EPA/600/R-05/103
August 2005
Organophosphate Pesticide Degradation Under
Drinking Water Treatment Conditions
By
Stephen E. Duirk and Timothy W. Collette
National Exposure Research Laboratory
Ecosystems Research Division
Athens, GA
U.S. Environmental Protection Agency
Office of Research and Development
Washington D.C. 20460
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NOTICE
The information in this document has been funded by the United States Environmental
Protection Agency. It has been subject to the Agency's peer and administrative review, and it
has been approved for publication as an EPA document. Mention of trade names of commercial
products does not constitute endorsement or recommendation for use.
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ABSTRACT
Chlorpyrifos (CP) was used as a model compound to develop experimental methods and
prototype modeling tools to forecast the fate of organophosphate (OP) pesticides under drinking
water treatment conditions. CP was found to rapidly oxidize to chlorpyrifos oxon (CPO) in the
presence of free chlorine. The primary oxidant is hypochlorous acid (HOC1); thus, oxidation is
more rapid at lower pH (i.e., below the pKa of HOC1 at 7.5). At elevated pH, both CP and CPO
are susceptible to alkaline hydrolysis and degrade to 3,5,6-trichloro-2-pyridinol (TCP), a stable
end product. Furthermore, the hydrolysis of both CP and CPO to TCP was shown to be
accelerated in the presence of free chlorine by OC1". These observations regarding oxidation and
hydrolysis are relevant to common drinking water treatment processes: disinfection and water
softening, respectively. In this work, intrinsic rate constants for these processes were
determined, and simple computer models have been developed that accurately predict the
concentration of CP, CPO, and TCP as a function of pH, chlorine dose, CP concentration, and
time after chlorine dosing. These models serve as a first step toward the development of tools to
assess the assessment of risk associated with consuming treated drinking water whose source is
contaminated with OP pesticides.
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FOREWORD
The National Exposure Research Laboratory Ecosystems Research Division (ERD) in Athens,
Georgia, conducts process, modeling, and field research to assess the exposure risks of humans
and ecosystems to both chemical and non-chemical stressors. This research provides data,
modeling tools, and technical support to EPA Program and Regional Offices, state and local
governments, and other customers, enabling achievement of Agency and ORD strategic goals for
the protection of human health and the environment.
ERD research includes studies of the behavior of contaminants, nutrients, and biota in
environmental systems, and the development of mathematical models to assess the response of
aquatic systems, watersheds, and landscapes to stresses from natural and anthropogenic sources.
ERD field and laboratory studies support process research, model development, testing and
validation, and the characterization of variability and prediction uncertainty. Leading-edge
computational technologies are developed to integrate core science research results into
modeling systems that provide predictive capabilities for complex environmental exposure
scenarios faced by the Agency.
This research project seeks to provide evaluated methods, tools, and databases for forecasting the
fate of pesticides and other toxic chemicals in drinking water treatment systems. These products
will be useful to EPA Program Offices and others who must evaluate the ultimate fate of
chemicals that occur in drinking water sources. This report describes the development and
testing of experimental methods and computational models to characterize and simulate
chlorination and hydrolysis of organophosphate pesticides under drinking water treatment
conditions. Chlorpyrifos and its degradates were used as model compounds for the study. This
work is the first step in developing screening-level tools for forecasting chemical transformations
in drinking water treatment scenarios, that ultimately will make assessment of risk from
consuming drinking water more accurate.
Eric J. Weber, Ph.D.
Director
Ecosystems Research Division
Athens, Georgia
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ACKNOWLEDGEMENT
The authors would like to thank Jimmy Avants and Chris Tarr for their technical assistance.
Also, we would like to thank Dr. Wayne Garrison, Dr. Jackson Ellington, Dr. Dan Cherney, and
Dr. John Kenneke for their consultation and expertise.
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OP Pesticide Degradation under DW Conditions
TABLE OF CONTENTS
TABLE OF CONTENTS i
LIST OF TABLES ii
LIST OF FIGURES iii
EXECUTIVE SUMMARY vi
1 INTRODUCTION 1
2 EXPERIMENTAL PROCEDURES 5
2.1 Materials 5
2.2 Methods 5
3 RESULTS AND DISCUSSION 9
3.1 Chlorpyrifos Reaction Order and Apparent Rate Constants 9
3.2 Degradation Pathways of Chlorpyrifos Oxon 10
3.3 Model Development 12
4 CONCLUSIONS 15
5 REFERENCES 18
TABLES 20
FIGURES 22
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OP Pesticide Degradation under DW Conditions
LIST OF TABLES
Table 1 Stoichiometric equations and rate coefficients used in the chlorpyrifos degradation
pathway model. Numbers in parenthesis are 95% confidence intervals for the rate coefficients
determined in this study 21
11
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OP Pesticide Degradation under DW Conditions
LIST OF FIGURES
Figure 1 Free chlorine loss in the presence of CP at pH 8.5. [CP]0 = 0.5 |iM, [CO3]T = 10
mM, Temperature = 25 °C, and [HOC1]T = 10, 50, 100 [iM [[[ 23
Figure 2 Free chlorine loss in the presence of CP at pH 9. [CP]0 = 0.5 (jM, [CO3]x = 10 mM,
Temperature = 25 °C, and [HOC1]T = 10, 50, 100 [iM [[[ 24
Figure 3 Free chlorine loss in the presence of CP at pH 10. [CP]0 = 0.5 (jM, [CO3]x =10 mM,
Temperature = 25 °C, and [HOC1]T = 10, 50, 100 |iM [[[ 25
Figure 4 Free chlorine loss in the presence of CP at pH 1 1 . [CP]0 = 0.5 |jM, [CO3]x =10
mM, Temperature = 25 °C, and [HOC1]T = 10, 50, 100 [iM [[[ 26
Figure 5 Observed first order loss of CP as a function of free chlorine at pH 6.36. [CP]0 = 0.5
, [PO4]T = 10 mM, Temperature = 25 °C, and [HOC1]T = 10, 50, 100 |iM ............................. 27
Figure 6 Observed first order loss of CP as a function of free chlorine at pH 7.5. [CP] = 0.5
, [PO4]T = 10 mM, Temperature = 25 °C, and [HOC1]T = 10, 50, 100 [iM ............................. 28
Figure 7 Observed first order loss of CP as a function of free chlorine at pH 8.5. [CP]0 = 0.5
, [CO3]T = 10 mM, Temperature = 25 °C, and [HOC1]T = 10, 50, 100 |iM ............................ 29
Figure 8 Observed first order loss of CP as a function of free chlorine at pH 8.75. [CP]0 = 0.5
, [CO3]T = 10 mM, Temperature = 25 °C, and [HOC1]T = 10, 50, 100 [iM ............................ 30
Figure 9 Observed first order loss of CP as a function of free chlorine at pH 9. [CP]0 = 0.5
, [CO3]T = 10 mM, Temperature = 25 °C, and [HOC1]T = 10, 50, 100 [iM ............................ 31
Figure 10 Observed first order loss of CP as a function of free chlorine at pH 10. [CP]0 = 0.5
, [CO3]T = 10 mM, Temperature = 25 °C, and [HOC1]T = 10, 50, 100 |iM ............................ 32
Figure 1 1 Observed first order loss of CP as a function of free chlorine at pH 1 1 . [CP]0 = 0.5
, [CO3]T = 10 mM, Temperature = 25 °C, and [HOC1]T = 10, 50, 100 [iM ............................ 33
Figure 12 Reaction order of free chlorine with CP at pH 8.5. [CP]0 = 0.5 |iM, [CO3]T = 10
mM, Temperature = 25 °C, and [HOC1]T = 10, 50, 100 |iM [[[ 34
Figure 13 Reaction order of free chlorine with CP at pH 9.0. [CP]0 = 0.5 |iM, [CO3]T = 10
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OP Pesticide Degradation under DW Conditions
Figure 1 5 Reaction order of free chlorine with CP at pH 1 1 . [CP]0 = 0.5 \jM, [CO3]T = 1 0
mM, Temperature = 25 °C, and [HOC1]T = 10, 50, 100 |iM [[[ 37
