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Combining top-down and bottom-up approaches to evaluate recent trends and seasonal patterns in U.K. N2O emissions
  • +15
  • Eric Saboya,
  • Alistair J. Manning,
  • Peter Levy,
  • Kieran M Stanley,
  • Joseph Pitt,
  • Dickon Young,
  • Daniel Say,
  • Aoife grant,
  • Tim Arnold,
  • Chris Rennick,
  • Samuel Tomlinson,
  • Edward Carnell,
  • Yuri Artioli,
  • Ann R Stavert,
  • T Gerard Spain,
  • Simon O´Doherty,
  • Matthew Rigby,
  • Anita L Ganesan
Eric Saboya
University of Bristol

Corresponding Author:[email protected]

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Alistair J. Manning
UKMet Office
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Peter Levy
Centre for Ecology and Hydrology
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Kieran M Stanley
Atmospheric Chemistry Research Group
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Joseph Pitt
University of Bristol
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Dickon Young
University of Bristol
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Daniel Say
University of Bristol
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Aoife grant
School of Chemistry, University of Bristol
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Tim Arnold
National Physical Laboratory
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Chris Rennick
National Physical Laboratory
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Samuel Tomlinson
UK Centre for Ecology and Hydrology
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Edward Carnell
CEH
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Yuri Artioli
Plymouth Marine Laboratory
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Ann R Stavert
CSIRO
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T Gerard Spain
University of Galway
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Simon O´Doherty
University of Bristol
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Matthew Rigby
University of Bristol
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Anita L Ganesan
University of Bristol
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Abstract

Atmospheric trace gas measurements can be used to independently assess national greenhouse gas inventories through inverse modelling. Here, atmospheric nitrous oxide (N2O) measurements made in the United Kingdom (U.K.) and Republic of Ireland are used to derive monthly N2O emissions for 2013-2022 using two different inverse methods. We find mean U.K. emissions of 90.5±23.0 (1\(\sigma\)) and 111.7±32.1 (1\(\sigma\)) Gg N2O yr-1 for 2013-2022, and corresponding trends of -0.68±0.48 (1\(\sigma\)) Gg N2O yr-2 and -2.10±0.72 (1\(\sigma\)) Gg N2O yr-2, respectively for the two inverse methods. The U.K. National Atmospheric Emissions Inventory (NAEI) reported mean N2O emissions of 73.9 Gg N2O yr-1 across this period, which is 14-33% 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 U.K. 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.
15 Jan 2024Submitted to ESS Open Archive
02 Feb 2024Published in ESS Open Archive