Stratospheric high-altitude balloons (HABs) have great potential as remote sensing platforms for Earth observations, complementing orbiting satellites and low-flying drones. At altitudes of 20–35 km, HABs operate significantly closer to the ground than orbiting satellites but significantly higher than most drones. Therefore, HABs offer unique potential for high-spatial-resolution imaging with large-area coverage. Two other imaging parameters important for Earth observation applications are spectral resolution and spectral range. Hence, in this work, we present the development and testing of a hyperspectral imaging system capable of recording near-video-rate images in narrow contiguous spectral bands from a HAB platform. In particular, we present the first stratospheric environmental tests and HAB flight of a snapshot hyperspectral camera based on computed tomography imaging spectroscopy, which is well-suited to address the challenges posed by the motion of the HAB platform and stratospheric environment. We successfully acquired images with the system under both simulated stratospheric conditions in the Mars Simulation Laboratory at Aarhus University and a 5-h HAB flight mission named HEIMDAL from Kiruna in October 2024 as part of the REXUS/BEXUS 34/35 2024 campaign organized by DLR-SNSA. This study represents a step toward deploying the HAB platform for high-quality land-cover classification.

The Máni mission will contribute to the overarching goal of enabling Europeans to explore the Moon by providing high-value and novel information that will assist in mission planning, de-risk landings, and facilitate scientific exploration. This will be achieved through a mapping mission that is designed from its inception to take advantage of recent advances in the field of photoclinometry and photometry.The Máni mission will be the first mission to employ a targeted multi-angular photoclinometric mapping approach to map key regions of interest of the Lunar surface. We aim to acquire the highest resolution orbital images of the Lunar surface, including the Polar regions, across a wide range of viewing geometries. From these images, we will produce detailed maps of the topography and reflectance properties at a resolution like that of the images. Additionally, through photometric analyses, we will provide sub-pixel information on surface properties down to mm-scale. Uniquely, from the probabilistic nature of the novel data processing employed, mission data products will all be accompanied with a measure of their level of confidence. This implies that future missions can select, e.g., landing sites that are not only predicted to comply with their mission requirements but also have a high level of confidence of complying with their requirements, thus lowering risks and increasing chances for mission success.The mission data processing is improved relative to already published work by mission members (1) in its integration of high-resolution imagery with available a priori information like laser altimetry data. It features a computationally efficient and advanced photoclinometric model that accounts for complex illumination and observing geometry. This enables pixel-level resolution in the simultaneous output of both topographic maps and surface reflectance maps. While novel and under ongoing development, the mission data processing approach is validated using available Lunar images.Exploration and scientific goalsBelow, we present a selection of studies that highlight the range of investigations that can be undertaken based on Máni mission data products.Assessing landing and mission sites of importance for human and robotic explorationThe primary focus of the Máni mission is to provide higher-resolution mapping of potential landing sites and locations of interest for exploration. The high-resolution images (as good as 20 cm/px at 50 km altitude) and topographic maps provided by the Máni mission enable unprecedented identification of hazards such as boulders, craters, and slopes that could jeopardize landing success. In particular, the ability to provide not only an accurate high-resolution topography of candidate landing sites but also assess the level of confidence of this presents a novel ability to not only select sites that are predicted to meet mission/lander requirements but sites that do so with a high probability.Sites of importance to future human and robotic exploration imposes demanding requirements on the operational orbit of the mission as many of these, e.g. for the Artemis missions, are situated close to the Lunar South Pole (2–4).Quantifying Earths albedo – a key parameter in climate modelsDetailed mapping of the lunar reflectance properties for two key regions, Grimaldi and Crisium, that has historically been used for Earthshine observations (5, 6) will enhance the value of lunar Earthshine data. It will not only strengthen future earthshine measurements but also enable a transformative reanalysis of archived earthshine data. This will yield more precise global (semi‐hemispheric) albedo estimates and facilitate targeted assessments of polar albedo—a critical parameter given current concerns over ice-cap melt, as well as address the observed decline in terrestrial albedo over a 20-year period.Effects of space weathering on the micro-texture of Lunar regolithWith the Máni mission we can take a new step forward in efforts to characterize and understand the lunar micro-texture. By deliberately targeting geological units from different ages and levels of maturity, we will be able to decipher the processes creating the regolith and estimate the evolution timescale. The Máni mission will augment these studies by mapping photometric properties at a resolution as good as ~20 cm/px. The high resolution provided by the Máni mission will also enable investigation of how other geological processes – e.g., lunar swirls, crater rays and volcanic flow – affect and modify the surface micro-texture. Mission and spacecraftThe Máni mapping methodology requires the acquisition of at least 5, preferentially 10, overlapping high-resolution images of a region of interest covering a range of viewing angles separated by more than 100°. Furthermore, at least two illumination angles, separated by at least 20°, must be captured as part of the images acquired of a region of interest. These requirements imply that at least two overflights, acquiring 5 images during each, of the target area separated in time by at least a full Lunar sideral period are needed to acquire the necessary image-data to map a region of interest.The Máni spacecraft is developed around the single large primary payload of the mission - an optical 300 mm telescope with a panchromatic 2D detector capable of acquiring images of the Lunar surface at a resolution as good or better than 20 cm/pixel at 50 km altitude. A secondary smaller colour imager intended to provide context for the primary images is also included.ReferencesI. Fernandes, K. Mosegaard, Planet. Space Sci. 218, 105514 (2022).E. Peña-Asensio, Á.-S. Neira-Acosta, J. M. Sánchez-Lozano, Acta Astronaut. 226, 469–478 (2025).C. Orgel et al., Planet. Sci. J. 5, 29 (2024).S. J. Boazman et al., Icarus. 421, 116240 (2024).P. R. Goode et al., Geophys. Res. Lett. 48 (2021), doi:10.1029/2021gl094888.P. Thejll, H. Gleisner, C. Flynn, Astron. Astrophys. 573, A131 (2015).

