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Bioplastics

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Bioplastics derived from microbial processes present a sustainable alternative to conventional petroleum-based plastics. Among these, polyhydroxyalkanoates (PHAs), particularly polyhydroxybutyrates (PHBs), have emerged as prominent candidates due to their biodegradability and biocompatibility. These polymers are synthesized by a variety of bacteria, such as Cupriavidus necator and Pseudomonas putida, which naturally accumulate PHAs as intracellular carbon and energy reserves, especially under...

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Updated: Jun 23, 2026

Protocol for Microplastics Sampling on the Sea Surface and Sample Analysis

Protocol for Microplastics Sampling on the Sea Surface and Sample Analysis

Published on: December 16, 2016

Data driven AI (artificial intelligence) detection furnish economic pathways for microplastics.

Mamta Latwal¹, Shefali Arora¹, K S R Murthy¹

¹Department of Chemistry, University of Petroleum and Energy Studies, Dehradun, UK, India.

Journal of Contaminant Hydrology

|May 22, 2024

Summary

This summary is machine-generated.

Microplastic pollution threatens aquatic life and human health. This review explores artificial intelligence (AI) solutions for microplastic eradication in water systems.

Keywords:

Artificial intelligence Environmental impact Machine learning Microplastics Ocean Toxic polymers

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Protocol for Microplastics Sampling on the Sea Surface and Sample Analysis

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Sampling, Sorting, and Characterizing Microplastics in Aquatic Environments with High Suspended Sediment Loads and Large Floating Debris

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Separation and Identification of Conventional Microplastics from Farmland Soils

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Published on: March 21, 2025

Area of Science:

Environmental Science
Analytical Chemistry
Computer Science

Background:

Microplastic pollution poses a significant threat to aquatic ecosystems and human health.
Current detection methods are more advanced for water compared to soil and air.
Microplastics bypass conventional water filtration, impacting marine life.

Purpose of the Study:

To review current research on microplastic detection and removal.
To explore the application of artificial intelligence (AI) in combating microplastic pollution.
To highlight AI as a novel strategy for clean water initiatives.

Main Methods:

Literature review of microplastic research.
Analysis of AI applications in environmental remediation.
Synthesis of findings on microplastic detection and AI-based eradication.

Main Results:

Microplastics are pervasive environmental contaminants affecting water systems.
AI offers promising, advanced solutions for microplastic detection and removal.
Integration of AI is crucial for effective clean water strategies.

Conclusions:

Microplastic pollution requires urgent, innovative solutions.
Artificial intelligence presents a powerful tool for addressing this global challenge.
Further research into AI-driven microplastic eradication is essential for environmental protection.