The presence of nitrate in groundwater and surface water in concentrations above levels suitable for human consumption is an increasingly common problem. This is mainly due to human activity, such as the excessive use of fertilizers and the inadequate deactivation of pits. Water analysis laboratories very often carry out analyses to determine nitrate to control the presence of this anion in water intended for human consumption. One of the most commonly used methods is spectrophotometry, both with commercially available kits and by direct measurement of specific wavelengths. However, in these methods, the presence of organic matter and chloride can influence the results obtained. Thus, in this study, the applicability of the simplification (without acidification) of two methods for the determination of nitrate in water by ultraviolet–visible absorbance was verified in the presence of the above-mentioned interfering factors, and it was found that the absorbance method at 220 nm corrected for the absorbance at 275 nm, in its simplified form without acidification, can be used with concentrations of organic matter of 20 mg L−1 for high nitrate concentrations (10 mg L−1 NO3-N).

  • SM-4500 without acidification is suitable for nitrate determination in the presence of chloride and organic matter.

  • The presence of organic matter up to 20 mg L−1 did not interfere with the analysis of nitrate by the simplified method.

  • The SM-4500 method should not be used at nitrate concentrations up to 10 and 20 mg L−1 of organic matter.

  • Avoiding the use of HCl is in line with the fifth principle of green chemistry.

Ultraviolet–visible (UV–Vis) spectrophotometry plays a crucial role in the characterization of water due to its effectiveness in the analysis of inorganic and organic compounds. It works by measuring the absorption or transmission of electromagnetic radiation in the UV–Vis regions of the electromagnetic spectrum. This technique is widely used in water analysis and environmental applications and provides a cost-effective and versatile method for assessing water quality. UV–Vis spectrophotometers enable rapid measurements, are simple, inexpensive, and require minimal sample preparation, making them valuable for drinking water quality monitoring and process control (Thomas et al. 2017; Shi et al. 2022).

A recurring problem in the analysis of individual species using UV spectrometry is interference due to absorption by other components in the analyzed systems, and the resulting increase in background absorption as well as the possible exceeding of measurement limits. Natural water consists of a complex matrix of components, of which mainly the inorganic components absorb in the UV wavelength range from 195 to 280 nm. (Collos et al. 1999; Johnson & Coletti 2002; Birkmann et al. 2018), while organic compounds absorb in the wavelength range from 220 to 280 nm, with absorption at 254 nm being typical for measurements of aromatic compounds (Korshin et al. 2009; Albrektienė et al. 2012). This results in a UV multicomponent spectrum, which is determined by superimposing the absorbances of the individual species. The direct measurement of nitrate by absorption of UV light is used in several methods, such as the Standard Methods for the Examination of Water and Wastewater 4500 NO3-B method (APHA/AWWA/WEF 2017) (measurement at 220 nm corrected by measurement at 275 nm), and the method described by the Adolfo Lutz Institute (Instituto Adolfo Lutz 2008) (measurement at 205 nm), both of which recommend prior acidification of the samples with HCl. The first method uses the intense absorption of nitrate in the 220 nm range. However, UV light is also strongly absorbed by dissolved organic substances in the same region of the spectrum (APHA/AWWA/WEF 2017), and certain saline constituents (such as hydroxides and carbonates) can also cause interference (Gross et al. 1999). Therefore, this method proposes to perform the measurement at two wavelengths for water with dissolved organic matter. In this method, the absorbance is measured at 220 nm, and a second reading at 275 nm, where the nitrate does not absorb UV light, is used as a correction for the absorbance of the organic matter at the shorter wavelength. In the second method, the absorbance is measured directly at 205 nm. Although Edwards et al. (2001) report that this method can be used without interference from the presence of organic matter at concentrations up to 20 mg L−1, Zhang et al. (2021) report that a humic acid concentration of 5 mg L−1 absorbance at 205 nm is negligible. According to Souto et al. (2006), interference from chloride ions was observed at concentrations above 50 mg L−1 when nitrate was determined at 205 nm.

