Abstract
[1] To produce a new daily record of trace gas emissions from biomass burning events for the Brazilian Legal Amazon, we have combined satellite advanced very high resolution radiometer (AVHRR) data on fire counts together for the first time with vegetation greenness imagery as inputs to an ecosystem biomass model at 8 km spatial resolution. This analysis goes beyond previous estimates for reactive gas emissions from Amazon fires, owing to a more detailed geographic distribution estimate of vegetation biomass, coupled with daily fire activity for the region (original 1 km resolution), and inclusion of fire effects in extensive areas of the Legal Amazon (defined as the Brazilian states of Acre, Amapa, Amazonas, Maranhao, Mato Grosso, Para, Rondonia, Roraima, and Tocantins) covered by open woodland, secondary forests, savanna, and pasture vegetation. Results from our emissions model indicate that annual emissions from Amazon deforestation and biomass burning in the early 1990s total to 102 Tg yr−1 carbon monoxide (CO) and 3.5 Tg yr−1 nitrogen oxides (NOx). Peak daily burning emissions, which occurred in early September 1992, were estimated at slightly more than 3 Tg d−1for CO and 0.1 Tg d−1for NOx flux to the atmosphere. Other burning source fluxes of gases with relatively high emission factors are reported, including methane (CH4), nonmethane hydrocarbons (NMHC), and sulfur dioxide (SO2), in addition to total particulate matter (TPM). We estimate the Brazilian Amazon region to be a source of between one fifth and one third for each of these global emission fluxes to the atmosphere. The regional distribution of burning emissions appears to be highest in the Brazilian states of Maranhao and Tocantins, mainly from burning outside of moist forest areas, and in Para and Mato Grosso, where we identify important contributions from primary forest cutting and burning. These new daily emission estimates of reactive gases from biomass burning fluxes are designed to be used as detailed spatial and temporal inputs to computer models and data analysis of tropospheric chemistry over the tropical region.
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