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Press release (dated 20 September 2006)

Chapter 3: Synthesis Assessment of Long-Term Climate Change Technology Scenarios

The synthesis assessment of global climate-change technology scenarios examined analyses based on a variety of models and tools. Courtesy: DOE/PNNL

Such assessments are complex and must consider many uncertainties, and hence they must include a range of assumptions about the future. Specifically, a technology strategy aimed at influencing global GHG emissions over the course of the 21st century would need to consider population change, varying rates of regional economic development, differing regional technological needs and interests, and availability of natural resources. In addition, the long-term costs of GHG emission reductions will depend in part on future technological innovations, many of which are unknown, and on other factors that could either promote or discourage the use of various technologies in the future. Finally, the uncertainties inherent in climate science and the fact that value judgments are involved make it difficult to determine a level at which atmospheric GHG concentrations in the Earth's atmosphere would meet the stabilization objective of the United Nations Framework Convention on Climate Change noted in Chapter 1.

Scenario analysis using various types of models is one valuable tool that can be used to assist in planning under uncertainty. Scenarios can present alternative views about the rate of future GHG emissions growth to help gauge the scope of the potential challenge by methodically and consistently accounting for the complex interactions among economic and demographic factors, energy supply and demand, the advance of technology, and GHG emissions. Scenarios can also investigate various proposed pathways toward achieving different levels of GHG emissions reductions. The results can provide relative indications of the potential emissions reductions and economic benefits of particular classes of technology under a range of different assumptions, and a better understanding of the factors and constraints that might affect their market penetration.

Many research organizations, university-based teams, government agencies, and other groups have engaged in scenario analyses to explore these topics. This chapter reviews and synthesizes the results of such efforts to gain insights, under a range of uncertainties, about the scale of the technological challenge, the potential contributions of various advanced technologies to GHG emissions reductions or avoidances, the timing of technology deployment, and associated economic benefits. These insights will be used to guide CCTP in developing an effective climate change technology strategy and associated portfolio of technology R&D.

3.1 The Greenhouse Gases

As a GHG resulting from human activities, methane's contribution is second only to CO₂. Methane, on a kilogram-for-kilogram basis, is 23 times more effective than CO₂ at trapping radiation in the atmosphere over a 100-year time period (although it has a shorter lifetime in the atmosphere). Methane is emitted from various energy-related activities (e.g., natural gas, oil and coal exploration, and coal mining), as well as from agricultural sources (e.g., emissions from cattle digestion and rice cultivation; and waste disposal facilities, landfills, and wastewater treatment plants). Methane emissions have declined in the United States since the 1990s, due to voluntary programs to reduce emissions and regulation requiring the largest landfills to collect and combust their landfill gas. [4]

Another important gas is nitrous oxide (N₂O), which is emitted primarily by the agricultural sector through direct emissions from agricultural soils and indirect emissions from nitrogen fertilizers used in agriculture, as well as from fossil fuel combustion, especially from fuel used in motor vehicles; adipic (nylon) and nitric acid production; wastewater treatment and waste combustion; and biomass burning (EPA 2005).

Global Emissions of GHGs in 2000 (percentage of total GtC-eq. using GWPs

Figure 3-1 Global Emissions of GHGs in 2000 (percentage of total GtC-eq. using GWPs) (Sources)

Other non-CO₂ GHGs, including certain fluorine-containing halogenated substances such as sulfur hexafluoride (SF₆), hydrofluorocarbons (HFCs), and perfluorocarbons (PFCs), often collectively called the "F-gases," are used or produced by a variety of industrial processes. In most cases, emissions of these F-gases were relatively low in 1990 but have since grown rapidly. The sources of these non-CO₂ GHG emissions are discussed in more detail in Chapter 7.

The radiation-trapping capacities of GHGs vary considerably. GHGs also have different lifetimes in the atmosphere. In addition, some anthropogenic emissions (such as aerosols) can have cooling effects. Combining these effects, the Intergovernmental Panel on Climate Change (IPCC) estimated the key anthropogenic and natural factors causing changes in warming and cooling from year 1750 to year 2000, [5] as shown in Figure 3-2. The figure shows warming and cooling in terms of radiative forcing�the change in the balance of infrared radiation coming into and going out of the atmosphere. Positive radiative forcing leads to warming, and negative radiative forcing leads to cooling.

The differences in the characteristics of GHGs and other radiatively important substances, as well as the potential differences in rates of the growth of their emissions over time, influence the formulation of strategies to stabilize overall GHG concentrations through emissions mitigation. In addition to the climate implications of increasing atmospheric CO₂, there are also concerns about chemical and biological impacts to the ocean. As discussed in Chapter 6, an increase in ocean CO₂ concentrations and the potential effect on ocean chemistry and biology provide additional motivation, apart from climate change and considerations of global temperature, to mitigate emissions and stabilize atmospheric CO₂ concentrations.

3.2 Factors Affecting Future GHG Emissions

Global Mean Radiative Forcing of the Climate System for the Year 2000, Relative to 1750

Figure 3-2 Global Mean Radiative Forcing of the Climate System for the Year 2000, Relative to 1750 (Source: IPCC 6)

CO₂ Emissions from Energy Consumption

Primary Energy Use Projections Using Various Energy-Economic Models and Assumptions

Figure 3-3 Primary Energy Use Projections Using Various Energy-Economic Models and Assumptions
Note: The mean, median, and percentile bands in the figure are based on the range of projections and do not represent probabilities of the projections. (Source: IPCC 2000)

Estimates of projected energy demand vary considerably. The Energy Information Administration (EIA 2005) projects world primary energy demand will increase from about 411.5 exajoules (EJ) in 2002 to 680 EJ in 2025. Most of that increase will come in demand from developing countries. EIA forecasts primary energy use in the developed world will rise just 1.1 percent annually while that in the developing world will rise 3.2 percent annually. Energy use in the emerging economies of developing Asia, driven largely by demand in China and India, is projected to more than double over the course of the quarter century.

In the IPCC's Special Report on Emissions Scenarios (SRES) (IPCC 2000), projected world primary energy use in 2100 fell within a range of 600 to 2800 EJ for 90 percent of the scenarios explored (Figure 3-3). Among the scenarios surveyed in SRES, the average annual growth rates for global energy demand over the period from 2000 to 2100 ranged from 2.4 percent per year to -0.1percent per year, with a median value of 1.3 percent per year. [10]

As about four-fifths of GHG emissions are energy related, energy generation and consumption are key determinants of CO₂ emissions. The scenarios with the highest CO₂ emissions are those that assume the highest energy demand along with the highest proportion of fossil fuel use unaccompanied by CO₂ capture and storage. Since 1900, global primary energy consumption has, on average, increased at more than two percent per year, similar to the 20-year trend from 1975 to 1995.

CO₂ Emissions Projections from Energy Use Using Various Energy-Economic Models and Assumptions

Figure 3-4 CO₂ Emissions Projections from Energy Use Using Various Energy-Economic Models and Assumptions Note: The mean, median, and percentile bands in the figure are based on the range of projections, and do not represent probabilities of the projections. (Source: IPCC 2000)

Without constraints, energy-related CO₂ emissions are expected to increase significantly over the next 100 years at rates similar to those for the growth in energy consumption. Specific projections vary depending on assumptions. According to EIA (2005), annual global CO₂ emissions may increase by about 60 percent between 2002 and 2025. Higher growth rates are expected in the developing regions of the world, where CO₂ emissions may increase by a factor of two or more by 2025.

In 2025, global use of petroleum products, primarily in the transportation sector, is expected to continue to account for the largest share of global emissions of CO₂. This is followed in importance by the use of coal, primarily for electricity generation, and natural gas. Natural gas is a versatile fuel, used for power generation, residential and commercial fuel, and many other uses. CO₂ emissions from fossil fuel combustion by end-use sector for 2002 can be broken down as follows: transportation, 24 percent; electricity and heat, 35 percent; and industrial and other end uses, 41 percent.

IPCC's SRES examined projections of CO₂ emissions from energy use based on multiple reference scenarios from six long-term modeling efforts. It found that different assumptions about the driving forces led to widely divergent emissions trajectories (Figure 3-4). Ninety percent of the CO₂ emissions projections fall within the upper and lower bounds shown in Figure 3-4. The mean, median, and percentage bands shown were calculated based on the range of projections across the full set of scenarios and do not represent probabilities associated with the projections.

The upper bounds in Figures 3-3 and 3-4 are formed by scenario results that assume very high world economic growth, high per-capita energy use, and continued dominance of fossil fuels. At this upper bound, world CO₂ emissions from energy use are projected to grow from about [6] GtC/year in 2000 to more than 30 GtC/year in 2100�a five-fold increase.

The lower bounds in Figures 3-3 and 3-4 are formed by scenarios that assume less population growth, changes in the composition of economic activity away from energy-intensive output, lower per-capita energy use, more energy efficiency, and considerably more use of carbon-neutral fuels, compared to the upper bound. At this lower bound, CO₂ emissions are projected to grow for the first half the century, but then to decline to levels about equal to those in 2000, representing no net growth by 2100. Assumptions for the various scenarios are described in Box 3-1. [11] The models used in this study include AIM, [12] ASF, [13] IMAGE, [14] MARIA, [15] MESSAGE, [16] and MiniCAM. [17]

Recent studies have explored the uncertainty in future emissions using a probabilistic approach (see for example, Webster et al. 2002). [18] While there are some differences in the upper and lower bounds of the emissions projections between the SRES scenarios and these more recent probabilistic-based analyses, the range of the SRES scenarios overlaps to a large degree with the range of emissions estimated using these probabilistic approaches.

