Atmospheric wet and dry phosphorus deposition in Lake Erhai, China

Abstract

Lake Erhai is a potentially phosphorus (P)-limited lake and its water quality may have been affected by atmospheric P deposition. However, there have been few studies on atmospheric P deposition in this lake. In this study, we established five wet deposition monitoring sites and two dry deposition monitoring sites around Lake Erhai to quantify the wet and dry deposition of total phosphorus (TP), including dissolved inorganic phosphorus (DIP), dissolved organic phosphorus (DOP) and particulate phosphorus (PP) from July 2022 to June 2023. Wet deposition fluxes of P species were collected by automatic rainfall collection instrument, and dry deposition fluxes were estimated using airborne concentration measurements and inferential models. The results reveal that among the different P components, DOP had the highest contribution (50%) to wet TP deposition (average all sites 12.7 ± 0.7 mg P m2/yr), followed by PP (40%) and DIP (10%). Similarly, DOP (51%) was the major contributor to dry TP deposition (average two sites 2.4 ± 0.9 mg P m2/yr), followed by DIP (35%) and PP (14%). Wet deposition dominated the annual total TP deposition (wet plus dry), accounting for approximately 83%. The key seasons for dry deposition were spring and autumn, which accounted for 64% of the annual total dry TP deposition. In comparison, wet deposition was significantly higher in the summer, accounting for 73% of the annual total wet TP deposition. The results of the potential source contribution function and concentration-weighted trajectories analysis indicate that local source emission and long-range transport from surrounding cities jointly exerted a substantial influence on aerosol P concentrations, particularly in the eastern and northwestern regions of the lake. These findings provide a comprehensive understanding of the different P components in atmospheric deposition, which is beneficial for developing effective strategies to manage the P cycle in Lake Erhai.