- The paper presents a participatory mapping framework that integrates spatial eligibility and renewable resource simulation to derive detailed green hydrogen cost-potential curves for 31 countries.
- It employs 20 years of climatic and water resource data under multi-scenario analyses to estimate LCOH below 2 €/kg by 2030 and outlines paths for export potential.
- The study links technical assessments with socio-economic metrics, highlighting regional disparities in energy access, job creation, and infrastructure needs.
Participatory Mapping of Green Hydrogen Cost-Potentials in Sub-Saharan Africa: Technical, Economic, and Socio-Economic Insights
Overview
This study conducts a highly granular, multidisciplinary assessment of the cost and potential for green hydrogen production from renewables in Sub-Saharan Africa. Integrating spatially explicit land eligibility analyses, renewable resource simulation (PV, wind, hydro, geothermal), sustainable water supply accounting (groundwater and desalination under climate scenarios), and composite socio-economic impact metrics, the authors derive cost-optimal system configurations and regionalized hydrogen supply curves for 31 countries. The analysis addresses theoretical, technical, and economic expansions and foregrounds the major constraints—water availability, land use, and local socio-economic factors—in green hydrogen value chains in the African context.
Land Eligibility and Renewable Potential Methodology
A key methodological contribution is the participatory assignment of 33 spatial criteria for exclusion of land for open-field PV and onshore wind, incorporating regional stakeholder inputs into the GLAES and GeoKit frameworks. This produces high-resolution eligibility masks that reflect local ecological, economic, and social constraints—yielding eligibility rates ranging from sub-percent in densely inhabited or biodiverse nations (e.g., Guinea, Seychelles) up to ~50% for arid, sparsely populated states (Niger, Mali, Mauritania). The differential availability translates directly to technically installable renewable capacity (PV up to 123 TW in S/EAf, 107 TW in WAf; wind potential is an order of magnitude lower), favoring hyper-arid regions for scale deployments.
Renewable simulation utilizes 20 years of ERA5 reanalysis and Global Solar/Wind Atlas, with techno-economic progression to 2050. LCOE minima for utility-scale PV reach below 2 c€/kWh (Nama Karoo, South Africa/Namibia, Mauritania/Niger), with >20% further cost reductions expected to 2050 as PV capex declines. Wind LCOE tracks higher, with only 5–9% of technical potential competitive with best PV. Hydro and geothermal resource modeling is geographically restricted but offers dispatchable options with competitive LCOE only in select subregions (e.g., Congo Basin for hydro, Rift Valley for geothermal).
Water Resource Constraints: Sustainable Groundwater and Desalination
The novelty in the water assessment is the modeling of groundwater sustainable yield, including three scenarios (conservative to extreme) under both RCP2.6 and RCP8.5 climate projections, with explicit consideration of environmental flow allocations and full accounting for sectoral water consumption. Results indicate regional heterogeneity in future sustainable yields, with persistent declines under RCP8.5, especially in arid zones. Critically, two-thirds of analyzed regions cannot supply sufficient water for >25% technical hydrogen expansion from local groundwater—creating a strong dependency on desalination, especially in the highest-potential inland deserts. The cost increment for desalination and pipeline transport, however, is <1% of final LCOH even in stressed regions, making water supply a logistical rather than economic barrier.
Cost-Potential Curves and System Architecture
The regionalized cost-potential curves are derived using the ETHOS.FINE optimization framework at GID-2 spatial resolution, accounting for local energy and hydrogen demand (prioritized over export). Entry-level LCOH for solar/wind systems falls below 2 €/kg by 2030 in Mauritania, reaching 1.6 €/kg by 2050; potential-weighted means for the whole region are 2.7 €/kg (2030) and 1.9 €/kg (2050). The cost-potential relationship is flat for PV-dominated systems (costs are insensitive to expansion across wide ranges), in contrast to wind-driven regions where LCOH rises more steeply with expansion.
The optimal generation mixes exhibit strong spatial variation: while PV is dominant in most regions, wind achieves high shares (70–95%) in Mauritania, Madagascar, northern Kenya, and parts of the Sahara due to high wind resource and its complementary diurnal profile, which enhances electrolyzer CF and reduces capex amortization. Hydropower and geothermal play minor, highly localized roles and are fundamentally limited by system-wide dispatch and resource constraints. Li-ion battery storage is systematically outcompeted by generation overbuild plus curtailed operation, given current/future cost assumptions.
