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Policy responses for mitigation (página 4)



Partes: 1, 2, 3, 4, 5

Historical evidence. Examining the history of existing energy technologies and the prominent role that public R&D and initial deployment have played in their development illustrates the potential effectiveness of technology policy. Extensive and prolonged public support and private markets were both instrumental in the development of all generating technologies. Military R&D, the US space programme and learning from other markets have also been crucial to the process of innovation in the energy sector. This highlights the spillovers that occur between sectors and the need to avoid too narrow an R&D focus. This experience has been mirrored in other sectors such as civil aviation and digital technologies where the source has also been military. Perhaps this is related to the fact that US public defence R&D was eight times greater than that for energy R&D in 2006 (US Federal Budget Authority). Historical R&D and deployment support has delivered the technological choices of the present with many R&D investments that may have seemed wasteful in the 1980s, such as investments in renewable energy and synfuels, now bearing fruit. The technological choices of the coming decades are likely to develop from current R&D.

Box 16.3 Development of existing technology options37

Nuclear: From the early stages of the Cold War, the Atomic Energy Commission in the US, created primarily to oversee the development of nuclear weapons, also promoted civilian nuclear power. Alic et al38 argue that by exploiting the "peaceful atom" Washington hoped to demonstrate US technological prowess and perhaps regain moral high ground after the atomic devastation of 1945. The focus on weapons left the non-defence R&D disorganised and starved of funds and failed to address the practical issues and uncertainties of commercial reactor design. The government"s monopoly of nuclear information, necessary to prevent the spreading of sensitive information, meant state R&D was crucial to development.

Gas: The basic R&D for gas turbine technology was carried out for military jet engines during World War II. Since then developments in material sciences and turbine design have been crucial to the technological innovation that has made gas turbines the most popular technology for electricity generation in recent years. Cooling technology from the drilling industry and space exploration played an important role. In the 1980s improvements came from untapped innovations in jet engine technology from decades of experience in civil aviation. Competitive costs have also been helped by low capital costs, reliability, modularity and lower pollution levels.

Wind: The first electric windmills were developed in 1888 and reliable wind energy has been available since the 1920s. Stand-alone turbines were popular in the Midwestern USA prior to centrally generated power in the 1940s. Little progress was made until the oil shocks led to further investment and deployment, particularly in Denmark (where a 30% capital tax break (1979-1989) mandated electricity prices (85% of retail) and a 10% target in 1981 led to considerable deployment) and California where public support led to extensive deployment in the 1980s. Recent renewable support programmes and technological progress have encouraged an average annual growth rate of over 28 % over the past ten years39 .

Photovoltaics: The first PV cells were designed for the space programme in the late 1950s. They were very expensive and converted less than 2% of the solar energy to electricity. Four decades of steady development, in the early phases stimulated by the space programme, have seen efficiency rise to nearly 25% of the solar energy in laboratories, and costs of commercial cells have fallen by orders of magnitude. The need for storage or ancillary power sources have held the technology back but there have been some niche markets in remote locations and, opportunities to reduce peak demand in locations where solar peaks and demand peaks coincide.

Public support has been important. A study by Norberg-Bohm40 found that, of 20 key innovations in the past 30 years, only one of the 14 they could source was funded entirely by the private sector and nine were totally public. Recent deployment support led the PV market to grow by 34% in 2005. Nemet41 explored in more detail how the innovation process occurred. He found that, of recent cost reductions, 43% were due to economies of scale, 30% to efficiency gains from R&D and learning-by-doing, 12% due to reduced silicon costs (a spillover from the IT industry).

Learning curve analysis. Learning curves, as shown in Box 9.4 and in other studies42 , show that increased deployment is linked with cost reductions suggesting that further deployment will reduce the cost of low-emission technologies. There is a question of causation since cost reductions may lead to greater deployment; so attempts to force the reverse may lead to disappointing learning rates. The data shows technologies starting from different points and achieving very different learning rates. The increasing returns from scale shown in these curves can be used to justify deployment support, but the potential of the technologies must be evaluated and compared with the costs of development.

16.5 Research, development and demonstration policies Government has an important role in directly funding skills and basic knowledge creation for science and technology At the pure science end of the spectrum, the knowledge created has less direct commercial application and exhibits the characteristics of a "public good". At the applied end of R&D, there is likely to be a greater emphasis on private research, though there still may be a role for some public funding.

Governments also fund the education and training of scientists and engineers. Modelling for this review suggests that the output of low-carbon technologies in the energy sector will need to expand nearly 20-fold over the next 40-50 years to stabilise emissions, requiring new generations of engineers and scientists to work on energy-technology development and use. The prominent role of the challenge of climate change may act as an inspiration to a new generation of scientists and spur a wider interest in science.

R&D funding should avoid volatility to enable the research base to thrive. Funding cycles in some countries have exhibited "roller-coaster" variations between years, which have made it harder for laboratories to attract, develop, and maintain human capital. Such volatility can also reduce investors" confidence in the likely returns of private R&D. Kammen43 found levels changed by more than 30% in half the observed years. Similarly it may be difficult to expand research capacity very quickly as the skilled researchers may not be available. Governments should seek to avoid such variability, especially in response to short-term fuel price fluctuations. The allocation of public R&D funds should continue to rely on the valuable peer review process and this should include post-project evaluations and review to maximise the learning from the research. Research with clear objectives but without over-commitment to narrow specifications or performance criteria can eliminate wasteful expenditures44 and allow researchers more time to apply to their research interests and be creative.

Governments should seek to ensure that, in broad terms, the priorities of publicly funded institutions reflect those of society. The expertise of the researchers creates an information asymmetry with policymakers facing a challenge in selecting suitable projects. Arms-length organisations and expert panels such as research-funding bodies may be best placed to direct funding to individual projects.

Three types of funding are required for university research funding.

• Basic research time and resources for academic staff to pursue research that interests them.

• Research programme funding (such as research councils) that directs funding towards important areas.

• Funding to encourage the transfer of knowledge outside the institution. The dissemination of information encourages progress to be applied and built on by other researchers and industry and ensures that it not be unnecessarily duplicated elsewhere.

Research should cover a broad base and not just focus on what are currently considered key technologies, including basic science and some funding to research the more innovative ideas45 to address climate change. Historical examples of technological progress when the research was not directed towards specific economic applications (such as developments in nanotechnology, lasers and the transistor) highlight the importance of open-ended problem specification. There must be an appropriate balance between basic science and applied research projects46 . Increases in energy R&D (as discussed in the final section of this chapter) can be complemented by increased funding for science generally. The potential scale of increase in basic science will vary by country depending on their current level and research capabilities47 .

There may also be a case for demonstration funding to prove viability and reduce risk. An example of this is the UK DTI"s "Wave and Tidal Stream Energy Demonstration Scheme" that will support demonstration projects undertaken by private firms. This has many features to encourage the projects and maximise learning through provision of test site and facilities and systematic comparison of competing alternatives. Governments can help such projects through providing infrastructure. Demonstration projects are best conducted or at least managed by the private sector.48

Energy storage is worthy of particular attention Inherent uncertainty on fruitful areas of research ensures governments should be cautious against picking winners. However, some areas of research suggest significant potential through a combination of probability of success, lead-times and global reward for success. Priorities for scientific progress in the energy sector should include PV (silicon and non-silicon based), biofuel conversion technologies, fusion, and material science.

As markets expand, all the key low carbon primary energy sources will run into constraints. Nuclear power will be confined to base-load electricity generation unless energy storage is available to enable its energy to follow loads and contribute to the markets for transport fuels. Intermittent renewable energy forms with backup generation will face the same problem. Electricity generation from fossil fuels with carbon capture and storage will likewise be unable to enter the transport markets unless improved and lower cost forms of hydrogen storage or new battery technology are developed. Solar energy can in theory meet the world"s energy needs many times over, but will, like energy from wind, waves and tides, eventually depend on the storage problem being solved.

The analysis of the costs of climate change mitigation in Chapter 9 provides further confirmation of the need for an expansion of RD&D activities in energy storage technologies. A failure to develop such technologies will inevitably increase the costs of mitigation once low- emission options for electricity generation are exploited. In contrast, success in this area will allow low-emission sources to provide energy in other sectors, such as transport. Current R&D and demonstration efforts on hydrogen production and storage along with other promising options for storing energy (such as advanced battery concepts) should be increased. This should include research on devices that convert the stored energy, such as the fuel cell.

In the case of applied energy research, partnership between the public and private sectors is key It is important that public R&D leverages private R&D and encourages commercialisation. Ultimately the products will be brought into the market by private firms who have a better knowledge of markets, and, so it is important that public R&D maintains the flow of knowledge by ensuring public R&D complements the efforts of the private sector.

