Assessing the Impact of Driving Bans with Data Analysis

Abstract

Suspended particulate matter (SPM) is a significant problem discussed in current environmental research with an impact on the every-day life of many people. Our goal for the BTW 2019 Data Science Challenge (DSC) is to leverage information from available sensor data about SPM and assess the benefits and disadvantages of driving bans. Our application builds upon data of 57 sensors in the city of Dresden and 338 sensors in the city of Stuttgart. Each sensor tracks particle concentration, temperature, and humidity. Stuttgart has a particular interesting situation because of the driving ban for outdated diesel engines on roads in the inner city introduced in January 2019. This gives us the possibility to compare the effectiveness of driving bans not only over time but also between two cities. While we only analyze two cities exemplary in this report, we see high potential of applying our tools to other cities and scenarios. We think, this universality of our approach is an important factor in knowledge transfer. The applications are not limited to SPM analyses but can be extended for example to weather and climate research.