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Data analysis from remote sensing to...
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Kampe, Thomas U.
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Data analysis from remote sensing to better constrain emission and transport of carbonaceous aerosol and carbon monoxide resulting from burning processes.
紀錄類型:
書目-語言資料,印刷品 : Monograph/item
正題名/作者:
Data analysis from remote sensing to better constrain emission and transport of carbonaceous aerosol and carbon monoxide resulting from burning processes./
作者:
Kampe, Thomas U.
面頁冊數:
302 p.
附註:
Adviser: Irina N. Sokolik.
Contained By:
Dissertation Abstracts International69-03B.
標題:
Atmospheric Sciences. -
電子資源:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3308675
ISBN:
9780549558293
Data analysis from remote sensing to better constrain emission and transport of carbonaceous aerosol and carbon monoxide resulting from burning processes.
Kampe, Thomas U.
Data analysis from remote sensing to better constrain emission and transport of carbonaceous aerosol and carbon monoxide resulting from burning processes.
- 302 p.
Adviser: Irina N. Sokolik.
Thesis (Ph.D.)--University of Colorado at Boulder, 2008.
The production of atmospheric pollution has been increasing significantly since the advent of the industrial age. After fossil fuel combustion, biomass burning is the second largest source of anthropogenic fine mode aerosols and possibly the largest source of black carbon particles. Biomass burning is a significant source of greenhouse gases as well as ozone precursor gases including CO. Satellite remote sensing offers the best approach for obtaining global measurements of tropospheric trace gases and aerosols to assess the impacts of biomass burning emissions on air quality, atmospheric chemistry and climate. Given a growing interest in the development of modeling tools capable of predicting emission sources and transport of gases and particulates in the atmosphere, satellite data can potentially provide useful information for testing and validating chemical transport models. We use data from multiple satellite sensors to estimate emissions of carbonaceous aerosol for several biomes from around the globe using the slope of the regression of fine mode aerosol optical depth tauf to CO (Deltatauf/DeltaCO). We find Deltatauf/DeltaCO slopes calculated for Eastern Siberian boreal fires are 1.5 times greater than those for North American boreal fires, and two to three times larger than those calculated for deforestation fires in South America or African savanna burning. Our results show that different measures of fine mode aerosol thickness strongly affect the Deltatau f/DeltaCO slope. Deltatauf/DeltaCO slopes calculated using the MODIS Collection 5 aerosol algorithm are consistently larger over ocean and land when compared to estimates of Deltatauf/DeltaCO obtained using the submicrometer fraction algorithm. Estimates using the MODIS Collection 5 algorithm are in better agreement than estimates using the earlier MODIS Collection 4 algorithm. We find the Deltatauf/DeltaCO slope to be robust over a range of spatial scales for large-scale burning events but less so for burning events with greater spatial variability. Our analysis of interannual variability of biomass burning shows that a single Deltatau f/DeltaCO slope can be used on a regional basis for average burning conditions. Estimates of aerosol number concentration to CO concentration emission ratio derived from Deltatauf/DeltaCO slopes are in good agreement with estimates from previous studies.
ISBN: 9780549558293Subjects--Topical Terms:
1019179
Atmospheric Sciences.
Data analysis from remote sensing to better constrain emission and transport of carbonaceous aerosol and carbon monoxide resulting from burning processes.
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The production of atmospheric pollution has been increasing significantly since the advent of the industrial age. After fossil fuel combustion, biomass burning is the second largest source of anthropogenic fine mode aerosols and possibly the largest source of black carbon particles. Biomass burning is a significant source of greenhouse gases as well as ozone precursor gases including CO. Satellite remote sensing offers the best approach for obtaining global measurements of tropospheric trace gases and aerosols to assess the impacts of biomass burning emissions on air quality, atmospheric chemistry and climate. Given a growing interest in the development of modeling tools capable of predicting emission sources and transport of gases and particulates in the atmosphere, satellite data can potentially provide useful information for testing and validating chemical transport models. We use data from multiple satellite sensors to estimate emissions of carbonaceous aerosol for several biomes from around the globe using the slope of the regression of fine mode aerosol optical depth tauf to CO (Deltatauf/DeltaCO). We find Deltatauf/DeltaCO slopes calculated for Eastern Siberian boreal fires are 1.5 times greater than those for North American boreal fires, and two to three times larger than those calculated for deforestation fires in South America or African savanna burning. Our results show that different measures of fine mode aerosol thickness strongly affect the Deltatau f/DeltaCO slope. Deltatauf/DeltaCO slopes calculated using the MODIS Collection 5 aerosol algorithm are consistently larger over ocean and land when compared to estimates of Deltatauf/DeltaCO obtained using the submicrometer fraction algorithm. Estimates using the MODIS Collection 5 algorithm are in better agreement than estimates using the earlier MODIS Collection 4 algorithm. We find the Deltatauf/DeltaCO slope to be robust over a range of spatial scales for large-scale burning events but less so for burning events with greater spatial variability. Our analysis of interannual variability of biomass burning shows that a single Deltatau f/DeltaCO slope can be used on a regional basis for average burning conditions. Estimates of aerosol number concentration to CO concentration emission ratio derived from Deltatauf/DeltaCO slopes are in good agreement with estimates from previous studies.
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http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3308675
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