Fig. 1. (Left 3) a) (LROC M119815703); b) (LROC M113921307R);  c) LROC M119815703+NAC DTM). Fig. 2.  (Right 2) a) LROC M119815703 showing locations of NAC DTM profiles. b) NAC DTM profiles.

References: 1) Braden et al. (2014) Nat. Geosci. 7, 787. 2) Qiao et al (2017) Geology 45, 455. 3) Wilson & Head (2017) JVGR 335, 113.  4) Qiao et al (2017) MAPS 53, 455.  5) Basilevsky (1976) PLSC7, 1005. 6) Zhang et al, (2021) JGR-P 126, e2021JE006880.

How to cite: Head, J., Qiao, L., Ivanov, B., and Wilson, L.: Ina summit pit-crater: Geology and stratigraphy of a young impact crater and implications for unit substrate characteristics, emplacement sequence and age., Europlanet Science Congress 2024, Berlin, Germany, 8–13 Sep 2024, EPSC2024-1160, https://doi.org/10.5194/epsc2024-1160, 2024.

INTRODUCTION

A better understanding of  lunar geology is critical both scientifically and practically for exploring and settling the Moon in the next decades. Improving our knowledge about the formation and evolution of the Moon helps us 1) to understand the geology of Earth and other terrestrial bodies in the Solar System, and 2) to prepare for in-situ utilisation of lunar resources. Irregular mare patches (IMPs), as well as lava tubes, pits and caves are such lunar geological phenomena that offer progress with both tasks. Even though multiple IMPs were found on the surface of the Moon, their age and formation processes remain enigmatic. Furthermore, many pits have been detected in various lunar geological settings, but it remains uncertain whether any of these openings could lead to extended cave conduits underground. The proposed Lunar Geology Orbiter LUGO aims primarily to reveal the formation ages and mechanisms of IMPs, and secondarily to identify the distribution and dimensions of lava tubes for future exploration.

WHY IRREGULAR MARE PATCHES?

Controversy surrounds the formation age of IMPs because very few impact craters are present at their surface. Whereas one scenario assumes that IMPs consist of compact igneous rocks and thus are relatively young (>100 My), another scenario assumes the existence of old (<3 Gy) but highly vesicular lava foams [1, 2]. The general shape of IMPs and their rugged landform characteristics are well known, but available Digital Terrain Models do not allow unambiguous determination of the properties of the material(s) in which the observed impact craters were formed. It is hence still impossible to distinguish between two possible scenarios for the formation of IMPs [1]. Recently, analysis of hyperspectral data revealed that darker deposits surrounding some IMPs as well as the IMP surfaces themselves contain little to no glassy material, and are barely distinguishable mineralogically from the surrounding mare material [3]. Despite these discoveries, it remains unclear how IMPs originated and what their actual age is, with far-reaching consequences for understanding the thermal evolution of small planetary bodies. For example, young age of IMPs might suggest that we could still expect volcanic eruptions on the Moon.

WHY LUNAR LAVA TUBES?

 Lava tubes are underground voids that can be tens of kilometers long and tens of meters wide and are formed when the solidified roof of a lava flow remains after lava supply ends and the lava channel is drained out. Even if the detection of subsurface lava tunnels on the Moon is currently difficult [4], their existence is suggested by the presence of lunar pits, or skylights, which are collapsed features on the lunar surface with near-vertical walls. However, there is still no clear confirmation of continuations of lava tunnels from these potential entrances, and no map of their distribution exists yet. Detection of lava tubes by LUGO would enable us to evaluate their basic characteristics (size, length, depth) as well as the potential for subsurface habitat utilization in the future, where future crews would be shielded from micrometeorites and cosmic radiation [5]. The identification of lava tube dimensions and morphology together with surface observations and composition of the lava would enable estimating the effusion rate, viscosity and related temperature of lunar lava under lower specific gravity.

LUGO payloads

To achieve the objectives of LUGO, the orbiter would collect targeted imagery and topographic data of the lunar surface and subsurface at a very high resolution from a highly eccentric orbit by a quartet of payloads: a ground penetrating radar (GPR), a LiDAR, a hyperspectral camera, and a narrow-angle camera (NAC). Combining such measurements would allow to characterise: a) the regolith thickness over IMPs’ and surrounding units and hence reveal whether IMPs were formed recently or in the distant past, b) the properties of the material forming IMPs and hence to find out if they are formed by lava foams or lava flows, c) variations in their spectral compositions across the lunar surface, d) boulder density and distribution estimates as a proxy of regolith maturity, e) nature of the subsurface volcanic feeder system to IMPs. Furthermore, these payloads will allow to compare the subsurface detection of lava tubes as voids (with the GPR) with morphological indicators at the lunar surface (with the stereo-capability of the NAC). The proposed payloads could also allow unprecedented investigations of secondary geological targets such as floor-fractured craters and lunar domes. Future investigations could assess if an end-of-mission impact on an IMP target could provide critical information regarding the lithological properties of IMPs. The LUGO mission concept could provide a feasible way to explore these unknown aspects and could be adapted to fit funding and logistical restrictions. A LUGO mission would provide efficient synergies with already planned lunar missions, and will serve as a blueprint for future repeated observation missions that will help uncover the relation between the geological characteristics and structures at the lunar surface and the geological architecture of the shallow lunar crust.

ACKNOWLEDGEMENT

This study was financed in 2023 by ESA contract 4000141104 in the framework of the Open Space Innovation Platform (OSIP) obtained by TRL Space Systems s.r.o., Brno, Czech Republic.

REFERENCES

[1] Qiao, L., et al. (2021). Ina Lunar Irregular Mare Patch Mission Concepts: Distinguishing between Ancient and Modern Volcanism Models. The Planetary Science Journal, 2, 66.

[2] Wilson, L., & Head, J. W. (2017). Eruption of magmatic foams on the Moon: Formation in the waning stages of dike emplacement events as an explanation of “irregular mare patches”. Journal of Volcanology and Geothermal Research, 335, 113-127.

[3] Vannier, H., et al. (2024). Constraining formation hypotheses for irregular mare patches on the Moon with orbital reflectance spectra. Journal of Geophysical Research: Planets, 129, e2023JE008108.

[4] Wagner, R. V., and Robinson, M. S. (2022). Lunar pit morphology: implications for exploration. Journal of Geophysical Research: Planets, 127(8), e2022JE007328.

[5] Naito, M., et al. (2020). Radiation dose and its protection in the Moon from galactic cosmic rays and solar energetic particles: at the lunar surface and in a lava tube. Journal of Radiological Protection, 40(4), 947.

How to cite: Poppe, S., Broz, P., Sofge, K., Kereszturi, A., Losiak, A., Hauber, E., Divoký, M., Kohout, T., Hargitai, H., Bohovic, R., Viru, J., Pajusalu, M., Carrer, L., Bruzzone, L., Gomes, R., Peace, J., Saimoon Islam, Q., Sauro, F., and Fernando, B.: Studying lunar Irregular Mare Patches and lava tubes with the Lunar Geology Orbiter, Europlanet Science Congress 2024, Berlin, Germany, 8–13 Sep 2024, EPSC2024-1275, https://doi.org/10.5194/epsc2024-1275, 2024.

Introduction: Limited modern day laboratory far-ultraviolet (FUV) reflectance data of minerals, ices, and a near absence of Apollo soil measurements beyond those collected a few decades ago [1, 2], has hindered a more complete understanding of the lunar surface observations returned by the Lunar Reconnaissance Orbiter’s Lyman-Alpha Mapping Project (LRO-LAMP) relative to other instruments. Measurements in the FUV are demanding compared to measurements in the near-ultraviolet (NUV) through thermal infrared (TIR), due to vacuum requirements and far lower signal available. However, since LAMP and the LRO Camera Wide Angle Camera (WAC) have been returning observations, the researchers of the lunar FUV have begun collecting topics that necessitate further investigation in a laboratory to gather additional context.

Recent work at APL’s Laboratory for Spectroscopy under Planetary Environmental Conditions (LabSPEC) and SwRI’s Southwest-ultraviolet reflectance chamber (SwURC) facilities have been at the forefront to remedy this. Recent examinations of minerals, glasses, analogs, lunar soil simulants, and Apollo soils are under way or recently published [3-5]. Here, we examine the lunar highland Apollo soils 61220, 61141, and 62231. These lunar soils were selected to examine maturity in the FUV and in comparison with the MUV through the mid-infrared (MIR). They have similar low-iron and low-titanium chemistries, and a range of maturities with I_s/FeO intensities of 9.2, 56, 91 for 61220, 61141, and 62231, respectively [6].

Methods: Spectra were collected in the APL LabSPEC facility under high vacuum conditions (10^-6-10^-7 Torr). FUV-NUV data were collected using a McPherson monochromator (130-570 nm) using MgF₂ as the standard and a scintillating material in front of a photomultiplier tube attached to chamber. VIS-NIR data are collected using a Spectra Vista Corporation (SVC) HR-1024i point spectrometer (350-2500 nm) using MgF₂ as the standard. MIR data are collected with a Bruker Vertex 70 lab FTIR (1.8-8 μm) using diffuse Au as the standard. Both use a halogen light source with beam splitters (Quartz, KBr) and both spectrometers are mounted outside the chamber at dedicated ports 60° from the light source (i=15°, e=45°). The SVC and FTIR detectors are mounted on a linear stage that allows toggling between the two spectrometers. A full UV to MIR (~0.13 to ~8 μm) spectrum is generated by combining 3 spectral ranges, scaled to the SVC VIS.

Results: Starting in the familiar NIR to MIR (Fig. 1a), samples 61220, 61141, and 62231 show what is expected of their maturities. Samples 61141 and 62231 show the darkened albedo and reddened spectral slopes recognized in maturing soil samples. The 3 μm water absorption feature may show slight attenuation, pending confirmation. In the VIS (Fig. 1b), these characteristics continue, but the differences in albedo between sample spectra decrease, particularly for the submature and mature samples (61141 & 62231). This gradual decrease in albedo difference continues in the NUV until there no longer appears to be a statistical difference between 61141 and 62231 in the MUV (~225 nm; Fig. 1c). In the FUV (Fig. 1d), any remaining differences between immature, submature, and mature Apollo soils samples is gone by ~160 nm. Measurements <150 nm can be collected (Fig. 1d), but signal is insufficient here.

Discussion: The potential implications of these measurements are consequential for our understanding of the lunar surface. The darkening and lessening of differences in albedo and slope between lunar soils of differing maturity levels moving from the MIR to the UV, particularly the dramatic changes in the transition from the VIS to NUV, is not new. However, these measurements do appear to confirm that the UV, and the MUV to FUV in particular, are more sensitive to the effects of space weathering on airless body soils [7]. In fact, conditions and samples measured here present an inability to differentiate submature from mature soils. However, these measurements do potentially explain differences between LRO’s LAMP and LROC WAC. For example, on the global Moon only younger craters, like Copernican and younger (Tycho, Jackson, etc.), are observable. More specifically, Reiner Gamma shows differences in a swirl, or albedo difference, between LAMP FUV and the WAC NUV. In particular, where magnetic intensity lessens in the southern and northern ‘limbs’ of Reiner Gamma (Fig. 2), it is more difficult to definitively detect these regions of the swirl with LAMP [8]. Waller et al. [8] suggest this may be due to lessened solar wind stand-off as a result of solar wind variability, where submature and mature sample trends are indistinguishable in the FUV (Fig. 1). However, these surface regions still possess “swirl-like” patterns detectable by WAC NUV because of ongoing solar wind standoff reducing weathering, where submature and mature sample trends become more discernable in the NUV-MIR (Fig. 1). However, this stands in contrast to reports by [9, 10] of photometric anomalies and swirls being detected by LAMP but not necessarily by the LROC WAC. In fact, the laboratory measurements collected here initially suggest the opposite effect. In this context, it is important to note those observations were made during a different nighttime context, under hemispheric (interplanetary medium + starlight) rather than point illumination conditions, and deeper in the FUV at Lyman-a (121.6 nm). The Apollo laboratory spectra collected here demonstrate that at those low wavelengths, below ~150 nm, a different scattering regime is dominating. Additional FUV laboratory measurements are necessary.

On-Going Work: Further TEM and EELS examination of grains of each lunar sample is underway at the JHU Materials Characterization and Processing (MCP; https://engineering.jhu.edu/MCP/) facility.

