• Title/Summary/Keyword: ISCST model

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The 3rd National Conference Of Professional engineers - On The Problems and Guideline of The Air Quality Model Operation (제3회 전국기술사대회 특집(환경) - 대기모델 운영의 문제점 및 가이드라인 설정방향)

  • Park, Sun-Hwan
    • Journal of the Korean Professional Engineers Association
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    • v.42 no.4
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    • pp.40-44
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    • 2009
  • The analysis of air quality model applied for EIA in Korea indicates that ISCST3 and CALINE3 dominate the model, and it causes the problem that regional and business characteristics are not taken into account. To solve this problem, it appears necessary to build guideline of the air quality model operation. First of all, to implement the above plan we need to categorize the site into simple and complex terrain, coast to consider regional characteristics, and the sources of pollutants into point/area/line as well. To make the procedure more efficient with reduced time and less cost, we are to apply screening model for prelimninary work of the suggested model.

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Sensitivity Analysis of Stability and Other Meteorological Input Parameters for ISC3 Model at Low Wind Speed (저풍속에서의 ISC3 모델의 안정도 및 기타 기상변수에 대한 민감도 분석)

  • 박영재;김유정;김성중;선우영
    • Proceedings of the Korea Air Pollution Research Association Conference
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    • 2003.11a
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    • pp.439-440
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    • 2003
  • 대기질 모델(Air Quality Model)은 환경영향평가에서 필수적이다. 환경영향평가에 쓰이는 대기질 모델은 대부분 가우시안 플륨 모델이며, 그 중 ISC(Industrial Source Complex 3)이 가장 널리 쓰인다. 그러나 ISC3가 저풍속시 정확도가 떨어지지만 환경영향평가의 대기질 평가시 이에 대한 고려가 거의 이뤄지지 않은채 대기질 평가가 이뤄지고 있다. 본 연구에서는 ISCLT(Long Term)와 ISCST(Short Term) 모델에 대하여 입력되는 기상변수에 대한 민감도 분석을 수행함으로써 기상변수가 모델의 결과에 미치는 영향을 알아보고자 하였다. (중략)

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Comparison between the Application Results of NNM and a GIS-based Decision Support System for Prediction of Ground Level SO2 Concentration in a Coastal Area

  • Park, Ok-Hyun;Seok, Min-Gwang;Sin, Ji-Young
    • Environmental Engineering Research
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    • v.14 no.2
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    • pp.111-119
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    • 2009
  • A prototype GIS-based decision support system (DSS) was developed by using a database management system (DBMS), a model management system (MMS), a knowledge-based system (KBS), a graphical user interface (GUI), and a geographical information system (GIS). The method of selecting a dispersion model or a modeling scheme, originally devised by Park and Seok, was developed using our GIS-based DSS. The performances of candidate models or modeling schemes were evaluated by using a single index(statistical score) derived by applying fuzzy inference to statistical measures between the measured and predicted concentrations. The fumigation dispersion model performed better than the models such as industrial source complex short term model(ISCST) and atmospheric dispersion model system(ADMS) for the prediction of the ground level $SO_2$ (1 hr) concentration in a coastal area. However, its coincidence level between actual and calculated values was poor. The neural network models were found to improve the accuracy of predicted ground level $SO_2$ concentration significantly, compared to the fumigation models. The GIS-based DSS may serve as a useful tool for selecting the best prediction model, even for complex terrains.

A Development of Air Dispersion Modeling Software, AirMaster (대기확산 모델링 Software, AirMaster 개발)

  • Koo, Youn-Seo;Yoon, Hee-Young;Kim, Sung-Tae;Jeon, Kyung-Seok;Park, Sung-Soon;Kweon, Hee-Yong;Hwang, Ju-Hyun;Kim, Jong-Hwa;Choi, Jong-Keun;Lee, Im-Hak
    • Journal of Environmental Impact Assessment
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    • v.9 no.4
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    • pp.323-338
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    • 2000
  • A Korean air dispersion modeling software, AirMaster, was developed on a basis of dispersion theories adopted in U.S. EPA's ISC3 (Industrial Source Complex - version 3) model to assess the air quality impact from the stacks. Key characteristics of AirMaster are as follows: 1) The building downwash effect can be easily simulated; 2) The screen, long term, and short term models can be run independently; 3) The input data to run the model such as meteorological and terrain data are supplied automatically from the databases in AirMaster; and 4) The modeling procedure is easy and simple under the GUI window environment. In order to validate AirMaster, comparisons with ISC3 model and Indianapolis tracer experiment were carried out. It was shown that AirMaster was identical to ISCST3 and ISCLT3 models in predicting the 1 hr to annual concentrations from the stack under various stack emission and meteorological conditions. The 1 hr concentrations predicted by AirMaster also showed a good agreement with the Indianapolis tracer measurements.

