Characterizing the risk posed by a mixture of chemicals is a challenging task due to the chemical interactions of individual components that may affect their physical behavior and hence alter their exposure to receptors. In this study, cell tests that represent subsurface environment were carried out using benz[a]anthracene (BaA) and p-xylene focusing on phasetransforming interaction to verify increased mobility and risk of highly sorbed pollutants in the presence of less sorbed, mobile liquid pollutants. A transport model was also developed to interpret results and to simulate the same process on a field scale. The experimental results showed that BaA had far greater mobility in the presence of p-xylene than in the absence of that. The main transport mechanisms in the vadose zone were by dissolution to p-xylene or water. The transport model utilizing Defined Time Steps (DTS) was developed and tested with the experimental results. The predicted and observed values showed similar tendency, but the more work is needed in the future study for more precise modeling. The field-scale simulation results showed that transport of BaA to groundwater table was significantly faster in the presence of NAPL, and the oral carcinogenic risk of BaA calculated with the concentration in groundwater was 15${\sim}$87 times larger when mixed with NAPL than when solely contaminated. Since transport rate of PAHs is very slow in the subsurface without NAPL and no degradation of PAHs was considered in this simulation during the transport, the increase of risk in the presence of NAPL is expected to be greater for the actual contaminated site.
Park, Jong-Yoon;Lee, Mi-Seon;Park, Geun-Ae;Kim, Seong-Joon
Journal of Korea Water Resources Association
/
v.41
no.11
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pp.1079-1094
/
2008
This study is to evaluate the impact of varying spatial resolutions on the uncertainty of Soil and Water Assessment Tool (SWAT) predicted streamflow, non-point source (NPS) pollution loads transport in a small agricultural watershed (1.21 $km^2$) for three cases of model input; Case A is the combination of 2 m DEM, QuickBird land use, Case B is the combination of 10 m DEM, 1/25,000 land use, and Case C is the combination of 30 m DEM, Landsat land use, soil data is used 1/25,000 for three cases respectively. The model was calibrated for 2 years (1999-2000) using daily streamflow and monthly water quality records, and verified for another 2 years (2001-2002). The average Nash and Sutcliffe model efficiency was 0.59 for streamflow and RMSE were 2.08, 4.30 and 0.70 tons/yr for sediment, T-N and T-P respectively. The model was run for a small agricultural watershed with three cases of spatial input data. The hydrological results showed that output uncertainty was biggest by spatial resolution of land use. Streamflow increase the watershed average CN value of QucikBird land use was 0.4 and 1.8 higher than those of 1/25,000 and Landsat land use caused increase of streamflow. On the other hand, The NPS loadings from the model prediction showed that the sediment, T-N and T-P of QuickBird land use (Case A) showed 23.7 %, 43.3 % and 48.4 % higher value than 1/25,000 land use (Case B) and 50.6 %, 50.8 % and 56.9 % higher value than Landsat land use (Case C) respectively.
Cholho Song;Hyun-Ah Choi;Jiwon Son;Youngjin Ko;Stephan A. Pietsch;Woo-Kyun Lee
Korean Journal of Environmental Biology
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v.41
no.4
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pp.400-412
/
2023
In this study, the biogeochemistry management (BGC-MAN) model was applied to North and South Korea pine and oak forest stands to evaluate the Net Primary Productivity (NPP), an indicator of forest ecosystem productivity. For meteorological information, historical records and East Asian climate scenario data of Shared Socioeconomic Pathways (SSPs) were used. For vegetation information, pine (Pinus densiflora) and oak(Quercus spp.) forest stands were selected at the Gwangneung and Seolmacheon in South Korea and Sariwon, Sohung, Haeju, Jongju, and Wonsan, which are known to have tree nurseries in North Korea. Among the biophysical information, we used the elevation model for topographic data such as longitude, altitude, and slope direction, and the global soil database for soil data. For management factors, we considered the destruction of forests in North and South Korea due to the Korean War in 1950 and the subsequent reforestation process. The overall mean value of simulated NPP from 1991 to 2100 was 5.17 Mg C ha-1, with a range of 3.30-8.19 Mg C ha-1. In addition, increased variability in climate scenarios resulted in variations in forest productivity, with a notable decline in the growth of pine forests. The applicability of the BGC-MAN model to the Korean Peninsula was examined at a time when the ecosystem process-based models were becoming increasingly important due to climate change. In this study, the data on the effects of climate change disturbances on forest ecosystems that was analyzed was limited; therefore, future modeling methods should be improved to simulate more precise ecosystem changes across the Korean Peninsula through process-based models.
