Emissions Scenarios - IPCC

Scenario Driving Forces 141
growth" and "evolutionary" economic models. They have been
able to demonstrate the flaws in some of the simpler solutions
to technology diffusion often advocated - for example, they
show how free trade might sometimes exacerbate existing gaps
in institutions, skills, and technology.
The complex interactions that underpin technology diffusion
may give rise to regularities at an aggregate level. The
geographical and spaflal distribution of successive
technologies displays patterns similar to those found in the
succession of biological species in ecosystems, and also in the
succession of social institutions, cultures, myths, and
languages. These processes have been analyzed, for example,
in CampbeU (1959), Marchetfl (1980), Grübler and
Nakicenovic (1991), and Grübler (1998a). An extensive review
of the process of international technology diffusion is available
in the IPCC Special Report on Methodological and
Technological Issues in Technology Transfer (IPCC, 2000).
That report provides a synthesis of the available knowledge and
experience of the economic, social and institutional processes
involved.
Many attempts to endogenize technical change in economic
models rely on a linear approach in which technical change is
linked to the level of investment in R&D (e.g., Grossman and
Helpman, 1991, 1993). More importantly, this linear model has
been the basis of many governments' strategies for
technological innovation. As mentioned above, important
additional features of technological change include
uncertainty, the reliance on sources of knowledge other than
R&D, "leaming by doing" and other phenomena of "increasing
returns" that often lead to technological "lock in" and hence
great difficulties in introducing new alternatives.
These features can be captured to some degree in models and a
great deal of experimentation has taken place with different
model specifications. However, the first feature, uncertainty,
means that models cannot be used to predict the process of
technical change. This uncertainty stems partly from lack of
knowledge - the outcomes of cutting-edge empirical research
simply cannot be predicted. It also stems from the complexity
of the influences on technological change, and in particular the
social and cultural influences that are extremely difficuh to
describe in fomal models. Recent attempts to endogenize
technical change in energy and economic models are reviewed
by Azar (1996). Opfimizafion models usually treat technology
development as exogenous, but technology deployment as
endogenous and driven by relative technology life-cycle costs.
A few GHG emission projection models (e.g., Messner, 1997)
were developed to incorporate "leaming by doing" - the
reduction in technology costs and improvement in performance
that can result from experience (Arrow, 1962). Models have
also been developed that explicifly include technological
uncertainty to analyze robust technology policy options (e.g.,
Grübler and Messner, 1996; Messner et al, 1996). Other
models developed more recently 1псофога1е the effects of
investment in knowledge and R&D (Goulder and Mathai,
1998). Economists and others who study technological change
have developed models that take a variety of dynamics into
account (Silverberg, 1988). Some models focus on
technologies themselves, for example examining the various
sources of "increasing returns to scale" and "lock-in" (Arthur,
1989, 1994). Other models focus on firms and other decisionmakers,
and their processes of information assimilation,
imitation, and leaming (Nelson and Winter, 1982; Silverberg,
1988; Andersen, 1994). Few of these dynamics, apart from
"increasing returns to scale," have been applied to the
projection of GHG emissions from the energy sector.
3.5. Agriculture and Land-Use Emissions
3.5.1. Introduction
The most important categories of land-use emissions are CO^
from net deforestation, CH^ from rice cultivation, CH^ from
enteric fermentation of cattle, and N^0 from fertilizer
application. These sources account for nearly all the land-use
emissions of COj (Schimel et al., 1995), about 53% of the
land-use emissions of CH4 (Prather, et al, 1995), and about
80% of land-use emissions of Np (Prather, et ai. 1995).
These estimates, however, have a high uncertainty.
Measurements and analyses of other sources of CH^ and N^O
(notably biomass burning, landfills, animal waste, and sewage)
ai-e relatively rare, but increasing (Bogner et al., 1997, in the
literature. Of the scenarios reviewed for this report (see Table
3.7), about 20 address emissions from agriculture and land-use
change (Lashof and Tirpak, 1990; Houghton, 1991; Leggett et
al., 1992; Matsuoka and Morita, 1994; Alcamo et ai, 1998;
Alcamo and Kreileman, 1996; Leemans et al, 1996).
Current assessments of GHG emissions indicate that land use or
land cover activities make an important contribution to the
concentration of GHGs in the atmosphere;-' these are referreà to
as "land-use emissions" in this report."* Of the tl-nee most
important GHGs, the contribution of land-use emissions to total
global COj is relatively small (23%), but it is very large for CH^
(74%) and N^0. Furthermore, although land-use emissions
make up only a small percentage of global COj emissions, they
comprise a large part (45%) of CO^ emissions from developing
countries, and an even larger percentage of their total CH^
(78%) and Np (76%) emissions (Pepper et
al.,1992). Hence, from a variety of perspectives, the
contribution of land-use emissions to total emissions of GHGs
is important, and consequently their future trends are relevant to
the estimation of climate change and its mitigation.
^ These activities include deforestation, afforestation, changes in
agricultural management, and other anthropogenic land-use changes
that result in a net flow of GHGs to or from the atmosphere. They
exclude natural biogenic emissions and emissions that are not
related to anthropogenic activity such as CO2 from volcanoes or
volatile organic compounds from forests.
We include deforestation in this category of emissions even though
this is a process of land-cover change rather than a land-use activity.