Effectiveness of Particulate Matter Forecasting and Warning Systems within Urban Areas

Yeeun Shin, Suyeon Kim, Jinsil Park, Sang-Woo Lee and Kyungjin An
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Yeeun Shin: Department of Forestry and Landscape Architecture, Konkuk University, Seoul 05029, Korea
Suyeon Kim: Rural Environment & Resource Division, National Institute of Agricultural Sciences, Wanju-gun 55365, Korea
Jinsil Park: Department of Forestry and Landscape Architecture, Konkuk University, Seoul 05029, Korea
Sang-Woo Lee: Department of Forestry and Landscape Architecture, Konkuk University, Seoul 05029, Korea
Kyungjin An: Department of Forestry and Landscape Architecture, Konkuk University, Seoul 05029, Korea

Sustainability, 2022, vol. 14, issue 9, 1-18

Abstract: The close relation between atmospheric pollution and human health has been well documented. Accordingly, various policies have been enacted worldwide to reduce and regulate air pollution, with most countries having established correlated monitoring systems. Notably in South Korea, increasing concerns about particulate matter (PM) concentrations led to the establishment of a nationwide forecasting and warning system in 2014. In this study, the PM trends in South Korea over the past decade were examined, and the correlated social issues were analyzed. In addition, the relationships between PM concentration, the forecasting–warning system, and people’s urban park use were analyzed to assess the efficacy of policy introduction. The results indicated that PM concentrations were an obstacle to outdoor activities, and the PM forecasting–warning system affected urban park use. Whereas the effects of PM forecasting and warning systems have not been sufficiently explored in practical terms in the literature, this study could be significant in proving the validity of environmental policies through the evidence including urban park visitors. This study also suggests future directions for developing PM forecasting and warning systems.

Keywords: particulate matter; PM forecasting; PM warning system; urban park; visitation; big data (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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