Estimating the nitrogen source apportionment of Sophora japonica in roadside green spaces using stable isotope

It is generally accepted that urban vegetation absorbs air pollutants resulting in improved air quality. However, limited work has provided experimental data that can be used to quantify this. In this study, Sophora japonica in the near-road environment was studied, and stable isotopes were used to estimate the proportional contributions of different nitrogen sources to the trees. δ¹⁵N and δ¹⁸O values were quantified for plant (n = 254) and soil samples (n = 86) collected from 12 sampling sites in Beijing. The elemental composition (total nitrogen (TN) and total carbon (TC)) of both samples types, and the ionic concentration (NO₃^- and NH₄⁺) of soil samples were also measured. δ¹⁵N in S. japonica sampled near the road was significantly lower than in samples collected far from the road. Variation of δ¹⁸O, TN, and TC in plant samples could not be explained by the road distance. Using the SIAR Bayesian isotope mixing model and the mixing polygon method, the average proportional contributions of three nitrogen sources for the tree samples among all experiment sites were estimated, with the proportion for each nitrogen source following the order: soil (69.2%) > traffic-related NO_x (19.3%) > dry deposition (11.5%). In addition, the results of the Bayesian model revealed that the nitrogen contribution of traffic-related NO_x at road-adjacent sites (23.0%) was higher than the contribution of traffic-related NO_x at sites far from the road (16.4%). These results indicated that the S. japonica in near-road green spaces was significantly influenced by traffic-related NO_x emissions that were characterized by lower δ¹⁵N values. We found that using the SIAR Bayesian isotope mixing model and mixing polygon method, the potential nitrogen sources of plants could be estimated and the proportional contributions estimated by the model can reflect the plant's ability to absorb air-borne NO_x.