Dynamics of particulate matter pollution in urban areas
Particulate matter pollution in urban areas is a key challenge for air quality and public health.
In addition to agriculture and industrial emissions, motor vehicles are also responsible for releasing particulate matter through exhaust emissions, brake wear and tire abrasion.
However, it is not only the volume of traffic, but also meteorological factors such as wind, temperature stratification and precipitation that have a significant influence on particle concentrations.
A key challenge is to record the distribution of particulate matter with high spatial and temporal resolution in order to enable reliable statements to be made with regard to reduction and avoidance.
Real-time data as key to clean air
We combine real-time data acquisition, numerical modelling and artificial intelligence to analyze particulate matter dynamics at different scale levels and derive optimized traffic controls.
Multiscale modeling of particulate matter dynamics
Our goal is the spatially differentiated investigation and modeling of particulate matter pollution in an exemplary urban quarter at the DLR research intersection in the city of Braunschweig.
Special sensors will be installed at a total of 10 points at the intersection. At the same time, test vehicles will be equipped with sensors in collaboration with IAV and Audi. In addition, together with the TU Braunschweig, a tethered balloon will be equipped with sensors to investigate the higher air layers in terms of distribution and propagation.
The values measured are transferred to a central database in real time as high-frequency, horizontally and vertically recorded particulate matter concentrations.
Data-driven AI algorithms and numerical multi-scale simulations are used to analyze the dispersion of the particles and determine their dependence on traffic flow and meteorological parameters.
Based on these findings, we develop adaptive measures to improve air quality, in particular through intelligent traffic flow controls that specifically minimize sources of particulate matter.
1. High-frequency Particulate Matter Measurement
- Use of mobile and stationary sensors for spatially and temporally resolved measurement of particulate matter concentrations
- Combination with vehicle-resolved traffic flow data to identify emission sources
- Consideration of meteorological factors such as wind, temperature stratification, precipitation, etc.
3. Multiscale Simulation of Particulate Matter Dynamics
- Modeling the time-resolved variability of particulate matter concentrations on different spatial scales
- Use of high-resolution numerical flow models for detailed analysis of particulate matter sources
- Prediction of particle movements under different traffic and weather conditions
