Environmental Engineering Reference
In-Depth Information
and burned areas widely available, and have also provided temporal and spatial res-
olution improvements (Ottmar et al.
2009
), but the presence of clouds or confused
signals could strongly affect data (Stroppiana et al.
2010
); Friedli et al. (
2009b
).
Fuel load (
F
l
) is considered as the source of the largest errors in FE esti-
mates (Peterson and Sandberg
1988
; Peterson
1987
; Hardy et al.
2001
), due
to the large variability in ecosystem types and species composition. For exam-
ple, Dimitrakopoulos (
2002
) pointed out the high variability of fuel load within
Mediterranean vegetation, ranging from 4.85 t ha
−
1
in grasslands to 53 t ha
−
1
in
evergreen sclerophyllous shrublands (fuel depth: 1.5-3 m). Recently, to obtain a
better simulation of spatial variability in fuel load, several Authors integrated bio-
chemical models (van der Werf et al.
2006
) or dynamic global vegetation models
(Thonicke et al.
2010
) in FE inventories.
Peterson (
1987
) and Peterson and Sandberg (
1988
) demonstrated that EF vari-
ability (mainly due to type of pollutant, type and arrangement of fuel, and com-
bustion efficiency, CE), contributes to about 16 % of the total error associated
with emissions. The uncertainty is higher for compounds and biomes that have not
been studied in detail (Langmann et al.
2009
). Ward and Hardy (
1991
) suggested
that EF could be better assessed considering the two phases of combustion, and
then the fraction of biomass consumed by each process. The CE concept was then
introduced, in order to involve the fractional rate of complete combustion. Values
of CE exceeding 90 % indicate the flaming phase, while values lower than 85 %
indicate smoldering combustion (Ward and Hardy
1991
; Yokelson et al.
2007
).
Another key component in the estimate of the amount and source of emissions
(Ottmar et al.
2009
) is the combustion completeness (CC, in %) (Shea et al.
1996
).
CC represents the ratio between consumed and available fuel load, and depends on
fire type, fuel type and its moisture content (Ward et al.
1996
; Battye and Battye
2002
;
Langmann et al.
2009
). CC of coarse and wet fuels is lower than fine and dry fuels.
Most FE estimation models determine combustion factors for each fuel strata (e.g.
stems, leaves and litter) and moisture conditions, allowing for a detailed description of
CC (e.g., Reinhardt et al.
1997
; Hardy et al.
2001
; van der Werf et al.
2006
). In order
to increase the level of accuracy for the assessment of CC, Chiriac et al. (
2013
) inte-
grated a methodology proposed by Bovio (
2007
) based on the level of damage assessed
on the basis of forest vegetation class and scorch height, which depends on two main
factors: the intensity of the fire and the type of forest vegetation affected by fire.
6.3 Description of Emission Factors for GHGs
According to Andreae and Merlet (
2001
), the mass of pollutant produced (M
x
, in
g) per mass of dry fuel consumed (M
b
, in kg) is referred to as emission factor of a
chemical species
x
(EF
x
) (g kg
−
1
), which translates biomass burned into trace spe-
cies emissions (see Eq.
6.2
).
M
X
M
B
EF
X
=
(6.2)