Edwards et al. (2001) reported that, based on the observed characteristics of the studies of both methods, it would be logical to choose a wavelength with greater sensitivity (205 nm) for concentrations up to 4 mg L−1 NO3-N and less sensitive wavelengths (220 nm) for concentrations above that. These results were confirmed by previous studies (Silva et al. 2023), where linearity of absorbance at 205 nm was observed at concentrations up to 3 mg L−1 NO3-N. Different methods have been developed to analyze the quantification of nitrate (exclusively or together with other parameters) by reading the absorbance at different wavelengths (multivariate analytical models) or the second derivative in UV spectrophotometry, but they are suitable for specific samples, such as wastewater or seawater, or for the determination of different compounds together (Karlsson et al. 1995; Dahlén et al. 2000; Causse et al. 2017; Meyer et al. 2018).

The variability of the natural water composition in terms of pH and alkalinity, characteristics that indicate the need for acidification of samples according to Examination of Water and Wastewater (2017) and Gross et al. (1999), suggest that for low alkalinity water (with low concentrations of hydroxides and carbonates), acidification may not be necessary for spectrophotometric methods, which has been confirmed in previous studies, allowing the analysis to be performed in less time and with less risk, considering that the determination of nitrate concentration is increasing in many water analysis laboratories. Avoiding the use of excipients in the analytical procedures is also in line with the fifth principle of green chemistry, a growing and necessary ideology of developing green methods in analytical chemistry (Anastas & Eghbali 2010).

Therefore, the aim of the present work is to evaluate the applicability of the investigated methods for samples containing organics and chloride ions in the determination of nitrate concentration by UV spectrophotometry, as well as the need for prior acidification of samples for analysis, as recommended in the methods evaluated here, using a 24-fold design.

Materials

  • - Ultrapure water (AP) (Table 1);

  • - Standard nitrate NO3-N solution (1,000 ± 6 mg L−1, QuimLab-SpecSol);

  • - Standard chloride Cl solution (1,004 ± 6 mg L−1, QuimLab-SpecSol);

  • - Standard organic matter solution (COD) (potassium hydrogen phthalate) (1,000 ± 6 mg L−1, QuimLab-SpecSol).

Table 1

Ultrapure water characteristics

ParameterAnalysis methodValue
pH SM 4500-H+ Ba 8.01 
Conductivity (μS cm−1SM 2510 Ba 1.30 
Fe3+ (mg L−1Merck Spectroquant 14761b <0.03 
Mn2+ (mg L−1DIN 38406-2c <0.06 
SiO2 (mg L−1SM 4500-SiO2 D and Ea <0.09 
Na+ (mg L−1SM 3500-Na+ Ba <0.01 
K+ (mg L−1SM 3500-K+ Ba <0.01 
NO3-N (mg L−1DIN 38405-9c <0.14 
Cl (mg L−1SM 4500-Cl Ea <2.42 
Cl2-free residual chlorine (mg L−1SM 4500-Cl2 Ga <0.11 
Total hardness (mg CaCO3 L−1SM 2340 Ca 3.55 
Organic matter (mg L−1SM 4500-O Da <0.1 
ParameterAnalysis methodValue
pH SM 4500-H+ Ba 8.01 
Conductivity (μS cm−1SM 2510 Ba 1.30 
Fe3+ (mg L−1Merck Spectroquant 14761b <0.03 
Mn2+ (mg L−1DIN 38406-2c <0.06 
SiO2 (mg L−1SM 4500-SiO2 D and Ea <0.09 
Na+ (mg L−1SM 3500-Na+ Ba <0.01 
K+ (mg L−1SM 3500-K+ Ba <0.01 
NO3-N (mg L−1DIN 38405-9c <0.14 
Cl (mg L−1SM 4500-Cl Ea <2.42 
Cl2-free residual chlorine (mg L−1SM 4500-Cl2 Ga <0.11 
Total hardness (mg CaCO3 L−1SM 2340 Ca 3.55 
Organic matter (mg L−1SM 4500-O Da <0.1 

aStandard Methods for the Examination of Water and Wastewater (APHA) (AWWA), 23a ed., 2017.

bMerck Spectroquant kit.

cDeutsches Institut für Normung E.V. (DIN).

