Key points are not available for this paper at this time.
NEO models for km-sized asteroids Near-Earth object (NEO) models are a useful tool for interpreting asteroid behaviour in near-Earth space (perihelion distances < 1.3 au). They can predict many asteroid properties such the size-dependent transport from the main-belt (Granvik et al., 2018; Nesvorn et al., 2023) and the disruptive processes of low perihelia passage (Granvik et al., 2016; Wiegart et al., 2020). They can also estimate the frequency of Earth impactors (Harris Chodas, 2021; Morbidelli et al., 2020), and trace the origins of meteorites to the main asteroid belt (e.g. Brown et al., 2023). This field of work is not static and model improvements are enabled by many factors. Continuing NEO surveys for one, as seen by the update on Nesvorn et al. (2023) by Nesvorn et al. (2024a) to include additional years of asteroid detections. Models are also improved by an increase in computational power to perform statistical analysis and numerical simulations (Greenstreet et al. (2012) reworking Bottke et al. (2002)), or by the addition of albedo or compositional information (e.g. Nesvorn et al. (2024b) and Bro et al. (2024)). Even with several iterations, all models to date have made use of telescopic data covering NEOs with diameters ranging from the order of a kilometre down to ~ 30 metres (absolute magnitude range H=17 to H=25). Calibrating models based solely on telescopically observed NEOs is a limitation when making predictions for smaller impacting meteoroids. Results must be extrapolated downorders of magnitude in massto as small as 3.5 kgor approximately H = 37.25, such is the size of the meteoroid for the Cavezzo orbital meteorite (Gardiol et al., 2021). This may not be appropriate as we expect there to be differences between km and m-sized NEO populations. NEO models themselves show size-dependent relative contributions of main-belt sources for NEOs over the range H=17 to H=25 (Granvik et al., 2018). Additionally, the abundance of currently known NEOs in the S-complex with an LL-ordinary chondrite like spectral classification does not match the abundance of LL-ordinary chondrite meteorites found on Earth (Vernazza et al., 2008). Future surveys such as the Legacy Survey of Space and Time (LSST) and NEO Surveyor will discover more NEOs and drive observational completeness down to smaller and smaller sizes. In the meantime, there exist a wealth of observationsof smaller bodies (1 m)in the form of bolides and fireballs. These phenomena are from meteoroids well below the size of what is observable with telescopes and more closely represent the meteorite precursor population. A model calibrated to cm to m-sized objects To probe the size dependent processes for smaller asteroids, we approach NEO modelling from a new direction. We calibrate a NEO model to Earth impactors using the data from the Global Fireball Observatory (Devillepoix et al., 2020). The Global Fireball Observatory is a network of cameras around the world optimised to the detection and triangulation of fireballs. The dataset we use consists of more than 1,200 triangulated fireballs spanning 9 years of observations. The pre-atmospheric masses of the meteoroids range from 0.01 kg to 100 kg; probing the centimetre to metre-sized bodies. Preliminary results and future prospects We attempt to debias the dataset by weighting the sporadic events by their Earth impact probability. Following the methods of Nesvorn et al. (2023), we fit a model to the fireball orbital data.We hope to use this model to compare the relative delivery ratios of main-belt sources for cm to m-sized objects to those derived for ~ 100 metre NEOs. We will present the modelling methodology and preliminary results, discussing the challenges of using a relatively smaller dataset. References Bottke, W. F., Morbidelli, A., Jedicke, R., et al. 2002, Icarus, 156, 399. Brown, P. G., McCausland, P. J. A., Hildebrand, A. R., et al. 2023, Meteoritics and Planetary Science, 58, 1773. Bro,M., Vernazza, P., Marsset, M., et al. 2024, arXiv:2403.08552. Devillepoix, H. A. R., Cupk, M., Bland, P. A., et al. 2020, Planetary and Space Science, 191, 105036. Gardiol, D., Barghini, D., Buzzoni, A., et al. 2021, MNRAS, 501, 1215, Granvik, M., Morbidelli, A., Jedicke, R., et al. 2016, Nature, 530, 303. Granvik, M., Morbidelli, A., Jedicke, R., et al. 2018, Icarus, 312, 181. Greenstreet, S., Ngo, H., Gladman, B. 2012, Icarus, 217, 355. Harris, A. W. Chodas, P. W. 2021, Icarus, 365, 114452. Morbidelli, A., Delbo, M., Granvik, M., et al. 2020, Icarus, 340, 113631. Nesvorn, D., Deienno, R., Bottke, W. F., et al. 2023, The Astronomical Journal, 166, 55. Nesvorn, D., Vokrouhlick, D., Shelly, F., et al. 2024a, Icarus, 411, 115922. Nesvorn, D., Vokrouhlick, D., Shelly, F., et al. 2024b, arXiv:2404.18805. Vernazza, P., Binzel, R. P., Thomas, C. A., et al. 2008, Nature, 454, 858. Wiegert, P., Brown, P., Pokorn, P., et al. 2020, The Astronomical Journal, 159, 143.
Deam et al. (Wed,) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: