Sources, Spatial Distribution and Extent of Heavy Metals in Relation to Land Use, Lithology and Landform in Fuzhou City, China
Bibliographic record
Abstract
Assessing the spatial distribution of soil heavy metals in urban areas in relation to land use, lithology and landform may provide insights for soil quality monitoring. This study evaluated the spatial distribution, the sources and the extent of heavy metal(loid)s in the topsoil of Fuzhou city, China. A combination of GIS and multivariate approaches was used to determine the spatial distribution and the sources of heavy metals. Additionally, analysis of variance was used to determine the variability of selected heavy metals across land use, landform, and lithology. The result show that the mean concentrations of Cd, Zn, As and Pb were higher than background values. Most of the heavy metals had significant correlations with each other. In particular, V and Fe (0.84 at p < 0.01) and Ni and Cr (0.74 at p < 0.01) had strong correlations, while Cu and Fe (0.68 at p < 0.01), Cu and V (0.63 at p < 0.01), Cu and Co (0.52 at p < 0.01), Zn and Ni (0.51 at p < 0.01), Co and Fe (0.54 at p < 0.01), and Cu and Zn (0.55 at p < 0.01) had moderate correlations. Arsenic, Cu, and Zn had significant positive correlations with total nitrogen (TN). Similarly, arsenic, Zn and Cr had positive correlations with total carbon (TC), while Co had negative correlations with TN and TC at p < 0.01. The peak values for Cr, Ni, Pb, Mn, and Zn were observed in the intensively urbanized central and eastern parts of the study area, suggesting that the main sources might be anthropogenic activities. Agricultural land use had the highest content of Cd, which may be attributed to the historical long-term application of agrochemicals in the area. Additionally, its content was significantly higher in agricultural land use with shale lithology, implying that shale lithology was a key geogenic source for Cd of soils in the study area. Pb content was affected by urban land use, which may be attributed to intensive human activities such as emissions from vehicles, industrial effluents, mining activities, and other discharges. The results show the high spatial variability of heavy metal(loid)s, implying that the soils in the study area were highly influenced by both geogenic variability and human activities. Moreover, land use and lithology had significant impacts on the variability of Cd, As and Pb. Sustainable agricultural practices and urban management are recommended to sustain the eco-environment of coastal city.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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 teacher head, 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".