Our methodology

Last update: 6 December, 2024

Climatiq is a carbon calculation solution. We provide the largest database of verified emission factors and an AI-powered carbon calculation engine for performing emission calculations across scopes 1, 2, and 3, including advanced use cases such as freight shipping, purchased goods and services, market- and location-based energy, and travel.

We uphold rigorous standards to ensure our data is reliable and our calculation methodology meets the requirements for compliant greenhouse gas (GHG) emissions measurements.

Climatiq’s calculation API for energy, procurement (Scope 3.1), freight, travel, and cloud computing has been audited and verified to meet the requirements of ISO 14067, the GHG Protocol, and ISO 14064-3:2020-05. Our freight calculation API is accredited by the Smart Freight Center for GLEC-compliant calculations.

This ensures our data and calculations can be used for reporting under regulations and standards requiring GHG Protocol compliance, for example CSRD / ESRS and IFRS, and region-specific reporting requirements such as CBAM (Europe) and NGER (Australia).

Our Scientific Advisory Board (SAB) is composed of experts across carbon accounting, climate science, ecological economics, and data science. We consult with our SAB for reviews, updates, and new feature releases.

Climatiq also holds certifications for ISO 27001:2017 and SOC 2 Type II, demonstrating adherence to high standards for information security and data privacy. Additionally, regular penetration testing is conducted, with reports available for review.

You can find our assurance certificates and audit reports here.

Climatiq’s data methodology

Our emission factor database is the largest of its kind. We integrate data from a range of sources such as governmental bodies, not-for-profit organizations (NGOs), and academic institutions to cover 300 regions, all scopes, and spend- and activity-based data.

Before ingression, new data undergoes a rigorous vetting process to ensure quality and reliability. It is then normalized to fit with our self-developed data schema.

Data coverage

Sources of emission factor data

Climatiq offers the largest emission factor database with 90,000+ factors. We include data from more than 40 sources and 70 datasets, including governmental bodies such as EPA in the United States and BEIS / DEFRA in the United Kingdom, and other verified providers such as NGOs, ecoinvent, and IEA. Discover the data sources we cover here.

Below is an interactive visualization of the datasets in our database.

Regional coverage

Our emission factors cover 300+ global regions, ranging from countries to local regions and cities. While some regions are more comprehensively represented than others, our database also includes data for underrepresented areas, ensuring broad and diverse geographic coverage.

Types of emission factors

Our data covers 20,000+ activities. We define activities as processes covered by emission factor data. This includes (but is not limited to) activities in energy covering electricity, fuel, cooling, and heat and steam; transport services and warehousing; consumer goods and services such as clothing, food and beverages, furnishings, and health care; materials and manufacturing products such as ceramics and clay, and many others.

The emission factors in the Climatiq database cover a broad range of units to accommodate for the largest selection of measurements possible across activities. This includes area, distance, energy, money, time, volume, and weight units.

The Climatiq database provides both activity-based and spend-based emission factors to ensure comprehensive coverage and applicability across various use cases.

Emission scopes

The database includes direct (scope 1), indirect (scope 2), and value chain (scope 3) data, including upstream and downstream emissions, to offer a fully rounded insight into a company’s footprint. All emission factors in the database will soon be categorized according to their appropriate scope. This facilitates compliance-ready reporting for evolving regulatory requirements such as CBAM.

Data updates & corrections

We release regular updates to our emission factor database, usually on a monthly basis. Each release consists of additions, deletions and updates. These releases are necessary when a source publishes errata, new data quality flags are applied to existing emission factors, or when changes are made to a factor's metadata, for example.

Updates like these often require changes in user applications. Therefore, we use the concept of data versioning, which allows users to choose when to opt-in to such changes, providing greater control over emission factors and data quality used in their calculations.

These updates ensure consistency and reproducibility in emissions calculations and ensure the database remains accurate and up-to-date.

New datasets are documented in our product release notes.  

Data quality

We ensure all our data is compliant with the requirements of the GHG Protocol through:

Vetted data sources: Climatiq uses vetted datasets sourced from leading government agencies and trusted global organizations.
Coverage: Our emission factors span multiple industries, activities, and geographies, ensuring relevance for diverse use cases.
Transparency: All methodologies, data sources, and assumptions are fully documented and accessible to our users, ensuring transparency.
Open data: We provide detailed references for every emission factor, allowing users to trace data back to the source.
Up-to-date data: Our platform continuously integrates updated emission factor datasets, following the latest regulations.
Uncertainty: When provided by the source, Climatiq displays the level of uncertainty associated with each emission factor.
(Coming soon) Scopes: All emission factors in our database are categorized according to their appropriate scope to support scope-specific calculations.

