The following policy implications can be drawn from this study: 1) The Air Pollution Emission Amount Report published by the Ministry of Environment since 1991 classifies industries into 4 sectors, i. e., heating, manufacturing, transportation and power generation. Currently, the usability of report is very low and extra efforts should be given to refine the current statistics and to improve the industrial classification. 2) Big pollution industries are as follows - s7, s17 and s20. The current air pollution control policy for these sectors compared to other sectors are found to be inefficient. This finding should be noted in the implementation of future air pollution policy. 3) s10 and s17 are found to be a big polluting industrial sector and its pollution reduction effect is also significant. 4) The effect of emission coefficient (${\Delta}f$) has the biggest impact on the reduction of emission amount change and the effect of economic growth coefficient (${\Delta}y$) has the biggest impact on the increase of emission volume. The effect of production technology factor (${\Delta}D$) and the effect of the change of the final demand structure (${\Delta}u$) are insignificant in terms of the change of emission volume. 5) Further studies on emission estimation techniques on each industry sector and the economic analysis are required to promote effective enforcement of the total volume control system of air pollutants, the differential management of pollution causing industrial sectors and the integration of environment and economy. 6) Korea's economic growth in 1990 is not pollution-driven in terms of the Barry Commoner's hypothesis, even though the overall industrial structure and the demand structure are not environmentally friendly. It indicates that environmental policies for the improvement of air quality depend mainly on the government initiatives and systematic national level consideration of industrial structures and the development of green technologies are not fully incorporated.
Soryeon Park;Sanghun Son;Jaegu Bae;Doi Lee;Dongju Seo;Jinsoo Kim
Korean Journal of Remote Sensing
/
v.39
no.5_1
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pp.655-667
/
2023
Algal bloom outbreaks are frequently reported around the world, and serious water pollution problems arise every year in Korea. It is necessary to protect the aquatic ecosystem through continuous management and rapid response. Many studies using satellite images are being conducted to estimate the concentration of chlorophyll-a (Chl-a), an indicator of algal bloom occurrence. However, machine learning models have recently been used because it is difficult to accurately calculate Chl-a due to the spectral characteristics and atmospheric correction errors that change depending on the water system. It is necessary to consider the factors affecting algal bloom as well as the satellite spectral index. Therefore, this study constructed a dataset by considering water quality, hydrological and meteorological factors, and sentinel-2 images in combination. Representative ensemble models random forest and extreme gradient boosting (XGBoost) were used to predict the concentration of Chl-a in eight weirs located on the Nakdong river over the past five years. R-squared score (R2), root mean square errors (RMSE), and mean absolute errors (MAE) were used as model evaluation indicators, and it was confirmed that R2 of XGBoost was 0.80, RMSE was 6.612, and MAE was 4.457. Shapley additive expansion analysis showed that water quality factors, suspended solids, biochemical oxygen demand, dissolved oxygen, and the band ratio using red edge bands were of high importance in both models. Various input data were confirmed to help improve model performance, and it seems that it can be applied to domestic and international algal bloom detection.
Journal of the Korean Association of Geographic Information Studies
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v.18
no.4
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pp.81-99
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2015
The acceleration of global warming has required better understanding of carbon cycles over local and regional areas such as the Korean peninsula. Since forests serve as a carbon sink, which stores a large amount of terrestrial carbon, there has been a demand to accurately estimate such forest carbon sequestration. In Korea, the National Forest Inventory(NFI) has been used to estimate the forest carbon stocks based on the amount of growing stocks per hectare measured at sampled location. However, as such data are based on point(i.e., plot) measurements, it is difficult to identify spatial distribution of forest carbon stocks. This study focuses on urban areas, which have limited number of NFI samples and have shown rapid land cover change, to estimate grid-based forest carbon stocks based on UNFCCC Approach 3 and Tier 3. Land cover change and forest carbon stocks were estimated using Landsat 5 TM data acquired in 1991, 1992, 2010, and 2011, high resolution airborne images, and the 3rd, 5th~6th NFI data. Machine learning techniques(i.e., random forest and support vector machines/regression) were used for land cover change classification and forest carbon stock estimation. Forest carbon stocks were estimated using reflectance, band ratios, vegetation indices, and topographical indices. Results showed that 33.23tonC/ha of carbon was sequestrated on the unchanged forest areas between 1991 and 2010, while 36.83 tonC/ha of carbon was sequestrated on the areas changed from other land-use types to forests. A total of 7.35 tonC/ha of carbon was released on the areas changed from forests to other land-use types. This study was a good chance to understand the quantitative forest carbon stock change according to the land cover change. Moreover the result of this study can contribute to the effective forest management.