The growth and direction of private R&D efforts will be a product of the incentives for low- emission investments provided by the structure of markets and public policies. Public R&D should aim to complement, not compete, with private R&D, generally by concentrating on more fundamental, longer-term possibilities, and by sharing in the risks of some larger-scale projects such as CCS. In many areas the private sector will make research investments without public support, as has been the case recently on advanced biofuels (see Box 16.4).

Box 16.4 Second generation biofuels Cellulosic ethanol is a not-yet-commercialized fuel derived from woody biomass. In his 2006 State of the Union address, Bush praised the fuel's potential to curb the nation's "addiction to foreign oil". A joint study by the Departments of Agriculture and Energy49 concludes that U.S. biomass feedstocks could produce enough ethanol to displace 30 percent of the nation's gasoline consumption by 2030.

In May 2006, Goldman Sachs & Co became the first major Wall Street firm to invest in the technology. Goldman Sachs & Co invested more than $26 million in Iogen Corp., an Ottawa- based company that operates the world's first and only demonstration facility that converts straw, corn stalks, switchgrass and other agricultural materials to ethanol. Iogen hopes to begin construction on North America's first commercial cellulosic ethanol plant next year.

In September 2006 Richard Branson announced plans to invest $3 billion in mitigating climate change. Some of this will be invested in Virgin Fuels, which will develop biofuels including cellulosic ethanol.

The OECD50 found that economic growth was closely linked to general private R&D, not public R&D, but that public R&D plays a vital role in stimulating private spending. There is evidence51 from the energy sector that patents do track public R&D closely, which suggests that they successfully spur innovation and private sector innovation. R&D collaboration between the public and private-sector is one way of reducing the cost and risks of R&D.

The public sector could fund private sector research through competitive research funding, with private sector companies bidding for public funds as public organisations currently do from research councils. Prizes to reward innovation can be used to encourage breakthroughs. Historically they have proved very successful but defining a suitable prize can be problematic52 . An alternative approach, as suggested for the pharmaceutical sector, is to commit to purchase new products to reward those that successfully innovate.53

Box 16.5 Public-private research models – UK Energy Technologies Institute54

In 2006, the UK launched the Energy Technologies Institute (ETI). It will be funded on a 50:50 basis between private companies and the public sector with the government prepared to provide £500 million, creating the potential for a £1 billion institute over a minimum lifetime of ten years.

The institute will aim to accelerate the pace and volume of research directed towards the eventual deployment of the most promising research results. ETI will work to existing UK energy policy goals including a 60% reduction in emissions by 2050.

The ETI will select, commission, fund, manage and, where appropriate, undertake research programmes. Most investment will focus on a small number of key technology areas that have greatest promise for deployment and contributing to low-emission secure energy supplies.

16.6 Deployment policy A wide range of policies to encourage deployment are already in use. In addition to direct emissions pricing through taxes and trading and R&D support, there are strong arguments in favour of supporting deployment in some sectors when spillovers, lock-in to existing technologies, or capital market failures prevent the development of potentially low- cost alternatives. Without support the market may never select those technologies that are further from the market but may nevertheless eventually prove cheapest. Policies to support deployment exist throughout the world including many non-OECD countries55 . China and India have both encouraged large-scale renewable deployment in recent years and now have respectively the largest and fifth largest renewable energy capacity worldwide56 .

There is some deployment support for clean technologies in most developed countries. The mechanism of support takes many forms though the costs are generally passed onto the consumer. The presence of a carbon price reduces the cost and requirement for deployment support. Deployment support is generally a small component of price when spread across all consumption (see Box 16.7) but does add to the impact of carbon pricing on electricity prices. Policymakers should consider the impact of deployment support on energy prices over time. Consumers will be paying for the development of technologies that benefit consumers in the future.

Box 16.6 Examples of existing deployment incentivesFiscal incentives: including reduced taxes on biofuels in the UK and the US; investment tax credits.

Capital grants for demonstrator projects and programmes: clean coal programmes in the US; PV "rooftop" programmes in the US, Germany and Japan; investments in marine renewables in the UK and Portugal; and numerous other technologies in their demonstration phase.

Feed-in tariffs are a fixed price support mechanism that is usually combined with a regulatory incentive to purchase output: examples include wind and PVs in Germany; biofuels and wind in Austria; wind and solar schemes in Spain, supplemented by "bonus prices"; wind in Holland.

Quota based schemes: the Renewable Portfolio Standards in twenty three US States; the vehicle fleet efficiency standards in California • Tradable quotas: the Renewables Obligation and Renewable Transport Fuels Obligation in the UK.

Tenders for tranches of output (the former UK Non Fossil Fuel Obligation) with increased output prices subsidised out of the revenues from a general levy on electricity tariffs.

Subsidy of the infrastructure costs of connecting new technologies to networks.

Procurement policies of public monopolies: This was the approach historically of the public monopolies in electricity for purchase of nuclear power throughout the OECD; it is currently the approach in China. It is often combined with regulatory agreements to permit recovery of costs, soft loans by governments, and, in the case of nuclear waste, government assumption of liabilities.

Procurement policies of national and local governments: these include demonstrator projects on public buildings; use of fuel cells and solar technologies by defence and aerospace industries; hydrogen fuel cell buses and taxis in cities; energy efficiency in buildings.

The deployment mechanisms described in Box 16.6 can be characterised as price or quantity support, with some tradable approaches containing elements of both. The costs of these policies are generally passed directly on to consumers though some are financed from general taxation. When quantity deployment instruments are not tradable, the policymaker should consider whether there are sufficient incentives to strive for cost reductions and whether the supplier can profit from passing an excessive cost burden onto the consumer. If the level of a price deployment instrument is too low no deployment will occur, while if it is too high large volumes of deployment will occur with financial rewards for participants which are essentially government created rents. With tradable quantity instruments, the market is left to determine the price, usually with tradable certificates between firms. This does lead to price uncertainty. If the quantity is too high, bottlenecks may lead to a high cost. If the quantity is too low, there may not be sufficient economies of scale to reduce the cost.

Both sets of instruments have proved effective but existing experience favours price-based support mechanisms. Comparisons between deployment support through tradable quotas and feed-in tariff price support suggest that feed-in mechanisms achieve larger deployment at lower costs57 . Central to this is the assurance of long-term price guarantees. The German scheme, as described in Box 16.7 below, provides legally guaranteed revenue streams for up to twenty years if the technology remains functional. Whilst recognising the importance of planning regimes for both PV and wind, the levels of deployment are much greater in the German scheme and the prices are lower than comparable tradable support mechanisms (though greater deployment increases the total cost in terms of the premium paid by consumers). Contrary to criticisms of the feed-in tariff, analysis suggests that competition is greater than in the UK Renewable Obligation Certificate scheme. These benefits are logical as the technologies are already prone to considerable price uncertainties and the price uncertainty of tradable deployment support mechanisms amplifies this uncertainty. Uncertainty discourages investment and increases the cost of capital as the risks associated with the uncertain rewards require greater rewards.

Box 16.7 Deployment support in Germany Feed-in tariffs have been introduced in Germany to encourage the deployment of onshore and offshore wind, biomass, hydropower, geothermal and solar PV58 . The aim is to meet Germany"s renewable energy goals of 12.5% of gross electricity consumption in 2010 and 20% in 2020. The policy also aims to encourage the development of renewable technologies, reduce external costs and increase the security of supply.

Each generation technology is eligible for a different rate. Within technologies the rate varies depending on the size and type. Solar energy receives between €0.457 to 0.624 per kWh while wind receives €0.055 to 0.091per kWh. Once the technology is built the rate is guaranteed for 20 years. The level of support for deployment in subsequent years declines over time by 1% to 6.5% each year with the rate of decline derived from estimated learning curves59 .

In 2005 10.2% of electricity came from renewables (70% supported with feed-in tariffs) the Federal Environment Ministry (BMU) estimate that the current act will save 52 million tonnes on CO2 in 2010. The average level of feed-in tariff was €0.0953 per kWh in 2005 (compared to an average cost of displaced energy of €0.047 kWh). The total level of subsidy was €2.4 billion Euro at a cost shared all consumers of €0.0056 per kWh (3% of household electricity costs)60 . There are an estimated 170,000 people working in the renewable sector with an industry turnover of €8.7 billion.61

The 43.7 TWh of electricity covered by the feed in tariffs was split mostly between wind (61%), biomass (19%) and hydropower (18%). It has succeeded in supporting several technologies. Solar accounted for 2% (0.2% of total electricity) with an average growth rate of over 90% over the last four years. Despite photovoltaic"s low share Germany has a significant proportion of the global market with 58% of the capacity installed globally in 2005 (39% of the total installed capacity) and 23% of global production.62

Regulation can also be used to encourage deployment, for example by reducing uncertainty and accelerating spillover effects, and may be preferable in certain markets (see Chapter 17 for details). Performance standards encourage uptake and innovation in efficient technologies by establishing efficiency requirements for particular goods, in particular encouraging incremental innovation Alternatively, technology specific design standards can be targeted directly at the cleanest technologies by mandating their application or banning alternatives.