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Variation of ANN Model's Predictive Performance Concerning Short-term (<24 hrs) $SO_2$ Concentrations with Prediction Lagging Time

  • Park, Ok-Hyun;Sin, Ji-Young;Seok, Min-Gwang
    • Journal of Korean Society for Atmospheric Environment
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    • v.24 no.E2
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    • pp.63-73
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    • 2008
  • In this study, neural network models (NNMs) were examined as alternatives to dispersion models in predicting the short-term $SO_2$ concentrations in a coastal area because the performances of dispersion models in coastal areas have been found to be unsatisfactory. The NNMs were constructed for various combinations of averaging time and prediction time in advance by using the historical data of meteorological parameters and $SO_2$ concentrations in 2002 in the coastal area of Boryeung, Korea. The NNMs were able to make much more accurate predictions of 1 hr $SO_2$ concentrations at ground level in the morning in coastal area than the atmospheric dispersion models such as fumigation models, ADMS3 and ISCST3 for identical conditions of atmospheric stability, area, and weather. Even when predictions of 24-h $SO_2$ concentrations were made 24 hours in advance, the predictions and measurements were in good accordance(correlation coefficient=0.65 for n=216). This accordance level could be improved by appropriate expansion of training parameters. Thus it may be concluded that the NNMs can be successfully used to predict short-term ground level concentrations averaged over time less than 24 hours even in complex terrain. The prediction performance of ANN models tends to improve as the prediction lagging time approaches the concentration averaging time, but to become worse as the lagging time departs from the averaging time.

Estimation of Fugitive Dust Emission and Impact Assessment in Constructing the New Port by Reclamation of Sea Sand (신항만 해사 매립 공사시 비산먼지 발생량 산정 및 주변영향평가)

  • Choi, Won-Joon;Cho, Ki-Chul;Lee, Eun-Yong;Na, Ha-Young;Lee, Soon-Kyu;Oh, Kwang-Joong
    • Journal of Environmental Impact Assessment
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    • v.15 no.4
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    • pp.237-247
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    • 2006
  • In case of studied area located around the sea, the data measured from the regional meteorological office is highly different from the local weather data because the diffusivity of fugitive dust varies considerably with meteorological conditions. Especially, it is very difficult to predict the amount of fugitive dust accurately as wind speed remains high frequently. In this study, the fluxes of suspended particulates as a function of the friction velocity were applied to consider the effect of wind speed on the amount of fugitive dust generated from the reclamation site. The amount of fugitive dust estimated as mentioned above was simulated by using ISCST3 model. As a result, in case of using only the Fugitive Dust Formula which is usually used in Environment Impact Assessment, the predicted $PM_{10}$ concentrations with points were $43.4{\sim}67.8{\mu}g/m^3$. However, in case of applying to the flux of suspended particulates, the predicted values of $PM_{10}$ with points were $43.3{\sim}69.1{\mu}g/m^3$, $49.5{\sim}90.4{\mu}g/m^3$ and $76.0{\sim}182.6{\mu}g/m^3$ with the wind speeds of 4.4, 5.8 and 7.7m/s, respectively. It could be possible to predict the amount of fugitive dust accurately because these predicted values were similar to the measured values. Consequently, we can establish alternatives for reduction of fugitive dust in this area damaged by fugitive dust which is caused by wind.

Comparative Study of Truck Traffic System Management for Reducing Air Pollution Impact - Forcusing on Sihwa National Industrail Complex, Siheung City - (교통체계개선에 의한 화물교통 대기오염영향 저감방안 - 시흥시 시화국가산업단지를 중심으로 -)

  • Lee, Hee-Kwan;Kim, Hyung-Chul;Kwon, Woo-Taeg
    • Journal of Environmental Impact Assessment
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    • v.15 no.1
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    • pp.23-33
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    • 2006
  • The factor of air pollution in a large industrial city is not only manufactories but also, activities related to trucks. Sihwa National Industrial Complex is located in Siheung City; due to the industries, more diverse activities related to trucks occur in Siheung City than other cities. In particular, the new residential area in Siheung City is close to the industrial complex; so, the damage of this residential area is expected that it would be more serious and vulnerable than other areas. The aim of this study is to analyze influence of the air pollution by a truck in Siheung City. ISCST3 Model and Arc View program were used for this study and Siheung City was divided into 1,000 meter by 1,000 meter grid to analyze. Furthermore, this study suggested two reduction controls of air pollution in Siheung City, and analyzed the results from these reduction managements. The results of the present condition showed that residences located in north of Sihwa Industrial Complex are influenced by air pollution material. Furthermore, air pollution by trucks has affected on the residents which is near the road in Siheung City. Therefore, this study suggested two reduction controls by the Traffic System Management. The first alternative plan is setting the truck traffic limitation zone in the road that is located in south of resident areas and many trucks traffic. Next, the second alternative plan is setting freight truck way on the most traffic road to enter the industrial complex. The reduction effect of the first alternative is good on the residential area. And, the second alternate about freight truck way is divided passenger cars into trucks. Therefore, there are increase of average speed and decrease of average concentration, and spatial reduction effects found in wide areas.