Speaker
Description
Recent developments in the monitoring of marine pollution using remote sensing have focused on characterizing hydrocarbon products. However, only a few studies have examined the remote sensing of Hazardous and Noxious Substances (HNS), even though their release at sea can pose risks to human health, harm living resources, and other marine life. Unlike hydrocarbons, which generally remain on the surface of the water, HNS exhibit a wide range of behaviors, including volatile substances with high vapor pressure. The accidental release of these chemicals into the sea can lead to the formation of toxic, flammable, and/or explosive gas plumes. Consequently, developing effective response protocols is a major challenge for marine pollution authorities, given the significant environmental and human stakes involved.
Within the European MANIFESTS project (2021-2023), dispersion models were developed to provide information on the atmospheric propagation of volatile HNS. However, observational data are required to optimize the model parametrizations and adapt them to the marine environment. Remote sensing in the thermal infrared is a powerful tool for characterizing volatile HNS released into the sea because it enables the identification of (i) slick thermal contrasts on the sea surface and (ii) spectral absorption/emission of evaporating gas plumes.
Nevertheless, the maritime environment is characterized by low thermal contrasts compared to continental surfaces. This can lead to mis-detecting and mis-quantifying gas plumes when using traditional infrared spectral imaging. Moreover, gas plumes are typically associated with extended chemical slicks rather than point sources.
In this work, a new method is presented for estimating gas flow rates per slick unit area using a cooled infrared multispectral imager called SIMAGAZ. SIMAGAZ is a pre-industrial imager with four spectral bands in the long-wave infrared (7.2-8.5 µm), a high acquisition frequency (up to 75 Hz), and a very low radiometric noise (<10 mK per band). The algorithm flowchart includes the following steps: (i) gas detection using spectral correlation, (ii) estimation of the integrated gas concentration by inverting a dedicated radiometric model, (iii) a gas velocity field derived from the Farnebäck optical flow algorithm, (iv) estimation of the gas mass flow rate based on the Cross-Sectional Flux method, and (v) estimation of the gas flow rate per slick unit area using thermal detection of the slick surface.
This method has been applied to several volatile HNS during experiments conducted at different scales in the CEDRE facilities, including laboratory scale (product confined to a Petri dish) and seawater pool scale (product spilled over a few square meters). Image sequences were acquired from the ground using SIMAGAZ for several minutes.
The results presented for two volatile HNS (butyl acetate and acetone) show a good agreement between the laboratory scale and balance measurements for gas mass flow rate, as well as between the laboratory and pool scales for gas flow rate per slick unit area. This approach can now be extended to large-scale datasets acquired under open-sea conditions during the MANIFESTS project, and compared with atmospheric dispersion models to develop operational response tools.
