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Moss biomonitoring and air pollution modelling on a regional scale: delayed reflection of industrial pollution in moss in a heavily polluted region?

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Abstract

A passive biomonitoring survey using terrestrial mosses was performed in a heavily polluted industrial region on the border between Czechia and Poland in a regular grid of 41 sampling points. The concentrations of 38 elements were determined in the moss samples, using Neutron Activation Analysis (NAA). Simultaneously, air pollution modelling was performed using the Czech reference methodology Symos’97 for the year of the sampling (2015) and 3 years prior (2012) in order to compare the results of both the approaches and evaluate the credibility of the moss biomonitoring method. The NAA results were transformed according to the principles of compositional data analysis and assessed using hierarchical clustering on principal components. The resulting clusters were compared with the results of air pollution modelling using one-way analysis of variance. The association of determined clusters with the pollution from industrial sources was confirmed only for the results of the 2012 modelling. This validates the complementarity of the air pollution modelling and the moss biomonitoring, ascertains the moss biomonitoring as a valid method for long-term pollution assessment and confirms one of the fundamentals of moss biomonitoring, the reflection of the atmospheric conditions prevailing in the period before the sampling.

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Acknowledgements

This paper was achieved in the frame of the projects SP2019/70 and LO1404 “Sustainable Development of ENET Center.” Authors would like to express their gratitude to Mr. Mark Landry for proofreading and language corrections.

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This paper was financially supported by the Ministry of Education, Youth and Sports of the Czech Republic.

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Motyka, O., Pavlíková, I., Bitta, J. et al. Moss biomonitoring and air pollution modelling on a regional scale: delayed reflection of industrial pollution in moss in a heavily polluted region?. Environ Sci Pollut Res 27, 32569–32578 (2020). https://doi.org/10.1007/s11356-020-09466-w

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