A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Adsorptive removal of organics and nutrients from septic tank effluent using oak wood chip biochar: Kinetic analysis and numerical modeling
Septic systems, though widely used, often fail, releasing contaminants into the environment. Cost-effective polishing techniques like biochar, a carbon-rich sorbent, can effectively treat septic effluent, protecting the environment and public health. However, studies have focused on its use to enhance sand filters or wetlands, relying on commercial biochar without examining the effect of particle size and preparation conditions on contaminant removal from septic tank effluent. Additionally, machine learning tools for predicting the performance of biochar have not been applied in septic tank effluent treatment. We conducted batch adsorption tests to investigate the influence of pyrolysis temperature, time, and particle size on biochar’s efficiency in removing contaminants (chemical oxygen demand (COD) and nitrates (NO3--N)) from septic tank effluent. The biochar types effectively removed NO3--N (∼ 64–98 %) and COD (∼ 50–88 %) from septic tank effluent with maximum adsorption capacities of 23.86 mg/g and 235 mg/g, respectively. Adsorption followed a pseudo-first-order model highlighting the role of physisorption in eliminating NO3-N and COD. Analysis of variance tests revealed that COD and NO3--N removal efficiencies are significantly affected by pyrolysis temperature, time, and biochar particle size (p < 0.05), with optimal conditions being 700 °C, 5 h, and fine-sized (< 0.5 mm) biochar, respectively. Pyrolysis temperature predominantly influenced biochar’s physicochemical properties. The ANN model accurately predicted NO3--N and COD removal from septic tank effluent (R² > 0.98). This study advances sustainable water management by presenting an innovative and eco-friendly approach to treating septic tank effluent.
Adsorptive removal of organics and nutrients from septic tank effluent using oak wood chip biochar: Kinetic analysis and numerical modeling
Septic systems, though widely used, often fail, releasing contaminants into the environment. Cost-effective polishing techniques like biochar, a carbon-rich sorbent, can effectively treat septic effluent, protecting the environment and public health. However, studies have focused on its use to enhance sand filters or wetlands, relying on commercial biochar without examining the effect of particle size and preparation conditions on contaminant removal from septic tank effluent. Additionally, machine learning tools for predicting the performance of biochar have not been applied in septic tank effluent treatment. We conducted batch adsorption tests to investigate the influence of pyrolysis temperature, time, and particle size on biochar’s efficiency in removing contaminants (chemical oxygen demand (COD) and nitrates (NO3--N)) from septic tank effluent. The biochar types effectively removed NO3--N (∼ 64–98 %) and COD (∼ 50–88 %) from septic tank effluent with maximum adsorption capacities of 23.86 mg/g and 235 mg/g, respectively. Adsorption followed a pseudo-first-order model highlighting the role of physisorption in eliminating NO3-N and COD. Analysis of variance tests revealed that COD and NO3--N removal efficiencies are significantly affected by pyrolysis temperature, time, and biochar particle size (p < 0.05), with optimal conditions being 700 °C, 5 h, and fine-sized (< 0.5 mm) biochar, respectively. Pyrolysis temperature predominantly influenced biochar’s physicochemical properties. The ANN model accurately predicted NO3--N and COD removal from septic tank effluent (R² > 0.98). This study advances sustainable water management by presenting an innovative and eco-friendly approach to treating septic tank effluent.
Adsorptive removal of organics and nutrients from septic tank effluent using oak wood chip biochar: Kinetic analysis and numerical modeling
Chimdi Muoghalu (author) / Herbert Cirrus Kaboggoza (author) / Swaib Semiyaga (author) / Musa Manga (author)
2025
Article (Journal)
Electronic Resource
Unknown
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