Unraveling the chemical fingerprint of the Miami River sources: Insights from high-resolution mass spectrometry and nontarget analysis

Abstract

This study investigated the chemical composition of waters in the heavily urbanized and historically polluted Miami River, Florida. The goal was to assess the different water sources and anthropogenic influence in this managed area using nontarget analysis (NTA) combined with high-resolution mass spectrometry (HRMS). Surface water samples were collected from 10 sites during five sampling events in the wet season of 2021 and 2022. The HRMS data was processed using Compound Discoverer™ version 3.3, and the results were analyzed using techniques including Principal Component Analysis and Kendrick Mass Defect plots. Results showed a gradient change in the chemical composition from the Everglades to Biscayne Bay endmembers. The Seybold Canal, an adjacent canal, was consistently identified as a unique source of contaminants, contributing its own specific set of tracers. Increased presence and intensity of organic contaminants along the waterway was observed, indicating significant anthropogenic influence in the area. The NTA and post-processing were evaluated for reproducibility, demonstrating robustness with a 71.2% average reproducibility for compounds detected in 3 out of 5 sampling trips. A detection frequency of 80% (4 out of 5) was the set criterion for detected compounds suggested as tracers. To prioritize samples, hierarchical cluster analysis was employed, and potential tracers for each water source were determined. Tracers included natural products and agricultural herbicides and insecticides for the Everglades, anthropogenic contaminants for the Seybold Canal, and a lack of unique tracers for Biscayne Bay. Additionally, urban-influenced contaminants such as flame retardants, insect repellents, pharmaceuticals, and non-agricultural herbicides were identified along the river. This study highlights the impact of human activities on the Miami River and demonstrates the effectiveness of NTA in differentiating and tracking water sources. The results emphasize the importance of reproducibility in NTA and provide guidance on implementing monitoring strategies by prioritizing samples based on chemical compositions.