cee 690k environmental reaction kinetics · 2013. 12. 1. · cee 697k environmental reaction...

CEE 697K ENVIRONMENTAL REACTION KINETICS

Introduction

CEE697K Lecture #21 1 Updated: 1 December 2013

Print version

Lecture #21 Case Study: NOM-oxidant kinetics Primary Literature as noted

http://www.ecs.umass.edu/cee/reckhow/courses/ERK/slides/ERKl21p.pdf

Kinetic Spectrum Analysis

CEE697K Lecture #21

2

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][][

3

Factors affecting DBP levels

Raw water NOM levels (e.g., TOC) Specific precursor content of the RW NOM NOM removal Disinfection regime

type & dose location in plant contact time & temp pH

Degradation in DS (affects some) CEE697K Lecture #21

NOM Origins

Aquifer

Lake

Upper Soil Horizon

Lower Soil Horizon

Sediment & Gravel in Lake Bed

Litter Layer

Algae

CEE697K Lecture #21

4

Practical Management Question: Which is the more important source?

allochthonous autochthonous

or

CEE697K Lecture #21

5

An Aquatic Humic “Structure”

COOH

O

COOH

COOH

COOH

HOOC

HOOC

HO

OH

COOH

H3CO

OHHydroxy Acid

AromaticDicarboxylicAcid

AromaticAcid

Aliphatic Acid

AliphaticDicarboxylicAcid

Phenolic-OH

HO

From Thurman, 1985

CEE697K Lecture #21

6

7

Chlorination of Resorcinol From Boyce & Hornig, 1983

All structures identified by GC/MS except those in brackets

Chorine + Aromatics

CEE697K Lecture #21

8

Aliphatics: Haloform Reaction

RLS is deprotonation (k1) under many conditions

Many LFERs exist for estimating Kas E.g., Perrin et al., 1982

Then relate k1 to Ka

CH 3 C

O

CH 3

H+

CH 3 C

O

CH 2

-

CH 3 C

O

CH 2

-

[ ]

CH 3 C

O

CH 2Cl

HOCl

CH 3 C

O

CHCl 2

HOCl

CH 3 C

O

CCl 3

CH 3 C

O

CCl 3

OH

CH 3 C

O

OH CH 3 C

O

CHCl 3

-

OH

-

CCl 3-

O -

OH -

H2O

HOCl

H2O

CEE697K Lecture #21

An Aquatic Humic “Structure”

COOH

O

COOH

COOH

COOH

HOOC

HOOC

HO

OH

COOH

H3CO

OHHydroxy Acid

AromaticDicarboxylicAcid

AromaticAcid

Aliphatic Acid

AliphaticDicarboxylicAcid

Phenolic-OH

HO

From Thurman, 1985

CEE697K Lecture #21

9

NOM Fractions: Mass Balance

HA8%HPL-N

25%

HPO-B2%

W-HPO-A4%

HPO-N7%

FA42%HPL-A

9%

HPL-B3%

10

HA0%

FA29%

W-HPO-16%

HPO-B0%

uHPL-A22%

HPL-B5%

HPL-N11%

HPL-A15%

HPO-N2%

Forge Pond Granby, MA

Northeast MA Tap Water

HPL=Hydrophilic HPO=Hydrophobic

A=Acids B=Bases N=Neutrals

W=Weak u=ultra

10 CEE697K Lecture #21

Absorbance of Acid Fractions

11

Wavelength (nm)

200 250 300 350 400 450 500 550 600 650

Sp.

Abs

. (L/

m/m

g-C

)

0.1

1

10

Weak Hydrophobic Acids

Hydrophilic Acids

Humic Acid

Fulvic Acid

Same DOC

254 nm

CEE697K Lecture #21

Formation Potentials of NOM Fractions 12

FP High dose Forces

reaction to endpoint

Neu

trals

TTH

MFP

(µg/

mg-

C)

0

10

20

30

40

50

60

70

Hydrophobic

Base

s

Acid

s

Neu

trals

Base

s

Wea

k Ac

ids

Hum

ic A

cid

Fulv

ic A

cid

Hydrophilic12 CEE697K Lecture #21

Leaching Experiments

White Pine

Red Maple

White Oak

Aged leaves from 3 locations in Wachusett watershed

CEE697K Lecture #21

13

14

Level 2 ecoregions

CEE697K Lecture #21

Leaching Time (days)

0 2 4 6 8

UV 2

54 A

bsor

banc

e (c

m-1

)

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

SU

VA

(L/m

g-C

/m)

