TY - JOUR
T1 - Assessing personal travel exposure to on-road PM2.5 using cellphone positioning data and mobile sensors
AU - Li, Qiuping
AU - Liang, Shen
AU - Xu, Yang
AU - Liu, Lin
AU - Zhou, Suhong
N1 - Funding Information:
This work was supported by National Natural Science Foundation of China [grant number 41971345 , 71961137003 , 42011530172 ]; Guangdong Basic and Applied Basic Research Foundation [grant number 2020A1515010695 ].
Publisher Copyright:
© 2022
PY - 2022/5
Y1 - 2022/5
N2 - PM2.5 pollution imposes substantial health risks on urban residents. Previous studies mainly focused on assessing peoples' exposures at static locations, such as homes or workplaces. There has been a scarcity of research that quantifies the dynamic PM2.5 exposures of people when they travel in cities. To address this gap, we use cellphone positioning data and PM2.5 concentration data collected from smart sensors along roads in Guangzhou, China, to assess personal travel exposure to on-road PM2.5. First, we extract the trips of cellphone users from their trajectories and use the shortest path algorithm to calculate their travel routes on the road network. Second, the travel exposure of each user is estimated by associating their movement patterns with PM2.5 concentrations on roads. The result shows that most users’ average travel exposures per hour fall within the range of 20 ug/m3 to 75 ug/m3. Travel exposure varies across users, and 54.0% of users experience low travel exposure throughout the day, 25.5% of users experience high travel exposure in the evening, and 20.5% of users experience high travel exposure in the afternoon. Furthermore, the impacts of on-road PM2.5 on urban populations are uneven across roads. More attention should be given to roads with high PM2.5 concentrations and traffic flows in each period, such as Huan Shi Middle Road in the morning, Inner Ring Road in the afternoon, and Xinjiao Middle Road in the evening. The findings in this study can contribute to a more in-depth understanding of the relationship between air pollution and the travel activities of urban populations.
AB - PM2.5 pollution imposes substantial health risks on urban residents. Previous studies mainly focused on assessing peoples' exposures at static locations, such as homes or workplaces. There has been a scarcity of research that quantifies the dynamic PM2.5 exposures of people when they travel in cities. To address this gap, we use cellphone positioning data and PM2.5 concentration data collected from smart sensors along roads in Guangzhou, China, to assess personal travel exposure to on-road PM2.5. First, we extract the trips of cellphone users from their trajectories and use the shortest path algorithm to calculate their travel routes on the road network. Second, the travel exposure of each user is estimated by associating their movement patterns with PM2.5 concentrations on roads. The result shows that most users’ average travel exposures per hour fall within the range of 20 ug/m3 to 75 ug/m3. Travel exposure varies across users, and 54.0% of users experience low travel exposure throughout the day, 25.5% of users experience high travel exposure in the evening, and 20.5% of users experience high travel exposure in the afternoon. Furthermore, the impacts of on-road PM2.5 on urban populations are uneven across roads. More attention should be given to roads with high PM2.5 concentrations and traffic flows in each period, such as Huan Shi Middle Road in the morning, Inner Ring Road in the afternoon, and Xinjiao Middle Road in the evening. The findings in this study can contribute to a more in-depth understanding of the relationship between air pollution and the travel activities of urban populations.
KW - Cellphone positioning data
KW - Mobile sensors
KW - On-road PM concentrations
KW - Travel exposure
UR - http://www.scopus.com/inward/record.url?scp=85128409872&partnerID=8YFLogxK
U2 - 10.1016/j.healthplace.2022.102803
DO - 10.1016/j.healthplace.2022.102803
M3 - Journal article
C2 - 35443227
AN - SCOPUS:85128409872
SN - 1353-8292
VL - 75
JO - Health and Place
JF - Health and Place
M1 - 102803
ER -