[Image above] A coal-fired power station in Mannheim, Germany. Many governments expect carbon capture and storage technologies to play an important role in combatting carbon emissions, but to date investments in such technologies have yielded underwhelming results. Credit: stanze, Flickr (CC BY-SA 2.0)
When it comes to climate policy, Democrats and Republicans often differ significantly in their preferred approaches for handling greenhouse gas emissions. Carbon capture and storage, however, is one method that generally receives bipartisan support.
Carbon capture and storage, or CCS, is the process of trapping carbon dioxide and storing it in such a way that it cannot affect the atmosphere. Bipartisan members of Congress have for years looked favorably on and funded CCS technologies and policies, and even recent hearings on developing a broad infrastructure package view CCS as a critical component of future legislation.
Despite the broad support and large expectations for CCS, investment in CCS technology has to date yielded underwhelming results. “The 2000s saw the largest U.S. push to commercialize the technology, with private industry and government investing tens of billions of dollars in dozens of industrial and power plant capture projects. Despite extensive support, the vast majority of these failed,” researchers explain in a recent open-access article.
The researchers come from the University of California, San Diego, along with colleagues from Carleton University (Canada) and Imperial College London (U.K.). In a UC San Diego press release, they explain that with so much riding on CCS technology, “Policy design is essential to help commercialize the industry because CCS projects require a huge amount of capital up front.” However, to design good policy, it is necessary to understand why investments in CCS projects to date have such a high failure rate.
Historically, studies on CCS failures and successes relied on analyzing CCS projects individually or in small studies. The researchers for this study, though, chose to robustly analyze the U.S. Department of Energy’s National Energy Technology Laboratory database, which contains information on more than 300 carbon capture, utilization, and storage projects of all types that have been proposed or built worldwide.
They narrowed the analysis down to 39 projects after selecting for projects based in the U.S. and that store some or all of the CO2 captured. Then, they used both a linear regression model and a random forest model to identify functional relationships between 12 project attributes (given below) to project outcome. They also conducted a highly structured invitational workshop with CCS experts to learn their thoughts on each attribute’s relative importance.
Table 1. The 12 CCS project attributes that can be evaluated quantitatively in a replicable manner. Hypothesis statements summarize how attributes could positively impact the likelihood of project success. Credit: Abdulla et al., Environmental Research Letters (CC BY 4.0)
|Category||Project attribute||Hypothesis statement|
|Engineering economics||Plant siting||Locating on brownfield sites entails less site preparation, less extensive development of new infrastructure, and less regulatory burden.|
|Capture technology readiness level||Deploying technologies already demonstrated at scale reduces technical, system integration, and project execution risks.|
|Capital cost||Cheaper projects are easier to finance and overall carry less risk.|
|Financial credibility||Employment impact||Projects that improve local or regional economies through employment are more likely to form coalitions in their favor.|
|Credibility of revenues||Projects that can demonstrate credible revenue streams or reduce their uncertainty are more likely to succeed.|
|Credibility of incentives||Projects that secure a greater share of their cost are more likely to succeed. Incentives that are unconditional and upfront are more credible.|
|Local political features||Population proximity||Projects in sparsely populated locales are more likely to succeed because they encroach on fewer people and organized interests.|
|Institutional setting||Projects benefit from jurisdictions with a legacy of supporting fossil infrastructure and attendant institutional memory in applying policy and regulatory frameworks.|
|Burden of CO2 disposal||Projects requiring less onerous arrangements for capture, storage, monitoring, and verification entail less risk.|
|Broader political features||Regulatory challenges||Projects that encounter neither legal difficulties nor regulatory delays are more likely to succeed.|
|Public opposition||Projects that enjoy support from environmental or civil society groups are more likely to succeed.|
|Industrial stakeholder opposition||Projects where concentrated industrial stakeholders align strategically with the developer are more likely to succeed.|
Three attributes emerged as significant variables across both the statistical models and expert-derived model.
- Capital cost: Projects with larger capital costs are more likely to fail.
- Technological readiness: High levels of readiness improve the chances of project success.
- Credibility of project revenues: More credible sources strongly increase odds of project success.
On the other hand, three different attributes witnessed disagreement among models.
- Regulatory challenges: While both statistical models found this attribute to be the fourth most important in explaining project outcome, experts ranked it seventh in importance. Analysis of the historical record suggests that projects that face permit denials, extended regulatory proceedings, or lawsuits are more likely to fail.
- Employment impact: This attribute is important in the random forest model but not statistically significant in the linear regression; the experts judged it to be largely irrelevant (ranked 12 of 12). Analysis of the historical record reveals projects that propose more extravagant plans to improve economies through employment are those that are expensive, high-profile, and high-risk—all factors that increase odds of failure.
- Burden of CO2 disposal: Experts ranked this attribute fourth of 12 in importance, whereas it is insignificant in the statistical models. The experts stated that the visibility of documentary evidence (which the statistical models focus on) inherently ignores the groundwork that disposal requires on the part of project developers.
A fourth attribute—credibility of incentives—was significant for both the linear regression and expert-derived models, but not in the random forest. However, the linear regression and expert-derived models felt incentives were significant for different reasons.
The linear regression model found an inverse relationship between incentives and project outcome—successful projects rely less on incentives than those that fail. “Projects with high price tags have generally received government incentives; they are flagship, high-profile, sometimes high-risk, demonstration projects. It is precisely these types of projects that often fail, often because they are vulnerable to ‘vetoes’ if policy makers waver in their support, especially given their potentially long lead times. By contrast, projects that succeed are smaller, less costly, and rely less on incentives,” the researchers write.
Nonetheless, CCS experts argue incentives are essential to successfully commercializing CCS technology—though not necessarily in the form of funding for specific projects. “In other words, experts believe that it is not direct support for the CCS industry that will lead to the largest volumes of CO2 capture; rather, what matters most are incentives that encourage systematic decarbonization, such as government procurement of decarbonized industrial products or a broad low-carbon fuel standard,” the researchers write.
In the conclusion, the researchers say the systematic framework and transparent coding system they developed will likely improve the success rate of projects by guiding developers and policymakers toward supporting projects with higher chances of success. In addition, “While we focus here on CCS, this framework can be employed in assessing a large number of promising yet fledgling technological systems that have been discussed as promising partial solutions to the climate crisis,” they write.
The open-access paper, published in Environmental Research Letters, is “Explaining successful and failed investments in U.S. carbon capture and storage using empirical and expert assessments” (DOI: 10.1088/1748-9326/abd19e).