IPCC Fourth Assessment Report: Climate Change 2007
Climate Change 2007: Working Group III: Mitigation of Climate Change

11.6.4 Complementary measures for deep emission reductions

The sectoral and multi-gas studies indicate that substantial emission savings are still available at low cost (< 20 US$/tCO2), particularly from buildings (Chapter 6) and end-use efficiencies in a number of industrial sectors (Table 7.8); many governments are therefore already well embarked upon policies to exploit these low-cost opportunities. The IEA’s World Energy Outlook (IEA, 2006b, Part 2) estimates that such measures could contribute a 16% reduction below the reference level by 2030. This would be an important contribution, but clearly insufficient to get close to halting or reversing global emissions growth in the absence of price-based measures.

Innovation will also be crucial for deep reductions by mid-century and in the longer term. Some of the technologies required to deliver ongoing emission reductions out to 2050 are already commercialized, but others (such as CCS) are not (see sector chapters). Deeper emission reductions will get more and more difficult over time without accelerated innovation bringing down costs, and increasing the diversity, of low-carbon options. Achieving the mitigation scenarios indicated therefore requires adequate progress in a range of relevant industries based on low-carbon technology (Weyant, 2004; IEA, 2006b). Chapter 2 has laid out the basic principles for low-carbon innovation and Chapter 3 the long-term role of technologies in stabilization scenarios. The sectoral chapters discussed the specific technologies and Section 11.5 covered the post-TAR modelling of induced technological change. This section briefly assesses the insights relating to innovation that are relevant to transitions in the second quarter of this century.

The conceptual relationship between such innovation investments and measures relating to carbon pricing is sketched out in Figure 11.10. Most low-carbon technologies (at least for supply) are currently much more expensive than carbon-based fuels. As R&D, investment and associated learning accumulates, their costs will decline, and market scale may grow. Rising carbon prices bring forward the time when they become competitive (indeed, many such technologies might never become competitive without carbon pricing). The faster the rise in carbon prices – particularly if industry can project such increases with confidence in a clear and stable policy environment – the sooner such technologies will become competitive and the greater the overall economic returns from the initial learning investment.

Figure 11.10

Figure 11.10: Relationship between learning investments and carbon prices

Notes: The figure illustrates cost relationships for new low-carbon technology as experience and scale build over time. Initially introduction is characterized by relatively high current costs and a very small market share, and requires a high unit rate for ‘learning investment’. With increasing scale and learning, costs move towards existing, higher-carbon sources, the costs of which may also be declining, but more slowly. Rising carbon prices over time bring forward the time when the new technology may be competitive without additional support, and may greatly magnify the economic returns from the initial learning investment.

Source: Adapted with author’s permission from Neuhoff (2004).

However, the literature also emphasizes that carbon pricing alone is insufficient. Sanden and Azar (2005) argue that carbon cap-and-trade is important for diffusion – ‘picking technologies from the shelf’ – but insufficient for innovation – ‘replenishing the shelf’. Foxon (2003) emphasizes the interaction of environmental and knowledge market failures, arguing that this creates ‘systemic’ obstacles that require government action beyond simply fixing the two market failures (of climate damages and technology spillovers) independently. There is therefore general consensus in the literature that, whilst emission reduction (including pricing) mechanisms are a necessary component for delivering such innovation, they are not sufficient: efficient innovation requires even more government action.

This underlines the complexity of measures required to drive adequate innovation. On the basis of four general lessons from US technology policy, Alic et al. (2003) derive various specific conclusions for action.[20] They break them down into direct R&D funding, support for deployment, and support for education and training. However, they also underline that ‘technology policies alone cannot adequately respond to global climate change. They must be complemented by regulatory and/or energy pricing policies that create incentives for innovation and adoption of improved or alternative technologies … the technological response will depend critically on environmental and energy policies as well as technology polices.’

Philibert (2005) places climate technology policy in the context of the wider experience of US, European and IEA technology programmes and present initiatives, and discusses explicitly the international dimensions associated with globalization, export credit, diffusion, standards and explicit technology negotiations. Grubb (2004) outlines at least six different possible forms of international technology-oriented agreements that could, in principle, help to foster global moves towards lower-carbon energy structures (see Chapter 13).

The common theme in all these studies is the need for multiple and mutually supporting policies that combine technology push and pull across the various stages of the ‘innovation chain’, so as to foster more effective innovation and more rapid diffusion of low-carbon technologies, both nationally (the tax and subsidy regime for Japan discussed in 11.4.3.4, for example) and internationally. Most studies also emphasize the need for feedback enabling policy to learn from experience and experimentation – using ‘learning-by-doing’ in the process of policy development itself.

  1. ^  Their four general lessons are: (i) Technology innovation is a complex process involving invention, development, adoption, learning and diffusion; (ii) Gains from new technologies are realized only with widespread adoption, a process that takes considerable time and typically depends on a lengthy sequence of incremental improvements that enhance performance and reduce costs; (iii) Technology learning is the essential step that paces adoption and diffusion; (iv) Technology innovation is a highly uncertain process.