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Economic and policy uncertainty in climate change mitigation: The London Smart City case scenario.
- Source :
- Technological Forecasting & Social Change; May2019, Vol. 142, p384-393, 10p
- Publication Year :
- 2019
-
Abstract
- Abstract Despite the overwhelming consensus within the scientific community concerning the causes and effects of climate change, decision-making processes often do not point out in the same direction. In order to effectively and satisfactorily tackle climate change, a legally and politically binding long-term policy architecture is needed. In practice, however, central governments and international policymakers have been unable to provide a successful policy architecture. Yet, city-level initiatives within the Smart City framework are a promising way to tackle climate change. An example of such a Smart City framework is the London Environment Strategy (LES). In this paper, we propose a zero mean reverting model for greenhouse gas emissions to quantitatively analyze its consistency with the 2050 Zero Carbon objectives. We consider different policy scenarios proposed in the LES and the forward-looking policy uncertainty embedded in different economic sectors, primarily domestic, industrial and commercial and transport. We find that, on average, only transport improves the historical greenhouse gas emissions trend, and most of this reduction comes from Smart Mobility and/or Smart Regulation programs focusing on the environment. Highlights • Most actions oriented to mitigate the effects of climate change are being taken at the city level. • The current GHG emission trend in London is not in line with the 2050 zero level objective. • Stress test analysis considering a zero mean reverting process and different policy scenarios • Considering the simulation average trend only Transport sector improves the historical trend. • Industrial and Commercial sector reports the highest level of uncertainty. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 00401625
- Volume :
- 142
- Database :
- Supplemental Index
- Journal :
- Technological Forecasting & Social Change
- Publication Type :
- Academic Journal
- Accession number :
- 135355112
- Full Text :
- https://doi.org/10.1016/j.techfore.2018.07.018