Figure 16 Apparent second order reaction rate coefficient for CP in the presence of free
chlorine at pH 6.36. [CP]0 = 0.5 |iM, [PO4]T = 10 mM, Temperature = 25 °C, and [HOC1]T = 10,
50, 100 (jM. 95% confidence intervals about the regression line shown .................................... 38
Figure 17 Apparent second order reaction rate coefficient for CP in the presence of free
chlorine at pH 7.5. [CP]0 = 0.5 |iM, [PO4]T = 10 mM, Temperature = 25 °C, and [HOC1]T = 10,
50, 100 (jM. 95% confidence intervals about the regression line shown .................................... 39
Figure 1 8 Apparent second order reaction rate coefficient for CP in the presence of free
chlorine at pH 8.5. [CP]0 = 0.5 |iM, [PO4]T = 10 mM, Temperature = 25 °C, and [HOC1]T = 10,
50, 100 (jM. 95% confidence intervals about the regression line shown .................................... 40
Figure 19 Apparent second order reaction rate coefficient for CP in the presence of free
chlorine at pH 8.75. [CP]0 = 0.5 |iM, [CO3]T = 10 mM, Temperature = 25 °C, and [HOC1]T = 10,
50, 100 (jM. 95% confidence intervals about the regression line shown .................................... 41
Figure 20 Apparent second order reaction rate coefficient for CP in the presence of free
chlorine at pH 9. [CP]0 = 0.5 |iM, [CO3]T = 10 mM, Temperature = 25 °C, and [HOC1]T = 10,
50, 100 (jM. 95% confidence intervals about the regression line shown .................................... 42
Figure 21 Apparent second order reaction rate coefficient for CP in the presence of free
chlorine at pH 10. [CP]0 = 0.5 |iM, [CO3]T = 10 mM, Temperature = 25 °C, and [HOC1]T = 10,
50, 100 (jM. 95% confidence intervals about the regression line shown .................................... 43
Figure 22 Apparent second order reaction rate coefficient for CP in the presence of free
chlorine at pH 1 1. [CP]0 = 0.5 |iM, [CO3]T = 10 mM, Temperature = 25 °C, and [HOC1]T = 10,
50, 100 (jM. 95% confidence intervals about the regression line shown .................................... 44
Figure 23 The pH dependence of the apparent second order rate constant for the reaction of
free chlorine with CP. [CP]0 = 0.5 |iM, [Buffer]T = 10 mM, Temperature = 25±FC, and
[HOCl]x= 10, 50, and 100 (jM. Error bars represent 95% confidence intervals ........................ 45
Figure 24 Experimental and model predictions for the first order observed hydrolysis of CPO
over the pH range of 1-11. [CPO]0 = 0.5 |iM, [Buffer]T = 10 mM, and Temperature = 25±1°C,.
Error bars represent 95% confidence intervals and the line represents model results .................. 46
Figure 25 Second order rate coefficient for chlorine assited hydrolysis of CPO at pH 9 and
10.9. [CPO]0 = 0.5 nM, [CO3]T = 10 mM, Temperature = 25±FC, and [HOC1]T = 0-250 |iM.
Error bars represent 95% confidence intervals [[[ 47
Figure 26 Simplified schematic of chlorpyrifos degradation pathways in the presence of
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OP Pesticide Degradation under DW Conditions
Figure 27 TCP experimental and model results for the loss of CP in the presence of free
chlorine at pH 1 1 . [CP]0 = 0.35 |iM, [CO3]T = 10 mM, Temperature = 25±1°C, and [HOC1]T =
0-150 |jM. Lines represent model results [[[ 49
Figure 28 CP degradation in the presence of free chlorine at pH 7. 15. [CP]0 = 0.33
[CC>3]x = 1 mM, Temperature = 25±1°C, and [HOCl]x = 20 |jM. Lines represent model results
and error bars are 95% confidence intervals [[[ 50
Figure 29 CP degradation in the presence of free chlorine at pH 9.0. [CP]0 = 0.5 |jM, [CC>3]x =
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OP Pesticide Degradation under DW Conditions
EXECUTIVE SUMMARY
Environmental regulations require that all relevant routes of human consumption be
considered in risk assessments for anthropogenic chemicals. A large percentage of the US
population consumes drinking water (DW) that is treated. There is available monitoring data for
important pesticides and toxic chemicals in DW sources (both surface and ground water).
However, there is very little monitoring data for these chemicals or their degradates in finished
DW. Limited experimental studies show that some chemicals are partially removed by physical
water treatment processes (e.g., filtration, flocculation, etc.), and some are transformed by
reactions that occur during chemical treatment (e.g., disinfection and softening).
Transformations of some contaminants have been shown to produce products that are more toxic
than the parent compound.
This report is in partial fulfillment of the National Exposure Research Laboratory Task #
16608, "Fate of Pesticides and Toxic Chemicals During Drinking Water Treatment", under Goal
4, GPRA Objective 4.5, and GPRA Sub-objective 4.5.2. The goals of this research task are to: 1)
provide chemical-specific information on the effects of water treatment for high-priority
pollutants, 2) provide physicochemical parameters for transformation products, and 3) develop
predictive models for forecasting treatment effects that cross chemical class and treatment
conditions. Toward this end, the efforts described in this report provide evaluated information
on the chemical transformations of chlorpyrifos (CP), a widely used organophosphate (OP)
pesticide, under drinking water treatment conditions. In addition, this report describes the first
steps toward developing predictive models for forecasting chemical treatment effects for the
entire class of OP pesticides.
VI
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OP Pesticide Degradation under DW Conditions
For this effort, the loss of CP in the presence of free chlorine in laboratory-prepared
aqueous solution was observed. This loss was found to be first order with respect to both CP
concentration and to free chlorine concentration. A total of two transformation products were
observed with near-complete mass balance - chlorpyrifos oxon (CPO) and 3,5,6-trichloro-2-
pyridinol (TCP). The transformation of CP to CPO occurs via oxidation by hypochlorous acid
(HOC1). This reaction is rapid, and increasingly so as pH decreases due to the pKa of HOC1 at
7.5. This observation is relevant for drinking water disinfection, which is often achieved using
chlorine near neutral pH. The oxon degradates of OP pesticides are typically much more toxic
than the parent compound.
Both CP and CPO were observed to hydrolyze to TCP, particularly at higher pH. The
most prominent form of hydrolysis is base-catalyzed. Also, for the first time, we report here a
transformation pathway of hydrolysis for both CPO and CP that is assisted by OC1" when
chlorine is present under alkaline conditions. These observations are relevant for drinking water
softening, which is often achieved by significantly raising the pH (by adding lime or soda ash) in
order to precipitate minerals. Hydrolysis products such as TCP are generally less toxic than the
parent OP pesticides.
Results of the experiments described herein demonstrate that the change in risk
(associated with anthropogenic chemicals in source waters) due to DW treatment is a complex
issue. For example, while oxidation of OP pesticides by chlorine below neutral pH leads very
rapidly to a more toxic form, hydrolysis (assisted by chlorine) above neutral pH leads to a less
toxic form. Because of this complexity, we have chosen to develop screening-level models that
forecast the concentrations of all reaction products as a function of pH, chlorine dose, OP
pesticide concentration, and time after chlorine dosing. To test this approach, we have
vn
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OP Pesticide Degradation under DW Conditions
determined intrinsic rate constants for all relevant pathways of transformation for CP in
chlorinated water. Using these simple models and intrinsic rate constants, we demonstrate that
the concentrations of CP, CPO, and TCP can be adequately described under a variety of
scenarios that are similar to DW treatment conditions.
