Evidence map›Paper›PMID 35444191›Full record

ArticleScientific reports2022

An innovative method for soil vapor extraction to improve extraction and tail gas treatment efficiency.

Yang Ding, Yuling Zhang, Zhiqun Deng, Hewei Song, Jili Wang, Haizhao Guo

Abstract read
In one paragraph

Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Yang DingKey Lab of Groundwater Resources and Environment, Ministry of Education, Jilin University, Changchun, 130021, China.
Yuling ZhangKey Lab of Groundwater Resources and Environment, Ministry of Education, Jilin University, Changchun, 130021, China. lingling29@126.com.
Zhiqun DengKey Lab of Groundwater Resources and Environment, Ministry of Education, Jilin University, Changchun, 130021, China.
Hewei SongKey Lab of Groundwater Resources and Environment, Ministry of Education, Jilin University, Changchun, 130021, China.
Jili WangKey Lab of Groundwater Resources and Environment, Ministry of Education, Jilin University, Changchun, 130021, China.
Haizhao GuoAcademic Affairs Office of Jilin University, Changchun, 130021, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study aims to improve soil vapor extraction (SVE) to address its shortcomings in treating halogenated hydrocarbon-contaminated soil. Indoor simulation experiments based on SVE were conducted to provide technical guidance for the remediation of 1,2-DCA-contaminated soil, with the overall intention of soil repair and ecological restoration. A thermal oxidation SVE (TOSVE) system was designed on the basis of SVE technology for application in the remediation of low-permeability soil contaminated with halogenated hydrocarbons from a chemical plant in Northeast China. Laboratory simulation experiments were conducted based on TOSVE technology to study the removal of target pollutants under different organic contents, moisture and air speeds. For the first time, a new material, scoria, was added to the oxidant at different proportions, and its effect on the exhaust gas treatment efficiency was examined. Thermal extraction improved the extraction efficiency of pollutants from low-permeability soil. Moreover, the adsorption-oxidation effect of 0.1-0.25 mm scoria prepared by 20% Na

Indexed as

Environmental PollutantsEnvironmental Restoration and RemediationSoil PollutantsGasesOxidantsSoilEnvironmental PollutantsGasesOxidantsSoilSoil Pollutants

Identifiers

PMID35444191
PMCPMC9021247

What OpenQuestion holds

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LicenceCC BY
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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.