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

Journal of Sustainable Development of Energy Water and Environment Systems 2024 3 citations ? Citation count from OpenAlex, updated daily. May differ slightly from the publisher's own count. Score: 40 ? 0–100 AI score estimating relevance to the microplastics field. Papers below 30 are filtered from public browse.

Lara Dronjak, Lara Dronjak, Lara Dronjak, Md Maruf Mortula, Lara Dronjak, Batoul Mohsen, Tarig Ali, Batoul Mohsen, Lara Dronjak, Tarig Ali, Md Maruf Mortula, Md Maruf Mortula, Md Maruf Mortula, Md Maruf Mortula, Lara Dronjak, Lara Dronjak, Serter Atabay, Batoul Mohsen, Tarig Ali, Tarig Ali, Tarig Ali, Md Maruf Mortula, Kazi Parvez Fattah Batoul Mohsen, Rahul Gawai, Md Maruf Mortula, Tarig Ali, Tarig Ali, Batoul Mohsen, Tarig Ali, Tarig Ali, Md Maruf Mortula, Md Maruf Mortula, Md Maruf Mortula, Md Maruf Mortula, Lara Dronjak, Md Maruf Mortula, Lara Dronjak, Lara Dronjak, Md Maruf Mortula, Kazi Parvez Fattah Lara Dronjak, Rahul Gawai, Lara Dronjak, Rahul Gawai, Serter Atabay, Serter Atabay, Zahid Khan, Kazi Parvez Fattah

Summary

Researchers collected coastal water samples from Dubai and combined laboratory spectral measurements with Sentinel-2 satellite imagery to build a model that estimates microplastic concentrations from space. The model achieved an R² of 87% and was used to map microplastic pollution trends along the Dubai coast from 2018 to 2021. This remote-sensing approach demonstrates a scalable method for monitoring coastal microplastic pollution over large areas without intensive fieldwork.

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.

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