MODELS-DATABASES

MODELS

The downloadable materials included on this website are provided to interested parties at no cost; however, to download any material you need to first request a password by sending an e-mail with your name and affiliation and download of interest to Jon Arnot. The registration information also provides us with contact information so that we can send notifications for model updates. The models are updated occasionally to address potential errors and “bugs in the code” and to reflect scientific advancements.

The most recent versions of the models and databases are most relevant since they include updates and possibly corrections to previous versions. Users are strongly encouraged to read the associated papers listed with the models and the “help” and “about” information accompanying the models (when included) before using them. Excel spreadsheet are expected to work using Microsoft Office or other similar programs (Note: Visual Basic for Applications support is often required).

For more information about these models and databases please contact Jon Arnot.

Limitations of liability and disclaimer of warranty
ARC Arnot Research & Consulting Inc. and all associated collaborators do not guarantee, warrant, or make any representations, either expressed or implied, regarding the use, or the results of the use of the materials provided with regards to reliability, accuracy, correctness, or otherwise. There are no warranty rights granted to users of the models or databases provided.

Users assume the entire risk as to the results and performance of the models and databases. ARC Arnot Research & Consulting Inc. and all associated collaborators are not liable under any circumstances, for any damages whatsoever, arising out of the use, or the inability to use, the models and databases provided, even if advised of the possibility of such damages.

jon@arnotresearch.com

The Bioaccumulation Assessment Tool (BAT)
The Bioaccumulation Assessment Tool (BAT) facilitates the systematic and transparent integration of information in a consistent framework to inform bioaccumulation assessment decision-making.

The BAT is a user-friendly spreadsheet-based tool to guide the collection, generation, evaluation, and integration of various lines of evidence (LOE) to aid bioaccumulation assessment decision-making for aquatic and terrestrial organisms.  The BAT provides a consistent Quantitative Weight of Evidence (QWOE) approach that includes critical evaluations of data confidence. The BAT can provide guidance for integrated testing strategies should further information be necessary for decision-making.

Chemicals are being assessed for bioaccumulation (B) potential using various LOEs, methods, metrics and classification criteria.  In vivo laboratory-based lines of evidence include the bioconcentration factor (BCF) and biomagnification factor (BMF).  In vitro biotransformation rate data (S9, hepatocytes) can also be applied for “B” assessment using in vitro-in vivo extrapolation (IVIVE) methods.  Field-based LOEs include the BMF, bioaccumulation factor (BAF), and the Trophic Magnification Factor (TMF). In silico LOEs include quantitative structure-activity relationships (QSARs) for the BCF and the biotransformation rate constant (kB) and mass balance bioaccumulation (toxicokinetic) models.

The BAT was developed with stakeholder involvement including representatives from academia, government and industry with research support from        Cefic-LRI. The BAT is implemented (coded) in Visual Basic for Applications (VBA) and the Graphical User Interface is designed in Excel™. The BAT User Manual and Quick Start Guide are embedded as pdfs within the Excel file. This Quick Start Guide can be considered to expedite the use of the BAT; however, all BAT users are strongly encouraged to read the User Manual before using the BAT. A recent presentation of the BAT system given to stakeholders is available here.

How to Cite:

– Armitage JM, Toose L, Embry M, Foster KL, Hughes L, Arnot JA. 2018. The Bioaccumulation Assessment Tool (BAT) Version 1.0. Developed by ARC Arnot Research and Consulting Inc., Toronto, ON, Canada

BAT Ver.1.0 was publicly released October 2018.

If you have not done so, fill out the Form here . You will be emailed a password that will allow you access to the model you requested.

NOTE:

The BAT will only function properly on a Windows operating system. The computer must use the period (.) as the decimal separator rather than the comma (,) to ensure accurate results. Reconfiguration guidance is provided in the User Manual.

An introductory video demonstration is available here.

Please provide feedback on your experience using the BAT and/or report any “bug or crash” issues you may experience here.

RAIDAR (Risk Assessment, Identification And Ranking ) model
RAIDAR is an evaluative, regional-scale, mass balance model for screening level exposure and risk assessment. The model simulates chemical fate and transport in the environment, bioaccumulation in a range of species, food web bioaccumulation, far-field exposures to humans and representative ecological species, and effects (risk). The general intent of the model is to screen and prioritize large numbers of chemicals based on hazard, exposure and risk assessment objectives for more comprehensive, higher-tiered assessments.

