No abstract

This study assessed the concentrations of airborne heavy metals (HMs) in particulate matter with a cutoff size of 10 µm (i.e., PM) in an industrialized urban area (Naraina Industrial Area) of New Delhi, India. The samples were collected from January to December, 2011. The annual mean concentrations of selected HMs were as follows As (0.002 ± 0.002), Cd (0.030 ± 0.020), Co (0.003 ± 0.002), Cr (0.170 ± 0.081), Cu (0.183 ± 0.120), Fe (4.774 ± 1.889), Mn (0.258 ± 0.145), Ni (0.170 ± 0.146), Pb (0.345 ± 0.207) and Zn (1.806 ± 1.042) µg/m. The seasonal trend for HMs followed the order postmonsoon > winter > premonsoon > monsoon. Principal component analysis-multiple linear regression (PCA-MLR) suggested the three major emission sources: industrial emission (70 %), mobile and stationary combustion sources (16 %), and suspended/re-suspended dust (14 %). Mean seasonal concentrations of PM exceeded both the 24-hour and annual Indian National Ambient Air Quality Standards (NAAQS) of 60 and 100 µg/m, respectively, in all four seasons. Mean seasonal Ni concentrations in Delhi ambient air also exceeded the 24-h annual NAAQS of 0.020 µg/m during all four seasons. Mean Pb concentrations exceeded the annual NAAQS of 0.50 µg/m only during the post monsoon season. The high levels of Ni- and Pb-contaminated PM would appear to present the possibility of significant health risks.

Air quality index (AQI) also known as air pollution index (API) is the way of describing ambient air quality to assess the health risk associated with pollution. With the advent of time, there have been several air quality indexing systems starting from the first air Quality Index developed in 1966 by Marvin H. Green and various modifications have been made ever since to improve the accuracy of measurement. Such systems can assess the air quality by several factors like the concentration of different pollutants or by various empirically established formulas based on past experiences. In this review article, an effort has been made to chronologically evaluate the AQI system developed across the world from 1966 to 2021. Every indexing system has its own unique method for air quality determination and each method has its own merits and demerits. This pape rcovers various parameters, empirical relationships, standards, merits, and demerits, which in hind sight will help to develop an amalgamation of various indexing systems that can be used as a standard method for monitoring the quality of air. This paper also covers the AQI systems that prevail in India. A fuzzy logic system is very helpful in handling the uncertainty in air quality assessment. So, fuzzy-based air quality indexing systems developed from 2010 to 2017 have also been reviewed. The review of articles established that the results obtained through fuzzybased AQI aremore reliable than the other methods. Out of all the above describing methods, fuzzy synthetic evaluation-based AQI system and fuzzy air quality health index (FAQHI) are more powerful tools to describe the air quality. But till 2017, thereis no development of AQI systems based on fuzzy logic, considering PM2.5 as one of the pollutants. So, there is a need to develop the fuzzy-based AQI system considering PM2.5 as a pollutant with other air pollutants.