Working Group III: Mitigation

Other reports in this collection Comparison of Technology and/or Policy Measures and Assessment of Robustness

Assumed technology and/or policy options differ among models (Morita et al., 2000a). These differences are strongly dependent on the model structure. MESSAGE-MACRO, LDNE, and MARIA are dynamic optimization-type models that incorporate detailed supply-side technologies; once a constraint on CO2 emission or concentration is imposed, the optimal set of technology and/or policy measures (focusing on energy supply) is automatically selected in the model. AIM and IMAGE are recursive simulation-type models which integrate physical and land-use modules rather than focus on energy demand, so that highly detailed technology and/or policy measures are assumed for each region and time as exogenous scenarios. ASF, MiniCAM, PETRO, and WorldScan are other types of integrated models focusing on the economics of energy systems. In these models, only a carbon tax is used for the post-SRES analyses.

In order to reduce CO2 and other GHG emissions, each modelling team assumed specific technology and/or policy measures for its scenario quantification. The main reduction measures are:

  • demand reductions and/or efficiency improvements;
  • substitution among fossil fuels;
  • switch to nuclear energy;
  • switch to biomass;
  • switch to other renewables;
  • CO2 scrubbing and removal; and
  • afforestation.

Table 2.7 summarizes the contribution of these emission mitigation options and/or measures for the post-SRES scenarios. The table shows the emission reduction (in GtC) between the baseline and the mitigation and/or stabilization cases, corresponding to the first six points of the list above. For simplicity, the total ranges as well as the median value in 2100 are shown only for the 550ppmv stabilization case. As shown in Table 2.7, no single source will be sufficient to stabilize atmospheric CO2 concentrations. Across the scenarios, the contributions of demand reduction, substitution among fossil fuels, and switching to renewable energy are all relatively large. The contributions of nuclear energy, of CO2 scrubbing and removal differ significantly among the models and also across the post-SRES scenarios.

Table 2.7: Sources of emissions reduction for 550ppmv stabilization across the nine post-SRES models. Minimum-maximum and (median) at 2100 (GtC)
  A1B A1FI A1T A2 B1 B2
Substitution among fossil fuels -0.1 – 2.2
0.2 – 11.8
0.1 – 0.1
2.4 – 5.4
0.0 – 0.2
0.6 – 2.7
Switch to nuclear 0.3 – 6.4
-2.4 – 1.9
0.0 – 2.0
0.3 – 1.7
0.0 – 3.1
-0.2 – 5.1
Switch to biomass -0.8 – 1.5
-0.2 – 5.5
-0.2 – 0.3
1.1 – 3.8
0.0 – 4.3
-1.9 – 1.5
Switch to other renewables 0.1 – 2.5
0.6 – 15.1
-0.1 – 0.0
2.2 – 6.7
0.1 – 0.3
0.1 – 3.2
CO2 scrubbing and removal 0.0 – 4.7
0.0 – 23.8
0.5 – 1.6
0.0 – 5.8
0.0 – 1.1
0.0 – 3.0
Demand reduction 0.5 – 6.6
1.9 – 17.7
0.0 – 0.2
5.2 – 15.6
0.1 – 0.3
0.7 – 3.5
TOTAL reduction 7.1 – 11.9
21.7 – 30.5
0.3 – 4.4
21.7 – 26.9
0.2 –9.6
6.0 – 10.6
Note: Emission reductions are estimated by subtracting the mitigation value (in GtC) from the baseline value (in GtC) of each scenario.

With respect to the role of biofuels, it should be noted that the models assume trade in biofuels across regions; hence, biomass produced in Africa and/or South America can satisfy the fuel needs of Asia. In all mitigation scenarios, the additional role of biomass, as a mitigation option, is limited and the world supply never exceeds 400EJ/yr; this is possible because the other options (solar and/or wind, nuclear, and CO2 removal and storage) also play a key role in mitigation strategies. Table 2.8 shows the ranges in primary biomass use in 2050 in the post-SRES scenarios.

Table 2.8: Ranges of primary use of biomass in 2050 in the post-SRES scenarios (EJ)
Stabilization target A1B A1FI A1T A2 B1 B2
450ppmv 246 - 328 226 - 246 137 - 246 128 96 - 186 127 - 189
550ppmv 76 - 228 78 - 217 74 - 217 22 - 232 36 - 176 27 - 157
650ppmv 0 -180 143 -184 133 (*)   121
750ppmv (*) 131   25 - 63    
Note: As the PETRO model does not separate biomass energy from primary energy, no number is filled in (*).

