In-home air quality changes through report-back of personal data

Abstract

Indoor air quality (IAQ) is a critical determinant of health, yet households face limited practical strategies for improvement. This study tested whether multi-pollutant monitoring paired with personalized, plain-language Home Health Reports (HHRs) featuring data-informed recommendation for improving IAQ could prompt effective actions. Results showed that ventilation-responsive pollutants—including CO2, NO2, and episodic volatile organic compounds (VOCs)—declined in treated homes, consistent with reported behaviors such as opening windows, using exhaust fans, and operating range hoods during pollutant-generating activities. NO2 reductions were especially evident in gas-stove households, reflecting the uptake of provided low- to no-cost recommendations, especially where a clear source exists. In contrast, particulate matter (PM2.5 and PM10) showed no consistent treatment effect, likely due to episodic sources, outdoor infiltration, and limited adoption of higher-effort measures such as filtration. A subset of highly polluted homes did achieve PM reductions, echoing findings that the greatest reductions occur where baseline pollution is highest. The VOC analysis reinforced the difference between pollutants diluted by ventilation and those requiring source removal. Episodic compounds such as carbon tetrachloride declined, while continuous emitters such as 1,4-dichlorobenzene were unaffected, underscoring the limits of ventilation-only strategies. Overall, findings align with prior work demonstrating that household behavior change can reduce short-term pollutant peaks, but structural or community-level measures are needed where emissions are persistent or outdoor-dominated. Broader implementation could pair low-cost feedback with building or community measures, and future research should evaluate long-term adherence, optimize messaging strategies, and link pollutant reductions to health outcomes.