0

1

2

3

4

5

6

7

8

9

Maple UV Oak UV Pine UV Maple SUVA Oak SUVA Pine SUVA

Leaching of leaves Dark

Non-sterile conditions

Substantial slow leaching of organics

100254 xDOCUVSUVA

≡

CEE697K Lecture #21

15

Leaching: Sp-THAAFP

Filtered leachate Chlorinated &

analyzed for THAAs Mostly

trichloroacetic acid

THAA yield divided by DOC Specific THAA

(precursors)

Specific THAA Formation for Leaching Study

Dar

k M

aple

#1

Dar

k M

aple

#2

Dar

k O

ak #

1

Dar

k O

ak #

2

Dar

k P

ine

#1

Dar

k P

ine

#2

Ligh

t Map

le

Ligh

t Oak

Ligh

t Pin

e

D.B

ioci

de M

aple

D.B

ioci

de O

ak

Spec

ific

THAA

For

mat

ion

(µg/

mg-

TOC

)

0

20

40

60

80

100

120

140

160

180

CEE697K Lecture #21

16

Lignin Monomers

Aromatic structures from CuO

degradation

Syringyl Vanillyl Cinnamyl

COOH

OH

4-Hydroxy-benzoic acid

COOH

OH

Vanillic acid

CHO

OH

4-Hydroxy-benzaldehyde

COOH

OH

CH3O OCH3

Syringic acid

CHO

OH

Vanillin

CO

OH

CH3

4-Hydroxy-acetophenone

CHO

OH

CH3O OCH3

Syringaldehyde

CO

OH

CH3

OCH3

COOH

OH

COOH

OHOH

CH3O OCH3

Acetovanilione

4-Hydroxy-cinnamic acid

CO

CH3

Acetosyringone

OCH3

Ferulic acid

OCH3

OCH3

CEE697K Lecture #21

17

18

Lignin

From: Perdue & Ritchie, 2004

CEE697K Lecture #21

Other plant products

Pyruvate

Acetate

Water Soluble Acids

Porphyrins

Amino Acids

Nucleic Acids

Misc. N & S compounds

Proteins Shikimic Acid

Carbohydrates Saponifiable

Liquids

Unsaponifiable Liquids

Mevalonic acid

Terpenoids

Steroids

Flavonoids

Aromatic Compounds

From: Robinson, 1991 Activated non-N precursors

Nitrogenous precursors

CEE697K Lecture #21

19

Aromatic Amines

Proposed degradation pathway for 3-amino benzoic acid.

C

NH2

O

OH 1, 2, or 3 chlorinations initially

NH2

Cl

Cl Cl

COOH

NCl2

Cl

NH2

Cl

Cl

COOH

Cl

Cl

OHAnd or chlorination of the amine

OH

NH2

Cl

Cl

COOH

Cl

ClCl2

COOH

Cl

Cl

O

Cl

Cl

COOH

Cl

Cl

Cl

Cl

O

OHOH

OH

Cl

Cl

Cl

Cl

Cl

COOHOHl

Cl

O

COOH

Cl

Cl

O

Cl

Cl

COOH

Cl

Cl

O

Cl

Cl

- NCl2H

Cl

Cl

O

Cl

Cl

OH

O

OH

Cl

Cl

O

Cl

Cl

O

OH

HO

COOH

Cl

Cl

O

Cl

Cl

COOH

Cl

Cl

Cl

Cl

Cl

Cl

COOH

Cl

Cl

O

Cl

Cl

COOH

Cl

Cl

O

Cl

Cl

Cl

Cl

O

Cl

Cl

Cl

HO

HO

HO

Cl

-CO2

O

OH

O

Cl

OH

O

Cl

Cl

ClHOOC

Cl

ClInitial decarboxylation that we would predict for thepara substituted compound is less likly here because the intermediateis not resonance stabilized

CEE697K Lecture #21

20

Aromatic Amines

0.000.010.020.030.040.050.060.070.08

Anthranilic acid 3 Aminobenzoicacid

4 Aminobenzoicacid

M/M

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

M-C

l/M

THMs HAAs HANs TOX Unknown TOX

THMs38%

Unknow nTOX16%

HAA645%

HANs1%

Anthranilic Acid

THMs25%

Unknow nTOX58%

HAA615%HANs

2%3-Aminobenzoic Acid

THMs31%

HAA615%HANs

3%

Unknow nTOX51%

4-Aminobenzoic Acid

6.0 7.7 7.8 Cl2 Demand (M/M)

CEE697K Lecture #21

21

22

THM Precursors (µg/mg-C)

0.01 0.1 1 10 100 1000 10000

TriH

AA

Pre

curs

ors

(µg/

mg-

C)

