Trajectories of the Carbon ClimateHuman System as Emergent Properties

It might seem that closing the carbon gap is simply a matter of managing the future values of the quantities P, g, e, f i, FLULuc , F^ , and FDp which determine the total direct-human-induced flux Fdhi (t), so that its trajectory conforms with a stabilization trajectory FStbh(t). Of course, the real world is not like this "command and control" or "rational" decision-making model (Keely and Scoones 1999). All these quantities are internal variables in a coupled carbon-climate-human system and are constrained by numerous interactions with other variables. The future trajectory of the system, and of each of its components, is an emergent property—that is, a property of component interactions rather than the result of external control.

To explore these constraints and interactions, we consider the multiple effects of a portfolio of mitigation options or technologies. These options may include any of those listed after equation (3), together with abatement of non-CO2 greenhouse gas emissions from agriculture and other sectors. The effect of any one mitigation technology can be described by its technical potential (T) and its uptake proportion (u), where T is the maximum mitigation or carbon equivalent avoided emission (in tCeq per year) that can be achieved by the technology, subject only to biophysical constraints such as resource availability; and u is a number between 0 and 1 determining how much of the technical potential is actually utilized, subject to additional economic, environmental, and sociocultural factors. The achieved mitigation from a portfolio of options will then be + u2 T2 + ... , where the subscripts refer to different technologies.

A range of constraints and driving factors influence the uptake of a mitigation technology, and the effort devoted to maximizing its technical potential. Briefly (pending more detailed discussion in the next subsection), these include:

• climate factors: the need to avoid dangerous anthropogenic interference in the climate system by minimizing CO2 and other greenhouse gas emissions (the direct purpose of mitigation);

• economic factors, including the competitiveness of energy options, the material and energy intensities of economic growth, access to markets, and industrialization pathways;

• non-greenhouse environmental factors, including the provision and maintenance of ecosystem services such as clean air, clean water, and biodiversity; and

• social, cultural, and institutional factors, including consumption patterns, lifestyles, class structures, incentives, policy climates, and demographics at scales from local to global.

To account for these influences, we consider "utility functions" or "benefit functions" U^,. , Un , Un , and Uc that quantify the effects of the portfolio of mitigation

Cltm Econ Env Soc l J r o options in climate, economic, environmental, and sociocultural spheres. These functions may be either positive (net benefits) or negative (net costs). They reflect all aspects of societal well-being and are not confined to measurement in economic terms. They depend on the uptake proportions of the various mitigation options: thus, UI,con = Ujicon u) (where the subscript k distinguishes the various technologies) and similarly for UEnv and USc. A major part of the climate utility Uclim is clearly the total achieved mitigation u 1^1 + u2T2 + . . ., though there may be climate costs as well, for instance through adverse effects of land use change on regional climates (Betts et al. 2000) or increased N2O emissions from higher fertilizer use.

It is possible to consider the overall utility or net benefit from the portfolio of mitigation options, UtoUi , accounting for benefits and costs in all spheres. This is a combination of the utilities U , U , U , and U . There is a substantial literature

Cltm Econ Env Soc from the discipline of welfare economics on the formulation and properties of such overall utility measures (see, for example, Brock et al. 2002). Here it suffices to assume that UTotal is the weighted sum

UTotal = wClimUClim (uk ) + WEconUEcon(uk ) + WSocUSoc(uk ) + WEnvUEnv(uk ) (4)

where the weight factors w describe the relative importance that a society gives to each component of the overall utility of the portfolio of options. The uptake proportions uk can now be formally specified as the quantities u(t), which maximize the overall utility, integrated over some time period, subject to several basic constraints: that energy supply meets demand and that requirements are met for other basic resources such as water, food, and land. It is also possible to regard the technical potentials Tk as variable to maximize U^g, to the extent that the technical potentials are influenced by societal choices such as investment in research and development. Thus, both uk and Tk emerge as "control variables" in a constrained optimization.

This is merely an indicative analysis rather than a quantitative recipe. Even so, several features emerge. First, major variables determining the outcome are the weights w, which express the economic, environmental, sociocultural, and policy priorities emerging from societal institutions and structures. These weights are key "levers" influencing future trajectories of the energy system and more generally the carbon-climate-human system.

Second, diverse societies have different institutions, structures, and priorities. The analysis and the outcomes are therefore both regionally specific. A major point of intersection between regions is that they all share the atmosphere as a global commons and hence all pay a climate-change cost as a result of global fossil-fuel emissions. Even so, climate-change impacts and hence the nature of this cost are different among regions.

Third, the existence of benefits as well as costs is of great significance. Here are two examples: (1) a switch to clean fuels or renewables is likely to have benefits for regional air quality, and (2) more efficient transport systems in cities usually confer net social and urban-environment benefits. Such benefits in the non-greenhouse aspects of the overall utility are crucial in adding to the likelihood that real greenhouse mitigation will occur through changes in energy use.

Fourth, there are synergisms between different constraints (or different components of the overall utility in equation (4)). For example, if the technology for a massive switch to biofuels were available at reasonable cost, consequences would include declines in the availability of land for agriculture, biodiversity, and carbon stocks in forest ecosystems. This point is expanded later.

Finally, the uptake of mitigation options is constrained by technological and institutional inertia or contingent history: for example, it is not usually practical to change technologies at a rate faster than the turnover time of the infrastructure (see Caldeira et al., Chapter 5, this volume).

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