Air Quality Improvement Based on the Application of Emission Monitoring System with Triangulation

In the context of smart city, there is a very strong need for real-time air quality data using air quality sensor. The aim of the chapter was to evaluate methods of triangulation of air quality data. A statistical smart city model was developed, which provided CO, CO2, NO2, PM, and SO2 emission data based on distribution of emission classes, fuel types, and implementation of renewable technology. Data validation was done using 40 existing measurement devices located in industrial applications in the Žilina Region in the “ATMO-PLAN” software. The results showed that the cubic Triangulated Indirect Network was the most appropriate method in order to capture air quality variations between family houses, apartment complexes, and industrial applications. The recommended resolution for a city of 9 km2 was 20 m × 20 m, with a ratio of 1 device per 8 buildings. Position of sensors at global maxima should be avoided for basic triangulation methods (large data skewness), or rely on more complex triangulation methods (Kringing, Radial Basic Function Interpolation) should be used. In conclusion, the chapter demonstrated a large potential in applying dispersion models taking into account the cities topology and weather conditions.