Seoul Region Research Articles

Exploring the network structure of coupled green-grey infrastructure to enhance urban pluvial flood resilience: A scenario-based approach focusing on ‘centralized’ and ‘decentralized’ structures

Urban pluvial floods pose a significant risk to cities, occurring when precipitation exceeds the carrying capacity of the urban drainage network. Coupled green-grey infrastructure has emerged as a sustainable solution for mitigating urban pluvial floods. This study aims to explore best practices in the network configuration of urban drainage systems coupled with low-impact development (LID) to enhance flow distribution and stormwater infiltration. To do so, we focused on two competing key concepts in network analysis: (1) Centralization and (2) Decentralization. We integrated a one-dimensional stormwater model with a rapid flood spreading model to assess the flood mitigation performance of various centralized and decentralized network configurations in the Gangnam region of Seoul, South Korea. To further assess the combined effects of green and grey infrastructure, we compared the performance of each drainage network configuration with and without identical mixed LID practices. Here we show that the centralized drainage network scenario performed best in reducing flood volume by 40.3%, the decentralized drainage network scenario performed best in shortening flood duration by 47.8%, and the LID practices scenario performed best in mitigating peak flooding rates by 4.2%, each as independent scenarios. When all three scenarios were coupled together, flood volume could be reduced by 73.5%, flood duration by 54.7%, and peak flooding rates by 19.8% in the study area. This exploratory study underscores the potential of network analysis in urban flood research, particularly the effectiveness of loosely-connected network topology. Our findings contribute to the development of best practices for coupled green-grey infrastructure, facilitating sustainable stormwater management and urban flood resilience.

A Study on the Change in Educational Disparities in Elementary and Middle Schools in Seoul region: Focusing on the Influence of Gender and Family Background

A Study on the Change in Educational Disparities in Elementary and Middle Schools in Seoul region: Focusing on the Influence of Gender and Family Background

Demographic Characteristics and Economic Burden of Clostridioides difficile Infection in Korea: A Nationwide Population-Based Study after Propensity Score Matching.

Clostridioides difficile infection (CDI) poses a considerable threat to global public health. However, there have been insufficient propensity score-matched data on its demographic characteristics and economic burden. Using nationwide claims data, we assessed longitudinal changes in the demographic characteristics and economic burden of CDI between 2011 and 2019 after propensity score matching. We performed a regression analysis to compare the differences in the length of hospital stay and medical costs between patients with CDI and controls (gastroenteritis and colitis). The CDI hospitalization rate increased 2.9-fold between 2011 and 2019. The CDI group had higher comorbidity index scores and was more frequently diagnosed at tertiary hospitals and in the Seoul region than the control group (all p < 0.001). The annual incidence rate of CDI/10,000 persons significantly increased in both sexes and all age groups. The length of hospital stay and medical costs were 3.3-fold and 5.0-fold greater, respectively, in the CDI than in the control group (both p < 0.001). Although the length of hospital stay decreased, total medical costs increased in all age groups and both sexes between 2011 and 2019 (all p < 0.001). When compared with the control group, the CDI-attributable length of hospital stay and medical cost were greater by 15.3 days and KRW 3413 (×103), respectively, after matching. In conclusion, CDI incidence, particularly among the elderly population with comorbidities, has been increasing. In addition, the length of hospital stay and total medical costs of the CDI group were greater than those of the control group.

