Key Messages

Stationary air-quality monitors do not capture spatial variations in air-pollution. Mobilemonitoring or "sensors on a mobile platform", is an increasingly popular approach to measure high-resolution pollution data at the street level. Coupled with location data, spatial visualisation of air-quality parameters helps detect localized areas of high air-pollution, also called hotspots. In this approach, portable sensors are mounted on a vehicle and driven on predetermined routes to collect high frequency data (1 Hz). Analysing this data involves cleaning and combining location data with pollutant data from different instruments. Some instruments are sensitive to factors like signal attenuation, humidity and vibrations; and require additional correction algorithms that are unique to each instrument. A typical mobile-monitoring campaign involves collecting millions of data points and a high burden of quality assurance and quality control. Our package attempts to automate and simplify the process using a Shiny app.


(*Adithi R. Upadhya, Pratyush Agrawal, and Meenakshi Kushwaha are other authors of this paper.)

mmaqshiny v1.0: R-Shiny package to explore Air-Quality Mobile-Monitoring data