Carbon capture, utilisation and storage technologies are increasingly recognised as critical components of global climate mitigation strategies. However, the effective monitoring and verification of greenhouse gas emission reductions from carbon capture, utilisation and storage facilities remain significant challenges. This review synthesises current monitoring methods, including in situ sensing, drone-based observations and satellite remote sensing, and critically evaluates their strengths, limitations and applicability to various carbon capture, utilisation and storage contexts. We analyse the regulatory frameworks that govern monitoring practices across jurisdictions, identify methodological gaps and assess the performance of existing technologies with respect to detection thresholds, the integration of multiple data sources and the requirements for long-term verification. Particular emphasis is placed on the role of data assimilation and inversion modelling in interpreting measurements and quantifying emissions. Based on this synthesis, we recommend a more harmonised, concentration-based approach to monitoring that combines diverse observation platforms to enhance the accuracy, transparency and cost-effectiveness of verification efforts. This review aims to support the development of best practices for environmental monitoring and assessment in the context of carbon capture, utilisation and storage deployment.

Carbon capture, utilisation and storage technologies are increasingly recognized as crucial components in the global strategy to mitigate climate change. As the deployment of carbon capture, utilisation and storage systems expands, there is a growing need for rigorous monitoring and verification methods to ensure that these technologies achieve their intended reduction in greenhouse gas emissions. This paper explores the current state of monitoring techniques for carbon capture, utilisation and storage facilities, highlighting the challenges and opportunities associated with accurately quantifying net greenhouse gas emissions. We analyse both traditional bookkeeping methods and direct measurement techniques. Our analysis reveals the limitations of current monitoring frameworks and underscores the importance of integrating advanced measurement technologies, such as in-situ sensors, drones and satellite observations, to enhance the accuracy and reliability of greenhouse gas reporting. By proposing a comprehensive monitoring strategy that combines these methods, we aim to provide a roadmap for more effective oversight of carbon capture, utilisation and storage facilities, thereby contributing to the broader goal of reducing global carbon emissions.

