LAMPO - Low-cost Aquatic MicroPlastic Observation system for ocean monitoring aboard ships
dc.contributor.author | Cristofolini, Peter | |
dc.contributor.author | Mühlebach, Lea | |
dc.contributor.author | Markocic, Miha | |
dc.contributor.author | Orawez, Georg | |
dc.contributor.author | Shynkarenko, Yevhen | |
dc.contributor.author | Martinez-Frances, Elena | |
dc.contributor.author | Van Bavel, Bert | |
dc.contributor.author | Cattaneo, Stefano | |
dc.date.accessioned | 2023-04-12T14:32:24Z | |
dc.date.available | 2023-04-12T14:32:24Z | |
dc.date.issued | 2022-11-06 | |
dc.description.abstract | Microplastic pollution has been found in the most remote parts of the ocean and constitutes a serious environmental problem for marine wildlife. Most microplastic is not bio-degradable and accumulates in the marine food chain, thereby also posing a risk to human health. The systematic study of microplastic contamination in the ocean remains a difficult endeavour and requires regular monitoring to collect a high density of data samples both spatially (to map origin and the effect of marine currents) and in time (to understand long-term trends). Ideally, the data obtained includes microplastic composition information: particle count, size fractions and plastic type. So far, most studies on microplastics have relied on samples collected on a single ship trip, which are subsequently analysed in a research lab by optical microscopy or Raman/FTIR spectroscopy. This method gives very good insight into the microplastic composition of the samples, however only limited information on its spatial and temporal distribution. The Horizon 2020 project NAUTILOS aims to develop low-cost sensors for autonomous continuous in-situ monitoring of ocean parameters. Herein, we are developing an in-line microplastic sensor, capable of analysing marine microplastic in real time in an automated manner. A sampler unit mounted onboard a ship filters the microplastic of size 300 um and smaller from the marine water. After sampling, the microplastic sample is oxidised to remove biomaterials and stained with Nile Red, a fluorescent dye that helps differentiate polar from non-polar plastic. Finally, the treated microplastic sample is run through an optical fluorescence detector capable of measuring blue and UV fluorescence intensity for multiple colour channels. By aggregation of time-series data from several sensors on a Raspberry Pi, we plan to measure and identify marine microplastic on-site and in real time. The microplastic sensor is planned to be deployed onboard a FerryBox on cruise ships and ferries, to automatically generate repeated microplastic datasets along the same shipping route, for long-term studies and monitoring purposes. The microplastic data will be matched with GPS position and other sensor data from the FerryBox and uploaded via satellite internet to the NIVA servers. | en_US |
dc.identifier.citation | Microplastics2022, Ascona, Switzerland 6-11 November 2022 | en_US |
dc.identifier.uri | https://hdl.handle.net/20.500.12839/1174 | |
dc.language.iso | en | en_US |
dc.title | LAMPO - Low-cost Aquatic MicroPlastic Observation system for ocean monitoring aboard ships | en_US |
dc.type | Conference / Workshop | en_US |
dc.type.csemdivisions | BU-R | en_US |
dc.type.csemresearchareas | Photonics | en_US |
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