• Journal of the Korean Society of Environmental Restoration Technology
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• v.12 no.2
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• pp.73-82
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• 2009

The traffic volume of Seoul is extremely high in comparison to other major cities in Korea, and the result has been harmful physical and mental exposure to pollution by Seoulites on a regular basis. The street air pollution is more important than the others, because the air pollution generated by street traffic directly impacts the health of nearby pedestrians. This problem requires urgent attention and resolution. Among the factors creating the air pollution originating from the street, is the configuration of streets, which have emerged as the most significant because it is related to air and pollutant dispersion. Therefore, this study was conducted under the assumption that street form affects the air quality. Study sites were classified by street characteristics, and air quality was analyzed in each class. Then the OSPM (Operational Street Pollution Model) was employed to simulate the relationship between street configuration and air quality of streets within the old city center and new city center in Seoul. After that this study analyzed the correlation between air pollution and the spatial configuration of urban streets (ex. street width, building height, building density, etc.) to determine their contributions to air pollution. The outcome of this study is as follows : First, the result that was derived from the correlation analysis between street configuration and air quality hewed that the air pollution of the street is influenced by the average height of building, width of the roads as well as traffic volume. On the roadside, the concentration level of $NO_2$ is mainly affected by the average height of building and the deviation of building height along the street and CO is affected by street width. The outcome of this study can be used as a basis for more sound urban design policies, and the promotion of desirable street environments for pedestrians.

• Journal of Environmental Science International
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• v.13 no.8
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• pp.733-737
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• 2004

FThe aim of this study was to carry out a preliminary test of the air quality modelling system (HIRES-AIRCHEM) developed at The University of New South Wales, particularly with regard to the forecast ozone distribution. This was achieved by assimilating the New South Wales State Environment Protection Authority (EPA) emissions inventory, consisting of road and non-road sources, and running the system over the Sydney metropolitan area for the four day period 25-28 February 1998. During this period ozone readings exceeded the EPA's goal of 8pphm on several occasions. The model forecasts of ozone distribution verified well with the EPA's ozone readings. This result has important implications for possible future use of the system as a tool for routinely predicting and assessing air quality.

• Proceedings of the Korean Environmental Sciences Society Conference
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• 2003.11a
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• pp.212-215
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• 2003

The aim of this study was to test the air quality modelling system (HIRES-AIRCHEM) of The University of New South Wales particularly with regard to forecast ozone distribution. This was achieved by assimilating the New South Wales State EPA emissions inventory consisting of road and non-road sources and running the system over the Sydney metropolitan area for the four day period 25-28 February 1998. During this period ozone readings exceeded the EPA＇s goal of 80ppb on several occasions. The model forecasts of ozone distribution verified well with the EPA＇s ozone readings. This result has important implications for possible future use of the system as a tool for routinely assessing air quality.

• Journal of Korean Society for Atmospheric Environment
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• v.25 no.4
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• pp.264-274
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• 2009

Concentration of Air Quality Models (CMAQ) has a deep connection with emissions and wind fields. In particular the wind field is highly affected by local topography and plays an important role in transport and dispersion of contaminants from the pollution sources. The purpose of this study is to examine the impact of interpolation on Air quality model. This study was designed to evaluate enhancement of MM5 and CMAQ predictions by using Four Dimensional Data Assimilation (FDDA), the SONDE data and the national meteorological station and the MODerate resolution Imaging Spectroradiometer (MODIS). The alternative meteorological fields predicted with and without MODIS data were used to simulate spatial and temporal variations of ozone in combined with CMAQ on June 2006. The result of this study indicated that data assimilation using MODIS data provided an attractive method for generating realistic meteorological fields and dispersion fields of ozone in the Korea peninsular, because MODIS data in 10 km domain are grid horizontally and vertically. In order to ensure the success of Air quality model, it is necessary to FDDA using MODIS data.

• Journal of Korean Society for Atmospheric Environment
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• v.21 no.3
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• pp.377-397
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• 2005

A new box model is proposed to describe the dynamic trend of the spatially averaged concentrations of pollutants over a large urban area such as metropolitan Seoul. Being averaged temporally and spatially over a thresh-hold scales, the dynamics of the pollutant concentration becomes simple enough that the governing equation can be expressed in an explicit algebraic form as a function of several meteorological factors and the pollutant emission rate. The single most important meteorological factor is the wind speed dominating the daily variations of the pollutant concentrations. Given the meteorological data from the surface station in the metropolitan Seoul, the model concentration shows excellent agreement with observations from January 1, 1990 to December 31, 2000: the modeling uncertainty, for example, of $NO_2$ concentrations, defined as mean differences between the model concentrations and observations is $16\%$ of the model concentrations. Even for $PM_{10}$ of which secondary sources are considered to be very important and simple box model is irrelevant to, the model performance turns out good, modeling uncertainty being about $32\%$.