After decades of steady growth, even reaching a growth rate of approximately zero from 2000 to 2006, the atmospheric methane (CH4) has returned to values observed in the second half of the twentieth century, and in recent years it has increased at a faster rate (Palmer et al., 2021). In this context, major initiatives involving the use of satellite-based inversion approaches have been implemented to respond to a growing demand from the climate community. One of this initiatives is the Integrated Methane Inversion (IMI, Varon et al., 2022). IMI is a cloud-based facility developed to infer regional CH4 emissions at 0.25° × 0.3125° resolution, with dynamic boundary conditions from a global archive of smoothed TROPOspheric Monitoring Instrument (TROPOMI) data. Three monthly IMI simulations were conducted over Denmark to estimate CH4 emissions before (June 2018), during (June 2020), and after (June 2021) the COVID-19-related lockdowns. The calculated a posteriori emissions for these periods were 0.579 Tg yr-1, 0.396 Tg yr-1, and 0.553 Tg yr-1, respectively. The approximately 31% emission reduction in June 2020 was almost swiftly reversed in June 2021, with a reduction of emissions in June 2021 by less than 5% compared to the same period in 2018. As many months other than June do not frequently meet the IMI preview configuration (a model feature to rate the quality of a proposed inversion without actually performing the inversion), multi-period simulations are being conducted to characterize CH4 emissions across the country. The new CH4 emissions data set will serve as a benchmark to evaluate the model performance of the Aarhus University Methane Inversion Algorithm (AUMIA, Vara-Vela et al., 2023). Currently under development, AUMIA is a satellite-based tool designed to quantify CH4 emissions over Europe, with a specific focus on anthropogenic activities.ReferencesPalmer, P. L., Feng, L., Lunt, M. F., Parker, R. J., Bosch, H., Lan, X., Lorente, A., and Borsdorff, T.: The added value of satellite observations of methane for understanding the contemporary methane budget, Philos. T. R. Soc. A., 379, 2210, https://doi.org/10.1098/rsta.2021.0106, 2021.Vara-Vela, A. L., Karoff, C., Benavente, R. N., and Nascimento, J. P.: Implementation of a satellite- based tool for the quantification of CH4 emissions over Europe (AUMIA v1.0) – Part 1: forward modelling evaluation against near-surface and satellite data, Geosci. Model Dev., 16, 6413-6431, 2023.Varon, D. J., Jacob, D. J., Sulprizio, M., Estrada, L. A., Downs, W. B., Shen, L., Hancock, S. E., Nesser, H., Qu, Z., Penn, E., Chen, Z., Lu, X., Lorente, A., Tewari, A., and Randles, C. A.: Integrated Methane Inversion (IMI 1.0): a user-friendly, cloud-based facility for inferring high- resolution methane emissions from TROPOMI satellite observations, Geosci. Model Dev., 15, 5787-5805, 2022.

Atmospheric CO2 concentrations in urban areas reflect a combination of fossil fuel emissions and biogenic fluxes, offering a potential approach to assess city climate policies. However, atmospheric models used to simulate urban CO2 plumes face significant uncertainties, particularly in complex urban environments with dense populations and vegetation. This study addresses these challenges by analyzing CO2 dynamics in the Metropolitan Area of S & atilde;o Paulo (MASP) using the Weather Research and Forecasting model with Chemistry (WRF-Chem). Simulations were evaluated against ground-based observations from the METROCLIMA network, the first greenhouse gas monitoring network in South America, and column concentrations (XCO2) from the OCO-2 satellite spanning February to August 2019. To improve biogenic fluxes, we optimized parameters in the Vegetation Photosynthesis and Respiration Model (VPRM) using eddy covariance flux measurements for key vegetation types, including the Atlantic Forest, Cerrado, and sugarcane. Results show that at the urban site (IAG), the model consistently underestimated CO2 concentrations, with a negative mean bias of -9 ppm throughout the simulation period, likely due to the complexity of vehicular emissions and urban dynamics. In contrast, at the vegetated site (PDJ), simulations showed a consistent positive mean bias of 5 ppm and closely matched observations. Seasonal analyses revealed higher CO2 concentrations in winter, driven by greater atmospheric stability and reduced vegetation uptake estimated by VPRM, while summer exhibited lower levels due to increased mixing and higher agricultural productivity. A comparison of biogenic and anthropogenic scenarios highlights the need for integrated emission modeling and improved representation of biogenic fluxes, anthropogenic emissions, and boundary conditions for high-resolution modeling in tropical regions.

