Disclosures ESG and Emissions Data Feed

The ESG Book Disclosures Data Feed grants access to a broad range of granular sustainability data, empowering clients to execute a comprehensive analysis of a company/portfolio's sustainability performance, risks, and opportunities. Our standardised and derived data points are able to directly plug and play into internal dashboards for reporting and monitoring use cases.

The Disclosures Data Feed brings together ESG Book's Sustainability Framework and Emissions Plus Framework together to form a single library of datapoints that allows users to deep dive into different themes around the company's sustainability reporting.

The Sustainability Framework covers three thematic areas, including both binary and quantitative metrics across the Environment, Social, and Governance domains.

1. Environment - Including data on Air Quality, Carbon Pricing, Water Withdrawal, Energy Efficiency, Supplier Environmental Criteria, and Environmental Investments.
2. Social – Including data on Community Grievance Mechanisms, CEO Salary, Gender Pay Gap, Diversity Training, Employee Turnover, Human Rights Monitoring, Injury Rate, Product Withdrawal, Low-Priced Products, Customer Data Protection, and Employee Career Development.
3. Governance - Including data on Board Size, ESG Materiality Assessment, Director Remuneration, Codes of Conduct, Corporate Culture Disclosure, Anti-Bribery/Corruption Training, and Tax-Related Lawsuits.

The Emissions Plus framework provides investors with historical emissions data for corporate entities. The dataset includes Scope 1, Scope 2 (location and market-based), Scope 3 total, the 15 Scope 3 categories, and the Kyoto gases emissions, providing a comprehensive picture of GHG emissions by companies and the climate impact of their full operations and value chains.

The disclosures data is diligently collected by subject matter experts and undergoes thorough data integrity checks. All metrics can be linked back to publicly available sources, including company websites, annual reports, sustainability reports, proxy filings, 10K reports, policy statements, and assurance statements.

Data for each indicator is collected from the aforementioned data sources through a set of Standard Operating Procedures (SOPs). These SOPs define each indicator in detail, direct the analyst to all relevant data sources, and instruct them on the acceptability and unacceptability of information as evidence for each indicator.

The SOPs have been developed with the objective to facilitate consistency and error minimisation when capturing ESG information.

In our Emissions Plus Framework, publicly disclosed emissions data are collected according to the GHG Protocol, and emissions that are not reported in line with the GHG Protocol will not be collected. In particular, Scope 1 and Scope 2 emissions that are reported as a sum rather than disclosed separately will not be collected as the GHG Protocol requires emissions to be reported separately, and in units of tCO2e.

The GHG Protocol defines 15 distinct reporting categories in scope 3. These categories have been designed in order to provide companies with a systematic categorisation system to measure, manage, and reduce emissions across the corporate value chain. More information on the GHG Protocol can be found here.

Where possible, assured data is collected preferentially during the data collection process. Where the company does not provide their assurance statement or state that their emissions data is assured, this data is collected if the data is in line with the GHG Protocol.

After data collection, all data goes through a series of data validation tests to ensure data accuracy. Our technical validation tests look at 8 dimensions of data quality: Completeness, Conformity, Validity, Accuracy, Consistency, Uniqueness, Reasonableness, and Timelines. Our technical validation tests are run on the entire dataset of collected data with the aim to identify any inconsistencies in the data. Examples of the technical validation tests include:

• Input error tests - Checking if the input field has been correctly filled (e.g., checking that the analyst has recorded the correct year).
• Inconsistency tests - Checking if the data is consistent in consecutive years (e.g., checking that data present in one year is also present in the subsequent year).
• Related questions tests - Checking the input for two metrics is reasonable and/or expected based on the established relationship between the two metrics (e.g., if GHG emissions data disclosure is NULL, the quantitative GHG emissions metric should also be NULL).

Companies with identified errors will be flagged for further manual comprehensive data integrity validation by our ESG analysts.

ESG Book's Disclosures Data Feed allows users to run comparison for quantitative metrics across the collection universe. All disclosures are standardised according to SI Units calculations [for measurable metrics], USD Thousands [for monetary metrics] and In Tonnes CO2 Equivalent [for Kyoto Gases]. The standardised output types are available to view here.

The Disclosure Data Feed also includes certain derived metrics that have been calculated using a mix of sustainability / emissions metrics and financial metrics. There are 3 distinct types of derived metrics:

• Compounded Annual Growth Rates (CAGR) over the time period of 5 years, 3 years and 1 year.
• Percentage metrics such as ' Renewable Energy (%) of Total Energy Consumption'.
• Ratio metrics for intensity-based metrics such as 'Scope 1 Intensity (Revenue Based)'.

Pricing is determined on a use-case basis, thus please contact for more information.

When requesting please include the following information:

• Organization Name
• Position (non-mandatory)
• Business Email Address or Telephone Number
• Country
• Use-case

This product is allowed for internal use only, users are not allowed to distribute the data externally.

If you're interested in a re-distribution of data use case, please contact us.

• If you have questions about our products, contact us at support@esgbook.com 

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