Cyclists' exposure to air pollution: in situ evaluation with a cargo bike platform.

Cyclists' exposure to air pollutants near roadways has been associated with numerous health effects. While the adverse health effects concerning aerosols have traditionally been assessed with data of particle mass concentrations, it appears that the number concentration is also another important indicator of toxicity. Thus, to holistically evaluate one's exposure to aerosol particles, assessments should be based on mass concentrations and number concentrations.

Modelling of Urban Air Pollutant Concentrations with Artificial Neural Networks Using Novel Input Variables.

Since operating urban air quality stations is not only time consuming but also costly, and because air pollutants can cause serious health problems, this paper presents the hourly prediction of ten air pollutant concentrations (CO, NH, NO, NO, NO, O, PM, PM, PM and PN) in a street canyon in Münster using an artificial neural network (ANN) approach. Special attention was paid to comparing three predictor options representing the traffic volume: we included acoustic sound measurements (sound), the total number of vehicles (traffic), and the hour of the day and the day of the week (time) as input variables and then compared their prediction powers. The models were trained, validated and tested to evaluate their performance.

Assessment of urban green space structures and their quality from a multidimensional perspective.

Facing the growing amount of people living in cities and, at the same time, the need for a compact and sustainable urban development to mitigate urban sprawl, it becomes increasingly important that green spaces in compact cities are designed to meet the various needs within an urban environment. Urban green spaces have a multitude of functions: Maintaining ecological processes and resulting services, e.g.