Use of Real-time Sensors to reduce drinking water nitrate exposures in rural public water supply systems
Christopher S. Jones, PhD; David Cwiertny, Ph.D., UI; Darrin Thompson, MPH, UI; Tianyi Li, BS, UI; Alex Sukalski, BS, UI
christopher-s-jones@uiowa.edu
Chris Jones is a Research Engineer with IIHR-Hydroscience and Engineering at the University of Iowa. His research focus is water quality.
Dave Cwiertny is Professor, Civil and Environmental Engineering, University of Iowa.
Darrin Thompson is Associate Director of the Center for Health Effects of Environmental Contamination, University of Iowa.
Tianyi Li recently finished her undergraduate training in chemistry at the University of Iowa.
Alex Sukalski is a Senior Application Developer at the Public Policy Center at the University of Iowa.
Learning objectives:
Participants will learn the risks of drinking high-nitrate water.
participants will learn how public water supplies comply with drinking water nitrate regulations.
Participants will learn how real-time monitoring can enhance compliance with drinking water regulations.
Discuss this presentation with the authors on Thursday, November 19 from noon – 12:30 on the Zoom Live-stream.
Abstract
Across the Midwestern U.S., Public Water Systems (PWSs) struggle with high levels of nitrate in source waters from intense agricultural activity. In the intensely farmed state of Iowa, nearly one-third of the state’s 900 public water supply systems are vulnerable to nitrate contamination and most of these systems serve rural Iowans. Leveraging a sensor network deployed across Iowa surface waters, we evaluated the potential of the Hach Nitratax SC Plus nitrate sensor, which uses UV-light absorption to quantify dissolved nitrate (NOx-N) down to 0.1 mg-N/L, for real-time monitoring of NOx-N in drinking water. For six different PWSs over multiple years, we compare NOx-N levels in source waters to those measured via traditional lab methods for US EPA compliance monitoring. We also evaluated sensor performance when applied to near-finished drinking water (filter effluent). We find good agreement between traditional analytical methods and in situ sensors. For example, for 771 filter effluent samples from 2006-2011, IC analysis averaged NOx-N of 5.8 ppm while corresponding sensor measurements averaged 5.7 ppm with a mean absolute error of 0.23 (5.6%). We identify several benefits of using real-time sensors in PWSs, including improved frequency to capture elevated NOx-N levels and as decision-support tools for NOx-N management. We believe these devices would reduce the risk of nitrate exposure for rural water users and enhance the service provided by these systems.
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