Determination of carbon, carbonate, nitrogen, and phosphorus in freshwater sediments by near-infrared reflectance spectroscopy: Rapid analysis and a check on conventional analytical methods

Sediments are typically analyzed for C, N, and P for characterization, sediment quality assessment, and in nutrient and contaminant studies. Cost and time required for analysis of these constituents by conventional chemical techniques can be limiting factors in these studies. Determination of these constituents by near-infrared reflectance spectroscopy (NIRS) may be a rapid, cost-effective method provided the technology can be applied generally across aquatic ecosystems. In this study, we explored the feasibility of using NIRS to predict total C, CO super(-) sub(3) super(2) organic C, N, and P in deep-water sediment cores from four Canadian lakes varying over 19 degrees of latitude. Concentration ranges of constituents in the samples (dry weight basis) were total C, 12-55; CO super(-) sub(3) super(2), 6-26; organic C, 7-31; N, 0.6-3.1; and P, 0.22-2.1 mg g super(-1). Coefficients of determination, r2, between results from conventional chemical analysis and NIR-predicted concentrations, based on calibrations across all the four lakes, were 0.97-0.99 for total C, organic C, and N. Prediction for CO super(-) sub(3) super(2) was good for the hard water lake from a calibration across all four lakes, but this constituent in the three soft water lakes was better predicted by a calibration across the soft water lakes. The NIR calibration for P fell below acceptable levels for the technique, but proved useful in the identification of outliers from the chemical method that were later removed with the re-analysis of several samples. This study demonstrated that NIRS is useful for rapid, simultaneous, cost-effective analysis of total C, CO super(-) sub(3) super(2), organic C, N, and P in dried sediments from lakes at widely varying latitudes. Also, this study showed that NIRS is an independent analytical tool useful for the identification of outliers that may be due to error during the analysis or to distinctive composition of the samples.