References: [1] Lucke (1976) AJ, 81, 1162 [2] Wagner (1987) Icarus, 69, 14. [3] Hibbitts & Stockstill (2018) AAS/DPS, 50, 504-2, [4] Raut (2018), JGR. [5] Gimar (2022) JGR, 127, (11). [6] Morris (1978) LPSC, 2287. [7] Hendrix & Vilas (2006) AJ, 132, [8] Waller (2022) FASS., 9, fspas.2022.926018. [9] Cahill (2019) JGR, 2018JE005754, [10] Cahill (2017) LPSC, 48, 2947.

Figure 1: Immature (black), sub-mature (green), and mature (red) Apollo 16 lunar highlands soils.

Figure 2: Observations of Reiner Gamma lunar swirl in LROC WAC NUV and LAMP FUV off/on band ratio.

How to cite: Cahill, J., Cahill, K., Hibbitts, K., Livi, K., Ramprasad, T., Waller, D., and Retherford, K.: Implications for interpreting LRO LAMP observations from an examination of Apollo lunar soils spectroscopically and microscopically, Europlanet Science Congress 2024, Berlin, Germany, 8–13 Sep 2024, EPSC2024-1337, https://doi.org/10.5194/epsc2024-1337, 2024.

Introduction:  The composition and provenance of the materials in South Pole - Aitken Basin (SPA) on southern farside is essential to a number of unresolved science questions relevant to lunar and solar system evolution. The Chang’E-4 mission is the first landed mission to this unexplored region, which provide a unique chance to further constrain the composition and provenance of the lunar interior [1].

There is still controversy about the composition and provenance of materials in Chang 'e-4 landing site [1-7]. The first spectral interpretation results based on the Modified Gaussian Model (MGM) indicate that the landing site is dominated by Low-Ca Pyroxene (LCP) and olivine, which may represent deep-seated materials potentially from the lunar mantle, delivered to the Chang’E-4 landing site by ejecta from the Finsen crater [1-3]. The Hapke model was also used to infer the minerals and glasses’ abundances, which indicated that the landing site is dominated by plagioclase and lesser amount of mafic minerals [4-6]. Other study suggests that the composition of the landing site is still dominated by mare materials, which may be excavated and delivered by Zhinyu Crater [7].

The Yutu-2 rover has been exploring on the lunar surface for more than 60 lunar days, lots of in-situ spectra have been obtained, we will use these in-situ spectral data, orbiting spectral data (M³) and Apollo lunar soils' spectral data in the laboratory to perform a detailed survey on the composition and provenance  of materials on the Yutu-2 rover tranverse.

Data and methods: Over 60 lunar days’ data of the Visible and Near-Infrared Imaging Spectrometer (VNIS) on the Yutu-2 lunar rover and the orbiting spectral data of the Moon Mineralogical Mapper (M³) are used. The VNIS data have been processed by dark current subtraction, flat field and instrument temperature correction, radiometric correction, reflectance calculation and spectral smoothing [1], etc. After deducting some data affected by terrain shadows and scattered light, a total of 131 spectral data of lunar soils were selected. For M³ data, the spectral data of some fresh impact craters in the ejecta area of Finsen impact crater and the inner area of Zhinyu impact crater are selected. The location and spectral curves of M³ data are shown in Figure 1. Besides, the spectral data of lunar soils (mare and highland) obtained by Relab are also used.

Figure 1: The location of typical spectra of the selected M³ data. a) the spectral data locations of the fresh impact craters selected along the wall of Finsen impact crater (points A and B) and along the direction of ejecta (points C-G), H point located in side of Zhinyu impact crater. b) Typical spectral curves of the selected M³.

Results and discussion:  We firstly calculated the absorption bands of VNIS, M³ and Relab data at ~1μm and ~2μm, the results show that the absorption bands of VNIS at ~1μm and ~2μm are different from M³ and RELAB data (Figure 2). The absorption bands of VNIS at ~1μm are mainly concentrated in the range of 0.95~1.0μm, while the absorption bands at ~2μm are mainly concentrated in the range of 1.95~2.1μm. The absorption bands of VNIS at 2μm is lower than that of the M³’s H point in the Zhiyu impact crater, and is closer or even shorter than that of M³’s A~G points in the Finsen impact ejecta. However, the absorption bands of VNIS at ~1μm is significantly higher than that of Finsen impact ejecta (A~G points) and Zhinyu impact crater (H points). The ~2μm absorption bands results indicate that the composition of the Chang 'e-4 landing site may be closer to the impact ejecta of Finsen crater, but the  ~1μm absorption bands results are different from that of the impact ejecta of Finsen crater. In order to further constrain the composition, the ~1μm asymmetry parameters are also calculated [8], and the results indicate that the Chang 'e-4 landing site may be rich in olivine or glass components (Figure 3).

Figure2: Plot of the absorption bands of VNIS, M3 and Relab spectral data at ~1μm and ~2μm. a) The black data points are VNIS spectral data, and the color data points are M3 spectral data selected in the ejecta direction of Finsen impact crater and Bajie / Zhinyu impact crater.

Figure 3: Plot of the ~1μm asymmetry of VNIS. The black data points are VNIS spectral data.

References: [1] Li.C. et al., (2019) Nature, 569. [2] Gou S. et al., (2019) EPSL, 528, 115829. [3] Gou S. et al., (2020)  Icarus, 345, 113776. [4] Lin H.L. et al., (2020)  NSR, 7, 913-920. [5] Hu X.Y. et al., (2019) GRL, 46, 9439-9447. [6] Ma P. et al., (2020) Icarus, 350, 113901. [7] Moriarty D. P. et al., (2020) LPSC, #2660. [8] Horgan B.H.N. et al., (2014) Icarus, 234, 132-154.

How to cite: Liu, B., Liu, D., Liu, J., Li, C., Su, Y., Zhu, X., and Zhang, H.: The composition and provenance analysis of materials on Chang’E-4 Yutu-2 rover traverse, Europlanet Science Congress 2024, Berlin, Germany, 8–13 Sep 2024, EPSC2024-491, https://doi.org/10.5194/epsc2024-491, 2024.

Energy circulation in geospace lies at the heart of space weather research. Establishing global mass and energy transportation image in the solar wind-magnetosphere coupling system is critical for space physics and space weather research. Remote sensing overcomes the difficulties of capturing global views and distinguishing spatiotemporal variations in in-situ particle and field detections. The moon is an idea platform for imaging the global magnetosphere. An extreme ultraviolet camera operating at 30.4 nm has successfully captured the global plasmaspheric images with the Chang’e-3 lunar landing mission. A new double-wavelength extreme ultraviolet camera and an energetic neutral atomic (ENA) imager have been carried by the Queqiao-2 satellite to image the magnetosheath at 30.4 nm, the plasmasphere at 30.4 nm, the ionospheric oxygen ion outflow and oxygen ion in the magnetosphere at 83.4 nm, and the ring current ENA. The two imagers will significantly benefit the investigations in solar wind-magnetosphere coupling.

How to cite: Zhang, X.-X., He, F., Liu, W., Sun, T., Zhang, X., He, L., Chen, B., and Yu, Q.: The extreme ultraviolet camera and energetic neutral atomic imager onboard the Queqiao-2 satellite, Europlanet Science Congress 2024, Berlin, Germany, 8–13 Sep 2024, EPSC2024-478, https://doi.org/10.5194/epsc2024-478, 2024.

Radiometric measurements of the (sub-)surface thermal emission allow determination of the microphysical structure (e.g. porosity and particle size) and thermophysical properties of the regolith. In our previous study (Bürger et al., 2024), we derived regolith grain size and regolith stratification from LRO/Diviner data (Paige et al., 2010) and a microphysical thermal model, but the derived parameter sets were non-unique. While radiometric observations in the infrared (e.g., LRO/Diviner) are sensitive to surface temperatures, microwave radiometric measurements are also sensitive to the thermal emission from the subsurface. Therefore, we will investigate whether the microwave data can be used to apply constraints on the sub-surface regolith properties (grain size, stratification) and the non-unique parameter sets derived in Bürger et al. (2024).

The microwave radiometer (MRM) on board the Chang'E-2 mission measured the brightness temperature of the lunar surface in four different frequency channels: 3, 7.8, 19.35 and 37 GHz (Feng et al., 2013; Zheng et al., 2019). It was in operation from October 2010 to May 2011 and the resolution of the instrument on the lunar surface was about two pixels per degree.

We filtered the Chang’E-2/MRM data to achieve the best quality by selecting only those pixels with low rock abundance, small local slope angle and within a narrow range of albedo values. The albedo filter also allowed us to separate measurements in the highlands and in the maria, as each has a characteristic difference in albedo. The measurements obtained in the maria were additionally filtered according to their TiO2 abundance, which has a pronounced influence on the optical properties of the regolith (Feng et al., 2020; Siegler et al., 2020; Sohn et al., 1994). The filtered data are sampled for every latitude in steps of 1° and the data points in the northern and southern hemisphere are combined under the assumption that the regolith properties are the same in both hemispheres. Figure 1 shows the filtered CE-2/MRM brightness temperatures measured at 37 GHz together with their mean values as a function of latitude for the highlands.

For the interpretation of the microwave measurements, a radiative transfer model is required in addition to a thermal model to generate synthetic brightness temperatures. In this project, we apply the radiative transfer model presented in Feng et al. (2020) and Siegler et al. (2020). First, physical temperatures in each layer are modelled using the microphysical thermal model introduced in Bürger et al. (2024), which describes the regolith in terms of grain size and volume filling factor. Second, a synthetic brightness temperature is obtained by multiplying the simulated physical temperature of each regolith layer with a weighting factor that depends on the frequency of the measurement and the relative dielectric constant, the loss tangent and the bulk density of the regolith layer, and then taking the sum of all weighted temperatures.

At the conference we will present and discuss the regolith properties derived from the CE-2/MRM data. In more detail, we will investigate the regolith properties for maria and highlands separately and revisit the latitudinal dependence of regolith properties. In Bürger et al. (2024) we found a latitudinal gradient between LRO/Diviner data and the microphysical thermal model, which could be reduced by a variation of the albedo as a function of solar incidence angle or a decrease in bulk density with increasing latitude. Figure 1 illustrates an initial comparison between model and Chang’E-2/MRM measurements and shows that, in contrast, the nighttime microwave data do not exhibit a pronounced latitudinal gradient. However, during the day and at the highest latitudes daytime shadowing effects are present. The brightness temperatures were modeled assuming constant regolith properties derived from a fit at 0° latitude and no albedo or bulk density variation with latitude was applied. These findings will be further investigated and discussed.

Figure 1: Filtered Chang’E-2/MRM measurements obtained at a frequency of 37 GHz as a function of local time and their corresponding mean values (black circles) for highlands. The measurements are collected in latitude bins with a bin size of 1°. The red solid line represents the modeled brightness temperature assuming constant regolith properties derived from a fit at 0° latitude for all latitudes.

References

Bürger, J. et al. (2024), JGR, 129(3). Feng, J. et al. (2020), JGR, 125(1). Paige et al. (2010), Space Sci. Rev., 150(1–4), 125–160. Siegler, M. A. et al. (2020), JGR, 125(9). Sohn et al. (1994), Jpn. J. Appl. Phys., 33, 5466-5470. Zheng et al. (2019), Icarus, 319, 627-644.

How to cite: Buerger, J., Feng, J., Siegler, M., and Blum, J.: Lunar regolith properties derived from Chang’E-2/MRM data: What can the microwave tell us?, Europlanet Science Congress 2024, Berlin, Germany, 8–13 Sep 2024, EPSC2024-83, https://doi.org/10.5194/epsc2024-83, 2024.

1. Introduction

Although the Moon lacks a global magnetic field, its crust features small-scale (smaller than a typical proton gyroradius) magnetized regions known as lunar magnetic anomalies [1] (Figure 1a). Their interaction with the solar wind gives rise to unique structures called lunar mini-magnetospheres [2]. These structures are characterized by a partial solar wind cavity surrounded by a region of enhanced precipitating proton flux [3] resulting from the deflection and reflection of protons above the anomaly [4]. As a significant fraction of the solar wind protons which interact with the lunar surface are backscattered as hydrogen ENAs [5], instruments measuring ENA and protons can be used to remotely observe lunar mini-magnetospheres and investigate their effect on the solar wind flow in-situ [6]. This study uses ENA and proton measurements from the Sub-KeV Atom Reflecting Analyzer (SARA) onboard Chandrayaan-1 [7] to examine the structure and dynamics of the magnetosphere-like object formed by the South Pole-Aitken (SPA) magnetic anomaly cluster.

