Open Access Peer-reviewed Research Article

Investigation of Atmospheric Particulates in Two Raingauged Stations, Aba and Umuahia Meteropolis Nigeria Using Artificial Neural Network and Fuzzy Logic

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Comparative Analysis For Aba
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Submitted   Jul 13, 2025
Published   Oct 27, 2025
Issue    Vol 7 No 1 (2025)
DOI   10.25082/REIE.2025.01.004

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U. L. Onu
Department of Chemistry, Federal University of Technology, Owerri, Imo State, Nigeria
U. U. Egereonu corresponding author
Department of Chemistry, Federal University of Technology, Owerri, Imo State, Nigeria
A. I. Otuonye
Department of Information Technology, Federal University of Technology, Owerri, Imo State, Nigeria
S. K. Egereonu
Department of Information Technology, Federal University of Technology, Owerri, Imo State, Nigeria
O. C. Nwokonkwo
Department of Information Technology, Federal University of Technology, Owerri, Imo State, Nigeria

Abstract

This study conducts a thorough and multifaceted analysis of atmospheric particulate matter within the urban conglomerates of Aba and Umuahia, two prominent metropolitan areas in Abia State, Nigeria, both undergoing significant industrial and economic growth. Leveraging on advanced artificial neural network (ANN) and fuzzy logic framework, rainwater samples were meticulously collected from strategically located rain gauge stations, positioned at an optimal elevation of three meters over a carefully designed ten-week sampling period. These rainwater samples were employed to accurately quantify particulate matter concentrations, enabling the assessment of spatial and temporal variations, along with the broader atmospheric deposition dynamics. Results revealed considerable disparities in particulate concentrations, with Aba displaying significantly higher levels than Umuahia, likely attributable to heightened anthropogenic sources such as industrial emissions, vehicular exhaust, and urban activities. The mean particulate concentrations were also computed for both locations, yielding deeper insights into regional atmospheric chemistry. Furthermore, graphical analysis demonstrated an inverse relationship between rainfall frequency and particulate loading, corroborating the hypothesis of precipitation-induced atmospheric cleansing. The effectiveness of ANN based and fuzzy logic environmental models are further validated, underscoring their critical role in forecasting pollutant dispersion and facilitating sustainable urban air quality management policies.

Keywords
atmospheric particulates, ANN, fuzzy logic, precipitation, urban emissions

Article Details

How to Cite
Onu, U. L., Egereonu, U. U., Otuonye, A. I., Egereonu, S. K., Nwokonkwo, O. C., Onwuka, C., Enyia, C., & Emeagubor, A. O. (2025). Investigation of Atmospheric Particulates in Two Raingauged Stations, Aba and Umuahia Meteropolis Nigeria Using Artificial Neural Network and Fuzzy Logic. Resources Environment and Information Engineering, 7(1), 381-394. https://doi.org/10.25082/REIE.2025.01.004
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This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

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