There are already considerable sums of money spent on supporting technology deployment. It is estimated that $10 billion63 was spent in 2004 on renewable deployment, around $16 billion is spent each year supporting existing nuclear energy and around $6.4billion64 is spent each year supporting biofuels. The total support for these low-carbon energy sources is thus $33 billion each year. Such sums are dwarfed by the existing subsidies for fossil fuels worldwide that are estimated at $150 billion to 250 billion each year. All these costs are generally paid by the consumer.

Technology-neutral incentives should be complemented by focused incentives to bring forward a portfolio of technologies Policy frameworks can be designed to treat support to all low-carbon technologies in a "technology-neutral" way. The dangers of public officials "picking winners" should point to this as the starting point in most sectors. Markets and profit orientated decisions, where the decision maker is forced to look carefully at cost and risk are better at finding the likely commercial successes. However, the externalities, uncertainties and capital market problems in some sectors combine with the urgency of results and specificity of some of the technological problems that need to be solved when tackling climate change, all point to the necessity to examine the issues around particular technologies and ensure that a portfolio develops.

The policy framework of deployment support could differentiate between technologies, offering greater support to those further from commercialisation, or having particular strategic or national importance. This differentiation can be achieved several ways, including technology-specific quotas, or increased levels of price support for certain technologies. Policies to correct the carbon externality (taxes / trading) are, and should continue to be, technology neutral. Technology neutrality is also desirable for deployment support if the aim is to deliver least cost reductions to meet short-term targets, since the market will deliver the least-cost technology.

However, as has already been discussed, the process of learning means that longer- established technologies will tend to have a price advantage over newer technologies, and untargeted support will favour these more developed technologies and bring them still further down the learning curve. This effect can be seen in markets using technology-neutral instruments: in the USA, onshore wind accounts for 92% of new capacity in green power markets65 .

This concentration on near-to-market technologies will tend to work to the exclusion of other promising technologies, which means that only a very narrow portfolio of technologies will be supported, rather than the broad range which Part III of this report shows are required. This means technology neutrality may be cost efficient in the short term, but not over time.

Most deployment support in the electricity generation sector has been targeted towards renewable and nuclear technologies. However, significant reductions are also expected from other sources. As highlighted in Box 9.2 carbon capture and storage (CCS) is a technology expected to deliver a significant portion of the emission reductions. The forecast growth in emissions from coal, especially in China and India, means CCS technology has particular importance. Failure to develop viable CCS technology, while traditional fossil fuel generation is deployed across the globe, risks locking-in a high emissions trajectory. The demonstration and deployment of CCS is discussed in more detail in Chapter 24. Stabilising emissions below 550ppm CO2e will require reducing emissions from electricity generation by about 60%66 . Without CCS that would require a dramatic shift away from existing fossil-fuel technologies.67

Policies should have a clear review process and exit strategies, and governments must accept that some technologies will fail. Uncertainty over the economies of scale and learning-by-doing means that some technological failures are inevitable. Technological failures can still create valuable knowledge, and the closing of technological avenues narrows the investment options and increases confidence in other technologies (as they face less alternatives). The Arrow-Lind theorem68 states that governments are generally large enough to be risk neutral as they are large enough to spread the risk and thus have a role to play in undertaking riskier investments. It is not a mistake per se to buy insurance or a hedge that later is not needed and that is in many ways a suitable analogy for fostering a wider portfolio of viable technologies than the market would do by itself69 .

Credibility is also important to policy design. Policies benefit from providing clear, bankable, signals to business. There is a role for monitoring and for a clear exit strategy to prevent excessive costs and signal the ultimate goal of these policies: competition on a level playing field. A good example has been the Japanese rebates in the "Solar Roofs" programme, which have declined gradually over time, from 50% of installed cost in 1994 to 12% in 2002 when the scheme ended.

Alternative approaches can also help spur the deployment of new innovations. For example, extension services, the application of scientific research and new knowledge to agricultural practices through farmer education, had a significant impact on the deployment of new crop varieties during the Green Revolution. Also, organisations such as the Carbon Trust in the UK, Sustainable Development Technologies Canada, established by governments but independent of them to allow the application of business acumen, have proved successful in encouraging investment in the development and demonstration of clean technologies. They can play an important role at each stage of the technology process, from R&D to ensuring their widespread deployment once they have become cost effective. They have proved especially successful in acting as a "stamp of approval" that spurs further venture capital investment. Finding niche markets and building these into large-scale commercialisation opportunities is a key challenge for companies with promising low carbon technologies. These organisations are at the forefront of identifying niche markets for commercialisation of new technologies and promoting public-private investment in deployment.

16.7 Other supporting policies Other policies have an important impact on the viability of technologies. There are many other policy options available to governments that can affect technology deployment and adoption. Governments set policies such as the planning regime and building standards. How these are set can have an important impact on the adoption of new technologies. They can constrain deployment either directly or indirectly by increasing costs. Regulations can stifle innovation, but if well designed they can drive innovation. Depending how these are set, they can act as a subsidy to low-emission alternative technologies or to traditional fossil fuels. Setting the balance is difficult, since their impacts are hard to value. But they must be considered since they can have an important effect on the outcome.

• The intellectual property regime can act as an incentive to the innovator, but the granting of the property right can also slow the dissemination of technological progress and prohibit others from building on this innovation. Managing this balance is an important challenge for policymakers.

• Planning and licensing regulations have proven a significant factor for nuclear, wind and micro-generation technologies. Planning can significantly increase costs or, in many cases, prevent investments taking place. Local considerations must be set against wider national or global concerns.

• It is important how governments treat risks and liabilities such as waste, safety or decommissioning costs for nuclear power or liabilities for CO2 leakage from CCS schemes. Governments can bear some of these costs but, unless suppliers and ultimately consumers are charged for this insurance, it will be a subsidy.

• Network issues are particularly important for energy and transport technologies. The existing transport network and infrastructure, especially fuel stations, is tailored to fossil fuel technologies.

• Intermittent technologies such as wind and solar may be charged a premium if they require back-up sources. How this is treated can directly affect economic viability, depending on the extent of the back-up generation required and the premium charged.

• Micro-generation technologies can sell electricity back to the grid and do not incur the same distribution costs and transmission losses as traditional much larger sources. The terms under which such issues are resolved has an important impact on the economics of these technologies. Commercially proven low-carbon technologies require regulatory frameworks that recognise their value, in terms of flexibility and modularity70 , within a distributed energy system. Regulators should innovate in response to the challenge of integrating these technologies to exploit their potential, and unlock the resultant opportunities that arise from shifting the generation mix away from centralised sources.

• Capacity constraints may arise because of a shortage in a required resource. For example, there may be a shortage of skilled labour to install a new technology.

• There are other institutional and even cultural barriers that can be overcome. Public acceptability has proven an issue for both wind and nuclear and this may also be the case for hydrogen vehicles. Consumers may have problems in finding and installing new technologies. Providing information of the risks and justification of particular technologies can help overcome these barriers.

16.8 The scale of action required Extending and expanding existing deployment incentives will be key Deployment policies encourage the private sector to develop and deploy low-carbon technologies. The resulting cost reductions will help reduce the cost of mitigation in the future (as explained in Chapter 10). Consumers generally pay the cost of deployment support in the form of higher prices. Deployment support represents only a proportion of the cost of the technology as it leverages private funds that pay for the market price element of the final cost.

It is estimated that existing deployment support for renewables, biofuels and nuclear energy is $33 billion each year (see Section 16.6). The IEA"s Energy Technology Perspectives71 looks at the impact of policies to increase the rate of technological development. It assumes that $720billion of investment in deployment support occurs over the next two to three decades. This estimate is on top of an assumed carbon price (whether through tax, trading or implicitly in regulation) of $25 per tonne of CO2. If the IEA figure is assumed to be additional to the existing effort, it suggests an increase of deployment incentives of between 73% and 109%, depending on whether this increase is spread over two or three decades.

