Generic NICA-Donnan model parameters for proton binding by humic substances

Proton binding by humic substances is a key process in soil and aquatic systems. Prior research has shown that humic and fulvic acids exhibit distinct chemical behaviors, but the specific mechanisms remain unclear. No prior work had resolved how to generalize these behaviors across different sources. This gap motivated the need for a unified modeling framework. Existing studies often used site-specific data, which limited broader applicability. That uncertainty drove the search for a generic model. Researchers have long sought to predict proton binding without site-specific parameters. This gap motivated the development of a model that could apply broadly. The goal is to provide a tool for environmental modeling without requiring extensive local data.

The aim of this study is to develop a generic NICA-Donnan model for proton binding by humic substances. The specific problem is the lack of a widely applicable model for predicting proton binding in the absence of site-specific data. The motivation comes from the need to estimate proton binding in diverse environmental conditions. The study addresses this by analyzing 49 datasets from various sources. The goal is to derive model parameters that can be used universally. This approach allows for accurate estimation within a 20% margin of error. The study tests whether the NICA-Donnan model can capture both similarities and differences between fulvic and humic acids. The focus is on site density and binding affinity parameters.

The researchers used the NICA-Donnan model to analyze 49 datasets from literature and experiments. Each dataset represented proton binding by either fulvic or humic acids. The model was applied to fit the data and extract site-specific parameters. The analysis highlighted differences in site density and binding affinity between the two acid types. The model's success was evaluated based on its ability to describe the datasets accurately. Parameters were derived for both fulvic and humic acids separately. The model was then used to generate generic parameters for each acid type. These generic parameters are intended for use in modeling when site-specific data are unavailable.

The NICA-Donnan model successfully described proton binding for all datasets with high accuracy. The model revealed that fulvic acids have higher site density than humic acids. The maximum proton site density was 7.74 equiv kg-1 for fulvic acids and 5.70 equiv kg-1 for humic acids. The binding affinity parameters also differed between the two acid types. For fulvic acids, the recommended parameters include b = 0.57 and log KH1 = 2.34. For humic acids, the corresponding values are b = 0.49 and log KH1 = 2.93. The model estimates proton binding within approximately +/- 20% accuracy for a wide range of humic substances. These findings suggest the model can be used for general environmental modeling.

The NICA-Donnan model provides a reliable framework for estimating proton binding by humic substances. The model successfully captures differences in site density and binding affinity between fulvic and humic acids. The derived generic parameters allow for accurate predictions in the absence of site-specific data. The accuracy of the model is within approximately +/- 20% for a wide range of conditions. The study confirms that fulvic acids have higher site density than humic acids. The binding affinity parameters also show distinct patterns for each acid type. These findings support the use of the model for environmental modeling applications. The authors propose that the model can be applied broadly without requiring extensive local data.