Estimating background particulate matter concentration in Indian cities through statistical methods

Chelani, A. B.

In India, ambient air quality monitoring is being carried out only for the sites with industrial, commercial, and residential land-use characteristics. The background concentration is not being measured, and the background monitoring stations have not been set up in any of the Indian cities. The background PM2.5 concentration in 9 Indian cities, namely, Delhi, Lucknow, Kanpur, Kolkata, Jaipur, Mumbai, Chennai, Nagpur, and Chandrapur, with different geological features is therefore estimated through several statistical techniques such as arithmetic mean and standard deviation, iterated 2 sigma, geometric mean and standard deviation, low pollution sector and condition, accumulative frequency analysis, and upper confidence limit. The estimated background concentration is evaluated by comparing with the confinement period during lockdown imposed due to COVID19 and also by comparing with the observed PM(2.5 )concentration at one of the background stations in Kolkata. The precision of the techniques in estimating the background concentration is also evaluated. The seasonal analysis of estimated background concentration revealed higher background PM2.5 concentration than the regulatory limit in winter and post-monsoon. Further, Indian cities showed much higher background concentration as compared to the locations in other countries. The particulate matter levels in India are therefore proposed to be compared with the other countries only after removing the background concentration from the measured data. The aspect of inherent geological dust in Indian cities needs to be considered in such comparison studies. While formulating the standard threshold limits by regulatory agencies, the presence of high background concentration also needs to be considered.