CEE 697K ENVIRONMENTAL REACTION KINETICS Lecture #21 Case Study: - - PDF document

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CEE 697K ENVIRONMENTAL REACTION KINETICS Lecture #21 Case Study: - - PDF document

12/1/2013 Updated: 1 December 2013 CEE697K Lecture #21 1 Print version CEE 697K ENVIRONMENTAL REACTION KINETICS Lecture #21 Case Study: NOM-oxidant kinetics Primary Literature as noted Introduction Kinetic Spectrum Analysis 2 For


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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

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 t k i t

i

e C C

1

] [ ] [

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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

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Practical Management Question: Which is the more important source?

 allochthonous  autochthonous

  • r

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An Aquatic Humic “Structure”

COOH O COOH COOH COOH HOOC HOOC HO OH COOH H3CO OH Hydroxy Acid Aromatic Dicarboxylic Acid Aromatic Acid Aliphatic Acid Aliphatic Dicarboxylic Acid Phenolic-OH HO

From Thurman, 1985

CEE697K Lecture #21

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7  Chlorination of Resorcinol  From Boyce & Hornig, 1983  All structures identified by GC/MS

except those in brackets

Chorine + Aromatics

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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

CH3 C O CH3 H+ CH3 C O CH2

  • CH3 C

O CH2

  • [

]

CH3 C O CH2Cl

HOCl

CH3 C O CHCl2

HOCl

CH3 C O CCl 3 CH3 C O CCl3 OH CH3 C O OH CH3 C O CHCl3

  • OH
  • CCl 3
  • O -

OH- H2O HOCl H2O

CEE697K Lecture #21

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An Aquatic Humic “Structure”

COOH O COOH COOH COOH HOOC HOOC HO OH COOH H3CO OH Hydroxy Acid Aromatic Dicarboxylic Acid Aromatic Acid Aliphatic Acid Aliphatic Dicarboxylic Acid Phenolic-OH HO

From Thurman, 1985

CEE697K Lecture #21

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NOM Fractions: Mass Balance

HA 8% HPL-N 25% HPO-B 2% W-HPO-A 4% HPO-N 7% FA 42% HPL-A 9% HPL-B 3%

10

HA 0% FA 29% W-HPO- 16% HPO-B 0% uHPL-A 22% HPL-B 5% HPL-N 11% HPL-A 15% HPO-N 2%

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

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Absorbance

  • f Acid

Fractions

11

Wavelength (nm)

200 250 300 350 400 450 500 550 600 650

  • Sp. Abs. (L/m/mg-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

Neutrals

TTHMFP (µg/mg-C)

10 20 30 40 50 60 70

Hydrophobic

Bases Acids Neutrals Bases Weak Acids Humic Acid Fulvic Acid

Hydrophilic

12 CEE697K Lecture #21

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Leaching Experiments

White Pine Red Maple White Oak

Aged leaves from 3 locations in Wachusett watershed

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 Level 2

ecoregions

CEE697K Lecture #21

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Leaching Time (days)

2 4 6 8

UV254 Absorbance (cm-1)

0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 SUVA (L/mg-C/m) 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

  • rganics

100

254 x

DOC UV SUVA       

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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

Dark Maple #1 Dark Maple #2 Dark Oak #1 Dark Oak #2 Dark Pine #1 Dark Pine #2 Light Maple Light Oak Light Pine D.Biocide Maple D.Biocide Oak

Specific THAA Formation (g/mg-TOC)

20 40 60 80 100 120 140 160 180

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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 OH OH CH3O OCH3 Acetovanilione 4-Hydroxy- cinnamic acid CO CH3 Acetosyringone OCH3 Ferulic acid OCH3 OCH3

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Lignin

From: Perdue & Ritchie, 2004 CEE697K Lecture #21

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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

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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 OH

And or chlorination of the amine

OH NH2 Cl Cl COOH Cl Cl Cl2 COOH Cl Cl O Cl Cl COOH Cl Cl Cl Cl O OH OH OH Cl Cl Cl Cl Cl COOH OHl 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 Cl HOOC Cl Cl

Initial decarboxylation that we would predict for the para substituted compound is less likly here because the intermediate is not resonance stabilized

