The Pearl River Estuary (PRE), one of the primary e-waste recycling centers in the world, has been suffering from the pollution of Liquid Crystal Monomers (LCMs), critical materials with persistent, bio-accumulative, and toxic substances used in electronic devices. It has been detected in seabed sediment with both high frequency and concentration near PRE - Hong Kong (HK) waters. In the same area, dredging operations with in-situ sediment have been frequently used in the last decades for coastal land reclamation projects. Dredging is known to cause a huge amount of sediment re-suspension into water columns, with potential damage to marine ecosystems and biodiversity. In this study, we proposed a new risk assessment strategy to estimate the secondary pollution due to the re-suspension sediment highly contaminated by LCMs. We formulate a robust and reliable probabilistic approach based on unsupervised machine learning and hydrodynamic and sediment transport numerical simulation. New risk indexes were also proposed to better quantify the impact of contaminated sediments. We applied the methodology to assess the potential impact of dredging operations in the PRE and Hong Kong waters on the local marine ecosystem. The results of the analysis showed how the potentially contaminated areas depended on the dredging locations.

Risk assessment of e-waste - Liquid Crystal Monomers re-suspension caused by coastal dredging operations

Stocchino A.;De Leo F.;
2024-01-01

Abstract

The Pearl River Estuary (PRE), one of the primary e-waste recycling centers in the world, has been suffering from the pollution of Liquid Crystal Monomers (LCMs), critical materials with persistent, bio-accumulative, and toxic substances used in electronic devices. It has been detected in seabed sediment with both high frequency and concentration near PRE - Hong Kong (HK) waters. In the same area, dredging operations with in-situ sediment have been frequently used in the last decades for coastal land reclamation projects. Dredging is known to cause a huge amount of sediment re-suspension into water columns, with potential damage to marine ecosystems and biodiversity. In this study, we proposed a new risk assessment strategy to estimate the secondary pollution due to the re-suspension sediment highly contaminated by LCMs. We formulate a robust and reliable probabilistic approach based on unsupervised machine learning and hydrodynamic and sediment transport numerical simulation. New risk indexes were also proposed to better quantify the impact of contaminated sediments. We applied the methodology to assess the potential impact of dredging operations in the PRE and Hong Kong waters on the local marine ecosystem. The results of the analysis showed how the potentially contaminated areas depended on the dredging locations.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11567/1232796
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