Evidence map›Paper›PMID 39771082›Full record

ReviewToxics2024

Challenges of E-Waste Dismantling in China.

Bitong Li, Dongling Liu, Lina Zhang, Yue Wu, Xianlin Ding, Xiang Zeng

Abstract readReview
In one paragraph

Review in Toxics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

6 authors.

Bitong LiSchool of Public Health, Zhejiang Chinese Medical University, 548 Binwen Road, Hangzhou 310053, China.
Dongling LiuSchool of Basic Medical Science, Zhejiang Chinese Medical University, 548 Binwen Road, Hangzhou 310053, China.
Lina ZhangSchool of Public Health, Zhejiang Chinese Medical University, 548 Binwen Road, Hangzhou 310053, China.ORCID 0000-0002-9686-8298
Yue WuSchool of Public Health, Zhejiang Chinese Medical University, 548 Binwen Road, Hangzhou 310053, China.
Xianlin DingLuqiao District Center for Disease Control and Prevention, 208 Lingshan Road, Taizhou 318050, China.
Xiang ZengSchool of Public Health, Zhejiang Chinese Medical University, 548 Binwen Road, Hangzhou 310053, China.ORCID 0000-0001-8252-3558

Funding

the Research Project of Zhejiang Chinese Medical University 2024JKZKTS21; 701200E003
6 · The paper itself

Abstract

Electronic and electrical products have deeply permeated all aspects of life, bringing a lot of convenience to individuals. However, the generation of e-waste after their end-of-life has resulted in serious risks both to the ecological environment and human health due to a lack of scientific and effective recycling and treatments. As two major types of components in e-waste, heavy metals and plastics can not only directly enter the human body via inhalation, ingestion, and skin absorption, but also accumulate in the human body indirectly through the food chain. E-waste is full of resources such as valuable metals like gold, silver, and copper that are often discarded incorrectly. Environmental and health risks derived from unregulated e-waste dismantling activities may be finally addressed through the application of advanced e-waste recycling technology, policy support of governments, legislation on recycling laws and regulations, and the improvement of public environmental protection awareness. This review gives a brief overview of the history, current situation, and future development of e-waste in China, which may provide novel thinking and approaches to e-waste management in the world.

Indexed as

Chinacircular parksdismantlinge-wasteinternet plusrecycling

Identifiers

PMID39771082
PMCPMC11679424

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.