Lower Douro River basin (Portugal) water quality – Focus on trace element changes and anthropogenic sources of contamination
Bibliographic record
Abstract
The Douro River lower basin water quality was studied regarding its concentration on 18 trace elements (Be, Al, Cr, Mn, Co, Ni, Cu, Zn, As, Se, Mo, Ag, Cd, Sb, Ba, Tl, Pb and U, measured by ICP-MS). Other physicochemical parameters, such as pH, conductivity, dissolved oxygen and water temperature were also determined in situ. To take into account the expected spatio-temporal changes and to look for anthropogenic influences on trace element levels, samples (n=88) were collected at 11 sampling sites in four sampling campaigns (October 2007; January, March and July 2008), in both low and high tides, in order to evaluate spatial, seasonal and tidal changes. A multivariate approach – principal component analysis – was used to investigate interelement correlations and the variability observed in the different data sets. According to aquatic life limits (CCME, 2011), the quality of Douro River water was found acceptable. Except for DO, where a significant number of samples presented levels below 5.0 mg l-1, Cr(VI) (mean±sd = 3.09±1.54; median = 2.82 ppb) and Se (10.9±10.1; 7.74 ppb) all the other parameters measured fell well within acceptable limits. Occasional high levels were found for most trace elements, reflecting sporadic and local inputs. Important spatial differences in trace element levels were also found. Except for Be, Al and Mn, most metals tended to increase in the downstream direction. Some trace elements related with agriculture practices (Zn, Cu and Ni) were higher in samples collected on sampling sites located at the middle part of the studied area and were highly correlated, reflecting an eventual common source. Important seasonal differences in trace element levels were also observed, e.g., October samples were generally characterized by higher Ni, Cu, Zn and Pb levels.
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 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 | 0.000 | 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) | 0.002 | 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".