The 'Stable Isotope Analysis in R' (SIAR), one of the Bayesian mixing models for stable isotopes, has been proven to be useful for source apportionment of nitrates in rivers. In this study, the contribution ratios of nitrate sources were quantified by using the SIAR based on nitrogen and oxygen stable isotope measurements in the Yeongsan River. From the measurements, it was found that the values of δ15N-NO3 and δ18O-NO3 ranged from -8.2 ‰ to +13.4 ‰ and from +2.2 ‰ to +9.8 ‰, respectively. We further analyzed the contribution ratios of the five nitrate sources by using the SIAR. From the modeling results, the main nitrate source was found to be soil N (29.3 %), followed by sewage (26.7 %), manure (19.6 %), chemical fertilizer (17.9 %) and precipitation (6.3 %). From the results, it was found that the anthropogenic sources, i.e., sewage, manure and chemical fertilizer contribute 64.2% of the total nitrate inflow from the watershed. Due to the significant correlation of δ15N-NO3 and lnNO3- in this study, the fractionation factors reflecting the biogeochemical processes of stable isotope ratios could be directly obtained. This may make the contribution ratios obtained in this study more precise. The fractionation factors were identified as +3.64 ± 0.91 ‰ for δ15N-NO3 (p<0.01) and -5.67 ± 1.73 ‰ for δ18O-NO3(p<0.01), respectively, and were applied in using the SIAR. The study showed that the stable isotope method using the SIAR could be applied to quantitatively calculate the contribution ratios of nitrate sources in the Yeongsan River.
Climate change is considered as the greatest threat to our future and descendants. The Korean government has set a target for 2030 to reduce emission of greenhouse gases (GHGs) by 37% from the business-as-usual levels which are projected to reach 851 million metric tons of $CO_2eq$ (Carbon dioxide equivalent). In Korea, GHGs emission from agriculture account for almost 3.1% of the total of anthropogenic GHGs. The GHGs emitted from agricultural land are largely classified into three types: carbon dioxide ($CO_2$), methane ($CH_4$), and nitrous oxide ($N_2O$). In Korea, rice paddies are one of the largest agricultural $CH_4$ sources. In order to analyze domestic research trends related to $CH_4$ emission from rice paddies, 93 academic publications including peer reviewed journals, books, working papers, reports, etc., published from 1995 to September 2017, were critically reviewed. The results were classified according to the research purposes. $CH_4$ characteristics and assessment were found to account for approximately 65.9% of the research trends, development of $CH_4$ emission factors for 9.5%, $CH_4$ emission reduction technology for 14.8%, and $CH_4$ emission modeling for 6.3%, etc. A number of research related to $CH_4$ emission characteristics and assessment have been studied in recent years, whereas further study on $CH_4$ emission factors are required to determine an accurate country-specific GHG emission from rice paddies. Future research should be directed toward both studies for reducing the release of $CH_4$ from rice paddies to the atmosphere and the understanding of the major controlling factors affecting $CH_4$ emission.
The purpose of this study is to create landslide vulnerability using frequency ratio (FR) and evidential belief functions (EBF) model which are two methods of probability model and to select appropriate model for each region through comparison of results in Sacheon-myeon and Jumunjin-eup of Gangneung. 762 locations in Sacheon-myeon and 548 landscapes in Jeonju-eup were constructed based on the interpretation of aerial photographs. Half of each landslide point was randomly selected for modeling and remaining landslides were used for verification purposes. Twenty landslide-inducing factors classified into five categories such as topographic elements, hydrological elements, soil maps (1:5,000), forest maps (1:5,000), and geological maps (1:25,000) were considered for the preparation of landslide vulnerability in the study. The relationship between landslide occurrence and landslide inducing factors was analyzed using FR and EBF models. The two models were then verified using the AUC (curve under area) method. According to the results of verification, the FR model (AUC = 81.2%) was more accurate than the EBF model (AUC = 78.9%) at Jeonjun-eup. In the Sacheon-myeon, the EBF model (AUC = 83.6%) was more accurate than the FR model (AUC = 81.6%). Verification results show that FR model and EBF model have high accuracy with accuracy of around 80%.
The purpose of this study was to evaluate effects of spatio-temporal changes in land uses and rainfall magnitude using the Soil and Water Assessment Tool (SWAT). Prior of application of the model to real-world problem, the model should be calibrated and validated properly. In most modeling approaches, the validation process is done assuming no significant changes occurring at the study watershed between calibration and validation periods, which is not proper assumption for agricultural watersheds. If simulated results obtained with calibrated parameters match observed data with higher accuracy for validation period, this does not always mean the simulated result represents rainfall-runoff, pollutant generation and transport mechanism for validation period because temporal and spatial variables and rainfall magnitude are often not the same. In this study SWAT was applied to Mandae study watershed in Korea to evaluate effects of spatio-temporal changes in landuses using 2009 and 2010 crop data for each field at the watershed. The Nash-Sutcliffe model efficiency (NSE) values for calibration and validation with either 2009 or 2010 was evaluated and the NSE value for calibration with 2009 and calibration with 2010 were compared. It was found that if there is substantial change in land use and rainfall, model calibration period should be determined to reflect those changes. Through these approaches, inherent limitation of the SWAT, which does not consider changes in land uses over the simulation period, was investigated. Also, Effects of changes in rainfall magnitude during calibration process were analyzed.
