Abstract
A direct, reagent-free, ultraviolet spectroscopic method for the simultaneous determination of nitrate (NO3−), nitrite (NO2−), and salinity in seawater is presented. The method is based on measuring the absorption spectra of the raw seawater range of 200–300 nm, combined with partial least squares (PLS) regression for resolving the spectral overlapping of NO3−, NO2−, and sea salt (or salinity). The interference from chromophoric dissolved organic matter (CDOM) UV absorbance was reduced according to its exponential relationship between 275 and 295 nm. The results of the cross-validation of calibration and the prediction sets were used to select the number of factors (4 for NO3−, NO2−, and salinity) and to optimize the wavelength range (215–240 nm) with a 1 nm wavelength interval. The linear relationship between the predicted and the actual values of NO3−, NO2−, salinity, and the recovery of spiked water samples suggest that the proposed PLS model can be a valuable alternative method to the wet chemical methods. Due to its simplicity and fast response, the proposed PLS model can be used as an algorithm for building nitrate and nitrite sensors. The comparison study of PLS and a classic least squares (CLS) model shows both PLS and CLS can give satisfactory results for predicting NO3− and salinity. However, for NO2− in some samples, PLS is superior to CLS, which may be due to the interference from unknown substances not included in the CLS algorithm. The proposed method was applied to the analysis of NO3−, NO2−, and salinity in the Changjiang (Yangtze River) estuary water samples and the results are comparable with that determined by the colorimetric Griess assay.
Highlights
Nitrate (NO3−) and nitrite (NO2−) are the essential nutrients for marine phytoplankton growth and play a key role in many biogeochemical cycles [1,2]
Many previous studies have suggested that the UV absorption spectrum of chromophoric dissolved organic matter (CDOM) in seawater fits an exponential function with wavelengths [36,37,38,39], which can be given in Equation (3)
The number of factors, or latent variables, is an important parameter governing the performance of the partial least squares (PLS) model
Summary
Nitrate (NO3−) and nitrite (NO2−) are the essential nutrients for marine phytoplankton growth and play a key role in many biogeochemical cycles [1,2]. Wet chemical analyses of NO3− and NO2− in seawater (e.g., the Griess assay) have been previously reviewed in the literature [4,5,6]. These chemical methods require the addition of chemical reagents, and are time-consuming, and waste is generated during measurement. The PLS model is built using a calibration or training set of samples that have known property values. The experimental spectra (matrix X) of single and mix standards, with known concentrations NO3−, NO2−, and salinity (matrix Y), were used as the calibration set. In PLS1, a separate set of scores and loading vectors is tuned and calculated for each variable (NO3−, NO2−, and salinity). The results from PLS1 and PLS2 models are compared
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