CEE697K Lecture #21

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Aromatic Amines

0.00 0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08 Anthranilic acid 3 Aminobenzoic acid 4 Aminobenzoic acid M/M 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 M-Cl/M THMs HAAs HANs TOX Unknown TOX

THMs 38% Unknow n TOX 16% HAA6 45% HANs 1%

Anthranilic Acid

THMs 25% Unknow n TOX 58% HAA6 15% HANs 2%

3-Aminobenzoic Acid

THMs 31% HAA6 15% HANs 3% Unknow n TOX 51%

4-Aminobenzoic Acid

6.0 7.7 7.8

Cl2 Demand (M/ M)

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THM Precursors (g/mg-C)

0.01 0.1 1 10 100 1000 10000

TriHAA Precursors (g/mg-C)

0.01 0.1 1 10 100 1000 Aromatics Nucleic Bases Simple Aliphatics Amino Acids Amino Sugars

 Wide

range for models

 Narrow

range for NOM

10-90%ile range for NOM

Compare with Model Compounds

CEE697K Lecture #21

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23

Elemental Ratios

From: Perdue & Ritchie, 2004

 Van Krevelen Plot

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Molecular Weight

100 1000 10000 100000

Charge Density @ pH 7 (meq/g-C)

  • 25
  • 20
  • 15
  • 10
  • 5

5 10

Hydrophilic Bases Hydrophobic Bases Neutrals Hydrophilic Acids Weak Hydrophobic Acids Humic Acid Fulvic Acid

from: Bezbarua and Reckhow, 1995

Size and Charge Relationships for NOM Fractions

CEE697K Lecture #21

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Van Krevelen diagram for the Dismal Swamp DOM, compound classes are represented by the circles

  • verlain 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

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Time (Days)

20 40 60 80 100

DOC F ti R

  • )

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 <3000 amu

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Leaching & Biodegradation

Cumulative Frequency

0.0 0.2 0.4 0.6 0.8 1.0

Specific THMFP (g/mg-C)

20 40 60 80 100 120

Specific THM-SDS (g/mg-C)

10 20 30 40 50 60

Pre-exponential Term (a)

0.0 0.1 0.2 0.3 0.4 0.5 0.6 Surface Waters Groundwaters

Maple Oak Pine

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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)

1 2 3 4 5

THMFP/DOC (g/mg)

20 40 60 80 100 Ohio River Wabash River Missouri 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

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The Future: Higher MW DBPs

 NOM research  ESI with Ultra High-

Resolution Fourier Transform Ion Cyclotron Resonance Mass Spectrometry

 Benefits  Unambiguous molecular

formulae

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32 m/z

900 800 700 600 500 400 300

Abundance

12 11 10 9 8 7 6 5 4 3 2 1

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 Intensity

  • ve ion

+ ve ion

ESI -TOF MS ESI -FTI CR MS

Same: comparison side-by-side

CEE697K Lecture #21

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33 m/z

425 420 415 410 405 400 395 390

Abundance

7 6 5 4 3 2 1

Chlorinated Water + Br Winnipeg

m/z

409.436 409.354 409.272 409.19 409.108 409.027 408.945 408.863

Abundance

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

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The dilemma of NOM

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 How to model reaction kinetics in such a complex

mixture?

 Kinetic spectrum?  Fictive components?  Fully empirical?

Lee & Von Gunten, 2010

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 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.

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Rate constants vs pH

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 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. 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.

Oxidant Residuals

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

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CEE697K Lecture #21

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 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. 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

  • xidant 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.

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Ferrate reaction with surface waters

 25 µM ferrate dose, pH 6.2

Time (min)

5 10 15 20 25 30

Ferrate Concentration (M)

5 10 15 20 25 30

Ferrate Concentration (mg/L as Fe)

0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 pH 6.2 Buffered Blank Houston TX pH 6.2 Palmer MA pH 6.2 Readsboro VT pH 6.2

From: Jiang et al., 2013

CEE697K Lecture #21

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Low Dose, High pH

Time (min)

5 10 15 20 25 30

Ferrate Concentration (M)

10 20 30 40

Ferrate Concentration (mg/L as Fe)

