Atmospheric modelling and top-down flux inference
This work package will advance current methods for sector-level top-down flux inversions. We will develop methods for using measurements of GHG tracers (O2, ∆14CO2, δ13CCH4, δDCH4, CO, C2H6, and NOx) to constrain source sectors for CO2 and CH4, ensuring that uncertainties are propagated through our inversions. We will expand our capability to couple in situ and remote-sensing data as seen in Ganesan et al., 2017, image below. We will address potential systematic model errors and poorly quantified model uncertainties by evaluating aspects of the physics and meteorology in the Numerical Atmospheric dispersion Modelling Environment model and use a new high-frequency 222Rn network to characterise remaining uncertainties.
Ganesan et al., 2017, Atmospheric observations show accurate reporting and little growth in India’s methane emissions. Nat. Comm., 8, 836