Relatively low efficiency in anaerobic digestion process is mainly caused by unproper mixing method. In this study, tray motion type agitator was applied in actual anaerobic digestion tank in order to improve the digestion efficiency, equalize the flow velocity distribution and energy saving. The impeller of tray motion type agitator was reciprocated vertically. Gas lift type agitator and tray motion type agitator appears almost same mixing efficiency include digestion rates. However, tray motion type agitator have shown that lower energy consumption compared to the conventional gas lift type agitator. Implementation of tray motion type agitator in the anaerobic digestion tanks contributed to the stabilization of mixing environment, efficiency and energy efficiency of the tank.

In this study, a newly developed agitator with hydrofoil impeller applied to actual biological process in advanced wastewater treatment plant was evaluated. Several series of experiments were conducted in two different wastewater treatment plants where actual problems have been occurred such as the production of scums and sludge settling. For more effective evaluation, computational fluid dynamics (CFD) and measurements of MLSS (Mixed Liquor Suspended Solids) and DO (Dissolved Oxygen) were used with other measuring equipments. After the installation of one unit of vertical hydrofoil agitator in plant A, scum and sludge settling problems were solved and more than seventy percent of operational energy was saved. In case of plant B, there were three cells of each anoxic and anaerobic tanks, and each cell had one unit of submersible horizontal agitator. After the integration of three cells to one cell in each tank, and installation of one vertical hydrofoil agitator per tank, all the problems caused by improper mixing were solved and more than eighty percent of operational energy was found to be saved. Simple change of agitator applied to biological process in wastewater treatment plant was proved to be essential to eliminate scum and sludge settling problems and to save input energy.

Numerical experiments were carried out to investigate the effect of data assimilation of observational data on weather and PM (particulate matter) prediction. Observational data applied to numerical experiment are aircraft observation, satellite observation, upper level observation, and AWS (automatic weather system) data. In the case of grid nudging, the prediction performance of the meteorological field is largely improved compared with the case without data assimilations because the overall pressure distribution can be changed. So grid nudging effect can be significant when synoptic weather pattern strongly affects Korean Peninsula. Predictability of meteorological factors can be expected to improve through a number of observational data assimilation, but data assimilation by single data often occurred to be less predictive than without data assimilation. Variation of air pressure due to observation nudging with high prediction efficiency can improve prediction accuracy of whole model domain. However, in areas with complex terrain such as the eastern part of the Korean peninsula, the improvement due to grid nudging were only limited. In such cases, it would be more effective to aggregate assimilated data.

Groundwater recharge characteristics in a fractured granite area, Mt. Geumjeong, Korea. was interpreted using bedrock groundwater and wet-land water data. Time series analysis using autocorreclation, cross-correlation and spectral density was conducted for characterizing water level variation and recharge rate in low water and high water seasons. Autocorrelation analysis using water levels resulted in short delay time with weak linearity and memory. Cross-correlation function from cross-correlation analysis was lower in the low water season than the high water season for the bedrock groundwater. The result of water level decline analysis identified groundwater recharge rate of about 11% in the study area.

The diagnostic software for the wastewater treatment plant using activated-sluge process is developed in order to increase the efficiency of management of the wastewater treatment plant. This software is based on the expert system and the visualized user interface including the diagnosis of quantitative and qualitative data. For the generalization of this software, the initialization of each unit process and updating the files can be possible.

Fuzzy algorithm of automatic control for dissolved oxygen(DO) concentration in the aeration tank of an activated sludge process is proposed. Among variables repirometry and air flowrate are selected as significant input factors and the relationship with DO is estimated using a multiple regression model. The DO concentration and the amount of repirometry are fuzzified and the fuzzy rule base are determined. Using the fuzzy algorithm, the change of amount of air flowrate are determined and the change of amount of DO is derived.

In this research, two stochastic models are considered to detect and estimate the effect of air temperature change due to industrialization in Ulsan area. Using the monthly mean minimum air temperature anomalies, the data are divided into pre-industrialization part and industrialization one for analysis. The ARMA(autoregressive moving-average) model and intervention model have been applied to the data for the analysis. The results show that the variability of minimum temperature anomalies are very significant in 1989, and also significant in 1971 when the industrialization have started. Therefore, it is stochastically possible to estimate the time when the affection of increase of the temperature concerning industrialization to climate change in Ulsan area has happened.