ENVIRONMENTAL REACTION KINETICS Lecture #18 REACTION KINETICS David A. Reckhow Introduction ... No...

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CEE 697KENVIRONMENTAL REACTION KINETICS

IntroductionDavid A. Reckhow

CEE 679 Kinetics Lecture #18 1Updated: 13 November 2013

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Lecture #18

Chloramines with Surface Reactions: Pipe walls & degradation in Distribution SystemsPrimary Literature

H2OH2O

NH3

NCl3

NH2ClHOCl

NOH

NHCl2

H2O

H2O

2H2O

1/2 NO3-

2HCl + 1/2 H+

N2H2O + HCl

HOCl + HCl

HCl

2HOCl + 3HCl

NH3

BreakpointReactions

Stable OxidationProducts

FRC

CRC

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Statistics


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Error types Analytical measurements Constant vs. proportional vs in-between

Experimental conditions e.g., pH, temperature

Model error Need for homoskedasticity

Use best transformation (or none at all) Use log for data with errors directly proportional to concentration No transform for data with constant error Use data weighting for other error distributions

Plot residuals to determine heteroskedasticity


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Kinetic Spectrum Analysis


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For mixtures of many closely related compounds A new continuum of rate constants E.g., NOM

Kinetic: Shuman model

Equilibria: Perdue model

Very general, but highly subject to errors

n

i

tkit

ieCC1

0][][

Seasonal Variability & Biodegradation6

Chen & Weisel study

JAWWA, April 1998

Intensive study of Elizabethtown, NJ system 125 MGD conventional plant

4.9 mg/L DOC (raw water average)

pH 7.2


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Elizabethtown, NJ: THMs7


Elizabethtown, NJ: TCAA8


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HAA Degradation9

Biodegradation:

dihaloacetic acids degrade more readily than trihaloacetic acids

On BACMHAA>DHAA>THAA

Wu & Xie, 2005 [JAWWA 97:11:94]

In distribution systems DHAA>MHAA>THAA

Many studies


Degradation in Dist. Systems

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Town Hall; Norwood, MA

Date1/

1/19

99

1/1/

2000

1/1/

2001

1/1/

2002

1/1/

2003

1/1/

2004

1/1/

2005

1/1/

2006

Co

ncen

trat

ion

(g/

L)

0

20

40

60

80

100

120

TTHMHAA5

Pier 1; Norwood, MA

Date1/

1/19

99

1/1/

2000

1/1/

2001

1/1/

2002

1/1/

2003

1/1/

2004

1/1/

2005

1/1/

2006

Co

ncen

trat

ion

(g/

L)

0

20

40

60

80

100

120

TTHMHAA5

Example: Norwood, MADavid A. ReckhowCEE 679 Kinetics Lecture #18

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Degradation of HAAs11

Norwood, MA example

Percentile

0 20 40 60 80 100

HA

A/T

HM

Rat

io ( g

/g)

0.0

0.2

0.4

0.6

0.8

1.0

1.2

Town HallPier 1

No Degradation

Degradation


Why the loss of HAAs?

Homogeneous Chemical Decomposition ? Decarboxylation

What is half-life Is it too slow to be very important?

Dehalogenation Probably too slow for chlorinated HAAs

Reaction with reduced pipe materials? Abiotic reductive dehalogenation not likely either,

especially for DCAA Biodegradation?

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A few recent studies


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Modeling HAA Biodegradation in Biofilters and Distribution Systems Alina S. Grigorescu and Ray Hozalski, University of

Minnesota at Minneapolis

Journal AWWA, July 2010, 102(7)67-80

Background conclusion?

