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.

Abstract. Gas flares are a regionally and globally significant source of atmospheric pollutants. They can be detected by satellite remote sensing. We calculate the global flared gas volume and black carbon emissions in 2017 by applying (1) a previously developed hot spot detection and characterisation algorithm to all observations of the Sea and Land Surface Temperature Radiometer (SLSTR) instrument on board the Copernicus satellite Sentinel-3A and (2) newly developed filters for identifying gas flares and corrections for calculating both flared gas volumes (billion cubic metres, BCM) and black carbon (BC) emissions (g). The filter to discriminate gas flares from other hot spots uses the observed hot spot characteristics in terms of temperature and persistence. A regression function is used to correct for the variability of detection opportunities. A total of 6232 flaring sites are identified worldwide. The best estimates of the annual flared gas volume and the BC emissions are 129 BCM with a confidence interval of [35, 419 BCM] and 73 Gg with a confidence interval of [20, 239 Gg], respectively. Comparison of our activity (i.e. BCM) results with those of the Visible Infrared Imaging Radiometer Suite (VIIRS) Nightfire data set and SWIR-based calculations show general agreement but distinct differences in several details. The calculation of black carbon emissions using our gas flaring data set with a newly developed dynamic assignment of emission factors lie in the range of recently published black carbon inventories, albeit towards the lower end. The data presented here can therefore be used e.g. in atmospheric dispersion simulations. The advantage of using our algorithm with Sentinel-3 data lies in the previously demonstrated ability to detect and quantify small flares, the long-term data availability from the Copernicus programme, and the increased detection opportunity of global gas flare monitoring when used in conjunction with the VIIRS instruments. The flaring activity and related black carbon emissions are available as “GFlaringS3” on the Emissions of atmospheric Compounds and Compilation of Ancillary Data (ECCAD) website (https://doi.org/10.25326/19, Caseiro and Kaiser, 2019).

Gas flaring is a disposal process widely used in the oil extraction and processing industry. It 1 consists in the burning of unwanted gas at the tip of a stack and due to its thermal characteristic and 2 the thermal emission it is possible to observe and to quantify it from space. Spaceborne observations 3 allows us to collect information across regions and hence to provide a base for estimation of emissions 4 on global scale. We have successfully adapted the Visible Infrared Imaging Radiometer Suite (VIIRS) 5 Nightfire algorithm for the detection and characterisation of persistent hot spots, including gas flares, 6 to the Sea and Land Surface Temperature Radiometer (SLSTR) observations on-board the Sentinel-3 7 satellites. A hot event at temperatures typical of a gas flare will produce a local maximum in the 8 night-time readings of the shortwave and mid-infrared (SWIR and MIR) channels of SLSTR. The 9 SWIR band centered at 1.61 µm is closest to the expected spectral radiance maximum and serves as the 10 primary detection band. The hot source is characterised in terms of temperature and area by fitting 11 the sum of two Planck curves, one for the hot source and another for the background, to the radiances 12 from all the available SWIR, MIR and thermal infra-red channels of SLSTR. The flaring radiative 13 power is calculated from the gas flare temperature and area. Our algorithm differs from the original 14 VIIRS Nightfire algorithm in three key aspects: (1) It uses a granule-based contextual thresholding to 15 detect hot pixels, being independent of the number of hot sources present and their intensity. (2) It 16 analyses entire clusters of hot source detections instead of individual pixels. This is arguably a more 17 comprehensive use of the available information. (3) The co-registration errors between hot source 18 clusters in the different spectral bands are calculated and corrected. This also contributes to the SLSTR 19 instrument validation. Cross-comparisons of the new gas flare characterisation with temporally close 20 observations by the higher resolution German FireBIRD TET-1 small satellite and with the Nightfire 21 product based on VIIRS on-board the Suomi-NPP satellite show general agreement for an individual 22 flaring site in Siberia and for several flaring regions around the world. Small systematic differences 23 to VIIRS Nightfire are nevertheless apparent. Based on the hot spot characterisation, gas flares can 24 be identified and flared gas volumes and pollutant emissions can be calculated with previously 25 published methods.26and global concern. GF impacts the local environment [1] through: noise [2,3], visual pollution [4,5], 31 heat stress [4,6] and the emission of air pollutants like black carbon, polycyclic aromatic hydrocarbons, 32 volatile organic compounds and acid rain precursors [7][8][9][10]. Flaring produces greenhouse gases (GHG) 33 and black carbon as the main by-products of the combustion. In terms of the global GHG budget 34 gas flaring produced an estimated yearly a...

Fire behavior is well described by a fire’s direction, rate of spread, and its energy release rate. Fire intensity as defined by Byram (1959) is the most commonly used term describing fire behavior in the wildfire community. It is, however, difficult to observe from space. Here, we assess fire spread and fire radiative power using infrared sensors with different spatial, spectral and temporal resolutions. The sensors used offer either high spatial resolution (Sentinel-2) for fire detection, but a low temporal resolution, moderate spatial resolution and daily observations (VIIRS), and high temporal resolution with low spatial resolution and fire radiative power retrievals (Meteosat SEVIRI). We extracted fire fronts from Sentinel-2 (using the shortwave infrared bands) and use the available fire products for S-NPP VIIRS and Meteosat SEVIRI. Rate of spread was analyzed by measuring the displacement of fire fronts between the mid-morning Sentinel-2 overpasses and the early afternoon VIIRS overpasses. We retrieved FRP from 15-min Meteosat SEVIRI observations and estimated total fire radiative energy release over the observed fire fronts. This was then converted to total fuel consumption, and, by making use of Sentinel-2-derived burned area, to fuel consumption per unit area. Using rate of spread and fuel consumption per unit area, Byram’s fire intensity could be derived. We tested this approach on a small number of fires in a frequently burning West African savanna landscape. Comparison to field experiments in the area showed similar numbers between field observations and remote-sensing-derived estimates. To the authors’ knowledge, this is the first direct estimate of Byram’s fire intensity from spaceborne remote sensing data. Shortcomings of the presented approach, foundations of an error budget, and potential further development, also considering upcoming sensor systems, are discussed.

Abstract. Gas flares are a regionally and globally significant source of atmospheric pollutants. They can be detected by satellite remote sensing. We calculate the global flared gas volume and black carbon emissions in 2017 by (1) applying a previously developed hot spot detection and characterisation algorithm to all observations of the Sea and Land Surface Temperature Radiometer (SLSTR) instrument on-board the Copernicus satellite Sentinel-3A in 2017 and (2) applying newly developed filters for identifying gas flares and corrections for calculating flared gas volumes (Billion Cubic Meters, BCM) and black carbon emission estimates. The filter to discriminate gas flares from other hot spots combines the unique flaring characteristics in terms of persistence and temperature. The comparison of our results with those of the Visible Infrared Imaging Radiometer Suite (VIIRS) nightfire data set indicates a good fit between the two methods. The calculation of black carbon emissions using our gas flaring data set and published emission factors show good agreement with recently published black carbon inventories. The data presented here can therefore be used e.g. in atmospheric dispersion simulations. The advantage of using our algorithm with Sentinel-3A data lies in the previously demonstrated ability to detect and quantify small flares and the foreseen long term data availability from the Copernicus program. Our data (GFlaringS3, flaring activity and the related black carbon emissions) are available on the Emissions of atmospheric Compounds and Compilation of Ancillary Data (ECCAD) web site (https://eccad3.sedoo.fr/#GFlaringS3, DOI https://doi.org/10.25326/19 (Caseiro and Kaiser, 2019)) for use in, e.g., atmospheric composition modelling studies.