Nebojsa Nakicenovic

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Numerous factors, sometimes called driving forces, influence future greenhouse gas (GHG) emissions. Both future emissions and the evolution of their underlying driving forces (e.g., rate of technology changes, prices) are highly uncertain. This is the reason scenarios are used to describe how the future may develop, based on a coherent and internally consistent set of assumptions about key relationships, driving forces, and the emissions outcomes. The emissions scenarios in the literature encompass a wide range of different future developments that might influence GHG sources and sinks, such as alternative structures of energy systems and land use changes (Nakicenovic et al. 2000). Clearly, demographic and economic developments play a crucial role in determining emissions. Another driving force, at least as important, is technological change. Other factors are diverse, and it is not possible to devise a simple scheme that accounts for all the factors considered and included in the scenarios. They range from human resources such as education, institutional frameworks, and lifestyles to natural resource endowments, capital vintage structures, and international trade patterns.

For this chapter, I choose a simple scheme captured by the so-called Kaya identity. This hypothetical identity represents the main emissions driving forces as multiplicative factors (Yamaji et al. 1991):

CO2 = (CO2/E x (E/GWP) x (GWP/P) x P, where E represents energy consumption, GWP the gross world product, and P population. Changes in CO2 emissions can be described by changes in these four factors or driving forces.

This type of identity was originally used to assess different impacts. The underlying method of analysis is called IPAT: Impact = Population x Affluence x Technology. The IPAT identity states that environmental impacts (e.g., emissions) are the product of the level of population, affluence (income per capita), and the level of technology deployed (emissions per unit of income).

The advantage of the Kaya identity, and the IPAT approach in general, is that it is simple and facilitates at least some standardization in the comparison and analysis of historical developments and many diverse scenarios of future emissions. An important caveat is that the driving forces that determine emissions are not independent of each other, even though they are treated as such in the identity. In fact, in many scenarios they explicitly depend on each other. For example, based on historical experience, scenario builders often assume that high rates of economic growth lead to high capital turnover. This favors more advanced and more efficient technologies, resulting in lower energy intensities and thus lower emissions. Often a weak inverse relationship is assumed between population and economic growth. Thus, the scenario ranges for these main driving forces are not necessarily independent of each other. Also note that these kinds of relationships tend to partially compensate for or offset emissions consequences of a wide range of individual driving forces, for example, higher economic growth rates are associated with lower population growth and lower emissions intensities.

In the following I present the historical developments and scenario ranges for each of the factors in the Kaya identity representing the main (energy-related) emissions driving forces: population, GWP, energy consumption (total consumption and energy intensity), and carbon emissions (total and intensity). This approach has been used often, to review historical developments and scenarios in the literature (Ogawa 1991; Parikh et al. 1991; Nakicenovic et al. 1993; Parikh 1994) and in particular by the Intergovernmental Panel on Climate Change (IPCC) (Alcamo et al. 1995; Nakicenovic et al. 2000; Morita et al. 2001). This chapter is based on the findings reported in Nakicenovic (1996) and Nakicenovic et al. (1998, 2000). I begin with global CO2 emissions, represented as a "dependent variable" in the Kaya identity, and then analyze the other factors, represented as "independent variables" (main emissions scenario driving forces). This sequence corresponds to the way the main scenario driving forces are represented in the Kaya identity, without implying a priori any causal relationships among the driving forces themselves or between the driving forces and the resulting CO2 emissions.

The scenarios in the literature cover a wide range of future GHG emissions. There are more than 500 emissions scenarios in the literature (Nakicenovic et al. 2000). Most of them are documented in a database (Morita and Lee 1998) that is accessible at www-cger.nies.go.jp/cger-e/db/ipcc.html.

Carbon Dioxide Emissions

The span of CO2 emissions across all scenarios in the database is indeed large, ranging in 2100 from 10 times the current emissions all the way to negative emissions (due to carbon sequestration and enhanced carbon sinks, which are included in some scenarios). There are many possible interpretations of this large range and many good reasons

Nebojsa Nakicenovic

Figure 11.1. Global carbon emissions: Historical development and scenarios. Emissions are indexed to 1990, when actual global energy-related CO2 emissions were about 6 PgC. The figure includes 232 scenarios. Three vertical bars on the right-hand side indicate the ranges for scenarios with emissions control such as mitigation measures (labeled "Intervention"), for scenarios that may or may not include controls ("Non-classified"), and for those without controls ("Non-intervention") (Morita and Lee 1998; Nakicenovic et al. 1998, 2000).

