As a result of the rapid growth of international trade, atmospheric pollution from transportation has been more topical than ever, especially in dense hub port-cities. The shipping industry should pay more attention corresponding to its contribution to local atmospheric pollution. This paper supports the application of data collected from the vessel tracking service system with a bottom-up approach to generate a comprehensive 2019 local ship emission inventory at Port of Incheon. The calculated emission inventory presented the dominance of CO₂ emission and the considerable contribution of NO_x and SO_x emissions, the significant contribution of auxiliary engines during the hotelling at berth during the year of 2019. Then, based on calculated emission inventory, this study suggested and simulated applicable green policies in the practice: (1) local emission control area realization, (2) vessel speed reduction program, (3) application of cold ironing, and (4) establishment of a national integrated emission platform. The combination of the three first policies could help reduce the significant volume of emitted CO (29), NO_x (30), SO_x (93), PM10 and PM2.5 (64), VOC (28), NH₃ (30), and CO₂ (30).

The distribution of unmanned parcel lockers is projected to proliferate nationwide significantly as it is promoted by the government for its potential to increase public safety and convenience. This study presents a decision making system that sequentially integrates the processes of finding potential locations, determining the number of locations, and selecting the optimal locations for effective installation of unmanned parcel lockers. First of all, the location requirements including the neighborhood, accessibility, and public facilities in the area are defined. Then, the number of locations and the optimal location are determined using the location set-covering model and the p-median model, respectively. The suitability and effectiveness of the decision making system are verified through an application to a residential complex located in Incheon Metropolitan City in Korea. This study provides guidelines and references for the effective implementation of distributing unmanned parcel lockers and contributes to prevention of violent crimes by impersonating a delivery person and the economic benefit from increased users of the parcel delivery service.

Due to increases in truck traffic, truck traffic safety has become an unavoidable societal issue in Korea. Truck traffic accidents were responsible for 24% of all traffic deaths in 2019, and the fatality rate was significantly higher than that of other forms of traffic. This study analyzes not only the driver and environmental factors, but also the traffic condition factors which are considered to contribute to the severity of truck traffic accidents, and presents practical truck safety solutions based on the findings. This study examines the fatal and serious injury truck traffic accidents in Incheon, which has large logistics facilities and the highest fatality rate (3.3) in Korea’s capital area. According to the regression analysis results, ‘Nighttime’, ‘Vehicle-single’, ‘Vehicle to Pedestrian’, ‘Lane violation’, and ‘Signal violation’ contribute to the severity of truck traffic accidents. Furthermore, truck traffic accidents in the logistics influencing area are more likely to be serious than in the non-influencing area. In terms of the traffic condition factors, the number of lanes, the maximum speed, and the number of road property-changing nodes were significant. The results of this study will provide useful data for establishing traffic safety policies in urban areas.

The neutrophil-to-high-density lipoprotein cholesterol ratio (NHR) has emerged as a promising biomarker for assessing inflammation and lipid dysregulation. Increasing evidence indicates that these metabolic disturbances play a crucial role in the development of metabolic dysfunction-associated steatotic liver disease(MASLD). This study aims to investigate the association between NHR, MASLD, and liver fibrosis. This cross-sectional study analyzed data from the 2017–2020 National Health and Nutrition Examination Survey (NHANES). Weighted multivariate logistic regression models were used to investigate the association between NHR and both MASLD and liver fibrosis. Smoothed curve fitting and threshold effect analysis were performed to detect potential nonlinear relationships. Subgroup analyses were conducted to assess the consistency of these associations across different groups. The study involved 4,761 participants. We observed a significant positive association between NHR and MASLD (OR = 1.20, 95% CI: 1.09–1.31). However, there was no significant association between NHR and liver fibrosis (OR = 1.01; 95% CI: 0.94–1.09). The analysis of smoothed curve fitting and threshold effect revealed an inverted U-shaped relationship between NHR and MASLD, with a turning point at 5.63. Our findings indicate a positive correlation between elevated NHR levels and MASLD prevalence. However, we did not observe a significant association between NHR and liver fibrosis prevalence. Further prospective research is needed to validate these findings in a longitudinal setting.

With the globalization of trade and the rapid development of the world economy, the problem of air pollution emissions produced by shipping is becoming more serious. The exhaust gas emitted by ships has become a significant source of air pollution in ocean and coastal areas. In recent years, governments have paid more attention to shipping emissions as a major source of environmental problems. Establishing ship emission inventories plays an important role in formulating ship emission control measures and regulations. This study aimed to propose a framework for calculating ship air pollutant emissions by comprehensively considering processes and methods officially used in developed countries such as the US and those in the EU, as well as South Korean circumstances and available data sets. The framework was divided into three sections: defining the inventory, data collection and analysis of the data, and ship air pollutant emission estimation. The results of this study provided a standard for South Korean domestic port emission inventories. A case study focused on the Gwangyang and Yeosu Ports, one of the leading port areas in South Korea, using adaptive data collection and emission-calculation processes. This study can be used as guidelines when the Ministry of Oceans and Fisheries (MOF) or the Ministry of Environment (MOE) adopts a standard process in South Korea in the near future. Subsequently, it is necessary to establish a national port emission management system to respond to world environmental changes.

In the face of an unprecedented public health crisis (COVID-19), despite tourist perceptions toward cultural heritage tourism having undergone significant transformation, such transitions are increasingly viewed as opportunities to enhance sustainability practices in cultural heritage tourism worldwide. This study traces the evolution of tourist perceptions at Lijiang Old Town, a UNESCO World Heritage Site, across three stages from 2017 to 2024—before the pandemic, during the pandemic, and after the pandemic. Data were collected from major tourism platforms, yielding a comprehensive dataset of 50,022 user-generated reviews. We adopt a mixed-method framework integrating TF-IDF, Social Network Analysis (SNA), and Latent Dirichlet Allocation (LDA) to identify salient terms, semantic structures, and latent themes from large-scale unstructured textual data across time. The findings indicate that cultural heritage tourism demonstrates adaptability and resilience through significant perceptual transitions. After the pandemic, visitors increasingly prioritized cultural depth and high-quality service experiences, whereas before the pandemic, tourists focused more on cultural heritage attractions and commercial experiences. Moreover, during the pandemic period, visitor narratives reflected adaptations toward quieter, safer, and more personalized experiences, highlighting the impact of safety measures on tourism patterns. These findings demonstrate the methodological potential for dynamically monitoring perception shifts and offer empirical grounding for future perception-oriented research and sustainable cultural heritage destination management practices in cultural heritage tourism toward sustainable tourism.