Nazif Sara, Naeeni Seyed Taghi Omid, Akbari Zahra, Fateri Sara, Moallemi Mohammad Ali
School of Civil Engineering, College of Engineering, University of Tehran, Tehran, Iran.
School of Chemical Engineering, College of Engineering, University of Tehran, Tehran, Iran.
J Environ Manage. 2023 Dec 15;348:119241. doi: 10.1016/j.jenvman.2023.119241. Epub 2023 Oct 19.
Greywater, with limited content of pathogens, makes up more than half of the produced wastewater in urban areas. Given the high cost of wastewater management and treatment, it causes sense to collect greywater separately at the source and employ an on-site treatment system to increase opportunities for on-site water reuse. For this purpose, this paper aims to propose a multilayer granular filter as an inexpensive and simple on-site treatment method for greywater reuse. Furthermore, as determining the optimal structure of multilayer filters is a serious challenge, a simulation-optimization model is developed for determining the best filter configuration. An Artificial Neural Network (ANN) is trained based on experimental results to simulate the filter performance with different combinations of layers and the Genetic Algorithm (GA) is used to find the optimal thickness of different layers based on ANN simulation results. The proposed filter in this paper for greywater treatment consists of silica sand (in three different gradings) and activated carbon (with fixed grading) and treatment measures for evaluation of filter performance are considered as Chemical Oxygen Demand (COD) and Electrical Conductivity (EC). Due to difficulties in collecting, transferring, and storing the real greywater, synthetic greywater was used in this study. 49 experiments with different combinations of filter media thicknesses were performed and the performance of the filter was analyzed. Generally, three-layer filters perform better in COD and EC reduction, however, the average COD and EC elimination equals 36.3% and 15.1%, respectively, which indicates more efficiency of filter in COD reduction in comparison with EC. Based on the optimization-simulation model and experimental results, a filter consisting of 33 cm of fine sand, 20 cm of activated carbon, and 7 cm of medium sand results in the maximum efficiency and can reduce the COD and EC of greywater by 72% and 30%, simultaneously. According to the optimization outputs, the ideal filter can treat greywater up to having EC of 1000 μS/cm and COD of 321 mg/L, which is generally suitable for irrigation purposes.
中水病原体含量有限，占城市地区产生的废水的一半以上。鉴于废水管理和处理成本高昂，在源头单独收集中水并采用现场处理系统以增加现场水回用机会是有意义的。为此，本文旨在提出一种多层颗粒过滤器，作为一种廉价且简单的中水回用现场处理方法。此外，由于确定多层过滤器的最佳结构是一项严峻挑战，因此开发了一个模拟优化模型来确定最佳过滤器配置。基于实验结果训练人工神经网络（ANN）以模拟不同层组合的过滤器性能，并使用遗传算法（GA）根据ANN模拟结果找到不同层的最佳厚度。本文提出的用于中水回用的过滤器由硅砂（三种不同粒径）和活性炭（固定粒径）组成，用于评估过滤器性能的处理措施为化学需氧量（COD）和电导率（EC）。由于收集、转移和储存实际中水存在困难，本研究使用了合成中水。进行了49次不同过滤介质厚度组合的实验，并分析了过滤器的性能。一般来说，三层过滤器在降低COD和EC方面表现更好，然而，平均COD和EC去除率分别为36.3%和15.1%，这表明过滤器在降低COD方面比降低EC更有效。基于优化模拟模型和实验结果，由33厘米细砂、20厘米活性炭和7厘米中砂组成的过滤器效率最高，可同时将中水的COD和EC分别降低72%和30%。根据优化输出，理想的过滤器可将中水的EC处理至1000μS/cm，COD处理至321mg/L，这通常适用于灌溉目的。