2. Dataset and methods

We produced hydrogen ENA and proton emission maps of the lunar far-side using orbital measurements from the Chandraayan-1 Energetic Neutrals Analyzer (CENA) and Solar Wind Monitor (SWIM) from the SARA instrument. To understand the surface-solar wind interaction, we limited our dataset to CENA/SWIM measurements acquired when Chandraayan-1 was on the lunar day-side and when the Moon was in the solar wind. All measurements contaminated by UV radiations and obtained for off-nadir pointing spacecraft operation modes (>15 deg) were removed. To quantitatively compare emission maps obtained under varying observation geometries and upstream solar wind conditions, the measured hydrogen ENA flux was normalized by the modeled ENA flux that would be observed in the absence of magnetic anomalies. This modeled flux was calculated using the empirical hydrogen ENA scattering function and energy spectra derived previously [8, 9], along with the upstream solar wind parameters measured by the ACE and WIND spacecraft. Similarly, the measured reflected proton flux was normalized by the solar wind proton flux impinging the surface. The obtained normalized emission maps were then classified into high (> 0.6 nPa) and low (< 0.6 nPa) solar wind dynamic pressures (nmu2/2) to examine the influence of this parameter on the structure of the SPA magnetic anomaly cluster.

3. Results

A region of reduced ENA flux is observed above the SPA magnetic anomaly cluster (Figure 1b), suggesting that a large-scale magnetosphere-like object forms above the SPA cluster under all solar wind conditions available in the dataset. Figure 1b also reveals a large ENA-enhanced flux region surrounding the SPA cluster. This feature could result from the deflection of solar wind protons above this object. We also confirm significant proton reflection above the SPA magnetic anomaly cluster (Figure 1c). Local proton reflection rates appear to be correlated with surface magnetic field strengths and ENA flux reduction rates (Figures 1a, b, and c).

Figure 2 shows the proton and ENA emission maps under the high and low solar wind dynamic pressure cases. Figures 2e and 2f suggest that proton reflection rates above magnetic anomalies are anti-correlated with the solar wind dynamic pressure. A comparison of ENA emission maps between the two dynamic pressure cases (Figures 2b and 2c) reveals that the small-scale structures of the SPA magnetic anomaly cluster, as well as its ring-shaped enhanced ENA flux region, are more prominent under low dynamic pressures. However, the size and peak shielding efficiency of the SPA magnetic anomaly cluster do not appear to differ significantly between the high and low dynamic pressure cases. These results suggest that under low solar wind dynamic pressures, the structure of the SPA magnetic anomaly cluster is mainly driven by small-scale crustal field variations. However, under higher dynamic pressures, the magnetic fields of the SPA cluster could be compressed and behave as a coherent obstacle to the solar wind flow.

4. Concluding remarks

ENA and proton observations of the lunar far side reveal that the SPA magnetic anomaly cluster causes large-scale (>1000 km) effects to the solar wind flow. The characteristics of these disturbances imply that the SPA magnetic anomaly cluster forms a large magnetosphere-like object which responds differently to varying upstream solar wind conditions compared to mini-magnetospheres formed by smaller isolated magnetic anomalies. These results suggest that the global effects of the SPA cluster on the solar wind proton precipitation patterns and local characteristics have been underestimated. These findings are critically important for interpreting plasma measurements on lunar landers on the far side, for example, Chang’E-4. How anomalies of small (< 100 km) vertical extent create large (> 1000 km) horizontal structures remains to be explained. Possible mechanisms to be examined involve the setup of large-scale Hall electric fields and the resulting horizontal proton drift.

5. References

[1] Tsunakawa, H. et al. (2015), Journal of Geophysical Research: Planets 120,1160-1185.

[2] Lin, R.P. et al. (1998), Science 281, 1480-1484.

[3] Wieser, M. et al. (2010), Geophysical Research Letters 37.

[4] Lue, C. et al. (2011), Geophysical Research Letters 38.

[5] Wieser, M. et al. (2009), Planetary and Space Science 57, 2132-4.

[6] Vorburger, A. et al. (2013), Journal of Geophysical Research: Space Physics 118, 3937-45.

[7] Barabash, S. et al. (2009), Current Science 96, 526-532.

[8] Vorburger, A. et al. (2012), Journal of Geophysical Research: Space Physics 117.

[9] Futaana, Y. et al. (2012), Journal of Geophysical Research: Space Physics 117, 432-45.

6. Figures

Figure 1: Lunar far-side maps for a) crustal magnetic fields at 30 km altitude from Tsunakawa et al. (2015), b) reflected proton produced by SWIM measurements, and c) ENA emissions produced by CENA measurements. The reflected proton flux is normalized by the incident solar wind proton flux, and the ENA flux by the empirically modelled undisturbed backscattered flux (see text).

Figure 2: Lunar far side maps of a-c) the backscattered ENA and d-f) reflected protons. The map was produced under different solar wind conditions: using (a, d) all the data and (b, e) the low (<0.6 nPa) and (c, f) high (>0.6 nPa) solar wind dynamic pressure cases.

How to cite: Maynadié, T., Futaana, Y., Barabash, S., Fatemi, S., Wieser, M., Vorburger, A., Bhardwaj, A., Wurz, P., and Asamura, K.: Dynamics and Structure of the South Pole-Aitken Mini-Magnetosphere from Proton and ENA measurements from the SARA Instrument on-board Chandraayan-1, Europlanet Science Congress 2024, Berlin, Germany, 8–13 Sep 2024, EPSC2024-79, https://doi.org/10.5194/epsc2024-79, 2024.

Traditionally the Moon is considered “boring” by space plasma physicists. Indeed, no dense atmosphere/ionosphere, no large scale magnetic field, and the solar wind absorption by non-conductive surface make this body an outcast among “exciting” objects being the primary interest for space plasma physics. However, lunar exploration for the last 20 – 25 years revealed a completely different picture of our only satellite. The Moon is non-magnetized body but possesses magnetic anomalies, localized (mostly on the far side) magnetic field structures of <300 nT with a a size of 100 km, smaller than a proton gyroradius but larger than an electron one, perfect hybrid objects! The Moon is an airless body but has a tenuous exosphere with densities up to 10⁵ cm^-3 that are a source of heavy pick-up ions. The lunar surface covered by non-conductive regolith is rough and absorbing but significant particle reflection occurs both as ions and neutrals. The Moon is a large body of 1740 km radius but a zoo of kinetic effects was identified, in particular, when plasma expands into vacuum, e. g., the wake or voids related to local topography such as permanently shadowed regions. The Moon spends 75% of the orbital period in the solar wind but experiences highly variable plasma environments inside the magnetosphere. At the surface dust particles interact strongly with near-surface plasma that defines their dynamics.

We formulate four main unique overarching science questions for space plasma physics at the Moon (“the main four”):

• How do the solar wind and magnetospheric plasmas interact with magnetic anomalies?
• How does near-Moon plasma expand into vacuum?
• How does plasma interact with dust at the surface?
• How does the plasma - surface interactions? How does the lunar surface charge?

Research on these topics not only advance fundamental lunar science and space plasma physics but are also critical for exploration as outlined in the table below. The Moon is not “boring”! We need dedicated space plasma missions to the Moon.

How to cite: Barabash, S.: The Moon is an exciting object for space plasma physics: the main science questions, Europlanet Science Congress 2024, Berlin, Germany, 8–13 Sep 2024, EPSC2024-279, https://doi.org/10.5194/epsc2024-279, 2024.

The Advanced Small Analyzer for Neutrals (ASAN) instrument [1] is the first instrument to measure energetic neutral atoms directly on the lunar surface. Installed onboard of the Yutu-2 rover of the Chinese Chang’E-4, mission it started operations in January 2019. The landing site in the Karman crater on lunar far side is at the edge of the large magnetic anomaly in the South Pole-Aitken basin. The ASAN instrument has been operated periodically since, making use of the mobility of the rover to get different observation geometries.

When the solar wind interacts with the lunar surface, a portion of it is reflected back as energetic netural atoms. Previous studies have provided evidence of neutral hydrogen atoms [2] and solar wind protons being reflected from the surface. However, prior to ASAN, all these measurements were performed form orbit and no direct measurements on the surface had been conducted. ASAN’s observation location directly at the surface allows to investigate the microphysics of the solar wind-surface interaction process and to study the effects of local magnetic anomalies on the emitted energetic neutral particle flux.

The ASAN instrument is an 8th generation instrument of the SWIM family [3]. ASAN uses a charge conversion surface to convert energetic neutral atoms to positive ions and analyzed them with s surface-interaction based time-of-flight system combined with an electrostatic analyzer and an electrostatic elevation scanning system. This enables ASAN to to measure the direction-, energy-, and mass-resolved energetic neutral atom flux on the surface.

We report on the instrument status and present a review of energetic neutral atoms observations done by ASAN on the lunar surface and discuss possible implications for the near-surface plasma environment.

[1] M. Wieser, S. Barabash, X.-D. Wang, A. Grigoriev, A. Zhang, C. Wang, and W. Wang. The Advanced Small Analyzer for Neutrals (ASAN) on the Chang’E-4 Rover Yutu-2. Space Science Reviews, 216(4):73, 2020.
[2] M. Wieser, S. Barabash, Y. Futaana, M. Holmström, A. Bhardwaj, R. Sridharan, M. B. Dhanya, A. Schaufelberger, P. Wurz, and K. Asamura. First observation of a mini-magnetosphere above a lunar magnetic anomaly using energetic neutral atoms. Geophys. Res. Lett., 37(5), 03 2010.
[3] M. Wieser and S. Barabash. A family for miniature, easily reconfigurable particle sensors for space plasma measurements. Journal of Geophysical Research: Space Physics, 2016

How to cite: Wieser, M., Barabash, S., Wang, X.-D., Williamson, H., and Stenberg-Wieser, G.: The Advanced Small Analyzer for Neutrals (ASAN) instrument on Chang’E-4: A review of five years on the lunar surface, Europlanet Science Congress 2024, Berlin, Germany, 8–13 Sep 2024, EPSC2024-238, https://doi.org/10.5194/epsc2024-238, 2024.

Several lunar samples collected during the Apollo missions were kept sealed and stored in controlled conditions in order to be studied decades later exploiting future, more advanced capabilities. Two of the preserved samples are Apollo 17 double drive tube 73002/73001. The double drive tube extracted a core sample of the Light Mantle deposit at Station 3 in the Taurus-Littrow Valley (Figure 1). As part of the NASA Apollo Next Generation Sample Analysis (ANGSA) program, samples 73002 and 73001 became available to study in 2019 and 2022, respectively [1][2]. The Apollo 17 double drive tube sampled the Light Mantle deposit material down to a depth of 70.6 cm; the effective material length of each tube is 21.3 cm for 73002 and 34.9 cm for 73001 (some material was lost during sampling). This represents an unprecedented opportunity to study the Light Mantle deposit to previously unsampled depths.

The Light Mantle deposit represents the only extraterrestrial landslide to have ever been studied in-situ. The Light Mantle is a 5-km-long deposit that formed from debris mobilised from the South Massif, a 2.2-km-high mountain in Taurus-Littrow Valley [3][4]][5]. The origin and hypermobility of the Light Mantle remain debated. The recently opened Apollo 17 double drive tube 73002/73001 provides a new set of samples to investigate the origin and the emplacement mechanisms of the Light Mantle.

Prior to dissection and opening of the sample containers, the double drive tube was scanned using X-ray computed tomography (XCT) [6] so that a digital, high-resolution 3D dataset of the whole core sample is available and represents one of the ‘next generation’ capabilities now available to researchers to interrogate the data using novel approaches and obtain new insights into lunar material and processes. Additionally, the 3D dataset preserves the 3D context of all the subsamples extracted from the original core sample.

In this work, we used high-resolution X-ray computed tomography (XCT) scans and high-resolution scans of thin sections of the upper 20 cm of the core, sample 73002, and conduct 3D clast-size analysis and investigation of clast morphological fabric. The aims of this work are to:

• Present a 3D data processing workflow that can be used as a basis for future investigations of lunar core samples.
• Demonstrate potential scientific information that can be extracted from 3D analysis of lunar core samples.

Within this framework, we conduct: (1) 3D grain size analysis and compare the results with grain size analyses conducted on the grains extracted during the dissection of the core sample; (2) 3D analysis of clast size distribution. Additionally, as part of our investigation of the emplacement mechanism of the Light Mantle, we use 2D continuous thin sections (backscattered electron maps) of sample 73002 to search for diagnostic clast fabric similar to those generated during the friction experiments conducted in simulated lunar landslides [7]. The clast fabric is called Clast Cortex Aggregate (CCA) and it’s constituted by a central clast surrounded by nano-scale fine material (Figure 2).

