Determination of concepts to reduce the aerosol particle load in public transport using flow simulations and sensor networks (AerÖPNV)

In the corona pandemic, public transport is considered a place with an increased risk of infection. A decrease in the number of passengers would result in the increased use of fossil raw materials due to increased motorized individual traffic, and this would have negative consequences for CO2 emissions and climate change. In the research project “AerÖPNV”, ventilation measures to reduce the aerosol exposure of passengers are to be derived and improved air routing concepts to reduce the aerosol particle concentration are to be proposed. In addition, for the first time, an adaptive and instant reaction to aerosol pollution is made possible by combining measurement technology and flow simulation profitably with data-driven AI-based learning, which should allow intelligent control of the ventilation.


To answer the research questions, the aerosol exposure in buses (Zügel Reisen) as well as intra-urban (Heilbronner Hohenloher Haller Nahverkehr GmbH - HNV) and inter-urban (Albtal-Verkehrs-Gesellschaft mbH - AVG) tram lines are to be illuminated. In detail, the following goals should be achieved for all vehicle types:

  1. Collection of a database of aerosol exposure of passengers in public transport and comparison with measurement data from non-moving interiors (e.g. classrooms), classification of occupancy and operating scenarios and creation of a scenario catalog
  2. Deriving concepts for reducing the aerosol particle concentration in existing vehicles with regard to ventilation settings, window and door ventilation
  3. Development of proposals for improved flow guidance that reduces the aerosol particle concentration at the point of inhalation by people (modernized vehicles)
  4. Intelligent AI-based control of ventilation measures with the aim of reducing the aerosol exposure of passengers based on online measurement data

Work packages:

Duration: 1.12.2021-31.5.2023

Funding: 510.000 €