Dissolved organic matter (DOM) is a key component in the biogeochemical cycling in freshwater ecosystem. However, it has been rarely explored, particularly complex river watershed dominated by natural and anthropogenic sources, such as various effluent facility and livestock. The current research developed a new analytical method for TOC/TN (Total Organic Carbon/Total Nitrogen) stable isotope ratio, and distinguish DOM source using stable isotope value (δ13C-DOC) and spectroscopic indices (fluorescence index [FI] and biological index [BIX]). The TOC/TN-IR/MS analytical system was optimized and precision and accuracy were secured using two international standards (IAEA-600 Caffein, IAEA-CH-6 Sucrose). As a result of controlling the instrumental conditions to enable TOC stable isotope analysis even in low-concentration environmental samples (<1 mgC L-1), the minimum detection limit was improved. The 12 potential DOM source were collected from watershed, which includes top-soils, groundwater, plant group (fallen leaves, riparian plants, suspended algae) and effluent group (pig and cow livestock, agricultural land, urban, industry facility, swine facility and wastewater treatment facilities). As a result of comparing characteristics between 12 sources using spectroscopic indices and δ13C-DOC values, it were divided into four groups according to their characteristics as a respective DOM sources. The current study established the TOC/TN stable isotope analyses system for the first time in Korea, and found that spectroscopic indices and δ13C-DOC are very useful tool to trace the origin of organic matter in the aquatic environments through library database.

PURPOSES : The aim of this study is to investigate the enhancement of performance and the mix design method for asphalt mixtures utilizing ferronickel slag, an industrial by-product METHODS : To enhance the performance of FNS asphalt, waste tire powder (CR) was incorporated, and the characteristics of FNS asphalt aggregate, along with the impact of CR, were evaluated through the mix design process. RESULTS : CR is found to be suitable with a size of 30 mesh, and the optimal usage amount is determined to be 1±0.1% of the mixture weight, considering dense grade asphalt mixture. Volumetric design considering the swelling characteristics of CR is necessary, and a mixing design with a consistent tendency can be achieved only when an appropriate VMA is secured. CONCLUSIONS : The mix design for FNS-R asphalt mixture requires an increase of approximately 1% in VMA compared to conventional dense-graded asphalt mixtures to accommodate the swelling of CR. Additionally, FNS-R asphalt exhibits improved resistance to rutting comparable to modified asphalt and meets quality standards, including stripping resistance.

PURPOSES : Derive a road pavement design method using Geocells, aim to derive a road pavement design and construction method suitable for the characteristics of the Bangladesh region METHODS : To assess long-term performance during road construction in Southeast Asia using Geocells, field tests and numerical analysis are conducted to verify stability. RESULTS : A total of 12 displacement measurements were conducted during the field tests, confirming an average load of 15.75 kN and an average displacement of 0.542mm. Inverse analysis was performed to obtain the properties of Geocell combined with compacted soil. The numerical analysis results confirmed that the insertion of Geocell provides better stability compared to the case with only compacted soil. CONCLUSIONS : Based on field tests and numerical analysis, a road design plan suitable for the Southeast Asian environment was proposed. A preliminary test section was selected in the Comilla region of Bangladesh, and test construction has been completed. Subsequent evaluations of the structural performance by soil layer in the test construction area will be conducted to develop a Geocell road pavement method, taking into consideration the characteristics of the Bangladesh region.

PURPOSES : This study aims to conduct a laboratory evaluation on the use of ferronickel slag for manufacturing Hot Mix Asphalat mixtures. METHODS : This research was based on laboratory evaluation only, where conventional aggregate and FNS at a ratio of 7:3 were used in HMA and the volumetric properties, physical and mechanical properties, and long-term performance of FNS in asphalt mixture were evaluated. RESULTS : The overall results showed that FNS can be applied as aggregate in a hot mix asphalt since volumetric, physical and mechanical properties and long-term performance of HMA mixture with ferronickel slags as aggregate met the required standards according to Korean standards for Asphalt Concrete. CONCLUSIONS : The tensile strength ratio results of HMA mixtures with ferronickel aggregate did not meet the required standards, yet the addition of anti-stripping agent and waste glass fibers to the HMA mixture with ferronickel slags improved the tensile strength results to meet the standards. Additionally, compared to the HMA mixture of the same aggregate gradation but with only natural aggregate, HMA mixture with ferronickel slags had almost the same results for the majority of tests conducted.

