Abstract. Many of the
proposed activities for mitigating global warming in the land-use and fores=
try
(LUCF) sector differ from measures to avoid fossil fuel emissions because
carbon (C) may be held out of the atmosphere only temporarily. In addition, the timing of the eff=
ects
is usually different. Many LU=
CF
activities alter C fluxes to and from the atmosphere several decades into t=
he
future, whereas fossil-fuel emissions avoidance has immediate effects. Non-CO2 greenhouse gases
(GHGs), which are an important part of emissions from deforestation in
low-latitude regions, also pose complications for comparisons between fossil
fuel and LUCF, since the mechanism generally used to compare these gases
(global warming potentials) assumes simultaneous emissions. A common numeraire is needed to ex=
press
global warming mitigation benefits of different kinds of projects, such as
fossil fuel emissions reduction, C sequestration in forest plantations, avo=
ided
deforestation by creating protected areas and through policy changes to slow
rates of land-use changes such as clearing. Megagram (Mg)-year (also known as
“ton-year”) accounting provides a mechanism for expressing the
benefits of activities such as these on a consistent basis. One can calculate the atmospheric =
load
of each GHG that will be present in each year, expressed as C in the form o=
f CO2
and its instantaneous impact equivalent contributed by other gases. The atmospheric load of CO2-equivalent
C present over a time horizon is a possible indicator of the climatic impac=
t of
the emission that placed this load in the atmosphere. Conversely, this index also provid=
es a
measure of the benefit of not producing the emission. One accounting method compares
sequestered CO2 in trees with the CO2 that would be in
the atmosphere had the sequestration project not been undertaken, while ano=
ther
method (used in this paper) compares the atmospheric load of C (or equivale=
nt
in non-CO2 GHGs) in both project and no-project scenarios.<=
/o:p>
Time preference,
expressed by means of a discount rate on C, can be applied to Mg-year
equivalence calculations to allow societal decisions regarding the value of
time to be integrated into the system for calculating global warming impacts
and benefits. Giving a high v=
alue
to time, either by raising the discount rate or by shortening the time hori=
zon,
increases the value attributed to temporary sequestration (such as many for=
est
plantation projects). A high =
value
for time also favors mitigation measures that have rapid effects (such as
slowing deforestation rates) as compared to measures that only affect emiss=
ions
years in the future (such as creating protected areas in countries with lar=
ge
areas of remaining forest). D=
ecisions
on temporal issues will guide mitigation efforts towards options that may or
may not be desirable on the basis of social and environmental effects in
spheres other than global warming.
How sustainable development criteria are incorporated into the appro=
val
and crediting systems for activities under the Kyoto Protocol will determine
the overall environmental and social impacts of pending decisions on tempor=
al
issues.
&n=
bsp;
Key words: carbon dioxide, discount rate, global warming,
greenhouse effect, land-use change, mitigation, time preference, deforestat=
ion.
1. Introduction
Temporal issues are=
among
the most fundamental questions governing the amount of credit that will be
given to different kinds of global warming mitigation measures. These issues include establishing =
both a
time horizon and a discount rate (zero or otherwise) for carbon (C). Temporal issues will be key factor=
s in
determining whether efforts to mitigate global warming will include CO=
2
sinks in the land-use change and forestry (LUCF) sector, and within the LUCF
sector whether priority is given to plantation forestry or to avoiding
deforestation.
Questions that are =
still
undecided include whether megagram (Mg)-year (also known as
“ton-year”) accounting will be applied to calculating the benef=
it
of mitigation activities under the Kyoto Protocol, what time horizon will be
used, and whether a non-zero discount rate will be applied. For the first commitment period
(2008-2012), these decisions will probably be made at the Sixth Conference =
of
the Parties (COP-6) in November 2000, after taking into consideration the
Intergovernmental Panel on Climate Change (IPCC) Special Report on Land-Use
Change and Forestry (SR-LUCF), to be completed in May 2000 (Watson and Vera=
rdo,
2000). The question of whethe=
r any
LUCF activities, especially forest conservation, will be included under the
Clean Development Mechanism (CDM) established in Article 12 of the Kyoto
Protocol (UN-FCCC, 1997a) will also be decided at that time. The Clean Development Mechanism pr=
ovides
a mechanism by which Annex B countries (countries that have commitments to
limiting their national emission totals under the Kyoto Protocol) can finan=
ce
activities in non-Annex B countries to offset the financing country’s
fossil fuel C emissions. Clean
Development Mechanism projects must demonstrate that C benefits are additio=
nal
to what would have occurred in the absence of the project.
Carbon dioxide (CO<=
sub>2)
sinks in general have been criticized as temporary and therefore inherently
less beneficial than avoiding fossil fuel emissions (e.g., Matoon, 1998). Confusion has often resulted from
lumping all LUCF activities in a single category as biotic sinks. Lashof and Hare (1999), for exampl=
e,
have argued that credits from biotic sinks under the Protocol carry a risk =
of
having perverse effects on atmospheric CO2 concentrations. However, Fearnside (1999a) has arg=
ued
that this reasoning applies only to forest plantations, and that within the
category of plantations it applies only to their role in CO2
sequestration (as distinct from fossil fuel substitution). Lashof and Hare's argument is that=
, by
allowing countries to emit more C from fossil stocks into the active C pool
(biosphere + atmosphere), the increases in biotic C stocks that have been
encouraged under the Kyoto Protocol as carbon offsets (1) have a risk of
subsequent release into the atmosphere, and (2) reduce the options available
for future responses in the forest sector because the capacity of these opt=
ions
to absorb C will have been saturated.
However, Fearnside (1999a) has argued that, in the case of avoiding
deforestation in low-latitude regions, the result is more like reducing fos=
sil
fuel C emissions than it is like carbon sequestration in plantations. C stocks in areas of high-biomass =
low-latitude
rain forests are very unlikely to be allowed to regenerate to their present
levels if these forests are cut down.
Most of the C released from deforesting these areas is, therefore, an
addition to what might be called the most active C pool (i.e., atmospheric =
C +
C in rapidly cycling stocks such as plantation biomass) that is as permanen=
t as
is release of fossil C. Clean
Development Mechanism or other activities that help low-latitude (tropical)
forest countries avoid deforestation keep C out of the “most active
pool” in the same way that avoiding fossil C emissions would. The C releases avoided are, for
practical purposes, as irreversible as fossil fuel combustion (Fearnside,
1999a.
If cMg-y=
ear
accounting (Chomitz, 1998; Fearnside, 1995a, 1997a; Tipper and de Jong, 199=
8; Moura-Costa and Wilson, 2000) =
is n=
eeded u=
seful for
comparing avoided fossil fuel emissions with plantations and other mitigati=
on
options in the forest sector. Under
a Mg-year system, credit would be given for the number of tons of C held ou=
t of
the atmosphere each year. Dis=
counting,
zero or otherwise, would apply to the C value calculated for each year over=
the
time horizon when the expectations for different proposed mitigation projec=
ts
are compared (“not discounting” is really only a special case of
discounting, where the discount rate is equal to zero). Discounting can be applied in
conjunction with Mg-year accounting, although use of a non-zero discount ra=
te
is not required. It is also
possible to apply discounting to net stock changes (i.e., to fluxes), rather
than to the atmospheric load of C as in Mg-year accounting (e.g., Hourcade =
et al., 1996; Schlamadinger and Ma=
rland,
1999).
Mg-year accounting recognizes that keepi=
ng a
unit of C out of the atmosphere during any given year has the same value,
whether the C atoms are cycled through successive short-lived products or
whether they are held in a mahogany wood desk that lasts a century. Under a Mg-year accounting system,
delaying deforestation merits credit irrespective of the long-term fate of =
the
forest, although the cumulative credit that can be earned from a given fore=
st
stand is obviously greater the longer the
forest remains intact. Compar=
isons
can be made between forest reserve creation and policies to slow deforestat=
ion
by using C Mg-year accounting.
