Atmosphere (Nov 2022)

Methodology for Virtual Prediction of Vehicle-Related Particle Emissions and Their Influence on Ambient PM<sub>10</sub> in an Urban Environment

  • Toni Feißel,
  • Florian Büchner,
  • Miles Kunze,
  • Jonas Rost,
  • Valentin Ivanov,
  • Klaus Augsburg,
  • David Hesse,
  • Sebastian Gramstat

DOI
https://doi.org/10.3390/atmos13111924
Journal volume & issue
Vol. 13, no. 11
p. 1924

Abstract

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As a result of rising environmental awareness, vehicle-related emissions such as particulate matter are subject to increasing criticism. The air pollution in urban areas is especially linked to health risks. The connection between vehicle-related particle emissions and ambient air quality is highly complex. Therefore, a methodology is presented to evaluate the influence of different vehicle-related sources such as exhaust particles, brake wear and tire and road wear particles (TRWP) on ambient particulate matter (PM). In a first step, particle measurements were conducted based on field trials with an instrumented vehicle to determine the main influence parameters for each emission source. Afterwards, a simplified approach for a qualitative prediction of vehicle-related particle emissions is derived. In a next step, a virtual inner-city scenario is set up. This includes a vehicle simulation environment for predicting the local emission hot spots as well as a computational fluid dynamics model (CFD) to account for particle dispersion in the environment. This methodology allows for the investigation of emissions pathways from the point of generation up to the point of their emission potential.

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