Response to discussion on: "An integrated statistical approach for evaluating the exceedance of criteria pollutants in the ambient air of megacity Delhi", Atmospheric Environment

Pragati Sharma, Prateek Sharma, Jain S, Kumar P
Atmospheric Environment, Vol. 71, pp.413-414

Like many countries, the Central Pollution Control Board (CPCB), Delhi, in India evaluates exceedences of air pollution levels against the National Ambient Air Quality Standards (NAAQS). One of the mandatory requirements for NAAQS compliance is that the probability of non-exceedence should be at least 0.98, meaning that the formulated framework of NAAQS is essentially statistical. The current practice for assessing the compliance criterion is based on simple computation of the count of number of exceedences in a given year, without giving any consideration to the distribution function followed by different pollutants in the ambient air. This becomes even more important for monitoring stations where continuous monitoring is not done for all 365 days, but assessment is based on a minimum sample of 104 readings recorded in a year. The proper method for evaluating the compliance is the foreknowledge of the population distribution and computation of non-exceedence (or exceedence) probability of NAAQS from the probability density function (pdf). The study proposes an integrated and scientifically robust methodology that is generic in nature and could well be used for assessing the air quality compliance criteria laid out by the NAAQS for India, besides suggesting percent reduction in source emissions to those pollutants that exceed the NAAQS. The usefulness of proposed methodology is exhibited by a case study conducted on four criteria air pollutants e sulphur dioxide (SO2), nitrogen dioxide (NO2), suspended particulate matter (SPM), and particulate matter less 10 micron in size (PM10) e monitored in the ambient air of megacity Delhi at six monitoring stations. The collected data at all these sites underwent statistical analysis for the: (i) identification and estimation of the best-fit distributions, (ii) computation of probability of exceedence of the NAAQS for the non-complying pollutants, (iii) determination of return period of NAAQS violation, and (iv) estimation of percentage source emission reduction to meet the NAAQS criteria for the non-complying pollutants using the statistical rollback theory. It was concluded that the knowledge of pdf is a basic and essential requirement for realistically evaluating the compliance of NAAQS.

Ambient air quality
Probability density function
Mega cities
Distributional models
National Ambient Air Quality Standards (NAAQS)
Air pollution
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