Policies affecting the motives for deforestation will have rapid eff=
ect
on GHG emissions, whereas the effect of reserve creation can only reduce
emissions years in the future when available forests outside of the reserve
have been exhausted.
The discounting app=
lied
here does not take into account threshold effects that may exist in the dam=
age
function relating climatic impacts to atmospheric changes. Our knowledge of such thresholds is
currently insufficient to incorporate them in calculations of this kind, al=
though
this could be done when our understanding of the climate system improves. As of now, decisions must be based=
on
the best available information, such as that in the IPCC’s Second Assessment Report (SAR).
2. Duration of Sequestration=
Carbon sequestratio=
n in
forest and other types of land cover is inherently reversible, unlike avoid=
ed
emissions of fossil fuel C (which is generally considered a permanent
gain). Carbon dioxide sequest=
ration
must be distinguished from fossil fuel substitution, which can also be achi=
eved
by some LUCF options, such as charcoal substitution for mineral coal. Fossil fuel substitution through
forestry is just as permanent as avoided emissions through measures such as
enhancing energy efficiency (Hall e=
t al.,
1993; Marland and Schlamadinger, 1997).
It has been argued =
that
postponing deforestation is a valid mitigation measure even if the forests =
in
question are later cut for harvesting or other purposes, including cutting =
up
to the theoretical maximum of clearing all forests in a country (Fearnside,
1999b). The credit for such a=
delay
depends on two key parameters: time horizon and discount rate (or other
alternative time-preference scheme).
From a CO2 perspective, under some conditions postponing a
given number of hectares of clearing for one year is equivalent to avoided
emissions by reduced combustion of fossil fuels. In the fossil fuel case, avoided
emissions are counted as a permane=
nt
gain, even though the same barrels of oil not burned in a given year will be
burned just one year later. T=
he
fossil fuel displacement is assumed to cascade forward, either (1) indefini=
tely
(i.e., assuming that fossil fuel stocks are infinite for practical purposes=
),
(2) until after the end of the time horizon, or (3) until fossil fuel burni=
ng
ceases at some fixed point in time due either to development of technologic=
al
alternatives or to social changes.
In the case of fossil fuels, the total stock of approximately 5000 Pg
(petagrams =3D gigatons) C (Bolin e=
t al.,
1979) is far beyond the capacity of human society to burn and to mitigate to
acceptable levels of environmental impact, and can be considered infinite f=
or
practical purposes. While some
categories of fossil fuels, such as natural gas, may be exhausted within a
100-year time horizon, one can assume that switching will then occur to oth=
er
forms of fossil fuel energy.
In the case of
deforestation, the assumption of an effectively infinite cascading effect c=
an
break down if the area of remaining forest is small enough that it could be
exhausted within the time horizon under consideration. If a country runs out of forest (o=
r of
accessible or unprotected forest) within the time horizon, then no carbon
advantage would accrue from postponing deforestation if the discount rate is
zero (except for credit for delay generated by the time horizon, to be
explained later).
It is importan=
t to
understand that the logic behind considering either fossil fuel or forest as
permanent is not based on the
assumption that specific atoms of C will remain in the ground or in the for=
est
forever. Instead, the effect =
of
delaying for one year a given amount of fossil fuel burning or a given amou=
nt
of deforestation will be delaying for one year the time that C is released =
from
each barrel of oil or hectare of forest that would be burned or deforested =
in
subsequent years. The emission
displacement cascades forward either forever or until the end of the time
horizon, resulting in a permanent savings.=
In Figure 1, Mg number 1 (Mg1) is burned in year 1 in the
baseline scenario, but in year 2 in the mitigation scenario. By the end of the time horizon (ye=
ar n),
n Mg have been burned in the baseline scenario, but only n-1 Mg in the
mitigation scenario. In the c=
ase of
forest, this example does not include the effect of degradation (or
aggradation).
&=
nbsp; [Figure
1 here]
The cascading =
effect
of displaced emissions depends heavily on the assumption that the C reserve
(either forest or fossil) will last beyond the end of the time horizon. If this is not the case, as in Fig=
ure 2
where only two Mg of C exist and the forest that contains them is destroyed
within the time horizon in both the baseline and mitigation scenarios, no
credit is gained by delaying deforestation in an accounting that considers =
only
the total emission (i.e., where no removal of C from the atmosphere is
considered). As will be shown
later, even in a case such as this where forest runs out within the time
horizon, delaying deforestation should receive some credit if a more comple=
te
accounting is made of the stocks in the atmosphere using a Mg-year
approach. In this simplified
example, the effect of degradation (or aggradation) is also not considered.=
[Figure 2 here]
3. Ti=
me
Horizons and Emissions Impacts
Establishing a=
finite
time horizon, as in Figures 1 and 2, implies a value for time independent of
any additional value for time preference that may be added through a mechan=
ism
such as a discount rate. The =
global
warming potentials (GWPs) from the SAR (Schimel et al., 1996) have been adopted by the Kyoto Protocol (Article =
5.3)
for establishing the equivalence among different GHGs, and a 100-year time
horizon has been specified for this purpose (UN-FCCC, 1997b). We assume that this time horizon w=
ill
apply to other aspects of GHG accounting.&=
nbsp;
Whether intended or not, choice of a time horizon has created a value
for time under the Protocol. =
The
100-year zero-discount formulation used for GWPs adopted from the SAR is
equivalent to an annual discount rate of approximately 10=
.9%
if w=
ith a very
long (1000-year) time horizon (Fig. 3)t=
he tail o=
f the
curve representing impacts is truncated at some sufficiently distant time, =
such
as 1000 years (Fig. 3).
A variety of arguments point to 100 years as a reasonable choice for
policy-making with a minimum of perverse distortions (Fearnside, 2000a).
&=
nbsp; [Figure
3 here]
In the context of the present calculation=
, the
impact of a GHG on global warming is represented by the amount of heat that=
it
has blocked from escaping into space over the 100-year time horizon. In other words, it is proportional=
to
the instantaneous radiative forcing of one Mg of the GHG multiplied by the
number of Mg present in each year, summed over the years in the time horizo=
n.
The parameters used in the SAR can be use=
d to calculate
the fraction of the atmospheric load from an emission that remains in any g=
iven
year. C emitted to the atmosp=
here
as CO2 declines in a non-linear fashion in accord with the Revis=
ed
Bern Model, which will be described shortly. Methane (CH4) and nitro=
us
oxide (N2O) decline exponentially with half lives of 12.2 years =
and
120 years, respectively (Schimel et=
al.,
1996). While these gases rema=
in in
the atmosphere, their instantaneous radiative forcings (not to be confused =
with
GWPs, which are integrated over a time horizon) per Mg of gas are 58 for CH=
4
and 206 for N2O, relative to a value of 1 for CO2 (Sh=
ine et al., 1995). For each year of the calculation, =
the
atmospheric load of the non-CO2 GHGs can be converted to CO=
2
gas equivalents in terms of instantaneous radiative forcing, and then conve=
rted
to C by multiplying by the ratio of the atomic weight of C to the molecular
weight of CO2 (12/44).
An example is given in Table 1 for emissions from 1 ha of deforestat=
ion,
using average per-hectare emissions from deforestation in Brazilian Amazoni=
a in
1990 and treating all emissions as net committed emissions (i.e., treating =
all
delayed emissions and CO2 uptakes as occurring in the year of
deforestation). The ability of
Mg-year accounting to deal fairly with non-CO2 GHGs is important,
especially for quantifying the benefits of avoiding deforestation, which is=
a
major source of these gases through biomass burning.
&nb=
sp; =
[Table
1 here]
Discounting can be used to express the im=
pact
of emissions of different gases occurring at different times in terms of
immediate C emission equivalents.
