Application of cavity ring-down spectroscopy and a novel near surface Gaussian plume estimation approach to inverse model landfill methane emissions.

Fugitive methane emissions from municipal solid waste landfills impact global climate change and reliable emissions quantification is of increasing importance. Ground-based cavity ring-down spectrometer (CRDS) measurements were used to determine methane concentrations and isotopic compositions of carbon in CH. Then, CH oxidation through various cover materials was assessed using the Keeling plot method. A novel inverse modeling approach using Gaussian dispersion analysis, termed near-surface Gaussian plume estimation (NSGPE), was developed to predict whole-site landfill methane emissions. The concentration data obtained around the landfill perimeter with the mobile ground-based CRDS were used. Methane concentration data were integrated to parameterize discretized point source emissions from a Gaussian dispersion model. Post-processing algorithms were applied to refine modeling predictions to account for the influence of topographical and meteorological conditions on methane transport. Results indicate spatially resolved and consistent emissions estimates among multiple optimization simulations, with refinements increasing the resolution and spatial trends of emissions. Post-processing algorithms resolve consistent overestimation of emissions commonly observed using conventional Gaussian dispersion models.•Ground-based CRDS used to obtain methane concentration and oxidation data.•Novel inverse Gaussian dispersion modeling approach developed to predict methane emissions from landfills accounting for site-specific topography and meteorology.•Post-processing algorithms refine emissions estimates.