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Designing optimal greenhouse gas monitoring networks for Australia
Geoscientific Instrumentation Methods and Data Systems Discussions
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 dioxidedoi:10.5194/gid-5-247-2015 fatcat:htlobwjl5razbdppxyiitq4bni