Demonstrating Regional Climate and Meteorological Sensitivity in Landfill Methane Inventories from Historical Californian Databases

The urgency to manage global methane emissions has been acknowledged with international pledges to reduce 2020 levels by 30% by 2030. Carbon management requires effective tools to monitor changes, including those from significant sources including waste disposed on land. The first order degradation model used to determine landfill methane emissions, has been described by researchers as highly variable, insensitive and inadequate, despite recent attempts to explain microclimate impacts on methane oxidation. The development of detailed regional inventories is hampered by these variables. The availability of historical waste management and meteorological data in California, enables a theoretical review and modelling of meteorological moisture changes with methane generation data in a region of decadal drought. This study identifies a novel approach in the modelling of regional optimisation of variable seasonal parameters of moisture and methane oxidation based on the adjustment of the methane correction factor (MCF) generally assumed to be MCF = 1 for managed sites, that is optimised as MCFsite ≠ 1 as the average regional MCFall sites, → 1 (Range: <1, ≥1). Regional annual unmitigated methane emitted in December 2010 after methane recovery, oxidation and flaring is estimated at 0.40 million tonnes, falling to 0.31 million tonnes in 2011 and back to 0.40 million tonnes in 2012 (Pr < 0.01, n = 370). as meteorological conditions returned to the changing decadal norm. Meteorological and climate sensitivity is demonstrated in relation to the regional water balance, spatial distribution of landfill site moisture levels, satellite imagery of 2012 wildfire intensity ranges, the 2011 El Nino impacts and independent data sources. The method provides accurate regional methane assessments inclusive of soil and cover material oxidation. This will primarily benefit developing countries where landfill remains a dominant option, enabling the development of database linked satellite monitoring and detailed regional landfill climate emission inventories.