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Quality assurance and quality control workflow for the non-targeted analysis of de facto water reuse
Citation:
Sayre-Smith, N., L. Brunelle, A. Batt, A. Chao, E. Carr, T. Cathey, J. McCord, J. Minucci, S. Purucker, A. Rashid, D. Smith, A. Williams, D. Alvarez, E. Furlong, S. Glassmeyer, D. Kolpin, M. Mills, AND J. Sobus. Quality assurance and quality control workflow for the non-targeted analysis of de facto water reuse. SERMACS, Durham, NC, October 25 - 28, 2023. https://doi.org/10.23645/epacomptox.24498436
Impact/Purpose:
N/A
Description:
Non-targeted analysis (NTA) studies of environmental systems generate a wealth of data that can be used to identify unexpected and/or unknown compounds that may affect human and ecological health. Though abundant environmental data ultimately enables a more complete assessment of risk, the profusion of data can be difficult to manage and interpret. Furthermore, accurate interpretations of NTA data must be founded upon appropriate quality assurance and quality control (QA/QC) protocols that are rooted in the study’s experimental design and incorporate statistical metrics with which to benchmark data integrity. Due to the complex and entangled data workflows of many NTA studies, practitioners in the field have developed generalized reporting standards, like the NTA “Study Reporting Tool” (SRT), to help guide various parts of the study design, including sample preparation, data acquisition, and QA/QC metrics. Although such theoretical frameworks exist, practical and explicit demonstrations of best practices remain lacking. As such, we report a NTA data analysis workflow that incorporates vendor software and a prototype U.S. Environmental Protection Agency (USEPA) web application in order to automate and standardize QA/QC protocols and outputs. Then as a proof-of-concept, we applied the NTA workflow to a de facto water reuse study done in collaboration with the U.S. Geological Survey and USEPA. The study was designed to investigate the fate and transport of water contaminants throughout a watershed representative of typical de facto water reuse. Included in the study were numerous quality control measures (e.g., system suitability mixture [SSM], pooled samples, various blanks, labeled spikes, technical replicates) which allowed for the quantitative evaluation of data integrity and, through the EPA web application, automated reporting. Specific outputs included summary tables of instrument accuracy, precision, sensitivity, and reproducibility (that of mass error and retention time drift); plots of sequencing, batching, and matrix effects; and visualizations of data filtering and flagging. After ensuring data integrity, we evaluated spatiotemporal trends utilizing k-means clustering, thus directing follow-up compound identification efforts.
URLs/Downloads:
DOI: Quality assurance and quality control workflow for the non-targeted analysis of de facto water reuse
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