CEE 697K ENVIRONMENTAL REACTION KINETICS Lecture #18 Chloramines - - PowerPoint PPT Presentation

CEE 697K

ENVIRONMENTAL REACTION KINETICS

Introduction

David A. Reckhow

CEE 679 Kinetics Lecture #18 1

Updated: 13 November 2013

Print version

Lecture #18

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

H2O H2O

NH3

NCl3 NH2Cl HOCl NOH NHCl2

H2O H2O 2H2O

1/2 NO3

• 2HCl + 1/2 H+

N2

H2O + HCl HOCl + HCl HCl 2HOCl + 3HCl

NH3

Breakpoint Reactions

Stable Oxidation Products 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 t k i t

i

e C C

1

] [ ] [

Seasonal Variability & Biodegradation

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 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: THMs

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Elizabethtown, NJ: TCAA

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HAA Degradation

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 Biodegradation:

dihaloacetic acids degrade more readily than

trihaloacetic acids

On BAC

 MHAA>DHAA>THAA  Wu & Xie, 2005 [JAWWA 97:11:94]

In distribution systems

 DHAA>MHAA>THAA  Many studies

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Degradation in Dist. Systems

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Town Hall; Norwood, MA

Date

1/1/1999 1/1/2000 1/1/2001 1/1/2002 1/1/2003 1/1/2004 1/1/2005 1/1/2006

Concentration (µg/L)

20 40 60 80 100 120 TTHM HAA5

Pier 1; Norwood, MA

Date

1/1/1999 1/1/2000 1/1/2001 1/1/2002 1/1/2003 1/1/2004 1/1/2005 1/1/2006

Concentration (µg/L)

20 40 60 80 100 120 TTHM HAA5

Example: Norwood, MA

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Degradation of HAAs

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 Norwood, MA example

Percentile

20 40 60 80 100

HAA/THM Ratio (µg/µg)

0.0 0.2 0.4 0.6 0.8 1.0 1.2 Town Hall Pier 1 No Degradation Degradation

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CEE 679 Kinetics Lecture #18

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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C C O O Cl Cl Cl

CHCl3 CO2 slow CHCl3 fast

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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

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

• f physical parameters (e.g., fluid velocity) and biological

parameters (e.g., biodegradation kinetics, biomass density) on HAA removal”

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CEE 679 Kinetics Lecture #18

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)

( )

U x

• verall

k

e C C

−

=

ra ma

k k

• verall

k

1 1

1 + =

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CEE 679 Kinetics Lecture #18

Biodegradation model

 Monod model  Simplified for low C

C K kXC dt dC

M +

− = XC k XC K k dt dC

r 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)

( ) ( )

L m cm r L m cm r ra

d X k Xa k k

2 2

10 10

4 = =

Where d is the pipe diameter in meters

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CEE 679 Kinetics Lecture #18

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CEE 679 Kinetics Lecture #18

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 ShD a d ShD a k k

w w m ma

= = =

33 . 83 .

Re 023 . Sc Sh =

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CEE 679 Kinetics Lecture #18

d ShD k

w m =

a k k

m ma =

Compare to equ 7.126 in Clark Eq 7.164 in Clark

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:

w w w

D Sc ρ µ =

w w

du µ ρ = Re

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Compare to equ 7.82 in Clark

Model Predictions

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Impact of biomass density

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CEE 679 Kinetics Lecture #18

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 biofilm

• n pipe walls”

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

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CEE 679 Kinetics Lecture #18

CEE 679 Kinetics Lecture #18

What could they have concluded?

 Variability vs diurnal demand

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) David A. Reckhow

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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

• f physical parameters (e.g., fluid velocity) and biological

parameters (e.g., biodegradation kinetics, biomass density) on HAA removal”

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CEE 679 Kinetics Lecture #18

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

• f biodegradation in distribution systems

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CEE 679 Kinetics Lecture #18

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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CEE 679 Kinetics Lecture #18

What else?

 Consider mass

transfer resistance within biofilm

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CEE 679 Kinetics Lecture #18

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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CEE 679 Kinetics Lecture #18

SANCHO Model

 B1: biologically fixed bacteria  B2: adsorbed bacteria 34

B1 B2 H1

H2

S CO2

Cl2 Mortality

B3

Cl2 Cl2

Mortality

BDOC

Fixed Bacteria

Free Bacteria

Input (H1, H2, B3) Output Internal 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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 To next lecture