Miniature Submarine using Near-Infrared Spectroscopy to Detect and Collect Microplastics

Abstract

A promising solution to detecting and collecting ocean microplastics is utilizing near-infrared (NIR) spectroscopy. NIR spectroscopy is a cost-effective, safe, and accurate method to determine the chemical composition of unknown materials. However, since it cannot easily function underwater as light cannot penetrate the ocean surface, a submarine drone design developed here will employ near-infrared spectroscopy to differentiate the collected micro-objects. In particular, an experiment was conducted where varying sizes of kombu (edible kelp) and microplastics were scanned by a NIR spectrometer to determine the mass composition of a given sample. A least sum of squares method was used to analyze the spectra data from an unknown concentration of microplastics by comparing the spectra data to stored spectra datasets which were produced from samples of known concentrations. The results showed that least squares analysis was a generally effective method to compare such spectra graphs and deduce the mass composition of a given sample. Although, more improvements including the analysis of the spectra graph's curvature and an increased amount of composition data, are necessary to make the approach more accurate.