General setup and limitations of a model

Models of energy-economic-environmental (E3) interactions provide a disciplined way in which long-term, global implications of a range of possible stories of the future might be evolved and examined. Rather than attempting to generate predictions of the future, these stories or scenarios are generated using relatively simple, transparent, and surprise-free deterministic models and assumptions to provide a future view that can be understood in terms of a relatively small set of input assumptions. In the present context of nuclear power and its potential for mitigating greenhouse-gas (GHG) emissions, the connectivities between the following elements must be understood:

• Energy (nuclear, fossil, and renewable) costs;

• Risks [e.g., global climate change (GCC) from use of fossil fuel or proliferation risk associated with nuclear energy, land use associated with some forms of renewable energies];

• Specific energy and support technologies adopted or evolved for each of these energy options;

• The desire and/or cost of diversity of energy supply;

• General global economic impacts (e.g.,per-capita GNP as impacted by the cost of energy); and

• The long-term impacts of non-price-driven improvements in the energy costs of generating a given amount of GDP [anticipated decreases in primary-energy demand, PE(GJ/yr), per unit of GDP, or energy intensity, PE/GDP (MJ/$)].

These elements are of prime interest to those making energy decisions today for periods that extend far into the millennium. Global, long-term E3 models, no matter how simplifying, are useful in developing an appreciation for these kinds of connectivities and the potential long-term impact of choices made or not made today.

Figure 7.26 depicts a simple input-output global E3 model used in a recent IAEA-sponsored study of implications of a range of possible futures for nuclear energy (Krakowski, 1999; Bennett and Zaleski, 2000). This model was adopted from a established "top-down" (macroeconomic) global E3 model (Edmonds and Reilly, 1985) to examine specifically the impacts of energy-generation costs (capital and fuel-cycle costs for nuclear energy, fuel cost for fossil energy vis a vis carbon taxes), GHG-mitigation potential and proliferation risk for nuclear energy, and broader economic issues (e.g.,per-capita GDP) related to energy costs. The scenario attributes listed under 'Input' in Fig. 7.26 generally determine the long-term outcomes (energy mixes, GHG emissions and atmospheric accumulations, per-capita GNP growths, accumulations of radioactive and other nuclear materials, etc.). Under a set of assumptions for (regional) population growths (Bos et al., 1995; DESA/UN, 1988; Lutz, 1996), economic productivity growths (Nakicenovic, 1995), energy resources (amounts versus cost and grade, and environmental impacts related thereto) (OECD, 1996; Rogner, 1997) and energy-generation costs (OECD, 1998a), and (particularly in the case of nuclear energy) the nature of the overall fuel cycle [e.g., once-through LWRs, MOX-recycle in LWRs, breeder reactors of given kinds, use of fast spectrum burners (FSBs) to reduce actinide and LLFP burdens on waste disposal] generally define a given view of the future attempted to be captured by a given scenario.

Typically, most-probable/credible projections for these "upper-level" scenario attributes listed on Fig. 7.26 are used to define a "point-of-departure" or "business-as-usual" (BAU) case against which other scenarios are compared. For example, in the recent IAEA E3 Consultancy Study (IAEA, 1999; Krakowski, 1999) this BAU basis scenario invokes two nuclear-energy (sub)scenarios:

INPUT

MODEL

OUTPUT

LU LU OC t

Stfih

INPUT

Limitations Reilly Model
REGIONAL RESOURCE CONSTRAINTS • Technology (Extraction) 1 Environment ■ Backstop Technologies

REGIONAL SUPPLY

REGIONAL

(FOSSIL)

PRICES

PRICES

DEMANDS

REGIONAL SUPPLY

NUCLEAR ENERGY MODEL

• Material Flows

• Proliferation

• Int'l Constraints

NUCLEAR ENERGY MODEL

• Material Flows

• Proliferation

• Int'l Constraints

MARKET PENETRATION OF ADVANCED TECHNOLOGIES

ECONOMIC WELFARE

ENERGY MIX AND INTENSITY

EMISSIONS AND ACCUMULATIONS

NUCLEAR MATERIAL INVENTORIES AND FLOWS

• Reprocessing

• Fuel Fabrication

PROLIFERATION

RISK

Figure 7.26 Structural layout of ERB global E3 model (Krakowski, 1999; Edmonds and Reilly, 1985) as adapted and modified for analysis support of Los Alamos Nuclear Vision Project (Arthur and Wagner, 1996); four main components comprise the ERB recursive economic-equilibrium model: energy demand; energy supply; energy balance; and greenhouse gas (GHG) emissions. Relationships between inputs and iterated (to common world fossil-fuel prices) outputs, as well as the addition of a higher-fidelity nuclear-energy model (e.g., resources, costs, nuclear-material flows, inventories, and proliferation risk) are also shown.

• A basic options (BO) scenario characteristic by nominal unit total cost (UTC ~ 2-2.4 $/We); and

• A case where nuclear energy was phased out (PO) through the imposition of very high capital costs, UTC.

An ecologically driven (ED) scenario was also considered, wherein a carbon tax was imposed on fossil fuels at a rate CTAX($/tonneC/15yr); the ED scenario also considered the two BO and PO (sub)scenarios for nuclear energy. The scenario approach adopted for the IAEA E3 Consultancy Study, both in scope and assumption, follows that reported in Nakicenovic (1995). The following section summarizes selected ERB results from this IAEA study dealing with the potential impact of nuclear energy on GHG emissions, RCO2 (GtonneC/yr), accumulations, IF(GtonneC), and the resultant potential for atmospheric heating (Hasselmann et al., 1995), AT(K), as UTC (BO ^ PO) and CTAX (BAU ^ ED) are varied.

While tracking the parametric trade-offs occurring between these variables, the accumulation of plutonium in four forms (reactor, once-exposed spent fuel, multiply recycled spent fuel, and separated plutonium in both reprocessing and fuel-fabrication plants) is followed as a function of time for a thirteen-region model of the globe. Using a multi-attribute utility analysis, these inventories are related through a relative (0,1) proliferation risk index (PRI) (Krakowski, 1996), against which the AT(K) measure of GCC potential can be compared. Both PRI and AT are metrics that remain to be formulated in terms of a common and absolute damage function. This formulation is particularly difficult for proliferation in that PRI attempts to capture proliferation risks associated only with the civil nuclear fuel cycle, which is generally considered to present an unattractive source of nuclear-explosive material to a would-be proliferator compared to other sources [e.g., use of undeclared (not under international safeguards) facilities, particularly uranium-enrichment plants, or direct acquisition of smuggled nuclear-weapons components and materials]. In all instances, only the MOX/LWR (/MOX = 0.3 MOX core fraction) fuel cycle was considered, although results from the OT/LWR fuel cycle are also reported.

7.5.2 Sample results: basis scenario (BAUIBO) demands and consequences

We report here the degree to which changes in the capital cost of nuclear energy, UTC($/We), and the fuel cost of fossil energy, through a carbon tax, UCTX($/tonneC), imposed at a rate CTAX($/tonneC/15yr), impacts nuclear-energy demand, carbon-dioxide emissions, nuclear material accumulations, and GDP growth rates; these impacts are inter-connected through the modified

1000

Was this article helpful?

0 0
Solar Power

Solar Power

Start Saving On Your Electricity Bills Using The Power of the Sun And Other Natural Resources!

Get My Free Ebook


Post a comment