UNEP CO2 Uncertainty - Model
Bruno Merven
Bryce McCall
10.25375/uct.7222895.v1
https://zivahub.uct.ac.za/articles/dataset/UNEP_CO2_Uncertainty_-_Model/7222895
<div><b>Quantifying uncertainty in baseline projections of carbon dioxide emissions for South Africa</b><br></div><div><br></div><div><p>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. <br></p><p><br></p>
<p>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.</p>
<p>This study was commissioned by the <a href="http://www.unep.org/">United Nations Environment Programme</a>.</p></div>
2019-10-18 10:33:10
carbon emissions
baseline emissions
probability distribution
energy
energy research centre
Energy Generation, Conversion and Storage Engineering