What Models Can (and Can't) Tell Us About Risk
..."McKone sees models as descriptors of the physical and chemical processes that govern the behavior or chemicals in the environment. "You can build relationships between factors that you can't otherwise do without a model," he says, including chemical properties, transport within and among different media, and abundance in the environment. "..."But just understanding how the pieces fit together doesn't guarantee correct results, McKone says. "You can still get results that don't correlate to the real thing. So models are both potentially powerful, and potentially dangerous."
While a model can hint at what interventions have the best chance of reducing pollutant concentrations and exposures, "A lot of people think models provide predictions," McKone says, "but they don't do this. Models are not very useful if you don't have something with which to anchor them. You need observations to confirm the model and move it closer to a representation of reality.This is a particular problem for policymakers, who "don't like to make choices involving uncertainty," McKone says. "A danger is that they may just use model results to tell them what to do.
"Adding more detail into a model doesn't necessarily get you a better result if you don't understand the basic science," says McKone. "Model development has to be paced with the science."..."Says McKone,
"The reliability of the calculation depends on the reliability of the least well known element. If you don't know how uncertain this weak link is, then you are making the model results look more accurate than they really are."...