경제범패 전승과 의례 현실 -동주 스님 구술을 통하여-

In this research, I focused on the life and succession of the Gyeongje Beompae through the oral dictation of Ven Dongju, Seoul's Intangible Cultural Heritage No. 43, while at the same time focusing on new related facts and previously misunderstood information. Ven Dongju was born in Onyang, South Chungcheong Province in 1945, and became a monk in 1961, He learned Beompae from instructor Ven Byeogeung, and completed all Yeongsan courses while attending Ven Songam at Bongwonsa Temple in Seoul, in 1967. At this time, a sound recording of Ven Songam's Beompae was included as key content in 『The Posthumous Works of Grand Master Ven Songam in the Korean Buddhist Chant Series 』. Because his father was a monk, he had been familiar with chanting and Beompae while growing up, and had a profound grasp of memorizing Beompae melodies and performing its rituals. Thus his instructor, Songam, had high expectations for him. In 1970, Ven Dongju left to practice Zen meditation and returned to Sajaam temple, Sangdo-dong, Seoul in 1977. Afterwards, he opened a course at the Institute for Ritual and Chanting and taught Beompae to various disciples. In 1993, he founded Hongwon Temple and has trained many disciples there to this day. He dictated what he heard or experienced while attending Beompae master Ven Songam’s classes, in addition to tose of Ven Kim Taeheup, who was a famous scholar and lecturer on Buddhism. Ven Dongju told me about the first Beompae lecture at Okcheon Beomeum Institute in 1969, especially the Beompae transmission circumstances of the western and eastern regions in Seoul at this time. He mentioned the activities of Ven Jeon Uun, who taught Beompae in Hamheung, Gaeseong, and all around Korea before and after liberation from Japanese occupation, He also talked of monk Eungtan from Jingwansa temple who lectured in Hwajangsa Temple in Gaeseong. These facts tell us that Gyeongje Beompae was not only influenced by Gaeseong Beompae, but also, in turn, influenced it. Above all, the fact that monks were active in the fields of Korean traditional music and Buddhist ritual music and had exchanges with traditional Korean musicians was an opportunity to confirm the important basis that Korean traditional music and Beompae are tied by one root.

Exploring optimal deep tunnel sewer systems to enhance urban pluvial flood resilience in the gangnam region, South Korea

Urban pluvial flooding is becoming a global concern, exacerbated by urbanization and climate change, especially in rapidly developing areas where existing sewer systems lag behind growth. In order to minimize a system's functional failures during extreme rainfalls, localized engineering solutions are required for urban areas chronically suffering from pluvial floods. This study critically evaluates the Deep Tunnel Sewer System (DTSS) as a robust grey infrastructure solution for enhancing urban flood resilience, with a case study in the Gangnam region of Seoul, South Korea. To do so, we integrated a one-dimensional sewer model with a rapid flood spreading model to identify optimal routes and conduit diameters for the DTSS, focusing on four flood-related metrics: the total flood volume, the flood duration, the peak flooding rate, and the number of flooded nodes. Results indicate that, had the DTSS been in place, it could have reduced historical flood volumes over the last decade by 50.1–99.3%, depending on the DTSS route. Regarding the conduit diameter, an 8 m diameter was found to be optimal for minimizing all flood-related metrics. Our research also developed the Intensity-Duration-Frequency (IDF) surfaces in three dimensions, providing a correlation between simulated flood-related metrics and design rainfall characteristics to distinguish the effect of DTSS on flood risk reduction. Our findings demonstrate how highly engineered solutions can enhance urban flood resilience, but they may still face challenges during extreme heavy rainfalls with a 80-year frequency or above. This study contributes to rational decision-making and emergency management in the face of increasing urban pluvial flood risks.

아파트 가격의 파급효과 분석 - VECM을 중심으로

This paper investigates the spillover effects of apartment prices. The transaction price index was used to estimate the connectedness among the five major regions of Seoul and among Seoul and six major metropolitan cities. In particular, considering the cointegration relationship between housing price indices, we apply the VECM model and estimate the connectedness by focusing on the southeast region of Seoul, which is generally accepted to play an important role in the domestic housing market. The sample period is from January 2006 to September 2022. The main findings are as follows. First, a cointegration relationship exists among regions in Seoul and among Seoul and the six metropolitan cities. In particular, we found that the spillover effects among housing markets are underestimated when using the first differenced-VAR model instead of VECM in situations where cointegration exists. Second, the southeast region of Seoul has been the most influential market in Korea. Third, the rolling sample analysis revealed increased interdependence among housing markets after the outbreak of the COVID-19 pandemic.

