Producing green e-methanol requires three major inputs: renewable electricity, hydrogen, and CO₂. In practice, these resources are rarely found in the same place. Finland is an excellent example: the best wind conditions are in the north, while the largest sustainable CO₂ point sources—mainly pulp and paper mills—are in the south and centre of the country. This raises a fundamental question for e-fuel developers: Which input should be transported, and which production configuration is most cost-effective?

This new study compares nine infrastructure scenarios for 2030–2050, examining whether it is cheapest to transport electricity, hydrogen, or CO₂. It also integrates Monte Carlo simulation and SimDec decomposition to quantify uncertainty and identify the most influential techno-economic parameters.

Why this question matters

Methanol is one of the most promising Power-to-X products. It can be used as a chemical feedstock, a maritime fuel, and potentially as an aviation fuel—if produced with green electricity and sustainable CO₂. More than 200 renewable methanol projects are already in development globally, and Finland is actively exploring multiple sites.

Yet the sector still lacks clear guidance on optimal plant placement in regions where renewable energy and CO₂ sources are geographically dispersed. This study fills that gap using a Finland-specific case study with global relevance.

What the study compares

The research evaluates three strategic options for producing e-methanol:

1. Transport CO₂ to the electricity generation site
2. Transport hydrogen from the electricity site to the CO₂ source
3. Transport electricity to the CO₂ source for hydrogen and methanol synthesis

All scenarios use consistent cost assumptions for wind and solar resources, point-source CO₂ capture, hydrogen production, electricity transmission lines, hydrogen pipelines, and CO₂ pipelines.

A map on page 3 illustrates locations of northern wind resources and southern CO₂ capture sites (Fig. 2), while Table 1 summarises all scenario configurations.

Key findings

1. Transporting CO₂ is the cheapest option across all scenarios

For 2030, methanol costs are:

• 99.7–112.4 €/MWh depending on scenario
• Scenarios that transport CO₂ consistently deliver the lowest cost
• Transporting electricity is always the most expensive option

By 2050, e-methanol costs fall by around 30%, to 68.5–79.1 €/MWh, but the ranking of options remains unchanged (Table 5).

2. Electricity transmission has the highest infrastructure cost share

Due to unavoidable line losses and high capex for long-distance powerlines, electricity transmission contributes up to 16.6% of the final methanol cost in some scenarios (Fig. 4).

3. Hydrogen transport is a viable middle option

Hydrogen pipelines are more expensive than CO₂ pipelines but cheaper than powerlines. Improvements in electrolyser costs and pipeline scaling help reduce overall costs.

4. Monte Carlo analysis confirms robust ranking

Across 10,000 simulations covering 2030–2050, CO₂ transport is the cheapest option in 100% of cases, even when capex and capture rates vary (Tables 6–7).

5. Weighted average cost of capital (WACC) dominates uncertainty

The sensitivity analysis shows:

• WACC accounts for 98–99% of total cost variance
• Methanol synthesis capex is the second-most influential variable
• Pipeline capex, CO₂ capture rate, and HVAC costs have minor influence
  

SimDec scenario decomposition (Fig. 6) visually demonstrates how different capex states shift the distribution of e-methanol costs.

Broader implications for Finland and beyond

The findings strengthen Finland’s position as a potential hub for Power-to-X fuels. Finland combines:

• high-quality wind resources
• abundant sustainable CO₂ from pulp and paper mills
• rapidly expanding renewable-energy projects
• strong political and economic stability

The analysis shows that locating methanol synthesis near wind generation sites and transporting CO₂ there is optimal. However, other factors—such as local permitting, safety considerations for pipeline construction, stranded-asset risk, and infrastructure flexibility—also matter in real-world planning (pp. 10–11).

Reference

Galimova, T., Karjunen, H., Lassila, J., Satymov, R., & Breyer, C. (2025). Techno-economic analysis of e-methanol infrastructure choice for the case of Finland. Energy, 334, 137531. https://doi.org/10.1016/j.energy.2025.137531

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