RAIDAR has been used for high-throughput risk assessments for Environment Canada to address legislation outlined under the Canadian Environmental Protection Act 1999. The RAIDAR model has been used in regulatory programs in Canada and is part of the US EPA’s ExpoCast System for the Empirical Evaluation of Models (SEEMS) human exposure framework (https://www.epa.gov/chemical-research/rapid-chemical-exposure-and-dose-research).

Full details of the model are available in the following publications:

– Arnot, J.A.; Mackay D. 2008. Policies for chemical hazard and risk priority setting: Can persistence, bioaccumulation, toxicity and quantity information be combined? Environ. Sci. Technol. 42: 4648-4654. DOI: 10.1021/es800106g

– Arnot, J.A.; Mackay, D.; Webster, E.; Southwood, J. 2006. Screening level risk assessment model for chemical fate and effects in the environment. Environ. Sci. Technol. 40: 2316-2323. DOI: 10.1021/es0514085

If you have not done so, fill out the Form here .

You will be emailed a password that will allow you access to the model you download below.

Download RAIDAR Ver.2.00 (Released March 2012)

Download RAIDAR Ver.2.01 (Released July 2012 to address a minor display error in Ver.2.00)

Download RAIDAR Ver.2.02 (Released 2014 to address .csv output error for Level II environmental fugacities)

RAIDAR Ver.3.0 (Coming Soon)

Risk Assessment, Identification And Ranking – Indoor Consumer Exposure (RAIDAR-ICE) model
RAIDAR-ICE is a versatile, efficient tool for screening and prioritization of neutral organic chemicals based primarily on near-field direct and indirect exposure pathways and associated potential human health concerns. The model development aims to balance the complexity of processes related to assessing human exposure and potential risk with data availability at a screening-level for thousands of chemicals.

RAIDAR-ICE builds onto the ICECRM mass balance framework. Both models contain an indoor chemical fate module, which describes a generic, evaluative indoor environment consisting of seven compartments (indoor air, polyurethane foam, carpet, vinyl floor, and organic films on vertical, up-facing and down-facing surfaces). In addition, the models include a PBTK model comprising compartments for (i) hand skin surface, (ii) the remaining skin surface on the body, and (iii) the human body. This toxicokinetic model describes the adsorption, metabolism (biotransformation) and elimination (exhalation, renal excretion, fecal egestion, skin desquamation) processes of chemicals and is parameterized here for a representative male adult. Whereas ICECRM considers only human exposure to chemicals released into physical compartments of the simulated indoor environment and subsequent indirect exposures, RAIDAR-ICE additionally includes the capacity for direct chemical applications to the body within the mass balance equations. Far-field exposure estimates (i.e., intake rates from water, food, outdoor air) can be used as input to the RAIDAR-ICE model for aggregate exposure assessment. RAIDAR-ICE also inherits concepts from the RAIDAR model. Most notably, the calculated human exposure is combined with user-defined toxicity (hazard) data to derive risk-based assessment endpoints and critical emission rates.

RAIDAR-ICE is part of the US EPA’s ExpoCast System for the Empirical Evaluation of Models (SEEMS) human exposure framework (https://www.epa.gov/chemical-research/rapid-chemical-exposure-and-dose-research).

RAIDAR-ICE Ver.1.0 (Coming Soon)

Indoor Chemical Exposure Classification/Ranking Model (ICECRM)
The Indoor Chemical Exposure Classification/Ranking Model (ICECRM) is a steady-state model for the screening-level assessment of near-field human exposure to neutral organic chemicals released indoors. ICECRM adopts an existing multimedia indoor chemical fate model and couples it with exposure routes to humans and a human toxicokinetic model. Modifications of the indoor chemical fate model include (1) a particle mass balance, (2) consideration of the orientation of indoor surfaces; and (3) allowing for the possibility of human feedback on the chemical mass balance in the indoor environment. The human model includes three compartments (hand skin surface, rest of body skin surface, rest of the human body). The first two compartments are separated from the main body because chemicals on hands and skin surfaces contribute to human exposure indoors via hand-to-mouth transfer and dermal permeation, respectively. By considering human feedback on the overall indoor mass balance, the model probes how human intake and elimination (biotransformation, renal clearance) impacts its overall fate indoors.

