Evidence map›Paper›PMID 24920264›Full record

ArticleEnvironmental science and pollution research international2014

Effect of water current on the distribution of polycyclic aromatic hydrocarbons, heavy metals and benthic diatom community in sediments of Haihe estuary, China.

Jinxia Yan, Jingling Liu, Yi Li, Sisi Lang

Abstract read
PubMed Publisher
In one paragraph

Article in Environmental science and pollution research international, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.3field-weighted citation impact, top 21% 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

6 citing papers in PubMed, 11 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Sediment heavy metals and benthic diversities in Hun-Tai River, northeast of China.Environmental science and pollution research international · 2017
    Article
  5. Article
  6. 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

4 authors at 2 institutions in 1 country.

Jinxia YanState Key Joint Laboratory of Environmental Simulation and Pollution Control and School of Environment, Beijing Normal University, 100875, Beijing, China.
Jingling Liu
Yi Li
Sisi Lang
Beijing Normal University · CNState Key Joint Laboratory of Environment Simulation and Pollution Control · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The pollution loads continuously increased in Haihe estuary, of Tianjin, China, due to intensive human activities, especially the construction of the Haihe Gate and Lingang Industrial Area. In 2011, hydrological variability in Haihe estuary was investigated and sediments were collected. Total organic carbon (TOC), particle size, total polycyclic aromatic hydrocarbons (ΣPAHs), heavy metals (Cd, Cr, Cu, Ni, Pb, and Zn), and benthic diatom community were analyzed. The highest concentrations of ΣPAHs and heavy metals were found near the Haihe Gate. The Shannon diversity index and the relative abundance of Coscinodiscus perforatus (RC) indicated a decreasing trend seaward. Results of Pearson correlation analysis illustrated significant relations between water current velocity and ΣPAHs (p < 0.01), Cr (p < 0.05), and RC (p < 0.05). Path analysis further indicated that water current played an important role in the distribution of PAH, Cr, and RC.

Indexed as

EstuariesWater MovementsChinaDiatomsEcosystemEnvironmental MonitoringGeographyGeologic SedimentsMetals, HeavyPolycyclic Aromatic HydrocarbonsPrincipal Component AnalysisWaterWater Pollutants, ChemicalMetals, HeavyPolycyclic Aromatic HydrocarbonsWaterWater Pollutants, Chemical

Identifiers

PMID24920264
OpenAlexW2084131646

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.