In a recent study published in the journal Optics Letters, researchers from the Institute for Laser Technology created a new hyperspectral Raman imaging lidar system that can remotely detect and identify different plastics. By offering improved monitoring and analysis tools, this technology may help address the serious problem of plastic pollution in the ocean.
Plastic pollution poses a serious threat to marine ecosystems and human livelihoods, affecting industries like fisheries, tourism, and shipping. To manage and protect the marine environment, it is essential to assess the size, concentration, and distribution of plastic debris, but traditional lab-based methods are often time-consuming, labor-intensive, and expensive.
Toshihiro Somekawa, Research Team Leader, Institute for Laser Technology
It is small and energy-efficient, making it appropriate for use on a drone. They demonstrate that, with a comparatively large field of view of 1 mm × 150 mm, the system can detect plastics up to 6 m away.
A drone equipped with our lidar sensor could be used to assess marine plastic debris on land or in the sea, paving the way for more targeted cleanup and prevention efforts. The system could also be used for other monitoring applications, such as detecting hazardous gas leaks.
Toshihiro Somekawa, Research Team Leader, Institute for Laser Technology
Achieving Remote Detection
In the monitoring system that the researchers previously demonstrated, which was based on a flash Raman lidar technique, bandpass filters were sequentially matched to each measurement target for detection. However, because changing the filters would prevent instantaneous 3D ranging and detection, this method is impractical for detecting marine plastics.
Other research teams have investigated hyperspectral Raman imaging as a means of tracking plastic pollution. This method creates detailed maps of a sample's molecular composition and structure by combining imaging and Raman spectroscopy to capture spatially resolved chemical information. However, traditional hyperspectral Raman imaging can only detect targets close to the instrument.
The researchers used a combination of hyperspectral Raman spectroscopy and lidar for remote detection. They achieved this by constructing a prototype system that featured a 2D imaging spectrometer with a gated intensified CCD (ICCD) and a pulsed 532-nm green laser for lidar measurements.
The hyperspectral information contained in each point was recorded horizontally, and the Raman signal backscattered from a distant target was detected as a vertical line. Achieving the Raman lidar measurement with fine range resolutions required the use of an ICCD camera that can be gated on a nanosecond time scale.
Range-Resolved Raman Imaging
We designed our system to acquire images and spectroscopic measurements simultaneously. Since the Raman spectrum is unique for each plastic type, the imaging information can be used to understand the spatial distribution and type of plastic debris and hyperspectral information can be obtained from targets at any distance due to the pulsed laser enabling range-resolved measurements.
Toshihiro Somekawa, Research Team Leader, Institute for Laser Technology
The researchers tested their prototype system using a plastic sample with a polyethylene sheet in the top position and a polypropylene sheet in the bottom position. The system obtained each plastic's distinctive spectrum from a distance of 6 m and generated images that demonstrated the plastics' vertical distribution.
According to the researchers, the ICCD camera's imaging pixel size of 0.29 mm at a 6 m standoff distance suggests that the hyperspectral Raman imaging lidar system could be used to measure and analyze tiny plastic debris.
Using their system, the researchers then intend to monitor floating or submerged microplastics in water. Since laser light at 532 nm transmits well through water, improving detection in aquatic environments should be possible.
Journal Reference:
Somekawa, T., et al. (2024) Remote detection and identification of plastics with hyperspectral Raman imaging lidar. Optics Letters. doi.org/10.1364/ol.544096.