RUS Copernicus will provide a full day hands-on training session where participants will access from their own laptop a Virtual Machine to exploit the open source toolboxes available in the RUS environment to download and process Sentinel-5P data.
Please note that the RUS Copernicus Virtual Machines used for this training course can only be provided to citizens/residents of the Copernicus programme member countries (EU plus Iceland and Norway).
Sentinel-5P was launched in October 2017 to screen the Earth’s atmosphere and quantify different pollutants (CO, NO2, SO2, O3, aerosols…) with a great accuracy and spatial resolution. It also provides measurement continuity with precedent and ongoing atmospheric spatial missions (OMI, IASI and SCHIAMACHY). The data recorded by this satellite are free of use and present a great interest to globally monitor air quality, greenhouse gas emissions and detect and assess the impact of polluting events.
This full day hands-on training session will focus on the processing of Sentinel-5P data to monitor NO2 concentration in the atmosphere. The Jupyter notebook environment and the specifically designed Atmospheric Toolbox will be used throughout the workshop. You will learn to monitor both daily pollution and polluting events based on processed Sentinel-5P data.
After a detailed introduction on the Sentinel-5P mission and associated products, you will manipulate Sentinel-5P data to study particular use cases. First you will get familiar with the automatic download of Sentinel data by command line. Then you will learn to compute and map the averaged NO2 concentration over Europe for a two-week time period during Spring 2020. You will see how it compares to the same time period in Spring 2019. This will lead to the quantification of the NO2 pollution drop over Europe resulting from the covid lockdown measures. Finally, we will monitor the NO2 concentration times series over a European city during the lockdown.
Due to the uncertainties related to the coronavirus situation, this hands-on session will be held fully online.
Attendees must be in possession of their own computer with a microphone to follow the online training and will be provided with access to the RUS platform Virtual Machine.
Attendance to the training course is free of charge.
Space is limited to 20 Participants on a first-come first-served basis.