Sub Saharan Africa

Each of the 47 countries in sub-Saharan Africa (SSA) has its own mix of primary crops and diets (Chapter 2). Nonetheless, as a whole Africa can be characterized as a continent heavily dependent on C4 cereals (maize, sorghum, and millets), cassava, groundnuts, and, to a lesser extent, rice and wheat. SSA is also generally characterized by hot growing conditions relative to much of the developed world, although Southern African growing seasons can be relatively cool. Outside of a few countries, such as Sudan, irrigation is very rare in SSA, with roughly 5% of cereal area in irrigation as of 1995 and little growth expected by 2025 (Rosegrant et al. 2002).

Given these conditions - a warm baseline climate, a lack of irrigation, and a predominance of C4 crops unlikely to respond strongly to higher CO2 - it is not surprising that model projections of climate impacts on SSA crops have tended to be negative. In a study using CERES-Maize for all countries in SSA and Latin America, Jones and Thornton (2003) project a fairly average modest decline of 10% by 2055 using a climate scenario from the Hadley CM2 model, though they point to a wide range of impacts between and even within several countries.

Others have suggested more negative impacts, most notably the fourth assessment report of the IPCC, whose chapter on Africa concludes that "reductions in yield in some countries could be as much as 50% by 2020" (Boko et al. 2007).

Though this statement is accompanied only by a citation of a discussion paper on historical losses in drought years in Northern Africa, it nonetheless received widespread media attention.

There has been less work specifically devoted to SSA than many other regions, and as a result the understanding of potential outcomes and uncertainties has been quite limited (Challinor et al. 2007). The World Bank recently commissioned a series of cross-sectional studies of crop revenue in Africa (e.g., Kurukulasuriya et al. 2006), with mixed results but generally negative impacts. Time series models indicate that Southern Africa is extremely sensitive to warming, more so than the warmer tropical regions (Lobell et al. 2008). A likely reason for this is that fertilizer rates and average yields in Southern Africa are considerably higher, so that there is more room for damage in hot years relative to cool years.

Combining data from all countries into a panel analysis for the 1961-2002 period, a recent analysis by Schlenker and Lobell (2009) attempted to estimate the probability of different levels of yield impacts by 2050 for five major crops in SSA: maize, sorghum, millet, groundnuts, and cassava. The first four were found to have significant negative responses (not accounting for CO2 fertilization), even in the case of millet that is generally regarded as relatively tolerant of hot conditions. There was no clear relationship between cassava production and either temperature or rainfall, likely because cassava harvests are irregular and therefore collection of production data and definition of growing season weather are much more difficult than for other crops.

A comparison of the impact probability distributions for maize with point-estimates from previous studies is shown in Fig. 10.5 for four countries (for a more complete comparison, see Schlenker and Lobell 2009). The estimates of Parry et al. (1999) and Jones and Thornton (2003) generally fall within the distributions, although they tend toward the optimistic end of the range in most countries. Impacts projected by the FAO model (Fischer et al. 2002) in contrast appear much more optimistic than the other three studies. Since Fischer et al. (2002) only report estimates

Fig. 10.5 Estimated probability distribution of maize yield impacts of climate change, without adaptation, in selected African countries, based on Schlenker and Lobell (2009). Gray bars show 25th-75th percentile of estimates, whiskers show 5th-95th percentile, and middle vertical line shows median projection. Point estimates from Parry et al. (1999) ("P"), Fischer et al. 2002 ("F"), and Jones and Thornton (2003) ("JT") are shown for comparison

Fig. 10.5 Estimated probability distribution of maize yield impacts of climate change, without adaptation, in selected African countries, based on Schlenker and Lobell (2009). Gray bars show 25th-75th percentile of estimates, whiskers show 5th-95th percentile, and middle vertical line shows median projection. Point estimates from Parry et al. (1999) ("P"), Fischer et al. 2002 ("F"), and Jones and Thornton (2003) ("JT") are shown for comparison of impacts with CO2 fertilization, we have subtracted 4% from each projection, equivalent to the reported CO2 response for the AEZ model (Tubiello et al. 2007). This may explain some of the positive bias in the FAO relative to the other models, but in general the FAO results appear hard to justify, especially given the limited documentation of the model's performance in simulating present-day African yields. Overall, the results in Fig. 10.5 support the notion that climate change presents a serious risk to African crop yields, and that losses by 2050 could easily exceed 20% in many countries.

Renewable Energy 101

Renewable Energy 101

Renewable energy is energy that is generated from sunlight, rain, tides, geothermal heat and wind. These sources are naturally and constantly replenished, which is why they are deemed as renewable. The usage of renewable energy sources is very important when considering the sustainability of the existing energy usage of the world. While there is currently an abundance of non-renewable energy sources, such as nuclear fuels, these energy sources are depleting. In addition to being a non-renewable supply, the non-renewable energy sources release emissions into the air, which has an adverse effect on the environment.

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