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首页> 外文期刊>Environmental Monitoring and Assessment >Combining an experimental study and ANFIS modeling to predict landfill leachate transport in underlying soil-a case study in north of Iran
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Combining an experimental study and ANFIS modeling to predict landfill leachate transport in underlying soil-a case study in north of Iran

机译:结合实验研究和ANFIS模型来预测下层土壤中垃圾渗滤液的运输-以伊朗北部为例

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摘要

In the contemporary world, urbanization and progressive industrial activities increase the rate of waste material generated in many developed countries. Municipal solid waste landfills (MSWs) are designed to dispose the waste from urban areas. However, discharged landfill leachate, the soluble water mixture that filters through solid waste landfills, can potentially migrate into the soil and affect living organisms by making harmful biological changes in the ecosystem. Due to well-documented landfill problems involving contamination, it is necessary to investigate the long-terminfluence of discharged leachate on the consistency of the soil beds beneath MSW landfills. To do so, the current study collected vertical deep core samples from different locations in the same unlined landfill. The impacts of effluent leachate on physical and chemical properties of the soil and its propagation depth were studied, and the leachate-transport pattern between successive boreholes was predicted by a developed mathematical model using an adaptive neuro-fuzzy inference system (ANFIS). The decomposition of organic leachate admixtures in the landfill yield is to produce organic acids as well as carbon dioxide, which diminishes the pH level of the landfill soil. The chemical analysis of discharged leachate in the soil samples showed that the concentrations of heavy metals are much lower than those of chloride, COD, BOD5, and bicarbonate. Using linear regression and mean square errors between the measured and predicted data, the accuracy of the proposed ANFIS model has been validated. Results show a high correlation between observed and predicated data.
机译:在当今世界,城市化和先进的工业活动增加了许多发达国家的废料产生率。市政固体垃圾填埋场(MSW)旨在处理城市地区的垃圾。但是,排出的垃圾填埋场渗滤液(通过固体垃圾掩埋场过滤的可溶水混合物)可能会通过对生态系统造成有害的生物变化而迁移到土壤中并影响生物。由于有据可查的垃圾填埋场涉及污染的问题,因此有必要研究排放的渗滤液对城市固体废弃物掩埋场下土壤床层稠度的长期影响。为此,当前的研究从同一无衬里垃圾填埋场的不同位置收集了垂直深层岩心样本。研究了污水中渗滤液对土壤理化性质及其传播深度的影响,并通过使用自适应神经模糊推理系统(ANFIS)建立的数学模型预测了连续钻孔之间的渗滤液运移方式。在垃圾填埋场中,有机渗滤液混合物的分解将产生有机酸和二氧化碳,从而降低垃圾填埋场土壤的pH值。土壤样品中排放的渗滤液的化学分析表明,重金属的浓度远低于氯化物,COD,BOD5和碳酸氢盐。使用线性回归和实测数据和预测数据之间的均方误差,已验证了所提出的ANFIS模型的准确性。结果显示,观察到的数据与预测的数据之间具有高度的相关性。

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