Total phosphorus analyses: is the convenience of automated inline-UV digestion robust enough for freshwater nutrient monitoring?

Abstract

Child AW, Moore BC. 2019. Total phosphorus analyses: is the convenience of automated inline-UV digestion robust enough for freshwater nutrient monitoring? Lake Reserve Manage. 35:140–147Phosphorus (P) is an essential and often growth-limiting nutrient in aquatic ecosystems. Excessive P in aquatic ecosystems can result in accelerated eutrophication and is a prime cause of “impaired” water quality listing under the Clean Water Act. Total phosphorus (TP) is a commonly used metric for predicting productivity and assessing nutrient enrichment in aquatic ecosystems. Accurate and precise TP data are essential for aquatic resource managers and scientists. Inline-ultraviolet (inline-UV) and persulfate digestions are both approved methods for estimating TP within water samples, and literature on their relative digestion efficiencies is available. However, the available literature to date has only evaluated relatively high TP concentrations, >90 µg P/L, considerably higher than critical trophic concentrations for natural lakes and streams. We compared inline-UV digestion with the more common autoclave persulfate digestion, analyzing TP from 32 freshwater sites in northern Idaho and eastern Washington. Sites were chosen to represent common ranges of TP (5 to 350 µg P/L) found in surface waters throughout the world. Both digestions performed adequately on third-party reference materials used for laboratory accreditation requirements. The linear model comparing logarithmic transformations of TP estimates from both digestion methods were correlated (p < 0.001, R2 = 0.8110), and suggested inline-UV digestion may not accurately estimate low-level TP concentrations in natural waters. Our results indicate that inline-UV digestion results are overall not comparable to autoclave digestion (absolute mean difference 16 µg/L or 22%, p < 0.001); lake managers should be aware that TP method selection can significantly alter data interpretation for nutrient monitoring plans.