Large spatial and temporal uncertainties for landfill CH 4 emissions remain unresolved by short-term field campaigns and historic greenhouse gas (GHG) inventory models. Using four field methods (aircraft-based mass balance, tracer correlation, vertical radial plume mapping, static chambers) and a new field-validated process-based model (California Landfill Methane Inventory Model, CALMIM 5.4), we investigated the total CH 4 emissions from a central Indiana landfill as well as the partitioned emissions inclusive of methanotrophic oxidation for the various cover soils at the site. We observed close agreement between whole site emissions derived from the tracer correlation (8 to 13 mol s –1 ) and the aircraft mass balance approaches (7 and 17 mol s –1 ) that were statistically indistinguishable from the modeling result (12 ± 2 mol s –1 inclusive of oxidation). Our model calculations indicated that approximately 90% of the annual average CH 4 emissions (11 ± 1 mol s –1 ; 2200 ± 250 g m –2 d –1 ) derived from the small daily operational area. Characterized by a thin overnight soil cover directly overlying a thick sequence of older methanogenic waste without biogas recovery, this area constitutes only 2% of the 0.7 km 2 total waste footprint area. Because this Indiana landfill is an upwind source for Indianapolis, USA, the resolution of m 2 to km 2 scale emissions at various temporal scales contributes to improved regional inventories relevant for addressing GHG mitigation strategies. Finally, our comparison of measured to reported CH 4 emissions under the US EPA National GHG Reporting program suggests the need to revisit the current IPCC ( 2006 ) GHG inventory methodology based on CH 4 generation modeling. The reasonable prediction of emissions at individual U.S. landfills requires incorporation of both cover-specific landfill climate modeling (e.g., soil temperature/moisture variability over a typical annual cycle driving CH 4 transport and oxidation rates) as well as operational issues (e.g., cover thickness/properties, extent of biogas recovery).