The European Space Agency has selected PLATO (PLAnetary Transits and Oscillations of stars) for its M3 launch which is scheduled for 2026. With its extremely large field of view, PLATO is designed to obtain photometric measurements over an extended period for bright stars in order to detect and characterise (primarily) rocky planets in the habitable zones of solar type stars. The PLATO measurements will have sufficient sensitivity to determine the mass, radius and age of the host stars with unprecedented accuracy. The PLATO planet database will provide the first large-scale catalogue of accurately and homogeneously characterised small planets at intermediate orbital periods, which will can be used to severely constraint planet formation theories. This would facilitate large scale comparative exo-planetology. In addition the bright PLATO host stars will be ideal targets for atmospheric study with next generation facilities such as the ELT. The PLATO sensitivity will be sufficient to detect pulsations from stars across the HR diagram allowing a deep understanding of stellar structure and evolution to be developed using parameters determined from asteroseismology.

After stabilizing in the mid-2000s, atmospheric methane (CH4) levels have accelerated over the past decade. In response, satellite-based inversion techniques have been employed to meet the increasing demands of the climate community. In this study, the Integrated Methane Inversion (IMI) model, a novel approach based on the TROPOspheric Monitoring Instrument (TROPOMI), is used to quantify CH4 emissions across Denmark. Over 900,000 TROPOMI observations from spring to early autumn of 2018–2022 were used to inform the inversions. Overall, TROPOMI CH4 concentrations within the inversion domain showed an upward trend of approximately 12.71 ppb per year, reflecting the global trend. Excluding 2022, which included only four months of data, the inversions suggest an underestimation of emissions by 190(160–215) × 103 tonnes, or 66(56–75)% of prior estimates. Northern and southern Jutland, along with the Copenhagen metropolitan area, were identified as key sources of CH4 emissions. Additionally, the inversions indicated a decline in emissions during the COVID-19 pandemic, despite stable activity data. This study demonstrates the feasibility of using the IMI model to monitor CH4 emissions in small countries like Denmark, offering a satellite-based perspective to better identify and mitigate these emissions.

The severe impact of global warming, especially in the arctic region, have a multitude of consequences spanning from sea-level rises and freshening of the ocean, to significant changes to the animal life, biodiversity and species distribution. As the arctic regions are inherently remote and can be both hazardous and difficult to reach, research to improve our understanding of the climate change impact is often limited to short term field-campaigns. Here we present the Danish DISCO-2 student CubeSat mission, designed to meet the growing need for an Earth-observing platform. This mission leverages the rapid advancements in CubeSat technology over the past decades to overcome the limitations of traditional fieldwork campaigns. DISCO-2 will assist on-going arctic climate research with a payload of optical and thermal cameras in combination with novel in-orbit data analysis capabilities. It will further be capable of performing photogrammetric observations to determine ice volumes from deteriorating glaciers and provide surface temperatures, enabling studies of heat transfer between glaciers and arctic fjords. As a student satellite, the payload capabilities will also be offered to novel student research ideas throughout the mission life time. The modularity and wide range of of-the-shelf-components for CubeSats has facilitated an immense opportunity to tailor this earth observing CubeSat to accommodate specific scientific goals and further provided students at the participating universities with an unparalleled possibility to go from an initial research idea to a running CubeSat mission.

