Estimates of Biomass Burning Particulate Matter (PM2.5) Emissions from the GOES Imager
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Estimates of Biomass Burning Particulate Matter (PM2.5) Emissions from the GOES Imager 0 20 40 60 80 100 3 45 87 129 171 213 255 297 339 17 59 101 143 185 227 269 311 353 31 73 115 157 199 241 283 325 3 45 87 129 171 213 255 297 339 D ay ofyear VCI 0 1 2 3 4 5 M oisturecatogery Needle leaf forests in the western USA Grass in the western USA Shrubsin the western U SA Broadleaf forests in the eastern U SA M ixed forests in the eastern U SA 2002 2005 2004 2003 Xiaoyang Zhang , Shobha Kondragunta, and Chris Schmidt Fuel loading derived from MODIS land product Fuel Moisture category derived from weekly NOAA GVIx vegetation health condition Half hourly PM2.5 emissions from GOES fires Annual PM2.5 emissions from GOES fires
description
Estimates of Biomass Burning Particulate Matter (PM2.5) Emissions from the GOES Imager. Xiaoyang Zhang , Shobha Kondragunta, and Chris Schmidt. Fuel Moisture category derived from weekly NOAA GVIx vegetation health condition. Fuel loading derived from MODIS land product. - PowerPoint PPT Presentation
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Estimates of Biomass Burning Particulate Matter (PM2.5) Emissions from the GOES Imager
0
20
40
60
80
100
3 45 87 129
171
213
255
297
339
17 59 101
143
185
227
269
311
353
31 73 115
157
199
241
283
325
3 45 87 129
171
213
255
297
339
Day of year
VC
I
0
1
2
3
4
5
Moi
stur
e ca
toge
ry
Needle leaf forests in the western USA Grass in the western USAShrubs in the western USA Broadleaf forests in the eastern USAMixed forests in the eastern USA
2002 200520042003
Xiaoyang Zhang , Shobha Kondragunta, and Chris Schmidt
Fuel loading derived from MODIS land product
Fuel Moisture category derived from weekly NOAA GVIx vegetation health condition
Half hourly PM2.5 emissions from GOES fires
Annual PM2.5 emissions from GOES fires