0.01

0.1

1

10

100

1000AromaticsNucleic BasesSimple AliphaticsAmino AcidsAmino Sugars

Wide range for models

Narrow range for NOM

10-90%ile range for NOM

Compare with Model Compounds

CEE697K Lecture #21

23

Elemental Ratios

From: Perdue & Ritchie, 2004

Van Krevelen Plot

CEE697K Lecture #21

24

Molecular Weight

100 1000 10000 100000

Cha

rge

Den

sity

@ p

H 7

(meq

/g-C

)

-25

-20

-15

-10

-5

0

5

10

Hydrophilic BasesHydrophobic Bases

Neutrals

Hydrophilic Acids

Weak Hydrophobic Acids

Humic AcidFulvic Acid

from: Bezbarua and Reckhow, 1995

Size and Charge Relationships for NOM Fractions

CEE697K Lecture #21

Van Krevelen diagram for the Dismal Swamp DOM, compound classes are represented by the circles overlain on the plot. The distinctive lines in the plot denote the following chemical reactions: (A) methylation/demethylation, or alkyl chain elongation; (B) hydrogenation/dehydrogenation; (C) hydration/condensation; and (D) oxidation/reduction.

25

Sleighter & Hatcher, 2007 [J. Mass Spec. 42:559] CEE697K Lecture #21

Fate & Transport:

Watershed Natural system

Physical processes

Chemical processes

Biological processes

Water Treatment Plant Engineered System

Physical processes

Chemical processes

Biological processes

“Full-scale monitoring

“Lab-scale simulation

Fundamental Testing CEE697K Lecture #21

26

Time (Days)

0 20 40 60 80 100

DO

C F

ti R

o)

0.0

0.2

0.4

0.6

0.8

1.0

1.2

Phase 1 (Co=6.7 mg/L)Phase 2 (Co=5.4 mg/L)Phase 3 (Co=7.9 mg/L)

Biodegradation of leaf leachate ~ 50% biodegradable

Bacteria grow preferentially on NOM

Leaching & Biodegradation

Cumulative Frequency

0.0 0.2 0.4 0.6 0.8 1.0

Spe

cific

TH

MFP

(µg/

mg-

C)

0

20

40

60

80

100

120

Spe

cific

TH

M-S

DS

(µg/

mg-

C)

0

10

20

30

40

50

60

Pre

-exp

onen

tial T

erm

(a)

0.0

0.1

0.2

0.3

0.4

0.5

0.6

Surface WatersGroundwaters

Maple

Oak Pine

CEE697K Lecture #21

28

29

Transport & Soil Properties

Case study: TOC & soil properties Parallel watersheds in Australia (Cotsaris et al., 1994) Clearwater Creek, high clay content: 2.5 mg/L TOC Redwater Creek, sandy soil: 31.7 mg/L TOC

Presumed Attenuated of TOC by adsorption to clay soils

Impacts on specific NOM components & precursors ??

CEE697K Lecture #21

Effect of Bank Filtration on Precursors

DOC (mg/L)

0 1 2 3 4 5

THM

FP/D

OC

(µg/

mg)

0

20

40

60

80

100

Ohio RiverWabash RiverMissouri River

Subsurface processes

River Bank Filtration Weiss et al., 2001 AWWA ACE

Groundwater recharge Aiken & others

Ratio climbs over very short distances and then declines

CEE697K Lecture #21

30

The Future: Higher MW DBPs

NOM research ESI with Ultra High-

Resolution Fourier Transform Ion Cyclotron Resonance Mass Spectrometry

Benefits Unambiguous molecular

formulae

CEE697K Lecture #21

31

32 m/z

900800700600500400300

Abu

ndan

ce

121110

987654321

Raw Water - Winnipeg

0.00E+00

5.00E+01

1.00E+02

1.50E+02

2.00E+02

2.50E+02

3.00E+02

3.50E+02

4.00E+02

150 250 350 450 550 650

m/z

Inte

nsity

-ve ion + ve ion

ESI-TOF MS

ESI-FTICR MS

Same: comparison side-by-side CEE697K Lecture #21

33

m/z425420415410405400395390

Abu

ndan

ce

7

6

5

4

3

2

1

Chlorinated Water + Br Winnipeg

m/z409.436409.354409.272409.19409.108409.027408.945408.863

Abu

ndan

ce

7

6

5

4

3

2

1

CEE697K Lecture #21

Ultra-high resolution MS 34

Area of predicted fulvic acid molecules in a C- vs molecular mass diagram for the mass range m/z 310-370 (marked by the lines) and fulvic acid molecules detected by SEC-FTICR-MS in the river isolate (dots (island no. 24) and triangles (island no. 25)).