아파트의 역전세에 영향을 미치는 요인에 관한 연구

This study focuses on the capital region to identify the factors that influence the recent socially problematic trend of apartment flipping. Specifically, this study examines the causes of the reversal trend in apartment buildings in three regions: the Seoul metropolitan area, the Seoul region, and the Gyeonggi-do region, categorized by real estate characteristics, macroeconomic characteristics, environmental characteristics, and timing characteristics. The data used in this study is an unbalanced panel. The entity data consisted of 59 observations in the Seoul metropolitan area, 25 in Seoul, and 26 in Gyeonggi Province, and 103 time series from April 2015 to October 2023. The main results of the analysis are as follows. In terms of environmental characteristics, we find that the implementation of the three housing lease protection laws reduces the Chonsei deposit default, which is identical to Models 1 (Seoul metropolitan area), 2 (Seoul), and 3 (Gyeonggi). After the Ukraine-Russia war, Model 2 shows an increase in apartment Chonsei default, while Models 1 and 3 show a decrease in apartment Chonsei default. The different signs suggest that the interest rate effect is stronger in Seoul. In comparison, the effect of supply shortage due to the surge in commodity prices is stronger in the Seoul metropolitan area and Gyeonggi province. In the case of COVID-19, Model 2 shows the decrease in the apartment Chonsei default due to increased money supply and decreased interest rates. Model 1 (Seoul metropolitan area) and Model 3(Gyeonggi) region generated an apartment Chonsei default because the liquidity was concentrated in Seoul, the largest investment destination due to COVID-19, the rental rate decreased in Gyeonggi-do, which increased the Chonsei default. Regarding timing characteristics, the 2023 dummy has a positive effect. The renters in the Seoul Metropolitan Area, Seoul, and Gyeonggi Province all signed Chonsei contracts in 2021, when the Chosei deposit was the highest. In 2022, the growth of apartment Chonsei deposits stagnated. In January 2023, apartment Chonsei deposits began to decline, leading to the phenomenon of apartment Chonsei deposit default, and as of November 2023, the Chonsei default phenomenon is intensifying.

Chemical composition and source apportionment of PM2.5 in Seoul during 2018–2020

Air pollution, particularly high ambient particulate matter (PM) concentrations, poses a serious public health concern in South Korea. This study analyzed 139 daily PM2.5 samples collected from an urban site in Seoul between March 2018 and January 2020. This study aimed to quantify the chemical composition of PM2.5 and identify the source characteristics. The average PM2.5 mass concentration for the entire study period was 25.3 μg m−3. The chemical composition was dominated by ionic particles (13.2 μg m−3, 52%), carbonaceous particles (7.0 μg m−3, 28%), and trace elements (0.5 μg m−3, 2%). The Positive Matrix Factorization (PMF) model was employed to identify PM2.5 sources using quality-controlled sampling data after eliminating factors that could adversely affect the modeling. Seven sources were resolved through PMF, applying a trial-and-error method to determine the optimal number of sources. The PMF modeling results indicated that secondary sulfate (28%) was the largest contributor, followed by internal factors (23%), secondary nitrate (19%), soil (14%), biomass burning (9%), and aged sea salt (7%). As an additional case study, the analysis of backward trajectories for the winter of 2018, which had the highest PM2.5 concentrations, revealed that the air current carrying PM2.5 had passed from the northwest region of Seoul. Particulary, source identification for this winter case resulted in the highest secondary nitrate across all study periods. This more specific interpretation of the pollutant characteristics of PM2.5 in Seoul could aid in developing effective control strategies and policies for air pollution mitigation.

Factors associated with different types of freight crashes: A macro-level analysis

Introduction: Despite evidence showing higher fatality rates in freight-related crashes, there has been limited exploration of their spatial distribution and factors associated with such distribution. This gap in the literature primarily stems from the focus of existing studies on micro-level factors predicting the frequency or severity of injuries in freight crashes. The present study delves into the factors contributing to freight crashes at the neighborhood level, particularly focusing on different types of freight crashes: collisions involving a freight vehicle and a passenger vehicle, crashes between freight vehicles, and freight vehicle–non-motorized crashes. Method: This study analyzes traffic crash data from the urbanized region of Seoul, collected between 2016 and 2019. To effectively deal with spatial autocorrelation and model different types of crashes in a unified framework, a Bayesian multivariate conditional autoregressive model was employed. Results: Findings show substantial differences in the factors associated with various types of freight crashes. The predictors for crashes between freight vehicles diverge significantly from those for freight vehicle–non-motorized crashes. Crashes between freight vehicles are relatively more influenced by road network structure, while freight crashes involving non-motorized users are relatively more affected by the built environment and freight facilities than the other crash types examined. Freight vehicle–passenger vehicle crashes fall into an intermediate category, sharing most predictors with either of the other two types of freight crashes. Conclusions and Practical Applications: The findings of this study offer valuable lessons for transportation practitioners and policymakers. They can guide the formulation of effective land use policies and infrastructure planning, specifically designed to address the unique characteristics of different types of freight crashes.

