Techno-environmental analysis measures treatment efficiency in Zambia, suggesting improvements for compliance and cost reduction.
Industrial expansion in Zambia has increased pollutant loads discharged into watercourses, necessitating robust and efficient effluent treatment. Existing systems often operate sub-optimally, with limited comprehensive analysis integrating technical performance with environmental and economic factors. This study aimed to assess the operational efficacy of prevalent industrial effluent treatment systems and develop a framework for their techno-environmental optimisation to enhance pollution control. A mixed-methods approach was employed, involving field sampling and laboratory analysis of influent and effluent from selected treatment plants. Performance was evaluated against Zambian regulatory standards. A techno-environmental optimisation model was developed using linear programming, with the objective function min Z = ∑ᵢ₌₁ⁿ (Cᵢ xᵢ + Eᵢ yᵢ) subject to contaminant removal constraints, where Cᵢ and Eᵢ represent cost and environmental impact coefficients for technology i. Approximately 65% of assessed systems failed to consistently meet permissible discharge limits for key parameters, notably biochemical oxygen demand and heavy metals. The optimisation model, validated with field data, demonstrated a potential reduction in operational costs by up to 22% while improving compliance, with a 95% confidence interval for the cost-saving estimate of [18%, 26%]. Current treatment infrastructure requires significant operational improvements. The proposed optimisation framework provides a viable, evidence-based pathway to enhance system performance and regulatory compliance cost-effectively. Implement regular performance audits guided by the developed model. Policy should encourage adoption of integrated techno-environmental assessments for new system designs and retrofits. effluent treatment, optimisation model, water pollution, industrial wastewater, Zambia, linear programming This research provides a novel, integrated techno-environmental optimisation model, calibrated with primary field data, to guide the cost-effective upgrade of industrial wastewater management.
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Mwale et al. (2021) studied this question.
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