Lunar Secondary Radiation Soil Response Toolkit and Applications for GRNS

The lunar radiation environment presents harsh conditions for both manned and unmanned lunar missions due to the lack of atmospheric and magnetic shielding from primary radiation, such as solar energetic particles and galactic cosmic rays. These highly energetic particles pose a significant risk for both biological tissue and electronics, and therefore set constraints on shielding, mission duration and material choices.

During impact on the lunar regolith, secondary radiation in the form neutrons, protons, electrons and gamma rays is generated and partially emitted from the lunar surface. This contributes to the overall radiation level experienced by humans and spacecraft near the lunar surface. Secondary radiation measurements therefore grow increasingly relevant with the current international efforts to return to the Moon and establish manned lunar bases within the next decade.

Due to specific absorption and emission lines from each element altering the regolith’s response to primary radiation, secondary radiation measurements are capable of determining elemental abundances in the lunar regolith. Gamma-ray and neutron spectroscopy (GRNS) can quantify abundances of elements, such as H, Fe, Mg, Si, Al, Na, O and Ti. GRNS methods can be applied both from orbit – for course mapping of larger areas, and on rovers for localizing resources on a much finer scale. Mapping reserves of such elements enables in-situ resource utilisation and resource mining, as it supports the identification of landing sites with suitable resources.

To predict the local radiation environment and prepare elemental abundance mapping missions, we developed a simulation toolkit of the interaction between primary cosmic rays and the lunar regolith, in addition to the subsequent secondary radiation response. Given primary radiation spectra from cosmic ray models, such as CREME96, the DLR GCR model¹, and SAPPHIRE, the particle propagation in the lunar regolith is simulated using Geant4 with BDSIM². Responses are determined for variations in lunar regolith properties including elemental soil composition, hydrogen content, temperature, as well as changes in primary radiation spectra. Figure 1 shows the block diagram of the simulation toolkit.

Figure 1 Lunar Secondary Radiation Simulation Toolkit Concept

 

Predicted secondary radiation spectra variations, such as epithermal neutron depletion or presence of spectral lines for different soil and irradiation conditions such as shown in Figure 2, provide crucial data for both instrument design and data processing of future GRNS missions, such as the Gamma-Ray-including-Neutrons Spectrometer (GRiNS)³ that was proposed onboard the SER3NE mission⁴. Our toolkit predicts the secondary radiation flux in a given orbit, and with that contributes to the dimensioning of the active detection area and anti-coincidence shield needed.

Figure 2 Neutron flux for various hydrogen contents in FAN. Epithermal neutrons within orange marked energy range as defined from Gd cut-off to fast neutron range

 

Secondary radiation flux predictions furthermore provide insight into the surface radiation environment on the lunar surface and can aid in manned and unmanned lunar mission planning by predicting more precise radiation doses and analysing the effect of soil compositions on the local radiation environment, such as ground level enhancement effects.

In this report, we introduce our simulation framework, verify the results, and demonstrate its application potential on the example of the GRiNS instrument in the SER3NE orbit.

 

Acknowledgements  

We would like to thank our colleagues Sam Holdcroft and Rebecka Wahlén at UiO/CENSSS for the input on the GRiNS instrument, and Stephanie Werner at UiO/PHAB and the SER3NE team for the mission details, science objectives and their discussions and reviews.

 

References

1) Daniel Matthiä, Thomas Berger, Alankrita I. Mrigakshi, Günther Reitz. A ready-to-use galactic cosmic ray model. Adv Space Res. 2013;51(3):329-338. doi:10.1016/j.asr.2012.09.022

2) Nevay LJ, Boogert ST, Snuverink J, et al. BDSIM: An accelerator tracking code with particle–matter interactions. Comput Phys Commun. 2020;252:107200. doi:10.1016/j.cpc.2020.107200

3) Kohfeldt A, Wahlén R, Holdcroft S, Teodoro LFA, Werner S. Element Abundance Mapping with the SER3NE Gamma-Ray and Neutron Spectrometer. Copernicus Meetings; 2025. doi:10.5194/epsc-dps2025-1439

4) Werner SC. The SER3NE Mission to Hunt for Water and Other Volatiles on the Moon. Copernicus Meetings; 2025. doi:10.5194/epsc-dps2025-1451