An LCI database is a collection of datasets that provide detailed data on the environmental inputs and outputs (flows) associated with the life cycle of a product, process, or service. These datasets capture (background) environmental data such as resource consumption, emissions, and waste, and are used when primary data (data collected directly from a process or product) is unavailable.

Put differently, LCI databases allow you to model the environmental impacts of complex products or supply chains using standardized secondary, (background) environmental data via datasets when primary data is either not feasible to collect or is incomplete. They do this in combination with LCIA methods, read more about the connection between the two here.

An LCI database is made up of thousands of LCI datasets. Each dataset represents a single product, process, or service and includes data on the associated resource inputs (e.g., raw materials, energy) and outputs (e.g., emissions, waste). This data within LCI datasets can be thought of as (background) environmental data which is used in combination with (foreground) product data to attribute the environmental impact of a product. For example, when you purchase PET granulates, you know your product contains x amount of PET (aka (foreground) product data), but you don't know the environmental impact of the PET - datasets quantify this. The data included in a dataset is scaled to the functional unit of your model.

LCI datasets are important for calculating environmental impacts (in combination with LCIA methods) when primary environmental data is lacking. LCI datasets include the following components to derive the environmental impact of an item.

LCI databases and LCIA methods work together to translate raw, foreground product data into meaningful environmental impact results. LCI databases provide the input and output flows—such as resource use, emissions, and waste—associated with a product or process throughout its life cycle. However, this raw data alone doesn't show environmental impacts.

This is where LCIA methods come in. These methods interpret the flows from the LCI database, converting them into measurable environmental impact categories, such as global warming potential, water use, or toxicity. Combining the two elements—an LCI database (for data) and an LCIA method (for interpretation)—allows users to accurately assess the environmental performance of products or services. This relationship ensures that the detailed inventory data from the LCI database is meaningfully translated into actionable environmental insights.

Thus, LCI database + LCIA method = Impact results, giving LCA users a comprehensive view of the environmental impacts tied to their product or process (Figure 1).

In addition to the above, several specialized databases are available in Helix:

LCI databases are integral to conducting a complete and reliable LCA, allowing you to supplement primary data with standardized secondary data when needed. By integrating these databases with LCIA methods, Mobius and Helix users can transform raw data into meaningful insights, facilitating a deeper understanding of a product's environmental impact.