Brussels / 1 & 2 February 2020


emissions API

a service to easily access air quality data from remote sensing

The European Space Agency’s Sentinel-5P satellite is built to monitor air quality data (carbon hydroxide, sulfur monoxide, ozone, …). All data gathered are publicly available …if you know what to do with those data sets, great, but if not:

Emissions API’s mission is to provide easy access to this data without the need of being an expert in satellite data analysis and without having to process terabytes of data.

This way, we hope to empower others to easily build apps that use this data – e.g. visually showing emissions of countries over time.

Achievements of climate goals are so far only verifiable for a very small group of people with specialized know-how. As a result, public discussion remains abstract and elusive for many people. Easy access to emissions data provides a more general audience with the opportunity to form a fact-based opinion. For example, one could evaluate the effectiveness of environmental regulations – such as diesel driving bans in inner cities or new sulfur limits in shipping–by comparing actual measurements from before and after on a map.

Emissions API is a solution that provides simple access to emissions data of climate-relevant gases. For this purpose, data of the European Space Agency’s Sentinel-5P earth observation satellite will be prepared in such a way that it allows programmers easy access without the need to have a scientific background in the field.

The project strives to create an application interface which lowers the barrier to use the data for visualization and/or analysis. Tackling the problem

The project’s core is an API, which can be used to query the processed data. For this purpose, we develop a cloud service which queries the freely accessible data of Sentinel-5P, aggregates it, stores it in a cache and makes it available. Target audience

This project targets developers who want to build their own services based on the satellite data of the Copernicus program, but who do not want to work with huge amounts of scientific data directly. We will provide examples and libraries to quickly get you started without being an expert in satellite data analysis.


Timo Nogueira Brockmeyer