Biochemical Methane Potential of Landfilled Municipal Solid Waste Using a Non-Slurry Approach

Abstract

The most widely-used procedure for forecasting landfill methane production in the laboratory is the biochemical methane potential (BMP) assay. Conventional BMP assays for assessing landfilled municipal solid waste (LMSW) use a slurry-based approach which simulates an environment that is predominantly liquid versus a predominance of solids in a landfill, which is likely to misrepresent actual landfill conditions, and could consequently lead to false gas volume predictions. This research was undertaken as a first-step towards modifying the current BMP assays to be more representative of natural landfill conditions termed; the Landfill BMP (LBMP) assay. Three sets of statistically-designed laboratory batch experiments were conducted using organic fraction of MSW to compare the CH4 generation potential (Lo), the rate of CH4 production (Rm) and the first-order rate coefficient (k) values from slurry-phase and solid-phase BMP experiments. The results showed statistically significant differences occurred between slurry-phase and solid phase BMP assays with Lo values obtained from slurry-phase experiments being overestimated by as much as 47 ±12%. Biosolids from Bonnybrook wastewater treatment plant, Calgary, was found to perform poorly compared to a laboratory-derived inoculum. Particle size reduction had a significant effect on Lo and Rm values with smaller particle sizes (< 10 mm) being optimal for CH4 gas production in solid-phase experiments in this study. The Lo values obtained from the LBMP method fell within the range of those obtained from lysimeter and field studies, indicating a possibility of solid-phase BMPs being more likely reliable in forecasting CH4 production from landfills than conventional BMP methods. However, k values were overestimated from both slurry and solid-phase conditions of moisture, suggesting that obtaining k values from laboratory experiments might not be the best approach. The highest coefficient of variation between duplicates in this study was less than 30% indicating good repeatability.