LCA Datasets

CarbonGraph connects you to a growing set of Life Cycle Assessment (LCA) datasets, which are sourced from authoritative external databases such as Ecoinvent, IDEMAT, and the NREL USLCI. In CarbonGraph, adataset refers to a versioned collection of LCA processes imported from a larger source database, adapted for seamless use within your models.

Our platform emphasizes the use of primary data—data you create or collect yourself—for the most accurate and relevant assessments. To support this, we offer a curated and expanding library of secondary datasets to help fill gaps where primary data may not be available.

All models and datasets created within your CarbonGraph account are fully version-controlled and can be synced or updated automatically. You can link your custom data with external datasets to build comprehensive, organization-specific models with both proprietary and reference content.

Don't see the dataset you need? We 're continually expanding our coverage. Reach out to us at support@carbongraph.io to request additional database integrations.

Any model you build in CarbonGraph becomes part of your private dataset. These LCAs are fully reusable within your organization and can be imported into other assessments as needed. They are designed to support team workflows and internal consistency.

• Private and secure: By default, models are only visible to your team. Sharing is optional and controlled.
• Version-controlled: Track changes, review previous states, and sync updates across linked assessments.
• Tailored to your data: Use your own inputs, operating conditions, and assumptions to reflect real-world performance.
• Integrates with reference datasets: Seamlessly combine proprietary models with secondary data where needed.

Ecoinvent is one of the most widely used and respected LCI databases globally. It is maintained by the Ecoinvent Association and supports consistent, transparent modeling of supply chains across numerous sectors.

Current Versions Available: 3.9.1 – Cut-off by Classification (with upcoming addition of 3.11)

Website: ecoinvent.org

Strengths:

• Comprehensive sector coverage with over 18,000 datasets covering energy, chemicals, materials, agriculture, transport, and more.
• Transparent documentation of system boundaries, allocations, and data sources.
• Regularly updated to reflect the latest scientific research, industry changes, and regulatory standards.
• Supports multiple system models including Cut-off, Allocation at the Point of Substitution, and Consequential modeling.

Coverage and Characterization:

• Global and regional datasets including detailed upstream processes and regional electricity mixes.
• Compatible with a range of LCIA methods including ReCiPe 2016, TRACI 2.1, EF 3.0/3.1, IMPACT World+, and EPS 2020.

The USLCI dataset, developed by the National Renewable Energy Laboratory (NREL), is a publicly available database representing U.S.-specific processes. It is part of the Federal LCA Commons and provides a valuable foundation for regionally relevant LCAs.

Current Version: v1.2025-03.0 (Elementary Flow List v1.3.0)

Website: lcacommons.gov

Strengths:

• U.S. specific data reflecting domestic technologies, infrastructure, and energy mixes.
• Transparent documentation and open access.
• Flexible modeling options through multiple dataset variants.

Coverage and Characterization:

• Approximately 1,500 processes spanning fuels, electricity, transportation, construction materials, and waste treatment.
• Supports LCIA methods such as ReCiPe 2016 (midpoint and endpoint) and TRACI 2.1.

Dataset Variants Available:

• Original Gate-to-Gate: Unmodified processes from the USLCI database.
• Simplified Gate-to-Gate: Cutoff flows are excluded to focus on core process performance.
• Cradle-to-Gate: Constructed models with upstream dependencies stitched together for complete system modeling.

IDEMAT, developed by TU Delft, is especially suited for early-stage product design and material selection. It emphasizes engineering applications and eco-cost modeling for circular design.

Current Version: IDEMAT 2023 – Cut-off by Classification

Website: ecocostsvalue.com

Strengths:

• Strong alignment with product design tools and academic eco-design methodologies.
• Emphasizes transparency and simple integration with engineering workflows.

Coverage and Characterization:

• Over 2,000 processes covering common materials, plastics, metals, and wood products.
• Strong focus on European infrastructure and energy systems.
• Supports ReCiPe 2016, Eco-costs, CED, and both midpoint and endpoint methods.

Selecting the appropriate dataset is a key part of LCA best practices, as described in ISO 14044. A good dataset choice ensures relevance, transparency, and alignment with your assessment goals. Consider the following factors when selecting a dataset:

• Geographic scope: Use regional datasets when modeling region-specific systems, especially for electricity, transport, and resource extraction.
• Sector specificity: Some datasets have stronger coverage in particular industries such as chemicals, agriculture, or construction.
• Data quality and completeness: Consider whether the dataset offers sufficient transparency in assumptions, sources, and methodological choices.
• LCIA compatibility: Ensure the dataset is compatible with the impact assessment methods you plan to use (e.g., ReCiPe, TRACI).
• Update frequency and maintenance: Prefer datasets that are regularly updated to reflect current practices and science.

CarbonGraph enables you to combine multiple datasets within a single model. This flexibility allows you to use the best available data for each part of your system while maintaining overall consistency.

Each dataset available in CarbonGraph reflects the methodological choices and data structure of its original source. We recommend reviewing the official documentation provided on each dataset's website for full details regarding data quality, assumptions, and conformance to standards such as ISO 14040 and 14044.

While CarbonGraph performs validation and quality checks during dataset ingestion, harmonizing diverse datasets into a consistent modeling environment can present challenges. Differences in system boundaries, flow naming, or characterization factors may introduce unintended inconsistencies. Despite our best efforts, errors may occasionally persist.

If you identify any issues or suspect a discrepancy in the data, please contact us at support@carbongraph.io. We actively investigate all reports and appreciate your help in maintaining the quality and reliability of our shared data resources.