journal article·2024-04-01Open access

Integrating direct air capture with small modular nuclear reactors: understanding performance, cost, and potential

Luca Bertoni, Simon Roussanaly, Luca Riboldi, Rahul Anantharaman, Matteo Gazzani

Journal of Physics: Energy· Volume 6· Issue 2

Abstract

Abstract Direct air capture (DAC) is a key component in the transition to net-zero society. However, its giga-tonne deployment faces daunting challenges in terms of availability of both financial resources and, most of all, large quantities of low-carbon energy. Within this context, small modular nuclear reactors (SMRs) might potentially facilitate the deployment of DAC. In the present study, we present a detailed thermodynamic analysis of integrating an SMR with solid sorbent DAC. We propose different integration designs and find that coupling the SMR with DAC significantly increases the use of thermal energy produced in the nuclear reactor: from 32% in a stand-alone SMR to 76%–85% in the SMR-DAC system. Moreover, we find that a 50–MW SMR module equipped with DAC could remove around 0.3 MtCO 2 every year, while still producing electricity at 24%–42% of the rated power output. Performing a techno-economic analysis of the system, we estimate a net removal cost of around 250 €/tCO 2 . When benchmarking it to other low-carbon energy supply solutions, we find that the SMR-DAC system is potentially more cost-effective than a DAC powered by high-temperature heat pumps or dedicated geothermal systems. Finally, we evaluate the potential of future deployment of SMR-DAC in China, Europe, India, South Africa and the USA, finding that it could enable up to around 96 MtCO 2 /year by 2035 if SMRs prove to be cost-competitive. The impact of regional differences on the removal cost is also assessed.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Carbon Dioxide Capture Technologies · Process Optimization and Integration · CO2 Sequestration and Geologic Interactions

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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