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Assessment of the Water Quality of the Benin River, Southern Nigeria, Prior to the Seaport Development Project

Assessment of the Water Quality of the Benin River, Southern Nigeria, Prior to the Seaport Development Project
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摘要 Water resources in the form of rivers, oceans and seas are prime natural resources that man has either explored or exploited. The need for clean water is on the increase and water degradation due to industrialization and development has further exacerbated the state of water bodies’ degradation. The need to assess the quality status of the Benin River prior to the seaport development was inherent to document the baseline of the physicochemical parameters of the study stretch. Four stations were studied from Ajoki to opposite Young Town between January 2019 and December 2020. Physicochemical parameters and heavy metals for water were collected and analyzed adhering to quality assurance/control measures and standard procedures. Significant spatial variations (P < 0.001) were observed in water physicochemical parameters, except pH across the four stations. Principal Component Analysis (PCA), Pollution Load Index and Water Quality Index (WQI) were used to establish a relationship among water quality parameters and determine the water quality status. The first six components of PCA accounted for 87.77% of observed variations. WQI for sampling Station 2 was very poor for drinking (90.46) and Stations 1, 3 and 4 were unsuitable (113.13 - 188.21) for human consumption. PLI showed turbidity as the major pollutant across stations. The concentrations of heavy metals in the Benin River stretch are within background concentration level, except Fe and Cd. The mean dissolved oxygen was below the recommended level of 7 mg/l for aquatic life. The continuous monitoring of this stretch of the River during the seaport development activities and during operational stage is very paramount to prevent further degradation of the environment. Water resources in the form of rivers, oceans and seas are prime natural resources that man has either explored or exploited. The need for clean water is on the increase and water degradation due to industrialization and development has further exacerbated the state of water bodies’ degradation. The need to assess the quality status of the Benin River prior to the seaport development was inherent to document the baseline of the physicochemical parameters of the study stretch. Four stations were studied from Ajoki to opposite Young Town between January 2019 and December 2020. Physicochemical parameters and heavy metals for water were collected and analyzed adhering to quality assurance/control measures and standard procedures. Significant spatial variations (P < 0.001) were observed in water physicochemical parameters, except pH across the four stations. Principal Component Analysis (PCA), Pollution Load Index and Water Quality Index (WQI) were used to establish a relationship among water quality parameters and determine the water quality status. The first six components of PCA accounted for 87.77% of observed variations. WQI for sampling Station 2 was very poor for drinking (90.46) and Stations 1, 3 and 4 were unsuitable (113.13 - 188.21) for human consumption. PLI showed turbidity as the major pollutant across stations. The concentrations of heavy metals in the Benin River stretch are within background concentration level, except Fe and Cd. The mean dissolved oxygen was below the recommended level of 7 mg/l for aquatic life. The continuous monitoring of this stretch of the River during the seaport development activities and during operational stage is very paramount to prevent further degradation of the environment.
作者 Anthony E. Ogbeibu Priscilla A. Oriabure Anthony E. Ogbeibu;Priscilla A. Oriabure(Department of Animal and Environmental Biology, Faculty of Life Sciences, University of Benin, Benin City, Nigeria)
出处 《Journal of Water Resource and Protection》 2023年第11期597-610,共14页 水资源与保护(英文)
关键词 Water Quality Heavy Metals Principal Component Analysis Water Quality Heavy Metals Principal Component Analysis
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