Chemical-specific Parameters Dataset

Dolislager, Fred; Stewart, Debra; Manning, Karessa; Noto, Katie

doi:10.11578/RAIS_CHEM_PARAMS_12_13_2024/2481708

Title: Chemical-specific Parameters Dataset

Dataset
Other Related Research

Abstract

The chemical-specific parameters dataset is searchable for physicochemical information for multiple chemicals simultaneously. After selecting chemicals of interest and the desired parameters, the RAIS will generate a table containing the values, chosen according to an established hierarchy. Results can be downloaded in Excel format. Over 40 parameters are available, including melting point, boiling point, density, density, vapor pressure, water solubility, and Henry’s Law constants. Thirteen primary sources are used to populate the dataset of chemical-specific parameters. These values should be used in cancer risk and noncancer hazard assessments for the calculation of preliminary remediation goals (PRGs), hazard characterization, and transport modeling. Users can select up to 1000 chemicals per query. The dataset supports environmental risk assessments, regulatory decision-making, and environmental planning with tools for benchmarking against risk-based standards. This structured approach ensures a robust evaluation of environmental risks tailored to regulatory needs.

Authors:

Dolislager, Fred; Stewart, Debra; Manning, Karessa; Noto, Katie

Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States); Oak Ridge National Laboratory
Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)

Publication Date:: Sat Nov 30 23:00:00 EST 2024

Other Number(s):: Runtime: 2024-12-13 15:17:43

Research Org.:: ORNLERASE (Oak Ridge National Laboratory Environmental Risk Assessment System Enterprise (ORNLERASE))

Sponsoring Org.:: USDOE Office of Environmental Management (EM)

OSTI Identifier:: 2481708

DOI:: https://doi.org/10.11578/RAIS_CHEM_PARAMS_12_13_2024/2481708

Citation Formats


                    Dolislager, Fred, Stewart, Debra, Manning, Karessa, and Noto, Katie. Chemical-specific Parameters Dataset.  United States: N. p., 2024. 
        Web.  doi:10.11578/RAIS_CHEM_PARAMS_12_13_2024/2481708.

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                    Dolislager, Fred, Stewart, Debra, Manning, Karessa, & Noto, Katie. Chemical-specific Parameters Dataset.  United States.  doi:https://doi.org/10.11578/RAIS_CHEM_PARAMS_12_13_2024/2481708

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                    Dolislager, Fred, Stewart, Debra, Manning, Karessa, and Noto, Katie. 2024.  
"Chemical-specific Parameters Dataset".  United States.  doi:https://doi.org/10.11578/RAIS_CHEM_PARAMS_12_13_2024/2481708.  https://www.osti.gov/servlets/purl/2481708. Pub date:Sat Nov 30 23:00:00 EST 2024

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@article{osti_2481708,

  title        = {Chemical-specific Parameters Dataset},

  author       = {Dolislager, Fred and Stewart, Debra and Manning, Karessa and Noto, Katie},

  abstractNote = {The chemical-specific parameters dataset is searchable for physicochemical information for multiple chemicals simultaneously. After selecting chemicals of interest and the desired parameters, the RAIS will generate a table containing the values, chosen according to an established hierarchy. Results can be downloaded in Excel format. Over 40 parameters are available, including melting point, boiling point, density, density, vapor pressure, water solubility, and Henry’s Law constants. Thirteen primary sources are used to populate the dataset of chemical-specific parameters. These values should be used in cancer risk and noncancer hazard assessments for the calculation of preliminary remediation goals (PRGs), hazard characterization, and transport modeling. Users can select up to 1000 chemicals per query. The dataset supports environmental risk assessments, regulatory decision-making, and environmental planning with tools for benchmarking against risk-based standards. This structured approach ensures a robust evaluation of environmental risks tailored to regulatory needs.},

  doi          = {10.11578/RAIS_CHEM_PARAMS_12_13_2024/2481708},

  journal      = {},

  number       = ,

  volume       = ,

  place        = {United States},

  year         = {Sat Nov 30 23:00:00 EST 2024},

  month        = {Sat Nov 30 23:00:00 EST 2024}

}

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DOI: https://doi.org/10.11578/RAIS_CHEM_PARAMS_12_13_2024/2481708

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