This can be thought of as a net present value, but we prefer the term
immediate C emission equivalent to make clear that the adjustment includes =
both
the effect of time and translating the effects of non-CO2 GHGs i=
nto
C (i.e., CO2 C) equivalents.
The difference between the integrals of t=
he C
load in the atmosphere (and its radiative equivalent from the atmospheric l=
oads
of other gases) is not the only possible index of the benefit of delaying
emissions. For example, one m=
ight
choose the reduction in the atmospheric load of C at some fixed point in ti=
me,
such as at the time the 2 ´ CO2 milestone is passed in
approximately 2070 (A in Fig. 4), rather than the difference in the integra=
ls
adopted here. The area under the curve in the
delayed-emission case is smaller than that in the immediate-emission case b=
y an
amount that has been pushed beyond the end of the time horizon (B in
Fig. 4). The difference betwe=
en the
integrals results in greater credit for delaying emissions than does the
fixed-year approach. For exam=
ple, a
one-year delay results in a decrease of 0.71% in the integral but only a 0.=
46%
decrease in the height of the curve (the instantaneous atmospheric load) in
2070.
=
[Figure
4 here]
=
When =
an
emission of CO2 ente=
rs the
atmosphere, the atmospheric load of the GHG will=
begin
to decay following a path that has the same integral over the first 100 yea=
rs
as an exponential decay with a time constant of 55 years. However, the precise path followed=
is
more complex than this, so that over 500 years the integral is the same as =
an
exponential decay with a time constant of 150 years. The actual decay will
depend on the future composition of the atmosphere and feedbacks from clima=
te
change.
In the
present paper the path assumed for C decline is that calculated by the version of=
the
Bern Model used in the SAR (Schi=
mel et al., 1996). Lack of published output from the
revised model has r=
esulted
in virtually all previous discussions of Mg-year
accounting being based on the earlier model used in the 1990 and 1992 IPCC reports.=
The revised version incorporates greater uptake by the biosphere,
described by the IPCC as a change that is “believed to be an important
improvement” (Albritton et al=
.,
1995). The resulting more rap=
id
decline in atmospheric C in t=
he early
years indicated by the revised model significantly increases the value of
temporary sequestration of CO2=
.
Output from the ver=
sion
of the Bern Model used in the SAR was illustrated graphically in the
IPCC’s 1994 special report (Albritton
et al., 1995), but the only
quantitative parameters published were for an approximation of the earlier
version used in the IPCC’s 1990 and 1992 reports (Albritton et al., 1995):
F[CO2(t)] =3D 0.3003 exp(-t/6.=
993) +
0.034278 exp(-t/71.109) + 0.35686 exp(-t/815.727)
where “F” is the fraction of =
CO2 remaining in the atmosphere and “t&#=
8221;
is the time after emission in years.
The approximation o=
f the
output of the revised model is given by:
F[CO2(t)] =3D 0.175602 + 0.137=
467
exp(-t/421.093) + 0.185762 exp(-t/70.5965) + 0.242302 exp(-t/21.42165) +
0.258868 exp(-t/3.41537).<=
/span>
=
When =
a Mg of C in t=
he
atmosphere decays as shown in Figure 4, the area under the curve over a 100=
-year
time horizon is equal to 46% of the area of the rectangle that would repres=
ent
the Mg of C rema=
ining
unchanged in the atmosphere over the same period. Keeping a Mg of C out =
of the
atmosphere for a full 100 years therefore represents 46 Mg-year equivalents, rather than the 100 =
Mg-years that would be earned if the CO2
entering the atmosphere had no movement to the ocean or other sinks. This is 16% lower than the corresp=
onding
number obtained using the older version of the Bern Model (55 =
Mg-years).
=
The n=
umber of
Mg-year equivalents represents the global warmi=
ng
impact caused by the emission in question.=
If, rather than the Bern Model, the ratio of global CO<=
sub>2 sinks to sources in the 1980s is used for
estimating Mg-year
equivalents, the value of 1 MgC of i=
mmediate
emission is 42 Mg-year
equivalents (Tipper and de Jong, 1998).&nb=
sp;
Because both terrestrial and ocean CO2 sinks could become saturated over the next ce=
ntury
(Cao and Woodward, 1998; Sarmiento =
et al.,
1998), use of a higher value would be wise in order to avoid risk of
under-compensating current GHG emiss=
ions
(Tipper and de Jong, 1998).
=
If re=
lease of
the Mg of C were=
delayed
for ten years, then the curve (Fig. 4) would be shifted to the right, and p=
art of
it would pass beyond the time horizon (only 90 years would be considered).<=
span
style=3D'mso-spacerun:yes'> The difference between the integra=
ls of
the two curves would represent the gain earned from having delayed the
emission. As the year of emis=
sion
is delayed successively further into the future, the impact of a one-=
Mg emission declines from 46 Mg-years in the first year to zero in year 100.=
Emitting one Mg in year 50 has 60% of =
the
impact of emitting one Mg in t=
he first
year. Conversely, a mitigation
project that results in a temporary delay of a C emission will gain progressively more credit=
the
longer the emission is postponed.
It will gain 100% of the credit of a permanent displacement if the d=
elay
lasts for 100 years, and 40% of =
the
credit if the delay lasts for 50 years.
=
The above calc=
ulations
consider the difference between the mitigation and baseline scenarios by
comparing the integrals of the atmospheric load of C over the time
horizon. Somewhat different r=
esults
are obtained in computing the benefits of LUCF mitigation projects such as
forest (silvicultural) plantat=
ions
if attention is focused on the C in the trees (e.g., Moura-Costa and Wilson,
2000). The distinction betwee=
n C in
trees and C in the atmosphere is important because atmospheric C is subject=
to
removal through natural processes that transfer it to CO2 sinks =
such
as oceans and the biosphere, whereas C present in the trees is assumed to
remain fixed. In the Moura-Co=
sta
method (Fig. 5 A), an equivalence time is calculated as the point at which =
the
area of the rectangle representing biomass C is equal to the area under the
atmospheric C decay curve over the 100-year time horizon. A different approach (the Lashof m=
ethod:
Fig. 5 B) reasons that, if C release is delayed because it is held in trees=
(as
in Figure 1), the benefit will be represented by the difference in the
integrals of the two curves within the time horizon, which is equal to the =
area
of the tail of the second curve that is pushed beyond the end of the time
horizon as a result of the delay.
The second method is used in the present paper.
&=
nbsp; [Figure
5 here]
In the case of
evaluating the C benefits of avoided deforestation, the size of the remaini=
ng
forest relative to prevailing rates of deforestation is critical (Fig. 6).<=
span
style=3D'mso-spacerun:yes'> The difference in the cascading ef=
fect
between countries with forest at risk of being cleared completely within the
time horizon and those that have sufficient forest to exclude this possibil=
ity
can be illustrated by a hypothetical example. Consider a hypothetical country wi=
th
only 3 ha of remaining forest and deforestation proceeding at a rate of 1
ha/year (Fig. 6). This is sim=
ilar
to the example in Figure 2, but includes the effect of forest degradation.<=
span
style=3D'mso-spacerun:yes'> Areas of forest that have been sav=
ed
from deforestation in a mitigation scenario may still lose C through
degradation or destruction by such forces as extreme weather events under
current climate regimes or under regimes altered by climate change, outbrea=
ks
of insects or diseases, and invasion by loggers or deforesters. Concern with permanence is one of =
the
main concerns
about the use of biotic sinks as climate change mitigation projectsd=
oubts that
has led some critics to oppose inclusion of biotic sinks among mitigation
measures under the Kyoto Protocol (e.g., Lashof and Hare, 1999;
Mattoon, 1998, but see Fearnside, 1999c).