As we only include data from trusted publishers, emission factors from Climatiq’s database can be used for reporting under local and international regulations and standards that require GHG Protocol compliance.

Traceable to source

All data provided by Climatiq is linked back to the original source and enriched with metadata such as validity year, source, CO2e calculation method, region, quality flags and LCA activity. Our goal is to make it as easy as possible to verify the origin of all data in our database.

Quality assurance

Climatiq ensures users are informed about data quality through a robust flagging system that highlights potential issues, such as methodological ambiguities, partial emission factors, or outliers. This approach empowers users to make confident and informed decisions about the emission factors they use, while eliminating the need for them to conduct their own quality assessments. 

Below is an outline of our quality assurance process:

Every new data point undergoes automated validation checks to identify inconsistencies, missing values, zero values, or misalignments with expected ranges.
We use machine learning algorithms to detect outliers and flag unusual values to alert users for data anomalies.
Emission factors for the same activity but sourced from different datasets are compared to ensure consistency and agreement, checking if there are any erroneous values.
We assess the IPCC Assessment Report (AR) calculation methods used by each source in calculating emissions.
We review the life cycle assessment (LCA) boundaries and ensure that the appropriate scope (1, 2, or 3) is applied to the data.
If a source provides only partial information (e.g. only CO2 emissions without other GHGs), we explicitly mark the data as partial to maintain transparency and inform users of its limitations.
After passing automated checks, the data is reviewed by our Science and Data team, which includes PhD-educated scientists and carbon accounting experts.
This manual review ensures that any issues—such as methodological limitations or data gaps—are addressed, adding a further layer of review that automated systems may overlook.
We continuously refine our QA processes based on user feedback, new sources, and changes in regulation standards.

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Our data vetting and ingestion process at a glance:

Uncertainties and data gaps

Our emission factor values typically don’t come with uncertainties because most sources do not report them. While Climatiq covers over 40 sources, only ADEME (the French Agency for Ecological Transition) explicitly provides uncertainty values. We understand that users value this information, but its absence reflects a broader challenge in carbon accounting practices and data reporting across the majority of sources.

Our dedicated Science and Data team works continuously to identify new sources and expand coverage, actively filling data gaps to enhance the database over time.

Public access

The Climatiq Data Explorer provides an easy-to-use interface to browse, review and verify the accuracy and reliability of the data provided.

By offering free access to the database, we also empower businesses across the globe to start assessing their environmental impact with reliable data.

Data schema for emission factors

The Climatiq Emission Factor Database offers a novel solution to the challenge of emission factor standardization. By harmonizing scientifically vetted emission factors into a cohesive schema, we provide a reliable resource that makes it easy to compare emission factors across a variety of sources, sectors, and regions.

Normalization

The process of normalizing emission factors ensures that factors from different datasets and for different regions are comparable, by adjusting or removing variables that could otherwise skew the data.

Key features of our schema and normalization process:

Emission factors are classified by sector, category and region, making it simple to search and compare data across industries, activities, and geographies.
Year information is clearly specified, distinguishing between the year of publication and the year for which the data is applicable, which can sometimes differ.
Activity units are consistent (e.g. kgCO2e per activity unit) to eliminate confusion and variability stemming from differing units across datasets.
We report the IPCC Assessment Report (AR4, AR5, or AR6) calculation method used, as provided by the source, to maintain transparency.
LCA activity and scope are reported to clearly define boundaries and applications.
Descriptions provide detailed context about the data’s origins, assumptions, and methodologies, offering users a deeper understanding of the factors.
Source links ensure traceability, enabling users to easily trace back to the original dataset.
The data quality field allows us to report potential issues, such as partial factors, methodological variances, erroneous calculations, or suspicious outliers, ensuring the user is aware of the quality of each emission factor.
The schema is dynamic and evolves to incorporate new datasets with new methodologies, as well as regulatory updates, ensuring the database remains up-to-date and comprehensive.
We standardize emission factor values by converting all data in the database to kilograms of CO2e for each greenhouse gas (carbon dioxide, methane, and nitrous oxide). This ensures the data accurately reflects the specific impact of each gas and enables precise calculations of CO2e.

Our schema is illustrated in the table below using a 2023 ‘LPG tanker’ emission factor provided by BEIS as an example. The first column lists the individual properties of the Climatiq schema.

Climatiq’s emission calculation methodology

Our plug-and-play API automates complex carbon calculations, and has been used by our customers to power over 1.5 billion CO2 estimates. The API transforms activity data from various use cases such as energy consumption or freight shipments into emissions estimates. It automatically selects the most fitting emission factor using AI, and then applies the necessary calculation logic to work out a CO2e estimate.

