To improve modeling performance of CALPUFF in predicting dispersions of methane as the greenhouse gas and hydrogen sulfide as odor inducing pollutants emitted from Daejeon Landfill, we conducted tracer experiments of C2H2 and compared calculated concentrations by CALPUFF model under different dispersion coefficients with those measured as the tracer. The PG (Pasquill-Gillford) and micro- meteorological options in determining the dispersion coefficients in CALPUFF were tested against the tracer measurements. The results show that the micro-meteorological option, in which the dispersion coefficients are calculated by a similarity theory in planetary boundary layer, leads to a better agreement with the measured tracer concentrations than ISC-PG option.

This study was conducted to induce the effective counterplan of odor management in the Sihwa industrial complex(SIC) utilizing to CALPUFF model with sensory odor. The CALPUFF model was applied to simulate a sensory odor, and was evaluated for odor applicability and the distribution status of odor in SIC was predicted. The simulated concentration showed lower than observed concentration but the prediction of odor was so excellent. The simulation result of CALPUFF model for SIC showed that annual mean odor unit was 5∼7 OU/㎥ (min. 3 OU/㎥, max. 25 OU/㎥). The annual mean odor unit in residential area was not high as 1∼3 OU/㎥ but was predicted to be affected by the weather status in the industrial complex. The odor emission sources of high concentration were distributed in the seashore. Therefore the management of the high concentration sources will be further demanded.

This study was carried out to find the optimal methods in odor dispersion modeling. The CALMET and CALPUFF recommended by US EPA were used in the study. The accuracy of 3 dimensional meteorological field was one of the important parameters in the modeling, To understand the sensitivity of CALMET according to meteorological input data, four Cases were tested and compared with the measurements. The four Cases with various input data were followed : Case 1 was surface and upper measured data, Case 2 was MM5 data only, Case 3 was surface weather station and MM5 data, Case 4 was surface weather station, upper-air weather station and MM5 data. The comparisons of wind speeds, wind direction and temperatures by CALMET model with observations under various input data showed that Case 4 was more accurate than the other Cases. The results of CALPUFF dispersion modeling were compared with odor complains data and they showed that there were similar patterns even if some discrepancies existed. CALPUFF dispersion modeling was also compared with odor monitoring station data, and there was a good agreement in the threshold odor concentrations. In order to get more accurate result for odor modeling, we need following additional measures: First, fine tuning of odor emission data with the consideration of variations of emission fate according to operation hour of the odor emitting facilities. Second, construction of continuous monitoring system(on-line GC, odor a sensor etc.) was necessary to monitor the odor compound concentrations.