This paper analyzes the potential contribution of carbon capture and storage (CCS) technologies to greenhouse gas emissions reductions in the U.S. electricity sector.  Focusing on capture systems for coal-fired power plants until 2030, a sensitivity analysis of key CCS parameters is performed to gain insight into the role that CCS can play in future mitigation scenarios and to explore implications of large-scale CCS deployment.  By integrating important parameters for CCS technologies into a carbon-abatement model similar to the EPRI Prism analysis (EPRI, 2007), this study concludes that the start time and rate of technology diffusion are important in determining the emissions reduction potential and fuel consumption for CCS technologies. 

Comparisons with legislative emissions targets illustrate that CCS alone is very unlikely to meet reduction targets for the electric-power sector, even under aggressive deployment scenarios.  A portfolio of supply and demand side strategies will be needed to reach emissions objectives, especially in the near term.  Furthermore, the breakdown of capture technologies (i.e., pre-combustion, post-combustion, and oxy-fuel units) and the level of CCS retrofits at pulverized coal plants also have large effects on the extent of greenhouse gas emissions reductions.

In this new working paper PESD research affiliate Danny Cullenward studies the required rates of growth and capital investments needed to meet various long-term projections for CCS. Using the PESD Carbon Storage Database as a baseline, this paper creates four empirically-grounded scenarios about the development of the CCS industry to 2020. These possible starting points (the scenarios) are then used to calculate the sustained growth needed to meet CO2 storage estimates reported by the IPCC over the course of this century (out to 2100).

Carbon capture and storage (CCS) is a promising technology that might allow for significant reductions in CO2 emissions. But at present CCS is very expensive and its performance is highly uncertain at the scale of commercial power plants. Such challenges to deployment, though, are not new to students of technological change. Several successful technologies, including energy technologies, have faced similar challenges as CCS faces now. In this paper we draw lessons for the CCS industry from the history of other energy technologies that, as with CCS today, were risky and expensive early in their commercial development. Specifically, we analyze the development of the US nuclear-power industry, the US SO2-scrubber industry, and the global LNG industry.

We focus on three major questions in the development of these analogous industries. First, we consider the creation of the initial market to prove the technology: how and by whom was the initial niche market for these industries created? Second, we look at how risk-reduction strategies for path-breaking projects allowed the technology to evolve into a form so that it could capture a wider market and diffuse broadly into service. Third, we explore the "learning curves" that describe the cost reduction as these technologies started to capture significant market share.

Our findings suggest that directly applying to CCS the conventional wisdom that is prevalent regarding the deployment and diffusion of technologies can be very misleading. The conventional wisdom may be summarized as: "Technologies are best deployed if left in the hands of private players"; "Don't pick technology winners" or "Technology forcing is wrong"; and "Technology costs reduce as its cumulative installed capacity increases". We find that none of these readily applies when thinking about deployment of CCS.

Through analyzing the development the analogous industries, we arrive at three principal observations:  

