Quantitative review and delivery of reliable physical property data: development of DIPPR® Environ 2001™ database and estimation software

Kline, Andrew; Whitten, C.R.; Heward, M.S.; Trumbell, M.R.; Wells, Philip M.; Rogers, Tony; Zei, D.A.; Mullins, Michael E.

doi:10.1016/s0378-3812(01)00453-8

Cited by 4 publications

(4 citation statements)

References 2 publications

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“…Certain organizations have undertaken efforts to evaluate and recommend physical parameter values for use in regulatory programs. ( 22,23 ) Incorporation of similar processes or the recommendations of current programs should help to considerably reduce the variability in physical parameter values reported here and help to ensure that chemicals are evaluated consistently under various regulatory programs.…”

Section: Discussionmentioning

confidence: 99%

Variability in Physical Constant Parameter Values from Standard Data Sources and the Implication of this Variability for Risk Analysis

Marino

2006

Risk Analysis

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Physical property values are used in environmental risk assessments to estimate media and risk-based concentrations. Recently, however, considerable variability has been reported with such values. To evaluate potential variability in physical parameter values supporting a variety of regulatory programs, eight data sources were chosen for evaluation, and chemicals appearing in at least four sources were selected. There were 755 chemicals chosen. In addition, chemicals in seven environmentally important subgroups were also identified for evaluation. Nine parameters were selected for analysis--molecular weight (MolWt), melting point (MeltPt), boiling point (BoilPt), vapor pressure (VP), water solubility (AqSOL), Henry's law constant (HLC), octanol-water partition coefficient (Kow), and diffusion coefficients in air (Dair) and water (Dwater). Results show that while 71% of constituents had equal MolWts across data sources, <3% of the constituents had equivalent parameter values across data sources for AqSOL, VP, or HLC. Considerable dissimilarity between certain sources was also observed. Furthermore, measures of dispersion showed considerable variation in data sets for Kow, VP, AqSOL, and HLC compared to measures for MolWt, MeltPt, BoilPt, or Dwater. The magnitude of the observed variability was also noteworthy. For example, the 95th percentile ratio of maximum/minimum parameter values ranged from 1.0 for MolWt to well over 1.0 x 10(6) for VP and HLC. Risk and exposure metrics also varied by similar magnitudes. Results with environmentally important subgroups were similar. These results show that there is considerable variability in physical parameter values from standard sources, and that the observed variability could affect potential risk estimates and perhaps risk management decisions.

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Section: Discussionmentioning

confidence: 99%

Variability in Physical Constant Parameter Values from Standard Data Sources and the Implication of this Variability for Risk Analysis

Marino

2006

Risk Analysis

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show abstract

Section: Discussionmentioning

confidence: 99%

Variability in Physical Constant Parameter Values from Standard Data Sources and the Implication of This Variability for Risk Analysis

Marino¹

2006

Risk Analysis

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Physical property values are used in environmental risk assessments to estimate media and risk-based concentrations. However, considerable variability has recently been reported with such values. To evaluate potential variability in physical parameter values supporting a variety of regulatory programs, eight data sources were chosen for evaluation, and chemicals appearing in at least four sources were selected. There were 755 chemicals chosen. In addition, chemicals in seven environmentally important subgroups were also identified for evaluation. Nine parameters were selected for analysis-molecular weight (MolWt), melting point (MeltPt), boiling point (BoilPt), vapor pressure (VP), water solubility (AqSOL), Henry's law constant (HLC), octanol-water partition coefficient (Kow), and diffusion coefficients in air (Dair) and water (Dwater). Results show that while 71% of constituents had equal MolWts across data sources, <3% of the constituents had equivalent parameter values across data sources for AqSOL, VP, or HLC. Considerable dissimilarity between certain sources was also observed. Furthermore, measures of dispersion showed considerable variation in data sets for Kow, VP, AqSOL, and HLC compared to measures for MolWt, MeltPt, BoilPt, or Dwater. The magnitude of the observed variability was also noteworthy. For example, the 95th percentile ratio of maximum/minimum parameter values ranged from 1.0 for MolWt to well over 1.0E + 06 for VP, and HLC. Risk and exposure metrics also varied by similar magnitudes. Results with environmentally important subgroups were similar. These results show that there is considerable variability in physical parameter values from standard sources, and that the observed variability could affect potential risk estimates and perhaps risk management decisions.

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“…The necessary physical-chemical input data for CHEMGL were obtained from databases (Kline et al 2000;ChemOffice 2000;US NLM 2005) and handbooks (Howard 1991;Mackay et al 1992) or estimated using the US EPA EPI Suite (US EPA 2000) based on chemical structure. The required properties include-half-life of each chemical in air, water, aerobic and anaerobic environment, Henry's law constant, octanol-water partition coefficient, molecular weight, melting point, vapor pressure, and diffusivity in both air and water.…”

Section: Life Cycle Impact Assessment Methodologymentioning

confidence: 99%

Integrating economic input–output life cycle assessment with risk assessment for a screening-level analysis

Wright

Zhang

Mihelcic

2008

Int J Life Cycle Assess

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Goal, Scope, and Background The paper describes the integration of the economic input-output life cycle assessment (EIO-LCA) model and the environmental fate and transport model (CHEMGL) with a risk assessment tool. Utilizing the EIO-LCA, instead of a traditional LCA, enables a rapid, screening-level analysis of an emerging chemical of concern, decabromodiphenyl ether (DecaBDE). The risk assessment in this study is evaluated based on the mass of chemical released, estimated concentrations, exposure, and chemical toxicity. Methods The relative risk from ten economic sectors identified within the EIO-LCA model, 55 chemicals utilized in those sectors and DecaBDE along with four potential DecaBDE breakdown products, were evaluated for the life cycle stages and exposure pathways. The relative risk (expressed as toluene equivalents) of the different chemicals, sectors, and life cycle stages were compared to assess those representing the greatest overall relative risks to humans (via inhalation and ingestion) and fish.

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Quantitative review and delivery of reliable physical property data: development of DIPPR® Environ 2001™ database and estimation software

Cited by 4 publications

References 2 publications

Variability in Physical Constant Parameter Values from Standard Data Sources and the Implication of this Variability for Risk Analysis

Variability in Physical Constant Parameter Values from Standard Data Sources and the Implication of this Variability for Risk Analysis

Variability in Physical Constant Parameter Values from Standard Data Sources and the Implication of This Variability for Risk Analysis

Integrating economic input–output life cycle assessment with risk assessment for a screening-level analysis

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