2020
DOI: 10.15244/pjoes/119098
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Spatio-Temporal Evaluation and Quantification of Pollutant Source Contribution in Little Akaki River, Ethiopia: Conjunctive Application of Factor Analysis and Multivariate Receptor Model

Abstract: Little Akaki River (LAR) is among the heavily polluted urban rivers in Ethiopia. A bimonthly physico-chemical and heavy metals water quality analysis was conducted aimed at assessing the spatio-temporal characteristics and quantifying sources contributing to the pollution during dry and wet season at 22 montoring stations. Accordingly, laboratory analysis results indicated that most of the constituents deviated from the national and international guideline limits and the river is critically polluted at the mid… Show more

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Cited by 22 publications
(8 citation statements)
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“…The sample points W4 and W2 recorded the lowest average values of 6.63 and 7.42 throughout the rainy and dry seasons, respectively. The lowest results were most likely attributable to the entry of commercial garbage from the town ( Angello et al., 2021 ) as well as the inflow of leachate from the disposal site during the rainy season. The lowest value of W4 during the rainy season was caused by the decomposition of organic materials in the town's wastewater.…”
Section: Resultsmentioning
confidence: 99%
See 1 more Smart Citation
“…The sample points W4 and W2 recorded the lowest average values of 6.63 and 7.42 throughout the rainy and dry seasons, respectively. The lowest results were most likely attributable to the entry of commercial garbage from the town ( Angello et al., 2021 ) as well as the inflow of leachate from the disposal site during the rainy season. The lowest value of W4 during the rainy season was caused by the decomposition of organic materials in the town's wastewater.…”
Section: Resultsmentioning
confidence: 99%
“…During the wet and dry seasons, TDS levels were 55 mg/L (T2) to 85.3 mg/L (W4) and 115 mg/L (T2) 204.7 mg/L (W5), respectively ( Table 4 ). During the wet season, W4 had the highest average TDS and EC due to runoff inflow from both urban and rural regions ( Angello et al., 2021 ; Bouslah et al., 2017 ); as well as leachate from a nearby landfill site ( Angello et al., 2021 ; Bouslah et al., 2017 ; Mekonnen et al., 2020 ). High temperatures accelerated evaporation and increased ionic content in river water throughout the dry period, resulting in the highest mean value ( Ngabirano et al., 2016 ).…”
Section: Resultsmentioning
confidence: 99%
“…The raw data need to be standardized as air quality parameters have different magnitudes and scales of measurements according to Z-scale to a mean of 0.0 and variance of 1.0 by using equation ( 2), [19,20]:…”
Section: Air Quality Monitoring Stationmentioning
confidence: 99%
“…The raw data need to be standardized as air quality parameters and meteorological parameters have different magnitudes and scales of measurements according to Z-scale by using Equation ( 1), [26,27]:…”
Section: Canonical Correlation Analysismentioning
confidence: 99%