactor

Gas Flow Meters

HOC Equilibrated Bubbles

Reactor Vessel

Temperature Regulated

Generator Columns

Heated Block

Sampling Port

Air Stone

Hig

h-P

uri

ty A

ir

Activated Carbon Trap

Laboratory PCB congener sorption experiments• Gas-phase equilibration maintains constant dissolved

PCB congener concentrations.

• Stationary-phase chrysophyte Isochrysis galbana

• 18 congeners studied over 120 hours

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Time (hours)

0 20 40 60 80 100 120

PC

B in A

lgae (

ug/g

)

0

100

200

300

400

500

PCB #52

PCB #101

PCB #97

PCB #77

PCB #118

PCB #105

0

100

200

300

400

500 PCB #3

PCB #10

PCB #15

PCB #180

PCB #170

PC

B C

on

cen

tra

tio

n i

n A

lga

e

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Uptake Rate Constant

L/k

g-h

r

103

104

105

Desorption Rate Constant

Log Kow

5 6 7

1/h

r

0.01

0.02

0.03

0.04

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Log Kow

4.5 5.0 5.5 6.0 6.5 7.0 7.5

Lo

g K

oc

4.5

5.0

5.5

6.0

6.5

7.0

7.5 15 minutes

72 hours

Ob

serv

ed

Lo

g K

OC

39


3. Types of aquatic particles

TSP

0 20 40 60

Fra

cti

on

Pla

nkto

n

0.2

0.4

0.6

0.8

1.0

CHARM 01 (Fall '99)

CHARM 02 (Winter '00)

CHARM 03 (Summer '00)

Fra

ctio

n d

isso

lve

d p

yre

ne

40

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1. Phase partitioning in the Water

Column

The observed variations in dissolved-particulate distributions of PCBs,

PAHs, etc. are large and real.

Although organic colloids likely moderate dissolved HOC concentrations,

DOC does not vary enough to explain the observed partitioning.

In studies with well-characterized solids, sorption kinetics

are sufficiently fast (at least on a log-log plot).

Remarkably large (i.e., order of magnitude) variations in HOC-solid

interactions among particle types.

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Non-Spherical Cows

2. Interactions among particles

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Physical characteristics of flocs

• Lower settling

velocity

• Lower bulk density

• Higher contact

area (porosity)

http://www.water-technology.net/contractor_images/cu_water/flocke.jpg

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How are flocs formed?

Yao and O’Melia (1971)

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Flocculation and PCB Models

• The model simulated the floc size among 2 to 1000 µm

• The multi-class flocculation model equations are based on the concept

of O’Melia (1982)

• The floc porosity and settling velocity are based on the concept of

Winterwerp (1998)

• The floc settling velocity, floc density, stickiness coefficient, and fraction

of organic carbon (fOC) are calculated simultaneously and temporally at

each class of flocculation particle

• The PCB mass transfer coefficient is varied with floc properties

46

Figure 6 c, d

Time (hour)0 10 20 30 40 50

TV

C (

m3/m

3)

0

1e-4

2e-4

3e-4

4e-4

5e-4

Predicted TVC

Measured TV

Figure 3d

PCB 52

Time (hour)

0 10 20 30 40 50

Cp

(u

g/m

3)

0

20

40

60

80

100

120

140

Model Cp

Measured Cp

Time (hour)

0 10 20 30 40 50

Cd

(u

g/m

3)

0

2

4

6

8

10

12

14

Model Cd

Measured Cd

Particulate PCB

Dissolved PCB

Total Volume Concentration

Total Suspended Solids

47

Non-Spherical Cows

3. Chemical release during resuspension

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Desorption Rates

Engineering Performance Standards for Dredging

Volume 2: Technical Basis and Implementation of the Resuspension

Standard

• Analysis assumes first order desorption kinetics during the first day of resuspension

• Experiments show rapid (nearly instantaneous) release at onset of resuspension

Given the length of time required for PCBs to reach equilibrium for desorption, it is

unlikely that there will be large release of dissolved phase PCBs as a result of dredging

activities.

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Objectives

• What is the initial release of PCBs from quiescent river sediment when it is resuspended (i.e. during high flow or dredging)?

• How does the frequency and duration of resuspension events affect PCB desorption?

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PCB Release from Sediment

• Particulate-bound

• Tracks sediment movement

• Reduced bioavailability(?)

• Engineering controls: solids management

• Dissolved

• Tracks water movement

• Directly bioavailable

• Engineering controls: readsorption (?)

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Release of Dissolved PCBs from Sediment

• Diffusion

• Bioturbation

• Resuspension

• Amount of sediment resuspended

• Residence time of the particles in the water column

• Desorption rate

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Methods: STORM Tanks

• The 1000L tanks produce high levels of bottom

shear stress without generating excessive water

column turbulence

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Dissolved PCB 49

resuspension time [hours]

0 1 2 3 4 5 6

PC

B 4

9 (

ng/L

)

2

4

6

8

10

12

54

Release of Resuspended PCBs into the

Dissolved Phase

• After 1 hour of resuspension

– First Resuspension: 20%

– Second and Third Resuspensions: 15%

• After 6 hours of resuspension

– First Resuspension: 40%

– Second and Third Resuspensions: 25%

55

Observations

• After only one hour, resuspension of 7.4 mg/kg t-PCB Hudson River sediment under gentle conditions yields:

– 34 mg/L suspended solids

– 75 ng/L dissolved t-PCB

– 300 ng/L particulate t-PCB

• 20% of the PCB mass resuspended is desorbed into the truly dissolved phase in one hour

• Higher levels of suspended solids and higher t-PCB levels in sediments will result in larger dissolved concentrations

56

Observations

• A fine fraction of the sediment enriched in t-PCBs is readily resuspended and does not resettle over 12 hours. This material will likely be transported downstream.

• Both desorption kinetics and observed PCB behavior during resettling are consistent with PCB release being dominated by fine-grain particles.

57

Lessons Learned (so far…)

1.“Don’t make me come out of retirement to come back here to fix

the loadings estimates” – R. Thomann

2.“Sediment transport is a side show” – D. DiToro

Keep your eye on the ball

3.“If a simulation won’t finish overnight the model is too complex”

The modeling effort must generate something that fits on a

manager’s laptop

4.Complex systems require continual review during development

Building inspectors

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Final Thoughts

Complex models are too expensive to develop and run too slowly to be useful

Moore’s Law and Silicon Qubits

You can’t calibrate a highly resolved model

Self-learning using real-time observations?

Sediment transport is too hard to model

In situ PSD measurements and highly resolved hydrodynamics

Nobody understand complex models

Pixar studios

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Dr. Joel Baker

Director, UW Puget Sound Institute

University of Washington Tacoma

[email protected]

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Links page

• Dr. Joel Baker ([email protected])

• Center for Urban Water at University of Washington Tacoma:http://www.tacoma.uw.edu/center-urban-waters

• University of Washington Superfund Research Program:http://depts.washington.edu/sfund/

• US EPA Region 10:http://www.epa.gov/aboutepa/region10.html

• National Institute of Environmental Health Institute (NIEHS)-Superfund Research Programhttp://www.niehs.nih.gov/research/supported/srp/

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