Nieuwenhuijsen et al. note that many studies have investigated people’s exposure to air pollution, which is associated with respiratory and cardiovascular problems. These studies usually create a picture of exposure based on air pollution levels outside people’s homes. This approach ignores big differences in air quality in school and work environments. It also ignores spikes in pollution that happen over the course of the day such as during rush hour. Nieuwenhuijsen’s team wanted to test technology's ability to fill in these gaps.

The researchers equipped more than 50 school children with smartphones with CalFit software to obtain information on their location and physical activity level. The children also received small sensors, the micro-aethalometer model AE51, to measure black carbon levels simultaneously and continuously.

The aims of this study were to examine (1) the variability in personal air pollution levels during the day and (2) the relationship between modeled home and school estimates and continuously measured personal air pollution exposure levels in different microenvironments (e.g., home, school, and commute). We focused on black carbon as an indicator of traffic-related air pollution.

—Nieuwenhuijsen et al.

Although most children spent less than 4% of their day traveling to and from school, commuting contributed to 13% of their total potential black carbon exposure. The researchers concluded that mobile technologies could contribute valuable new insights into air pollution exposure.

Resources

• Mark J. Nieuwenhuijsen, David Donaire-Gonzalez, Ioar Rivas, Montserrat de Castro, Marta Cirach, Gerard Hoek, Edmund Seto, Michael Jerrett, and Jordi Sunyer (2015) “Variability in and Agreement between Modeled and Personal Continuously Measured Black Carbon Levels Using Novel Smartphone and Sensor Technologies” Environmental Science & Technology doi: 10.1021/es505362x