Ion Transport from Soil to Air and Electric Field Amplitude of the Boundary Layer - Muhammad, Ahmad; Kulahci, Fatih; Danbatta, Salim Jibrin (Pleiades Publishing Ltd, 2024)
The presence of ions within the atmospheric region near the soil surface has considerable implications for enhancing our understanding of Earth's complex systems. This study delves into the intricate relationship between the atmospheric electric field in the boundary layer and lithosphere. The focus was specifically on investigating how soil radon and its progeny influence the production rate of ions in both the soil and the atmosphere. To achieve this, we combined the radon transport equation with advanced machine learning techniques. Using a well-suited machine learning model, we effectively modeled the responses of soil radon and seamlessly integrated them into the radon transport equation. The resulting insights were used to predict the rates at which radon-induced ion pairs were produced. A particularly important parameter is the surface-ion production rate, which is crucial for estimating the amplitude of the near-surface electric field. This methodology was applied to analyze data from two radon monitoring stations in Turkey: Erzincan, located along the North Anatolian Fault (NAF), and Malatya, situated close to the East Anatolian Fault regions. The significance of this estimation approach resonates within the field of lithospheric-atmospheric studies. This innovative methodology holds promise as a valuable tool for future investigations in the domains of lithosphere-atmosphere-ionosphere coupling (LAIC), global electric circuits (GEC), and seismo-ionospheric coupling. Ultimately, this study underscores the importance of carefully considering the intricate interconnections that exist among different components of Earth's intricate system. This advocates the adoption of novel methods to shed light on these complex interactions.
Keywords: surface atmospheric electric field; radon transport; ion production rates; machine learning