Bowman Gordon, Harris Gabe, Kirk Matthew, Jin Qusheng
Department of Earth Science, University of Oregon, Eugene, OR, 97403.
Department of Geology, Kansas State University, Manhattan, KS, 66506.
Ground Water. 2025 Sep-Oct;63(5):725-735. doi: 10.1111/gwat.70010. Epub 2025 Aug 7.
Reduction potentials of redox couples are fundamental for understanding subsurface geochemistry and guiding water resource exploration and management. Reduction potentials are routinely calculated with the Nernst equation, which requires detailed chemical composition data and complex speciation modeling-factors that limit its application in large-scale or data-limited field settings. To address these limitations, we developed a data-driven simplified Nernst equation that estimates the reduction potentials of individual redox couples using only pH and temperature. By integrating geochemical modeling with a global groundwater chemistry dataset, we demonstrate that pH is the dominant control on redox potential, while temperature and redox species activity play secondary roles. The resulting formulation reduces computational demands while maintaining high-predictive accuracy across diverse groundwater environments. This approach enables rapid and scalable estimation of reduction potentials, supporting applications in geochemical modeling, contaminant transport prediction, and groundwater quality assessments. Furthermore, it offers a thermodynamically grounded yet practical framework for interpreting electron transfer dynamics in natural groundwater systems.
氧化还原电对的还原电位对于理解地下地球化学以及指导水资源勘探和管理至关重要。还原电位通常使用能斯特方程来计算，该方程需要详细的化学成分数据和复杂的物种形成模型，这些因素限制了其在大规模或数据有限的野外环境中的应用。为了解决这些限制，我们开发了一种数据驱动的简化能斯特方程，该方程仅使用pH值和温度来估算单个氧化还原电对的还原电位。通过将地球化学模型与全球地下水化学数据集相结合，我们证明pH值是氧化还原电位的主要控制因素，而温度和氧化还原物种活性起次要作用。由此产生的公式降低了计算需求，同时在不同的地下水环境中保持了较高的预测精度。这种方法能够快速且可扩展地估算还原电位，支持在地球化学建模、污染物迁移预测和地下水质量评估中的应用。此外，它为解释天然地下水系统中的电子转移动力学提供了一个基于热力学但实用的框架。