Analyzing the Factors that Affect and Predict Employment Density Using Spatial Machine Learning: The Case Study of Seoul, South Korea

There is a regional disparity in the employment density of Seoul. Considering problems such as traffic congestion and jobs‐housing imbalance, it is important to understand the spatial pattern of employment density and identify key influencing factors to determine the changes in the future urban spatial structure. This study analyzed employment density in each region of Seoul to derive important predictors. We examined the spatial patterns of employment density and evaluated the effects of spatial and nonspatial factors based on the general model and the spatial heterogeneity model. To predict the distribution of employment density, we used two statistical models (i.e., ordinary least squares regression [OLS] and geographically weighted regression [GWR] models) and two machine learning models (i.e., the random forest [RF] and geographically weighted random forest [GWRF] models). The results showed that the key influencing factors were the number of corporate business companies, number of main and attraction facilities, accessibility to subway stations, areas of commercial and industrial districts, and distance to business districts.

서울 동남권과 경기 남부지역 신도시 아파트 가격변동 특성 비교 연구

Recognizing the importance of the housing market in the Seoul metropolitan area, this study conducted a time series study based on the theory of the housing submarket in the southern part of Gyeonggi-do apartment markets in the metropolitan area in terms of diversity in research. The main research results derived from the empirical analysis results are as follows. First, through the Grandeur causality test, the sale price of apartments in the southeastern part of Seoul was confirmed as the cause variable, and the sale price of apartments in Bundang, Pangyo, Gwanggyo, and Dongtan was confirmed as the result variable, and the causal relationship existed. Second, through the results of shock response analysis and variance decomposition analysis, it was found that apartment sales prices in Bundang, Pangyo, Gwanggyo, and Dongtan were greatly affected by the southeastern region of Seoul. Third, the results of impact response analysis and distributed decomposition analysis showed that the four regions of Bundang, Pangyo, Gwanggyo, and Dongtan had a mutual influence relationship. The research results showed how the housing market in the Seoul metropolitan area changed until 2022 after the long-term recession after the global financial crisis in late 2008, and the significance of the study was found in that it confirmed the relationship between regions in southern Gyeonggi Province.

Decomposing structural changes of production network for electronics industry in Northeast Asia regions in the 2010s

ABSTRACT This article analyzes structural changes of regional production network (RPN) for the electronics industry across 20 Northeast Asia regions for the period 2005–2015. We develop an extended Structural Decomposition Analysis approach which decomposes changes in Vertical Specialization (VS) share into seven components of foreign intermediate suppliers, input composition, and import intensity in terms of the import structure; and production structure, trade balance, trade openness, and domestic demand in terms of the export one. The development of production fragmentation in Northeast Asia’s electronic industry was associated with the coexistence of nine subregional patterns, including four VS patterns of Coastal China, Inland China, North China, and Central China; four vertical integration (VI) patterns of Northeast Japan, Central Japan, Seoul region, and Busan region. The substantial increases in the VS of North China and Central China result from changes in domestic demand and production structure, while the decline in the VS in Central Japan and Busan region is influenced by the shifts in import intensity and trade openness.

