The Nexus between Energy, Food, Land Use, and Water
Application of a Multi-Scale Integrated Approach

The Republic of South Africa

  • The Nexus Assessment Project was commissioned by the Energy Team of the Climate, Energy and Tenure Division (NRC) of the UN Food and Agriculture Organisation (FAO)

    and sponsored by the Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ).

Artist's impression of PS50 superheated solar power tower; courtesy of Abengoa.
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In 2004, the South African government set a 100% electrification target by the end of 2012. However, given current electrification rates it recently had to push the universal electrification goal out to 2025. South Africa’s energy system is heavily based on conventional non-renewable energy resources. It is Africa's largest generator of GHG emissions and is among the top 10 countries with the worst “carbon footprint” in the world. In addition, current dependence of its food-supply on fossil energy (the food sector accounting for 30% of SA’s total energy consumption) makes it vulnerable to fluctuating and rising fossil-fuel prices.

How can MuSIASEM be employed to generate an integrated assessment of the potential contribution and convenience of Concentrated Solar Power (CSP) and woody biomass as alternative sources for the production of electricity?


The objective of this case study was to check how MuSIASEM can be employed to generate an integrated assessment of the potential contribution (quantity) and convenience (quality) of concentrated solar power (CSP) and woody biomass as alternative sources for the production of electricity in South Africa. We used ‘plausible’ results of published studies providing quantitative analysis of CSP and woody biomass as input for our analysis, and in particular for the characterization of the demand of production factors per net supply of energy carrier (in this case electricity). This characterization includes technical and logistic aspects. Thus, in this case study we illustrate the handling of a technical and a spatial analysis in an integrated system of accounting capable of assessing the potential (both in quantitative and qualitative terms) of alternative energy sources. Most of the data used in this case study are from the International Energy Agency and refer to 2010 unless stated otherwise.

Diagnostic Analysis of the South African Energy Sector

Given the focus on the assessment of the quality of primary energy sources (PES) and the production process of energy carriers (EC), we single out the energy sector as the hypercyclic compartment of society. The requirement of energy carriers in society or gross supply of energy carriers (depending on whether we look at the metabolic flow from the demand or supply side) is determined by: (i) the sum of the consumption of energy carriers in the various compartments of society, as indicated by the vectors of end-uses, plus the exports (the net supply of energy carriers), and (ii) the losses. The gross supply is generated by the hypercyclic part (Energy & Mining) plus the imports.

In our analysis we address the external and internal view, given that primary energy sources belong to the perception from outside and the generation of surplus of energy carriers in the process of exploitation of primary energy sources to the perception from within society. This interface between the set of locally available primary energy sources and the processes taking place within the energy and mining sector is shown in Fig. 10.

The change of perspective, from the external to the internal view, implies switching from ‘scalars’ to ‘vectors’ in the quantitative representation, that is switching from Gross Energy Requirements (scalar quantities measured in GER-thermal joules) to Energy Carriers (vectors of different typologies of EC in joules) in the assessment of energy quantities. We recall here that according to the first and second laws of thermodynamics energy cannot be created. Therefore, by definition, primary energy sources must be favourable physical gradients provided by boundary conditions (by processes taking place outside human control) available to humans. These favourable boundary conditions enable the production of a net supply of energy carriers.

In the PES/EC supply matrix shown in Fig. 10, we assess the relative contribution of each energy source in relation to the total net supply of energy carriers in the EM sector. We establish a relation between the overall characteristics of the EM sector (using a vector) and the characteristics of its subparts (using matrices). In particular, we distinguish three main categories of energy products: (1) Physical gradients, which correspond to the domestic supply of primary energy sources (PES); (2) Imports as GER-thermal, which correspond to the imported products used for making energy carriers (e.g. coal or fuel to power plants or refineries); and (3) Imports as energy carrier (EC), which correspond to the import of energy products that are used directly as energy carriers (e.g. petroleum products or electricity with no conversion losses).

The energy supply matrix is useful to identify the profiles of use of production factors (labour and power capacity) and the requirement of energy carriers required for the exploitation of different types of primary energy sources. The combination of the characteristics of the various vectors of the matrix (determined by the relative contribution of each energy source) define the overall consumption of production factors and energy carriers that society has to invest in the energy & mining sector to generate its internal gross supply of energy carriers. On the basis of this representation of energy flows, we propose the following two indicators:

  1. Potential Supply of a given energy source - external view: this indicator is useful to perform a check on external constraints as it provides an assessment of the size (in extensive terms) of the Net Supply of Energy Carriers (NSEC) expressed in PJ-GER using the GER/NSEC equivalence ratios;
  2. Energy Return On Investment (EROI) – internal view: within our approach, this indicator is defined as the amount of energy carriers that has to be invested in the exploitation of a Primary Energy Source in order to generate the net supply of energy carriers. We calculated the EROI ratio for the production of electricity from different types of primary energy sources, from the vectors and matrices. Note that with our method of calculation, EROI values differ from those obtained with the conventional method developed by Charlie Hall. For example, in our accounting the EROI of imported energy carrier results infinite as no investments in the energy and mining sector are required for its generation.

