Six fast and highly sensitive UV and three IR cameras were custom-built. The UV camera systems were equipped with PCO.ultraviolet camera cores, band-pass filters centered at ~310 nm and ~330 nm, and a co-aligned AvaSpec-ULS2048x64 spectrometer from Avantes for robust SO2 calibration. The TIR SO2 camera systems were based on three co-located IR cameras (Xenics Gobi-384-GigE), which were equipped with three filters (centered at 8.62 µm, 10.00 µm and 10.87 µm). Images were recorded with frame rates of up to about 5 Hz. Both systems contain peripheral instruments, i.e., a visible camera, an inclinometer, and a GPS. A separate computer box contains a high performance fanless embedded computer with a 1 TB solid-state disk. The systems, which are operated by custom written software, can be operated with 220 V as well as with 12 V battery power.
Figures of the cameras set up at the Rena field site and on Stromboli are shown below.
Figure 1: Photograph of the COMTESSA UV camera set up 7 July 2018 in the Rena field.
Figure 2: UV and IR camera heads set up 11 June 2019 on Stromboli Island.
Figure 3: Setup of the six UV cameras on Stromboli Island.
Analysis software for SO2 camera images were further developed, as documented in Gliss et al (2017, 2018). A software toolbox for analysis of SO2 images for emission rate retrievals from point sources was developed, and the optical flow velocity analysis in SO2 camera images could be improved, as demonstrated for volcanic plume applications. The Software package was further developed to include the analysis of the turbulent dispersion parameter from SO2 camera images (see Dinger et al., 2018).
Dinger, A. S., Stebel, K., Cassiani, M., Ardeshiri, H., Bernardo, C., Kylling, A., Park, S.-Y., Pisso, I., Schmidbauer, N., Wasseng, J., and Stohl, A.: Observation of turbulent dispersion of artificially released SO2 puffs with UV cameras, Atmos. Meas. Tech., 11, 6169–6188, https://doi.org/10.5194/amt-11-6169-2018, 2018.
Gliss, J., Stebel, K., Kylling, A., Dinger, A. S., Sihler, H., & Sudbø, A.: Pyplis – A Python software toolbox for the analysis of SO2 camera images for emission rate retrievals from point sources. Geosciences, 7, 134, https://doi.org/10.3390/geosciences7040134, 2017.
Gliß, J., Stebel, K., Kylling, A., and Sudbø, A.: Improved optical flow velocity analysis in SO2 camera images of volcanic plumes – implications for emission-rate retrievals investigated at Mt Etna, Italy and Guallatiri, Chile, Atmos. Meas. Tech., 11, 781–801, https://doi.org/10.5194/amt-11-781-2018, 2018.