Evidence map›Paper›PMID 29270684›Full record

ArticleEnvironmental monitoring and assessment2017

Effects of coal spoil amendment on heavy metal accumulation and physiological aspects of ryegrass (Lolium perenne L.) growing in copper mine tailings.

Zhaoxia Chu, Xingming Wang, Yunmin Wang, Guijian Liu, Zhongbing Dong, Xianwen Lu, Guangzhou Chen, Fugeng Zha

Abstract read
PubMed Publisher
In one paragraph

Article in Environmental monitoring and assessment, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.5field-weighted citation impact, top 35% 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

1 citing paper in PubMed, 12 citations in OpenAlex.

  1. 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

8 authors at 5 institutions in 2 countries.

Zhaoxia ChuSchool of Earth and Environment, Anhui University of Science and Technology, Huainan, 232001, China.
Xingming WangSchool of Earth and Environment, Anhui University of Science and Technology, Huainan, 232001, China. xmwang-2004@126.com.
Yunmin WangSinosteel Maanshan Institute of Mining Research Company Limited, Maanshan, 243000, China.
Guijian LiuSchool of Earth and Space Sciences, University of Science and Technology of China, Hefei, 230026, China.
Zhongbing DongSchool of Earth and Environment, Anhui University of Science and Technology, Huainan, 232001, China. dongzb@huainan.gov.cn.
Xianwen LuSchool of Bioengineering, Huainan Normal University, Huainan, 232038, China.
Guangzhou ChenSchool of Environment and Energy Engineering, Anhui Jianzhu University, Hefei, 230022, China.
Fugeng ZhaSchool of Earth and Environment, Anhui University of Science and Technology, Huainan, 232001, China.
Anhui University of Science and Technology · CNUniversity of Science and Technology of China · CNAnhui Jianzhu University · CNHuainan Normal University · CNMasteel (China) · CN

Funding

Anhui Postdoctoral Science Foundation 2017B147Anhui University Natural Science Research Project KJ2016A827; KJ2016A191; KJ2017A463China Postdoctoral Science Foundation 2016M602010National Key Research and Development Program of China 2016YFC0201605National Natural Science Foundation of China No. 41471422; No. E080404; No. 51608006Natural Science Foundation of Anhui Province (CN) 1608085QE125; 1508085MD67Postdoctoral Scientific Research Project sponsored by Sinosteel Maanshan Institute of Mining Research Company Limited 05417YF001Scientific Research Project from Huainan Normal University 2017xj89; 2016xj04zd
6 · The paper itself

Abstract

Copper mine tailings pose many threats to the surrounding environment and human health, and thus, their remediation is fundamental. Coal spoil is the waste by-product of coal mining and characterized by low levels of metals, high content of organic matter, and many essential microelements. This study was designed to evaluate the role of coal spoil on heavy uptake and physiological responses of Lolium perenne L. grown in copper mine tailings amended with coal spoil at rates of 0, 0.5, 1, 5, 10, and 20%. The results showed that applying coal spoil to copper mine tailings decreased the diethylenetriaminepentaacetic acid (DTPA)-extractable Cd, Cu, Pb, and Zn contents in tailings and reduced those metal contents in both roots and shoots of the plant. However, application of coal spoil increased the DTPA-extractable Cr concentration in tailings and also increased Cr uptake and accumulation by Lolium perenne L. The statistical analysis of physiological parameters indicated that chlorophyll and carotenoid increased at the lower amendments of coal spoil followed by a decrease compared to their respective controls. Protein content was enhanced at all the coal spoil amendments. When treated with coal spoil, the activities of superoxide dismutases (SOD), peroxidase (POD), and catalase (CAT) responded differently. CAT activity was inhibited, but POD activity was increased with increasing amendment ratio of coal spoil. SOD activity increased up to 1% coal spoil followed by a decrease. Overall, the addition of coal spoil decreased the oxidative stress in Lolium perenne L., reflected by the reduction in malondialdehyde (MDA) contents in the plant. It is concluded that coal spoil has the potential to stabilize most metals studied in copper mine tailings and ameliorate the harmful effects in Lolium perenne L. through changing the physiological attributes of the plant grown in copper mine tailings.

Indexed as

CoalMiningCoal MiningCopperLoliumMetals, HeavyModels, TheoreticalOxidative StressWaste ProductsCoalCopperMetals, HeavyWaste ProductsAntioxidant enzymeCoal spoilCopper mine tailingsLolium perenne L.Plant growth

Identifiers

PMID29270684
OpenAlexW2780840629

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.