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Record W3043610513

Avaliação espacial de metais pseudo-totais e disponíveis em sedimento de fundo do Rio Alegria – PR

2018· dissertation· pt· W3043610513 on OpenAlexaboutno aff
Jonikey Neri Roos

Bibliographic record

VenueInstitutional Repository of the Federal Technological University of Paraná (RIUT) (Federal University of Technology – Paraná) · 2018
Typedissertation
Languagept
FieldEnvironmental Science
TopicWater Quality and Pollution Assessment
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPhysicsHeavy metalsArtEnvironmental chemistryChemistry
DOInot available

Abstract

fetched live from OpenAlex

Sediments are fundamental components in the water course. In addition to serving as a source of nutrients for various aquatic organisms, they are also present as reservoirs of environmental contaminants, such as metals. The present work evaluated spatially the concentration of pseudo-total and environmentally available metals in the bottom sediment of the Alegria River, which is located in the municipality of Medianeira, Paraná. Two sampling campaigns were carried out at four different points along the river, during the winter and spring periods corresponding to the year 2017. A Petersen dredger was used to collect sediment from the river bottom and was characterized by physico- (Al), chromium (Cr), copper (Cu), zinc (Zn) and potassium (K) were determined by the following parameters: pH, total organic carbon, organic matter, total phosphorus and aluminum in the available and pseudo-total plots, using the technique called Atomic Absorption Spectroscopy (FAAS). Subsequently, the contents of the metals were determined and the results obtained in the analyzes were compared with the guiding values stipulated in the US National Oceanic and Atmospheric Administration (NOAA) Sediment Quality Guide (SQG), as well as the concentrations limits established by CONAMA Resolution No. 454 of 2012, a standard based on the Canadian Sediment Quality Guide. As for the characterization of the collection points, point 1 was located in a rural area, near the source of the sanga Magnolia (affluent of the Alegria river), with agricultural and agricultural activities. Point 2 was located downstream of point 1, at the water catchment dam for public water supply in the municipality. Point 3 was located in the region where the Alegria river leaves the urban area, passing through precarious houses where several point sources of pollution have been identified. Point 4 was delimited near the mouth of the river Alegria near the Ocoí River, in the São Bernardo community in the rural area, predominantly agricultural area. From the results, it was found that Al was the metal found in the highest proportions in the pseudo-total plot in the bottom sediment of the Alegria river, due to the fact that this element is one of the main metals found in rocky material and consequently, in soils and sediments, due to erosion caused by abiotic factors such as wind and precipitation. All concentrations related to the pseudo-total plot of Al were above the highest limit, which is found in the ARCS guide. The metals Al and Cr, in their available plots, did not exceed their respective minimum background values of NOAA. As for Zn, only in P3, during the spring, a value above which no toxic effect was known was known (Level 1/TEL). Cu was the only metal in which the available portion resulted in thresholds that overlapped Level 1/TEL. Correlating only the organic matter, the total organic carbon and the pH values of this study, it can be inferred that the points P2 and P3 contain conditions more favorable to the retention of the metals and other contaminants in the background sediment phase, causing such components do not harm aquatic biota or even water quality and do not endanger human health.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.203
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0040.010
Scholarly communication0.0000.001
Open science0.0040.001
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.015
GPT teacher head0.236
Teacher spread0.221 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2018
Admission routes1
Has abstractyes

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