Assessment of the Dynamic Exposure to PM 2.5 Based on Hourly Cell Phone Location and Land Use Regression Model in Beijing

Junli Liu, Panli Cai, Jin Dong, Junshun Wang, Runkui Li and Xianfeng Song
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Junli Liu: College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China
Panli Cai: College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China
Jin Dong: College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China
Junshun Wang: College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China
Runkui Li: College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China
Xianfeng Song: College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China

IJERPH, 2021, vol. 18, issue 11, 1-14

Abstract: The spatiotemporal locations of large populations are difficult to clearly characterize using traditional exposure assessment, mainly due to their complicated daily intraurban activities. This study aimed to extract hourly locations for the total population of Beijing based on cell phone data and assess their dynamic exposure to ambient PM 2.5 . The locations of residents were located by the cellular base stations that were keeping in contact with their cell phones. The diurnal activity pattern of the total population was investigated through the dynamic spatial distribution of all of the cell phones. The outdoor PM 2.5 concentration was predicted in detail using a land use regression (LUR) model. The hourly PM 2.5 map was overlapped with the hourly distribution of people for dynamic PM 2.5 exposure estimation. For the mobile-derived total population, the mean level of PM 2.5 exposure was 89.5 ?g/m 3 during the period from 2013 to 2015, which was higher than that reported for the census population (87.9 ?g/m 3 ). The hourly activity pattern showed that more than 10% of the total population commuted into the center of Beijing (e.g., the 5th ring road) during the daytime. On average, the PM 2.5 concentration at workplaces was generally higher than in residential areas. The dynamic PM 2.5 exposure pattern also varied with seasons. This study exhibited the strengths of mobile location in deriving the daily spatiotemporal activity patterns of the population in a megacity. This technology would refine future exposure assessment, including either small group cohort studies or city-level large population assessments.

Keywords: cell phone; activity pattern; exposure assessment; fine particulate matter; land use regression model (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2021
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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