UNEP CO2 Uncertainty - Reports
Domaine:
climateenvironment and energyType de record:
projectdataset
Créateur:
McC
McCÉditeur:
Uni
Hôte:
Quantifying uncertainty in baseline projections of carbon dioxide emissions for South Africa
The objective of this project is to quantify the uncertainty associated with key model inputs to develop a probability distribution of baseline emissions for South Africa over the 2015-2050 period. This objective is to be met in two phases. In the first phase, the most important and uncertain input parameters were selected for uncertainty analysis, and the associated uncertainty was described. In the second phase the uncertainty in inputs is propagated via an E3 model of South Africa (South African TIMES Model - SATIM) to obtain the probability distribution for the baseline emissions of South Africa, over the period of interest.
Projecting this far into the future is an extremely, perhaps impossibly, complex task. We use a combination of methodological approaches to do this, triangulating between these approach in an attempt to arrive at some kind of consensus projections. The approach followed here is to assess uncertainty on a small number of key drivers influencing the energy system, and hence GHG emissions associated with it. We assess distributions over possible values that these drivers can obtain in the future, and pass these values to the E3 model. For each combination of possible inputs, the model returns outputs for quantities like GHG emissions. By submitting many possible inputs to SATIM, a range of possible outputs is obtained. This process takes the form of a Monte Carlo simulation. This study was commissioned by the United Nations Environment Programme.
The objective of this project is to quantify the uncertainty associated with key model inputs to develop a probability distribution of baseline emissions for South Africa over the 2015-2050 period. This objective is to be met in two phases. In the first phase, the most important and uncertain input parameters were selected for uncertainty analysis, and the associated uncertainty was described. In the second phase the uncertainty in inputs is propagated via an E3 model of South Africa (South African TIMES Model - SATIM) to obtain the probability distribution for the baseline emissions of South Africa, over the period of interest.
Projecting this far into the future is an extremely, perhaps impossibly, complex task. We use a combination of methodological approaches to do this, triangulating between these approach in an attempt to arrive at some kind of consensus projections. The approach followed here is to assess uncertainty on a small number of key drivers influencing the energy system, and hence GHG emissions associated with it. We assess distributions over possible values that these drivers can obtain in the future, and pass these values to the E3 model. For each combination of possible inputs, the model returns outputs for quantities like GHG emissions. By submitting many possible inputs to SATIM, a range of possible outputs is obtained. This process takes the form of a Monte Carlo simulation. This study was commissioned by the United Nations Environment Programme.