The ICECRM model considers the following “indirect” chemical exposure pathways to humans: 1) inhalation of gaseous and particulate chemicals in indoor air, 2) non-dietary ingestion of dust and through hand-to-mouth contact following indoor surface contact, and 3) dermal permeation. The model equations, formulated in fugacity notation and programmed in Visual Basic for Application (VBA) in Excel™, quantify chemical transport, degradation, distribution and exposure processes for up to 10,000 chemicals at a time. Full details of the model are available in the following publication:

– Zhang, X.M.; Arnot, J.A.; Wania, F. 2014. A model for screening-level assessment of near-field human exposure to neutral organic chemicals released indoors. Environ. Sci. Technol. 48 (20), pp 12312–12319 DOI: 10.1021/es502718k

The ICECRM model is implemented (coded) in Visual Basic for Applications (VBA) and the Graphical User Interface is designed in Excel™. A User Manual is embedded within the Excel file. The ICECRM model will only function properly on a Windows operating system. The computer must use the period (.) as the decimal separator rather than the comma (,) to ensure accurate results.

Download ICECRM Ver.1.1

FHX (Far-field Human eXposure) model
FHX is an evaluative, regional-scale, mass balance model for screening level far-field human exposure assessment. The general objective of the FHX model is to provide information on far-field human exposures to chemicals by linking information on physical-chemical properties and chemical emissions to the environment with simulations for chemical fate in the physical environment (air, water, soil and sediment), food web bioaccumulation (including aquatic and agricultural food chains), and multimedia contact rates (inhalation of outdoor air, ingestion of drinking water and foodstuffs) for different human age classes representing the Canadian population.

The FHX model was co-developed with scientists at Health Canada and is currently parameterized using Health Canada Exposure Factor Data (ca. 1998) for seven age classes. The model calculates chemical intake rates and intake fractions.

Full details of the model are available in the following publications:

-Arnot JA, Mackay D, Sutcliffe R, Lo B. 2010. Estimating farfield organic chemical exposures, intake rates and intake fractions to human age classes. Environ Modell Softw 25:1166-1175.

Versions for Download: FHX Ver.1.11 (Released March 2012)

Download FHX Ver.1.11 

For earlier versions of the FHX model, please go the Canadian Centre for Environmental Modelling and Chemistry (CEMC) website
or 
contact Jon Arnot

FHX-CAN (Far-field Human eXposure in Canada) model
FHX-CAN is an evaluative, regional-scale, mass balance model for screening level far-field human exposure assessments in selected regional areas of Canada. The general objective of the FHX-CAN model is to provide information on far-field human exposures to chemicals by linking information on physical-chemical properties and chemical emissions to the environment with simulations for chemical fate in the physical environment (air, water, soil and sediment), food web bioaccumulation (including aquatic and agricultural food chains), and multimedia contact rates (inhalation of outdoor air, ingestion of drinking water and foodstuffs) for seven human age classes in five specific Canadian regions. The model calculates chemical intake rates and intake fractions.

The FHX-CAN model was developed for Health Canada and is based on the FHX model and includes regional environments from the ChemCAN model.

Most details of the model are available in the following publications:

– Arnot JA, Mackay D, Sutcliffe R, Lo B. 2010. Estimating farfield organic chemical exposures, intake rates and intake fractions to human age classes. Environ Modell Softw 25:1166-1175.

– Webster E, Mackay D, Di Guardo A, Kane D, Woodfine D. 2004. Regional differences in chemical fate model outcome. Chemosphere 55: 1361-1376.

Versions for Download:

FHX-CAN Ver.1.11 (Released March 2012)

Download FHX-CAN Ver.1.11 

In Vitro Mass Balance Model (IV-MBM)
Toxicity testing in the 21st Century is shifting towards more in vitro based experiments to obtain empirical data for different decision-making contexts, e.g., ToxCast, Tox21, Safety Evaluation Ultimately Replacing Animal Testing (SEURAT). Generally speaking, in vitro toxicity and bioactivity dose-response curves are reported using (initial) nominal concentrations in the test medium, i.e., the amount of chemical added divided by the volume of medium.  However, the use of nominal concentrations can be problematic for the interpretation and use of in vitro data for hazard and risk evaluations because nominal concentrations do not account for the behaviour of the chemical in the test system.

