3.2. Socioeconomic Scenarios
3.2.1. Purpose
The main purposes of socioeconomic scenarios in the assessment of climate impacts,
adaptation, and vulnerability are:
- To characterize demographic, socioeconomic, and technological driving forces
underlying anthropogenic GHG emissions that cause climate change
- To characterize the sensitivity, adaptive capacity, and vulnerability of
social and economic systems in relation to climate change.
This section focuses on the second use. However, in integrated global assessments,
scenarios underpinning these two applications should be consistent with one
another. Many key parameters, such as population and economic growth, are common
to both types of exercise. More flexibility with regard to consistency may be
appropriate at local and regional scales. Regional trends may be diverse, and
developments in a specific region may diverge from those at the global level.
The use of socioeconomic scenarios in assessing vulnerability to climate change
is less well developed than their use in exploring GHG emissions. The IPCC Technical
Guidelines for Assessing Climate Change Impacts and Adaptations (IPCC, 199)
recommend the use of socioeconomic scenarios, with and without climate change,
to assess impacts and adaptive responses. At that time, few studies had reached
that ideal. As new frameworks for characterizing vulnerability develop (Downing
et al., 1999), impact studies can begin to use more consistent, global
scenario approaches.
Socioeconomic scenarios in impact assessment have tended to focus on quantitative
characterization of key parameters and to ignore the qualitative "storyline"
elements of a fully developed scenario approach. If the implications of climate
change impacts and adaptation on sustainable development are to be assessed
(Munasinghe, 2000), much more sophisticated descriptions of vulnerable impact
units will be required, along with better understanding of institutional and
economic coping capacity. Section 3.2 provides examples
of emerging work of this kind.
Socioeconomic scenarios in general have been developed to aid decisionmaking
under conditions of great complexity and uncertainty in which it is not possible
to assign levels of probability to any particular state of the world at a future
point in time. Therefore, it usually is not appropriate to make a statement
of confidence concerning a specific socioeconomic scenario (Moss and Schneider,
2000). However, this does not mean that all scenarios are equally likely. Some,
used to test sensitivities, may be at the limits of the range of plausibility.
More robust statements may be possible about the level of confidence in specific
quantitative indicators, such as population or GDP, associated with given scenarios.
3.2.2. Representing Baseline Conditions
The socioeconomic baseline describes the present or future state of all nonenvironmental
factors that influence an exposure unit. The factors may be geographical (land
use or communications), technological (pollution control, water regulation),
managerial (forest rotation, fertilizer use), legislative (water-use quotas,
air quality standards), economic (income levels, commodity prices), social (population,
diet), or political (levels and styles of decisionmaking). The IPCC has published
a set of baseline statistics for 195 countries that are representative of the
early to mid-1990s (IPCC, 1998). The data were collected from a variety of sources,
such as the World Bank, the United Nations Environment Programme (UNEP), and
the Food and Agriculture Organization (FAO) (see Table 3-1).
These are only selected, summary data; individual impact studies are likely
to require information on other factors or at a much higher spatial resolution.
Climate change impact assessment requires sound understanding of current socioeconomic
vulnerabilities. These vulnerabilities have implications for deliberate adaptations
that "involve conscious actions to mitigate or exploit the effects of climate
change" (Adger, 1999). Many of those who are exposed will be vulnerable
to a range of other stresses, irrespective of climate change (e.g., high population
growth, rapid urbanization, environmental degradation, ambient air pollution,
social inequality, infrastructure degradation, and health hazards). In time,
stresses associated with the development process may reinforce those generated
by climate change. For instance, sea-level rise causes saltwater intrusion,
which can be aggravated by diverting freshwater outflows to satisfy the needs
of agriculture, energy, and human consumption.
| Table 3-1: Dimensions and attributes of socioeconomic
scenarios reported in some recent climate change impact and adaptation assessments. |
 |
| Scenarios |
IPCC Basea |
SRES |
Pakistanc |
UKCIPd |
ACACIAe |
USNACCf |
| |
| Time frame/horizon |
Early 1990s |
1990-2100 |
2020/2050 |
2020s/2050 |
2020s/2050s/2080s |
2050/2100 |
| |
| Focus |
Impacts |
Emissions |
Impacts |
Impacts |
Impacts |
Both |
| |
| Scenario attributesg |
|
|
|
|
|
|
| - Economic growth |
X
|
X
|
X
|
X
|
X
|
X
|
| - Population |
X
|
X
|
X
|
X
|
|
X
|
|
- Land use
|
X
|
X
|
X
|
X
|
|
X
|
|
- Energy
|
X
|
X
|
X
|
X
|
|
X
|
|
- Agriculture/food production
|
X
|
|
X
|
X
|
|
|
|
- Technological change
|
|
X
|
|
X
|
X
|
X
|
|
- Water
|
X
|
|
|
X
|
|
|
|
- Level of governance
|
|
X
|
|
X
|
X
|
|
|
- Social values
|
|
X
|
|
X
|
X
|
|
|
- Contextual data
|
|
|
|
|
|
X
|
|
- Institutional change
|
|
|
|
|
|
X
|
|
- Biodiversity
|
X
|
|
|
X
|
|
|
|
- Coastal zone management
|
|
|
|
X
|
|
|
|
- Settlement patterns
|
|
|
|
X
|
|
|
|
- Political organization
|
|
|
|
|
X
|
|
|
- Social policy
|
|
X
|
|
|
X
|
|
|
- Environmental policy
|
|
X
|
|
|
X
|
|
|
- Regional development
|
|
X
|
|
|
X
|
|
|
- Literacy
|
|
|
X
|
|
|
|
|
- Health care
|
|
|
X
|
|
|
|
| |
|
