Fuzzy Logic Modeling of Contamination Degree of Ni and V Metal Species in Sediments from the Crude Oil Prospecting Area of the Ondo Coast, Nigeria
No Thumbnail Available
Taylor and Francis
There are numerous statistical models for evaluating the degree of pollution in an environment. This study presents a fuzzy logic–based model—simple fuzzy classification (SFC)—for evaluating contamination of Ni and V species in the sediments of Nigeria’s Ondo coastal area. Concentrations of five species of these metals were obtained from 10 sampling sites following sequential extractions from sediments. The results were formulated into a fuzzy membership function matrix based on three classifications relative to regulatory standards and sediments’ degree of contamination. The results of the SFC show that the estuary is moderately enriched by Ni species in a range of 61–84% and further introduction of Ni may shift its contamination level into the highly polluted category. The SFC results also show that the estuary is clean of V species contamination in a range of 77–99%. The Ni and V were associated with the organic specie notably at the crude oil exploration site and at the coastal discharge point. Crude oil exploration and domestic wastes discharges are notable sources of metal contaminations into the estuary. However, the salinity incursion from the coastal ocean and prevailing biogeochemistry affect the species in which the metals exist.
fuzzy logic , heavy metals speciation , Ondo Estuary , sediments , Research Subject Categories::TECHNOLOGY::Information technology
Olu-Owolabi, B. I., Agunbiade, F. O., Oseghe, E. O., & Adebowale, K. O. (2012). Fuzzy logic modeling of contamination degree of Ni and V metal species in sediments from the crude oil prospecting area of the Ondo coast, Nigeria. Human and Ecological Risk Assessment: An International Journal, Vol.18(4), 902-918pp.