The data analysis and visualization of the XCT dataset of core sample 73002 were performed using 3D visualization software Avizo 2022.2 by ThermoFisher. We customized our workflow and established a best-practice protocol so that they can be used as reference for future analysis of 73001. We used backscattered electron (BSE) maps of the sample’s thin sections (73002,6011; 73002,6012; 73002,6013; 73002,6014) [8] to search for (CCAs).

The results of clast-size distribution show that the sample is characterised by lack of the largest clast-size fraction in the top 4-5 cm, which we attribute to the fragmentation of larger regolith-hosted clasts and bedrock by space weathering and meteoroid bombardment. The observation of an uppermost layer presenting characteristics of reworked regolith is consistent with results from previous studies of lunar regolith and from other works conducted on 73002 as part of the ANGSA program [8][9]. Moreover, we found extensive presence of CCAs. The formation of CCAs in natural and lab-simulated landslides is attributed to granular flow dynamics, presence of nanoparticles, and adhering forces between such particles. Therefore, we concluded that the presence of CCAs in sample 73002 represents the first evidence that the Light Mantle was emplaced as a granular flow. This work shows that valuable information can be extracted from the 3D analysis of lunar core samples and, more generally, it shows the potential of morphometric and morphological clast analysis using high resolution XCT dataset and thin sections combined.

Our work represents the first study to conduct a 3D clast analysis of a lunar regolith core sample. As such, it constitutes an important step in showing the novel information that can be extracted, and presenting a potential workflow for studying lunar regolith core samples that will be collected during future missions to the Moon.

REFERENCES. [1] Shearer et al. (2020). AGU Fall Meeting. Abstract V013-0001. [2] Shearer et al. (2022). 53rd LPSC. Abstract 2546. [3] Schmitt (1973). Science, 182(4113), 681–690. [4] Lucchitta (1977). Icarus, 30(1), 80–96. [5] Kokelaar et al. (2017). JGR:Planets, 122(9), 1893-925. [6] Gross et al. (2023).     https://curator.jsc.nasa.gov/lunar/angsa_attachments/aapreliminary_20catalog/preliminary_73001-73002_catalog.pdf. [7] Magnarini et al. (2023). JGR:Planets, 128(6), e2022JE007520. [8] Bell et al. (2024). Submitted to JGR:Planets – In review. [9] Neuman et al. (2024). Submitted to Science – In review.

Figure 1 – a) Oblique view of Taurus-Littrow Valley; the yellow dot shows the location of the Apollo 17 landing site (LROC/NAC image M1266925685L. Image credit: NASA/GSFC/ASU); b) A frame from the original footage recorded from the Lunar Rover Vehicle onboard camera the showing astronaut Gene Cernan extracting the double drive tube containing material from the Light Mantle deposit. c) Double drive tube in the ground prior extraction (AS17-137-20981. Image credit: NASA). The yellow star in the three panel shows the location where the double drive tube core sample 73002/73001 was collected.

Figure 2 – Comparison of Clast Cortex Aggregates (CCAs). (a-b) CCAs generated during the friction experiments conducted on anorthosite-bearing gouges by [7]; (c-f) CCAs found in the Apollo 17 core sample 73002. The red dotted lines and the white dotted line in (d) show the corona of finer fragments found around clasts.

How to cite: Magnarini, G., Mitchell, T. M., Grindrod, P. M., Bell, S. K., Joy, K. H., Eckley, S. A., Zeigler, R. A., Schmitt, H. H., and Shearer, C. and the ANGSA Science Team: 3D and 2D clast analysis of Apollo 17 core sample 73002: insights into the Light Mantle dynamics and regolith reworking., Europlanet Science Congress 2024, Berlin, Germany, 8–13 Sep 2024, EPSC2024-329, https://doi.org/10.5194/epsc2024-329, 2024.

The surface heat flux provides important constraints on the present-day thermal state of the lunar interior. In situ surface heat flux measurements, performed during the Apollo program, obtained surface heat flux values of 21±3 and 14±2 mW/m² at the landing sites of Apollo 15 and 17, respectively [1]. Recently, a peak heat flux of ~180 mW/m² was inferred by [2] from the Chang’E 1 and 2 data at the Compton-Belkovich location. A lower bound for global lunar heat flux of ~6 mW/m², based on measurements of the Diviner Lunar Radiometer Experiment onboard LRO, has been suggested for Region 5, a location at the eastern edge of Haworth crater [3]. In addition to heat flux measurements, global thermal expansion/contraction estimates can be used to constrain the thermal state of the interior throughout lunar history [4].

Differences between the surface heat flux measurements, even for geographically close regions, indicate a high heat flux variability on the Moon. Previous work investigated regional combinations of crustal thermophysical properties (thickness, density, thermal conductivity), distribution of heat producing elements (HPEs), and heat flux coming from the mantle to explain the differences between the two Apollo measurements [5,6]. The results of these regional-scale models suggested  heat-flux values of 7-13 mW/m²  and 12-14 mW/m²  at the crust-mantle interface and for the global average, respectively. These studies also highlighted the need to include regional-scale scenarios within global thermal evolution models and investigate key aspects (e.g., the geographical extent of a subsurface KREEP layer), in order to relate local heat flux measurements and regional-scale estimates to the global properties of the Moon. 

Here, we construct 3D thermal evolution models using the fluid solver GAIA [7]. The interior dynamics of the Moon are simulated over 4.5 billion years, by solving the conservation equations of mass, linear momentum and thermal energy. Similar to [8], we account for  spatially variable crustal thickness, derived from gravity and topography data [9] (Fig. 1a). We consider higher HPEs abundances in the PKT and crust compared to the mantle, and compute the interior dynamics (Fig. 1b) using an Arrhenius viscosity for diffusion creep similar to [11]. This setup is designed to allow for an extensive investigation of lunar crustal properties and their spatial variability.

In our models we vary critical parameters such as the location, size, thermal conductivity, and HPE enrichment of the PKT region, but also the location of a putative KREEP layer (i.e., within or below the crust). Finally, we consider various thermal conductivity values and HPE enrichment of the anorthositic crust, and initial temperature profile of the interior. In addition to present-day surface heat flux, we compute the heat flux at the crust-mantle interface and also estimate the time-variable thermal expansion/contraction during lunar evolution. These values are compared to all available constraints [1-6] to select best-fit models.

Our models that are best compatible with the Apollo measurements are in agreement with [5] and [6]. These models have a bulk uranium content of 25 ppb [11], and show average and standard deviation surface and crust-mantle interface heat flux values of ~14±5 and ~8±1  mW/m², respectively (Fig. 2a and b). For the Compton-Belkovich anomaly, none of our models can reproduce the high heat flux value proposed by [2]. Therefore, we conclude that the inferred heat flux value of ~180 mW/m² indicates either very specific local processes (e.g., overly high radiogenic enrichment) [2] or large measurement uncertainties.

We find that, without considering 3D lateral variability in thermal conductivity across the lunar surface, measurably lower heat flux values at Region 5 [3] with respect to Apollo 15 & 17 require for KREEP material to extend at least partly beneath mare Serenitatis. In this case, the Apollo 15 measurement would be representative of the PKT average heat flux, while Apollo 17 would lie on its edge (Fig. 2c). On the other hand, a smaller PKT could imply that the low heat flux at Region 5 is caused by different phenomena, for instance a laterally variable thermal conductivity. Heat flux measurements that will be performed by the Farside Seismic Suite [12] at Schrödinger crater, if successful, will provide key information that would help to exclude one of these two scenarios, and thus potentially constrain the extent on the KREEP layer underneath PKT region.

The full spatial variations of the surface heat flux on the Moon obtained by our models are an important step forward towards understanding the thermal history and present-day state of the lunar interior. Such models can help to put current and future heat flux measurements into a global context and to constrain the distribution of the KREEP layer beneath the PKT region. Future work will include a laterally variable thermal conductivity of the crust to test the effects of the spatial distribution of lunar regolith on the surface heat flow and subsurface temperature variations.

References:

[1] Langseth et al., 1976; [2] Siegler et al., 2023; [3] Paige & Siegler, 2016; [4] Andrews-Hanna et al. 2013; [5] Siegler and Smrekar, 2013; [6] Warren and Rasmussen, 1987; [7] Hüttig et al., 2013; [8] Plesa et al., 2016;  [9] Broquet & Andrews-Hanna, 2023; [11] Laneuville et al., 2013 [12] Panning et al., LPSC 2024.

How to cite: Santangelo, S., Plesa, A.-C., Broquet, A., Breuer, D., and Root, B. C.: The present-day surface heat flux of the Moon from global geodynamic and crustal thickness models., Europlanet Science Congress 2024, Berlin, Germany, 8–13 Sep 2024, EPSC2024-959, https://doi.org/10.5194/epsc2024-959, 2024.

Introduction

The Moon has many permanently shadowed regions (PSRs) inside of craters at the poles, which are only illuminated by indirect (reflected) sunlight and thermal radiation because of the small solar incidence angle and obliquity. That is why the terrain of the poles strongly influences the temperature profile of the regolith. These exceptionally cold PSRs are areas that are most likely to harbor water ice (Vasavada 1999; Watson et al. 1961) and are therefore of interest to future landing missions. One example is the NASA CLPS-10, which carries ESA’s PROSPECT instrument, which, using the Drill, will sample the lunar surface up to 1 m depth with the aim to detect volatiles including water ice if present (Boazman et al. 2023).

The temperature of the regolith can be described as a function of depth using a one-dimensional thermal model. In craters, it is necessary that the incident radiation on each surface element is accurately considered as a boundary condition, as this depends strongly on the surrounding topography. The crater walls can block radiation, but they can also reflect it.

Coupling the surface boundary condition determined in this model with a thermal model from Bürger et al. (2024) for the regolith layers allows conclusions to be drawn about the depth and position of water ice in such craters and surface temperatures measured remotely by instruments such as Diviner (Paige et al. 2010).

Method

In our model, the topography of the region of interest is then transformed into a mesh of triangles using Delaunay triangulation. For each facet, the conservation of energy applies, which states that the radiated heat must be equal to the direct absorbed solar radiation, plus the direct absorbed IR radiation emitted by all other facets, plus the absorbed radiation (solar and IR) reflected by all other facets, plus the heat flux from the sub-surface. Reflections in the visible and IR range are taken into account for all orders. The sun is approximated as a point source and its position is calculated using SPICE. Whether a facet is seen by the sun is determined using ray tracing. The proportion of radiation transmitted from one facet to another is proportional to the view factor, also known as the form factor, and the associated albedos and emissivities. Previous similar models, e.g. Potter et al. (2023), Vasavada (1999) or Gläser et al. (2019), usually use only angle-independent albedos. However, laboratory measurements (Foote et al. 2020), thermal models for the lunar surface (e.g. Keihm 1984; Vasavada et al. 2012; Hayne et al. 2017; Bürger et al. 2024) and a model that estimates the albedo from the lunar noontime surface temperatures as a function of latitude (Feng et al. 2020) show that the albedo is indeed angle-dependent, which is why this effect is also taken into account, as some other models already do (King et al. 2020).

Initial Results

As a first step and as a verification method, we neglect the sub-surface heat flow, i.e. the thermal model, and compare the numerical raytracing model for a constant solar incidence angle (equilibrium case), constant albedo and a perfectly bowl-shaped crater (see fig. 1) with the analytical solution of Ingersoll et al. (1992). We find a good agreement between these two models.

Figure 1: Equilibrium surface temperature distribution of a perfectly bowl-shaped crater for a solar incidence angle of e_⊙ = 15° (emissivity = 0.99, albedo = 0.3).

In the next step, the model was equipped with an angle-dependent albedo. As expected, the albedo models used always cause the temperature in the crater to drop, as less radiation is absorbed at higher angles of incidence. The extent to which the temperature drops depends heavily on the albedo model and can be up to 30 K.

Applying the model to real craters with realistic topography produces surface temperature maps for a specific position of the sun (again in the equilibrium case, see fig. 2) or over the course of a lunar day (e.g. for maximum temperatures) while also neglecting sub-surface heat flow.

Figure 2: Equilibrium surface temperature distribution for solar incidence angle of e_⊙ = 20.07° with angle-dependent albedo (Feng et al. 2020) for the Theon Junior crater.

