Ylva Palmgren

In recent years the use of aeolian sand influx (ASI) analyses on ombrotrophic peat sequences (c.f. Björck and Clemmensen, 2004) has become an increasingly popular method for reconstructing past storminess. This method is based on the assumption that all mineral grains deposited on the surface of the hydrologically isolated bog must have been brought to the site by wind. Thus, changes in the amount and size of the mineral grains found over time/depth can be related to past storm frequency and intensity. During the last two decades, several different methods of quantifying ASI have been developed. Three major drawbacks of these methods are that they are (i) often time- and labour intensive; (ii) rely on high temperature dry ashing to remove organic material from samples before ASI quantification and (iii) non-continuous, requiring discrete sampling.In an attempt to address these issues, we investigate whether X-ray computed tomography (CT) can be used to count and measure sand grains in peat. Drawing from the methods used by Cederstrøm et al. (2021) for IRD quantification in marine sediments, we added known amounts of sand (manually counted) in certain grain size fractions (63-1000, 125-1000, 63-125, 125-250, 250-500 and 500-1000 µm) and with known grain size distributions (laser diffraction) to test peat samples. The samples were then CT-scanned at a voxel resolution of 27.5 µm, and in the resulting 3D imagery, sand grains were identified, counted and measured using basic image processing tools. Our preliminary results indicate that it is possible to reliably count and measure sand grains in peat using a CT-based method, especially for grain sizes larger than 4-5 voxels (≥125 µm in this study). Grain size distributions for peat samples with sand grains ≥125 µm acquired through the CT method are strongly correlated to standard laser diffraction results (r = 0.81–0.98, p < 0.01). Similarly, CT-based and manual grain counts show a strong correlation (r = 0.94–1.00, p < 0.01) and the number of grains counted using the CT method differs on average by only 4 % from manual counts. Early-stage trials with full peat sequences further indicate that CT could be a reliable and efficient method for quantifying ASI and reconstructing past storm variability.ReferencesBjörck, S., Clemmensen, L., 2004. Aeolian sediment in raised bog deposits, Halland, SW Sweden: A new proxy record of Holocene winter storminess variation in southern Scandinavia? Holocene 14, 677–688. https://doi.org/10.1191/0959683604hl746rpCederstrøm, J.M., van der Bilt, W.G.M., Støren, E.W.N., Rutledal, S., 2021. Semi-automatic ice-rafted debris quantification with computed tomography. Paleoceanography and Paleoclimatology 36, e2021PA004293. https://doi.org/10.1029/2021PA004293

Virtual reality is a technological development that, among others, has revolutionized Earth sciences. Its advantages include an opportunity to examine places otherwise difficult or impossible to access and it may also become an important component of education, fostering a better understanding of processes and landforms, geohazard awareness, and an appreciation of geoheritage. This paper reports on the GeoVT project, which aims to create a platform to build and disseminate Virtual Field Trips (VFTs) focused on geomorphology, natural hazards associated with geomorphological processes, and geoheritage sites. To put the GeoVT project in context, an overview of applications of VR in geosciences is provided. This paper subsequently proceeds with a presentation of the project and the GeoVT Authoring application, which is an innovative platform designed to help teachers and students, followed by brief presentations of a number of VFTs developed within the project. They address themes such as fluvial landforms and valley development, coastal landforms, evidence of past glaciation, coastal erosion, wildfire effects, mud volcanoes, and landslides.