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| Titel |
The wildland fire emission inventory: western United States emission estimates and an evaluation of uncertainty |
| VerfasserIn |
S. P. Urbanski, W. M. Hao, B. Nordgren |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1680-7316
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| Digitales Dokument |
URL |
| Erschienen |
In: Atmospheric Chemistry and Physics ; 11, no. 24 ; Nr. 11, no. 24 (2011-12-20), S.12973-13000 |
| Datensatznummer |
250010290
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| Publikation (Nr.) |
 copernicus.org/acp-11-12973-2011.pdf |
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| Zusammenfassung |
Biomass burning emission inventories serve as critical input for atmospheric
chemical transport models that are used to understand the role of biomass
fires in the chemical composition of the atmosphere, air quality, and the
climate system. Significant progress has been achieved in the development of
regional and global biomass burning emission inventories over the past
decade using satellite remote sensing technology for fire detection and
burned area mapping. However, agreement among biomass burning emission
inventories is frequently poor. Furthermore, the uncertainties of the
emission estimates are typically not well characterized, particularly at the
spatio-temporal scales pertinent to regional air quality modeling. We
present the Wildland Fire Emission Inventory (WFEI), a high resolution model
for non-agricultural open biomass burning (hereafter referred to as wildland
fires, WF) in the contiguous United States (CONUS). The model combines
observations from the MODerate Resolution Imaging Spectroradiometer (MODIS)
sensors on the Terra and Aqua satellites, meteorological analyses, fuel
loading maps, an emission factor database, and fuel condition and fuel
consumption models to estimate emissions from WF.
WFEI was used to estimate emissions of CO (ECO) and PM2.5 (EPM2.5)
for the western United States from 2003–2008. The uncertainties in the
inventory estimates of ECO and EPM2.5 (uECO and uEPM2.5, respectively) have been explored across spatial and temporal
scales relevant to regional and global modeling applications. In order to
evaluate the uncertainty in our emission estimates across multiple scales we
used a figure of merit, the half mass uncertainty, ũEX
(where X = CO or PM2.5), defined such that for a given aggregation
level 50% of total emissions occurred from elements with uEX
ũEX. The sensitivity of the WFEI estimates of ECO and
EPM2.5 to uncertainties in mapped fuel loading, fuel consumption, burned
area and emission factors have also been examined.
The estimated annual, domain wide ECO ranged from 436 Gg yr−1 in 2004
to 3107 Gg yr−1 in 2007. The extremes in estimated annual, domain wide
EPM2.5 were 65 Gg yr−1 in 2004 and 454 Gg yr−1 in 2007.
Annual WF emissions were a significant share of total emissions from non-WF
sources (agriculture, dust, non-WF fire, fuel combustion, industrial
processes, transportation, solvent, and miscellaneous) in the western United
States as estimated in a national emission inventory. In the peak fire year
of 2007, WF emissions were ~20% of total (WF + non-WF) CO
emissions and ~39% of total PM2.5 emissions. During the months
with the greatest fire activity, WF accounted for the majority of total CO
and PM2.5 emitted across the study region. Uncertainties in annual,
domain wide emissions was 28% to 51% for CO and 40% to
65% for PM2.5. Sensitivity of ũECO and
ũEPM2.5 to the emission model components depended on
scale. At scales relevant to regional modeling applications (Δx = 10 km, Δt = 1 day) WFEI estimates 50% of total ECO with
an uncertainty <133% and half of total EPM2.5 with an uncertainty
<146%. ũECO and ũEPM2.5 are
reduced by more than half at the scale of global modeling applications
(Δ x = 100 km, Δ t = 30 day) where 50% of total emissions
are estimated with an uncertainty <50%
for CO and <64% for PM2.5. Uncertainties in the estimates of
burned area drives the emission uncertainties at regional scales. At global
scales ũECO is most sensitive to uncertainties in the fuel
load consumed while the uncertainty in the emission factor for PM2.5
plays the dominant role in ũEPM2.5. Our analysis
indicates that the large scale aggregate uncertainties (e.g. the uncertainty
in annual CO emitted for CONUS) typically reported for biomass burning
emission inventories may not be appropriate for evaluating and interpreting
results of regional scale modeling applications that employ the
emission estimates. When feasible, biomass burning emission inventories
should be evaluated and reported across the scales for which they are
intended to be used. |
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