Diwali Affect: Air Pollution reaches 3 times more than normal day in city

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Air and Noise Pollution in city during Diwali
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Thanks to the Diwali festivity, the city recorded the highest pollution with 3 times more than the normal day on one single day.

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According to the report released by the Telangana State Pollution Control Board (TSPCB) here today, the concentration of the Particulate Matter of size less than 2.5 Microns (PM2.5) increased by three times and that of the Particulate Matter of size less than 10 Microns (PM10) by twice when compared to normal day.

TSPCB is regularly monitoring the Ambient Air Quality(AAQ) with respect to the particulate matter, gases and noise levels in the city and at various places in the state of Telangana as per the directions of the Central Pollution Control Board.

The special-purpose (Diwali) AAQ monitoring has been carried out from October 20 2019, to till date and will be continued up to November 3 2019. Noise level monitoring has also been carried out through 10 real-time noise monitoring stations. As instructed by CPCB the data of the October 26 was taken as pre-Diwali data and that of the October 27 as Diwali data. 

The findings have been furnished hereunder: 

Meteorological parameters:

The transport and the diffusion of the air pollutant depends upon the dynamics of the atmosphere. The wind plays a major role in the transportation and diffusion of the pollutants. The gaseous waste or the smoke is taken away or diluted by the wind. The stronger the wind, greater will be the dilution of pollutant. On the other hand, stable air discourages the dispersion and the diffusion of the pollutants. Hence, Air Pollution data has to be seen in conjunction with the meteorological data.

The average wind speed of Hyderabad, in general, is 2.8mts/sec, however, on 27-10-2019 the wind speed on an average is around 0.5mtrs/sec indicating poor dispersion. During the last year, the wind speed is about 1.6mtrs/sec. The relative humidity is about 75%.

Parameter 2018 2019 Remarks
Normal Diwali Normal Diwali
PM2.5 in ug/m3 Standard 24 hours average – 60 59 95 22 71.6 On Diwali day the concentration of the PM2.5 increased by three times and that of the PM10 by twice when compared to normal day.
PM10 in ug/m3Standard 24 hours average – 100 104 140 85 163.4

The data of the CAAQMS on the Diwali day for the years 2014 to2019 indicates a decreasing trend of PM10 and PM2.5 concentrations in Hyderabad city. 

Average Concentrations of PM10 & PM2.5 in ug/m3 in Hyderabad during Diwali

M2.5 in ug/m3 in Hyderabad during Diwali

The hourly average of the CAAQMS data at the six locations during the evening hours on Diwali day (27th October 2019) from 5 PM (17.00Hrs) onwards indicate gradual increase in concentrations and also higher contribution to PM2.5.

Time in Hrs. HCU Pashamylaram Sanath nagar Zoopark ICRISAT Bollaram
PM2.5 PM10 PM2.5 PM10 PM2.5 PM2.5 PM10 PM2.5 PM10 PM2.5 PM10
17-18  14 30 10 25 20 45 77 15 25 23 62
18-19  11 27 12 22 140 40 50 13 19 35 56
19-20  16 39 15 35 620 74 86 26 30 164 190
20–21 72 91 32 43 310 168 193 49 64 274 310
21- 22 68 96 34 46 1000 163 184 60 78 250 273
22–23 139 179 42 68 830 228 256 68 85 442 541
23–00 141 171 52 70 560 191 217 140 180 333 393
00-01  283 354 44 81 300 72 93 128 171 372 426
01-02 310 395 51 68 170 73 95 76 106 372 418
02-03 318 400 210 60 67 57 97 250 298
03-04 310 386 100 41 62 94 140 133 151
04-05 133 173 80 63 83 99 140 53 70
05-06 49 82 40 47 66 83 146 40 66

The AQI at the CAAQMS at the monitored stations is as follows:

Location Air Quality Index (AQI) 
Bollarum 300
ICRISAT 68
Sanath Nagar 361
Zoopark 113
Pashamylaram 40
HCU 170

Gaseous Parameters:  The gaseous parameters are within the limits though the concentrations have moderately increased.

Parameter 2018 2019
Normal Diwali Normal Diwali
Sulphur dioxide (SO2)in ug/m3 Standard 24 hours average – 80 ug/m3 6.5 7.6 4.0 6.0
Oxides of Nitrogen (NOx)in ug/m3 Standard 24 hours average – 80 ug/m3 35 43.5 46 65

Noise Levels: The Noise levels are being monitored in and around the city at 10 locations through continuous Real-Time Noise monitoring stations that capture data at regular intervals. 

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