The need for energy storage to balance intermittent and inflexible electricity supply with demand is driving interest in conversion of renewable electricity via electrolysis into a storable gas. But, high capital cost and uncertainty regarding future cost and performance improvements are barriers to investment in water electrolysis. Expert elicitations can support decision-making when data are sparse and their future development uncertain. Therefore, this study presents expert views on future capital cost, lifetime and efficiency for three electrolysis technologies: alkaline (AEC), proton exchange membrane (PEMEC) and solid oxide electrolysis cell (SOEC). Experts estimate that increased R&D funding can reduce capital costs by 0–24%, while production scale-up alone has an impact of 17–30%. System lifetimes may converge at around 60,000–90,000 h and efficiency improvements will be negligible. In addition to innovations on the cell-level, experts highlight improved production methods to automate manufacturing and produce higher quality components. Research into SOECs with lower electrode polarisation resistance or zero-gap AECs could undermine the projected dominance of PEMEC systems. This study thereby reduces barriers to investment in water electrolysis and shows how expert elicitations can help guide near-term investment, policy and research efforts to support the development of electrolysis for low-carbon energy systems

Electrical energy storage could play a pivotal role in future low-carbon electricity systems, balancing inflexible or intermittent supply with demand. Cost projections are important for understanding this role, but data are scarce and uncertain. Here, we construct experience curves to project future prices for 11 electrical energy storage technologies. We find that, regardless of technology, capital costs are on a trajectory towards US$340 ± 60 kWh⁻¹ for installed stationary systems and US$175 ± 25 kWh⁻¹ for battery packs once 1 TWh of capacity is installed for each technology. Bottom-up assessment of material and production costs indicates this price range is not infeasible. Cumulative investments of US$175–510 billion would be needed for any technology to reach 1 TWh deployment, which could be achieved by 2027–2040 based on market growth projections. Finally, we explore how the derived rates of future cost reduction influence when storage becomes economically competitive in transport and residential applications. Thus, our experience-curve data set removes a barrier for further study by industry, policymakers and academics.

The feasibility of large-scale biological CO₂removal to achieve stringent climate targets remains unclear. Direct Air Carbon Capture and Storage (DACCS) offers an alternative negative emissions technology (NET) option. Here we conduct the first inter-model comparison on the role of DACCS in 1.5 and 2 °C scenarios, under a variety of techno-economic assumptions. Deploying DACCS significantly reduces mitigation costs, and it complements rather than substitutes other NETs. The key factor limiting DACCS deployment is the rate at which it can be scaled up. Our scenarios’ average DACCS scale-up rates of 1.5 GtCO₂/yr would require considerable sorbent production and up to 300 EJ/yr of energy input by 2100. The risk of assuming that DACCS can be deployed at scale, and finding it to be subsequently unavailable, leads to a global temperature overshoot of up to 0.8 °C. DACCS should therefore be developed and deployed alongside, rather than instead of, other mitigation options.

This paper reviews the many criticisms that Integrated Assessment Models (IAMs)—the bedrock of mitigation analysis—have received in recent years. Critics have asserted that there is a lack of transparency around model structures and input assumptions, a lack of credibility in those input assumptions that are made visible, an over-reliance on particular technologies and an inadequate representation of real-world policies and processes such as innovation and behaviour change. The paper then reviews the proposals and actions that follow from these criticisms, which fall into three broad categories: scrap the models and use other techniques to set out low-carbon futures; transform them by improving their representation of real-world processes and their transparency; and supplement them with other models and approaches. The article considers the implications of each proposal, through the particular lens of how it would explore the role of a key low-carbon technology—bioenergy with carbon capture and storage (BECCS), to produce net negative emissions. The paper concludes that IAMs remain critically important in mitigation pathways analysis, because they can encompass a large number of technologies and policies in a consistent framework, but that they should increasingly be supplemented with other models and analytical approaches.

While the decarbonization of the global economy will bring immense benefits in the aggregate and to many individuals, it will also be disruptive and costly for some, at least in the short term. As these disruptions and costs have become increasingly salient in recent years, there has been an explosion of interest in the climate policy community about how low-carbon transitions can be implemented justly, equitably, and politically smoothly. A key part of what is needed in responding to this growing interest is a better understanding of the suite of ‘transitional assistance policies’ and strategies that can be deployed, alongside or as part of climate change mitigation policies and processes. Responding to this need, we survey a wide, multi-disciplinary literature to answer the ‘who’, ‘what’ and ‘how’ of transitional assistance policy: who is likely to be adversely affected by the low-carbon transition, and in what ways? What substantive strategies and policy instruments are available to governments to mitigate the burdens of low-carbon transitions? And how can governments implement such strategies and policies successfully? In the course of answering the first two of these questions, we develop a novel typology of transitional assistance policies, in which multiple policies are parsimoniously classified according to one of four coherent policy strategies, and one of five kinds of beneficiaries. In answering the third question, we emphasize the importance of certain ‘state capacities’ for shaping transition processes and managing vested interests. Key policy insights GRAPHICAL ABSTRACT