When we aggregate the information of the various EROI (using vectors and matrices) into an assessment referring to the whole society - considering GSEC of the whole society as “the energy return” and the energy carriers consumed in the end-uses of the energy & mining sector as “the energy investment” - we obtain an assessment of the so-called Strength of the Exosomatic Hypercycle (SEH). This parameter is defined as the ratio of the overall size of the gross supply of energy carriers to the whole society (including both the dissipative and hypercyclic parts) to the energy throughput within the energy & mining sector (hypercycle part, when focusing on the metabolic pattern of energy). Including the effect of imports, the strength of the exosomatic hypercycle is 60:1 for the South African energy sector. When the analysis is limited to the generation of electricity, it drops to 46:1 because the cost of production is generally higher for mechanical energy (electricity) than for thermal energy carriers.

Integrated assessment of the potential of CSP and woody biomass for electricity production

We consider here two options for generating electricity with alternative primary energy sources that can potentially replace fossil energy sources:

  1. Concentrated Solar Power (CSP): power tower systems similar to the one considered for the 50 MW Bokpoort CSP power plant in South Africa under the UN’s CDM programme (UNFCC 2012-TR). For this scenario, we used data referring to the similar 20MW Gemasolar plant in Spain with molten salt storage and wet cooling (Torresol Energy 2011).
  2. Woody biomass for electricity production: dry woodchips production from forestry residue in South Africa. For this scenario, we used data from the literature (Torresol Energy 2011; Larrain and Escobar 2012 (CSP); Pimentel et al. 2002; Buhholz et al. 2012) and from the Centre for Renewable and Sustainable Energy Studies (CRSES) of Stellenbosch University (

The EROI values of the hypercycle for the two alternative primary energy sources are: 12-20:1 for CSP and 7-11:1 for woody biomass for electricity. Thus, both alternatives have a significantly lower EROI of the hypercycle compared to the present electricity production in South Africa (46:1). Hence, a significant deployment of these two alternative primary energy sources would reduce the overall strength of the South African exosomatic hypercycle (SEH) in relation to electricity production. As a consequence, a larger share of the production factors available to South Africa would have to be invested in generating electricity (since the requirement of production factors per unit of energy carrier supplied is larger than the average of the hypercycle allocated to the production of electricity) rather than using them for producing and consuming goods and services.

Having defined the relation between the requirement of primary energy sources and the net supply of energy carriers to society, we can characterize the two alternative energy sources in relation to external constraints (spatial constraints).

As regards concentrated solar power, the spatial constraints and ‘plausible’ exclusion criteria are determined by: (1) the availability of direct normal solar irradiation (DNI superior to 7.0kWh/m2); (2) the slope (inferior to 2%); and (3) the distance to the existing transmission grid (inferior to 20km). A spatial analysis of these external constraints and the resulting potential net supply of electricity for South Africa is illustrated in Fig. 11. Thus, in the short term, this alternative energy source (CSP) can only supply a tiny fraction of the electricity consumed in South Africa.

As regards woody biomass, spatial constraints and ‘plausible’ exclusion criteria are determined by: (1) availability of biomass resources (forests, excluding protected areas); the biomass land productivity; and (3) logistics for transportation. A spatial analysis of these external constraints and the resulting potential net supply of electricity for South Africa is illustrated in Fig. 12.

These data show that the short-term potential of electricity production from CSP and woody biomass in South Africa is 1.2% and 2.3%, respectively of the total annual amount of electricity production. Given these short-term potentials, we can assess the requirement of production factors that would have to be invested in the Energy and Mining Sector to generate this amount of electricity (all together 3.5% of the total). The requirement of production factors associated with the CSP & woody biomass scenario is shown in Tab. 1 (data for CSP from Larrain and Escobar, 2012; data for woody biomass from Forestry South Africa, 2010). The assessments refer to the production factors required only by CSP and WB for generating their “maximum short-term potential” equal to 3,000 GWh (1.2% of total electricity production) and 5,900 GWh (2.3%) respectively.

Table 1. Requirement of production factors in the scenario of CSP and Woody Biomass based electricity.

CSP (solar tower) 2.7 9.1 5,100
Woody biomass 120 N/A 9,241,000

In this way we can check the trade-offs of increasing the net supply of electricity with these two alternative energy sources. In this case what appears highly relevant is that these alternative energy sources, when compared with fossil energy and import do imply a larger demand of production factors in order to cover only a very tiny fraction of the consumed electricity.

Forestry South Africa (2010). The South African Forestry and Forest Products Industry 2009. (accessed 19 March 2013)

Buchholz T., et al. (2012). Modeling the profitability of power production from short-rotation woody crops in Sub-Saharan Africa. Biomass and Bioenergy. Available online 23 December 2012. In Press

Larrain T. and Escobar R. (2012). Net energy analysis for concentrated solar power plants in northern Chile. Renewable Energy, vol. 41, May 2012, pp. 123–133.

Pimentel, D. et al. (2002). Renewable energy: current and potential issues. Bioscience 52 (12): 1111-20.

Torresol Energy (2011). Gemasolar power plant. (accessed 22 March 2013)