Hindustan Times (Jalandhar)

Prediction in advance: Delhi to get pollution warning system this month

System to draw data from 36 monitoring stations, help enforce graded response system

- Joydeep Thakur joydeep.thakur@htlive.com

NEWDELHI: Delhi is expected to be better equipped to tackle sudden pollution spikes this winter, with an ‘early warning system’ that can predict air quality levels at least two days in advance, according to senior government officials familiar with the developmen­t.

This system, which will be in place by the end of the month, will draw data from 36 monitoring stations run by the Central Pollution Control Board (CPCB), Delhi Pollution Control Committee (DPCC) and Safar, and will factor in real-time aerosol informatio­n from Nasa satellites, giving a prediction taking meteorolog­ical factors into account, the officials added.

This will not only help residents brace for high-pollution days, it will also enable the Graded Response Action Plan (Grap) that kicked in last year to be implemente­d in advance.

“Delhi’s early warning system for predicting air pollution levels is almost ready. We have been working on it for the past eight to nine months. The system would be installed by the end of October or the first week of November,” M Rajeevan, secretary of the Union ministry of earth sciences, told HT. As of now, Safar, which is operated by the government, collates data from 11 stations it runs in Delhi, and the prediction mechanism it employs is not enough to give an accurate forecast of what is coming because it focuses more on local emission sources. Explaining how the new system will work, Sachin C Ghude, a scientist with the Indian Institute of Tropical Meteorolog­y-Pune who is associated with the project, said it will give Delhi the most accurate pollution informatio­n it has got so far.

“Satellites will pick up realtime sources of pollution, such as stubble burning in northwest India or dust storms in west Asia,” said Ghude.

“These would be fed into the model along with daily meteorolog­ical data and data from air quality monitoring stations in the national capital. With these, the model would be able to tell us how pollution levels in Delhi would shoot up in the next 48 hours and what would be the contributi­on of each source,” he added.

Experts said the system becomes all the more important as meteorolog­ical factors, such as wind speed and wind direction, play an important role in determinin­g Delhi’s pollution levels. Also, at least 64% of the ultra fine particles (PM2.5) in Delhi’s air come from outside the city during winters, according to a study by The Energy Resources Institute. These pollutants also come from NCR towns, and sometimes even from as far as Pakistan, Afghanista­n and Oman.

“Such a system would help Delhi be better prepared when it comes to implementi­ng measures under the Graded Response Action Plan (Grap). As of now, Grap measures come into play when pollution level has already spiked. But if we get to know in advance that pollution levels could spike after two days, we can implement some measures in advance to prevent the spike,” said Anumita Roy Chowdhury, executive director (research and advocacy) of Centre for Science and Environmen­t.

Supreme Court-appointed body Environmen­t Pollution (Prevention and Control) Authority, which enforces Grap during the winter, has been pushing for such a system over the past one year. Last November, when dust from Sahara pushed up pollution levels resulting in a week-long smog and the city’s air quality index shot up to a peak of 486 on November 9, the authoritie­s were caught unawares and had to scramble to bring in emergency measures. But by the time the authoritie­s planned to introduce the odd-even road rationing scheme and other such restrictio­ns listed under Grap, the smog had already dispersed. Things got so bad that the city declared a public health emergency.

“If we get to know the sources that could lead to a spike in pollution levels after a gap of two days, it would give us a buffer time to take actions on the ground.

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