Radiation treatment techniques using photon beam such as three-dimensional conformal radiation therapy (3D-CRT) as well as intensity modulated radiotherapy treatment (IMRT) demand accurate dose calculation in order to increase target coverage and spare healthy tissue. Both jaw collimator and multi-leaf collimators (MLCs) for photon beams have been used to achieve such goals. In the Pinnacle3 treatment planning system (TPS), which we are using in our clinics, a set of model parameters like jaw collimator transmission factor (JTF) and MLC transmission factor (MLCTF) are determined from the measured data because it is using a model-based photon dose algorithm. However, model parameters obtained by this auto-modeling process can be different from those by direct measurement, which can have a dosimetric effect on the dose distribution. In this paper we estimated JTF and MLCTF obtained by the auto-modeling process in the Pinnacle3 TPS. At first, we obtained JTF and MLCTF by direct measurement, which were the ratio of the output at the reference depth under the closed jaw collimator (MLCs for MLCTF) to that at the same depth with the field size $10{\times}10\;cm^2$ in the water phantom. And then JTF and MLCTF were also obtained by auto-modeling process. And we evaluated the dose difference through phantom and patient study in the 3D-CRT plan. For direct measurement, JTF was 0.001966 for 6 MV and 0.002971 for 10 MV, and MLCTF was 0.01657 for 6 MV and 0.01925 for 10 MV. On the other hand, for auto-modeling process, JTF was 0.001983 for 6 MV and 0.010431 for 10 MV, and MLCTF was 0.00188 for 6 MV and 0.00453 for 10 MV. JTF and MLCTF by direct measurement were very different from those by auto-modeling process and even more reasonable considering each beam quality of 6 MV and 10 MV. These different parameters affect the dose in the low-dose region. Since the wrong estimation of JTF and MLCTF can lead some dosimetric error, comparison of direct measurement and auto-modeling of JTF and MLCTF would be helpful during the beam commissioning.
This study attempts to estimate the value of the water quality improvement by deriving the equilibrium price of the water pollutant emission permit for the imaginary water pollutant emission trading market. It is reasonable to say that there is already an implicit social agreement for the unit value of water pollutant, when the government set the Total Water Pollutant Loading System for the major river basin as a part of the Comprehensive Measures for Water Management, particularly for the Nakdong River Basin. Therefore, we can derive the unit value of water pollutant emission, which is already implied in the pollution allowance for each city or county by the Total Water Pollutant Loading System. Once estimated, it will be useful to the economic assessment of the water quality related projects. An imaginary water pollutant emission trading system for the Nakdong River Basin, where Total Water Pollutant Loading System is already effective, is constructed for the estimation of the equilibrium price of water pollutant permit. By estimating marginal abatement cost curve or each city or county, we can compute the equilibrium price of the permit and then it is regarded as the economic value of the water pollutant. The marginal net benefit function results from the relationship between the emission and the benefit, and then the equilibrium price of permit comes from constructing the excess demand function of the permit by using the total allowable permit of the local government entity. The equilibrium price of the permit would be estimated to be $1,409.3won/kg{\cdot}BOD$. This is within reasonable boundary compared for the permit price compared to foreign example. This permit price would be applied to calculate for the economic value of the water quality pollutants, and also be expected to use directly for the B/C analysis of the business involved with water quality change.
The study aim was to derive a stem taper equation for Phyllostachys pubescens, a type of bamboo in South Korea, and to develop a stem volume table. To derive the stem taper equation, three stem taper models (Max & Burkhart, Kozak, and Lee) were used. Since bamboo stalks are hollow because of its woody characteristics, the outer and inner diameters of the tree were calculated, and connecting them enabled estimating the tree curves. The results of the three equations for estimating the outer and inner diameters led to selection of the Kozak model for determining the optimal stem taper because it had the highest fitness index and lowest error and bias. We used the Kozak model to estimate the diameter of Phyllostachys pubescens by stem height, which proved optimal, and drew the stem curve. After checking the residual degree in the stem taper equation, all residuals were distributed around "0", which proved the suitability of the equation. To calculate the stem volume of Phyllostachys pubescens, a rotating cube was created by rotating the stem curve with the outer diameter at 360°, and the volume was calculated by applying Smalian's method. The volume of Phyllostachys pubescens was calculated by deducting the inner diameter calculated volume from the outer diameter calculated volume. The volume of Phyllostachys pubescens was only 20~30% of the volume of Larix kaempferi, which is a general species. However, considering the current trees/ha of Phyllostachys pubescens and the amount of bamboo shoots generated every year, the individual tree volume was predicted to be small, but the volume/ha was not very different or perhaps more. The significance of this study is the stem taper equation and stem volume table for Phyllostachys pubescens developed for the first time in South Korea. The results are expected to be used as basic data for bamboo trading that is in increasing public and industrial demand and carbon absorption estimation.
The CY can be said to function in various respect as a buffer zone between the maritime and overland inflow-outflow of container. The amount of storage area needed requires a very critical appraisal at pre-operational stage. A container terminal should be designed to handle and store containers in the most efficient and economic way possible. In order to achieve this aim it is necessary to figure out or forecast numbers and types of containers to be handled, CY area required, and internal handling systems to be adopted. This paper aims to calculate the CY area required for each container handling system in Mokpo New Port. The CY area required are directly dependent on the equipment being used and the storage demand. And also the CY area required depends on the dwell time. Furthermore, containers need to be segregated by destination, weight, class, FCL(full container load), LCL(less than container load), direction of travel, and sometimes by type and often by shipping line or service. Thus the full use of a storage area is not always possible as major unbalances and fluctuations in these flow occuring all the time. The calculating CY area must therefore be taken into account in terms of these operational factors. For solving such problem, all these factors have been applied to estimation of CY area in Mokpo New Port. The CY area required in Mokpo New Port was summarized in the conclusion section.
