Collecting the Right Data for Your LCA

Accurate data is the backbone of any Life Cycle Assessment (LCA). The quality of your results depends directly on the quality of your inputs. In XYCLE, you combine your own operational data with high-quality datasets to build a complete model of your product or process. Understanding which type of data you are working with will help you enter it correctly and interpret results more effectively.

Beginner’s Guide: Foreground and background data

At this stage the Life Cycle Inventory (LCI) is built and involves collecting, compiling and quantifying all the inputs (materials, chemicals, energy, resources) and outputs (products, waste and emissions) associated with a product throughout its life cycle. This data will be collected in two forms:

• Foreground data: Information collected directly from your own operations or supplied by your partners. This could include quantities of raw materials used, energy consumption, or waste generated.

• Background data: Information from external databases that fills in the rest of the picture. For example, the emissions associated with producing 1 kWh of electricity in a specific country.

Foreground data is specific to your case. Background data provides the standardised context needed to complete the life cycle picture.

Advanced Detail: Choosing the right data sources

At Minviro, background data is typically sourced from the Ecoinvent database or Minviro’s own curated datasets, like our XYCLE Battery Materials Database. For certain chemicals, Carbon Minds data may also be used. When selecting background data, it is important to match the geographic, technological, and time-related characteristics of your processes as closely as possible.

For suppliers, the focus is often on providing accurate and representative foreground data. For manufacturers, the task may involve collecting data across multiple suppliers and ensuring it integrates well with selected background datasets.

In XYCLE: Working with data

When building your model in XYCLE:

1. Enter your primary (foreground) data for each process.

2. XYCLE will suggest matching background datasets based on your process description and location.

3. You can review these matches and replace them with a more suitable dataset if needed.

By combining accurate foreground data with the most relevant background data, you create a model that is both realistic and useful for decision-making.

Next Steps Checklist

1. List the data you can collect directly from your own operations or suppliers

2. Confirm the measurement units and ensure data is scaled to the correct functional unit

3. Review background datasets suggested by XYCLE to ensure they match your process context

4. Fill in any missing data before running your impact assessment