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

Abstract

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.