Comparison of the silver nitrate and bacterial denitrification methods for the determination of nitrogen and oxygen isotope ratios of nitrate in surface water

Abstract

Nitrogen (N) and oxygen (O) isotope ratios of NO(3) (-) are often used to trace dominant NO(3) (-) pollution sources in water. Both the silver nitrate (AgNO(3)) method and the bacterial denitrification method are frequently used analytical techniques to determine delta(15)N- and delta(18)O-NO(3) (-) in aqueous samples. The AgNO(3) method is applicable for freshwater and requires a concentration of 100-200 micromol of NO(3) (-) for isotope determination. The bacterial denitrification method is applicable for seawater and freshwater and for KCl extracts of soils with a NO(3) (-) concentration as low as 1 micromol. We have carried out a thorough method comparison using 42 real surface water samples having a wide range of delta(15)N- and delta(18)O-NO(3) (-) values and NO(3) (-) concentrations. Various correction pairs using three international references and blanks were used to correct raw delta(15)N- and delta(18)O-NO(3) (-) values. No significant difference between the corrected data was observed when using various correction pairs for each analytical method. Both methods also showed excellent repeatability with high intraclass correlation coefficients (ICC). The ICC of the AgNO(3) method was 0.992 for delta(15)N and 0.970 for delta(18)O. The ICC of the bacterial denitrification method was 0.995 for delta(15)N and 0.954 for delta(18)O. Moreover, a positive linear relationship with a high correlation coefficient (r >or= 0.88) between the two methods was found for delta(15)N- and delta(18)O-NO(3) (-). The comparability of the methods was assessed by the Bland-Altman technique using 95% limits of agreement. The average difference between results obtained by the bacterial denitrification and the AgNO(3) method for delta(15)N was -1.5 per thousand with 95% limits of agreement -3.6 and +0.5 per thousand. For delta(18)O this was +2.0 per thousand, with 95% limits of agreement -3.3 and +7.3 per thousand. We found that for delta(15)N and for delta(18)O, 97% of the differences fell within these 95% limits of agreement. In conclusion, the AgNO(3) and the bacterial denitrification methods are highly correlated and statistically interchangeable.

Error assessment of nitrogen and oxygen isotope ratios of nitrate as determined via the bacterial denitrification method

“…Furthermore, in our study, the mean corrected δ 15 N and δ 18 O values of 132 (4 KNO 3 ‐IWS per batch) The KNO 3 ‐IWS measurements in these batches were 8.4 ± 1.0‰ for δ 15 N‐NO and 25.1 ± 2.0‰ for δ 18 O‐NO, which is 1.5‰ lower and 1.1‰ higher for δ 15 N and δ 18 O, respectively, as determined via TC/EA‐IRMS. This demonstrates the same tendency of underestimation for δ 15 N and overestimation for δ 18 O in the bacterial denitrification method as reported by Xue et al 12. The latter offsets for δ 15 N‐ and δ 18 O‐NO are, however, in the range of the computed overall uncertainties for the 33 batches (0.3 to 2.2‰ for δ 15 N and 0.8 to 2.5‰ for δ 18 O).…”

Drivers of atmospheric nitrate processing and export in forested catchments

“…Xue et al . [] compared δ 18 O‐ values in surface waters analyzed using both techniques, and concluded that the silver nitrate‐ and denitrifier‐derived results were highly correlated and generally statistically comparable. However, no precipitation samples were analyzed by Xue et al .…”

“…However, no precipitation samples were analyzed by Xue et al . [] and the range of δ 18 O‐ values in their study was −19‰ to +31‰. It is unclear whether analysis of precipitation nitrate samples would show the same degree of correlation between analytical methods.…”

Mass-Independent Isotopic Composition of Terrestrial and Extraterrestrial Materials

“…However, proper correction methods with international references (USGS32, USGS34, and USGS35) are needed. As a consequence, it is important to realize that the corrected isotope values are derived from a combination of several other measurements with associated uncertainties (Casciotti et al, 2007;Chmura et al, 2009;Xue et al, 2010).…”