Raw ESG data of 10,000+ listed companies in Europe, including scope 1, 2 & 3

# Introduction

This carbon emissions dataset provides an overview of the scope 1, 2, and 3 emissions of publicly listed companies in Europe. Oxari ensures full data coverage across all three scopes by leveraging AI to model emission profiles of companies that partly report or lack reporting at all. Our AI based methodology incorporates various factors to precisely model emission data. These factors include for example industry specifics, balance sheet data and financial statements.

# Our approach

Unlike traditional approaches that rely solely on directly reported data and pre-existing databases, we leverage the latest developments in AI and machine learning to model corporate carbon emissions when reporting is lacking. More information about our model can be found in the linked documentation. Following this approach we provide access to reported and modeled emission data for over 10,000 companies.

# Use cases

- **Historic emissions modeling:** With our in house developed AI models we calculated historic emissions of individual companies and portfolios.
- **Dataset completion:** Our AI models enable you to fill gaps in emission datasets effortlessly. For example, if scope 3 is missing, we model the expected scope 3 value and include it in the data ensuring 100% data coverage.
- **Carbon footprint assessment:** With our data you can assess the environmental impact of any investment portfolio by quantifying carbon emissions associated with each holding.
- **Identify environmental leaders and laggards:** Oxari facilitates informed decision making, since you can identify the frontrunners and laggards in emission reduction efforts.
- **Decoupling evaluation:** You can evaluate the decoupling scale of companies by analyzing their economic growth pathway and compare it to their climate impact and emissions.

# AI pipeline

Our AI pipeline consists of five steps, starting with data collection and cleaning all the to emission modeling. The process is as follows:

1. **Data collection:** Oxari gathers granular emission data from trusted sources, such as the OECD and company reports.
2. **Data cleaning:** We validate the collected datapoints both manually and automatically to ensure data integrity.
3. **Categorize scope data:** A cleaned emission dataset is categorized into variables, such as scope 1, 2, and 3. Collected financial data, such as income statements and industry specific data is categorized and added to the datasets.
4. **AI modeling and training:** Oxari developed multiple AI models that identify distinct patterns in the datasets. We use these academically validated models to compute missing carbon emissions and ensure full data coverage.
5. **Result:** Our AI models compute missing emissions associated with a specific company, based on the company's unique profile. This output is derived from a weighted average of variables in our models, tailored towards the unique characteristics of a company, such as the sector and industry.

# Other

Our dataset supports sustainability disclosures, ESG reporting, and regulatory compliance initiatives. Hedge funds, venture capital, banks, impact consultants, and insurance companies leverage our data to evaluate investment opportunities and identify potential growth prospects across various industries.

Included are direct emissions (Scope 1), indirect emissions (Scope 2), and upstream and downstream emissions (Scope 3).

搜集汇总

背景与挑战

背景概述

该数据集涵盖欧洲10,000余家上市公司的范围1/2/3碳排放原始数据，通过AI建模技术填补未报告或部分报告企业的排放数据缺口，支持碳足迹评估、ESG披露及投资组合分析等应用场景。