Hyperlocal air pollution in an urban environment- measured with low-cost sensors

Air pollution levels can vary significantly over short distances, particularly in urban areas and near emission sources. This study examined the performance of low-cost sensor devices for monitoring levels of NO2, O-3, and PM2.5 along two closely spaced (average 8 m) routes in Copenhagen, Denmark. One route was located near a lake (Route 1) and the other near a busy road (Route 2). The routes were walked in tandem for 84 h. The mode of deployment was determined using an accelerometer, gyroscope, and light sensor, achieving a 97.4 % accuracy rate. Field calibration with multivariate linear regression proved the most robust calibration model across pollutants, yielding mean R-2-values of 0.64, 0.79, and 0.48 for NO2, O-3, and PM2.5, respectively. The sensor intervariability was generally low, with mean R-2-values of 0.84-0.94 for PM2.5 measured with optical particle sensors and 0.88-0.90 for NO2 and O-3 measured with metal oxide sensors. Results showed significantly higher NO2 concentrations on Route 2 (21.6 +/- 6.6 ppb) compared to Route 1 (10.1 +/- 4.0 ppb) during mornings. However, no significant differences in O-3 and PM2.5 concentrations were observed. Our findings demonstrate that low-cost sensors can accurately quantify air pollution exposure in urban areas with high spatiotemporal resolution.

Automated summary

This study examined the performance of low-cost sensor devices for monitoring air pollution levels in urban areas. The results showed significant variations in air pollution levels over short distances, with higher concentrations of NO2 near busy roads. The study demonstrated that low-cost sensors can accurately measure air pollution exposure with high spatiotemporal resolution.