Outlook

In the future, the sub-surface heat flow will be taken into account by coupling the thermal model of Bürger et al. (2024) with the surface boundary condition determined here to obtain more accurate surface temperatures and temperatures of the deeper layers of the regolith.

The primary objective is then to determine the water ice stability as a function of location and depth. This will provide us with valuable constraints for upcoming missions and instruments searching for water ice at the lunar South pole, such as the Prospect drill, in order to identify suitable drilling targets.

References

Boazman, S. J. et al. (2023). 54th LPSC. Vol. 2806. LPI Contributions, 2019. Bürger, J. et al. (2024). JGR Planets 129.3. Feng, J. et al. (2020). JGR Planets 125.1, e2019JE006130. Foote, E. J. et al. (2020). Icarus 336, 113456. Gläser, P. et al. (2019). A&A 627, A129. Hayne, P. O. et al. (2017). JGR Planets 122.12, 2371–2400. Ingersoll, A. P. et al. (1992). Icarus 100.1, 40–47. Keihm, S. J. (1984). Icarus 60.3, 568–589. King, O. et al. (2020). P&SS, 182, 104790. Paige, D. A. et al. (2010). Science, 330.6003, 479–482. Potter, S. F. et al. (2023). J. Comput. Phys., X 17, 100130. Vasavada, A. (1999). Icarus 141.2, 179–193. Vasavada, A. R. et al. (2012). JGR Planets 117.E12.

How to cite: Volkhardt, E., Bürger, J., and Blum, J.: 3D Surface Radiative Transfer Model via Raytracing for Airless Bodies with the Application to Lunar Craters and Possible Ice-Stability, Europlanet Science Congress 2024, Berlin, Germany, 8–13 Sep 2024, EPSC2024-84, https://doi.org/10.5194/epsc2024-84, 2024.

Introduction: Dark mantle deposits (DMDs) are one of the lunar lithological units commonly composed of mafic minerals mixed with pyroclasts [1,2]. Lunar pyroclasts in the form of partially crystallized Fe-Ti bearing volcanic glasses provide records of the early history of lunar volcanism [3]. DMDs of diverse nature in terms of their mineralogy and physical characteristics indicate complex nature of lunar explosive volcanism which is not yet fully understood.

 This study focuses on regional (>1000 km²) pyroclastic deposits around Sinus Aestuum (12.1˚ N, 8.3˚ W) and Aristarchus (23.7˚ N, 47.5˚ W) regions and local deposits (<1000 km²) at Atlas (46.3˚ N, 44.9˚ E) and Alphonsus (13.4˚ S, 2.8˚ W) craters.

Data and methods: We constructed reflectance mosaics of the study regions using level-2 spectral reflectance data of the Moon Mineralogical Mapper (M³) onboard Chandrayaan-1 [6] for carrying out the mineralogical analysis. We prepared false color composite (FCC) (Fig. 1) images of these region following the methodology described in [7]. We used the Fe and TiO₂ maps of [8] and [9], respectively, to assess the compositional variation over these studied regions in comparison with lunar volcanic glasses [10], mare and highland soil samples [LSCC] [11]. We acquired multiband polarimetric images of pyroclastic deposits using a monochrome industrial camera DZK 33GX250 of The Image Source company mounted on the 43 cm telescope of the Physical Research Laboratory observatory, situated at Mount Abu, India. We followed the data processing steps mentioned in [12].

Results and Discussion: Lunar volcanic glasses have overlapping spectral characteristics in the visible to near-infrared (VIS-NIR) wavelength range with other common mafic minerals (e.g., Olivine, Pyroxene) [2]. Hence, its remote detection is feasible only if more than 70 wt.% volcanic glass present in the mafic mixture [1]. Fig. 1 shows that the FCC scheme used here can identify pyroclastics successfully. DMDs are showing distinct color variation from the surroundings, presumably due to presence of volcanic glasses in the crystalline matter. Olivine-enriched mafic mixture is represented by the yellowish trend, whereas cyan color corresponds to the fresh craters with spectral signature of pyroxene. Based on the amount of pyroxene present on the surface, the shades of green are changing from one rock unit to other. Anorthositic rock type is characterized by red pixels, whereas blue pixels represent pyroxene-bearing and highly weathered mafic compositions. Though using uniform methodology over different regions, DMDs (outlined by white dashed line in Fig. 1) are reflecting variation in color, which indicates that DMDs have heterogeneous mineralogical and compositional association. 

Figure 1: FCC of the M³ based mosaic around the study regions. (a) Sinus Aestuum, (b) Aristarchus, (c) Atlas, and (d) Alphonsus, respectively. The FCC color scheme is: avg. glass BD [red], avg. BD I [green], avg. BD II [blue]. The regions outlined by white dashed lines represent the DMDs.

To understand the compositional variations within DMDs exposed at different locations, we plot FeO vs. TiO₂ in Fig. 2. The compositional variations of Apollo sample glasses [10] area also plotted along with lunar highland and mare soil samples in the background for a reference. 

Figure 2: Average FeO variation with respect to mean TiO₂ concentration around the study regions. Lunar sample data from different Apollo missions are denoted through distinct shape of legend. Highland and mare soil sample data are plotted in gray and brown color, respectively. Volcanic glasses are represented in their true color (e.g., green, yellow, orange, black, and red) except very-low Ti (VLT) glasses (marked in blue). The error bars correspond to one standard deviation.

Figure 3: (a) Phase ratio intensity (19/4) image of crater Alphonsus and its surroundings in I filter. (b) Variation in average phase ratio in DMDs, crater floor, and mare region.

The regional DMDs around Aristarchus and the local deposits in Alphonsus crater have relatively high Fe and very-low to low Ti concentration, similar to the composition of reported green and VLT lunar volcanic glasses.  In the case of Atlas crater, the northern deposit has very low Fe and Ti similar to Apollo 14 highland soil, whereas the southern deposit has intermediate Fe and Ti concentration, similar to the Apollo 17 mare soil. Possibly the northern deposit is more strongly contaminated by highland crater ejecta, corresponding to a heterogeneity on the surface that leads to compositional variations within DMDs across the small areal extent of Atlas crater. On the other hand, both regional deposits in the Sinus Aestuum region have high Fe and Ti concentrations. It can be inferred that the northern deposit of this region has a higher glass content, similar to the composition of orange glass, whereas in the southern deposit pyroclastic materials are less and mixed with surrounding mare composition.

Phase ratio images (Fig. 3) are a proxy to understand variation of surface roughness and porosity. As the variation range is small, we extracted average phase ratio values from the Alphonsus crater floor, nearby mare region and from DMDs (Fig. 3b). We observed that the phase ratio values of DMDs are intermediate to mare and highland regions. Further, we will be deriving polarimetric properties of Pyroclastics in the negative branch of polarization as part of the integrating framework for analyzing DMDs. The work will be extended to all DMD locations considered from nearside of the Moon.

References: [1] Horgan, B.H. et al. (2014), Icarus, 234, 132-154; [2] Bennet, K.A. et al. (2016) Icarus, 273, 296-314; [3] Gaddis, L.R. et al. (1985), Icarus, 61 (3), 461-489; [4] Head, J. W. and Wilson, L. (1979), LPSC, 10, 2861-2897; [5] Gaddis et al. (2003), Icarus, 161(2), 262-280; [6] Green et al. (2011), JGR Planets, 116 (E10); [7] Misra, D. et al. (2024), LPI Contributions, 3040, 2134; [8] Bhatt, M. et al. (2019). Astronomy & Astrophysics, 627, A155; [9] Sato, H. et al. (2017), Icarus, 296, 216-238; [10] Delano, J. W. (1986), JGR: Solid Earth, 91 (B4), 201-213; [11] Taylor, L.A., et al., 2001, JGR, 106 (E110, 27, 985-28, 000; [12] Wöhler C. et al. (2024), AJ, 167:187. 

How to cite: Misra, D., Bhatt, M., Wöhler, C., Arnaut, M., Rai, N., Srivastava, N., Ganesh, S., and Bhardwaj, A.: Towards understanding spectral and physical characteristics of lunar pyroclastics, Europlanet Science Congress 2024, Berlin, Germany, 8–13 Sep 2024, EPSC2024-1085, https://doi.org/10.5194/epsc2024-1085, 2024.

Motivation

Solar wind ion precipitation on airless rocky bodies like the Moon has been linked to a variety of processes summarised by the term space weathering, including darkening and a red shift in optical reflectance spectra, the formation of vesicles and implantation of ions in mineral grains and the formation of an amorphised rim therein [1]. Solar wind irradiation additionally leads to the release of surface material via the kinetic sputtering process. These ejecta undergo ballistic trajectories and take part in the formation of the Lunar exosphere, which is well documented by space missions and ground-based observations. To properly gauge the importance of the sputtering contribution, however, a more detailed physical implementation of the sputtering process is necessary than used so far in, e.g., [2]. Prior, this has typically been approximated by simulation codes using the binary collision approximation (BCA) like SRIM [3], see also the review in [4]. On the other hand, more recent literature suggests significant limitations of this software [5,6] – especially related to real-life surfaces like lunar regolith. We present a combined experimental and numerical work on the sputtering yields of lunar regolith and discuss the validity of popular BCA codes.

Methods

Experimental data on sputtering yields, i.e., the amount of material released normalised per number of incidence ions, were obtained using a quarz crystal microblance (QCM) setup [7]. To overcome limitations on the sample configuration that come with this approach, an additional QCM served as a catcher for the sputtered material [8]. This allowed us to conduct experiments on rough bulk samples and additionally probe the ejecta angular distribution. We perform such experiments with lunar regolith (from Apollo 16 sample #68501) and helium and hydrogen ions at solar wind energies of 1 keV/nucleon. Numerical investigations were carried out both using SRIM and variants of SDTrimSP in its 1D and 3D version [9]. The latter in particular enables systematic investigations with varying surface roughness comparable to the experiments, as well as surface porosity resembling the regolith structures observed on the Moon [10].

Results

In line with previous studies, a comparison for flat samples reveals that the BCA approach consistently overestimates sputtering yields, with SRIM deviating the most [6]. By introducing surface roughness through consideration of regolith grains, the sputtering yield as a function of incidence angle is both flattened and reduced. Both effects become even more pronounced when surface porosity is included in the description. Three-dimensional simulations match these results qualitatively and, when the initial offset is factored out, also quantitatively. We will present these findings in greater detail and discuss possible implications in the context of the lunar exosphere.

[1] B. Hapke, J. Geophys. Res. Planets 106 (2001) 10039–10073.
[2] P. Wurz, U. Rohner, J.A. Whitby, C. Kolb, et al., Icarus 191 (2007) 486–496.
[3] J.F. Ziegler, M.D. Ziegler, J.P. Biersack, Nucl. Instrum. Methods. Phys. Res. B 268 (2010) 1818–1823.
[4] P. Wurz, S. Fatemi, A. Galli, J. Halekas, et al., Space. Sci. Rev. 218 (2022) 10.
[5] K. Wittmaack, Nucl. Instrum. Methods Phys. Res. B 380 (2016) 57–70.
[6] P.S. Szabo, H. Biber, N. Jäggi, M. Brenner, et al., ApJ 891 (2020) 100.
[7] G. Hayderer, M. Schmid, P. Varga, HP. Winter, et al., Rev. Sci. Instrum. 70 (1999) 3696–3700.
[8] H. Biber, J. Brötzner, N. Jäggi, P.S. Szabo, et al., Planet. Sci. J. 3 (2022) 271.
[9] U. von Toussaint, A. Mutzke, A. Manhard, Phys. Scr. 2017 (2017) 014056.
[10] P.S. Szabo, A.R. Poppe, H. Biber, A. Mutzke, et al., Geophys. Res. Lett. 49 (2022) e2022GL101232

How to cite: Brötzner, J., Biber, H., Szabo, P. S., Jäggi, N., Nenning, A., Fuchs, L., Mutzke, A., Galli, A., Wurz, P., and Aumayr, F.: Roughness and porosity significantly reduce the sputtering yield of solar wind ions on the lunar surface, Europlanet Science Congress 2024, Berlin, Germany, 8–13 Sep 2024, EPSC2024-243, https://doi.org/10.5194/epsc2024-243, 2024.

• Mission description

The Negative Ions at the Lunar Surface (NILS) instrument (Fig. 1) is the first instrument to measure negative ions directly on the lunar surface. Launched aboard the Chinese Chang’E-6 sample-return mission on May 3, 2024, the instrument will land on the lunar far-side (South Pole-Aitken basin) in early June 2024. During the surface phase of the lander, the NILS instrument will be active, measuring negative ion and electron fluxes from the lunar surface.

