The determination of agricultural methane emissions in New Zealand using inverse modelling techniques

A receptor-oriented modelling system, consisting of a mesoscale meteorological model (RAMS) and a Lagrangian particle dispersion model (LPD) is applied to the determination of emissions of methane from livestock in agricultural regions in New Zealand. Aircraft measurements of methane mixing ratio profiles are input to the model, from which influence functions are obtained; these are the footprints of potential contributing emissions. Inversion techniques and statistical analysis enable the determination of confidence intervals for methane emissions. Results are compared with prior emissions data obtained by other methods. For two case studies in the Manawatu region of New Zealand in June 1995 and April 1997, methane emission fluxes of 54±32 and 56±54 mg m−2 d−1 are obtained (95% confidence intervals). These are consistent with independently estimated per-animal emission rates and observed livestock densities. For a field campaign in New Zealandʹs Waikato region in 1999, where no emissions estimates were available a priori, the average emission fluxes derived using receptor-oriented techniques are 67±46 mg m−2 d−1. The error-bars on the emission fluxes are arguably quite large. This is due to uncertainties in the methane observations and errors in the meteorological simulations, which play a different role in each case study. Improvements in both the experimental and modelling procedures are proposed to reduce uncertainties in the calculated emission fluxes.