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| Titel |
The Fire INventory from NCAR (FINN): a high resolution global model to estimate the emissions from open burning |
| VerfasserIn |
C. Wiedinmyer, S. K. Akagi, R. J. Yokelson, L. K. Emmons, J. A. Al-Saadi, J. J. Orlando, A. J. Soja |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1991-959X
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| Digitales Dokument |
URL |
| Erschienen |
In: Geoscientific Model Development ; 4, no. 3 ; Nr. 4, no. 3 (2011-07-20), S.625-641 |
| Datensatznummer |
250001779
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| Publikation (Nr.) |
 copernicus.org/gmd-4-625-2011.pdf |
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| Zusammenfassung |
| The Fire INventory from NCAR version 1.0 (FINNv1) provides daily, 1 km
resolution, global estimates of the trace gas and particle emissions from
open burning of biomass, which includes wildfire, agricultural fires, and
prescribed burning and does not include biofuel use and trash burning.
Emission factors used in the calculations have been updated with recent
data, particularly for the non-methane organic compounds (NMOC). The
resulting global annual NMOC emission estimates are as much as a factor of 5
greater than some prior estimates. Chemical speciation profiles, necessary
to allocate the total NMOC emission estimates to lumped species for use by
chemical transport models, are provided for three widely used chemical
mechanisms: SAPRC99, GEOS-CHEM, and MOZART-4. Using these profiles, FINNv1
also provides global estimates of key organic compounds, including
formaldehyde and methanol. Uncertainties in the emissions estimates arise
from several of the method steps. The use of fire hot spots, assumed area
burned, land cover maps, biomass consumption estimates, and emission factors
all introduce error into the model estimates. The uncertainty in the FINNv1
emission estimates are about a factor of two; but, the global estimates
agree reasonably well with other global inventories of biomass burning
emissions for CO, CO2, and other species with less variable emission
factors. FINNv1 emission estimates have been developed specifically for
modeling atmospheric chemistry and air quality in a consistent framework at
scales from local to global. The product is unique because of the high
temporal and spatial resolution, global coverage, and the number of species
estimated. FINNv1 can be used for both hindcast and forecast or near-real
time model applications and the results are being critically evaluated with
models and observations whenever possible. |
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