PURPOSES : This study is aimed to economic analysis of the ferronickel slag pavement method carried out to suggest the necessity of developing ferronickel slag pavement technology. METHODS : A life cycle cost analysis of the application of the Ferronickel Slag pavement method and the cutting + overlay pavement method was performed to compare the economic indicators and greenhouse gas emissions for each pavement method. RESULTS : As a result of the analysis, regardless of the Ferronickel Slag mixing rate, if the common performance of the Ferronickel Slag pavement method is the same or superior to the existing pavement method, it is more economical than the existing pavement method. Furthermore, the lower the maintenance cost of the Ferronickel Slag pavement method, the higher the economic feasibility due to the high Ferronickel Slag mixing rate. Greenhouse gas emissions can be reduced from at least 9% to up to 53% through the application of the Ferronickel Slag pavement method, except for some scenario analysis results. CONCLUSIONS : This study provided that the Ferronickel Slag pavement method was superior to the existing pavement method in terms of economic and environmental aspects. Therefore, it was found that the objective justification of developing road pavement technology using Ferronickel Slag was secured.

PURPOSES : The current research aims to evaluate the impact of coating materials and temperature on the percentage of bead loss in pavement markings. METHODS : Five mixtures with varying numbers of coating layers (C0, C1, C2, C3, and C4) were prepared to assess the effect of coating layers on bead loss. The effect of stripping was simulated using a modified Hamburg Wheel Tracking test. Furthermore, the influence of temperature and coating material on bead loss was examined using control mixture (without coating), YR, and SY coating mixtures. The percentage bead loss was evaluated by a developed image analysis program. RESULTS : The results demonstrated a substantial reduction in bead loss as the number of coating layers increased, with the C4 mixture showing an impressive 4.3% bead loss after 500 HWT braking cycles compared to 27.4% for the C0 mixture. Higher testing temperatures resulted in increased bead loss, with the control mixture exhibiting the highest percentage loss at 7,500 HWT rolling cycles. Conversely, the YR and SY coating mixtures displayed superior resistance to bead loss. Statistical analysis confirmed the significance of coating layers in reducing bead loss, further supporting the effectiveness of coatings in preserving bead adhesion during HWT cycles. CONCLUSIONS : The findings highlight the potential of coating materials as a key protective measure for enhancing the longevity and performance of pavement markings.

PURPOSES : The objective of this study is to develop the data driven pavement condition index by considering the traffic and climatic characteristics in Incheon city. METHODS : The Incheon pavement condition index (IPCI) was proposed using the weighted sum concept with standardization and coefficient of variation for measured pavement performance data, such as crack rate, rut depth, and International Roughness Index (IRI). A correlation study between the National Highway Pavement Condition Index (NHPCI) and Seoul Pavement Condition Index (SPI) was conducted to validate the accuracy of the IPCI. RESULTS : The equation for determining the IPCI was developed using standardization and the coefficient of variation for the crack rate, rut depth, and IRI collected in the field. It was found from the statistical analysis that the weight factors of the IPCI for the crack rate were twice as high as those for the rut depth and IRI. It was also observed that IPCI had a close correlation with the NHPCI and SPI, albeit with some degree of scattering. This correlation study between the NHPCI and SPI indicates that the existing pavement condition index does not consider the asymmetry of the original measured data. CONCLUSIONS : The proposed pavement condition provides an index value that considers the characteristics of the original raw data measured in the field. The developed pavement condition index is extensively used to determine the timing and method of pavement repair, and to establish pavement maintenance and rehabilitation strategies in Incheon.