Figure 11.1. Global carbon emissions: Historical development and scenarios. Emissions are indexed to 1990, when actual global energy-related CO2 emissions were about 6 PgC. The figure includes 232 scenarios. Three vertical bars on the right-hand side indicate the ranges for scenarios with emissions control such as mitigation measures (labeled "Intervention"), for scenarios that may or may not include controls ("Non-classified"), and for those without controls ("Non-intervention") (Morita and Lee 1998; Nakicenovic et al. 1998, 2000).

it should be so large. Common to all of them is the high uncertainty about how the main driving forces such as population growth, economic development, and energy production, conversion, and end use might unfold during the next century.

Figure 11.1 shows the global, energy-related, and industrial CO2 emission paths from the database as "spaghetti" curves for the period to 2100 against the background of the historical emissions from 1900 to 1990. Historical emissions increased continuously, whereas the emissions scenarios cover a wider range of alternative developments. Future emissions are normalized against an index on the vertical axis rather than as absolute values, because of large differences in the values assumed for the base year, 1990. These sometimes arise from genuine differences among the scenarios (e.g., different data sources, definitions), different base years assumed in the analysis, or alternative calibrations.

Historically, gross CO2 emissions have increased at an average rate of about 1.7 percent per year (y-1) since 1900 (Nakicenovic 1996); if that trend continues, global emissions would double during the next three to four decades and increase more than sixfold by 2100. Many scenarios in the database describe such a development. Even by 2030, however, the range around this possible doubling of global emissions is very large.

The highest scenarios have emissions four times the 1990 level by 2030, whereas the lowest are barely above half the current emissions. This divergence continues so that the highest scenarios envisage a 10-fold increase of global emissions in 2100. These high emissions levels would no doubt lead to an alarming increase in atmospheric CO2 concentrations and could cause significant global climate change. The median scenarios lead to about a 3-fold emissions increase over the same time period or to about 16 PgC. This is somewhat lower than the medians from the earlier scenarios comparisons (see Alcamo et al. 1995). Nevertheless, the median emissions path would more than double atmospheric concentrations of CO2 to approximately 750 parts per million (ppm) by 2100. (The current value is about 370 ppm.) The distribution of emissions, however, is asymmetric with long "tails." The thin emissions tail that extends above the 95th percentile (i.e., between the 6- and 10-fold increase of emissions by 2100 compared with 1990) includes only a few scenarios. A number of scenarios in the low range below the 5th percentile are consistent with stabilizing concentrations at relatively benign levels of450 to 550 ppm. All scenarios that are consistent with stabilization paths reach maximum emissions and decline to below current emissions levels by the end of the 21st century.

The spaghetti curves in Figure 11.1 do not include all of the global emissions paths in the database, but are a representative sample of scenarios, selected to be discernable as individual trajectories. It should be noted that not all emissions paths in Figure 11.1 increase monotonically; some oscillate from high rates of increase to periods of declining emissions; other paths cross each other. What is important is that, on average, there is a strong trend toward continuous increases in emissions, with most of the scenarios clustering between a small decrease in global emissions over the next century to more than a 4-fold increase. It is also important to note that the distribution of scenarios is asymmetric with long tails.

Population Projections

Population is one of the fundamental driving forces of future emissions. Consequently, all emissions scenarios require some kind of population assumptions. Nevertheless, relatively few of the underlying population projections are reported in the literature, perhaps because they are exogenous inputs in most of the models used to formulate emissions scenarios.

Three main research groups project long-term global population: United Nations (UN 1998), World Bank (Bos and Vu 1994), and the International Institute for Applied Systems Analysis (IIASA) (Lutz et al. 1997). The so-called central, or median, population projections lead to less than a doubling of current global population to some 10 billion people by 2100 compared with 6 billion in 2000. In recent years the central population projections for the year 2100 have declined somewhat. The latest long-term UN (2002) medium-low and medium-high projections show a range of 5.2 to 16.2 bil-

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1800 1850 1900 1950 2000 2050 2100

Figure 11.2. Global population projections: Historical development and scenarios. The figure includes 59 scenarios (Durand 1967; Demeny 1990; Morita and Lee 1998; Nakicenovic et al. 1998, 2000).

lion people by 2100, with the medium scenario at 9.5 billion. The IIASA central estimate for 2100 is also 8.4 billion, with 95 percent of projections above 7.3 and below 12 billion (Lutz et al. 2001).

