Marco A. Janssen

The influence of human activities on the environment has reached such a scale and complexity that unequivocal solutions to the dis­ ruption can no longer be given. That is why increasing use is being made of integrated assessment, which is a multi-discipli­ nary process, having as its objective the integration of scientific knowledge drawn from a variety of areas. One instrument that is used in this process is the computer simulation model. There are various types of these integrated assessment models (IAM), as they are called. In general, these models are a combination of simplified versions of different expert models, allowing future scenarios to be analyzed of the entire problem area.

As the resistance of the malaria parasite to antimalarial drugs continues to increase, as does that of the malarial mosquito to insecticides, the efficacy of efforts to control malaria in many tropical countries is diminishing. This trend, together with the projected consequences of climate change, may prove to exacerbate substantially the significance of malaria in the coming decades.

In this article we introduce the use of an evolutionary modeling approach to simulate the adaptation of mosquitoes and parasites to the available pesticides and drugs. By coupling genetic algorithms with a dynamic malaria-epidemiological model, we derive a complex adaptive system capable of simulating adapting and evolving processes within both the mosquito and the parasite populations.

This approach is used to analyze malaria management strategies appropriate to regions of higher and lower degrees of endemicity. The results suggest that adequate use of insecticides and drugs may reduce the occurrence of malaria in regions of low endemicity, although increased efforts would be necessary in the event of a climate change. However, our model indicates that in regions of high endemicity the use of insecticides and drugs may lead to an increase in incidence due to enhanced resistance development. Projected climate change, on the other hand, may lead to a limited reduction of the occurrence of malaria due to the presence of a higher percentage of immune persons in the older age class.

We regard the global climate system as a controlled dynamic system, with controls corresponding to economic activities causing emissions of greenhouse gases. Previous optimization studies for climate change have used descriptions of the environmental system which are found to be too unrepresentative of what is known in the scientific community. In this paper an approach is applied which tries to include a more sophisticated model of the environmental system. The resulting continuous dynamic control problem is solved by the application of a set of non-linear optimization techniques to find optimal response strategies to maximize the discounted sum of future consumption while adhering to certain environmental constraints.

Keywords: Non-linear optimization; CO2; Climate change.

When tackling a subject as complex as global change and sustainable development, it is essential to be able to frame the issues. This was one of the main reasons for developing the TARGETS model, an integrated model of the global system, consisting of metamodels of important subsystems. In this chapter, we introduce TARGETS. Building on the previous chapters, we elaborate on the possibilities and limitations of integrated assessment models. Some of the key issues discussed are aggregation, model calibration, and validation, and dealing with uncertainty.

This submodel simulates the supply and demand for fuels and electricity, given a certain level of economic activity. It is linked to other submodels, for example through investment flows, population sizes, and emissions. The energy model consists of five modules: Energy Demand, Electric Power Generation, and Solid, Liquid and Gaseous Fuel supply. Effects such as those of depletion, conservation, fuel substitution, technological innovation, and energy efficiency are incorporated in an integrated way, with prices as important signals. Renewable sources are included as a non-thermal electricity option and as commercial biofuels.

In this chapter we present simulation experiments and outcomes of the energy submodel TIME. First, the major controversies and uncertainties are discussed. Next, the cultural perspectives are introduced with reference to world energy, after which we clarify the way in which these are linked to assumptions and model routes. Some results of sensitivity and uncertainty analyses are also given. We discuss a few energy dystopias which could emerge if, for a given population-economy scenario, the world view and the management style within the energy system are discordant. Some conclusions are presented about the plausibility of and risks related to the Utopian energy futures. The impacts of the emissions from fossil fuel combustion on water, land, and element cycles are discussed in the next three chapters.