Evidence map›Paper›PMID 28845451›Full record

ArticleScience advances2017

Extensive arsenic contamination in high-pH unconfined aquifers in the Indus Valley.

Joel E Podgorski, Syed Ali Musstjab Akber Shah Eqani, Tasawar Khanam, Rizwan Ullah, Heqing Shen, Michael Berg

Abstract read
In one paragraph

Article in Science advances, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.

0numbers the graph read from it
0cells of the map it votes in
31citing 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

31 citing papers in PubMed.

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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

6 authors.

Joel E PodgorskiEawag, Swiss Federal Institute of Aquatic Science and Technology, Department Water Resources and Drinking Water, 8600 Dübendorf, Switzerland.ORCID 0000-0003-2522-1021
Syed Ali Musstjab Akber Shah EqaniPublic Health and Environment Division, Department of Biosciences, COMSATS Institute of Information Technology, Islamabad, Pakistan.
Tasawar KhanamPublic Health and Environment Division, Department of Biosciences, COMSATS Institute of Information Technology, Islamabad, Pakistan.
Rizwan UllahDepartment of Zoology, Mirpur University of Science and Technology, Azad Jammu and Kashmir, Pakistan.
Heqing ShenCAS Key Laboratory of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen, China.
Michael BergEawag, Swiss Federal Institute of Aquatic Science and Technology, Department Water Resources and Drinking Water, 8600 Dübendorf, Switzerland.ORCID 0000-0002-7342-4061

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Arsenic-contaminated aquifers are currently estimated to affect ~150 million people around the world. However, the full extent of the problem remains elusive. This is also the case in Pakistan, where previous studies focused on isolated areas. Using a new data set of nearly 1200 groundwater quality samples throughout Pakistan, we have created state-of-the-art hazard and risk maps of arsenic-contaminated groundwater for thresholds of 10 and 50 μg/liter. Logistic regression analysis was used with 1000 iterations, where surface slope, geology, and soil parameters were major predictor variables. The hazard model indicates that much of the Indus Plain is likely to have elevated arsenic concentrations, although the rest of the country is mostly safe. Unlike other arsenic-contaminated areas of Asia, the arsenic release process in the arid Indus Plain appears to be dominated by elevated-pH dissolution, resulting from alkaline topsoil and extensive irrigation of unconfined aquifers, although pockets of reductive dissolution are also present. We estimate that approximately 50 million to 60 million people use groundwater within the area at risk, with hot spots around Lahore and Hyderabad. This number is alarmingly high and demonstrates the urgent need for verification and testing of all drinking water wells in the Indus Plain, followed by appropriate mitigation measures.

Identifiers

PMID28845451
PMCPMC5567761

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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.