PURPOSES : For most local governments, including that of Gangwon-do, the establishment of an organized pavement management system is insufficient, resulting in problems such as inefficient distribution and use of maintenance budgets for deteriorated road pavements. In this study, we aimed to contribute to the establishment of a more reasonable road maintenance strategy by developing a model for predicting the annual international roughness index (IRI) change for national highway asphalt pavements in Gangwon-do based on big data analysis. METHODS : Data on independent and dependent variables used for model development were collected. The collected data were subjected to exploratory data analysis (EDA) and data preprocessing. Independent variable candidates were selected to reduce multicollinearity through correlation analysis and specific conditions. A final model was selected, and sensitivity analysis was performed. RESULTS : The final model that predicts annual IRI change uses independent variables such as annual temperature range, minimum temperature, freeze-thaw days, IRI, surface distress (SD), and freezing days. The sensitivity analysis confirmed that the annual IRI change was affected in the order of annual temperature range, minimum temperature, freeze-thaw days, IRI, SD, and freezing days. CONCLUSIONS : Road maintenance can be performed rationally by predicting future pavement conditions using the model developed in this study. The accuracy of the prediction model can be improved if additional data, such as material properties and pavement thickness, are obtained in future studies.

PURPOSES : Local governments in Korea, including Incheon city, have introduced the pavement management system (PMS). However, the verification of the repair time and repair section of roads remains difficult owing to the non-existence of a systematic data acquisition system. Therefore, data refinement is performed using various techniques when analyzing statistical data in diverse fields. In this study, clustering is used to analyze PMS data, and correlation analysis is conducted between pavement performance and influencing factors. METHODS : First, the clustering type was selected. The representative clustering types include K-means, mean shift, and density-based spatial clustering of applications with noise (DBSCAN). In this study, data purification was performed using DBSCAN for clustering. Because of the difficulty in determining a threshold for high-dimensional data, multiple clustering, which is a type of DBSCAN, was applied, and the number of clustering was set up to two. Clustering for the surface distress (SD), rut depth (RD), and international roughness index (IRI) was performed twice using the number of frost days, the highest temperature, and the average temperature, respectively. RESULTS : The clustering result shows that the correlation between the SD and number of frost days improved significantly. The correlation between the maximum temperature factor and precipitation factor, which does not indicate multicollinearity, improved. Meanwhile, the correlation between the RD and highest temperature improved significantly. The correlation between the minimum temperature factor and precipitation factor, which does not exhibit multicollinearity, improved considerably. The correlation between the IRI and average temperature improved as well. The correlation between the low- and high-temperature precipitation factors, which does not indicate multicollinearity, improved. CONCLUSIONS : The result confirms the possibility of applying clustering to refine PMS data and that the correlation among the pavement performance factors improved. However, when applying clustering to PMS data refinement, the limitations must be identified and addressed. Furthermore, clustering may be applicable to the purification of PMS data using AI.

PURPOSES : In this study, surface distress (SD), rutting depth (RD), and international roughness index (IRI) prediction models are developed based on the zones of Incheon and road classes using regression analysis. Regression analysis is conducted based on a correlation analysis between the pavement performance and influencing factors. METHODS : First, Incheon was categorized by zone such as industrial, port, and residential areas, and the roads were categorized into major and sub-major roads. A weather station triangle network for Incheon was developed using the Delaunay triangulation based on the position of the weather station to match the road sections in Incheon and environmental factors. The influencing factors of the road sections were matched Based on the developed triangular network. Meanwhile, based on the matched influencing factors, a model of the current performance of the road pavement in Incheon was developed by performing multiple regression analysis. Sensitivity analysis was conducted using the developed model to determine the influencing factor that affected each performance factor the most significantly. RESULTS : For the SD model, frost days, daily temperature range, rainy days, tropical nights, and minimum temperatures are used as independent variables. Meanwhile, the truck ratio, freeze–thaw days, precipitation days, annual temperature range, and average temperatures are used for the RD model. For the IRI model, the maximum temperature, freeze–thaw days, average temperature, annual precipitation, and wet days are used. Results from the sensitivity analysis show that frost days for the SD model, precipitation days and freeze–thaw days for the RD model, and wet days for the IRI model impose the most significant effects. CONCLUSIONS : We developed a road pavement performance prediction model using multiple regression analysis based on zones in Incheon and road classes. The developed model allows the influencing factors and circumstances to be predicted, thus facilitating road management.

