DEISO Agri & Industrial LCI Database™
Download the Sample Database
Explore a truncated demo version of the DEISO Agri & Industrial LCI Database™ to review the structure, readability, and separation between normalized datapoints and true emission factors before purchase.
Why the DEISO Agri & Industrial LCI Database™ Exists
The DEISO Agri & Industrial LCI Database™ was developed as a literature-based gap-filling resource for sustainability professionals who need emission factors and inventory datapoints that are often missing from existing databases. Its purpose is to transform published scientific literature into a structured, usable format that supports practical work across GHG accounting, Product Carbon Footprint (PCF), Scope 3 emissions assessment, and broader Life Cycle Assessment (LCA) applications.
Unlike conventional database content presented only as background data, this product is explicitly built on literature-derived emission factors and inventory datapoints compiled from scientific studies. This makes it especially useful when current databases do not provide sufficient coverage for a specific product, material, region, process stage, or supply chain context.
Although some underlying studies are not the most recent available, many emission factors remain highly useful over time because they do not materially change every year, particularly for stable processes, established production systems, and literature-based reference conditions. For this reason, the database serves as a practical and transparent literature-based support tool for screening, modeling, benchmarking, and gap-filling analysis where newer or more specific data are unavailable.
In short, the value of this database lies in making scientific literature operational — turning dispersed published data into a structured dataset that helps practitioners work faster, document assumptions more clearly, and strengthen the technical basis of sustainability studies.
DEISO Agri & Industrial LCI Database™
A literature-based life cycle inventory database compiled from scientific sources and structured into ready-to-use datapoints for agriculture, livestock, food processing, and industrial systems.
This database is transparently built from published literature and scientific studies. It combines normalized inventory datapoints and a dedicated emission factor subset in a structured format designed for practical use in LCA, PCF, and Scope 3 analysis.
Database Scale at a Glance
Records by Sector
Records by Dataset Type
Records by Flow Direction
The database is dominated by inventory inputs and output flows, while the strict emission-factor subset isolates only the environmental emission records required for direct factor-based applications.
Download the Sample Database
Explore a truncated demo version of the DEISO Agri & Industrial LCI Database™ to review the structure, readability, and separation between normalized datapoints and true emission factors before purchase.
Product Coverage
The DEISO Agri & Industrial LCI Database™ currently covers the products listed below. The database is strictly available at this stage only for these products and their related literature-based datapoints, emission factors, and inventory records.
Important note: Coverage in the current release is limited to the products listed in this section. Additional products, sectors, and extensions may be added in future versions as the database expands.
Agriculture & Crops
- Rice
- Corn
- Sugarcane
- Sugar beet
- Tomato
- Cucumber
- Cacao
- Coffee
- Tea
- Palm oil
Livestock & Animal Products
- Beef
- Pork
- Chicken
- Lamb
- Milk
- Cheese
- Meat products
Food Processing
- Beer production
- Chocolate
- Processed meat products
- Canned food systems
Industrial & Materials
- Aluminum
- Nickel
- Copper
- Gold
- Lithium
- Iron ore
- Chromium
- Cobalt
Overview
11,800+ Structured Datapoints and 3,400+ Emission Factors — Ready for LCA, PCF, and Scope 3 Analysis
Stop spending weeks extracting data from scientific literature. The DEISO Agri & Industrial LCI Database™ delivers a curated, structured, and ready-to-use dataset covering agriculture and industrial systems — built for real-world sustainability analysis.
The database currently covers the following products:
- Rice
- Corn
- Sugarcane
- Sugar beet
- Tomato
- Cucumber
- Cacao
- Coffee
- Tea
- Palm oil
- Beef
- Pork
- Chicken
- Lamb
- Milk
- Cheese
- Meat products
- Beer
- Chocolate
- Processed food systems
- Aluminum
- Nickel
- Copper
- Gold
- Lithium
- Iron ore
- Chromium
- Cobalt
For each product, the database compiles all emission factors and inventory datapoints reported in the reviewed academic literature, rather than providing a single averaged or selected value.
For example, for a product such as tomato, you may find emission factor values for the same pollutant (e.g., CO₂ emissions) reported across multiple independent studies — sometimes 10+ different values from different academic papers, regions, assumptions, and system boundaries.
The concept of this database is therefore not to prescribe a single “correct” emission factor, but to:
- capture the full range of literature-reported values,
- preserve transparency across sources, and
- provide users with the ability to select the most appropriate value based on their specific goal, scope, geography, and methodological assumptions.
This makes the database particularly powerful for:
- sensitivity analysis
- scenario comparison
- literature-backed justification
- transparent reporting
Final responsibility remains with the user to determine which emission factor is most appropriate for their specific application.
