Oil Spill Detection Using Fluorometric Sensors: Laboratory Validation and Implementation to a FerryBox and a Moored SmartBuoy
A large part of oil spills happen near busy marine fairways. Presently, oil spill detection and monitoring are mostly done with satellite remote sensing algorithms, or with remote sensors or visual surveillance from aerial vehicles or ships. These techniques have their drawbacks and limitations. We...
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2021
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oai:doaj.org-article:e9792ae7618140cb89c089654e5a2df32021-12-01T18:40:54ZOil Spill Detection Using Fluorometric Sensors: Laboratory Validation and Implementation to a FerryBox and a Moored SmartBuoy2296-774510.3389/fmars.2021.778136https://doaj.org/article/e9792ae7618140cb89c089654e5a2df32021-11-01T00:00:00Zhttps://www.frontiersin.org/articles/10.3389/fmars.2021.778136/fullhttps://doaj.org/toc/2296-7745A large part of oil spills happen near busy marine fairways. Presently, oil spill detection and monitoring are mostly done with satellite remote sensing algorithms, or with remote sensors or visual surveillance from aerial vehicles or ships. These techniques have their drawbacks and limitations. We evaluated the feasibility of using fluorometric sensors in flow-through systems for real-time detection of oil spills. The sensors were capable of detecting diesel oil for at least 20 days in laboratory conditions, but the presence of CDOM, turbidity and algae-derived substances substantially affected the detection capabilities. Algae extract was observed to have the strongest effect on the fluorescence signal, enhancing the signal in all combinations of sensors and solutions. The sensors were then integrated to a FerryBox system and a moored SmartBuoy. The field tests support the results of the laboratory experiments, namely that the primary source of the measured variation was the presence of interference compounds. The 2 month experiments data did not reveal peaks indicative of oil spills. Both autonomous systems worked well, providing real-time data. The main uncertainty is how the sensors' calibration and specificity to oil, and the measurement depth, affects oil detection. We recommend exploring mathematical approaches and more advanced sensors to correct for natural interferences.Siim PärtHarri KankaanpääJan-Victor BjörkqvistJan-Victor BjörkqvistJan-Victor BjörkqvistRivo UiboupinFrontiers Media S.A.articleoil spillflow-trough systemfluorometric sensorsBaltic Seanatural interferencessensor selectivityScienceQGeneral. Including nature conservation, geographical distributionQH1-199.5ENFrontiers in Marine Science, Vol 8 (2021) |
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oil spill flow-trough system fluorometric sensors Baltic Sea natural interferences sensor selectivity Science Q General. Including nature conservation, geographical distribution QH1-199.5 |
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oil spill flow-trough system fluorometric sensors Baltic Sea natural interferences sensor selectivity Science Q General. Including nature conservation, geographical distribution QH1-199.5 Siim Pärt Harri Kankaanpää Jan-Victor Björkqvist Jan-Victor Björkqvist Jan-Victor Björkqvist Rivo Uiboupin Oil Spill Detection Using Fluorometric Sensors: Laboratory Validation and Implementation to a FerryBox and a Moored SmartBuoy |
description |
A large part of oil spills happen near busy marine fairways. Presently, oil spill detection and monitoring are mostly done with satellite remote sensing algorithms, or with remote sensors or visual surveillance from aerial vehicles or ships. These techniques have their drawbacks and limitations. We evaluated the feasibility of using fluorometric sensors in flow-through systems for real-time detection of oil spills. The sensors were capable of detecting diesel oil for at least 20 days in laboratory conditions, but the presence of CDOM, turbidity and algae-derived substances substantially affected the detection capabilities. Algae extract was observed to have the strongest effect on the fluorescence signal, enhancing the signal in all combinations of sensors and solutions. The sensors were then integrated to a FerryBox system and a moored SmartBuoy. The field tests support the results of the laboratory experiments, namely that the primary source of the measured variation was the presence of interference compounds. The 2 month experiments data did not reveal peaks indicative of oil spills. Both autonomous systems worked well, providing real-time data. The main uncertainty is how the sensors' calibration and specificity to oil, and the measurement depth, affects oil detection. We recommend exploring mathematical approaches and more advanced sensors to correct for natural interferences. |
format |
article |
author |
Siim Pärt Harri Kankaanpää Jan-Victor Björkqvist Jan-Victor Björkqvist Jan-Victor Björkqvist Rivo Uiboupin |
author_facet |
Siim Pärt Harri Kankaanpää Jan-Victor Björkqvist Jan-Victor Björkqvist Jan-Victor Björkqvist Rivo Uiboupin |
author_sort |
Siim Pärt |
title |
Oil Spill Detection Using Fluorometric Sensors: Laboratory Validation and Implementation to a FerryBox and a Moored SmartBuoy |
title_short |
Oil Spill Detection Using Fluorometric Sensors: Laboratory Validation and Implementation to a FerryBox and a Moored SmartBuoy |
title_full |
Oil Spill Detection Using Fluorometric Sensors: Laboratory Validation and Implementation to a FerryBox and a Moored SmartBuoy |
title_fullStr |
Oil Spill Detection Using Fluorometric Sensors: Laboratory Validation and Implementation to a FerryBox and a Moored SmartBuoy |
title_full_unstemmed |
Oil Spill Detection Using Fluorometric Sensors: Laboratory Validation and Implementation to a FerryBox and a Moored SmartBuoy |
title_sort |
oil spill detection using fluorometric sensors: laboratory validation and implementation to a ferrybox and a moored smartbuoy |
publisher |
Frontiers Media S.A. |
publishDate |
2021 |
url |
https://doaj.org/article/e9792ae7618140cb89c089654e5a2df3 |
work_keys_str_mv |
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