Abstract
Agricultural soils are the primary source of nitrous oxide emissions due to management practices including fertiliser application. While fertiliser rates are one of the main drivers of nitrous oxide emissions, emissions are also dependent on other variables such as climate and soil properties. To understand the spatial and inter-annual variations in emission rate, simulations of N2O emissions were made from 2000 to 2010 for UK grass and croplands. In addition, the sensitivity of these emissions to soil and climate inputs was also tested. Emissions of between 0.3 to 3.5kgNha−1yr−1 and 0.7–7kgNha−1yr−1 were simulated across UK croplands and grasslands, respectively. While inter-annual variations can be attributed to climate influences, the primary driver of spatial variations in emissions was soil clay content. However, when the sensitivity of nitrous oxide emissions to soil clay content alone was tested, it was not always the best predictor of emissions, when soil texture is altered outside of the normal range used as inputs to the model from different databases.
Highlights
National Greenhouse Gas inventories for quantifying emissions from agriculture and land use change often calculate emissions using default emission factors (EFs) coupled with country specific activity data in the form of land use and management information (Intergovernmental Panel on Climate Change (IPCC), 2006; Ogle et al, 2013, 2014)
The average annual N2O emissions from the two dominant soil types defined as occurring on UK grassland and croplands from 2001 to 2010 are detailed in Figs. 1 and 2, respectively
As grassland management was assumed to be the same across the UK, while N fertiliser was a driver of emissions, the results demonstrated how N2O emissions varied in relation to soil and climate drivers
Summary
National Greenhouse Gas inventories for quantifying emissions from agriculture and land use change often calculate emissions using default emission factors (EFs) coupled with country specific activity data in the form of land use and management information (IPCC, 2006; Ogle et al, 2013, 2014). Calculate estimates on a Tier 2 or 3 level, spatially disaggregated land use and land management information, in combination with country specific EFs, are increasingly being used. Extrapolating site derived EFs to a regional or national scale may not accurately reflect the complex interaction between soil, management, climate and crop type (Butterbach-Bahl et al, 2013)
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