The work reported here serves as the first steps - and the "proof-of-concept" - towards
the development of a comprehensive modeling tool for OP fate in drinking water treatment
plants and distribution systems. Following the reported work, we have now begun to apply the
experiments and models to other OP pesticides that were judiciously selected to reflect the full
range of chemical structure variability in this class. Our objective is to develop predictive
models that associate relative rates of reactivity to structural variability. This will allow decision
makers to rank and prioritize chemicals found in drinking water sources according to potential
risk. Also, we are currently in the process of identifying natural aqueous matrix components that
most significantly affect the rates and pathways of transformation of anthropogenic chemicals
under DW treatment conditions. For example, we are evaluating the impacts of natural organic
matter (NOM) and bromide ion concentration on the oxidation of CP. NOM can serve as a
"sink" (or "demand") for free chlorine and reduce the observed rate of oxidation. On the other
hand, bromide can be oxidized by chlorine to form hypobromous acid, which is a more potent
oxidant than hypochlorous acid. Therefore, the presence of bromide can increase the observed
oxidation of CP. The goal of these experiments is to incorporate these most-important matrix
effects into our models so that the models can be applied to actual DW treatment scenarios.
Vlll
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1 INTRODUCTION
Numerous drinking water sources have been contaminated with pesticides,
Pharmaceuticals, plasticizers, antimicrobial agents, as well as many other potentially harmful
chemicals.1'2 The fate for many of these compounds under drinking water treatment conditions
is a concern due to the potential adverse health effects by consuming contaminated potable
water. Physical surface water treatment processes (coagulation/flocculation, sedimentation, and
filtration) do not appear to remove or transform most hydrophilic chemicals.3 On the other hand,
chlorine has been shown to transform some of these chemicals.4"7 However, few studies have
included a thorough investigation of the ultimate fate of these transformation products.
The Food Quality Protection Act of 1996 (FQPA) requires that all pesticide chemical
residuals in or on food be considered for anticipated exposure. Drinking water is considered a
potential pathway for dietary exposure, but there is reliable monitoring data for only the source
water. For example, the United States Geological Survey (USGS) completed a national
reconnaissance survey known as NAWQA (National Water Quality Assessment) to help define
human exposure to various contaminants.8 For the NAWQA survey, 90 pesticides (and some
selected metabolites) were chosen as target chemicals to monitor in US drinking water sources.
However, there is a relative dearth of information on occurrence of pesticide residuals and
pesticide metabolites in finished drinking water. Two surveys have been conducted for a few
community water systems examining pesticide concentrations in the source and finished drinking
water.9'10 Neither of these studies thoroughly examined the effect of each treatment process on a
single slug of water, hence only the influent and effluent of each treatment facility could be
qualitatively discussed with respect to overall removal efficacy. Also, these studies did not
account for the treatment plant hydraulic retention time, thus it was not possible to ensure that
1
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OP Pesticide Degradation under DW Conditions
influent and effluent samples were properly paired. Clearly, more thorough occurrence studies
that include monitoring drinking water for both pesticides and their expected transformation
products are needed.
Chlorination is the most commonly used chemical disinfectant for community water
systems u and is known to react with numerous pesticides. For example, four s-triazines were
found to degrade in the presence of free chlorine (HOC1 + OC1").12'13 The proposed reaction
center and transformation pathway for each s-triazine was oxidation of the sulfur resulting in the
formation of sulfoxide and sulfone degradation products. Atrazine was also found to be
significantly degraded by ozone;14 however, subsequent chlorination of the ozonated effluent had
very little affect on concentration of residual atrazine or its ozone degradation products.9
Some carbamate pesticides have been shown to react with free chlorine while other
members of this pesticide class were found to be stable in chlorinated water. For example,
carbaryl and propoxur do not react with free chlorine; but, aldicarb, methomyl, and thiobencarb
do exhibit significant reactivity.15"17 The sulfoxide degradate of thiobencarb - produced by
reaction with free chlorine - was found to be mutagenic.17 However, the by-products of aldicarb
were found to be less toxic than the parent.15 These findings demonstrate that free chlorine
reactivity with different members in a specific class of pesticides can vary significantly due to
chemical structure variations. Therefore, it is prudent to study the fate and transformation
pathways of entire chemical classes, using class members that exhibit systematic structural
variations and employing carefully selected experimentation and numerical modeling.
When chlorine reacts with the phosphorothioate subgroup of organophosphate (OP)
pesticides, the thiophosphate functionality (P=S) can be oxidized to its corresponding oxon
(P=O).18"20 The resulting oxons are typically more potent than the parent as an inhibitor of
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OP Pesticide Degradation under DW Conditions
acetlycholinesterase, an enzyme necessary for proper function of the nervous system.20 Margra
et al.,19 investigated the stability of diazoxon at neutral pH in the presence of chlorine and found
that it was relatively stable after 48 hours (i.e., over 50% remained). Thus, it was assumed that
the oxons are resistant to further oxidation by aqueous chlorine. However, the oxon form is
more susceptible to neutral and alkaline hydrolysis than is the parent pesticide.21 To our
knowledge, no additional experiments have been conducted to determine the stability of oxons
under conditions relevant to drinking water treatment.
As mentioned previously, twelve community water systems were recently surveyed for
pesticide contamination in both their source and finished waters.10 Three OP pesticides
(diazinon, chlorpyrifos, and malathion) were commonly detected in the source water. However,
the parent compounds were never detected in finished potable water. This suggests that the
pesticides were completely eliminated by drinking water treatment, but this seems unlikely given
that most hydrophilic chemicals are not significantly removed by physical treatment processes.
On the other hand, this observation could mean that the parent OPs were completely transformed
to the more toxic oxon forms, which were not target analytes in the surveys. The reaction rates
and pathways of OP pesticide degradation under drinking water treatment conditions have yet
been investigated fully enough to determine if such an assumption is warranted.
The purpose of this study reported herein was to further elucidate the kinetics and
degradation pathways of OP pesticides in the presence of free chlorine. Chlorpyrifos (CP) was
chosen as a model OP pesticide due to its widespread use and the frequency that it has been
found in drinking water sources. The first-order observed rate constants were obtained for CP
loss in the presence of increasing chlorine concentrations over the pH range of 6.3-11. The
reaction orders for both CP and free chlorine were then determined. Then, from the apparent
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OP Pesticide Degradation under DW Conditions
second order rate coefficients, the intrinsic rate coefficient for hypochlorous acid (HOC1)
reacting with CP was determined. Since the aqueous stability of chlorpyrifos oxon (CPO) was
relatively unknown, hydrolysis experiments for CPO were conducted over the pH range of 1-11.
Also, CPO stability in the presence of free chlorine was examined over the pH range of 4-11.
These experiments resulted in elucidation of the degradation pathways for CP and CPO in the
presence of free chlorine. A model was developed from the proposed degradation pathways that
is capable of temporally predicting the loss of CP and CPO as well as the formation of 3,5,6-
trichloro-2-pyridinol (TCP), which is the final degradate for these reactions.
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OP Pesticide Degradation under DW Conditions
2 EXPERIMENTAL PROCEDURES
2.1 Materials
Chlorpyrifos (99.5%), chlorpyrifos oxon (98.7%), and 3,5,6-trichloro-2-pyridinol (99%)
were purchased from ChemService (West Chester, PA). Commercial 10-13% sodium
hypochlorite (NaOCl), purchased from Aldrich (Milwaukee, WI), contained equimolar amounts
of OC1" and Cl". Aqueous stock solutions and experiments utilized laboratory-prepared
deionized water (18 MQ cm"1) from a Barnstead ROPure Infinity™/NANOPure ™ system
(Barnstead-Thermolyne Corp., Dubuque, IA). Phosphate and carbonate salts used for buffer
solutions were dissolved in deionized water and filtered through a 0.45 |j,m filter, which was pre-
rinsed with deionized water. The pH for the experiments was adjusted with either 1 N H2SO4 or
NaOH. All organic and inorganic chemicals were certified ACS reagent grade and used without
further purification.
