Central Pollution Body Explains Data Gaps On Diwali Night

The past couple of days have triggered immense conversation and scrutiny around AQI numbers. On Diwali, while the Central Pollution Control Board's (CPCB) Sameer app showed numbers pegged around 400 in the 'severe' category, websites and private applications showed AQI numbers even above 1000. As soon as the numbers came in, netizens compared the figures and criticised government numbers for being opaque in their reporting of AQI. Since the incident, multiple explanations have been issued, educating citizens about the differences in calculation models. 

The CPCB has now broken its silence and issued a clarification on the core mechanics of India's National Air Quality Index (NAQI) framework, its design methodology, and its international alignment.

AQI As Health Monitor

The CPCB emphasises that the index is fundamentally designed as an effective communication tool. The body says, "The Air Quality Index (AQI) is a tool for effective communication of air quality status to people in terms that are easy to understand. AQI is an indicative scale designed to convey likely health implications of prevailing air quality conditions."

How The NAQI Model Works

To understand why official boards sometimes differ from what people feel in real-time, the CPCB explains the foundational mechanics behind how the NAQI is calculated. The body argues that the index takes into account comprehensive health metrics.

CPCB elaborates, "NAQI system takes into account Indian and international health studies, Indian background concentrations and internationally comparable concentration breakpoints."

The body says that instead of tracking raw, second-by-second volatility, the CPCB model is built around cumulative exposure duration as outlined in the National Ambient Air Quality Standards (NAAQS), 2009.

The body clarifies, "The occasional short-lived spikes of pollutant concentrations in ambient air, such as those during the bursting of firecrackers, are episodic and short-lived in nature. The NAQI recognises that prolonged exposure, rather than a momentary reading, is the more relevant indicator of ill effects on human health."

The CPCB clarifies that because the index relies on weighted short-term and long-term averages (such as 24-hour or 8-hour windows), individual health statements take priority over raw digits: "The AQl category along with the associated health statement is more significant than the corresponding AQl value within that category."

Furthermore, explaining how extreme events are handled, the CPCB notes: "During extreme episodes, which are occasional, like Diwali firecracker bursting, this may appear as a data gap at the particular station concerned, and those hours do not contribute to the 24-hour average of relevant pollutant for concerned station."

Why The CPCB Model Caps The Index At 500  

A central point of confusion during severe smog events is why the index stops rising at 500. The CPCB clarifies that this ceiling is an intentional design choice modelled after global standards:

"The upper limit of 500 represents the highest level of health concern. Therefore, an AQl of 500 or above indicates almost the same health risk, i.e. the 'Severe' category - May cause respiratory effects on healthy people and serious health impacts on people with lung diseases."

Explaining further why pushing the numerical scale beyond 500 serves no functional purpose in public health communication, the CPCB states: "Beyond this level, the AQI remains in the 'Severe' category and extrapolation of the index would not alter the assigned health impact category. The capping at 500 is thus a design feature of the index, as has been evolved in the 2015 methodology of NAQI in line with the prevailing international practice, including US EPA AQI."

Why Private Apps Differ In AQI Reporting

Addressing widespread perceptions that global or private apps show higher AQI values during pollution peaks, the CPCB points directly to fundamental differences in sensor technology, data sources, and mathematical methodology.

"Various organisations, global platforms and private entities also disseminate AQI. They draw data from government and non-government sources, including monitoring techniques not prescribed under the NAAQS, 2009, such as low-cost sensors, which have calibration and data quality assurance limitations. Their methodologies may also apply breakpoints different from the NAQI. For example, some platforms derive AQl from instantaneous hourly readings, at times from low-cost sensors and other sources. Such values cannot be directly compared with the NAQI, which is based on 24-hour/8-hour averaged, calibrated and quality-assured data."

Highlighting the time-lag effect in the NAQI model compared to real-time apps, the CPCB adds: "It is generally perceived that private apps show higher AQI. This may hold during short peaks, when hourly values rise sharply. However, when concentrations fall, such apps show lower AQI than the NAQI, since the NAQI continues to reflect the exposure of the preceding 24 hours."

Ultimately, the CPCB rejects accusations of data manipulation: "The difference in AQl values is thus attributable to differences in measurement of pollutant concentration and in methodology, and not to under-reporting."

Talking about its mechanisms, the CPCB says that it increased the network of Continuous Ambient Air Quality Monitoring Stations (CAAQMS) in the country from 30 in 2014-15 to 634, including 10 in Delhi in 2014-15 to 59.