Understanding the Database Structure
Why This Database Includes Two Data Layers
The DEISO Agri & Industrial LCI Database™ is designed to serve both practical and advanced use cases in sustainability analysis.
To achieve this, the database is structured into two distinct but connected data layers:
- Emission Factors (Ready to Use)
- Full LCI Database (Inputs, Outputs & Emissions)
Each layer serves a different purpose. Understanding the difference will help you use the database effectively.
1. Emission Factors (Ready to Use)
This sheet contains only true emission factors, meaning environmental emissions per functional unit.
These are directly usable in:
- Life Cycle Assessment (LCA)
- Product Carbon Footprint (PCF)
- Scope 3 emissions calculations
- Sustainability reporting
What is Included
- Greenhouse gases (CO₂, CH₄, N₂O)
- Air emissions (NH₃, NOx, SO₂, etc.)
- Water emissions (BOD, COD, nutrients, wastewater)
- Other environmental releases
What is NOT Included
- Electricity or fuel inputs
- Material consumption (e.g., steel, plastic)
- Intermediate products
- Transport or process parameters
Example
0.6427 kg CO₂ per kg aluminium
866 g CH₄ per kg live weight
Use this sheet if you need direct emission factors without additional processing.
2. Full LCI Database (Inputs, Outputs & Emissions)
This sheet contains the complete structured dataset, including all extracted information from the literature.
It represents full Life Cycle Inventory (LCI) data.
What is Included
- Emission factors
- Resource inputs (water, materials, energy)
- Products and coproducts
- Waste and wastewater flows
- Transport activities
- Process-level inventory data
Example
- Electricity input = 0.14 kWh per kg product
- Water input = 2.56 L per kg product
- Organic waste output = 0.2 kg per kg product
Use this sheet if you need:
- Full process modeling
- Custom LCA model development
- Data gap filling
- Advanced sustainability analysis
Key Difference Summary
| Feature | Emission Factors | Full LCI Database |
|---|---|---|
| Purpose | Direct use | Full modeling |
| Data Type | Emissions only | Inputs, outputs, emissions |
| Complexity | Low | High |
| Best For | Quick calculations | Advanced LCA work |
When Should You Use Each?
- Use Emission Factors → if you need fast, reliable emission values
- Use Full LCI Database → if you are building or customizing models
Most users will primarily use the Emission Factors sheet, while advanced users and consultants will benefit from the full LCI dataset.
Important Note
The full LCI database includes a larger number of datapoints because it contains complete inventory data.
The emission factor sheet is a filtered subset of this dataset.
Total datapoints: 11,800+
Emission factors: 3,400+
Frequently Asked Questions (FAQ)
Goal of the Database
The DEISO Agri & Industrial LCI Database™ was developed to help close a persistent data gap in sustainability analysis. In many real-world projects, existing databases do not provide sufficient coverage for specific products, materials, regions, supply chain stages, or inventory flows. This becomes a practical challenge in GHG accounting, Product Carbon Footprint (PCF) studies, Scope 3 emissions assessment, and broader Life Cycle Assessment (LCA) work.
The goal of this database is to bridge that gap by transforming literature-based data into a structured, usable format. Rather than leaving practitioners to manually search, extract, interpret, and compare values across scientific papers, the database provides curated datapoints compiled from the literature and organized for direct application. This makes it easier to identify relevant emission factors, inventory inputs, and process outputs when conventional databases are incomplete or when project-specific evidence is needed.
This is especially valuable for:
- filling data gaps in LCA and carbon footprint models,
- supporting Scope 3 category analysis where secondary data are often limited,
- identifying literature-based emission factors for agricultural and industrial systems,
- strengthening transparency and documentation in studies that require traceable published sources.
It is important to note that the underlying references are not always the most recent available in the market. However, this does not automatically reduce the usefulness of the database. Many emission factors and inventory values do not change materially from year to year, particularly when they relate to stable processes, established production systems, or literature-derived reference conditions. In practice, older literature-based values are often still used for screening studies, secondary-data modeling, benchmarking, and gap filling when newer primary data are unavailable.
For this reason, the database should be understood as a gap-filling, literature-based support tool
What is meant by a “datapoint” in this database?
A datapoint refers to a single structured piece of information extracted from scientific literature and standardized into a consistent format.
Datapoints include:
- emission factors
- inventory inputs (e.g., energy, water, materials)
- outputs (e.g., products, waste, emissions)
- transport activities
- process-related parameters
Each datapoint represents a specific value reported in a study, including its unit, context, and reference. The database contains 11,800+ structured datapoints covering multiple products and sectors.