Figure 11.2 contrasts the global population projections across the scenarios in the literature with the historical trend. The long-term historical population growth rate has averaged about 1 percent y-1 during the past two centuries and at about 1.3 percent y-1 since 1900. Currently, the world's population is increasing at about 2 percent y-1. The global population projections envision a slowing population growth in the future. The most recent doubling of the world population took approximately 40 years. Even the highest population projections in Figure 11.2 require 70 years or more for the next doubling, while roughly half of the scenarios are well below these levels during the 21st century. The lowest average population growth across all projections is 0.1 percent per year, the highest is 1.2 percent per year, and median is about 0.7 percent per year.

Of the 428 scenarios documented in the database (Morita and Lee 1998), only 59 report their underlying population projections. The range is from more than 6 to about 19 billion in 2100, with the central or median estimates in the range of 10 billion. Thus, the population assumptions in the emissions scenarios appear to be broadly consistent with the recent population projections, with the caveat that only a few underlying pro

jections have been reported in the literature. The population projections across the emission scenarios are not evenly distributed across the whole range. Instead, they are grouped into three clusters. The middle cluster is representative of the central projections, with the range of about 9 billion to fewer than 12 billion people by 2100. The other two clusters mark the highest and the lowest population projections available in the literature with about 6 billion on the low end and between 14 and 19 billion at the high end.

Despite the large range of future global populations across alternative projections, the variation by 2100, compared with the base year, is the smallest of all scenario-driving forces considered in this comparison. Compared with 1990 global population, the proportional increase varies from less than one to less than four.

Gross World Product (GWP)

Economic development is a fundamental prerequisite for achieving an increase in living standards. It is thus not surprising that the assumptions about economic development are also among the most important determinants of emissions levels in the scenarios. At the same time, the prospects for economic growth are among the most uncertain determinants of future emissions. This uncertainty is reflected in the very wide range of economic development paths assumed in the scenarios. Figure 11.3 shows the future increase in GWP compared with the historical experience since 1950 (measured at market exchange rates).

The historical GWP growth rate has been about 4 percent y-1 since 1950. In the scenarios the average growth rates to 2100 range from 1.1 percent y-1 to 3.2 percent y-1, with the median value of 2.3 percent y-1. This translates into a GWP in 2100 that varies from 3.5 to more than 32 times the 1990 GWP. The 1990 and 2000 GWP were about US$20 trillion and US$35 trillion, respectively. These translate into a range of about US$70 to more than US$640 trillion (in 1990 dollars) by 2100. The full range of GWP development includes a few noticeable outliers, while the rest of the scenarios are grouped much more closely, compressing the range to a proportional increase of about 7 to 17 times compared to 1990.

Gross World Product per Capita

The scenarios in the literature portray a weak, slightly negative relationship between population and economic growth. Scenarios that lead to very high GWP are generally associated with central to low population projections, while high population projections do not lead to the highest GWP scenarios. This important tendency tends to lead to higher development in scenarios with completion of the population transition during the 21st century. Scenarios with continuous population growth tend to lag in economic development, magnifying current poverty and deprivation in the world. At the same

Median 25%

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Figure 11.3. Global economic development measured by gross world product (GWP) measured at market exchange rates: Historical development and scenarios. The figure includes 167 scenarios. Because of the relatively large differences in the base-year GWP across scenarios, the GWP paths are plotted as an index and spliced to historical data in 1990 (United Nations 1993a, b; Morita and Lee 1998; Nakicenovic et al. 2000).

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Figure 11.3. Global economic development measured by gross world product (GWP) measured at market exchange rates: Historical development and scenarios. The figure includes 167 scenarios. Because of the relatively large differences in the base-year GWP across scenarios, the GWP paths are plotted as an index and spliced to historical data in 1990 (United Nations 1993a, b; Morita and Lee 1998; Nakicenovic et al. 2000).

time, this tendency "compresses" the range of economic development, because scenarios with high population tend to have lower per capita economic development, and ones with low population tend to have higher per capita GWP.

Figure 11.4 illustrates some of the relationships between population and GWP in the scenarios. It compares only 39 scenarios, because the information about population assumptions is available for only a few scenarios. In most of them, a global population transition is achieved during the next century and stabilization occurs at a population between 10 and 12 billion people. Generally, this is associated with relatively high levels of economic development, in the range from US$200 to US$500 trillion (in 1990 dollars).

