6 ways to accelerate negative emissions technology
6 ways to accelerate negative emissions technology
Meeting the ambitious climate change targets agreed upon in Paris last December will require deep transformation of the global economy — especially in energy systems, transportation systems and industry — over the next several decades.
It is becoming increasingly clear that such a transition will almost certainly require substantial deployment of negative emissions technologies (NETs) during the course of the 21st century.
One way to look at this challenge is through the lens of integrated assessment models (IAMs), which are optimization models that minimize the costs of reaching climate targets over the long term.
Even though they have so far included only a subset of potential NETs, these models deploy 5 to 20 gigatonnes (GT = 1 billion tonnes) of CO2 removal per year (global CO2 emissions are around 40GT per year today) in scenarios that correspond to the Paris targets (e.g. limiting warming to +2C degrees). Deployment of NETs will surely increase as these models start to develop ways to achieve +1.5C degree targets, as the IPCC has been asked to report on.
A less black box way to understand the challenge is through carbon budgeting. Meeting those targets allows the world to emit about 1000 more gigatons of CO2 — at current rates we’d reach that limit around 2040 and we’d have to be at 0 from then on. The budget for +1.5C degrees, which also was included in a more aspirational way in the Paris Agreement, would mean getting to zero in the 2020s if emissions were to stay constant until then.
More realistic scenarios include a peak reasonably soon and then smooth decarbonization thereafter. But the math of +2C degrees, means that peak has to occur very soon and the decarbonization must be rapid, not gradual.
If we want a more gradual transition, we need to start thinking about a warmer world than +2C or think seriously about negative emissions. Many possible ways have been proposed to remove CO2 from the atmosphere. I found at least six in which peer reviewed journal articles have included estimates of potentials of at least 1 gigawatt of CO2 removal per year. Some have potentials of 10 GT/year or more.
It would be a mistake to interpret this comparison as saying that our capacity for removal exceeds our need. These are simply estimates. There may be negative interactions among them so that they do not sum. Each has potentially serious questions including: competition with food; permanence of storage; energy consumption; cost; public acceptance; and verifiability.
All of these issues merit serious consideration and may limit realistic potentials. What is a valid insight from this comparison is that a diverse set of possibilities exists. While it is far too soon to concentrate on any of them, it is also too early to write off any of these methods based on their challenges.
To turn these possibilities into options — that is, technologies we can deploy if we need them — we need a set of policies to accelerate innovation in them so that they become scalable, real-world technologies. I’d suggest that designing such policies should start with what we know about historical case studies of analogous innovations and government efforts to encourage them. Here are a few to begin:
1. Historical case studies show that successful innovations are those that combine technological opportunity with a market opportunity. Market experience is crucial; it informs new research and incremental improvements via learning by doing and economies of scale.
2. Research and development is needed, but to make these technologies real, look to early deployment, not scientific breakthroughs. R&D can enable scale up and address challenges, such as in materials, reactions and storage. But NETs are not a challenge like the Manhattan or Apollo Projects, even if it shares the urgency of ending a war or landing on the moon. The challenge of developing NETs is more like rural electrification, the interstate highway system and the green revolution. These involved variation, gradual scale up, integration with a larger technological system and serving diverse end-users.
3. Scale up is central to the challenge and is not trivial. Both making larger units and deploying many units take time and continuous improvements that learn from previous efforts. There are plenty of examples of failure due to scaling up too big, too fast. Iteration and gradual scale up would replicate successful strategies in analogous technologies.
4. Expect dynamic costs and non-linear deployment. Learning by doing and economies of scale bring down costs. Deployment is likely to follow an S-curve; slow at first due to technical problems and risk averse adopters; and rapid once scale reached, dominant designs achieved, and reliability proven. Like many other technologies, expect adoption to be slower than expected in near term and faster than expected in the medium term.
6. Public acceptance will be crucial for all NETs. In simple terms, we know that public perceptions are favorable when there is familiarity, involvement in decision-making process, and when scales involved are human rather than industrial. Perceptions are unfavorable when deployment is rapid and adverse outcomes are experienced nearby. If publics are skeptical, interim failures can become high profile and create insurmountable setbacks.
A technology strategy for NETs in the near term should focus on initial deployment and iteration. It should target learning, intelligent failures and improvement. The quantity of CO2 stored, efficiency and cost are secondary; they are progress indicators, not program objectives. Later is the time for de-risking the technology and targeting cost reductions. Look for places where many small units are deployed in real-world conditions, rather than a few large installations — even if some units must be large eventually.
NETs are only viable as a defense against rapid climatic changes if many units are deployed at small scale before they are needed. Without this experience, rapid scale up from lab scale to address an emergency are likely to generate: large technical failures, public opposition, and lock-in to problematic designs.NETs only have "option value" once they have been deployed at a small but substantial level. In short, an innovation strategy for NETs that learns from the past would include:
NETs only have "option value" once they have been deployed at a small but substantial level. In short, an innovation strategy for NETs that learns from the past would include:
- Repeat — many times, with a diverse set of approaches, at incrementally larger scale, and in increasingly realistic conditions.