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, δ¹³C_CH4, δD_CH4, CO, C₂H₆, and NO_x) 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.

References

Ganesan et al., 2017, Atmospheric observations show accurate reporting and little growth in India’s methane emissions. Nat. Comm., 8, 836