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Temporal Changes in Air Quality According to Land-Use Using Real Time Big Data from Smart Sensors in Korea

This study analyzed the changes in particulate matter concentrations according to land-use over time and the spatial characteristics of the distribution of particulate matter concentrations using big data of particulate matter in Daejeon, Korea, measured by Private Air Quality Monitoring Smart Senso...

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Detalles Bibliográficos
Autores principales: Jo, Sung Su, Lee, Sang Ho, Leem, Yountaik
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7664872/
https://www.ncbi.nlm.nih.gov/pubmed/33182238
http://dx.doi.org/10.3390/s20216374
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author Jo, Sung Su
Lee, Sang Ho
Leem, Yountaik
author_facet Jo, Sung Su
Lee, Sang Ho
Leem, Yountaik
author_sort Jo, Sung Su
collection PubMed
description This study analyzed the changes in particulate matter concentrations according to land-use over time and the spatial characteristics of the distribution of particulate matter concentrations using big data of particulate matter in Daejeon, Korea, measured by Private Air Quality Monitoring Smart Sensors (PAQMSSs). Land-uses were classified into residential, commercial, industrial, and green groups according to the primary land-use around the 650-m sensor radius. Data on particulate matter with an aerodynamic diameter <10 µm (PM10) and <2.5 µm (PM2.5) were captured by PAQMSSs from September‒October (i.e., fall) in 2019. Differences and variation characteristics of particulate matter concentrations between time periods and land-uses were analyzed and spatial mobility characteristics of the particulate matter concentrations over time were analyzed. The results indicate that the particulate matter concentrations in Daejeon decreased in the order of industrial, housing, commercial and green groups overall; however, the concentrations of the commercial group were higher than those of the residential group during 21:00–23:00, which reflected the vital nighttime lifestyle in the commercial group in Korea. Second, the green group showed the lowest particulate matter concentration and the industrial group showed the highest concentration. Third, the highest particulate matter concentrations were in urban areas where commercial and business functions were centered and in the vicinity of industrial complexes. Finally, over time, the PM10 concentrations were clearly high at noon and low at night, whereas the PM2.5 concentrations were similar at certain areas.
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spelling pubmed-76648722020-11-14 Temporal Changes in Air Quality According to Land-Use Using Real Time Big Data from Smart Sensors in Korea Jo, Sung Su Lee, Sang Ho Leem, Yountaik Sensors (Basel) Article This study analyzed the changes in particulate matter concentrations according to land-use over time and the spatial characteristics of the distribution of particulate matter concentrations using big data of particulate matter in Daejeon, Korea, measured by Private Air Quality Monitoring Smart Sensors (PAQMSSs). Land-uses were classified into residential, commercial, industrial, and green groups according to the primary land-use around the 650-m sensor radius. Data on particulate matter with an aerodynamic diameter <10 µm (PM10) and <2.5 µm (PM2.5) were captured by PAQMSSs from September‒October (i.e., fall) in 2019. Differences and variation characteristics of particulate matter concentrations between time periods and land-uses were analyzed and spatial mobility characteristics of the particulate matter concentrations over time were analyzed. The results indicate that the particulate matter concentrations in Daejeon decreased in the order of industrial, housing, commercial and green groups overall; however, the concentrations of the commercial group were higher than those of the residential group during 21:00–23:00, which reflected the vital nighttime lifestyle in the commercial group in Korea. Second, the green group showed the lowest particulate matter concentration and the industrial group showed the highest concentration. Third, the highest particulate matter concentrations were in urban areas where commercial and business functions were centered and in the vicinity of industrial complexes. Finally, over time, the PM10 concentrations were clearly high at noon and low at night, whereas the PM2.5 concentrations were similar at certain areas. MDPI 2020-11-09 /pmc/articles/PMC7664872/ /pubmed/33182238 http://dx.doi.org/10.3390/s20216374 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Jo, Sung Su
Lee, Sang Ho
Leem, Yountaik
Temporal Changes in Air Quality According to Land-Use Using Real Time Big Data from Smart Sensors in Korea
title Temporal Changes in Air Quality According to Land-Use Using Real Time Big Data from Smart Sensors in Korea
title_full Temporal Changes in Air Quality According to Land-Use Using Real Time Big Data from Smart Sensors in Korea
title_fullStr Temporal Changes in Air Quality According to Land-Use Using Real Time Big Data from Smart Sensors in Korea
title_full_unstemmed Temporal Changes in Air Quality According to Land-Use Using Real Time Big Data from Smart Sensors in Korea
title_short Temporal Changes in Air Quality According to Land-Use Using Real Time Big Data from Smart Sensors in Korea
title_sort temporal changes in air quality according to land-use using real time big data from smart sensors in korea
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7664872/
https://www.ncbi.nlm.nih.gov/pubmed/33182238
http://dx.doi.org/10.3390/s20216374
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