From left to right you can see a tractor spreading liquid manure, two cows standing next to each other, a forest and an aerial view of agricultural fields.

QS_II | Agri-For-Live: Modelling greenhouse gas emissions from agriculture, forestry and livestock farming in Germany

The joint project Agri-For-Live associated with ITMS with the partners KIT, Thünen Institute and FZJ deals with three central aspects of ITMS:
(A) High temporal and spatial resolution of activity data from agriculture, forestry and land use (AFOLU), (B) Emission of greenhouse gases (GHG) from livestock, (C) Biogeochemical modelling of GHG exchange processes in agricultural and forestry ecosystems to improve the spatial and temporal resolution of bottom-up GHG inventories.

Within the ITMS project, atmospheric observations from the ground, the air and space (Module B) are combined with greenhouse gas inventories (Module Q&S) as "a priori" information. Subsequent atmospheric (inverse) modelling (Module M) then makes it possible to monitor the sources and sinks of greenhouse gases (GHG) with high spatial and temporal resolution. An essential prerequisite is that the GHG inventories achieve the highest possible spatial and temporal resolution.

Agri-For-Live uses detailed activity, soil and vegetation data to calculate GHG emissions (CO2, N2O, CH4) from agriculture, forestry and livestock farming with an unprecedented spatial and temporal resolution. The input data is generated and compiled by the Thünen Institute for two federal states with good data availability and a large agricultural area.

The LandscapeDNDC, CLM and GasEM models will be tested and further developed better to represent the temporal and spatial patterns of GHG exchange and to assess their suitability as a priori estimates for Module M. A central goal of ITMS is to develop a GHG monitoring system that can be operated operationally. Therefore, input data with different spatial and temporal resolutions will be used to investigate and evaluate their suitability as well as the costs (data protection, computing power) and benefits (spatial and temporal improvement) for improving the quality of GHG inventories and their integration capability into atmospheric (inverse) modelling.
In addition to improving data sources, recommendations are an important result of Agri-For-Live, in which quality data sources and data are necessary to achieve the goals of ITMS and where there is still a need for research.

Participating Institutions:

Involved persons:

 

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