6. Impact vulnerability.
The anticipated impact of sea-level rise (SLR) has three elements: Natural expansion as the ocean warms; higher ocean levels from icecap melting; and higher storm surges. Recent evidence suggests that the polar caps are melting more quickly than anticipated, and forecasts of a 1-meter rise in this century no longer appear implausible. If melting accelerates further, a 3-meter forecast will become plausible. (8) A recent study by DECRG (Dasgupta et al., 2007) has used high-resolution digital mapping to estimate country impacts of SLR in the range of 1-5 meters. Using GIS overlays, the study computes the percentages of total population, agriculture and general economic activity on land that will be covered by a 1 and 3-meter SLR. For this paper, we index the potential impact using the average 3-meter percent coverage for GDP. The study focuses on developing countries that are not small islands, so we do not have comparative SLR impact measures for most islands. However, it is clear that many small islands will be seriously impacted by SLR. We have only one comparable island economy, the Bahamas, whose estimated coverage area at 3-meter SLR accounts for 14.5% of current GDP. This is one of the highest estimated impacts in the world. To account for this factor in our comparative assessment, we arbitrarily assign other small islands a 15% estimate for GDP coverage. Table 13 provides a summary of SLR estimates that we use for this study. With the exception of island states, coverage is reasonably complete for World Bank client countries. Non-island states with measured impacts (9) include 27 of 42 countries in Sub-Saharan Africa, 10 of 11 in East Asia / Pacific, 7 of 28 in Europe / Central Asia, 21 of 23 in Latin America / Caribbean, 9 of 14 in Middle East / North Africa, and 4 of 7 in South Asia.
Table 14 presents impact estimates for specific countries. Besides island states, where significant impacts are likely in most cases, the distribution of potential impacts for a 3-meter SLR is strongly skewed in all regions. East Asia / Pacific registers most strongly, with 8 of 10 measured non-island countries experiencing an impact of 1% or more. These are large, populous countries, so the implications of SLR for this region (which also includes many islands) are clearly serious. Vietnam is particularly striking (24.2%, reflecting heavy impacts in the Mekong and Red River Deltas), and China's estimated impact (5.6%) is huge in absolute value. Sub-Saharan Africa has a lower incidence, with impacts over 1% in 10 of 27 measured non-island countries. However, four states experience heavy impacts: Mauritania (17.5%), Benin (14.8%), Senegal (8.1%) and Gambia (7.6%). Among European and Central Asian countries 4 have impacts above 1% of GDP: Georgia (2%), Ukraine (1.5%), Estonia (1.5%) and Turkey (1.1%). In Latin America, 12 countries have impacts in a comparable range, while Middle East./North Africa has four: Egypt (12.1%), Tunisia (4.9%), Libya (2.4%) and Oman (1.4%).
In summary, our assessment for a 3-meter SLR suggests that GDP impact percentages greater than 5% will be mostly limited to islands and small coastal states. However, there are important exceptions to this pattern in Sub-Saharan Africa, North Africa and East Asia. In South Asia and Latin America as well, relatively "modest" impacts for states such as India, Bangladesh, Brazil and Mexico translate to very large absolute numbers.
6.2 Weather Damage
Regional forecasts of climate change remain uncertain, although there is general agreement that variability will increase, and existing weather conditions are likely to be exacerbated. At present, it seems most reasonable to assume that future weather conditions in each country will reflect historical conditions, but with more extreme events. To index expected damage, we draw on the Emergency Disasters Database (EMDAT) maintained by the Center for Research on the Epidemiology of Disasters at the Universite Catholique de Louvain in Brussels. We develop our country indices from all recorded disasters during the period 1960-2002 that are attributed to weather-related events: droughts, extreme temperatures, floods, wild fires and wind storms. Since estimates of economic damage are extremely spotty, we develop a weighted damage measure from population impacts in three categories: killed (weight 1000), homeless (10) and affected (1). Then we divide by population for 1980 (the midpoint of the period) to develop the final index: population impact relative to population size. Table 15 summarizes the results by region, while Table 16 presents country indices.
Both tables illustrate two striking facets of these data. First, there are very large regional differences in human vulnerability to weather events. For South Asia and East Asia / Pacific, the median indices for population impact relative to size are over twice the indices for Sub-Saharan Africa and Latin America / Caribbean. These are, in turn, at least four times the index for Middle East / North Africa and 14 times the index for Eastern Europe and Central Asia. Second, intraregional distributions are quite skewed, and at least one country in several regions has extreme vulnerability relative to the others. Clear outlier countries include Ethiopia, Mozambique, Sudan, Honduras, Iran and Bangladesh.
Among countries with large populations, those with vulnerability indices above 200 are Ethiopia (1,809), Philippines (392), Vietnam (235), China (223), Bangladesh (1,940) and India (566). Island states with indices above 200 also figure prominently in the Pacific (Tonga, Somoa, Solomons, Vanuatu, Fiji) and the Caribbean (Antigua and Barbuda, Haiti, St. Lucia).
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|Author:||Buys, Piet; Deichmann, Uwe; Meisner, Craig; That, Thao Ton; Wheeler, David|
|Publication:||Country Stakes In Climate Change Negotiations: Two Dimensions of Vulnerability|
|Date:||Aug 1, 2007|
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