Reemtsma et al., 2006 [ES&T: 40:19:5839]

Zone of low solubility

CEE697K Lecture #21

The dilemma of NOM

CEE697K Lecture #21

35

How to model reaction kinetics in such a complex mixture? Kinetic spectrum? Fictive components? Fully empirical?

Lee & Von Gunten, 2010

CEE697K Lecture #21

36

Comparative study of 5 oxidants

Looked at rates of removal for micropollutants for each

Compared to bulk oxidant demand

Lee, Y. and U. von Gunten (2010). "Oxidative transformation of micropollutants during municipal wastewater treatment: Comparison of kinetic aspects of selective (chlorine, chlorine dioxide, ferrate(VI), and ozone) and non-selective oxidants (hydroxyl radical)." Water Research 44(2): 555-566.

http://www.ecs.umass.edu/eve/secure/ferrate/Lee von Gunten 2010 micropollutants.pdfhttp://www.ecs.umass.edu/eve/secure/ferrate/Lee von Gunten 2010 micropollutants.pdfhttp://www.ecs.umass.edu/eve/secure/ferrate/Lee von Gunten 2010 micropollutants.pdf

Rate

con

stan

ts v

s pH

CEE697K Lecture #21

37

ss

Fig. 1. pH dependent second-order rate constants (k) for the reaction of the oxidants, chlorine (HOCl), chlorine dioxide (ClO2), ferrateVI (HFeO4−), hydroxyl radicals (HO), and ozone (O3)

Lee, Y. and U. von Gunten (2010). Water Research 44(2): 555-566.

http://www.ecs.umass.edu/eve/secure/ferrate/Lee von Gunten 2010 micropollutants.pdf

CEE697K Lecture #21

38

Fours species

Fig. 2. Consumption kinetics of the selective oxidants, (a) ozone, (b) ferrateVI, (c) chlorine, and (d) chlorine dioxide, in a secondary wastewater effluent (RDWW) at pH 8. Symbols represent measured data and lines connect each data point to show the trend.

Oxi

dant

Res

idua

ls

Lee, Y. and U. von Gunten (2010). Water Research 44(2): 555-566.

http://www.ecs.umass.edu/eve/secure/ferrate/Lee von Gunten 2010 micropollutants.pdfhttp://www.ecs.umass.edu/eve/secure/ferrate/Lee von Gunten 2010 micropollutants.pdfhttp://www.ecs.umass.edu/eve/secure/ferrate/Lee von Gunten 2010 micropollutants.pdfhttp://www.ecs.umass.edu/eve/secure/ferrate/Lee von Gunten 2010 micropollutants.pdf

CEE697K Lecture #21

39

gd

Fig. 3. Logarithm of the residual concentrations (log(c/c0)) of selected micropollutants as a function of oxidant doses in a secondary wastewater effluent (RDWW) at pH 8: (a) EE2, (b) SMX, (c) CBZ, (d) ATL, and (e) IBP. Symbols represent measured data and lines connect each data point to show the trend. The lines for hydroxyl radicals represent the linear regression of data. For the selective oxidants, the reaction time of 1 h was given to simulate realistic treatment conditions.

Micropollutant Destruction Lee, Y. and U. von Gunten (2010). Water Research 44(2): 555-566.

http://www.ecs.umass.edu/eve/secure/ferrate/Lee von Gunten 2010 micropollutants.pdf

CEE697K Lecture #21

40

cs

Fig. 4. Effect of (a) ammonia (NH4+) and (b) nitrite (NO2−) on the transformations of EE2 during treatment of a secondary wastewater effluent (RDWW) by different oxidants at pH 8. Preliminary experiments were conducted to determine the oxidant dose for each oxidant to achieve a 80% transformation of EE2 in RDWW without additionally spiked ammonia and nitrite. They were 20 μM for chlorine, 3 μM for chlorine dioxide, 8 μM for ozone, 8 μM for ferrateVI, and 37 μM for hydroxyl radicals. Symbols represent measured data and lines connect each data point to show the trend. Lee, Y. and U. von Gunten (2010). Water Research 44(2): 555-566.

http://www.ecs.umass.edu/eve/secure/ferrate/Lee von Gunten 2010 micropollutants.pdfhttp://www.ecs.umass.edu/eve/secure/ferrate/Lee von Gunten 2010 micropollutants.pdfhttp://www.ecs.umass.edu/eve/secure/ferrate/Lee von Gunten 2010 micropollutants.pdfhttp://www.ecs.umass.edu/eve/secure/ferrate/Lee von Gunten 2010 micropollutants.pdf

