- Title
- A control-theoretic approach to incorporate uncertainty into the dynamic integrated climate-economy (DICE) model
- Creator
- Hafeez, Salman
- Relation
- University of Newcastle Research Higher Degree Thesis
- Resource Type
- thesis
- Date
- 2018
- Description
- Research Doctorate - Doctor of Philosophy (PhD)
- Description
- Anthropogenic climate change causes geophysical changes i.e. sea-level rise and ocean acidification, resulting in economic damages. Integrated assessment models (IAM) are a key tool used to compute the dollar cost of economic damages caused by the emission of a one ton of carbon dioxide (CO₂) into the atmosphere. This dollar cost is known as the social cost of carbon (SCC). The Dynamic Integrated Climate-Economy (DICE) model is one of the most widely used IAMs, in which a dynamic non-linear model of geophysics is coupled with a stylised dynamic non-linear global macroeconomic model in feedback form. Based on Ramsey's optimal theory of savings, an optimal control problem is solved for the DICE model, maximising the discounted utility of economic consumption over multiple centuries subject to constraints of geophysics and economy. Doing so, DICE and the associated optimal control problem provide estimates of optimal CO₂ abatement pathways for the future, while computing the SCC associated with each pathway. A key observation is that uncertainty is an integral part of the integrated assessment of climate change. This uncertainty arises from incomplete knowledge of dynamics of the geophysics and the global economy, unclear knowledge of climate change impacts, or uncertain response of the global community towards the adoption of CO₂ abatement policies. In its standard formulation, DICE does not incorporate uncertainty in its integrated assessment of climate change. Uncertainty has long been studied in control engineering, yielding sophisticated techniques for incorporating, analysing, and quantifying uncertainty in mathematical models. In this thesis, we incorporate key scientific and socio-economic uncertainties present in the integrated assessment of climate change in DICE and quantify their impacts on estimates of the SCC produced by DICE. By incorporating key scientific uncertainties into DICE, 5-95% confidence interval values of the SCC are estimated between $4.05-$63.99 in US 2005$ for the year 2015. With the climate modelling uncertainty incorporated into DICE, estimates of the SCC range between $10-$39 in US 2005$ for year 2015. In comparison, the default SCC estimate of DICE for year 2015 is $17.7 in US 2005$. While impacts of uncertainties on estimates of the SCC in DICE are quantified, the primary focus in this thesis is to propose methods that use control engineering techniques for incorporating and analysing uncertainty in DICE.
- Subject
- uncertainty; control engineering; climate change; DICE; SCC; MPC
- Identifier
- http://hdl.handle.net/1959.13/1393758
- Identifier
- uon:33606
- Rights
- Copyright 2018 Salman Hafeez
- Language
- eng
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| Thumbnail | File | Description | Size | Format | |||
|---|---|---|---|---|---|---|---|
| View Details Download | ATTACHMENT01 | Thesis | 2 MB | Adobe Acrobat PDF | View Details Download | ||
| View Details Download | ATTACHMENT02 | Abstract | 340 KB | Adobe Acrobat PDF | View Details Download |