7.2.2 Sensitivity and Vulnerability of Human Settlements to Direct and Indirect
Impacts of Climate Change
This chapter highlights some of the key processes through which climate impacts
could occur; individual regional chapters categorize settlements based on size,
location, or complete coverage of the population.
As a result of research that has been done on settlements since the SAR and
RICC, as well as additional interpretation of older research, it is becoming
clearer where many of the key vulnerabilities of human settlements, energy,
and industry occur, although it is still very difficult to provide more than
qualitative guidance. Table 7-1 provides an overview
of these vulnerabilities for the years between approximately 2050 and 2080;
much of the available literature concentrates on the effects of climate change
of a magnitude roughly corresponding to that time period. The table divides
human settlements into general size categories and economic function in a hierarchy
of settlements. The table emphasizes the most salient effects that appear to
be characteristic of certain types of settlements and mechanisms that might
make the settlements more or less sensitive to climate change.
Implications of climate change for development of settlements, energy, and
industry are highly location-specific. For instance, as shown in Table
7-1, climate change is more likely to have important impacts on the development
of settlements in resource-dependent regions or coastal or riverine locations.
Most of the concerns are about possible negative impacts on development (e.g.,
on the comparative advantage of a settlement for economic growth compared with
other locations), although impacts on some areas are likely to be positive.
Impacts on sustainability depend very largely on how climate change interacts
with other processes related to multiple stresses and opportunities—such as
economic, demographic, and technological change—except in low-lying areas that
may be subject to sea-level rise or polar regions whose physical conditions
will be more directly affected by global warming. Equity effects are of considerable
concern because the ability to cope with negative impacts or to take advantage
of positive impacts is likely to be greater among advantaged groups than among
disadvantaged groups, within regions and between regions. As a result, climate
change has the potential to enlarge equity-related gaps in human settlements
and systems.
In general, country studies that have been completed since the SAR was published
have provided more specific regional details concerning sensitivities and vulnerabilities
to climate change (e.g., IPCC, 1998; see Chapters 10–17).
Because of variability in settlements across the world, it is virtually impossible
to create rankings of impacts that do not contain numerous exceptions. However,
the impact ratings in Table 7-1 provide a framework
that can be adapted to local circumstances. Table 7-1
shows the author team’s judgments, based on the available literature, about
the vulnerability of different types of settlement to various aspects of climate
change. The horizontal axis differentiates vulnerability according to type of
settlement, capacity to adapt, and the mechanism through which the settlement
is affected by climate change. For example, the resource base of settlements
that are economically dependent on activities such as agriculture, forestry,
fishing, hunting and gathering, or tourism may be affected; housing and infrastructure
may be affected in coastal areas, riverine floodplains, islands that are sensitive
to flooding, steeplands that are sensitive to landslides, and urban/wildland
boundaries that are sensitive to fires; and the health and productivity of urban
populations may be affected directly through air pollution, heat waves, and
heat island effects. The vertical axis identifies 12 different types of climate
change impact in descending order of global importance. Vulnerabilities are
rated as low, medium, or high magnitude as described in Box
7-1. The information in Table 7-1 generally
is presented as a range, reflecting the diversity of settlements within each
broad class. The final column shows the level of confidence that the author
team assigns to each type of climate impact. Table 7-1
depicts vulnerabilities for the years between approximately 2050 and 2080. Much
of the available human settlements literature is silent on the timing of impacts;
the choice of the years 2050–2080 in Table 7-1 is
based on the size of the impacts or amount of climate change addressed in the
literature reviewed by the author team. Table 7-1
takes into account the number and type of settlements affected worldwide and
the likely strength of these effects by mid-to-late 21st century, as well as
the financial, technical, and institutional capacity of settlements to respond.
Figure 7-2 provides confidence scores for the impacts
on individual scales described more fully in Box 7-1 (see
also Moss and Schneider, 2000).
The negative impacts in Table 7-1 generally would
be less negative or even positive in some regions before 2050 but greater than
shown and becoming more negative in more regions after 2100. The table is not
intended to show that only specific types of settlements would be harmed (or
helped) in certain ways by certain changes; it is intended to show that settlements
of certain types probably are likely to be affected by certain impact mechanisms
and are likely to be particularly vulnerable to certain types of climate changes
or conditions.
