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Modelling of greenhouse gas emissions from land use in Germany
Project
Project code: TI-AK-08-PID1529
Contract period: 01.11.2010
- 31.05.2015
Purpose of research: Inventory & Assessment
Germany claimed to reduce its green house gas emission by 40% until 2020. Agriculture has to contribute to this ambiguous goal. Mitigation strategies for greenhouse gases from agriculture have to be developed and evaluated on the national and regional level. It is the aim of the joint research project CC-LandStraD to assess strategies of greenhouse gas mitigation and strategies of land use adaption on climate change. Strategies are evaluated with regard to their effectiveness and their implications for major land use claims and ecosystem functions. To increase practical relevance of the study stake holder accompany the process of scenario development and assessment. The modeling of land use scenarios with a joint modeling framework combining socioeconomic and biophysical models provides information necessary for the assessment process. Within the sub project “Modeling impacts of land management on greenhouse gas emissions from German agriculture and forestry” model approaches and regionalization methods are developed to quantify nitrous oxide and methane emissions from land use and live stock management and green house gas emissions from organic soils. Within the project statistical approaches are developed which are trained on data sets of measured GHG emissions and related anthropogenic and natural factors. These models are used to regionalize GHG emissions and mitigation potentials from land use in Germany. Up-scaled GHG emissions are used to generate maps of regional specific emission factors. Those emission factor maps are used in the CC-LandStraD modeling network to calculate the mitigation effects of agricultural management strategies. Furthermore modules which estimate daily nitrous oxide emissions will be developed and coupled to process based models.
Section overview
Subjects
- Crop Production
- Animal Husbandry
- Climate Change