GIS and MATLAB modeling of criteria pollutants: A study of Lower Onitsha Basin during rains

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dc.contributor.authorAnyika, L. C.
dc.contributor.authorAlisa, C. O.
dc.contributor.authorNkwoada, A. U.
dc.contributor.authorOpara, A. I.
dc.contributor.authorEjike, E. N.
dc.contributor.authorOnuoha, G. N.
dc.date.accessioned2025-05-06T12:42:21Z
dc.date.available2025-05-06T12:42:21Z
dc.date.issued2018-10-14
dc.descriptionA research article with figures and tables
dc.description.abstractThe study of air pollutants SO2, NO2 and PM10 in lower Onitsha basin, a densely populated city was performed using GPS and Matlab modeling. The pollutants were studied in nine specific locations for 3 months of rains over 3 consecutive years with each georeferenced. The Matlab pollution model was generated by integrating the spatial database and measured pollution attributes database using a polynomial expression. SO2 highest concentration (141 µg/m3) peaked in Upper Iweka at sampling point 1 before dispersing to lower concentrated regions in Awada and Resthouse. NO2 peaked at 207 µg/m3 in Upper Iweka at sampling point 3 and driven by wind towards Borromeo area to very low concentration of 38 ug/m3. The PM10 peaked in Upper Iweka (180 µg/m3) and driven by rains towards Borromeo before increasing again in concentration levels at Awada. The AQI showed that SO2 pollutants had acceptable air quality at all sampling points while NO2 and PM10 air quality affected sensitive groups. SO2 concentration levels exceeded the National air quality standard in Nigeria (NAQS) while NO2 and PM10 were below the NAQS standard. The GIS plot showed that 3 metrological forces were driving pollutants from Upper Iweka and Awada to other sampling areas in the order of SO2> NO2> PM10. The Matlab wind speed plot showed that there was an upward wind in upper Iweka driving the pollutants towards dispersal at some other region. Thus, Upper Iweka is an active point source pollution area and dispersed to Borromeo and Awada by scavenging rains under prevailing wind speed, wind direction and humidity. Hence calls for improved monitoring and regulation to address poll.
dc.identifier.citationAnyika, L. C., Alisa, C. O., Nkwoada, A. U,, Opara, A. I., Ejike, E. N. & Onuoha, G. N. (2018). GIS and MATLAB modeling of criteria pollutants: A study of Lower Onitsha Basin during rains. Journal of Science, Technology and Environmental Informatics, 06(01), 443 - 457
dc.identifier.doihttps://doi.org/10.18801/jstei.060118.47
dc.identifier.issne-2409-7632
dc.identifier.uriwww.journalbinet.com
dc.identifier.urihttps://repository.futo.edu.ng/handle/20.500.14562/1835
dc.language.isoen
dc.publisherJournal BiNET Scientifc Publishing
dc.rightsAttribution-NonCommercial-ShareAlike 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/
dc.subjectPollutants
dc.subjectair quality
dc.subjectmodel
dc.subjectrains
dc.subjectOnitsha Nigeria
dc.subjectDepartment of Chemistry
dc.titleGIS and MATLAB modeling of criteria pollutants: A study of Lower Onitsha Basin during rains
dc.typeArticle

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