3 Issues related to mitigation in the long-term context

Baseline scenario drivers

Population projections are now generally lower than in the IPCC Special Report on Emission Scenarios (SRES), based on new data indicating that birth rates in many parts of the world have fallen sharply. So far, these new population projections have not been implemented in many of the new emissions scenarios in the literature. The studies that have incorporated them result in more or less the same overall emissions levels, due to changes in other driving factors such as economic growth (high agreement, much evidence) [3.2.1].

Economic growth perspectives have not changed much. There is a considerable overlap in the GDP numbers published, with a slight downwards shift of the median of the new scenarios by about 7% compared with the median in the pre-SRES scenario literature. The data suggest no appreciable change in the distribution of GDP projections. Economic growth projections for Africa, Latin America and the Middle East are lower than in the SRES scenarios (high agreement, much evidence) [3.2.1].

Baseline scenario emissions (all gases and sectors)

The resulting span of energy-related and industrial CO₂ emissions in 2100 across baseline scenarios in the post-SRES literature is very large, ranging from 17 to around 135 GtCO₂-eq (4.6-36.8 GtC)^[8], about the same as the SRES range (Figure TS.7). Different reasons may contribute to the fact that emissions have not declined despite somewhat lower projections for population and GDP. All other factors being equal, lower population projections would result in lower emissions. In the scenarios that use lower projections, however, changes in other drivers of emissions have partly offset the consequences of lower populations. Few studies incorporated lower population projections, but where they did, they showed that lower population is offset by higher rates of economic growth, and/or a shift toward a more carbon-intensive energy system, such as a shift to coal because of increasing oil and gas prices. The majority of scenarios indicate an increase in emissions during most of the century. However, there are some baseline (reference) scenarios both in the new and older literature where emissions peak and then decline (high agreement, much evidence) [3.2.2].

Figure TS.7: Comparison of the SRES and pre-SRES energy-related and industrial CO₂ emission scenarios in the literature with the post-SRES scenarios [Figure 3.8].

Note: Two vertical bars on the right extend from the minimum to maximum of the distribution of scenarios and indicate the 5^th, 25^th, 50^th, 75^th and the 95^th percentiles of the distributions by 2100.

Baseline land-related GHG emissions are projected to increase with growing cropland requirements, but at a slower rate than energy-related emissions. As far as CO₂ emissions from land-use change (mostly deforestation) are concerned, post-SRES scenarios show a similar trend to SRES scenarios: a slow decline, possibly leading to zero net emissions by the end of the century.

Emissions of non-CO₂ GHGs as a group (mostly from agriculture) are projected to increase, but somewhat less rapidly than CO₂ emissions, because the most important sources of CH₄ and N₂O are agricultural activities, and agriculture is growing less than energy use. Emission projections from the recent literature are similar to SRES. Recent non-CO₂ GHG emission baseline scenarios suggest that agricultural CH₄ and N₂O emissions will increase until the end of this century, potentially doubling in some baselines. While the emissions of some fluorinated compounds are projected to decrease, many are expected to grow substantially because of the rapid growth rate of some emitting industries and the replacement of ODS with HFCs (high agreement, medium evidence) [3.2.2].

Noticeable changes have occurred in projections of the emissions of the aerosol precursors SO₂ and NO_x since SRES. Recent literature shows a slower short-term growth of these emissions than SRES. As a consequence also the long-term ranges of both emissions sources are lower in the recent literature. Recent scenarios project sulphur emissions to peak earlier and at lower levels than in SRES. A small number of new scenarios have begun to explore emission pathways for black and organic carbon (high agreement, medium evidence) [3.2.2].

In general, the comparison of SRES and new scenarios in the literature shows that the ranges of the main driving forces and emissions have not changed very much.

GDP metrics

For long-term scenarios, economic growth is usually reported in the form of growth in GDP or gross national product (GNP). To get a meaningful comparison of the real size of economic activities over time and between countries, GDP is reported in constant prices taken from a base year.

The choice of the conversion factor, Market Exchange Rate (MER) or Purchasing Power Parity (PPP), depends on the type of analysis being undertaken. However, when it comes to calculating emissions (or other physical measures like energy), the choice between MER and PPP-based representations of GDP should not matter, since emission intensity will change (in a compensating manner) when the GDP numbers change. Thus, if a consistent set of metrics is employed, the choice of metric should not appreciably affect the final emission level. A number of new studies in the literature concur that the actual choice of exchange rates does not itself have an appreciable effect on long-term emission projections. In the case of SRES, the emissions trajectories are the same whether economic activities in the four scenario families are measured in MER or PPP.

There are studies that find some differences in emission levels between PPP and MER-based estimates. These results depend critically on convergence assumptions, among other things. In some of the short-term scenarios (with a horizon to 2030) a bottom-up approach is taken where assumptions about productivity growth and investment/saving decisions are the main drivers of growth in the models. In long-term scenarios, a top-down approach is more commonly used where the actual growth rates are more directly prescribed on the basis of convergence or other assumptions about long-term growth potentials. Different results can also be due to inconsistencies in adjusting the metrics of energy efficiency improvement when moving from MER to PPP-based calculations.

Evidence from the limited number of new PPP-based studies indicates that the choice of metric for GDP (MER or PPP) does not appreciably affect the projected emissions, when the metrics are used consistently. The differences, if any, are small compared with the uncertainties caused by assumptions on other parameters, for example, technological change. The debate clearly shows, however, the need for modellers to be more transparent in explaining conversion factors as well as taking care in making assumptions on exogenous factors (high agreement, much evidence) [3.2.1].