대기질 빅데이터를 활용한 시군구 단위 시공간 분포 특성

Translated title of the contribution: Spatiotemporal distribution characteristics at the municipal level using air quality big data

Kangmin Kim, Chul Sue Hwang

Research output: Contribution to journalArticlepeer-review

Abstract

Human health is directly impacted by air quality, which is why it is still being studied. Specifically, air quality data is disseminated on a national scale to safeguard public health. Nevertheless, this is carried out on a limited scale and for a brief duration. Thus, it is imperative to broaden the scope of the research to encompass a longer-term outlook. This study involved the computation of the comprehensive air quality index for the entire nation spanning from 2012 to 2023. Additionally, we determined the patterns of distribution in both space and time. The integrated air quality index revealed both temporal and spatial hot spots in the capital area and Chungcheongdo with O3 and PM2.5 having a significant influence, according to the results. Furthermore, it was discovered that SO2, CO, NO2, PM10 were relatively cold spots. This indicated that the air quality had improved over time. The findings of this study are anticipated to aid in the identification of air pollutants and specific regions that warrant attention in policy implementation.

Translated title of the contributionSpatiotemporal distribution characteristics at the municipal level using air quality big data
Original languageKorean
Pages (from-to)295-308
Number of pages14
JournalJournal of the Korean Society of Surveying Geodesy Photogrammetry and Cartography
Volume42
Issue number4
DOIs
Publication statusPublished - 2024

Bibliographical note

Publisher Copyright:
© 2024 Korean Society of Surveying. All rights reserved.

Keywords

  • Air pollutants
  • Air quality
  • Big data
  • Comprehensive Air-quality Index(CAI)
  • Emerging hot spot analysis

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