• The Journal of the Convergence on Culture Technology
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• v.9 no.6
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• pp.1065-1071
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• 2023

In this paper discuss with research developing an LSTM model for classifying the behavior of occupants within a residence. The multi-sensor consists of an IAQ (Indoor Air Quality) sensor that measures indoor air quality, a UWB radar that tracks occupancy detection and location, and a Piezo sensor to measure occupants' biometric information, and collects occupant behavior data such as going out, staying, cooking, cleaning, exercise, and sleep by constructed an experimental environment similar to the actual residential environment. After the data with removed outliers and missing, the LSTM model is used to calculate accuracy, sensitivity, specificity of the occupant behavior classification model, T1 score.

• Journal of Environmental Science International
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• v.19 no.8
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• pp.971-981
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• 2010

The objectives of this study were to measure ambient total gaseous mercury (TGM) concentrations in Seoul, to analyze the characteristics of TGM concentration, and to identify of possible source areas for TGM using back-trajectory based hybrid receptor models like PSCF (Potential Source Contribution Function) and RTWC (Residence Time Weighted Concentration). Ambient TGM concentrations were measured at the roof of Graduate School of Public Health building in Seoul for a period of January to October 2004. Average TGM concentration was $3.43{\pm}1.17\;ng/m^3$. TGM had no notable pattern according to season and meteorological phenomena such as rainfall, Asian dust, relative humidity and so on. Hybrid receptor models incorporating backward trajectories including potential source contribution function (PSCF) and residence time weighted concentration (RTWC) were performed to identify source areas of TGM. Before hybrid receptor models were applied for TGM, we analysed sensitivities of starting height for HYSPLIT model and critical value for PSCF. According to result of sensitivity analysis, trajectories were calculated an arrival height of 1000 m was used at the receptor location and PSCF was applied using average concentration as criterion value for TGM. Using PSCF and RTWC, central and eastern Chinese industrial areas and the west coast of Korea were determined as important source areas. Statistical analysis between TGM and GEIA grided emission bolsters the evidence that these models could be effective tools to identify possible source area and source contribution.

• Journal of Environmental Science International
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• v.15 no.5
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• pp.387-396
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• 2006

The numerical modeling and comparison with observations are performed to find out the detailed structure of meteorology and the characteristic of related dispersion phenomena of the non-reactive air pollutant at Kyoungin region, South Korea, where several industrial complex including Siwha, Banwol and Namdong is located. MM5 (Fifth Generation NCAR/Penn State Mesoscale Model), 3-D Land/sea breeze model and 3-D diagnostic meteorological model have been utilized for the meteorological simulation for September, 2002 with each different spatial resolution, while 3-D Eulerian air dispersion model for the air quality study. We can see the simulated wind field shows the very local circulation quitely well compared with in-site observations in shoreline area with complex terrains, at which the circulation of Land/sea breeze has developed and merged with the mountain and valley breeze eventually. Also it is shown in the result of the dispersion model that the diurnal variation and absolute value of daily mean $SO_2$ concentrations have good agreement with observations, even though the instant concentration of $SO_2$ simulated overestimates around 1.5 times rather than that of observation due to neglecting the deposition process and roughly estimated emission rate. This results may indicate that it is important for the air quality study at shoreline region with the complex terrain to implement the high resolution meteorological model which is able to handle with the complicate local circulation.

• Environmental Engineering Research
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• v.14 no.1
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• pp.53-60
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• 2009

The main objective was to develop and assess a dynamic fate and transport model for lead in air, soil, sediment, water and vegetation. Daejeon was chosen as the study area for its relatively high contamination and emission levels. The model was assessed by comparing model predictions with measured concentrations in multi-media and atmospheric deposition flux. Given a lead concentration in air, the model could predict the concentrations in water and soil within a factor of five. Sensitivity analysis indicated that effective compartment volumes, rain intensity, scavenging ratio, run off, and foliar uptake were critical to accurate model prediction. Important implications include that restriction of air emission may be necessary in the future to protect the soil quality objective as the contamination level in soil is predicted to steadily increase at the present emission level and that direct discharge of lead into the water body was insignificant as compared to atmospheric deposition fluxes. The results strongly indicated that atmospheric emission governs the quality of the whole environment. Use of the model developed in this study would provide quantitative and integrated understanding of the cross-media characteristics and assessment of the relationships of the contamination levels among the multi-media environment.

• Journal of Korea Multimedia Society
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• v.22 no.11
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• pp.1300-1312
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• 2019

BSTRACT In this paper, PM10 forecast model using DNN(Deep Neural Network) is developed for Seoul region. The previous Julian forecast model has been developed using weather and air quality data of Seoul region only. This model gives excellent results for accuracy and false alarm rates, but poor result for POD(Probability of Detection). To solve this problem, an WA(Wide Area) forecasting model that uses Chinese data is developed. The data is highly correlated with the emergence of high concentrations of PM10 in Korea. As a result, the WA model shows better accuracy, and POD improving of 3%(D+0), 21%(D+1), and 36%(D+2) for each forecast period compared with the Julian model.