Birmingham [UK], February 28 (HBTV): A new study reveals that people may be exposed to unhealthy levels of airborne pollutants inside their homes, even when outdoor air quality is good.

Researchers at the University of Birmingham used low-cost sensors and innovative techniques over two weeks to compare particulate matter (PM) levels in three homes. They found that indoor pollution levels were higher and more variable than outdoor levels. One of the homes exceeded the World Health Organisation's (WHO) 24-hour PM2.5 limit on nine days, highlighting the importance of monitoring air quality at a household-specific level.

Published in Scientific Reports, this study is the second paper from McCall MacBain Clean Air Fellows, part of a philanthropically funded Master's degree in Air Pollution Management and Control at the University of Birmingham.

Co-author and Clean Air Fellow Catrin Rathbone stated: ‘Our study shows the need to monitor indoor air pollution, as people can have unhealthy air at home even if outdoor air is good. PM levels varied significantly between homes, indicating that monitoring just one location isn’t enough.’

The study found that factors such as household location, ventilation, and occupancy patterns influenced particle levels, demonstrating the complexity of indoor air quality.

Co-author and Clean Air Fellow Owain Rose said: ‘With more time spent working from home, understanding the factors that affect air quality within households is increasingly important. The methods we used accurately modelled indoor PM levels, helping to improve exposure estimates at a low cost.’

Researchers identified five key factors contributing to indoor PM levels—two linked to indoor activities, such as increased movement by residents, and three related to external sources, including a nearby restaurant's kitchen vent. They observed that larger particles (PM10) settled faster compared to smaller particles (PM1, PM2.5).

The study employed Non-negative Matrix Factorization (NMF), a tool for identifying hidden patterns in data, to model indoor PM levels more accurately. By using low-cost sensors, researchers created a more detailed picture of pollutant levels within homes. (ANI)