2.2 Methods
The glassware and polytetrafluoroethylene (PTFE) septa used in this study were soaked
in a concentrated free chlorine solution for 24 hours, rinsed with deionized water, and dried at
105 °C prior to use. All pH measurements were obtained using an Orion 940 pH meter with a
Ross combination electrode from Fisher Scientific (Pittsburgh, PA). All chlorination and
hydrolysis experiments were conducted at constant temperature (25±1°C). All kinetic
experiments used to estimate rate coefficients measured at least 87% loss in parent compound.
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OP Pesticide Degradation under DW Conditions
For all CP oxidation experiments, CP was spiked by adding 1 mL of 4 mM stock in ethyl
acetate into an empty 4 L borosilicate glass Erlenmeyer flask. A gentle flow of nitrogen gas was
used to evaporate the ethyl acetate and 4 L of deionized water was then added to the flask. The
solution was slowly stirred and allowed to dissolve for 12 hours resulting in an aqueous
concentration of 1 |jM. CP chlorination kinetic experiments were conducted under pseudo-first-
order conditions, total chlorine to chlorpyrifos molar ratios of 20:1, 100:1, and 200:1. Chlorine
was added to solutions under rapid mix conditions achieved with a magnetic stir plate and a
PTFE-coated stir bar. At each discrete sampling interval, two reaction vessels were sacrificed in
their entirety. One vessel was used to determine total free chlorine concentration ([HOCl]x =
[HOC1] +[OCr]) via Standard Method 4500-C1 F DPD-FAS titrimetric method.22 In the other
vessel, free chlorine residuals were quenched with sodium sulfite in 20% excess of the initial free
chlorine concentration. The pH of a 100 mL aliquot was then adjusted to 2 for analysis of CP
and its degradation products.
Above pH 8, 10 mM carbonate [CO3]T buffer was used to maintain pH. The purchased
free chlorine solution was first diluted to 18,000 mg-C^/L. The diluted free chlorine stock
solution was added to the aqueous system containing 0.5 |jM chlorpyrifos and 10 mM carbonate
buffer in a 2 L Erlenmeyer flask. After mixing, thirteen aliquots from the large 2 L reactor were
placed into 128 mL amber reaction vessels with PTFE septa and stored in a water bath at 25±1°C
in the dark.
In the pH range of 6.0-7.5, the rate of CP loss in the presence of free chlorine was very
fast. Therefore, twelve 100 mL aliquots from a 2 L aqueous system containing 10 mM
phosphate buffer, [PO^x, and 0.5 |jM CP were placed in 250 mL amber Erlenmeyer flasks.
Each individual reaction vessel was brought up to 25±1°C via water bath immersion. Free
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OP Pesticide Degradation under DW Conditions
chlorine was then added to each reactor while under rapid mix conditions with a magnetic stir
plate and PTFE-coated stir bar. The reaction vessels where then re-immersed in the water bath.
At designated time intervals, reactors were quenched with 20% excess stoichiometric sodium
sulfite compared to the initial free chlorine concentration and CP and its degradation products
were extracted. The time frame of these experiments was under 1 hour. Parallel experiments
were conducted to determine free chlorine concentrations as a function of time.
The reactivity of free chlorine with CPO was also examined. The experimental
procedures were the same as for CP in the presence of free chlorine above pH 8. Since there is a
lack of CPO hydrolysis rate coefficients in the literature, hydrolysis experiments in the absence
of free chlorine were also conducted over the pH range of 1 to 11.
Additionally, model validation experiments were conducted at pH 7.1 and 9.0. These
experiments were conducted in triplicate via the procedures outlined previously for CP oxidation
experiments above pH 8. Experimental conditions were chosen to reflect drinking water
treatment conditions: [CO3]T = 1.0 mM and [HOC1]T = 20 and 10 (jM at pH 7.1 and 9
respectively.
CP and its degradation products were extracted from water using C-18 solid phase
extraction (SPE) cartridges purchased from Supleco (Bellefonte, PA). First, the pH of a 100 mL
sample was adjusted to pH < 2 to increase the recovery of TCP (pKa = 4.55) on the solid phase
adsorbent.23 Then, the sample was spiked with 1 |jM of phenthorate (internal standard), mixed
thoroughly by hand for two minutes, passed through the SPE cartridge at an approximate flow-
rate of 7 mL/min, and eluted with 3 mL of ethyl acetate. Quantification for each analyte was
compared to eight extracted standards over the concentration range of 0.01 to 1 |jM. A Hewlett-
Packard 6890 GC equipped with a 5973 MSD was used to analyze CP, CPO, and TCP. GC
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OP Pesticide Degradation under DW Conditions
conditions were as follows: 30-m Restek Rtx-200 column with a 0.25-mm ID and 0.5-|j,m film
thickness. The temperature profile was: 100 °C for 5 minutes, 100 to 250 °C at 10 °C/minute,
and then held at 250 °C for 25 minutes. Mass balances of 80% or greater were obtained for each
experiment.
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OP Pesticide Degradation under DW Conditions
3 RESULTS AND DISCUSSION
3.1 Chlorpyrifos Reaction Order and Apparent Rate Constants
The observed loss of CP in the presence of free chlorine was initially assumed to be first
order with respect to CP concentration. If linearity is observed when plotting ln([CP]/[CP]0)
versus time (t), then this assumption would be valid when free chlorine is present in excess.
(Note that [CP]/[CP]0 is the measured concentration of CP at a discrete sampling time divided by
the initial concentration of CP.) The slope of the regression line from such a plot yields the
observed first order rate coefficient (k0bs) for CP loss as described by the following rate
expression:
[CP]
ln-—- = -kobst (1)
[CP]0
Prior to examining plots of ln([CP]/[CP]0) versus t, we established, as shown in Figures 1
- 4, that free chlorine was in excess and that the concentration of free chlorine did not change
significantly over the course of the reactions. Then, we generated plots of ln([CP]/[CP]0) versus
t at a variety of pHs and for different concentrations of free chlorine. As demonstrated in Figures
5 - 11, CP exhibited first order dependency with respect to itself when reacting in the presence
of free chlorine under these experimental conditions. For example, Figure 7 shows the first order
observed loss of CP at pH 8.5 and [HOC1]T = 10, 50, and 100 |iM. The first order rate
coefficients for the various experimental conditions were determined from the slopes of the
regression lines displayed in Figures 5-11.
Next, we determined the order of the reaction with respect to free chlorine at the various
pHs by plotting the log of the observed first order rate coefficients versus the log of the initial
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OP Pesticide Degradation under DW Conditions
free chlorine concentrations (Figures 12 - 15). The slope of the regression lines in these figures
indicate the reaction order with respect to total free chlorine was approximately 1 over the entire
pH range sampled. For example, as demonstrated in Figure 12, at pH 8.5 the slope was found to
be 1.103 with an r2 of 0.998.
The second order apparent rate coefficient (kapp) at each pH was determined by plotting
k0bs versus the initial free chlorine concentration. Since both species of free chlorine are present
(HOC1 + OC1"), the apparent second order loss of CP in the presence of free chlorine can be
described as
kobs=kapP[HOCl]T (2)
[HOCi]T[CP] (3)
dt
Figures 16-22 show that, for all pH k0bs increases linearly with increasing free chlorine
concentration. This indicates that the observed first order rate coefficients are proportional with
increasing free chlorine concentration for each pH examined. In addition, kapp (calculated from
equation 2) increased as pH decreased from 1 1 to 6.3 (Figure 23). The pKa of hypochlorous acid
(HOC1) is 7.5.24 If the dominant reacting species is HOC1, then the apparent rate coefficient
should increase as pH decreases.
