As aeration is an energy-intensive process, its control has become more important to save energy and to meet strict effluent limits. In this study, predictive aeration control based on the respirometric method has been applied to the sequencing batch reactor (SBR) process. The variation of the respiration rate by nitrification was great and obvious, so it could be a very useful parameter for the predictive aeration control. The maximum respiration rate due to nitrification was about 60 mg O2/L‧h and the maximum specific nitrification rate was about 7.5 mg N/g MLVSS‧h. The aeration time of the following cycle of the SBR was daily adjusted in proportion to that which was previously determined based on the sudden decrease of respiration rate at the end of nitrification in the respirometer. The aeration time required for nitrification could be effectively predicted and it was closely related to influent nitrogen loadings. By the predictive aeration control the aerobic period of the SBR has been optimized, and energy saving and enhanced nitrogen removal could be obtained.

Recent focus on wastewater treatment includes energy-saving and renewable energy generation for energy-independence of water infrastructures. Aeration and pumping in biological wastewater removal processes account for nearly 30-60% of the total electricity cost in real wastewater treatment plants. In this study, the performance and microbial characteristics were investigated in sequencing batch reactor under typical oxygen and oxygen limited condition. Under typical DO (7.55±0.99 mg/L) and low DO (0.23±0.08 mg/L) conditions, COD removal was stable over 91 % during SBR operation. Ammonia removal efficiency was reduced from 95.6 % to 89.2 % when DO concentration was dropped sharply. Phosphorus removal efficiency also reached 77% at oxygen-limited condition. The results indicated that removal efficiency both ammonia and phosphorus was influenced by DO condition. Microbial analysis revealed that Proteobacteria and Bacteroidetes at phylum level was dominant in typical DO and low DO conditions and DO concentration did not much affect phylum distribution. Population decrease of genera of nitrifying bacteria(Dokdonella) and Dechloromonas spp. affect removal efficiency of nitrogen and phosphorus at low DO condition.

As the sequencing batch reactor process is a time-oriented system, it has advantages of the flexibility in operation for the biological nutrient removal. Because the sequencing batch reactor is operated in a batch system, respiration rate is more sensitive and obvious than in a continuous system. The variation of respiration rate in the process well represented the characteristics of biological reactions, especially nitrification. The respiration rate dropped rapidly and greatly with the completion of nitrification, and the maximum respiration rate of nitrification showed the activity of nitrifiers. This study suggested a strategy to control the aeration of the sequencing batch reactor based on respirometry. Aeration time of the optimal aerobic period required for nitrification was daily adjusted according to the dynamics of respiration rate. The aeration time was mainly correlated with influent nitrogen loadings. The anoxic period was extended through aeration control facilitating a longer endogenous denitrification reaction time. By respirometric aeration control in the sequencing batch reactor, energy saving and process performance improvement could be achieved.

MBR공정에서 물리적 세정방법인 공기폭기(Aeration)는 장기간 막성능을 유지시키기 위한 주요 핵심 방법으로, 기존의 연구들은 산기관의 성능을 극대화시켜 공기세정을 최적화시키려 하였다. 분리막의 효율적인 슬러지 탈리를 위해 폭기위 치⋅시간⋅균일 배출성 및 데드존(Dead Zone) 감소 등에 대한 다양한 연구들이 진행되어 왔으나, 이를 통한 더 이상의 성능향상은 기대하기 어려운 상황이다. 본 연구에서는 기존의 분리막 모듈을 개량하여 공기폭기의 효과를 극대화 하는 연구를 진행하였다. 선행연구로 진행된 Lab-scale실험을 기반으로, Pilot-scale 장치를 세팅하여 장기평가 및 분석 등을 진행하였다. 동일 site에서 개량모듈한 것과 그렇지 아니한 것에 대하여 비교분석하였다.

고농도의 MBR처리공정에서 물리적 세정방법인 공기폭기(Aeration)는 장기간 막성능을 유지시키는기 위한 주요 방법으로, 기존의 연구들은 산기관의 성능을 극대화시켜 공기세정을 최적화시키는 연구를 주로 하였다. 효율적인 슬러지 탈리를 위해 폭기위치⋅시간⋅균일 배출성 및 데드존(Dead Zone) 감소 등 다양한 연구들이 진행되어 왔으며, 이를 통한 더 이상의 성능향상은 기대하기 어려운 상황이다. 산기관 최적화 이외에 막성능을 장기간 유지하기 위해서는 막모듈 전체에 공기에 의한 슬러지 탈리가 일어나야 하며, 이는 모듈의 구조적인 문제를 개선함으로써 해결책을 찾을 수 있다. 본 연구에서는 기존의 분리막 모듈과 구조가 변경된 모듈의 오염(fouling)에 따른 분리막 성능을 비교하고자 한다.

저농도 합성폐수를 처리하는 membrane bioreactor (MBR) 시스템에서 공기폭기와 PET (polyethertaraphtalate) 입상메디아 혼합사용이 멤브레인 파울링과 처리효율에 미치는 영향을 관찰하였다. 일정한 공기폭기유량과 투과플럭스로 실험한 결과, PET 메디아를 첨가 시 메디아를 첨가하지 않은 경우보다 낮은 파울링 속도가 관찰되었다. MBR 반응기에서 입상 메디아에 의한 파울링 감소효과는 중공사막 모듈에 비해 평막 모듈이 더욱 효과적이었다. 공기폭기와 함께 멤브레인 표면을 따라 움직이는 입상 메디아의 접근성과 접촉성이 중공사막보다 효과적이었던 것으로 사료된다. MBR 적용에 있어 PET 메디아의 적용은 메디아를 적용하지 않았을 때와 비교 시 MBR 처리효율에 큰 영향을 주지 않았다.

Activated sludge sewage treatment processes are difficult to be controlled because of their complex and nonlinear behaviour, however, the control of the dissolved oxygen level in the reactors plays an important role in the operation of the facility. For this reason, this study is designed to present a system which accurately measures DO, MLSS, pH and ORP in the aeration tank to alleviate situations above and provide the automatization of a sewage treatment plant (STP) using new DO control system. The automatic control systems must be guaranteed the accuracy. Therefore, the proposed automatic DO control system in this study could be commercial applications in the aeration tanks by means of operating cost analysis and user-friendly for operation and maintenance. We could get accurate data from the lab tank which has water quality checker because there was no vortex and air bubble during the measurement process. Improvement of confidence in the lab tank enabled effective and automatic operation of sewage treatment plants so that operation costs and manpower could be saved. If this result is put in place in every sewage treatment plant nationwide for practical purposes, it is estimated to cost 18.5 million dollars in installing the lab tank and to save 9.8 million dollars in management cost a year, except for cost saved by automation.

Fuzzy algorithm of automatic control for dissolved oxygen(DO) concentration in the aeration tank of an activated sludge process is proposed. Among variables repirometry and air flowrate are selected as significant input factors and the relationship with DO is estimated using a multiple regression model. The DO concentration and the amount of repirometry are fuzzified and the fuzzy rule base are determined. Using the fuzzy algorithm, the change of amount of air flowrate are determined and the change of amount of DO is derived.