아파트 실거래가를 기반한 전월세전환율의 영향요인 분석

This study examines the theoretical assumptions and previous studies on the factors affecting the conversion rate for Jeonse to Monthly Payment and conducts an empirical analysis of the determinants of the conversion rate for Jeonse to Monthly Payment. The study covers three regions in Seoul of Gangnam (Seocho-gu, Gangnam-gu, and Songpa-gu) and three regions in Seoul (Gangdong-gu, Yangcheon-gu, and Nowon-gu), which are the most active areas for apartment sales, rental, and leasing transactions. In order to empirically analyze the determinants of the conversion rate for Jeonse to Monthly Payment, this study uses the SVAR model based on theoretical constraints between variables, a methodology developed by Lee (2008). The main influencing factors of the conversion rate for Jeonse to Monthly Payment are the 3-year government bond yield, the conversion rate for Jeonse to Monthly Paymentby region, real estate market consumer sentiment index, and mortgage loan amount. The variables except for the real estate market sentiment index had an impact on the sublease conversion rate. By region, the effect was different, with the conversion rate for Jeonse to Monthly Payment in 3 regions (Gangdong-gu, Yangcheon-gu, and Nowon-gu) responding more strongly than in 3 regions (Gangnam (Seocho-gu, Gangnam-gu, and Songpa-gu).

아파트 실거래가를 기반한 전월세전환율의 영향요인 분석

This study examines the theoretical assumptions and previous studies on the factors affecting the conversion rate for Jeonse to Monthly Payment and conducts an empirical analysis of the determinants of the conversion rate for Jeonse to Monthly Payment. The study covers three regions in Seoul of Gangnam (Seocho-gu, Gangnam-gu, and Songpa-gu) and three regions in Seoul (Gangdong-gu, Yangcheon-gu, and Nowon-gu), which are the most active areas for apartment sales, rental, and leasing transactions. In order to empirically analyze the determinants of the conversion rate for Jeonse to Monthly Payment, this study uses the SVAR model based on theoretical constraints between variables, a methodology developed by Lee (2008). The main influencing factors of the conversion rate for Jeonse to Monthly Payment are the 3-year government bond yield, the conversion rate for Jeonse to Monthly Paymentby region, real estate market consumer sentiment index, and mortgage loan amount. The variables except for the real estate market sentiment index had an impact on the sublease conversion rate. By region, the effect was different, with the conversion rate for Jeonse to Monthly Payment in 3 regions (Gangdong-gu, Yangcheon-gu, and Nowon-gu) responding more strongly than in 3 regions (Gangnam (Seocho-gu, Gangnam-gu, and Songpa-gu).

The microbiota in feces of domestic pigeons in Seoul, Korea

In Korea, feral pigeons pose significant public health risks because they carry various zoonotic pathogens. Human population density is a significant factor in zoonotic disease events. Seoul is one of the largest cities by population density among developed countries and where most of the homeless population in Korea exists. We designed this study to compare the microbiota of pigeon feces by regional characteristics and the presence of homeless individuals. Therefore, this study used 16S rRNA amplicon sequencing to detect possible pathogenic microbes and assess the current risk of zoonosis in Seoul, South Korea. Pigeon fecal samples (n = 144) obtained from 19 public sites (86 and 58 fecal samples from regions in and outside Seoul, respectively) were examined. Potentially pathogenic bacteria were also detected in the fecal samples; Campylobacter spp. was found in 19 samples from 13 regions, Listeriaceae was found in seven samples, and Chlamydia spp. was found in three samples from two regions. Principal coordinates analysis and permutational multivariate analysis of variance revealed a significant difference in bacterial composition between the regions in Seoul (n = 86) and outside Seoul (n = 58) and between the regions with (n = 81) and without (n = 63) homeless individuals. Overall, this study identified various potentially pathogenic microorganisms in pigeon feces at public sites in South Korea. Moreover, this study demonstrates that the microbial composition was influenced by regional characteristics and homelessness. Taken together, this study provides important information for public health strategic planning and disease control.

지역난방 적용 공동주택의 동절기 급탕 사용패턴과 열손실 분석

In this study, consumption pattern and heat loss of hot water of a 84 m² floor area apartment located in the western region of Seoul using district heating as heat source were analyzed for winter season. Measurement systems for measuring temperatures and flow rates of hot water, indoor and ambient temperature and humidity, temperature and humidity of pipe shaft and heat fluxes of pipe shaft wall were installed and measurements were taken for a whole year from November, 2013 to October, 2014. Measurement results showed that hot water consumption was the highest between 6:00 and 9:00 in the morning and 19:00 and 22:00 in the evening. Average hot water consumption for five months (November-March) in winter season was 14 kWh/house during peak 6 hours, three hours in the morning and three hours in the evening. As a result of analyzing hot water consumption and heat loss rate according to average outdoor temperature in winter, hot water consumption in February was the highest at 15.5 kWh/house during peak 6 hours and heat loss rate was 5.1%. Hot water consumption in November was the lowest at 11.6 kWh/house during peak 6 hours and the heat loss rate was 4.6%.

