ALBERT

Description: New burned area datasets and top-down constraints from atmospheric concentration measurements of pyrogenic gases have decreased the large uncertainty in fire emissions estimates. However, significant gaps remain in our understanding of the contribution of deforestation, savanna, forest, agricultural waste, and peat fires to total global fire emissions. Here we used a revised version of the Carnegie-Ames-Stanford-Approach (CASA) biogeochemical model and improved satellite-derived estimates of area burned, fire activity, and plant productivity to calculate fire emissions for the 1997–2009 period on a 0.5° spatial resolution with a monthly time step. For November 2000 onwards, estimates were based on burned area, active fire detections, and plant productivity from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. For the partitioning we focused on the MODIS era. We used burned area estimates based on Tropical Rainfall Measuring Mission (TRMM) Visible and Infrared Scanner (VIRS) and Along-Track Scanning Radiometer (ATSR) active fire data prior to MODIS (1997–2000) and Advanced Very High Resolution Radiometer (AVHRR) derived estimates of plant productivity during the same period. Average global fire carbon emissions were 2.0 Pg yr−1 with significant interannual variability during 1997–2001 (2.8 Pg yr−1 in 1998 and 1.6 Pg yr−1 in 2001). Emissions during 2002–2007 were relatively constant (around 2.1 Pg yr−1) before declining in 2008 (1.7 Pg yr−1) and 2009 (1.5 Pg yr−1) partly due to lower deforestation fire emissions in South America and tropical Asia. During 2002–2007, emissions were highly variable from year-to-year in many regions, including in boreal Asia, South America, and Indonesia, but these regional differences cancelled out at a global level. During the MODIS era (2001–2009), most fire carbon emissions were from fires in grasslands and savannas (44%) with smaller contributions from tropical deforestation and degradation fires (20%), woodland fires (mostly confined to the tropics, 16%), forest fires (mostly in the extratropics, 15%), agricultural waste burning (3%), and tropical peat fires (3%). The contribution from agricultural waste fires was likely a lower bound because our approach for measuring burned area could not detect all of these relatively small fires. For reduced trace gases such as CO and CH4, deforestation, degradation, and peat fires were more important contributors because of higher emissions of reduced trace gases per unit carbon combusted compared to savanna fires. Carbon emissions from tropical deforestation, degradation, and peatland fires were on average 0.5 Pg C yr−1. The carbon emissions from these fires may not be balanced by regrowth following fire. Our results provide the first global assessment of the contribution of different sources to total global fire emissions for the past decade, and supply the community with an improved 13-year fire emissions time series.

Description: Fires are a major source of trace gases and aerosols to the atmosphere. The amount of biomass burned is becoming better known, most importantly due to improved burned area datasets and a better representation of fuel consumption. The spatial and temporal variability in the partitioning of biomass burned into emitted trace gases and aerosols, however, has received relatively little attention. To convert estimates of biomass burned to trace gas and aerosol emissions, most studies have used emission ratios (or emission factors (EFs)) based on the arithmetic mean of field measurement outcomes, stratified by biome. However, EFs vary substantially in time and space, even within a single biome. In addition, it is unknown whether the available field measurement locations provide a representative sample for the various biomes. Here we used the available body of EF literature in combination with satellite-derived information on vegetation characteristics and climatic conditions to better understand the spatio-temporal variability in EFs. While focusing on CO, CH4, and CO2, our findings are also applicable to other trace gases and aerosols. We explored relations between EFs and different measurements of environmental variables that may correlate with part of the variability in EFs (tree cover density, vegetation greenness, temperature, precipitation, and the length of the dry season). Although reasonable correlations were found for specific case studies, correlations based on the full suite of available measurements were lower and explained about 33%, 38%, 19%, and 34% of the variability for respectively CO, CH4, CO2, and the Modified Combustion Efficiency (MCE). This may be partly due to uncertainties in the environmental variables, differences in measurement techniques for EFs, assumptions on the ratio between flaming and smoldering combustion, and incomplete information on the location and timing of EF measurements. We derived new mean EFs, using the relative importance of each measurement location with regard to fire emissions. These weighted averages were relatively similar to the arithmetic mean. When using relations between the environmental variables and EFs to extrapolate to regional and global scales, we found substantial differences, with for savannas 13% and 22% higher CO and CH4 EFs than the arithmetic mean of the field studies, possibly linked to an underrepresentation of woodland fires in EF measurement locations. We argue that from a global modeling perspective, future measurement campaigns could be more beneficial if measurements are made over the full fire season, and if relations between ambient conditions and EFs receive more attention.

