Environmental characterization and investigation of the presence of trace metals in the water column and sediment of the Rio Piranhas, Sao Bento, Paraíba
Bibliographic record
Abstract
Due to the intense activity in the textile business Piranhas River, which traverses the city of São Bento-PB is serving as the depletion for the waste generated in the steps of bleaching and dyeing of yarn, since the networks are made by artisans, many them in the backyards of residences. On this context, for this work, we collected water and sediment samples at three different points of the Piranhas, with the objective to evaluate a possible contamination of these compartments resulting from dumping of textile effluent. Were also determined the variables Dissolved Oxygen (DO), Total Dissolved Solids (TDS), OM (Organic Matter), Conductivity, pH and temperature. The results obtained for these parameters are consistent with those expected for the location of the environment under study, where the rainfall is marked by extreme irregularity. An analysis screening using the voltammetry technique was used to indicate the presence of trace metals in water, this analysis showed the possible presence of metals, Zn, Pb and Cu. Concerning the sediment samples, the quantitative analysis performed using the technique of ICP-MS (Inductively Coupled Plasma-Mass Spectrometry) showed that among the investigated metals, Cd, Pb, Cu, Cr, Ni, Cr and Ni elements were those with higher levels during the study period. Using parameters of the sediment quality evaluators, it was observed that the metals Cr and Ni had values that exceeded the lower limit TEL (Canadian guideline value) thus indicating a deleterious made occasional on aquatic biota of the environment under study. Principal components analysis (PCA) using variables such as the physical-chemical parameters and concentrations of metals investigated, highlighted the influence of parameters and STD Conductivity, pH and organic matter in the grouping of data and also showed that the differences in metal contents between months in the study (rainy and dry) were more relevant than the differences between the sampling sites investigated. From the results and taking into account the variables measured along the river, it was found that there is no evidence that the textile wastewater at the moment, is affecting the characteristics of the Piranhas.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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".