Geochemistry and mineralogy of lacustrine and fluvio-lacustrine sediments: The case of the Pietra del Pertusillo fresh-water reservoir (Basilicata region, Southern Italy)
Bibliographic record
Abstract
The Pietra del Pertusillo fresh-water reservoir is located in the High Agri Valley (Basilicata region, Southern Italy). The present work represents a first comprehensive study about the mineralogy and the geochemistry of fluvial-lacustrine sediments and bedrock lithologies of this fresh-water reservoir catchment area. Lacustrine (15 samples), fluvial-lacustrine (14 samples) and local bedrock sediments (27 samples) have been sampled and mineralogical and geochemical analyses have been performed on the sampled sediments. The mineralogical assemblage is mainly composed of quartz and calcite and minor feldspars, muscovite, illite, chlorite, and interstratified clay minerals. The geochemistry reveals that major oxides are SiO2, Fe2O3, Al2O3, and CaO. Attention has been paid to the presence of potentially toxic chemical elements (heavy metals) within the sampled sediments. The heavy metals are mainly enriched in the fine fraction of lacustrine sediments since they are mostly absorbed in the clay fraction (<2 µm). Geochemistry of fluvial-lacustrine and bedrock sediments revealed that, in some cases, several heavy metal elements like Cr, Co, Ni, Zn, As, Ni and Pb exceed some regulatory limits concerning their distribution in lake sediments. It should be noted that, in Italian legislation, there are no regulations concerning limit concentrations of heavy metals in fluvial and fluvio-lacustrine sediments and therefore, for lacustrine sediments, values related to aquatic environments are taken into account. The considered regulatory are the Canadian ISQG (Interim Freshwater Sediments Quality Guidelines) and the Italian D.M. 367/03 (Regulation on the setting of quality standards in the aquatic environment for dangerous substances). Furthermore, enrichment factors (EFs) for heavy metals were calculated, assuming Ti as an immobile element, both with respect to UCC (Upper Continental Crust) and local bedrock composition. Local bedrock composition was calculated based on the average composition and weighted on the areal extension of the outcropping bedrock lithologies. Enrichment factors showed that heavy metals like Pb, Zn, and Co, in relation both on UCC and local bedrock, showed values of EFs >2, which corresponds to a moderate enrichment. Other heavy metals, in particular Cu and As, showed EFs >5, which corresponds to a significant enrichment. This work aims to get a clear picture of the causes which control and influence heavy metals concentration as well as their distribution within sampled sediments. Finally, it would be appropriate to establish worldwide quality standards on all pollutants in different natural environments in order to obtain a homogeneous reference for all countries. References: Giocoli, A. , Stabile, T. A., Adurno, I., Perrone, A., Gallipoli, M. R., Gueguen, E., Norelli, E., Piscitelli, S., 2015. Geological and geophysical characterization of the southeastern side of the High Agri Valley (southern Apennines, Italy), Nat. Hazards Earth Syst. Sci. 15, 315-323. McLennan, S.M., Taylor, S.R., Hemming, S.R., 2006. Compostion differentiation and evolution of continental crust: constraints from sedimentary rocks and heat flow. In: Brown, M Rushmere T (eds) Evolution and differentiation of continental crust. Cambridge p 377. Reimann, C., De Caritat, P., 2005. Distinguishing between natural and anthropogenic sources for elements in the environment: regional geochemical surveys versus enrichment factors, Science of the Total Environment 337(1-3), 91-107.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".