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Sensitivity and uncertainty studies of the CRAC2 computer code.

D C Kocher1, R C Ward, G G Killough

  • 1Health and Safety Research Division, Oak Ridge National Laboratory, Tennessee 37831.

Risk Analysis : an Official Publication of the Society for Risk Analysis
|December 1, 1987
PubMed
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This study assessed uncertainties in nuclear accident health impact predictions from the CRAC2 code. Key factors influencing health effects include wet deposition models and inhalation dose conversion factors.

Area of Science:

  • Nuclear Safety and Health Physics
  • Environmental Science and Risk Assessment

Background:

  • Nuclear reactor accidents pose risks to public health.
  • Accurate prediction of health impacts is crucial for emergency preparedness.
  • The CRAC2 computer code is widely used for consequence assessment.

Purpose of the Study:

  • To investigate the sensitivity of CRAC2-predicted health impacts to various uncertainty sources.
  • To identify key parameters driving uncertainty in nuclear accident consequence analysis.
  • To inform risk assessment and mitigation strategies for nuclear facilities.

Main Methods:

  • Sensitivity analysis of the CRAC2 code using multiple uncertainty sources.
  • Evaluation of plume rise models, wet deposition models, and meteorological bin-sampling.

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  • Assessment of uncertainties in inhalation dose conversion factors and ground-surface exposure.
  • Analysis of terrestrial foodchain transfer coefficients.

    • Main Results:

    • Health impacts showed low sensitivity to plume rise models and modified rain-bin sampling.
    • Wet deposition models significantly impacted health effects in single runs but less so in bin-sampling.
    • Inhalation dose conversion factor uncertainties strongly affected early injury predictions.
    • Latent cancer fatalities were moderately sensitive to ground-surface exposure weathering times.

    Conclusions:

    • The CRAC2 code's predictions are sensitive to specific uncertainty sources, notably wet deposition and inhalation dose factors.
    • Uncertainty in weather sequence selection can be comparable to model parameter uncertainties for early health effects.
    • Risk assessments must carefully consider uncertainties in dose conversion factors and deposition models for accurate health impact predictions.