Box 3-1 The SRES Scenarios The SRES scenarios are organized around four major storylines, which received the names A1, A2, B1, and B2. Each of these storylines represented different general conceptions of how the world might evolve over time, including the evolution of key drivers such as economic growth (including differences or convergence in regional economic activity), population growth, and technological change. Each driver was interpreted by the participating modeling teams in terms of quantitative assumptions about the evolution of specific model parameters. Some scenario drivers, such as economic growth, final energy, and population growth, were harmonized across many of the models, while others, such as the specific technology assumptions, were developed by the individual modeling teams to be generally consistent with the storylines. For the A1 Scenario, four basic assumptions about technology were also developed, so there are four categories of technology scenarios under the A1. The scenarios are described as follows: A1. The A1 storyline and scenario family describe a future world of very rapid economic growth, global population that peaks in mid-century and declines thereafter, and the rapid introduction of new and more efficient technologies. Major underlying themes are convergence among regions, capacity building, and increased cultural and social interactions, with a substantial reduction in regional differences in per capita income. The A1 scenario family develops into three groups that describe alternative directions of technological change in the energy system. The four A1 groups are distinguished by their technological emphasis: fossil intensive (A1C � coal- and A1G � gas), non-fossil energy sources (A1T), or a balance across all sources (A1B), where balanced is defined as not relying too heavily on one particular energy source, on the assumption that similar improvement rates apply to all energy supply and end-use technologies. A2. The A2 storyline and scenario family describe a very heterogeneous world. The underlying theme is self-reliance and preservation of local identities. Fertility patterns across regions converge very slowly, which results in a continuously increasing population. Economic development is primarily regionally oriented, and per capita economic growth and technological change more fragmented and slower than in other storylines. B1. The B1 storyline and scenario family describe a convergent world with the same global population, which peaks in mid-century and declines thereafter, as in the A1 storyline, but with rapid change in economic structures toward a service and information economy, with reductions in material intensity and the introduction of clean and resource-efficient technologies. The emphasis is on global solutions to economic, social, and environmental sustainability, including improved equity, but without additional climate initiatives. B2. The B2 storyline and scenario family describe a world in which the emphasis is on local solutions to economic, social, and environmental sustainability. It is a world with continuously increasing global population, at a rate lower than in A2, intermediate levels of economic development, and less rapid and more diverse technological change than in the B1 and A1 storylines. While the scenario is also oriented towards environmental protection and social equity, it focuses on local and regional levels. The set of harmonized drivers depended both on the scenario and the specific model. Key drivers that characterized the scenarios are summarized qualitatively in the table below. All scenarios assume energy intensity reductions over the coming century at or greater than the historical average over the past few decades. Comparison of the emissions trajectories in Figures 3-5 and 3-6 can be interpreted in terms of the relative evolution of these drivers and the discussion of these drivers above. DRIVER A1C A1G A1B A1T A2 B1 B2 Population Growth low low low low high low med GDP Growth very high very high very high very high med high med Energy Use very high very high very high high high low med Energy Intensity Improvement high high high high low very high med Land-use Changes low-med low-med low low med-high high med Availability of Conventional Oil & Gas high high med med low low med Pace of Technological Change rapid rapid rapid rapid slow med med

Net CO₂ Emissions from Land-Use Change

Figure 3-5 Net CO₂ Emissions from Land-Use Change Note: The mean, median and percentile bands in the figure are based on the range of projections, and do not represent probabilities. (Source: IPCC 2000)

CO₂ Emissions and Sequestration from Changes in Land Use

The role of land-use change has received relatively limited consideration (compared to energy use) in prior modeling exercises aimed at developing long-run GHG emissions scenarios. To date, the most comprehensive treatment is contained in the scenarios developed for the IPCC SRES (IPCC 2000). In developing these scenarios, the IPCC assembled a data base of over 400 earlier emissions scenarios. Of these, 26 scenarios (all the work of three modeling groups) explicitly considered the role of land-use change on global CO₂ emissions. The projections vary considerably in the near term, with some scenarios showing increasing and some decreasing net global CO₂ emissions from land-use change (Figure 3-5). A key insight to emerge from the IPCC exercise was that the link between land-use change and global CO₂ emissions is more complex and uncertain than had been reflected in previous analyses.

Across and within the four storylines described in Box 3.1, the scenarios produced a wide range of land-use paths that included large increases and decreases in the global areas of cropland, grassland, and forest over the course of the century. Differences in land-use patterns resulted primarily from alternative assumptions about population and income growth. Hence, the scenarios indicate that land-use change could become either an important source or sink of global CO₂ emissions over the next 100 years, depending on the mix of goods and services the world's population demands from its land resources.

Further, future paths of technological change in today's land-intensive sectors�including agriculture, forestry, energy, construction, and environment quality�will help to define the contribution land-use change makes to net CO₂ emissions. Many of the IPCC scenarios show that CO₂ emissions from deforestation are likely to peak after several decades and then subsequently decline.20 Despite the differences among the scenarios' assumptions, most of the scenarios show a net decrease to below current levels by the end of the century.

Sohngen and Mendelsohn (2003) linked a global forestry model with the global optimization model DICE to more explicitly explore the relationships between forestry management, land-use emissions, and global energy systems. They reported a net sequestration potential ranging from 32 to 102 GtC in the coming century, depending on carbon prices. Much of the sequestration occurs through avoided deforestation.

Other Greenhouse Gases

Integrated assessment models have only recently begun to project long-term trends in non-CO₂ GHGs. In a recent international modeling exercise conducted by the Stanford Energy Modeling Forum (EMF-21), non-CO₂ emissions and mitigation potential were projected by 18 models of various forms (Weyant and de la Chesnaye 2005). [21] Each model ran a "reference case" scenario, in which non-CO₂ GHGs were allowed to grow in the absence of any constraints or incentives for GHG emissions mitigation.

The results for methane and N₂O are shown in Figures 3-6 and 3-7, respectively. The projections vary considerably among models. On average, emissions of non-CO₂ GHGs were projected to increase from 2.7 gigatons of carbon equivalent emissions (GtC-eq.) in 2000 to 5.1 GtC-eq. in 2100. On average, methane emissions were projected to increase by 0.6 percent/year between 2000 and 2100; nitrous oxide by 0.4 percent/year; and the fluorinated gases by 1.9 percent/year. (By comparison, in these same scenarios, CO₂ emissions were projected to grow by 1.1 percent/year over the same time period.)

A recent modeling study conducted for CCTP projected the contributions of CO₂ and other GHGs to future radiative forcing (Clarke et al. 2006). In the reference case scenario (without actions specifically targeted toward lowering GHGs), radiative forcing from pre-industrial levels was projected to increase to 6.5 watts per square meter (W/m2), compared to a level of about 2 W/m2 in 2000 (Figure 3-8). In this projection, CO₂ contributed approximately 80 percent of the radiative forcing in 2100, with other GHGs (CH₄, N₂O, and the F-gases) contributing about 20 percent.

Some other models show larger contributions from non-CO₂ GHGs. The analysis for CCTP (which used MiniCAM) projects a considerable amount of control of methane in the absence of mandated controls. [22] In results from other models, radiative forcing was projected to increase to over 9 W/m2, due in part to growth in non-CO₂ GHG emissions (van Vuuren et al. 2006). These studies indicate the importance of non-CO₂ GHGs, especially in the future, as their emissions rise as a result of increased industrial and agricultural activity and population growth.

Analytical Context for CCTP Planning

Figure 3-6 Methane Emissions Projections from the EMF-21 Study, With No Explicit Initiatives to Reduce GHG Emissions

Figure 3-7 Nitrous Oxide Emissions Projections from the EMF-21 Study, With No Explicit Initiatives to Reduce GHG Emissions

Figure 3-8 Radiative Forcing in a Reference Case Scenario (Source: Clarke et al. 2006)

Cost-effective means to stabilize radiative forcing would include reductions in emissions of both CO₂ and other GHGs. A recent analysis by Pacific Northwest National Laboratory (PNNL) examined various GHG emissions reduction options associated with a range of radiative forcing levels in the year 2100, each leading to long-run stabilization of radiative forcing (Clarke et al. 20006). The results are presented in Figure 3-9, which compares the estimated radiative forcing in 2000 to projected radiative forcing in 2100 under an unconstrained emissions scenario (Reference Case) and four emissions-constrained scenarios that lead to lower radiative forcing in 2100.

Other studies also examined integrated multi-gas strategies for reducing radiative forcing, considering possible tradeoffs among CO₂ and other GHG emissions. For example, using results from a variety of different models, an analysis by Weyant and de la Chesnaye (2005) showed that a multi-gas approach results, on average, in CH₄ emissions reductions of almost 50 percent, N₂O reductions of about 40 percent, and a reduction in F-gases of almost 75 percent (on a GtC-eq. basis) by 2100, compared to reference case levels.

Figure 3-9 Radiative Forcing Levels under Different Degrees of Constraint (Source: Clarke et al. 2006)

For any assumed constrained radiative forcing scenario, reductions in the non-CO₂ gases lead to the need for smaller reductions in CO₂ emissions. Nevertheless, CO₂ remains by far the most important GHG. Accordingly, a range of potential CO₂ stabilization levels have been explored, using different models and assumptions. Figure 3-10 shows one set of relationships between CO₂ emissions and CO₂ concentrations over time, across a range of CO₂ stabilization levels commonly found among the literature on scenarios. [23]

The set of hypothetical CO₂ emissions scenarios (Figure 3.10-A), shown here across a range of five corresponding CO₂ concentration stabilization levels (Figure 3.10-B), illustrates a general pattern found consistently across the analyses. Emissions scenarios leading to CO₂ stabilization typically show growth of emissions in the near term, but with that growth slowing; the emissions eventually peak and then gradually decline; and ultimately they approach levels that are low or near zero. In almost all stabilization scenarios, emissions must continue to decline beyond 2100 and into the 22nd century and beyond. Over the same time period, as discussed earlier, the world's energy needs can be expected to continue to grow.

