Global agricultural ammonia emissions simulated with the ORCHIDEE land surface model
<p>Ammonia (<span class="inline-formula">NH<sub>3</sub></span>) 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 th...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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Copernicus Publications
2023-02-01
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| Series: | Geoscientific Model Development |
| Online Access: | https://gmd.copernicus.org/articles/16/1053/2023/gmd-16-1053-2023.pdf |
| _version_ | 1811168366500511744 |
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| author | M. Beaudor N. Vuichard J. Lathière N. Evangeliou M. Van Damme M. Van Damme L. Clarisse D. Hauglustaine |
| author_facet | M. Beaudor N. Vuichard J. Lathière N. Evangeliou M. Van Damme M. Van Damme L. Clarisse D. Hauglustaine |
| author_sort | M. Beaudor |
| collection | DOAJ |
| description | <p>Ammonia (<span class="inline-formula">NH<sub>3</sub></span>) 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 <span class="inline-formula">%</span> of <span class="inline-formula">NH<sub>3</sub></span> 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 (CTMs) rely on bottom-up emission inventories, which are subject to significant uncertainties.
In this study, we estimate emissions from livestock by developing a new module to calculate ammonia emissions from the whole agricultural sector (from housing and storage to grazing and fertilizer application) within the ORCHIDEE (Organising Carbon and Hydrology In Dynamic Ecosystems) global land surface model.
We detail the approach used for quantifying livestock feed management, manure application, and indoor and soil emissions and subsequently evaluate the model performance.
Our results reflect China, India, Africa, Latin America, the USA, and Europe as the main contributors to global <span class="inline-formula">NH<sub>3</sub></span> emissions,
accounting for 80 % of the total budget.
The global calculated emissions reach 44 <span class="inline-formula">Tg N yr<sup>−1</sup></span> over the 2005–2015 period, which is within the range estimated by previous work.
Key parameters (e.g., the pH of the manure, timing of N application, and atmospheric <span class="inline-formula">NH<sub>3</sub></span> surface concentration) that drive the soil emissions have also been tested in order to assess the sensitivity of our
model.
Manure pH is the parameter to which modeled emissions are the most sensitive, with a 10 <span class="inline-formula">%</span> change in emissions per percent change in pH.
Even though we found an underestimation in our emissions over Europe (<span class="inline-formula">−26</span> <span class="inline-formula">%</span>) and an overestimation in the USA (<span class="inline-formula">+56</span> <span class="inline-formula">%</span>) compared with previous work, other hot spot regions are consistent.
The calculated emission 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 the CEDS (Community Emissions Data System).</p> |
| first_indexed | 2024-04-10T16:25:06Z |
| format | Article |
| id | doaj.art-caeb4f14bcb444a6afbc054d81dd4b0f |
| institution | Directory Open Access Journal |
| issn | 1991-959X 1991-9603 |
| language | English |
| last_indexed | 2024-04-10T16:25:06Z |
| publishDate | 2023-02-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Geoscientific Model Development |
| spelling | doaj.art-caeb4f14bcb444a6afbc054d81dd4b0f2023-02-09T07:22:38ZengCopernicus PublicationsGeoscientific Model Development1991-959X1991-96032023-02-01161053108110.5194/gmd-16-1053-2023Global agricultural ammonia emissions simulated with the ORCHIDEE land surface modelM. Beaudor0N. Vuichard1J. Lathière2N. Evangeliou3M. Van Damme4M. Van Damme5L. Clarisse6D. Hauglustaine7Laboratoire des Sciences du Climat et de l'Environnement (LSCE), CEA–CNRS–UVSQ, Gif-sur-Yvette, FranceLaboratoire des Sciences du Climat et de l'Environnement (LSCE), CEA–CNRS–UVSQ, Gif-sur-Yvette, FranceLaboratoire des Sciences du Climat et de l'Environnement (LSCE), CEA–CNRS–UVSQ, Gif-sur-Yvette, FranceDepartment of Atmospheric and Climate Research (ATMOS), Norwegian Institute for Air Research (NILU), Kjeller, NorwaySpectroscopy, Quantum Chemistry and Atmospheric Remote Sensing (SQUARES), Université libre de Bruxelles (ULB), Brussels, BelgiumRoyal Belgian Institute for Space Aeronomy, Brussels, BelgiumSpectroscopy, Quantum Chemistry and Atmospheric Remote Sensing (SQUARES), Université libre de Bruxelles (ULB), Brussels, BelgiumLaboratoire des Sciences du Climat et de l'Environnement (LSCE), CEA–CNRS–UVSQ, Gif-sur-Yvette, France<p>Ammonia (<span class="inline-formula">NH<sub>3</sub></span>) 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 <span class="inline-formula">%</span> of <span class="inline-formula">NH<sub>3</sub></span> 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 (CTMs) rely on bottom-up emission inventories, which are subject to significant uncertainties. In this study, we estimate emissions from livestock by developing a new module to calculate ammonia emissions from the whole agricultural sector (from housing and storage to grazing and fertilizer application) within the ORCHIDEE (Organising Carbon and Hydrology In Dynamic Ecosystems) global land surface model. We detail the approach used for quantifying livestock feed management, manure application, and indoor and soil emissions and subsequently evaluate the model performance. Our results reflect China, India, Africa, Latin America, the USA, and Europe as the main contributors to global <span class="inline-formula">NH<sub>3</sub></span> emissions, accounting for 80 % of the total budget. The global calculated emissions reach 44 <span class="inline-formula">Tg N yr<sup>−1</sup></span> over the 2005–2015 period, which is within the range estimated by previous work. Key parameters (e.g., the pH of the manure, timing of N application, and atmospheric <span class="inline-formula">NH<sub>3</sub></span> surface concentration) that drive the soil emissions have also been tested in order to assess the sensitivity of our model. Manure pH is the parameter to which modeled emissions are the most sensitive, with a 10 <span class="inline-formula">%</span> change in emissions per percent change in pH. Even though we found an underestimation in our emissions over Europe (<span class="inline-formula">−26</span> <span class="inline-formula">%</span>) and an overestimation in the USA (<span class="inline-formula">+56</span> <span class="inline-formula">%</span>) compared with previous work, other hot spot regions are consistent. The calculated emission 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 the CEDS (Community Emissions Data System).</p>https://gmd.copernicus.org/articles/16/1053/2023/gmd-16-1053-2023.pdf |
| spellingShingle | M. Beaudor N. Vuichard J. Lathière N. Evangeliou M. Van Damme M. Van Damme L. Clarisse D. Hauglustaine Global agricultural ammonia emissions simulated with the ORCHIDEE land surface model Geoscientific Model Development |
| title | Global agricultural ammonia emissions simulated with the ORCHIDEE land surface model |
| title_full | Global agricultural ammonia emissions simulated with the ORCHIDEE land surface model |
| title_fullStr | Global agricultural ammonia emissions simulated with the ORCHIDEE land surface model |
| title_full_unstemmed | Global agricultural ammonia emissions simulated with the ORCHIDEE land surface model |
| title_short | Global agricultural ammonia emissions simulated with the ORCHIDEE land surface model |
| title_sort | global agricultural ammonia emissions simulated with the orchidee land surface model |
| url | https://gmd.copernicus.org/articles/16/1053/2023/gmd-16-1053-2023.pdf |
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