Identification of Critical Water-Quality Parameters in an Abattoir-Impacted River Using Principal Component and Multivariate Statistical Analyses

Abattoir wastewater introduces organic matter, nutrients, suspended solids, microorganisms and potentially toxic metals into receiving rivers, producing complex water-quality responses that are difficult to interpret using single-parameter assessments. This study identified the critical variables and dominant pollution processes controlling water quality in the Effurun River, Delta State, Nigeria, using principal component analysis (PCA) and multivariate statistical analysis. Water samples were collected at an upstream control station, the abattoir-effluent discharge point and a downstream recovery station during rainy-season (June 2025) and dry-season (November 2025) campaigns on Days 1, 15 and 30, yielding 18 station-level observations. Physicochemical, nutrient, organic, heavy-metal and microbiological parameters were determined using standard laboratory procedures. Seasonal differences in the combined water-quality profile were assessed by multivariate analysis of variance, while PCA with varimax rotation was used for dimensionality reduction and identification of variables with absolute loadings of at least 0.70. Four retained principal components explained 92.62% of the total variance. After rotation, PC1 explained 49.12% and represented ionic-organic enrichment dominated by electrical conductivity, total dissolved solids, major ions, nutrients, chemical and biochemical oxygen demand, ammonium and heterotrophic bacteria. PC2 explained 25.48% and represented heavy-metal contamination, with high loadings for Pb, Zn, Cu, Fe, Cd, Mn and Cr. PC3 explained 12.15% and reflected suspended-solids, nutrient and microbial pollution, while PC4 explained 5.87% and represented oxygen-regime processes dominated by dissolved oxygen. The seasonal MANOVA was not statistically significant (Pillai's Trace = 0.667, F (14, 3) = 0.429, p = 0.881; partial eta squared = 0.667), indicating that the overall seasonal difference was not established at alpha = 0.05. The findings show that a relatively small group of highly loaded parameters can serve as priority indicators for routine monitoring and targeted pollution control in abattoir-impacted tropical rivers.

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Journal
International Journal of Safety Research
Published
2026-09-30
DOI
https://doi.org/10.11648/j.ijsr.20260103.13
Primary Topic
Water Quality and Pollution Assessment
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article
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Identification of Critical Water-Quality Parameters in an Abattoir-Impacted River Using Principal Component and Multivariate Statistical Analyses

Enemugha Emmanuel Ebikabowei, Onyeka Edike
International Journal of Safety Research
Water Quality and Pollution Assessment
article

Identification of Critical Water-Quality Parameters in an Abattoir-Impacted River Using Principal Component and Multivariate Statistical Analyses

Enemugha Emmanuel Ebikabowei, Onyeka Edike
article en

Abstract

Abattoir wastewater introduces organic matter, nutrients, suspended solids, microorganisms and potentially toxic metals into receiving rivers, producing complex water-quality responses that are difficult to interpret using single-parameter assessments. This study identified the critical variables and dominant pollution processes controlling water quality in the Effurun River, Delta State, Nigeria, using principal component analysis (PCA) and multivariate statistical analysis. Water samples were collected at an upstream control station, the abattoir-effluent discharge point and a downstream recovery station during rainy-season (June 2025) and dry-season (November 2025) campaigns on Days 1, 15 and 30, yielding 18 station-level observations. Physicochemical, nutrient, organic, heavy-metal and microbiological parameters were determined using standard laboratory procedures. Seasonal differences in the combined water-quality profile were assessed by multivariate analysis of variance, while PCA with varimax rotation was used for dimensionality reduction and identification of variables with absolute loadings of at least 0.70. Four retained principal components explained 92.62% of the total variance. After rotation, PC1 explained 49.12% and represented ionic-organic enrichment dominated by electrical conductivity, total dissolved solids, major ions, nutrients, chemical and biochemical oxygen demand, ammonium and heterotrophic bacteria. PC2 explained 25.48% and represented heavy-metal contamination, with high loadings for Pb, Zn, Cu, Fe, Cd, Mn and Cr. PC3 explained 12.15% and reflected suspended-solids, nutrient and microbial pollution, while PC4 explained 5.87% and represented oxygen-regime processes dominated by dissolved oxygen. The seasonal MANOVA was not statistically significant (Pillai's Trace = 0.667, F (14, 3) = 0.429, p = 0.881; partial eta squared = 0.667), indicating that the overall seasonal difference was not established at alpha = 0.05. The findings show that a relatively small group of highly loaded parameters can serve as priority indicators for routine monitoring and targeted pollution control in abattoir-impacted tropical rivers.

International Journal of Safety ResearchVol. 1(3)
Delta State University (NG), Nigeria Maritime University
Clean water and sanitation
Openalex Percentile: Top 21%
Water Quality and Pollution Assessment
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