Methane is the second-most important greenhouse gas after carbon dioxide and accounts for around 10 % of total European Union greenhouse gas emissions. Given that the atmospheric methane budget over a region depends on its terrestrial and aquatic methane sources, inverse modelling techniques appear as powerful tools for identifying critical areas that can later be submitted to emission mitigation strategies. In this regard, an inverse modelling system of methane emissions for Europe is being implemented based on the Weather Research and Forecasting (WRF) model: the Aarhus University Methane Inversion Algorithm (AUMIA) v1.0. The forward modelling component of AUMIA consists of the WRF model coupled to a multipurpose global database of methane anthropogenic emissions. To assure transport consistency during the inversion process, the backward modelling component will be based on the WRF model coupled to a Lagrangian particle dispersion module. A description of the modelling tools, input data sets, and 1-year forward modelling evaluation from 1 April 2018 to 31 March 2019 is provided in this paper. The a posteriori methane emission estimates, including a more focused inverse modelling for Denmark, will be provided in a second paper. A good general agreement is found between the modelling results and observations based on the TROPOspheric Monitoring Instrument (TROPOMI) onboard the Sentinel-5 Precursor satellite. Model–observation discrepancies for the summer peak season are in line with previous studies conducted over urban areas in central Europe, with relative differences between simulated concentrations and observational data in this study ranging from 1 % to 2 %. Domain-wide correlation coefficients and root-mean-square errors for summer months ranged from 0.4 to 0.5 and from 27 to 30 ppb, respectively. On the other hand, model–observation discrepancies for winter months show a significant overestimation of anthropogenic emissions over the study region, with relative differences ranging from 2 % to 3 %. Domain-wide correlation coefficients and root-mean-square errors in this case ranged from 0.1 to 0.4 and from 33 to 50 ppb, respectively, indicating that a more refined inverse analysis assessment will be required for this season. According to modelling results, the methane enhancement above the background concentrations came almost entirely from anthropogenic sources; however, these sources contributed with only up to 2 % to the methane total-column concentration. Contributions from natural sources (wetlands and termites) and biomass burning were not relevant during the study period. The results found in this study contribute with a new model evaluation of methane concentrations over Europe and demonstrate a huge potential for methane inverse modelling using improved TROPOMI products in large-scale applications.

Over the last decade we have witnessed a rapid, so far unexplained, increase in the emission of methane to the atmosphere and this increase could lead to an acceleration of the ongoing climate changes. The increase is likely to originate from agriculture, but oil and gas production as well as wetlands are also under suspicion. The best way to quantify the emission of methane and other greenhouse gasses to our atmosphere is by using space based remote sensing. Here, we analyse 3 years of measurements of the column-averaged dry-air mole fraction of methane from the Tropospheric Monitoring Instrument on Sentinel-5P obtained with two different retrieval methods in order to evaluate the dependency on geographic, land cover type and season. The land cover types were obtained from the Moderate Resolution Imaging Spectroradiometer aboard the Terra and Aqua satellites and from the World Cover data product using observations from the Copernicus Sentinel-1 and Sentinel-2 missions. The analysis reveals that while the highest methane concentrations are generally found over croplands, the lowest are generally found over shrublands, which is in agreement with expectations. It is more surprising that the analysis also reveals lower than average methane concentrations over wetlands as wetlands are generally thought to be a major source of methane emission. Until this discrepancy is resolved the methane concentration over wetlands from the Tropospheric Monitoring Instrument on Sentinel-5P should be handled with caution. It is also found that the annual methane cycle, as seen in the measured methane concentrations, for croplands, shrublands and savannas is delayed in Africa compared to Asia.

Context. Stellar coronal mass ejections (CMEs) are the primary driver of exoplanetary space weather and may affect the habitability of exoplanets. However, detections of possible stellar CME signatures are extremely rare. Aims. This work aims to detect stellar CMEs from time-domain spectra observed through the LAMOST Medium-Resolution Spec-troscopic Survey (LAMOST-MRS). Our sample includes 1 379 408 LAMOST-MRS spectra of 226 194 late-type main-sequence stars (Teff < 6000 K, log[g/(cm s−2)] > 4.0). Methods. We first identified stellar CME candidates by examining the asymmetries of Hα line profiles and then performed double Gaussian fitting for Hα contrast profiles (differences between the CME spectra and reference spectra) of the CME candidates to analyse the temporal variation in the asymmetric components. Results. Three stellar CME candidates were detected on three M dwarfs. The Hα and Mg I triplet lines (at 5168.94 Å, 5174.13 Å, and 5185.10 Å) of candidate 1 all exhibit a blue-wing enhancement, and the corresponding Doppler shift of this enhancement shows a gradually increasing trend. The Hα line also shows an obvious blue-wing enhancement in candidate 2. In candidate 3, the Hα line shows an obvious red-wing enhancement, and the corresponding projected maximum velocity exceeds the surface escape velocity of the host star. The lower limit of the CME mass is estimated to be ~8 × 1017 g to 4 × 1018 g for these three candidates.

