LCA and Carbon Footprint Data: How Do You Read a Recycled Material Number?

Buyers receive carbon numbers in three forms: a figure on a supplier slide, a figure in a tender question, and a figure a customer asks them to explain. All three arrive without the two sentences that make them readable — what was counted, and per what. The result is a number that cannot be compared, defended or repeated, and a buyer who either quotes it and hopes, or drops it and loses the tender question.

This page is about reading the data rather than producing it. It sets out what a life cycle assessment answers, which boundary and functional unit make two studies comparable, how to read a system boundary honestly, where supplier figures usually go wrong, and what can and cannot be claimed from the result.

What Question Does an LCA Actually Answer?

It answers a comparative question about a defined function over a defined life, not an absolute question about a product. An assessment compares the environmental burdens of delivering that function under two or more scenarios. It does not say a bag is good or bad, and it does not produce a single universal number that belongs on a hangtag. Where a supplier sends a single figure with no comparison and no scenario, it is not an assessment result; it is a data point from one, and its value is limited to that scenario.

The standards behind the method — ISO 14040 for principles and framework, and ISO 14044 for requirements and guidelines — are about how the study is conducted and reported, not about what the answer should be. That distinction matters: conformance to the standards means the study was done in a defined way, not that the result transfers to your product.

What Is the Difference Between Cradle-to-Gate and Cradle-to-Grave?

Cradle-to-gate stops at the factory gate: raw material, processing, and the manufacturing steps up to the point the finished article leaves the site. Cradle-to-grave continues through distribution, use and end of life. For a bag programme the difference is not academic, because the use phase can include washing, and washing is often the largest single contributor in a textile study. A cradle-to-gate figure and a cradle-to-grave figure for the same bag are different numbers measuring different things.

Most supplier data is cradle-to-gate, because that is what the supplying site controls and can evidence. That is legitimate, but it has to be labelled as such, and it cannot be compared with a competitor cradle-to-grave figure. Where a customer asks for "the carbon footprint", the honest reply starts by asking which boundary they mean.

Which Functional Unit Makes Two Studies Comparable?

The functional unit is the thing being counted: one bag, one bag delivering a defined service for a defined period, or one kilogram of material. Studies are only comparable when the unit matches. One bag is the unit most buyers assume and the least useful, because two bags of different size or durability deliver different service. One bag delivering a defined function for a defined number of years is the unit that makes a durability difference visible, and it is the one a serious study uses.

Where a supplier quotes per kilogram and a customer reads per unit, the conversion is simple but the interpretation is not: a heavier bag with a lower figure per kilogram can be worse per unit. Ask for the unit in writing, convert deliberately, and state the conversion wherever the number is repeated.

What Is Inside the System Boundary of a Bag Study?

Materials, processing, assembly, transport between stages, packaging, and — depending on the boundary — distribution, use and end of life. Each stage carries an allocation decision and a data source, and the two that dominate the result in a bag study are the fibre production stage and, where it is included, the use stage. Coatings, laminations and trims are frequently excluded or estimated, and their exclusion is disclosed in a serious study and omitted in a marketing summary.

Ask for the exclusion list rather than the inclusion list. Inclusions are easy to assert; exclusions are where the figure was decided. A summary that lists what was counted and says nothing about what was not is a summary that should be read with care.

How Should a Carbon Figure Be Read and Rounded?

As a range with a stated confidence, not as a point. Assessments carry uncertainty from data quality, allocation choices and assumptions about transport and energy, and a figure quoted to two significant figures implies a precision the study does not have. Where a number has to be printed, round it to the precision the uncertainty supports and state the boundary beside it.

There is a second discipline about rounding that is easy to get wrong: do not round downward to make a comparison look better. Where two options differ by less than the uncertainty of the study, the honest statement is that the study cannot separate them, and that statement is more useful to a buying decision than a false ranking.

1. Boundary

Cradle-to-gate, cradle-to-grave, or another, stated in words

2. Functional unit

What is being counted, and over what service life

3. Method and standard

The assessment standard, and the impact method used

4. Data quality

Primary or secondary data, and the reference year

5. Exclusions

What was left out, and why it was judged immaterial

What Does a Percentage Reduction Actually Mean Without a Baseline?

