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Janssen, M.A. 1996
PhD Dissertation, University Maastricht ISBN 90-9009908-5
The objective of this paper is to demonstrate a methodology whereby reductions of greenhouse gas emissions can be allocated on a regional level with minimal deviation from the “business as usual emission scenario”. The methodology developed employs a two stage optimization process utilizing techniques of mathematical programming. The stage one process solves a world emission reduction problem producing an optimal emission reduction strategy for the world by maximizing an economic utility function. Stage two addresses a regional emission reduction allocation problem via the solution of an auxiliary optimization problem minimizing disruption from the above business as usual emission strategies. Our analysis demonstrates that optimal CO2 emission reduction strategies are very sensitive to the targets placed on CO2 concentrations, in every region of the world. It is hoped that the optimization analysis will help decision-makers narrow their debate to realistic environmental targets.
This report contains an integrated analysis of the Targets/IMage Energy (TIME) model. In a previous report (De Vries and Van den Wijngaart, 1995) the five submodels of the energy model were described in detail. Here, we describe a number of applications with the (stand-alone) TIME model.
After the introduction and a brief outline of the TIME framework in Chapter 2, Chapter 3 describes the calibration of the world version for the period 1900-1990. Given the exogenous drivers like population size and economic activities, the energy demand, fuel mix, fuel prices, energy investments- and C02 emissions are calculated and compared with observed values. We discuss what assumptions had to be made to derive a suitable fit with the observed values.
Chapter 4 present the methodology for scenario construction. Furthermore, we discuss uncertainties and assumptions on structural change, energy efficiency improvements, long-term supply cost curves of fossil fuel resources, and technology in energy supply options.
An application of the methodology of Chapter 4 is discussed in Chapter 5 where a reference scenario is constructed based on the IS92a scenario of the IPCC. In Chapter 6 some scenarios from other institutions are investigated by assessing their outcomes in terms of the underlying assumptions. In Chapter 7, we will discuss energy futures according to alternative perspectives or world views. Finally, in Chapter 8, we give some results of optimized mitigation strategies using the CYCLES module of TARGETS to assess the impacts of scenarios. We especially address the role of technological change in meeting climate change policy targets.