An illustration of the scale of the overall emissions reductions needed to achieve stabilization of CO₂ concentrations is shown in Figure 3-11. To meet the CO₂ stabilization level in this hypothetical example, by 2100 annual CO₂ emissions would need to be reduced by almost 15 GtC-eq/year below the level in an otherwise "unconstrained" emissions scenario case. [24] For the example shown, the cumulative emissions reduction would be approximately 600 GtC-eq over the course of the 21st century. For other scenarios (PNNL), the 100-year cumulative CO₂ emissions reductions ranged from about 300 to about 1,000 GtC-eq. [25]

Figure 3-10 Illustrative CO₂ Emissions Profiles and Corresponding Concentrations

Box 3-2 provides illustrations of technological measures that could achieve an annual reduction of one GtC-eq./yr. As these illustrations suggest, GHG-reducing technologies would need to be implemented on a significant scale. The costs of achieving such reductions using today's technology options could be high. Developing and deploying advanced technology with significantly improved performance and cost characteristics could substantially lower these costs, thereby facilitating their entry into the marketplace or their expanded adoption. The implication for CCTP and its associated science and technology R&D programs is that advanced technologies, including novel or breakthrough technologies, are important, if not essential, to the CCTP goals of significantly reducing or avoiding GHG emissions, while maintaining economic growth and ensuring safety and overall environmental quality.

Figure 3-11 Potential Scale of CO₂ Emissions Reductions to Stabilize GHG Concentrations: Hypothetical Unconstrained and Constrained Emissions Scenarios (Source: Clarke et al. 2006)

3.4 Exploring the Role for Advanced Technology

Estimating the potential contribution to CCTP strategic goals of any technology is difficult and depends in large part on assumptions about the success of scientific and technical advancements and other factors. These assumptions may be explored in scenario analyses featuring advanced technology. For example, several studies have projected that lower carbon fuels (e.g., natural gas) and lower GHG-intensity technologies (e.g., coal gasification) could bridge the transition to zero- or very low-carbon technologies. [26] Two other themes common among many GHG mitigation technology scenarios are steady improvement in energy efficiency (e.g., lowering of GHG-intensity) and the emergence of bio-based products as an important energy source throughout the 21st century.

In addition to technological considerations, cost considerations are major elements in the mitigation scenarios. When projected declines in the costs of low-carbon-emitting technologies make them attractive economically, they play major roles in many scenarios. Different technologies may mature and become cost-competitive at different times over the course of a 100-year planning horizon. For example, increased energy efficiency (using today's technologies), mitigation of non-CO₂ GHGs such as methane, and terrestrial sequestration may be cost-effective options in the near term. Transformative supply-side and end-use technologies with greatly reduced GHG emissions profiles could become more cost-effective later, as these technologies advance.

Several landmark multi-model studies, [27] as well as various scenario analysis efforts based on individual models, have explored a range of emission reduction scenarios. In most of these analyses, advanced technology scenarios are modeled under a range of hypothetical GHG emissions constraints (e.g., low, medium, high, and very high). These advanced technology scenarios, in turn, can be compared against baseline scenarios, where the given GHG emissions constraints are met, but with less optimistic assumptions about the advancement of technology. The results can suggest what roles various technologies may play, if assumptions about their advancement could be realized. The results can also, by inference, provide insights about various R&D programmatic goals, suggesting what technological progress would be needed, and by when, in order to achieve the hypothesized results.

Box 3-2 How Big is One Gigaton Per Year of GHG Reduction? Actions that provide 1 gigaton per year of carbon-equivalent mitigation for the duration of their existence: Coal-Fired Power Plants. Build 1,000 "zero-emission" 500-MW coal-fired power plants to supplant coal-fired power plants without CO2 capture and storage. (Current global installed generating capacity is about 2 million MW.) Geologic Storage. Install 3,700 carbon storage sites like Norway's Sleipner project (0.27 MtC/year). Nuclear. Build 500 new nuclear power plants, each 1 GW in size, to supplant an equal capacity of coal-fired power plants without CO2 capture and storage. This would more than double the current number of nuclear plants worldwide. Electricity from Landfill Gas Projects. Install 7,874 "typical" landfill gas electricity projects (typical size being 3 MW projects at non-regulated landfills) that collect landfill methane emissions and use them as fuel for electric generation. Efficiency. Deploy 1 billion new cars at 40 miles per gallon (mpg), instead of new cars at 20 mpg. Wind Energy. Install 650,000 wind turbines (1.5 MW each, operating at 0.45 capacity factor) to supplant coal-fired power plants without CO2 capture and storage. Solar Photovoltaics. Install 6 million acres of solar photovoltaics to supplant coal-fired power plants without CO2 capture and storage (assuming 10% cell DC efficiency, 1700 kWhr/m2 solar radiance, and 90% DC-AC conversion efficiency). Biomass Fuels from Plantations. Convert a barren area about 15 times the size of Iowa's farmland (about 33 million acres) to biomass crop production. CO2 Storage in New Forest. Convert a barren area about 40 times the size of Iowa's farmland to new forest. Note: SRES (IPCC 2000) scenarios assume that all of these technologies will be used extensively prior to 2100.

Reference Case, Baseline, and Advanced Technology Scenarios

Other analytical approaches address important underlying factors that may influence a technology's ability, within a larger competitive context, to achieve its technical potential. In this context, advanced technologies would need to meet an array of conditions before they could be successfully adopted. They would need to be cost-competitive, in the context of the future global economy and the world energy market, compared to other available technologies. Other considerations include ease of use, reliability, public safety, and acceptance; and still others include policy, environmental, or regulatory factors. Taking these considerations into account requires an integrated assessment approach using models, which typically require competition among technologies to meet certain exogenously imposed emissions constraints, in conjunction with other emissions-related factors and considerations.

Such models simulate, for each step in time, the competitive deployment of technologies and approaches that would be needed to achieve a given amount of emissions reductions at the lowest cost in that time period. Depending on the level of emissions constraint assumed, low- or no-cost approaches may supply a large portion of the emissions reduction. [28] More costly advanced technologies may be adopted more widely in scenarios that require moderate to high levels of emissions reduction. Expensive, undeveloped, or undemonstrated technologies, or technologies that face difficult challenges to wide-scale deployment, may enter the market later in the mitigation period. Hence, the mix of technologies in any given scenario depends on assumptions about technical readiness, costs, and barriers to adoption for each technology, as well as the level of emissions constraint assumed.

In a recent model-based integrated assessment, sponsored by CCTP and conducted by PNNL, a set of 17 scenarios was developed to explore and compare advanced technology options for achieving significant GHG emission reductions. The 17 scenarios include a Reference Case and four sets of GHG-emissions-constrained scenarios (each set has four different levels of emission constraint). One set of emissions-constrained scenarios (the Baseline Scenarios) assumes reference case technologies are available to meet the emissions constraints, and three sets of emissions-constrained scenarios assume advanced technologies become available. [29] The scenarios are summarized as follows:

• A Reference Case scenario represents a hypothetical technological future, where GHG emissions are not constrained, but where significant technical improvements are achieved in a broad spectrum of currently known or available technologies for supplying and using energy. [30] This scenario results in improvements in global GHG-intensity over time, but not in lower GHG emissions. It provides reference level energy and emissions projections to which the energy and emissions in the emissions-constrained scenarios can be compared.
• A set of four Baseline Scenarios use the same Reference Case technology assumptions described above but applies four hypothesized GHG emissions constraints. Because these scenarios require emission reductions from the Reference Case, low- or zero-emission technologies and other means to reduce GHG gases are deployed at higher rates in these baseline emission-constrained scenarios than in the Reference Case. These baseline scenarios provide energy and mitigation cost projections to which the energy mix and costs in the advanced technology scenarios can be compared.
• Each of the three advanced technology scenarios includes a distinct set of technology advancements, beyond those in the Reference Case. [31] Each of these, in turn, is also applied under the four GHG emissions constraints (for a total of twelve advanced technology cases). The advanced technology scenarios include:

  Scenario 1, which assumes successful development of carbon capture and storage technologies for use in electricity, as well as in applications such as hydrogen and cement production.

  Scenario 2, which assumes additional technological improvement and cost reduction for carbon-free energy sources, such as wind power, solar energy systems, and nuclear power. [32]

  Scenario 3, which assumes major advances in fusion energy and/or novel energy applications for solar energy and biotechnology such that they can provide zero-carbon energy at competitive costs in the second half of this century. [33]

A number of common features cut across all three of the advanced technology scenarios:

• Additional gains in energy efficiency beyond the reference case occur.
• Additional technologies for managing non-CO₂ GHGs become available.
• Terrestrial carbon sequestration increases.
• The full potential of conventional oil and gas is realized.
• Hydrogen production technology advances.

Figures 3-12 and 3-13 provide illustrative results across the three advanced technology scenarios for a high emissions constraint case. Figure 3-12 shows the mix of technologies and their associated contributions to total global energy demand for the three advanced energy scenarios. Figure 3-13 shows the CO₂ emissions reduction contributions from the various energy sources and technologies, under the same set of assumptions.

Although each scenario assumes advances in particular classes of technology, all scenarios result in a mix of energy efficiency and energy supply technologies. The overall results show the extent of the variation possible in the mix of emissions-reducing technologies under a variety of assumptions and planning uncertainties.

Economic Benefits of Advanced Technologies

In the PNNL analysis (Clarke et al. 2006), the estimated costs of achieving a range of emission reductions were compared for cases with and without the use of advanced technology. [34] The scenarios described above were supplemented by an additional scenario in which the advanced technologies in all three scenarios were combined in one model run. The resulting cost estimates (Figure 3-14) show that the cumulative cost for meeting the hypothetical carbon constraints is significantly lower in all three advanced technology scenarios than in the Baseline Scenarios that use reference case technology assumptions. Accumulated over the course of the 21st century, the potential economic benefits of an advanced technology strategy are likely to be significant, independent of which technologies eventually emerge as most successful. Furthermore, the cumulative cost for meeting the carbon constraints was even lower in the case in which all technology advances were combined, implying that benefits will be greatest if many types of advanced technologies achieve success.

