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Indoor radon concentration data often exhibit log-normal distribution, a phenomenon termed "log-normal mysticism." This study verifies this for Austrian and European datasets, finding approximate log-normality with limitations due to outlier "fat tails."

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Area of Science:

  • Environmental Science
  • Geophysics
  • Radiological Protection

Background:

  • Indoor radon (Rn) concentration data from geographical surveys frequently display log-normal distributions.
  • This observation, termed "log-normal mysticism," has remained largely unexplained.
  • Log-normality is a key assumption in some radon mapping methodologies.

Purpose of the Study:

  • To verify the prevalence of log-normal distribution in indoor radon concentration data.
  • To assess the validity of "log-normal mysticism" using Austrian and European datasets.
  • To investigate the impact of outliers on the log-normality of radon data.

Main Methods:

  • Analysis of indoor radon concentration data from the Austrian indoor radon survey.
  • Utilisation of data from the ongoing European indoor radon mapping project.
  • Statistical investigation of frequency distributions and outlier identification.

Main Results:

  • Approximate log-normality was observed across large spatial scales in the datasets, albeit with limitations.
  • A systematic presence of a "fat tail" in radon frequency distributions was identified, indicating frequent extreme values.
  • These extreme values (outliers) were found to disturb the overall log-normality.

Conclusions:

  • The "log-normal mysticism" holds with some limitations for large-scale spatial ranges in indoor radon data.
  • The presence of "fat tails" in radon distributions is a significant factor affecting strict log-normality.
  • Understanding "local log-normality" within specific neighborhoods or geological units is crucial for accurate radon mapping.