Advancing Nitrogen Source Identification with Compounds Emerging Concern Co-Tracers and Isotope Analysis in Natural Waters

The application of stable isotope techniques toward the identification and quantification of nitrogen pollution has been a topic of significant interest in recent decades. The overlap of isotopic signatures for animal manure, septic waste, soil derived nitrogen, and ammonium-based fertilizers can obscure the source of pollutants, which are desirable to identify. To overcome this overlap of signals, the utilization of co-tracers, such as chemical compounds, which can be attributed to specific source inputs, becomes advantageous. An approach, which has commonly been utilized to identify chemical compounds – compounds of emerging concern (CECs) in this context – is the utilization of quantitative structure-activity relationship (QSAR) models. Through QSAR models, CECs may be identified and grouped based on known physical and chemical properties to predict their behavior in different scenarios. To better delineate sources of nitrate pollution, a QSAR analysis was applied with the aim of identifying CECs, which act as conservative environmental tracers and are specifically linked to nitrate pollution sources. For this purpose, stable nitrate isotope data was coupled with CEC data collected from several case study sites in Austria, France, Greece, and Nigeria. Additionally, nitrate isotope data was introduced to a Bayesian mixing model (MixSIAR) to delineate potential pollution sources. The QSAR model results revealed the CECs with high potential, and were compared with those of the MixSIAR model in order to identify those compounds, which could be strong candidates as co-tracers in nitrate pollution studies. Further, the parameters of the QSAR model were extracted to identify compound specific parameters which may be indicators for other compounds with tracer potential in future studies. The goal of this work was to identify CECs or types of CECs as robust co-tracers for nitrate source determination in order to better understand N cycling in ecosystems and contribute towards the protection and sustainable management of water resources.