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Fine-regolith production on asteroids controlled by rock porosity

Abstract

Spacecraft missions have observed regolith blankets of unconsolidated subcentimetre particles on stony asteroids1,2,3. Telescopic data have suggested the presence of regolith blankets also on carbonaceous asteroids, including (101955) Bennu4 and (162173) Ryugu5. However, despite observations of processes that are capable of comminuting boulders into unconsolidated materials, such as meteoroid bombardment6,7 and thermal cracking8, Bennu and Ryugu lack extensive areas covered in subcentimetre particles7,9. Here we report an inverse correlation between the local abundance of subcentimetre particles and the porosity of rocks on Bennu. We interpret this finding to mean that accumulation of unconsolidated subcentimetre particles is frustrated where the rocks are highly porous, which appears to be most of the surface10. The highly porous rocks are compressed rather than fragmented by meteoroid impacts, consistent with laboratory experiments11,12, and thermal cracking proceeds more slowly than in denser rocks. We infer that regolith blankets are uncommon on carbonaceous asteroids, which are the most numerous type of asteroid13. By contrast, these terrains should be common on stony asteroids, which have less porous rocks and are the second-most populous group by composition13. The higher porosity of carbonaceous asteroid materials may have aided in their compaction and cementation to form breccias, which dominate the carbonaceous chondrite meteorites14.

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Fig. 1: The thermal inertia of Bennu’s rocks is positively correlated with the local surface abundance of fine regolith.
Fig. 2: The porosities of most of Bennu’s and Ryugu’s rocks are much higher than that of Itokawa’s rocks.
Fig. 3: Fine-regolith production is frustrated in the presence of high-porosity rocks.

Data availability

Raw through-calibrated OTES52 and OCAMS53 data are available via the Planetary Data System (https://sbn.psi.edu/pds/resource/orex/). The SPC/OLA v34 shape model is available via the Small Body Mapping Tool (http://sbmt.jhuapl.edu/). The IDs of the OTES observations used here and the best-fitting solutions for the thermophysical model are provided in Supplementary Table 1. The boulder size, location and reflectance used to test the robustness of the results are available in refs. 34,46Source data are provided with this paper.

Code availability

The thermophysical analysis reported here uses custom code based on the thermophysical model of ref. 16, available at https://www.oca.eu/images/LAGRANGE/pages_perso/delbo/thermops.tar.gz. The code to compute the geometry of the OTES acquisitions and boresight is available at https://doi.org/10.5281/zenodo.4781752 (ref. 54). The code to compute Γc for the thermophysical analysis is available at https://doi.org/10.5281/zenodo.4763783 (ref. 55). The rock mapping in Extended Data Fig. 3 was performed using the SAOImageDS9 software available at https://sites.google.com/cfa.harvard.edu/saoimageds9. Other codes that support the findings of this study are available at https://doi.org/10.5281/zenodo.4771035 (ref. 56).

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Acknowledgements

This material is based on work supported by NASA under contract NNM10AA11C issued through the New Frontiers Program. We are grateful to the entire OSIRIS-REx team for making the encounter with Bennu possible, to C. Wolner and F. Murphy for editorial help, and to the OPAL infrastructure of the Observatoire de la Côte d’Azur (CRIMSON) for providing computational resources and support. S.C. thanks the University of Arizona for supporting this study. M.D., C.A., J.D.P.D. and  M.A.B. acknowledge the French space agency CNES. C.A. and M.D. acknowledge support from ANR “ORIGINS” (ANR-18-CE31-0014). C.A. was supported by the French National Research Agency under the project “Investissements d’Avenir” UCAJEDI ANR-15-IDEX-01. G.P. and J.R.B. were supported by Italian Space Agency grant agreement INAF/ASI number 2017-37-H.0. B.R. acknowledges financial support from the UK Science and Technology Facilities Council (STFC). E.C. thanks CSA, NSERC, CFI, MRIF and UWinnipeg for supporting this study.