The study applies a hydrologic simulation model, HEC-1 developed by Hydrologic Engineering Center to Daecheong dam watershed for modeling hourly inflows of Daecheong dam. Although the HEC-1 model provides an automatic optimization technique for some of the parameters, the built-in optimization model is not sufficient in estimating reliable parameters. In particular, the optimization model often fails to estimate the parameters when a large number of parameters exist. In this regard, a main objective of this study is to develop Bayesian Markov Chain Monte Carlo simulation based HEC-1 model (BHEC-1). The Clark IUH method for transformation of precipitation excess to runoff and the soil conservation service runoff curve method for abstractions were used in Bayesian Monte Carlo simulation. Simulations of runoff at the Daecheong station in the HEC-1 model under Bayesian optimization scheme allow the posterior probability distributions of the hydrograph thus providing uncertainties in rainfall-runoff process. The proposed model showed a powerful performance in terms of estimating model parameters and deriving full uncertainties so that the model can be applied to various hydrologic problems such as frequency curve derivation, dam risk analysis and climate change study.
Kim, Ju-Hwan;Lee, Doo-Jin;Bae, Cheol-Ho;Woo, Hyung-Min
Proceedings of the Korea Water Resources Association Conference
/
2009.05a
/
pp.260-266
/
2009
Non-revenue water reduction(NRW) technologies are implemented to evaluate and manage leakages scientifically in water distribution systems under local governments. A development of quantitative leakage indicator by measuring minimum night flow, pressure control policy by installation of PRV(pressure reducing valve) and the establishment of leakage prevention schemes by residual life modeling of deteriorated water pipes are reviewed and studied. Estimation models of allowable leakage are developed by measuring and analyzing minimum night flow at residential and commercial area in Nonsan city, which is suggested from UK water industry and can improve an existing leakage indicator for the evaluation of non-revenue water. Also, pressure control method is applied and analyzed to Uti distribution area in Sacheon city in the operation aspect. As results, $466\;m^3/day$ of leakage can be reduced and it is expected that 113million won of annual cost can be saved. In the part of corrosion velocity and residual life assessment, non-linear prediction models of residual thickness are proposed by assessment of corrosion velocity based on exposure years, soil and water quality etc., since the deteriorated water pipe play a major role to increase leakage. It is expected that collection data and analyzing results can be applied effectively and positively to reduce non-revenue water by accumulating surveying data and verifying the results in the business field of water distribution systems under local governments.
Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
/
2001.06a
/
pp.1617-1617
/
2001
It is well known now that near infrared spectroscopy (NIRS) is a fast, no destructive, and inexpensive analytical technique that could be used to classify, identify, and authenticate a wide range of foods and food items. Therefore, the main aims of this study were to provide a new insight into the authentication of five strawberry (Fragaria x ananassa) varieties and to correlate them with geographical zones and the propagating methods used. Three weeks plants of five different strawberry varieties (F. x ananassa Duch. cv Camarosa, Seascape, Chandler, F. Chiloensis, and F. Virginiana) were cultivated in vitro first and then transferred to pots with special soil, and grown in a greenhouse at CINVESTAV, all varieties were acquired from California (USA). After 18 months, ten leaves from each variety were collected. Transmission spectra from each leave were recorded over a range of 10, 000-4, 000 cm$-^{1}$, 32 scans of each strawberry leave were collected using a resolution of 4 cm$-^{1}$ with a Paragon IdentiCheck FT-NIR System Spectrometer. Triplicates of each strawberry leave were used. All spectra were analyzed using principal component analysis (PCA) and soft independent modeling class analogy (SIMCA). The optimum number of components to be used in the regression was automatically determined by the software. Camarosa was the only variety grown from the same shoot but propagated by a different method (direct or in vitro). Five different classes (varieties) or clusters were observed among samples, however, larger inter class distances were presented by the two wildtype samples (F. Chiloensis and F. Virginiana). Camarosa direct and Camarosa in vitro displayed a small overlapping region between them. On the other hand, Seascape variety presented the smallest rejection percentage among all varieties (more similarities with the rest of the samples). Therefore, it can be concluded that the application of NIRS technique allowed the authentication of all strawberry varieties and geographical origin as well. It was also possible to form subclasses of the same materials. The results presented here demonstrate that NIRS is a very powerful and promising analytical tool since all materials were authenticated and classified based on their variety, origin, and treatment. This is of a tremendous relevance since the variety and origin of a plant material can be established even before it gives its typical fruit or flower.
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