A novel model concept for modelling the leaching of natural toxins: results for the case of ptaquiloside
Environmental Science: Processes & Impacts Pub Date: 2020-07-20 DOI: 10.1039/D0EM00182A
Abstract
Phytotoxins are a large class of highly diverse emerging environmental contaminants that have been detected at high concentrations in plants, water and soils. This study presents a novel modelling approach for assessing the fate of plant toxins in the soil–plant–atmosphere continuum, developed for the specific case of ptaquiloside (PTA), a carcinogenic phytotoxin produced by Pteridium aquilinum. The mechanistic model DAISY has been adapted for reproducing phytotoxin dynamics in plants, covering processes such as toxin generation in the canopy, wash off by precipitation and toxin recovery in the canopy after depletion events. Transport of the toxin in the soil was simulated by the advection–dispersion equation assuming weak sorption and degradation for two Danish soils. The model simulates realistic toxin contents in the plant during the growing season, where the actual PTA content is dynamic and a function of the biomass. An average of 48% of the PTA produced in the canopy is washed off by precipitation, with loads in the soil often in the order of mg m?2 and up to a maximum of 13 mg m?2 in a single rain event. Degradation in the soil removes 99.9% of the total PTA input to the soil, while only 0.1% leaches into the soil. The median annual flux-averaged predicted environmental concentrations during single events are often in the order of μg L?1, reaching up to 60 μg L?1 for the worst-case scenario. The simulated results for both degradation and wash off are of the same order of magnitude as the published data. Based on the results, we conclude that DAISY, with the newly implemented processes, is a useful tool for understanding, describing and predicting the fate of PTA in the soil. Further work comparing the model results with real data is needed for the calibration and validation of the model.
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Journal Name:Environmental Science: Processes & Impacts
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CAS no.: 89640-58-4