2025, Vol.34, No.1

Journal of Environmental Impact Assessment 2024 KCI Impact Factor : 0.6

pISSN : 1225-7184
https://journal.kci.go.kr/kseia

With the recent development of information and communication technology, there has been an increasing demand for the digitalization of environmental impact assessment report and the enhancement of information accessibility within these reports. In response, this study developed a system that automates the operation of the American Meteorological Society and U.S. Environmental Protection Agency Regulatory Model (AERMOD), a key model used for air quality assessments, to support the digitalization of environmental impact assessments. The system is designed to automatically collect basic meteorological data and construct terrain data required for model operation. Additionally, it provides a web-based user interface for inputting emission sources and emission quantities. The consistency between the Linux-based and Windows-based model systems built to operate AERMOD was ensured through this system. This system is expected to produce standardized results during AERMOD modeling and serve as a foundation for the implementation of digital environmental impact assessments.

This study investigates the application of the TNFD (Task Force on Nature-related Financial Disclosures) framework within the context of South Korea, with a particularfocus on how businesses can evaluate their environmental dependencies and impacts, especially in relation to water resource vulnerabilities. Utilizing the LEAP (Locate, Evaluate, Assess, Prepare) approach, the research employs national data systems to conduct a thorough, data-driven risk assessment. The results underscore the value of leveraging domestic data sources, identifying regions like Idong-myeon and Gwanin-myeon as being highly susceptible to prolonged drought risks. In contrast, areas such as Seondang-dong, Soheul-eup, Pocheon-dong, Gasan-myeon, Gunnae-myeon, and Naechon-myeon face heightened risks from flooding. The study highlights that adopting a data-driven methodology allows businesses to better evaluate and address nature-related risks, ultimately supporting more accurate and sustainable decision-making processes. Through this approach, companies can develop more resilient strategies to mitigate the impacts of climate change and ensure long-term sustainability.

With the increasing occurrence of wildlife in urban areas, the coexistence of humans and wildlife has emerged as a critical issue in urban ecosystems. This study aims to analyze public perceptions of wildlife occurrence in Seoul using blog data and derive policy implications based on the findings. Through frequency analysis and network analysis, the most frequently mentioned wildlife species in Seoul were wild boars, raccoon dogs, water deer, crows, and stray dogs. While negative adjectives were frequently associated with wild boars, no nouns related to accidents involving them were found. In contrast, species-specific human-wildlife conflicts were identified, such as roadkill incidents for water deer and rabies concerns for stray dogs. Despite hygiene-related issues, raccoon dogs were perceived as relatively familiar animals. Crows were mainly associated with noise problems, which caused discomfort among citizens, but they were not considered a direct threat. Wild boars, stray dogs, and water deer were frequently mentioned in suburban areas, whereas raccoon dogs were linked to parks and rivers within urban areas. This study emphasizes the necessity of species-specific management policies based on occurrence locations and risk levels. It argues that social media data can serve as a crucial tool for policy approaches to foster urban ecosystems where humans and wildlife can coexist. Integrating large-scale social media data with field-based research could enable the development of effective wildlife management and conservation strategies.