• First, government played a decisive role in the development of all of these analogous technologies. Much of the early government role was to provide direct backing for R&D work and demonstration projects that validated the technological concepts. For example, the US government directly supported for over two decades most of the basic science and engineering research in both SO2 scrubbers and nuclear power. Most of the demonstration projects were significantly underwritten by government as well; the Japanese government was the principal backer of LNG technology through its promises to buy most of the world's LNG output over many years. Direct government support created the niche opportunities for these technologies.
• Second, diffusion of these technologies beyond the early demonstration and niche projects hinged on the credibility of incentives for industry to invest in commercial-scale projects. In each of the historical cases, government made a shift in its support strategy as the technology diffused more widely. In the early phase (when commercial uncertainties were so high that businesses found it extremely risky to participate in more than small, isolated projects) success in achieving technology diffusion required a direct role for government. But as uncertainties about the technology's performance reduced and operational experience accumulated, direct financial support became less important, and indirect instruments to lower commercial risk rose in prominence. Those instruments included tax breaks, portfolio/performance standards, purchase guarantees, and low-interest-rate loans linked to specific commercial-scale investments. It is conceivable that such incentives could have been supplied by non-governmental institutions, such as large firms or industry associations, but the three analogs point strongly to a governmental role-perhaps because only government action was viewed as credible. (In the United States, many of the key decisions to support new technologies were crafted at the state level, such as through rate base decisions to allow utilities to purchase nuclear plants.)
• Third, the conventional wisdom that experience with technologies inevitably reduces costs does not necessarily hold. Risky and capital-intensive technologies may be particularly vulnerable to diffusion without accompanying reductions in cost. In fact, we find the opposite of the conventional wisdom to be true for nuclear power in the US (1960-1980) and global LNG (1960-1995). Costs increased as cumulative installed capacity increased. A very rapid expansion of nuclear power plants in the US around 1970 led to spiraling costs, as the industry had no chance to pass lessons from one generation of investment to the next-a fact evident, for example, in the failure to standardize design and regulation that would allow firms to exploit economies of scale. For natural gas liquefaction plants, costs stayed high for decades due to a market structure marked by little competition among technology suppliers and the presence of a single dominant customer (Japanese firms organized by the Japanese government) willing to pay a premium for safety and security of supply. The same attributes that allowed LNG to expand rapidly-namely, promises of assured demand made credible by the singular backing of the Japanese state-were also a special liability as the technology struggled to compete in other markets. The experience with SO2 scrubbers was more encouraging-costs declined fairly promptly once industrial-scale investment was under way. But that happened only after sufficient clarity on technological performance and capability of FGD systems had been established. What followed was a strict performance standard-in the form of a government mandate, imposed by environmental regulators-that effectively picked FGD as a technology winner. The guaranteed market for FGD led to serious investment, innovations, and learning-by-doing cost reductions. We do not argue that this technology-forcing approach was economically efficient but merely underscore that rates of diffusion of FGD technology akin to what is imagined for CCS technology today were possible only under this technology-forcing regulatory regime.

As CCS commercialization proceeds, policymakers must remain mindful that cost reduction is not automatic-it can be derailed especially by non-competitive markets, unanticipated shifts in regulation, and unexpected technological challenges. At the same time, there may be some inevitable tradeoffs, at least for a period, between providing credible mechanisms to reduce commercial risk, such as promises of assured demand for early technology providers, and stimulating market competition that can lead to lower costs. History suggests that government-backed assurances are essential to creating the market for capital-intensive technologies; yet those very assurances can also create the context that makes it difficult for investors to feel the pressure of competition that, over successive generations of technology, leads to learning and lower costs.

We are also mindful that our history here-drawn on the experience of three technologies that have been successful in obtaining a substantial market share-is a biased one. By looking at successes we are perhaps overly prone to derive lessons for success when, in fact, most visions for substantial technological change actually fail to get traction.

Carbon capture and storage (CCS) is among the technologies with greatest potential leverage to combat climate change. According to the PRISM analysis, a technology assessment performed by the Electric Power Research Institute (EPRI), wide deployment of CCS after 2020 in the US power sector alone could reduce emissions by approximately 350 million tonnes of CO₂ per year (Mt CO₂/yr) by 2030, a conclusion echoed by the McKinsey U.S. Mid-range Greenhouse Gas Abatement Curve 2030. But building CCS into such a formidable climate change mitigation “wedge” will require more than technological feasibility; it will also require the development of policies and business models that can enable wide adoption. Such business models, and the regulatory environments to support them, have as yet been largely undemonstrated. This, among other factors, has caused the gap between the technological potential and the actual pace of CCS development to remain large.

The purpose of the present work is to quantify actual progress in developing carbon storage projects (here defined as any projects that store carbon underground at any stage of their operation or development, for example through injection into oil fields for enhanced recovery or in saline aquifers or other geological formations). In this way, the real development ramp may be compared in scale and timing against the perceived need for and potential of the technology. Some very useful lists of carbon storage projects already exist – see, for example, the IPCC CCS database, the JP Morgan CCS project list, the MIT CCS database, and the IEA list. We seek to maintain an up-to-date database of all publicly-announced current and planned projects from which we can project a trajectory of carbon stored underground as a function of time. To do this, we estimate for each project the probability of completion as well as the potential volume of CO₂ that can be stored as of a given year.