09/05/2026
What happens when we look at radon beyond county and ZIP-code averages?
A new study published in the *Journal of Environmental Radioactivity* used **19,497 residential radon measurements from Utah** to develop a high-resolution spatial model capable of examining radon patterns at a much finer geographic scale.
The research raises an important question for those of us working in radon policy and public health:
**Are the geographic tools we have relied on for decades still giving us enough information to make the best decisions today?**
In the United States, the EPA Map of Radon Zones remains an important reference, and those zone designations have also influenced where radon-resistant new-construction provisions are applied through the International Residential Code.
Wu and colleagues demonstrate why looking at radon at finer spatial resolution matters. Broad geographic averages can obscure meaningful local variation.
But there is another finding in this paper that deserves just as much attention: **better models still need better data.**
The researchers found that areas with greater testing density provided richer information about fine-scale spatial patterns, while sparse measurement data limited what could be resolved.
That creates an important connection between **radon testing, surveillance, research, and policy.**
More measurements don't just tell us more about the buildings being tested. Collectively, quality measurement data can help us better understand where radon risk occurs and ultimately help inform better public-health decisions.
And no matter how sophisticated our mapping becomes, a prediction of radon potential is not a measurement of an individual building. **The way to know the radon concentration in a building is still to test it.**
Research like this gives us an opportunity to improve both sides of that equation: better testing data and better tools for understanding what those data can tell us.
**Wu Y, et al. (2026). “High-resolution modeling of indoor radon exposure with uncertainty quantification in Utah.” Journal of Environmental Radioactivity, 299, 108141.**