Description: New burned area datasets and top-down constraints from atmospheric concentration measurements of pyrogenic gases have decreased the large uncertainty in fire emissions estimates. However, significant gaps remain in our understanding of the contribution of deforestation, savanna, forest, agricultural waste, and peat fires to total global fire emissions. Here we used a revised version of the Carnegie-Ames-Stanford-Approach (CASA) biogeochemical model and improved satellite-derived estimates of area burned, fire activity, and plant productivity to calculate fire emissions for the 1997–2009 period on a 0.5° spatial resolution with a monthly time step. For November 2000 onwards, estimates were based on burned area, active fire detections, and plant productivity from the MODerate resolution Imaging Spectroradiometer (MODIS) sensor. For the partitioning we focused on the MODIS era. We used maps of burned area derived from the Tropical Rainfall Measuring Mission (TRMM) Visible and Infrared Scanner (VIRS) and Along-Track Scanning Radiometer (ATSR) active fire data prior to MODIS (1997–2000) and estimates of plant productivity derived from Advanced Very High Resolution Radiometer (AVHRR) observations during the same period. Average global fire carbon emissions according to this version 3 of the Global Fire Emissions Database (GFED3) were 2.0 Pg C year−1 with significant interannual variability during 1997–2001 (2.8 Pg C year−1 in 1998 and 1.6 Pg C year−1 in 2001). Globally, emissions during 2002–2007 were relatively constant (around 2.1 Pg C year−1) before declining in 2008 (1.7 Pg C year−1) and 2009 (1.5 Pg C year−1) partly due to lower deforestation fire emissions in South America and tropical Asia. On a regional basis, emissions were highly variable during 2002–2007 (e.g., boreal Asia, South America, and Indonesia), but these regional differences canceled out at a global level. During the MODIS era (2001–2009), most carbon emissions were from fires in grasslands and savannas (44%) with smaller contributions from tropical deforestation and degradation fires (20%), woodland fires (mostly confined to the tropics, 16%), forest fires (mostly in the extratropics, 15%), agricultural waste burning (3%), and tropical peat fires (3%). The contribution from agricultural waste fires was likely a lower bound because our approach for measuring burned area could not detect all of these relatively small fires. Total carbon emissions were on average 13% lower than in our previous (GFED2) work. For reduced trace gases such as CO and CH4, deforestation, degradation, and peat fires were more important contributors because of higher emissions of reduced trace gases per unit carbon combusted compared to savanna fires. Carbon emissions from tropical deforestation, degradation, and peatland fires were on average 0.5 Pg C year−1. The carbon emissions from these fires may not be balanced by regrowth following fire. Our results provide the first global assessment of the contribution of different sources to total global fire emissions for the past decade, and supply the community with an improved 13-year fire emissions time series.

Description: 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.

Description: Recent studies based on trace gas mixing ratios in ice cores and charcoal data indicate that biomass burning emissions over the past millennium exceeded contemporary emissions by up to a factor of 4 for certain time periods. This is surprising because various sources of biomass burning are linked with population density, which has increased over the past centuries. We have analysed how emissions from several landscape biomass burning sources could have fluctuated to yield emissions that are in correspondence with recent results based on ice core mixing ratios of carbon monoxide (CO) and its isotopic signature measured at South Pole station (SPO). Based on estimates of contemporary landscape fire emissions and the TM5 chemical transport model driven by present-day atmospheric transport and OH concentrations, we found that CO mixing ratios at SPO are more sensitive to emissions from South America and Australia than from Africa, and are relatively insensitive to emissions from the Northern Hemisphere. We then explored how various landscape biomass burning sources may have varied over the past centuries and what the resulting emissions and corresponding CO mixing ratio at SPO would be, using population density variations to reconstruct sources driven by humans (e.g., fuelwood burning) and a new model to relate savanna emissions to changes in fire return times. We found that to match the observed ice core CO data, all savannas in the Southern Hemisphere had to burn annually, or bi-annually in combination with deforestation and slash and burn agriculture exceeding current levels, despite much lower population densities and lack of machinery to aid the deforestation process. While possible, these scenarios are unlikely and in conflict with current literature. However, we do show the large potential for increased emissions from savannas in a pre-industrial world. This is mainly because in the past, fuel beds were probably less fragmented compared to the current situation; satellite data indicates that the majority of savannas have not burned in the past 10 yr, even in Africa, which is considered "the burning continent". Although we have not considered increased charcoal burning or changes in OH concentrations as potential causes for the elevated CO concentrations found at SPO, it is unlikely they can explain the large increase found in the CO concentrations in ice core data. Confirmation of the CO ice core data would therefore call for radical new thinking about causes of variable global fire rates over recent centuries.

