Abstract. Landscape fires show large variability in the amount of biomass or fuel consumed per unit area burned. Fuel consumption (FC) depends on the biomass available to burn and the fraction of the biomass that is actually combusted, and can be combined with estimates of area burned to assess emissions. While burned area can be detected from space and estimates are becoming more reliable due to improved algorithms and sensors, FC is usually modeled or taken selectively from the literature. We compiled the peerreviewed literature on FC for various biomes and fuel categories to understand FC and its variability better, and to provide a database that can be used to constrain biogeochemical models with fire modules. We compiled in total 77 studies covering 11 biomes including savanna (15 studies, average FC of 4.6 t DM (dry matter) ha −1 with a standard deviation of 2.2), tropical forest (n = 19, FC = 126 ± 77), temperate forest (n = 12, FC = 58 ± 72), boreal forest (n = 16, FC = 35 ± 24), pasture (n = 4, FC = 28 ± 9.3), shifting cultivation (n = 2, FC = 23, with a range of 4.0-43), crop residue (n = 4, FC = 6.5 ± 9.0), chaparral (n = 3, FC = 27 ± 19), tropical peatland (n = 4, FC = 314 ± 196), boreal peatland (n = 2, FC = 42 [42-43]), and tundra (n = 1, FC = 40). Within biomes the regional variability in the number of measurements was sometimes large, with e.g. only three measurement locations in boreal Russia and 35 sites in North America. Substantial regional differences in FC were found within the defined biomes: for example, FC of temperate pine forests in the USA was 37 % lower than Australian forests dominated by eucalypt trees. Besides showing the differences between biomes, FC estimates were also grouped into different fuel classes. Our results highlight the large variability in FC, not only between biomes but also within biomes and fuel classes. This implies that substantial uncertainties are associated with using biome-averaged values to represent FC for whole biomes. Comparing the compiled FC values with co-located Global Fire Emissions Database version 3 (GFED3) FC indicates that modeling studies that aim to represent variability in FC also within biomes, still require improvements as they have difficulty in representing the dynamics governing FC.

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).

Abstract. Landscape fires show large variability in the amount of biomass or fuel consumed per unit area burned. These fuel consumption (FC) rates depend on the biomass available to burn and the fraction of the biomass that is actually combusted, and can be combined with estimates of area burned to assess emissions. While burned area can be detected from space and estimates are becoming more reliable due to improved algorithms and sensors, FC rates are either modeled or taken selectively from the literature. We compiled the peer-reviewed literature on FC rates for various biomes and fuel categories to better understand FC rates and variability, and to provide a~database that can be used to constrain biogeochemical models with fire modules. We compiled in total 76 studies covering 10 biomes including savanna (15 studies, average FC of 4.6 t DM (dry matter) ha−1), tropical forest (n = 19, FC = 126), temperate forest (n = 11, FC = 93), boreal forest (n = 16, FC = 39), pasture (n = 6, FC = 28), crop residue (n = 4, FC = 6.5), chaparral (n = 2, FC = 32), tropical peatland (n = 4, FC = 314), boreal peatland (n = 2, FC = 42), and tundra (n = 1, FC = 40). Within biomes the regional variability in the number of measurements was sometimes large, with e.g. only 3 measurement locations in boreal Russia and 35 sites in North America. Substantial regional differences were found within the defined biomes: for example FC rates of temperate pine forests in the USA were 38% higher than Australian forests dominated by eucalypt trees. Besides showing the differences between biomes, FC estimates were also grouped into different fuel classes. Our results highlight the large variability in FC rates, not only between biomes but also within biomes and fuel classes. This implies that care should be taken with using averaged values, and our comparison with FC rates from GFED3 indicates that also modeling studies have difficulty in representing the dynamics governing FC.

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.