posted on 2017-10-22, 00:00authored byRajiv Kumar Giri
Disposal of municipal solid waste (MSW) in landfills is one of the most commonly adopted options to manage MSW in the United States and many other countries worldwide. Bioreactor landfills that involve controlled injection of leachate to increase moisture and distribute nutrients/microbes within the MSW are being practiced as a means for striving towards sustainability in solid waste management. In bioreactor landfill, enhanced moisture levels promote rapid MSW biodegradation, faster MSW compression and the waste stabilization, thus eliminating long term environmental risk to the surrounding environment and public. However, the dynamic coupled hydraulic, biodegradation and mechanical processes in bioreactor landfills significantly affect the MSW compression, slope stability and in-plane shear response (shear stress-displacement) of the composite side slope and base liner and final cover system. This study presented a new mathematical modeling framework based on a rational approach for designing new bioreactor landfills as well as optimizing the performance of existing bioreactor landfills subjected to coupled hydro-bio-mechanical processes. The mathematical modeling framework was developed by integrating and simultaneously solving a mechanical model based on plain-strain formulation of Mohr-Coulomb criterion, a hydraulic two-phase flow model based on 2-D unsaturated Richards’s equation and a biodegradation model formulated using the first-order decay kinetics similar to USEPA’s LandGEM model. The developed framework was validated based on previous laboratory experiment and a field monitoring study. Afterwards, the integrated mathematical framework was employed to evaluate the performance of bioreactor landfills, such as, flow and distribution of moisture, the stability of landfill slopes, the landfill settlement, the changes in geotechnical properties with waste degradation, and the interface shear stress-displacement response of composite side slope and bottom liner and final cover systems. Moreover, a parametric study using the coupled hydro-bio-mechanical framework was performed to assess various system designs and operational conditions, namely: the bioreactor landfill slope configurations, the geometric configuration of trench systems, and the modes (continuous v/s intermittent) of leachate injection. In addition, Monte-Carlo simulations and reliability assessment of performance of bioreactor landfills were carried out by employing the coupled mathematical framework to examine the influence of spatial variability (uncertainties) in major geotechnical properties of MSW (e.g., unit weight, shear strength, anisotropy, saturated hydraulic conductivity, initial saturation, porosity, residual saturation, and unsaturated hydraulic parameters). Overall, this research study provided a new mathematical modeling framework that can account for both spatial and temporal changes in major geotechnical properties of MSW due to the extent of degradation, and successfully predicts the long-term performance (e.g., landfill settlement and stabilization, slope stability, hydraulic response, and liner interface shear response) of bioreactor landfills subjected to coupled hydro-bio-mechanical processes during leachate injection. Additional research is warranted to formulate/validate the model to accurately account for biodegradation of MSW and its effects on constitutive behavior and geotechnical properties of MSW, validate the model based on full-scale field bioreactor performance data, evaluate coupled response of bioreactor landfills under various landfill configurations with varying cover and liner systems, and perform reliability assessment with variable mechanical, hydraulic and biodegradation properties of MSW. Moreover, the effects of temperature on properties of MSW and coupled processes should be investigated.
History
Advisor
Reddy, Krishna R.
Department
Civil Engineering
Degree Grantor
University of Illinois at Chicago
Degree Level
Doctoral
Committee Member
Issa, Mohsen
Foster, Craig
Khodadoust, Amid
Ai, Ning