Vehicle indoor air quality is determined by the complex interaction between interior material emissions (such as VOCs and aldehydes) and road-sourced pollutants. Despite growing public concern, existing frameworks often focus on single pollutants and lack a comprehensive health-impact-based evaluation. This study proposes the Vehicle Indoor Air Quality Index (VIAQI), which integrates acute, chronic, and odor-related exposures from internal sources with the infiltration of ambient air pollutants. The VIAQI adopts a safety-oriented priority (HQacute → SF → OA → HQchronic), reflecting the driver’s cognitive safety. It consists of 10 levels, ranging from Grade 1 (Excellent) to Grade 10 (Hazardous). Under three operating modes (AM, PM-6 hr, and DM), the analysis includes 21 chemical substances, as well as PM2.5 and NO2. Acute risks are assessed using OEHHA’s RELs, chronic risks via US EPA’s RfC, odor effects are quantified using a smell sensitivity index (SF), and outdoor air infiltration is evaluated through a weighted hazard index (OA). After evaluating actual new vehicles, Vehicles A, C, and D are categorized as Grade 3 (Good), while Vehicle B is categorized as Grade 9 (Very Unhealthy) and Vehicle E is categorized as Grade 10 (Hazardous). Notably, Vehicle B is rated Grade 9 due to acute toxicity risks identified through RELs-based assessment, even though it meets all current national regulatory standards. This highlights the existence of health hazards that conventional concentration-based regulations may overlook. As Korea’s first multi-dimensional evaluation system for vehicle air quality, the VIAQI offers a practical tool for manufacturers to implement quality control, set policy, and communicate consumer information, providing a proactive assessment based on real-world driving environments.

농촌은 인구감소, 고령화, 정주환경 악화 등으로 위기를 맞고 있다. 본 연구는 이러한 문제에 대응하 기 위해 농촌공간 회복력을 정량적으로 평가하기 위한 농촌재생지수를 개발하고 농촌지역에 적용 하였다. 이를 위해 농촌회복력 평가를 지표를 선정하고 시계열 자료를 활용하여 적응요소와 쇠퇴 요소로 구분하고 정규화, 증감률 분석, 지수화를 통해 농촌재생지수를 도출하였다. 대상지인 충청 남도 부여군과 당진시에 대한 농촌재생지수를 분석한 결과, 두 지역 모두 재생지수가 지속적으로 감소하는 경향을 보여 회복력이 약화되고 있음을 확인할 수 있었으며 주요 원인은 고령인구 증가와 노후주택 비율 상승인 것으로 나타났다. 부여군은 지속적으로 낮은 재생지수를 보인 반면 당진시 는 상대적으로 높은 재생지수를 보이다가 2021년부터는 부여군과 유사하게 낮은 회복력 기준인 1 이하의 값을 보였다. 본 연구를 통해 농촌지역에 대한 회복력을 시계열적이고 정량적으로 분석하 여 향후 농촌공간계획 정책 수립의 기초자료로 활용될 수 있을 것으로 보인다.

Lentic ecosystems, including lakes, reservoirs, and marshes, are vital ecological assets increasingly threatened by anthropogenic pressures, necessitating robust tools for assessing their biological integrity. This study aimed to develop and apply an aquatic plant-based Multi-metric Index (MMI) to evaluate the biological integrity of 90 lentic systems (primarily lakes and reservoirs) across the Republic of Korea, using a standardized dataset from a three-year national monitoring program (2022~2024). We selected eight metrics based on their ecological relevance, sensitivity to disturbance, and scientific robustness. These were organized into three categories: Species richness (30% weight), eutrophication and disturbance (30%), and habitat integrity (40%). Scoring criteria for each metric were established using cumulative distribution functions, and the final MMI scores were used to classify the ecosystems into five integrity classes (A: Excellent to E: Very Poor). The assessment revealed that the majority of the surveyed ecosystems (87.8%) were in a moderate to slightly poor state (Classes B, C, and D), with only 4.4% classified as excellent. Widespread loss of submerged and floating leaved aquatic plants suggests that many domestic lentic systems may be approaching or have already undergone a regime shift to a turbid, phytoplankton-dominated state. This MMI provides a scientifically-defensible tool for managing lentic ecosystems, underscoring the urgent need to restore aquatic plants communities by improving underwater light conditions and rehabilitating littoral habitats.