Nothing that can be checked. A reduction claim is a comparison, and a comparison needs both sides stated: the scenario it is measured against, the unit, the boundary and the method. "Thirty percent lower" against an unnamed baseline is not a result; it is an advertisement. Where a supplier quotes a percentage, ask for the baseline in the same units, and check that the two sides differ only in the variable being claimed.

The second check is whether the difference is inside the uncertainty. A reduction smaller than the combined uncertainty of the two scenarios is not a finding, and printing it as one is the kind of claim that fails review. Where the difference is large enough to be real, it will also be large enough to state in absolute terms, which is always the safer form.

Which Data Quality Issues Invalidate a Supplier Figure?

Four, in descending order of frequency. Secondary data presented as primary: industry average datasets used for a specific factory, with no note that they are averages. Outdated reference years: energy grids change, and a study built on data from several years ago can overstate emissions substantially. Unstated allocation: a recycled input carries a burden-sharing decision between the first life and the second, and the choice moves the result.

And undisclosed exclusions, most often coating, lamination, trims and packaging. None of these are dishonest in themselves; all of them are dishonest when they are not disclosed. Ask for the data quality statement rather than the headline, and treat a supplier who produces one as a supplier worth keeping.

How Do You Compare Two Suppliers Honestly?

Only after you have normalised boundary, unit, method and reference year, and only where both studies are of comparable quality. Where one supplier offers cradle-to-gate primary data and the other offers cradle-to-grave secondary data, they cannot be ranked, and saying so is the correct answer to the internal question. A comparison that has been forced is worse than no comparison, because it will be repeated in a tender.

What Does a Carbon Figure Do Inside a Buying Decision?

Less than most expect, and in a specific way: it decides between options, it does not rank suppliers. A study that compares two materials at one site tells you which material to specify, and it tells you nothing about whether another supplier would run that material better. Where a buying decision is between two suppliers rather than between two materials, carbon data is a weak instrument, and delivery performance, defect rates and document discipline are the ones that carry the decision.

Where it does earn its place is in a tender that asks for it, in a customer questionnaire that scores it, and in a design review where two constructions are genuinely close. In those three situations the figure is part of the evidence pack and it should be presented with the same care as a test report: method, boundary, unit, date, and the name of the person who can produce the study.

What Can Be Claimed From LCA Data, and What Cannot?

What can be claimed: a comparison between two specified options, under a stated boundary and unit, with the study available on request. What cannot be claimed: an absolute statement that a product is low-carbon, neutral or better, because those are claims about a product in the world rather than about a comparison between scenarios. The second family is where enforcement attention sits, and the first is where a buyer can safely operate.

A figure quoted in a business-to-business context — a tender response, a customer questionnaire, a sourcing decision document — is also a claim, and it is read against the same evidence. The discipline is identical: state the boundary, the unit and the method, and keep the study behind the sentence.

What Changes the Number Once the Specification Is Fixed?

Three levers remain after the material is chosen, and they are worth knowing because a design review can still move them. The first is mass: every gram of fabric, coating, hardware and packaging enters the material stage, and a reduction in GSM or in trim weight lowers the figure in roughly direct proportion. The second is cutting yield, because a marker that wastes more fabric carries the burden of material that was produced and then discarded inside the plant. The third is the transport assumption between stages, which is often the only part of the chain a buyer can influence without changing the product.

None of the three changes a published figure, and that is the point worth holding onto. A study describes one scenario; a change in the construction creates a second scenario that nobody has assessed. Where a programme alters the specification after the study, the figure that was quoted belongs to the earlier construction, and repeating it against the new one is a claim the study does not support. The disciplined move is to ask which parameters were sensitive, then re-run the study when one of them moves.

The question that produces that answer is short: which single assumption, if it were wrong by a stated margin, would change the ranking between the two options. A study built to support a decision can answer it, and the answer names the parameter that belongs under control in the specification. A study that cannot answer it was built to produce a number rather than to choose between two materials, and it should be treated accordingly.

How Should Carbon Data Be Requested in an Enquiry?

Ask for the five fields listed above, in one email, before the quotation is requested. A supplier with a real study will answer within a day; a supplier with a slide will take a week and then send the slide. The response time is itself a useful signal, and it costs nothing to find out.

Then ask the question that produces decisions rather than documents: which stage dominates, and what would change it. In most bag studies the answer points at the material stage and, where the boundary includes it, at the use stage. That answer tells a buyer where design effort changes the number, which is the only reason to have commissioned the study in the first place.

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