Development of the Environmental Fate Simulator (EFS): A

tool for predicting the degradation pathways of organic

chemicals in groundwater aquifers

Process

Scientists:

Caroline Stevens

Said Hilal

Software

Engineers:

Kurt Wolfe

Rajbir Parmar

Ecosystems Research

Division

US Environmental

Protection

Caroline Stevens

Said Hilal

Dalizza Colón

Jack Jones

Eric Weber

Rajbir Parmar

Mike Galvin

Mitch Pelton

(PNNL)Multi-Media Modelers:

Gene Whelan

Justin Babendreier

US Environmental

Protection

Athens, GA

The EFS will be

publicly

available

What is the need for the

Environmental Fate Simulator?

Our Response:

Development of the Environmental

Fate Simulator (EFS):

• High throughput computational

system for providing molecular

and environmental descriptors for

consumption by EF&T models

The Problem:

Current tools available to EPA for

conducting exposure and health

(human and ecological) assessments

are not adequate:

• TSCA inventory :

− > 85,000 chemicals consumption by EF&T models

Requires:

� Knowledge of the process science

controlling chemical fate and

transport

� The ability to encode this

information into a readable format

� Integration of existing

cheminformatics applications and

modeling software technologies

− > 85,000 chemicals

− High quality data for < 2%

• New Chemicals (PMN Program):

− 20 to 30 new chemicals per

week

• FIFRA inventory:

− ~ 1,100 agrochemicals

− High quality pchem data for

nearly 100%

• Knowledge of the process

science underlying

transformation pathways

Chemical Structure of

Parent Chemical Cheminformatics

applications for encoding

the process science

Exposure/Testing

Scenario:

What is needed to

automate this process:

What is it that requires automation?

The information required

to simulate this scenario:

transformation pathways

• Molecular descriptors

necessary for predicting

mobility and reaction rates

• Environmental descriptors

necessary for predicting

reaction rates

• Parameritization of EF&T

models

Reaction

Medium

Estimated Concentrations of

the Parent Chemical and

Predicted Transformation

Products

Access to physico-chemical

calculators

Software for providing

access to data from

online databases

the process science

Software providing

seamless

parameritization of

EF&T models

The EFS represents the integration of the most robust process

science available with state-of-the-art cheminformatics

application and modeling software technologies

Process

science

Java-based

cheminformatics

applications Modeling software technologies

developed through ERD-Athens

Integrated Environmental

Modeling (IEM) Program

5

Modeling (IEM) Program

EFS

Cheminformatics:

the generation, storage, indexing and

search of information relating to chemical

structure and chemical processes

Example of an EFS Workflow

Chemical Editor (CE):

Provides options for

chemical entry

Reaction Pathway

Simulator (RPS):

Generates potential

transformation products

based on user-specified

conditionsPhysicochemical

Properties Calculator

(PPC):

Molecular descriptors

Structure-based Database

(SBD): Molecular descriptors

for the parent chemical

and predicted

transformation products

(SBD):

populated with calculated

and measured physico-

chemical properties of

parent and potential

transformation products

Earth Systems

Model: Data

Mining for

environmental

descriptors

Reaction Rate

Calculator:

Parameritization and

Execution of QSARs

and Algorithms

Tautomer Identification/distribution

MarvinSketch: Calculation of pKa values

The selection of the environmental

conditions will determine which reaction

libraries will be executed in the Reaction

Pathway Simulator

Reaction Libraries consisting of one-

step reactions and reaction rules for

various transformation pathways:

Chemical Processes:

• Reduction

• Hydrolysis

• Photolysis

Biological Processes:

• Aerobic Biotransformation

• Anaerobic Biotransformation

UM-Pathway Prediction System (UM-PPS)• Web-based system for the prediction of microbial biotransformation

Database

(http://umbbd.ethz.ch)

Prediction System

(http://umbbd.ethz.ch/predict)

11

MarvinSketch: Translation of

chemical structures into a

readable code

Encoding the Process Science

NH2

12

O=N(=O)C1=CC=CC=C1

SMART Reaction String

SMILES String

O=N(=O)C1=CC=CC=C1>>NC1=CC=CC=C1

Development of

Reaction

Libraries based

on Chemical

Terms Language

Abiotic Reductions:Abiotic Reductions:

Data Sources:

• Peer-reviewed

literature

• Registration data

submitted to EPA

Implementing the Reaction Libraries

Functional group transformation

based on execution of reaction

libraries

X

Encoding the Process Science

Product formation

based on the

execution of the

15

execution of the

reduction library

Likelihood: Likely

Generation: 95%

Accumulation: 10%

Prototype EFS: Environmental Systems Model

Environmental Descriptor collection

for site-specific assessments

Environmental Descriptor collection through

the executions of Data for Environmental

Modeling (D4EM):

an open source software system consisting of a

library of utilities that can be used to access,

retrieve and process model data automatically

from sources on the internet

Access the necessary databases for the

collection of the required environmental

descriptors (e.g., pH, aqueous Fe(II) and (DOC))

AquiferFlow Path

Primary Redox Reactions

Intrusion of Dissolved Organic Matter

Identifying Predominant Chemical

Reductants Anaerobic Aquifers and

Sediments

Aerobic NitrateReducing

Manganese Reducing

IronReducing

SulfateReducing

Methanogeni c

Corg CO2

O2 H2O

Corg HCO3-

NO3- N2

Corg HCO3-

MnO2 Mn2+

Corg HCO3-

Fe(OH)3 Fe2+

Corg HCO3-

SO42- H2S

Corg HCO3

CH4

Working Hypothesis: The reactivity of chemical reductants in natural sediments will

vary as a function of redox zonation as described by the dominant terminal electron

accepting processes (TEAPs)

Formation of Potential Chemical Reductants

as a Function of Redox Zonationu

cin

g

Complexation

Chemical Reductants

Mineral Formation Redox (DOM)

C

O

O

Fe2+O

Fe2+ Fe2+ + HCO32- FeCO3 + H+

Green Rust Formation

O O

e-, H+

Red

ox

Zo

nes

Met

han

og

enicF

e R

edu

Su

lfat

e R

edu

cin

g

OFe

2+

Surface Solution Phase

Fe3+

O Green Rust Formation

[Fe42+Fe23+(OH)12]2+ [CO3 nH2O]

[Fe42+Fe23+(OH)12]2+ [SO4 nH2O]2

[Fe2+Fe3+(OH)8+ [Cl nH2O]-

Fe2+ + HS- FeS + H+

FeS + So FeS2+ H2S

O

O OH

OH

SH

O OH

e , H+

Group A — Laboratory Transport Test Guidelines

835.1230 - Adsorption/Desorption (Batch Equilibrium) (November 2008)835.1240 - Leaching Studies (November 2008)835.1410 - Laboratory Volatility (November 2008)

Group B — Laboratory Abiotic Transformation Test Guidelines835.2120 - Hydrolysis (November 2008)835.2130 - Hydrolysis as a Function of pH and Temperature (January 1998)835.2210 - Direct Photolysis Rate in Water by Sunlight (January 1998))

OCSPP Harmonized* Test Guidelines

Series 835 - Fate, Transport and

Transformation Test Guidelines

*Harmonized OPPT, OPP and OECD Test guidelines

Environmental conditions

can also be entered by the

user through selection of the

appropriate test OECD test

guideline

835.2210 - Direct Photolysis Rate in Water by Sunlight (January 1998))835.2240 - Photodegradation in Water (November 2008)835.2410 - Photodegradation in Soil (November 2008)835.Weber- Reduction

Group C — Laboratory Biological Transformation Test Guidelines

Group D —Transformation in Water and Soil Test Guidelines835.4100 - Aerobic Soil Metabolism / 835.4200 – Anaerobic Soil Metabolism (October 2008)835.4300 - Aerobic Aquatic Metabolism / 835.4400 – Anaerobic Aquatic Metabolism (October 2008)

Group E — Transformation Chemical-Specific Test Guidelines835.5045 - Modified SCAS Test for Insoluble and Volatile Chemicals (January 1998)835.5154 - Anaerobic Biodegradation in the Subsurface (January 1998)835.5270 - Indirect Photolysis Screening Test: Sunlight Photolysis in Waters Containing Dissolved Humic Substances (January 1998)

Prototype EFS: Physico-Chemical Properties Calculator

The number of required calculated

data for a given physico-chemical data for a given physico-chemical

property is based on its intended use

Chemical Specific Parameters

Abbrev Units MeasuredCalculated

(EPI Suite)

Calculated(SPARC)

Calculated(ChemAxon)

Calculated(QSAR)

3-nitro-5-oxo-1,4-dihydro-1,2,4-triazol-1-ide major species

at pH 7.5

O

O

N

ONH

NHN

EPI Suite

– Fragment based

SPARC

– Mechanistic based

Physico-Chemical Properties CalculatorGoal:

