QSPR models for predicting the adsorption capacity for microplastics of polyethylene, polypropylene and polystyrene.


Journal

Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288

Informations de publication

Date de publication:
03 09 2020
Historique:
received: 28 03 2020
accepted: 10 08 2020
entrez: 5 9 2020
pubmed: 5 9 2020
medline: 5 9 2020
Statut: epublish

Résumé

Microplastics have become an emerging concerned global environmental pollution problem. Their strong adsorption towards the coexisting organic pollutants can cause additional environmental risks. Therefore, the adsorption capacity and mechanisms are necessary information for the comprehensive environmental assessments of both microplastics and organic pollutants. To overcome the lack of adsorption information, five quantitative structure-property relationship (QSPR) models were developed for predicting the microplastic/water partition coefficients (log K

Identifiants

pubmed: 32883986
doi: 10.1038/s41598-020-71390-3
pii: 10.1038/s41598-020-71390-3
pmc: PMC7473759
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

14597

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Auteurs

Miao Li (M)

College of Geography and Environmental Sciences, Zhejiang Normal University, Yingbin Avenue 688, Jinhua, 321004, China.

Haiying Yu (H)

College of Geography and Environmental Sciences, Zhejiang Normal University, Yingbin Avenue 688, Jinhua, 321004, China.

Yifei Wang (Y)

College of Geography and Environmental Sciences, Zhejiang Normal University, Yingbin Avenue 688, Jinhua, 321004, China.

Jiagen Li (J)

College of Geography and Environmental Sciences, Zhejiang Normal University, Yingbin Avenue 688, Jinhua, 321004, China.

Guangcai Ma (G)

College of Geography and Environmental Sciences, Zhejiang Normal University, Yingbin Avenue 688, Jinhua, 321004, China.

Xiaoxuan Wei (X)

College of Geography and Environmental Sciences, Zhejiang Normal University, Yingbin Avenue 688, Jinhua, 321004, China. xxwei@zjnu.edu.cn.

Classifications MeSH