Figure 3-12 World Primary Energy Demand for Three Advanced Technology Scenarios Under a High GHG-Emissions-Constraint Case Note: "Energy Use Reduction" is the amount of energy conserved or saved through advanced energy-efficient end-use technologies compared to a Reference Case, which also includes a considerable increase in energy efficiency compared to today's level. (Source: Clarke et al. 2006)

Numerous other studies reach similar conclusions. For example, Manne and Richels (2004) examined limiting global temperature rise using scenarios with "optimistic" technological assumptions. They assumed advanced technologies, such as fuel cells and integrated gasification combined cycle with CO₂ capture and storage, are available in the future. They compared these to more "pessimistic" scenarios without such advanced technologies. The costs [35] were estimated to be 2.5 times lower in the advanced technology cases than in the scenarios without advanced technologies. In another study, Edmonds et al. (2004) report that when a suite of advanced technologies (such as carbon capture and storage, biotechnology, and hydrogen energy systems) are available to be deployed at a large scale, the inferred added dollar value to GHG emissions that would be required to achieve the assumed reduction was 60 percent lower than when the advanced technologies were not available.

Figure 3-13 World Carbon Dioxide Emissions for Three Advanced Technology Scenarios Under a High GHG-Emissions-Constraint Case Note: "Energy Use Reduction" is the amount of energy conserved or saved through advanced energy-efficient end-use technologies compared to a Reference Case, which also includes a considerable increase in energy efficiency compared to today's level. (Source: Clarke et al. 2006)

The economic benefits of accelerated technical advances are also identified by a class of studies that explore the dynamics of technical change (e.g., Edenhofer et al. (2005), Manne and Richels (2004), van Vuuren et al. (2004), L�schel (2002), Gerlagh and van der Zwaan (2003) and Goulder and Mathai (2000)). These analyses model technical change through mechanisms such as "technology learning" or "learning by doing," where costs of technologies decline with experience as a function of investment in R&D or other mechanisms. The mechanisms are then used to examine the effects of the technological change on the costs of complying with various climate policy and emissions constraints.

Figure 3-14 Cost Reductions Associated with Advanced Technology Scenarios, Compared to a Baseline Case without Advanced Technologies (Source: Clarke et al. 2006)

Note: Cumulative released emissions (shown in the bar graphs) are highest and mitigated emissions are lowest when the emissions constraint is least stringent (Low Constraint). Costs (line graphs) are highest when the emissions constraint is most stringent (Very High Constraint). Costs are lower when advanced technology was assumed to be available (purple, red, green, and blue lines), than when technology was assumed to advance only incrementally (black line).

Although these studies vary in design, model platform, and methodology, a common conclusion can be drawn from all of them. That is, technological change can significantly reduce the costs of emissions reduction policies. In these studies, the costs were typically reduced by over 50 percent when technological change was introduced in a portfolio of mitigation options. One of the major conclusions drawn at the recent IPCC Expert Meeting on Emission Scenarios was that technological change can have a significant impact on reducing costs of GHG stabilization. [36]

In addition, the studies indicate that the benefits are greatest when technology advancement is pervasive. A study conducted using the MESSAGE model (Roehrl and Riahi 2000) concluded that mitigation costs are highest in scenarios with static technologies and lowest in scenarios where technology improvements span both supply and end-use sectors.

A multi-gas, rather than a CO₂-only, approach is another important dimension to lowering the costs of stabilizing radiative forcing from GHGs. Weyant and de la Chesnaye (2005) showed that using a multi-gas approach results in a cost reduction of 30 to 50 percent, compared to CO₂-only approaches.

Timing of Advanced Technology Market Penetration

As an illustration, in the PNNL scenario analysis under a "high" emissions constraint, advanced technologies for reducing emissions for energy end use and infrastructure begin achieving emissions reductions at a significant level (one GtC/year) between 2030 and 2040. Under a similar constraint, technologies effecting capture, storage, and sequestration of CO₂ begin making significant contributions (one GtC/year) around 2040 or later. Variations among these dates result from varying assumptions about technologies. A summary of the insights about timing, shown for each CCTP strategic goal, is presented in Table 3-1, across a wide range of hypothesized GHG emissions constraints. In general, the higher the emissions constraint, the sooner the advanced technologies are needed and deployed.

Table 3-1 Estimated Timing of the First GtC-eq./Year of Reduced or Avoided Emissions (Compared to the Reference Case) for Advanced Technology Scenarios (Source: Clarke et al. 2006)

The following chapters focus in depth on various technological means for making progress toward, and eventually achieving, each CCTP strategic goal. Guided in part by the insights gained through the review and synthesis of the scenario analyses, each chapter's discussion addresses the rationale and technology strategy that would guide investments in the current technology portfolio, explains potential R&D progress, and identifies candidate areas for future research directions that could enrich and broaden the overall portfolio.

3.5 CCTP Goals for Advanced Technology

1. Energy End-Use Efficiency and Infrastructure
2. Low- and Zero-CO₂ Emissions Energy Supply
3. CO₂ Capture/Storage and Sequestration
4. Non-CO₂ GHGs

Energy End-Use Efficiency and Infrastructure

In published scenarios, increasing demand for energy services, driven by population and economic growth, drives growth in GHG emissions over the 21st century. If gross world product were to grow by 2.0 percent per year over the span of the 21st century, and the demand for energy services were to grow at a commensurate 2.0 percent per year, then energy demand would grow seven-fold by 2100. Many published scenarios assume gross world product growth above these rates. For example, at the top of the range of the IPCC's Special Report on Emissions Scenarios (SRES) scenarios, gross world product grows at more than 3.0 percent per year from 1990 through 2100.

In virtually all published scenarios, however, the demand for final energy [38] and associated emissions of CO₂ grows at rates lower than the growth rates of gross world product. This is because improvements in end-use efficiency, along with structural changes in economic activity, tend to drive up economic value-added and drive down energy inputs associated with increasing global prosperity. [39] In 1990, global final energy intensity (energy used per constant dollar of gross world product) was roughly 17 million joules per dollar. In the IPCC's SRES scenarios, final energy intensities in 2100 ranged from 1.4 million to 5.9 million joules per dollar of gross world product. [40] Without these reductions in energy intensity, which are significant, energy demand growth and associated GHG emissions would be significantly higher. This point is illustrated in Figure 3-15, which shows the relationship between global CO₂ emissions and energy intensities in 2100 in various published scenarios. Although Figure 3-15 shows variation across multiple scenarios due to differences in energy mix and the levels of deployment of low or zero-emitting technologies, the general pattern indicates that lower energy use per unit of economic output leads to lower CO₂ emissions per unit of economic output.

This relationship suggests the significance of the emissions reduction benefits that would accrue from increasing the efficiency of end-use technologies. If R&D efforts were to increase the rate of final energy intensity improvement by one-quarter of one percent per year over the span of the 21st century (leading to an increase in energy efficiency by the end of the century of roughly 25 percent), scenario analyses indicate that CO₂ emissions would be reduced by 3.5 GtC/year by 2100. For perspective, this is roughly half of the total global CO₂ emissions in 2006. [42]

Figure 3-15 Global CO₂ Emissions Intensity versus Global Energy Intensity
(Source: Data from the Greenhouse Gas Emissions Scenario Database)

This point is further illustrated by the advanced technology scenarios in the PNNL report on climate change technology strategies (Clarke et al. 2006). In this study, advanced energy-efficiency technologies were assumed to lower final energy requirements by 17 to 32 percent globally in 2100. These reductions were responsible for a cumulative decrease of between 130 to 270 GtC of CO₂ emissions over the course of the 21st century. Energy-efficiency improvements also contributed to the lowering of the costs for achieving stabilization of GHG concentrations across a range of varied assumptions.

Similarly, one of the IPCC's SRES scenarios featuring advanced end-use technologies (A1T) indicates that reductions from end-use efficiency (through reduced final energy intensity) could be responsible for roughly 4.0 GtC/yr by 2100. [43] In addition, Hanson and Laitner (2004) developed an advanced technology scenario and projected that approximately one-third of the U.S. carbon emissions reductions in 2050�roughly one GtC/yr�were attributable to the deployment of more efficient end-use technologies. [44]

Providing technological options to improve energy end-use efficiency can provide a fundamental way to achieve GHG emissions reductions and lower the need for CO₂-free energy supply. This insight is robust across a full spectrum of varied technology futures�whether these futures emphasize fossil fuels combined with CO₂ capture and storage, renewable or nuclear power, or novel technologies such as fusion and advanced bio-technology.

Low- and Zero-CO₂-Emissions Energy Supply Technologies

In integrated assessment models, low- and near-zero- emissions energy supply technologies are modeled at varying levels of technological detail. While some models explicitly model various low- and near-zero- emissions energy supply technologies, others use one or more generic technology classes to represent these technologies. In either case, the low- and near-zero- emissions technologies prove to be important components to technology strategies aimed at stabilizing GHG concentrations. Figure 3-16 shows the strong correlation between the CO₂ emissions intensity (tonnes of CO₂ emissions per constant dollar of GWP) of the global economy and the percentage of renewable and nuclear energy found in the energy supply mix, as projected in a wide number of scenarios.

Figure 3-16 Global CO₂ Emissions Intensity versus Percentage of Renewable and Nuclear Energy in the Energy Supply Mix
(Source: Data from the Greenhouse Gas Emissions Scenario Database)

A number of scenario analyses give quantitative significance to the importance of low- and near-zero-emissions energy supply technologies in reducing emissions. For example, Akimoto et al. (2004) [46] show that for a hypothetical climate policy where emissions are constrained, the share of the world's primary energy in 2100 met by biomass and wind energy increased by more than 70 percent from their reference case contributions of 10 percent and 4 percent, respectively. In addition, solar power supplied almost 5 percent of the world's primary energy demand by 2100. [47] Growth in nuclear energy (fission), biomass, and renewable energy accounted for about 30 percent of the emissions reduction in 2100, in about equal shares. Similarly, Edmonds et al. (2004) reported that contributions from solar and nuclear energy grew under CO₂ emissions constraints, especially when no technological advancement was assumed for fossil-based generation technologies and CO₂ capture and storage (CCS) technologies. [48]

As discussed in previous sections, Clarke et al. (2006) examined several advanced technology scenarios to achieve a range of emissions reductions. Low- and near-zero-emissions energy technologies (including solar, wind, biomass, nuclear fission, and advanced concepts such as nuclear fusion and novel biotechnology) contribute between 23 percent and 34 percent of world primary energy demand by 2100. These technologies were projected to contribute between 30 and 340 GtC of CO₂ emissions reductions (cumulative) over the course of the 21st century, under a variety of scenarios aimed at stabilizing GHG concentrations (Clarke et al. 2006).

