TY - JOUR
T1 - Hyperlocal air pollution in an urban environment - measured with low-cost sensors
AU - Frederickson, Louise Bøge
AU - Russell, Hugo Savill
AU - Fessa, Dafni
AU - Khan, Jibran
AU - Schmidt, Johan Albrecht
AU - Johnson, Matthew Stanley
AU - Hertel, Ole
N1 - Publisher Copyright:
© 2023 The Authors
PY - 2023/11
Y1 - 2023/11
N2 - 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.
AB - 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.
KW - Hyperlocal air pollution
KW - Low-cost sensors
KW - Personal exposure monitoring
KW - Pollution exposure
KW - Urban air pollution
UR - http://www.scopus.com/inward/record.url?scp=85172196615&partnerID=8YFLogxK
U2 - 10.1016/j.uclim.2023.101684
DO - 10.1016/j.uclim.2023.101684
M3 - Journal article
AN - SCOPUS:85172196615
SN - 2212-0955
VL - 52
JO - Urban Climate
JF - Urban Climate
M1 - 101684
ER -