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Using the EU farm sustainability data network to inform GHG and ammonia national inventory accounts

C. Buckley et al · Elsevier · 2026

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This research demonstrates how the EU Farm Accountancy Data Network (now Farm Sustainability Data Network) can be used to generate more accurate farm-level activity data to inform national inventory accounts for GHG and NH3 at a EU member state level. In an effort to reduce gaseous emissions from agriculture, farmers are persistently encouraged to change farm practices or adopt new technologies, yet it can to difficult to capture these changes and hence claim credit for these efforts in the national inventories. Until recent times, a historic survey method was used to capture important farm-level activity manure management based data (animal housing periods, structure of management facilities, timing and method of slurry spreading) in Ireland. The FADN is now used to inform this on a temporal basis in Ireland. Results here suggest that if this transition had not occurred then NH3 emissions could have been overestimated by up to 34% and GHG emissions by up to 7.5%, depending on the category in question.

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APA 7

al, C. B. E. (2026). Using the EU farm sustainability data network to inform GHG and ammonia national inventory accounts. https://doi.org/10.1016/j.indic.2026.101218

MLA

al, C. Buckley et. "Using the EU farm sustainability data network to inform GHG and ammonia national inventory accounts." 2026. https://doi.org/10.1016/j.indic.2026.101218.

Chicago

al, C. Buckley et. 2026. "Using the EU farm sustainability data network to inform GHG and ammonia national inventory accounts.". https://doi.org/10.1016/j.indic.2026.101218.

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al, C. B. E. 2026, Using the EU farm sustainability data network to inform GHG and ammonia national inventory accounts, Elsevier, available at: https://doi.org/10.1016/j.indic.2026.101218 [Accessed 7 Aug. 2026].

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Title
Using the EU farm sustainability data network to inform GHG and ammonia national inventory accounts
Author / contributors
C. Buckley et al
Publisher
Elsevier
Publication year
2026
ISSN
2665-9727
ISSN
2665-9727
Language
English

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