Abstract
Persistent organic pollutants (POPs) are globally distributed toxic contaminants. Since 1990, mosses have been used in the UNECE European Moss Survey as cost-effective biomonitors of atmospheric deposition. This study provides the first predictive maps of POP concentrations in mosses, revealing nationwide contamination patterns across Germany. As a case study within the Moss Survey, predictive models were built from POP concentrations measured at 21 sites in 2020 and combined with environmental and land-use data. Random Forest analyses explained more than 20% of the variance for seven of eleven POP groups, yielding robust spatial estimates, particularly for PAH, BDE 209, and DBDPE, despite moderate systematic differences. Explanatory power was limited for PCDD/F, PCDD/F TEQ values, DPTE, and HBBz, while HBCD, PBDE, DP, and PBT showed a moderate performance. A comparison with geostatistical reference maps indicated moderate to good concordance, though regional uncertainties persisted. Industrialized regions such as North Rhine–Westphalia, Rhine Neckar, Halle/Leipzig, and Saarland emerged as consistent hotspots, whereas rural and forested areas showed lower contamination. The findings highlight the value of moss surveys for spatial POP assessment and underscore the need for additional predictors, especially atmospheric deposition, and for integrating Random Forest models with geostatistical approaches such as regression kriging to enhance predictive accuracy.