Scenarios on the lower end of this scale are collectively labeled the "mid-range cluster." One example (IS92f) leads to 18 billion people by 2100 with comparatively low economic growth. The two highest scenarios are labeled as the "extra-high-growth" cases. On the other side of the scale are two scenarios with low population projections (about 6 billion people by 2100). They are representing the "great transitions" scenarios, because they lead to relatively high economic growth with low global populations1.

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Figure 11.4. GWP and population growth: Historical development and scenarios. The figure includes 39 scenarios. Some of the scenarios are identified by name (Nakicenovic et al. 1998, 2000).

Recently, demographers have given a lot of attention to such low population scenarios, because they are consistent with continuous declines in fertility rates across the world.

Primary Energy Requirements

Primary energy requirements are another of the fundamental determinants of GHG emissions. Clearly, high primary energy levels tend to result in high GHG emissions. More important for emissions, however, is the structure of energy systems. High carbon intensities of energy—namely high shares of fossil energy sources, especially coal—lead to scenarios with very high carbon emissions. Here, the primary energy paths of different scenarios and energy carbon intensity are treated in turn.

Figure 11.5 shows the primary energy consumption paths across the scenarios, plus the historical development since 1900. Because of relatively large differences in the base-year values, the primary energy consumption paths are plotted as an index and spliced to the historical data in 1990. In 1990 primary energy was about 360 exajoules (EJ). It was about 400 EJ (10 petagrams [Pg] oil iv) in 2000.

On average, global primary energy consumption has increased at more than 2 percent y-1 (fossil energy alone has risen at almost 3 percent y-1) since 1900. In the sce

Figure 11.5. Global primary energy requirements: Historical development and scenarios. The figure includes 153 scenarios. Because of the relatively large differences in the base-year primary energy requirements across scenarios, the primary energy paths are plotted as an index and spliced to historical data in 1990 (Morita and Lee 1998; Nakicenovic et al. 1998).

1900 1950 2000 2050 2100

Figure 11.5. Global primary energy requirements: Historical development and scenarios. The figure includes 153 scenarios. Because of the relatively large differences in the base-year primary energy requirements across scenarios, the primary energy paths are plotted as an index and spliced to historical data in 1990 (Morita and Lee 1998; Nakicenovic et al. 1998).

narios, the average growth rates to 2100 range from 0.1 percent y-1 to 2.4 percent y-1, with a median value of 1.3 percent y-1.

The full range includes a few noticeable outliers (Figure 11.5), especially some scenarios without emissions control (non-control) or mitigation measures, which fall toward the high end of energy consumption levels. The rest of the scenarios are grouped more closely, compressing the range to a factor increase of about one to eight times compared with 2000.

Primary Energy Intensities

Most of the scenarios in the literature portray a clear relationship between primary energy and GWP. In all scenarios, economic growth outpaces the increase in primary energy requirements, leading to substantial reductions in energy intensities (the ratio of primary energy requirements to GWP). This tendency across scenarios is the cumulative result of technological and structural changes. Individual technologies improve or are replaced by new ones—inefficient technologies are retired in favor of more efficient

1000

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GDP per Capita (1990 US$)

Figure 11.6. Primary energy intensity versus GDP per capita measured at market exchange rates: Regional historical developments for USA, North America (NAM), Latin America and Caribbean (LAM), Western Europe (WEU), Eastern Europe (EEU), former Soviet Union (FSU), Middle East and North Africa (MEA), Sub-Saharan Africa (AFR), centrally planned Asia and China (CPA), South Asia (SAS), other Pacific Asia (PAS), and Pacific OECD (PAO). Future global developments of energy intensities across scenarios are shown as a range (IEA 1993; World Bank 1993; Morita and Lee 1998; Nakicenovic etal. 1998).

ones. Also, the structure of the energy system and patterns of energy services change. All of these factors tend to reduce the aggregate amount of primary energy needed per unit of GWP. All other things being equal, the more rapid is the economic growth, the higher is the turnover of capital, and the greater is the resulting decline in energy intensity. These long-term relationships between energy and economic development are reflected in the majority of scenarios and are consistent with historical experience across a range of alternative development paths in different countries.

Figure 11.6 shows the historical relationship since 1970 between energy intensity and gross domestic product (GDP) per capita for the major world regions. This shorter-term historical record of development is contrasted with the experience of the United States since 1800. In all cases economic development is associated with a reduction in energy intensity; the levels of energy intensities in developing countries today are generally comparable to that of the now industrialized countries when they had the same per capita

Mvb Pathwy

1900 1950 2000 2050 2100

Figure 11.7. Global decarbonization of primary energy: Historical development and scenarios. The carbon intensities of the scenarios are shown as indexes spliced into the base year 1990 (Nakicenovic 1996; Morita and Lee 1998).