• Scientific objectives

When the solar wind interacts with the lunar surface, a portion of it is reflected back instead of being absorbed. Previous studies have provided evidence of neutral hydrogen atoms [1] and solar wind protons [2] being reflected from the surface. However, to date, no measurements of negative ions have been conducted. It remains unclear whether a significant population of negative ions exists near the lunar surface. The NILS instrument, the first-ever dedicated negative ion instrument flown beyond the Earth, will address this gap by performing in-situ measurements directly on the lunar surface.

• Instrument description

The NILS instrument is a 9th generation instrument of the SWIM family [3]. NILS uses a surface-interaction based time-of-flight system combined with an electrostatic analyzer and an electrostatic elevation scanning system to measure the direction-, energy-, and mass-resolved negative ion flux on the surface. A electromagnetic electron suppression system allows to switch between negative ion and electron measurements. NILS can separate the main solar wind components as well as negative sputtered oxygen ions and heavier species. Key performance parameters are shown in Table 1.

Table 1: Instrument performances

Figure 1: NILS flight model

At the Europlanet Science Congress 2024, we present and interpret the first data obtained and discuss the implications of the observed negative ion flux on the lunar near-surface plasma environment.

• References

[1] M. Wieser, S. Barabash, Y. Futaana, M. Holmström, A. Bhardwaj, R. Sridharan, M. B. Dhanya, A. Schaufelberger, P. Wurz, and K. Asamura. First observation of a mini-magnetosphere above a lunar magnetic anomaly using energetic neutral atoms. Geophys. Res. Lett., 37(5), 03 2010.

[2] Y. Saito, S. Yokota, T. Tanaka, K. Asamura, M. N. Nishino, M. Fujimoto, H. Tsunakawa, H. Shibuya, M. Matsushima, H. Shimizu, F. Takahashi, T. Mukai, and T. Terasawa. Solar wind proton reflection at the lunar surface: Low energy ion measurement by map-pace onboard selene (kaguya). Geophys. Res. Lett., 35, 12 2008.

[3] M. Wieser and S. Barabash. A family for miniature, easily reconfigurable particle sensors for space plasma measurements. Journal of Geophysical Research: Space Physics, 2016

How to cite: Canu-Blot, R., Wieser, M., Barabash, S., Kérényi, M., Xiao-Dong, W., and Melville, N.: The Negative Ions at the Lunar Surface (NILS) instrument on Chang’E-6: the instrument, objectives and first results, Europlanet Science Congress 2024, Berlin, Germany, 8–13 Sep 2024, EPSC2024-308, https://doi.org/10.5194/epsc2024-308, 2024.

1. The LUMIO mission

The Lunar Meteoroid Impacts Observer (LUMIO) mission represents a critical step in advancing our understanding of the meteoroid population nearby the Earth-Moon system [1]. This 12U CubeSat, coordinated by the European Space Agency (ESA) and supported by the Italian Space Agency (ASI) and the Norwegian Space Agency (NOSA), is designed to observe and characterize meteoroid impact on the lunar far side. Utilizing the LUMIO-Cam, an optical instrument sensitive to the visible and near-infrared spectrum (450-950 nm), the mission aims to detect impact flashes from a quasi-halo orbit at Earth-Moon L2 [2], enhancing the global knowledge base beyond the capabilities of Earth-based observations (Figure 2).

Figure 1. Schematic representation of an impact flash detected by LUMIO on the lunar farside.

The continuous influx of meteoroids into the Earth-Moon system poses a not well characterized risk to space assets. The Moon, devoid of an atmospheric shield, faces direct impacts from these space rocks, which alter its surface and could potentially jeopardize human and robotic missions aimed at prolonged lunar habitation [3]. As plans for lunar colonization advance, a comprehensive characterization of the meteoroid environment becomes paramount to ensure the safety and success of these endeavors. Furthermore, LUMIO seeks to resolve existing discrepancies within meteoroid bombardment models concerning the impact ratio at the poles compared to equatorial regions: current models show variance in predicting meteoroid impacts across different latitude [4].

LUMIO will employ a vision-based navigation algorithm that utilizes a limb-based approach to accurately determine the spacecraft's position relative to the Moon [5]. This algorithm achieves sub-pixel accuracy of less than 0.2 pixels in numerical simulations. Such positioning will directly influence the correct localization of lunar impact flashes.

2. Scientific challenges of LUMIO

Although LUMIO could precisely pinpoint the impact location of a meteoroid, the spacecraft would primarily capture the kinetic energy. This limitation presents a challenge in deriving detailed information about the characteristics of the impactor. To gain insights into the meteoroid's composition and velocity, LUMIO's observations will be correlated with known meteoroid streams. However, in the absence of velocity vector measurements, this analysis will depend on statistical models, specifically, machine learning algorithms are well-suited for this task. These models will facilitate the estimation of the meteoroid's properties and impact conditions, which will be relatively straightforward during the peaks of the most active meteor showers and increasingly complex with the minor ones.

Thanks to observing campaigns coordinated concurrently with ground-based networks, well-characterized meteors will facilitate the establishment of the size distribution of meteoroid streams for specific time periods. This information can then be extrapolated to LUMIO detections on the lunar far side during the same times. Additionally, this approach will enable the analysis of potential substructures or components within the meteoroid stream, which may lead to variations in meteoric activity between the Moon and Earth.

The inferred meteoroid parameters and impact conditions will be further utilized to enhance scientific investigation such as impact modeling.

3. Refining prediction models

Recent advancements in the predictive models for meteoroid impact observations, spearheaded by the Department of Aerospace Science and Technology (DART) at the Polytechnic University of Milan (PoliMi), have introduced the Payload, Orbit, and Environment (POE) and the Meteoroid Gun (MeGun) models [6]. These models now incorporate over 50 meteoroid streams and a comprehensive meteoroid background, with efforts underway to expand to more than 500 streams [7]. Such enhancements are anticipated to increase the expected observations of impact flashes by approximately 10% [6]. Moreover, these models will account for lunar surface obstructions by local topography, which vary based on the impact location. This data is derived from a global digital elevation model of the Moon [8], utilizing Monte Carlo ray tracing techniques (Figure 2).

Figure 2. Surface obstruction of the lunar farside from 36000 km of altitude.

Furthermore, LUMIO's approach to image generation, which considers relevant detector noises and optical head effects, aims to produce radiometrically consistent images that reflect the observational geometry between LUMIO, the Moon, and the Sun. These efforts will be combined for software and hardware-in-the-loop (HIL) testing, with future developments planned to incorporate synthetic impact flashes.

4. Conclusions

In conclusion, LUMIO stands as a fundamental mission in the cislunar space exploration endeavor, poised to significantly enhance the fidelity of meteoroid models and thus support both scientific research and planetary defense mechanisms. The integration of advanced algorithms, enhanced modeling capacities, and innovative imaging techniques marks a significant progression in our capabilities to predict and understand the phenomena occurring within our near-Earth environment.

Acknowledgements

The scientific activities of LUMIO are supported by the Italian Space Agency (ASI), whereas the Phase B engineering work has been conducted under ESA Contract No. 4000139301/22/NL/AS within the General Support Technology Programme (GSTP) through the support of the national delegations of Italy (ASI) and Norway (NOSA).

References

[1] Topputo, F., Merisio, G., Franzese, V., Giordano, C., Massari, M., Pilato, G., ... & Koschny, D. (2023). Meteoroids detection with the LUMIO lunar CubeSat. Icarus, 389, 115213.

[2] Cipriano, A. M., Dei Tos, D. A., & Topputo, F. (2018). Orbit design for LUMIO: The lunar meteoroid impacts observer. Frontiers in Astronomy and Space Sciences, 5, 29.

[3] Robertson, D., Pokorný, P., Granvik, M., Wheeler, L., & Rumpf, C. (2021). Latitude variation of flux and impact angle of asteroid collisions with Earth and the Moon. The Planetary Science Journal, 2(3), 88.

[4] Drolshagen, G. (2008). Impact effects from small size meteoroids and space debris. Advances in space Research, 41(7), 1123-1131.

[5] Panicucci, P., Piccolo, F., Rizza, A., Merisio, G., Topputo, F., & Walker, R. (2024). Vision-Based Navigation for the LUMIO CubeSat Mission. In 46th AAS Guidance, Navigation and Control Conference (pp. 1-20).

[6] Merisio, G., & Topputo, F. (2023). Present-day model of lunar meteoroids and their impact flashes for LUMIO mission. Icarus, 389, 115180.

[7] Jenniskens, P. (2023). Atlas of Earth's Meteor Showers. Elsevier.

[8] Smith, D. E., Zuber, M. T., Neumann, G. A., Lemoine, F. G., Torrence, M. H., McGarry, J. F., Rowlands, D. D., et al. (2010). Initial observations from the Lunar Orbiter Laser Altimeter (LOLA). Geophysical Research Letters, 37(18).

How to cite: Peña-Asensio, E., Ferrari, F., Topputo, F., Koschny, D., Ammannito, E., and Moissl, R.: The LUMIO mission: refining prediction models for meteoroid impact observation on the lunar farside, Europlanet Science Congress 2024, Berlin, Germany, 8–13 Sep 2024, EPSC2024-471, https://doi.org/10.5194/epsc2024-471, 2024.

The lunar environment is known to be characterized by complex interactions between plasma, the exosphere, dust, and the surface. However, our understanding of the environment is limited due to the lack of experimental evidence. Here we propose a small, low-cost mission to characterize the dust and exosphere environment of the Moon. Named the Limb Pathfinder (LimPa), this is a proof-of-concept mission aimed toward understanding the coupling between plasma, dust, and tenuous neutral atmosphere. The LimPa mission was proposed to a call for the Small Mission to the Moon issued by European Space Agency in 2023. LimPa is designed to examine the dust exosphere above the lunar polar regions by using an utterly novel remote-sensing technique to measure the solar wind hydrogen atoms—the solar wind protons that are neutralized to hydrogen atoms (Figure 1). Its goals are 1) to detect for the first time the neutralized solar wind hydrogen produced by exospheric gas and levitated dust; 2) to measure the height profiles of the levitated dust and exospheric gas densities; and 3) to determine the emission mechanism of the horizon glow. Our baseline design of the LimPa mission is a 12U CubeSat (Figure 2). Three highly matured instruments are used: an energetic neutral atom camera, a proton sensor, and a camera system. The LimPa CubeSat is proposed to be inserted into a circular lunar polar orbit, with an altitude of 100 km as a baseline. The Sun-pointing attitude will allow measurements of neutralized solar wind that are produced by the exosphere and dust grains above the polar regions. The nominal lifetime is for three months as a pathfinder mission. The LimPa mission will open a new window to remote characterization of the lunar dust exosphere environment above the poles, and will demonstrate that this monitoring can be achieved with a simple and low-cost instrument system and spacecraft operation. The concept to be proven by the LimPa mission will enable long-term monitoring of the fragile dust exosphere environment, which substantially impacts on lunar exploration and will be significantly altered by human activities.

Figure 1: A conceptual illustration of the LimPa mission. The solar wind protons (pink trajectories) are neutralized by the exospheric gas or by the dust grains (green trajectories). By measuring these neutrals by LimPa Cubesat, we can retrieve the exosphere and dust information near the Moon.

Figure 2: A conceptual design of the LimPa Cubesat (12U).

How to cite: Futaana, Y., Kallio, E., Knuuttila, O., Nyman, L., Shimoyama, M., and Barabash, S.: LimPa mission: A small mission proposal to characterize the enigmatic lunar dust exosphere, Europlanet Science Congress 2024, Berlin, Germany, 8–13 Sep 2024, EPSC2024-515, https://doi.org/10.5194/epsc2024-515, 2024.

Lunar lava tubes are of significant interest for potential human exploration of the Moon, therefore it is important to study their subsurface extent and physical properties in detail. The underground existence of the lava tubes in the mare regions due to past volcanic activity has been predicted in the past (e.g. [1,2]) and orbiting missions for gravity surveys (GRAIL) and radar investigations (Lunar Radar Sounder onboard SELENE) have identified candidate locations of these subsurface structures (e.g. [3-5]). But only global constraints could be inferred, because the spatial resolution achievable from orbit is not sufficient compared to the estimated extents of the lava caves. To better understand the real extent and depth of the lava tubes, measurements on the lunar surface have to be performed. In this study we propose surface microgravity survey techniques to measure gravitational anomalies. A gravimeter experiment on a lunar rover would map out the spatial variation of the surface gravity and constrain subsurface voids shown as mass deficits accurately when traversing a lava tube. Microgravity survey yield very high spatially resolved gravity mapping. Microgravity surveys is a geophysical mapping technique commonly used on Erath to aid the location of buried features such as faults, sinkholes, tunnels and voids associated with mines, quarries as well as lava tubes [6]. The Traverse Gravimeter Experiment (TGE) on the Apollo 17 Lunar mission, allowed to determine presence and properties of a higher density lava flow [7,8]. Microgravimeter measurements can be made across linear profiles and/or equally spaced grids at survey stations in varying increments dependent on the depth of investigation.

