1. Environmental Effects on Radon Concentrations
Beth Hall1, Leslie Stoecker1,
Paul Francisco2, Stacy Gloss2, Yigang Sun2
1Midwestern Regional Climate Center, University of Illinois
2Indoor Climate Research & Training, University of Illinois

2. Background Indoor Radon (Rn) testing (practices, motivation)
“Conventional wisdom” of seasonal trends
Greater in winter
Inverse relationship - outdoor temperatures, Rn
Past research indicated strong in-ground Rn correlations to
Precipitation
Soil moisture
Air pressure

3. Motivation
2013, 2014 study results – Contradiction to “conventional wisdom”?

4. Possibly Seasonal Cycle?
Motivation
Combining different case periods – Contradiction to “conventional wisdom”?
Indoor Rn from 3 different studies (2013, 2014, 2016) in Champaign County
Possibly Seasonal Cycle?

5. Study Questions Is indoor Rn concentrations seasonally different?
Does data support seasonal “conventional wisdom”?
What atmospheric and/or soil parameters influence Rn concentrations?
What are climate trends in those parameters?
Could findings be used to improve:
Contextual understanding of indoor Rn?
Timing of indoor Rn testing?
Future studies?

6. Methodology
Analyze various atmospheric, soil parameters to indoor Rn concentrations
More sites
Some overlapping sites
Examine coincident and lag correlations
Examine proxy parameters if possible

7. Indoor Rn Data RADStar R5300 CRM
Living space and foundation (crawl space / basement)
Hourly sampling
4 different study periods across Champaign County

8. Indoor Rn Data Winter 2013/2014 – 5 sites Spring 2014 – 5 new sites
Oct ‘13 – Jan ‘14
Spring 2014 – 5 new sites
Apr ‘14 – July ‘14
Summer 2014 – 5 new sites
Aug ‘14 – Nov ‘14
Spring/Summer 2016 – 15 sites
Apr ‘16 – Aug ‘16
2 from Winter
1 from Spring
1 from Summer

9. Atmospheric / Soil Data
4 data sources: Gridded and point datasets
Variable list:
Temperature
Air pressure
Precip amts
Wind speed, dir
Specific Humidity
Solar Radiation
Soil Moisture
0-10 cm
0-100 cm
0-200 cm
10-40cm
40-100cm
Soil Temperature
0-10cm cm

10. Results – Part 1 Inconsistent correlations between sites
Strongest correlations (r) with NLDAS data:
SoilM (depths); give ranges of r2; show maps <make locations larger circles to avoid specific locations>
SoilT (depths)
Neither precipitation nor pressure showed strong correlations – contradicting past research in-ground

11. Correlations (r) – Living space over Basement
Results – Part 1
Correlations (r) – Living space over Basement

12. Correlations (r) – Living space over Crawl Space
Results – Part 1
Correlations (r) – Living space over Crawl Space

13. Correlations (r) – Basement
Results – Part 1
Correlations (r) – Basement

14. Correlations (r) – Crawl Space
Results – Part 1
Correlations (r) – Crawl Space

15. Results – Part 1 Inconsistent correlations between sites
Strongest correlations (r) with “in ground” parameters:
SoilM (varying depths)
SoilT (varying depths)
Weakest correlations (r) with “above ground” parameters:
Winds
Solar radiation
Precipitation
Air pressure
Some “above ground” good correlations:
Air temperature
Specific humidity

16. Results – Part 1
Soil Moisture cm vs Living Space Over Basement Radon Correlations

17. Results – Part 2 Challenges with soilM: Proxy for soilM?
Extremely variable across space, time (geology)
Not well modeled
Sparsely observed
Proxy for soilM?
Should be correlated to precipitation and evaporation
How are greater depths affected?
Keetch-Byrum Drought Index (KBDI)
Simple, daily drought index
Max temperature, precipitation

18. Living Space over Crawl Space
Results – Part 2
Living Space over Crawl Space

19. Results – Part 3 Possible theories: Underlying geology
Structural aspects of homes
Age of homes

20. Results – Part 4 Seasonal climatology of soil moisture
Seasonal climatology of KBDI

21. “Possible” seasonal trends in Rn concentrations?
Results – Part 4
“Possible” seasonal trends in Rn concentrations?
Mar ‘16 – Aug ‘16
Oct ‘13 – Jan ‘14
May ‘14 – Jul ‘14
Aug ‘14 – Dec ‘14

22. Conclusions Indoor Rn highly variable in space and time
“In-ground” variables (e.g., soilM, soilT) more often have stronger correlations than atmospheric
Many factors influence indoor Rn
Needs:
Test both inside and near outside home for assessing structural impact (house-shadow effect?)
Track windows open/closed
Understand spikes in Rn
Full annual cycle at sites
Examine temperature differences (indoorT– outdoorT)

23. Illinois Emergency Management Agency Patrick Daniels
Acknowledgements
Illinois Emergency Management Agency Patrick Daniels
Thank you!