Ion Transport from Soil to Air and Electric Field Amplitude of the Boundary Layer

IF 0.7 4区 地球科学 Q4 GEOCHEMISTRY & GEOPHYSICS
Ahmad Muhammad, Fatih Külahcı, Salim Jibrin Danbatta
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Abstract

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.

Abstract Image

Abstract Image

从土壤到空气的离子传输与边界层的电场振幅
摘要 在土壤表面附近的大气区域中存在离子,这对于加深我们对地球复杂系统的了解具有重要意义。本研究深入探讨了边界层大气电场与岩石圈之间错综复杂的关系。重点是研究土壤氡及其后代如何影响土壤和大气中离子的产生率。为此,我们将氡迁移方程与先进的机器学习技术相结合。通过使用合适的机器学习模型,我们对土壤氡的反应进行了有效建模,并将其无缝集成到氡迁移方程中。由此获得的洞察力被用来预测氡诱导离子对产生的速率。其中一个特别重要的参数是表面离子产生率,它对于估计近表面电场的振幅至关重要。该方法适用于分析土耳其两个氡监测站的数据:埃尔津詹位于北安纳托利亚断层(NAF)沿线,马拉蒂亚则靠近东安纳托利亚断层地区。这种估算方法的意义在岩石圈-大气研究领域引起了共鸣。这一创新方法有望成为岩石圈-大气层-电离层耦合(LAIC)、全球电路(GEC)和地震-电离层耦合领域未来研究的宝贵工具。最终,这项研究强调了仔细考虑地球复杂系统不同组成部分之间错综复杂的相互联系的重要性。这就需要采用新颖的方法来揭示这些复杂的相互作用。
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来源期刊
Geomagnetism and Aeronomy
Geomagnetism and Aeronomy Earth and Planetary Sciences-Space and Planetary Science
CiteScore
1.30
自引率
33.30%
发文量
65
审稿时长
4-8 weeks
期刊介绍: Geomagnetism and Aeronomy is a bimonthly periodical that covers the fields of interplanetary space; geoeffective solar events; the magnetosphere; the ionosphere; the upper and middle atmosphere; the action of solar variability and activity on atmospheric parameters and climate; the main magnetic field and its secular variations, excursion, and inversion; and other related topics.
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