Here, we will present the lunar microgravimetric survey concept to explore subsurface extent and physical properties of lunar lava caves. For different scenarios consisting of different depth size etc. of subsurface lava tubes, the gravitational anomalies will be calculated and the traverse gravity survey will be simulated [9]. The measurements concepts and instrument requirements will be presented. A possible application of this study is the robotic explorer concept LunarLeaper [10], recently selected from the ESA 2023 Small Missions for Exploration call for a Pre-Phase A study.

These measurements are ideally supported by ground penetrating radar (GPR) measurements, a technique commonly used on Earth to map shallow subsurface structures using electromagnetic reflection waves. GPR has been successfully applied to various problems in the geological, archaeological, and engineering fields as well as on mapping of lava tubes [11-14]. This combined, non-intrusive method, can help to characterize the physical properties of the lava tubes, as for example their stability and the composition of the surrounding material. These are important considerations for future human exploration of the Moon.

References: [1] Murase and McBirney, 1970, Science 167, 1491. [2] Greeley, 1971, The moon, 3, doi:10.1007/BF00561842. [3] Chappaz et al., 2017, Geophysical Research Letters, 44, doi :10.1002/2016GL071588. [4] Kaku et al., 2017, Geophysical Research Letters, 44, doi.org/10.1002/2017GL074998. [5] Zhu et al., 2024, Icarus, doi :10.1016/j.icarus.2023.115814. [6] Deroussi et al., 2009, Journal of Volcanology and Geothermal Research, 184, doi:10.1016/j.jvolgeores.2008.10.002. [7] Talwani and Kahle, 1976, NASA STIRecon Tech. Rep. A, vol. 77. [8] Urbancic et al., 2017, Journal of Geophysical Research: Planets, 122, doi:10.1002/2017JE005296. [9] Noeker and Karatekin, 2022, EPSC2022-361, Europlanet Science Congress. [10] Mittelholz et al., 2024, EGU General Assembly, doi:10.5194/egusphere-egu24-21578 [11] Esmaeili et al., 2020, Journal of Geophysical Research: Planets, 125, doi:10.1029/2019JE006138. [12] Miyamoto et al., 2005, Geophysical Research Letters, 32, doi:10.1029/2005GL024159. [13] Rowell et al., 2010 CREWES Research Report, 22. [14] Gómez-Ortiz, 2014, Journal of Applied Geophysics, 109, doi:10.1016/j.jappgeo.2014.07.009.

How to cite: Ritter, B., Karatekin, Ö., Mittelholz, A., and Stähler, S. C.: Exploring subsurface extent and physical properties of lunar lava tubes using surface microgravity survey, Europlanet Science Congress 2024, Berlin, Germany, 8–13 Sep 2024, EPSC2024-904, https://doi.org/10.5194/epsc2024-904, 2024.

Introduction

The polarisation of the sunlight reflected by the surface of the Moon contains information about the structural properties of the surficial regolith layer, such as the grain size and the microscale roughness [1, 2]. The internal structure or layering of regolith grains can be assessed using wavelength-dependent polarisation data [3]. Most of the existing lunar polarisation data were acquired at large phase angles exceeding approximately 23° in the visible wavelength range and were in part linked quantitatively to structural regolith properties based on laboratory experiments [e.g., 1, 2, 3, 4, 5]. At smaller phase angles, in the so-called ``negative polarisation branch'', the lunar polarisation is less well understood, and especially polarisation imaging data of high spatial resolution are scarce [e.g., 6, 7]. In this work, we present first results of a telescopic observation campaign aiming at the acquisition of multispectral (Johnson-Cousins UBVRI) imaging polarimetric data at small phase angles of a variety of typical lunar terrain types, including maria, highlands, pyroclastic deposits and fresh crater materials.

Data and Methods

The dataset analysed in this study was acquired during five nights between February 21st and 26th, 2024, at phase angles between 4° and 30° with a reflector telescope of 430 mm aperture and 3000 mm focal length at Mount Abu Observatory in Rajasthan, India. We used a monochrome the Imaging Source DZK 33UX250 industrial polarisation camera, which is constructed such that the individual sensor pixels are equipped with polarization filters rotated by 0°, 45°, 90° and 135°. In that way, for each 2 by 2 pixels neighbourhood of sensor pixels values for the intensity, degree of polarisation (DoLP) and angle of polarisation (AoLP) can be obtained [8]. The image scale is 0.9 km per pixel, the spectral filter set is Johnson-Cousins UBVRI ranging from the near-ultraviolet throughout the visible range into the near-infrared domain. To obtain a polarisation image, a set of 3500 individual camera frames was acquired, the individual sub-frames corresponding to the four polarization directions were extracted, and the sharpest 10% of the sub-frames were selected and stacked with the software Autostakkert3 [9].
 
So far, our analysis is restricted to the DoLP inferred from the stacked images. The telescopic data were georeferenced to the Lunar Reconnaissance Orbiter (LRO) Wide Angle Camera (WAC) mosaic as described in [4, 5], resulting in one image cube per wavelength channel containing the pixel-wise DoLP in dependence on the phase angle. To each pixel of each image cube, a third-degree polynomial with zero intercept was fitted [7], allowing for a computation of the absolute value P_min of the minimal DoLP, the phase angle α_min at which the minimum occurs, the phase angle of inversion α_inv of zero DoLP, and the slope h of the DoLP vs. phase angle curve at α_inv [7]. The resulting 20 polarisation features were transformed to zero mean and unit standard deviation, and a Principal Component Analysis (PCA) [10] was applied. The small DoLP values in the negative polarisation branch have the effect that only the scores on the first 2-3 principal components are not dominated by noise.

Fig. 1: IVU composite of the study area. Colour saturation has been enhanced.

Fig. 2: Derived polarisation parameters in the V band.

Fig. 3: PCA composite image of the study area.

Results and Discussion

Our study area is located between the lunar craters Copernicus and Manilius and comprises the mare regions of Sinus Aestuum and Mare Vaporum, the neighbouring highland terrain, and the well-known regional pyroclastic deposits near Rima Bode, in Sinus Aestuum and in Mare Vaporum [e.g., 11]. For orientation, Fig. 1 depicts an RGB composite consisting of the I, V and U channels. Maps of the polarisation parameters P_min, α_min, α_inv and h in the V band are shown in Fig. 2 and the scores on the first three principal components in Fig. 3.

Fig. 2 shows that P_min and h hardly differ between dark mature maria and brighter neighbouring highlands, but pyroclastic deposits stand out as positive anomalies and fresh craters as negative anomalies. Both parameters are correlated with the grain size inferred in [5] from the DoLP at large phase angles. The value of α_inv is generally different for maria than for highlands, whereas α_min shows a weak dependence on the terrain. The PCA of the polarisation parameters indicates that each terrain type, in particular pyroclastic deposit terrain, is represented by a specific signature, corresponding to variations in the behaviour of the polarisation parameters. The peculiar behaviour exhibited by pyroclastic deposits in the negative polarisation branch, which is different from that of normal mature mare surfaces, may be due to unusual structural regolith properties as a consequence of their formation by explosive volcanism. Laboratory analyses and physical modelling studies are needed to quantitatively link the observed polarisation parameters in the negative branch to specific structural regolith parameters.

References

[1] Shkuratov, Y. and Opanasenko, N. (1992) Icarus 99(2), 468-484.
[2] Dollfus, A. (1998) Icarus 136(1), 69-103.
[3] Shkuratov, Y. et al. (2007) Icarus 187(2), 406-416.
[4] Bhatt, M. et al. (2023) A&A 674, A82.
[5] Wöhler, C. et al. (2024) AJ 167:187.
[6] Shkuratov, Y. et al. (1992) Icarus 95, 283-299.
[7] Opanasenko, N. et al. (2022) LPSC LIII, 1194.
[8] The Imaging Source (2019) https://www.theimagingsource.com/de-de/product/unique/33u-polarsens/?resolution=5013504&fps=75&mono_color=monochrome
[9] Kraaikamp, E. (2023) https://www.autostakkert.com
[10] Marsland, S. (2015) Machine Learning: An Algorithmic Perspective. 2nd ed., CRC Press.
[11] Gaddis, L. et al. (2003) Icarus 161(2), 262-280.

How to cite: Wöhler, C., Bhatt, M., Arnaut, M., Misra, D., Ganesh, S., and Bhardwaj, A.: Terrain-dependent spectral properties of lunar polarisation at small phase angles, Europlanet Science Congress 2024, Berlin, Germany, 8–13 Sep 2024, EPSC2024-995, https://doi.org/10.5194/epsc2024-995, 2024.

The chronology function and production function have been widely used to derive the model ages of lunar mare regions from crater size-frequency distributions (CSFDs). Challenges remain in homogenous counting area selection, crater saturation and crater rim identification. Geological unit-based ages are also difficult to study the continuous surface evolution among adjacent areas. Using regression-learning models, we have tried a new method on the Em4 unit of the Chang’e 5 landing area to explore a quantitative relationship between ages and surface morphometric expressions by using texture features. Four features (Contrast, Energy, Entropy and Homogeneity), together with a stepwise linear model (SL) and a linear support-vector-machine model (LS) are well selected to produce a pixel-level continuous age map of the Em4 unit. Mean age values of 1.75 ±0.26 Ga and 1.69 ±0.22 Ga obtained respectively from the two models are consistent with the ages of Chang’e 5 samples returned from this area. Both texture features and age maps are separated along the NW-SE sinuous rilles (Rima Sharp and Rima Mairan). Comprehensively considering geology, geomorphology, and newly retrieved ages of the study region, we have proposed a three-stage evolution process for the Em4 unit. Our new age-retrieving method is useful to obtain a pixel-level high-resolution age map in the study region and has the potential to be widely used in other lunar mare areas. 

How to cite: Chen, Y. and Huang, Q.: Surface geological evolution in the Chang’e 5 landing area (Em4 unit) revealed by a new age-retrieving method from regression learning, Europlanet Science Congress 2024, Berlin, Germany, 8–13 Sep 2024, EPSC2024-1003, https://doi.org/10.5194/epsc2024-1003, 2024.

Introduction: LUNINA is an in-situ navigation and communication node. Proposed LUNINA platform is designed to be a compact, independent, cost effective, robust, and location independent navigation beacon and communication relay on the Moon that can operate 24/7.

The proposed concept is based on the ESA funded MiniPINS [1] project LINS platform capable of withstanding extended time periods on the lunar surface. The LINS was developed for the Schrödinger crater, but it can be deployed in any location on the Moon where there is at least some sunlight available. Each unit has been equipped with a RHU that keeps it warm and together with using solar panels and a battery is able to operate continuously. 

The LUNINA node can be utilized in two main use cases, reliable navigation and communication on and around the moon. Each LUNINA unit provides the signal for navigation purposes. At an elevated location the unit helps with ground navigation for line-of-sight users as well as lunar orbit spacecraft. Accurate navigation is provided for applications such as spacecraft landing and launch from the lunar surface.

LUNINA node can work as a communication and data transfer relay for both ground and in-orbit users. At elevated location the node can cover a large surface area in line-of-sight and through a network of nodes relay messages. Around a base or other infrastructure, it can cover its vicinity and provide a communication link for the various applications.

Application: The LUNINA concept is a durable and relatively affordable navigation and communication node designed for lunar environment.

The MiniPINS developed the LINS capable of withstanding extended time periods on the lunar surface. An LTE system is used as a default communication and navigation payload for LUNINA platform.

The concept will work as a communication network and navigation aid for lunar missions, both on-ground and orbiting. The idea is to develop a 'drop and forget' long-term reliable element of a lunar infrastructure that will enable safe, reliable and flexible exploration of the lunar environment.

The LUNINA node can be deployed anywhere on the Moon where there is at least some sunlight present. The LINS platform was developed to operate on the Schrödinger crater (see Figure 1). Platform design has been equipped with a radioactive heating unit (RHU) that keeps the payload compartment warm and together with using solar panels and a battery the unit is able to operate continuously.