To address these concerns, the In Vitro Mass Balance Model (IV-MBM) was designed to simulate the distribution of neutral organic chemicals in the in vitro test systems based on i) the partitioning properties of the chemical and ii) the properties (e.g., volume fraction of serum albumin in the test medium) and dimensions of the in vitro test system. IV-MBM is being used by regulatory agencies (EPA, NTP) in the United States (e.g., Casey et al., Environ Health Persp 2018).   Full details of the model are available in the following publication:

– Armitage, J. M.; Wania, F.; Arnot, J. A. 2014. Application of mass balance models and the chemical activity concept to facilitate the use of in vitro toxicity data for risk assessment. Environ. Sci. Technol. 48, (16), 9770-9779. DOI: 10.1021/es501955g

Download IV-MBM Ver.3.0
Try the on-line version of IV-MBM Ver.3.0 here

AQUAWEB (Aquatic Food Web) model
AQUAWEB is a site-specific bioaccumulation model for aquatic food webs and provides estimates of chemical concentrations in organisms of aquatic food webs from chemical concentrations in the water and the sediment. The model is presented in rate constant format for assessing the bioaccumulation of non-ionic hydrophobic organic chemicals at steady-state.

For zooplankton, aquatic invertebrates and fish the model calculates rates of chemical uptake from the water and the diet and rates of chemical elimination to the water, feces and the “pseudo-loss” mechanism of growth dilution. Metabolic biotransformation rate data can also be included as a mechanism of chemical elimination (see database and the BCFBAF module of US EPA EPI Suite™). AQUAWEB is a modification of a previous food web model (Gobas 1993). The models are intended to estimate chemical concentrations and associated bioconcentration factors (BCF), bioaccumulation factors (BAF) and biota-sediment accumulation factors (BSAF) of non-ionic hydrophobic organic chemicals. The models are useful for assessing exposure and risks of chemicals in the water and sediment to organisms in aquatic ecosystems and higher trophic level organisms that eat aquatic species such as birds and mammals, including humans.

Both the Gobas 1993 and Arnot and Gobas 2004 models have been evaluated using empirical data from three different freshwater ecosystems involving 1,019 observations for 35 species and 64 chemicals and are coded in one Microsoft Excel™ workbook. The AQUAWEB model also forms the basis of the U.S. Environmental Protection Agency’s KABAM model used primarily for pesticide assessments.

Full details of the 2004 model are available in the following publication:

– Arnot JA, Gobas FAPC. 2004. A food web bioaccumulation model for organic chemicals in aquatic ecosystems. Environ Toxicol Chem 23(10): 2343–2355.

Versions for Download: For earlier versions of the AQUAWEB model please contact Jon Arnot.

Download AQUAWEB Ver 1.3

Bioconcentration for Ionizable Organics (BIONIC)
The BIONIC model estimates the bioconcentration factor (BCF, L/kg) of neutral organic and ionizable organic chemicals (IOCs) in fish and is an outcome of the CEFIC-LRI ECO21 project which ended in 2015. The main features and modelling approaches for the BIONIC model are described in Armitage et al. 2013.  In short, BIONIC is a modification of the Arnot and Gobas 2004 AQUAWEB model for neutral organic chemicals such that the model can be applied to IOCs as well.  The most important modifications are to the description of partitioning to phases in the organism (distribution ratios rather than partition coefficients) and to the gill uptake sub-model.  

The gill uptake model was revised in BIONIC V1 such that resistance to transport of the chemical across organic diffusion layers (i.e., membranes) is scaled by a factor driven by the ratio of the neutral to charged form of the chemical in the gill.  The gill uptake model from V1 was replaced with a new formulation in BIONIC V2 such that transport of the charged form of the chemical is explicitly considered in the model calculations. BIONIC V2 is recommended for simulating the BCFs of IOCs that lie at the extreme range of typical acidic and basic IOCs, i.e., organic acids with pKa < 3 and organic bases with pKa > 12. Full details of the model are available in the following publication:

– Armitage, J. M.; Arnot, J. A.; Wania, F.; Mackay, D. 2013. Development and evaluation of a mechanistic bioconcentration model for ionogenic organic chemicals in fish. Environ. Toxicol. Chem. 32, (1), 115–128. DOI: 10.1002/etc.2020

The BIONIC models are implemented (coded) in Visual Basic for Applications (VBA) and the Graphical User Interface is designed in Excel™. A User Manual is embedded within the Excel file. The BIONIC models will only function properly on a Windows operating system. The computer must use the period (.) as the decimal separator rather than the comma (,) to ensure accurate results.

