Life cycle assessment, or LCA, is a method for measuring the environmental impacts of a product, service, or process from raw material extraction to disposal. This cheat sheet helps students compare choices using evidence instead of assumptions. It is useful for environmental science, sustainability projects, engineering design, and consumer product analysis.
A clear LCA reference also helps students organize data and explain tradeoffs.
Key Facts
- The four main LCA phases are goal and scope definition, inventory analysis, impact assessment, and interpretation.
- A functional unit defines the exact service being compared, such as 1,000 liters of bottled water delivered to consumers.
- System boundaries state which life cycle stages are included, such as raw materials, manufacturing, transport, use, and end of life.
- Total impact can be estimated with Total impact = sum of activity data x emission factor for all included processes.
- Carbon footprint is often reported as CO2e, where CO2e = mass of gas x global warming potential.
- Energy intensity can be calculated as Energy intensity = total energy used / functional unit.
- Allocation divides shared environmental burdens among co-products, often by mass, economic value, or energy content.
- Interpretation checks whether conclusions are supported by the data, assumptions, uncertainty, and sensitivity analysis.
Vocabulary
- Life Cycle Assessment
- A method for evaluating environmental impacts across the full life of a product, service, or process.
- Functional Unit
- The measured amount of service used as the basis for comparison in an LCA.
- System Boundary
- The set of life cycle stages and processes included or excluded from the assessment.
- Life Cycle Inventory
- A list of all material inputs, energy inputs, emissions, and waste flows for the system being studied.
- Impact Category
- A type of environmental effect measured in LCA, such as climate change, water use, or eutrophication.
- Sensitivity Analysis
- A test of how much results change when key assumptions, data values, or methods are adjusted.
Common Mistakes to Avoid
- Comparing products without the same functional unit is wrong because the products may not provide the same amount of service.
- Ignoring system boundaries is wrong because excluding stages such as transport or disposal can change the final conclusion.
- Treating carbon footprint as the only impact is wrong because products may also differ in water use, toxicity, land use, and waste.
- Using average data without checking assumptions is wrong because local electricity sources, transport distances, and use patterns can strongly affect results.
- Assuming recycling always lowers impact is wrong because collection, processing, contamination, and material quality also affect the net benefit.
Practice Questions
- 1 A product uses 4.0 kWh of electricity per functional unit. If the emission factor is 0.45 kg CO2e per kWh, what is the climate impact from electricity use?
- 2 A reusable bottle causes 2.4 kg CO2e to manufacture and saves 0.08 kg CO2e each time it replaces a single-use bottle. After how many uses does it break even?
- 3 A shipment travels 300 km by truck with an emission factor of 0.12 kg CO2e per ton-km. If the shipment mass is 2.0 tons, what is the transport impact?
- 4 Two products have the same carbon footprint, but one uses much more water in a drought-prone region. Explain why an LCA conclusion should not be based only on carbon.
Understanding Life Cycle Assessment Reference
The goal of a study controls every later decision. A company may want to improve one product design. A school project may compare two ways of providing the same service.
The comparison must be fair. A reusable cup and a disposable cup cannot be compared simply by counting cups. The study needs to describe how many drinks are served, how often the reusable cup is washed, and how long it lasts.
The functional unit acts like a measuring rule. If the rule changes, the result can change too. Students should write this rule early and keep it unchanged throughout the work.
Inventory work is often the longest part of an LCA. It involves collecting amounts of materials, fuel, electricity, water, packaging, and waste for each included process. Some data come from direct measurements, such as a factory electricity bill.
Other data come from databases, government reports, or scientific studies. Secondary data can be useful, but it may describe another country, an older technology, or an average factory. This creates uncertainty.
Small inputs can matter when they occur many times. For example, a thin plastic wrapper may have little impact per item, yet its total can become large across millions of items. Cutoff rules should be stated clearly when small flows are left out.
Impact assessment turns inventory flows into environmental indicators. Climate change is one indicator, but it is not the only one. Energy use, water scarcity, air pollution, acidification, nutrient pollution, land use, and resource depletion can point in different directions.
A choice that lowers carbon emissions may use more water in a dry region. Recycling may reduce demand for new material, though collection, sorting, and reprocessing require energy. Location matters because one kilogram of pollution does not cause the same harm everywhere.
Time matters too. Electricity from a grid can have different impacts during the day if the mix of power sources changes.
Interpretation is where careful thinking matters most. Results are estimates rather than permanent facts. Students should identify the processes that contribute the most impact.
These are often called hotspots. A sensitivity check changes one reasonable assumption at a time, such as transport distance, product lifetime, recycling rate, or electricity source. If the ranking between options changes easily, the conclusion is weak and should be reported carefully.
Allocation needs special attention when one process makes several useful outputs. Assigning impacts by mass can produce a very different answer from assigning them by market value. A strong conclusion explains what the evidence supports, what remains uncertain, and which improvement would likely matter most.