The “Microplastome” – A Holistic Perspective to Capture the Real-World Ecology of Microplastics

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

Published: Feb. 8, 2024

Microplastic pollution, an emerging pollution issue, has become a significant environmental concern globally due to its ubiquitous, persistent, complex, toxic, and ever-increasing nature. As multifaceted diverse suite of small plastic particles with different physicochemical properties associated matters such as absorbed chemicals microbes, future research on microplastics will need comprehensively consider their multidimensional attributes. Here, we introduce novel, conceptual framework the "microplastome", defined entirety various (<5 mm), found within sample overall toxicological impacts. novel concept, this paper aims emphasize call for collective quantification characterization more holistic understanding regarding differences, connections, effects in biotic abiotic ecosystem compartments. Deriving from lens, present our insights prospective trajectories characterization, risk assessment, source apportionment microplastics. We hope new paradigm can guide propel microplastic toward era contribute informed strategy combating important issue.

Language: Английский

---

Degradation of emerging contaminants in water by a novel non-thermal plasma/periodate advanced oxidation process: Performance and mechanisms

Chemical Engineering Journal, Journal Year: 2024, Volume and Issue: 483, P. 149194 - 149194

Published: Jan. 29, 2024

Language: Английский

---

Using artificial intelligence to rapidly identify microplastics pollution and predict microplastics environmental behaviors

Journal of Hazardous Materials, Journal Year: 2024, Volume and Issue: 474, P. 134865 - 134865

Published: June 12, 2024

Language: Английский

---

Triggering nanoconfinement effect in advanced oxidation processes (AOPs) for boosted degradation of organic contaminants: A review

Chemical Engineering Journal, Journal Year: 2024, Volume and Issue: 503, P. 158428 - 158428

Published: Dec. 9, 2024

Language: Английский

---

Current Status of Emerging Contaminant Models and Their Applications Concerning the Aquatic Environment: A Review

Water, Journal Year: 2025, Volume and Issue: 17(1), P. 85 - 85

Published: Jan. 1, 2025

Increasing numbers of emerging contaminants (ECs) detected in water environments require a detailed understanding these chemicals’ fate, distribution, transport, and risk aquatic ecosystems. Modeling is useful approach for determining ECs’ characteristics their behaviors environments. This article proposes systematic taxonomy EC models addresses gaps the comprehensive analysis applications. The reviewed include conventional quality models, multimedia fugacity machine learning (ML) models. Conventional have higher prediction accuracy spatial resolution; nevertheless, they are limited functionality can only be used to predict contaminant concentrations Fugacity excellent at depicting how travel between different environmental media, but cannot directly analyze variations parts same media because model assumes that constant within compartment. Compared other ML applied more scenarios, such as identification assessments, rather than being confined concentrations. In recent years, with rapid development artificial intelligence, surpassed becoming one newest hotspots study ECs. primary challenge faced by outcomes difficult interpret understand, this influences practical value an some extent.

Language: Английский

---

Machine Learning-Enhanced Electrochemical Sensors for Food Safety: Applications and Perspectives

Trends in Food Science & Technology, Journal Year: 2025, Volume and Issue: unknown, P. 104872 - 104872

Published: Jan. 1, 2025

Language: Английский

---

Integrating Remote Sensing Methods for Monitoring Lake Water Quality: A Comprehensive Review

Hydrology, Journal Year: 2024, Volume and Issue: 11(7), P. 92 - 92

Published: June 26, 2024

Remote sensing methods have the potential to improve lake water quality monitoring and decision-making in management. This review discusses use of remote for assessing lakes. It explains principles different used retrieving parameters complex waterbodies. The highlights importance considering variability optically active need comprehensive studies that encompass seasons time frames. paper addresses specific physical biological can be effectively estimated using sensing, such as chlorophyll-α, turbidity, transparency (Secchi disk depth), electrical conductivity, surface salinity, temperature. further provides a summary bands, band combinations, equations commonly these per satellite sensor. also limitations challenges associated with systems. recommends integrating situ measurements computer modelling understanding quality. suggests future research directions, including optimizing grid selection frame by combining hydrodynamic models retrieval methods, when analysing imagery, development advanced technologies, integration machine learning algorithms effective problem-solving. concludes proposed workflow lakes methods.

Language: Английский

---

The Synergy of Artificial Intelligence and Nanotechnology Towards Advancing Innovation and Sustainability- A Mini-Review

Nano Trends, Journal Year: 2024, Volume and Issue: unknown, P. 100052 - 100052

Published: Sept. 1, 2024

Language: Английский

---

Transforming PFAS management: A critical review of machine learning applications for enhanced monitoring and treatment

Journal of Water Process Engineering, Journal Year: 2025, Volume and Issue: 70, P. 106941 - 106941

Published: Jan. 15, 2025

Language: Английский

---

Combining size distribution and shape of plastic and oxide particles to evaluate physicochemical interactions: Aggregation and attachment

Journal of Hazardous Materials, Journal Year: 2025, Volume and Issue: unknown, P. 137385 - 137385

Published: Jan. 1, 2025

Language: Английский

---