Ferrate reaction with surface waters

25 µM ferrate dose, pH 6.2

Time (min)

0 5 10 15 20 25 30

Ferra

te C

once

ntra

tion

( M

)

0

5

10

15

20

25

30

Ferra

te C

once

ntra

tion

(mg/

L as

Fe)

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6pH 6.2 Buffered BlankHouston TX pH 6.2Palmer MA pH 6.2Readsboro VT pH 6.2

From: Jiang et al., 2013

CEE697K Lecture #21

41

Low Dose, High pH

Time (min)

0 5 10 15 20 25 30

Ferra

te C

once

ntra

tion

(M

)

0

10

20

30

40

Ferra

te C

once

ntra

tion

(mg/

L as

Fe)

0.0

0.5

1.0

1.5

2.0pH 7.5 Buffered BlankAmherst MA pH ~7.5Houston TX pH 7.5Palmer MA pH 7.5Readsboro MA pH 7.5

25 µM, pH 7.5


CEE697K Lecture #21

42

High Dose, Low pH

Time (min)

0 5 10 15 20 25 30

Ferra

te C

once

ntra

tion

(M

)

0

10

20

30

40

50

60

Ferra

te C

once

ntra

tion

(mg/

L as

Fe)

0

1

2

3pH 6.2 Buffered BlankHouston TX pH 6.2Palmer MA pH 6.2Readsboro VT pH 6.2

50 µM, pH 6.2


CEE697K Lecture #21

43

High Dose, High pH

Time (min)

0 5 10 15 20 25 30

Ferra

te C

once

ntra

tion

(M

)

0

10

20

30

40

50

60

Ferra

te C

once

ntra

tion

(mg/

L as

Fe)

0

1

2

3pH 7.5 Buffered BlankAmherst MA pH ~7.5Houston TX pH 7.5Palmer MA pH 7.5Readsboro MA pH 7.5

50 µM, pH 7.5


CEE697K Lecture #21

44

Houston Data Isolated

CEE697K Lecture #21

45

More data improves accuracy

Time (min)

0 5 10 15 20 25 30

Ferr

ate

Con

cent

ratio

n (

M)

0

10

20

30

40

50

60

Ferr

ate

Con

cent

ratio

n (m

g/L

as F

e)

0

1

2

3Houston TX pH 7.5

Integrate curve to get CT vs time

CEE697K Lecture #21

46

Simple “rectangle” method

Time (min)

0 5 10 15 20 25 30

Ferr

ate

Con

cent

ratio

n (

M)

0

10

20

30

40

50

60

Ferr

ate

Con

cent

ratio

n (m

g/L

as F

e)

0

1

2

3Houston TX pH 7.5

Light scattering background (not ferrate)

Model for pollutant oxidation

CEE697K Lecture #21

47

Simple 2nd order kinetics Pollutant (P) reacts with an oxidant (O)

Integrate but keep [O] time variable

And you end up with an expression in terms of CT

𝑑𝑑𝑑𝑑

= −𝑘 𝑑 𝑂 𝑑𝑑𝑑

= −𝑘 𝑂 dt

𝑙𝑙 𝑑𝑡 − 𝑙𝑙 𝑑0 = −𝑘� 𝑂 𝑑𝑑𝑡

0

𝑑𝑡 = 𝑑0𝑒−𝑘 ∫ 𝑂 𝑑𝑡𝑡0 𝑑𝑡 = 𝑑0𝑒−𝑘 𝐶𝐶

𝑙𝑙 𝑑 = −𝑘� 𝑂 𝑑𝑑𝑡

0

Po

Pt

pH

6.0 6.5 7.0 7.5 8.0 8.5

Frac

tion

Rem

aini

ng

0.0

0.2

0.4

0.6

0.8

1.0

ethynlestradiol sulfamethoxazole bromide Sulfide Nitrite Phenol Analine

Kinetic Analysis, high dose

50 µM dose, Houston Water

Alkyl alcohols

Alkyl amines

sulfides CEE697K Lecture #21

48

Kinetic Analysis, low dose

pH

6.0 6.5 7.0 7.5 8.0 8.5

Frac

tion

Rem

aini

ng

0.0

0.2

0.4

0.6

0.8

1.0

ethynlestradiol sulfamethoxazole bromide Sulfide Nitrite Phenol Analine

25 µM dose, Houston Water

Alkyl alcohols

Alkyl amines

sulfides CEE697K Lecture #21

49

The “problems” with ozone

CEE697K Lecture #21

50

Many important secondary oxidants, especially OH radical

Ozone decomposition in real waters does not match predictions

Mechanistic model is “off”

CEE697K Lecture #21

51

Initiation reaction rate constant must be “adjusted” to match actual data

Elovitz, M. S. and U. Von Gunten (1999). "Hydroxyl Radical Ozone Ratios During Ozonation Processes. I-the R-Ct Concept." Ozone-Science & Engineering 21(3): 239-260.

