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Interpreting life cycle assessment data and results

Using resourcesLife cycle assessment and recycling

Flashcards

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How does a high manufacturing impact but low use-phase impact affect overall choice?

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A product with high manufacturing impact and low use-phase impact may still have lower lifetime impact if the use phase dominates total lifetime emissions and the product performs efficiently.

Key concepts

What you'll likely be quizzed about

Definition of life cycle assessment (LCA)

Life cycle assessment quantifies environmental impacts associated with all stages of a product’s life: raw material extraction, manufacture, transport, use and end-of-life. The functional unit defines the basis for comparison so results become comparable between different products or processes. LCA outputs appear as impact category values such as carbon dioxide equivalent (global warming potential) or resource depletion, which require interpretation in context.

Functional unit and system boundaries

The functional unit specifies the service provided (for example '1 kg of material' or '1000 hours of light') and normalises results for fair comparison. System boundaries decide which processes appear in the LCA (cradle-to-gate, cradle-to-grave, or cradle-to-cradle). Narrow boundaries exclude life stages and therefore cause underestimation of total impacts; wide boundaries include more processes and therefore increase reported impacts.

Impact categories and indicators

Impact categories group environmental effects such as global warming potential, acidification, eutrophication and human toxicity. Indicators convert inputs and emissions into comparable values (for example CO2e for greenhouse gas emissions). Different indicators emphasise different problems so a low impact in one category can coexist with a high impact in another; comparisons require matching which categories are reported.

Data quality and modelling assumptions

Data sources, age of data, and regional specifics affect LCA results because input emissions and efficiencies vary geographically and over time. Allocation rules for shared processes (for example co-products) and assumptions about product lifetime or recycling rates change final numbers. Low-quality or generic data increase uncertainty and reduce confidence in conclusions.

Comparative interpretation

Comparisons between LCAs require identical functional units, matched system boundaries, and the same impact categories. If comparisons show one option with higher manufacturing impact but lower use-phase emissions, the overall result depends on use duration and performance. Cause → effect logic clarifies outcomes: higher material energy use causes higher manufacturing impact; greater durability causes fewer replacements and therefore lower lifetime impact.

Sensitivity and uncertainty analysis

Sensitivity analysis tests how changes in assumptions (for example lifetime or recycling rate) change results. High sensitivity indicates that small assumption shifts cause large result changes and therefore reduce result robustness. Uncertainty analysis quantifies probable ranges; wide ranges indicate low certainty and require cautious interpretation.

Limitations and ethical choices

LCA excludes some social and economic factors unless specifically included, so it does not provide a complete sustainability judgement. Choices about weighting different impact categories or monetising impacts introduce value judgements that alter outcomes. Time and location dependence of impacts limit global applicability of a single LCA result.

Reading LCA results and graphs

Bar charts and pie charts commonly present impact contributions by life stage or category. Identification of the largest bars or slices shows dominant contributors. Cause → effect interpretation links the large contributor to the process that produces it (for example electricity use in manufacture causes a large share of greenhouse gas emissions).

Key notes

Important points to keep in mind

Always check the functional unit before comparing results.

Match system boundaries and impact categories for valid comparisons.

Identify the largest life-stage contributor to find improvement targets.

Treat generic or outdated data as high-uncertainty evidence.

State allocation and end-of-life assumptions when reporting LCA conclusions.

Use sensitivity analysis to test critical assumptions.

Recognise that LCA focuses on environmental impacts, not social factors.

Avoid comparing LCAs that use different units or weighting schemes.

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