Technical University of Denmark, Department of Environmental Engineering, Bygningstorvet 115, DK-2800, Kongens, Lyngby, Denmark; Department of Industrial Engineering, University of Padova, via Marzolo 9, 35131, Padova, Italy.
Technical University of Denmark, Department of Environmental Engineering, Bygningstorvet 115, DK-2800, Kongens, Lyngby, Denmark; DHI A/S, Agern Allé 5, 2970, Hørsholm, Denmark.
Chemosphere. 2020 Apr;244:125534. doi: 10.1016/j.chemosphere.2019.125534. Epub 2019 Dec 4.
Perfluoroalkyl acids (PFAAs) bioaccumulate in crops, with uptake being particularly high for short-chain PFAAs that are constantly transported with transpiration water to aerial plant parts. Due to their amphiphilic surfactant nature and ionized state at environmental pH, predicting the partitioning behavior of PFAAs is difficult and subject to considerable uncertainty, making experimental data highly desirable. Here, we applied a plant uptake model that combines advective flux with measured partition coefficients to reproduce the set of empirically derived plant uptake and soil-partitioning data for nine PFAAs in red chicory, in order to improve the mechanistic understanding and provide new insights into the complex uptake processes. We introduced a new parameter for retarded uptake (R) to explain the slow transfer of PFAA across biomembranes of the root epidermis, which has led to low transpiration stream concentration factors (TSCFs) presented in literature so far. We estimated R values for PFAAs using experimental data derived for red chicory and used the modified plant uptake model to simulate uptake of PFAA into other crops. Results show that this semi-empirical model predicted PFAAs transport to shoots and fruits with good accuracy based on experimental root to soil concentration factors (RCF) and soil to water partition coefficients (K) as well as estimated R values and plant-specific data for growth and transpiration. It can be concluded that the combination of rather low K with high RCF and the absence of any relevant loss are the reason for the observed excellent plant uptake of PFAAs.
全氟烷基酸（PFAAs）在作物中积累，短链 PFAAs 特别容易被吸收，它们会随着蒸腾水流不断被运输到植物的空中部分。由于其两亲性表面活性剂性质和在环境 pH 值下的离子状态，预测 PFAAs 的分配行为具有挑战性，并且存在相当大的不确定性，因此非常需要实验数据。在这里，我们应用了一种植物吸收模型，该模型将平流通量与测量的分配系数相结合，以重现九种 PFAAs 在菊苣中基于经验得出的植物吸收和土壤分配数据，以提高对复杂吸收过程的机制理解并提供新的见解。我们引入了一个用于解释 PFAA 跨根表皮生物膜缓慢转移的迟滞吸收（R）新参数，这导致了迄今为止文献中提出的低蒸腾流浓度因子（TSCF）。我们使用从菊苣中获得的实验数据来估计 PFAAs 的 R 值，并使用改进后的植物吸收模型来模拟 PFAA 进入其他作物的吸收情况。结果表明，该半经验模型基于实验得到的根到土壤浓度因子（RCF）和土壤到水分配系数（K）以及估计的 R 值和特定于植物的生长和蒸腾数据，能够很好地预测 PFAAs 向茎叶和果实的传输，具有良好的准确性。可以得出结论，低 K 值与高 RCF 以及缺乏任何相关损失的结合是观察到 PFAAs 良好植物吸收的原因。