Figure 1: LUNINA nodes (in red dots) in Schrödinger crater around the Lunar Base (green dot).

The ESA MiniPINS LINS platform, as well as LUNINA, is designed to be deployed from a rover but can be modified to be deployable with other means such as from commercial lander missions.

The inclusion of an RHU would allow the thermalization of the in-situ LUNINA unit during the Lunar night, where energy storage need may lead to unaffordable battery volumes. Radioisotope power systems utilising americium-241 as a heat source fuel have been under development in Europe since 2009 as part of a European Space Agency funded programme led by the University of Leicester [2].

Use Case: The LUNINA node can be utilized in two main use cases - reliable navigation and communication on and around the Moon.

LUNINA can provide the signal with which different navigation methods can be used, such as ranging and range-rate. At an elevated location the node could help with ground navigation for line-of-sight users as well as lunar orbit spacecraft.

More accurate navigation could be provided for applications such as spacecraft landing and launch from the lunar surface with for example using the signal of more than one node around the surface launch site.

With respect to the communication, the node can work as a communication and data transfer relay for both ground and in-orbit users. At elevated location the node can cover a large surface area in line-of-sight and through a network of nodes relay messages. Around a base or other infrastructure, it can cover its vicinity and provide a reliable communication link for the various applications there, such as an ubiquitous safety and emergency link (see Figure 2).

Figure 2: Different applications of the LUNINA node.

Once the LCNS (Lunar Communications and Navigation Services) space segment is available the node is modular and can be updated to continue as a supporting infrastructure. The node signal can be used as one more source to provide an even more accurate navigation solution. Its drop locations can be chosen such that it helps with any location or temporal blind spots for the LCNS satellite signals (such as for example near crater edges).

Innovation: LUNINA is designed to be a compact, independent, cost effective, robust, and location independent navigation beacon and communication relay on the Moon that can operate 24/7 in any location.  It's designed to be 'invisible' infrastructure. The platform is modular, the payload is easily updatable as long as the new payload meets the platform's  requirements. The innovative features of the LUNINA node are:

• Compactness. The platform is based on the MiniPINS LINS
• Independency. The LINS his designed to operate 24/7 on Lunar environment. The same approach is used in the LUNINA platform.
• Cost-effectiveness. Using the heritage LINS, standardized parts and systems and existing payloads, the costs of development is  minimized. Once node is developed, the node can be mass produced, bringing down its cost.
• Robustness and modularity. The node will use standardized interfaces and form factors both for its payload as well as its software will also be updateable.
• Durability.  The node will have a long lifetime. All the node components will be designed and tested with durability in mind, the software will be upgradeable, and the node functionality and interfacing follow standards.
• Location-independency. The node will be a small and independent system deployable anywhere on the Moon.

References:

[1]  Genzer M., et. al. "MiniPINS - Miniature Planetary In-situ Sensors", EGU21-11282, EGU General Assembly 2021 (2021), https://doi.org/10.5194/egusphere-egu21-11282. Contract is carried out and funded by the European Space Agency activity no. 1000025265 in the “ESA-Star” System. 

[2]  Ambrosi, et al., "European Radioisotope Thermoelectric Generators (RTGs) and Radioisotope Heater Units (RHUs) for Space Science and Exploration.", Space Sci Rev 215, 55 (2019), https://doi.org/10.1007/s11214-019-0623-9

How to cite: Haukka, H., Kestilä, A., Arruego, I., Harri, A.-M., Genzer, M., Apéstigue, V., Hieta, M., Camañes, C., Ortega, C., Kivekäs, J., and Koskimaa, P.: Lunar In-situ Navigation and Communication Node - LUNINA, Europlanet Science Congress 2024, Berlin, Germany, 8–13 Sep 2024, EPSC2024-43, https://doi.org/10.5194/epsc2024-43, 2024.

 1.     The importance of studying lunar dust particles

International scientific and commercial interests in exploration missions to solar system bodies such as the Moon, asteroids and comets have increased significantly during the last two decades and will continue to increase in the future. One major environmental constraint during exploration missions is the presence of charged dust-like particles. They can be a threat for both human and robotic exploration missions.

The effects of lunar dust on Extra-Vehicular Activity systems can take many forms such as external vision obscuration, false instrument readings, dust coating and contamination, loss of traction, clogging of mechanisms, abrasion, thermal control problems and seal failures. One of the most serious effects is the compromising of astronaut health by irritation and inhalation of lunar dust.

Therefore, it is of utmost importance to characterise the properties of the dust particles present on the exploration sites and their transportation mechanisms to enable efficient mitigation techniques to be put in place. The main objective of DUSTER (Dust Study, Transport, and Electrostatic Removal for Exploration Missions) is to investigate in detail the charging and cohesion of the dust grain in the regolith. The project addresses key questions about the surfacing of airless bodies as observed by telescopes and scientific probes, such as the formation of dust ponds and the dust haze at the limb of the moon observed by the astronaut during the Apollo missions. It also addresses more engineering-oriented concerns regarding the adhesion of dust particles to man-made surfaces (spacecraft, instruments, spacesuits, solar panels, etc.).

The goal of DUSTER is to develop the instrumentation and technologies for in situ analysis of the electrical charging and transport of those dust particles. In addition, the project aims at developing a ground based test facility to validate the instrument in representative conditions and improve dust charging and transportation models.

2.     The DUSTER instrument

Given that the surface gravity as well as the UV and soft X-ray fluxes, which are drivers for the electrical charging of the dust, can be obtained by existing measurement data or reliable modelling, those two physical quantities do not need to be measured by the instrument. The remaining parameters that are needed to quantify dust charging and electrostatic transportation are the level of charging, the ambient plasma and the current resulting from the displacement of the dust particles.

The level of charging is assessed by measuring the electric field above the dust layer with a DC E-Field probe and using the Gauss theorem. The ambient plasma parameters (electron density and temperature) are measured with a Langmuir probe. To study the dust particles displacement, a Faraday cup (FC) is placed above the dust layer. When a voltage is applied to the FC (up to several kV), this creates an E-field that applies a force on the charged particles. When the voltage is high enough, the charged particles are attracted inside the FC. By measuring the resulting current from the FC the amount of charged dust that has been moved can be quantified.

The block diagram of the multi-sensor instrument is depicted in Fig. 1. It includes three front ends with specific probes/electrodes.

Fig. 1. Block diagram of the instrument.

The instrument prototype will be entirely designed by the members of the consortium. The electronics will include a Data Processing Unit (DPU), based on a FPGA design running a Leon3 microprocessor, and a Low Voltage Power Supply (LVPS) as main power interface for the instrument, both designed and built at IAA-CSIC. The very sensitive front ends which will acquire the readings and the High Voltage Power Supply (HVPS) are designed and built at BIRA-IASB. The probes/electrodes are designed and built at ONERA and BIRA-IASB.

The application software to control the instrument, implement the science sequences, acquire the data obtained from the probes, process it and send it through the spacecraft interface is developed at IAA-CSIC. The EMC tests will be carried out by TAS-E.

3.     Preliminary results obtained with a dedicated laboratory test setup

The laboratory test setup is built on the existing DROP chamber at ONERA Toulouse, France (see Fig. 2). It is a vacuum chamber that allows irradiating the dust particles with a VUV lamp, includes a Kelvin probe to infer the charging level of the dust layer and accommodates an FC that is used to attract the dust particles and measure the current resulting from the displacement of the charges.

Fig. 2. DROP chamber at ONERA Toulouse, France.

An example of the measured signal from the FC when biased at 3 kV is depicted in Fig. 3. It shows that several charged dust grains (or aggregates of grains) are mobilised.

Fig. 3. Output voltage of the transimpedance amplifier as a function of the polarization time of the detector. The background noise is depicted in dark and the dust grain detection is highlighted in red. The detector is polarized at +3 kV after 5 minutes of VUV irradiation.

Fig. 4. Zoom in of the peaks at 18 seconds in Fig. 3. It shows a clear pair of two consecutive peaks of opposite polarity, indicating that the dust grain entered into the FC and then fell back onto the sample holder.

This project is funded by the European Union’s HORIZON Research and Innovation programme under grant agreement No 101082466. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or the granting authority. Neither the European Union nor the granting authority can be held responsible for them.

How to cite: Ranvier, S., Lefever, K., Matéo Vélez, J.-C., Candini, G. P., Anciaux, M., Pacaud, R., Pastor Morales, C., Sanz Mesa, R., Berkenbosch, S., Hess, S., Gómez Lopez, J. M., Sanchez Carrasco, M. A., Lobón Villanueva, F., Muñoz, O., Rodriguez Gomez, J., del Estal Fernández, V., and De Keyser, J.: DUSTER: Dust Study, Transport, and Electrostatic Removal for Exploration Missions, Europlanet Science Congress 2024, Berlin, Germany, 8–13 Sep 2024, EPSC2024-923, https://doi.org/10.5194/epsc2024-923, 2024.

Interestingly, the lunar north pole does not show similar d/D trend as the south pole [2]. However, several other measurements including neutron spectrometer, radar, illumination and temperature variations [4, 5, 6] suggest ice containing north polar region albeit with a lower ice concentration compared to the south pole. This observed discrepancy is the motivation of this work where we used an existing d/D catalogue and integrated the outcomes with several other parameters like temperature, radar based circular polarisation ratio (CPR) and NIR based water detections.

Methods: About 9100 simple craters spanning both the poles within a latitudinal range of 65° N/S to 90° N/S, with crater diameter range between 5-20 km were analyzed to understand if d/D can be used as a proxy to water ice filling.  We considered already available illumination, temperature [6], CPR [7] and NIR [5] based water ice detection maps in order to establish the correlation if any with d/D parameter.

Fig 1. Depth to diameter (d/D) ratio distribution for craters of north (a) and south (b) poles. Base image LROC WAC mosaic.

Fig 2. The depth-to-diameter ratio (d/D) for craters at lunar poles: (a) north (65-90 ̊N) and (b) south (65-90 ̊S), integrated with temperature, DFSAR, and M3 observations. Black markers depict mean d/D in 3 ̊ bins. Dark grey markers signify non-PSR craters. The horizontal dashed line serves as a reference based on average d/D values at 65 ̊N/S.

As per the results from [2] it is anticipated that craters identified as water ice-rich using radar and NIR techniques would exhibit lower d/D values. However, contrary to expectations, Fig. 2 illustrates no clear correlation between d/D values and confirmed water ice detections. These findings highlight that the lower d/D of craters towards the poles might be influenced by additional factors and should not be singularly relied upon for estimating water ice filling. Also it is expected to have a lower d/D for craters with PSRs as compared to illuminated craters of the same diameter range due to water ice infilling in PSRs. Comparing the d/D of PSRs and non PSRs (illuminated craters) at both the poles, we found that the mean d/D value of PSRs and non-PSR craters differed, with the non-PSR craters having a significantly lower d/D. In case of the North Pole, this effect is particularly noticeable.

Conclusion: We found that the analysis of d/D ratio of craters is shown to have a latitudinal dependence in case of the south pole as observed by [2] but the obvious correlations with other measurement techniques are missing. The result so far is not supporting the decrease in d/D ratio and its linkage to water ice deposition. Also the contribution of sub surface ice deposits to the observed d/D trend cannot be ignored as the datasets used in the study have a detection limit of water ice only at surface level. Analysis involving changes in the slope of the crater due to water ice deposition is under progress which will further help in understanding clear trends if any on the topographic modification of craters due to water ice infilling.

References: Kokhanov et al., (2015) Sol. Sys. Res., 49, pp.295-302 [2] Rubanenko L. et al., (2019) Nat. Geosci., 12(8), 597-601. [3] Marco Figuera R. et al., (2022) Remote Sensing, 14(3), 450. [4] Lawrence D. J. (2006) JGR Planets, 111(E8). [5] Williams J. P. et al., (2019) JGR: Planets, 24, 2505–2521. [6] Li S. (2018) PNAS 115(36), 8907-8912. [7] Putrevu D. et al., (2023) JGR Planets, 128(12), e2023JE00774

How to cite: Sathyan, S., Bhatt, M., Kumar, S., Srivastava, N., and Bharadwaj, A.: Depth to diameter ratio of lunar craters and its possible correlation to the water ice deposits, Europlanet Science Congress 2024, Berlin, Germany, 8–13 Sep 2024, EPSC2024-1086, https://doi.org/10.5194/epsc2024-1086, 2024.