In response to a Parliament question, the Government of India stated that “…there is no conclusive data which establishes a direct correlation between higher AQI levels and lung diseases…”
This position appears technically correct (although it overlooks the possibility that lung elasticity and capacity may be adversely affected by pollution, which is alluded to later in the response).
Determining public-health causation is complex, and robust conclusions require long-term, localised data. Equally, we have yet to suffer catastrophes where our air causes immediate death (for which mercy we must clearly be grateful!).
Remarkably, though, we’ve comfortably accepted the status quo. We’re carrying on as usual, and the most significant public health risk since the pandemic occupies an insignificant fraction of media coverage and even less of public discourse.
The fact of the matter is that the deteriorated (and rapidly worsening) air quality affects all of us. It’s a genuine concern with significant, at least and reductively, economic consequences.
While our politicians will continue to engage in what passes for dialogue in our times, the fact remains that there can be no ‘political divide’ when it comes to the air we breathe.
Pollution Without Politics, Data Without Accountability
The principal question is: Does our establishment at the Centre and in the states consider it necessary to assess air quality?
The answer must be ‘yes’ because air quality is routinely assessed, and we know that our air is polluted and that pollution is harmful.
The government may be justified in calibrating pollution standards to our economic and developmental realities since developing economies must balance aspiration and pragmatism. Still, these positions cannot justify inertia nor an absence of transparency.
If our national interest requires tolerance of higher pollution levels, that interest must be articulated clearly.
We must determine whether the dominant sources of pollution align with national priorities or are the result of lax enforcement. This is a fundamental question, but it is secondary to a more basic problem: we know that we do not know.
It follows that the government’s response in Parliament may well be correct—that we currently lack the data to establish, among other things, a causal link between air pollution and lung diseases.
However, we have no visibility into whether there is any meaningful effort to systematically collate data on the underlying problem.
That there is some relationship is clear even from that response, since the closing notes to the government response, cited at the beginning of this article, reference government initiatives to address air pollution.
Mumbai as a Case Study in 'Not Knowing'
Apart from Delhi, Mumbai too demonstrates the absence of meaningful data. The distribution of air-quality monitors across the city is uneven.
Several neighbourhoods have limited coverage; others have none. These gaps create blind spots that distort our understanding of the city’s air.
Navy Nagar (Colaba) offers a helpful illustration: The sensor consistently records poor air quality despite the absence of industry and minimal, at least by Mumbai standards, local construction activity.
So, where does this pollution come from? Would sensors in each locality at Navy Nagar show similar results, indicating a consistently high level of local pollution?
Is the extent of construction, minimal or otherwise, in the area causing this pollution?
Or do prevailing winds and the daily land and sea breeze import this pollution to the vicinity of the Navy Nagar sensor?
What impact does this pollution have on residents and passersby, especially on children, the elderly, and urban fauna and flora?
We know only that we do not know.
Here is where hyperlocal sensors become indispensable. Compact, lower-cost devices can supplement high-grade monitors to capture micro-environmental variations across localities.
They reveal how pollution shifts street by street, at pedestrian level, and across elevations that matter in a vertical city like Mumbai—linking AQI data to lived reality rather than abstract averages.
Such data can, and in this time of our AQI crisis, must be augmented through structured, voluntary participation by citizens and communities installing approved low-cost sensors, thereby densifying an otherwise sparse monitoring network.
In this context, the Air Quality Monitoring, Emission Inventory, and Source Apportionment study for Mumbai, undertaken by the Maharashtra Pollution Control Board, CSIR-National Environmental Engineering Research Institute (NEERI), and IIT Bombay, stands out for its methodological rigour.
That rigour, however, also exposes the structural data gaps that continue to constrain effective air-quality governance in the city.
The report flags two unresolved failures: the absence of ward-level monitoring, and the failure to treat Mumbai as part of the wider Mumbai Metropolitan Region (MMR) airshed to further understand the city’s pollution in the context of pollution across the MMR. This remains to be addressed, and so we lack the requisite data.
The Cost of Flying Blind
The consequences of this data deficit are concrete.
Public-health initiatives are reactive
Economic analysis excludes pollution-linked productivity losses
Regulatory oversight and enforcement operate in a data vacuum
Citizens seek recourse before courts which also operate in this data-sparse environment
This was most recently demonstrated during hearings before the Bombay High Court in the week of 22 December, where the court questioned the extent of BMC's monitoring of construction sites, and noted that several installed sensors were non-functional.
Through it all, we must understand the health, economic, and social costs that our air imposes on us; and we must equip ourselves with information that allows mitigation, adaptation, and informed choice.
Without credible data, none of this is possible.
Calibrating standards to our realities cannot fail to assess those standards and address the costs which we have chosen to incur.
Delhi dominates the national pollution narrative since its winter smog is dramatic and most visible. The rest of us must take no comfort in that focus.
Taking Mumbai as an example again, the MMR experiences prolonged periods during which PM2.5 levels exceed even India’s already lenient standards.
Coastal geography, construction intensity, industrial peripheries, and vehicular congestion combine to produce chronic pollution that rarely attracts sustained attention.
The fact that our crisis is less photogenic does not make it less harmful, and this holds for literally every urban agglomeration in our country.
The learning is straightforward. A network of high-grade monitors is essential, and in our population-dense urban environment, it must be supplemented by a dense network of calibrated sensors.
The resulting data must be shared among regulators and made available to the public in real time, so we no longer operate on broad assumptions based on a limited dataset.
We must establish a data spine. Mumbai is making progress in this direction with a proposal to install monitors at construction sites and link them to existing sensors, but this remains aspirational and executory as of this date.
Given that our pollution thresholds will, for the foreseeable future, be higher than those of wealthier economies, the obligation to measure increases.
Tolerating pollution without understanding its sources or consequences is an abdication of our responsibilities to ourselves and to the most vulnerable in our country.
(Justin M Bharucha is the Managing Partner at Bharucha & Partners. This is an opinion piece and the views expressed above are the author’s own. The Quint neither endorses nor is responsible for the same.)