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 PM_2.5 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 PM_2.5, respectively. The sensor intervariability was generally low, with mean R²-values of 0.84–0.94 for PM_2.5 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 PM_2.5 concentrations were observed. Our findings demonstrate that low-cost sensors can accurately quantify air pollution exposure in urban areas with high spatiotemporal resolution.