Modelling Climate Policy – Trade-Off Metrics, Resource Markets, and Uncertainty
Abstract: This thesis consists of five papers related to climate change policy. In paper I andpaper II we discuss the use of Global Warming Potentials (GWPs) that facilitate the tradeoffbetween abatement of the different greenhouse gases (GHGs). In paper I we estimatethe cost of using GWPs instead of a cost-effective trade-off between the different GHGs,using a dynamic integrated climate economic model, MiMiC. The results show that thiscost is rather small, ~5% increase in net present value abatement cost, if the surfacetemperature is to be stabilised at 2ºC above the pre-industrial level. In paper II, we takethe analysis of cost-effective trade-off ratios between the different GHGs one step furtherand introduce uncertainty and learning in climate sensitivity. We find that the moreuncertain we are about climate sensitivity today, the higher should a short-lived GHG,methane, be valued relative to a long-lived GHG, carbon dioxide. However, the costeffectivetrade-off ratio is still lower than methane’s GWP as used in the Kyoto Protocol.In paper III, we study uncertainties in the emissions inventories and the proposal thatemissions targets should be met with a degree of certainty above 50%. We find that giventhat compliance cost should be minimized, emissions with quantification uncertaintiesshould be taxed higher (lower) per expected ton if abatement of these emissions reduces(increases) the uncertainty of the emissions portfolio.In paper IV, we develop a dynamic non-cooperative game model to analyse howOPEC’s oil rent is affected by carbon prices. We find that in the majority of cases analysedOPEC may actually gain rent due to carbon prices. The reason for the increase in rent isthat most of the cost-effective alternatives to conventional oil have higher life cycle CO2emissions.In paper V, we study how carbon taxes would affect the demand for bioenergy andhow this would affect the agricultural sector using an energy-agricultural-economy model,LUCEA. We find that food prices may increase substantially due to the land scarcityinduced by the cultivation of energy crops. In addition, our analysis does not support thebelief that energy crops will be cultivated on low quality lands so as to avoid landcompetition with food production.
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