Luncheon Description: Due to evolving regulatory requirements, wastewater utilities face increasing pressure to monitor, characterize, and reduce PFAS discharges. This challenge is compounded by the diversity of potential industrial and consumer sources, as well as the technical complexity and cost associated with PFAS sampling and analysis. To address these challenges, South Platte Renew, University of Oklahoma, and Brown and Caldwell are collaborating to advance PFAS source identification in wastewater systems. The project evaluates the use of hyperspectral sensing applied to influent streams to collect high-frequency spectral data. This data is paired with targeted laboratory analyses of PFAS for validation. Machine learning techniques are then used to develop predictive models that correlate spectral signatures with PFAS presence and, where feasible, source characteristics. The long-term objective is to establish a reference library of spectral “fingerprints” associated with specific source types or discharge profiles. Such a library could enable more efficient and cost-effective source tracking, support prioritization of high-risk dischargers and targeted sampling efforts, and enhance regulatory compliance. It also has the potential to improve decision-making within utility operations and Industrial Pretreatment Programs, with broader applicability to other complex wastewater monitoring and source identification challenges.
Presenter: Anthony Hernandez is an Engineer II at South Platte Renew with a background in chemical engineering and cross-industry experience in process systems and analytical instrumentation. Prior to joining SPR, he supported beverage quality operations for Coca-Cola and Pepsi and worked with analytical systems in energy production facilities, gaining hands-on experience across 12 states in a variety of industrial environments. At South Platte Renew, Anthony supports process engineering and applied research initiatives, including work related to emerging contaminants such as PFAS. His experience with field instrumentation, data collection, and system troubleshooting contributes to ongoing efforts to improve monitoring strategies and better understand complex wastewater characteristics.
| 5/21/2026 |    |