MELS

Greenhouse gas and ammonia (NH3) emissions from agricultural systems occur from multiple, interacting sources (Chadwick et al. 2011, Sajeev et al. 2018), making it challenging to estimate emissions at the farm- and national scales.

MELS will collate CH4, N2O and NH3 emissions datasets associated with manure management in livestock production from international project participants along with ancillary data. MELS builds on the Global Research Alliance (GRA) supported DATAMAN project (van der Weerden et al. 2018), which incorporates existing databases (e.g. ALFAM2, AEDA, ELFE; Hafner et al. 2018; AEDA, 2018; Vigan et al. 2018) and datasets from developed and developing countries. Analysis of the resulting data will allow the project team to generate empirical and/or process-oriented relationships between GHG emissions and manure composition, management, climate and abiotic data. This will allow the development of better GHG emission inventory methodologies that take account of regional variations in GHG emissions from livestock systems and mitigation efficiencies, providing an improved basis for assessing and documenting mitigation options. A whole system approach will be used, in which the mass flow of both C and N will be followed, allowing a quantification of the effect of applying a mitigation measure to one GHG source on other sources (knock-on effects). This will assist with identifying potentially unintended consequences. Equally, emission reduction co-benefits will be identified.

• To improve the methodologies available to inventory compilers to estimate the direct and indirect greenhouse gas (GHG) emissions from livestock production systems, with a particular emphasis on manure management and grassland management.
• To assist inventory compilers to estimate and document the impact of mitigation measures on the emissions reported within national inventories.
• To provide improved algorithms and emission factors for use in farm-scale GHG decision support systems (DSSs).
• To provide simplified methods for accounting for carbon (C) sequestration in soils.
• To develop an open-access prototype farm-scale GHG DSS.
• To improve methods to assess the cost and savings associated with mitigation measures at the farm and national scales.

1. Leibniz Institute for Agricultural Engineering and Bioeconomy (ATB), DE – COORDINATOR
2. ΤEAGASC – Agriculture and Food Development Authority (TEAGASC), IE
3. Aarhus University (AU), DK
4. AgResearch (AgR), New Zealand
5. French National Research Institute for Agriculture, Food and Environment (INRAe), IN1, FR
6. Agricultural Research Institute (INIA Chile), Chile
7. University of Zielona Góra (UZG), PL
8. Cork University Business School (CUBS), IE
9. French National Research Institute for Agriculture, Food and Environment (INRAe), FR
10. Agricultural University of Athens (AUA), GR