School of Geophysics and Measurement-control Technology, East China University of Technology, Nanchang, 330013, People's Republic of China.
Jiangxi Earthquake Agency, Nanchang, 330026, People's Republic of China.
J Environ Radioact. 2024 Jan;271:107310. doi: 10.1016/j.jenvrad.2023.107310. Epub 2023 Oct 25.
Many factors influence the accurate identification of radon anomalies triggered by earthquakes to varying degrees. Therefore, this paper primarily provides a comprehensive review of the various factors influencing radon concentrations over the past two decades. In addition to examining the individual effects of these factors on radon concentrations, it explores the interactions among multiple factors, particularly the correlations among radon anomalies and seismic events as well as the environmental context. This review mainly includes the classification of groundwater radon anomalies and their potential formation mechanisms, the environmental impact on radon concentrations, the effects of soil and rock structures on radon migration, and the application of machine learning in detecting radon anomalies induced by earthquakes.
许多因素不同程度地影响地震引发的氡异常的准确识别。因此，本文主要对过去二十年影响氡浓度的各种因素进行了全面回顾。除了检查这些因素对氡浓度的单独影响外，还探讨了多种因素之间的相互作用，特别是氡异常与地震事件之间的相关性以及环境背景。本综述主要包括地下水氡异常的分类及其可能的形成机制、环境对氡浓度的影响、土壤和岩石结构对氡迁移的影响以及机器学习在地震诱发氡异常检测中的应用。
