Preprints
https://doi.org/10.5194/egusphere-2022-626
https://doi.org/10.5194/egusphere-2022-626
 
05 Sep 2022
05 Sep 2022
Status: this preprint is open for discussion.

Global agricultural ammonia emissions simulated with the ORCHIDEE land surface model

Maureen Beaudor1, Nicolas Vuichard1, Juliette Lathière1, Nikolaos Evangeliou2, Martin Van Damme3,4, Lieven Clarisse3, and Didier Hauglustaine1 Maureen Beaudor et al.
  • 1Laboratoire des Sciences du Climat et de l’Environnement (LSCE) CEA-CNRS-UVSQ, Gif-sur-Yvette, France
  • 2Norwegian Institute for Air Research (NILU), Department of Atmospheric and Climate Research (ATMOS), Kjeller, Norway
  • 3Université libre de Bruxelles (ULB), Spectroscopy, Quantum Chemistry and Atmospheric Remote Sensing (SQUARES), Brussels, Belgium
  • 4Royal Belgian Institute for Space Aeronomy, Brussels, Belgium

Abstract. Ammonia (NH3) is an important atmospheric constituent. It plays a role in air quality and climate through the formation of ammonium sulfate and ammonium nitrate particles. It has also an impact on ecosystems through deposition processes. About 85 % of NH3 global anthropogenic emissions are related to food and feed production and, in particular, to the use of mineral fertilizers and manure management. Most global chemistry transport models rely on bottom-up emission inventories subject to significant uncertainties. In this study, we estimate emissions from livestock by developing a new module to calculate ammonia emissions coming from the whole agricultural sector (from housing and storage to grazing and fertilizer applications) within the global land surface model ORCHIDEE. We detail the approach used for quantifying livestock feeding management, manure applications, and indoor and soil emissions and evaluate the model performance. Our results reflect China, India, Africa, Latin America, the USA, and Europe as the main contributors to the global NH3 emissions accounting for 80 % of the total budget. The global calculated emissions reach 44 Tg/yr over the 2005–2015 period, which is within the range estimated by previous work. Key parameters (pH of the manure, timing of the N application, atmospheric NH3 surface concentration, etc...) which drive the soil emissions have also been tested in order to assess the sensibility of our model. Manure pH is the parameter to which modeled emissions are the most sensitive with a 10 % change in emissions per % change in pH. Even though we found an under-estimation in our emissions over Europe (−26 %) and an over-estimation in the USA (+56 %) compared to previous work, other hot-spot regions are consistent. The calculated emissions seasonality is in very good agreement with satellite-based emissions. These encouraging results prove the potential of coupling ORCHIDEE land-based emissions to CTMs, which are currently forced by bottom-up anthropogenic-centered inventories such as CEDS.

Maureen Beaudor et al.

Status: open (until 31 Oct 2022)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse

Maureen Beaudor et al.

Data sets

Global agricultural ammonia emissions simulated with the ORCHIDEE land surface model : Model Ouput Data Beaudor Maureen; Vuichard Nicolas; Lathière Juliette; Evangeliou Nikolaos; Van Damme Martin; Clarisse Lieven; Hauglustaine Didier https://doi.org/10.5281/zenodo.6818373

Model code and software

ORCHIDEE CAMEO 2022 Version Beaudor Maureen; Vuichard Nicolas; Lathière Juliette; Evangeliou Nikolaos; Van Damme Martin; Clarisse Lieven; Hauglustaine Didier https://forge.ipsl.jussieu.fr/orchidee/wiki/GroupActivities/CodeAvalaibilityPublication/ORCHIDEE_CAMEO_gmd_2022

Maureen Beaudor et al.

Viewed

Total article views: 218 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
145 64 9 218 26 5 4
  • HTML: 145
  • PDF: 64
  • XML: 9
  • Total: 218
  • Supplement: 26
  • BibTeX: 5
  • EndNote: 4
Views and downloads (calculated since 05 Sep 2022)
Cumulative views and downloads (calculated since 05 Sep 2022)

Viewed (geographical distribution)

Total article views: 209 (including HTML, PDF, and XML) Thereof 209 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 28 Sep 2022
Download
Short summary
Ammonia mainly comes from the agricultural sector and its volatilization relies on environmental variables. Our approach aims at benefiting from an Earth System Model framework to estimate it. By doing so, we represent a consistent spatial distribution of the emissions replying to environmental changes. We greatly improved the seasonal cycle of the emissions compared to previous works. In addition, our model includes natural soil emissions, almost never represented in the modeling approaches.