This paper describes the performance of the module-type drying apparatus for the composting of a food waste. The drying apparatus mainly consists of a screw-type food waste agitator, an air exhaust blower, a heat supply tube and a heat source. Two different discharging flow conditions of the drying apparatus, 4 and 5 m3/min, are introduced. Partly dried by-products after six hours drying operation in the drying apparatus is obtained while drying temperature keeps constant of 60oC. It is noted that the by-products needs to sufficient decay period for the composting. Deodorizing apparatus having a zigzag flow and a nozzle, which is connected to the drying apparatus, is also designed to enhance the removing performance of the odor. Throughout experimental measurements, time to the drying temperature of 60oC near the screw-type food waste agitator is shortened as discharging flow rate of the system decreases. The moisture content decreases to 50 percent after operation for 4 hours. Furthermore, the odor of the food waste is satisfied with the environment exhaust standard through the deodorizing apparatus.

The MFFn(Mass first flush), EMCs(Event mean concentrations) and runoff loads were analyzed for various rainy events(monitoring data from 2011 to 2012) in transportation area(rail road in station). The pollutant EMCs by volume of stormwater runoff showed the BOD5 9.6 ㎎/L, COD 29.9 ㎎/L, SS 16.7 ㎎/L, T-N 3.271 ㎎/L, T-P 0.269 ㎎/L in the transportation areas(Railroad in station). The average pollutant loading by unit area of stormwater runoff showed the BOD5 27.26 kg/㎢, COD 92.55 kg/㎢, SS 50.35 kg/㎢, T-N 10.13 kg/㎢ and T-P 10.13 kg/㎢ in the transportation areas. Estimated NCL-curve(Normalized cumulated-curve) was evaluated by comparison with observed MFFn. MFFn was estimated by varying n-value from 10% to 90% on the rainy events. The n-value increases, MFFn is closed to '1'. As time passed, the rainfall runoff was getting similar to ratio of pollutants accumulation. The result of a measure of the strength of the linear relationship between observed data and expected data under model was good.