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

Summary, in English

Atmospheric 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.

• Author: Eric Saboya; Alistair J. Manning; Peter Levy; Kieran M. Stanley; Joseph Pitt; Dickon Young; Daniel Say; Aoife Grant; Tim Arnold; Chris Rennick; Samuel J. Tomlinson; Edward J. Carnell; Yuri Artoli; Ann Stavart; T. Gerard Spain; Simon O’Doherty; Matthew Rigby; Anita L. Ganesan
• Department/s: Dept of Physical Geography and Ecosystem Science; MERGE: ModElling the Regional and Global Earth system
• Publishing year: 2024-07
• Language: English
• Publication/Series: Journal of Geophysical Research: Atmospheres
• Volume: 129
• Issue: 14
• Links: http://dx.doi.org/10.1029/2024JD040785
• Document type: Journal article
• Publisher: Wiley-Blackwell
• Topic: Physical Geography
• Keywords: greenhouse gases; NO; regional inverse modeling; seasonal cycle; top-down bottom-up evaluation
• Status: Published
• ISBN/ISSN/Other: ISSN: 2169-897X