In the present study, the BOD and T-N concentrations of dewatered cake required to estimate the GHG emissions from the sewage treatment were estimated from the TS and VS concentrations in dewatered cake.
The regression analysis between (TS × VS) vs BOD and (TS × VS) vs. T-N of digested sludge was studied to derive the methods to estimate BOD and T-N concentrations from TS and VS concentrations of dewatered cake. The optimal regression equation derived from regression analysis was as follows: y=152425x (R2=0.969, p<0.05) for BOD and y=128378x (R2=0.970, p<0.05) for T-N.
As a result of verifying the applicability of the regression equation to the digested sludge of the period not included in the regression analysis, the differences between the measured and estimated concentration data (derived by regression equation) were within the standard deviation of measured concentration. These results indicate that it is possible and appropriate to estimate the BOD and T-N concentrations of sewage sludge from (TS × VS). The reason for the concentration difference in BOD is that (TS × VS) does not accurately reflect the VS fraction in the TS. For T-N, the constant of the regression equation is set to zero, which tends to somewhat decrease the inorganic nitrogen content.
The results of the verification for the applicability of the regression equation to dewatered cake suggested that the differences between the BOD and T-N estimated by the regression equation and those by the mass balance were considerably large. The main reason for the differences can be that the method of estimation by the material balance is greatly affected by the filtrate of dewatering facility. However, the differences did not significantly affect the total GHG emissions in the municipal waste sector.
The results of the verification of the applicability of the regression equation to other sewage treatment plants demonstrated that the differences between the estimation concentration by the regression equation and the actual measurement concentration were inconsistent according to the sewage treatment plant. Therefore, it can be suggested that the application of the regression equations to other sewage treatment plants was not appropriate. However it appears to be possible to derive the plant specific regression equations according to this study method and to reflect the equations to the estimation of GHG emissions.
From the results outlined above, it can be concluded that (TS × VS) of sewage sludge has sufficient correlation to represent BOD and T-N concentration, and that BOD and T-N concentrations can be estimated with (TS × VS) as an independent variable.
In this study, we present BODsl = 152425 (TS × VS) and T-Nsl = 128378 (TS × VS) as the method to estimate BOD and TN concentration of dewatered cake by (TS × VS) in sewage treatment plant A. We also propose the following new modified formula to estimate GHG emissions by sewage treatment plants that reflects the method of estimating BOD and T-N concentrations by the (TS × VS) of the dewatered cake at sewage treatment plant A.

CH4={BODin×Qin-BODout×Qout-152425(TS×VS)sl×Qsl}×0.000001×EF-R

N2O={T-Nin×Qin-T-Nout×Qout-128378(TS×VS)sl×Qsl}×0.000001×EF×1.571