Detection of Secondary Microplastics in an Aquatic Mesocosm by Means of Object-Based Image Analysis

Abstract

When plastics are discarded, they do not biodegrade and instead break down over time into progressively smaller particles, termed secondary microplastics, which adversely impact biota and human health as well as persist in the environment for centuries. Our research objective was to evaluate the capabilities of object-based image analyses in detecting compositionally varied microplastics suspended in an aquatic mesocosm under no-slip and turbulent water conditions. We found that the presence of polypropylene, polyethylene terephthalate, and low-density polyethylene microplastic pollution in both single-type and mixed-type suspensions was not detectable by either average red (R), average blue (B), average green (G), or average RBG pixel intensities, but was significantly detectable by means of total RBG pixel intensity from digital imagery of the surface-water. Our findings suggest that object-based image analyses of surface waters to quantify pixel information is better suited for monitoring the presence and absence of suspended microplastics, rather than for the stepwise determination of microplastic concentrations. We propose the development of a smartphone application to facilitate citizen-science monitoring of microplastic contamination as well as comment on future applications utilizing drone imagery to boost cloud-based mapping spatiotemporal plumes.

Keywords

• digital image analysis
• pixel
• plastic pollution
• sustainability
• water quality