Preparation of the test solution

Using a mixture of ultrapure water and standard solutions of NO3-N, Cl and organics, intermediate solutions were prepared with concentrations based on the limits set by the Brazilian Ministry of Health Decree No. 888 (2021) which amended Annex XX of the Brazilian Ministry of Health Consolidation Decree No. 5 (2017). These concentrations were also based on known levels of nitrate, chloride, and organics found in real groundwater and surface water samples from the Maringá-PR region, as well as on the acidification of the samples. The concentration of NO3-N varied between 5 and 10 mg L−1, and the interference of chloride was evaluated with a concentration of Cl of 50 mg L−1 and of organic matter at 20 mg L−1 (Mantovani et al. 2018; Rezende et al. 2015, 2019; Brasil. Ministério da Saúde 2021). Acidification was tested with 1 M HCl (Dahlén et al. 2000; Oliveira 2007).

For both methods evaluated, the absorbance measurements were made in triplicate, and the values reported refer to the mean of these values.

Method 1: Spectrophotometric NO3-N determination method at 205 nm (A205) from Instituto Adolfo Lutz (Scorsafava et al. 2018) (IAL method)

In a test tube, 10 mL of the sample (for non-acidified assays) or 10 mL of the sample and 0.2 mL HCl 1 mol L−1 solution were homogenized (for acidified assays). Measurements were performed at 205 nm in a Merck Prove 600 UV–Vis spectrophotometer, using a quartz bucket with an optical path length of 10 mm.

Method 2: Standard Methods NO3-N spectrophotometric determination at 220 and 275 nm (APHA/AWWA/WEF 2017) (SM-4500 method)

In a test tube, 10 mL of the sample (for non-acidified tests) or 10 mL of the sample and 0.2 mL HCl 1 mol L−1 solution were homogenized (for acidified tests). Measurements were performed at 220 and 275 nm (designated A220 and A275, respectively) in a Merck Prove 600 UV–Vis spectrophotometer, using a quartz bucket with an optical path length of 10 mm.

The nitrate absorbance () was determined according to Equation (1):
formula
(1)

If the correction value (2A275) is more than 10% of A220, the method should not be used.

Factorial planning

To evaluate the importance of variables in relation to absorption by NO3-N, a factorial design 24 was performed according to Table 2. The factorial planning was performed without experiments with central points because one of the factors has no quantitative levels, which makes analysis at the central point impossible. The factorial planning matrix with the respective response values for A205 (for the IAL method) and (for the SM-4500 method) is shown in Table 3. To avoid statistical bias in the results, the tests were performed randomly.

Table 2

Factors and levels values in factorial planning

FactorsLevels
+
Nitrate 10 mg L−1 
Chloride 50 mg L−1 
Organic matter 20 mg L−1 
Acidification Not acidified 0.2 mL HCl 1 M  
FactorsLevels
+
Nitrate 10 mg L−1 
Chloride 50 mg L−1 
Organic matter 20 mg L−1 
Acidification Not acidified 0.2 mL HCl 1 M  
Table 3

