Unified Modeling Approach for Quantifying the Proton and Metal Binding Ability of Soil Dissolved Organic Matter

Soil dissolved organic matter (DOM) is composed of a mass of complex organic compounds in soil solutions , significantly affects a range of (bio)geochemical processes in soil environment. However, how the chemical complexity (i.e., heterogeneity and chemodiversity) of soil DOM molecules affects their proton and metal binding ability remains unclear, which limits our ability for predicting the environmental behavior of DOM and metals. In this study, we developed a unified modeling approach for quantifying the proton and metal binding ability of soil DOM based on Cu titration experiments, Fourier transform ion cyclotron resonance mass spectrometry data , molecular modeling method. Although soil DOM samples from different regions have enormously heterogeneous and diverse properties, we found that the molecules of soil DOM can be divided into three representative groups according to their Cu binding capacity. Based on the molecular models for individual molecular groups and the relative contributions of each group in each soil DOM, we were able to further develop molecular models for all soil DOM to predict their molecular properties and proton and metal binding ability. Our results will help to develop mechanistic models for predicting the reactivity of soil DOM from various sources.

Automated summary

Soil dissolved organic matter (DOM) is a complex mixture of organic compounds in soil solutions, which has a significant impact on various biogeochemical processes in the soil environment. However, the relationship between the chemical complexity of soil DOM molecules and their proton and metal binding abilities is still unclear, limiting our ability to predict the behavior of DOM and metals in the environment. In this study, we developed a modeling approach to quantify the proton and metal binding abilities of soil DOM, based on Cu titration experiments, Fourier transform ion cyclotron resonance mass spectrometry data, and molecular modeling methods. Despite the heterogeneity and diversity of soil DOM properties in samples from different regions, we were able to classify the molecules into three representative groups based on their Cu binding capacity. By developing molecular models for each group and considering their relative contributions in each soil DOM sample, we could predict the molecular properties and binding abilities of soil DOM as a whole. These findings will contribute to the development of mechanistic models for predicting the reactivity of soil DOM from different sources.