Environmental Chemistry Letters, Journal Year: 2024, Volume and Issue: 22(3), P. 1221 - 1255
Published: March 26, 2024
Language: Английский
Environmental Chemistry Letters, Journal Year: 2024, Volume and Issue: 22(3), P. 1221 - 1255
Published: March 26, 2024
Language: Английский
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
124Applied 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
78The Science of The Total Environment, Journal Year: 2023, Volume and Issue: 888, P. 164157 - 164157
Published: May 16, 2023
Language: Английский
Citations
57Journal of Hazardous Materials, Journal Year: 2024, Volume and Issue: 469, P. 133926 - 133926
Published: March 1, 2024
Language: Английский
Citations
17The Science of The Total Environment, Journal Year: 2021, Volume and Issue: 818, P. 151851 - 151851
Published: Nov. 22, 2021
Language: Английский
Citations
87Applied 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
58Reviews in Environmental Science and Bio/Technology, Journal Year: 2022, Volume and Issue: 21(3), P. 771 - 798
Published: May 26, 2022
Language: Английский
Citations
54Trends in Environmental Analytical Chemistry, Journal Year: 2022, Volume and Issue: 36, P. e00181 - e00181
Published: Oct. 7, 2022
Language: Английский
Citations
49Theranostics, 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
43Environmental 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