Finally, in several scenarios that explored the use of hydrogen as a fuel or energy carrier, renewable energy sources were found to be important means for generating hydrogen and other fuels. Edmonds et al. (2004) showed that, under a medium carbon constraint, the preferred feedstock for hydrogen production shifts from fossil fuels to biomass, because the application of CCS to biomass-based H2 production can result favorably in net negative emissions. Alternatively, Mori and Saito (2004) report that H2 production from fast breeder reactors can, under certain emissions constraints, cost-effectively supply nearly all of the final energy demand for hydrogen. [49]

Carbon Capture/Storage and Sequestration

Capture and Storage of Carbon Dioxide

Figure 3-17 Carbon Dioxide Captured and Stored, as a Function of Primary Energy Supplied from Fossil Fuels for Various IPCC Scenarios. Note: The dashed lines in the figures reflect the correlation between fossil energy and CCS deployment. (Source: Various scenario results were extracted from the database maintained by the Center for Global Environmental Research, National Institute for Environmental Studies, Tsukuba, Japan.

Figure 3-17 shows the amount of carbon dioxide captured and stored, as a function of the amount of primary energy supplied by fossil fuels for various scenarios from the Center for Global Environmental Research data base [50] in the years 2050 and 2100. Both parts of the figure show a relationship between the amount of carbon sequestered and the amount of fossil fuel used. The plots show that by the middle of the century, the deployment of CCS technologies in conjunction with fossil fuel use is occurring in many scenarios, even though lower-carbon fuels (such as natural gas) are still available. By the end of the century, when such fuels are less abundant and/or expensive, CCS is almost always deployed in scenarios with high fossil fuel consumption.

A number of recent studies using integrated assessment models have examined the potential of CCS to lower future CO₂ emissions. Edmonds et al. (2004) report that fossil energy technologies with CCS can supply approximately 55 percent of the global electricity generation by the end of the century in an advanced technology scenario with high emissions reductions. [51] This was more than twice the contribution than in a case where CCS (and other advanced energy technologies) was not assumed to advance. McFarland et al. (2004) find that fossil-based power systems with CCS account for approximately 70 percent of global electricity production by 2100 under a high GHG emissions constraint, where CCS systems and other advanced fossil energy systems are allowed to deploy to their full market potential. [52] Clarke et al. (2006) show fossil systems with CCS contributing up to 50 percent more of the world's total primary energy consumption in 2100 in scenarios featuring technology advancement in CCS, compared to other advanced technology scenarios. [53]

Recent studies have also examined the economic benefits of using CCS in isolation or along with other technological advancements. By allowing fossil energy resources to be used while simultaneously delivering reductions in CO₂ emissions, CCS technologies help to constrain the rate of increase and ultimate peak of carbon prices (an indication of the overall cost of achieving the emission reductions). [54] For example, Edmonds et al. (2004) show that through the large-scale adoption of CCS and other advanced fossil energy technologies, peak carbon permit prices were 62 percent lower than if those technologies were not deployed to their full market potential. In the study by McFarland et al. (2004), CCS reduces carbon prices by 33 percent at the end of the century.

While many studies employ different modeling approaches, technology representations, and assumed climate policies, the synthesis assessment of scenarios shows that CCS has the potential to play a significant role in emissions mitigation during the 21st century. The advancement of CCS-related technologies magnifies this contribution, delivering substantial economic savings. Early technical resolution of the viability of various CCS options could have significant implications for subsequent R&D investment strategies.

Terrestrial Sequestration

Globally, the goods and services derived from land resources�including food, water, shelter, energy, and recreation�are basic to human existence and quality of life. Future changes in cropland, grassland, and forest land areas�regionally and globally�will be driven by the ability of land resources to provide these basic goods and services. Hence, the potential to use terrestrial systems to sequester carbon and mitigate global GHG emissions will be directly affected by the development of advanced technologies that reduce human pressures on land by increasing land productivity across a range of economic sectors�including (but not limited to) agriculture, forestry, and energy.

In agriculture, advanced technologies could enhance terrestrial carbon sequestration by enabling the development of new food and fiber products, production processes, and distribution systems that reduce the amount of land needed to feed and clothe the world's population. In forestry, advanced technologies could accelerate the processes of reforestation and afforestation, as well as increase the quantity of wood products that could be obtained from a unit of forest land. Advanced energy technologies could increase terrestrial sequestration by reducing deforestation pressures in developing countries and shifting cropland to bioenergy crop systems that not only increase soil carbon levels but also shift energy production toward technologies that recycle atmospheric CO₂.

Sohngen and Mendelsohn (2003) suggest that global forests have a net sequestration potential ranging from 32 to 102 GtC in the coming century, depending on carbon prices (see Section 3.2.1.2). In a more recent study performed as part of EMF-21, the net sequestration was projected to increase from today's level by 48 to 148 GtC by 2100 under different climate policies (Sohngen and Sedjo, 2006). The cost of land-use and forest sequestration has been estimated to range between $10 and $200 per ton of carbon stored (Richards and Stokes 2004).

Non-CO₂ GHG Emissions

Potential reductions and cost savings are illustrated in the Energy Modeling Forum multi-gas scenario study�EMF-21 (Weyant and de la Chesnaye 2005)� and other long-term multi-gas studies (e.g., Manne and Richels 2000, 2001; Reilly et al. 2002). The various models exercised in the EMF-21 study used a range of assumptions about technology development, leading to a range of reductions of non-CO₂ GHGs. The studies suggest that, between 2000 and 2100, emissions of non-CO₂ "well mixed" gases (methane, nitrous oxide, and the F-gases) in a moderately constrained emissions case [55] could be reduced by as much as 48 percent, and the cost of GHG stabilization could be lowered by 30 to 60 percent compared to a CO₂-only scenario.

In addition to the long-term EMF-21 multi-gas scenarios, two other studies illustrate maximum technology potential of non-CO₂ mitigation options over the medium term. Delhotal and Gallaher (2005) projected the reduction potential of technological improvements out to 2030 in the three major methane emitting sectors�landfills, natural gas, and coal�for selected countries. By 2030, cost-effective technologies could reduce methane emission to less than 50 percent of current levels in the United States, and could potentially reduce emissions by a factor of two in countries such as China, Mexico, and Russia in the same time frame. Another study by the International Institute for Applied Systems Analysis (IIASA) (Cofala et al. 2005) shows the "maximum potential reductions" to 2030. This study concluded that if all currently available technologies were applied to landfills, agriculture, the natural gas sector, the coal sector, and oil and gas extraction, without consideration of cost, global CH₄ emissions would stop increasing and remain constant through 2030.

The scenarios described above do not explicitly include new or highly advanced mitigation technologies for non-CO₂ GHGs. An analysis conducted by PNNL in cooperation with the U.S. Environmental Protection Agency assumed the development of advanced technologies in areas such as methane emissions from waste and energy sectors, methane and nitrous oxide emissions from agriculture, and high-GWP emissions from the industrial sector (Clarke et al. 2006). Compared to a reference scenario with no emissions constraints and no new non-CO₂ mitigation technologies, the advanced technology scenarios showed that reductions in emissions of non-CO₂ GHGs could potentially contribute 91 to 165 GtC-eq. in cumulative emissions reductions over the 21st century. The assumptions underlying the advanced technology scenario are based on the currently known methods to achieve emissions reduction, as well as detailed "bottom-up" analyses of the technical potential to reduce non-CO₂ GHGs further. Results from this analysis for a high GHG-constrained case are shown in Figure 3-18.

Summary of Relative Contributions of Four CCTP Goals

1. Reduce emissions from energy end-use and infrastructure.
2. Reduce emissions from energy supply.
3. Capture and sequester CO₂.
4. Reduce emissions of non-CO₂ GHGs.

Figure 3-18 World Non-CO₂ GHG Emissions Under High Emissions Constraints (Source: Clarke et al. 2006)

In general, scenario analyses indicate that no single technology option, as presently envisioned, is able to provide sufficient emissions reductions to meet stabilization objectives. Rather, even when assumptions vary, the analyses strongly indicate that a portfolio of technologies is required, with each technology contributing significantly to the GHG emission reductions required.

This point is illustrated by the results of a recent PNNL study (Clarke et al. 2006) in which each of the four technology areas was shown to make contributions toward stabilizing concentrations. Based on the assumptions used in this set of scenarios, no one area was markedly more or less important than others. Figure 3-19 shows the contributions of four technology categories (directly linked to the four CCTP goals stated above) to cumulative GHG emissions reductions between 2000 and 2100. The figure represents one set of possible outcomes from scenarios that are based on a particular set of assumptions about advanced technologies over the next century. It offers a glimpse of the range of emissions reductions new technologies might make possible through reduced energy end use; low- or zero-emission energy supply; carbon capture, storage, and sequestration; and reduction of other GHGs�on a 100-year scale and across a range of uncertainties. Given the magnitude of the CO₂ challenge and the uncertainties in cost, efficacy, impacts, and ultimate design of the mitigation technologies being considered, pursuit of new technological advances and alternative approaches may prove beneficial to the formulation of GHG stabilization strategies.

