ArticleEnvironmental science and pollution research international2021
Contaminated site-induced health risk using Monte Carlo simulation: evaluation from the brownfield in Beijing, China.
Article in Environmental science and pollution research international, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Pooled it
- Probabilistic human health risk assessment of trace metal exposure in Australian homes: insights from a legacy industrial region.Environmental geochemistry and health · 2026Article
- Source identification and risk assessment of potentially toxic elements in surface soil of townships in the northwest Hebei region.PloS one · 2026Article
- Brownfield-related studies in the context of climate change: A comprehensive review and future prospects.Heliyon · 2024Review
- Probabilistic health risk assessment of inorganic arsenic and some heavy metals in rice produced from a typical multi-mining county, China.Environmental science and pollution research international · 2022Article
- Trace Metal Lead Exposure in Typical Lip Cosmetics From Electronic Commercial Platform: Investigation, Health Risk Assessment and Blood Lead Level Analysis.Frontiers in public health · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
The occurrence of contaminated sites has caused serious public health problems, and there are significant health risks. This paper applies Monte Carlo simulations to evaluate the impact of pollutants on human health at a contaminated site in Beijing, China. In this study, a total of 429 soil samples were collected. The exposure routes considered were oral ingestion and skin contact. The log-normal distribution or triangular distribution was adopted to convert exposure parameters into statistical parameters, and the final risk probability was estimated through Monte Carlo simulations. The results show that the 95th percentile risk indexes of As, Ni, Zn, and Hg are 1.22E-1, 5.05E-3, 5.10E-4, and 1.69E-1, respectively, which are all within acceptable levels. The maximum values of As and Hg are 2.15E+0 and 1.04E+0, respectively, with a 5% and 4% probability, respectively, of exceeding the acceptable health risk level. In theory, it is believed that they do not pose a potential threat to human health. Nevertheless, As and Hg in soil are still major pollution sources. The results also show that C (pollutant concentration), AT (mean action time), and ED (exposure duration) are the three parameters with the highest sensitivity to the health risk value. The results of this study can help to improve soil risk control measures and remediation decisions for contaminated sites to reduce the environmental risk in contaminated areas.
Indexed as
Identifiers
33449319What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.