&=
nbsp; [Figure
6 here]
In the hypothe=
tical
example (Fig. 6) the forest is assumed to be rapidly degrading: 20 MgC/ha is
lost to degradation between the first and the second year, 30 MgC/ha is lost
between the second and the third year, and 10 MgC/ha is lost between the th=
ird
and the fourth year. The emis=
sion
from 1 ha of deforestation would be 100 MgC if it were cut in year 1, 100
– 20 =3D 80 MgC if it were cut in year 2, 80 - 30 =3D 50 MgC in year =
3 and 50
- 10 =3D 40 MgC in year 4. In=
the
baseline scenario, the emission from degradation in the second year of 20
MgC/ha will apply over the two remaining hectares of forest (the third hect=
are
is already cut), making the degradation emissions 20 ´ 2 =3D 40 MgC and =
the
total in that year 80 + 40 =3D 120 MgC.&nb=
sp;
In the third year the degradation of 30 MgC/ha will apply only to the
one remaining hectare of forest, making the total emission in the third yea=
r 50
+ 30 =3D 80 MgC. In the fourt=
h year
both deforestation and degradation C emissions are zero because all forest =
has
already been cleared. The tot=
al
emission over the four years is 300 MgC.&n=
bsp;
In the mitigat=
ion
scenario, deforestation is postponed by one year. In this case the degradation in the
second year will apply to 3 ha rather than 2 ha, and will decrease in the t=
wo
subsequent years as successively less standing forest is present to
degrade. At the end of four y=
ears
the total (cumulative) emission will also be 300 MgC. Here no net gain in C has been ach=
ieved except for that which comes from =
credit
for having delayed the emission, the credit being based on the effect of
atmospheric C stocks decaying over time (i.e., Fig. 4), plus any additional
credit that may be awarded using a discount rate with a value greater than =
zero
to represent time preference.
The effect of
correction for decay in atmospheric C stocks is shown by the last row of
numbers in both the baseline and the mitigation scenario sections in Figure=
6. Here, the total emission in each ye=
ar is
multiplied by the corresponding proportion of the (full) impact of an immed=
iate
emission of a Mg of C, to obtain the immediate emission equivalent in Mg of=
C. The total in the baseline scenario=
is
279.1 MgC, while that in the mitigation scenario is 263.6 MgC, resulting in=
a
gain of 15.4 MgC. Although su=
ch a
gain is not insignificant, it is substantially lower than what can be gaine=
d if
the forest lasts beyond the end of the time horizon. It should be noted that the values=
would
be approximately double those in this example if a more realistic net emiss=
ion
per hectare of deforestation of 200 MgC/ha were used; within the bounds of
uncertainty this represents the per-hectare net committed emission (i.e.,
adjusting for CO2 uptake in secondary forests after deforestatio=
n)
of clearing in 1990 in Brazilian Amazonia, which averaged 194 MgC/ha
(Fearnside, 1997b).
If the forest =
lasts
beyond the end of the time horizon, then the credit that can be gained from
delaying deforestation increases substantially (Fig. 7). In this hypothetical example, the =
time
horizon is set at the end of year four.&nb=
sp;
As in the previous example (Fig. 6), deforestation proceeds at 1 ha/=
year
and the forest degrades at the same rapid rate. An important difference is that, b=
ecause
not all of the forest will be cleared before the end of the time horizon in=
the
mitigation scenario, one must follow the fate of an additional hectare of
forest that would have been cleared in the baseline scenario. This displaced area degrades from =
100
MgC/ha in year 1 to 40 MgC/ha at the end of the time horizon in year 4. These 40 MgC/ha represent a net ga=
in in
the total emission, being equal to the 400 MgC total emission in the baseli=
ne
scenario minus the 360 MgC total emission in the mitigation scenario. With a Mg-year equivalence account=
ing of
the immediate emission equivalent, the net gain is 363.6 – 315.8 =3D =
47.8
MgC, which is much greater than the 15.4 MgC gain in the case where the for=
est
runs out before the end of the time horizon.
&=
nbsp; [Figure
7 here]
Possible
effects of forest degradation (or aggradation) in forest areas saved from
deforestation could be corrected by appropriate adjustments in the crediting
system (e.g., as in Figs. 6 and 7).
Whether actions changing forest degradation and/or aggradation will =
be
included among the additional activities under Article 3.4 of the Kyoto
Protocol is still undecided (Schlamadinger and Marland, 1998). This will be critical for determin=
ing
the baseline for emissions trading under Article 17 for any tropical countr=
ies
that join Annex B of the Protocol.
For non-Annex B countries, credit under the Clean Development Mechan=
ism
(Article 12) will be based on additional C effects in a project scenario as
compared to a baseline or no-project scenario. Assuming that deforestation avoida=
nce is
included under the Clean Development Mechanism, it remains undecided whether
effects such as degradation would be included in the accounting. Nothing prevents degradation (or
aggradation) effects from being estimated and the corresponding adjustments
made to C credit earned. Fore=
st
aggradation, the opposite of degradation, could also be adjusted for in the
areas that are saved from deforestation.&n=
bsp;
The principle is relevant that changes that result in damage to the
atmosphere (i.e., forest degradation) should have obligatory adjustments, w=
hile
changes that result in atmospheric benefits (i.e., forest aggradation) shou=
ld
be optional (Sathaye, et al., 1=
997).
It is importan=
t to
note that the examples given in Figures 6 and 7 do not include a discount r=
ate
on C benefits to reflect society’s time preference (to be discussed in
the next section). Over a 100=
-year
time horizon, applying a discount rate, even if no greater than 1-2%/year,
would add substantially to the attractiveness of delaying deforestation as
compared to other mitigation options, because delaying deforestation result=
s in
substantial reduction in annual emissions in the short term. All C accounting implies a discount
rate, whether it is zero or otherwise.&nbs=
p;
A decision to use a zero discount rate is just as much a decision as
choosing any other rate. Ther=
e is
no escape from facing the choice of specifying a value for time. Sound reasons exist for adopting a
discount rate for C greater than the zero value currently used in most
discussions of C accounting.
4. Time Preferences and Discounting
4.1. RATIONALE FOR
DISCOUNTING
Applying to C either
discounting or some alternative form of time preference can be justified fo=
r reasons
other than the selfish interests of the current generation weighting
(Fearnside, 2000c, Richards, 1997).
Global warming impacts need to be separated into two categories that=
are
calculated and reported separately: impacts that can be expressed in terms =
of
money, and those that cannot, especially human life impacts (Fearnside,
1998). Discounting is the mec=
hanism
by which a value for time is normally translated into economic decision-mak=
ing.
Value for time, or =
the
social rate of time preference, is a combined result of the pure rate of ti=
me
preference (time preference based solely on an event’s position in ti=
me,
independent of how wealthy we expect to be at that time) and the utility (t=
he
utility per unit of wealth multiplied by the expected wealth per capita). Two approaches exist for deriving =
these
values: a prescriptionist approach based on ethical principles, usually
assigning a low or zero value to the pure rate of time preference (e.g., Cl=
ine,
1992), and a descriptionist approach based on observed economic behavior (e=
.g.,
Nordhaus, 1991). Annual disco=
unt
rates (social rates of time preference) over the long term are usually in t=
he
0.5-3% range for prescriptionists and in the 3-6% range for descriptionists
(Arrow et al., 1996). The result is that prescriptionists
recommend greater spending on mitigation and adaptation than do description=
ists
because long-term impacts of climate change have a greater net present valu=
e at
low discount rates (Arrow et al=
.,
1996). It is important to not=
e,
however, that the effect of discount rate on the overall level of spending
justified by climatic change is not the same as the effect on how the money
would be allocated among different mitigation response options: higher disc=
ount
rates will increase the relative attractiveness of options with rapid effec=
ts
on atmospheric GHG levels, such as slowing deforestation.=
Derivation of the social rate of time
preference requires values for three factors, all of which are subjects of
controversy: the pure rate of time preference, which is often described as =
the
result of “impatience” or “myopia” is greater than =
zero
if based on the observed behavior of individuals (whose behavior is influen=
ced
by awareness of their own mortality), but which can be argued to be zero fr=
om
the perspective of whole societies.
