1. Improving the Agricultural Greenhouse Gas Emission Inventory for the UK, Focusing on Soil Nitrous Oxide Emissions Ute Skiba Centre for Ecology and Hydrology Bush Estate, near Edinburgh ums@ceh.ac.uk

2. The atmospheric increase of N 2 O is largely attributed to agricultural activity and CH 4 to fossil fuel use and animal rearing Agriculture contributes to 30% of global GHG emissions

3. Agriculture is responsible for 10% of UK GHG emissions 5.4% N 2 O, 4% CH 4, 0.7% CO 2 UK Agricultural sources 0.9% CO 2 44% CH 4 81% N 2 O of annual budgets CO 2 CH 4 N2O + Waste

4. Agricultural emissions Gg N 2 O Direct51.4 Indirect29 manure6.4

5. N 2 O flux measurement methodologies Static Chamber / GC Dynamic Chamber / QCL Eddy Covariance / QCL Autochamber / GC

6. Development of the emission factor EF1 for N fertilised soils EF1 for N additions from mineral fertilisers, organic amendments and crop residues, and N mineralised from mineral soil as a result of loss of soil carbon IPCC 1996 guidelines: E = 1 + 0.0125 ● F based on 20 * one year studies The background of 1 kg N/ha/y is based on 5 studies from unfertilised plots IPCC 2006 guidelines: E = 1 + 0.01 ● F (2002) 846 measurements from 126 studies Uncertainty range 0.3% – 3% Data are skewed towards temperate climate zones & wealthy states Very little data from Africa different cropping systems, climate but slowly rising N fertiliser use Bouwman, A.F. (1996) Nutrient Cycling in Agroecosystems, 46, 53-70, Bouwman A.F. et al (2002) Global Biogeochemical Cycles 16, 28-1–28-9

7. Rainfall and fertiliser induced N 2 O emissions Skiba et al, 2013, Biogeosciences, 10, 1231–1241

8. Spatial Variability

9. Requirements for N 2 O production in soil Nitrogen (fertiliser, manure, atmospheric deposition) Low oxygen (rain, heavy soil, high microbial activity) Temperature Soil is NOT uniform: large spatial and temporal variability Eric Davidson

10. ADAS AFBI CEH Keith Smith Met Office RRes SRUC (SAC) Univ. of Aberdeen Univ. Bangor Univ. of East Anglia inveN 2 Ory 2010 – 2015

11. inveN 2 Ory site network Representative of geo-climatic zones of agricultural regions Address data gaps Same experiments at all sites (arable / grass) (12 months) Unfertilised Control FYM (autumn) Poultry (autumn/spring) Slurry (timing/application) Urine (timing/DCD) Dung (timing)

12. Example: Arable crops daily - weekly flux measurements Increasing fertiliser N Bell et all, Agriculture Ecosystems and Environment, 212, 134-347. Emission Factor %

13. Regression model combining data from two DEFRA projects (MinNO and inveN 2 Ory) David Chadwick (Bangor Uni) Bob Rees (SRUC) Christine Watson (AFBI) Laura Cardenas (RRES) Roger Sylvester-Bradley (ADAS) Rachel Thorman (ADAS) Emission = f (N, Clay%, Annual Rain, Clay%*Annual Rain) cumulative annual flux, calculated by linear interpolation

14. Summary of Emission Factors from all inveN 2 Ory experiments Direct Emissions EF1; Default value 1% – Fertiliser to arable0.46% – Fertiliser to grass1% – Manure 0.6% Grazing returns Default EFs: dung and urine 2% – Dung0.2% – Urine0.7% David Chadwick (Bangor Uni) Bob Rees (SRUC) Christine Watson (AFBI) Laura Cardenas (RRES) Rachel Thorman (ADAS) Kairsty Topp (SRUC)

15. Upscaling from plot to field Wind Soil Eddy covariance can miss important N 2 O hotspots, such as tree shelters on grazed grasslands

16. Eddy Covariance and chamber comparison EC (2.4 m) Chamber (20) Fertiliser Event Grassland field Easter Bush Sept 2012 95% confidence intervals Nick Cowan, CEH

17. Comparison of Methods at 6 inveN 2 Ory locations In Fetch Outside Fetch 1:1 Nick Cowan, Pete Levy, Ute Skiba, CEH Plot scale Field scale

18. Cumulative Fluxes Comparison of Eddy Covariance and Chambers Gap filling models and their associated uncertainties need to be improved in order to obtain better cumulative flux / emission factors Nick Cowan, Pete Levy, Ute Skiba, CEH

19. Comparing Regional Scale Concentration measurements with UK disaggregated emission maps Ed Carnell, Ulli Dragosits (CEH) Nuala Fitton (Aberdeen Uni.) a)IPCC Tier 1 EF b)inveN2Ory new EF Temporal disaggregation monthly, based on N fertiliser timing for Manure spreading 86.34 kt N 2 O y -1 52.07 kt N 2 O y -1

20. Regional Scale verification Ed Carnell, Ulli Dragosits, CEH, Nuala Fitton, Aberdeen Uni Elena Meneguz, Alistair Manning, MetOffice

21. Measured and modelled N 2 O data Regional scale Ridge Hill Tacolneston Ed Carnell, Ulli Dragosits, CEH, Elena Meneguz, Alistair Manning, MetOffice

22. Summary N 2 O emissions are very variable in space and time UK specific data showed that on average the Tier 1 EF 1 is too large Measurements at plot & field scales show reasonable agreement, but improvements (gapfilling) are advisable Bottom–up Tier 2 map may agree better with tower measurements Tower measurements constrain emission inventories and could be used to monitor change (i.e. mitigation)

23. Mitigation of ruminant methane emissions Diet & genotypes influence CH 4 emissions from cattle and sheep Largest reductions can be achieved by increasing efficiency, which includes reducing the animals life time rearing fewer animals Jon Moorby et al, DEFRA GHGPlatform CH 4 project

24. Thankyou