To contribute to a synthesis of findings, each modelling team was asked to respond to the following questions about the policy implications of the scenarios:

  • How do technology and/or policy measures vary among different baselines for a given stabilization level?
  • How does the stabilization level affect the technology and/or policy measures used in the scenarios?
  • What packages of technology and/or policy measures are robust enough to beeffected in the different baseline worlds?

As shown in Table 2.7, high emission worlds such as A1FI, A2, and A1B require a larger introduction of energy demand reduction, switching to renewable energy, and substitution among fossil fuels, in comparison to other SRES worlds. The contribution of CO2 scrubbing and removal is largest in the A1FI stabilization scenarios, while mitigation measures in the A1T world depend mainly on a switch to nuclear power as well as carbon scrubbing and removal. Biomass energy steadily contributes across the SRES worlds and also across stabilization targets.

The following summarizes more detailed differences in technology and/or policy measures across the regions as well as the different SRES worlds:

  • The timing and the pace of the emissions reduction are particularly influenced by the region’s resource availability. Regions with large amounts of cheap fossil fuel reserves and resources (ASIA: coal; EFSU: natural gas) rely comparatively longer on fossil fuel-based power generation. In the long run the emissions mitigation measures are predominantly the result of the technology assumptions consistent with the scenario storylines. In the fossil-intensive A2 scenario, emissions reduction for 2100 in ASIA and EFSU are mainly a result of shifts to advanced fossil technologies in combination with carbon scrubbing and/or removal and increasing shares of solar-photovoltaic, and advanced nuclear technologies. For the B2 scenario, the shift towards non-fossil fuels in ASIA and EFSU is more complete, and hence, scrubbing plays a less important role. In A2 and B2, synthetic fuel production from biomass plays a key role in the ALM region. In both scenarios the emissions mitigation in the OECD region is because of shifts to wind, solar-photovoltaic, biomass, and nuclear technologies. In the OECD, fossil fuels contribute roughly 30% to the power generation, which comes predominantly from fuel cells (MESSAGE-MACRO team: Riahi and Roehrl, 2000);
  • In the 550ppmv cases, the composition of primary energy is diversified, with increased shares of various renewable energy sources, nuclear power, and natural gas. Among the renewable energy sources, photovoltaics (PV) seem to be the most promising abatement measure in the A1 and A2 scenarios, where the final energy demands grow quite substantially, while CO2 recovery and disposal measures play a very important role in the B1 and B2 scenarios. In the case of A1B and A2, PV would increase rapidly especially in the Middle East and North Africa (ALM) where PV panels could be set in wide desert areas. For the entire SRES world, methanol would be made from hydrogen (H2) and carbon monoxide (CO) through gas splitting mainly in the Former Soviet Union and Eastern Europe (EFSU) where there are plenty of natural gas resources. Wind energy production would play an important role in North America (LDNE team: Yamaji et al., 2000);
  • In the A1B and A1T worlds, expansion of biomass utilization is the major strategy, rather than nuclear power, for carbon emission control in OECD and EFSU. In the latter, biomass mainly substitutes for natural gas in public and other sectors, and a shift from coal to natural gas in the industry sector is also observed. Nuclear power is mainly used in the Asia-Pacific and ALM regions. In contrast, the B1 scenarios give very similar figures among regions, except for a small increase of biomass in the OECD region. Carbon sequestration is implemented in all regions for the purpose of carbon emission control. B2 scenarios are basically similar to those of the A1 family, except that nuclear energy and biomass are introduced in the OECD region (MARIA team: Mori, 2000);
  • In the A1 and B1 families, technology transfer to developing countries would occur with respect to renewable energy production, unconventional oil and gas exploitation, and nuclear power generation. In these worlds, there would be a large increase in biomass use in the Asia and ALM regions. Coal is mainly produced in the Asia-Pacific region. Nuclear technology is widely used in developing regions. In the A2 and B2 worlds, energy supply and use heavily depend on local energy resources because of international trade barriers. The Asia-Pacific region will rely on nuclear energy and coal, while ALM may use much renewable energy. The OECD region makes much use of advanced end-use technology and modern renewable energy technologies. Large gas resources in the EFSU region can satisfy much of the energy demand in that region (AIM team: Jiang et al., 2000);
  • The allocation of carbon “taxes” across regions based on their per capita GDP levels leads to substantial differences in levels of CO2 reductions relative to the baseline. The largest relative reductions are implemented in regions with relatively high per capita GDP growth (e.g., OECD) and regions with a relatively low cost of renewable energy (Latin America). The lowest relative reductions are achieved in regions with low per capita GDP and a relatively high cost of renewable energy (e.g., Africa) (ASF team: Sankovski et al., 2000); and
  • Assuming that there are no constraints on fuel trade, the Middle East and later the Commonwealth of Independent States (CIS) will still be major fossil fuel exporters; their revenues may decline significantly by the middle of the 21st century as a consequence of carbon mitigation measures. Parts of Africa and South America may develop into important biofuel exporters. High-income regions with limited fossil fuel resources, such as Europe and the USA, will probably be among the first to introduce high-efficiency and non-carbon technologies. This results over time in sizeable cost reductions, enabling less industrialized regions to replace their indigenous coal use by these relatively capital-intensive supply side options.

