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Locating and quantifying gas emission sources using remotely obtained concentration data

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  • B. Hirst
  • P. Jonathan
  • F. González del Cueto
  • D. Randell
  • O. Kosut
<mark>Journal publication date</mark>2013
<mark>Journal</mark>Atmospheric Environment
Number of pages18
Pages (from-to)141-158
Publication StatusPublished
<mark>Original language</mark>English


We describe a method for detecting, locating and quantifying sources of gas emissions to the atmosphere using remotely obtained gas concentration data; the method is applicable to gases of environmental concern. We demonstrate its performance using methane data collected from aircraft. Atmospheric point concentration measurements are modelled as the sum of a spatially and temporally smooth atmospheric background concentration, augmented by concentrations due to local sources. We model source emission rates with a Gaussian mixture model and use a Markov random field to represent the atmospheric background concentration component of the measurements. A Gaussian plume atmospheric eddy dispersion model represents gas dispersion between sources and measurement locations. Initial point estimates of background concentrations and source emission rates are obtained using mixed ℓ2-ℓ1 optimisation over a discretised grid of potential source locations. Subsequent reversible jump Markov chain Monte Carlo inference provides estimated values and uncertainties for the number, emission rates and locations of sources unconstrained by a grid. Source area, atmospheric background concentrations and other model parameters, including plume model spreading and Lagrangian turbulence time scale, are also estimated. We investigate the performance of the approach first using a synthetic problem, then apply the method to real airborne data from a 1600km2 area containing two landfills, then a 225km2 area containing a gas flare stack. © 2013 Elsevier Ltd.