An integrated statistical approach for evaluating the exceedence of criteria pollutants in the ambient air of megacity Delhi
Sharma, P, Sharma, P, Jain, S and Kumar, P (2013) An integrated statistical approach for evaluating the exceedence of criteria pollutants in the ambient air of megacity Delhi Atmospheric Environment, 70. pp. 7-17.
Sharma_Kumar (2013)_Teri DelhiAE.pdf
Available under License : See the attached licence file.
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 – sulphur dioxide (SO2), nitrogen dioxide (NO2), suspended particulate matter (SPM), and particulate matter less 10 micron in size (PM10) – 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.
|Divisions :||Faculty of Engineering and Physical Sciences > Civil and Environmental Engineering|
|Date :||May 2013|
|Identification Number :||10.1016/j.atmosenv.2013.01.004|
|Uncontrolled Keywords :||Probability density function, Distributional models, Ambient air quality data, Air quality standards, Model identification and estimation, Megacity Delhi|
|Related URLs :|
|Additional Information :||NOTICE: this is the author’s version of a work that was accepted for publication in Atmospheric Environment. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Atmospheric Environment, 70(0), May 2013, DOI 10.1016/j.atmosenv.2013.01.004.|
|Depositing User :||Symplectic Elements|
|Date Deposited :||01 Mar 2013 12:19|
|Last Modified :||23 Sep 2013 20:00|
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