Lichen - air quality association rule mining for urban environments in the tropics.
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 carri...
| Publicado en: | International Journal of Environmental Health Research Vol. 34; no. 3; pp. 1713 - 1725 |
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| Autores principales: | , |
| Formato: | pictorial research tables/charts Journal Article |
| Publicado: |
Taylor & Francis Ltd
Mar2024
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=175749855&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 175749855 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 09603123 57L jtl: International Journal of Environmental Health Research issn: 09603123 maglogo: Y pubinfo: dt: Mar2024 vid: 34 iid: 3 pid: 377 pub: Taylor & Francis Ltd place: Philadelphia, Pennsylvania artinfo: ui: 175749855 166099185 175749855 175749855 10.1080/09603123.2023.2239716 175749855 ppf: 1713 ppct: 12 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Lichen - air quality association rule mining for urban environments in the tropics. aug: au: Lawal, Olanrewaju Ochei, Laud Charles affil: Department of Geography and Environmental Management, University of Port Harcourt, Port Harcourt, Nigeria sug: subj: Lichens Air Pollution Evaluation Urban Areas Biological Indicators Human Nigeria Low and Middle Income Countries Data Mining Nitrogen Oxides Algorithms Funding Source ab: 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. pubtype: Academic Journal doctype: pictorial research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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