Values of the factorial planning matrix for Methods 1 and 2

Factorial 24
RunNitrate (mg L−1)Chloride (mg L−1)Organic matter (mg L−1)Acidification
Not acidified 
10 Not acidified 
50 Not acidified 
10 50 Not acidified 
20 Not acidified 
10 20 Not acidified 
50 20 Not acidified 
10 50 20 Not acidified 
0.2 mL HCl 1 M 
10 10 0.2 mL HCl 1 M 
11 50 0.2 mL HCl 1 M 
12 10 50 0.2 mL HCl 1 M 
13 20 0.2 mL HCl 1 M 
14 10 20 0.2 mL HCl 1 M 
15 50 20 0.2 mL HCl 1 M 
16 10 50 20 0.2 mL HCl 1 M 
Factorial 24
RunNitrate (mg L−1)Chloride (mg L−1)Organic matter (mg L−1)Acidification
Not acidified 
10 Not acidified 
50 Not acidified 
10 50 Not acidified 
20 Not acidified 
10 20 Not acidified 
50 20 Not acidified 
10 50 20 Not acidified 
0.2 mL HCl 1 M 
10 10 0.2 mL HCl 1 M 
11 50 0.2 mL HCl 1 M 
12 10 50 0.2 mL HCl 1 M 
13 20 0.2 mL HCl 1 M 
14 10 20 0.2 mL HCl 1 M 
15 50 20 0.2 mL HCl 1 M 
16 10 50 20 0.2 mL HCl 1 M 

After preparing the solutions, the absorbance values of the samples were determined using the IAL method and the SM-4500 method.

R software was utilized to analyze the factorial design data using the FrF2 package of functions. The effects of the factors and their interactions as well as the obtained results were evaluated using regression models for each response variable, using confidence intervals at a 95% level.

The β0 coefficient obtained for each model is referred to as the axis coefficient, interpreted as the mean of y when all control variables are zero. The T-statistic presented for each of the coefficients (β1 to βn) aims to test the statistical significance of the effect of each factor on the response variable. The significance of the T-statistic is indicated by the p-value (MONTGOMERY 2005). For this design, the Breusch–Pagan tests indicate that the residuals of both regressions are homogeneous and satisfy the assumption of non-heteroscedasticity, and the Durbin–Watson tests indicate that the errors generated by the residuals of both regressions are independent and there is no effect of autocorrelation. The coefficient of determination (R2) is a measure of how well the model explains the variability of the data.

The results for absorbance at 205 nm (A205) (IAL method) and (SM-4500 method) are presented in Table 4. The IAL method has no specific requirements for applicability, except for the possibility of deviations from Beer's law at concentrations above 6 mg L−1 (Scorsafava et al. 2018). In addition, the SM-4500 method is applicable when the correction value (2A275) is less than 10% of A220. Otherwise, the method should not be used (APHA/AWWA/WEF 2017). Hence, its applicability was confirmed through the examination of the studied samples. It is worth noting that the method SM-4500 was found to be unsuitable for acidified samples containing 20 mg L−1 of organic matter, regardless of low (5 mg L−1) or high (10 mg L−1) nitrate content (essays 13–16), as well as for non-acidified samples with any tested concentration of organic matter but with the lowest nitrate concentration (5 mg L−1) (essays 5 and 7). Based on these findings, it can be concluded that the SM-4500 method can be used to samples containing up to 20 mg L−1 organic matter when the nitrate concentration is high (10 mg L−1) without the need to acidify the samples with HCl, indicating that no acidification step is required.

Table 4

Results obtained (nitrate-related absorbance) for factorial design using Methods 1 and 2

EssayA205SM-4500 method applicability
2.054 1.415 Applicable 
2.088 2.113 Applicable 
2.080 1.436 Applicable 
2.088 2.146 Applicable 
2.145 1.659 Not applicable 
2.176 2.136 Applicable 
2.222 1.811 Not applicable 
2.176 2.140 Applicable 
2.038 1.337 Applicable 
10 2.088 2.111 Applicable 
11 2.038 1.404 Applicable 
12 2.080 2.108 Applicable 
13 2.155 1.533 Not applicable 
14 2.166 2.059 Not applicable 
15 2.187 1.676 Not applicable 
16 2.155 2.073 Not applicable 
EssayA205SM-4500 method applicability
2.054 1.415 Applicable 
2.088 2.113 Applicable 
2.080 1.436 Applicable 
2.088 2.146 Applicable 
2.145 1.659 Not applicable 
2.176 2.136 Applicable 
2.222 1.811 Not applicable 
2.176 2.140 Applicable 
2.038 1.337 Applicable 
10 2.088 2.111 Applicable 
11 2.038 1.404 Applicable 
12 2.080 2.108 Applicable 
13 2.155 1.533 Not applicable 
14 2.166 2.059 Not applicable 
15 2.187 1.676 Not applicable 
16 2.155 2.073 Not applicable 

