Futureemission scenarios

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The starting point for the critical cascade of uncertainties is the Special Report on Emission Scenarios (SRES) by Nakicenovic and Swart, (2001). The authors develop 35 scenarios, each claimed to be internally consistent and plausible. These fall into four families of scenarios, or storylines, out of which emerge six actual scenarios used to drive the succeeding steps in the cascade. The scenario families reflect a simple matrix expressing antitheses between high economic growth and environmental sustainability in one dimension, and between global equalisation and regional differentiation in the other. Scenario family A1 emphasises rapid economic growth, with population increasing to the middle of this century, then declining. Implicit in this group of scenarios is the theme of rapid technology transfer and upward convergence between economies, leading to generally higher per capita incomes over the world as a whole and less differentiation into 'haves' and 'have-nots'. It is the most optimistic family in terms of conventionally defined global economic growth and material prosperity. Within the family, three scenarios are proposed, one with heavy dependence on fossil fuel (A1FI), one with rapid expansion of non-fossil-fuel use (A1T) and one with a balance between the two (A1B). The single A2 storyline envisages a more fragmented world with little convergence and great regional differentiation. Fertility patterns remain divergent between regions and global population growth continues. The single B1 scenario is comparable to A1 in terms of demography, but social, economic and technological changes lead to a much greater emphasis on reducing dependence on materials, improving efficiency of resource use and promoting environmental sustainability. In B2, the final scenario, the themes that characterise B1 are retained, but with a much higher level of regional differentiation and continued population growth, though at

CO2 emissions (Gt C)

CO2 concentration (ppm)

CO2 emissions (Gt C)

2000 2050 2100

More economic

More global

More environmental

Scenarios

--IS92a

700-

900-

700-

CO2 concentration (ppm)

900-

Figure 13.2 A summary of the IPCC TAR scenarios and their conversion to atmospheric concentrations in the case of CO2 and sulphate aerosols. (From IPCC TAR, 2001.)

2000 2050 2100

2000 2050 2100

SO2 emissions (Tg S)

More economic

More global

- FI: fossil-intensive

- T : non-fossil

A2

B1

SO2 emissions (Tg S)

2000 2050 2100

Figure 13.2 A summary of the IPCC TAR scenarios and their conversion to atmospheric concentrations in the case of CO2 and sulphate aerosols. (From IPCC TAR, 2001.)

2000 2050 2100

a slower rate than in A2. Figure 13.2 gives a schematic guide to the various scenarios referred in this and succeeding chapters.

Each socio-economic/demographic/technological scenario is translated into evolving emissions until the year 2100 for CO2, CH4, N2O and SO4. Figure 13.2 shows the results for all six scenarios, as well as the emission figures used in the 1992 equivalent of SRES for CO2 and SO4. The main change since 1992 has been the projections of a large but variable downturn in SO2 from the middle of the century onwards. Some divergence between the SRES emission scenarios is apparent from the beginning of the projections, but becomes greatly emphasised from around 2030 onwards.

All the scientific evidence considered in this book has very little bearing on the question of which among these scenarios is more or less likely. Present-day demographic, socio-economic, geopolitical and technological trends suggest that, barring a major reversal of current economic and demographic forces, or some major discontinuities in the form of global war, famine or disease, the mid- to higher-range emission scenarios, with strong rather than reduced regional differentiation, are the more probable. Put another way, there is as yet no reason for projecting a future in which emission scenarios A1T, B1 or B2 will prevail, without huge efforts, coordinated on a global scale and effective for curbing energy-rich life styles and fossil-fuel use in the richest nations. The Kyoto agreement (Bolin, 1998; Grubb et al., 1999) was designed to take a decisive first step in this direction, but it has had limited success. Notable is the refusal of the United States to subscribe, despite having signed the United Nations Framework Convention on Climate Change (UNFCCC), with its stated objective to stabilise greenhouse-gas concentrations at a level that prevents dangerous interference with the climate system. There is no justification for ignoring the higher-emission scenarios and their possible future consequences. At the same time, it may be unrealistic to opt for the A1F scenario without some qualifications, in view of (1) the widespread, albeit modest development of alternative-energy sources in a growing number of developed countries including the United Kingdom (Batchold, 2003), (2) the recent, but perhaps only temporary, emission reductions in at least one major developing country, China (Streets et al., 2001) and (3) the five-fold or even greater acceleration in the rate of increase in atmospheric CO2 concentrations that would be involved were the A1F scenario to unfold. If all the currently known fossil-fuel reserves were to be exhausted, with no additional attempts to capture and store emissions, CO2 would eventually reach around 1000 ppmv, according to Lenton and Cannell (2002), a figure only slightly in excess of the A1F projection for 2100. One further point to bear in mind is that ongoing land-use change could significantly add to atmospheric CO2 concentrations. In the model-based study of Gitz and Ciais (2003) replacement of forest by cultivated land tends to increase the atmospheric burden in both the short and longer term. The short-term loss arises from the release of carbon during deforestation; in the longer term there is a reduction in the turn-over time of carbon in biomass and soil, leading to shorter periods of sequestration, after deforestation. The likely size of this effect is impossible to predict in view of the degree to which it is strongly scenario and model dependent.

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