Temporal trends of mercury levels in fish (dab, Limanda limanda) and sediment from the German Bight (North Sea) in the period 1995–2020
Notice bibliographique
Résumé
As a toxic and harmful global pollutant, mercury (Hg) enters the marine environment through natural sources, and human activities. It bioaccumulates through the food chain and therefore, Hg is of great importance for environmental monitoring. This study aims to answer the question if Hg contamination in fish and sediment from the German Bight follows temporal trends. Therefore, 496 individual female dab (Limanda limanda) were analyzed. The Hg concentrations in the muscle of dab from the German Bight showed significant increase in function of time with an annual percental change of 1.4%, leading to a 41% increase in Hg contamination level within 25 years of monitoring. At the same time, Hg concentrations in sediment—analyzed in 86 samples—significantly decreased in the nearby North Sea environment. This surprising contradiction is shown in the present study and possible causes are discussed. It could be clearly shown that contamination in sediment and biota can follow completely different time courses and therefore, different environmental matrices should be considered in future monitoring studies. Age of the fish turned out to be a biological factor of particular importance for temporal trend analysis. Methode Mercury in fish The determination of Hg in fish from 1995 to 2009 followed the protocol described by Harms (1981, 1998). Briefly, wet samples were subjected to a pressure digestion by nitric acid in PTFE tubes heated up to 135 °C for 2 h. This was partly supported by a microwave system, “MLS-Ethos-plus” (MLS Mikrowellen Labor-Systeme GmbH, Leutkirch, Germany). Mercury was determined by cold vapor atomic absorption spectrometry using a flow injection mercury system Model 420 (Perkin Elmer, Rodgau, Germany) with background compensation and Hg lamp. A clean bench was used to avoid contamination during sample processing. The limit of detection (LD) was calculated according to DIN 32,645 (DIN, 1994) and was always below 1.2 μg Hg/kg wet weight (ww). The method used from 2010 to determine Hg in fish is in detail described in Kammann et al. (2021). Briefly, samples were freeze-dried using a lyophilizer (LD 1–2,Christ, Osterode, Germany) and subsequently homogenized using an agate mortar or an ultra Turrax tube drive dispenser (IKA, Staufen, Germany) to obtain a dry and homogenous sample powder. Total Hg was determined by atomic absorption spectrometry using a Direct Mercury Analyzer (DMA-80, MLS, Leutkirch, Germany). A total of 20–30 mg of each sample were weighted into the boat containers of the DMA-80. Direct analysis for total Hg content was performed using a 10-level calibration with standards in 0.5 M nitric acid. The LD and the limit of quantification (LQ) were calculated from a standard curve according to DIN 32,645 (DIN, 1994) with a confidence level of 99%. Considering the sample preparation, a LD of 0.080 μg/kg ww and a LQ of 0.230 μg/kg ww were determined for Hg. No values below these limits were found in any sample under investigation. Preparation steps were carried out under clean benches all the time. Clean lab conditions of ISO class 7 were available since 2018. Nitric acid (69%, ultrapure quality) and certified standard solutions of Hg were purchased from Carl Roth, Karlsruhe, Germany, in 0.5 M nitric acid. Ultrapure water was obtained from a Purelab Flex 3 device (Elga Veolia; High Wycombe, UK). The accuracy of the Hg measurement in fish was determined by analysis of Certified Reference Materials (e.g., DORM-4) obtained from the National Research Council (NRC) in Canada which was taken through the same analytical procedure as the samples. All samples were measured in triplicates. External quality assurance was done by participation in laboratory proficiency tests conducted by QUASIMEME (www.wepal.nl) designed for marine environment analytics from 1997 to 2021. Results of 55 QUASIMEME intercalibrations are presented in Table S1 with a mean z-score of 0.09 and only 7% of unsatisfying results (z-score > = │2.5│).
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| 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 | 0,001 | 0,001 |
| 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 source (Gemma direct ou Codex distillé), 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 ».