Air pollution is the world’s deadliest environmental risk factor. Yet there is little effort to educate the public about personal exposure to pollutants such as Particulate Matter (PM). This thesis presents an approach to calibrate low-cost sensors and combine them into a Portable Sensor Box (PSB) to collect local, spatially highly resolved particulate matter data. We counteract common inaccuracies in mobile particulate matter measurements by aggregating and cleaning all collected data according to their location. The result is robust, reliable data to simulate particulate matter exposure along an independently monitored test track in Potsdam.
We use parameter mapping sonification for intuitive, nonetheless scientific communication of the collected data. The sonification, i.e., the transformation of data to non-speech sound, is made accessible to listeners within a test area using an independently developed sonification device. The implementation of a simulated, scripted exposure design allows us to make realistic, comparable statements about the use of the sonification device and the evaluation of the sonification. The study design allows for real-world investigation without having to move to uniform yet unrealistic laboratory settings.
The 21 participants in the simulated scripted exposure study predominantly rated our sonification design as informative and comprehensible in terms of content. Thus, the sonification design enables an intuitive understanding of the data by non-experts even without a longer training period. However, it is questionable to what extent visual or olfactory environmental factors influence the listeners in their assessment of the sonification. The results of our study indicate that in places with particularly strong expectations of the sonified data (e.g., in a park or along a busy street), the perception of the sonification is biased.