We assessed the quality and pollution status of source surface waters in Zaria, Nigeria by monitoring the nature, cause and extent of pollution in Samaru stream, Kubanni River and Kubanni dam over a period of 10 months, between March and December 2002. A total of 228 water samples was collected from 12 sites and analysed for a total of ten physicochemical and one bacteriological quality indicators, using standard methods. Aesthetic water quality impairment parameters were also observed. The mean values of most water quality parameters were significantly higher (P < 0.05) in both the stream and river than in the dam. There was no significant correlation between faecal coliform counts (FCC) and water temperature (in the range 15-33°C); pH (5.77-7.32); and turbidity (1.4-567 NTU). The high FCC ranged from 2.0 × 10(1) to 1.6 × 10(6) MPN/100 ml and exceeded the WHO standards for drinking water and water used for fresh-produce irrigation, and correlated positively (P < 0.05) with conductivity (in the range 68-1,029 μS/cm); TDS (10.0-70.0 mg/l); TSS (10.0-70.0 mg/l); Cl (7.5-181 mg/l); PO(4)(-) P (0.01-0.41 mg/l); NO(3)(-) N (0.6-3.8 mg/l) and BOD(5) (0.1-14.9 mg/l). The main pollution sources were municipal wastewater, stormwater runoffs, the ABU sewage treatment plant, abattoir effluents and irrigation farms treated with chemical fertilisers. We conclude that these water bodies are potentially hazardous to public health and that proper sewage treatment and river quality monitoring are needed to warn against hazards to public health.

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Modeling of adsorption process establishes mathematical relationship between the interacting process variables and process optimization is important in determining the values of factors for which the response is at maximum. In this paper, response surface methodology was employed for the modeling and optimization of adsorption of phenol onto rice husk activated carbon. Among the action variables considered are activated carbon pretreatment temperature, adsorbent dosage, and initial concentration of phenol, while the response variables are removal efficiency and adsorption capacity. Regression analysis was used to analyze the models developed. The outcome of this research showed that 99.79% and 99.81% of the variations in removal efficiency and adsorption capacity, respectively, are attributed to the three process variables considered, that is, pretreatment temperature, adsorbent dosage, and initial phenol concentration. Therefore, the models can be used to predict the interaction of the process variables. Optimization tests showed that the optimum operating conditions for the adsorption process occurred at initial solute concentration of 40.61 mg/L, pretreatment temperature of 441.46 ∘ C, adsorbent dosage 4 g, adsorption capacity of 0.9595 mg/g, and removal efficiency of 97.16%. These optimum operating conditions were experimentally validated.

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The fate of end-of-life electronics (e-wastes) is of increasing concern because of their toxicity and ever increasing volumes. Addressing these concerns requires proper management plans and strategy which in turn requires reliable estimates of e-waste generation in the present as well as future times. In this study, a material flow model for the analysis of e-waste generation from computer equipments in Nigeria has been developed. Data used to develop the model are the sales data from major distributors of electronics, usage time of computer equipments and transfer coefficients of the electronics from one stage to another. The analysis of individual flows of computer from the material flow model showed that the fate of obsolete computer equipments were storage (41%), reuse (35%) and direct disposal (24%). The projections of the flows for a period of 15 years also indicated that storage and reuse of computer equipments would be preferred over direct disposal; and computer equipments would continue to remain in either storage, re-use or gradually disposed off for about 11 years after its inflow. This delay or staggering disposal is of advantage as it would reduce the amount of e-waste disposed yearly and also afford the country some time to make plans to accommodate and manage the e-wastes generated more efficiently.