The calculations shown in Section 9.8 include estimates of the level of deployment incentives required to encourage sufficient deployment of new technologies (consistent with a 550ppm CO2e stabilisation level). The central estimates from this work are that the level of support required will have to increase deployment incentives by 176% in 2015 and 393% in 202572 .

These estimates are additional to an assumed a carbon price at a level of $25 per tonne of CO2.

At this price the abatement options are forecast to become cost effective by 2075 so the level of support tails off to zero by this time. If policies lead to a price much higher than this before the technologies are cost effective then less support will be required. Conversely if no carbon price exists the level of support required will have to increase (by a limited amount initially but by much larger amounts in the longer term). While most of this cost is expected to be passed on to consumers, firms may be prepared to incur a proportion of this learning cost in order to gain a competitive advantage.

Such levels of support do represent significant sums but are modest when compared with overall levels of investment in energy supply infrastructure ($20 trillion up to 203073 ) or even estimates of current levels of fossil-fuel subsidy as shown in the graph below.74

Figure 16.7 Estimated scale of current and necessary global deployment support

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The level of support required to develop abatement technologies depends on the carbon price and the rate of technological progress, which are both uncertain. It is clear from these numbers that the level of support should increase in the decades to come, especially in the absence of carbon pricing. Based on the numbers above, an increase of 2-5 times current levels over the next 20 years should help encourage the requisite levels of deployment though this level should be evaluated as these uncertainties are resolved.

The scale is, however, not the only issue. It is important that this support is well structured to encourage innovation at low cost. A diverse portfolio of investments is required as it is uncertain which technologies will prove cheapest and constraints on individual technologies will ensure that a mix is necessary. Those technologies that are likely to be the cheapest warrant more investment and these may not be those that are the currently the lowest cost. This requires a reorientation of public support towards technologies that are further from widespread diffusion.

Some countries are already offering significant support for new technologies but globally this support is patchy. Issues on coordinating deployment support internationally to achieve the required diversity and scale are examined in Chapter 24.

Global energy R&D funding is at a low level and should rise Though benefits of R&D are difficult to evaluate accurately a diverse range of indicators illustrate the benefits of R&D investments. Global public energy R&D support has declined significantly since the 1980s and this trend should reverse to encourage cost reductions in existing low-carbon technologies and the development of new low-carbon technological options. The IEA R&D database shows a decline of 50% in low-emission R&D75 between 1980 and 2004. This decline has occurred while overall government R&D has increased significantly76 . A recent IEA publication on RD&D priorities77 strongly recommends that governments consider restoring their energy RD&D budgets at least to the levels seen, in the early 1980s. This would involve doubling the budget from the current level of around $10 billion78 . This is an appropriate first step that would equate to global levels of public energy R&D around $20 billion each year.

Figure 16.8 Public energy R&D in IEA countries79

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The directions of the effort should also change. A generation ago, the focus was on nuclear power and fossil fuels, including synthetic oil fuels from gas and coal, with comparatively few resources expended on conservation and renewable energy. Now the R&D efforts going into carbon capture and storage, conservation, the full range of renewable energy technologies, hydrogen production and use, fuel cells, and energy storage technologies and systems should all be much larger.

A phased increase in funding, within established frameworks for research priorities, would allow for the expansion in institutional capacity and increased expertise required to use the funding effectively. A proportion of this public money should target be designed to encourage private funds, as is proposed for the UK"s Energy Technology Institute (see Box 16.5).

Private R&D should rise in response to market signals. Private energy R&D in OECD countries fell in recent times from around $8.5bn at the end of the 1980s to around $4.5bn in 200380 . Significant increases in public energy R&D and deployment support combined with carbon pricing should all help reverse this trend and encourage an upswing in private R&D levels.

This is not just about the total level of support. How this money is spent is crucial. It is important that the funding is spread across a wide range of ideas. It is also important that it is structured to provide stability to researchers while still providing healthy competition. There should be rigorous assessment of these expenditures to ensure that they maintained at an appropriate level. Approaches to encourage international co-operation to achieve these goals are explored in Chapter 24.

16.9 Conclusions This chapter explores the process of innovation and discovers that externality from the environmental impact of greenhouse gas emissions exacerbates existing market imperfections, limiting the incentive to develop low-carbon technologies. This provides a strong case for supporting the development of new and existing low-carbon technologies, particularly in a number of key climate change sectors. The power of market forces is the key driver of innovation and technical change but this role should be supplemented with direct public support for R&D and, in some sectors, policies designed to create new markets. Such policies are required to deliver an effective portfolio of low-carbon technologies in the future.

References For an excellent overview of innovation theory and its application in the case of climate change see Foxon, T J (2003), "Inducing innovation for a low-carbon future: drivers, barriers and policies" (full reference and link below). A good exploration of the barriers within the electricity generation sector can be found in Neuhoff, K. (2005), "Large-Scale Deployment of Renewables for Electricity Generation".

A good overview of innovation in the climate change context and technology policy can be found in Grubb (2004), "Technology Innovation and Climate Change Policy: an overview of issues and options" and a thorough exploration of the market failures and evidence on policy instruments can be found in both Jaffe, Newell and Stavins publications listed below. An excellent review of existing US based R&D policies and their effectiveness is Alic, Mowery and Rubin (2003), "U.S. Technology and Innovation Policies: Lessons for Climate Change". Newell and Chow also provide some valuable insights reviewing the literature on the effectiveness of energy R&D policy.

Aghion, P., N. Bloom, R. Blundell, R. Griffith and P. Howitt (2002). 'Competition and innovation: an inverted U relationship', NBER Working Paper No. 9269, London: UCL.

Alic, J., D. Mowery, and E. Rubin (2003): 'U.S. technology and innovation policies: Lessons for climate change', Virginia: Pew Center on Global Climate Change, available from http://www.pewclimate.org/docUploads/US%20Technology%20%26%20Innovation%20Polici es%20%28pdf%29%2Epdf Amin, A-L. (2000): 'The power of networks – renewable electricity in India and South Africa', unpublished thesis, SPRU, University of Sussex.

Anderson, D., C. Clark, T. Foxon, et al. (2001): 'Innovation and the environment: challenges and policy options for the UK'. A report for the UK Economic and Social Science Research Council. Imperial College London, Centre for Energy Policy and Technology (ICEPT) and the Fabian Society, London: Imperial College.

Arrow, K. and R. Lind (1970): 'Uncertainty and the evaluation of public investment decisions', American Economic Review, 60: 364-78 Barreto, L. and G. Klaassen (2004): 'Emissions trading and the role of learning-by-doing spillovers in the "bottom-up" energy-systems ERIS model'. International Journal of Energy Technology and Policy (Special Issue on Experience Curves).

Bird, L. and B. Swezey (2005): 'Estimates of new renewable energy capacity serving U.S. green power markets' available from http://www.eere.energy.gov/greenpower/resources/tables/new_gp_cap BMU (Germany"s Federal Ministry for the Environment, Nature Conservation and Nuclear Safety). (2006a): 'What electricity from renewable energies costs', available from www.bmu.de/files/pdfs/allgemein/application/pdf/electricity_costs.pdf BMU (2006b): Renewable energy sources in figures – national and international development available from http://www.bmu.de/files/english/renewable_energy/downloads/application/pdf/broschuere_ee _zahlen_en.pdf Butler, L. and K. Neuhoff (2005): 'Comparison of feed in tariff, quota and auction mechanisms to support wind power development', Cambridge Working Papers in Economics 0503, Faculty of Economics (formerly DAE), Cambridge: University of Cambridge.

Chow, J. and R. Newell (2004): 'A retrospective review of the performance of energy R&D RFF discussion paper' [in draft] available from:

http://www.energycommission.org/files/finalReport/VI.1.e%20- %20Retrospective%20of%20Energy%20R&D%20Perf.pdf Deutch, J. (2005): 'What should the Government do to encourage technical change in the energy sector?', MIT Joint Program on the Science and Policy of Global Change Report No.120. available from http://mit.edu/globalchange/www/MITJPSPGC_Rpt120.pdf Department of Trade and Industry 2003): 'Innovation report – competing in the global economy: the innovation challenge' available from http://www.dti.gov.uk/files/file12093.pdf E4tech. (2006): 'UK carbon reduction potential from technologies in the transport sector', prepared for the UK Department for Transport and the Energy Review team, available from http://www.dti.gov.uk/files/file31647.pdf European Community (2005): 'The support of electricity from renewable energy sources', Communication from the Commission available from http://ec.europa.eu/energy/res/biomass_action_plan/doc/2005_12_07_comm_biomass_electri city_en.pdf Fouquet D., C. Grotz, J. Sawin and N. Vassilakos (2005): 'Reflections on a possible unified eu financial support scheme for renewable energy systems (res): a comparison of minimum- price and quota systems and an analysis of market conditions'. Brussels and Washington, DC: European Renewable Energies Federation and Worldwatch Institute.