Figure 3-19 Cumulative Contributions Between 2000 and 2100 to the Reduction, Avoidance, Capture, and Sequestration of Greenhouse Gas Emissions for the Three Advanced Technology Scenarios, Under Varying Carbon Constraints

Summary of Insights

Further scientific study is required to understand the quantities and timing of GHG emissions reductions that would be needed to stabilize GHG concentrations at a level that would prevent dangerous anthropogenic interference (DAI) with the climate system. In the approach adopted by CCTP to explore the potential roles for and benefits of advanced technologies, four levels of GHG concentrations were assumed, with results presented for each.

Regarding the scale of the challenge, the scenarios analysis conducted for CCTP suggests that mid-range estimates of the cumulative global emissions reductions needed to result in progress over the course of the 21st century toward eventual stabilization, across a range of GHG concentrations, would be on the order of 300 to 1,000 GtC-eq. [58] Analyses using different assumptions may result in different values, but a number of mid-range analyses indicate 100-year cumulative reductions of similar magnitude. [59] These reductions (or avoidances) would be in addition to the GHG emissions avoided by the substantial energy-efficiency improvements and CO₂-emission-free energy sources already assumed (embedded) in their respective reference case scenarios. Technology advancements could make such reductions much more feasible in the context of economic growth.

The synthesis assessment of a large number of scenario analyses conducted by different research groups indicates that emissions reductions of the scale needed to achieve stabilization of GHG concentrations can be achieved through various combinations of many different technologies. An important insight that can be drawn from these studies is that, under a wide range of differing assumptions, advanced technologies associated with CCTP Strategic Goals 1 through 4 could all contribute significantly to overall GHG emission reductions.

While many technologies may reduce or avoid GHG emissions, scenario analyses can suggest roles for advanced technologies that could result in potentially large relative economic benefits. When the costs of achieving different levels of emissions reductions were compared for cases with and without advanced technologies, the cumulative cost savings of the former were projected to be 60 percent or more over the course of the 21st century. Further, by including the non-CO₂ gases in a multi-gas GHG reduction strategy aimed at stabilizing at various DAI levels of radiative forcing, overall costs of goal attainment were reduced, potentially by 30 to 50 percent when compared to CO₂-only approaches.

Finally, scenario analyses indicate that the timing of the commercial readiness of advanced technology options is an important R&D planning consideration, and particularly so for R&D planning under scenarios with the higher GHG emissions constraints.

Table 3-1 is one set of representative results in this regard, showing when the first GtC/year of reduced or avoided emissions would be needed, depending on the range of GHG emissions constraints. Looking over a 100-year planning horizon, and allowing for capital stock turnover and other inertias, inherent in the global energy system and infrastructure, technologies with low or near-zero net emissions characteristics would need to be available and moving into the marketplace years before the periods shown on

References

Alcamo, J., R. Leemans, and E. Kreileman, eds. 1998. Global change scenarios of the 21st century. Results from the IMAGE 2.1 model. London: Elsevier Science.

Ausubel, J.H., A. Gr�bler, and N. Nakicenovic. 1988. Carbon dioxide emissions in a methane economy. Climatic Change 12:245-263.

Brown, M.A., M.D. Levine, and W.D. Short. 2000. Scenarios for a clean energy future. Interlaboratory Working Group. Published by Oak Ridge National Laboratory, Oak Ridge, TN; and Lawrence Berkeley National Laboratory, Berkeley, CA; ORNL/CON-476 and LBNL-44029.

Brown, S., J. Sathaye, M. Cannell, and P.E. Kauppi. 1996. Mitigation of carbon emissions to the atmosphere by forest management. Commonwealth Forestry Review 75:80-91.

Clarke, L., M. Wise, M. Placet, C. Izaurralde, J. Lurz, S. Kim, S. Smith, and A. Thomson. 2006. Climate Change Mitigation: An Analysis of Advanced Technology Scenarios. Richland, WA: Pacific Northwest National Laboratory.

Cofala, J. Markus Amann, and Reinhard Mechler. 2005. Scenarios of world anthropogenic emissions of air pollutants and methane up to 2030. Laxenburg, Austria: International Institute for Applied Systems Analysis.

Coppock, R. and S. Johnson. 2004. Direct and indirect human contributions to terrestrial carbon fluxes: a workshop summary. Washington, DC: National Academies Press.

Delhotal, K.C., and M. Gallaher. 2005. Estimating technical change and potential diffusion of methane abatement technologies for the coal-mining, natural gas, and landfill sectors. Conference proceedings, IPCC Expert Meeting on Industrial Technology Development, Transfer and Diffusion.

De Jong, A., and G. Zalm. 1991. Scanning the future: a long-term scenario study of the world economy 1990-2015. In Long-term prospects of the world economy, 27-74. Paris: OECD.

De Vries, H.J.M., J.G.J. Olivier, R.A. van den Wijngaart, G.J.J. Kreileman, and A.M.C. Toet. 1994. Model for calculating regional energy use, industrial production and greenhouse gas emissions for evaluating global climate scenarios. Water, Air Soil Pollution 76:79-131.

De Vries, B., M. Janssen, and A. Beusen. 1999. Perspectives on global energy futures�simulations with the TIME model. Energy Policy 27:477-494.

De Vries, B., J. Bollen, L. Bouwman, M. den Elzen, M. Janssen, and E. Kreileman. 2000. Greenhouse gas emissions in an equity-, environment- and service-oriented world: An IMAGE-based scenario for the next century. Technological Forecasting & Social Change 63(2-3).

Edenhofer, O., N. Bauer, and E. Kriegler. 2005. The impact of technological change on climate protection and welfare: Insights from the model MIND. Ecological Economics 54:277� 292.

Edmonds, J., J. Clarke, J. Dooley, S.H. Kim, and S.J. Smith. 2004. Stabilization of CO₂ in a B2 world: insights on the roles of carbon capture and disposal, hydrogen, and transportation technologies. Energy Economics 26(4):517-537. Special Issue EMF 19 Alternative technology strategies for climate change policy, John P. Weyant, ed.

Edmonds, J., M. Wise, and C. MacCracken. 1994. Advanced energy technologies and climate change. an analysis using the Global Change Assessment Model (GCAM). PNL-9798, UC-402. Richland, WA: Pacific Northwest Laboratory.

Edmonds, J., M. Wise, H. Pitcher, R. Richels, T. Wigley, and C. MacCracken. 1996a. An integrated assessment of climate change and the accelerated introduction of advanced energy technologies: an application of MiniCAM 1.0. Mitigation and Adaptation Strategies for Global Change 1(4):311-339.

Edmonds, J., M. Wise, R. Sands, R. Brown, and H. Kheshgi. 1996b. Agriculture, land-use, and commercial biomass energy: a preliminary integrated analysis of the potential role of biomass energy for reducing future greenhouse related emissions. PNNL-11155. Washington, DC: Pacific Northwest National Laboratories.

Energy Information Administration (EIA). 2005. International energy outlook 2005. DOE/EIA-0484 (2005). Washington, DC: U.S. Department of Energy.

EPA (See U.S. Environmental Protection Agency)

Gerlagh, R. and B. van der Zwaan. 2003. Gross world product and consumption in a global warming model with endogenous technological change. Resource and Energy Economics 25:35�57.

Goulder, L.H., and K. Mathai. 2000. Optimal CO Abatement in the Presence of Induced Technological Change. Journal of Environmental Economics and Management 39:1-38.

Grübler, A., and N. Nakicenovic. 1996. Decarbonizing the global energy system. Technological Forecasting and Social Change 53(1):97-110.

Halmann, H.M. 1993. Chemical fixation of carbon dioxide. Boca Raton, Florida: CRC Press.

Hanson, D., and J. Laitner. 2004. An integrated analysis of policies that increase investments in advanced energy-efficient/low-carbon technologies, Energy Economics 26(4):739-755. Special Issue EMF 19 Alternative technology strategies for climate change policy, John P. Weyant, ed.

Hoffert, Martin L. et al. 2002. Advanced technology paths to global climate stability: energy for a greenhouse planet. Science 298:981-987.

IIASA-WEC (International Institute for Applied Systems Analysis-World Energy Council). 1995. Global energy perspectives to 2050 and beyond. London: WEC.

Intergovernmental Panel on Climate Change (IPCC). 1996. Climate change 1995: the science of climate change. Contribution of Working Group I to the Second Assessment Report. Cambridge, UK: Cambridge University Press.

Intergovernmental Panel on Climate Change (IPCC). 2000. Special report on emissions scenarios. Cambridge, UK: Cambridge University Press.

Intergovernmental Panel on Climate Change (IPCC). 2001. Climate Change 2001. Mitigation: a report of Working Group III of the Intergovernmental Panel on Climate Change. Bert Metz, Ogunlade Davidson, Rob Swart and Jiahua Pan, eds. Cambridge, UK: Cambridge University Press.

Inui, T., M. Anpo, K. Izui, S. Yanagida, and S. Yamaguchi. 1998. Advances in chemical conversions for mitigating carbon dioxide. Amsterdam: Elsevier. IPCC (See Intergovernmental Panel on Climate Change).

Kojima, T. 1997. The carbon dioxide problem: Integrated energy and environmental policies for the 21st century. Amsterdam: Gordon and Breach.

Lackner, K.S. 2002. Carbonate chemistry for sequestering fossil carbon. Annual Review of Energy and Environment 27:193-232.

Lashof, D., and D.A. Tirpak. 1990. Policy options for stabilizing global climate. 21P-2003. Washington, DC: U.S. Environmental Protection Agency.

Löschel, A. 2002. Technological change in economic models of environmental policy: a survey. Ecological Economics 43:105-126.

Manne, A., and R. Richels. 2000. A multi-gas approach to climate policy�with and without GWPs.

Manne, A., and R. Richels. 2001. An alternative approach to establishing trade-offs among greenhouse gases. Nature 410:675-677.