Taking into account the concentration range of the IAL method and the corrections needed for the SM-4500 method, both approaches were included in all experiments. This comprehensive approach enabled factorial planning analyses to provide insight into the significant factors influencing absorption. The results of the marginal means for the absorbance at 205 nm (for the IAL method) are shown in Figure 1, while the results for the absorbance at 220 nm corrected for the absorbance at 275 nm (for the SM-4500 method) are shown in Figure 2.
Figure 1

Marginal means diagram for the main effects of absorbance at 205 nm and the IAL method.

Figure 1

Marginal means diagram for the main effects of absorbance at 205 nm and the IAL method.

Close modal
Figure 2

Diagram of marginal mean values for the main effects of absorbance at 220 nm corrected by absorbance at 275 nm using the SM-4500 method.

Figure 2

Diagram of marginal mean values for the main effects of absorbance at 220 nm corrected by absorbance at 275 nm using the SM-4500 method.

Close modal

For the absorbance in the IAL method (Figure 1), it can be seen that the organic matter was the most influential factor (highest mean difference between factors). The other factors had little or no significant influence on this method. The importance of organic matter for this method is justified because this method is suitable for water with low organic matter content (Mazon et al. 2005), since according to Edwards et al. (2001), both organic matter (between 2 and 12 mg L−1 of polymaleic acid) and nitrate (between 0.4 and 4 mg L−1 NO3-N) strongly absorb wavelengths of this range. The fact that nitrate concentrations of 5 or 10 mg L−1 of NO3-N have no effect on absorbance indicates that this method is not a valid alternative for the determination of nitrate in the concentration range studied, since absorbance is expected to vary as a function of analyte concentration. This method was previously considered inadequate due to nonlinearity in the range of 1 to 7 mg L−1 NO3-N (Mazon et al. 2005).

In the results of the SM-4500 method (Figure 2), it can be seen that nitrate was the most influential factor, followed by organic matter. The influence of nitrate is to be expected since the 220 nm absorption method is designed to quantify this ion. Chloride and acidification of the medium, on the other hand, apparently had little or no effect in this case. The potential to omit acidification from the procedure is once again emphasized, thereby simplifying the analysis.

To determine whether the influence of the factors observed in the limit plots was statistically significant in relation to the results obtained (A205 and ), factorial regression models capable of describing the relationship between the response and the terms of the model obtained were constructed.

For the IAL method (absorbance at 205 nm), as already expected from the analysis of the marginal mean plots, it was found, in terms of model coefficients, that only the organic matter showed a statistically significant effect, with the coefficient βOrganic matter = 0.05175, t (5) = 15.66, p < 0.0001. This means that a change in organic matter concentration from 0 to 20 mg L−1 leads to an increase in method absorbance of 0.05175 on average, holding the effects of the other factors constant. However, as discussed in connection with the marginal mean plots, the non-significance of nitrate in this case (at concentrations of 5 and 10 mg L−1) indicates that this method is unsuitable for quantifying nitrate. Regarding the interactions, the steeper the lines go up or down and across, the more influential is the interaction of the tested factors. Figure 3 shows that the interaction between the factors nitrate and chloride and nitrate and organic matter has statistical significance at the 95% confidence level. Both interactions resulted in a decrease in method absorbance, taking into account the constant effects of the other factors, with an average decrease in absorbance of 0.0096 for an interaction between nitrate concentration and chloride concentration, and an average decrease in absorbance of 0.0106 for an interaction between nitrate concentration and organic matter concentration. From the latter two values, it appears that the interactive effect of the factors with the greatest impact was that between the nitrate concentration and the organic matter concentration. These data suggest that the non-significance of nitrate is due to the lack of linearity of absorbance at 205 nm with respect to nitrate concentration, but possibly such interactions at lower concentrations, where the behavior of absorbance at 205 nm is linear with respect to nitrate concentration, could actually affect the quantification of this ion.
Figure 3

