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Advanced Guide to Life Cycle Assessment (LCA) for XYCLE Users

A detailed look at LCA concepts, processes, and standards for advanced practitioners.

Life Cycle Assessment (LCA) is a scientific method for quantifying the environmental impacts of products, services, or systems. While XYCLE is designed to make the process more intuitive and efficient, understanding the detailed methodology behind LCA can significantly improve the quality of your modelling and interpretation.

This guide is based on the ILCD Handbook: General Guide for Life Cycle Assessment – Detailed Guidance (European Commission, 2010) and supplemented with insights from ISO 14040, ISO 14044, and leading academic resources. It is intended for advanced users who want to go beyond the basics and apply LCA best practice at a professional standard.

1. Core Concepts in LCA

The ISO framework defines four main phases:

  1. Goal and Scope Definition – Establishes the purpose of the assessment, the intended audience, and the system boundaries. This step also determines key assumptions, the level of detail required, and the choice of functional unit.

  2. Life Cycle Inventory (LCI) – The data collection phase, where every relevant input and output is measured or estimated. This includes raw material use, energy consumption, transport, emissions, and waste generation.

  3. Life Cycle Impact Assessment (LCIA) – The translation of inventory flows into environmental impact results through selected impact categories.

  4. Interpretation – The stage where results are evaluated for reliability, significance, and alignment with the original goals.

In XYCLE, these phases are built into the workflow, with the modelling interface helping you apply these principles without needing to build every step manually.

2. Modelling Systems with Precision

Accurate modelling requires a clear understanding of system boundaries and the distinction between foreground and background processes:

  • Foreground system – Directly controlled or influenced by the study commissioner (e.g. a manufacturer’s own production lines).

  • Background system – Processes indirectly linked to the system but not under direct control (e.g. raw material mining or national grid electricity).

The ILCD Handbook recommends that practitioners clearly document boundary choices to ensure transparency and reproducibility. In XYCLE, these definitions are embedded in your model setup, but advanced users may choose to adjust and document them explicitly when communicating results.

3. Data Quality, Representativeness, and Reliability

High-quality LCAs rely on datasets that are technologically, geographically, and temporally representative. The ILCD framework outlines Data Quality Indicators (DQIs) to assess:

  • Technological representativeness – The match between the dataset and the actual technology in use.

  • Geographical representativeness – The degree to which the dataset matches the location of the process.

  • Temporal representativeness – The currency of the data relative to the study period.

  • Completeness and precision – Whether the dataset includes all relevant flows and the level of uncertainty.

While XYCLE’s built-in datasets are pre-screened, advanced users should evaluate additional imported datasets using these DQIs to maintain scientific robustness.

4. Impact Assessment – Midpoint vs Endpoint Indicators

Impact categories provide the framework for translating LCI data into meaningful environmental results. Two key types are:

  • Midpoint indicators – Focused on specific impact pathways (e.g. greenhouse gas emissions, acidification). These are more transparent and widely comparable.

  • Endpoint indicators – Aggregated to reflect damage to areas of protection (e.g. human health, ecosystem quality, resource availability).

The ILCD recommends midpoint indicators for most applications, as they provide a clearer link between processes and impacts. This aligns with XYCLE’s impact category setup.

5. Interpretation, Sensitivity, and Uncertainty

Interpretation is not just the final step but an ongoing consideration throughout the assessment. Advanced interpretation includes:

  • Sensitivity analysis – Identifying parameters that have the greatest influence on results and testing alternative scenarios.

  • Uncertainty analysis – Understanding the statistical reliability of your results, especially when dealing with incomplete or estimated data.

  • Contribution analysis – Determining which life cycle stages contribute most to each impact category, helping to prioritise interventions.

In XYCLE, you can replicate these approaches by iteratively adjusting process inputs, swapping datasets, and reviewing changes in category results.

6. Transparency and Communication

A critical element of advanced LCA practice is transparency. The ILCD emphasises that all methodological decisions, data sources, assumptions, and limitations should be documented in a way that allows others to replicate the study.

For XYCLE users, this means:

  • Keeping records of dataset sources and reasons for selection.

  • Clearly stating modelling assumptions, especially around allocation, cut-off criteria, and background data.

  • Providing results alongside relevant context to avoid misinterpretation.

7. Recommended Reading for Further Depth

  • European Commission, Joint Research Centre (2010) ILCD Handbook: General Guide for Life Cycle Assessment – Detailed Guidance. Luxembourg: Publications Office of the European Union.

  • ISO (2006) ISO 14040: Environmental Management – Life Cycle Assessment – Principles and Framework. Geneva: International Organization for Standardization.

  • ISO (2006) ISO 14044: Environmental Management – Life Cycle Assessment – Requirements and Guidelines. Geneva: International Organization for Standardization.

  • Hauschild, M.Z., Rosenbaum, R.K. and Olsen, S.I. (2018) Life Cycle Assessment: Theory and Practice. Cham: Springer.

Next Steps for XYCLE Users

  1. Apply these principles to refine existing models.

  2. Test sensitivity by adjusting data sources and assumptions.

  3. Use midpoint categories for clearer, more comparable results.

  4. Explore the recommended literature to develop greater expertise in LCA methodology.

Need Expert Support?

If you are looking for more in-depth support, our in-house consultancy team is available to help at any stage of your LCA journey. We can also work with you to upskill your team members, ensuring they have the confidence and capability to apply LCA best practice in their work.