Biogas is a combustible gas generated by the biodegradation reactions of organic matter in the absence of oxygen, either due to the action of microorganisms or other factors. Biogas can be produced in landfills by the decomposition of organic matter present in the waste, and this is mainly composed of methane (CH4) and carbon dioxide (CO2) plus traces of organic and inorganic volatile compounds. Part of the emissions generated in controlled landfills are reduced by the installation of drainage systems for the leachate collection and extraction systems for the recovery of biogas. Extraction systems are implemented with the aim of preventing the emissions of gases generated in the landfill and subsequent reuse of energy, thus obtaining an economic benefit. However, there is always a percentage of uncontrolled or fugitive emissions that escape or diffuse through the surface of the controlled deposit.
This project aims at developing and testing a field methodology to quantify the fugitive emissions flows produced over the entire surface of the landfill as well as to validate the efficiency of the biogas capture systems in Catalan landfills. Out of the several validated methodologies for quantifying diffuse emissions, the flow chamber or accumulation chamber method coupled to direct (field sensors) and indirect (gas chromatography) measurements are used. This is as an economically viable and statistically reliable methodology that will be applied to a range of operating and closed landfill sites with different type of coverage and conditions for the sake of comparison. Diffuse emissions in this project consider not only methane but also CO2, volatile organic compounds and N2O in order to assess GHG emissions.
The IPPC Waste Model, which is based on a first-order organic matter decomposition model, will be used to estimate the potential for CH4 generation of waste over the years based on the quantities and composition of input waste in each landfill under study. Experimental diffuse methane emissions and biogas collected from extraction wells will be compared with model predictions.