Estimating farfield organic chemical exposures, intake rates and intake fractions to human age classes

Arnot, Jon A.; Mackay, Don; Sutcliffe, Roger; Lo, Belinda

doi:10.1016/j.envsoft.2010.03.026

Cited by 13 publications

(21 citation statements)

References 34 publications

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“…Direct application of the standard equilibrium Equations 1 and 2 is therefore justified, support is gained for their use in this context, and validity is given to the earlier application to PFC(A)s of the more complex multimedia models that are dependent on these equilibrium models [20][21][22][23][24][25][26]. Indeed, in modeling ionizing chemicals in general, recent models designed for regulatory use [49,50] assume that the solubility of the neutral species in organic phases is sufficient to describe the chemical's bioaccumulation and its concentration in abiotic organic carbon. Using our previously published pK a measurement of 3.8 for PFOA [42] for all of the long-chain PFCAs with the average of QSAR-estimated K OW values, as listed in Table 1 Agreement with the standard equilibrium model for BCF for perfluorooctanoic acid (PFOA), perfluoroundecanoic acid, perfluorodecanoic acid, and perfluorododecanoic acid (the 8-, 10-, 11-, and 12-carbon PFCAs, respectively) is within a factor of three for the carcass, four for the liver, and 19 for blood, or 83% (Table SI-3 of the Supplemental Data).…”

Section: Resultsmentioning

confidence: 98%

Equilibrium modeling: A pathway to understanding observed perfluorocarboxylic and perfluorosulfonic acid behavior

Webster

Ellis

2011

Environmental Toxicology and Chemistry

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Equilibrium distribution models of hydrophobic neutral partitioning of the perfluorinated carboxylic and sulfonic acids were shown, without the need for any physical chemical properties, to successfully predict the sediment-water distribution (D(SW) ) directly from independently measured equilibrium tissue distributions known as the bioconcentration factor (BCF). The constant of proportionality required by the models successfully predicted the correlation between the biotic and abiotic distributions of both sets of chemicals, thus demonstrating the applicability of the assumptions inherent in the models, that is, hydrophobically driven partitioning of the neutral species, and thus the applicability of the models themselves. Colloquially speaking, the models are thus validated as applicable to these chemicals. Subsequent application of the standard equilibrium models showed order of magnitude agreement for 83% of measured BCF values and 88% of measured D(SW) for the perfluorinated carboxylic acids, confirming the physical chemical properties used. The applicability of the models to perfluorooctane sulfonic acid (PFOSA) was shown by the successful prediction of D(SW) from BCF. Therefore, the measured D(SW) and BCF could be used to calculate the octanol-water distribution, D(OW) , and hence the corresponding pK(a):K(OW) solution set, thus providing independent experimentally based estimates of these properties. For both the perfluorinated carboxylic and sulfonic acids, the existing standard equilibrium models are shown to be applicable.

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Section: Resultsmentioning

confidence: 98%

Equilibrium modeling: A pathway to understanding observed perfluorocarboxylic and perfluorosulfonic acid behavior

Webster

Ellis

2011

Environmental Toxicology and Chemistry

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“…Direct application of the standard equilibrium Equations 1 and 2 is therefore justified, support is gained for their use in this context, and validity is given to the earlier application to PFC(A)s of the more complex multimedia models that are dependent on these equilibrium models 20–26. Indeed, in modeling ionizing chemicals in general, recent models designed for regulatory use 49, 50 assume that the solubility of the neutral species in organic phases is sufficient to describe the chemical's bioaccumulation and its concentration in abiotic organic carbon. Using our previously published p K a measurement of 3.8 for PFOA 42 for all of the long‐chain PFCAs with the average of QSAR‐estimated K OW values, as listed in Table 1, Equation 1 was used to calculate the D SW values that are compared with independent measurements with results given in Figure 3.…”

Section: Resultsmentioning

confidence: 99%

Activation Instead of Inhibition: Targeting Proenzymes for Small‐Molecule Intervention

2010

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“…Some of the endpoints used in the comparisons below are “exposure potential” i.e., intake fractions and some are “exposure” endpoints, i.e., internal concentrations or body burdens. (For more information on exposure metric development the reader is directed to Rosenbaum et al (2008), Bennett et al (2002), and Arnot et al (2010).) It is emphasized that the modeling approaches also used different model input parameters for chemical properties, use and release rates.…”

Section: Methodsmentioning

confidence: 99%

Comparison of modeling approaches to prioritize chemicals based on estimates of exposure and exposure potential

Mitchell

Arnot

Jolliet

et al. 2013

Science of The Total Environment

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While only limited data are available to characterize the potential toxicity of over 8 million commercially available chemical substances, there is even less information available on the exposure and use-scenarios that are required to link potential toxicity to human and ecological health outcomes. Recent improvements and advances such as high throughput data gathering, high performance computational capabilities, and predictive chemical inherency methodology make this an opportune time to develop an exposure-based prioritization approach that can systematically utilize and link the asymmetrical bodies of knowledge for hazard and exposure. In response to the US EPA’s need to develop novel approaches and tools for rapidly prioritizing chemicals, a “Challenge” was issued to several exposure model developers to aid the understanding of current systems in a broader sense and to assist the US EPA’s effort to develop an approach comparable to other international efforts. A common set of chemicals were prioritized under each current approach. The results are presented herein along with a comparative analysis of the rankings of the chemicals based on metrics of exposure potential or actual exposure estimates. The analysis illustrates the similarities and differences across the domains of information incorporated in each modeling approach. The overall findings indicate a need to reconcile exposures from diffuse, indirect sources (far-field) with exposures from directly, applied chemicals in consumer products or resulting from the presence of a chemical in a microenvironment like a home or vehicle. Additionally, the exposure scenario, including the mode of entry into the environment (i.e. through air, water or sediment) appears to be an important determinant of the level of agreement between modeling approaches.

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Estimating farfield organic chemical exposures, intake rates and intake fractions to human age classes

Cited by 13 publications

References 34 publications

Equilibrium modeling: A pathway to understanding observed perfluorocarboxylic and perfluorosulfonic acid behavior

Equilibrium modeling: A pathway to understanding observed perfluorocarboxylic and perfluorosulfonic acid behavior

Activation Instead of Inhibition: Targeting Proenzymes for Small‐Molecule Intervention

Comparison of modeling approaches to prioritize chemicals based on estimates of exposure and exposure potential

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