Estimates of regional and national nitrous oxide (N2O) emissions rely on emission factors (EFs) commonly derived from measurements using static chambers. These measurements can include high uncertainties and might obscure the quantification of N2O fluxes. Advances in micrometeorological eddy covariance technique (EC) now allow direct measurements of N2O fluxes at the field scale. Here, we compared N2O emissions calculated from site-specific EFs with N2O flux data derived from year-round EC measurements on an intensively grazed dairy pasture in the Waikato region, NZ. Annual N2O emissions of 7.30 kg N2O-N ha−1 yr−1 determined using gap-filled EC flux data were greater than N2O estimates of 3.82 kg N2O-N ha−1 yr−1 based on site-specific EFs for cattle urine (1.53%), cattle dung (0.24%) and urea fertiliser (0.16%). Likely reasons for this difference were that the EF approach did not take into account the seasonal variability of EFs, the effect of supplementary feed on cattle nitrogen (N) excretion and background N2O emissions (BNE). Including calculated emissions from supplementary feed N (0.92 kg N2O-N ha−1 yr−1) and BNE (1.09 kg N2O-N ha−1 yr−1) increased annual EF-based emissions to 5.83 kg N2O-N ha−1 yr−1. The site-specific EFs were established in spring 2017 and may not have adequately represented summer, winter and particularly autumn N2O emissions. The EF approach, therefore, did not fully account for the seasonal variability of N2O fluxes as measured by EC but, if quantified, could have led to further agreement between measurements. Using EC measurements to complement static chambers and EF approaches altered annual N2O emissions estimates from intensively grazed pastoral land. Hence, we conclude that N2O budgets derived from EFs need to better capture the effect of seasonal variability, supplementary feed and BNE.
Wecking, A. R., Wall, A. M., Liang, L. L., Lindsey, S. B., Luo, J., Campbell, D. I., & Schipper, L. A. (2020). Reconciling annual nitrous oxide emissions of an intensively grazed dairy pasture determined by eddy covariance and emission factors. Agriculture, Ecosystems and Environment, 287, 106646. doi:10.1016/j.agee.2019.106646