Sensitivity tests of discounting in the Dynamic Integrated Model of Climate and the Economy (DICE) by Nordhaus (1997) indicate that optimal
allocation to combating global warming is most sensitive to the pure rate of
time preference. The other
parameters are the expected level of wealth in the future and the marginal
utility per unit of additional wealth, which is expected to range from 1.5 =
to
0.8 (Scott, 1989; Pearce and Ulph, 1995; see Arrow et al., 1996).
Many people will di=
e as
impacts begin to appear from global warming. Using Fankhauser's (1995) estimate=
s for
a jump to double the pre-industrial CO2 concentration with the w=
orld
(including its population size) as it was in 1990, the result would be loss=
of
US$ 221 billion (in 1990 prices) annually, exclusive of human life losses, =
that
would total 138,000 lives per year (115,000 of which would be in non-OECD
countries) (see Pearce et al.,
1996). The above reasoning as=
sumes
that global warming initiates a step-function change in death rates, rather
than an increase that lasts for a finite period of time. =
All such estimates =
are
subject to great uncertainty, especially on the high side due to its unboun=
ded
nature.
It is important to
understand that avoiding mortality, even by delaying global warming by a si=
ngle
year, represents a permanent gain.
This is true even though the individuals so saved may die the next y=
ear
from this or some other cause. The
avoided mortality benefits cascade forward in the same way as avoided C
emissions in Figure 1. Based =
on
global emissions from fossil fuel and tropical forest land-use change (Table
2), one can calculate the human life value of avoided C emissions (including
immediate emission equivalents gained from delaying emissions or temporary
sequestration of C). This
calculation does not consider the CO2 sink of 0.5 PgC/year in
temperate and boreal forest growth.
Note that the value of 2.4 PgC/year for emission from tropical forest
land-use change (Fearnside, 2000d) used in Table 2 is 50% higher than the 1=
.6
PgC/year value used by the SAR, and that the additional size of the missing
sink implied by this difference results in the impact per Mg of current
emission being reduced in proportion to the change in the total anthropogen=
ic emission. It is 26% higher than the value of=
1.9
PgC estimated by Houghton (1999).
Each million Mg of avoided emission results in the saving of 16.4 li=
ves
(Table 2). The obviously
unrealistic assumption of fixed global population size over the 1990-2070 p=
eriod
makes this value conservative by a factor of two or more (Fankhauser and To=
l,
1997). The human-life value of
delaying global warming gives time a value that is independent of arguments
based on money, and provides a rationale for applying some form of time
preference, as by discounting, to C.
=
[Table
2 here]
The human-life bene=
fit of
delaying global warming is illustrated schematically in Figure 8. Here it is arbitrarily assumed that
global warming-induced mortality simply ramps up in a linear fashion from z=
ero
in 2000 to the SAR figure of 138,000 deaths/year in 2070 (the approximate y=
ear
of 2 × CO2), and remains constant thereafter. Delaying global warming by one year
shifts the curve to the right, creating a gain of 138,000 lives regardless =
of
what time horizon is adopted (so long as it is after 2070). It should be emphasized that this =
gain
is not reduced by discounting C, and that human life is not discounted.
=
[Figure
8 here]
Various other argum=
ents
for discounting have been put forward by different authors, although none of
these controversial arguments is necessary to justify the use of discounting
(or of some alternative means of expressing time preference) in global warm=
ing
calculations. One argument is=
that
expected increases in the wealth of the population suffering global warming
impacts will reduce the perceived loss of utility from the monetary impacts=
of
global warming because wealthier people attribute less value to a given amo=
unt
of monetary loss (Azar and Sterner, 1996).=
The opposite relationship between wealth and value has been suggested
for human life losses (Fankhauser and Tol, 1997), and strongly contested
(Fearnside, 1998). Yet another
argument for discounting is that it favors temporary carbon sequestration
activities that buy time for expected technological improvements reducing t=
he
future cost of mitigation per Mg of C (Chomitz, 1998). Another line of argument would even
indicate negative discount rates: greater movement of C to ocean and
terrestrial sinks as a result of CO2 fertilization and other eff=
ects
of future increases in atmospheric CO2 levels, as well as greater
time that atmospheric loads of C could be present to decay while still below
dangerous levels, led Wigley et al<=
/i>.
(1996) to suggest that C emissions are better now than later. Schnei=
der
(1997) counters the argument of Wigley et
al. (1996) by noting that greater loads of carbon in the atmosphere mig=
ht
trigger non-linearities, sometimes referred to as “climatic
surprises.” In addition,
immediate policy responses can restore efficiency that is hampered by
pre-existing market failures, such as spillovers in research and development
markets (Schneider and Goulder, 1997).
Exponential discount
rates greater than zero can have perverse effects on economic decision maki=
ng
because even catastrophic events in the long-term future are reduced to
insignificance (Cline, 1992; Costanza, 1991; Fearnside, 1989; Pearce, 1991;
Price, 1993). Rejection of
discounting in these contexts must be tempered with recognition of its
appropriateness in the context of carbon accounting. Pretending that time has no value =
also
has potential perverse effects.
The effect of disco=
unting
reducing long-term costs and benefits to insignificance is a characteristic=
of
the exponential discounting most commonly employed in economic analyses. A variety of alternative time-weig=
hting
mechanisms has been proposed =
to
avoid this consequence, including hyperbolic discounting where the annual
discount rate decreases as time progresses (Schneider et al., 2000), Heal discounting (Heal, 1997) where the discount
rate falls in steps, for example using a market rate (the opportunity cost =
of
capital) for the first 30 years and thereafter using a discount rate derived
from a zero rate of pure time preference and conservative assumptions about
long-term economic growth, a generation-weighting system that results in a
thicker tail of the distribution than does traditional discounting (but only
within a limited time horizon) (Fearnside, 2000c), and an alternative to pa=
ss a
fixed percentage of decision-making weight beyond the end of the time horiz=
on
(Fearnside, 2000a).
Agreement on a disc=
ount
rate or other time-preference weighting arrangement for C is fundamental to=
comparing
forest-sector options with fossil fuel substitution (Fearnside, 1995a,
1999c). Interpretation would =
be
greatly simplified if the discount rate chosen is consistent with choices f=
or
global warming potentials (Lashof and Ahuja, 1990). Discounting C need not be the same=
as
money, although some advocate that the same rate should be applied (e.g., v=
an
Kooten et al., 1997). The implications of discount rates=
as
high as those for money are substantial for the relative impacts of differe=
nt
activities (Fearnside, 1997a). The
choice of discount rates for other purposes, such as private investment
decisions, public expenditures, and public regulation of renewable natural
resources management, all have independent rationales. Since decisions are so sensitive to
discount rate choices (for example, the difference between a 3% and 6% annu=
al
discount rate is a factor of 20 over the course of a century), the conseque=
nces
of allowing choices on global warming decisions to be determined by discount
rates derived in other spheres could be severe.
4.2. CONSEQUENCES OF
DISCOUNTING
The impact of one M=
g of C
emission at different discount rates is shown in Figure 9, indicating the
percent of full impact recognized depending on the year that an emission oc=
curs
(considering a discrete
approximation using one-year increments). For example, for the zero-discount=
case,
the impact of a one-Mg emission is 46 Mg-years if emitted in year 0 (i.e., =
the
area under the baseline curves in Figure 5), and declines to 46 – 17 =
=3D 29
Mg-years if emitted in year 46 (i.e., the mitigation case in Figure 5 B). The impact of emitting one Mg in y=
ear 46
is therefore 29/46 =3D 63% of the immediate emission impact (Fig. 9). From the zero-discount line,
progressively larger discount rates cause impact to decrease rapidly in the
first years after emission (Fig. 9).
