The Xiamen Symposium on Marine Environmental Sciences (XMAS 2025)

The extent of oceanic microplastic pollution has yet to be fully understood in part due to the challenges associated with discrete water sampling in the vast global ocean. Due to these challenges, the optical detection of microplastics presents a promising measurement approach with the potential to circumnavigate the temporal and spatial limitations of discrete water sampling. Using measurements of IOPs of several types of virgin microplastics samples, we have conducted radiative transfer simulations to determine the concentrations of plastics which are theoretically detectable from the Ocean and Land Color Instrument (OLCI) on the Sentinel-3 satellite. We present simulation results of the remote sensing reflectance from two water bodies representative of the South Pacific Subtropical Gyre with varying concentrations of microplastics, in which the addition of microplastics increases reflected light for nearly all wavelengths. Assuming an equal-part mixture of the three most common marine microplastic types distributed homogeneously throughout the water column, the detectable SPM of microplastics for most visible bands of OLCI is estimated to be about 10 mg m−3, with concentrations as low as 2 mg m−3 detectable in the blue and green bands. Realistic variability in the algal and nonalgal composition of the background material shows that the limit of 2 mg m−3 is only detectable at 510 nm, while relatively large changes in reflected blue light are seen following changes in background composition. Challenges with the differentiability of the optical signature of microplastics from other marine assemblages suggests that the remote detection of microplastics may be limited to oligotrophic open-ocean environments and for blue-green bands. As the expectation is that the presence of microplastics would present optically as an anomaly in the blue-green portion of the spectrum, we present preliminary analysis of blue-green anomalies in the pacific subtropical gyre using novel PACE data.