3.2 Degradation Pathways of Chlorpyrifos Oxon
Due to the fact that diazoxon was resistant to further oxidation by free chlorine,19
disappearance of CPO in the presence of free chlorine was assumed to only occur via alkaline
hydrolysis. Unlike CP,25 there has been no thorough examination of CPO hydrolysis. It was
thought that CPO would behave similarly to CP except the oxon hydrolysis rate would be faster,
10
-------
OP Pesticide Degradation under DW Conditions
as has been seen with other OP pesticides and their oxon analogues.21 The hydrolytic behavior
of CPO in the absence of chlorine was found in the study reported here (Figure 24) to be similar
to that found previously for CP. Both CPO and CP do not have an acid assisted component to
the observed first order hydrolytic loss. Over the pH range of 1-7, the neutral hydrolysis
component was found to be: kN,cpo = 2.19 * 10"3 ± 1.73 x 10"3 h"1. This is an order of magnitude
faster than the neutral hydrolysis component previously reported for CP.25 The alkaline
hydrolysis rate coefficient (kB,cpo) was determined by plotting the observed first order loss of
CPO versus the hydroxide ion concentration over the pH range of 8.5-11. The slope of the
regression line yielded the alkaline hydrolysis rate coefficient: kB,cpo = 229.2 ± 18.7 M^h"1.
Half-lives for CPO at pH 9, 10, and 11 were 80.5, 17.7, and 2.8 hours respectively. In Figure 24,
the first order observed rate coefficients for CPO were adequately predicted using the neutral and
alkaline assisted hydrolysis rate coefficients. Alkaline hydrolysis appears to be the only relevant
CPO hydrolysis pathway under drinking water treatment conditions in the absence of chlorine.
The stability of CPO in the presence of free chlorine over the pH range of 4-11 was also
invstigated. Over the pH range pH 4-7, less than 1% of CPO was lost over a period of 6 hours in
the presence of 100 (jM free chlorine. These experiments established that CPO is not susceptible
to further oxidation since they were conducted below the pKa of HOC1, which is a stronger
oxidant than OC1". However, the first order observed loss of CPO increased linearly with
increasing free chlorine concentration from 0-250 |jM at both pH 9 and 10.9 (Figure 25). The
only detected transformation product was TCP at greater than 80% mass balance for all
experiments. The regression lines in Figure 25 were found to be parallel and the slope of each
line was an order of magnitude greater than the rate coefficient determined for alkaline
hydrolysis (kB,cpo) in the absence of chlorine. These results suggest the presence of an OC1"
11
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OP Pesticide Degradation under DW Conditions
assisted hydrolysis pathway. For example, OC1" could be serving as a nucleophile similar to OH"
in the alkaline hydrolysis process. It could then be proposed that CP would also be susceptible to
chlorine assisted hydrolysis. Chlorine assisted hydrolysis has been observed by others
investigating the formation and degradation of dichloroacetonitrile, a disinfection by-product
(DBF), in the presence of chlorine and natural organic matter (NOM).26
3.3 Model Development
A kinetic model was developed to predict temporal concentrations of CP, CPO, and TCP.
Figure 26 schematically shows the proposed degradation pathways for CP and CPO in the
presence of free chlorine. This includes the observed pathways for which kinetic rate
coefficients were experimentally determined. However, the intrinsic rate coefficients for
hypochlorous acid and hypochlorite reacting with CP cannot be determined through direct
experimental observation. The following set of ordinary differential equations (ODEs), based
upon the presumed stoichiometric reactions in Table 1, were used to model the fate of CP and its
degradates in the presence of free chlorine.
d[CP]
dt
d[CPO]
dt~~
d[TCP]
= -kr[HOCl][CP]-khcp[CP]-koclcp[OCr][CP] (4)
= kr[Hoci][CP] -khcpo[cpo] -koclcpo[ocr][cpo] (5)
= khcp[cp] + koclcp[ocr ][CP] + khcpo[cpo] + koclcpo[ocr ][CPO] (6)
dt
Equation 4 describes the loss of CP due to oxidation by hypochlorous acid, hydrolysis, and
chlorine assisted hydrolysis. Equation 5 describes the formation of CPO as well as its loss by
hydrolysis and chlorine assisted hydrolysis. TCP was found to be a stable end-product from the
12
-------
OP Pesticide Degradation under DW Conditions
loss of CP and CPO. Equation 6 incorporates all known and proposed TCP formation pathways,
i.e., hydrolysis and chlorine assisted hydrolysis pathways for both CP and CPO.
Scientist™, an ODE solver by Micromath (Salt Lake City, UT), was used to fit the
intrinsic rate coefficients for CP oxidation by hypochlorous acid (kr) and chlorine assisted
hydrolysis of CP by hypochlorite (k0ci,cp), using non-linear regression analysis and the Powell
algorithm solution method. The intrinsic rate coefficient (kr) was first fitted using the lower pH
data, pH 6.3, because TCP formation was less than 0.025 |jM and approximately 93% of free
chlorine was in the form of HOC1. Hence, hydrolysis of CP under these conditions could be
largely neglected. The kapp at pH 6.3 was 1.51 (±0.26) x 106 M'V (Figure 23) and the fitted
value for kr = 1.72 (±0.68) x 106 M'V (Table 1). (The numbers in parentheses are 95%
confidence intervals.) The fitted value for kr was expected to be slightly higher to account for
the small amount of free chlorine in the hypochlorite form. Since the confidence intervals for
kapp at pH 6.3 and kr overlap, the intrinsic rate coefficient kr can be approximated quite well from
experiments conducted just below neutral pH. The intrinsic rate coefficient koci,cp was fitted at
pH 11 and [HOC1]T = 0-150 |iM (Figure 27). As the initial dose of free chlorine increased, TCP
formation increased. While CPO was detected at [HOCl]x equal to or greater than 50 |jM,
[CPO] never exceeded 0.025 |jM over the time course of the experiments. Using the fitted value
for k,, the value for koci,cp was found to be 990 (±200) M'V (Table 1). The kapp for these
experiments at pH 11 was 2355 (±859) M'V, which is more than twice the fitted value of
koci,cp- However, the kapp at pH 11 accounts for the total loss of CP including losses due to trace
quantities of HOC1 oxidizing CP to CPO. The kr was found to be sufficiently large to describe
the oxidation of CP over the pH range of 6.3-11, and k0ci,cp was found to adequately describe
chlorine assisted hydrolysis when the dominant form of free chlorine is OC1".
13
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OP Pesticide Degradation under DW Conditions
Previous work with diazinon had proposed that hypochlorite participated in the formation
of diazoxon 18. This assumption was derived by plotting apparent second order rate coefficients
versus hydrogen ion activity. The intercept of the plot was then interpreted as the intrinsic rate
coefficient for hypochlorite reacting with diazinon at zero hydrogen ion activity. However,
diazoxon was not measured in each experiment; therefore, the disappearance of diazinon in the
presence of hypochlorite was assumed to be an oxidation reaction but was never confirmed. The
intrinsic rate coefficient for hypochlorous acid (ko) was calculated based on the proportions of
each chlorine species present at a given pH, the kapp with respect to experimental conditions, and
the intrinsic rate coefficient for hypochlorite (ki) reaction with diazinon that was previously
determined at zero hydrogen ion activity.
kaPP=a0k0+a1k1 (7)
where a0 and oti are the fractions of free chlorine that are present as hypochlorous acid and
hypochlorite, respectively. The intrinsic rate coefficients for diazinon loss in the presence of free
chlorine were: ko = 4.68 x 105 M^h"1 and ki = 972 M'V1.18 The experimental procedure was
similar to the work presented here but only over the pH range of 9-11. Since experiments were
not conducted near neutral pH, ko may have been underestimated. However, ki for diazinon loss
was similar to our fitted rate coefficient for chlorine assisted hydrolysis of CP.
14
-------
OP Pesticide Degradation under DW Conditions
4 CONCLUSIONS
Experiments measuring CP loss in the presence of free chlorine identified degradation
pathways based on mass balances over the pH range of 6.3-11. Hypochlorous acid was found to
rapidly oxidize CP to CPO, and CP hydrolysis rate constants were obtained from literature. It
was proposed that hypochlorite assists hydrolysis of CP, based on experimental observations of
CPO hydrolysis in the presence of free chlorine at pH 9 and 10.9. Also, TCP was found to be a
stable end-product for both CP and CPO degradation pathways in the presence of free chlorine.
