• Korean Journal of Environment and Ecology
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• v.35 no.5
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• pp.569-575
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• 2021

This study analyzed the effect of forests on reducing particulate matter by investigating the particulate matter concentration and influencing factors between urban forest and traffic forest. The concentrations of particulate matter in Hongreung Experimental Forest (urban forest) and a forest (traffic forest) formed at the intersection of Cheongryangri Station in Dongdaemun-gu, Seoul were measured with the light scattering method instrument from January to November 2018. During the study period, the average PM₁₀ concentrations in the urban forest and the traffic forest were 12.5㎍/m³ and 15.7 ㎍/m³, respectively, and the average PM_2.5 concentrations were 16.6㎍/m³and 6.9 ㎍/m³, respectively. Comparing the concentration by the urban atmospheric measurement network of the Ministry of Environment and the concentration in urban forests showed that the reduction rate of PM₁₀ was 66.9±28.6% in urbanforest and 58.6±44.1% in traffic forest and that of PM_2.5 was 71.3±23.0% and 64.9±31.3%. The difference in the reduction rate of particulate matter is likely related to the size and structure of the urban forest, and the wind velocity is considered the reduction factor.

• Journal of the Korean Institute of Landscape Architecture
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• v.47 no.6
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• pp.67-77
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• 2019

The purpose of this study is to analyze how much particulate matter at the center of the urban park is reduced compared to the entrance of the park, where the particulate matter problem is serious. It also endeavored to analyze the relationship between the space closure rate and particulate matter reduction rate in the center of the park through the collection and analysis of experimental data. Seven flat land type urban neighborhood parks in Suseong-gu, Daegu were measured at the same place for three days. The research results are as follows. First, the center of the urban neighborhood park had an average temperature 1.05℃ lower than at the entrance and an average humidity of 2.57% higher. Second, the rate of fine dust reduction was PM1- 17.09%, PM2.5- 17.65%, PM10- 14.99%. As for the reduction rate of particulate matter, the smaller the size of the park, the greater the reduction rate. In addition, the reduction rate at the center of the park was lower on days when particulate matter concentration based on the weather reports was low. The higher the concentration at the park entrance, the higher the reduction rate was. Third, a higher the rate of space closures at the center of the park resulted in a higher effect of particulate matter reduction. Noting this, the relationship between particulate matter reduction and the space closure rate in urban neighborhood parks was clearly shown. We hope to be the basis for more extensive experimental data collection.

• Journal of Korean Society of Forest Science
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• v.112 no.1
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• pp.1-10
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• 2023

Urbanization and industrialization associated with rapid economic development have resulted in air pollution in urban areas, which adversely affects human health and the environment around the world. Growing awareness of the health effects of airborne particulate matter (PM) has led to the emergence of urban greening as a promising eco-friendly, nature-based solution to reduce the concentration of PM (especially PM_2.5) to which individuals are exposed, thereby promoting public health. In this review, we highlight fundamental insights about PM and recent research on the ability of urban greening to capture PM. Reports from the scientific literature on PM published from 1992 to 2021 were retrieved from Google Scholar. Here, we explore some of the main complex relationships between leaf traits and the ability to retain PM for research or management to optimize greenspaces.

• Journal of the Korean Institute of Landscape Architecture
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• v.49 no.5
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• pp.79-96
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• 2021

Green infrastructure planning represents landscape planning measures to reduce particulate matter. This study aimed to derive factors that may be used in planning green infrastructure for particulate matter reduction using text mining techniques. A range of analyses were carried out by focusing on keywords such as 'particulate matter reduction plan' and 'green infrastructure planning elements'. The analyses included Term Frequency-Inverse Document Frequency (TF-IDF) analysis, centrality analysis, related word analysis, and topic modeling analysis. These analyses were carried out via text mining by collecting information on previous related research, policy reports, and laws. Initially, TF-IDF analysis results were used to classify major keywords relating to particulate matter and green infrastructure into three groups: (1) environmental issues (e.g., particulate matter, environment, carbon, and atmosphere), target spaces (e.g., urban, park, and local green space), and application methods (e.g., analysis, planning, evaluation, development, ecological aspect, policy management, technology, and resilience). Second, the centrality analysis results were found to be similar to those of TF-IDF; it was confirmed that the central connectors to the major keywords were 'Green New Deal' and 'Vacant land'. The results from the analysis of related words verified that planning green infrastructure for particulate matter reduction required planning forests and ventilation corridors. Additionally, moisture must be considered for microclimate control. It was also confirmed that utilizing vacant space, establishing mixed forests, introducing particulate matter reduction technology, and understanding the system may be important for the effective planning of green infrastructure. Topic analysis was used to classify the planning elements of green infrastructure based on ecological, technological, and social functions. The planning elements of ecological function were classified into morphological (e.g., urban forest, green space, wall greening) and functional aspects (e.g., climate control, carbon storage and absorption, provision of habitats, and biodiversity for wildlife). The planning elements of technical function were classified into various themes, including the disaster prevention functions of green infrastructure, buffer effects, stormwater management, water purification, and energy reduction. The planning elements of the social function were classified into themes such as community function, improving the health of users, and scenery improvement. These results suggest that green infrastructure planning for particulate matter reduction requires approaches related to key concepts, such as resilience and sustainability. In particular, there is a need to apply green infrastructure planning elements in order to reduce exposure to particulate matter.