Foxon, T. J. (2003):. 'Inducing innovation for a low-carbon future: drivers, barriers and policies', London: The Carbon Trust, available from http://www.thecarbontrust.co.uk/Publications/publicationdetail.htm?productid=CT-2003-07 Freeman, C. (1992): 'The economics of hope', New York, Pinter Publishers.

Gibbs, W. (2006): 'Plan B for energy', Scientific American, September 2006 issue, New York: Scientific American.

Grubb, M. (2004): 'Technology innovation and climate change policy: an overview of issues and options', Keio Economic Studies. Vol.XLI. no.2. available from http://www.econ.cam.ac.uk/faculty/grubb/publications/J38.pdf International Energy Agency (2006): 'Energy technology perspectives – scenarios & strategies to 2050', Paris: OECD/IEA.

International Energy Agency (in press): 'World Energy Outlook 2006', Paris: OECD/IEA. International Rice Research Institute (2006): 'Climate change and rice cropping systems:

Potential adaptation and mitigation strategies', available from www.sternreview.org.uk Jaffe, A., R. Newell and R. Stavins (2004): 'A tale of two market failures', RFF Discussion paper, available from http://www.rff.org/Documents/RFF-DP-04-38.pdf Jaffe, A., R. Newell and R. Stavins. (2003): 'Technological change and the environment', Handbook of Environmental Economics K. Mäler and J. Vincent (eds.), Amsterdam: North- Holland/Elsevier Science pp. 461-516 Kammen, D.M. and R. Margolis (1999): 'Evidence of under-investment in energy R&D in the United States and the impact of federal policy', Energy Policy, Oxford: Elsevier.

Kammen, D.M. (2004): 'Renewable energy options for the emerging economy: advances, opportunities and obstacles. Background paper for 'The 10-50 Solution: Technologies and Policies for a Low-Carbon Future' Pew Center & NCEP Conference, Washington, D.C., March 25-26, 2004, available from http://rael.berkeley.edu/old-site/kammen.pew.pdf Kammen, D.M. and G.F. Nemet. (2005): 'Real numbers: reversing the incredible shrinking energy R&D budget', Issues in Science Technology, 22: 84 – 88 Kremer, M. and R. Glennerster (2004): 'Strong medicine: creating incentives for pharmaceutical research on neglected diseases', Princeton: Princeton University Press.

Nemet, G. F. (in press): 'Beyond the learning curve: factors influencing cost reductions in photovoltaics'. Energy Policy, Oxford: Elsevier.

Neuhoff, K. (2005): 'Large-scale deployment of renewables for electricity generation', Oxford Review of Economic Policy', Oxford University Press, 21(1): 88-110, Spring.

Newell R. C. and N.E Wilson (2005): 'Technology prizes for climate change mitigation, resources for the future discussion paper #05-33', available from http://www.rff.org/rff/Documents/RFF-DP-05-33.pdf Norberg-Bohm, V. and J. Loiter (1999): 'Public roles in the development of new energy technologies: The case of wind turbines'. Energy Policy, Oxford: Elsevier.

Norberg-Bohm, V. (2000): 'Creating incentives for environmentally enhancing technological change: lessons from 30 years of U.S. energy technology policy'. Technological Forecasting and Social Change 65: 125-148, available from http://bcsia.ksg.harvard.edu/publication.cfm?program=CORE&ctype=article&item_id=222 Norse D. (2006): "Key trends in emissions from agriculture and use of policy instruments", available from www.sternreview.org.uk OECD (2005): 'Innovation in the business sector working paper 459' Paris: OECD, available from http://www.olis.oecd.org/olis/2005doc.nsf/43bb6130e5e86e5fc12569fa005d004c/5d1216660b 7d83dcc12570ce00322178/$FILE/JT00195405.PDF OECD (2006): 'Do we have the right R&D priorities and programmes to support energy technologies of the future'. 18th Round Table on Sustainable Development background paper Paris: OECD, available from http://www.oecd.org/dataoecd/47/9/37047380.pdf Pindyck, A.K. and R.S. Dixit (1994): 'Investment under uncertainty' Princeton, NJ: University Press.

Ragwitz, M. and C. Huber (2005): 'Feed-in systems in Germany and Spain and a comparison', Germany: Fraunhofer Institut für Systemtechnik und Innovationsforschung.

REN21 Renewable Energy Policy Network, (2005): 'Renewables 2005 Global Status Report'. Washington, DC: Worldwatch, available from http://www.ren21.net/globalstatusreport/RE2005_Global_Status_Report.pdf REN 21. (2006): 'Renewables Global Status Report: 2006 update', Washington, DC: Worldwatch, available from http://www.ren21.net/globalstatusreport/download/RE_GSR_2006_Update.pdf Scotchmer, S. (1991):' Standing on the shoulders of giants: cumulative research and the patent law', Journal of Economic Perspectives 5(1): 29-41, Winter. Reprinted in The Economics of Technical Change (1993): Mansfield, E. and E. Mansfield, (eds.), Cheltenham: Edward Elgar Publishing.

Taylor, M., E. Rubin and G. Nemet (2006): 'The role of technological innovation in meeting California"s greenhouse gas emissions targets', available from http://calclimate.berkeley.edu/3_Innovation_and_Policy.pdf US Departments of Agriculture and Energy (2005): 'Biomass as feedstock for a bioenergy and bioproducts industry: the technical feasibility of a billion-ton annual supply', available from http://feedstockreview.ornl.gov/pdf/billion_ton_vision.pdf NOTAS:

1 DTI (2003)

2 Freeman (1992)

3 Aghion et al (2002): Monopolists do not have competitive pressures to innovate while intense competition means firms may lack the resource or extra profit for the innovator may be competed away too quickly to be worthwhile.

4 R,D&D (Research, Development and Demonstration) can be used for this but it can lead to confusion over the final D as some of the literature uses deployment or diffusion in the same acronym.

5 Grubb (2004)

6 For an excellent overview of innovation theory see Foxon (2003)

7 The learning rate is the cost reduction for a doubling of production and this requires much more deployment after significant levels of investment.

8 Scotchmer (1991)

9 Barreto and Klaassen (2004)

10 The agreement on Trade Related Intellectual Property Rights (TRIPs) is an international treaty administered by the World Trade Organization which sets down minimum standards for most forms of intellectual property regulation within all WTO member countries.

11 Taylor, Rubin and Nemet (2006)

12 Anderson et al (2001); Jaffe, Newell and Stavins (2004) and (2003)

13 This is consistent with the ACT scenarios p86 IEA, 2006 which would also require eliminating land use change emissions to put us on a path to stabilising at 550ppm CO2e 14 Alic, Mowery and Rubin (2003)

15 Page 35: OECD, (2006)

16 There are doubts as to the accuracy of the data and the IEA"s general view is that private energy R&D is considerably higher than public energy R&D (though this still represents a significant share).

17 Page 33-37: OECD (2006)

18 Source: IEA R&D database http://www.iea.org/Textbase/stats/rd.asp Categories covered broken down in IEA total Figure 16.8 19 OECD countries Page 32: OECD (2006)

20 Source Page 35 OECD (2006); For US evidence see Kammen and Nemet (2005)

21 Neuhoff (2005).

22 Source: REN21 (2005) which cites; UNEP & IEA. (2002). Reforming Energy Subsidies. Paris. www.uneptie.org/energy/publications/pdfs/En-SubsidiesReform.pdf Also Johansson, T. & Turkenburg, W. state in (2004). Policies for renewable energy in the European Union and its member states: an overview. Energy for Sustainable Development 8(1): 5-24.that "at present, subsidies to conventional energy are on the order of $250 billion per year" and $244 billion per annum between 1995 and 1998 (34% OECD) in Pershing, J. and Mackenzie (2004)

Removing Subsidies.Leveling the Playing Field for Renewable Energy Technologies. Thematic Background Paper. International Conference for Renewable Energies, Bonn (2004)

23 WEO, (in press)

24 Amin (2000)

25 There are exceptions in the case of biofuels with many countries offering incentives through tax incentives.

26 Intelligent infrastructure uses information to encourage efficient use of transport systems. http://www.foresight.gov.uk/Intelligent_Infrastructure_Systems/Index.htm 27 E4tech, (2006)

28 Norse (2006).

29 Box 25.4 provides further examples of sustainable farming practices.

30 IRRI (2006).

31 Pindyck and Dixit (1994)

32 In this figure the policy encourage learning but firms may be prepared to undertake investments in anticipation of technological progress or carbon price incentives.

