We spent an hour at SF Climate Week 2026 asking a deceptively simple question: who should pay for air quality data?
The room included Max Interbrick from Sparrow Analytics, Michael Hopps from R-Zero, and Iyad Kheirbek from C40 Cities alongside other industry professionals and experts. The answer we kept circling back to: nobody wants to, so the cost will land on the public sector, and from there, it will cascade.
Here’s the logic. When air quality goes untracked, the consequences don’t disappear. They show up later in public health data, hospital admissions, school attendance, worker productivity. At some point, a city or an air district draws the correlation and decides to act. That’s when policy enters the picture, and policy has a way of making the economics of data collection suddenly very clear to everyone downstream.
We’re already seeing early versions of this. Air districts today can issue penalties when pollution levels are out of compliance, but the measurement infrastructure is expensive and geographically sparse. Large fixed monitoring stations, infrequent readings, enforcement that’s more reactive than systematic. Iyad shared an interesting example. China’s approach with static sensor networks feeding simulation models gives a sense of where this is heading: real measurements, continuously compared against predictions, with inspectors dispatched when something doesn’t add up. The results have been significant. Measure, correlate, enforce.
What’s less obvious is how this plays out in correlation to us being in the buildings.
The problem in the built environment isn’t just a data gap. It’s an accountability gap. The chain of responsibility runs through property owners, building operators, and service companies. And in practice, responsibility tends to dissolve somewhere in between. Filters don’t get changed when they should. Building codes are built on averages that no longer reflect how or where people live and work. Nobody has a view into what’s actually happening at the level of a specific address or even a block level.
The interesting thing Michael raised: we already have enough evidence that indoor air quality affects how people think, work, and feel. The data exists. The financial case is real. But there is no clear signal about where to act, and who’s on the hook.
That’s the flywheel. As outdoor air quality data gets more granular and more continuous, it becomes easier to tie indoor conditions to specific buildings and specific locations. That makes the public health correlations sharper, which makes policy arguments stronger, which creates pressure on the real sector to move from schedule-based maintenance to performance-based maintenance. And performance-based maintenance requires the kind of address-level intelligence that hasn’t existed until very recently.
I don’t think anyone at the table was certain where the true inflection point is. Whether it starts with a public health study, a regulatory update, a high-profile lawsuit, or just a handful of early movers in the private sector proving out the model. Probably some combination. But the direction of travel seems clear enough.
The question for anyone in filtration or HVAC isn’t really whether this shift is coming. It’s whether the shift finds you ready for it.
