New Delhi, Nov. 5 -- Delhi's official air quality index (AQI) dropped from 366 to 309 between November 2 and 3, but a detailed examination of Central Pollution Control Board (CPCB) data raises questions about whether the readings accurately captured pollution levels during one of the city's most toxic weeks of the year. An HT analysis of monitoring data reveals missing readings, suspicious measurement patterns, and algorithmic loopholes in how the city's average AQI is calculated - all of which may have contributed to an overly favourable picture of Delhi's air quality. The analysis of 168 hours of data from October 28 to November 4 found that missing station data was not random. The AQI is calculated through a multi-step process. At each of Delhi's 39 air quality monitoring stations, 24-hour average concentrations of six pollutants - and 8-hour averages for carbon monoxide and ozone - are converted into sub-indices. The highest sub-index among these eight pollutants becomes that station's AQI, and the average AQI across all stations becomes the city's official figure. However, the system allows three significant relaxations that can affect accuracy: One: The citywide AQI can be calculated without including data from all 39 stations. Two: Only 16 out of 24 hourly readings are required to calculate a pollutant's sub-index. Three: A sub-index need not be available for all eight pollutants - data from just three, including at least one of PM2.5 or PM10, is enough to compute a station's AQI. These relaxations were designed to ensure that a citywide AQI can still be calculated even if some monitoring stations malfunction. However, when data is missing during particularly polluted hours or when the dominant pollutant changes, this flexibility can yield artificially low readings. Yes. CPCB bulletins show that all 39 stations were used only on November 1 for the week ending November 3. On other days, only 37 or 38 stations were included in Delhi's official AQI calculation. More crucially, the prominent pollutant - the pollutant whose sub-index determines a station's AQI - also changed at several stations through the week. Chart 1 While PM2.5, the expected dominant pollutant during this season, was prominent at 32 to 36 stations, PM10 became the leading pollutant at most of the others. On November 3, nitrogen dioxide replaced PM2.5 as the prominent pollutant at the Lodhi Road station operated by the Indian Institute of Tropical Meteorology (IITM). The switch in the prominent pollutant does not necessarily indicate foul play, but it raises concerns when data for PM2.5 and PM10 is incomplete. Even among stations where PM2.5 data was available for at least 16 hours, between 8% (October 28 and 29) and 19% (November 3) lacked the full 24-hour dataset. Chart 2 Theoretically, missing data can either raise or lower the 24-hour average depending on whether the missing hours are cleaner or more polluted. But HT's examination of 168 hours of PM2.5 data between October 28 and November 4 shows that missing data was not random. The fewest active stations were observed from noon to 3 p.m., typically the cleanest hours of the day. This would tend to raise the overall PM2.5 average. However, the next set of hours with the most missing data - between 7 a.m. and 11 a.m. and around 2 a.m. - are generally among the most polluted periods, which would tend to lower the average. These conflicting gaps suggest that Delhi's official AQI may fluctuate due to data inconsistency rather than actual atmospheric changes. Determining whether this pattern is new or long-standing is difficult because the CPCB's data dashboard is slow and cumbersome, making historical analysis nearly impossible. Chart 3 Between November 2 and 3, Delhi's average AQI dropped from 366 to 309. While meteorological changes partly explain this decline, data irregularities also appear to have contributed. Three stations - Lodhi Road (IITM), Shri Aurobindo Marg (DPCC), and ITO (CPCB) - recorded the most dramatic improvements. Their AQI readings nearly halved: from 319 to 164, 294 to 157, and 280 to 155 respectively, even as the city's average improved by just 16%. At all three stations, the prominent pollutant changed - from PM2.5 to PM10 at ITO and Aurobindo Marg, and from PM2.5 to nitrogen dioxide at Lodhi Road-IITM. While Aurobindo Marg's data shows missing PM2.5 and PM10 readings for two hours (a plausible explanation for the shift), the patterns at Lodhi Road and ITO raise red flags. At Lodhi Road-IITM, the PM2.5 sub-index remained above PM10 for most of the day but dropped sharply during three isolated hours. Moreover, IITM's PM2.5 readings were significantly lower than those recorded by the India Meteorological Department's station at the same location, pointing to measurement discrepancies. Chart 4 At ITO, both PM2.5 and PM10 sub-indices were below 50 between 4-5 a.m. when data transmission stopped. When reporting resumed at noon, both values spiked above 350 - an implausible jump if attributed only to natural conditions. The data gaps and shifting pollutant dominance suggest that Delhi's official AQI may not fully capture pollution severity during critical periods. Missing PM2.5 readings - especially at heavily polluted sites such as ITO - can lower the city's average even when local conditions remain hazardous. Some monitoring stations also show abrupt spikes and drops in readings, possibly due to calibration errors or interference. Environmental groups have alleged that water sprinkling near certain monitoring stations may be skewing measurements, though officials have not confirmed this. Taken together, these inconsistencies indicate that Delhi's official AQI - intended to convey public health risk - may at times provide an incomplete or misleading picture of real air quality, especially during high-pollution episodes....