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The Earth surface Mineral dust source InvesTigation (EMIT) is a remote visible to shortwave infrared (VSWIR) imaging spectrometer that has been operating onboard the International Space Station since July 2022. This article describes EMIT's on-orbit spectroradiometric calibration and validation. Accurate spectroscopy is vital to achieve consistent mapping results with orbital imaging spectrometers. EMIT takes a unique approach to this challenge, with just six optical elements, no shutter, and no onboard calibration systems. Its simple design focuses on uniformity and stability to enable vicarious spectroradiometric calibration. Our experiments demonstrate that this approach is successful, approaching the fidelity of manual field spectroscopy in some cases, and enabling new and more accurate products across diverse Earth science disciplines. EMIT achieves several notable firsts for an instrument of its class. It demonstrates successful on-orbit adjustments of Focal Plane Array (FPA) alignment with sub-micron precision. It offers spectral uniformity better than 98%. Optical artifacts in the measurement channels are at least three orders of magnitude below the primary solar-reflected surface signals. Its noise performance enables percent-level discrimination in the depths of mineral absorption features. In these aspects, EMIT satisfies the stringent performance needs for the next generation of VSWIR imaging spectrometers to observe the Earth's ecosystems, geology, and water resources., EMIT is supported by the National Aeronautics and Space Administration Earth Venture Instrument program, under the Earth Science Division of the Science Mission Directorate. K. Dana Chadwick is supported by the NASA Applied Sciences Program. Carlos P´ erez García- Pando and María Gonçalves Ageitos acknowledge support from the European Research Council (ERC) Consolidator Grant FRAGMENT (grant agreement No. 773051), and the AXA Chair on Sand and Dust Storms at the Barcelona Supercomputing Center funded by the AXA Research Fund. Martina Klose has received funding through the Helmholtz Association’s Initiative and Networking Fund (grant agreement No. VH-NG-1533). We thank Jeffrey Czapla-Myers and the University of Arizona team for their maintenance and operation of the Railroad Valley automated calibration facility. This research was performed at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration. We acknowledge the support and assistance of NASA’s International Space Station Program. The USGS authors’ contribution to this published Work was prepared by U.S. federal government employees as part of their official duties and constitutes a “work of the United States government,” and is considered to be in the public domain and therefore domestic copyright does not apply. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government. Copyright 2024 California Institute of Technology. All rights reserved. US Government Support Acknowledged., Peer Reviewed, Article signat per 56 autors: David R. Thompson, Robert O. Green, Christine Bradley, Philip G. Brodrick, Natalie Mahowald, Eyal Ben Dor, Matthew Bennett, Michael Bernas, Nimrod Carmon, K. Dana Chadwick, Roger N. Clark, Red Willow Coleman, Evan Cox, Ernesto Diaz, Michael L. Eastwood, Regina Eckert, Bethany L. Ehlmann, Paul Ginoux, María Gonçalves Ageitos, Kathleen Grant, Luis Guanter, Daniela Heller Pearlshtien, Mark Helmlinger, Harrison Herzog, Todd Hoefen, Yue Huang, Abigail Keebler, Olga Kalashnikova, Didier Keymeulen, Raymond Kokaly, Martina Klose, Longlei Li, Sarah R. Lundeen, John Meyer, Elizabeth Middleton, Ron L. Miller, Pantazis Mouroulis, Bogdan Oaida, Vincenzo Obiso, Francisco Ochoa, Winston Olson-Duvall, Gregory S. Okin, Thomas H. Painter, Carlos Pérez García-Pando, Randy Pollock, Vincent Realmuto, Lucas Shaw, Peter Sullivan, Gregg Swayze, Erik Thingvold, Andrew K. Thorpe, Suresh Vannan, Catalina Villarreal, Charlene Ung, Daniel W. Wilson, Sander Zandbergen., Objectius de Desenvolupament Sostenible::13 - Acció per al Clima, Postprint (published version)

The effects of desert dust upon climate and ecosystems depend strongly on its particle size and size-resolved mineralogical composition. However, there is very limited quantitative knowledge on the particle size and composition of the parent sediments along with their variability within dust-source regions, particularly in dust emission hotspots. The lower Drâa Valley, an inland drainage basin and dust hotspot region located in the Moroccan Sahara, was chosen for a comprehensive analysis of sediment particle size and mineralogy. Different sediment type samples (n=¿42) were collected, including paleo-sediments, paved surfaces, crusts, and dunes, and analysed for particle-size distribution (minimally and fully dispersed samples) and mineralogy. Furthermore, Fe sequential wet extraction was carried out to characterise the modes of occurrence of Fe, including Fe in Fe (oxyhydr)oxides, mainly from goethite and hematite, which are key to dust radiative effects; the poorly crystalline pool of Fe (readily exchangeable ionic Fe and Fe in nano-Fe oxides), relevant to dust impacts upon ocean biogeochemistry; and structural Fe. Results yield a conceptual model where both particle size and mineralogy are segregated by transport and deposition of sediments during runoff of water across the basin and by the precipitation of salts, which causes a sedimentary fractionation. The proportion of coarser particles enriched in quartz is higher in the highlands, while that of finer particles rich in clay, carbonates, and Fe oxides is higher in the lowland dust emission hotspots. There, when water ponds and evaporates, secondary carbonates and salts precipitate, and the clays are enriched in readily exchangeable ionic Fe, due to sorption of dissolved Fe by illite. The results differ from currently available mineralogical atlases and highlight the need for observationally constrained global high-resolution mineralogical data for mineral-speciated dust modelling. The dataset obtained represen, Peer Reviewed, Postprint (published version)