Evidence map›Paper›PMID 39602348›Full record

ArticleEnvironmental science & technology2024

Form-Specific Prospective Environmental Risk Assessment of Graphene-Based Materials in European Freshwater.

Hyunjoo Hong, Bernd Nowack

Abstract read
In one paragraph

Article in Environmental science & technology, 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

2 authors.

Hyunjoo HongEmpa, Swiss Federal Laboratories for Materials Science and Technologies, Technology and Society Laboratory, Lerchenfeldstrasse 5, St. Gallen 9014, Switzerland.
Bernd NowackEmpa, Swiss Federal Laboratories for Materials Science and Technologies, Technology and Society Laboratory, Lerchenfeldstrasse 5, St. Gallen 9014, Switzerland.ORCID 0000-0002-5676-112X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

As graphene-based materials (GBMs) such as pristine graphene, graphene oxide, and reduced graphene oxide show great potential to be integrated in various applications, the need for environmental risk assessments grows, aiming to navigate the environmental fate and potential risk of the different forms of GBM. This study used dynamic probabilistic material flow analysis (DPMFA) to ascertain the prospective production volumes and distribution of GBMs within European freshwaters. The hazard assessment leveraged 113 data sets from peer-reviewed studies, addressing aquatic ecotoxicity across 26 species, by performing probabilistic species sensitivity distributions (SSD). Our findings reveal distinct environmental distribution patterns for GBM forms with predicted environmental concentrations in European freshwaters by 2030 of approximately 0.67 ng/L (SD = 0.24 ng/L) for pristine graphene and 0.33 ng/L (SD = 0.10 ng/L) for both graphene oxide and reduced graphene oxide, suggesting not only similar but notably minimal exposure levels. The risk characterization ratios (RCRs) for all forms of GBM were significantly below 1, indicating a negligible environmental risk within the scenarios assessed. Through detailed analysis considering the forms of the material, this research can inform regulatory decisions, support sustainable material design, and provide a solid foundation for a further investigation considering the environmental fate of GBM.

Indexed as

Fresh WaterGraphiteEuropeRisk AssessmentWater Pollutants, ChemicalGraphiteWater Pollutants, Chemicalenvironmental risk assessmentgraphene based materialMFAPECPNECSSD

Identifiers

PMID39602348
PMCPMC11636196

What OpenQuestion holds

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Registered trials

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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.