Hyperlocal air pollution in an urban environment - measured with low-cost sensors
Louise Bøge Frederickson, Hugo S. Russell, Dafni Fessa, Jibran Khan, Johan A. Schmidt, Matthew S. Johnson, Ole Hertel
Abstract
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, O3, 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 R2-values of 0.64, 0.79, and 0.48 for NO2, O3, and PM2.5, respectively. The sensor intervariability was generally low, with mean R2-values of 0.84–0.94 for PM2.5 measured with optical particle sensors and 0.88–0.90 for NO2 and O3 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 O3 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.