Estimating microplastic concentrations in surface water using satellite-based turbidity measurements: a case study on the New River, VA

Abstract

Microplastic (<5 mm) pollution in rivers poses a threat to ecosystems and human livelihood around the world, yet the methods used to quantify and monitor their occurrence, distribution, and transport are highly limited. A substantial portion of plastics make their way into rivers through a variety of pathways such as direct dumping and environmental transport processes (wind, surface runoff, etc.). To detect and quantify microplastic abundance in rivers, traditional detection methods rely on visual observation and enumeration techniques, resulting in error due to bias in counting. These methods are time-consuming and require laborious field collection and laboratory work, inhibiting high-frequency observations over large spatial extents, which is needed to better understand the sources, sinks, and dynamics of microplastic pollution in waterways. Satellite remote sensing can provide regular water quality estimates in rivers with large spatial and temporal coverage, and we could use these estimates as a proxy for surface river microplastic concentrations. In this study, we relate the satellite-derived normalized difference turbidity index (NDTI) to co-temporal in situ turbidity and surface water microplastic concentrations. We focused our study on the New River, in Southwest Virginia, USA. Over the course of a year (September 2023 - September 2024), we collected and analyzed over 100 co-temporal water quality measurements, surface water microplastic concentration samples, and corresponding observations from satellite imagery. Using linear regression, we derived a relationship between NDTI and in situ turbidity that explains 71% of the variance (R2 = 0.71). Seasonal relationships varied between in situ turbidity and microplastic concentrations which varied between R2 0.19 and 0.56. We combined the equations relating NDTI, in situ turbidity, and co-temporal microplastic concentrations to directly relate satellite-derived NDTI to microplastic concentrations. With this equation, we can estimate microplastic concentrations along the New River on clear-sky days using Sentinel-2 at 10-m resolution, allowing us to delineate microplastic concentrations along the river. The method developed here can be used to advance our ability to track the dynamics of microplastic for improved assessments of sources and sinks of mismanaged plastic waste in Earth's waterways.