Key role of iron oxyhydroxides in dust aerosol from high and low latitudes
Notice bibliographique
Résumé
Millions of tonnes of dust are emitted into the atmosphere every year, a large proportion of which is transported and deposited to the oceans. Dust particles can directly affect the climate via dust&#8211;radiation interaction and indirectly via dust&#8211;cloud interaction, the snow/ice albedo effect and impacts on ocean biogeochemical cycles. Dust impacts on the climate and ecosystems depend on their mineralogical, chemical, microphysical, and optical properties. Over the past 20 years, important progress has been made in determining the properties of low-latitude dust and understanding how they change in the atmosphere.The mineralogical compositions, including iron mineralogy, of northern African and Asian dust are now better known and show a large variability depending on the source region. Distinctive patterns were found. For example, more calcium minerals (such as calcite) are found in dust from the Taklamakan Desert and palaeolakes in northern Africa than in dust from the Gobi and Sahara Desert; the contribution of iron oxides to the total iron in Saharan dust (25%-40%) is lower than in Sahel dust (ca. 60%), whereas dust from palaeolakes, including that from the Bodele depression, has lower iron oxide content (<25%). Most of the Fe oxide particles from the Sahara and Gobi Desert are as goethite, while more hematite is found in Sahel dust. These new data have allowed a much better modelling of the role of low-latitude dust in the Earth system.Only until recently, we started to study the properties of high-latitude dust, including from Iceland, Canada (Yukon), and Alaska. Icelandic dust particles are distinguished by the fact that most of them consist primarily of amorphous basaltic materials, up to 90&#8201;wt&#8201;%. The total Fe content is usually very high (10%&#8211;13%), and hematite and goethite contribute only 1%&#8211;6% of the total Fe, which is significantly lower than in low-latitude dust (except in palaeolakes). Magnetite accounts for 7%&#8211;15% of the total Fe, which is orders of magnitude higher than in dust from northern Africa. Nevertheless, about 80%&#8211;90% of the Fe is contained in pyroxene and amorphous glass. Data from both low- and high-latitude dust showed that the iron mineralogy is associated with the degree of chemical weathering and the composition of the parent sediments.The spectral single scattering albedo (SSA) of Icelandic dust falls within the range of low-latitude dust. The complex refractive index of dust is highly dependent on its source region, with Sahel and Icelandic dust showing highest values of imaginary index - k(&#955;). This indicates that Sahel and Icelandic dust is likely to be more absorbing. The measured spectral optical properties of both low- and high- latitude dust in the short-wave spectrum are consistent with what was predicted from their iron mineralogy.The iron mineralogy in dust also determines the rate of dissolution during atmospheric processing, and thus its impact on ocean biogeochemical processes after dust deposition. For example, the high dissolution rate in the first few minutes in dust under acidic conditions is related to the content of amorphous Fe oxides.
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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».