Photo-oxidation of Micro- and Nanoplastics: Physical, Chemical, and Biological Effects in Environments

Environmental Science & Technology, Journal Year: 2024, Volume and Issue: 58(2), P. 991 - 1009

Published: Jan. 3, 2024

Micro- and nanoplastics (MNPs) are attracting increasing attention due to their persistence potential ecological risks. This review critically summarizes the effects of photo-oxidation on physical, chemical, biological behaviors MNPs in aquatic terrestrial environments. The core this paper explores how photo-oxidation-induced surface property changes affect adsorption toward contaminants, stability mobility water porous media, as well transport pollutants such organic (OPs) heavy metals (HMs). It then reviews photochemical processes with coexisting constituents, highlighting critical factors affecting MNPs, contribution phototransformation other contaminants. distinct mechanism aged pointed out, terms toxicity organisms, biofilm formation, planktonic microbial growth, soil sediment community function. Furthermore, research gaps perspectives put forward, regarding underlying interaction mechanisms natural constituents under conditions, combined fate microbiological effect photoaged especially biotransformation pollutants.

Language: Английский

---

Machine learning-driven prediction of phosphorus removal performance of metal-modified biochar and optimization of preparation processes considering water quality management objectives

Bioresource Technology, Journal Year: 2024, Volume and Issue: 403, P. 130861 - 130861

Published: May 18, 2024

Language: Английский

---

Joule heat assisting electrochemical degradation of polyethylene microplastics melted on anode

Applied Catalysis B Environment and Energy, Journal Year: 2024, Volume and Issue: 357, P. 124281 - 124281

Published: June 12, 2024

Language: Английский

---

Predicting microplastic quantities in Indonesian provincial rivers using machine learning models

The Science of The Total Environment, Journal Year: 2025, Volume and Issue: 961, P. 178411 - 178411

Published: Jan. 1, 2025

Language: Английский

---

Developing a machine learning-based predictive model for cesium sorption distribution coefficient on crushed granite

Journal of Environmental Radioactivity, Journal Year: 2025, Volume and Issue: 283, P. 107628 - 107628

Published: Feb. 4, 2025

Language: Английский

---

Exploring the response of bacterial community functions to microplastic features in lake ecosystems through interpretable machine learning

Environmental Research, Journal Year: 2025, Volume and Issue: unknown, P. 121098 - 121098

Published: Feb. 1, 2025

Language: Английский

---

Deep convolutional neural networks for aged microplastics identification by Fourier transform infrared spectra classification

The Science of The Total Environment, Journal Year: 2023, Volume and Issue: 913, P. 169623 - 169623

Published: Dec. 28, 2023

Language: Английский

---

Assessment of Global Antibiotic Exposure Risk for Crops: Incorporating Soil Adsorption via Machine Learning

Environmental Science & Technology, Journal Year: 2024, Volume and Issue: unknown

Published: July 20, 2024

The overuse and misuse of antibiotics could significantly increase their accumulation in soils. Consequently, possibly enter food chain through crop uptake, posing a threat to global security. Assessing the exposure risks for crops is crucial addressing this issue. In study, we assessed antibiotic risk crops, incorporating machine learning adsorption model based on 4893 data sets from nine antibiotics. optimized model, using eXtreme Gradient Boosting algorithm class-specific modeling strategy, demonstrated relatively good performance. Notably, introduced unsaturated soil conditions considered spatiotemporal variations moisture temperature first time such assessment. Global distributions were predicted March, June, September, December. results indicate that influences Relatively high was observed during months with colder local temperatures: generally June Southern Hemisphere December Northern Hemisphere. resulting map highlights high-risk agricultural regions, including southern Canada, western Russia, Australia.

Language: Английский

---

Machine learning-driven QSAR models for predicting the cytotoxicity of five common microplastics

Toxicology, Journal Year: 2024, Volume and Issue: 508, P. 153918 - 153918

Published: Aug. 11, 2024

Language: Английский

---

A Critical Review of an Environmental Risk Substance Induced by Aging Microplastics: Insights into Environmentally Persistent Free Radicals

Environmental Science & Technology, Journal Year: 2024, Volume and Issue: 58(51), P. 22502 - 22518

Published: Dec. 11, 2024

Microplastics (MPs), as an emerging contaminants category, can undergo complex aging in a variety of environmental matrices which the chemical bonds polymer molecules be broken to form free radicals. While existence radicals aged plastics has been known for over half century, only recently significant research on new type environmentally risky substance, namely persistent (EPFRs), present MPs and their effects, started, but it is still its infancy. To address these issues, this work examines EPFR generation effect by reviewing publications from 2012 2023. The processes mechanisms environment are first summarized. Then, occurrence formation EPFRs specifically discussed. Additionally, reactivity influencing factors comprehensively considered, such physicochemical properties, oxygen content, coexisting substances. Due reactivity, interact directly with some substances (e.g.,

Language: Английский

---