In this research, we present a new methodology to indirectly assess the concentration levels of the biochemical oxygen demand (BOD) and total nitrogen (T-N) of dewatered cake by evaluating the amounts of the volatile solids (VS) and total solids (TS). Information regarding the BOD and T-N concentrations of dewatered cake could then be used to estimate the Greenhouse Gas (GHG) emissions caused by sewage treatment. To this end, regression equations were derived by considering the relationship between the product of two solid terms: (TS × VS) and BOD/T-N levels of digested sludge. The optimal regression equations for BOD and T-N were computed as y = 152425x (R2= 0.969, p < 0.05) and y = 128378x (R2= 0.970, p < 0.05), respectively. For the purposes of verification, the applicability of the regression equations was tested using the data for other periods not considered in the regression analysis. Accordingly, the differences between the measured and estimated concentration data (derived using the regression equations) were within the standard deviation of the measured concentrations. However, the concentrations estimated by regression equations were quite different from those obtained by conventional methods. Nonetheless, such differences did not significantly change GHG emissions, thus we conclude that the plant specific regression equations can be derived from the methods presented in this study, although more efforts are needed for its validation in various respects.

최근 국내 하천 및 호소와 연안해역의 부영양화로 인한 녹조 및 적조현상이 커다란 환경 문제로 대두되고 있으며 용수이용에 지장을 초래하고 있다. 정부의 환경정책이 하수처리체계를 BOD 등 유기물질 처리위주에서 질소･인 처리체계로 전환하여 하천, 호소, 해역의 부영양화를 방지하기 위해 질소･인 등의 방류수 수질기준을 강화하였다. 강화된 방류수 수질기준 준수를 위한 2000년대 이후 하수처리시설의 고도개량사업이 진행되어 2013년말 기준 시설용량 500톤/일이상 하수처리시설의 90%가 고도처리시설을 도입한 실정이다. 본 연구에서는 고도처리공정 도입 전･후의 슬러지 발생량을 비교, 검토하였으며 2013년말 기준 통계자료에 의한 비교, 검토한 결과, 생물학적처리방법으로 처리되는 하수처리시설의 톤당 슬러지 발생원단위는 0.55kg/㎥･일이며 고도처리시설이 도입된 처리시설의 슬러지 발생원단위는 0.48kg/㎥･일로 나타나 고도처리시설 도입후 슬러지 발생량이 저감되는 것으로 분석되었다. 또한 고도처리공법을 크게 A2/O계열, SBR계열, 담체계열, 미생물계열, 막계열, 기타 6계열로 분류하여 고도처리공법 계열별로 슬러지 발생원단위를 비교･검토한 결과 SBR계열 및 담체계열에서 0.50kg/㎥･일의 높은 슬러지 발생원단위를 보였으며 막계열에서 가장 적은 0.30kg/㎥･일의 슬러지 발생원단위를 보였다.

To identify the characteristics of wastewater flow generated in treatment basins of Seogwipo-city, we selected 3 stations representing the basin and performed 7 times of field survey including 5 times in dry periods and 2 times in wet periods from Feb. 25 to May 27, 2002 for the selected stations. From the analysis of flow data measured for more than 60 days in the interval of 5 minutes and concentration data obtained from laboratory analysis, we can draw several conclusions. First, in the analysis of diumal variation of wastewater flow for land-use types, we could find the following results: in the residential area, it is observed that wastewater flow rates rise early in the morning for the office-going hour and fall gradually and rise again after the office-leaving hour, showing typical residential wastewater flow pattern, while for the residential and commercial area flow rates rise early in the morning at the office-going hour and move up and down repeatedly within wide range and last till the office-leaving hour, which can be resulted from wastewater that is generated by tourists activated after early in the afternoon, while for the touristy area flow rates rise early in the morning and fall gradually and rise again within wide range. Second, in the analysis of temporal variation of wastewater flow for monthly, it can be observed that in the residential area, in the residential and commercial areas the flow rate of May is higher than that of Feb., March, while for the touristy area flow rate is without monthly because it reflects the movement of population, Third, in wet periods concentration of water-quality item such as SS, BOD, and CODCr is high in the beginning of rainfall by first flush, and falls down gradually to reach the steady state, which is the level of wastewater in dry periods after the cease of storm water due to diluting effect resulting from additional runoff water through storm sewers.

This study was performed to improve water demand estimation and analize correlation between generation of domestic sewage and domestic water use. To improve the prediction of water demand estimation, new water demand equation was developed. The results is as follows. InQt = β0 + β₁InPt + β₂InYt + β₃InHt + εt By using the statistical analysis of the "generation of domestic sewage" and "domestic water use", the regression equation between them is formed. The result is as follows. ＿ Generation of domestic sewage = 0.8487 × Domestic water use + 684.57 (R² = 0.972)