Monitoring the transport of biomass burning emission in South America

被引:23
|
作者
Pereira, Gabriel [1 ]
Shimabukuro, Yosio E. [1 ]
Moraes, Elisabete C. [1 ]
Freitas, Saulo R. [2 ]
Cardozo, Francielle S. [1 ]
Longo, Karla M. [3 ]
机构
[1] Natl Inst Space Res INPE, Remote Sensing Div, BR-12227010 Sao Jose Dos Campos, SP, Brazil
[2] Natl Inst Space Res INPE, Ctr Weather Forecasting & Climate Studies, BR-12227010 Sao Jose Dos Campos, SP, Brazil
[3] Natl Inst Space Res INPE, Ctr Space & Atmospher Sci, BR-12227010 Sao Jose Dos Campos, SP, Brazil
关键词
Biomass burned coefficient; Aerosol and trace gases emission; Fire radiative energy; FIRE RADIATIVE ENERGY; SMOKE PARTICLES; SATELLITE; AEROSOLS; CLIMATE; CLOUDS; BRAZIL; AREA; VARIABILITY; VEGETATION;
D O I
10.5094/APR.2011.031
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The main objective of this work is to use Fire Radiative Power (FRP) to estimate particulate matter with diameter less than 2.5 mu m (PM2.5) and carbon monoxide (CO) emissions for the South America 2002 burning season. Sixteen small-scale combustion experiments were performed near the Laboratory of Radiometry (LARAD) at the National Institute for Space Research (DSR/INPE) to obtain the coefficient that relates the biomass consumption with the FRP released. The fire products MOD14/MYD14 from the MODIS Terra/Aqua platforms and the Wildfire Automated Biomass Burning Algorithm (WFABBA) on the Geostationary Operational Environmental Satellite (GOES) were utilized to calculate the total amount of biomass burned. This inventory is modeled in the Coupled Chemistry-Aerosol-Tracer Transport model coupled to the Brazilian developments on the Regional Atmospheric Modeling System (CCATT-BRAMS) and compared with data collected in the Large Scale Biosphere-Atmosphere (LBA) Smoke, Aerosols, Clouds, rainfall, and Climate (SMOCC) and Radiation, Cloud, and Climate Interactions (RaCCI) Experiments. The relationship between the modeled PM2.5 and CO shows a good agreement with SMOCC/RaCCI data in the general pattern of temporal evolution. The results showed high correlations, with values between 0.80 and 0.95 (significant at 0.05 level by student t-test), for the CCATT-BRAMS simulations with PM2.5 and CO. Furthermore, the slope analysis reveals an underestimation of emission values with CCATT-BRAMS modeled values, 20-30% lower than observed data with discrepancies mainly on days with large fires. However, the underestimation is similar to the uncertainties in traditional emissions methods. (c) Author(s) 2011. This work is distributed under the Creative Commons Attribution 3.0 License.
引用
收藏
页码:247 / 254
页数:8
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