Inventories for global aerosol and aerosol precursor emissions have been collected (based on published inventories and published simulations), assessed and prepared for the year 2000 (present-day conditions) and for the year 1750 (pre-industrial conditions). These global datasets establish a comprehensive source for emission input to global modeling, when simulating the aerosol impact on climate with state-of-the-art aerosol component modules. As these modules stratify aerosol into dust, sea-salt, sulfate, organic matter and soot, for all these aerosol types global fields on emission strength and recommendations for injection altitude and particulate size are provided. Temporal resolution varies between daily (dust and sea-salt), monthly (wild-land fires) and annual (all other emissions). These datasets benchmark aerosol emissions according to the knowledge in the year 2004. They are intended to serve as systematic constraints in sensitivity studies of the AeroCom initiative, which seeks to quantify (actual) uncertainties in aerosol global modeling.

In many regions of the world, fires are an important and highly variable source of air pollutant emissions, and they thus constitute a significant if not dominant factor controlling the interannual variability of the atmospheric composition. This paper describes the 41‐year inventory of vegetation fire emissions constructed for the Reanalysis of the Tropospheric chemical composition over the past 40 years project (RETRO), a global modeling study to investigate the trends and variability of tropospheric ozone and other air pollutants over the past decades. It is the first attempt to construct a global emissions data set with monthly time resolution over such a long period. The inventory is based on a literature review, on estimates from different satellite products, and on a numerical model with a semiphysical approach to simulate fire occurrence and fire spread. Burned areas, carbon consumption, and total carbon release are estimated for 13 continental‐scale regions, including explicit treatment of some major burning events such as Indonesia in 1997 and 1998. Global carbon emissions from this inventory range from 1410 to 3140 Tg C/a with the minimum and maximum occurring in 1974 and 1992, respectively (mean of 2078 Tg C/a). Emissions of other species are also reported (mean CO of 330 Tg/a, NO_xof 4.6 Tg N/a, CH₂O of 3.9 Tg/a, CH₄of 15.4 Tg/a, BC of 2.2 Tg/a, OC of 17.6 Tg/a, SO₂of 2.2 Tg/a). The uncertainties of these estimates remain high even for later years where satellite data products are available. Future versions of this inventory may benefit from ongoing analysis of burned areas from satellite data going back to 1982.

The new Global Wildland Fire Emission Model (GWEM) has been developed on the basis of data from the European Space Agency's monthly Global Burnt Scar satellite product (GLOBSCAR) and results from the Lund‐Potsdam‐Jena Dynamic Global Vegetation Model (LPJ‐DGVM). GWEM computes monthly emissions of more than 40 chemical compounds and aerosols from forest and savanna fires. This study focuses on an evaluation of the GLOBSCAR data set. The GWEM version presented here makes use of the Moderate‐Resolution Imaging Spectroradiometer (MODIS) land cover map. Emission totals for the year 2000 are 1741 Tg C, 5716 Tg CO₂, 271 Tg CO, 12.52 Tg CH₄, 9.09 Tg C (as nonmethane hydrocarbons), 8.08 Tg NO_x (as NO), 24.30 Tg PM_2.5, 15.80 Tg OC, and 1.84 Tg black carbon. These emissions are lower than other estimates found in literature. An evaluation assesses the uncertainties of the individual input data. The GLOBSCAR product yields reasonable estimates of burnt area for large wildland fires in most parts of the globe but experiences problems in some regions where small fires dominate. The seasonality derived from GLOBSCAR differs from other satellite products detecting active fires owing to the different algorithms applied. Application of the presented GWEM results in global chemistry transport modeling will require additional treatment of small deforestation fires in the tropical rain forest regions and small savanna fires, mainly in subequatorial Africa. Further improvements are expected from a more detailed description of the carbon pools and the inclusion of anthropogenic disturbances in the LPJ model.

Quantifying the contribution of biomass burning to the global distribution of emissions of carbon into the atmosphere requires knowledge of the area burnt. The GLOBSCAR project was initiated in 2001 as part of the European Space Agency (ESA) Data User Programme, with the objective of producing global incremental monthly maps of burnt areas, using daytime data from year 2000 of the Along Track Scanning Radiometer (ATSR‐2) instrument onboard the ESA ERS‐2 satellite. The processing system combines the use of two algorithms representing different approaches to burnt area detection. The K1 algorithm is a contextual algorithm based on the geometrical characteristics of the burnt pixels in the near‐infrared (NIR, 0.87 microns)/thermal infrared (TIR, 11 microns) space, while the E1 algorithm consists of a series of fixed threshold tests applied to the data using information from four different spectral channels. The GLOBSCAR products are available from the GeoSuccess Web site (http://www.geosuccess.net) in ASCII and vector format. The products were validated using a variety of qualitative and quantitative tests against other field and remote sensing data. The GLOBSCAR results are presented per region and are compared to available statistics and other remote sensing products such as the ATSR‐2 World Fire Atlas (WFA) and the Global Burnt Area product derived from SPOT/VEGETATION (GBA‐2000). The potential and limitations of the GLOBSCAR products are then discussed. It is concluded that while the GLOBSCAR products represent a definite progress toward a better quantification of the areas burnt annually at the larger scales, coordinated improvements in remote sensing products are needed in order to better address the requirements of the user community. Future activities include the consolidation of the results through further qualification and the development of a multiyear multisensor product building upon the experience gained from both GLOBSCAR and GBA‐2000 projects.