TY - GEN
T1 - Spatial and aspatial clustering analysis of PM2.5 concentrations in Temuco, Chile using mobile measurements
AU - Blazquez, Carola A.
AU - Montero, Elizabeth
N1 - Funding Information:
Authors want to thank to Dr. Pablo Ruiz from Public Health School at Universidad de Chile and Dr. Mar?a Elisa Quinteros from Universidad de Talca for providing the mobile PM2.5 measurement data.
Publisher Copyright:
© 2020 Latin American and Caribbean Consortium of Engineering Institutions. All rights reserved.
Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2020
Y1 - 2020
N2 - Air pollution due to wood burning produces severe health and environmental problems. Clustering methods are needed to estimate PM2.5 exposures, and identify locations with high PM2.5 concentrations. This study performed a spatial and aspatial clustering analysis of PM2.5 pollutant collected in a mobile campaign in the conurbation of Temuco and Padre Las Casas, Chile. The Getis Ord G∗i statistic was employed to obtain spatial variability of PM2.5 concentrations, and a K-Means clustering method was used to group PM2.5 concentrations with a aspatial perspective. In addition, an integrated spatial and aspatial clustering approach was implemented with the PM2.5 concentration and measurement spatial location. The comparison results suggest that integrating the spatial and aspatial clustering methods yield high quality partitions when considering spatial information.
AB - Air pollution due to wood burning produces severe health and environmental problems. Clustering methods are needed to estimate PM2.5 exposures, and identify locations with high PM2.5 concentrations. This study performed a spatial and aspatial clustering analysis of PM2.5 pollutant collected in a mobile campaign in the conurbation of Temuco and Padre Las Casas, Chile. The Getis Ord G∗i statistic was employed to obtain spatial variability of PM2.5 concentrations, and a K-Means clustering method was used to group PM2.5 concentrations with a aspatial perspective. In addition, an integrated spatial and aspatial clustering approach was implemented with the PM2.5 concentration and measurement spatial location. The comparison results suggest that integrating the spatial and aspatial clustering methods yield high quality partitions when considering spatial information.
KW - Clustering
KW - Getis-Ord G
KW - K-Means
KW - Mobile measurements
KW - PM2.5 concentrations
UR - http://www.scopus.com/inward/record.url?scp=85096796798&partnerID=8YFLogxK
U2 - 10.18687/LACCEI2020.1.1.528
DO - 10.18687/LACCEI2020.1.1.528
M3 - Conference contribution
AN - SCOPUS:85096796798
T3 - Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology
BT - 18th LACCEI International Multi-Conference for Engineering, Education Caribbean Conference for Engineering and Technology
PB - Latin American and Caribbean Consortium of Engineering Institutions
T2 - 18th LACCEI International Multi-Conference for Engineering, Education Caribbean Conference for Engineering and Technology: "Engineering, Integration, and Alliances for a Sustainable Development" "Hemispheric Cooperation for Competitiveness and Prosperity on a Knowledge-Based Economy", LACCEI 2020
Y2 - 27 July 2020 through 31 July 2020
ER -