Evaluating Microplastic Pollution Along the Dubai Coast: An Empirical Model Combining On-Site Sampling and Sentinel-2 Remote Sensing Data

Identifier:  imarina:9362446

Handle: https://hdl.handle.net/20.500.11797/imarina9362446

Authors:  Ali, T; Mortula, M; Mohsen, B; Dronjak, L; Gawai, R; Atabay, S; Khan, Z; Fattah, K

Abstract:
The study addresses the growing concern of microplastic pollution in environmental matrices, emphasizing the significance of monitoring to understand their distribution, sources, and mitigation. Laboratory-based spectral reflectance analysis of water samples containing visible microplastics revealed distinctive spectral signatures. Coastal water samples collected over two campaigns were subjected to pretreatment to extract microplastics, and spectroscopic confirmation was followed by microscopic inspection. Results indicated average microplastics concentrations of 0.633 and 0.324 mg/L and 7.85 and 5.30 items/L in the datasets. Leveraging these findings, along with Sentinel-2 (Level-1C) data and spectral signatures, an empirical spectral microplastics model was developed to convert Sentinel-2's reflectance into microplastics concentrations. This model displayed an R2 of 87.30% and RMSE of +/- 0.015 mg/L. Subsequently, the model was employed to estimate microplastics concentrations in 2018, 2019, 2020, and 2021, showcasing its potential for monitoring microplastic pollution in the study area and similar regions.