Spatial correlation analysis using the indicators of the anthropocene focusing on atmospheric pollution: A case study of Seoul

• Main Authors: Lee, G.-E (Author), Lee, J.-H (Author)
• Format: Article
• Language: English
• Published: Elsevier B.V. 2021
• Subjects: Air pollutant emission; Air pollution; Air pollution indicators; Anthropocene; atmospheric pollution; Atmospheric pollution; Correlation methods; Earth system change; Economics; Explanatory variables; Fine particulate matter; Great acceleration; metropolitan area; ozone; Ozone; parking; particulate matter; Reconstruction projects; Seoul; Socio-economic indicators; socioeconomic status; Spatial correlation analysis; Spatial model; Spatial variables measurement; urbanization
• Online Access: View Fulltext in Publisher

 We analyzed the correlation between air pollution indicators representing the earth changes in urban areas and socio-economic indicators representing human influences in urban areas spatially. This study is meaningful as it spatially represents the correlation between human influences and Earth system changes. Seoul and its surrounding metropolitan area were selected as the case study area, as these areas have experienced urbanization at the same rates depicted in the Great Acceleration graphs of the Anthropocene. Data corresponding to the socio-economic and Earth system change indicators used in the Great Acceleration graphs were collected to create a spatial model. Four cases with different spatial ranges and variables were composed and compared. Of the four cases, the Seoul range model using ground-level ozone rate was observed to have the highest explanatory power. Ground-level ozone rate was highly correlated with air pollutant emissions, number of parking lots, number of residential facilities, and reconstruction projects in urban areas. The model that had used fine particulate matter rate as the dependent variable did not significantly correlate with the explanatory variables. The results from the spatial correlation analysis were meaningful as they may be used to inform policy decisions relating to mitigating changes in the district system in local urban areas. © 2021 The Author(s)