Adsorptive removal of organics and nutrients from septic tank effluent using oak wood chip biochar: Kinetic analysis and numerical modeling

Chimdi Muoghalu , Herbert Cirrus Kaboggoza , Swaib Semiyaga , Musa Manga
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Abstract

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.
利用橡木木屑生物炭吸附去除化粪池污水中的有机物和营养物:动力学分析和数值模拟
化粪池系统虽然被广泛使用,但经常发生故障,将污染物释放到环境中。具有成本效益的抛光技术,如生物炭,一种富含碳的吸附剂,可以有效地处理化粪池污水,保护环境和公众健康。然而,研究主要集中在利用它来增强砂过滤器或湿地,依赖于商业生物炭,而没有研究粒度和制备条件对化粪池出水污染物去除的影响。此外,用于预测生物炭性能的机器学习工具尚未应用于化粪池污水处理。通过间歇式吸附试验,研究热解温度、热解时间和热解粒度对生物炭去除化粪池出水污染物(COD)和硝酸盐(NO3—N)效率的影响。生物炭对化粪池出水NO3—N(~ 64—98 %)和COD(~ 50—88 %)的最大吸附量分别为23.86 mg/g和235 mg/g。吸附遵循伪一阶模型,强调物理吸附在去除NO3-N和COD中的作用。方差分析表明,热解温度、热解时间和生物炭粒径对COD和NO3——N去除率有显著影响(p <; 0.05),最佳热解条件为700℃、5 h、细粒径(<;0.5 mm)生物炭。热解温度是影响生物炭理化性质的主要因素。人工神经网络模型准确预测化粪池出水NO3—N和COD去除率(R²>;0.98)。本研究通过提出一种创新和环保的方法来处理化粪池污水,从而推进可持续水管理。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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