The converse of Figure 9, for purposes of calculating credit for
delaying emissions through sequestration, is given in Figure 10.=
=
[Figures
9 and 10 here]
Discounting can rad=
ically
alter choices of energy sources and mitigation options (Fearnside, 1995a,
1997a; Marland et al., 1997; Pr=
ice
and Willis, 1993). The length=
of
the time horizon has a strong effect on the importance of discounting. As time horizons become longer, the
distortions become greater if no discounting is applied. In the case of forest sector optio=
ns
that can transfer C to very long-term pools, these pools can dominate the
results if very long horizons are considered without discounting. In the case of an infinite or very=
long
time horizon, equilibrium conditions will apply. Slow buildup of C in very-slow-tur=
nover
classes of wood products dominates the results at equilibrium, but occurs at
such remote times that it has little bearing on present decisions when
discounting is applied. These
problems also apply to calculations made under the assumption that the shad=
ow
price of C increases at the same rate as the discount rate for money, there=
by
allowing analysis without discounting C (Fearnside, 1995a).
In the energy secto=
r,
higher discount rates for C will progressively reduce the attractiveness of
building hydroelectric dams to substitute for fossil fuel-based thermal
generation. This is because d=
ams
produce substantial emissions from concrete, steel and energy use during the
construction phase years before any power is generated, followed soon after
filling the reservoir by a large peak of additional emissions of CO2
from above-water decay of flooded trees (if the dam is in a tropical forest
area) as well as emissions of CH4 (Fearnside, 1995b, 1997a). Thermal power, in contrast, produc=
es
little emission during power plant construction, followed by emissions at a
constant rate over many decades, emissions impacts and energy benefits comi=
ng
in direct proportion and at the same time.=
Consequently, the cost of carbon benefits earned by switching from
thermal to hydroelectric power will increase with higher discount rates for=
C,
approaching infinity at the breakeven point between the two energy
sources. Similarly, higher dis=
count
rates will tend to reduce the benefits attributed to wind, solar and energy=
-e=
fficiency
projects compared to fossil fuel power plants t=
o the
extent that they involve larger=
=
emissions
related to building the capital equipment=
(with no emissions d=
uring
operation). Hi=
gher
financial discount rates also make these projects =
less economically
attractive.
In forest-sector op=
tions,
higher discount rates for C would favor deforestation avoidance (by slowing
rates of forest loss) over plantation silviculture because deforestation
produces large and immediate releases of GHGs, while plantations accumulate=
C
slowly. As discount rates for=
C
increase, the cost per Mg of C can be expected to climb for forest plantati=
on
mitigation options, but would remain relatively flat for avoided
deforestation. Policy measure=
s with
immediate effects on reducing deforestation rates will be favored over crea=
tion
of protected areas which can only be expected to result in reduced
deforestation rates years later when the remainder of the available forest =
has
been exhausted. This can be s=
een by
considering a hypothetical case to illustrate the implications of Mg-year
accounting and discounting for the two major categories of deforestation
avoidance efforts: creation of protected areas and policy changes to slow r=
ates
of clearing.
Consider a country =
(Fig.
11 A) that is clearing its remaining forest at a constant rate and will run=
out
of forest in nine years. If a=
park
is created from 1/18 (5.5%) of the remaining forest (Fig. 11 B), the availa=
ble
forest will be exhausted in 8.5 years, after which there will be no more
clearing. Note that this impl=
ies
some simplifying assumptions as compared to real cases: deforestation activ=
ity
shifts completely from the reserve area to other sites (i.e., there is 100%
leakage), and deforestation proceeds linearly until the last tree is cut. The alternative strategy—pol=
icy
measures to reduce clearing rates—is illustrated in Figure 11 C, where
clearing rate is reduced by 50% and proceeds to destroy the entire forest i=
n 18
years.
=
[Figure
11 here]
The effect of disco=
unt
rate on the choice between park creation and policy measures to slow
deforestation is shown in Figure 12, using as an example the same scenario =
as
Figure 11 with a baseline deforestation time of nine years. If the park option is to be as
attractive as the slowing deforestation option, the area of park that would
need to be created, expressed as a percent of the remaining forest area,
increases steadily with increasing discount rates; examples for 50% and 40%
reduction in deforestation rate are shown from the family of curves that wo=
uld
describe this relationship.
=
[Figure
12 here]
Another means of
visualizing the choice between parks and slowing deforestation is illustrat=
ed
in a second example (Fig. 13). A
ratio of the atmospheric impact the under slowing deforestation scenario and
under the park creation scenario greater than one indicates that park creat=
ion
would be preferable. Here a
baseline time to deforestation of 45 years is assumed, and a fixed park are=
a of
1/9 (11%) of the remaining forest.
The annual discount rates needed to cause a switchover in deforestat=
ion
avoidance strategy are substantially lower in this example than in the prev=
ious
one: for a 25% reduction in deforestation rate, parks are favored if the an=
nual
discount rate is less than 1.45%, whereas for a 50% reduction in deforestat=
ion
rate slowing deforestation is the favored option at all discount rates.
=
[Figure
13 here]
Results such as tho=
se in
Figure 11 are highly dependent on all of the emissions in all of the scenar=
ios
compared occurring within the time horizon. If, for example, the time to comple=
te
deforestation under the baseline scenario extends beyond the time horizon, =
then
park creation will receive no credit (or partial credit in the case of
deforestation ending soon after the time horizon). If slowing deforestation results i=
n the
demise of the forest being pushed beyond the end of the time horizon, then
policy changes to slow clearing rates get substantially more credit. These discontinuities may be seen =
as
either benefits or distortions, depending on the point-of-view. Choice of the time horizon is the
critical factor in determining when they come into play. The shorter the time horizon, the =
more
countries will be affected by this factor.=
At 100 years, Brazil would only escape the time horizon effect after
about 200 years, given (extremely optimistic) linear extrapolation of recent
deforestation rates as the baseline.
5. Sustainable
Development Implications of Mitigation
The above consequen=
ces of
discounting C have a variety of implications for other environmental and so=
cial
costs and benefits. Generatio=
n of
electrical power from fossil fuels has significant health consequences thro=
ugh
air pollution (Rosa and
Schechtman, 1996). On the other hand, hydroelectric p=
ower
can have tremendous impacts on biodiversity, indigenous peoples and
resettlement, as well as impacts on health, fisheries and a long list of ot=
her
concerns. Two of the most not=
orious
dams in the world in terms of these associated impacts are the Belo
Monte/Altamira (formerly Babaquara) complex in Brazil and the Three Gorges =
Dam
in China (Barber and Ryder, 1993; Dai
Qing, 1994; Fearnside, 1988, 1994, 1996a; Santos and de Andrade, 199=
0).
Both of these have been put forward in recent debates over the Clean
Development Mechanism as possibly meriting C credit! The almost total lack of connection
between discussions in the carbon sphere and those in other spheres of
environmental and social impact assessment is evident.
In the forestry sec=
tor,
the effect of discounting C in favoring deforestation avoidance over forest
plantations is highly beneficial from the biodiversity standpoint. On the other hand, the effect in
favoring policy initiatives over establishing protected areas is perhaps not
the best result for long-term maintenance of biodiversity (Fearnside,
1999d). Natural forests provi=
de
critical environmental services, including maintenance of biodiversity and
watershed functions (e.g., Daily, 1997; Schneider, 1998).=
The associated
environmental and social impacts of energy and forestry choices that are
influenced by decisions regarding time preference for C make clear the need=
for
explicit consideration of these impacts in decision making on global-warming
abatement. They cannot be add=
ressed
indirectly by fiddling with the discount rate in order to achieve progress =
on
an alternative environmental and social agenda through global-warming
mitigation efforts. Neither c=
an
these concerns be compartmentalized as beyond the ken of mitigation decisio=
ns
and left up to each country to decide as it sees fit through whatever syste=
m of
environmental impact assessment, if any, it may have. Such a solution would both favor t=
he
implantation of mitigation projects in countries with little or no
environmental and social impact regulation and would result in projects bei=
ng
funded that grossly violate standards in the funding countries (the two
hydroelectric dam examples mentioned earlier provide glaring examples). How sustainable development criter=
ia are
applied in carrying out global-warming mitigation measures under the Kyoto
Protocol will be crucial in determining the associated impacts and benefits=
of
the projects (e.g., Fearnside, 1996b, 1999e). Sustainable development criteria a=
nd
procedures represent another undecided area in Kyoto Protocol implementatio=
n.