Using the rate coefficients in Table 1, the proposed model was validated at pH 7.1 and 9
under conditions similar to drinking water treatment. At pH 7.1 and [HOCl]x = 20 |jM (Figure
28), almost all of the CP present was oxidized to CPO in 5 minutes. After 35 minutes, CP was
no longer detected and CPO was the primary degradation product. Since CPO was found to be
stable near neutral pH and 100 |jM free chlorine, the potential toxicity of the effluent could pose
a greater risk to human health than if CP did not degrade.
At pH 9 and [HOCl]x =10 |jM (Figure 29), CP loss was significantly slower than at pH
7.1. This was due both to the higher pH and lower chlorine dose. The predominant product after
six hours was CPO; however, TCP concentrations were found to increase with time throughout
the experiment. The increase in TCP concentration over the experimental time-frame is likely
due to both ordinary alkaline hydrolysis and chlorine assisted hydrolysis.
Our computational model adequately predicted loss of CP, the formation and degradation
of CPO, and the formation of TCP for both experimental conditions. This shows that CPO
formation is controlled by the presence and availability of HOC1. Also, CPO stability is highly
15
-------
OP Pesticide Degradation under DW Conditions
pH dependent. These conditions were chosen to reflect water plant operating parameters and
also to show that mechanistic models are robust and have the ability to predict degradation
pathways under a variety of conditions.
The ability to model the fate and kinetics of a single compound (e.g., CP) under drinking
water chlorination conditions has been established. Other recent papers have reported thorough
studies of the degradation of surface water contaminants and model compounds in the presence
of chlorine.4'6'27 These studies included investigation of chlorination at relatively low pH, below
6, and found that the rate of disappearance of some pharmaceuticals, dihydroxybenzenes, and
endocrine disrupters increased significantly compared to reactions at higher pH. We observed a
similar phenomenon in experiments at pH below 6 with CP. To explain the significant increase
in observed degradation rates, other researchers have proposed an acid catalyzed process
resulting in the formation of H2OC1+. The pKa of this species was approximated to be in the
range of-3 to-4.28
H2OCl+< >H++HOC1 (8)
The reaction rate coefficients for the H2OC1+ species were calculated and found to be diffusion
controlled for dihydroxybenzenes and endocrine disrupters, involving attack at the phenolic
ring.6'27 Wang and Margerum 29 theorized that a form similar to this species could exist in the
transition state as part of the one-step acid catalyzed mechanism in the reversible hydrolysis of
aqueous Cb. However, it is unclear if H2OC1+ is the reacting species or Cl2(aq). We are currently
investigating this phenomenon for low pH oxidation of CP.
Mechanistic models greatly increase our understanding of the parameters controlling the
rate of reactions for a specific compound. The ability to model degradation pathways of
chemicals within a specific class still needs to be addressed. The research presented here is the
16
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OP Pesticide Degradation under DW Conditions
first step towards developing models to predict degradation pathways for the entire class of OP
pesticides under more realistic drinking water treatment condition, e.g., in the presence of NOM
and other aqueous constituents. OP pesticides, in the phosphorothioate subgroup, have been
found to be transformed to their corresponding oxon in the presence of free chlorine, and
phosphate esters have been found to undergo chlorine assisted hydrolysis. However, only rate
coefficients for the oxidation of diazinon have been reported.18 Therefore, the need exists to
systematically investigate chlorination of OP pesticides as a class and determine if reactivity
with aqueous chlorine is related in a predictable way to OP chemical structure. If a relationship
between reactivity and pesticide structure exists, the ability to predict the fate of OP pesticides in
the presence of free chlorine would greatly aid regulators in assuring that tolerances to OP
pesticide exposure are not exceeded. After developing predictive tools for the entire class of OP
pesticides, we plan to address other important classes of pesticides and toxic chemicals.
17
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OP Pesticide Degradation under DW Conditions
REFERENCES
(1) Kolpin, D. W.; Furlong, E. T.; Meyer, M. T.; Thurman, E. M.; Zaugg, S. D.; Barber, L.
B.; Buxton, H. T. Environmental Science & Technology 2002, 36, 1202-1211.
(2) Squillace, P. J.; Scott, J. C.; Moran, M. J.; Nolan, B. T.; Kolpin, D. W. Environmental
Science & Technology 2002, 36, 1923-1930.
(3) Miltner, R. J.; Baker, D. B.; Speth, T. F.; Fronk, C. A. Journal American Water Works
Association 1989, 81, 43-52.
(4) Pinkston, K. E.; Sedlak, D. L. Environmental Science & Technology 2004, 38, 4019-
4025.
(5) Dodd, M. C.; Huang, C. H. Environmental Science & Technology 2004, 38, 5607-5615.
(6) Deborde, M.; Rabouan, S.; Gallard, H.; Legube, B. Environmental Science & Technology
2004, 38, 5577-5583.
(7) Hu, J. Y.; Cheng, S. J.; Aizawa, T.; Terao, Y.; Kunikane, S. Environmental Science &
Technology 2003, 37, 5665-5670.
(8) Kolpin, D. W.; Barbash, J. E.; Gilliom, R. J. Ground Water 2000, 38, 858-863.
(9) Verstraeten, I. M.; Thurman, E. M.; Lindsey, M. E.; Lee, E. C.; Smith, R. D. Journal of
Hydrology 2003, 276, 287-288.
(10) Coupe, R. H.; Blomquist, J. D. Journal American Water Works Association 2004, 96, 56-
68.
(11) Community Water System Survey, United States Environmental Protection Agency, 1997;
Vol. l,EPA815-R-97-011a.
(12) Lopez, A.; Mascolo, G.; Tiravanti, G.; Santori, M.; Passino, R. Water Science and
Technology 1994, 30, 53-59.
(13) Mascolo, G.; Lopez, A.; Passino, R.; Ricco, G.; Tiravanti, G. Water Research 1994, 28,
2499-2506.
(14) Adams, C. D.; Randtke, S. J. Journal American Water Works Association 1992, 84, 91-
102.
(15) Miles, C. J. Environmental Science & Technology 1991, 25, 1774-1779.
(16) Mason, Y. Z.; Choshen, E.; Ravacha, C. Water Research 1990, 24,11-21.
(17) Kodama, S.; Yamamoto, A.; Matsunaga, A. Journal of Agricultural and Food Chemistry
1997, 45, 990-994.
(18) Zhang, Q.; Pehkonen, S. O. Journal of Agricultural and Food Chemistry 1999, 47, 1760-
1766.
(19) Magara, Y.; Aizawa, T.; Matumoto, N.; Souna, F. Water Science and Technology 1994,
30, 119-128.
(20) Wu, J. G.; Laird, D. A. Environmental Toxicology and Chemistry 2003, 22, 261-264.
(21) Wolfe, N. L. Chemosphere 1980, 9, 571-579.
(22) Standard Methods for the Examination of Water and Wastewater; 20 ed.; APHA ,
AWWA, and WEF: Washington D.C., 1998.
(23) Liu, B.; McConnell, L. L.; Torrents, A. Chemosphere 2001, 44, 1315-1323.
(24) Snoeyink, V. L.; Jenkins, D. A. Water Chemistry, John Wiley & Sons: New York, NY,
1980.
18
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OP Pesticide Degradation under DW Conditions
(25) Macalady, D. L.; Wolfe, N. L. Journal of Agricultural and Food Chemistry 1983, 31,
1139-1147.
(26) Reckhow, D. A.; Platt, T. L.; MacNeill, A. L.; McClellan, J. N. Journal of Water Supply
Research and Technology-Aqua 2001, 50, 1-13.
(27) Rebenne, L. M.; Gonzalez, A. C.; Olson, T. M. Environmental Science & Technology
1996, 30, 2235-2242.
(28) Arotsky, J.; Symons, M. C. R. Quarterly Reviews 1962, 16, 282-297.
(29) Wang, T. X.; Margerum, D. W. Inorganic Chemistry 1994, 33, 1050-1055.
19
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OP Pesticide Degradation under DW Conditions
TABLES
20
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OP Pesticide Degradation under DW Conditions
Table 1 Stoichiometric equations and rate coefficients used in the chlorpyrifos degradation
pathway model. Numbers in parenthesis are 95% confidence intervals for the rate
coefficients determined in this study.
