Exploring the self similar properties for monitoring of air quality information

Air quality information has assumed much importance over the years due to the increase in air pollution. One major hindrance in monitoring of air pollutants is the dearth of spatial availability of aerosol concentration measurements due to the cost involved in deployment of sensors. In this respect, self similarity analysis of data can be very useful. This work is based on standard grid based pollutant dispersion models in a simulated environment over different scales of grid size. The fractal dimension is considered as a scale invariant metric which gives an idea about the variation in pollutant concentration across different scales. A method is detailed for measuring the fractal dimension properties. Results indicate that it is possible to apply the dispersion models across different scales and also the air quality monitored in one region can be compared with other regions.