Countries often have very different views=
as to
what constitutes sustainable development.&=
nbsp;
The United Nations Framework Convention on Climate Change (UN-FCCC)
clearly recognizes the sovereignty of each country in deciding how to mitig=
ate
global warming within its borders.
LUCF activities funded internationally for carbon credit under the K=
yoto
Protocol will inevitably have to meet the sustainable development criteria =
of both the countries receiving and =
those
providing the funds (Fearnside, 1999a).&nb=
sp;
Specifying the criteria to be used in this winnowing process and the
institutional mechanism for carrying it out are tasks that can only be done=
by
the Parties. As a hypothetical
example, a country might propose to cut a tropical forest containing endang=
ered
species and tribal peoples in order to implant a Eucalyptus plantation with C benefits. The criteria used to define sustai=
nable
development will determine whether such a project would receive funding and=
/or
carbon credit, and thereby determine the environmental and social implicati=
ons
of the mitigation effort. In
addition to screening out unacceptable projects, sustainable development
criteria could also play a role through a reward system to encourage more
desirable projects. Premiums =
for
benefits in such areas as biodiversity and social parameters could be
incorporated into the carbon crediting structure adopted by the Parties (e.=
g.,
Schneider, 1998; Schneider et al.,
2000). The extent that such a
system is implemented will determine the extent to which the effects of
discount rate choices for C will guide development in desirable or perverse
directions, or a mixture of both.
6. Conclusions=
1.) Mg-year equival=
ence
provides a needed mechanism for comparing the global warming impacts of
different activities and the benefits of different mitigation projects. It allows temporary sequestration =
of CO2
to be compared on a equitable and consistent basis with permanent C
sequestration or fossil fuel emission avoidance.
2.) Time preference,
expressed by means of a discount rate on C, can be applied to Mg-year
equivalence calculations to allow societal decisions regarding the value of
time to be integrated into the system for calculating global warming impacts
and benefits. The moral choic=
e of
specifying a value for time, zero or otherwise, cannot be avoided.
3.) Time-preference
choices for C through discount rate (or alternative mechanisms) can strongly
influence economic decisions and the social and environmental impacts and/or
benefits of the favored mitigation options. For example, the choice between cr=
eating
protected areas and instituting policy measures to slow deforestation rates=
is
heavily depending on time preference.
Pending decisions on sustainable development criteria under the Kyoto
Protocol could be critical in determining the consequences that C
time-preference choices have in spheres other than global warming.
&n=
bsp;
Acknowl=
edgments
An earlier version of this discussion was
presented at the 8th Meeting of the F-7 research network on trop=
ical
forests and climate change, 27-28 August 1999, Wageningen, the
Netherlands. Brazil's National
Council of Scientific and Technological Development (CNPq AIs 350230/97-98
& 523980/96-5) and the National Institute for Research in the Amazon (I=
NPA
PPIs 5-3150 & 1-3160) provided financial support. We thank F. Joos for =
the
revised Bern model. S.=
V.
Wilson P.M.L.A. Graça, R. Dixon and three reviewers provided helpful
comments.
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FIGURE LEGENDS
Figure 1. Cascading effect of displaced emis=
sions:
case where C reserve (forest or fossil) lasts beyond the end of the time
horizon. In this example no a=
ccount
is taken of movement of carbon from atmosphere to other pools over the time
horizon. A net gain is achiev=
ed.
Figure 2. Cascading effect of displaced emis=
sions:
case where C reserve (forest) runs out within the time horizon. In this example no account is take=
n of
movement of CO2 from atmosphere to other pools over the time
horizon. No net gain is achie=
ved.
Figure 3. Discount rate equivalent of a time
horizon. The area under a neg=
ative
exponential curve at approximately 1% annual discount (assuming truncation =
at
year 1000) is equal to that under the 100-year time horizon zero discount
system adopted for global warming potentials.
Figure 4. Alternative indices of the value of
delaying emissions. Benefit i=
n a
fixed year, such as 2070 (option A) is one measure. The difference between the integra=
ls
within the time horizon, which is equal to the area pushed beyond the time
horizon in the curve for the delayed emission (option B) is the index used =
in
the present paper.
Figure 5. Alternative methods of crediting C=
O2
sequestration. Method (A) fol=
lows C
in planted trees, results in a greater calculated benefit for delaying an
emission (through sequestration) than does Method (B), which follows
atmospheric pools of carbon.
Figure 6. Effect of forest degradation on
mitigation through avoided deforestation: case where forest is destroyed be=
fore
the end of the time horizon.
Figure 7. Effect of forest degradation on
mitigation through avoided deforestation: case where forest lasts beyond the
end of the time horizon.
Figure 8. Human-life benefit of delaying glo=
bal
warming. This provides a rati=
onale
for discounting independent of arguments based on money.<=
/p>
Figure 9. Discount rate effects on the impac=
t of C
emissions in different years.
Figure 10. Discount rate effects on C credit =
earned
by delaying emissions for different periods.
Figure 11. Comparison =
of
park creation versus policy changes to slow deforestation in a hypothetical
country where continuation of the current rate of deforestation would elimi=
nate
the remaining forest in nine years (A.).&n=
bsp;
Here, creation of a park from 1/18 (5.5%) of the remaining forest (B=
.)
is compared with a policy change slowing deforestation by 50% (i.e., doubli=
ng
the time to the expected demise of the forest to 18 years) (C.). In the park creation case, defores=
tation
is assumed to continue unchanged outside of the park (i.e., there is 100%
leakage). The graphs at the r=
ight
include effects of CO2, CH4 and N2O. A 100-year time horizon is assumed=
.
Figure 12. Effect of
discount rate on the area of park that would need to be created to be
equivalent to deforestation rate reductions of 50% and 40%. If park area is 5.5% of remaining =
forest
and the deforestation rate reduction is 50% (as in Fig. 11), the switchover
from parks to slowing deforestation as the preferred strategy occurs at an
annual discount rate of 0.73%, assuming a time horizon of 100 years.
Figure 13. Relation of=
the
relative impact on the atmosphere of park creation versus slowing deforesta=
tion
at different discount rates. =
In
this example, a 25% reduction in deforestation rate would be preferable to
creating a park from 11% of the remaining forest if the annual discount rat=
e is
less than 1.45%, but the 25% deforestation rate reduction would be preferab=
le
at discount rates above this value; a 50% deforestation rate reduction woul=
d be
preferable to a park of the same size at all discount rates. A 45-year baseline time to defores=
tation
and a 100-year time horizon are assumed.
