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Scenario modeling of ammonia emissions from surface applied urea under temperate conditions: application effects and model comparison

Author:
Pacholski, Andreas, Doehler, Johannes, Schmidhalter, Urs, Kreuter, Thomas
Source:
Nutrient cycling in agroecosystems 2018 v.110 no.1 pp. 177-193
ISSN:
1385-1314
Subject:
ammonia, data collection, dynamic models, emissions, emissions factor, empirical models, fertilizer application, flowering, meteorological data, nitrogen, prediction, urea, urea fertilizers, urea nitrogen, vegetation, winter wheat, Germany
Abstract:
The use of emission factors (EF) for ammonia (NH₃) after fertilizer application is a central tool for nitrogen management. Ammonia loss measurements after application of urea fertilizer at three research sites in Germany indicated that emissions deviated from European standard EFs. Scenario modelling of emissions based on long term weather data and variable application dates could provide a robust basis for the derivation of EFs. Two model approaches were used to test this approach for urea applied to winter wheat. The two model approaches comprised the dynamic model Volt’Air’ and a statistical model. Scenario calculations were run for 15 years and 4 application dates in each year for the 3 sites. The empirical model performed better at predicting cumulative losses. Both models simulated more than half of relative NH₃ emissions (% urea N applied) in a range of 0–10%. The average and median EFs by both models over all application dates were 10.2 and 8.1%, respectively, and were substantially lower than the current European EFs for urea (15–16%). The lowest median and mean EFs were observed at beginning of the vegetation period with 4.3/4.8 and 7.2/6.7% applied N for empirical and Volt’Air model, respectively, and highest at wheat anthesis (15/17.4 and 11/10.2%). Scenario modelling can be considered as a tool for the derivation of robust and representative EFs for NH₃ emissions not only for urea but also other emitting fertilizer sources. A much more expanded data set is needed and both model approaches require further development to reach this aim.
Agid:
5889008