9.2.2.8 Energy

Access to energy is severely constrained in sub-Saharan Africa, with an estimated 51% of urban populations and only about 8% of rural populations having access to electricity. This is compared with about 99% of urban populations and about 80% of rural populations who have access in northern Africa (IEA, 2002). Other exceptions also include South Africa, Ghana and Mauritius. Extreme poverty and the lack of access to other fuels mean that 80% of the overall African population relies primarily on biomass to meet its residential needs, with this fuel source supplying more than 80% of the energy consumed in sub-Saharan Africa (Hall and Scrase, 2005). In Kenya, Tanzania, Mozambique and Zambia, for example, nearly all rural households use wood for cooking and over 90% of urban households use charcoal (e.g., IEA, 2002, p. 386; van Jaarsveld et al., 2005). Dependence on biomass can promote the removal of vegetation. The absence of efficient and affordable energy services can also result in a number of other impacts including health impacts associated with the carrying of fuelwood, indoor pollution and other hazards (e.g., informal settlement fires - IEA, 2002). Further challenges from urbanisation, rising energy demands and volatile oil prices further compound energy issues in Africa (ESMAP, 2005).

9.2.2.9 Complex disasters and conflicts

The juxtaposition of many of the complex socio-economic factors outlined above and the interplay between biophysical hazards (e.g., climate hazards - tropical cyclones, fire, insect plagues) is convincingly highlighted in the impacts and vulnerabilities to disaster risks and conflicts in several areas of the continent (see, for example, several reports of the International Federation of the Red Cross and Red Crescent Societies (IFRCRCS) of the past few years, available online at http://www.ifrc.org/; and several relevant documents such as those located on http://www.unisdr.org/) (see Figure 9.1b). Many disasters are caused by a combination of a climate stressor (e.g., drought, flood) and other factors such as conflict, disease outbreaks and other ‘creeping’ factors e.g., economic degradation over time (Benson and Clay, 2004; Reason and Keibel, 2004; Eriksen et al., 2005). The role of these multiple interactions is well illustrated in the case of Malawi and Mozambique. In 2000 in Malawi, agriculture accounted for about 40% of the GDP, a drop of about 4% from 1980. The real annual fluctuations in agricultural, non-agricultural and total GDP for 1980 to 2001 show that losses during droughts (e.g., as occurred in the mid-1990s) were more severe than disaster losses during the floods in 2001 (Benson and Clay, 2004) (for more details on structural causes and drought interactions and impacts, e.g., food security, see Section 9.6.1). Likewise, the floods in Mozambique in 2000 revealed a number of existing vulnerabilities that were heightened by the floods. These included: poverty (an estimated 40% of the population lives on less than US$1 per day and another 40% on less than US$2 per day); the debt problem, which is one of the biggest challenges facing the country; the fact that most of the floodwaters originated in cross-border shared basins; the poor disaster risk-reduction strategies with regard to dam design and management; and the poor communication networks (Christie and Hanlon, 2001; IFRCRCS, 2002; Mirza, 2003).

Conflicts, armed and otherwise, have recently occurred in the Greater Horn of Africa (Somalia, Ethiopia and Sudan) and the Great Lakes region (Burundi, Rwanda and the Democratic Republic of Congo) (Lind and Sturman, 2002; Nkomo et al., 2006). The causes of such conflicts include structural inequalities, resource mismanagement and predatory States. Elsewhere, land distribution and land scarcity have promoted conflict (e.g., Darfur, Sudan; see, for example, Abdalla, 2006), often exacerbated by environmental degradation. Ethnicity is also often a key driving force behind conflict (Lind and Sturman, 2002; Balint-Kurti, 2005; Ron, 2005). Climate change may become a contributing factor to conflicts in the future, particularly those concerning resource scarcity, for example, scarcity of water (Ashton, 2002; Fiki and Lee, 2004),).

It is against this background that an assessment of vulnerability to climate change and variability has to be contextualised. Although the commonly used indicators have limitations in capturing human well-being (Arrow et al., 2004), some aggregated proxies for national-level vulnerability to climate change for the countries in Africa have been developed (e.g., Vincent, 2004; Brooks et al., 2005). These indicators include elements of economy, health and nutrition, education, infrastructure, governance, demography, agriculture, energy and technology. The majority of countries classified as vulnerable in an assessment using such proxies were situated in sub-Saharan Africa (33 of the 50 assessed by Brooks et al., 2005, were sub-Saharan African countries). At the local level, several case studies similarly show that it is the interaction of such ‘multiple stresses’, including composition of livelihoods, the role of social safety nets and other social protection measures, that affects vulnerability and adaptive capacity in Africa (see Section 9.5).