Can Mumbai trust its official air data? An IIT scientist on what to check

Air-quality readings describe conditions at a particular place and time. They are not automatically interchangeable across networks. A government station and a private monitor may stand in different microenvironments, so each can provide a valid but different picture of Mumbai’s pollution.

For example, a private monitor beside construction activity or heavy traffic may detect a local spike in dust or exhaust. A government station in a less exposed location may report lower levels. Technology, calibration, maintenance and humidity can also affect measurements. Different averaging periods, pollutants, timestamps or AQI methods create further differences.

The article does not establish that either network systematically overestimates or underestimates pollution. The fairest comparison uses PM2.5 and PM10 from the same time intervals and applies the same AQI method. Regular checks between networks, calibration records and data validation would make results easier to understand and trust.

The Air Quality Index, or AQI, translates measured pollutant concentrations into a simpler health-related scale. Instead of asking people to interpret several concentrations separately, it summarizes air conditions using categories such as satisfactory or poor. The exact pollutants, breakpoints, averaging periods and categories depend on the national method.

In general, each pollutant concentration is matched to a concentration range and converted into a pollutant-specific sub-index. The overall AQI is usually determined by the highest relevant sub-index, although the precise calculation follows the applicable authority’s rules. PM2.5 and PM10 are among the measurements that may be included.

That method makes comparability essential. Mumbai readings cannot be fairly compared if networks use different pollutants, averaging periods, timestamps or AQI formulas. The article recommends comparing PM2.5 and PM10 over identical intervals and using the same methodology before concluding that one network is wrong.

A monitor’s reading is shaped by both the air around it and the way that air is measured. Location matters because pollution varies sharply between a construction site, traffic corridor, residential area and less exposed setting. Thus, two monitors can disagree without either being systematically wrong.

Technology and calibration affect how particles are detected. Maintenance problems or calibration drift can reduce data quality. Humidity can make airborne particles absorb moisture and grow, increasing light scattering. Averaging periods also matter: a short interval may show a local spike, while a longer average can smooth it. Different AQI formulas can create another difference.

The article gives no fixed percentage or concentration change for these effects. Their size depends on conditions and equipment. Reliable comparison requires matching locations or interpreting their microenvironments, checking calibration and maintenance, and comparing identical PM2.5 and PM10 intervals.

Public decisions depend on knowing where pollution is high, how severe it is and whether conditions are changing. If official data are inaccurate or incomplete, authorities may misjudge pollution sources or overlook neighbourhoods and hotspots. If the data are not transparent, residents cannot understand why advisories or control measures were issued.

For example, faulty instruments, calibration drift or inadequate maintenance can affect a government station’s data quality. Without validation or comparison with nearby stations, a misleading reading may influence decisions about construction dust, traffic, waste burning or other sources. A satisfactory reading might also conflict with visible haze, creating confusion.

The article does not quantify the health impact of inaccurate data. It does identify practical safeguards: regular calibration, preventive maintenance, data validation, monitoring audits and open reporting. Comparisons between government and private networks would strengthen confidence and support better-targeted short- and long-term action.

Visibility and AQI measure different aspects of the atmosphere. A skyline can look blurred because light is being scattered, while the measured pollutant concentrations remain within a satisfactory AQI category. Therefore, visual appearance alone cannot establish pollution severity or health risk.

Humidity is a key mechanism. Airborne particles can absorb moisture and grow, increasing their ability to scatter light. Construction dust and combustion emissions can add more particles, making the haze more noticeable. Mumbai’s skyline may therefore appear hazy because of a combination of moisture, fine particles and local emissions rather than one single cause.

The article cautions against treating visible haze as a complete pollution assessment. Instrument readings still need quality checks, including calibration, maintenance and data validation. Comparing PM2.5 and PM10 over the same periods can clarify conditions. Authorities should also maintain transparent monitoring while targeting construction and road dust and combustion sources.

Mumbai’s pollution comes from several human activities rather than one dominant source in every situation. The article identifies construction and road dust, vehicular traffic, industries, port and shipping activity, diesel generators and open waste burning. Pollution transported from other regions can also influence the city’s air.

Weather determines how those emissions behave. Wind speed and direction can disperse pollutants, redistribute them between coastal and inland areas or contribute to accumulation under unfavourable conditions. Rainfall, humidity and atmospheric mixing also affect the atmosphere. Mumbai’s coastal location therefore does not guarantee clean air; sea breezes can move pollution rather than remove it.

The balance between weather and human activity varies by season. Explaining an early deterioration requires analysing weather conditions alongside monitoring data. Effective action must target local sources while considering regional transport. Longer-term planning should connect air-quality management with transport, infrastructure and regional coordination.

PM10 refers to particulate matter with an aerodynamic diameter of up to 10 micrometres. PM2.5 refers to the finer fraction, up to 2.5 micrometres. These measurements describe particle pollution by size, which matters because particle size affects how pollution behaves in air and how deeply it can enter the respiratory system.

They are central to comparison because the article specifically recommends examining PM2.5 and PM10 concentrations over the same time intervals. A monitor near construction may record more coarse dust, while traffic or combustion can contribute fine particles. Humidity can also affect particle growth and the way instruments detect or estimate pollution.

AQI results depend on the chosen methodology, pollutants and averaging periods. Therefore, PM2.5 and PM10 values should not be compared casually across networks. Matching time intervals, methods, calibration and data quality checks gives a more meaningful picture of Mumbai’s pollution than relying on a single headline AQI.