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    Spatial distribution and isotopic signatures of N and C in mosses across Europe
    (Elsevier B.V., 2025) Izquieta-Rojano, Sheila; Morera-Gómez, Yasser; Elustondo, David; Lasheras, Esther; Santamaría, Carolina; Torrens-Baile, Julen; Alber, Renate
    The accumulation of nitrogen (N) in moss tissue has proven to be a reliable marker of increasing N deposition. However, this measurement does not offer additional data about the origin of pollution. In this respect, the analysis of the N isotopic ratios might be a helpful tool in providing supplementary information about the nature of the nitrogenous species in biomonitoring surveys. Furthermore, isotopic signatures have been extensively used in the study of N and carbon (C) biogeochemical cycles. The main purpose of this study was to determine N and C elemental contents and their stable isotopes in mosses to investigate atmospheric pollution patterns across Europe. We aimed at identifying the main N polluted areas and evaluating the potential use of isotopic signatures in the attribution of pollution sources at a regional scale. With these objectives in mind, >1300 samples from 15 countries from Europe, all of them participants of the ICP-Vegetation programme 2005–2006, were analyzed for their C and N contents and ?15N and ?13C. The results were compared to those derived from EMEP model, which provided modeled deposition and emission data, as well as to the predominant land uses at the sampling sites (based on CORINE Land Cover). This evaluation suggests that additional measurements of stable C and N isotopes in mosses could be a valuable tool in European environmental surveys. Such measurements not only provide useful information for identifying probable pollution sources but also enable the quantification of their contributions, serving as biological indicators of significant environmental processes. This study presents the first quantitative assessment of major atmospheric nitrogen (N) sources based on stable isotope analysis on a European scale, establishing a framework for evaluating historical changes in N across the region. © 2024 The Author(s)