|
Table 1: =
|
|
|
|
|
|
|
|
|
|
|
|
Climatic impact
per hectare of tropical deforestation, including effects of non-CO2<=
/sub>
GHGs and discounting
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
Year
|
Atmospheric lo=
ad
(t gas)(a)
|
|
CO2=
-C
equivalent (t)(b)
|
|
Total CO2=
-C
equivalent (t)
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
CO2
|
CH4
|
N2O
|
|
CO2
|
CH4
|
N2O
|
|
Discount =
|
Discount<=
/span>
|
Discount<=
/span>
|
|
|
|
|
|
|
|
|
|
|
|
0 %/year<=
/span>
|
1 %/year<=
/span>
|
2 %/year<=
/span>
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1
|
677
|
0.97
|
0.09
|
|
185
|
15.42
|
5.09
|
|
205
|
205
|
205
|
|
|
2
|
623
|
0.92
|
0.09
|
|
170
|
14.57
|
5.06
|
|
190
|
188
|
186
|
|
|
3
|
581
|
0.87
|
0.09
|
|
158
|
13.76
|
5.03
|
|
177
|
175
|
174
|
|
|
4
|
540
|
0.82
|
0.09
|
|
149
|
13.00
|
5.00
|
|
167
|
166
|
164
|
|
|
5
|
520
|
0.78
|
0.09
|
|
142
|
12.28
|
4.97
|
|
159
|
156
|
156
|
|
|
:
|
:
|
:
|
:
|
|
:
|
:
|
:
|
|
:
|
:
|
:
|
|
|
10
|
441
|
0.58
|
0.09
|
|
120
|
9.25
|
4.83
|
|
134
|
133
|
132
|
|
|
:
|
:
|
:
|
:
|
|
:
|
:
|
:
|
|
:
|
:
|
:
|
|
|
25
|
350
|
0.25
|
0.08
|
|
95
|
3.94
|
4.43
|
|
104
|
103
|
102
|
|
|
:
|
:
|
:
|
:
|
|
:
|
:
|
:
|
|
:
|
:
|
:
|
|
|
50
|
281
|
0.06
|
0.07
|
|
77
|
0.95
|
3.83
|
|
81
|
81
|
80
|
|
|
:
|
:
|
:
|
:
|
|
:
|
:
|
:
|
|
:
|
:
|
:
|
|
|
75
|
246
|
0.01
|
0.06
|
|
67
|
0.23
|
3.32
|
|
71
|
70
|
69
|
|
|
:
|
:
|
:
|
:
|
|
:
|
:
|
:
|
|
:
|
:
|
:
|
|
|
100
|
225
|
0.00
|
0.05
|
|
61
|
0.06
|
2.87
|
|
64
|
64
|
63
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
Total
|
|
|
|
|
8,509
|
278.18
|
387.68
|
|
9,175
|
9,085
|
8,995
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
(a) Per-hectare
emissions are average net committed emissions for 1990 deforestation in
Brazilian Amazonia (Fearnside, 2000b).&nbs=
p;
Atmospheric loads of all gases decline as in the IPCC’s Second
Assessment Report (SAR) (Schimel et=
al.,
1996): CO2 declines non-linearly in accord with the Revised Bern
Model while CH4 and N2O decline exponentially with ha=
lf
lives of 12.2 and 120 years, respectively.
(b) Instantane=
ous
radiative forcings per ton of gas are taken from the SAR (Shine et al., 1995): 1 for CO2, 58
for CH4 and 206 for N2O.
|
Table 2:
|
|
|
|
|
|
|
|
|
|
|
Human life value of delaying global warming
Item &nbs=
p; &=
nbsp; &nbs=
p; &=
nbsp;
Value &nbs=
p;
Units &nbs=
p;
Source
|
|
|
|
|
|
|
|
|
|
|
|
|
Mortality at 2 X CO2, with constant
population
|
138,000
|
lives/year
|
(Fankhauser, 1995;
Pearce et =
al.,
1996)
|
|
|
|
|
|
|
|
|
|
Fossil fuel annual emission 1981-1990
|
|
|
6
|
PgC/year
|
(Watson et=
al.,
1992: 29)
|
|
|
|
|
|
|
|
|
|
|
|
|
Tropical forest land-use change<=
/p>
annual emission 1981-1990
|
|
|
2.4
|
PgC/year
|
(Fearnside, 2000d).
|
|
|
|
|
|
|
|
|
|
Total annual anthropogenic emission
1981-1990
|
|
8.4
|
PgC/year
|
Calculated as fossil fuel + tropical land-use chan=
ge
annual emissions
|
|
|
|
|
|
|
|
|
|
|
|
|
Value of avoided emission
|
|
|
60,870
|
MgC immediate emission equivalent/life<=
/span>
|
Calculated as total annual anthropogenic emission /
mortality at 2 X CO2
|
|
|
|
|
|
|
|
|
|
|
|
|
|
Value of avoided emission
|
|
|
16.4
|
lives/million MgC immediate emission equivalent
|
Calculated as mortality at 2 X CO2 / to=
tal annual
anthropogenic emission
|
|
|
|
|
|
|
|
|
|
|
|
|
Fig 1
Cascading effect of displaced emissions: large forest ca=
se
&=
nbsp; &nbs=
p; &=
nbsp; &nbs=
p; &=
nbsp; &nbs=
p; =
Time
Total
&=
nbsp; &nbs=
p; &=
nbsp; &nbs=
p; &=
nbsp; &nbs=
p; =
Horizon
emission
&=
nbsp; &nbs=
p; &=
nbsp; &nbs=
p; &=
nbsp; &nbs=
p; &=
nbsp; ¯<=
/span>&nb=
sp;
(tC)
&nb=
sp;
&=
nbsp; &nbs=
p; Year&nb=
sp; =
1=
&=
nbsp; 2 &=
nbsp; 3 . . . n
&nb=
sp;
&=
nbsp; &nbs=
p; Baseline&nb=
sp; =
ton1 ton2 ton3 . .ton<=
sub>n n
&=
nbsp; &nbs=
p; Scenario
&nb=
sp;
&=
nbsp; &nbs=
p; Mitigation&nb=
sp; =
ton1 ton2 . .ton<=
sub>n-1 n-1
&=
nbsp; &nbs=
p; Scenario
&nb=
sp;
&=
nbsp; &nbs=
p; Benefit &=
nbsp; &nbs=
p; &=
nbsp; 1
Fig. 2
Cascading effect of displaced emissions:
small forest case
&=
nbsp; &nbs=
p; &=
nbsp; &nbs=
p; &=
nbsp; &nbs=
p; =
Time Total
&=
nbsp; &nbs=
p; &=
nbsp; &nbs=
p; &=
nbsp; &nbs=
p; =
Horizon
emission
&=
nbsp; &nbs=
p; &=
nbsp; &nbs=
p; &=
nbsp; &nbs=
p; &=
nbsp; ¯<=
/span>&nb=
sp;
(tC)
&nb=
sp;
&=
nbsp; &nbs=
p; Year&nb=
sp; =
1=
&=
nbsp; 2 &=
nbsp; 3 . . . n
&nb=
sp;
&=
nbsp; &nbs=
p; Baseline&nb=
sp; =
ton1 ton2 &=
nbsp; &nbs=
p; 2
&=
nbsp; &nbs=
p; Scenario
&nb=
sp;
&=
nbsp; &nbs=
p; Mitigation&nb=
sp; =
ton1 ton2 &=
nbsp; 2
&=
nbsp; &nbs=
p; Scenario
&nb=
sp;
&=
nbsp; &nbs=
p; Benefit &=
nbsp; &nbs=
p; &=
nbsp; 0
&nb=
sp;
Fig. 3
![](3D"timing-revised-2_arquivos/image002.gif")
Fig. 4
![](3D"timing-revised-2_arquivos/image004.jpg")
Fig. 5
![](3D"timing-revised-2_arquivos/image006.jpg")
Fig. 6![](3D"timing-revised-2_arquivos/image008.jpg")
Fig. 7
![](3D"timing-revised-2_arquivos/image010.jpg")
Fig. 8
![](3D"timing-revised-2_arquivos/image012.gif")
Fig. 9
![](3D"timing-revised-2_arquivos/image014.gif")
Fig. 10
![](3D"timing-revised-2_arquivos/image016.gif")
Fig. 11
![](3D"timing-revised-2_arquivos/image018.gif")
Fig. 12
![](3D"timing-revised-2_arquivos/image020.gif")
Fig. 13
![](3D"timing-revised-2_arquivos/image022.gif")
------=_NextPart_01C721FF.C33FBDA0
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