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

Original scientific paper

Journal of Sustainable Development of Energy, Water and Environment Systems
Volume 12, Issue 1, 1110482
DOI: https://doi.org/10.13044/j.sdewes.d11.0482
Tarig Ali1, Md Mortula1, Batoul Mohsen1, Lara Dronjak2 , Rahul Gawai1, Serter Atabay1, Zahid Khan3, Kazi Fattah4
1 American University of Sharjah, Sharjah, United Arab Emirates
2 University Rovira and Virgily, Tarragona, Spain
3 AECOM, Aecom, Canada
4 Department of Civil, Environmental & Architectural Engineering, University of, Kansas, United States


The study addresses the growing concern of microplastic pollution in environmental matrices, emphasizing the significance of monitoring for understanding 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 pre-treatment in order to extract microplastics and microscopic inspection followed by spectroscopic confirmation. Results indicated average microplastics concentrations of 0.633 and 0.324mg/L, along with 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 87.30% R2 and ±0.015mg/L RMSE. Subsequently, the model was employed to estimate microplastics concentrations in 2018, 2019, 2020, and 2021, showcasing its potential for monitoring microplastics pollution in the study area and similar regions.

Keywords: microplastics; remote sensing; Sentinel-2; regression

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