Evidence map›Paper›PMID 31960242›Full record

ArticleEnvironmental science and pollution research international2020

Characteristics and influencing factors of hydrochemistry and dissolved organic matter in typical karst water system.

Weiwei Lü, Xin Yao, Chuntian Su, Haoyu Ren, Min Yao, Baohua Zhang

Abstract read
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In one paragraph

Article in Environmental science and pollution research international, 2020. 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
2.1field-weighted citation impact, top 16% 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, 15 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.

Weiwei LüSchool of Environment and Planning, University of Liaocheng, Liaocheng, 252000, China.
Xin YaoSchool of Environment and Planning, University of Liaocheng, Liaocheng, 252000, China. yaoxin@lcu.edu.cn.
Chuntian SuInstitute of Karst Geology, Chinese Academy of Geological Sciences, Guilin, 541004, China. suchuntian@karst.ac.cn.
Haoyu RenSchool of Environment and Planning, University of Liaocheng, Liaocheng, 252000, China.
Min YaoSchool of Environment and Planning, University of Liaocheng, Liaocheng, 252000, China.
Baohua ZhangSchool of Environment and Planning, University of Liaocheng, Liaocheng, 252000, China.
Liaocheng University · CNChinese Academy of Geological Sciences · CN

Funding

China Geological Survey project DD20160303,DD20190342National Natural Science Foundation of China 41977322, 41901120, 41502332Natural Science Foundation of Shandong Province, China ZR2019BD052Open research Foundation of the State Key Laboratory of Lake Science and Environment, Chinese Academy of Sciences 2018SKL004
6 · The paper itself

Abstract

The unique hydrogeological conditions of karst area make the groundwater react rapidly to rainfall events, which makes the groundwater more susceptible to anthropogenic pollutions. The current study based on a combined excitation-emission matrix fluorescence spectroscopy and parallel factor analysis (EEM-PARAFAC) and geochemical-statistical investigation of water samples from the karst water system in Xintian County, Hunan Province, China, gives crucial information about the principal factors influencing karst water hydrochemistry and dissolved organic matter (DOM). The analyzed data revealed that both surface water and descending spring samples were within the Ca-Mg-HCO

Indexed as

GroundwaterWaterChinaSpectrometry, FluorescenceWater QualityWaterDissolved organic matter (DOM)HydrochemistryKarstPARAFACXintian County

Identifiers

PMID31960242
OpenAlexW2999044631

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.