Abstract. Etesian winds represent one of the most stable summer circulation regimes in the Eastern Mediterranean. The Indian Summer Monsoon (ISM) variability and tropical/extra-tropical teleconnections are influencing the Eastern Mediterranean, given that a stronger ISM is often associated with more intense and persistent Etesian winds. The response of Etesian winds to external forcing on interannual and longer time scales, however, is not well understood. Here, for the first time, we investigate responses of Etesian winds to large volcanic eruptions by analysing a blend of model simulations covering the last millennium and reanalysis data over the 20th century. We provide model evidence for significant volcanic signatures, manifested as a robust reduction of the average wind speed in late summer months and the total number of days with Etesian winds. These signatures are attributed to the weakening of the ISM in the post-eruption summer, which reduces large scale subsidence in the Eastern Mediterranean, weakens the Anatolian low, and finally reduces the intensity and persistence of the Etesian winds. We find a stronger sensitivity of Etesian winds to Northern Hemisphere volcanoes, particularly before the 20th century, while for the latest large eruption of Pinatubo, modelled and observed responses are insignificant. Our results could be applied to improve seasonal prediction of wind circulation in the Eastern Mediterranean in the post-eruption summers.

The northerly Etesian winds are a stable summertime circulation system in the eastern Mediterranean, emerging from a steep pressure gradient between the central Europe and Balkans high-pressure and the Anatolian low-pressure systems. Etesian winds are influenced by the variability in the Indian summer monsoon (ISM), but their sensitivity to external forcing on interannual and longer timescales is not well understood. Here, for the first time, we investigate the sensitivity of Etesian winds to large volcanic eruptions in a set of model simulations over the last millennium and reanalysis of the 20th century. We provide model evidence for significant volcanic signatures, manifested as a robust reduction in the wind speed and the total number of days with Etesian winds in July and August. These are robust responses to all strong eruptions in the last millennium, and in the extreme case of Samalas, the ensemble-mean response suggests a post-eruption summer without Etesians. The significant decline in the number of days with Etesian winds is attributed to the weakening of the ISM in the post-eruption summers, which is associated with a reduced large-scale subsidence and weakened surface pressure gradients in the eastern Mediterranean. Our analysis identifies a stronger sensitivity of Etesian winds to the Northern Hemisphere volcanic forcing, particularly for volcanoes before the 20th century, while for the latest large eruption of Pinatubo modelled and observed responses are insignificant. These findings could improve seasonal predictions of the wind circulation in the eastern Mediterranean in the summers after large volcanic eruptions.

This study investigates solar variability between 650 CE and 1900 based on new and published 14C records with a time resolution of two years or higher. The new high-resolution 14C data presented here are derived from Danish oak and span the period 1058–1250 CE. We determine the durations of past solar minima and periods with moderate solar activity from the solar modulation potential calculated using a carbon-box model with the high-resolution 14C records as input. The observed intervals of solar minima and intermittent periods with moderate activity levels suggest that a Maunder-type minimum occurred in 656–707 CE. We tentatively propose to name this minimum the Horrebow Minimum after Christian Horrebow, an early Danish astronomer who studied the occurrence of sunspots and was the first to propose that they follow a cyclic behaviour. Changes in amplitude and cycle length of the 11-year solar cycle are investigated by bandpass filtering 23 individual 14C records. The filtered 14C data indicate that the length of the 11-year solar cycle may be prolonged before the onset of the Oort, Maunder, and Spörer minima. The amplitude of the 11-year solar cycle associated with solar minima and periods with moderate solar activity between 650 CE and 1900 is estimated to 1.1‰. A two-sample Kolmogorov-Smirnov goodness-of-fit test indicates that there is no significant difference between the amplitude distribution of 11-year solar cycles during solar minima and periods of moderate solar activity. A review of the high-resolution 14C records encompassing the near-Earth supernova events that occurred in 1006 CE, 1054, 1181, 1572, and 1604 suggests that these events were not accompanied by distinct changes in the 14C production rate. Nonetheless, an unusual increase of c. 10‰ in Δ14C between 1048 CE and 1055 is observed and discussed.

