Inventory Analysis: Data Collection, Modelling and Allocation
What this domain tests
Inventory Analysis tests whether you can build a transparent flow model: collect valid data, link unit processes, handle multi-output processes, and check mass and energy balance before impact assessment.
Core rules and concepts
- The LCI compiles exchanges with the environment and technosphere for every unit process in the boundary.
- Prefer specific, primary data for influential processes; use secondary or background data where appropriate and document representativeness.
- Validate data for units, completeness, consistency, and plausibility. Mass and energy balances are basic checks.
- Allocation hierarchy under ISO 14044: avoid allocation by subdivision or system expansion; if unavoidable, use a physical relationship; then use another relationship such as economic value.
- Recycling and multi-output processes need explicit methods to avoid double counting and to reflect actual substitution or quality changes.
Worked example
A dairy plant produces milk and cream from the same raw milk input. If the study cannot subdivide the process, it may allocate burdens by economic value. Suppose milk contributes 80% of revenue and cream 20%; the milk line receives 80% of the shared processing burden. That is defensible only if revenue reflects the causal driver. If cream production causes a disproportionate share of refrigeration energy, a physical energy allocation may be better. The reasoning must be stated, because changing allocation can change the ranking.
Traps that cost marks
- Allocating by mass when products have very different value or function.
- Double counting recycled material as both waste and input.
- Mixing data from different years, geographies, or technologies without adjustment.
- Skipping mass or energy balance checks.
- Treating background database values as site-specific measurements.