Download BIONIC VER.1.0 
Download BIONIC VER.2.0 

San Francisco Bay Food Web Bioaccumulation model
This model was developed to assess the effects of PCBs in wildlife and fishermen in San Francisco Bay and to identify potential risk management actions. The objective of this model is to estimate the concentrations of PCBs in a set of key species that reside in the Bay as a result of PCB concentrations in sediments and water in the Bay. 

The species that are the main focus of the study are the double-crested cormorant (Phalacrocorax auritus), the Forster’s tern (Sterna Forsteri), and the harbor seal (Phoca vitulina richardsi), as well as three fish species that are frequently caught by fishermen in the Bay, i.e. shiner surfperch (Cymatogaster aggregata), jacksmelt (Atherinopsis californiensis) and white croaker (Genyonemus lineatus). The fish species are important end-points of the model because of their role in passing PCBs to fishermen. Double-crested cormorants, Forster’s terns and harbor seals are included in the model because they have been identified as sensitive receptors of PCBs.

The model can be used to determine what concentrations of PCBs in the water and sediments of the Bay need to be reached to achieve an adequate margin of safety in wildlife and humans exposed to PCBs in the Bay area. This information can be used as part of a Total Maximum Daily Loading (TMDL) characterization to formulate remedial actions to achieve desired water quality goals.

The model is in the form of a Microsoft Excel™ workbook.

General information on the model is available in the following publication:

– Gobas FAPC, Arnot JA. 2010. Food web bioaccumulation model for polychlorinated biphenyls in San Francisco Bay, California, USA. Environ Toxicol Chem 29:1385-1395.


For more information on this model please contact Jon Arnot or Frank Gobas.

Screening-level BCF and BAF models
This model provides screening-level estimates of the bioaccumulation factor (BAF) for generic fish species in lower, middle and upper trophic levels of aquatic food webs. The model also provides screening-level estimates of the bioconcentration factor (BCF) for water exposures only (i.e., in laboratory bioconcentration tests). The models require only the octanol-water partition coefficient (KOW) of the chemical and the metabolic biotransformation rate constant as input parameters (see database and the BCFBAF module of U. S. EPA’s EPI Suite™).

The BAF models are derived from the parameterization and calibration of a mechanistic bioaccumulation model to a large database of evaluated measured BAFs. The measured BAFs are for chemicals that are poorly metabolized and are grouped into lower, middle and upper trophic levels of fish species. The model is calibrated to each trophic level of measured BAF values thus providing estimates that are in general agreement with measured BAFs, thus capturing the overall food web biomagnification potential of chemicals in aquatic food webs for screening assessments.

The model is intended to estimate BCFs and BAFs for non-ionic organic chemicals only. Thus it provides generic estimates in absence of site-specific measurements or estimates. The model can be used to predict dietary concentrations for higher trophic level predators (e.g., birds and mammals) including human exposure concentrations from fish in their diet. A previous version of the model has been used to categorize chemicals for their potential to bioaccumulate in aquatic food webs for Environment Canada to address legislation outlined under the Canadian Environmental Protection Act 1999. The model is coded in a Microsoft Excel™ workbook.

General information on the model is available in the following publication:

– Arnot JA, Gobas FAPC. 2003. A generic QSAR for assessing the bioaccumulation potential of organic chemicals in aquatic food webs. QSAR Comb Sci 22(3): 337-345.