One of the major results of the post-SRES analyses is the identification of “robust climate policy options” across the different SRES worlds as well as across different stabilization targets. Most of the modelling teams have identified several such options based on their simulations. The following list summarizes the major findings:

  • Robust policies include technological efficiency improvements for both energy use technology and energy supply technology, social efficiency improvements such as public transport introduction, dematerialization promoted by lifestyle changes and the introduction of recycling systems, and renewable energy incentives through the introduction of energy price incentives such as a carbon tax (AIM, IMAGE, MARIA, MiniCAM (Pitcher, 2000), PETRO (Kverndokk et al., 2000), and WorldScan teams);
  • It would be reasonable to start with energy conservation and reforestation to cope with global warming. However, innovative supply-side technologies will eventually be required to achieve stabilization of atmospheric CO2 concentration (AIM, ASF, IMAGE, and LDNE teams);
  • Robust options across the SRES worlds are natural gas and the use of biomass resources. Innovative transitional strategies of using natural gas as a “bridge” towards a carbon-free hydrogen economy (including CO2 sequestration) are at a premium in a possible future world with low emissions (MESSAGE-MACRO, AIM, MARIA, and MiniCAM teams);
  • In all mitigation scenarios, gas combined-cycle technology bridges the transition to more advanced fossil (fuel) and zero-carbon technologies. The future electricity sector is not dominated by any single dominant technology, however, hydrogen fuel cells are assumed to be the most promising technology among all stabilization cases (MESSAGE-MACRO, IMAGE, and MiniCAM teams);
  • Climate stabilization requires the introduction of natural gas and biomass energy in the first half of the 21st century, and either nuclear energy or carbon removal and storage in the latter half of the century as the cost effective pathways. Carbon removal and storage has a role to play in high emission worlds such as A1FI and A1B for the serious or moderate targets (LDNE, MiniCAM, and MARIA teams);
  • Even in the B1 world there are very difficult decisions to be made and these may well imply the need to significantly further redirect the energy system (MiniCAM and WorldScan teams); and
  • Energy systems would still be dependent on fossil fuels at more than 20% of total primary energy over the next century, even with the stabilization of CO2 concentration (LDNE and WorldScan teams).

The post-SRES analyses supplied several other findings from individual model simulations. The AIM and the MESSAGE-MACRO teams as well as other teams found that technological progress plays a very important role in stabilization, and that knowledge transfer to developing countries is a key issue in facilitating their participation in early CO2 emission reduction. With respect to policy integration, the AIM team found that integration between climate policies and domestic policies could effectively reduce GHGs in developing regions from their baselines, especially for the next two or three decades. On the other hand, the MESSAGE-MACRO team estimated that regional air pollution control with respect to sulphur emissions tends to: (1) amplify global climate change in the medium-term perspective, and (2) accelerate the shift towards less carbon (and sulphur) intensive fuels such as renewables. The MiniCAM team concluded that agriculture and land use and energy system controls need to be linked, and that failure to do this can lead to much larger than necessary costs.

The above results are found with robust technology and/or policy measures across the SRES worlds and across different stabilization targets, and many of them are common among different modelling teams. A part of these common results can be tested by more detailed analyses of emission reduction sources, shown in Table 2.7. This table as well as time series analyses of the contribution of sources clearly show that:

  • Large and continuous energy efficiency improvements are common features of mitigation scenarios in all the different SRES worlds;
  • Introduction of low-carbon energy is also a common feature of all scenarios, especially biomass energy introduction over the next one hundred years and natural gas introduction in the first half of the 21st century;
  • Solar energy and other renewable energy sources could play an important role in climate stabilization in the latter half of the 21st century, especially for higher emission baselines or lower stabilization levels; and
  • Mitigation scenarios with reduced fossil fuel use will further decrease regional sulphur emissions and hence open up the possibility of earlier and larger climate change effects.

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