Our team of climate scientists generally develops the calculation logic in-house, which is then reviewed and certified by third parties such as the Smart Freight Center to ensure reliability.

To address gaps in our data, our API applies a region fallback logic to identify the most relevant emission factor when data for a specific area is unavailable. Similarly, we use a year fallback logic to account for missing data from specific time periods, ensuring users receive the closest applicable emission factors.

ERP platforms, supply chain management platforms, and ESG solutions can then integrate Climatiq’s API into their own software to provide their customers with emissions estimates across a range of activities.

Energy emission calculations

Our energy API gives access to built-in logic for scope 1 fuel combustion, scope 2 location- and market-based electricity, and upstream scope 3.3 fuel and energy-related activity (FERA) calculations. The energy endpoint automatically calculates the greenhouse gas emissions from the energy consumed by using relevant emission factors. Where emission factors for particular regions are not available, the endpoint uses Climatiq’s advanced calculation methodology to estimate emissions, thus helping reduce gaps in reporting.

Drawing on data from the International Energy Agency (IEA), Association of Issuing Bodies (AIB), Environmental Protection Agency (EPA) and more, users input region, quantity of energy consumed, and year (optional) to receive emission insights.

For more advanced users, Climatiq includes emission factors specific to electricity suppliers in several countries. Users are also able to specify their own supply-specific factors or fuel mix if they have the data available.

The API provides results for location-based and market-based approaches. We offer support for all fuel types and 19 input units, auto-allocation of renewable energy certificates (RECs), and coverage for heat and steam, well-to-tank (WTT), transmission & distribution (T&D), and WTT of T&D. Over 120 global regions are covered, with state or sub-grid coverage across the US, Canada, and Australia.

Freight emission calculations

Climatiq’s freight API has Smart Freight Centre Accreditation, which ensures its calculations align with the GLEC framework.

All emission factors used are from the Global Logistics Emissions Council (GLEC) framework, except for grid electricity factors for powering electric vehicles from the International Energy Agency (IEA). Routing between start and end location is done via OpenStreetMap (rail), HereMaps (road), Eurostat (sea) and Great Circle Distance method (air).

The GLEC Framework follows international standard ISO 14083 and is recognized by major carbon accounting and reporting organisations (GHG Protocol, CDP, SBTi).

The user must supply the weight of cargo and the start and end destination of the shipment or a distance. They may also add multiple journey legs—up to five by default with the option to request more. The API then automatically selects emission factors for the regions, vehicles and load from GLEC. It calculates the distance between the start and end location of the shipment, and finds the logistics hub (port, railway terminal, or airport) that is closest to those locations. In the case that there is no logistics hub within the specified radius, the user must add another leg to account for inland travel. Users may specify region, fuel type, size, or load type to increase precision.

In the case of missing or partial address information, there is resolution logic for addresses, including geocode, partial/full street addresses, ZIP/postal codes, UN-Locodes, or IATA airport codes.

For air travel, a distance uplift is applied to account for maneuvering in accordance with the EN16258 methodology requirements, usually 95km per leg. The estimate is also multiplied by a Radiative Forcing Index of 2 to account for the fact that greenhouse gasses emitted at higher altitudes contribute more to global warming.

Users are supplied with a source trail detailing all emission factors used in the calculation.

Travel emission calculations

The API calculates emissions from air, train, and car (including taxi) travel globally, as well as hotel stays, to cover emissions under scope 3.6: business travel. Spend-based and activity-based approaches are supported. It uses logic developed by Climatiq, taking into account upstream and use-phase emissions.

Air travel

The air travel endpoint calculates flying emissions based on emission factors from the UK Government. The UK Government's datasets are especially well-regarded and widely used around the world; other providers, such as the EPA and GHG Protocol, often publish emission factors sourced from UK datasets rather than calculating their own. The UK Government has a nuanced methodology for calculating air travel emissions that incorporates a multitude of factors such as fuel type, cargo weight, distance traveled, and ground operations.

The endpoint automatically applies a Radiative Forcing Index of 2, which is used to account for the increased environmental impact of fuel burn at high altitudes.

The endpoint factors haul type (domestic, short haul, or long haul), cabin class (optional) and year (optional) into its calculations.

Car journeys

For cars with unspecified or unknown fuel types, the car travel endpoint uses the average factor from the UK Government, except in the USA where the EPA provides a specific average car factor.

