Locating and quantifying gas emission sources using remotely obtained concentration data

Hirst, B. and Jonathan, P. and González del Cueto, F. and Randell, D. and Kosut, O. (2013) Locating and quantifying gas emission sources using remotely obtained concentration data. Atmospheric Environment, 74. pp. 141-158. ISSN 1352-2310

Full text not available from this repository.

Abstract

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.

Item Type:
Journal Article
Journal or Publication Title:
Atmospheric Environment
Subjects:
ID Code:
133065
Deposited By:
Deposited On:
22 Apr 2019 14:20
Refereed?:
Yes
Published?:
Published
Last Modified:
07 Oct 2020 07:37