In the last decade, the Kepler and CoRoT space-photometry missions have demonstrated the potential of asteroseismology as a novel, versatile and powerful tool to perform exquisite tests of stellar physics, and to enable precise and accurate characterisations of stellar properties, with impact on both exoplanetary and Galactic astrophysics. Based on our improved understanding of the strengths and limitations of such a tool, we argue for a new small/medium space mission dedicated to gathering high-precision, high-cadence, long photometric series in dense stellar fields. Such a mission will lead to breakthroughs in stellar astrophysics, especially in the metal poor regime, will elucidate the evolution and formation of open and globular clusters, and aid our understanding of the assembly history and chemodynamics of the Milky Way’s bulge and a few nearby dwarf galaxies.

In the last decade, the Kepler and CoRoT space-photometry missions have demonstrated the potential of asteroseismology as a novel, versatile and powerful tool to perform exquisite tests of stellar physics, and to enable precise and accurate characterisations of stellar properties, with impact on both exoplanetary and Galactic astrophysics. Based on our improved understanding of the strengths and limitations of such a tool, we argue for a new small/medium space mission dedicated to gathering high-precision, high-cadence, long photometric series in dense stellar fields. Such a mission will lead to breakthroughs in stellar astrophysics, especially in the metal poor regime, will elucidate the evolution and formation of open and globular clusters, and aid our understanding of the assembly history and chemodynamics of the Milky Way's bulge and few nearby dwarf galaxies.

ABSTRACTWe here present a comparison of methods for the pretreatment of a batch of tree rings for high-precision measurement of radiocarbon at the Aarhus AMS Centre (AARAMS), Aarhus University, Denmark. The aim was to develop an efficient and high-throughput method able to pretreat ca. 50 samples at a time. We tested two methods for extracting α-cellulose from wood to find the most optimal for our use. One method used acetic acid, the other used HCl acid for the delignification. The testing was conducted on background 14C samples, in order to assess the effect of the different pretreatment methods on low-activity samples. Furthermore, the extracted wood and cellulose fractions were analyzed using Fourier transform infrared (FTIR) spectroscopy, which showed a successful extraction of α-cellulose from the samples. Cellulose samples were pretreated at AARAMS, and the graphitization and radiocarbon analysis of these samples were done at both AARAMS and the radiocarbon dating laboratory at Lund University to compare the graphitization and AMS machine performance. No significant offset was found between the two sets of measurements. Based on these tests, the pretreatment of tree rings for high-precision radiocarbon analysis at AARAMS will henceforth use HCI for the delignification.

ABSTRACT In this work, we analysed the magnetic activity of 5349 Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) low-dispersion spectra of 3539 red giants by calculating equivalent width (EW) of magnetic activity lines (H α, H β, H γ, H δ, $\rm{Ca~{ii} H\&K}$, $\rm{Ca~{ii} IRT}$). Combining LAMOST spectral parameters, asteroseismic parameters, and EWs of the magnetic activity lines, an attempt was made to estimate the age of red giants using neural networks. By using the neural networks to select the input parameters, we get the best age estimation of the red giants with the input parameters ‘Teff’, ‘[Fe/H]’, ‘log g’, ‘νmax’, and ‘Δν’, which is in line with expectations. The average value of the relative error between the estimated age and the isochronous age is 22.4 per cent. The age estimation was not improved by adding the EWs of more magnetic activity lines. This indicates that the EWs of these spectral lines are not directly related to the age of the red giants. The reason for this might be that the dynamo operating in the outer layers of the red giants has shut off at the end of core-hydrogen-burning. The absence of emission in all the magnetic activity lines of the 5349 LAMOST spectra also confirms this conclusion. In addition, the results indicate that the EWs of the magnetic activity lines are more related to the effective temperature, which is also in line with expectations.