Models provide an opportunity to predict outcomes based on theory, empirical data describing relationships and site and temporal specific inputs. Levels of sophistication can vary from simple to extremely complex. However, complexity does not necessarily mean that models do a better job of predicting outcomes. Weather forecasting is an excellent example of low albeit improving success using very complex models. That is largely due to the complexity of atmospheric dynamics.
This model strives for simplicity by making worst case assumptions for driving the various preservative-specific models that have been integrated. This leads to predictions of environmental levels of contaminants that are generally higher than those actually observed in model verification studies making the models conservative from an environmental risk perspective. It is emphasized that the models are not designed to provide exact predictions of environmental responses on small spatial scales (meters). They are designed to conservatively predict specific sites where pressure treated wood projects have a reasonable probability of creating an unacceptable environmental risk and a range of projects and sites where there is little environmental risk.
The following sources provide additional information regarding this model: