Assessing effects of exogenous assumptions in GHG emissions forecasts – a 2020 scenario study for Portugal using the Times energy technology model
Assessing effects of exogenous assumptions in GHG emissions forecasts – a 2020 scenario study for Portugal using the Times energy technology model
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DOI：
10.1016/j.techfore.2014.09.016
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发表时间：
2015-05
影响因子：
12
通讯作者：
S. Simoes;P. Fortes;J. Seixas;G. Huppes
中科院分区：
文献类型：
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作者：
S. Simoes;P. Fortes;J. Seixas;G. Huppes
能源-经济-环境模型是制定切实可行的成本效益气候政策的基础。然而，这些模型必然根据共同决定情景模拟结果的假设加以简化。主要假设涉及人口和经济发展、技术演变和部署以及政策决定。这种分析的核心是量化具体假设如何影响情景的结果;不像文献中通常那样将它们放在一起，而是逐一研究。TIMES建模框架被广泛用于气候政策支持，在这里我们使用葡萄牙语版本作为例子。由于TIMES模型的结构在其他国家类似，也适用于欧盟和世界等更大的总量，该方法可以直接应用于那里，尽管由于能源技术和能源市场的差异，各国之间的结果会有所不同。使用TIMES_PT的葡萄牙基线情景的结果显示了这项工作在假设敏感性分析中的相关性。与预期相反，对能源资源的可用性和价格的不同假设导致模拟结果中温室气体排放量的微小变化，不到2020年基准情景排放量的2%。与总体不确定性更相关的假设与社会经济发展有关，其次是关于技术部署的假设。对假设的详细不确定性分析有助于评估TIMES模型框架中建模结果的稳健性，以及模型结构和有效性等其他方面。
Energy-economy-environment models are fundamental in developing realistic cost-effective climate policy. However, such models by necessity are simplified based on assumptions which co-determine the outcomes of scenario modelling. Major assumptions relate to demographic and economic development, technology evolution and deployment and policy decisions. The core of this analysis is to quantify how specific assumptions influence the outcomes of scenarios; not taking them together as usually in the literature but instead looking into them apiece. The TIMES modelling framework is broadly used for climate policy support and here we used the Portuguese version as an example. As the structure of TIMES modelling is similar in other countries and also for larger aggregates as the EU and the World, the method can be applied there quite directly, although outcomes will differ between countries due to differences in energy technologies and energy markets. The outcomes for the Portugal Baseline scenario using TIMES_PT show the relevance of this exercise in this sensitivity analysis on assumptions. Contrary to what might be expected, varying assumptions on the availability and price of energy resources lead to minor variations on GHG emissions in the modelling outcomes, less than 2% of the Baseline scenario emissions in 2020. The more relevant assumptions to overall uncertainty are related to socio-economic development, followed by assumptions on technology deployment. This detailed uncertainty analysis on assumptions helps to assess the robustness of modelling outcomes in the TIMES model framework, next to other aspects like model structure and validity.