How relevant is the deposition of mercury onto snowpacks? – Part 2: A modeling study
Notice bibliographique
Résumé
Abstract. An unknown fraction of mercury that is deposited onto snowpacks is revolatilized to the atmosphere. Determining the revolatilized fraction is important since mercury that enters the snowpack meltwater may be converted to highly toxic bioaccumulating methylmercury. In this study, we present a new dynamic physically-based snowpack/meltwater model for mercury that is suitable for large-scale atmospheric models for mercury. It represents the primary physical and chemical processes that determine the fate of mercury deposited onto snowpacks. The snowpack/meltwater model was implemented in Environment Canada's atmospheric mercury model GRAHM. For the first time, observed snowpack-related mercury concentrations are used to evaluate and constrain an atmospheric mercury model. We find that simulated concentrations of mercury in both snowpacks and the atmosphere's surface layer agree closely with observations. The simulated concentration of mercury in both in the top 30 cm and the top 150 cm of the snowpack, averaged over 2005–2009, is predominantly below 6 ng L−1 over land south of 66.5° N but exceeds 18 ng L−1 over sea ice in extensive areas of the Arctic Ocean and Hudson Bay. The average simulated concentration of mercury in snowpack meltwater runoff tends to be higher on the Russian/European side (>20 ng L−1) of the Arctic Ocean than on the Canadian side (<10 ng L−1). The correlation coefficient between observed and simulated monthly mean atmospheric surface-level gaseous elemental mercury (GEM) concentrations increased significantly with the inclusion of the new snowpack/meltwater model at two of the three stations (midlatitude, subarctic) studied and remained constant at the third (arctic). Oceanic emissions are postulated to produce the observed summertime maximum in concentrations of surface-level atmospheric GEM at Alert in the Canadian Arctic and to generate the summertime volatility observed in these concentrations at both Alert and Kuujjuarapik on subarctic Hudson Bay, Canada. We find that the fraction of deposited mercury that is revolatilized from snowpacks increases with latitude from 39% between 30 and 45° N, to 57% from 45 to 60° N, 67% from 60 to 66.5° N, and 75% polewards of 66.5° N on an annual basis. Combining this latitudinal gradient with the latitudinally increasing coverage of snowpacks causes yearly net deposition as a fraction of gross deposition to decrease from 98% between 30 and 45° N to 89% between 45 and 60° N, 73% between 60 and 66.5° N, and 44% within the Arctic Circle. The yearly net deposition and net accumulation of mercury at the surface within the Arctic Circle north of 66.5° N are estimated at 153 and 117 Mg, respectively. We calculate that 58 and 50 Mg of mercury are deposited annually to the Arctic Ocean directly and indirectly via melting snowpacks, respectively. For terrestrial surfaces within the Arctic Circle, we find that 29 and 16 Mg of mercury are deposited annually directly and indirectly via melting snowpacks, respectively. Within the Arctic Circle, multi-season snowpacks on land and over sea ice gained, on average, an estimated 0.1 and 0.4 Mg yr−1 mercury, respectively, from 2000–2005. The developed snowpack/meltwater model can be used for investigating the impact of climate change on the snowpack/atmosphere exchange of mercury.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
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) | 0,000 | 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 ».