实现前所未有:为雄心勃勃的气候政策目标建立扩散路径模型

IF 5.8 Q2 ENERGY & FUELS
Tomás Mac Uidhir , Brian Ó Gallachóir , John Curtis , Fionn Rogan
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引用次数: 2

摘要

爱尔兰有一些非常大胆的目标,作为总体温室气体减排雄心的一部分。然而,尚不清楚这些目标在多大程度上符合新技术进入市场并被广泛采用的速度。本文通过结合备受尊重和经验验证的技术扩散估计与能源模型来解决这个问题。其目的是阐明爱尔兰在实现这些目标方面面临的一些挑战。结果表明,爱尔兰的电动汽车和住宅改造目标需要的技术扩散速度远远超过国际上迄今为止最成功的转型的历史速度。这一结果使爱尔兰的雄心受到质疑。根据技术扩散理论,本文还提供了爱尔兰可能考虑的额外补充政策的见解,以加速关键技术的扩散。本文论证了借鉴历史先例的方法和价值,以帮助确定未来过渡情景的可行性。它还指出了工业标准扩散理论如何帮助确定加速能源转型的政策解决方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Achieving the unprecedented: Modelling diffusion pathways for ambitious climate policy targets

Ireland has some very bold targets, as part of a substantial overall greenhouse gas emissions reduction ambition. It is unclear however to what extent these targets are consistent with the pace at which new technologies can enter the market and become widely adopted. This paper grapples with this by combining well-respected and empirically validated estimates of technology diffusion together with energy models. Its purpose is to illuminate some of Ireland's challenges associated with meeting these targets. The results show Ireland's electric vehicle and residential retrofitting goals would require rates of technology diffusion that are well beyond the historical rates internationally of even the most successful transformations to date. This result calls Ireland's ambitions into question. Drawing on the theory of technology diffusion, the paper also provides insights into additional complementary policies that Ireland might consider in order to accelerate diffusion of key technologies. The paper demonstrates the means and the value of drawing on historical precedents to help determine the feasibility of future transition scenarios. It also points to how industry-standard diffusion theory can help to identify policy solutions to accelerate the energy transition.

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来源期刊
Energy and climate change
Energy and climate change Global and Planetary Change, Renewable Energy, Sustainability and the Environment, Management, Monitoring, Policy and Law
CiteScore
7.90
自引率
0.00%
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