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STATISTICAL AND NUMERICAL ASSESSMENT OF PETROLEUM HYDROCARBON AND HEAVY METAL POLLUTION IN GROUNDWATER IN KWAWA COMMUNITY IN OGONILAND

Abstract

This study investigated mitigation strategies for reducing petroleum hydrocarbon and heavy metal pollution in groundwater within the Kwawa community in Ogoniland, Rivers State, with a focus on sediment analysis as a key component. The heterogeneity in physicochemical parameters within sediment samples from different locations, underscored the influence of geological, environmental, and anthropogenic factors on sediment composition in the area. These findings were crucial for environmental assessments and geological studies, aiding in the understanding of sediment characteristics and potential implications for the surrounding ecosystem. Groundwater analysis, provided essential insights into the chemical composition of samples collected from various locations within the study area. Concentrations of cations, anions, and selected heavy metals revealed potential variations across sampling stations, reflecting differences in biological activity, land use, and contamination sources within the groundwater. Notably, variations in nitrate content suggested influences from agricultural practices, industrial activities, and natural processes. Furthermore, fluctuations in concentrations of Fe3+, Fe2+, and manganese indicated potential contamination sources and geological characteristics within sampled groundwater locations. Overall, this study underscored the importance of comprehensive analysis and targeted mitigation strategies to safeguard groundwater quality in Kwawa and similar communities. Collaborative efforts between stakeholders were essential to implement effective mitigation measures, including remediation techniques, regulatory frameworks, and community education initiatives. By addressing the root causes of pollution and prioritizing environmental conservation, long-term health and resilience of groundwater resources could be ensured in K wawa and beyond.

Keywords

Vulnerability, Environmental Pollution, Statistical Analysis, Risk Assessment

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