A simpler view: Direct & Indirect Pathways

52

O3

·OH

High pH UV light H2O2

H2O, O2

H2O, O2

Direct Reaction

Indirect Reaction

NOM VOCs Fe/Mn

Oxidized Products

Oxidized Products

Use of peroxide with ozone is an “advanced oxidation process” (AOP)

Bicarbonate

Classic “ozone demand” D

ecom

posi

tion

Natural waters cause ozone decomposition to varying degrees without any added initiators

CEE697K Lecture #21

Ozone Loss: focus on NOM

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

0.45

0 1 2 3 4 5

Specific UV Absorbance

5-m

in o

zone

con

sum

ptio

n (m

g/m

g-C

)

53

» Ozone loss in first 5

minutes

fulvic acids data from Legube

et al., 1989

Organic Demand in colored waters – Empirical stoichiometric approach

Direct reaction with NOM, Doesn’t really account for “decomposition”

CEE697K Lecture #21

Ozone loss: focus on decomposition

Incorporating Inorganic Reactions: Semi-empirical kinetic approach First-order decay in solution

Specific ozone loss rate (w) in s -1 Yurteri & Gurol (1988)

Orta de Velasquez et al. (1994)

tinitialOO eCC

ω−= ,33

54

Log pH TOC Alkω = − + + −356 0 66 0 61 0 42. . . log . log

Log pH Abs TOC Alkω = − + + + −393 0 24 0 75 108 019254. . . log . log . log

Takes inorganic matrix into account, and allows for variable contact times, but treats all DOC as the same

][][ 33 OdtOd ω−=

CEE697K Lecture #21

Ozonation of trace organics: Direct Rcn

CEE697K Lecture #21

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Shut down OH radical formation to isolate molecular ozone (O3) rate.

Oxidation of nitroimidazoles during ozonation. [Nitroimidazole]0 = 10 mg/L., T = 298 K.

pH = 2; [t-BuOH] = 0.1 M

(♢), MNZ; (□), DMZ; (▵), TNZ; (○), RNZ.

Sanchez-Polo, M., J. Rivera-Utrilla, et al. (2008). "Removal of pharmaceutical compounds, nitroimidazoles, from waters by using the ozone/carbon system." Water Research 42(15): 4163-4171.

Indirect Rcn: But we can’t measure OH•

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If you can’t measure them directly maybe you can do it indirectly Use small amounts of a “probe compound” Sacrificial reactant that is easy to measure and selective

Benzene (Hoigne & Bader, 1979) by GC p-chlorobenzoic acid is now more common Easy to measure by HPLC 5x10-9 M-1s-1 with OH radical, but ≤0.15 M-1s-1 with O3

Hoigne, J. and H. Bader (1979). "Ozonation of Water - Oxidation-Competition Values of Different Types of Waters Used in Switzerland." Ozone-Science & Engineering 1(4): 357-372.

Competitive kinetics with probe

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Pollutant (P) and probe compound (pCBA)

𝑑𝑡 = 𝑑0𝑒−𝑘𝑃 𝐶𝐶 𝑝𝑝𝑝𝑝𝑡 = 𝑝𝑝𝑝𝑝0𝑒−𝑘𝑝𝑝𝑝𝑝 𝐶𝐶

𝑙𝑙𝑑𝑡𝑑0

= −𝑘𝑑 𝑝𝐶 𝑙𝑙

𝑝𝑝𝑝𝑝𝑡𝑝𝑝𝑝𝑝0

= −𝑘𝑝𝐶𝑝𝑝 𝑝𝐶

𝑝𝐶 = −1

𝑘𝑝𝐶𝑝𝑝𝑙𝑙



=𝑘𝑑



If you know kp and want to estimate oxidation of P:

If you want to determine kp from measurements of P:

𝑘𝑑 = 𝑘𝑝𝐶𝑝𝑝𝑙𝑙 𝑑𝑡𝑑0

𝑙𝑙 𝑝𝑝𝑝𝑝𝑡𝑝𝑝𝑝𝑝0

�

Determining OH• rate constants

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Fig. 3. Determination of OH radical reaction constant. pH = 9; T = 298 K; [nitroimidazole]0 = 7 × 10−5 M;

[pCBA]0 = 7.25 × 10−5 M. (♢), MNZ; (□), DMZ; (▵), TNZ; (○), RNZ.

