نمایش مختصر رکورد

dc.contributor.authorHorsfall, I.T.en_US
dc.contributor.authorOkosa, I.en_US
dc.contributor.authorAdumbu, T.en_US
dc.contributor.authorEkiyor, T.H.en_US
dc.date.accessioned1399-11-28T14:15:42Zfa_IR
dc.date.accessioned2021-02-16T14:15:44Z
dc.date.available1399-11-28T14:15:42Zfa_IR
dc.date.available2021-02-16T14:15:44Z
dc.date.issued2021-04-01en_US
dc.date.issued1400-01-12fa_IR
dc.date.submitted2020-06-06en_US
dc.date.submitted1399-03-17fa_IR
dc.identifier.citationHorsfall, I.T., Okosa, I., Adumbu, T., Ekiyor, T.H.. (2021). Statistical evaluation of surface water quality parameters: the extent of industrial effluent pollution in urban settlement. International Journal of Human Capital in Urban Management, 6(2), 125-134. doi: 10.22034/IJHCUM.2021.02.02en_US
dc.identifier.issn2476-4698
dc.identifier.issn2476-4701
dc.identifier.urihttps://dx.doi.org/10.22034/IJHCUM.2021.02.02
dc.identifier.urihttp://www.ijhcum.net/article_47852.html
dc.identifier.urihttps://iranjournals.nlai.ir/handle/123456789/710576
dc.description.abstractABSTRACT: BACKGROUND AND OBJECTIVES: Industrial effluent contamination of water resources has emerged as a major challenge in developing and densely populated countries like Nigeria where river systems are the primary means for disposal of waste, especially the effluents from surrounding industries. This study seeks to determine the extent of surface water pollution from industrial effluent discharge. METHODS: Principal Component Analysis (PCA) and analysis of variance (ANOVA) were applied on the surface water quality data to identify the pollution sources and their contribution toward water quality variation. Water samples were collected from 4 sampling locations along the Onne-Okirika river. FINDING: The characteristics of the river showed a mean concentration of biochemical Oxygen Demand (BOD = 19.73 mg/l), Chemical Oxygen Demand (COD = 54.53 mg/l), Ammonia (NH3 = 21.00 mg/l), Dissolved Oxygen (DO = 5.78 mg/l) and temperature (28.40ᵒC) which varied significantly among sampling locations. Site 1, 2, and 3 showed a high level of NH3 and Chemical Oxygen Demand while site 4 (the control) has slightly high salinity when compared. The extent of pollution could be classified as; site 1 (High Pollution), site 2 (Moderate Pollution), and site 3 (Low Pollution). CONCLUSION: Sources of pollution include effluents from industrial plants such as fertilizer plants and oil refineries due to the high level of NH3. While the higher Chemical Oxygen Demand level is an indication of a greater amount of biodegradable organic material, which reduced the amount of Dissolved Oxygen. Additionally, a reduction in Dissolved Oxygen level can lead to an anaerobic condition, which is insidious to aquatic life forms. Therefore, the state environmental regulatory agency should ensure compliance monitoring of the industry's activities. =============================================================================================== COPYRIGHTS: ©2021 The author(s). This is an open access article distributed under the terms of the Creative Commons Attribution (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, as long as the original authors and source are cited. No permission is required from the authors or the publishers. ===================================================================================================en_US
dc.format.extent768
dc.format.mimetypeapplication/pdf
dc.languageEnglish
dc.language.isoen_US
dc.publisherMunicipality of Tehranen_US
dc.relation.ispartofInternational Journal of Human Capital in Urban Managementen_US
dc.relation.isversionofhttps://dx.doi.org/10.22034/IJHCUM.2021.02.02
dc.subjectExtenten_US
dc.subjectIndustrial effluenten_US
dc.subjectpollutionen_US
dc.subjectSurface water qualityen_US
dc.subjectPrincipal Component Analysis (PCA)en_US
dc.subjectUrban ecology and related environmental concernsen_US
dc.titleStatistical evaluation of surface water quality parameters: the extent of industrial effluent pollution in urban settlementen_US
dc.typeTexten_US
dc.typeORIGINAL RESEARCH PAPERen_US
dc.contributor.departmentDepartment of Agricultural and Bio-resources Engineering, Michael Okpara University of Agriculture, Umudike, P. M. B. 7267 Umuahia, Abia State, Nigeriaen_US
dc.contributor.departmentDepartment of Agricultural and Bio-resources Engineering, Michael Okpara University of Agriculture, Umudike, P. M. B. 7267 Umuahia, Abia State, Nigeriaen_US
dc.contributor.departmentDepartment of Agricultural and Bio-resources Engineering, Michael Okpara University of Agriculture, Umudike, P. M. B. 7267 Umuahia, Abia State, Nigeriaen_US
dc.contributor.departmentDepartment of Science Laboratory Technology, Ken Saro-wiwa Polytechnic, Bori, Rivers State, Nigeriaen_US
dc.citation.volume6
dc.citation.issue2
dc.citation.spage125
dc.citation.epage134


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