This study was conducted to develop a fish-based Multi-metric Index (MMI) for assessing the ecological health of lake ecosystems using fish assemblage data collected from the national lake biomonitoring program between 2022 and 2024. A total of 34 fish assessment metrics widely used in the United States, Europe, and Korea were first reviewed for applicability, from which 16 candidate metrics were selected. These candidate metrics were then evaluated in terms of statistical distribution characteristics, correlations with water quality variables, redundancy among metrics, and consistency with existing river-based metrics used in Korea. Based on these evaluations, eight core indicators and four supporting indicators were finalized. For ecological health scoring, boundary values for metric scoring classes were determined using percentiles (10-25-50-75-90%), and metric weights were applied to ensure balanced contribution and discriminative power among classes. The final set of metrics consisted of three indicators in the Diversity/Richness category, two in the Trophic category, two in the Tolerance category, and one in the Individual Health category, collectively reflecting the ecological responses of fish assemblages in lake environments. The developed MMI framework is expected to provide a robust and applicable tool for future ecological assessments and management of lakes in Korea.

This study presents a modified version of the Lake Benthic Macroinvertebrate Multimetric Index (LBMMI) originally proposed by Park et al. (2024) in Korea. Among the six core metric elements of LBMMI, two elements-total number of taxa and the proportion of predator taxa-were excluded, as they were considered to be strongly influenced by vascular hydrohytes following eutrophication. The revised LBMMI was constructed using the remaining four metrics: Pielou’s evenness index, proportion of insect taxa, individual proportion of oligochaetes and chironomids with blood tubules, and proportion of clinger taxa. Compared to the original LBMMI, the modified index showed approximately a 6% improvement in explanatory power for the first principal component (PC 1) in principal component analysis of environmental factors, and it also exhibited a broader range of discrimination. These results suggest that the modified LBMMI can be more effectively utilized for environmental assessment of lake ecosystems.

Zooplankton are dominant pelagic consumers in lake ecosystems with high population and biomass. Their broad geographical distribution, ease of quantification, and rapid responses to abiotic environmental factors, such as eutrophication, acidification, and climate change, make them highly suitable as indicator organisms for assessing lake ecosystem health. The multi-metric index (MMI) provides an effective framework for capturing the complex responses of biological communities to varying environmental stressors, making it a valuable approach for improving the practical effectiveness of lake ecosystem management based on biological assessments. This study introduces the Lake Zooplankton Assessment Index (LZAI), developed for 90 lakes in South Korea. The LZAI comprises four components: a sensitive species index based on cladocerans, a eutrophication index based on rotifers, a food web index based on copepods, and a habitat index based on species diversity. Applying the LZAI to 90 lakes showed that lake grades followed a normal distribution regardless of sampling season, though A-grade and E-grade lakes exhibited greater seasonal variability. When compared with the clustering results based on zooplankton community composition, the LZAI closely reflected the underlying patterns in community structure. However, in brackish lakes-where population densities are lower and Calanoida copepods dominate relative to freshwater lakes-the M1 and M4 indices were consistently low, while M2 and M3 were high. This suggests that the LZAI requires index adjustments tailored to regional and lake-type factors, including size, depth, and salinity. Incorporating biomass data into the index would further improve the accuracy of assessing community structure and its role in nutrient and energy cycling.

The absence of standardized, biology-based assessment criteria for lake ecosystems at the national level underscores the need for developing systematic and integrative phytoplankton-based evaluation tools. Phytoplankton are primary producers that regulate energy flow and nutrient cycling in lake ecosystems, and their rapid responses to environmental changes such as eutrophication, altered hydrodynamics, and seasonal fluctuations make them highly effective biological indicators. Multimetric indices (MMIs) offer a structured and integrative approach for capturing complex community level responses to environmental stressors, thereby enhancing the ecological relevance and management utility of biological assessment tools for lentic systems. This study presents the Lake Phytoplankton Assessment Index (LPAI), developed using long term ecological and water quality data from 90 lakes and reservoirs across South Korea. The LPAI comprises six ecologically meaningful metrics: total cell density (M2), cell density of flagellated algae (M10), cell density of harmful cyanobacteria (M17), cell density of eutrophic Chlorophyta (M18), relative abundance of saprophilous diatoms (M23), and relative abundance of eutraphentic diatoms (M25). Application of the LPAI demonstrated that lake health grades exhibited a broad and near-normal distribution across seasons, while summer assessments showed a marked increase in lower grade (C~E) lakes associated with elevated temperatures and cyanobacterial blooms. Conversely, winter assessments showed improved conditions due to reduced phytoplankton biomass and the dominance of low eutrophic diatom assemblages. Correlation analyses confirmed that the selected metrics captured distinct ecological gradients, particularly nutrient enrichment and organic matter driven turbidity, while PCA results indicated that the LPAI performed consistently across lake types without structural bias. Overall, the LPAI reliably reflects trophic conditions, harmful algal risks, and structural changes in phytoplankton communities, offering a scientifically grounded and management-relevant tool for evaluating the ecological health of Korean lakes and reservoirs.