Many of the effects in Table 7-1 are quite likely
for some communities in some places; other effects are extremely uncertain,
controversial, or inapplicable. Key articles that underlie the ratings are provided
as footnotes to Table 7-1.
Confidence in the main conclusions of this chapter in Table
7-1 is rated in Figure 7-2 from very high (5)
to very low (1) in four dimensions: support from theory, support from model
results, support from data or trends in the existing environment, and the degree
of consensus in expert opinion. Although these ratings reflect the subjective
judgments of the chapter’s authors concerning the weight that can be given to
each element that increases confidence in the findings, the figure is useful
in depicting the dimensions of the underlying literature that are particularly
strong or weak in support of the chapter’s conclusions. Confidence levels vary
widely:
- Results that are very high on all dimensions, as in the expected vulnerability
of at least some coastal settlements to sea-level rise
- Results that are very strong on most dimensions, such as local capacity
being very important in practice for successful adaptation to environmental
problems (even though the theory has not really been applied to climate change)
- Results that are very high on one or two dimensions, such as human health
effects, where theory and model results are strongly supportive of the conclusion,
whereas data are weaker or ambiguous and experts are somewhat divided
- Results for which there is some evidence, but most of it is only modestly
supportive; one or two modestly strong elements lead to the conclusion, but
confidence is weak.
Box 7-1. Development of Scales for Assessing Potential Vulnerability
of Human Settlements to Effects of Climate Change and Confidence in the
Certainty of Impacts
Climate affects the stability of resources that support human systems.
One way to assess the potential impact of climate change on human systems
is by using a qualitative scale that expresses the vulnerability of settlements
to various kinds of climate effects (e.g., floods) in terms of how potentially
disruptive these climate effects are expected to be for various types
of human settlements (based on differences in their economic base, location,
size, and adaptability). The definitions in the rating system below are
derived from standard environmental impact assessment language and are
intended to apply to local climate impacts. However, the scale may be
used nationally if the nation is small and homogeneous or if most of the
population lives in settlements of a certain type.
Magnitude Ratings (Size of Impacts)
- Low: Impacts of changed climate are not distinguishable from normal
background variability in weather impacts or there is little noticeable
effect.
- Moderate: Resources or sectors are affected noticeably, even substantially,
but the effect is not destabilizing and recovery is rapid.
- High: Impacts are large and sometimes catastrophic. Resources or settlements
are destabilized, with little hope for near-term recovery.
A semi-quantitative approach is used with a 5-point confidence scale
to indicate the certainty of the effects of climate change. The author
team subjectively rated confidence on the basis of the literature in four
dimensions: consensus among experts (consensus), the extent to which underlying
theory and data is developed (theory), the quality of model results (model
results), and the consistency of observational evidence (observations).
The scores were used to create a four-sided polygon, as shown in Figure
7-2 on the facing page. All four dimensions were weighted equally to determine
the area of the polygon and an overall confidence score.
Polygon Area = 0.5 • (Theory • Observations + Observations • Model
Results + Model Results • Consensus + Consensus • Theory)
The overall confidence score assigned was based on the area of the polygon.
For example, to rate a 4 for “high confidence,” the polygon had to have
an area between 16 and 25—the area of a polygon with ratings of greater
than 4 but less than 5 on all four dimensions.
Confidence Rating (Certainty of Impacts)
- Very Low: Impacts are extremely difficult to predict (confidence <
5%) (Polygon Area = 0–8).
- Low: Impacts are regularly much greater or less than the median value
(confidence < 33%) (Polygon Area = 8–18).
- Medium: Impacts are regularly greater or less than the median value
(confidence Ž 33%) (Polygon Area = 18–32).
- High: There is noticeable variation in the size of impacts (confidence
Ž 67%) (Polygon Area = 32–50).
- Very High: There is little variation in impact among scenarios, within
a settlement type (confidence = 95%) (Polygon Area = 50).
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