The Tropical Forest and Fire Emissions Experiment (TROFFEE) used laboratory measurements followed by airborne and ground based field campaigns during the 2004 Amazon dry season to quantify the emissions from pristine tropical forest and several plantations as well as the emissions, fuel consumption, and fire ecology of tropical deforestation fires. The airborne campaign used an Embraer 110B aircraft outfitted with whole air sampling in canisters, mass-calibrated nephelometry, ozone by UV absorbance, Fourier transform infrared spectroscopy (FTIR), and proton-transfer mass spectrometry (PTR-MS) to measure PM10, O-3, CO2, CO, NO, NO2, HONO, HCN, NH3, OCS, DMS, CH4, and up to 48 non-methane organic compounds (NMOC). The Brazilian smoke/haze layers extended to 2 - 3 km altitude, which is much lower than the 5 - 6 km observed at the same latitude, time of year, and local time in Africa in 2000. Emission factors (EF) were computed for the 19 tropical deforestation fires sampled and they largely compare well to previous work. However, the TROFFEE EF are mostly based on a much larger number of samples than previously available and they also include results for significant emissions not previously reported such as: nitrous acid, acrylonitrile, pyrrole, methylvinylketone, methacrolein, crotonaldehyde, methylethylketone, methylpropanal, '' acetol plus methylacetate,'' furaldehydes, dimethylsulfide, and C-1-C-4 alkyl nitrates. Thus, we recommend these EF for all tropical deforestation fires. The NMOC emissions were similar to 80% reactive, oxygenated volatile organic compounds (OVOC). Our EF for PM10 (17.8 +/- 4 g/kg) is similar to 25% higher than previously reported for tropical forest fires and may reflect a trend towards, and sampling of, larger fires than in earlier studies. A large fraction of the total burning for 2004 likely occurred during a two-week period of very low humidity. The combined output of these fires created a massive '' mega-plume '' > 500 km across that we sampled on 8 September. The mega-plume contained high PM10 and 10 - 50 ppbv of many reactive species such as O-3, NH3, NO2, CH3OH, and organic acids. This is an intense and globally important chemical processing environment that is still poorly understood. The mega-plume or '' white ocean '' of smoke covered a large area in Brazil, Bolivia, and Paraguay for about one month. The smoke was transported > 2000 km to the southeast while remaining concentrated enough to cause a 3 - 4-fold increase in aerosol loading in the S (a) over tildeo Paulo area for several days.

Attribution of the causes of atmospheric trace gas and aerosol variability often requires the use of high resolution time series of anthropogenic and natural emissions inventories. Here we developed an approach for representing synoptic- and diurnal-scale temporal variability in fire emissions for the Global Fire Emissions Database version 3 (GFED3). We disaggregated monthly GFED3 emissions during 2003–2009 to a daily time step using Moderate Resolution Imaging Spectroradiometer (MODIS)-derived measurements of active fires from Terra and Aqua satellites. In parallel, mean diurnal cycles were constructed from Geostationary Operational Environmental Satellite (GOES) Wildfire Automated Biomass Burning Algorithm (WF_ABBA) active fire observations. Daily variability in fires varied considerably across different biomes, with short but intense periods of daily emissions in boreal ecosystems and lower intensity (but more continuous) periods of burning in savannas. These patterns were consistent with earlier field and modeling work characterizing fire behavior dynamics in different ecosystems. On diurnal timescales, our analysis of the GOES WF_ABBA active fires indicated that fires in savannas, grasslands, and croplands occurred earlier in the day as compared to fires in nearby forests. Comparison with Total Carbon Column Observing Network (TCCON) and Measurements of Pollution in the Troposphere (MOPITT) column CO observations provided evidence that including daily variability in emissions moderately improved atmospheric model simulations, particularly during the fire season and near regions with high levels of biomass burning. The high temporal resolution estimates of fire emissions developed here may ultimately reduce uncertainties related to fire contributions to atmospheric trace gases and aerosols. Important future directions include reconciling top-down and bottom up estimates of fire radiative power and integrating burned area and active fire time series from multiple satellite sensors to improve daily emissions estimates.