Quantitative Green Hydrogen Potential and Demand Alignment
The aggregated green hydrogen technical potential (~400,000 TWh/a) exceeds current global primary energy use by over 2x, with local demand (electricity + H2) only ~0.5% of potential. Only three states (e.g., Guinea, Seychelles, Mauritius) cannot achieve full self-sufficiency under all criteria; nearly all nations retain substantial export potential after meeting modeled Net Zero 2050 local requirements. However, the fraction of technical potential realizable under water constraints is only 16%. Full technical exploitation often implies that up to 84% of water input must come from desalination, necessitating a massive buildout of coastal desalination and transport infrastructure.
Hydrogen system designs increasingly favor PV through 2050 as PV capex undercuts further wind cost reductions; consequently, electrolyzer full-load hours decline in many regions as deployment shifts from wind to solar, with only Mauritania and parts of Kenya/Madagascar retaining significant wind shares.
Socio-Economic Impact Assessment
The composite socio-economic indicator integrates access to energy services, macroeconomic effects (direct job creation potential), and indirect effects (poverty, biomass dependence), informed by local stakeholder priorities. The analysis identifies the African Great Lakes region, Upper Guinea Coast, and parts of Mozambique, Zimbabwe, Lesotho, and Nigeria as loci for maximum positive impact, primarily driven by low energy access, high population density, and unemployment relative to renewable potential.
Specific outcomes:
- Nigeria emerges as a core labor impact node due to size and labor cost advantage.
- Rwanda and Uganda in S/E Africa, and Benin, Burkina Faso, and Sierra Leone in West Africa, are highlighted for major gains in energy access and employment.
- Coastal/desert regions with both resource and grid access (Mauritania, Kenya, Madagascar) are identified as dual opportunity zones for export and local uplift.
- Countries with high existing energy access (e.g., South Africa, Ghana) have limited direct local impact for new projects.
Challenges include the stark intra-country disparities, the exclusion of indirect and induced jobs in the current model due to data sparsity, and lack of direct capacity-building metrics—all relevant for policymaking on maximizing just transition outcomes.
Theoretical and Practical Implications
From a systems analysis standpoint, the research substantiates:
- Green hydrogen from renewables, at <2 €/kg by 2050 (in the best African regions), is cost-competitive at global scale, particularly with cross-sector hybridization and aggressive learning rates for PV and electrolysis.
- Water stress is not a binding economic constraint, but technical and logistical (transport, cross-border cooperation) limitations are substantial for large inland deployments.
- The largest and cheapest production capacities cluster in arid regions with low local demand, reinforcing Africa’s potential as a global green H2 exporter—conditional on infrastructure, finance, and trade policy enablement.
- Socio-economic benefits from distributed hydrogen and renewables deployment are maximized in high-population, low-access regions, rather than in absolute cost-optimal export enclaves—policy trade-offs will be required.
Speculation on Future AI Developments for Green Hydrogen Mapping
- Expansion of the participatory land eligibility approach, automated through federated learning with satellite/aerial data and structured/crowdsourced local stakeholder feedback, could further enhance spatial precision and policy legitimacy.
- Integration of dynamic agent-based socio-techno-economic models in hydrogen planning—enabled by large-scale AI-driven scenario engines—may refine employment, migration, and distributional impact forecasts.
- Advances in multi-scale optimization (stochastic, robust) for green hydrogen supply-chain design, incorporating probabilistic climate, market, and policy drivers, will become increasingly tractable with generative surrogate models and quantum-inspired solvers.
Conclusion
This study provides a robust, spatially explicit framework for quantifying cost-optimal green hydrogen potential and its social impacts in Sub-Saharan Africa, resolving major technical and system-level uncertainties pertaining to water supply, land competition, and local benefit sharing. The African continent has both the technical and economic conditions for large-scale green hydrogen production; realizing this potential requires coordinated investment in water infrastructure, regulatory harmonization for land and labor mobilization, and deliberate distributional policies to avoid enclave dynamics. The provided approach and results set the technical basis for integrated hydrogen infrastructure and just energy transition planning in Africa and serve as a template for similar regions globally.
Citation: "Participatory Mapping of Local Green Hydrogen Cost-Potentials in Sub-Saharan Africa" (2408.10184).