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Duration: 2008 -

MAIOLICA: Simulation of vegetation emitted greenhouse gases

Greenhouse gases emitted from vegetation feed back on the atmospheric chemistry and climate. We aim to simulate such vegetation produced greenhouse gases and to provide information on emissions from other sources.

Embedding 

The project is part of the interdisciplinary MAIOLICA project (http://www.cces.ethz.ch/projects/clench/maiolica) - framed within the Swiss CCES (ETH Competence Center of Environment and Sustainability).  MAIOLICA aims at improving the understanding of processes contributing to GHG emissions, including CH4, N2O, CO2 and H2O, from temperate, mid-latitude terrestrial ecosystems and investigating the interactions and feedbacks among the terrestrial biosphere, the atmospheric composition and the climate.  

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Rationale

In existing climate driven biogeochemical models or dynamic global vegetation GHGs besides CO2 are not fully represented. In the MAIOLICA project, multiple spatial scales are addressed from measurement sites up to the temperate zone, which requires models capable of working at different scales. With climate change, vegetation changes in space and time.  Furthermore, land use (change) influences vegetation strongly and other GHG emissions (e.g. methane from cows) can not be neglected in studying feedbacks.

Aims

  • to incorporate advances in our fundamental understanding of GHG emissions from vegetation and soils, into a scalable dynamic vegetation model.
  • to determine the appropriate resolution that is needed to represent GHG emissions a) at a regional scale in the complex terrain of Switzerland, b) as well at a global scale given the heterogeneity of processes involved in GHG emissions in various ecosystems.
  • to quantify the sensitivity of trace gas emissions to climate-induced changes in vegetation structure, composition and phenology.
  • to provide data and scenarios of land use (change) and of non-vegetation GHG scenarios on the resolutions required in MAIOLICA.

Methods

We compile data and scenarios on global land use, land use change, and non-vegetation emissions of GHGs from various sources and scale them to the appropriate resolution. Starting from existing DGVMs, we assemble a new model covering non-CO2 GHG emissions and improve it based on measurements in MAIOLICA. We test the sensitivity of this model to different spatial scales and to vegetation structure and dynamics.

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Keywords vegetation, greenhouse gases, simulation, modelling, scaling, DGVM