Browse data: Variable
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Variable
> Is input for 
: Atmospheric composition and climate or Energy supply or Terrestrial biodiversity
: Atmospheric composition and climate or Energy supply or Terrestrial biodiversity
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Is input for: (Click arrow to add another value) Showing below up to 22 results in range #1 to #22.
- BC, OC and NOx emissions (Emissions of BC, OC and NOx per year., type: model (from/to model))
- CO and NMVOC emissions (Emissions from CO and NMVOC., type: model (from/to model))
- CO2 emission from energy and industry (CO2 emission from energy and industry., type: model (from/to model))
- Cloudiness - grid (Percentage of cloudiness per month; assumed constant after the historical period, type: historical data)
- Demand for primary energy (Total demand for energy production. Sum of final energy demand and energy inputs into energy conversion processes., type: model (from/to model))
- Energy resources (Volume of energy resource per carrier, region and supply cost class (determines depletion dynamics)., type: driver)
- Global mean temperature (Average global temperature., type: model (from/to model))
- Land cover, land use - grid (Multi-dimensional map describing all aspects of land cover and land use per grid cell, such as type of natural vegetation, crop and grass fraction, crop management, fertiliser and manure input, livestock density., type: model (from/to model))
- Land supply for bioenergy - grid (Land available for sustainable bioenergy production (abandoned agricultural land and non-forested land)., type: model (from/to model))
- Land-use CO2 emissions - grid (Land-use CO2 emissions from deforestation, wood harvest, agricultural harvest, bioenergy plantations and timber decay., type: model (from/to model))
- Learning rate (Determines the rate of technology development in learning equations., type: driver)
- Management intensity crops (Management intensity crops, expressing actual yield level compared to potential yield. While potential yield is calculated for each grid cell, this parameter is expressed at the regional level. This parameter is based on data and exogenous assumptions - current practice and technological change in agriculture - and is endogenously adapted in the agro-economic model., type: model (from/to model))
- Management intensity livestock (Management intensity of livestock, expressed at the regional level. This parameter is based on data and exogenous assumptions, i.e. current practice and technological change in livestock sectors, and is endogenously adapted within the Agricultural economy component., type: model (from/to model))
- NEP (net ecosystem production) - grid (Net natural exchange of CO2 between biosphere and atmosphere (NPP minus soil respiration), excluding human induced fluxes such as decay of wood products., type: model (from/to model))
- Nitrogen deposition - grid (Deposition of nitrogen., type: model (from/to model))
- Non-CO2 GHG emissions (CH4, N2O and Halocarbons) (Non-CO2 GHG emissions (CH4, N2O, Halocarbons)., type: model (from/to model))
- Number of wet days - grid (Number of days with a rain event, per month; assumed constant after the historical period, type: historical data)
- Potential bioenergy yield - grid (Potential yields of bioenergy crops., type: model (from/to model))
- Protected area - grid (Map of protected nature areas, limiting use of this area., type: driver)
- SO2 emissions (SO2 emissions, per source (e.g. fossil fuel burning, deforestation)., type: model (from/to model))
- Technology development of energy supply (Learning curves and exogenous learning that determine technology development., type: driver)
- Trade restriction (Trade tariffs and barriers limiting trade in energy carriers (in energy submodel)., type: driver)