Manne, A., and R. Richels. 2004. The impact of learning-by-doing on the timing and costs of CO₂ abatement. Energy Economics 26(4):603-619. Special Issue EMF 19 Alternative technology strategies for climate change policy, John P. Weyant, ed.

McFarland, J.R., J.M. Reilly, and H.J. Herzog. 2004. Representing energy technologies in top-down economic models using bottom-up information. Energy Economics 26(4):685-707. Special Issue EMF 19 Alternative technology strategies for climate change policy, John P. Weyant, ed.

Messner, S., and M. Strubegger. 1995. User's guide for MESSAGE III. WP-95-69. Laxenburg, Austria: International Institute for Applied Systems Analysis.

Mori, S. 2000. The development of greenhouse gas emissions scenarios using an extension of the MARIA model for the assessment of resource and energy technologies. Technological Forecasting & Social Change 63(2-3).

Mori, S., and M. Takahashi. 1999. An integrated assessment model for the evaluation of new energy technologies and food productivity. International Journal of Global Energy Issues 11(1-4):1-18.

Mori, S., and T. Saito. 2004. Potentials of hydrogen and nuclear towards global warming mitigation�expansion of an integrated assessment model MARIA and simulations. Energy Economics 26(4):565-578. Special Issue EMF 19 Alternative technology strategies for climate change policy, John P. Weyant, ed.

Morita, T., Y. Matsuoka, I. Penna, and M. Kainuma. 1994. Global carbon dioxide emission scenarios and their basic assumptions: 1994 survey. CGER-1011-94. Tsukuba, Japan: Center for Global Environmental Research, National Institute for Environmental Studies.

Pacala, S., and R. Socolow. 2004. Stabilization wedges: solving the climate problem for the next 50 years with current technologies. Science 305:968-972.

Pepper, W.J., J. Leggett, R. Swart, J. Wasson, J. Edmonds, and I. Mintzer. 1992. Emissions scenarios for the IPCC. An update: assumptions, methodology, and results. Support document for Chapter A3. In Climate change 1992: supplementary report to the IPCC scientific assessment, J.T. Houghton, B.A. Callandar, and S.K. Varney, eds. Cambridge, UK: Cambridge University Press.

Reilly, J., M. Mayer, and J. Harnisch. 2002. The Kyoto Protocol and non-CO₂ greenhouse gases and carbon sinks. Environmental Modeling and Assessment 7(4):217-229.

Riahi, K., and R.A. Roehrl. 2000. Greenhouse gas emissions in a dynamics-as-usual scenarios of economic and energy development. Technological Forecasting & Social Change 63:175-206.

Richards, K. and C. Stokes. 2004. A review of forest carbon sequestration cost studies: A dozen years of research. Climatic Change. 63 (1-2): 1-48.

Richels, R.G., A.S. Manne, and T.M.L. Wigley. 2004. Moving beyond concentrations: the challenge of limiting temperature change. Working Paper 04-11. AEI-Brookings Joint Center for Regulatory Studies.

Roehrl, R.A., and K. Riahi. 2000. Technology dynamics and greenhouse gas emissions mitigation: a cost assessment. Technological Forecasting and Social Change 63, 231�261

Sankovski, A., W. Barbour, and W. Pepper. 2000. Quantification of the IS99 emission scenario storylines using the atmospheric stabilization framework (ASF). Technological Forecasting & Social Change 63(2-3).

Sohngen, B., and R. Sedjo (2006). Carbon sequestration costs in global forests. Energy Policy. Special Edition on Multi-Gas Scenarios and Climate Change (to be published).

Sohngen, B. and R. Mendelsohn. 2003. An optimal control model of forest carbon sequestration. American Journal of Agricultural Economics, 85(2): 448-457.

Stern, P.C. 2002. Human interactions with the carbon cycle: summary of workshop. Washington, DC: National Academies Press.

United Nations Development Program (UNDP). 2000. World Energy Assessment. New York.

U.S Climate Change Science Program. 2003. Strategic plan for the U.S. Climate Change Science Program.

U.S. Environmental Protection Agency. 2005. U.S. emissions inventory: inventory of U.S. greenhouse gas emissions and sinks: 1990-2003. EPA 430-R-05-003. Washington, DC: U.S. Environmental Protection Agency.

van Vuuren, D.P., B. de Vries, B. Eickhout, and T. Kram. 2004. Responses to technology and taxes in a simulated world. Energy Economics 26(4):579-601. Special Issue EMF 19 Alternative technology strategies for climate change policy, John P. Weyant, ed.

Webster, M.D., M. Babiker, M. Mayer, J.M. Reilly, J. Harnisch, R. Hyman, M.C. Sarofim, and C. Wang. 2002. Uncertainty in emissions projections for climate models. Atmospheric Environment 36 (2002) 3659�3670.

Wexler, L. 1996. Improving population assumptions in greenhouse emissions models. WP-96-099. Laxenburg, Austria: International Institute for Applied Systems Analysis.

Weyant, J.P., ed. 2004. Energy Economics 26(4): Special Issue EMF 19 Alternative technology strategies for climate change policy.

Weyant, J.P., and F. de la Chesnaye. 2005. Multigas scenarios to stabilize radiative forcing. Energy Journal. Special Edition on Multi-gas Scenarios and Climate Change.

Wigley T., R. Richels, and J. Edmonds. 1996. Economic and environmental choices in the stabilization of atmospheric CO₂ concentrations. Nature 379(6562): 240-243.

Footnotes

1 Water vapor and ozone are also GHGs.

2 Global warming potentials (GWPs) are used to compare the abilities of different GHGs to trap infared radiation in the atmosphere. GWPs are based on the radiative efficiency (radiation-absorbing ability) of each gas relative to that of carbon dioxide (CO₂), as well as the decay rate of each gas (the amount removed from the atmosphere over a given number of years) relative to that of CO₂. The GWP provides a simplified construct for converting emissions of various gases into a common measure. However, it is important to note that GWPs are only an approximate metric for considering the relative impacts of different gases on the radiative balance of the Earth's atmosphere, because atmospheric lifetimes differ dramatically among gases. For example, methane's lifetime in the atmosphere is shorter than CO₂, so the radiative impact of a ton of methane emitted today will attenuate more quickly over time with respect to the radiative impact of a ton of CO₂ emitted today. Hence, the timeframe over which the GWP is developed critically affects the relative magnitude of the contributions of various gases (typically a 100-year timeframe is used), and GWPs serve as an indication of the relative importance of different gases, not as a precise measurement of the relative long-term impacts on the Earth's radiative balance.

3 The ozone-depleting halocarbons and other chlorine- and bromine-containing substances are addressed by the Montreal Protocol and are not directly addressed by this Plan. Besides CO₂, N₂O, and CH₄, the Intergovernmental Panel on Climate Change (IPCC) definitions of GHGs include sulfur hexafluoride (SF₆), hydrofluorocarbons (HFCs), and perfluorocarbons (PFCs), often collectively called the "F-gases."

4 See Methane: Voluntary Programs (EPA).

5 A large body of work has been undertaken to understand the influence of external factors on climate using the concept of changes in radiative "forcing" due to changes in the atmospheric composition, alteration of surface reflectance by land use, and variations in solar input. Some of the radiative forcing agents, such as CO₂, are well mixed over the globe, thereby perturbing the global heat balance. Others, such as aeresols, represent perturbations with stronger regional signatures because of their spatial distribution. For this and other reasons, a simple sum of the positive and negative bars cannot be expected to yield the net effect on the climate system.

6 Available at IPCC Website.

7 One study that examined emissions growth in the absence of special initiatives directed at climate change is the Special Report on Emissions Scenarios (SRES) by the Intergovernmental Panel on Climate Change (IPCC 2000), in which six leading energy-economic models were used to explore a suite of scenarios that projected growth in global energy and GHG emissions.

8 See Energy Modeling Forum publications index.

9 See for example, Direct and Indirect Human Contributions to Terrestrial Carbon Fluxes: A Workshop Summary (2004) and Human Interactions with the Carbon Cycle: Summary of a Workshop (2002), both available from the National Academies Press (Coppock and Johnson 2004 and Stern 2002).

10 Scenarios that show low or negative energy consumption growth rates over time represent cases where technological improvement is projected to be very rapid and where population and GDP growth rates lie at the lower bounds of the projections.

11 The range of CO₂ emissions in the SRES has been compared to scenarios done later (post-SRES). In general, the ranges are not very different. The estimated CO₂ emissions in post-SRES scenarios have a higher lower bound, a similar median, and a higher upper bound of the distribution. The post-SRES scenarios use lower population estimates, both in range and median. The post-SRES economic development projections (based on market exchange rates) have approximately the same lower bound and median but a lower upper bound of the distribution. A comprehensive database of emissions scenarios.

12 Asian Pacific Integrated Model (AIM) from the National Institute of Environmental Studies in Japan (Morita et al. 1994).

13 Atmospheric Stabilization Framework Model (ASF) from ICF Consulting in the USA (Lashof and Tirpak 1990; Pepper et al. 1992, 1998; Sankovski et al. 2000).

14 Integrated Model to Assess the Greenhouse Effect (IMAGE) from the National Institute for Public Health and Environmental Hygiene (RIVM) (Alcamo et al. 1998; de Vries, Olivier et al. 1994, de Vries, Janssen et al. 1999; de Vries, Bollen et al. 2000), used in connection with the Dutch Bureau for Economic Policy Analysis (CPB) WorldScan model (de Jong and Zalm 1991), the Netherlands.

15 Multiregional Approach for Resource and Industry Allocation (MARIA) from the Science University of Tokyo in Japan (Mori and Takahashi 1999; Mori 2000).

16 Model for Energy Supply Strategy Alternatives and their General Environmental Impact (MESSAGE) from the International Institute of Applied Systems Analysis (IIASA) in Austria (Messner and Strubegger 1995; Riahi and Roehrl 2000).

17 Mini Climate Assessment Model (MiniCAM) from the Pacific Northwest National Laboratory (PNNL) in the USA (Edmonds et al. 1994, 1996a, 1996b).

