MPI can be defined as:
where n is the total number of pollutants taken in consideration, ACi is the atmospheric concentration of a pollutant in a certain location and CGi is the guideline concentration of a pollutant recommended by a national or international agency such as the WHO.
A clean environment (in the absence of air pollutants) has an MPI equal to ?1, while for a location with ACi equal to the CGi (i.e. a location with borderline air quality), the MPI would be around 0. No upper limit is given for the MPI, with relatively higher values corresponding to poorer air quality. We refer to Gurjar et al. (2008) for a detailed discussion on this index.
For example, MPI (WHO) Measured pollutants mean values (ppm) are: SO2: 63, CO: 12, NO2: 222 and guideline values are respectively 125, 10 and 200. The calculation is MPI=1/3 (65-125)/125)+(12-10)/10)+ (222-200/200) =-0.19 Negative values are good air-quality range values. So, you can calculate MPI from data in an easy way using R software.
Another example could be to calculate an index as “Index Català de Qualitat de l’Aire“, air quality index of Environmental Protection Agency (USA) in a 0-500 scale for individual pollutants