Abstract
AbstractRecently, the air pollution has been seriously regarded in the urban environment. Particularly, the substantial relationship between the air pollution and the daily movements of citizens has not been sufficiently investigated yet. This study attempts to empirically identify the patterns of air pollution using association rule mining from Seoul, the metropolitan city in South Korea. As a result, 214 patterns on air pollution are discovered, and those are embedded into vectors based on Doc2Vec technique. Then, this paper further examines how the movement of citizens reacts to the discovered patterns of air pollution by deploying the linear regression on the floating population with emphasis on the walk-traffic. Specifically, the walk-traffic is categorized into 14 categories by gender and age group, and the effects of air pollution patterns on each subgroup walk traffic were analyzed. Findings of this paper provide the empirical evidences on the estimated air pollution sensitivity by generation and gender to researchers and practitioners. This paper has the contribution on newly proposing the methodological framework for further managing the air pollution in the urban environment.
Graphical abstract
Funder
National Research Foundation of Korea (NRF) grant funded by the Korea government
Publisher
Springer Science and Business Media LLC