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Hyperspectral imaging of black microplastics directly in water

Hafiz Ramzan Mubarak

Hyperspectral imaging of black microplastics directly in water.

Rel. Carlo Ricciardi. Politecnico di Torino, Corso di laurea magistrale in Nanotechnologies For Icts (Nanotecnologie Per Le Ict), 2023

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Abstract:

Environmental pollution by microplastics is now recognized as an issue with strong possible impact on ecology, society, and economy. Black microplastics (BMPs) have attracted attention due to their prolonged existence and potential for toxicity. This thesis investigates the utilization of hyperspectral imaging (HSI) techniques for detecting and characterizing black microplastics (BMPs) in water samples directly. The thesis begins by introducing the issue of microplastic pollution, emphasizing the importance of distinguishing BMPs from natural particles. Hyperspectral imaging, known for its ability to capture both spatial and spectral information, is proposed as a promising approach to address this challenge. A comprehensive overview of hyperspectral imaging techniques, including point scanning, line scanning, and focal plane array (FPA) scanning, is presented. The principles of hyperspectral cameras, such as optics, detectors, and spectral dispersing elements, are discussed. Additionally, specific data acquisition and processing techniques applicable to hyperspectral imaging are examined. The experimental procedures section describes the materials and methods used in the study, including the use of various BMP concentrations in water. The thesis describes the measurements and calculations used to analyze the hyperspectral data, with a focus on BMP reflectance and transmittance. The results and discussion section presents the findings from the experiments and provides a comprehensive analysis of BMPs in water. The thesis explores the reflectance and transmittance characteristics of BMPs, contributing to their characterization in aquatic environments. In conclusion, this thesis showcases how hyperspectral imaging serves as an effective means to identify and characterize black microplastics in water. By capturing intricate spectral details, HSI facilitates the recognition and analysis of BMPs within intricate environmental samples. The outcomes of this study hold the potential to provide guidance for future initiatives aimed at monitoring microplastic pollution, thereby playing a vital role in safeguarding ecosystems.

Relators: Carlo Ricciardi
Academic year: 2023/24
Publication type: Electronic
Number of Pages: 77
Subjects:
Corso di laurea: Corso di laurea magistrale in Nanotechnologies For Icts (Nanotecnologie Per Le Ict)
Classe di laurea: New organization > Master science > LM-29 - ELECTRONIC ENGINEERING
Aziende collaboratrici: University of Eastern Finland
URI: http://webthesis.biblio.polito.it/id/eprint/29000
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