Home / Science / Environmental science / Carbon and energy accounting / Life cycle comparison (LCA lite)Tool #162

LCA lite: compare the carbon footprint of two products over their life cycle, with break-even uses and uncertainty

Compare two products, such as a reusable and a single-use one, across life stages (materials, manufacturing, transport, use, end of life) with your own emission factors. See the totals for any number of uses, the break-even point, a stacked bar by stage, which input would flip the result, and how sure the answer is when the factors are uncertain.

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  1. Inputs
  2. Factors
  3. Compare
  4. Break-even
Nothing is uploadedWorks offline once open

Products

Compare the two on the same job, such as a year of drinks. A product that wears out after a number of uses is made again, so its once-only inputs count again each time.

Inputs and factors

No emission factors are built in, and the example factors are made up. Use factors from a database or study you trust, all for the same impact (for example kg CO₂e per kg of steel or per kWh). Stages can be any names. The uncertainty run draws each factor 10,000 times, spread evenly within ± its percentage. Up to 500 rows.

Comparison

Every input and what would flip the result (table)
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What it does

Is a reusable bottle really better than single-use ones? A life cycle assessment (LCA) answers questions like this by adding up the impact of everything a product needs, from raw materials to the bin. A full LCA needs big licensed databases. This tool does the core arithmetic for two products using factors you supply, which is enough to see which stages matter, where the break-even point is, and how sure the answer is.

For each input, impact = amount × factor. An input is counted either once per product made (materials, manufacturing, transport, end of life) or every use (washing, electricity while running). When a product wears out after a set number of uses, a new one is made and its once-only inputs count again.

How to use it

  1. Products. Name A and B, say how many uses each lasts before it is replaced, and choose how many uses to compare over (the job both must do, such as 365 drinks).
  2. Inputs. One row per input: product (A or B), stage, input name, amount, factor, counted (once or use) and ± % uncertainty in the factor. Factors must all be for the same impact, for example kg CO₂e per kg, per kWh or per tonne-kilometre. A negative factor is a credit, such as avoided material from recycling.
  3. Seed. Fixes the random draws of the uncertainty run, so you get the same result again.

No factors are built in, and the example factors are made up. Take factors from a database, an environmental product declaration or a study you trust.

What you get

  • The total for each product, per use and over all uses, and how much lower the better one is.
  • A stacked bar by stage, so you can see where the impact comes from.
  • The break-even number of uses, where the better choice switches, and a chart of totals against uses.
  • Easiest flip: for each input, how much its impact would need to change to make the two equal. A small number means the answer is fragile.
  • An uncertainty run of 10,000 draws: how often A is lower, and the 90 % range of the difference.

Worked example

With the made-up inputs, the reusable bottle (lasting 500 uses) costs 2.76 kg CO₂e to make and deliver, plus 0.02 kg per wash. A single-use bottle costs 0.11 kg. Over 365 uses the reusable bottle comes to 10.0 kg CO₂e against 41.8 kg for 365 single-use bottles, so the reusable bottle is 76 % lower. The break-even point is 29 uses. In the uncertainty run the reusable bottle is lower in 100 % of draws. Over only 30 uses it would be lower in just 59 %, too close to call.

FAQs

Is this a real LCA? No. It is a screening tool for one impact category, with no allocation rules, no system expansion, and no critical review. Use it to learn and to see what matters, not for public claims.

Where do I get factors? From life cycle databases, environmental product declarations, government greenhouse gas factor lists or published studies. Make sure they cover the same boundary (for example, cradle to gate).

Does it upload my data? No. Everything runs in your browser.

Where the numbers come from

  • Simple attributional life cycle arithmetic: impact = amount × factor, summed over stages, with once-per-product inputs repeated each time a product is replaced. Break-even, one-at-a-time sensitivity and Monte Carlo (factors spread evenly within ± their uncertainty, seeded random numbers) written by fibub.
  • No emission factors are built in. The example amounts and factors are made up for illustration and are not data for any real product.
  • Checked in the tests against an independent Python version, including the same random number stream for the Monte Carlo run.

Standard scientific values, such as constants, atomic weights and melting points, are facts found in every textbook; we name where ours were checked. If you are an author or publisher and want a value, a credit or a table changed or removed, tell us and we will act quickly.

Last updated 2026-11-09.

Change log for Life cycle comparison (LCA lite)

  1. Add #162 LCA lite comparison (user factors, break-even, flip sensitivity, Monte Carlo) Details on GitHub

Every change to fibub

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