Comparative study of three methods for the analysis of nitrate nitrogen in synthetic water and wastewater samples

摘要

Measurement of nitrate nitrogen is relatively less easy and reliable, given the complexity of analytical procedures already marred by interferences. Interfering constituents like organics are frequently integral to the nature of the samples. As a result, in practice nitrate nitrogen () concentrations often go under-/over-reported. Objective of this study was to compare three analytical procedures extensively used for determination of , namely Ultraviolet Spectrophotometric Screening (UV) Method, Nitrate Electrode Method (Ion-Electrode method) and Phenol Disulphonic Acid (PDA) Method. Usually, these methods of nitrate measurement are commonly employed based on availability of analytical facilities rather than the characteristics of the samples that carry many constituents other than nitrates also, which can limit their application in certain cases. The paper can help serve as a guide to method selection. Comparative investigation on the basis of Passing-Bablok and Bland-Altman analyses showed that when samples had no organics, the accuracy of the three methods was in the order: UV > PDA > Ion-Electrode. Ion-Electrode method was found to be affected by a positive bias of 0.799 for a confidence interval of (0.161, 1.436). For samples containing organics, all three methods were affected by proportional bias. UV method was most affected by interference, exhibiting a bias, regression intercept and slope coefficient of -1.733, -1.359 and 0.922, respectively. Interference due to organics was further analysed experimentally and accuracy with respect to rising organic concentration was found to be in the order: UV < Ion-Electrode < PDA, i.e. PDA method gave least percentage error for high organic concentrations. Multiple linear regression (MLR) models were developed for predicting more accurate readings. MLR models based on two and four explanatory variables for PDA (R-2 = 92.86%, predicted R-2 = 91.33%) and UV method (R-2 = 99.87%, predicted R-2 = 99.83%) respectively are reported.