Reaction Stoichiometry
Rate/Equilibrium Coefficient
(25 °C)
Reference
HOC1
kr= 1.72(±0.68)xl06M'1h'
This work
CP khcp >TCP
CPO
^TCP
CP + OC1
>TCP
5 CPO±OCI- k°acpo
HOC1
•OC1 +H4
h,cp
kB,Cp[OH"]
kB,cp = 37.0 M'V
h,cpo
kN,cpo = 2.13 (±1.73)xlO'3h'1
koci,cp = 990 (±200) M'V
koci,cpo = 1340 (±110) M'V
pKa = 7.5
25
This work
This work
This work
24
21
-------
OP Pesticide Degradation under DW Conditions
FIGURES
22
-------
OP Pesticide Degradation under DW Conditions
1
H
o
o
K
i ju
125 -
100 *
75 -
50 i
25 -
1
n -
• [HOCl]T = 10uM
• [HOC1]T = 50 uM
A [HOCl]T = 100uM
' A A A A A
••• * A ^ A
r • • • • •
> • • A A A
^ W W W ~9
0.00
0.25
0.50 0.75
Time (hours)
1.00
1.25
Figure 1 Free chlorine loss in the presence of CP at pH 8.5. [CP]0 = 0.5 |jM, [CO3]x = 10
mM, Temperature = 25 °C, and [HOC1]T = 10, 50, 100 |_tM.
23
-------
OP Pesticide Degradation under DW Conditions
1 J(J
125 -
-
100 *
=7 75 -
O
O
SO 1
25 -
1
n -
• [HOCl]T=10uM
• [HOC1]T = 50 nM
A [HOCl]T=100uM
' A A i •
* —A A A A
h
*
0.0
0.5
1.0 1.5
Time (hours)
2.0
Figure 2 Free chlorine loss in the presence of CP at pH 9. [CP]0 = 0.5 (jM,
Temperature = 25 °C, and [HOC1]T = 10, 50, 100
2.5
=10 mM,
24
-------
OP Pesticide Degradation under DW Conditions
150
125 -
100
=7 75 -
O
o
50
25 -
0.0
0.5
[HOCl]T=10uM
[HOC1]T = 50 uM
[HOCl]T=100uM
1.0 1.5
Time (hours)
2.0
2.5
Figure 3 Free chlorine loss in the presence of CP at pH 10. [CP]0 = 0.5 |_tM, [CO3]T = 10
mM, Temperature = 25 °C, and [HOC1]T = 10, 50, 100 |_tM.
25
-------
OP Pesticide Degradation under DW Conditions
150
125 -
100
=7 75 -
O
o
50
25 -
[HOCl]T=10uM
[HOC1]T = 50 uM
[HOCl]T=100uM
012345
Time (hours)
Figure 4 Free chlorine loss in the presence of CP at pH 11. [CP]0 = 0.5 |_tM, [CO3]T = 10
mM, Temperature = 25 °C, and [HOC1]T = 10, 50, 100 |_tM.
26
-------
OP Pesticide Degradation under DW Conditions
-3.0
0.00 0.05 0.10 0.15 0.20 0.25
Time (hours)
0.30
Figure 5 Observed first order loss of CP as a function of free chlorine at pH 6.36. [CP]
0.5 nM, [PO4]T = 10 mM, Temperature = 25 °C, and [HOC1]T = 10, 50, 100
27
-------
OP Pesticide Degradation under DW Conditions
[HOCl]T=10uM
• [HOC1]T = 50
A [HOCrjT=100uM
-1.2
0.00 0.05
0.10 0.15 0.20
Time (hours)
0.25
0.30
0.35
Figure 6 Observed first order loss of CP as a function of free chlorine at pH 7.5. [CP]0 = 0.5
, [PO4]T = 10 mM, Temperature = 25 °C, and [HOC1]T = 10, 50, 100
28
-------
OP Pesticide Degradation under DW Conditions
fin
L^
fi
[HOCl]T=10uM
[HOC1]T = 50
[HOCl]T=100uM
-0.5 -
-1.0 -
-1.5 -
-2.0 -
-2.5 -
0.0
0.2
0.4
Time (hours)
0.6
0.8
Figure 1 Observed first order loss of CP as a function of free chlorine at pH 8.5. [CP]0 = 0.5
, [CO3]T = 10 mM, Temperature = 25 °C, and [HOC1]T = 10, 50, 100 \\M.
29
-------
OP Pesticide Degradation under DW Conditions
0.0
[HOCl]T=10uM
• [HOC1]T = 50
A [HOCl]T=100uM
-3.5
0.0
0.5
1.0
1.5 2.0
Time (hours)
2.5
3.0
3.5
Figure 8 Observed first order loss of CP as a function of free chlorine at pH 8.75. [CP]
0.5 nM, [CO3]T = 10 mM, Temperature = 25 °C, and [HOC1]T = 10, 50, 100
30
-------
OP Pesticide Degradation under DW Conditions
fin
L^
fi
[HOClJT=10uM
[HOC1]T = 50 uM
[HOCl]T=100uM
-0.5 -
-1.0 -
-1.5 -
-2.0 -
-2.5 -
-3.0
0.0
0.5
1.0 1.5
Time (hours)
2.0
2.5
Figure 9 Observed first order loss of CP as a function of free chlorine at pH 9. [CP]0 = 0.5
, [CO3]T = 10 mM, Temperature = 25 °C, and [HOC1]T = 10, 50, 100
-------
OP Pesticide Degradation under DW Conditions
-0.2 -
-0.4 -
^o -0.6 -
fin
o
fin
O
£ -i.o :
-1.2 '-_
-1.4 :
-1.6
-0.8 -
[HOCl]T=10uM
[HOC1]T = 50 |aM
[HOCl]T=100|aM
0.0
0.5
1.0 1.5
Time (hours)
2.0
2.5
Figure 10 Observed first order loss of CP as a function of free chlorine at pH 10. [CP]0 = 0.5
, [CO3]T = 10 mM, Temperature = 25 °C, and [HOC1]T = 10, 50, 100 \\M.
32
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OP Pesticide Degradation under DW Conditions
0.0
o -0.6 :
fin
O
[HOCl]T=10|jM
[HOC1]T = 50
[HOCl]T=100nM
012345
Time (hours)
Figure 11 Observed first order loss of CP as a function of free chlorine at pH 11. [CP]0 = 0.5
, [CO3]T = 10 mM, Temperature = 25 °C, and [HOC1]T = 10, 50, 100
33
-------
OP Pesticide Degradation under DW Conditions
0.4
0.2 -
0.0 -
-0.2 -
I -04H
-0.6 -
-0.8 -
-1.0
y(x)=1.103(x)-5.351 r = 0.998
3.8 4.0 4.2 4.4 4.6
-log [HOC1]T
4.8
5.0
5.2
Figure 12 Reaction order of free chlorine with CP at pH 8.5. [CP]0 = 0.5 |iM, [CO3]T = 10
mM, Temperature = 25 °C, and [HOC1]T = 10, 50, 100
34
-------
OP Pesticide Degradation under DW Conditions
0.8
0.6 -
0.4 -
00
•? 0.0-
-0.2 -
-0.4 -
-0.6
y(x) = 1.006(x) - 4.408 r = 0.994
.8 4.0 4.2 4.4 4.6
-log [HOC1]T
4.8
5.0
5.2
Figure 13 Reaction order of free chlorine with CP at pH 9.0. [CP]0 = 0.5 |iM, [CO3]T = 10
mM, Temperature = 25 °C, and [HOC1]T = 10, 50, 100
35
-------
OP Pesticide Degradation under DW Conditions
1.2
oo
o
1.0 -
0.8 -
0.6 -
0.4 -
0.2 -
0.0
y(x) = 0.927(x) - 3.622 r = 0.993
3.8 4.0 4.2 4.4 4.6 4.8 5.0 5.2
-log [HOC1]T
Figure 14 Reaction order of free chlorine with CP at pH 10. [CP]0 = 0.5 |iM, [CO3]T = 10
mM, Temperature = 25 °C, and [HOC1]T = 10, 50, 100 |iM.
