The ALFAM2 Project - Ammonia Loss from Field-Applied Manure

Welcome to the ALFAM2 project on ammonia emission from field-applied manure. This objective of this collaborative project is to develop tools for understanding and predicting ammonia loss from field-applied manure. On this page you can find the two primary project products: emission measurements and a model.


June 2024. The ALFAM2 R package is now on CRAN: The CRAN version can be installed in R with install.packages('ALFAM2'). Users can still find the latest work and discussion on the GitHub repository:

June 2024. New parameter set 3 has been developed based on the latest version of the database and an extended model structure. See v3.9 of the Excel model or v4.0 of the R package (links to left).

May 2024. A new version of the ALFAM2 database is now available from the ALFAM2-data repository and the database web app (v2.50). This version includes new measurements from Aarhus University (Denmark), WUR (the Netherlands), INRAE (France), DiSAA (Italy), UNIMI (Italy), and UNINA (Italy). Canada, Denmark, Italy,

The ALFAM2 database

The ALFAM2 database contains original measurements on ammonia emission from animal manure applied in field trials, along with supporting information. The current version has data from more than 2,600 plots and more than 70,000 measurement intervals. The plot below shows average flux for all measurement intervals in the database within the first 5 days or so, with a different color for each application method.

For a simple interface to the database that includes filtering, see the ALFAM2 database web app:

For dataset version history or to report errors in the data, please see the ALFAM2-data repository on GitHub:

For more details on the ALFAM2 database, check out our paper in Agricultural and Forest Meteorology.

To submit data, please send an email message to sasha.hafner(at) A data submission template is available here.

The ALFAM2 model

The ALFAM2 model is a semi-empirical (semi-mechanistic) dynamic model that predicts ammonia emission from field-applied slurry in response slurry properties, management, and weather. The figure below shows the general structure of the model.

There are two interfaces: the ALFAM2 R package provides the most power and flexibility, but requires some basic understanding of R, while the Excel version is very easy to use but not as flexible. 

For more details on the ALFAM2 model, check out our paper in Atmospheric Environment.

Looking for the original ALFAM model?

Compared to the new model, it is based on older data, a less flexible approach, and does not include acidification or incorporation timing, but you can download it here.

Mailing list

Sign up for the mailing list to receive infrequent updates by sending a message to sasha.hafner(at)


This project was led by Sasha D. Hafner and Sven G. Sommer. The database contains measurements made by many reseachers. The following individuals contributed data: Jesper Nørlem Kamp, Johanna Pedersen, Sven G. Sommer, Massimo Zilio, Fabrizio Adani, Francisco Salazar, Ester Scotto di Perta, Stefania Pindozza, Andreas Pacholski, Shabtai Bittman, William Burchill, Wim Bussink, Martin Chantigny, Marco Carozzi, Sophie Génermont, Christoph Häni, Martin N. Hansen, Jan Huijsmans, Derek Hunt, Thomas Kupper, Gary Lanigan, Benjamin Loubet, Tom Misselbrook, John J. Meisinger, Albrecht Neftel, Tavs Nyord, Simon V. Pedersen, Jörg Sintermann, and Rodney B. Thompson. Sasha D. Hafner, Simon V. Pedersen, and Sven G. Sommer (all at the University of Southern Denmark at the time) created the dataset and Jon Katz created the database interface. Sasha D. Hafner created and maintains the model, with help and constructive criticism from Christoph Häni, Roland Fuß, Nick Hutchings, Anders Peter S. Adamsen, Andreas Pacholski, Shabtai Bittman, Marco Carozzi, Martin Chantigny, Sophie Genermont, Martin Hansen, Jan Huijsmans, Thomas Kupper, Tom Misselbrook, Albrecht Neftel, Tavs Nyord, and Sven Sommer. Sasha D. Hafner, Christoph Häni, and Roland Fuß wrote the ALFAM2 R package.