Utilizing In Situ Ultraviolet-Visual Spectroscopy to Measure Nutrients and Sediment Concentrations in Stormwater Runoff


The capacity to collect meaningful data to estimate stormwater runoff water quality and subsequent system removal performance is key to selecting the appropriate solutions to protect water resources. Historically, grab sampling and automated composite sampling approaches have been used with training and comprehensive quality assurance protocols to produce defensible data. Innovative approaches use real-time ultraviolet-visual spectrometry (UV-Vis) can provide a powerful tool for understanding pollutant loading regionally. This study found that real-time UV-Vis sensing is a potential new tool for understanding stormwater effluent pollutant dynamics. Researchers compared data from real-time sensing using UV-Vis spectrometers to develop calibration curves for predicting pollutant concentrations in stormwater flows. Results from paired laboratory data and raw spectral data established calibrations for the stormwater runoff composition and support further investigations of the use of this technology to predict in situ concentrations of total Kjeldahl nitrogen (TKN), dissolved organic carbon (DOC), total phosphorus (TP), total suspended solids (TSS), total nitrogen (TN), and nitrate as nitrogen (NO3−N) resulted in robust models with R2 values in the range 0.99–0.93. Using partial least squares regression (PLSR) methods, the study demonstrated a strong correlation between concentrations generated by the raw absorbance data across the full available spectrum (220 to 730 nm). These results indicate the potential for developing specific stormwater calibration curves for pollutants of interest representative of stormwater runoff. Collectively, these results indicate that real-time UV-Vis spectrometers can redefine stormwater control monitoring by potentially delivering more accurate, more repeatable laboratory quality data instantaneously, with greater efficiency.

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Journal of Sustainable Water in the Built Environment



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