Exploring atmospheric radon with airborne gamma-ray spectroscopy

TL;DR

This study demonstrates the first use of airborne gamma-ray spectroscopy to quantify atmospheric radon, revealing its vertical distribution and concentration, which has implications for environmental health and climate research.

Contribution

It introduces a novel application of AGRS for measuring atmospheric radon levels and profiles, expanding its use beyond background radiation estimation.

Findings

Detected atmospheric radon with AGRS for the first time.

Measured radon concentration as 0.96 ± 0.07 Bq/m³.

Estimated atmospheric layer depth as 1318 ± 22 m.

Abstract

$^{222}$Rn is a noble radioactive gas produced along the $^{238}$U decay chain, which is present in the majority of soils and rocks. As $^{222}$Rn is the most relevant source of natural background radiation, understanding its distribution in the environment is of great concern for investigating the health impacts of low-level radioactivity and for supporting regulation of human exposure to ionizing radiation in modern society. At the same time, $^{222}$Rn is a widespread atmospheric tracer whose spatial distribution is generally used as a proxy for climate and pollution studies. Airborne gamma-ray spectroscopy (AGRS) always treated $^{222}$Rn as a source of background since it affects the indirect estimate of equivalent $^{238}$U concentration. In this work the AGRS method is used for the first time for quantifying the presence of $^{222}$Rn in the atmosphere and assessing its vertical profile. High statistics radiometric data acquired during an offshore survey are fitted as a superposition of a constant component due to the experimental setup background radioactivity plus a height dependent contribution due to cosmic radiation and atmospheric $^{222}$Rn. The refined statistical analysis provides not only a conclusive evidence of AGRS $^{222}$Rn detection but also a (0.96 $\pm$ 0.07) Bq/m$^{3}$ $^{222}$Rn concentration and a (1318 $\pm$ 22) m atmospheric layer depth fully compatible with literature data.