Knowledge-Based Generation of Plausible Air Quality Maps in the Absence of Sensor Data

Abstract

Industrialization increased air pollution sources, which is a cause of major health problems. As such, air pollution became a growing concern and there is a need to monitor and easily visualize air pollution data. There are thousands of air quality monitoring stations throughout the world that are used to measure air quality. Moreover, there are plenty of applications that have been developed to visualize air pollution that use information gathered by these air quality monitoring stations as well as other sources of information, such as traffic intensity or weather forecasts. This paper introduces a novel graphical tool that taps on a new source of information: expert knowledge of air pollution sources. This tool allows experts to represent air pollution sources and their dynamics, and to assign them to different map elements. The authors have performed tool's usability and viability tests with 30 participants of which 6 are environmental experts. The obtained results and the provided feedback show that the proposed approach is a promising complement to sensor-based mapping approaches.