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Authors

Contributions

S.C. led the project, the interpretation of the results and the manuscript development, and performed the thermophysical simulations and data analysis. M.D. provided the thermophysical software, performed the thermal cracking calculations, and contributed to the interpretation of the results and the development of the manuscript. G.P. developed the pipeline to retrieve OTES detailed survey data and performed rock mapping in PolyCam images. C.A. curated the discussion on meteoroid bombardment and contributed to writing the manuscript. A.J.R. contributed with the code to convert thermal inertia values in fine-regolith particle size and developed the iterative approach to determine the cut-off value of thermal inertia, together with S.C. J.D.P.D. extracted the observation geometry of the spacecraft and Bennu from mission kernels. R.-L.B. proposed important tests of the robustness of the results. E.A., W.F.B. and J.R.B. contributed to the interpretation of the data and writing of the manuscript. D.N.D., K.N.B., C.A.B. and K.J.W. provided support in the interpretation of spacecraft imagery. J.P.E. and B.R. contributed to the data interpretation during the OSIRIS-REx Thermal Analysis Working Group meetings, and to the design of the observations and data acquisition. M.A.B. and E.C. contributed to the interpretation of the results. D.S.L. made this study possible as the PI of the OSIRIS-REx mission and contributed to the discussion of the results.

Corresponding author

Correspondence to S. Cambioni.

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The authors declare no competing interests.

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Peer review information Nature thanks Guy Consolmagno and Seiji Sugita for their contribution to the peer review of this work. Peer reviewer reports are available.

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Extended data figures and tables

Extended Data Fig. 1 The thermal inertia of Bennu’s rocks and the surface abundance of fine regolith were measured in 122 quasi-randomly–distributed regions.

a, OTES spots on Bennu plotted on the global basemap of Bennu32 as function of longitude and latitude (red: Equatorial Station 1 at 3:00 pm, or EQ1; blue: Equatorial Station 2 at 3:20 am, or EQ2). b, comparison between modelled and observed radiance for one of the 122 areas (ID: 609491396:610102222). c, comparison between the emissivity of Bennu and the residuals of the analysis for the spots 609491396:610102222; the residual curves closely resemble Bennu’s emissivity, which is not modelled by our thermophysical model. The error bars correspond to 3 times the Noise Equivalent Spectral Radiance of the OTES instrument15. Credit for global mosaic in panel a: NASA/Goddard/University of Arizona.

Extended Data Fig. 2 There is less fine regolith at the OSIRIS-REx’s backup sampling site Osprey than at the primary sampling site Nightingale.

Blue and yellow pixels represent areas where no particles bigger than 2 cm, ~ls, were mapped by ref. 43. The value DPls is the upper limit for the sizes of fine regolith detected by our thermophysical model. There are fewer blue and yellow pixels at Osprey (image resolution: 0.3 cm per pixel, panels a, b) than at Nightingale (image resolution: 0.4 cm per pixel, panels c, d), implying that Osprey has less unresolved material than Nightingale. Consistently and independently, our thermophysical model indicates αOsprey<αNightingale (Supplementary Table 1, spots 609505286:610098718 and 609504794:610100730, respectively). Credit for bird graphics and PolyCam images: NASA/Goddard/University of Arizona.

Extended Data Fig. 3 The fine-regolith abundance derived from OTES data is lower than the area of unresolved material measured in Bennu’s images.

Our visual mapping and size measurement of rocks within two OTES spots: a, OTES spots 609493058:610103962; b, OTES spots 609487186:610098206. In both areas, the values of α from our thermophysical solution are smaller than the areas of unresolved materials seen in the images. Given the coarse PolyCam32 resolution, it is possible that there are unmapped particles larger than ls (but smaller than the image resolution) that our thermophysical model detects as rocks and thus do not contribute to the value of α. Credit for PolyCam images: NASA/Goddard/University of Arizona.

Source data

Extended Data Fig. 4 The correlation between ΓR and α is statistically significant.

a, Spearman correlation coefficient. b, Spearman P-value; a Spearman P < 0.05 indicates that the correlation between ΓR and α is statistically significant. The figure corresponds to the results for a value of regolith macroporosity of φ = 40%.

