Exposure to fine particulate matter (PM2.5) is responsible for millions of premature deaths globally each year. Wildfires are a major source of PM2.5, creating dangerously high levels of air pollution across extensive regions. Current public health recommendations for wildfire-related PM2.5 exposure include staying indoors and using portable air cleaners or central air systems with adequate filtration. We addressed the gaps in understanding central air system usage during wildfires by studying smart thermostat data from approximately 5000 California homes during the 2020 wildfire peak, proving that these systems are not effectively utilized for improving air quality. We explored the potential health benefits of optimizing central air system operation using smart thermostats and air quality data through modelling and simulation. An automated optimization approach could decrease indoor PM2.5 exposure by up to 54 ± 5 % compared to standard air conditioning use, and up to 61 ± 5 % during peak wildfire smoke days. While this increased operation incurs an additional energy cost of about $5 per month per household (totalling $75 million), it is partially offset by an estimated 53 ± 5 % reduction in premature mortality, which translates to $29 million in monetized health benefits. Installing a MERV 13 filter and reducing house leakage further reduces indoor PM2.5 concentrations. Overall, using a central air system with proper filtration can be as effective as using four portable air cleaners for on average house. The greatest potential for reducing health risks associated with PM2.5 exposure through an automated optimised system is in lower-income areas. This study reveals that existing technologies and infrastructure, often overlooked, could significantly improve protection for building occupants from wildfire smoke.

Using smart thermostats to reduce indoor exposure to wildfire fine particulate matter (PM2.5)

Federico Dallo
Primo
Writing – Original Draft Preparation
;
Carlo Barbante
Funding Acquisition
;
2025

Abstract

Exposure to fine particulate matter (PM2.5) is responsible for millions of premature deaths globally each year. Wildfires are a major source of PM2.5, creating dangerously high levels of air pollution across extensive regions. Current public health recommendations for wildfire-related PM2.5 exposure include staying indoors and using portable air cleaners or central air systems with adequate filtration. We addressed the gaps in understanding central air system usage during wildfires by studying smart thermostat data from approximately 5000 California homes during the 2020 wildfire peak, proving that these systems are not effectively utilized for improving air quality. We explored the potential health benefits of optimizing central air system operation using smart thermostats and air quality data through modelling and simulation. An automated optimization approach could decrease indoor PM2.5 exposure by up to 54 ± 5 % compared to standard air conditioning use, and up to 61 ± 5 % during peak wildfire smoke days. While this increased operation incurs an additional energy cost of about $5 per month per household (totalling $75 million), it is partially offset by an estimated 53 ± 5 % reduction in premature mortality, which translates to $29 million in monetized health benefits. Installing a MERV 13 filter and reducing house leakage further reduces indoor PM2.5 concentrations. Overall, using a central air system with proper filtration can be as effective as using four portable air cleaners for on average house. The greatest potential for reducing health risks associated with PM2.5 exposure through an automated optimised system is in lower-income areas. This study reveals that existing technologies and infrastructure, often overlooked, could significantly improve protection for building occupants from wildfire smoke.
2025
Istituto di Scienze Polari - ISP
Air cleaning
Fine particulate matter
Indoor air quality
Public health
Ventilation
Wildfires
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/563949
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