Mpumalanga

This page provides a summary of key provincial climate change issues and links to district level climate change information. Click on the links for more information on each of the District Municipalities in the Province.

Climate Change Strategy

Description
Link
Date
Climate Support Programme (CSP) – Climate Change Adaptation Staretegies Click hereAugust 2015

Provincial Overview

Mpumalanga Province is situated in the northeast of South Africa, sharing its north and south east borders with Mozambique and Swaziland, and its national borders with Limpopo, Gauteng, Free State and KwaZulu-Natal. Most of the provincial land is on the high plateau grasslands of the Middleveld, with mountainous regions in the north-eastern parts of the province. Mpumalanga is the second-smallest province after Gauteng, covering an area of 76,495 square kilometers (6.3% of of South Africa’s land area). The province has a population of 4,229,300 people making up 7.8% of South Africa’s total population. Mpumalanga comprises of 21 municipalities: three districts (Ehlanzeni, Nkangala and Gert Sibande) further divided into 18 local municipalities. It’s capital city is Mbombela, previously known as Nelspruit, located in the Mbombela Local Municipality and is the administrative and business hub of the Lowveld (MCCVA, 2015MPSoER, 2008Odunyi et al., 2013). Mpumalanga is rich in coal reserves and therefore has substantial coal mining activity and an active mining sector. It produces close to 90% of South Africa’s coal and is home to three of the biggest coal power stations in Southern Africa. Other important mineral resources mined in the area include chrome, steel, vanadium, asbestos, magnesite, iron ore, vanadium, limestone, dolomite, silica and construction materials some of which are an important source of exports for South Africa (PGDS, 2004). In addition to mining, other major sectors in the province include forestry and agriculture. The province has a large fruit and vegetable market which accounts for a significant percentage contribution towards the province’s economy (PGDS, 2004).

Figure: Mpumalanga province and its municipalities

Greenhouse Gas Data

Electricity Sales

There are a range of sources of Greenhouse Gas (GHG) emissions at the provincial and district level. One of the main sources of GHGs is from electricity. Although the GHGs associated with the generation of electricity is recorded at a national level, provinces and municipalities typically record the GHGs associated with the sale of electricity.  The map below is a summary of the GHGs from the sale of electricity in the province. This data is sourced from Stats SA for the provinces and divided into district data by the proportion of houshold numbers in the district.

Figure: Total electricity sales (GgCO2e) in Mpumalanga

Liquid Fuel Sales

A second major source of GHGs is from the sale of liquid fuels. This includes jet fuel, aviation gasoline, diesel, furnace oil, LPG, paraffin and petrol. The map below is a summary of the GHGs from the sale of liquid fuels in the province. Each fuel is converted to Gigagram Carbon Dioxide equivalent (GgCO2e) using specific emission factors from the Intergovernmental Panel on Climate Change Emission Factor Database. 

Figure: Total liquid fuel sales (GgCO2e) in Mpumalanga

Key Climate Hazards

Increasing temperatures

The figure below shows projected changes in annual average temperatures, highlighting increasing temperatures throughout the province for the period 2021-2050 under the RCP 8.5 scenario. By 2050, the province is projected to be affected by higher annual average temperatures, which will adversely affect water and food security.  Evaporation rates will also likely increase and agricultural outputs may reduce.

Figure: Projected changes in annual average temperatures throughout Mpumalanga over the period 2021-2050 under the RCP 8.5 scenario (CSIR 2019)

Increasing rainfall variability

The figure below shows projected shifts in annual average rainfall throughout the province between 2021-2050 under the RCP 8.5 scenario. Annual average rainfall amounts vary across the province. There is uncertainty regarding projected future rainfall.

Figure: Projected changes in annual average rainfall throughout Mpumalanga over the period 2021-2050 under the RCP 8.5 scenario (CSIR 2019)

Increasing storms and flooding events

The figure below shows projected changes in the annual average number of extreme rainfall days throughout the province over the period 2021-2050 under the RCP 8.5 scenario.  Increases in the number of rainfall days are likely to result in an increase in intense storms, and flooding events across the province.

Figure: Projected changes in the annual average number of extreme rainfall days throughout Mpumalanga over the period 2021-2050 under the RCP 8.5 scenario (CSIR 2019)

Changing Biomes

The current delineation of biomes is depicted in the figure below, with the predicted shift in biomes shown in the following figure based on a high-risk scenario. The biomes have varying sensitivities to the projected impacts of climate change which are further exacerbated by issues such as the fragmentation of natural areas and unsustainable water usage rates.

Figure: The current delineation of biomes in Mpumalanga (SANParks 2011a)
Figure: The predicted shift in biomes in Mpumalanga using a high-risk scenario (SANParks 2011b)

Climate Change Vulnerability

The CSIR Greenbook has developed and refined a vulnerability assessment framework by collating relevant data into composite vulnerability indicators. Four local municipality level vulnerability indices were computed and are shown spatially below.

Socio-Economic Vulnerability

Social inequalities are the factors that affect the susceptibility and coping mechanisms of communities and households. Indicators for social vulnerability attempt to consider the sensitivity, response and recovery from the impacts of natural hazards. The CSIR Green Book has developed a socio-economic vulnerability index that is measured on a scale from 1 (low vulnerability) to 10 (high vulnerability).   The map below shows the Socio-Economic vulnerability score of each municipality in the province visually.

Figure: Socio-economic vulnerability per local municipality in Mpumalanga (Le Roux, van Huyssteen, et al. 2019)

Environmental Vulnerability

Environmental vulnerability describes the vulnerability and risk to the natural environment and the impacts on the ecological infrastructure of which surrounding settlements are dependent. The environmental risk of an area includes ecosystems, habitats, physical and biological processes (reproduction, diversity, energy flows, etc). The CSIR Green Book has developed an Environmental Vulnerability Index that is measured on a scale from 1 (low vulnerability) to 10 (high vulnerability). The map below shows the environmental vulnerability score of each municipality in the province visually.

Figure: Environmental vulnerability per local municipality in Mpumalanga (Le Roux, van Huyssteen, et al. 2019)

Physical Vulnerability

Physical vulnerability describes the physical fabric and connectedness of settlements (buildings and infrastructure) and focuses mainly on the conditions that exist before a hazard occurs and the expected level of resulting loss. The CSIR Green Book has developed a physical vulnerability index that is measured on a scale from 1 (low vulnerability) to 10 (high vulnerability). The map below shows the physical vulnerability score of each municipality in the province visually.

Figure: Physical vulnerability per local municipality in Mpumalanga (Le Roux, van Huyssteen, et al. 2019)

Economic Vulnerability

Economic vulnerability describes the potential risks posed by hazards on economic assets and processes. Potential hazards can include job losses, increased poverty and interruptions in business activities. The CSIR Green Book has developed an economic vulnerability index that is measured on a scale from 1 (low vulnerability) to 10 (high vulnerability). The map below shows the economic vulnerability score of each municipality in the province visually.

Figure: Economic vulnerability per local municipality in Mpumalanga (Le Roux, van Huyssteen, et al. 2019)

References