Evidence map›Paper›PMID 22260208›Full record

ArticleEnvironmental science & technology2012

Can arsenic occurrence rates in bedrock aquifers be predicted?

Qiang Yang, Hun Bok Jung, Robert G Marvinney, Charles W Culbertson, Yan Zheng

Abstract read
In one paragraph

Article in Environmental science & technology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

16 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Evaluating Geologic Sources of Arsenic in Well Water in Virginia (USA).International journal of environmental research and public health · 2018
    Article
  6. Article
  7. Review
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. A cross-sectional study of well water arsenic and child IQ in Maine schoolchildren.Environmental health : a global access science source · 2014
    Article
  16. Survey ofAWWA water science
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Qiang YangQueens College and Graduate Center, City University of New York, 6530 Kissena Blvd., Flushing, New York 11367, United States.
Hun Bok Jung
Robert G Marvinney
Charles W Culbertson
Yan Zheng

Funding

Training CoreP42ES010349 · NIEHS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI NAVAS-ACIEN, ANA · 2000 to 2020
$53.6M
NIEHS NIH HHS 2 P42 ES10349NIEHS NIH HHS P42 ES010349
6 · The paper itself

Abstract

A high percentage (31%) of groundwater samples from bedrock aquifers in the greater Augusta area, Maine was found to contain greater than 10 μg L(-1) of arsenic. Elevated arsenic concentrations are associated with bedrock geology, and more frequently observed in samples with high pH, low dissolved oxygen, and low nitrate. These associations were quantitatively compared by statistical analysis. Stepwise logistic regression models using bedrock geology and/or water chemistry parameters are developed and tested with external data sets to explore the feasibility of predicting groundwater arsenic occurrence rates (the percentages of arsenic concentrations higher than 10 μg L(-1)) in bedrock aquifers. Despite the under-prediction of high arsenic occurrence rates, models including groundwater geochemistry parameters predict arsenic occurrence rates better than those with bedrock geology only. Such simple models with very few parameters can be applied to obtain a preliminary arsenic risk assessment in bedrock aquifers at local to intermediate scales at other localities with similar geology.

Indexed as

Logistic ModelsArsenicEnvironmental MonitoringForecastingGroundwaterHydrogen-Ion ConcentrationMaineNitratesOxygenSulfatesWater Pollutants, ChemicalArsenicNitratesOxygenSulfatesWater Pollutants, Chemical

Identifiers

PMID22260208
PMCPMC3307801

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.