36
-------
OP Pesticide Degradation under DW Conditions
1.6 -
1.4 -
/"~«> 1 9 -
£
00
•? 1.0 -
0.8 -
0.6 -
0.4
y(x)= 1.087(x)-3.755 r2 = 0.989
3.8 4.0 4.2 4.4 4.6
-log [HOC1]T
4.8
5.0
5.2
Figure 15 Reaction order of free chlorine with CP at pH 11. [CP]0 = 0.5 |iM, [CO3]T = 10
mM, Temperature = 25 °C, and [HOC1]T = 10, 50, 100 |iM.
37
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OP Pesticide Degradation under DW Conditions
Figure 16
25
50 75
[HOCl]TxlO"6(M)
100
125
Apparent second order reaction rate coefficient for CP in the presence of free
chlorine at pH 6.36. [CP]0 = 0.5 |iM, [PO4]T = 10 mM, Temperature = 25 °C, and
[HOCl]x =10, 50, 100 |jM. 95% confidence intervals about the regression line
shown.
38
-------
OP Pesticide Degradation under DW Conditions
75
50 -
25 -
y(x) = 4.87 x 105(x) - 0.76 r2 = 0.99
25
50 75
[HOCl]TxlO'6(M)
100
125
Figure 17 Apparent second order reaction rate coefficient for CP in the presence of free
chlorine at pH 7.5. [CP]0 = 0.5 |iM, [PO4]T = 10 mM, Temperature = 25 °C, and
[HOCl]x =10, 50, 100 |jM. 95% confidence intervals about the regression line
shown.
39
-------
OP Pesticide Degradation under DW Conditions
15
10 -
5 -
y(x) = 1.07 x 105(x) - 0.23 r = 0.98
25
50 75
[HOCl]TxlO'6(M)
100
125
Figure 18
Apparent second order reaction rate coefficient for CP in the presence of free
chlorine at pH 8.5. [CP]0 = 0.5 |iM, [PO4]T = 10 mM, Temperature = 25 °C, and
[HOCl]x =10, 50, 100 |jM. 95% confidence intervals about the regression line
shown.
40
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OP Pesticide Degradation under DW Conditions
7.5
y(x) = 6.49 x 104(x) - 0.05 r2 = 1.00
5.0 -
2.5 -
25
50
75
100
125
-6
[HOCl]TxlO"°(M)
Figure 19 Apparent second order reaction rate coefficient for CP in the presence of free
chlorine at pH 8.75. [CP]0 = 0.5 |iM, [CO3]T = 10 mM, Temperature = 25 °C, and
[HOC1]T =10, 50, 100 |jM. 95% confidence intervals about the regression line
shown.
41
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OP Pesticide Degradation under DW Conditions
5.0
y(x) = 3.28 x 104(x) - 0.03 r2 = 0.99
2.5 -
25
50
75
[HOCl]TxlO'6(M)
100
125
Figure 20 Apparent second order reaction rate coefficient for CP in the presence of free
chlorine at pH 9. [CP]0 = 0.5 |iM, [CO3]T = 10 mM, Temperature = 25 °C, and
[HOCl]x =10, 50, 100 |jM. 95% confidence intervals about the regression line
shown.
42
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OP Pesticide Degradation under DW Conditions
1.5
1.0 -
0.5 -
y(x) = 7.71 x 103(x) + 0.03 r2 = 0.99
25
50
75
-6
[HOCl]TxlO"°(M)
100
125
Figure 21 Apparent second order reaction rate coefficient for CP in the presence of free
chlorine at pH 10. [CP]0 = 0.5 |iM, [CO3]T = 10 mM, Temperature = 25 °C, and
[HOC1]T =10, 50, 100 |jM. 95% confidence intervals about the regression line
shown.
43
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OP Pesticide Degradation under DW Conditions
0.3
0.2 -
0.1 -
0.0
y(x) = 1.97 x 103(x) + 0.03 r2 = 0.99
25
50
75
-6
[HOCl]TxlO"°(M)
100
125
Figure 22 Apparent second order reaction rate coefficient for CP in the presence of free
chlorine at pH 11. [CP]0 = 0.5 |iM, [CO3]T = 10 mM, Temperature = 25 °C, and
[HOC1]T =10, 50, 100 |jM. 95% confidence intervals about the regression line
shown.
44
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OP Pesticide Degradation under DW Conditions
2.0xl06
1.5xl06 -
l.OxlO6 -
SOO.OxlO3 -
0.0
10
11
12
pH
Figure 23 The pH dependence of the apparent second order rate constant for the reaction of
free chlorine with CP. [CP]0 = 0.5 |iM, [Buffer]T = 10 mM, Temperature =
25±1°C, and [HOC1]T = 10, 50, and 100 |iM. Error bars represent 95% confidence
intervals.
45
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OP Pesticide Degradation under DW Conditions
400
350
300
^ 250
Us
1= 200
X
^ 150 -
100 :_
50 :
kobs (experimental)
k = k +
h N,CPO
(model)
6
pH
10 11
12
Figure 24
Experimental and model predictions for the first order observed hydrolysis of CPO
over the pH range of 1-11. [CPO]0 = 0.5 |jM, [Buffer]T = 10 mM, and Temperature
= 25±1°C,. Error bars represent 95% confidence intervals and the line represents
model results.
46
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OP Pesticide Degradation under DW Conditions
0.7
0.6 -
0.5 -
• pH 9.0
O pH 10.9
y(x) = 1360.43(x) + 0.21 r2 =
0
50
100
150
200
250
300
[HOC1]T i
Figure 25 Second order rate coefficient for chlorine assited hydrolysis of CPO at pH 9 and
10.9. [CPO]0 = 0.5 nM, [CO3]T = 10 mM, Temperature = 25±1°C, and [HOC1]T :
0 - 250 |jM. Error bars represent 95% confidence intervals.
47
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OP Pesticide Degradation under DW Conditions
CP
/O-CH2— CH
CYV° ^°-CH-CH3
cr^^ci
HOC1
CPO
oxidation
CK^N^O o-
cr^^ci
H+ + C1 +S
/"'TT /"'TJ
^,±17 L,±lll
HOC1
H,O, OH , or OC1
H2O, OH , or OC1
S042
hydrolysis |1 TCP
Figure 26 Simplified schematic of chlorpyrifos degradation pathways in the presence of
chlorine at near neutral and alkaline pH.
48
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OP Pesticide Degradation under DW Conditions
0.5
fin
o
H
0.4 -
0.3 -
0.2 -
0.1 -
0.0
• [HOC1]T = 0
D [HOCl]T=10|_iM
A [HOC1]T = 25
O [HOC1]T = 50
• [HOC1]T=
A [HOC1]T= ISO^M
Time (hours)
Figure 27 TCP experimental and model results for the loss of CP in the presence of free
chlorine at pH 11 . [CP]0 = 0.35 |iM, [CO3]T = 10 mM, Temperature = 25±FC,
and [HOCl]x = 0-150 |jM. Lines represent model results.
49
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OP Pesticide Degradation under DW Conditions
0.00
0.0
0.1
0.2 0.3 0.4
Time (hours)
0.5
0.6
Figure 28 CP degradation in the presence of free chlorine at pH 7.15. [CP]0 = 0.33
[CO3]T = 1 mM, Temperature = 25±FC, and [HOC1]T = 20 |iM. Lines represent
model results and error bars are 95% confidence intervals.
50
-------
OP Pesticide Degradation under DW Conditions
o
O
O
O
0.0
Figure 29
1234567
Time (hours)
CP degradation in the presence of free chlorine at pH 9.0. [CP]0 = 0.5 |jM,
= 1 mM, Temperature = 25±1°C, and [HOCl]x = 10 |jM. Lines represent model
results and error bars are 95% confidence intervals.
51
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