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Two-Phase Flow Modeling to Evaluate Effectiveness of Different Leachate Injection Systems for Bioreactor Landfills

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Abstract

Leachate injection in bioreactor landfills increases the moisture content within the municipal solid waste and facilitates rapid waste decomposition, thereby leading to early waste stabilization. Three types of leachate injection systems (LIS), namely, horizontal trenches (HT), vertical wells (VW), and drainage blankets (DB), are commonly used for leachate injection in bioreactor landfills. This study compares the performance of the three LIS to distribute a specific amount of injected leachate into a typical bioreactor landfill configuration considering the effects of waste characteristics, the rate of leachate injection, the mode of leachate injection, and saturated and unsaturated hydraulic conductivity parameters. A numerical two-phase flow model is used to predict evolution of saturation levels, pore-fluid pressures, when subjected to the same volume of leachate injection. Based on the results, the relative effectiveness of each LIS for achieving maximum uniform moisture distribution without inducing excessive pore-fluid pressures is determined. The results showed that the DB is effective in uniformly distributing the leachate and increasing the moisture levels across the landfill than the HT and VW for the same leachate injection rates. Intermittent mode of leachate injection was found to induce lower pore-water pressures in the waste while maintaining required saturation levels. The unsaturated hydraulic properties of waste were found to have considerable impact on moisture distribution by affecting the hydraulic conductivity of waste.

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Funding

This project was funded by the US National Science Foundation (grant CMMI #0600441 and CMMI #1537514), which is gratefully acknowledged.

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Correspondence to Krishna R. Reddy.

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Reddy, K.R., Kumar, G. & Kulkarni, H.S. Two-Phase Flow Modeling to Evaluate Effectiveness of Different Leachate Injection Systems for Bioreactor Landfills. Environ Model Assess 25, 115–128 (2020). https://doi.org/10.1007/s10666-019-09663-z

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