Measure the footprint before you scale it
Matflow prices the environmental side of a material or process: cradle-to-gate global warming potential, cumulative energy demand, waste E-factor and a 0–100 ESG score — with process flowsheet modelling and carbon-price sensitivity when a candidate needs deeper review.
Four metrics from one composition
Score a material or formulation by mass fraction against a built-in factor library, with the result reported per kg of product.
kg CO₂eq per kg of product, weighted by the mass fraction of every component in the composition.
MJ per kg of product, so energy-intensive routes are visible before a candidate reaches the bench.
kg of waste per kg of product — the process-efficiency metric chemists already use to compare routes.
A 0–100 score derived from the computed GWP (higher is cleaner), so a footprint can travel with a candidate as one number.
From a recipe to an annual footprint
Scale a synthesis route to a production rate and get utility demand, greenhouse-gas emissions and — where the full engine runs — process economics from the same solved flowsheet.
- Two engines, one reporting contract — a real BioSTEAM steady-state flowsheet when the package is installed — precursor mixing, a sol-gel stirred hold tank, a 110 °C dryer and a calciner at your setpoint — or a mass & energy balance surrogate that is always available. Every response states which engine ran.
- Shared factors across engines — both engines use the same grid and steam emission factors, so switching engines does not silently change the answer for the same utilities.
- Real process economics on the BioSTEAM path — the solved flowsheet feeds a bst.TEA cash-flow analysis — minimum selling price, fixed and total capital, annual operating and utility cost — not a fixed formula.
- Versioned background data — eGRID 2023 subregion averages and USEEIO v2.0 sector aggregates are static, versioned tables with source and vintage attached — never live-scraped.
- Annual scale in, annual footprint out — set the production rate in kg/year and the calcination temperature; the response reports GWP including material emissions, electricity and steam demand, and tonnes of CO₂eq per year.
- Four biorefinery templates — cellulosic ethanol, lactic acid/PLA, HEFA sustainable aviation fuel and CO₂-to-green-methanol run through a factor-method TEA, delegating to the real BioSTEAM service when a flowsheet specification is supplied and the package is installed.
- Engine — BioSTEAM or the mass & energy balance surrogate.
- Metrics — GWP with material emissions, CED, electricity and steam demand.
- Annual footprint — tonnes of CO₂eq per year at your production scale.
- Provenance — grid and steam factor source and vintage.
- Database — ecoinvent, useeio_screening or builtin, stated honestly.
Stress-test a route against the price of carbon
A dedicated carbon-sensitivity engine builds a Scope 1/2/3 inventory from documented process benchmarks, then re-prices it across a carbon-tax range.
Direct emissions, regional grid electricity and upstream emissions for a named process benchmark, each reported separately and as a total.
Tax exposure from $0 to $200 per tonne of CO₂, showing the green product penalty against the fossil baseline at each price point.
Decarbonisation measures ranked by dollars per tonne abated, each marked profitable or not at the carbon price you choose.
One-at-a-time ±10% swings on electricity use, grid factor and upstream emissions, plus a seeded 400-draw Monte-Carlo p5/p50/p95 band.
Screening-grade, and labelled that way
The same discipline the platform applies to prediction applies to sustainability: state the boundary, name the engine, report the database.
- Screening-grade, not certified — results are screening-grade COMPUTED estimates over a stated system boundary. They are not a certified ISO 14040/14044 study and are not suitable for product claims or environmental product declarations (EPDs).
- ecoinvent is never bundled — the commercial ecoinvent database is paid and is never vendored, downloaded, scraped or redistributed. An operator holding a license can point the server at their own copy; otherwise the response honestly reports ecoinvent_available: false.
- The database is reported — every flowsheet response carries lca_db — ecoinvent, useeio_screening or builtin — alongside the engine that ran, so you can always see what produced the number.
- Provenance on the factors — grid and steam factors carry their source and vintage (eGRID 2023, USEEIO v2.0, curated), not just a value.
- Named gaps, not silent ones — a material name that is not in the factor library is costed with a documented generic factor rather than dropped — check the library before treating a composition number as material-specific.
Environment, performance and cost on one candidate set
The LCA studio runs beside the rest of the pipeline: score the footprint, then carry the candidate into TEA for the scale-up case.
Enter a composition and read GWP, cumulative energy demand, E-factor and the ESG score, then move to the flowsheet and carbon-sensitivity panels.
TEA folds raw materials, equipment sizing, CapEx/OpEx and end-of-life value into one net-value score for the same candidate.
The docs page carries the endpoint map and the same honest-scope statement this page makes.
What these numbers are, and are not
Is this a certified life-cycle assessment?
Which background database actually runs?
What does the ESG sustainability score mean?
Composition result or flowsheet result — which do I need?
What can the carbon sensitivity tool compare?
Do these numbers replace a real LCA or lab validation?
Put a footprint next to every candidate
Score a composition, solve the flowsheet across an annual production scale, and stress-test the result against a carbon price — then carry the candidate into TEA for the scale-up case.