Characterization of precipitation-induced radon progeny deposition events using a city-scale sensor network
Snehadri Das, Nicolas Abgrall, Mark Bandstra, Reynold Cooper, Yongho Kim, Emil Rofors, Rajesh Sankaran, Sean Shahkarami
TL;DR
Precipitation-driven radon progeny deposition introduces significant background variability in urban radiological sensing. The study deploys a city-scale PANDA-DAWN sensor network in Chicago and applies spectral non-negative matrix factorization to separate static and radon-enhanced backgrounds, leveraging the radon progeny proxy $RPP$ and implied relative radon concentration $IRRC$ alongside back-trajectory analysis via $HYSPLIT$. It finds a moderate power-law relationship between peak $RPP$ and peak radon-associated NMF weight ($R^2=0.452$) and identifies an anomalous Event A linked to a uranium-rich air-mass path from Wyoming, with PCA clustering revealing three meteorological regimes tied to radon enrichment. The results support context-aware background models tailored to meteorological categories, enhancing the sensitivity and robustness of urban radiological anomaly detection and highlighting the utility of air-mass history in predicting radon content.
Abstract
Networks of radiation detectors provide a platform for real-time radioactive source detection and identification in urban environments. Detection algorithms in these systems must adapt to naturally-occurring changes in background, which requires well-characterized relationships between precipitation events and their corresponding radiological signature. We present a description of rain-induced radon progeny deposition events occurring in Chicago from September 2023 through February 2024. We measure ambient gamma radiation levels, precipitation rate, temperature, pressure and relative humidity in a network of sensor nodes. For each identified precipitation period, we decompose spectra into static- and radon-associated components as defined by a non-negative matrix factorization (NMF) algorithm. We find a consistent power-law relationship between a precipitation-dependent peak of the radon progeny proxy (RPP) and the peak strength of radon-associated NMF component for most precipitation events. We conduct a case study of a rainfall period with abnormally high levels of implied radon progeny concentration and describe its temporal and spatial evolution. We hypothesize this phenomenon is due to the air mass path that intersects a uranium-rich region of Wyoming. Finally, we cluster precipitation events into three distinct categories. One category roughly corresponds to events with deep low-pressure systems and high relative radon concentration, while another is characteristic of light stratiform rain with slightly higher temperatures and intermediate relative radon concentration. The third category contains a weak-gradient or lake breeze convection showers with intermittent precipitation and low relative radon concentration. These findings suggest that radiological anomaly detection could be improved by training unique background models corresponding to each category of meteorological event.