Estimation of long-term methane emissions from Mechanical-Biological Treatment waste through biomethane potential test

ABSTRACT

Mechanical-Biological Treatment (MBT) is a technology applied to reduce the environmental impacts of urban waste based on stabilizing the organic matter content. As the process is not entirely efficient, the residue can generate methane when it is landfilled. Long-term methane emissions estimation based on models is usually over or underestimated because the actual waste composition after stabilization is generally unknown. This work proposes a single tool to improve the emission estimations of the landfilled MBT waste based on the determination of the biomethane potential test (BMP). Experimental BMP of the crude and stabilized organic fractions of municipal solid waste obtained from an MBT plant were carried out, and the results were used to predict the methane emission from two models, LandGEM (2005) and IPCC (2006). In the LandGEM model, the experimental value of BMP represents the methane potential L₀ while in the IPCC model it allowed to obtain the ultimate organic carbon anaerobically degraded (DOC_f), based on a linear correlation (R² = 0.944, p-value < .05) that can be used to obtain the DOC_f in a waste of any composition. The results of the long-term (40 years) methane emissions of the stabilized waste disposed on land showed overestimations of up 56.0% (IPCC model) and 259.5% (Landgem model) when default data, instead the actual DOC_f were applied in stabilized waste; similar behaviour was observed for the crude waste (23.3% and 241.3% overestimations). Moreover, the impact of the stabilization process revealed methane emission reductions of 5.1% and 20.9% based on LandGEM and IPCC models, respectively.

GRAPHICAL ABSTRACT

KEYWORDS:

• Municipal solid waste
• biomethane potential
• mechanical biological treatment
• methane emissions modelling

Acknowledgment

The authors thank the College of Engineering for the scholarship awarded to Luisina Aristaran who carried out the BMP tests, and to CONICET for the postdoctoral fellowship of Verónica Córdoba.

Disclosure statement

No potential conflict of interest was reported by the author(s).