Sanchez-Polo, M., J. Rivera-Utrilla, et al. (2008). "Removal of pharmaceutical compounds, nitroimidazoles, from waters by using the ozone/carbon system." Water Research 42(15): 4163-4171.

𝑘𝑑 = 𝑘𝑝𝐶𝑝𝑝𝑙𝑙 𝑑𝑡𝑑0

𝑙𝑙 𝑝𝑝𝑝𝑝𝑡𝑝𝑝𝑝𝑝0

�

Can we simplify a bit?

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Oxidation competition values Based on relatively linear pseudo-1st order loss rate for

micropollutants (i.e., ln(P/Po) vs t gives a straight line) Expected if aggregate OH• reacting substances do not

undergo appreciable depletion during ozonation

Ozone decomposition produces a uniform yield of OH• over time and ozone dose (typically ~0.5M/M)


Oxidation-competition method

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First assume a near constant OH• yield from ozone decomposition so that monitoring loss of ozone provides an estimate of the OH reactions taking place

Then all OH• produced either reacts with the target pollutant (M) or the background matrix (Si) and the two are in direct competition

And the fraction reacting with M is: 𝑓 = 𝑘𝑀 𝑀∑𝑘𝑖 𝑆𝑖

From: Hoigne & Bader, 1979

Using M as a probe

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Now:

Where the oxidation-competition value is defined as:

And as we’ve shown previously

We can now use Ω to estimate loss of “P” by simply measuring ∆O3

−𝑑 𝑀𝑑𝑑

= 𝜂𝑑 Δ𝑂3𝑑𝑑

𝑘𝑀 𝑀∑𝑘𝑖 𝑆𝑖

=𝑑 Δ𝑂3𝑑𝑑 Ω𝑀

𝑓 =𝑘𝑀 𝑀∑𝑘𝑖 𝑆𝑖

Ω𝑀 =∑𝑘𝑖 𝑆𝑖𝜂𝑘𝑀

=Δ𝑂3

𝑙𝑙 𝑀𝑡 𝑀0�


=𝑘𝑑




=𝑘𝑑𝑘𝑀

𝑙𝑙𝑀𝑡𝑀0

𝑙𝑙 𝑀𝑡 𝑀0� =Δ𝑂3Ω𝑀


=𝑘𝑑𝑘𝑀

Δ𝑂3Ω𝑀

Production rate of OH radicals

Fraction of OH that reacts with M

And rearranging:

This is what we can actually measure

or

Field Values

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Values of Ω have been measured on many natural waters


Some complications

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Yet they noted an initial reaction that did not conform to their simple model

RCT concept

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Recall from the discussion on simple consecutive reactions:

The ratio of the concentrations of intermediate to the

reactant approaches a constant, when kii>>ki

Now consider A to be ozone and B to be OH radical, and

we get:

ii

i

iii

i

kk

kkk

AB

≈−

→][][

CBA iii kk →→

𝑅𝐶𝐶 ≝𝑂𝑂𝑂3

= 𝑐𝑐𝑙𝑐𝑑𝑐𝑙𝑑

RCT concept

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Elovitz & Von Gunten, 1999 Use the same competitive OH reaction approach with a

probe compound as Hoigne & Bader


However, instead of measuring ∆O3, they chose to record the full ozone CT

RCT concept II

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The simple 2nd order model is:

Rearranging and integrating we get:

Which gives the final form used in experimental evaluation:

𝑑 𝑝𝑝𝑝𝑝𝑑𝑑

= −𝑘𝑝𝐶𝑝𝑝 𝑝𝑝𝑝𝑝 𝑂𝑂



𝑑 𝑝𝑝𝑝𝑝𝑑𝑑

= −𝑘𝑝𝐶𝑝𝑝 𝑝𝑝𝑝𝑝 𝑅𝐶𝐶 𝑂3

𝑑 𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝

= −𝑘𝑝𝐶𝑝𝑝𝑅𝐶𝐶 𝑂3 𝑑𝑑 𝑙𝑙𝑝𝑝𝑝𝑝𝑡𝑝𝑝𝑝𝑝0

= −𝑘𝑝𝐶𝑝𝑝𝑅𝐶𝐶 � 𝑂3 𝑑𝑑𝑡

0

𝑅𝐶𝐶 =𝑙𝑙 𝑝𝑝𝑝𝑝𝑡𝑝𝑝𝑝𝑝0

−𝑘𝑝𝐶𝑝𝑝 ∫ 𝑂3 𝑑𝑑𝑡0

�

RCT concept III

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Simple model system




�

RCT concept IV

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Lake Zurich water Apparent 2-stage

kinetics 1st stage may or may not

be linear




�

Incorporating both pathways

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The expanded 2nd order model is:

