title: Exploration of the spatial-Composite Risk Index (CRI) for the characterization of toxicokinetics in petrochemical active areas.
abstract: The spatial modeling of the petrochemical active regions in the Niger Delta (ND), Nigeria was carried out through the analysis exploration and extraction of geospatial data and resultant risk maps were generated. The pollutants assessed include; heavy metals, polychlorinated aromatic hydrocarbons (PAHs), benzene-toluene-ethylene-xylene (BTEX), and total petroleum hydrocarbons (TPHs) and properties of the pollutants such as bioaccumulation, persistence and toxicity were used to calculate the Hazard Index (HI) and thus created a ranking system. The Composite Risk Index (CRI) was developed successively considering the concentrations of all pollutants and the computed HI using the samples collected in ND areas of Nigeria. The carcinogenic PAHs showed spatial abundance in the areas sampled and elevated levels of soil heavy metals were also observed. In this study, mathematical tool such as the artificial neural network (ANN) self-organizing map (SOM) and geostatistical analysis such as kriging were applied to develop the risk map of the areas which represent the spatial spread of the CRI. The results show that the application of spatially developed integral risk map for pollutant assessment is effective and facilitates with decision making with regards the environment and humans exposed in this region.
authors.affiliation: The John and Willie Leone Family Department of Energy and Mineral Engineering, The Pennsylvania State University, University Park, PA 16802, USA. rzo5017@psu.edu
authors.forename: Richard
authors.initials: R
authors.lastname: Olawoyin
mesh_terms: D004784:Environmental Monitoring; D004785:Environmental Pollutants / Q000737:chemistry / Q000378:metabolism*; D006801:Humans; D006838:Hydrocarbons / Q000737:chemistry / Q000378:metabolism* / Q000633:toxicity; D007700:Kinetics; D019216:Metals, Heavy / Q000737:chemistry / Q000378:metabolism* / Q000633:toxicity; D016571:Neural Networks, Computer; D010578:Petroleum; D011084:Polycyclic Aromatic Hydrocarbons / Q000737:chemistry / Q000378:metabolism / Q000633:toxicity; D018570:Risk Assessment
chemical_list: D004785:Environmental Pollutants; D006838:Hydrocarbons; D019216:Metals, Heavy; D010578:Petroleum; D011084:Polycyclic Aromatic Hydrocarbons
keywords: Hazard index; Modeling; Pollutants; Risk map; Self-organizing maps; Toxicokinetics