서울시 5대 권역 주택매매가격 변동성과 이전효과

서울시 5대 권역 주택매매가격 변동성과 이전효과

서울시 학교 주변의 식품환경과 청소년 식생활 및 비만 관련성

Objectives: The obesity rate among adolescents in Korea is continuously increasing. This study aimed to examine the relationship between dietary habits and obesity in Korean adolescents by focusing on the food environment around schools in Seoul. Methods: We used data from the 2020 Korea Youth Risk Behavior Survey and 2021 administrative data. In total, 7,691 middle and high school students from four regions in Seoul were included. Multilevel logistic regression analysis was performed to examine the effects of individual level and food environment factors around schools affecting adolescent obesity. Results: Adolescents in the southeastern region of Seoul had higher fruit intake and lower obesity rate compared to others. As a result of multilevel logistic regression analysis, sex and school had a significant effect on adolescent obesity in individual level factors. In school level factors, the number of convenience stores and fast food restaurants around the schools had a significant effect on adolescent obesity. Conclusion: The food environment around schools influenced adolescent dietary habits and obesity in that they spend most of their time in schools. Based on the results, there is need for ordinance enactment and promotion of related policies on improving the food environment around schools to form proper adolescent dietary habits and reduce Korean adolescent obesity.

Effect of Redevelopment Project District Characteristics on Neighboring Housing Prices

This study analyzed the impact of nearby redevelopment project characteristics on the apartment and single/multi-family house prices in all areas of Seoul. The impact of the distance to the redevelopment project area, the number of supply households, and the number of project areas were analyzed using the housing sale transaction price from 2006 to 2020, and all housing types show the same direction. Findings reveal that the closer the supply of households, the higher the transaction price. Moreover the number of project areas has a positive effect after a certain distance. This indicates a positive effect on factors such as price synchronization when new houses are supplied from nearby project areas, expectations as project candidates, and shares in the benefits of improving the residential environment. Redevelopment projects are likely to be used as large-scale housing supply assurance measures in the future. When designing an area, one must consider planning and progress by region so that the size, number of union members, and maintenance infrastructure ratio do not significantly impact the housing market. This study obtained general results for all regions in Seoul, yielding important policy implications and providing useful basic data to investors, public policymakers, and practitioners.

지체장애인의 다차원적 경험회피와 건강증진행위의 구조적 관계

The purpose of this study is to examine the structural relationship between multidimensional experience avoidance and health promotion behaviors of physically handicapped people. In order to achieve the purpose of this study, data were collected from 170 persons with physical disabilities living in five regions of Seoul, Gyeonggi, Chungcheong, Jeolla, and Gyeongsang. For the collected data, frequency analysis, exploratory factor analysis, reliability analysis, confirmatory factor analysis, and structural equation model analysis were performed using SPSS 22.0 and AMOS 22.0 programs. the results are as follow. First, pain tolerance, a sub-factor of experience avoidance, was found to have a positive (+) effect on interpersonal relationships and physical activity, which are sub-factors of health promoting behavior. Second, pain aversion, a sub-factor of experience avoidance, was found to have a negative (-) effect on interpersonal relationships and physical activity, which are sub-factors of health promotion behavior. Third, suppression and denial, which are sub-factors of experience avoidance, were found to have a positive (+) effect on health management and physical activity, which are sub-factors of health promotion behavior. Fourth, distraction and inhibition, which are sub-factors of experience avoidance, were found to have a positive (+) effect on health management, interpersonal relationships, and physical activity, which are sub-factors of health promotion behavior. Fifth, delayed behavior, a sub-factor of experience avoidance, was found to have a negative (-) effect on physical activity, a sub-factor of health promoting behavior. Sixth, it was found that avoidance behavior, a sub-factor of experience avoidance, did not affect all sub-factors of health promotion behavior.