Reproduced with permission, from: Edmonds, J.A., M.A. Wise, and C.N.
MacCracken. 1994. Advanced Energy Technologies and Climate Change: An
Analysis Using the Global Change Assess ment Model (GCAM). Pacific
Northwest Laboratory, Richland, Washington.
Energy demand for each of the six major fuel types is developed for each of the nine regions. Five major exogenous inputs determine energy demand: population; labor productivity; exogenous energy end-use intensity; energy prices; and energy taxes, subsidi es, and tariffs.
The model calculates base GNP directly as a product of labor force and labor productivity. An estimate of base GNP for each region is used both as a proxy for the overall level of economic activity and as an index of income. The base GNP is, in turn, modi fied within the model to be consistent with energy-economy interactions. The GNP feedback elasticity is regional, allowing the model to distinguish energy supply dominant regions, such as the Mideast, where energy prices and GNP are positively related, fr om the rest of the world where the relationship is inverse.
The exogenous end-use energy-intensity improvement parameter is a time-dependent index of energy productivity. It measures the annual rate of growth of energy productivity that would continue independent of such other factors as energy prices and real inc ome changes. In the past, technological progress and other non-price factors have had an important influence on energy use in the manufacturing sector of advanced economies. Including an exogenous end-use energy-intensity improvement parameter allows scen arios to be developed that incorporate either continued improvements or technological stagnation assumptions as an integral part of these scenarios.
The final major energy factor influencing demand is energy prices. Each region has a unique set of energy prices derived from world prices (determined in the energy balance component of the model) and region-specific taxes and tariffs. The model can be mo dified to accommodate nontrading regions for any fuel or set of fuels. The model assumes that regions do not trade solar, nuclear, or hydroelectric power, but all regions trade fossil fuels.
The energy-demand module performs two functions: it establishes the demand of energy, and its services, and it maintains a set of energy flow accounts for each region. Oil and gas are transformed into secondary liquids and gases that are used either dire ctly in end-use sectors or indirectly as electricity. Hydro, nuclear, and solar electric or fusion are accounted for directly as electricity. Nonelectric solar energy is included with conservation technologies as a reduction in the demand for marketed fue ls.
The four secondary fuels are consumed to produce energy services. In each region of the model, energy is consumed by three end-use sectors: residential/commercial, industrial, and transportation.
The demand for energy services in each region's end-use sectors is determined by the cost of providing these services and by the levels of income and population. The mix of secondary fuels used to provide these services is determined by the relative costs of providing these services using each alternative fuel. The demand of fuels to provide electric power is then determined by the relative costs of production, as is the share of oil and gas transformed from coal and biomass.
Energy supply is disaggregated into two categories, renewable and non-renewable. Energy supply from all fossil fuels is related directly to the resource base by grade, the cost of production (both technical and environmental) and to the historical produc tion capacity. The introduction of a graded resource base for fossil fuel (and nuclear) supply allows the model to explicitly test the importance of fossil fuel resource constraints as well as to represent fuels such as shale oil, in which only small amou nts are likely available at low costs but for which large amounts are potentially available at high cost.
Note here that nuclear is treated in the same category as fossil fuels. Nuclear power is constrained by a resource base as long as light-water reactors are the dominant producers of power. Breeder reactors, by producing more fuel than they consume, are mo deled as an essentially unlimited source of fuel that is available at higher cost.
A rate of technological change is also introduced on the supply side. This rate varies by fuel and is expected to be both higher and less certain for emerging technologies.
The supply and demand modules each generate energy supply and demand estimates based on exogenous input assumptions and energy prices. If energy supply and demand match when summed across all trading regions in each group for each fuel, then the global en ergy system balances. Such a result is unlikely at an arbitrary set of energy prices. The energy balance component of the model is a set of rules for choosing energy prices which, on successive attempts, bring supply and demand nearer a system-wide balanc e. Successive energy price vectors are chosen until energy markets balance within a prespecifed bound.
Given the solution of the energy balance component of the model, greenhouse gas emissions for CO2, CH4, and N2O are calculated by applying emissions coefficients. Emissions coefficients for CO2 are as follows:
* liquids 19.2 TgC/EJModern biomass is treated as if its carbon absorption occurred in the year of release. This approximation can either underestimate or overestimate actual net annual fluxes depending upon whether the underlying stock of biomass is either expanding or contr acting. (See Edmonds and Barns 1990).
* gases 13.7 TgC/EJ
* solids 23.8 TgC/EJ
* carbonate rock mining 27.9 TgC/EJ
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