UNEP CO2 Uncertainty - Model

<b>Quantifying uncertainty in baseline projections of carbon dioxide emissions for South Africa</b><br><br>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><br> 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.

<b>南非二氧化碳基线排放预测的不确定性量化</b><br><br>本项目旨在量化核心模型输入参数相关的不确定性，以构建2015-2050年南非基线碳排放的概率分布。本项目将通过两个阶段完成既定目标：第一阶段，遴选对结果影响显著且不确定性较高的输入参数开展不确定性分析，并对其关联的不确定性进行量化刻画；第二阶段，通过南非能源-经济-环境（E3，Energy-Economy-Environment）模型（South African TIMES Model，简称SATIM）传递输入参数的不确定性，最终得到目标研究时段内南非基线碳排放的概率分布。<br><br>对如此久远的未来开展排放预测，是一项极为复杂甚至近乎难以实现的任务。本研究采用多种方法论组合开展此项工作，并通过三角验证法整合不同方法的结果，以期得到具备共识性的预测结论。本研究采用的核心思路为：针对影响能源系统进而关联温室气体（Greenhouse Gas，GHG）排放的少量关键驱动因子开展不确定性评估。我们将先评估这些驱动因子未来可能取值的概率分布，再将其输入至E3模型中。针对每一组可能的输入参数组合，模型将输出温室气体排放等相关量化结果。通过向SATIM模型输入多组不同的参数组合，可得到一系列潜在的输出结果，该过程采用蒙特卡洛模拟（Monte Carlo simulation）方法实现。本研究由联合国环境规划署（United Nations Environment Programme，UNEP）委托开展。