Analysis of the Thermal Environment around an Urban Green Area in Seoul, Korea Using Climate Analysis Seoul (CAS)

Abstract

Climate Analysis Seoul (CAS) which provides gridded data relevant for thermal assessment was applied to one of the urban green areas, the Seonjeongneung, in Seoul, Korea. The thermal environment in the Seonjeongneung was evaluated from the CAS simulation for the five heat-wave issued cases during the last five years (2011~2015). The CAS has been improved continuously since it was developed. An updated version with a higher resolution of the CAS simulation domain and an addition of the vegetation information was used in this study. The influence of vegetation in the Seonjeongneung is estimated through the amount of the cold air generation (Q ca ) and air temperature deviation at each grid points, which are calculated by incorporating Geographic Information System (GIS) analysis on the simulation domain and meteorological analysis with the METeorology and atmospheric PHOtochemistry mesoscale MODel (MetPhoMod) in the CAS. The average amount of the cold air generation (Q ca ) at the Seonjeongneung is about 25.5 m 3 m −2 h −1 for the whole cases, and this value is similar to the ones in a forest or a well-wooded region. The average value of the total air temperature deviation (TD) is −2.54 o C at the Seonjeongneung for the five cases. However, this cooling effect of the urban green area disappeared when the region is replaced by high-rise buildings in the CAS simulation. The Q ca drastically decreases to about 1.1 m 3 m −2 h −1 and the average TD shows an increase of 1.14 o C for the same events. This result shows that the vegetation in the Seonjeongneung supposes to keep down temperature during the heat-wave issued day and the average cooling effect of the green region is 3.68 o C quantitatively from the TD difference of the two simulations. The cooling effect represented with the TD difference is larger than 0.3 o C within 200 m distance from the boundary of the Seonjeongneung. Further improvements of the thermodynamical and advection processes above the model surface are required to consider more accurate assessment of the cooling effect for the urban green area.

Network Analysis on Green Technology in National Research and Development Projects in Korea

“…Social network analysis (SNA) has been increasingly used in fields of social science such as psychology, sociology, economics, and innovation studies. SNA applies network and graph theory to investigate social relations between people or objects [19,20,[42][43][44][45]. In the field of GT, several studies have used SNA, for example to observe specialized GTs, emerging GT fields, and clusters in GT in green-tech firms in San Francisco, New York City, and London [19].…”

“…This study uses SNA that considers the co-occurrence of keywords [1,46] and centrality [43,45]. Co-occurrence analysis is used to generate a matrix of relationships between pairs of keywords for further network analysis and visualization.…”

“…Co-occurrence analysis is used to generate a matrix of relationships between pairs of keywords for further network analysis and visualization. Co-occurrence analysis identifies pairs of nodes (keywords in this study) that co-occur in a defined group of a network [43,47]. We calculated the co-occurrence frequency of pairs of keywords in the same R&D project.…”

“…To observe the status and change of keywords, we adopted three basic centrality indices: degree, closeness, and betweenness [45]. Centrality quantifies the importance or influence of a specific object within a network [43,45,47,48].…”

“…Degree centrality counts the number of connections to other nodes in the network; the power and importance of a node in the network increases with its degree centrality [43,45]. To easily compare with other types of centrality, we standardized degree centrality by dividing it by the total number of nodes, not including the node considered.…”