Evidence map›Paper›PMID 33503895›Full record

SynthesisInternational journal of environmental research and public health2021

Current Status and Temporal Trend of Potentially Toxic Elements Pollution in Agricultural Soil in the Yangtze River Delta Region: A Meta-Analysis.

Shufeng She, Bifeng Hu, Xianglin Zhang, Shuai Shao, Yefeng Jiang, Lianqing Zhou, Zhou Shi

Abstract readMeta-AnalysisReview
In one paragraph

Synthesis in International journal of environmental research and public health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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

7 authors.

Shufeng SheInstitute of Applied Remote Sensing and Information Technology, Zhejiang University, Hangzhou 310058, China.
Bifeng HuInstitute of Applied Remote Sensing and Information Technology, Zhejiang University, Hangzhou 310058, China.ORCID 0000-0001-9353-0307
Xianglin ZhangInstitute of Applied Remote Sensing and Information Technology, Zhejiang University, Hangzhou 310058, China.
Shuai ShaoInstitute of Applied Remote Sensing and Information Technology, Zhejiang University, Hangzhou 310058, China.
Yefeng JiangInstitute of Applied Remote Sensing and Information Technology, Zhejiang University, Hangzhou 310058, China.
Lianqing ZhouInstitute of Applied Remote Sensing and Information Technology, Zhejiang University, Hangzhou 310058, China.
Zhou ShiInstitute of Applied Remote Sensing and Information Technology, Zhejiang University, Hangzhou 310058, China.ORCID 0000-0003-3914-5402

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Potentially toxic elements (PTEs) pollution in the agricultural soil of China, especially in developed regions such as the Yangtze River Delta (YRD) in eastern China, has received increasing attention. However, there are few studies on the long-term assessment of soil pollution by PTEs over large regions. Therefore, in this study, a meta-analysis was conducted to evaluate the current state and temporal trend of PTEs pollution in the agricultural land of the Yangtze River Delta. Based on a review of 118 studies published between 1993 and 2020, the average concentrations of Cd, Hg, As, Pb, Cr, Cu, Zn, and Ni were found to be 0.25 mg kg

Indexed as

Metals, HeavySoil PollutantsChinaEnvironmental MonitoringEnvironmental PollutionRisk AssessmentSoilMetals, HeavySoilSoil Pollutantsagricultural soilmeta-analysispotentially toxic elementsspatial distributiontemporal trendYangtze River Delta

Identifiers

PMID33503895
PMCPMC7908581

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.