ABSTRACT
There are significant gaps in air quality monitoring across many low- and middle-income countries, which can be filled by bioindicators like lichen. This study examined the links between lichen and air quality across urban environments in Nigeria. Lichen surveys and air quality monitoring were carried out across four major cities focusing on NO2, SO2, PM2.5, and PM10. Association rule mining was used to identify robust rules defining the association between lichen and air quality categories. For the maximal frequent set with Lichen in the antecedent, 9 and 5 rules were identified by A priori and Eclat, respectively. These indicated that three genera: Diorygma, Pyxine, and Physcia are the most commonly associated lichen with poor air quality particularly NO2 and SO2. This showed that these lichens are viable indicators of long-term air quality due to their consistent occurrence across the rules from different algorithms.
Acknowledgements
This research was funded by grant from the Tertiary Education Trust Fund (TETFUND), under the National Research Fund (NRF) grant. We are immensely grateful to Prof A. Aptroot for his help in the lichen identification.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Data availability statement
The scientific data for this study is deposited in the Mendeley Data platform: https://data.mendeley.com/datasets/dmzrf779st/1.
Declaration
We wish to confirm that there are no known conflicts of interest associated with this publication and there has been no significant financial support for this work that could have influenced its outcome. We confirm that the manuscript has been read and approved by all named authors and that there are no other persons who satisfied the criteria for authorship but are not listed.
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