PURPOSES : The aim of this study is to evaluate the effects of air voids, binder content, and aggregate gradation on the indirect tensile strength (IDT) and cracking tolerance index (CTindex) of cored asphalt pavements. METHODS : Cored samples were obtained from roads in Incheon city, and several laboratory experiments were performed. First, the cored samples were first to cut into a size appropriate for the IDT test. Subsequently, the air voids of the samples were measured. The damaged sample from the IDT test was loose mixed at 150 ℃ before the binder content was determined, which was conducted via an asphalt extraction test. Finally, the clean aggregates obtained from asphalt extraction process were analyzed in the aggregate gradation test. RESULTS : The result shows that an increase in air voids from 4% to 8% decreases the IDT and cracking tolerance index (CTindex) by 30% and 28%, respectively. Incorporating a binder enhances the ductile behavior of the asphalt mixture, resulting in a higher CTindex. Finally, the contribution of the aggregate grade on the IDT and CTindex is negligible. CONCLUSIONS : The IDT and CTindex are primarily affected by the air voids and binder content. A higher percentage of air voids results in a lower IDT. In addition, a higher amount of binder increases the IDT and CTindex of the cored samples. Meanwhile, the aggregate grade does not affect the IDT.

PURPOSES : To efficiently manage pavements, a systematic pavement management system must be established based on regional characteristics. Suppose that the future conditions of a pavement section can be predicted based on data obtained at present. In this case, a more reasonable road maintenance strategy should be established. Hence, a prediction model of the annual surface distress (SD) change for national highway pavements in Gangwon-do, Korea is developed based on influencing factors. METHODS : To develop the model, pavement performance data and influencing factors were obtained. Exploratory data analysis was performed to analyze the data acquired, and the results show that the data were preprocessed. The variables used for model development were selected via correlation analysis, where variables such as surface distress, international roughness index, daily temperature range, and heat wave days were used. Best subset regression was performed, where the candidate model was selected from all possible subsets based on certain criteria. The final model was selected based on an algorithm developed for rational model selection. The sensitivity of the annual SD change was analyzed based on the variables of the final model. RESULTS : The result of the sensitivity analysis shows that the annual SD change is affected by the variables in the following order: surface distress ˃ heat wave days ˃ daily temperature range ˃ international roughness index. CONCLUSIONS : An annual SD change prediction model is developed by considering the present performance, traffic volume, and climatic conditions. The model can facilitate the establishment of a reasonable road maintenance strategy. The prediction accuracy can be improved by obtaining additional data, such as the construction quality, material properties, and pavement thickness.

PURPOSES : In this study, the characteristics of fine particulate matter (PM2.5) concentrations under different weather conditions of different types of bus stops, such as enclosed-type and open-type bus stops, were analyzed using statistical methods. METHODS : Data was collected inside and outside an enclosed bus stop on sunny and rainy days to compare and analyze the characteristics of fine particulate matter concentration in the target bus stop. The probability distributions were estimated for each data point using the Anderson–Darling test. Based on the estimated probability distributions, probability density functions were computed, and the values were used to estimate and compare probability for each air quality index inside and outside the bus stop under different weather conditions RESULTS : For the results of descriptive statistics, the average concentrations of fine particulate matter inside and outside the bus stop were 42.296 and 35.482 μg/m3 on a sunny day and 40.831 and 39.321 μg/m3 on a rainy day, respectively. Results of the statistical method, obtained using the Anderson-Darling test, indicate that the probability of the air quality index inside the bus stop reaching high concentrations on a sunny day was "high" or "very high," compared to that outside the bus stop. However, on rainy days, the differences in fine particulate matter concentrations inside and outside the bus stops were difficult to identify based on statistical evidence. CONCLUSIONS : It was found that the open-type bus stop had an advantage of preventing fine particulate matter effects on sunny days, compared to the enclosed-type bus stops. Furthermore, there were slight differences in fine particulate matter concentrations inside and outside the bus stop on a rainy day because of atmospheric flow and stormwater.