This study aims to advance Korea’s aquatic ecosystem assessment framework by developing and validating an Integrated Assessment Index (IAI) that synthesizes three biological indicators: the Diatom Assessment Index (DAI), the Benthic Macroinvertebrate Assessment Index (BAI), and the Fish Assessment Index (FAI). Using biomonitoring data collected from 2019 to 2021, three integration methods: the minimum grade method, most frequent grade method, and arithmetic mean method, were compared. The arithmetic mean method demonstrated the highest suitability and was adopted as the final integration approach. The resulting IAI showed stronger correlations with major water quality factors (BOD, TN, TP) than individual biological indices, indicating its enhanced capacity to capture both water quality gradients and ecological response patterns across biological assemblages. Application of the IAI to aquatic ecosystem assessment data from 2016 to 2023 revealed that the overall ecological condition of Korean rivers remained at a “fair (C)” level. Approximately half of the sites were classified as good to very good (A~B), while around 20% were rated as poor to very poor (D~E). Annual cycle analysis further indicated that first-year surveys within each monitoring phase exhibited higher proportions of good conditions, whereas second- and third-year surveys showed increasing frequencies of fair conditions, suggesting cumulative environmental stressors or progressive habitat alteration. Mid-sized basin target standards achievement analysis showed a clear discrepancy between waterquality and biological outcomes. While BOD and TP targets were met at relatively high rates, IAI achievement rates were the lowest across all major river basins (18~33%). This indicates that current water quality centered management goals insufficiently reflect actual ecological conditions. The results highlight that improvements in physico-chemical factors alone are insufficient for biological recovery and that habitat structure, flow regime, and substrate conditions are critical drivers of ecological integrity. Overall, the IAI effectively integrates biological and physico-chemical information, offering a more comprehensive quantification of river aquatic ecosystem health than single metric approaches. The index demonstrates strong potential as a practical tool for future policy applications, including mid-sized basin target management, ecological restoration prioritization, and integrated water resource planning.

Biological assessments of streams have been developed in many countries to evaluate ecological integrity. A multimetric index is one of the primary methods used for this purpose, incorporating chemical, physical, and biological variables of the environment. In Korea, the Benthic Macroinvertebrates Index (BMI) is currently applied in national biological monitoring programs; however, BMI reflects only organic pollution and does not account for other environmental variables in streams. This study aimed to develop a new multimetric index, the Benthic Macroinvertebrate-based Multimetric Index (BMMI), for assessing the ecological integrity of Korean streams. We analyzed data from 3,307 sites, including water quality information. Reference and disturbed streams were identified based on PC 1 scores with 7 environmental factors (Axis 1 of the PCA), genus levelbased taxa richness, and BMGI values used for trimming. From an initial set of 82 candidate metrics, six (genus level-based taxa richness, Shannon’s diversity index, percent of taxa in E.P.T., percent of individuals in collectorsgatherers, percent of individuals in clingers, BMGI based on saprobity) were selected through statistical analyses, including coefficient of variation and discriminant analysis. BMMI successfully distinguished between reference and disturbed streams and showed significant correlations with various environmental factors. These results indicate that BMMI is suitable for evaluating the ecological integrity of streams in Korea. Therefore, it is recommended that stream ecosystem assessments transition from BMI to BMMI in the future to provide a more comprehensive evaluation of stream integrity.