Versions for Download:

BCFBAF Ver1.2 model (Spreadsheet Model)
Download BCFBAF VER1.2

OR available in U. S. EPA’s EPI Suite

Human Biotransformation and Total Elimination Half-life QSARs (IFS)
The whole body, total elimination half-life (HLT) and the whole body, primary biotransformation half-life (HLB) are key parameters determining the extent of bioaccumulation, biological concentration, and risk from chemical exposure. We have developed and published HLT and HLB databases that have subsequently been used to develop and validate QSARs for predicting HLB and HLT from chemical structure. Full details of the methods and validation statistics of the these QSARs are available:

– Arnot, J. A.; Brown, T. N.; Wania, F. 2014. Estimating screening-level organic chemical half-lives in humans. Environ. Sci. Technol. 48, (1), 723–730. DOI: 10.1021/es4029414

Download IFS Human Half-Life QSAR

– Papa, E.; Sangion, A.; Arnot, J.A.; Gramatica, P. 2018. Development of human biotransformation QSARs and application for PBT assessment refinement. Food. Chem. Toxicol. 112:535-543. DOI: 10.1016/j.fct.2017.04.016

Download QSARINS at the University of Insubria

IVIVE-Fish BCF
In Vitro-In Vivo Extrapolation: Fish Bioconcentration Factor (IVIVE – Fish BCF) Model

Regulatory testing in the 21st Century is shifting towards more in vitro based experiments to obtain empirical data for different decision-making contexts, e.g., Bioaccumulation Assessment. Biotransformation rates play a critical role in mitigating bioaccumulation potential in fish and other species; however, measured biotransformation rate data are limited compared to the number of chemicals requiring evaluation. The OECD has developed standardized test guidelines for measuring in vitro biotransformation rates using S9 and hepatocyte (HEP) assay systems from rainbow trout liver tissues.

Models are required to extrapolate the in vitro rates to in vivo liver clearance and whole-body biotransformation rates and to incorporate these rates in toxicokinetic models to calculate bioaccumulation assessment endpoints such as the bioconcentration factor (BCF). One model for extrapolating in vitro S9 and HEP biotransformation rates to fish BCFs is described in:

– Nichols, J. W.; Huggett, D. B.; Arnot, J. A.; Fitzsimmons, P. N.; Cowan-Ellsberry, C. E. 2013. Toward improved models for predicting bioconcentration of well-metabolized compounds by rainbow trout using measured rates of in vitro intrinsic clearance. Environ. Toxicol. Chem. 32, (7), 1611-22. DOI: 10.1002/etc.2219

Try the on-line version of the Nichols et al., 2013 IVIVE – Fish BCF model here

Fish biotransformation rate constant (or half-life) QSARs
We have developed and published databases that have subsequently been used to develop and validate QSARs for predicting fish biotransformation half-lives from chemical structure. The first fish biotransformation half-life QSAR is included in the BCFBAF module of the U. S. EPA’s EPI Suite™ software package. Full details of the methods and validation statistics of the these QSARs are available:

– Arnot, J. A.; Meylan, W.; Tunkel, J.; Howard, P. H.; Mackay, D.; Bonnell, M.; Boethling, R. S. 2009. A quantitative structure-activity relationship for predicting metabolic biotransformation rates for organic chemicals in fish. Environ. Toxicol. Chem. 28, (6), 1168-1177. DOI: 10.1021/es4029414

Download BCFBAF here – U. S. EPA’s EPI Suite™ 

– Brown, T. N.; Arnot, J. A.; Wania, F. 2012. Iterative fragment selection: A group contribution approach to predicting fish biotransformation half-lives. Environ. Sci. Technol. 46, (15), 8253–8260. DOI: 10.1021/es301182a

Download IFS Fish Half-Life QSAR

– Papa, E.; van der Wal, L.; Arnot, J. A.; Gramatica, P., Metabolic biotransformation half-lives in fish: QSAR modelling and consensus analysis. Sci. Tot. Environ. 2014, 470–471, 1040–1046. DOI: 10.1016/j.scitotenv.2013.10.068

Download QSARINS at the University of Insubria

For more information about these models and databases or to request download permission, please contact Jon Arnot and state which model(s) you are requesting information or download access.

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DATABASES

The Excel spreadsheet models and databases are expected to work using Microsoft Office or other similar programs (Note: Visual Basic for Applications support is often required).

Fish BCF and BAF database
This database is the result of a review of 392 scientific papers and publicly available bioaccumulation data sources and includes 5,317 BCFs and 1,656 BAFs measured for 842 organic chemicals in 219 aquatic species. The data were subject to a data quality evaluation and scoring method. 

Details about the database and the data quality assessment method are available in the following publication:

– Arnot JA, Gobas FAPC. 2006. A review of bioconcentration factor (BCF) and bioaccumulation factor (BAF) assessments for organic chemicals in aquatic organisms. Environ Rev 14: 257-297.

