Probabilistic Emissions Scenarios

Joint Program Technical Note
Probabilistic Emissions Scenarios
Reilly, J., M. Babiker, M. Webster and M. Sarofim (2001)
Joint Program Technical Note

Note #2 [Download]

Abstract/Summary:

We provide a set of three emissions scenarios with known probability characteristics generated using an uncertainty technique known as the deterministic equivalent modeling method (DEMM), which requires distributions for uncertain parameter inputs and then uses a statistical sampling technique to generate parameter sets, and the MIT Emissions Prediction and Policy Analysis (EPPA) model. Emissions of CO2, CH4, N2O, SF6, PFC, HFC, NOx, SOx, CO, NMVOC, NH3 and carbonaceous particulates from 1995 through 2100 at 5 year intervals are provided on a 1° by 1° latitude-longitude grid. These scenarios do not include emissions from natural sources or sinks of carbon, other GHGs, or other substances. They include emissions of carbon and other substances from land use change (deforestation) and agriculture (waste burning, livestock, rice production, soils) but do not include carbon sinks due to forest regrowth. The scenarios were selected by chosing parameter sets that produced the median (50 percentile value) and 97.5 percentile value (upper) and 2.5 percentile value (lower) limit for CO2 emissions in 2100 (i.e. a range covering 95 percent of the distribution). Conditional on these values, we then chose parameter sets that produced 50 percentile values for each of the other emissions. This scenario selection design was chosen so that the resulting scenarios are approximately 2.5, 50, 97.5 percentile outcomes yet retain the characteristic that the scenarios for all substances are the result of internally consistent scenarios given the structure of the EPPA model.

Citation:

Reilly, J., M. Babiker, M. Webster and M. Sarofim (2001): Probabilistic Emissions Scenarios. Joint Program Technical Note TN #2. (http://globalchange.mit.edu/publication/14340)
  • Joint Program Technical Note
Probabilistic Emissions Scenarios

Reilly, J., M. Babiker, M. Webster and M. Sarofim

2001

Abstract/Summary: 

We provide a set of three emissions scenarios with known probability characteristics generated using an uncertainty technique known as the deterministic equivalent modeling method (DEMM), which requires distributions for uncertain parameter inputs and then uses a statistical sampling technique to generate parameter sets, and the MIT Emissions Prediction and Policy Analysis (EPPA) model. Emissions of CO2, CH4, N2O, SF6, PFC, HFC, NOx, SOx, CO, NMVOC, NH3 and carbonaceous particulates from 1995 through 2100 at 5 year intervals are provided on a 1° by 1° latitude-longitude grid. These scenarios do not include emissions from natural sources or sinks of carbon, other GHGs, or other substances. They include emissions of carbon and other substances from land use change (deforestation) and agriculture (waste burning, livestock, rice production, soils) but do not include carbon sinks due to forest regrowth. The scenarios were selected by chosing parameter sets that produced the median (50 percentile value) and 97.5 percentile value (upper) and 2.5 percentile value (lower) limit for CO2 emissions in 2100 (i.e. a range covering 95 percent of the distribution). Conditional on these values, we then chose parameter sets that produced 50 percentile values for each of the other emissions. This scenario selection design was chosen so that the resulting scenarios are approximately 2.5, 50, 97.5 percentile outcomes yet retain the characteristic that the scenarios for all substances are the result of internally consistent scenarios given the structure of the EPPA model.