When Machine Learning Uncovers Microplastics – Enerzine

Plastic pollution, a major environmental problem of our time, is not limited to the oceans. Soil around the world is also affected, which can have serious environmental and health consequences.

A team of researchers used machine learning to assess and predict the effect of microplastics on soil properties. This innovative study could revolutionize the management of plastic waste and contribute to a better understanding of the impact of microplastics on the environment.

Importance of microplastics in soils

The presence of plastics in soils that fragment into microplastics by natural and anthropogenic processes it significantly modifies the properties of soils. These microplastics can also be absorbed by plants, potentially entering the human food chain and causing health complications.

Understanding the effect of microplastics on soil properties is extremely important to us business sustainability, especially in relation to environmental, social and governance (ESG) objectives. Global businesses are often faced with increasing expectations for environmentally friendly strategies, with a particular focus on addressing plastic-related issues.

Given the alarming impact of microplastic pollution in nature, it is important to understand how these toxic wastes are changing the environment. However, little research has been conducted on the impact of microplastic waste on soil quality. To this end, the researchers, led by Professor Yong Sik Ok, applied machine learning models to find that the characteristics of microplastics, such as their type, size, shape and dosage, can significantly change soil properties, including pH, organic carbon, phosphorus, nitrogen. and acid phosphatase enzyme activity. Credit: Hillary Daniels on Flickr

Using self-learning to study microplastics

A team of scientists led by Professor Yong Sik Ok used machine learning algorithms to assess and predict the effect of microplastics on soil properties.

” Machine learning is a dynamic and transformative field of artificial intelligence that uses algorithms and models to learn and make predictions from large data sets with high accuracy. “, explains Professor Ok TO UNHCR.

Machine learning algorithms were programmed to predict the effect of microplastics on soil properties and found that various microplastic factors such as type, size, shape and dose significantly changed soil properties. Specifically, the size of microplastics has been identified as a major factor affecting soil properties.

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This innovative study provides baseline data to support informed driving decision-making plastic waste, in line with the global focus on sustainability and ESG principles. It highlights the importance of innovative research to drive the sustainability efforts of a society where plastic-related issues are a growing concern.

For better understanding

What are microplastics?

Microplastics are small fragments of plastic, usually less than 5 mm in diameter, which can come from a variety of sources, including plastic waste which decompose.

Microplastics can alter soil properties, potentially affecting plant growth and the soil ecosystem. They can also be absorbed by plants and enter the food chain.

What is machine learning?

Machine learning is a field Artificial Intelligence which uses algorithms and models to learn and make predictions from large data sets.

The researchers used machine learning algorithms to predict the effect of microplastics on soil properties. They found that various microplastic factors such as type, size, shape and dose significantly changed soil properties.

What are the implications of this study?

This study could help in making decisions about plastic waste management and understanding the impact of microplastics on the environment. It could also lead to corporate sustainability efforts and encourage more environmentally friendly practices.

Reference

Article: “Prediction and interpretation of the effect of microplastics on soil properties using machine learning”

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