What is an emission factor?
An emission factor is a quantified value that represents the amount of a pollutant released per unit of activity or product.
Examples:
- kg CO₂ per kg product
- g CH₄ per kg live weight
- kg NH₃ per hectare
In this database, emission factors are:
- extracted directly from scientific literature
- clearly separated into a dedicated sheet
- ready for use in LCA, PCF, Scope 3, and sustainability reporting
The database includes 3,400+ emission factors across multiple sectors.
What is the difference between “Emission Factors” and “Normalized Records Database”?
The database is structured into two layers:
Emission Factors Only
- Contains only true environmental emission factors
- Ready for direct use in calculations and reporting
- Simplified and easy to filter
Normalized Records Database
- Contains the full structured dataset
- Includes inputs, outputs, emissions, and inventory data
- Intended for advanced analysis and LCA modeling
The emission factor sheet is a filtered subset of the full dataset.
Are the datapoints normalized to 1 kg or a standard unit?
No.
All datapoints and emission factors are presented exactly as reported in the original literature, including their original units and functional units.
No mathematical normalization, scaling, or unit conversion has been applied.
This ensures:
- full transparency
- traceability to source studies
- flexibility for different modeling approaches
Why are multiple emission factors provided for the same product?
For many products, multiple studies report different emission factor values due to:
- geographic differences
- system boundaries
- methodological assumptions
- production practices
For example, a product like tomato may have emission factors reported across multiple academic papers, sometimes with more than 10 different values for the same pollutant.
The database is designed to:
- capture all literature-reported values
- preserve transparency across sources
- allow users to select the most appropriate value
The responsibility for selecting the appropriate emission factor remains with the user.
Is the database based on scientific literature?
Yes.
The database is fully literature-based, compiled from over 160 scientific sources, including peer-reviewed academic studies.
All datapoints are:
- extracted from published research
- structured into a consistent format
- linked to their original references
This ensures a transparent and traceable dataset for professional use.
Is the database based on scientific literature?
Yes.
The database is fully literature-based, compiled from over 160 scientific sources, including peer-reviewed academic studies.
All datapoints are:
- extracted from published research
- structured into a consistent format
- linked to their original references
This ensures a transparent and traceable dataset for professional use.
Are the data up to date?
The database includes studies up to approximately 2019–2020 in most cases.
However, many emission factors remain valid over time because:
- they represent stable processes
- they are based on established production systems
- they are used as reference values in LCA practice
As a result, the database remains highly useful for:
- screening studies
- gap filling
- benchmarking
- literature-supported analysis
Can this database replace commercial LCI databases?
No.
This database is designed to complement, not replace, existing databases.
Its primary role is:
- to fill gaps where data are missing
- to provide literature-based values
- to support transparency and justification
It is especially valuable when:
- existing databases lack specific products or regions
- literature-based justification is required
Who is responsible for selecting the correct emission factor?
The user is responsible.
The database provides:
- multiple literature-based values
- structured datapoints
- full transparency
Users must select emission factors based on:
- goal and scope
- geography
- system boundaries
- methodological requirements
Who is responsible for selecting the correct emission factor?
The user is responsible.
The database provides:
- multiple literature-based values
- structured datapoints
- full transparency
Users must select emission factors based on:
- goal and scope
- geography
- system boundaries
- methodological requirements
What license model applies to the database?
The database is provided under a perpetual license.
- Access is granted permanently for the purchased version
- Future updates or new versions may require additional fees
License types include:
- Educational
- Research
- Commercial
- Enterprise
- SaaS / AI integration
Can the database be used in software or AI systems?
Only under a SaaS / AI / Platform license.
This includes:
- integration into tools or platforms
- API usage
- AI model training or deployment
Such use requires a custom license agreement.
Pricing
| License Type | Price (USD) | Access Basis | License Term | Future Updates | Notes |
|---|---|---|---|---|---|
| Educational | $350 | Per user | Perpetual | Subject to additional fees if an updated version is requested | Academic and educational use only |
| Research | $680 | Per user | Perpetual | Subject to additional fees if an updated version is requested | Individual researcher use |
| Commercial | $1,800 | Per user | Perpetual | Subject to additional fees if an updated version is requested | Internal professional or company use |
| Enterprise | $7,500+ | Company-wide | Perpetual | Subject to additional fees if an updated version is requested | Organization-wide internal use |
| SaaS / AI | Custom quotation | Based on scope and deployment model | Perpetual | Subject to additional fees if an updated version is requested | SaaS, cloud, API, platform, AI, or software integration use |
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