Identifying Particulate Matter Variances Based on Environmental Contexts: Installing and Surveying Real-Time Measuring Sensors

Eunseo Shin, Yeeun Shin, Suyeon Kim, Sangwoo Lee and Kyungjin An ()
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Eunseo Shin: Department of Forestry and Landscape Architecture, Konkuk University, Seoul 05029, Republic of Korea
Yeeun Shin: Department of Forestry and Landscape Architecture, Konkuk University, Seoul 05029, Republic of Korea
Suyeon Kim: Rural Environment & Resource Division, National Institute of Agricultural Sciences, Wanju-gun 55365, Republic of Korea
Sangwoo Lee: Department of Forestry and Landscape Architecture, Konkuk University, Seoul 05029, Republic of Korea
Kyungjin An: Department of Forestry and Landscape Architecture, Konkuk University, Seoul 05029, Republic of Korea

Land, 2023, vol. 12, issue 4, 1-15

Abstract: Previous research suggests that there should be environmental solutions for the emerging health threats caused by poor air quality, such as particulate matters (PM, including PM 2.5 and PM 10 ). Research related to air quality (measured by PM) using land-use regression and geographically weighted regression shows some patterns among different environmental contexts which could reduce the threats from such elements; however, there is little concrete evidence for such threats. To fill this research gap, this study installed real-time PM sensors at human breathing heights at five locations in Seoul, South Korea, and recorded the PM values collected between November 2021 and January 2023. Three-phase time-series analyses were conducted on the collected data. Lower levels of PM concentration were found in more enclosed spaces. In particular, when a space was surrounded by vegetation, the air quality significantly increased. The purpose of this study is to explore variations in air quality, particularly PMs densities, in different types of land use within urban areas such as Seoul. Greater metropolitan areas such as Seoul have a great number of health problems caused by air quality. This study’s results contribute to policy and decision-making in urban design to tackle such problems and to provide spatial guidelines for public health and welfare.

Keywords: environmental context variance; land-use regression; geographically weighted regression; particulate matter; PM 10; PM 2.5 (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2023
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