33 Weak demand-side policies risk wasting R&D investments see Norberg-Bohm and Loiter (1999) and Deutch (2005)

34 Source GE press release May 2006:

http://home.businesswire.com/portal/site/ge/index.jsp?ndmViewId=news_view&newsId=20060517005223&newsLang =en&ndmConfigId=1001109&vnsId=681 35 Kammen and Margolis (1999)

36 When public expenditure limits private expenditure by starving it of potential resources such as scientists OECD (2005)

37 Alic, Mowery and Rubin (2003)

38 Alic, Mowery and Rubin (2003)

40 Norberg-Bohm (2000)

41 Source: Nemet, in press 42 For an example Taylor, Rubin and Nemet (2006)

43 Kammen (2004)

44 Newell and Chow (2004)

45 For some examples, see Gibbs (2006)

46 Newell and Chow (2004)

47 In 2004 the UK Government published a ten-year Science and Innovation Investment Framework, which set a challenging ambition for public and private investment in R&D to rise from 1.9% to 2.5% of UK GDP, in partnership with business; as well as the policies to underpin this. An additional £1 billion will be invested in science and innovation between 2005-2008, equivalent to real annual growth of 5.8% and to continue to increase investment in the public science base at least in line with economic growth. http://www.dti.gov.uk/science/science- funding/framework/page9306.html 48 Newell and Chow (2004)

49 US Departments of Agriculture and Energy (2005)

50 OECD (2005)

51 Kammen and Nemet (2005)

52 Newell and Wilson (2005)

53 Kremer and Glennerster (2004)

54 http://www.dti.gov.uk/science/science-funding/eti/page34027.html 55 Page 20 REN 21 Renewables global status report 2005 – See page 20 REN 21 (2005)

56 Figures from 2005 – excluding large scale hydropower. Page 6 REN 21 (2006)

57 Butler and Neuhoff (2005); EC (2005); Ragwitz, and Huber (2005); Fouquet et al (2005)

58 Originally introduced in 1991 with the Electricity Feed Act this was replaced in 2000 with the broader Act on Granting Priority to Renewable Energy Sources (Renewable Energy Sources Act) and amended in 2004 http://www.ipf-renewables2004.de/en/dokumente/RES-Act-Germany_2004.pdf 59 Small hydropower does not decline and is guaranteed for 30 years and large hydropower only 15 years.

60BMU (2006a)

61 BMU (2006b)

62 http://www.iea-pvps.org/isr/index.htm 63 Deployment share of figure page 16 REN 21, 2005 grossed up to global figure based on IEA deployment figures. Nuclear figure from same source.

64 Based on global production of 40 billion litres and on an average support of £0.1 per litre and a PPP exchange rate of $1.6 to £1 65 Bird and Swezey (2005)

66 This is consistent with the IEA ACT scenarios see Box 9.7 67 For more on CCS see Boxes 9.2 and 24.8 and Section 24.3 68 Arrow and Lind (1970)

69 Deutch (2005)

70 Small-scale permits incremental additions in capacity unlike large technologies such as nuclear generation.

71Page 58, IEA (2006)

72 See papers by Dennis Anderson available at www.sternreview.org.uk 73 IEA (in press)

74 In this graph mid points in the fossil fuel subsidy range is used in and the IEA increase made over a 20 year period.

75 For countries available includes renewables, conservation and nuclear. The decline is 36% excluding nuclear.

76 OECD R&D database shows total public R&D increasing by nearly 50% between 1988 and 2004 whilst public energy R&D declined by nearly 20% over the same period.

77 Page 19 OECD (2006)

78 2005 figure Source: IEA R&D database http://www.iea.org/Textbase/stats/rd.asp 79 Source: IEA Energy R&D Statistics 80 Page 35, OECD (2006)

17 Beyond Carbon Markets and Technology

Key Messages Policies to price greenhouse gases, and support technology development, are fundamental to tackling climate change. However, even if these measures are taken, barriers and market imperfections may still inhibit action, particularly on energy efficiency.

These barriers and failures include hidden and transaction costs such as the cost of the time needed to plan new investments; lack of information about available options; capital constraints; misaligned incentives; as well as behavioural and organisational factors affecting economic rationality in decision-making.

These market imperfections result in significant obstacles to the uptake of cost-effective mitigation, and weakened drivers for innovation, particularly in markets for energy efficiency measures.

Policy responses which can help to overcome these barriers in markets affecting demand for energy include:

• Regulation: Regulation has an important role, for example in product and building markets by: communicating policy intentions to global audiences; reducing uncertainty, complexity and transaction costs; inducing technological innovation; and avoiding technology lock-in, for example where the credibility of carbon markets is still being established.

• Information: Policies to promote: performance labels, certificates and endorsements; more informative energy bills; wider adoption of energy use displays and meters; the dissemination of best practice; or wider carbon disclosure help consumers and firms make sounder decisions and stimulate more competitive markets for more energy efficient goods and services.

• Financing: Private investment is key to raising energy efficiency. Generally, policy should seek to tax negative externalities rather than subsidise preferable outcomes, and address the source of market failures and barriers. Investment in public sector energy conservation can reduce emissions, improve public services, fostering innovation and change across the supply chain and set an example to wider society.

Careful appraisal, design, implementation and management helps minimise the cost and increase the effectiveness of regulatory, information and financing measures. Energy contracting can reduce the costs of raising efficiency through economies of scale and specialisation.

Fostering a shared understanding of the nature and consequences of climate change and its solutions is critical both in shaping behaviour and preferences, particularly in relation to their housing, transport and food consumption decisions, and in underpinning national and international political action and commitment.

Governments cannot force this understanding, but can be a catalyst for dialogue through evidence, education, persuasion and discussion. And governments, businesses and individuals can all help to promote action through demonstrating leadership.

17.1 Introduction Chapters 14, 15 and 16 have outlined the arguments, and appropriate policies, for establishing well-functioning carbon markets and encouraging technological research, development and diffusion. These are necessary to provide incentives and enable mitigation responses by households and firms. However, alone, they are not sufficient to elicit the necessary scale of investment and behavioural responses from households and firms due to the presence of failures and barriers in many relevant markets.

These obstacles are outlined in Section 17.2, in particular in relation to actions and investments for energy saving (although the framework is broadly applicable to other aspects of mitigation such as fuel switching). The significant untapped energy efficiency potential which exists, for example, in the buildings, transport, industry, agriculture and power sectors provides evidence of the impact of these failures and barriers.

Sections 17.3 to 17.5 outline the role of regulation, information and financing policies in responding to obstacles to energy efficiency:

• Regulation: such as forward-looking standards stimulate innovation by reducing uncertainty for innovators; encourage investment by increasing the costs and commercial risks of inaction for firms; and reduce technology costs by facilitating scale economies. In some respects regulation involves the creation of an implicit carbon price; • Information: encourages efficient consumption and production decisions by raising awareness of the full energy costs and climate impacts; evidence and guidance on how to assess options and reduce energy bills can explicitly shape the direction and priorities for innovation; • Financing: can accelerate the uptake of energy efficiency in both private and public sector.

Section 17.6 outlines issues relating to policy delivery. Section 17.7 discusses the role of public policy, information, education and discussion in influencing the perceptions and attitudes of individuals, firms and communities towards both adopting environmentally responsible behaviour and co-operating to reduce the impacts of climate change.

17.2 Market Failures and Responses to Incentives Behaviour is driven by a number of factors, not just financial costs and benefits.

For the most part, investment decisions in energy-using technologies rest on the balance of financial costs and benefits facing an individual or firm: for example, how much additional investment is required, what is the (opportunity) cost of capital and, in comparison, how much energy is the investment expected to save?

However, consumers and firms frequently do not make energy efficiency investments that appear cost-effective.1 The IEA estimate that unexploited energy efficiency potential offers the single largest opportunity for emissions reductions, with major potential across all major end uses and in all economies. For example, energy efficiency accounts for between 31% and 53% of CO2 emissions reductions by 2050 under the accelerated technology scenario (see Chapter 9 for a discussion of sources and costs of mitigation). 2

It is difficult to explain low take up of energy efficiency as purely a rational response to investment under uncertainty.3 This implies the existence of one or more of a potentially wider set of costs, market failures, or "barriers"4 to "rational" behaviour and motivation. These fall into three main groups:5

• Financial and "hidden" costs and benefits; • Multiple objectives, conflicting signals, or, information and other market failures; • Behavioural and motivational factors.

