Greenhouse Gas Emissions Reductions from In-Situ Aeration in a Landfill: A Multi-Parameter Sensitivity Analysis Approach

Abstract

In this study, estimates of greenhouse gas (GHG) emissions (for methane, carbon monoxide and nitrous oxide) following the potential installation of an aerated bioreactor landfill system at the Mare Chicose landfill in Mauritius have been determined based on procedures outlined in the Approved Baseline and Monitoring Methodology AM0083, "Avoidance of landfill gas emissions by in-situ aeration of landfills" from the UNFCCC/CCNUCC CDM, and compared to the baseline emissions (flaring method) for a credit period of 10 years to compute emissions reductions (ERs). The second part of this study has employed a combined multi-parameter sensitivity analysis (MPSA) and response surface methodology (RSM) approach to assess the relative importance of 5 selected parameters in influencing the amount of ERs. This technique of data analysis is reportedly novel in this field of research in environmental engineering for GHG emissions quantification. The parameters tested were the monitored methane content in venting well/header k during in-situ aeration in the year y (MCCH4,v,k,q), monitored methane content from surface emissions during in-situ aeration in zone i in the quarter q (MCCH4,s,i,q), total volume of surface emissions in zone i in quarter q (SGs,i,q), potential methane generation capacity (L0,i) of the waste in landfill zone i as determined by sampling and lab analysis and fraction of degradable waste (fdg,i) in landfill zone i. Results from the MPSA and mesh plots from the RSM showed that L0,i had the most influence on the ERs. The largest ERs amounted to 835,104.61 tCO2e obtained from the variations in L0,i whereas 189,343.30 tCO2e was the lowest predicted ERs. The best working values for the five parameters with respect to a better environmental performance for minimal GHG emissions and maximum ERs were: 0.077-0.134 ton CH4/ton waste for L0,i, 0.713-0.8 for fdg,i, 688,829.30-972,916.67 m 3 for SGs,i,q, 1.01×10 -5 to 1.75×10 -5 tCH4/m 3 for MCCH4,v,k,q and 6.70×10 -8 to 5.16×10 -7 tCH4/m 3 for MCCH4,s,i,q. The results of this study present a novel tool of optimized parameter values and ERs data which can be used to decide on how to better design and operate the landfill in Mauritius under the Clean Development Mechanism.

Optimal control of greenhouse gas emissions and system cost for integrated municipal solid waste management with considering a hierarchical structure

“…Recent researches have determined that municipal solid waste (MSW) is a major contributor to global warming due to extensive emissions of greenhouse gases (GHGs) (Khan and Samadder, 2016;Mudhoo, et al, 2013;Muehle et al, 2010;O'Brien et al, 2014;Picao-Tadeo et al, 2014;Sanjeevi and Shahabudeen, 2016). GHGs could be emitted during the processes of MSW transportation, treatment, and disposal (Bunsan et al, 2013;Miller et al, 2013), and then trap heat in the atmosphere and lead to warming of the earth and changes in climate (Sanchez-Molina et al, 2014).…”

Uncertainty Assessment of Non-normal Emission Estimates Using Non-parametric Bootstrap Confidence Intervals

“…Numerous studies have attempted to reduce GHG emissions and their effects (e.g. Erickson et al, 2012;Millar et al, 2012;Shen et al, 2012;Mudhoo et al, 2013;Watson et al, 2013). The Kyoto Protocol was developed by United Nations Framework Convention on Climate Change to reduce GHG emissions (UNFCCC, 1997).…”