Optimizing the fugacity model to select appropriate remediation pathways for perfluoroalkyl substances (PFASs) in a lake

Increased anthropogenic activities have caused contamination of perfluoroalkyl substances (PFASs) in lakes worldwide. However, how to remediate their contamination remains unclear. In this study, a heavily polluted lake, Baiyangdian Lake in China, was selected to investigate current PFASs levels in multimedia, stimulate their transport fate based upon an optimized fugacity model, and finally identify appropriate remediation pathways. From 2008-2019, the average concentrations of PFASs in the lake increased approximately 7-40 times in the environment and biota. Spatially, with continuous import of perfluorohexane sulfonate (PFHxS) and perfluorooctanoic acid (PFOA), barring fish, a noticeable north-south difference was distinguished in the PFASs composition in multimedia from the lake. Based on the optimized fugacity model simulation, the water phase was the primary transport path (~76.5%) for PFASs, with a total flux of 333 kg y-1. Compared with bioaccumulation fluxes in submerged plants (6.2 kg y-1), emerged plants (2.6 kg y-1), and fish (1.1 kg y-1), the exchange flux of PFASs between water and sediment remained high (~94 kg y-1). Considering remediation cost, sediment cleaning is currently the most cost-effective pathway, while harvesting submerged plant could be a promising pathway in the future. This study provides a basis for remediating PFASs-polluted lakes on a global scale.