Regardless of the approach or model used, uncertainties associated with N2O estimates for livestock systems are very large due to the complexity of the N2O emissions and their drivers in different systems. These uncertainties are associated with both the actual emission estimates, and the assessment of the effectiveness of mitigation strategies. When discussing uncertainties in N2O emission estimates, Oenema et al (2005) distinguished between fundamental and operational uncertainties. These authors described fundamental uncertainties as being associated with the methodology or structure (and upscaling) of the estimation procedure, whereas operational uncertainties relate to those associated with EFs and/or the input variables that underpin the estimates (for example fertilizer use, manure production, N excretion etc.). The uncertainties associated with EFs are partly due to uncertainties arising from the measurement methodology. Careful deployment of the measurement methodology and procedures, as discussed above for soil chamber measurements, will help to minimize some of the uncertainties associated with EFs. However, accounting for the large spatial and temporal variability of N2O emissions will remain a key challenge when seeking to minimize uncertainties associated with upscaling small-scale measurements to regional or national inventory estimates. These uncertainties can only be addressed by applying appropriate measurement technologies and methods, including online measurement from automated chambers or micrometeorological systems, with sufficient spatial replication, fetch size and measurement frequency to ensure that spatial and temporal variability issues are addressed.

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