0.0 0.5 1.0 1.5 2.0 pH 7.5 Buffered Blank Amherst MA pH ~7.5 Houston TX pH 7.5 Palmer MA pH 7.5 Readsboro MA pH 7.5

 25 µM, pH 7.5 From: Jiang et al., 2013

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High Dose, Low pH

Time (min)

5 10 15 20 25 30

Ferrate Concentration (M)

10 20 30 40 50 60

Ferrate Concentration (mg/L as Fe)

1 2 3 pH 6.2 Buffered Blank Houston TX pH 6.2 Palmer MA pH 6.2 Readsboro VT pH 6.2

 50 µM, pH 6.2 From: Jiang et al., 2013

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High Dose, High pH

Time (min)

5 10 15 20 25 30

Ferrate Concentration (M)

10 20 30 40 50 60

Ferrate Concentration (mg/L as Fe)

1 2 3 pH 7.5 Buffered Blank Amherst MA pH ~7.5 Houston TX pH 7.5 Palmer MA pH 7.5 Readsboro MA pH 7.5

 50 µM, pH 7.5 From: Jiang et al., 2013

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Houston Data Isolated

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 More data improves accuracy

Time (min)

5 10 15 20 25 30

Ferrate Concentration (M)

10 20 30 40 50 60

Ferrate Concentration (mg/L as Fe)

1 2 3 Houston TX pH 7.5

Integrate curve to get CT vs time

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 Simple “rectangle” method

Time (min)

5 10 15 20 25 30

Ferrate Concentration (M)

10 20 30 40 50 60

Ferrate Concentration (mg/L as Fe)

1 2 3 Houston TX pH 7.5

Light scattering background (not ferrate)

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Model for pollutant oxidation

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 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

  • dt
  • Po

Pt

pH

6.0 6.5 7.0 7.5 8.0 8.5

Fraction Remaining

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

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Kinetic Analysis, low dose

pH

6.0 6.5 7.0 7.5 8.0 8.5

Fraction Remaining

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

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The “problems” with ozone

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Many important secondary oxidants, especially OH radical Ozone decomposition in real waters does not match predictions

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Mechanistic model is “off”

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 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” Decomposition

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

CEE697K Lecture #21

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Ozone Loss: focus on NOM

0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 1 2 3 4 5 Specific UV Absorbance 5-min ozone consumption (mg/mg-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)

t initial O O

e C C

 

,

3 3

54

Log pH TOC Alk       356 0 66 0 61 0 42 . . . log . log Log pH Abs TOC Alk        393 0 24 0 75 108 019

254

. . . log . log . log

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

] [ ] [

3 3

O dt O d   

CEE697K Lecture #21

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Ozonation of trace organics: Direct Rcn

CEE697K Lecture #21

55  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

CEE697K Lecture #21

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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.

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Competitive kinetics with probe

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 Pollutant (P) and probe compound (pCBA)

  • 1
  • If you know kp and want to

estimate oxidation of P: If you want to determine kp from measurements of P:

  • Determining OH rate constants

CEE697K Lecture #21

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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.

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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

  • ver time and ozone dose (typically ~0.5M/M)

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.

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:

From: Hoigne & Bader, 1979

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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  to estimate loss of “P” by simply measuring

O3

  • Δ

Δ Ω ∑

Ω ∑

  • Δ
  • Δ

Ω

  • Δ

Ω

Production rate of OH radicals Fraction of OH that reacts with M And rearranging: This is what we can actually measure

  • r

Field Values

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 Values of  have

been measured on many natural waters

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.

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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 i ii i

k k k k k A B    ] [ ] [ C B A

ii i

k k

   

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RCT concept

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

probe compound as Hoigne & Bader

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.

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:

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RCT concept III

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 Simple model system

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.

  • RCT concept IV

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 Lake Zurich water  Apparent 2-stage

kinetics

 1st stage may or may not

be linear

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.

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Incorporating both pathways

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 The expanded 2nd order model is:  Rearranging and integrating we get:  or:

  • both pathways II

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 Porrentruy Water

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.

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both pathways III

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

 Natural waters

  • 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.

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Role of pH

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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.

 Increase in RCT

Role of Bicarbonate

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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.

 Decrease in RCT

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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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