KSCE Journal of Civil and Environmental Engineering Research
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v.32
no.6D
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pp.679-686
/
2012
KTX step 1 April 2004, after the opening, the second phase of the project was opened in November 2010. High-speed rail after the opening and continue to increase the demand of high-speed rail, Have the speed of competitive advantage compared too the means of transportation. The opening of these high-speed rail has led to changes of the move, the company's position, and the spatial structure of the population of reorganization, such as the social, economic, transportation. In this study, survey data using the High Speed Rail Station EMME/2 of the program to take advantage of the 2-Dimentional Blancing trip distribution to investigate the passage through the trip distribution by the estimation of the parameters of the model to estimate the distribution of the means of access and high-speed rail station to reproduce and Analysis of the results by means of access parameters (${\theta}$) autos 0.0395, buses 0.0390, subway 0.0650, taxi 0.0415, the frequency distribution (Trip Length Frequency Distribution: TLFD) were analyzed survey data value model with the results of comparing $R^2$ cars analysis and model values similar survey data 0.909 bus 0.923, subway 0.745 to 0.922, taxi, F test P value analysis is smaller than 0.05 at the 95% confidence level as a note that was judged to have been. Trip frequency distribution analysis, but in the future, set the unit to 5km-trip frequency distribution middle zone Units from small zone units (administrative district) segmentation research is needed, and can reflect the trip distance 0~5 km interval combined function to take advantage of the gravity model and the 3-Dimentional Blancing applied research is needed to be considered.
Journal of Korean Society of Environmental Engineers
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v.33
no.4
/
pp.289-299
/
2011
We studied the characteristics of pollutant concentrations in 9 streams that flow into Shihwa Lake in order to provide the scientific data for effective implementation of total pollution loads management system (TPLMS) of the Lake. Suspended solid (SS), chemical oxygen demand (COD), dissolved nutrients ($NO_2$, $NO_3$, $NH_4$, $PO_4$ and $SiO_2$), total phosphorus (TP) and total nitrogen (TN) in stream water from industrial complexes, urban and agricultural regions were determined. Pollutant concentrations in December were higher than that in other sampling periods. COD concentration from industrial complex region with average of 12.6 mg/L was 2 times higher those from urban region (6.6 mg/L) and agricultural region (5.9 mg/L). TP concentration from industrial region also showed higher concentration than other regions. TN concentration in stream water was 5.89 mg/L for industrial region, 3.02 mg/L for urban region and 5.27 mg/L for agricultural region, respectively, suggesting inflow of TN due to fertilizer usage in agricultural field. Relative percentage of nitrogen compounds in TN follows the sequence: $NH_4$ (35.1%) > $NO_2$ (20.0%) > DON (22.8%) > PON (8.9%) > $NO_2$ (3.2%). Concentrations of dissolved nutrients, TP and TN in stream water were 3.2~37.2 times higher than that in Shihwa Lake seawater, therefore large amount of pollutants may be directly entered into Shihwa Lake without any treatment. For Gunja stream of industrial region, pollutants at midstream showed relatively higher concentration compared to upstream and downstream. It is necessary to manage the illegal discharging of sewage and waste water. Our results provide valuable informations on the estimation and reduction of total pollutant loads in the process of establishing adequately strategic and implemental plan of Shihwa Lake TPLMS.
Bird strike accidents, a collision between aircraft and birds, have been increasing annually due to an increasing number of aircraft operating each year to meet heavier demand for air traffic. As such, many airports have conducted studies to assess and manage bird strike risks effectively by identifying and ranking bird species that can damage aircraft based on the bird strike records. This study was intended to investigate the bird species that were likely to threaten aircraft and compare and discuss the risk of each species estimated by the single-matrix and multi-matrix risk assessment models based on the Integrated Flight Information Service (IFIS) data collected in Gimpo, Gimhae and Jeju Airports in South Korea from 2005 to 2013. We found that there was a difference in the assessment results between the two models. The single-matrix model estimated 2 species and 6 taxa in Gimpo and Gimhae Airports and 2 species and 5 taxa in Jeju Airport to have the risk score above "high," whereas the multi-matrix model estimated 3 species and 5 taxa in Gimpo Airport, 4 species and 5 taxa in Gimhae Airport, and 2 species and 3 taxa in Jeju Airport to have the risk score above "very high." Although both models estimated the similar high-risk species in Gimpo and Gimhae Airports, there was a significant difference in Jeju Airport. Gimpo and Gimhae Airports are near the estuary of a river, which is an excellent habitat for large and heavy waterbirds. On the other hand, Jeju Airport is near the coast and the city center, and small and light bird species are mostly observed. Since collisions with such species have little effect on aircraft fuselage, the impact of common variables between the two models was small, and the additional variables caused a significant difference between the estimation by the two models.
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