Combining Top‐Down and Bottom‐Up Approaches to Evaluate Recent Trends and Seasonal Patterns in UK N2O Emissions

Author:

Saboya Eric1ORCID,Manning Alistair J.2ORCID,Levy Peter3ORCID,Stanley Kieran M.4ORCID,Pitt Joseph4,Young Dickon4ORCID,Say Daniel4,Grant Aoife4,Arnold Tim567ORCID,Rennick Chris5ORCID,Tomlinson Samuel J.8ORCID,Carnell Edward J.3,Artioli Yuri9ORCID,Stavart Ann10ORCID,Spain T. Gerard11,O’Doherty Simon4,Rigby Matthew4ORCID,Ganesan Anita L.1ORCID

Affiliation:

1. School of Geographical Sciences University of Bristol Bristol UK

2. Met Office Hadley Centre Exeter UK

3. UK Centre for Ecology and Hydrology Edinburgh UK

4. School of Chemistry University of Bristol Bristol UK

5. National Physical Laboratory Teddington UK

6. School of GeoSciences University of Edinburgh Edinburgh UK

7. Department of Physical Geography and Ecosystem Science Lund University Lund Sweden

8. UK Centre for Ecology and Hydrology Lancaster UK

9. Plymouth Marine Laboratory Plymouth UK

10. Climate Science Centre CSIRO Oceans and Atmosphere Aspendale VIC Australia

11. School of Natural Sciences University of Galway Galway Ireland

Abstract

AbstractAtmospheric trace gas measurements can be used to independently assess national greenhouse gas inventories through inverse modeling. Atmospheric nitrous oxide (N2O) measurements made in the United Kingdom (UK) and Republic of Ireland are used to derive monthly N2O emissions for 2013–2022 using two different inverse methods. We find mean UK emissions of 90.5 ± 23.0 (1σ) and 111.7 ± 32.1 (1σ) Gg N2O yr−1 for 2013–2022, and corresponding trends of −0.68 ± 0.48 (1σ) Gg N2O yr−2 and −2.10 ± 0.72 (1σ) Gg N2O yr−2, respectively, for the two inverse methods. The UK National Atmospheric Emissions Inventory (NAEI) reported mean N2O emissions of 73.9 ± 1.7 (1σ) Gg N2O yr−1 across this period, which is 22%–51% smaller than the emissions derived from atmospheric data. We infer a pronounced seasonal cycle in N2O emissions, with a peak occurring in the spring and a second smaller peak in the late summer for certain years. The springtime peak has a long seasonal decline that contrasts with the sharp rise and fall of N2O emissions estimated from the bottom‐up UK Emissions Model (UKEM). Bayesian inference is used to minimize the seasonal cycle mismatch between the average top‐down (atmospheric data‐based) and bottom‐up (process model and inventory‐based) seasonal emissions at a sub‐sector level. Increasing agricultural manure management and decreasing synthetic fertilizer N2O emissions reduces some of the discrepancy between the average top‐down and bottom‐up seasonal cycles. Other possibilities could also explain these discrepancies, such as missing emissions from NH3 deposition, but these require further investigation.

Publisher

American Geophysical Union (AGU)

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