“Thus aerobic biodegradation is believed to be the dominant HAA degradation process in ….…..water distribution systems” Citing: Tung & Xie, 2009; Zhang et al., 2009a; 2009b;

Bayless & Andrews, 2008

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CEE 679 Kinetics Lecture #18

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Objective/hypothesis

Not really stated, but they did end the intro with: “In this work, computer simulations were performed to predict

the fate of three HAAs (MCAA, DCAA, and TCAA) along a distribution system and within a biologically active filter. Sensitivity analyses were performed to investigate the effects of physical parameters (e.g., fluid velocity) and biological parameters (e.g., biodegradation kinetics, biomass density) on HAA removal”

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Transport Model

Loss of HAAs in a pipe One dimensional plug flow

Overall rate is a combination of rate of biodegradation (kra) and mass transfer (kma)

Ux

overallkeCC 0

rama kkoverallk

11

1

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Biodegradation model

Monod model

Simplified for low C

CK

kXC

dt

dC

M

XCkXCK

k

dt

dCr

M

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Biodegradation model II

Biodegradation rate (kra; in day-1) is the pseudo-first order biodegradation rate constant (kr; in L/day/µg-protein) times the biofilm density (X; in µg-protein/cm2) and the specific surface area (a; in m-1)

Lmcmr

Lmcm

rra d

XkXakk

22 1010 4

Where d is the pipe diameter in meters

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Mass Transfer Model I

Mass transfer constant (kma) is the mass transfer velocity (km; m/s) times the specific surface area; and km is related to the Sherwood number

combining

Linton & Sherwood (1950) found the following correlation for flow in pipes (fn(Reynolds and Schmidt numbers)):

2

4

d

ShDa

d

ShDakk ww

mma

33.083.0Re023.0 ScSh

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d

ShDk w

m akk mma Compare to equ7.126 in Clark

Eq 7.164 in Clark

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Mass Transfer Model II

The Schmidt number is the ratio of mass to viscous diffusion timescales, and calculated from the viscosity, the density and the diffusion coefficient:

And the Reynolds number can be calculated from the pipe diameter, velocity, density and viscosity:

ww

w

DSc

w

wdu

Re

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Compare to equ7.82 in Clark

Model Predictions

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Impact of biomass density

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Impact of flow velocity


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Impact of Pipe Diameter

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Combining


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Conclusions

“Overall the model calculations suggest that biodegradation is…..not likely to play a major role in most water distribution systems” “the conditions needed for significant HAA removals in a

distribution system (i.e., total biomass densities > 105

cells/cm2 over long distances of pipe) are unlikely in the US water distribution systems where total chlorine residuals typically are high and thus inhibit the development of biofilmon pipe walls”

But this seems to contradict their introductory conclusion – how to reconcile?

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What could they have concluded?

Variability vs diurnal demand

0

5

10

15

20

25

30

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25

Q/Qavg

u (ft/s)

t (hr)

C (ug/L)

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Objective/hypothesis

Not really stated, but they did end the intro with: “In this work, computer simulations were performed to predict

the fate of three HAAs (MCAA, DCAA, and TCAA) along a distribution system and within a biologically active filter. Sensitivity analyses were performed to investigate the effects of physical parameters (e.g., fluid velocity) and biological parameters (e.g., biodegradation kinetics, biomass density) on HAA removal”

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What could they have said?

To determined if observed HAA loss could be attributed to biodegradation on pipe walls given known physical and microbial characteristics of distribution systems

To estimate spatial and temporal variability of HAA concentrations based on a rational physical model of biodegradation in distribution systems

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What could they have done?

Find some direct evidence for biodegradation of HAAs in distribution systems A product of the enzymatic reaction? Chlorohydroxyacetate?

Evidence of abiotic reactions? Increase in MCAA?

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What else?

Consider mass transfer resistance within biofilm

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What should be done next?

Experimental Work In-situ controlled study of flow velocity vs DCAA loss in

a pipe segment?

Effect of biocide in above segment?

Model Refinement Account for internal mass transfer resistance

Combine with growth model for HAA degraders

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SANCHO Model

B1: biologically fixed bacteria

B2: adsorbed bacteria

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B1

B2

H1

H2

S

CO2

Cl2

MortalityB3

Cl2

Cl2

Mortality

BDOC

Fixed Bacteria

FreeBacteria

Input(H1, H2, B3)

OutputInternal Processes


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Effect of Zn on HAAs


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Effect of Zinc on the Transformation of HAAs in Drinking Water Wei Wang and Lizhong Zhu Journal of Hazardous Materials 174:40-46.

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