Comprehensive review of the environmental impacts of mining and smelting at the Baiyinchang Cu–Zn–Pb ore deposit, Gansu Province, China, with new inputs from the sulfide compositions
Bibliographic record
Abstract
This review paper presents an in-depth synthesis of the environmental aspects associated with the mining of the Baiyinchang Cu–Zn–Pb deposit in China. The review covers contamination by atmospheric deposition and sewage irrigation, soil contamination, and ecosystem health to evaluate current environmental conditions, identify potential impacts, and suggest sustainable mitigation measures for the Baiyin district. With a focus on soil, river water, and crop pollution levels, our review indicates that several heavy metals (HMs), particularly Cd, have been gradually accumulated in soils and streams due to the natural occurrence of the deposits close to the surface and mining–smelting activities, and pose a serious environmental threat. Detailed studies on sulfide minerals have found that although Cd is mainly hosted in sphalerite, all common sulfide minerals (galena, chalcopyrite, pyrite) also contain Cd. There were significant spatial variations in HM speciation; upstream areas near ore deposits exhibited lower pH and higher Zn concentrations, due to acidic mine drainage and the presence of sphalerite. As the stream flows through the Baiyin district, the increasing influence from domestic wastewater led to a rise in pH, impacting HMs mobility. Mining–smelting activities were identified as the primary source of HM pollution. Crops grown near the ore district and irrigated with contaminated water were most susceptible to contamination due to combined soil and atmospheric HM uptake. Our review highlights the importance of stricter pollution control measures, cleaner irrigation sources, and careful crop selection to safeguard food safety and ecosystem health.
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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".