Description: Recent studies based on trace gas mixing ratios in ice cores and charcoal data indicate that biomass burning emissions over the past millennium exceeded contemporary emissions by up to a factor of 4 for certain time periods. This is surprising because various sources of biomass burning are linked with population density, which has increased over the past centuries. Here we have analyzed how emissions from several biomass burning sources could have fluctuated to yield emissions that are in correspondence with recent results based on ice core mixing ratios of carbon monoxide (CO) and its isotopic signature measured at South Pole station (SPO). Based on estimates of contemporary fire emissions and the TM5 chemical transport model, we found that CO mixing ratios at SPO are more sensitive to emissions from South America and Australia than from Africa, and are relatively insensitive to emissions from the Northern Hemisphere. We then explored how various biomass burning sources may have varied over the past centuries and what the resulting emissions and corresponding CO mixing ratio at SPO would be, using population density variations to reconstruct sources driven by humans (e.g. fuelwood burning) and a new model to relate savanna emissions to changes in fire return times. We found that to match the observed ice core CO data all savannas in the Southern Hemisphere had to burn annually, or bi-annually in combination with deforestation and slash and burn agriculture matching current levels despite much lower population densities and lack of machinery to aid the deforestation process. While possible, these scenarios are unlikely and in conflict with current literature. However, we do show the large potential for increased emissions from savannas in a pre-industrial world. This is mainly because in the past, fuel beds were probably less fragmented compared to the current situation; we show that the majority of savannas have not burned in the past 10 yr, even in Africa which is considered "the burning continent". Our new modelling results, together with existing literature, indicate that no definitive conclusions can be drawn about unprecedentedly high or low biomass burning rates from current data analyses.

Description: Landscape fires occur on a large scale in (sub)tropical savannas and grasslands, affecting ecosystem dynamics, regional air quality and concentrations of atmospheric trace gasses. Fuel consumption per unit of area burned is an important but poorly constrained parameter in fire emission modelling. We combined satellite-derived burned area with fire radiative power (FRP) data to derive fuel consumption estimates for land cover types with low tree cover in South America, SubSaharan Africa, and Australia. We developed a new approach to estimate fuel consumption, based on FRP data from the polar orbiting MODerate-resolution Imaging Spectroradiometer (MODIS) and the geostationary Spinning Enhanced Visible and Infrared Imager (SEVIRI) in combination with MODIS burned area estimates. The fuel consumption estimates based on the geostationary and polar orbiting instruments showed good agreement in terms of spatial patterns, but absolute fuel consumption estimates remained more uncertain. Fuel consumption varies considerably in space and time, complicating the comparison of various approaches and using field measurements to constrain our results. Spatial patterns in fuel consumption could be partly explained by vegetation productivity and fire return periods. In South America, most fires occurred in savannas with relatively long fire return periods, resulting in comparatively high fuel consumption as opposed to the more frequently burning savannas in Sub-Saharan Africa. Strikingly, we found the infrequently burning interior of Australia having higher fuel consumption than the more productive but frequently burning savannas in northern Australia. Vegetation type also played an important role in explaining the distribution of fuel consumption, both by affecting fuel build up rates and fire return periods. Hummock grasslands, which were responsible for a large share of Australian biomass burning, showed larger fuel build up rates than equally productive grasslands in Africa, although this effect might have been partially driven by the presence of grazers in Africa. Finally, land management in the form of deforestation and agriculture also considerably affected fuel consumption regionally. We conclude that combining FRP and burned area estimates, calibrated against field measurements, is a promising approach in deriving quantitative estimates of fuel consumption. Satellite derived fuel consumption estimates may both challenge our current understanding of spatiotemporal fuel consumption dynamics and serve as reference datasets to improve biogeochemical modelling approaches. Future field studies especially designed to validate satellite-based products, or airborne remote sensing, may further improve confidence in the absolute fuel consumption estimates which are quickly becoming the weakest link in fire emissions estimates.