**3. Results and discussion**

This part of the chapter scrutinize the diversity in mean centralization of PM of size 1 micron, 2.5 micron and 10 micron generally perceived as PM 1.0, PM2.5 and PM10, over DEL and GW. The provocation of meteorology on PM and its relationship to TC and RC related to COVID-19 also covered here.

#### **3.1 Dissemination of PM**

The noteworthy distinction is clearly appearing for fine (PM1.0, PM 2.5) and coarse (PM10) over DEL and GW in box and whiskers charts view.

The dissimilar dispersal is clearly visible from the distribution pattern of PM concentration (PM1.0, PM2.5 and PM10) in above two sites during the period 1st January 2020 to 15th May 2020 (**Figure 2**). The concentrations are expressed in μg.m−3 for PM1.0, PM2.5 and PM10.

The low mean convergence of PM (PM1.0, PM2.5 and PM10) over the site GW pronounce the better air quality as contrast with DEL. The entirety of the spans of PM were displayed divergent focus that shows the different wellsprings of contaminations over both of areas for example DEL and GW. The higher mean fixation and conspicuous trait of PM2.5 and PM10 showed in Box plot (**Figure 3**), propose street traffic [20] just as ventures, power plants and homegrown discharge.

In pattern investigation (**Figure 3a** and **b**) during first January 2020 to fifteenth May 2020, PM10 display a higher mean convergence of 127.61 μg-m−3 (DEL) and 57.53 μg-m−3 (GW) though PM1.0 and PM2.5, delineate the mean grouping of 69.22 μg-m−3 (DEL), 34.20 μg-m−3 (GW) and 111.75 μg-m−3(DEL) and 53.10 μg-m−3 (GW), separately.

The higher PM concentration during this period, obviously recommends the effect of vehicular emanation, modern outflow, and different types of burning cycle as the significant wellsprings of toxins. After execution of comprehensive lockdown through restricting various activities and operations related to social assembly, travel, industries operations and transport, started from 23rd March 2020, PM mass concentration in DEL (**Figure 3a**) and GW (**Figure 3b**) were significantly

#### **Figure 2.**

*Boxplots of daily concentrations of analyzed pollutants over Delhi and Gurgaon; the median is shown by the middle line of the box.*

*Consequence of Meteorological Parameters on the Transmission of Covid-19 DOI: http://dx.doi.org/10.5772/intechopen.98978*

**Figure 3.** *(a, b). Trend analysis showing the effect of lockdown period on particulate matter in Delhi (a) and Gurgaon (b).*

declined. The significant decline in the concentration of PM, clearly confirms the influence of the transport and traffic movement in the air quality of DEL. The tremendous decline of 48.21%, 51.82% and 52.45% in PM1.0 (21.90 μg-m−3), PM2.5 (32.19 μg-m−3) and (34.52 μg-m−3) were witnessed the impact of lockdown over GW.

Because of discontinue of all kind of developments, mechanical emanation and transportation out and about, the fine (PM1.0 and PM2.5) and coarse (PM 10) particulate were essentially diminished over both of the areas (DEL and GW) and drew closer inside the restriction of NAAQS (PM2.5 = 60 μg-m−3, PM10 = 100 μg-m−3, in view of 24-hours normal [2] exhibiting the perceptible improvement in air quality. The huge abatement in climatic contamination credited to transportation and mechanical outflows over Beijing, Shanghai, Guangzhou, and Wuhan urban communities were likewise seen during the crown pandemic.

### **3.2 Effect of meteorology on PM**

The past examinations exhibited the impact of meteorological factors, which influence the air quality [21, 22]. The complete example of the improvement of discretionary pollutions has the phenomenal relationship with the toxic substance release rate into the air all along, wind speed, unevenness level, air temperature, and precipitation [23]. Generally, T (°C) has a substantial involvement in air quality of the province therefore correlation analysis by considering the period of 1st March 2020 - 15th May 2020 between PM concentrations and T (°C) for the site DEL (**Figure 4**) and GW (**Figure 5**) were studied to understand the role of T (°C).

The results shows a significant negative correlation between T (°C) and PM1.0 (0.72), PM2. (0.73) and PM10 (0.73) in DEL while over GW, it is as 0.54 (PM1.0), 0.58 (PM2.5) and 0.25 (PM10). In the related **Figures 4** and **5**, the red, green and black dots indicate the data corresponding to PM1.0, PM2.5 and PM10, respectively.

**Figure 4.** *Scatter plot among PM1.0, PM2.5 and PM10 and T (°C) over DEL.*

**Figure 5.** *Scatter plot among PM1.0, PM2.5 and PM10 and T (°C) over GW.*

Here the regression analysis reveals significant negative correlation (r) of T (°C) with PM in DEL whereas GW has the low negative correlation of 0.25 with PM10. The total time of insight demonstrates the declining qualities of PM fixations on the increment of the T (°C).
