1. Evaluating Microplastic Pollution Along the Dubai Coast: An Empirical Model Combining On-Site Sampling and Sentinel-2 Remote Sensing Data
- Author
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Tarig Ali, Md Mortula, Batoul Mohsen, Lara Dronjak, Rahul Gawai, Serter Atabay, Zahid Khan, and Kazi Fattah
- Subjects
microplastics ,remote sensing ,sentinel-2 ,regression ,Technology ,Economic growth, development, planning ,HD72-88 - Abstract
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.
- Published
- 2024
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