Analysing Temporal Variations in Radon Concentrations: Identifying Trends and Changes

ABSTRACT Radon is a well‐known precursor for geodynamic events such as earthquakes and volcanic tremors. Radon concentration variations in soil gas have been monitored worldwide, and extreme radon values have been identified as radon anomalies associated with geodynamic events. A radon time series contains many noise signals, primarily based on meteorological effects. Therefore, detecting pre‐seismic anomalies may not always yield good results. Interpreting long‐term trend changes in the radon time series offers an alternative to examining specific radon anomalies and individual earthquakes. This study examines locally estimated scatterplot smoothing (LOESS) to identify changes in the trend of the radon time series. In this dataset, two distinct radon trends and anomaly mechanisms associated with earthquakes were identified. In the first group, radon activity concentrations increase before and decrease after the earthquake, whereas in the second group, they exhibit the opposite behaviour.