These are illustrated in the Figure 17.1 below. Standard economic theory of rational decision- making under uncertainty is important in understanding each. However, moving down this list, systems and behavioural theories of decision-making are progressively more relevant.

Figure 17.1 Barriers to and drivers for energy efficiency uptake6

Monografias.com

Note: CSR is Corporate Social Responsibility

An assessment of the case for action has to take into account the existence of "hidden" costs and benefits The primary driver of much investment in energy-using technologies is the balance of financial costs and benefits facing an individual or firm. However, accounting for "hidden" costs, such as those associated with researching different options, taking time off work to wait in for tradesmen, or the opportunity cost of devoting managerial time to efficiency projects is required for an assessment of the full range of costs and benefits.7 These hidden costs may be counter-balanced by wider benefits such as reduced risk exposure to energy price volatility, or reputational benefits from demonstrating environmental responsibility.

Hidden or transaction costs are difficult to measure. One study found search and information costs of energy efficiency measures of between 3% and 8% of total investment costs.8 Box 17.1 below summarises research highlighting the likelihood of significant transaction costs associated with energy efficiency measures. In general, these wider costs are expected to have most significant impact among small and medium-level energy users such as households, non-energy intensive and particularly small firms, as well as the public sector.

Box 17.1 Estimating the Costs of Energy Savings Joskow and Marron (1992) undertook a study of the costs of information and particularly investment programs undertaken by energy suppliers designed to reduce demand among residential, commercial and industrial customers in the US. The authors identified a tendency for studies to underestimate the costs of actions to save energy,9 in particular:

• Supplier transaction costs: full accounting for all administrative costs was likely to increase the cost per kWh saved by 10% to 20%. Supplier administration costs were likely to exceed 30% of the total for commercial and industrial programs; • Customer transaction costs and "free riding": customer transaction costs varied from close to zero to close to 100% of the direct investment costs across the programmes sampled. "Free riding"10 was considered a significant risk particularly among the heaviest energy users within any target group. It was estimated that full accounting of these factors was likely to increase costs of demand side management programmes by about 25% to 50%; • Energy saving measurement issues: The study identified significant methodological issues estimating energy savings given diverse, dynamic patterns of customer demand and limited availability of baseline information. In addition, they identified a tendency for widely used ex post engineering based forecasts to significantly overstate economic savings. Overall, accurate measurement of energy savings was considered likely to increase estimated costs by about 50%.

Individuals and firms are not always aware of the full costs and benefits of energy conservation, are capital constrained, or do not have sufficient incentives to invest.

Reliable, accessible and easily understandable information is important in making consumers and firms aware of the full lifetime costs and benefits of an economic decision, and hence supporting good decision-making. Whilst there are information difficulties in many or most markets, they may be particularly powerful in relation to energy efficiency measures.

Capital and/ or asset market failures also inhibit action. For example, a lack of available capital prevents people investing in more energy efficient processes which typically have higher upfront costs (but are cheaper overall when evaluated over a longer period). Restricted access to capital is especially common among poor households and small firms, particularly in developing countries.

Incentive failures restrict the effectiveness of price instruments. An example in the buildings sector is the "landlord-tenant" problem in which landlords do not invest in the energy efficiency of their asset, because tenants benefit from lower energy bills, and more efficient capital typically does not command sufficiently higher rents.

Individuals and firms are not always able to make effective decisions involving complex and uncertain outcomes. Social and institutional norms and expectations strongly influence decision-making, although these norms are not immutable.

Some economists have suggested that people use simple decision rules when faced with complexity, uncertainty or risk.11 For example, many people are unable to calculate the long- run value of energy savings, or have difficulties determining appropriate responses to risks and uncertainties around future energy costs or the potential impacts of climate change. As a result, individuals and firms commonly make decisions which simply meet their needs, rather than undertaking complex analysis to determine the best possible decision.12

Shared social and institutional norms are important determinants of behaviour.13 Individuals and firms behave habitually and in response to social customs and expectations. This leads to "path dependency", which limits their responses to policies designed to raise efficiency (or encourage fuel switching). However, these norms change over time in response to a whole range of factors, including the influence of the media and action by governments. Developing and encouraging a shared concept of what responsible behaviour is, and of the consequences of irresponsible actions, is therefore an important aspect of policy (see Section 17.7).

17.3 Policy responses: Regulation and Standards, Direct Controls Regulatory measures are less efficient and flexible than market mechanisms in the context of perfect markets, but can be an efficient response to the challenge of irremovable or unavoidable imperfections.

This section discusses the economic rationale for different types of regulatory policy instruments. As Chapter 14 discussed, regulatory measures are generally less efficient than market mechanisms when applied to perfect markets. However, the existence of market failures and barriers outlined in the previous section mean that there are circumstances in which standards and regulations have an important role to play.

Regulatory measures may be appropriate either instead of, or complementary to, tax or trading instruments, and can be more effective and efficient in a number of important circumstances, in particular to:

• Reduce the complexity faced by consumers or firms, by restricting or removing the availability of inefficient (or polluting) technologies, for example through banning of Chloroflourocarbons (or CFC"s) in cooling systems; • Cut the transaction costs associated with investments, through measures, for example by simplifying planning rules relating to the installation of micro-generation technologies; • Overcome barriers to the transmission of incentives throughout the supply chain, for example, agreements with cable and satellite television providers have resulted in significant improvements in the efficiency of licensed "set top" boxes; • Stimulate competition and innovation, by signaling policy intentions, reducing uncertainty and increasing scale in markets for outputs of technological innovation; • Promote efficiency through strategic coordination of key markets, for example by reducing long-run transport demand through integrated land-use planning and infrastructure development; • Overcome practical constraints on policymakers to imposing the appropriate explicit carbon price,14 for example where this may be politically difficult to achieve or administratively expensive to implement directly through markets; • Avoid capital stock "lock in", particularly in markets which are subject to lengthy capital replacement cycles, for example buildings and power sectors.15 This may be important where the credibility of carbon markets is still being established (issues discussed in Chapter 15).

Regulatory approaches, in contrast with market mechanisms, place a value on reducing greenhouse gas emissions implicitly rather than explicitly and can help reduce obstacles associated with information or other market failures. This value can be calculated by dividing the cost of the measure (to firms, consumers and regulators) by the estimated savings in greenhouse gas emissions. From the point of view of maximizing efficiency losses, it is important that the implied value of carbon, at the margin, is broadly the same whether market mechanisms or regulatory measures are used.

Performance standards help to limit energy demand by removing inefficient products from the market, and promoting mass diffusion of more efficient alternatives.

Performance standards establish requirements to achieve particular levels of energy efficiency or carbon intensity without prescribing how they are delivered. This can take the form of a minimum standard for a particular type of good, or a requirement on their average performance (commonly known as a "fleet averages").16

Standards encourage the removal of poorly performing equipment from the market completely, or improve availability and uptake of more efficient alternatives. In addition, by projecting the future levels of performance which will be required, standards have the potential to encourage innovation towards the production of more efficient products: for example, US federal energy efficiency standards on room air conditioner and gas water heaters are estimated to have elicited energy efficiency improvements of approximately 2% per annum.17

The overall costs of regulation depend on the precise policy context. It is likely that performance standards induce the creation and adoption of new technologies although at some real opportunity cost.18 Nevertheless, there are opportunities to promote efficiency at very low, or even negative cost, for example in certain product markets. Box 17.2 shows examples of effective performance based regulations. Section 17.6 outlines issues relating to design and implementation of performance standards.

