Investigating the Effects of the Built Environment on PM2.5 and PM10: A Case Study of Seoul Metropolitan City, South Korea

Park, Seung-Hoon; Ko, Dongwon

doi:10.3390/su10124552

Cited by 28 publications

(23 citation statements)

References 31 publications

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“…The level of air pollution in Seoul has been increasing, as mentioned above, and the air pollution caused by the PM fraction has been increasing significantly. The average PM levels in Seoul have increased significantly over the years, and reached more than three times (32 µm/m 3 ) the WHO standard of 10 µm/m 3 for the annual mean both in 2017 and 2018 [38].…”

Section: Social Benefits Of Fine Particulate Matter (Pm) Mitigationmentioning

confidence: 99%

Benefit–Cost Analysis of Green Roof Initiative Projects: The Case of Jung-gu, Seoul

Shin

Kim

2019

Sustainability

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Green roofs, which have various economic, environmental and social effects, have been acknowledged as an alternative green space in urban areas. This study aims to investigate the economic feasibility of green roof projects by conducting a benefit–cost analysis on the case of Jung-gu, Seoul. The analysis estimates and compares five different scenarios applied in the study area with a 20-year operation period in all cases. This set of scenarios aims to compare the most idealistic situation with more achievable and realistic situations, to provide policy implications for green roof initiative projects in Seoul. The analysis consists of estimating six cost items and eight benefit items. Among the benefit items, two non-marketable elements are estimated by the contingent valuation method. The scenario with 100% application of a green roof, has benefits exceeding the costs with a benefit–cost ratio of 1.174. However, the other scenarios with certain prerequisites have a benefit–cost ratio that is very close, but still smaller than 1. Therefore, it is possible to claim that green roof initiative projects are economically viable under specific conditions. However, there are many restrictions to engaging in green roof constructions for entire building rooftops.

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Section: Social Benefits Of Fine Particulate Matter (Pm) Mitigationmentioning

confidence: 99%

Benefit–Cost Analysis of Green Roof Initiative Projects: The Case of Jung-gu, Seoul

Shin

Kim

2019

Sustainability

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“…However, according to the land use data, residential areas showed a significant positive correlation with PM 2.5 concentration in DKI Jakarta. Studies of PM, the correlation have demonstrated high correlation between PM 2.5 level and residential areas, especially in high-density residential areas [29,30].…”

Section: Discussionmentioning

confidence: 99%

PM2.5 Pollutant in Asia—A Comparison of Metropolis Cities in Indonesia and Taiwan

Kusuma

Yu-Ting

et al. 2019

IJERPH

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Air pollution has emerged as a significant health, environmental, economic, and social problem all over the world. In this study, geospatial technologies coupled with a LUR (Land Use Regression) approach were applied to assess the spatial-temporal distribution of fine particulate (PM2.5). In-situ observations of air pollutants from ground monitoring stations from 2016–2018 were used as dependent variables, while the land-use/land cover, a NDVI (Normalized Difference Vegetation Index) from a MODIS sensors, and meteorology data allocations surrounding the monitoring stations from 0.25–5 km buffer ranges were collected as spatial predictors from GIS and remote sensing databases. A linear regression method was developed for the LUR model and 10-fold cross-validation was used to assess the model robustness. The R2 model obtained was 56% for DKI Jakarta, Indonesia, and 83% for Taipei Metropolis, Taiwan. According to the results of the PM2.5 model, the essential predictors for DKI Jakarta were influenced by temperature, NDVI, humidity, and residential area, while those for the Taipei Metropolis region were influenced by PM10, NO2, SO2, UV, rainfall, spring, main road, railroad, airport, proximity to airports, mining areas, and NDVI. The validation of the results of the estimated PM2.5 distribution use 10-cross validation with indicated R2 values of 0.62 for DKI Jakarta and 0.84 for Taipei Metropolis. The results of cross-validation show the strength of the model.

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“…In recent years, with the rapid economic development based on industry and urbanization, serious particle pollution has occurred, especially in metropolitan areas such as Beijing, and has attracted increasing attention from the public, government, and scientific institutions worldwide. The pollution problem is not conducive to the construction of an eco-friendly society and the development of sustainability [1]. The atmospheric particles (particulate matter, PM) have posed a threat to climate change and human health [2][3][4], especially PM 10 and PM 2.5 , which are defined as the particles with aerodynamic diameters of less than 10 µm (PM 10 ) and 2.5 µm (PM 2.5 ), respectively [5].…”

Section: Introductionmentioning

confidence: 99%

The Concentrations and Removal Effects of PM10 and PM2.5 on a Wetland in Beijing

Huang

Guo

et al. 2019

Sustainability

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Particulate matter (PM) is an essential source of atmospheric pollution in metropolitan areas since it has adverse effects on human health. However, previous research suggested wetlands can remove particulate matter from the atmosphere to land surfaces. This study was conducted in the Hanshiqiao Wetland National Nature Reserve in Beijing during 2016. The concentrations of PM10 and PM2.5 on a wetland and bare land in the park, as well as metrological data, were collected during the whole year. Based on the observed data, removal efficiency of each land use type was calculated by empirical models and the relationships between concentrations and metrological factors were also analyzed. The results indicated that: (1) In general, the PM10 and PM2.5 concentrations on the bare land surface were higher than those on the wetland surface, in both of which the highest value appeared at night and evening, while the lowest value appeared near noon. In terms of season, the average concentration of PM10 was higher in winter (wetland: 137.48 μg·m−3; bare land: 164.75 μg·m−3) and spring (wetland: 205.18 μg·m−3; bare land: 244.85 μg·m−3) in general. The concentration of PM2.5 on the wetland surface showed the same pattern, while that on the bare land surface was higher in spring and summer. (2) Concentrations of PM10 and PM2.5 were significantly correlated with the relative humidity (p < 0.01) and inversely correlated with wind speed (p < 0.05). The relationship between PM10 and PM2.5 concentrations and temperature was more complicated—it showed a significantly negative correlation (p < 0.01) between them in winter and spring, however, the correlation was insignificant in autumn. In summer, only the correlation between PM10 concentration and temperature on the wetland surface was significant (p < 0.01). (3) The dry removal efficiency of PM10 was greater than that of PM2.5. The dry removal efficiencies of PM10 and PM2.5 followed the order of spring > winter > autumn > summer on the wetland. This study seeks to provide practical measures to improve air quality and facilitate sustainable development in Beijing.

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Investigating the Effects of the Built Environment on PM2.5 and PM10: A Case Study of Seoul Metropolitan City, South Korea

Cited by 28 publications

References 31 publications

Benefit–Cost Analysis of Green Roof Initiative Projects: The Case of Jung-gu, Seoul

Benefit–Cost Analysis of Green Roof Initiative Projects: The Case of Jung-gu, Seoul

PM2.5 Pollutant in Asia—A Comparison of Metropolis Cities in Indonesia and Taiwan

The Concentrations and Removal Effects of PM10 and PM2.5 on a Wetland in Beijing

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