By Nivedita Khandekar
New Delhi, Nov 26 (SocialNews.XYZ) There is a Decision Support System (DSS) offered by the Indian Institute of Tropical Meteorology (IITM) that offers advisories to not just help zero in on exact sources contributing to Delhi's pollution but also predict practical scenarios in winters.
The DSS was devised by the scientists at the IITM exclusively for Delhi NCR and has been regularly dishing out forecasts and possible scenarios that -- if heeded to -- can help restrict pollution levels.
However, the manner in which things have unfolded in the last few days, it is not clear whether or not the Commission for Air Quality Management in Delhi and Surrounding Areas (CAQM) is using inputs from the DSS.
In fact, on Wednesday, the Supreme Court slammed the Centre and the Delhi government in a case about air pollution exactly about such a thing. Expressing concern about the critical levels of air pollution in Delhi, a Supreme Court bench headed by Chief Justice N.V. Ramana and comprising Justices D.Y. Chandrachud and Surya Kant, on Wednesday had emphasized that the authorities should anticipate that the air quality will deteriorate in the future and then develop measures accordingly. The judges suggested that the statistical models should be examined to identify the major factors for air pollution and then act on them.
In fact, the DSS is a better model than the statistical model that the judges suggested. It started with the IITM providing an Air Quality Early Warning System (AQEWS) to alert the citizens and the policymakers about the possible severe air-quality events about 7-10 days in advance from 2018-19.
After the CAQM was formed, in February 2021, it had approached IITM, India Meteorological Department (IMD), IIT Delhi, C-DAC and The Energy and Resources Institute (TERI) with its requirement of more precise information on the potential sources responsible for the degraded air quality when a forecast for severe air-quality is made as that would help the Commission monitor and control such emission sources.
That was how the AQEWS was extended to the 'Decision Support System' (DSS) for air-quality management in Delhi'.
"DSS is based on the state-of-the-science online chemistry transport model 'Weather Research and Forecasting with Chemistry' (WRF-Chem), which utilizes the anthropogenic emissions inventory prepared by 'The Energy and Resources Institute' (TERI) for Delhi and the surrounding 19 districts," IITM's Project Lead, Wifex/AQEWS, Dr Sachin Ghude told IANS.
Ghude and his colleague Dr Gaurav Govardhan led the team that prepared the DSS within six months after that February meeting. This system provides quantitative information about the contribution of emissions from Delhi and the surrounding 19 districts to the air quality in Delhi; the contribution of emissions from eight different emission sectors in Delhi to the air quality Delhi; the contribution from biomass-burning activities in the neighbouring states to the degradation of air quality in Delhi, and the effects of possible emission source-level interventions on the forecast severe air-quality event in Delhi.
Since 2018, the Central Pollution Control Board (CPCB) has been taking decisions vis-A-vis action to be taken, e.g., halt construction activity or stop vehicular movement, etc., based on the three-day or 10-day AQEWS forecast. This year, with this WEF-Chem model, IITM went a step further to first zero in on exact sources of pollution -- Industrial sources, traffic sources, residential fuel burning, road dust, etc., -- and then, giving a scientific basis to decide which source to control on top priority, which on secondary priority.
"In fact, our input was sought even 10 days ago when the CAQM held the crucial meeting on November 16," Ghude said.
On Wednesday, when the Supreme Court reprimanded the Centre, the Solicitor General asked for time, when the next date of hearing was announced as November 29.
Despite repeated calls and text messages, there was no response from the officials from CAQM and MoEF&CC to queries sent by IANS.
Source: IANS
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