Understanding and interpreting ecoinvent datasets, the most commonly used Life Cycle Inventory (LCI) database in Ecochain’s Mobius and Helix software, is essential for attributing accurate environmental impact to your model. This article answers the following questions about ecoinvent datasets:
What are ecoinvent datasets?
How to ecoinvent datasets?
How to select an ecoinvent dataset?
Feel like you're missing information? This article builds upon the following articles, check them out if you want to learn more:
On adding datasets in Mobius: Mobius - How to: Add impact to your model using datasets
On adding datasets in Helix: Helix - How to: Company level inputs
On LCA data types: Explained: Data in LCA
On the LCI phase: Explained: Life Cycle Inventory (LCI) phase
On LCI databases: Explained: LCI databases
What are ecoinvent datasets?
Ecoinvent datasets, like other Life Cycle Inventory (LCI) datasets, are standardized, comprehensive records of secondary (background) environmental data that capture the inputs, outputs, and emissions of production processes. Ecoinvent datasets come from the ecoinvent database, the world’s most comprehensive, transparent, and international LCI database, featuring over 19,000 datasets across various industries. Ecoinvent datasets are available in Ecohain’s Mobius and Helix software.
How to interpret ecoinvent datasets?
The following subsections break down the naming structure of ecoinvent datasets, helping you interpret them more effectively. Read the explanations while referring to Figures 1 and 2 below.
Interpret ecoinvent datasets in Mobius and Helix
Ecoinvent datasets follow similar naming structures in Mobius (Figure 1) and Helix (Figure 2), although, they vary slightly. The figures below highlight the differences between the two software. The different elements of the dataset name are numbered corresponding to the numbered elements above.
Figure 1: An ecoinvent dataset as it appears using the dataset search function in Mobius.
Figure 2: An ecoinvent dataset as it appears using the dataset search function in Helix.
A breakdown of ecoinvent dataset’s naming structure
Dataset name & production method
The second part of the name: This is the first thing you should pay attention to. This input should match or represent the item you are searching for.
The first part of the name: The first part of the name describes the production process (activity) that is used to create the output described in the second part of the dataset name. This is relevant because there may be several production methods creating the same good, which will affect its environmental impact. This part of the name typically indicates two main groups of ecoinvent datasets - market and production datasets (see the subsection below).
Database or system model: This part of the name is less relevant than the first two parts. A system model defines how environmental impacts are allocated across different life cycle stages. In Mobius and Helix, we currently offer the most commonly accepted "Allocation, cut-off by classification" system model, “Cutoff, U” for short. This model follows the recycled content or cut-off approach, meaning:
Producers are responsible for waste disposal.
No credits are given for recyclable materials.
Recyclable materials become "burden-free" for subsequent users.
The region: Select datasets that match your product's manufacturing region. If a specific country isn’t available, opt for neighboring countries, continental data, or global datasets. Look out for database codes indicating regions:
Region: Try filtering for a region (e.g., Europe).
Rest-of-world: A rest-of-world dataset represents every region except the specific regions that might be available for the same activity.
Global: Global datasets are representative of the entire world.
Pro tip - Datasets available on regional levels: Generally, ecoinvent has good coverage of energy datasets on a country level (e.g. electricity usage, natural gas etc.). Materials, transportation and waste datasets typically are available on a regional level.
4. The units: The unit for which the dataset is expressed.
Caution - Dataset units in Mobius: If you are a Mobius user, it is important to compare the units used in your model with dataset units. Do so via the properties feature.
5. Database version: Both software contain different ecoinvent versions. We always suggest using the most recent database version, unless you’re following LCA rules or standards that state otherwise.
Pro tip - Most recent version of ecoinvent: The most recent ecoinvent version available in Mobius and Helix is ecoinvent v3.9.1.
What is the difference between Market and Production datasets?
Market datasets represent a regional or global average of a product. They account for multiple production methods and include average transportation distances and potential losses during distribution.
Production datasets focus on the specific manufacturing process of a product, detailing its inputs and outputs. These datasets are more precise and may specify a particular production method, which is important when multiple manufacturing techniques exist.
Are you still deciding between market or production datasets? Consider the following:
Transport: The main difference between the two datasets is that a market dataset builds on its corresponding production dataset by adding representative transportation impacts. Market datasets may be preferred if you do not know the exact transport distances of goods from your supplier (whether they are a direct supplier or intermediary supplier). This transport can reflect either. The transportation impact included in a market dataset depends on the dataset’s regional scope. For example, a European market dataset reflects typical transport distances within Europe.
Production method: If you know how the good was produced, production datasets are favorable because they are more specific to one production method. Whereas, if the production method is unknown, market datasets represent a market average of all production methods.
What are general tips for selecting an ecoinvent dataset?
Here are some general tips to guide your selection process for ecoinvent datasets.
Use keywords: Enter relevant keywords related to the item or object you wish to assess.
Pro tip - Synonyms: Sometimes the keywords or the words you use to describe what you’re looking for will not yield the desired results. If you’re running into this issue, try using synonyms, scientific names, and other means of describing the object you need a dataset for. For example, the dataset for ‘cardboard’ is ‘corrugated board box’ - a synonym for cardboard, or use ‘lorry’ when you’re looking to model the impact of transporting items with a truck.
Consider looking at our Datasets collection for more tips for specific cases!
Match the process: Ensure the dataset’s production method aligns with your product.
For example, "foam glass" might appear in multiple datasets (Figure 3), but each will reflect different production methods.
Figure 3: Example of ecoinvent datasets for the same material with different production methods. The first dataset uses market activities, while the third dataset does not use glass cullet to produce the foam glass.
Check geographical relevance: Use datasets that reflect your production location as closely as possible.
Seek additional information: In Mobius, you can choose to view a more detailed description of the dataset. This may give you extra information to feel confident selecting a dataset.
How to select (ecoinvent) datasets in Mobius and Helix?
While the tips above generally help select ecoinvent datasets regardless of the software, follow these links for more specific guidance on dataset selection in Mobius or Helix.
Next steps
Understanding ecoinvent datasets is key to building accurate and reliable environmental models in Mobius and Helix. By understanding their naming structure and selecting datasets accordingly, you ensure that your impact assessments reflect real-world processes as closely as possible.