Published December 11, 2025 | Version v1
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Files for "Global Model Estimates of Atmospheric Al, Ca, Fe, Si, and Ti from Dust and Non-Dust Aerosols Informed by EMIT Surface Mineralogy and Evaluated Against Observations"

  • 1. ROR icon Cornell University
  • 2. ROR icon Universitat Politècnica de Catalunya
  • 3. ROR icon Barcelona Supercomputing Center
  • 4. Goddard Institute of space studies
  • 5. ROR icon Institució Catalana de Recerca i Estudis Avançats
  • 6. NOAA Geophysical Fluid Dynamics Laboratory
  • 7. ROR icon Jet Propulsion Laboratory
  • 8. ROR icon Planetary Science Institute
  • 9. ROR icon Université Paris Cité
  • 10. ROR icon University of California, Los Angeles
  • 11. EDMO icon National Aeronautics and Space Administration, Jet Propulsion Laboratory
  • 12. University of Aveiro
  • 13. ROR icon Consejo Superior de Investigaciones Científicas
  • 14. Center for Amazonian Sustainability - USP
  • 15. ROR icon Universidade de São Paulo
  • 16. EDMO icon University of East Anglia, School of Environmental Sciences
  • 17. Saw Science
  • 18. ROR icon University of Florence
  • 19. ROR icon Skidaway Institute of Oceanography
  • 20. ROR icon Fudan University
  • 21. ROR icon University of California, Santa Cruz
  • 22. ARPA Lombardia
  • 23. ROR icon National Centre of Scientific Research "Demokritos"
  • 24. ROR icon Desert Research Institute
  • 25. CNRS Delegation Occitanie Ouest
  • 26. University of Miami Rosenstiel School of Marine and Atmospheric Science
  • 27. ROR icon Comisión Nacional de Energía Atómica
  • 28. CIMEL Electronique
  • 29. ROR icon Colorado State University
  • 30. ROR icon University of Birmingham
  • 31. ROR icon Israel Oceanographic and Limnological Research
  • 32. ROR icon University of Rochester Medical Center
  • 33. HUN-REN Institute for Nuclear Research (ATOMKI)
  • 34. Finnish Accreditation Service FINAS
  • 35. ROR icon Pontificia Universidad Católica de Chile
  • 36. ROR icon Florida State University
  • 37. Università degli Studi di Firenze
  • 38. ROR icon University of Delaware
  • 39. ROR icon Nagoya University
  • 40. ROR icon Universidad de Navarra
  • 41. Univ. of Miami
  • 42. Consejo Superior de Investigaciones Científicas,IPNA CSIC
  • 43. CNRS Délégation Bretagne et Pays de Loire
  • 44. University of Palermo

Description

Datasets for "Global Model Estimates of Atmospheric Al, Ca, Fe, Si, and Ti from Dust and Non-Dust Aerosols Informed by EMIT Surface Mineralogy and Evaluated Against Observations"

Atmospheric deposition of micro-nutrients like Fe has been shown to be important for ocean biogeochemistry.  The largest source of atmospheric Fe and other elements (e.g., Ca, Al, Si, and Ti) is desert dust, although there are significant non-dust sources in some regions. However, past estimates of these elements have been substantially uncertain due to limited information about the composition of the desert source regions.  Here we use elemental distributions estimated from new Earth Surface Mineral Dust Source Investigation (EMIT) observations, which provide mineralogical composition at the surface of the Earth based on imaging spectroscopy measurements from the International Space Station. We add in other sources of these elements (anthropogenic and natural) and compare to a compilation of available surface concentration data from stations over land and from shipborne observations.  Our results suggest that the modeled distribution is similar to available observations, but discrepancies still exist in both natural desert dust regions as well as regions dominated by anthropogenic sources.  Global budgets for the elements Ca, Al, Fe, Si, and Ti suggest that desert dust remains the dominant source for these elements but anthropogenic or volcanic sources are also important for these elements.  Changes in elemental distributions since preindustrial times were also estimated.

Files

modelfiles.zip

Files (43.4 MB)

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md5:76685f288454785bc3d81e283e69cda9
40.5 MB Preview Download
md5:8b07458b33da819674383c884959e640
5.7 kB Download
md5:562ab9adbd0d35b9a766956fc36196a7
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md5:1a6a63ef8f4d4825ff618a8ea2f39df9
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md5:aa81ede868de5f40daee6377377280b0
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md5:5053ef70e7b5d7144595519b6ab55bc2
1.3 MB Download

Additional details

Dates

Created
2025-12-11