Box 17.2 Successful Performance Standards Programmes Buildings: Building codes have been applied in many different countries.19 In California, they are estimated to have saved approximately 10,000 GWh of electricity roughly equal to 4% of annual electricity use in 2003.20 Studies of codes applied in Massachusetts and Colorado in have also demonstrated their potential to deliver energy saving.21 In the UK, building regulations are expected to yield a cumulative saving of 1.4 MtC02 per year in 2010.22 The EU Commission established a framework to realize an estimated cost-effective savings potential of around 22% of present consumption in buildings across the EU by 2010 as part of the European Energy Performance of Buildings Directive. In China, regulations are estimated to apply to buildings with a floor space of approximately 500 million square meters (among a total of approximately 40 billion nationwide) and have saved 36 MtCO2.23

Appliances: Since the introduction of federal standards by the US Department of Energy in 1978, total government programme expenditure is equivalent to US$2 per household. This is estimated to have delivered US$1,270 per household of net-present-value savings to the U.S. economy during the lifetimes of the products affected. Projected annual residential carbon reductions in 2020 due to these appliance standards are approximately 37 MtC02, an amount roughly equal to 9% of projected US residential carbon emissions in 2020.24

China first introduced appliance standards in 1989 and expanded their application rapidly during the 1990"s to include, for example: refrigerators, fluorescent ballasts and lamps, and room air-conditioners. By 2010, energy savings are estimated to reach 33.5 TWh, or about 9% of China's residential electricity. This is equivalent to a CO2 emission reduction of 11.3MtC02.25 A more recent study highlighted the potential for significant energy savings in the longer term from more stringent performance standards on three major residential end uses: household refrigeration, air-conditioning, and water heating.26

Transport: Japan"s Top Runner scheme, a leading programme of fleet averages in which future average performance requirements are based on current best available technologies, applies to a range of energy using products.27 It is estimated to have delivered energy savings on diesel passenger vehicles of 15% between 1995 and 2005 (and 7% on diesel freight vehicles). By 2010, it is expected to deliver energy savings on gasoline passenger vehicles of 23% (and 13% on passenger freight vehicles).28

In response to the introduction of Corporate Average Fuel Economy (CAFE) standards in the USA in 1975, the average fuel economy of new cars almost doubled and that of light trucks increased by 55% from 1975 to 1988.29 Without these efficiency improvements it is estimated that the US car and light truck fleet would have consumed an additional 2.8 million barrels of gasoline per day in the year 2000 (about 14% of 2002 consumption levels).30 However, the average rated fuel economy of new cars and light trucks combined declined from a high of 25.9 miles per gallon in 1987 to 23.9 miles per gallon in 2002, partly because of the shift from cars towards less efficient sport utility vehicles, pick-up trucks and minivans (which were classified as cargo transport under CAFE standards).

Design standards are inflexible, but can create scale economies for strategically important technologies.

Design standards mandate, or prohibit, the use of a particular technology. For example, CFC gases were prohibited in refrigerators in favour of alternative coolants, following the Montreal Protocol in 1987 and the establishment of a strong causal link with ozone depletion. Design standards and prohibitions are inflexible measures and, as such, risk being inefficient relative to performance standards or market mechanisms.

However, their application may be appropriate where a particular technological solution is highly preferable (or undesirable in the case of prohibitions) in the short term, where it is considered imperative to accelerate "pull through" and create scale economies for a particular technology in the medium or longer term, or where alternative measures have proved unsuccessful. The need for medium term "pull" through, for example, is likely to apply in the context of certain carbon capture and storage technologies since coal is a particularly damaging source of GHG"s while it is likely to be widely used in power markets in a number of countries on grounds of cost and energy security (see Chapters 16 and 24 for details).

Urban design and land use planning regulations have the potential to facilitate a less energy intensive society, while balancing a range of wider economic and social objectives.

Planning rules and regulations balance a complex range of economic, social, and environmental objectives. However, their design and implementation can have important implications for mitigating climate change and also has the potential to influence the resilience to the impacts of climate change, for example, in the management of flood risks or water scarcity (these issues are examined in Part 5 of the report).

Achieving planning permission is often an important transaction cost when installing renewable energy technologies, such as wind turbines or solar panels, or energy conservation measures such as solar water heaters. This applies to both large-scale commercial as well as microgeneration installations (see Box 17.3 below).

Box 17.3 Microgeneration Technologies Microgeneration technologies produce thermal and/or electrical energy. Examples include small-scale wind, solar, hydro or combined heat and power installations, as well as heat pumps and solar water heaters. According to the Energy Saving Trust, micro-generation could supply 30-40% of UK electricity demand by 2050.31

Deployment of microgeneration capacity has the potential to reduce the carbon intensity of industrial, commercial, public as well as residential buildings and developments. In addition, it can reduce energy wastage compared to centralised systems.32 Greater uptake could be driven by: consumers, energy suppliers and firms selling energy services, and the implementation of private wire networks by planners and developers (see Box 17.9 on Woking).

However, many of the technologies are currently expensive relative to the delivered price of conventional energy sources. Enabling investors to sell excess electricity at the real-time market price, and subject to distribution or other charges reflecting limited demand on low voltage networks, is key to their cost effectiveness: the use of smart meters in microgeneration installations is an important enabler.33 Appropriate regulatory frameworks for energy markets and distribution networks are also important to achieving a level playing field.

Incentives to consumers and energy suppliers could accelerate the reduction of technology costs and promote diffusion. Finally, relaxation of planning rules also has the potential to reduce transaction costs and promote network effects through heightened awareness of these technologies.

Spacial and strategic planning can affect patterns of energy consumption. Higher-density urban environments, for example, typically consume less energy for transport and in buildings. In addition, land use controls such as restrictions on the availability and pricing of parking spaces, the use of pedestrian zones and parks, and land use zonal strategies (including congestion charging), have the potential to support integrated public transport to reduce the use of private motor vehicles.

Higher energy prices and rising congestion require central and municipal planners to develop mass transit systems to cope with inner city and suburban traffic such as: bus rapid transit, urban trams and relatively cheap light railway systems, in addition to subways for larger, higher density metropolitan centres. Such systems lead to large gains in energy efficiency and reduced emissions as passengers transfer from private cars to public transport.

The development of Dongtan in China provides an important example of the potential for sustainable urban development across the rapidly urbanising transition and developing economies of the world (see Box 17.4).

Box 17.4 Dongtan, Eco-City, Shanghai Dongtan is situated on Chongming Island off the coast of Shanghai. This rural area is undergoing a rapid economic transformation into an "eco city", facilitated by the construction of the Shanghai Yangtze River Tunnel bridge, which began in 2004, linking this region directly to the Shanghai conurbation.

Project engineers at Arup are working with Shanghai Industrial Investment Company to develop and construct Dongtan, an 86-square kilometer project, into a prosperous city which achieves a stable balance between economy, society and the environment. The city is being developed in phases but is expected to have a population of 25,000 by 2010 and around 80,000 after 2020, growing to a total of several hundred thousands in the longer term.

Dongtan will have highly energy efficient buildings powered by renewable energy sources including wind, solar and biofuels. Its energy intensity will be reduced through the use of passive energy systems: for example by making full use of natural sunlight to light public and private spaces or by varying the heights of buildings to reduce heating and cooling arising from adverse weather conditions. In addition, its waste will be recycled and composted.

Chinese policy makers and planners have been impressive in scaling up best practice to help achieve their objective to reduce the ratio of energy demand to output by 20% over 5 years. In the case of Dongtan, a high-speed rail link to Shanghai is planned, while the city itself is being designed in a compact, inter-linked way, supported by mixed patterns of land use, and a network of pedestrian and cycle routes, in order to reduce the demand for private motorised transport (and associated infrastructure costs).34

17.4 Policy Responses: Information policy Information policies can achieve a number of objectives.

Well-designed information policies can:

• Provide people with a fuller picture of the economic and environmental consequences of their actions; • Stimulate and provide the framework for market innovation and competition in environmentally friendly goods and services, for example through performance indicators and labels; • Reduce the transaction costs associated with investments, by providing information on the energy use characteristics of different products or processes; • Prompt people to take responsible action, by informing them about the wider implications of their choices and by highlighting public policy priorities.

Information policies take a number of forms. This section discusses a few generic types and their potential market applications including: labelling and certification, billing and metering, and policies to disseminate best practice.

Labels, certificates and endorsements raise the visibility of energy costs in investment decisions, promote innovation in product markets, and support procurement initiatives.

The energy use, costs and environmental consequences of purchasing decisions commonly have low visibility, particularly when compared to the purchase price of a good.35 Where such labels do exist, they can have a significant impact on consumer behaviour: organic certification and the FAIRTRADE mark are two examples (see Section 17.7 discussion of preferences for environmentally and socially responsible production and consumption).

In the field of energy efficiency, labels, certificates and endorsements support more rational purchasing decisions, by allowing people to make comparisons between competing goods on the basis of their operating cost and environmental impact. They also make it cheaper and easier for firms or the public sector to implement sustainable procurement policies.

Box 17.5 highlights a number of successful schemes. These vary in design, and include labels giving comparative information on energy use, and endorsements which state that a product meets a particular standard.

There are considerable opportunities for broader or more stringent application of performance and endorsement labels in key product areas such as: domestic lighting, consumer electronics, white goods, electric motors, boilers, air conditioning units, and office equipment.36 Biogas is an example of an agricultural product that could have value as a renewable substitute for fossil fuels; establishing product standards supported by labelling can allow consumer demand to help to create this market.

The cost and regulatory burden of such measures should be taken into account when designing them; Section 17.6 outlines key principles for effective design and management. Such measures may be much more powerful if they are applied at an international level. The issues involved in this are discussed in Chapter 24.

Partes: 1, 2, 3, 4, 5
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