Enhanced silicate rock weathering (ERW), deployable with croplands, has potential use for atmospheric carbon dioxide (CO2) removal (CDR), which is now necessary to mitigate anthropogenic climate change1. ERW also has possible co-benefits for improved food and soil security, and reduced ocean acidification2,3,4. Here we use an integrated performance modelling approach to make an initial techno-economic assessment for 2050, quantifying how CDR potential and costs vary among nations in relation to business-as-usual energy policies and policies consistent with limiting future warming to 2 degrees Celsius5. China, India, the USA and Brazil have great potential to help achieve average global CDR goals of 0.5 to 2 gigatonnes of carbon dioxide (CO2) per year with extraction costs of approximately US$80–180 per tonne of CO2. These goals and costs are robust, regardless of future energy policies. Deployment within existing croplands offers opportunities to align agriculture and climate policy. However, success will depend upon overcoming political and social inertia to develop regulatory and incentive frameworks. We discuss the challenges and opportunities of ERW deployment, including the potential for excess industrial silicate materials (basalt mine overburden, concrete, and iron and steel slag) to obviate the need for new mining, as well as uncertainties in soil weathering rates and land–ocean transfer of weathered products.
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Environmental and health impacts of atmospheric CO2 removal by enhanced rock weathering depend on nations’ energy mix
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We thank A. Azapagic and J. Shepherd for comments on an earlier draft, and acknowledge discussions with additional members of the Royal Society-Royal Academy of Engineering Greenhouse Gas Removal Working Group. We acknowledge funding of this research with a Leverhulme Research Centre Award (RC-2015-029) from the Leverhulme Trust. We thank L. Taylor for advice and discussions during model development and J. Quirk for data and analysis on plant weathering. P.R. acknowledges UKRI funding under the UK Greenhouse Gas Removal Programme (NE/P019943/1, NE/P019730/1); I.A.J. acknowledges financial support from the Research Council of the University of Antwerp. We acknowledge the World Climate Research Programme’s Working Group on Coupled Modelling responsible for CMIP and thank the climate modelling groups for producing and making available their model output. For CMIP, the US Department of Energy’s Program for Climate Model Diagnosis and Intercomparison provides coordinating support and led the development of software infrastructure in partnership with the Global Organization for Earth System Science Portals.
The authors declare no competing interests.
Peer review information Nature thanks Johannes Lehmann, Keith Paustian and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.
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Extended data figures and tables
Results are shown for the top seven nations of the world (a–g), and the top five European nations (h–l), as ranked by net CDR capacity, with increasing fractional cropland area of ERW deployment. Curves depict simulations for the BAU and 2 °C energy policy scenarios. The grey-shaded area for each nation represents the 90% confidence interval calculated for basalts with relatively slow- versus fast-weathering rates for the BAU scenario; short green dashed lines indicate the 90% confidence limits of the corresponding 2 °C scenario simulations.
Net rates of CO2 sequestration on croplands (annual and perennial combined) for the four targeted global CDR rates, 0.5 Gt CO2 yr–1, 1.0 Gt CO2 yr–1, 1.5 Gt CO2 yr–1 and 2.0 Gt CO2 yr–1 (Table 1) for the BAU (a–d) and the 2 °C (e–h) energy policy scenarios.
Results are shown for the seven nations of the world (a–g) and the five European nations (h–l) with the highest CDR, as ranked by net CDR capacity, with increasing fractional cropland area deployment of ERW. Note the y-axis scale changes for European countries. Curves are the same irrespective of energy policy scenario.
a–d, Results are shown for the seven nations of the world (a, c) and the five European nations (b, d) with the highest CDR potential for the BAU scenario (a, b) and for the 2 °C energy policy scenario (c, d). For each country, from left to right, bars are for fractions of 0.25, 0.5, 0.75 and 1.0 of ERW deployment on croplands. Under the BAU scenario, CO2 emissions from grinding dominate secondary emissions associated with ERW, except for France, where low-carbon nuclear power dominates. Under the 2 °C energy policy scenario (c and d), secondary CO2 emissions generally drop for most nations as they transition to low-carbon energy sources in 2050 and implement negative emissions.
Illustrative multi-year simulations of annual basalt application with the performance model showing the effects on soil pH, average efficiency of CDR (RCO2), and soil mineral masses over a 10-year time horizon. a–c, pH, RCO2 and mineral mass results for the tholeiitic basalt, respectively. d–f, pH, RCO2 and mineral mass results for the alkali basalt (Supplementary Tables 1–3). All simulations used the same p80 particle size (100 µm) and were undertaken at 20 °C. Multi-year simulations capture the effect of basaltic minerals undergoing dissolution at different rates, with some minerals continuing to undergo dissolution and capture CO2 after the first year of application. Such simulations allow average rates of weathering and CDR from repeated basaltic rock dust applications to be computed. Our extended theory underpinning the simulation framework tracks cohorts of particles applied each year and their mineral composition over time to account for cumulative effects (Supplementary Methods).
a, Soil temperature from the Hadley Centre coupled Earth System Model (HadGEM) RCP 8.5 simulation for 2050 (the worst-case scenario). b, The HYDE harmonized soil pH database. c, Annual cropland soil water infiltration (irrigation water + precipitation minus evapotranspiration). d, e, Net primary production index for perennial and annual crops as derived from FAO datasets, respectively. Data sources and spatial resolution are specified in Supplementary Table 14.
a, Industrial diesel prices. b, c, CO2 emissions intensity for the BAU scenario (b) and the 2 °C scenario (c). d, Gross national income per capita. e, Industrial electricity prices. Data sources and spatial resolution are specified in Supplementary Table 14.
a, Relationship between particle size and surface area. b, Relationship between surface area and grinding energy. c, Relationship between particle size and grinding energy. p80 is defined as 80% of the particles having a diameter less than or equal to the specified size. Derived from data in ref. 73.
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Beerling, D.J., Kantzas, E.P., Lomas, M.R. et al. Potential for large-scale CO2 removal via enhanced rock weathering with croplands. Nature 583, 242–248 (2020). https://doi.org/10.1038/s41586-020-2448-9
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