Non-target Analysis of Wastewater Treatment Plant Effluents: Chemical Fingerprinting as a Monitoring Tool.

Abstract

This study aims at discovering and characterizing the plethora of xenobiotic substances released into the environment with wastewater effluents. We present a novel non-targeted screening methodology based on ultra-high resolution Orbitrap mass spectrometry and nanoflow ultra-high performance liquid chromatography together with a new data-processing pipeline. This approach was applied to effluent samples from two state-of-the-art urban, and one small rural wastewater treatment facility. In total, 785 structures were obtained, of these 38 were identified as single compounds, while 480 structures were identified at a putative level. The vast majority of these were therapeutics and drugs, present as parent compounds and metabolites. Using the R packages Phyloseq and MetacodeR, we here present a novel way of visualizing LCMS data while showing significant difference in xenobiotic presence in the wastewater effluents between the three sites. 1. SignificanceWe characterized a wide spectrum of xenobiotic substances using ultra-high performance liquid chromatography, and analysed the data with a new data-processing pipeline using microbial ecological tools to visualize and perform statistical testing of the chemical data to reveal trends in compound composition at the three WWTPs. This approach was applied to obtain and analyse data from effluent samples collected at three wastewater treatment facilities. In total, 785 chemical structures were achieved, with a majority identified as therapeutics and drugs. Several of the compounds are suspected endocrine disruptors. The data reveal a significant difference in compound diversity persisting in the wastewater effluents at the three sites. Our findings reveal the presence of undesirable compounds in effluent released into waterways, and address the greatest challenge in environmental chemistry - pinpointing single compounds of interest from masses of data produced.