DETERMINING REGIONAL CARBON EMISSIONS UNDER VARIABLE FIRE REGIMES IN CENTRAL SIBERIA D.J. McRae 1, S.G. Conard 2, G.A. Ivanova 3, S.P. Baker 4, A.I. Sukhinin 3, W.M. Hao 4, and T.W. Blake 1 For more information contact: 1 Canadian Forest Service, 1219 Queen St. E., Sault Ste. Marie, ON. P6A 2E5 Contact: Douglas J. McRae, Telephone: ; Tom W. Blake, Telephone: ; 2 USDA Forest Service, RPC-4, 1601 N. Kent St., Arlington, VA Contact: Susan G. Conard, Telephone: ; 3 V.N. Sukachev Institute of Forest Research, Akademgorodok, Krasnoyarsk Russia. Contact: Galina A. Ivanova, Telephone: ; Anatoly I. Sukhinin, Telephone: ; 4 USDA Forest Service, Fire Sciences Laboratory, 5775 US Highway 10 West, Missoula, MT Contact: Wei Min Hao, Telephone: ; Steve P. Baker, Telephone: ; Low-intensity surface fire burning in a Siberian Scots pine forest. Eighty percent of fires in a typical year burn as surface fires, which in many cases will not cause any damage to the mature trees. NASA’s Land Cover Land Use Change Program FACTS The Russian boreal forest contains up to 20% of the global terrestrial carbon storage. Wildfires affect from million ha annually in typical burning years. Fires are projected to increase in both frequency and severity across Siberia under climate change. Fire behavior and impacts are highly variable across this landscape. Information on fire severity and its effects on factors such as emissions, carbon storage, and ecosystem recovery are scarce. Carbon emissions are roughly 45-50% of the fuel consumed during a fire, which can be modeled from fire data. AGU Fall Meeting 11 December 2007 Paper Number: GC23A-0999 Results to date are: RUSSIAN FIRE BEAR (Fire Effects in the Boreal Eurasia Region) PROJECT A major goal of this project is to provide fire data and models required to estimate carbon emissions from wildfires in central Siberia. Research is being carried out in Scots pine (Pinus sylvestris) and larch (Larix sp.) forest types, which together make up 58% of the forest area in the Asian portion of Russia. The overall objective of this research is to develop validated estimates of fire areas, fire severity, emissions, and the impact of fire on carbon balance for key forest types of central Siberia. This project is building on our past research efforts in Scots pine forests ( ), while initiating similar research in larch forests by: Quantifying and modeling effects of different severity fires on Scots pine sites to estimate effects of fire severity on carbon cycle, direct fire emissions, and forest dynamics. Developing models relating fire behavior, fire weather, and fuel condition at the time of burning to carbon emissions, energy release, and other ecosystem impacts. Evaluating the potential for estimating emissions directly from satellite infrared channels through relationships between the fire’s energy release and its emissions. 20 experimental fires have been conducted in central Siberia. Fire behavior (e.g., fire spread) models have been created. Carbon emission (i.e., from fuel consumption data) models have been created. Emissions sampling has quantified the composition of carbon and aerosols in the smoke. PROBLEMS Changes in boreal fire regimes can be expected to lead to large changes in patterns of burn severity, with attendant effects on emissions per unit burned area and on postfire vegetation recovery. Developing accurate regional to continental estimates of carbon emissions from wildfires in Siberia requires the collection of data and creation of models that will enable us to accurately quantify not only the areas that are burned annually, but the emissions per unit of burned area for fires of widely varying characteristics. Estimates of fire emissions must account for the heterogeneous nature of fire behavior. This is due to the constant changes in daily burning conditions (e.g., drought), topography, and wildland fuel types. While remote sensing has been proven in estimating burn area, the direct estimate of carbon emissions from satellite images may not be possible as fuel consumption cannot be determined. Satellite images provide an excellent means of obtaining burned area estimates. Polygon outlines represent burn areas with red shading showing locations where active fires are burning. Arrows show areas of saturation that differentiate between crown fires and surface fires. While satellite images can determine specific fire types, they cannot determine actual fuel consumption which is imperative in estimating carbon emissions. QUESTION How can accurate estimates of carbon emissions from biomass burning be made to better understand the contribution of Russian fires to greenhouse gases? 15 June 2003 APPROACH FOR ESTIMATING EMISSIONS 1. Determination of burned area through remote- sensing analysis. Red polygons indicate areas that have burned between June 6-16, Gray polygons indicate areas that have already burned in the current fire season. 2. Creation of carbon emission models from experimental fire results which documented fuel consumption (~50% carbon content). 3. Determination of the Canadian Fire Weather Index (FWI) at target sites in central Siberia coinciding with fires shown in Figure 1. Note how the location of fire hot spots, depicted in yellow from Figure 1, correlate well with the high FWI values found in this region. Estimated ranges in carbon emissions for fires burning at the different FWI in the figure are based on data from Figure Carbon emissions (t/ha) Fire Weather Index TAKE-HOME MESSAGE Remote-sensing, by itself, cannot be used to determine emissions. Carbon emission models have been created for Russian Scots pine forest types. A Russian fire danger database ( ) has been created allowing us to use our model for estimating emissions for any year, provided we have fire size and location information. The ranges of emission factors (EF) for the major carbon emission products for these fires were correlated with the FWI for each fire. Higher EF values for CO 2 and modified combustion efficiency (MCE) occurred with increasing FWI values. At the same time, EF values for CO and CH 4 were observed to decrease. Carbon emissions = (0.554*FWI) R 2 = 0.82