RV Pathway Explorer.
An interactive read of the process layer for converting captured CO₂ and green hydrogen into chemicals and fuels: e-methanol, e-SAF, green ammonia, and DME. Reaction chemistry, indicative operating windows, and references for each pathway.
Instrument 02 of the digital layer. It models the chemistry of every route from captured CO₂ and green hydrogen to finished product.
Process layer: source → conversion → product. Reactions, indicative operating windows, energy intensity, and paper citations for each step.
Pathway screening for industrial hosts, technology providers, project developers, investors, and public-sector programmes evaluating Saudi-context CO₂-to-fuels routes.
No capex, opex, revenue, credit pricing, IRR, or NPV. Project economics are scoped through a separate engagement with Renewable Vision.
Carbon to chemicals and fuels, pathway by pathway.
An interactive read of the process layer — captured CO₂ plus green hydrogen, routed through the chemistry, parameters, and references that govern each pathway. The economics layer is a separate, internal tool.
CO₂ + H₂ → e-Methanol
Captured CO₂ reacts with green hydrogen over a Cu/ZnO/Al₂O₃ catalyst to produce methanol. The product is drop-in compatible with existing methanol value chains for chemicals, shipping (FuelEU Maritime), and fuel blending.
Direct Air Capture
Solid-sorbent or liquid-solvent capture of atmospheric CO₂. Energy intensity dominates DAC economics; pairing with low-cost solar is the structural Saudi advantage.
Parameters
- Capture energyThermal + electric, solid-sorbent reference.
- 1500–2500kWh / tCO₂E_DAC
- CO₂ purity (post-capture)
- >99% v/v
- Compression to synthesis
- 50–100bar
Play with the operating point.
Sliders move within paper-cited bounds. Mass balance uses IUPAC 2021 stoichiometry. PEM curve runs Butler–Volmer + ohmic + concentration overpotentials in your browser.
ΔHrxn at standard conditions.
FuelEU Maritime regulatory floor; Asian + European petrochemical offtake; immediate drop-in.
- Energy and exergy analysis of methanol synthesis via CO₂ hydrogenationPérez-Fortes, Schöneberger, Boulamanti, Tzimas · 2016Appl. Energy 161, 718–732
Which knobs actually move the answer.
Deterministic tornado: each parameter perturbed to its low/high bound, others held at mid. Monte Carlo: independent triangular sampling of every input, recomputing the metric for every scenario. Both run in your browser on the same mass + energy balance engine that powers the rest of the simulator.
Parameter influence ranking.
Output distribution.
Tornado holds all parameters at their mid value except one, which sweeps low → high. Rows sorted by absolute swing. Monte Carlo draws each parameter independently from a triangular distribution (low, mid, high); samples are passed through the same mass + energy balance used elsewhere in the explorer, then quantiles are read from the empirical sorted set. No correlation is modelled between parameters — a stronger v3 would add a correlation matrix from project portfolio data. P90 here means "90% of scenarios give a value at or below this," consistent with the techno-economic convention.
Where the infrastructure sits.
Twelve curated industrial CO₂ sources plotted at their real coordinates on an OpenStreetMap base layer. Marker size scales with annual CO₂ tonnage; color encodes sector. Click any marker for detail.
Where the carbon actually lives.
A curated set of major Saudi industrial CO₂ sources with indicative tonnages from public disclosures and sector benchmarks. Each host is mapped to the pathways that are technically compatible with its CO₂ stream quality. Click any host to see the engineering fit.
All facility names are from public operator disclosures. Indicative CO₂ tonnages are mid-points of public ranges from sector benchmarks (refining 4–8 Mt CO₂/y per plant; cement ~30% process CO₂ in flue stream; ammonia ~1.5–2 t CO₂ per t NH₃) and Climate-TRACE-style facility-level data sets. Numbers are ranges, not point measurements. Pathway compatibility is determined by CO₂ stream quality (high-purity / concentrated / dilute flue) and integration considerations (existing H₂ availability, downstream chemistry overlap). Per-host scoping requires project-specific data — contact Renewable Vision for confidential engagement.
Constrained resources, optimal mix.
Given a CO₂ supply, a green H₂ supply, and per-product demand caps, the optimiser solves an LP over the four pathways to find the allocation that maximises your chosen objective. Mass balance uses IUPAC 2021 stoichiometry; the LP runs in your browser via dense-vertex enumeration.
LP over 4 pathways with 2 resource constraints (CO₂, H₂) and 4 demand caps. Solver enumerates vertices of the feasible polytope by activating every 4-subset of 14-constraint system, solving the resulting linear system, and selecting the best feasible vertex. Per-pathway coefficients are IUPAC 2021 derived. Energy intensities use the published operating-window centres; the interactive controls above let you walk the operating point off-centre. Economics are computed only inside the internal RV-CMP engine and are intentionally not exposed here.
The Pathway Explorer is a public read of the process layer. For project-specific screening, methodology selection, host fit, and structured project support, contact the Renewable Vision team.