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correlation value shows a very strong correlation between PM10 and PM2.5 and SO2 and
CO in winter, representing the accumulation of pollutants in the ambient air due to
meteorological conditions that prevent the dispersion of pollutants. A very strong
correlation to strong correlation between PM10 and PM2.5 in summer represents the
common sources of generation of particulate matter. The time series analysis depicts
that the pollutants' concentration is higher during morning and evening peak hours. It is
higher in evening peak hours compared to morning peak hours. The higher concentration
of particulate matter during morning peak hours may be due to the resuspension of road
dust due to road sweeping. The wind rose diagram depicted that the average wind
velocity ranges from 2.4 m/s to 2.9 m/s in winter, while in summer, it ranges from 3.1 m/s
to 4.6 m/s. So based on that, it is concluded that a wind velocity of more than 11 km/hr,
i.e., 3 m/s helps the dispersion of the pollutants. The higher the wind velocity, the more
the dispersion of pollutants. At all the selected locations, the average ozone
concentration is insignificant in summer compared to winter despite higher solar
radiation. It may be due to higher level maximum mixing depth, i.e., higher boundary layer
in summer, resulting in a low ozone concentration in lower heights. Carbon monoxide
acts as a precursor gas in ozone production. In summer, carbon monoxide concentration
is also less than in winter (Lal et al., 2000). The UV index value is substantially lower at all
selected locations in winter than in summer.

The exceedance factor has also been determined for the collected data. Based on the
analysis, it is found that during monitoring in summer, at all the selected locations, the
average concentration of pollutants are within NAAQS, 2009, i.e., the exceedance factor is
either in the low or moderate pollution category. In winter, the average concentration of
gaseous pollutants, NO2, SO2, CO and O3 are within NAAQS, 2009. In contrast, the
average concentration of particulate matter (PM10 and PM2.5) exceeded the NAAQS,
2009. So, the exceedance factor is either in the high pollution or in the critical pollution
category for particulate matter in winter.

The ambient air quality monitoring data of selected locations are used to calculate the
National Air Quality Index, India (NAQI) and Composite Air Quality Index (CAQI). The air
quality index values obtained by both the indexing systems are compared to see the
variation between these two systems. The comparison evaluates which indexing system
functions better out of the two. Considering monitoring data of all locations in summer,
95.6% of NAQI values and 92.6% of CAQI values are below NAQI and CAQI standards,
respectively. While in winter, 20.3% of NAQI values and 6.3% of CAQI values are below
NAQI and CAQI standards. NAQI and CAQI trend lines follow the same pattern in most of
the locations for both seasons. The comparison between the two indexing systems
shows that the composite air quality index estimates the pollutants exposure to the

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