Journal article

Designing optimal greenhouse gas monitoring networks for Australia

T Ziehn, RM Law, PJ Rayner, G Roff

Geoscientific Instrumentation Methods and Data Systems Discussions | Copernicus GmbH

Abstract

Abstract. Atmospheric transport inversion is commonly used to infer greenhouse gas (GHG) flux estimates from concentration measurements. The optimal location of ground based observing stations that supply these measurements can be determined by network design. Here, we use a Lagrangian particle dispersion model (LPDM) in reverse mode together with a Bayesian inverse modelling framework to derive optimal GHG observing networks for Australia. This extends the network design for carbon dioxide (CO2) performed by Ziehn et al. (2014) to also minimize the uncertainty on the flux estimates for methane (CH4) and nitrous oxide (N2O), both individually and in a combined network using multiple objectiv..

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University of Melbourne Researchers