18 Use of uncertainty analysis and probabilistic forecasting can help identify and quantify critical but uncertain parameters (such as demographic or technology trends over time). Multiple simulations are performed by sampling from those distributions to construct probability distributions of the outcomes (such as GHG emissions). Distributions for factors, such as labor productivity growth, energy efficiency improvement, agricultural and industrial emissions coefficients for various GHGs, etc., are quantified by expert elicitation or from a review of the literature. These distributions are then used in assessment models to generate a distribution of results, such as GHG emissions and/or climate impacts (e.g., temperature change or sea-level rise).

19 The structure of the underlying modeling exercise required harmonization in 2000. Such harmonization in the context of a modeling exercise does not necessarily reflect agreement.

20 This pattern is tied to declines in the rate of population growth toward the latter half of the century and increases in agricultural productivity.

21 The models included a variety of model types, including integrated assessment models and general equilibrium models.

22 Note that certain models (such as MiniCAM) project that some GHG-reducing technologies penetrate the market without incentives or policies. For example, in MiniCAM, technologies for reducing methane emissions from coal and natural gas production would penetrate the market when it is cost-effective to do so, based on the value of the methane (natural gas) collected, which is marketable as a fuel.

23 Derived from Wigley et al. 1996. The emissions scenarios represent net emissions from fossil fuels (i.e., including emissions reductions from carbon dioxide capture and storage) and industrial sources. They do not include emissions from land use and land-use change. The concentration levels are based on a range of specific assumptions regarding net emissions from land use and land-use change, and about the carbon cycle more generally, including assumptions regarding the rate of ocean uptake. Note that significant uncertainties remain about many aspects of the carbon cycle; reducing these carbon cycle uncertainties is one of the goals of the U.S. Climate Change Science Program (CCSP). Other estimated scenarios showing relationships between emissions and concentrations can be found in the literature on scenarios.

24 The "unconstrained" case in this illustrative example is based on the reference scenario developed for CCTP by PNNL; see Clarke et al. (2006). Note that this reference scenario includes a considerable amount of energy efficiency as well as increased use of renewable and nuclear energy resulting from improvements in these technologies over time, increased prices for fossil fuels, and hence increased ability of renewable and nuclear technologies to compete in the market. The lower curve represents a reduced-emissions scenario leading to stabilization; it is a slightly modified version of the 550 ppmv trajectory shown in Figure 3-10A.

25 See Clarke et al. 2006 and IPCC 2001. Estimates of the emissions reductions required to stabilize concentrations are uncertain and vary based on assumptions. Key assumptions include: (1) estimates of future emissions to 2100 in the absence of actions aimed at GHG mitigation (i.e., the "reference" scenario); (2) selection of the stabilization level or levels of atmospheric GHG concentrations; and (3) the nature of baseline and advanced technology scenarios and their associated time-specific emissions trajectories. Results for CCTP are shown as "mitigated emissions" on Figure 3-14.

26 See, for example, studies by van Vuuren et al. (2004) and Manne and Richels (2004), and the the mitigation scenarios studied in the IPCC Working Group III .

27 For example, the IPCC "Post-SRES" report on mitigation (IPCC 2001) and the EMF studies (Weyant 2004).

28 The low- or no-cost suite of technologies generally includes improvements to current systems and various cost-effective energy conservation strategies. These are usually modeled as a general rate of energy-efficiency (or intensity) improvement, and are often included in the business-as-usual (or "reference case") emissions projections.

29 The four hypothesized GHG emissions constraints (i.e., Very High, High, Medium, and Low) were designed to stabilize, over the long term, the aggregated radiative forcing of the following GHGs: CO₂, CH₄, N₂O, and the so-called "F-gases" (hydrofluorocarbons [HFCs], perfluorocarbons [PFCs], and sulfur hexafluoride [SF₆]). A range of additional substances, such as aerosols, also have important effects on radiative forcing. These substances are not included in this analysis.

30 The reference case assumes energy efficiency improvements occur, as well as cost decreases in renewable and nuclear technologies that bring their costs to below today's levels.

31 In the PNNL analysis, Scenarios 1, 2, and 3 are given representative labels of "Closing the Loop on Carbon," "A New Energy Backbone," and "Beyond the Standard Suite," respectively.

32 Note that renewables and nuclear energy increase over time in the reference case scenario, but increase more in Scenario 2 due to more significant decreases in cost and performance.

33 Advanced biotechnologies (sometimes called "Bio-X") are those that combine the biosciences with fields such as nanotechnology, chemistry, computers, medicine, and others to create novel solutions for technology challenges. This could lead to innovative concepts such as the use of "enzyme machines" or even new materials (e.g., bio-nano hybrids) that could replace traditional technology altogether.

34 The term "advanced technologies" is used to represent major improvement in current technologies, as well as novel technologies currently not in use. In this study, technology advancement was assumed to lead to more efficient energy technologies with lower capital and operating costs. Details on the assumptions can be found in Clarke et al. (2006). The resulting cost reductions do not consider the cost associated with performing any R&D that might be necessary to achieve the improved technology performance.

35 In the study, costs included those associated with fuel switching (to fuels or technologies with lower emissions), changes in domestic and international fuel prices, and price-induced conservation activities.

36 Meeting Report of the IPCC Expert Meeting on Emission Scenarios, 12-14 January 2005, Washington D.C. http://www.ipcc.ch/meet/washington.pdf.

37 CCTP also includes two supporting technology areas. These are measuring and monitoring technologies, and application of basic science to applied technology R&D. These supporting areas are not discussed in this chapter, although they are integral elements of the overall CCTP technology strategic plan.

38 Final energy refers to energy delivered to the point of end use (e.g., to buildings or gas stations) as opposed to energy used as an input to, for example, electricity generation. However, final energy does not represent the actual energy ultimately delivered in the way of services to end-users (e.g., building cooling or vehicle miles traveled) because final energy must be converted to these final services by equipment such as air conditioners and automobiles. Hence, changes in final energy should be interpreted as combining changes both in the level of services demanded and in the efficiency at which final energy is used to supply those services.

39 See the GHG Emissions Scenario Database.

40 Range based on the illustrative scenarios from IPCC (2000). Changes in final energy intensity incorporate both changes in end-use efficiency and changes in the relationship between economic output and the demand for services such as transportation and air conditioning (see footnote 39). Hence, improvements in energy intensity should not be interpreted strictly as improvements in end-use efficiency.

41 See website.

42 This calculation is based on the illustrative B2 scenario from IPCC (2000). It assumes that lower final energy requirements would not alter the relative proportions of energy provided from different sources.

43 Result based on the illustrative scenarios for the A1 set. It was calculated based on a comparison of the illustrative A1T scenario with the illustrative A1B scenario, assuming no change in the primary energy mix between the two. While not identical to A1T, A1B is similar in terms of the emissions per unit of primary energy and therefore serves as an effective reference. The particular scenario cited above used the AIM (model).

44 Note that many of the assumptions in this study followed from the study, Scenarios for a Clean Energy Future (Brown et al. 2000).

45 Visit Web site.

46 The study used an updated version of the DNE21 model, an integrated assessment model which hard-links macroeconomic, energy systems, and climate change models, and seeks optimal development of the world's energy system for a given climate policy based on maximizing macroeconomic consumption.

47 The upper limit of the world total nuclear production assumed in this scenario was 920 GW in 2050 and 1450 GW in 2100, so nuclear energy was not a major contributor in this analysis.

48 This study used the MiniCAM model and the IPCC SRES B2 Scenario to examine the role of advanced technologies under a climate policy aimed at stabilizing atmospheric CO₂ concentrations at 550 ppmv.

49 This study used the MARIA integrated assessment model to examine the role of nuclear technology and hydrogen use under different climate policies, and different technology advancement assumptions.

50 Center for Global Environmental Research, National Institute for Environmental Studies, Tsukuba, Japan.

51 This analysis employed the PNNL MiniCAM model, using the IPCC SRES B2 scenario as the reference case, and compared that case to an advanced technology case that incorporates more efficient and economical CCS, higher efficiency fossil generation, and hydrogen energy systems.

52 This study used the MIT EPPA model, a recursive dynamic multi-regional general equilibrium model of the world economy. Bottom-up information about coal- and natural gas-based generation systems with CCS were used in a top-down energy economics model to examine the effect of CCS on different climate policies.

53 This study used the PNNL MiniCAM model to examine energy and economic implications of different technology futures and different levels of emissions reductions. One future assumes that CCS technologies meet aggressive technical, economic, and environmental goals for application on fossil and biomass-based energy systems, along with higher-efficiency fossil generation and greater end-use efficiency gains.

54 Since the cost of compliance is the total area under the marginal abatement curve, the last two metrics are strongly correlated, i.e., the greater the reduction in the carbon price, the greater the reduction in the cost of compliance.

55 The constrained case was defined as 4.5 W/m2 stabilization target by 2100.

56 This figure was based on the A New Energy Backbone scenario (Scenario 2).

57 The figure shows the cumulative contributions between 2000 and 2100 to the reduction, avoidance, capture/storage, and sequestration of GHG emissions under the three Advanced Technology Scenarios, based on varying emissions constrained cases. The thick bars show the contribution under the high emission constraint and the thinner, semi-transparent bars show the variation in the contribution between the very high emissions constraint and the low emissions constraint. "Energy End-Use" includes emission reductions due to energy-efficiency measures. "Energy Supply" includes emissions reductions from the substitution of non-fossil energy supply technologies with low or zero CO₂ emissions for fossil-based power generation without capture and storage of CO₂. "Sequestration" includes carbon capture and storage from fossil-based technologies, as well as terrestrial sequestration.

58 Estimates of emissions reductions required to stabilize GHG concentrations are uncertain and vary based on assumptions. See Section 3.3 and footnote 25. See also "mitigated emissions" in Figure 3-14.

59 Manne and Richels 2004, Weyant 2004, and Roehrl and Riahi 2000.