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Suitability Analysis of Optimal PM Monitoring Stations Using Kernel Density Function and PCA

Jeong, Jong Chul 1

1남서울대학교

Accredited

ABSTRACT

For optimal new PM(Particulate Matter) monitoring locations, it is important to consider the spatial distribution between monitoring station and user along with the accessibility. This study used spatial analysis to analyze the shortest distance among the centers of administrative dong and PM monitoring stations to show the influence of PM monitoring stations. In addition, this research suggested the new PM monitoring location through distance analysis and kernel density estimation of PM monitoring stations and public facilities such as community service center. This study proposed the method to select new PM monitoring station from an area outside the scope of the existing PM monitoring station, without showing redundancy with the existing network. Then the principal component analysis was performed in order to determine the priority PM monitoring stations that have a higher value for environment variables and kernel density estimation related to PM. The new PM monitoring stations suggested in this study will provide the more improved PM measured value service for users than the conventional PM monitoring network.

Citation status

* References for papers published after 2022 are currently being built.