Interaction diagrams of the factors for the absorption method at 205 nm.

Figure 3

Interaction diagrams of the factors for the absorption method at 205 nm.

Close modal
For the SM-4500 method, as also expected from the analysis of the plots, the factorial model showed statistical significance for the data, F (5, 10) = 189.5, p < 0.0001, R2 = 0.9974, which means that the variation of the factor levels in the model explained about 99.74% of the variation of the absorbance values for the SM-4500 method. The model estimated an overall mean absorbance value of 1.822, which was statistically significant at the 95% confidence level, β0 = 1.822, t (5) = 256.87, p < 0.001. Regarding the coefficients of the model, it is now found that all factors have a statistically significant effect: βnitrate = 0.2884375, t (5) = 40.66, p < 0.0001; βchloride = 0.0269375, t(5) = 3.80, p = 0.0127; βorganic matter = 0.0635625, t(5) = 8.96, p = 0.0003; and βacidification =−0.0346875, t(5) = −4.89, p = 0.0045. This means that changes in the concentrations of nitrate, chloride, and organic matter lead to an increase in absorbance, while acidification of the medium leads to a decrease, indicating that the acidification step leads to an underestimated quantification of nitrate. For each case, the value of the coefficients indicates how much the absorption increases or decreases on average. As for the interactions (Figure 4), the interactions between nitrate and chloride and between nitrate and organic matter were the only ones that showed statistical significance at the 95% confidence level. Both of these interactions, holding the effects of the others constant, also resulted in a decrease in method absorbance for an interaction between changes in nitrate concentration and chloride concentration, the average decrease in absorbance was 0.0209375, and for an interaction between changes in nitrate concentration and organic matter concentration, the average decrease in absorbance was 0.0723125. From these last two figures, it can be seen that the interactive effect of the factors with the greatest impact was again that between the nitrate concentration and the concentration of organic matter, which indicates the need for correction with the absorbance at 275 nm.
Figure 4

Interaction diagrams of the factors for the SM-4500 method.

Figure 4

Interaction diagrams of the factors for the SM-4500 method.

Close modal

In the factorial design, it was found that in the IAL method, the nitrate concentration (of 5 and 10 mg L−1 NO3-N) has no significant effect on the absorption. This indicates that this method does not obey Beer's law in these concentration ranges, so it should not be used for its intended purpose regardless of the presence or absence of confounding factors. In terms of factorial design, the SM-4500 method had as significant factors the nitrate concentration, the chloride concentration, the organic matter concentration, and the acidification of the sample. However, one should consider the applicability of this method (the double absorbance for organic material should not exceed 10% of the absorbance for nitrate), which indicates that this method in its standardized form should not be used in standard methods (with acidification) in the presence of organic material at a concentration of 20 mg L−1 for nitrate concentrations up to 10 mg L−1 NO3-N. Considering the results obtained in this study and the trend toward high nitrate concentrations increasingly observed in water analysis laboratories, the SM-4500 method in its simplified form (without acidification) can be considered suitable for nitrate determination, even in the presence of chloride (up to 50 mg L−1) and organic matter (up to 20 mg L−1) as interfering factors, with a confidence level of 95%, and environmentally friendly.

All relevant data are included in the paper or its Supplementary Information.

The authors declare there is no conflict.

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