Versions for Download: >

Download Here – BCF and BAF database – 2006 

Fish biotransformation rate constant (kM) database

Fish biotransformation rate constant (kM) database

More than 5,400 bioaccumulation measurements in fish for more than 1,000 organic chemicals were critically reviewed to compile a database of 1,535 kM estimates for 702 organic chemicals. Biotransformation rates range over six orders of magnitude across a diverse domain of chemical classes and structures. Screening-level uncertainty analyses provide guidance for the selection and interpretation of kM values.

Details about the database are available in the following publication:

– Arnot JA, Mackay D, Parkerton TF, Bonnell M. 2008. A database of fish biotransformation rates for organic chemicals. Environ Toxicol Chem 27(11): 2263-2270.

Versions for Download:

Download Here – kMdatabase 

Human Whole-Body Total Elimination and Biotransformation Half-life Database
The whole body, total elimination half-life (HLT) and the whole body, primary biotransformation half-life (HLB) are key parameters determining the extent of bioaccumulation, biological concentration, and risk from chemical exposure. A one-compartment physiologically-based pharmacokinetic (PBPK) mass balance model was developed to estimate organic chemical HLB from measured HLT data in mammals. Approximately 1,900 HLs for human adults were collected and reviewed and the PBPK model was parametrized for an adult human to calculate HLB from HLT. The databases have been used to develop and validate QSARs for predicting HLB and HLT from chemical structure. These databases are included in the OECD QSAR Toolbox. Full details of the database development methods are available here:

– Arnot, J. A.; Brown, T. N.; Wania, F. 2014. Estimating screening-level organic chemical half-lives in humans. Environ. Sci. Technol. 48, (1), 723–730. DOI: 10.1021/es4029414

Download – HumanHalfLifeDatabases

Fish Dietary Bioaccumulation and Toxicokinetics Database
A database of 3,032 measurement end points for 477 discrete organic chemicals including 964 half-lives, 1,199 absorption efficiencies and 869 biomagnification factors from 19 species (primarily trout and carp) was developed from the literature. Biological properties (e.g., organism weight, lipid content) and exposure conditions (e.g., temperature, feeding rate, dietary lipid content, exposure duration) are documented. Data confidence assessment methods were developed and applied to the database.

Details about the database are available in the following publication:

– Arnot, J. A.; Quinn, C. L. 2015. Development and evaluation of a database of dietary bioaccumulation test data for organic chemicals in fish. Environ. Sci. Technol. 49, (8), 4783-96. DOI: 10.1021/es506251q

Download FishDietaryBioaccumulationDatabase

Plant Bioaccumulation Database
More than 350 articles were reviewed to develop a database with 7,049 entries of measured bioaccumulation data (e.g., bioconcentration factors, root concentration factors, transpiration stream concentration factors) for 310 organic chemicals and 112 terrestrial plant species. Various experimental approaches have been used to obtain these bioaccumulation metrics; therefore, interstudy comparisons and data-quality evaluations are difficult. Key exposure and plant growth conditions were often missing, and units were often unclear or not reported. Data confidence assessment methods were developed and applied to the database.

Details about the database are available in the following publication:

– Doucette, W. J.; Shunthirasingham, C.; Dettenmaier, E. M.; Zaleski, R. T.; Fantke, P.; Arnot, J. A. 2018. A review of measured bioaccumulation data on terrestrial plants for organic chemicals: Metrics, variability, and the need for standardized measurement protocols. Environ. Toxicol. Chem. 37, (1), 21-33. DOI: 10.1002/etc.3992

Download PlantBioaccumulationDatabase

Limitations of liability and disclaimer of warranty
ARC Arnot Research & Consulting Inc. and all associated collaborators do not guarantee, warrant, or make any representations, either expressed or implied, regarding the use, or the results of the use of the materials provided with regards to reliability, accuracy, correctness, or otherwise. There are no warranty rights granted to users of the models or databases provided.

Users assume the entire risk as to the results and performance of the models and databases. ARC Arnot Research & Consulting Inc. and all associated collaborators are not liable under any circumstances, for any damages whatsoever, arising out of the use, or the inability to use, the models and databases provided, even if advised of the possibility of such damages.

jon@arnotresearch.com

Thank you for your interest in these databases.
For more information about these databases please contact Jon Arnot.

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