Song, Yu
- Institutionen för skogens ekologi och skötsel, Sveriges lantbruksuniversitet
- Chinese Academy of Sciences
Sammanfattning
Urban residents face serious health issues owing to air pollution, especially from particulate matter (PM). The dynamic exposure risk of PM exhibits intricate spatiotemporal fluctuations influenced by resident activity and urban patterns. Therefore, high spatiotemporal resolution assessments and researches are needed. In this study, high-resolution dynamic exposure risk was assessed using mobile monitoring of three types of PM (PM1, PM2.5, and PM10) and cell phone signaling data in the center of Shenyang, China, combined with geographically weighted regression model and dynamic exposure risk model. And influencing factors of dynamic exposure risks were explored by boosted regression tree model. The results showed that high-risk areas were concentrated along the main roads. Residents suffered greater risks during the morning peak than evening peak, and weekday than weekend. The dynamic exposure risk was significantly affected by the speed of population mobility (relative influence>55.49), surpassing the effect of POI (Point of Interest) density (relative influence
Nyckelord
Dynamic exposure risks; Mobile monitoring; Particulate matter; Human activity; Big data; Urban air pollution
Publicerad i
Urban Climate
2025, volym: 59, artikelnummer: 102261
Utgivare: ELSEVIER
SLU författare
UKÄ forskningsämne
Meteorologi och atmosfärsvetenskap
Miljövetenskap
Publikationens identifierare
- DOI: https://doi.org/10.1016/j.uclim.2024.102261
Permanent länk till denna sida (URI)
https://res.slu.se/id/publ/140582