1900 1950 2000 2050 2100

Figure 11.7. Global decarbonization of primary energy: Historical development and scenarios. The carbon intensities of the scenarios are shown as indexes spliced into the base year 1990 (Nakicenovic 1996; Morita and Lee 1998).

GDP. The historical experiences illustrate that different countries and regions can follow different development paths with some persistent differences in energy intensities, even at similar levels of per capita GDP.

Global energy intensities diverge across scenarios in the literature. They are contained within a "cone" that opens from the base year 1990, into the future (Figure 11.6). The cone delineates alternative developments across scenarios, with the same general relationship that higher levels of economic development are associated with lower energy intensities. This pattern clearly illustrates the persistent inverse relationship between economic development and energy intensity, across the wide range of scenarios with numerous other differences.

Decarbonization of Primary Energy

Decarbonization denotes the declining average carbon intensity of primary energy over time. Although the decarbonization of the world's energy system is comparatively slow (0.3 percent y-1) (Figure 11.7), the trend has persisted throughout the past two centuries (Nakicenovic 1996). The overall tendency toward lower carbon intensities is due to the continuous replacement of energy sources with high carbon content, such as coal, by those with low carbon content, such as natural gas; intensities are, however, currently increasing in some developing regions. The carbon intensity at the global level has decreased by a third since 1900. This decline is primarily associated with the replacement of coal, which was the dominant energy source at the beginning of the 20th century and accounted for almost 60 percent of all primary energy during the 1920s. Oil and natural gas substituted for coal during the 20th century. Zero-carbon sources such as hydropower and nuclear energy had a much less important role in reducing carbon intensities, because their shares in total global primary energy were relatively small.

The median of all the scenarios indicates the continuation of the historical trend, with a decarbonization rate of about 0.4 percent y-1. At this rate, the global carbon intensity would decline by some 40 percent by the end of the 21st century.

All of the scenarios below the median would lead to higher rates of decarbonization. The highest rates (up to 3.3 percent y-1) occur in scenarios that envision a complete transition in the energy system away from carbon-intensive fossil fuels. Generally, these are scenarios that describe more sustainable development paths with lower energy intensities as well as significant contributions of renewables. Some of the scenarios in this low range include large shares of nuclear energy and significant decarbonization of fossil energy sources through carbon sequestration and disposal. In such scenarios, carbon is removed from fossil energy sources, primarily natural gas and coal, either pre- or postcombustion, and stored over geological timescales. The most promising storage options are depleted oil and gas fields and deep aquifers, while deep ocean storage possibilities continue to be highly controversial (Brewer, Chapter 27, this volume).

The scenarios that are most intensive in use of fossil fuels lead to practically no reduction in carbon intensity. Some of the scenarios above the median actually anticipate significant increases in carbon intensity, particularly over the next few decades. They include cases where developing countries rich in domestic coal resources, including India and China, as well as other now more developed countries, such as the United States, remain on or return to carbon-intensive development paths. Coal technologies are assumed to improve in these scenarios, leading to much cleaner and less environmentally intrusive development paths, but with extremely high GHG emissions.

Figure 11.8 illustrates the relationships between energy intensities of GWP and carbon intensities of energy across the scenarios in the literature. Scenarios that unfold horizontally are pure decarbonization cases with little structural change in the economy; scenarios that unfold vertically indicate reduction of energy intensity of economic activities, with little change in the energy system. Most scenarios stay away from these extremes and develop a fan-shaped pattern—marked by both decarbonization and declining energy intensity (Figure 11.8).

The fan-shaped graph illustrates the wide range in the policies and structures of the global energy systems among scenarios. For example, even the scenarios that achieve high levels of decarbonization can take alternative development paths. In some, decar-bonization is achieved largely through energy-efficiency improvements, while in others,

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Figure 11.8. Global decarbonization and decline of energy intensity (1990-2100). Both intensities are shown on logarithmic scales. The starting point is the base year 1990, normalized to an index (1990 = 100) for both intensities. Some of the scenarios are identified by name (Morita and Lee 1998; Nakicenovic et al. 1998).

decarbonization is mainly the result of lower carbon intensity, due to vigorous substitution of fossil energy sources.

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