Extended Data Fig. 5 The correlation between ΓR and α is robust against the choice of the fine-regolith macroporosity.

The results for macroporosity φ = 15% and φ = 60% have Spearman correlation coefficients 0.56 ± 0.06 and 0.58 ± 0.06, probability of non-correlation P < 0.05, and are within 3 standard deviations of the best-fit values for regolith macroporosity of φ = 40% in 99% and 92% of the cases, respectively. The correlations are robust against removing the areas whose solutions are statistically distinct from the data set with macroporosity φ = 40% (Spearman correlation index: 0.55 ± 0.07 and P < 0.05 in 100% of 10,000 trials). The error bars correspond to 1 standard deviation (Supplementary Table 1; Methods) computed on ~450 and ~880 samples on average. The results for a regolith macroporosity of φ = 40% are described in the main text (Fig. 1).

Source data

Extended Data Fig. 6 The correlation between ΓR and α is not an artefact of thermophysical modelling.

We fit model radiances emitted by a single triangular facet with zero roughness; if the thermal inertia Γ ≤ Γc = 100 Jm−2K−1s−0.5, then α = 100%, and if Γc<Γ<2,500 Jm−2K−1s−0.5, then α = 0%. We retrieve the expected step function of α as a function of Γ, indicating that the correlation in Fig. 1 is unlikely to be an artefact of the model. The error bars correspond to 1 standard deviation computed on ~ 1.76 × 104 samples on average (Methods).

Source data

Extended Data Fig. 7 The correlation between ΓR and α is not a geometric effect due to boulders’ sizes.

a, PolyCam image of the surface corresponding to spots 609486110:610097198 where α is low probably because the spots are filled by a large, dark boulder. b, PolyCam image of the surface corresponding to spots 609495164:610106090 where α does not correlate with the size of the largest boulder; this is representative of most of the surveyed areas. c, plot of α as function of the percentage of the OTES spot covered by the largest boulder on the surface. The Spearman test reveals that these two quantities have a probability of non-correlation above the critical threshold of 0.05 in 99.99% of 10,000 trials. This indicates that the ΓR-α correlation of Fig. 1 is not the result of geometric effects. The error bars in panel c correspond to 1 standard deviation (Supplementary Table 1; Methods) computed on ~ 670 samples on average. Credit for global mosaic: NASA/Goddard/University of Arizona.

Source data

Extended Data Fig. 8 The time required to thermally break rocks is shorter for low-porosity rocks than for high-porosity rocks.

We consider the asteroid to be in near-Earth space and explore a range of rotation periods corresponding to the shaded areas. The latter is to take into account changes in the current rotation periods (4.296 h and 12.1 h for Bennu and Itokawa, respectively) that these asteroids may have experienced in the past49 due to the Yarkovsky–O’Keefe–Radzievskii–Paddack (YORP) effect. We estimate that in their main belt source region, at about 2.3 au from the Sun, the time to break is ~60 times longer.

Source data

Extended Data Fig. 9 Examples of in-situ boulder fragmentation on Bennu.

a, a 5.4 m-diameter boulder located at 22° N 157° E. b, a 5.6 m-diameter boulder located at 42° N 170° E. c, a 5.3 m-diameter boulder located at 57° N 304° E. d, a 5 m-diameter boulder located at 39° S 203° E. The images are from the global mosaic32 acquired by the PolyCam33 imager of OCAMS. Credit for PolyCam images: NASA/Goddard/University of Arizona.

Supplementary information

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Supplementary Table 1

This table contains 4 spreadsheets; properties of the OTES spots (including the unique data identifiers); two-component thermophysical solution for a regolith macroporosity of 40%; two-component thermophysical solution for a regolith macroporosity of 15%; two-component thermophysical solution for a regolith macroporosity of 60%.

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Cambioni, S., Delbo, M., Poggiali, G. et al. Fine-regolith production on asteroids controlled by rock porosity. Nature 598, 49–52 (2021). https://doi.org/10.1038/s41586-021-03816-5

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