Transport of layered and spherical microplastics in aqueous ecosystems: a review DOI

Kheerthana Ramesh,

Padmanaban Velayudhaperumal Chellam,

Baranidharan Sundaram

et al.

Environmental Chemistry Letters, Journal Year: 2024, Volume and Issue: 22(3), P. 1221 - 1255

Published: March 26, 2024

Language: Английский

Possibility Routes for Textile Recycling Technology DOI Open Access
Damayanti Damayanti, Latasya Adelia Wulandari, Adhanto Bagaskoro

et al.

Polymers, Journal Year: 2021, Volume and Issue: 13(21), P. 3834 - 3834

Published: Nov. 6, 2021

The fashion industry contributes to a significant environmental issue due the increasing production and needs of industry. proactive efforts toward developing more sustainable process via textile recycling has become preferable solution. This urgent important need develop cheap efficient methods for waste led research community’s development various methods. can be categorized into chemical mechanical paper provides an overview state art regarding different types technologies along with their current challenges limitations. critical parameters determining performance are summarized discussed focus on in (pyrolysis, enzymatic hydrolysis, hydrothermal, ammonolysis, glycolysis). Textile been demonstrated re-spun yarn (re-woven or knitted) by spinning carded mixed shoddy through recycling. On other hand, it is difficult recycle some textiles means hydrolysis; high product yield shown under mild temperatures. Furthermore, emergence existing technology such as internet things (IoT) being implemented enable sorting identification also discussed. Moreover, we provide outlook upcoming technological developments that will contribute facilitating circular economy, allowing process.

Language: Английский

Citations

124

Surface-enhanced Raman spectroscopy for the detection of microplastics DOI Creative Commons
Lara Mikac, István Rigó,

L. Himics

et al.

Applied Surface Science, Journal Year: 2022, Volume and Issue: 608, P. 155239 - 155239

Published: Oct. 12, 2022

Detection of microplastics is still challenging due to limitations current methods, instrumentation, and particle size. In this work, surface-enhanced Raman spectroscopy (SERS) was used detect polystyrene (PS, 350 nm) polyethylene (PE, 1–4 µm) particles in pure water. Gold nanoparticles (Au NPs) four different sizes were synthesized, characterized, as SERS active substrate for microplastic detection. The Au NPs obtained had a spherical shape with diameters 33.2, 67.5, 93.7 nm an elliptical shorter longer (nanorods) 23.5 35.5 nm, respectively. optimal conditions (volume ratio sample gold colloid, aggregating agent its concentration) determined. efficient stable signals observed on the PS microparticles, while PE signal difficult obtain. developed method allows detection microparticles at concentrations low 6.5 μg mL−1. described can be useful tool pollutants particular

Language: Английский

Citations

78

Standardization of micro-FTIR methods and applicability for the detection and identification of microplastics in environmental matrices DOI

Chayanika Rathore,

Mahua Saha,

Priyansha Gupta

et al.

The Science of The Total Environment, Journal Year: 2023, Volume and Issue: 888, P. 164157 - 164157

Published: May 16, 2023

Language: Английский

Citations

57

A comprehensive assessment of macro and microplastics from Rivers Ganga and Yamuna: Unveiling the seasonal, spatial and risk factors DOI
Priyansha Gupta,

Mahua Saha,

Akshata Naik

et al.

Journal of Hazardous Materials, Journal Year: 2024, Volume and Issue: 469, P. 133926 - 133926

Published: March 1, 2024

Language: Английский

Citations

17

The development and application of advanced analytical methods in microplastics contamination detection: A critical review DOI
Yongkai Ye,

Keqiang Yu,

Zhao Yanru

et al.

The Science of The Total Environment, Journal Year: 2021, Volume and Issue: 818, P. 151851 - 151851

Published: Nov. 22, 2021

Language: Английский

Citations

87

Methods of Analyzing Microsized Plastics in the Environment DOI Creative Commons

Hyunjeong Woo,

Kang-Min Seo,

Yonghyun Choi

et al.

