Evidence map›Paper›PMID 34402015›Full record

ArticleEnvironmental science and pollution research international2022

Concentration and speciation of mercury in atmospheric particulates in the Wuda coal fire area, Inner Mongolia, China.

Yahui Qian, Yanci Liang, Qingyi Cao, Zhe Wang, Yunyun Shi, Handong Liang

Abstract read
PubMed Publisher
In one paragraph

Article in Environmental science and pollution research international, 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
0.3field-weighted citation impact, top 43% of its field
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, 3 citations in OpenAlex.

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 at 2 institutions in 1 country.

Yahui QianState Key Laboratory of Coal Resources and Safe Mining, China University of Mining and Technology, Beijing, 100083, China.
Yanci LiangCenter for Imaging and Systems Biology, Minzu University of China, Beijing, 100081, China.
Qingyi CaoCollege of Geoscience and Surveying Engineering, China University of Mining and Technology (Beijing), Beijing, 100083, China.
Zhe WangCollege of Geoscience and Surveying Engineering, China University of Mining and Technology (Beijing), Beijing, 100083, China.
Yunyun ShiCollege of Geoscience and Surveying Engineering, China University of Mining and Technology (Beijing), Beijing, 100083, China.
Handong LiangState Key Laboratory of Coal Resources and Safe Mining, China University of Mining and Technology, Beijing, 100083, China. hdl6688@cumtb.edu.cn.
China University of Mining and Technology · CNMinzu University of China · CN

Funding

National Natural Science Foundation of China 41371449State Key Laboratory of Coal Resources and Safe Mining SKLCRSM19ZZ03
6 · The paper itself

Abstract

Coal-seam fire is a source of atmospheric mercury that is difficult to control. The Wuda Coalfield in Inner Mongolia, China, is one of the most severe coal fire disaster areas worldwide and has been burning for more than 50 years. To investigate atmospheric mercury pollution from the Wuda coal fire, gaseous elemental mercury (GEM) concentrations and atmospheric particulate mercury (PHg) speciation were measured using a RA-915+ mercury analyzer and the temperature-programmed desorption method. Near-surface GEM concentrations in the Wuda Coalfield and adjacent urban area were 80 ng m

Indexed as

Air PollutantsFiresMercuryChinaCoalEnvironmental MonitoringAir PollutantsCoalMercuryAtmospheric mercuryAtmospheric particulate matterCoal fireMercuryParticulate mercury speciationWuda

Identifiers

PMID34402015
OpenAlexW3176659023

What OpenQuestion holds

Textmetadata
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.