•Provide complete

coverage

•Consensus approach

Suite)Molecular Weight MW g/mole

Melting Point MP oC

Boiling PointBP

oC

Water Solubility WS mg/LVapor Pressure VP torr

Molecular diffusivity in water

cm2/sec

Ionization constant pKa unitlessHenry’s Law

ConstantAtm

m3/moleOctanol Water

Partition Coefficient

Kow mL/g

Organic Carbon Partition

CoefficientKoc mL/g

Distribution Coeffecient

(pH dependentKD

mL/g

– Mechanistic based

ChemAxon

– Atom based

Available

Not Available

Chemical Specific

22

Calculation of P-Chem Data Base Based on Consensus Approach

SPARC EPIsuite EPIsuite ChemAx ChemAx ChemAx AVERAGE

Braekevelt et al

(2003)

calculated calculated measured KLOP PHYS VG calculated measured

Name log Kow log Kow log Kow log Kow log Kow log Kow log Kow

PBDE-28 6.46 5.88 ---- 5.97 5.51 5.85 5.94 5.94

PBDE-47 7.14 6.77 ---- 6.76 6.25 6.64 6.71 6.81

PBDE-66 7.22 6.77 ---- 6.76 6.25 6.64 6.73

PBDE-85 7.96 7.66 ---- 7.54 6.98 7.43 7.51 7.37

PBDE-99 7.92 7.66 6.84 7.54 6.98 7.43 7.51 7.32

PBDE-100 7.95 7.66 ---- 7.54 6.98 7.43 7.51 7.24

PBDE-138 8.74 8.55 ---- 8.32 7.71 8.23 8.31

PBDE-153 8.71 8.55 ---- 8.32 7.71 8.23 8.30 7.90

PBDE-154 8.73 8.55 ---- 8.32 7.71 8.23 8.31 7.82

• Structure

Searching

• Data

Analysis

Provide structure

PBDE-154 8.73 8.55 ---- 8.32 7.71 8.23 8.31 7.82

PBDE-183 9.52 9.44 ---- 9.10 8.44 9.02 9.10 8.27

PBDE-209 12.01 12.11 ---- 11.45 10.64 11.39 11.52

SSE = 4.638 2.706 1.297 0.915 0.923 1.237

5.0

5.5

6.0

6.5

7.0

7.5

8.0

8.5

9.0

9.5

10.0

5.0 6.0 7.0 8.0 9.0

Ca

lcu

late

d l

og

Ko

w

Measured log Kow

SPARC

EPIsuite

ChemAxon KLOP

ChemAxon PHYS

ChemAxon VG

y = x

Compound class KOWWIN SPARC VG KLOP PHYS ALOGP XLOGP2 XLOGP3-AA

PBDEs 0.58 0.76 0.34 0.40 0.34 0.25 0.38 0.39

Phthalate esters 0.78 0.40 0.48 0.79 0.54 0.53 1.17 0.79

PCBs 0.76 0.87 0.57 0.72 0.71 0.73 0.77 0.65

Calculation of P-Chem Data Base Based on Consensus Approach

PCBs 0.76 0.87 0.57 0.72 0.71 0.73 0.77 0.65

Fused ring

structures

0.29 0.41 0.74 0.85 0.93 1.24 0.36 0.37

Others 0.31 0.86 1.51 0.87 0.61 1.19 1.32 1.09

ALL 0.58 0.74 0.94 0.75 0.64 0.90 0.96 0.78

Root mean square error (RMSE) for log Kow calculated by selected models

Results of Consensus Approach for poorly soluble chemicals

Ability to populate and

execute QSARs for

calculating rate constants

2.15

Reaction Rate Calculator:

Parameritization and Execution of

QSARs and Algorithms

DNAN

QSAR based on irreversible sorption of mono-

substituted anilines in aerobic sediment

5.71

2.98

3.03

Temperature:

aE

RTk Ae−

=

Sorption:

where A is the frequency factor or pre-

exponential factor and Ea is the activation

energy (Default value for Ea = 50 kJ/mol)

Reaction Rate

Calculator:

Parameritization and

Execution of QSARs

and Algorithms

Correcting for environmental

conditions

( )1appd

kk

Kρ=

+

Sorption:

where k is the first-order rate constant for

transformation in the aqueous phase, (Kd) is the

sorption coefficient and ρ is the solid-to-

solution ratio

, , ,

1 10

1 10 1 10

a

a a

pH pK

d app d HApH pK pH pK d AK K K −

−

− −

= + + +

where pKa is the negative of the logarithm

of the acid dissociation constant for the

chemical

Ionization :

Required Hallmarks of the EFS:

� Vibrant

– Representing the most current process science and software

technologies available

� Transparent

– Presentation of the meta data

� High Throughput capability

– Relatively short run times

– Allows for operation in batch mode

� Accessible

– Web-based

� Usable

– Reasonable run times

– User friendly

� Flexible

– Customized for the user’s need

� Quality Controlled

– Based on peer-reviewed science