article · Sustainability
South Africa's updated Nationally Determined Contribution establishes a 2030 emissions ceiling of 420 MtCO2. By integrating logistic decay modelling, linear programming, genetic algorithm optimisation, and Pareto analysis on historical and projected data from 2000 to 2050, optimal decarbonisation pathways were identified. Rather than consuming the remaining 239.1 MtCO2 carbon headroom, optimal pathways reduce emissions 67 to 85 percent below 2023 levels. Crucially, phasing out coal too aggressively in the near term disrupts energy efficiency investments, which worsens emissions by 2050. The optimal trajectory prioritises a modest initial coal reduction of 0.69 percent annually alongside aggressive efficiency improvements of 4.46 percent annually up to 2035, before accelerating coal phase-out to reach a 96 percent reduction by 2050. All Pareto-optimal solutions require coal reliance below 40 percent by 2030, which directly conflicts with current Integrated Resource Plan constraints and creates a feasibility gap.
Timing is critical when transitioning from fossil fuels. Rushing coal plant closures immediately can divert capital away from essential energy efficiency upgrades, ultimately increasing cumulative carbon output. By strategically sequencing high-impact efficiency programmes first and accelerating coal phase-outs after 2035, South Africa could dramatically cut total emissions and provide clearer direction for sustainable climate finance initiatives.
This computational modelling research provides decision-support pathways for energy policymakers, national grid planners, and sustainable climate finance investors. Because the findings depend on reconciling conflicting policy constraints like the national Integrated Resource Plan, the work represents early-stage macro-level systems modelling rather than an immediate commercial technology. It can guide capital allocation for energy efficiency programmes and schedule infrastructure phase-outs.
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South Africa’s updated Nationally Determined Contribution sets a 2030 emissions ceiling of 420 MtCO2. Using historical data from 2000 to 2023 and projections to 2050, this study identifies optimal decarbonization pathways by integrating logistic decay model, linear programming, genetic algorithm optimization (Decay–LP–GA), and Pareto analysis. A prior study notes that 2023 emissions lie substantially below the NDC ceiling, leaving 239.1 MtCO2 of unused carbon space. However, the present study finds that optimized pathways transcend rather than utilize this space, achieving 67–85% emissions below 2023 levels. Notably, aggressive near-term coal phase-out increases 2050 emissions by disrupting efficiency investment, indicating that timing governs long-term outcomes. The optimal strategy therefore prioritizes slow near-term coal reduction (0.69% annually) to allow front-loaded efficiency gains (4.46% annually) through 2035, followed by accelerated phase-out to achieve 96% reduction by 2050. This sequencing reduces cumulative emissions by 8.0% (300 MtCO2) relative to the LP minimum. The Pareto frontier spans 51.5–92.6 MtCO2 in 2030 and 52.8–64.2 MtCO2 in 2050, with all Pareto-optimal solutions requiring coal shares below 40% by 2030, conflicting with Integrated Resource Plan constraints. Consequently, maintaining a ≥40% coal floor raises minimum feasible emissions to 101.5 MtCO2, generating a 22.8–49.4 MtCO2 feasibility gap. The findings show that optimal strategy is not to use its remaining carbon space, but to render the 420 MtCO2 target redundant through front-loaded efficiency gains and strategically timed coal phase-out, providing clear direction for sustainable climate finance.
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DOI: 10.3390/su18168460
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