Persistent Hot Spot Detection and Characterisation Using SLSTR

Abstract

Gas flaring is a disposal process widely used in the oil extraction and processing industry. It consists in the burning of unwanted gas at the tip of a stack and due to its thermal characteristic and the thermal emission it is possible to observe and to quantify it from space. Spaceborne observations allows us to collect information across regions and hence to provide a base for estimation of emissions on global scale. We have successfully adapted the Visible Infrared Imaging Radiometer Suite (VIIRS) Nightfire algorithm for the detection and characterisation of persistent hot spots, including gas flares, to the Sea and Land Surface Temperature Radiometer (SLSTR) observations on-board the Sentinel-3 satellites. A hot event at temperatures typical of a gas flare will produce a local maximum in the night-time readings of the shortwave and mid-infrared (SWIR and MIR) channels of SLSTR. The SWIR band centered at 1.61 μm is closest to the expected spectral radiance maximum and serves as the primary detection band. The hot source is characterised in terms of temperature and area by fitting the sum of two Planck curves, one for the hot source and another for the background, to the radiances from all the available SWIR, MIR and thermal infra-red channels of SLSTR. The flaring radiative power is calculated from the gas flare temperature and area. Our algorithm differs from the original VIIRS Nightfire algorithm in three key aspects: (1) It uses a granule-based contextual thresholding to detect hot pixels, being independent of the number of hot sources present and their intensity. (2) It analyses entire clusters of hot source detections instead of individual pixels. This is arguably a more comprehensive use of the available information. (3) The co-registration errors between hot source clusters in the different spectral bands are calculated and corrected. This also contributes to the SLSTR instrument validation. Cross-comparisons of the new gas flare characterisation with temporally close observations by the higher resolution German FireBIRD TET-1 small satellite and with the Nightfire product based on VIIRS on-board the Suomi-NPP satellite show general agreement for an individual flaring site in Siberia and for several flaring regions around the world. Small systematic differences to VIIRS Nightfire are nevertheless apparent. Based on the hot spot characterisation, gas flares can be identified and flared gas volumes and pollutant emissions can be calculated with previously published methods.

Gas flaring activity and black carbon emissions in 2017 derived from Sentinel-3A SLSTR

“…The average temperature at the flaring locations approximately ranges from 950 K to 2250 K. This is slightly lower than the range reported by Liu et al (2018) who used Visible Infrared Imaging Radiometer Suite (VIIRS) Nightfire data, as expected from our previous study (Caseiro et al, 2018). It confirms the bi-modal distribution with modes around 1750 K and 1200 K 5 that is has also been observed by VIIRS.…”

“…We already tested the method using oil and/or gas producing regions within a limited timespan and compared the results to the VIIRS Nightfire "flares only" product (Caseiro et al, 2018). The results showed a good agreement of our hot source detection when investigating persistent hot spots with the advantage of the Sentinel-3A's SLSTR algorithm in detecting and 25 quantifying smaller flares, due to the night-time availability of a second SWIR channel.…”

“…We base our work on the persistent hot spots detection and characterisation algorithm described in Caseiro et al (2018) to process a full year (2017) of Sentinel-3A's Sea and Land Surface Temperature Radiometer (SLSTR) data. Using radiometrically calibrated radiance data as input, our algorithm detects hot spots and fits the sum of two Planck curves: one representing the hot source and the other the cool background.…”

“…This is a spatial resolution which reflects 10 the reality on the ground, where several flares, separated by tens to hundreds of meters, may be operated within a single oil and gas facility, while facilities are tens of kilometers apart. The following quantities are then computed for each grid cell: the number of hot spot detections (n Obs ), the number of high-accuracy (Caseiro et al, 2018) hot spot detections (n ObsHA ), the minimum, maximum, average and standard deviation of the high-accuracy hot spot retrieved temperature (T ), area (A) and radiative power (RP ) as well as the earliest and the latest hot spot observation date.…”

“…Noise, such as detections in the open ocean and the South Atlantic anomaly, is filtered out when considering only the high- 5 accuracy hot spots as defined by Caseiro et al (2018). There are 95906 high-accuracy hot spots in the dataset.…”