Current assessments of stream ecosystem health in Korea using benthic diatoms rely primarily on the Trophic Diatom Index (TDI), which is highly sensitive to phosphorus concentrations but has limited ability to capture complex environmental stressors such as organic pollution and physical habitat degradation. To address these limitations and enhance the ecological diagnostic capacity of diatom-based assessments, we developed a Korean-type multimetric diatom index, the Diatom Assessment Index (DAI). Using benthic diatom assemblage data and environmental variables collected from 3,029 sites nationwide between 2019 and 2021, we screened candidate metrics based on variability, redundancy, discriminatory power, and sensitivity analyses. Five metrics-TDI, proportion of motile diatoms, proportion of sensitive diatoms, proportion of saprophilous diatoms, and the [Achnanthes / (Achnanthes+Navicula)] ratio-were ultimately selected and integrated to calculate the DAI score. Applying the DAI to an independent dataset from 3,005 sites (2022~2024) demonstrated that the index exhibited a near-normal distribution across assessment classes, in contrast to the TDI, which tended to be skewed toward specific ranges. The DAI showed strong correlations not only with physicochemical parameters such as BOD and TP but also with physical habitat indicators, including flow velocity and the proportion of fine substrates. In addition, the DAI was significantly correlated with other biological indices, such as the Benthic Macroinvertebrate Index (BMI) and the Fish Assessment Index (FAI). These results indicate that the DAI provides a more comprehensive and ecologically meaningful measure of stream health in Korea and can serve as an effective tool for national aquatic ecosystem assessment and management.

수도권으로 인구가 집중되면서 광역 통행의 비중이 증가하게 되었다. 이러한 상황에서 서울시는 광역 통행에서 승용차 통행량을 줄 이고 대중교통의 편리성을 강화하여 대중교통이 광역 통행 수요를 분담하도록 하는 동시에 도심 주요 지역의 고밀복합개발을 통해 효 율적으로 도시 인프라를 개발하고자 하는 목적으로 서울시 여러 곳에 광역복합환승센터를 설치하였다. 본 연구는 이러한 복합환승센 터가 잘 기능하는지 평가하고 추후 다른 환승센터를 계획할 때에도 활용 가능한 평가 지표를 개발하고자 하였다. 평가를 위한 지표는 교통 기능 평가 지표 4가지, 도시 기능 평가 지표 3가지로 총 7가지의 지표를 선정하였으며, 환승센터마다 하나 의 점수로 환산 가능하도록 이 지표들을 하나의 선형식으로 통합하였다. 스마트카드 데이터로 환승시간, 광역교통분담률을 계산하였으 며, 교통카드 빅데이터 시스템상의 데이터를 통해 혼잡도와 접근성 평가 데이터를 추출하였다. 또한, 주변 지역 활성화도 관련 지표들 은 서울 열린 데이터 광장에서 취득하였다. 선형식의 각 변수의 계수는 서울시립대학교 교통공학과 구성원들을 대상으로 AHP 설문을 실시하여 얻은 지표별 가중치를 이용하여 결정하였다. 그 결과 광역복합환승센터 평가에 가장 큰 영향을 미치는 요소는 환승시간과 혼잡도였으며, 가장 적은 영향을 미친 요소는 용적률 활용도였다. 또한 완성된 선형식으로 서울역과 청량리역 환승센터를 평가한 결과 종합적으로 서울역 0.801543점, 청량리역 0.742488점으로 서울역이 청량리역보다 광역복합환승센터로서의 기능을 더 잘 수행하고 있는 것을 확인할 수 있었다. 환승시간, 용적률 활용도 등 일부 지표가 청량리역에서 우세하였으나 혼잡도나 주변 지역 활성화 지표가 서울 역에서 더 좋은 평가를 받은 점이 원인일 것으로 분석되었다.

PURPOSES : This study aimed to develop a transportation-energy linkage model and performance evaluation indicators to improve the sustainability operation and technology of smart city transportation-energy services. METHODS : This study derived a new transportation-energy linkage system model for 15 services designated by the national pilot city. Evaluation indicators for energy-oriented transportation services in smart cities were selected, and a methodological framework was proposed for selecting quantitative evaluation indicators based on text mining and importance-performance analysis (IPA). RESULTS : Twenty indicators, confirmed as crucial for successful transportation-energy linkage in smart cities, were selected. These covered data linkage between services, IoT-based information linkage driving rate, and network and energy efficiency indicators. The proposed quantitative methodological framework can complement expert subjective evaluation by identifying meaningful implications in research literature that experts may have missed. The methodology can consistently derive indicators even when new services are added, aiding policymakers’ decisions. CONCLUSIONS : The methodological framework can contribute to minimizing operational risks in smart city transportation-energy expansion. It can also be used to prioritize service investment in smart cities by estimating benefit effects through quantitative indicators.