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Models in Environmental Regulatory Decision Making (2007)
Board on Environmental Studies and Toxicology (BEST)

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. "5 Model Selection and Use." Models in Environmental Regulatory Decision Making. Washington, DC: The National Academies Press, 2007.

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Models in Environmental Regulatory Decision Making

that is equivalent to peer review for public models. If necessary, nondisclosure agreements could be used for experts to perform a thorough review of the proprietary portions of the model. The review process and results could then be made public without compromising proprietary features. General-purpose proprietary software (for example, Excel, SAS, and MATLAB) usually will not require such scrutiny, although EPA should be cognizant of the costs that obtaining and using such software may impose on interested parties.

Extrapolation

Model use in the environmental regulatory process may involve using the model to extrapolate beyond conditions for which the model was constructed or calibrated or conditions for which the model outputs cannot be verified. For example, it might be necessary to extrapolate laboratory animal data to assessments of possible human effects or to extrapolate the recent history of global environmental conditions to future conditions. In these circumstances, uncertainties about the form of a model and the parameters in the model might yield large uncertainties in model outputs. This problem can be compounded by making a model more complex if the additional processes in the more complex model are unimportant; any extra parameters that need to be estimated could degrade the confidence in the estimates of all parameters.

Recommendations

Extrapolating far beyond the available data for the model draws particular attention in the evaluation process to the theoretical basis of the model, the processes represented in the model, and the parameter values. When critical model parameters are estimated largely on the basis of matching model output to historical data, care must be taken to provide uncertainty estimates for the extrapolations, especially for models with many uncertain parameters.

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