Applied Sciences, Journal Year: 2021, Volume and Issue: 11(22), P. 10640 - 10640

Published: Nov. 11, 2021

Microplastics are found in various environments with the increasing use of plastics worldwide. Several methods have been developed for sampling, extraction, purification, identification, and quantification microplastics complex environmental matrices. This study intends to summarize recent research trends on subject. Large microplastic particles can be sorted manually identified through chemical analysis; however, sample preparation small analysis is usually more difficult. by evaluating physical properties plastic separated extraction washing steps from a mixture inorganic organic particles. identification has high risk producing false-positive false-negative results microplastics. Currently, combination (e.g., microscopy), spectroscopy), thermal analyses widely used. We aim best strategies comparing strengths limitations each method.

Language: Английский

Citations

58

Unravelling the emerging threats of microplastics to agroecosystems DOI
Shweta Yadav,

Ekta Gupta,

Anju Patel

et al.

Reviews in Environmental Science and Bio/Technology, Journal Year: 2022, Volume and Issue: 21(3), P. 771 - 798

Published: May 26, 2022

Language: Английский

Citations

54

An insight on sampling, identification, quantification and characteristics of microplastics in solid wastes DOI
Palas Samanta,

Sukhendu Dey,

Debajyoti Kundu

et al.

Trends in Environmental Analytical Chemistry, Journal Year: 2022, Volume and Issue: 36, P. e00181 - e00181

Published: Oct. 7, 2022

Language: Английский

Citations

49

Enhanced ASGR2 by microplastic exposure leads to resistance to therapy in gastric cancer DOI Creative Commons
Hyeongi Kim, Javeria Zaheer, Eui‐Ju Choi

et al.

Theranostics, Journal Year: 2022, Volume and Issue: 12(7), P. 3217 - 3236

Published: Jan. 1, 2022

Background: Microplastics (MPs) are a new global environmental threat. Previously, we showed the biodistribution of MPs using [64Cu] polystyrene (PS) and PET in mice. Here, aimed to identify whether PS exposure has malignant effects on stomach induces resistance therapy. Methods: BALB/c nude mice were fed 1.72 × 104 particles/mL MP. We investigated accumulation radioisotope-labeled fluorescent-conjugated PS. Further, evaluated induced cancer stemness multidrug resistance, it affected tumor development, growth, survival rate vivo 4-week PS-exposed NCI-N87 mouse model. Using RNA-Seq analysis, analyzed gene expression changes gastric tissues Results: imaging results that single dose [64Cu]-PS remained for 24 h stomach. The daily repetitive fluorescent conjugated was deposited When exposed, 2.9-fold increase migration observed cells. Immunocytochemistry decreased E-cadherin increased N-cadherin expression, flow cytometry, qPCR, western blot analysis indicated 1.9-fold after exposure. PS-induced bortezomib, paclitaxel, gefitinib, lapatinib, trastuzumab model due upregulated CD44 expression. RNA-seq identified asialoglycoprotein receptor 2 (ASGR2) exposure, ASGR2 knockdown cell proliferation, migration, invasion, drug resistance. Conclusion: demonstrated enhanced hallmarks chemo- monoclonal antibody-therapy. Our preclinical findings may provide an incentive further epidemiological studies role MP its association with cancer.

Language: Английский

Citations

43

Spectral Classification of Large-Scale Blended (Micro)Plastics Using FT-IR Raw Spectra and Image-Based Machine Learning DOI
Yanlong Liu, Wenli Yao,

Fenghui Qin

et al.

Environmental Science & Technology, Journal Year: 2023, Volume and Issue: 57(16), P. 6656 - 6663

Published: April 13, 2023

Microplastics (MPs) are currently recognized as emerging pollutants; their identification and classification therefore essential during monitoring management. In contrast to most studies based on small datasets library searches, this study developed compared four machine learning-based classifiers two large-scale blended plastic datasets, where a 1D convolutional neural network (CNN), decision tree, random forest (RF) were fed with raw spectral data from Fourier transform infrared spectroscopy, while 2D CNN used the corresponding images input. With an overall accuracy of 96.43% dataset 97.44% large dataset, outperformed other models. The was best at predicting environment samples, RF robust less data. Overall, CNNs might be evaluated for fewer data; however, thought effective sufficient Accordingly, open-source MP spectroscopic analysis tool facilitate quick accurate existing samples.

Language: Английский

Citations

33