• Korean Journal of Remote Sensing
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• v.38 no.4
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• pp.421-434
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• 2022

Fine particulate matter (PM2.5) has been the biggest environmental problem in Korea since the 2010s. The present study considers the value of urban forests and green infrastructure as an ecosystem service (ES) concept for PM2.5 reduction based on satellite and spatial data, with a focus on Seoul, Korea A method for the spatial ES assessment that considers social demand variables such as population and land price is suggested. First, an ES assessment based on natural environment information confirms that, while the vitality of vegetation is relatively low, the ES is high in the city center and residential areas, where the concentration of PM2.5 is high. Then, the ES assessment considering social demand (i.e., the ESS) confirms the existence of higher PM2.5 values in residential areas with high population density, and in main downtown areas. This is because the ESS of urban green infrastructure is high in areas with high land prices, high population density, and above-average PM2.5 concentrations. Further, when a future green infrastructure improvement scenario that considers the urban forest management plan is applied, the area of very high ESS is increased by 74% when the vegetation greenness of the green infrastructure in the residential area is increased by only 20%. This result suggests that green infrastructure and urban forests in the residential area should be continuously expanded and managed in order to maximize the PM2.5 reduction ES.

• Atmosphere
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• v.28 no.2
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• pp.201-209
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• 2018

Benefits of the next generation geostationary meteorological satellite observation (e.g., GEO-KOMPSAT-2A) are qualitatively and comprehensively described and discussed. Main beneficial phenomena for application can be listed as tropical cyclones (typhoon), high impact weather (heavy rainfall, lightning, and hail), ocean, air pollution (particulate matter), forest fire, fog, aircraft icing, volcanic eruption, and space weather. The next generation satellites with highly enhanced spatial and temporal resolution images, expanding channels, and basic and additional products are expected to create the new valuable benefits, including the contribution to the reduction of socioeconomic losses due to weather-related disasters. In particular, the new satellite observations are readily applicable to early warning and very-short time forecast application of hazardous weather phenomena, global climate change monitoring and adaptation, improvement of numerical weather forecast skill, and technical improvement of space weather monitoring and forecast. Several policy plans for expanding the application of the next generation satellite data are suggested.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.24 no.2
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• pp.57-69
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• 2021

Urban green spaces supply ecosystem services (ESs), which are consumed by city residents and generate demand, to improve air quality. It is important to determine supply and demand for ESs and reduce the gap for efficient management. This study proposed a method to use the concept of supply and demand for ESs in the decision-making process for urban planning or management. PM₁₀ concentrations were converted to weight for demand assessment on PM₁₀ reduction, and PM₁₀ absorption capacity of all green spaces including the forests, and that of urban green spaces excluding forests, was calculated for each supply assessment. The differences in the calculated supply and demand were analyzed to derive the mismatched regions in Suwon. As a result, regions with big forested areas showed sufficient supply, indicating that the degree of mismatch among administrative neighborhoods (dong) varied greatly depending on whether they had a forest. An analysis of only urban green spaces showed that all neighborhoods lacked supply. Forests with high PM₁₀ absorption capacity had a great effect, but urban green spaces can be considered a key element in reducing PM₁₀ in daily life. Considering the mismatch of supply and demand, spatial distribution, and population distribution, it is possible to prioritize the supply of urban green spaces to reduce PM₁₀ and, furthermore, support decision making for priority zones subject to forest conservation and designation and cancellation of green spaces, which gives significance to this study.