Estimations are based on powertrain, car size, and distance traveled. The endpoint considers a range of car types (e.g. diesel, petrol, electric, etc.).

Train journeys

For the UK and US, the endpoint uses the train travel emission factors from the UK Government and EPA respectively, which account for the level of electrification within those countries. For other countries where national factors are not available, the endpoint chooses either diesel or electricity according to the primary energy source used for rail in that country.

Estimates are based on distance and electrification rates of the specified country. The train travel endpoint uses a routing algorithm through rail networks. We do not have full coverage of the global rail network. If data on specific rail segments is missing, we may use car routes for distance calculations.

Hotel accommodation

For hotel stays, the API can use activity- and spend-based data, drawing on the UK Government and EXIOBASE datasets respectively depending on whether calculating by nights stayed or cost of stay in the given region.

In cases where the region of interest is not covered by the UK Government or EXIOBASE, a fallback logic is applied using median values.

Procurement emission (spend-based) calculations

Spend-based emission calculations are a common way to estimate emissions for purchased goods and services (GHG Protocol category 3.1) when detailed activity data is not available. The Environmentally-Extended Input-Output Model EXIOBASE is the most commonly used resource for spend-based emission factors.

The API streamlines the calculation of carbon footprint for purchased goods and services by automatically deriving basic (factory-gate) prices, which are necessary for EXIOBASE calculations.

If the expenditure occurred in a different year than the emission factor's year, the expenditure amount has to be adjusted to match that emission factor's year. This requires taking into account both inflation adjustment and exchange rate fluctuations to arrive at the adjusted spend amount. The procurement endpoint automatically corrects for currency exchange rates and inflation adjustments, using rates from the UN Treasury, the IRS and the World Bank, supplemented with per-industry inflation numbers from Eurostat.

The endpoint provides the flexibility to provide your own margin rates in the API query, or, if unknown, to default to margins derived from EXIOBASE.

For the development of the Procurement endpoint, we collaborated with Prof. Richard Wood, a key developer of EXIOBASE. Prof. Wood is a member of our scientific advisory board.

Autopilot for scope 3.1 emission calculations

Autopilot automatically matches unstructured text from purchase orders, Bills of Materials, or invoices to the closest emission factors using Climatiq’s proprietary NLP model. The user has the option to input descriptive text explaining what was purchased to improve accuracy of matching.

It matches emission factor(s) to text by assessing how similar two strings of text are based on their semantic meaning. We use ranking to assess relevancy. Our models are regularly fine-tuned on real-world data.

The Autopilot API uses emission factor data from the entire Climatiq database (and ecoinvent, if included in the user’s package). All regions are covered. Depending on the emission factor availability, region fallbacks are implemented.

The response includes the CO2e estimate and details about the calculation. The user also receives a confidence score to indicate the reliability of the match.

Autopilot includes a Suggest feature that returns suggested emission factors for a particular calculation. The user can specify the number of suggestions to return. These are then ordered by the most likely match first.

The Estimate feature calculates total estimated emissions produced for an Autopilot-matched activity, in kgCO2e. Estimations can be performed with a suggested activity from the Suggest endpoint, or by using free-text input, which will automatically calculate emissions with the best emission factor match.

Cloud computing emission calculations

The cloud computing endpoint converts cloud CPU and memory usage, storage, and networking traffic to CO2e estimates for Amazon Web Services (AWS), Google Cloud Platform (GCP), and Microsoft Azure.

Data for this endpoint is obtained from the Cloud Carbon Footprint (CCF) website, along with regional electricity emissions data from the Climatiq database. Inputs vary for Virtual Machine instance, CPU, storage, and memory.

It incorporates both use-phase emissions, using regional electricity grid emissions intensity and CCF equipment efficiency assumptions, and embodied emissions from the production and disposal of the hardware.

CBAM emission calculations

The CBAM endpoint covers emissions under scope 3.1: purchased goods and services which are imported into the EU and fall under CBAM regulation. CBAM currently applies to cement, iron and steel, aluminum, fertilizers, electricity, and hydrogen.

To use the endpoint, the user provides a country and a CN code and the API returns the associated direct and indirect emissions taken from the official CBAM data. At present, the tool covers iron and steel, aluminum, cement, and fertilizer (not hydrogen or electricity).

The endpoint also returns the estimated cost of purchasing CBAM certificates equivalent to total emissions.

Audit- and source trails

Audit trails provide detailed information about the emission factors used in calculations for advanced endpoints such as freight shipping, cloud computing, and classification. They can be stored with calculated emissions for future reference and audits.

The audit-ready calculation trail includes applied emission factor, data source, year valid, and more.