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The goal is to foster understanding of complex fire emission system dynamics and feedbacks.
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The modeling system used spatial estimates of wildland fire emission (kg PM/m) computed in the Wildland Fire Emissions Information System (WFEIS; Figure 1a) for specific times across Southern California as inputs to the transport model.
The error bars associated with the fire emission estimates represent the standard deviation of the annual emissions for 2002 2006.
The validation of fire emission estimates is difficult, since the emissions from fire to fire are highly variable, and direct flux measurements from fires are extremely difficult.
CW performed the fire emission estimates and processed the DOE FFB emissions and the NPP data.
Inverse modeling of fire emissions using in situ measurements or satellite observations provides a means to constrain fire emission estimates: however, these methods can not provide a direct quantification of emissions from fires.
An analysis of the fire emission estimates presented here shows that the majority of the emissions from fires in the US are from needleleaf forests.
The Southeastern and Western states have the largest amount of CO2 from fires: Alabama, Florida, Georgia, Louisiana, and Washington all have an average annual fire emission > 75 metric ton CO2 km-2.
The Northeastern states have the least amount of emissions per area: Vermont, Rhode Island, Maine, and New Hampshire all have an average annual fire emission of <1 metric ton CO2 km-2.
Forest fire emissions modify the chemical composition of the atmosphere and the earth's climate system.
Van Beuzekom used an automated microwave solvent extraction system (MASE) coupled to a liquid chromatograph for the analysis of fine particles from fire emissions [ 59].
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