Background element content of the lichen Pseudevernia furfuracea: a comprehensive overview. From the supranational state of art to a new methodological framework for the assessment of regional benchmarks

In biomonitoring, the knowledge of Background Element Content (BEC) values is an essential pre-requisite for the correct assessment of pollution levels. Supranational BECs for the highly performing lichen biomonitor Pseudevernia furfuracea were estimated by a literature review integrated by an extensive field survey. Methodologically homogeneous element content datasets, reflecting different exposure conditions across 16 countries, were compiled and comparatively analysed. Element content in samples from remote areas was compared to that of potentially enriched samples, indicating that the former were unaffected by anthropogenic contributions, thus allowing to propose their metrics as a supranational benchmark. The literature survey revealed a huge methodological variability: in particular, the sample acid digestion was identified as one of the most neglected pieces of information. Indeed, such analytical step was never expressly considered in the built up of review-based lichen BEC values, introducing a bias due to the merging of data from highly heterogeneous sample digests. Therefore, limited to original data from Italy, we investigated the variability of 43 elements in remote mountain areas, after having digested samples with two acid mixtures, with and without HF (i.e. total vs. partial digestion), both associated to ICP-MS multi-element analysis. The digestion performance was evaluated by comparing analytical results of field samples with the accuracy obtained on the standard BCR 482 (P. furfuracea). Overall, the total digestion showed a better performance, especially for Al, As, Ba, Cd, Cu, Fe, Mn, Ni, Sn and Zn. Moreover, the sampling sites were characterized for anthropization, land use, climate and lithology at different scale resolution and the relationships between environmental descriptors and BECs based on partial sample digestion were tested by Principal Component Regression (PCR) modelling. Elemental composition resulted significantly dependent on land use, climate and lithology and regression models correctly reproduced the content of lithogenic elements at randomly selected sites. Finally, a methodological gap in biomonitoring procedures was filled by providing two sets of BEC values based on different sample digests for use as a reference in biomonitoring applications. Since BEC patterns were proved to be context-dependent, both sets referred to environmentally homogeneous macro-regions, thoroughly identified by a multivariate approach.