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global scale, influencing regional environment (e.g. Sinha et al. 2003 ; Jaffe et al. 2004 ;
Miranda et al. 2009a , b ) and global atmospheric chemistry (e.g. Novelli et al. 2003 ; van
der Werf et al. 2004 ). Moreover, there is a continuous loop between fire emissions and
climate, the first influencing the second while contributing to GHGs and aerosol parti-
cles, and the second affecting length and intensity of fire season. These complex interac-
tions have been emphasized in the last years (e.g. Langmann et al. 2009 ), and there is
an increasing interest on the definition of sound EF inventories and the regulation of
regional emissions to the atmosphere (e.g. Wiedinmyer and Neff 2007 ).
There is a significant uncertainty regarding fire emission amount, timing, and
variability (Wiedinmyer and Neff 2007 ). As illustrated by a number of studies (e.g.
Jain 2007 ; Al-Saadi et al. 2008 ; Stroppiana et al. 2010 ), burned area and fuel vari-
ability are the main issues in estimating fire emissions. Langmann et al. ( 2009 ),
Stroppiana et al. ( 2010 ) pointed out that, despite the improvements achieved by
remote sensing, fire emissions estimates are still affected by large uncertainties,
mainly due to the differences in the area burned (see Sect. 6.5 ). In addition, other
inconsistencies derive from the assessment of emission factors and combustion
estimation (Ottmar et al. 1993 ). Several Authors suggested that including EF large
variability from field studies might improve estimate variation in tracing gas and
aerosol emissions. The considerable progress in measuring methodologies and the
number of projects aimed at assessing and determining accurate values of EF have
been presented in Sect. 6.4 , even if the amount and accuracy of EF data is not
equally balanced among ecosystems (Jain 2007 ). Finally, the application of semi-
physical modeling systems (Bacciu et al. 2012 ) seems to be a benefit when evalu-
ating and assessing emissions from forest fires.
Another point of open discussion is the role of fire in climate policies. Despite
the fact that long-term impacts of FE is not as much as from fossil fuel emissions,
the fire impacts over shorter time periods are highly considerable (Wiedinmyer
and Neff 2007 ). In addition, the changing climate, with a likely increase of
extreme events conducive to large or more severe fires (Fried et al. 2004 ; Arca
et al. 2009 ; Flannigan et al. 2009 ), might lead to FE that increasingly diverge from
historical means. This point has been recalled also during the Durban conference
in 2011: the countries, when accounting for forest management, “may exclude
from the accounting emissions from natural disturbances that in any single year
exceed the forest management background level” (UNFCCC 2012 ).
References
Albini FA (1976a) Computer-based models of wildland fire behavior: a users' manual. USDA
Forest Service, Intermountain and Range Experiment Station, Ogden, UT
Albini FA, Brown JK, Reinhardt ED, Ottmar RD (1995) Calibration of a large fuel Burnout
model. Int J Wildland Fire 5(3):173-192
Albini FA, Reinhardt ED (1995) Modeling ignition and burning rate of large woody natural fuels.
Int J Wildland Fire 5(2):81-91
Albini FA, Reinhardt ED (1997) Improved calibration of a large fuel burnout model. Int J
Wildland Fire 7(1):21-28
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