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Computing optimal carbon dioxide removal portfolios

Nature Computational Science volume 2, pages 465–466 (2022)Cite this article

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To the editor — The Glasgow Agreement statement on the “phase-down” of coal means that limiting global warming to well below 2 °C will require emissions cuts through other means. To achieve mid-century carbon neutrality, aggressive policies are needed to reduce point-source emissions primarily through the increased use of renewables. Since many developing nations will be unable to make this transition by 2050, negative emissions technologies (NETs) will also have to be scaled up rapidly to offset residual emissions from fossil fuels through carbon dioxide removal (CDR)1. Many start-ups have followed the trend of the emerging “drawdown economy” to commercialize NETs through the sale of credits from CDR. However, there remains a gap in providing computational decision support for their strategic deployment.

The ramp-up of CDR to the gigaton scale has serious implications for energy systems due to the electricity requirement of many NET alternatives2. Timing is also critical; recent modeling results focusing on bioenergy with carbon capture and storage (BECCS) and direct air capture (DAC) show that early deployment can reduce cumulative costs of achieving net-zero emissions in the European Union3. Exploring diverse NET portfolios is critical due to their potential to avoid risks in large-scale deployment4. For example, vast tracts of monoculture plantations for BECCS can threaten biodiversity5. No single option can sustainably meet the climate targets, so multiple NETs at moderate scales are needed. However, most research studies still focus on individual NETs, with few of them taking a system-level outlook. The global and regional potential capacities of NETs have largely been evaluated individually rather than as part of a carbon management portfolio6. Integrated assessment modeling (IAM) studies have focused mainly on BECCS and afforestation/reforestation (AR) analyzed separately7. To date, only one IAM study has attempted the optimization of a NETs portfolio consisting of BECCS, DAC, enhanced weathering, and AR8. The results of the study show that a full portfolio supports the attainment of net-zero faster and with a better balance of regional CDR contributions.

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Fig. 1: Modeling framework for supporting large-scale NET deployment.

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Acknowledgements

This work was supported by The British Council Japan under the COP26 Trilateral Research Initiative. M.V.M.-S. received additional support from the Department of Science and Technology of the Philippines via the ERDT scholarship program.

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Authors and Affiliations

  1. Department of Chemical Engineering, De La Salle University, Manila, Philippines

    Raymond R. Tan, Kathleen B. Aviso & Maria Victoria Migo-Sumagang

  2. Department of Chemical and Environmental Engineering, University of Nottingham Malaysia, Semenyih, Malaysia

    Dominic C. Y. Foo & Purusothmn Nair S. Bhasker Nair

  3. Centre of Excellence for Green Technologies, University of Nottingham Malaysia, Semenyih, Malaysia

    Dominic C. Y. Foo & Purusothmn Nair S. Bhasker Nair

  4. Department of Chemical Engineering, University of the Philippines Los Baños, Laguna, Philippines

    Maria Victoria Migo-Sumagang

  5. Department of Chemical and Process Engineering, University of Surrey, Guildford, United Kingdom

    Michael Short

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  1. Raymond R. Tan
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All authors contributed to conceptualizing and writing the paper; D.C.Y.F. and M.V.M.-S. prepared the figure.

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Correspondence to Raymond R. Tan.

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Tan, R.R., Aviso, K.B., Foo, D.C.Y. et al. Computing optimal carbon dioxide removal portfolios. Nat Comput Sci 2, 465–466 (2022). https://doi.org/10.1038/s43588-022-00286-1

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