• Korean Journal of Soil Science and Fertilizer
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• v.44 no.4
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• pp.527-533
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• 2011

Decomposition of compost applied to soils is affected basically by its biological stability; but, many other chemical properties of the compost may also influence compost organic-C mineralization. This study was conducted to investigate the principal substrate quality factors of composts that determine C mineralization of compost with similar stability degree (SD). Three composts samples with similar SD but different chemical properties such as pH, C/N, $K_2SO_4$-extractable C, and molar ratio of $NH_4^+$ to $NO_3^-$ were mixed with an acid loamy soil and $CO_2$ emission was monitored during the laboratory incubation for 100 days. Temporal pattern of cumulative compost organic-C mineralization expressed as % of total organic C ($C_{%\;TOC}$) followed double exponential first order kinetics model and the $C_{%\;TOC}$ ranged from 4.8 to 11.8% at the end of incubation. The pattern of C%TOC among the composts was not coincident with the SD pattern (40.1 to 58.6%) of the composts; e.g. compost with the lowest SD resulted in the least $C_{%\;TOC}$ and vice versa. This result indicates that SD of compost can not serve as a concrete predictor of compost mineralization as SD is subject not only to maturity of compost but also to characteristics of co-composting materials such as rice hull (low SD) and sawdust (high SD). Meanwhile, such pattern of $C_{%\;TOC}$ collaborated with pH, C/N, $K_2SO_4$-extractable C, and molar ratio of $NH_4^+$ to $NO_3^-$ of the composts that are regarded as chemical indices of the progress of composting. Therefore, for better prediction of compost mineralization in soils, it is necessary to consider both SD and other chemical indices (pH, C/N, and molar ratio of $NH_4^+$ to $NO_3^-$).

• Journal of Korean Society of Environmental Engineers
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• v.33 no.1
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• pp.25-31
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• 2011

In this study, model-based $NH_4-N$ predictive control algorithm by using influent pattern was developed and evaluated for effective control application in $A^2/O$ process. A pilot-scale $A^2/O$process at S wastewater treatment plant in B city was selected. The behaviors of organic, nitrogen and phosphorous in the biological reactors were described by using the modified ASM3+Bio-P model. A one-dimensional double exponential function model was selected for modeling of the secondary settlers. The effluent $NH_4-N$ concentration on the next day was predicted according to model-based simulation by using influent pattern. After the objective effluent quality and simulation result were compared, the optimal operational condition which able to meet the objective effluent quality was deduced through repetitive simulation. Next the effluent $NH_4-N$ control schedule was generated by using the optimal operational condition and this control schedule on the next day was applied in pilot-scale $A^2/O$ process. DO concentration in aerobic reactor in predictive control algorithm was selected as the manipulated variable. Without control case and with control case were compared to confirm the control applicability and the study of the applied $NH_4-N$control schedule in summer and winter was performed to confirm the seasonal effect. In this result, the effluent $NH_4-N$concentration without control case was exceeded the objective effluent quality. However the effluent $NH_4-N$ concentration with control case was not exceeded the objective effluent quality both summer and winter season. As compared in case of without predictive control algorithm, in case of application of predictive control algorithm, the RPM of air blower was increased about 9.1%, however the effluent $NH_4-N$ concentration was decreased about 45.2%. Therefore it was concluded that the developed predictive control algorithm to the effluent $NH_4-N$ in this study was properly applied in a full-scale wastewater treatment process and was more efficient in aspect to stable effluent.