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Modeling direct air carbon capture and storage in a 1.5 °C climate future using historical analogs

Significance

Technological innovation is central to sustainable development, but representing novel technologies in systems models is difficult due to limited data on their past performance. We propose a method to model the feasibility space for novel technologies that combines empirical data on historical analogs and early adoption with a global integrated assessment model. Applying this method to direct air carbon capture and storage (DACCS), we find that the feasibility space is large, with DACCS contributing meaningfully to net-zero goals if it grows like some analogs and failing to do so with others. The results can be used to identify technology and policy features that may be important in enabling rapid adoption to avert the worst effects of climate change.

Abstract

Limiting the rise in global temperature to 1.5 °C will rely, in part, on technologies to remove CO2 from the atmosphere. However, many carbon dioxide removal (CDR) technologies are in the early stages of development, and there is limited data to inform predictions of their future adoption. Here, we present an approach to model adoption of early-stage technologies such as CDR and apply it to direct air carbon capture and storage (DACCS). Our approach combines empirical data on historical technology analogs and early adoption indicators to model a range of feasible growth pathways. We use these pathways as inputs to an integrated assessment model (the Global Change Analysis Model, GCAM) and evaluate their effects under an emissions policy to limit end-of-century temperature change to 1.5 °C. Adoption varies widely across analogs, which share different strategic similarities with DACCS. If DACCS growth mirrors high-growth analogs (e.g., solar photovoltaics), it can reach up to 4.9 GtCO2 removal by midcentury, compared to as low as 0.2 GtCO2 for low-growth analogs (e.g., natural gas pipelines). For these slower growing analogs, unabated fossil fuel generation in 2050 is reduced by 44% compared to high-growth analogs, with implications for energy investments and stranded assets. Residual emissions at the end of the century are also substantially lower (by up to 43% and 34% in transportation and industry) under lower DACCS scenarios. The large variation in growth rates observed for different analogs can also point to policy takeaways for enabling DACCS.

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