A coupled ODE-diffusion modeling framework for removing organic contaminants in crops using a simple household method

Abstract

Organic contaminants are frequently detected in fresh crops and can cause severe damage to human health. To help control this risk, we introduce a diffusion-based model framework for estimating the removal efficiency for organic contaminants in fresh crops using a simple water soaking method. The framework was developed based on the diffusion coefficient of the organic contaminants, and its application indicates that the removal factor (RF) for organic contaminants has an inverse-exponential relationship with log Kow (Kow is the octanol-water partition coefficient), which thermodynamically restricts the removal efficiency for chemicals with large steady state log Kow. Additionally, the diffusion coefficient of the chemical in water affects the kinetic removal efficiency. For example, the RF simulated for glyphosate, which has a relatively high diffusion coefficient, is 0.592 (61.9% of the steady state RF) after soaking for 1 h, while the RF of lindane is 0.224, which is only 25.0% of the steady state RF. However, if a refreshing method is applied, the RF of lindane can be significantly improved even if more potatoes are used in the water bowl, and this has been demonstrated theoretically with the refreshing function. Model validation indicates that the macro properties of crops, e.g., the active area through which crop tissues interact with water, have a larger impact on the results than do the micro-properties of crops and the physiochemical properties of the organic contaminants. Comparison of our results with those of other studies shows that the simulated ranges for some pesticides compare well with experimental data collected using other household washing methods. However, for other pesticides such as HCB and DDT, the simulated results and current studies are inconsistent due to physical interactions between the water and crop tissues not considered in our model.