Status assessment and probabilistic health risk modeling of metals accumulation in agriculture soils across China: A synthesis
Bibliographic record
Abstract
Heavy metal accumulation in agriculture soils is of particular concern in China, while the status and probabilistic health risks of metal contamination in Chinese agriculture soils have been rarely studied at the national scale. In this study, we compiled a database of heavy metal concentrations in Chinese agriculture soils and selected six heavy metals for pollution assessment and risk screening: arsenic (As), cadmium (Cd), chromium (Cr), nickel (Ni), lead (Pb) and Zinc (Zn). Monte Carlo simulation was employed to assess the probabilistic health risks, the associated uncertainties, as well as variations in toxicity parameters, ingestion rate and body weight. Results indicated that the concentrations of Cd were elevated above their reference standard and Cd had the highest mean geo-accumulation index ( I geo ) of 1.79. Moreover, the mean hazard index ( HI ) through exposure to six heavy metals was 1.85E−01 and 2.87E−02 for children and adults, respectively, with 2.2% of non-cancer risks for children that exceeded the guideline value of 1. In contrast, 95.0% and 90.0% of the total cancer risks ( TCR ) through exposure to six heavy metals for children and adults, respectively, exceeded the guideline value of 1E−06. Six metals were ranked based on their percent of risk outputs exceeding the guideline values. Arsenic had the high exceedance of both cancer and non-cancer risks, while both Cr and Cd were metals with high concern that had high exceedance of cancer risk. Sensitivity analyses indicated that metal concentrations and ingestion rate of soil were the predominant contributors to total risk variance. Overall, the adverse health risks induced by exposure to heavy metals contaminated farmland were elevated. Results from this study may provide valuable implications for public health professionals and policy-makers to design effective strategy to manage nation-wide farmland and reduce heavy metal exposure.
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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".