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Are scenarios of energy demand in the building stock in line with Paris targets?

机译:建筑库存中的能源需求情景是否符合巴黎的目标?

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COP21 led to an agreed target of keeping the increase in global average temperature well below 2 degrees C compared to pre-industrial levels. Due to its high potential for decarbonisation, the building stock will have to contribute a reduction of at least 85-95% in greenhouse gas (GHG) emissions until 2050. Policy-driven scenario analysis is, therefore, important for assisting policy makers who are called upon to develop a corresponding framework to achieve those targets. The research questions of this paper are (1) Do long-term scenarios (in particular those labelled as ambitious) of energy demand in buildings reflect the COP21 target? (2) If not: What are reasons for the gap in terms of scenario assumptions, in particular, regarding the policy framework in the corresponding scenarios? The method builds on following steps: (1) analysis of GHG-emission reduction in scenarios from the policy-driven, bottom-up model Invert/EE-Lab; (2) compare scenarios among each other and analyse if they are in line with Paris targets; (3) discuss possible explanations for any gaps and the implications on future modelling work and policy making. Results show that scenarios labelled as being ambitious for several EU MSs achieve GHG-emission reductions of 56-96% until 2050. However, just 27% of these ambitious scenarios achieve reductions above 85%. The reason is that policies for most of the modelled scenarios were developed together with policy makers and stakeholders, whofor different reasonswere not willing to go beyond a certain stringency in the modelled instruments. In particular, this was the case for regulatory instruments, which show to be essential for achieving ambitious climate targets.
机译:COP21达成了一个商定的目标,即与工业化前的水平相比,将全球平均温度的升高保持在2摄氏度以下。由于其高脱碳潜力,到2050年,建筑材料将必须减少至少85-95%的温室气体(GHG)排放。因此,政策驱动的情景分析对于协助决策者来说非常重要。呼吁开发相应的框架以实现这些目标。本文的研究问题是(1)建筑的能源需求的长期情景(尤其是那些雄心勃勃的情景)是否反映了COP21目标? (2)如果不是,那么:在情景假设方面,尤其是在相应情景中的政策框架方面,造成差距的原因是什么?该方法基于以下步骤:(1)从政策驱动的自下而上模型Invert / EE-Lab分析情景中的温室气体排放减少; (2)相互比较情景并分析它们是否符合巴黎目标; (3)讨论任何差距的可能解释,以及对未来建模工作和政策制定的影响。结果显示,到2050年,被标记为对多个欧盟成员国有雄心的方案可实现56-6%的温室气体减排。但是,在这些雄心勃勃的方案中,只有27%的减排量超过85%。原因是大多数建模场景的政策都是与决策者和利益相关者共同制定的,出于不同的原因,他们不愿意超出建模工具的特定严格性。尤其是监管手段的情况就是如此,这对实现雄心勃勃的气候目标至关重要。

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