Rearranging and integrating we get:

or:

𝑑 𝑑𝑑𝑑

= −𝑘𝑂𝑂 𝑑 𝑂𝑂 + 𝑘𝑂3 𝑑 𝑂3



𝑑 𝑑𝑑𝑑

= −𝑘𝑂𝑂 𝑑 𝑅𝐶𝐶 𝑂3 + 𝑘𝑂3 𝑑 𝑂3

𝑑 𝑑𝑑

= − 𝑘𝑂𝑂𝑅𝐶𝐶 + 𝑘𝑂3 𝑂3 𝑑𝑑 𝑙𝑙𝑑𝑡𝑑0

= − 𝑘𝑂𝑂𝑅𝐶𝐶 + 𝑘𝑂3 � 𝑂3 𝑑𝑑𝑡

0

𝑑𝑡 = 𝑑0 𝑒− 𝑘𝑂𝑂𝑅𝑝𝐶+𝑘𝑂𝑂 ∫ 𝑂𝑂 𝑑𝑡𝑡0

both pathways II

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Porrentruy Water


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both pathways III

Elovitz, M. S. and U. Von Gunten (1999).

Natural waters

𝑓𝑂𝑂 =𝑘𝑂𝑂𝑅𝐶𝐶

𝑘𝑂𝑂𝑅𝐶𝐶 + 𝑘𝑂3

Role of Temperature

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Increase in RCT

Elovitz, M. S., U. Von Gunten, et al. (2000). "Hydroxyl Radical/Ozone Ratios During Ozonation Processes. II. The Effect of Temperature, pH, Alkalinity, and DOM Properties." Ozone-Science & Engineering 22(2): 123-150.

Role of pH

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73


Increase in RCT

Role of Bicarbonate

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74


Decrease in RCT

Similar approach used for AOPs

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Advanced oxidation processes UV with H2O2

Rosenfeldt, E. J. and K. G. Linden (2007). "The R-OH,R-UV concept to characterize and the model UV/H2O2 process in natural waters." Environmental Science & Technology 41(7): 2548-2553.

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76

To next lecture

http://www.ecs.umass.edu/cee/reckhow/courses/ERK/slides/ERKl22.pdf

CEE 697K�Environmental Reaction KineticsKinetic Spectrum AnalysisFactors affecting DBP levelsNOM OriginsPractical Management Question:�Which is the more important source?An Aquatic Humic “Structure”Chorine + AromaticsAliphatics: Haloform ReactionAn Aquatic Humic “Structure”NOM Fractions:� Mass BalanceAbsorbance�of Acid�FractionsFormation Potentials of NOM FractionsLeaching ExperimentsSlide Number 14Leaching of leavesLeaching: Sp-THAAFPLignin MonomersLigninOther plant productsAromatic AminesAromatic AminesCompare with Model CompoundsElemental RatiosSlide Number 24Slide Number 25Fate & Transport:Biodegradation of leaf leachateLeaching & BiodegradationTransport & Soil PropertiesSubsurface processesThe Future: Higher MW DBPsSlide Number 32Slide Number 33Ultra-high resolution MSThe dilemma of NOMLee & Von Gunten, 2010Rate constants vs pHOxidant ResidualsMicropollutant DestructionSlide Number 40Ferrate reaction with surface watersLow Dose, High pHHigh Dose, Low pHHigh Dose, High pHHouston Data IsolatedIntegrate curve to get CT vs timeModel for pollutant oxidationKinetic Analysis, high doseKinetic Analysis, low doseThe “problems” with ozoneMechanistic model is “off”A simpler view: Direct & Indirect PathwaysOzone Loss: focus on NOMOzone loss: focus on decompositionOzonation of trace organics: Direct RcnIndirect Rcn: But we can’t measure OHCompetitive kinetics with probeDetermining OH rate constantsCan we simplify a bit?Oxidation-competition methodUsing M as a probeField ValuesSome complicationsRCT conceptRCT conceptRCT concept IIRCT concept IIIRCT concept IVIncorporating both pathwaysboth pathways IIboth pathways IIIRole of TemperatureRole of pHRole of BicarbonateSimilar approach used for AOPsSlide Number 76

cee 690k environmental reaction kinetics · 2013. 12. 1. · cee 697k environmental reaction...

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