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Escribano, Jerónimo
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1

Modeling dust mineralogical composition: sensitivity to soi..:

Gonçalves Ageitos, María ; Obiso, Vincenzo ; Miller, Ron L...
https://publikationen.bibliothek.kit.edu/1000167730.  , 2024
Link: https://publikationen.bi..
 
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2

Insights into the size-resolved dust emission from field me..:

González-Flórez, Cristina ; Klose, Martina ; Alastuey, Andrés...
https://tuprints.ulb.tu-darmstadt.de/24772/10/acp-23-7177-2023.pdf.  , 2024
Link: http://tuprints.ulb.tu-d..
 
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3

Data presented in González-Flórez et al. 2023 "Insights int..:

González-Flórez, Cristina ; Klose, Martina ; Alastuey, Andrés...
https://publikationen.bibliothek.kit.edu/1000167729.  , 2024
Link: https://publikationen.bi..
 
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4

Modeling dust mineralogical composition: sensitivity to soi..:

Gonçalves Ageitos, María ; Obiso, Vincenzo ; Miller, Ron L....
Atmospheric Chemistry and Physics.  23 (2023)  15 - p. 8623-8657 , 2023
Link: https://doi.org/10.5194/..
 
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5

Insights into the size-resolved dust emission from field me..:

González-Flórez, Cristina ; Klose, Martina ; Alastuey, Andrés...
Atmospheric Chemistry and Physics.  23 (2023)  12 - p. 7177-7212 , 2023
Link: https://doi.org/10.5194/..
 
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6

Modeling dust mineralogical composition: sensitivity to soi..:

Gonçalves Ageitos, María ; Obiso, Vincenzo ; Miller, Ron L...
Atmospheric Chemistry and Physics -- http://www.atmos-chem-phys.net/volumes_and_issues.html -- http://www.bibliothek.uni-regensburg.de/ezeit/?2069847 -- 1680-7324.  , 2023
Link: https://doi.org/10.5194/..
 
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7

MONARCH data presented in Klose et al. (2021), "Mineral dus..:

Klose, Martina ; Jorba, Oriol ; Gonçalves Ageitos, María...
https://publikationen.bibliothek.kit.edu/1000154875.  , 2023
Link: https://publikationen.bi..
 
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8

Modeling dust mineralogical composition: sensitivity to soi..:

Gonçalves Ageitos, María ; Obiso, Vincenzo ; Miller, Ron L...
info:eu-repo/grantAgreement/EC/H2020/821205/.  , 2023
Link: https://zenodo.org/recor..
 
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9

Modeling dust mineralogical composition: sensitivity to soi..:

Ageitos, María Gonçalves ; Obiso, Vincenzo ; Miller, Ron, L...
info:eu-repo/semantics/altIdentifier/doi/10.5194/acp-23-8623-2023.  , 2023
Link: https://hal.science/hal-..
 
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10

Modeling dust mineralogical composition: sensitivity to soi..:

Ageitos, María Gonçalves ; Obiso, Vincenzo ; Miller, Ron, L...
info:eu-repo/semantics/altIdentifier/doi/10.5194/acp-23-8623-2023.  , 2023
Link: https://hal.science/hal-..
 
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11

Modeling dust mineralogical composition: sensitivity to soi..:

Ageitos, María Gonçalves ; Obiso, Vincenzo ; Miller, Ron, L...
info:eu-repo/semantics/altIdentifier/doi/10.5194/acp-23-8623-2023.  , 2023
Link: https://hal.science/hal-..
 
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12

Modeling dust mineralogical composition: sensitivity to soi..:

Gonçalves Ageitos, María ; Obiso, Vincenzo ; Miller, Ron L...
https://acp.copernicus.org/articles/23/8623/2023/acp-23-8623-2023.html.  , 2023
Link: http://hdl.handle.net/21..
 
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13

Data presented in González-Flórez et al. 2023 "Insights int..:

González-Flórez, Cristina ; Klose, Martina ; Alastuey, Andrés...
info:eu-repo/grantAgreement/EC/H2020/773051/.  , 2023
Link: https://zenodo.org/recor..
 
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14

Modeling dust mineralogical composition: sensitivity to soi..:

Gonçalves Ageitos, María ; Obiso, Vincenzo ; Miller, Ron L...
doi:10.5194/acp-23-8623-2023.  , 2023
Link: https://doi.org/10.5194/..
 
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15

Modeling dust mineralogical composition: sensitivity to soi..:

Ageitos, María Gonçalves ; Obiso, Vincenzo ; Miller, Ron, L...
info:eu-repo/semantics/altIdentifier/doi/10.5194/acp-23-8623-2023.  , 2023
Link: https://hal.science/hal-..
 
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