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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
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