GOALI: Developing Sensor-Mediated Control Strategies that Allow Innovative Treatment of Nitrogen in Wastewater

1438560LoveGOALI：开发传感器中介的控制策略，允许对废水中的氮进行创新处理该提案将汉普顿路卫生区和密歇根大学联合起来，开发一种传感器中介的控制策略，以实现从下一代主流废水系统中高效地去除氮，并通过中试系统演示该策略。正在考虑的脱氮技术是新颖的，尚未开发用于主流实施，但通过显著减少处理过程的能源、碳和土地足迹，满足美国相当大比例污水流量的严格营养法规，脱氮技术大有希望。为了充分了解传感器介导的控制策略如何为组成这些处理系统的微生物群落提供持续的性能和弹性，需要建立强有力的大学伙伴关系。在正在评估的生物反应器中，密歇根大学将负责进行分子微生物分析，以评估传感器介导的控制策略对微生物联合体的组成和代谢功能的影响。实验室规模的实验系统将在密歇根大学运行，而现有的试点系统将在密歇根大学和汉普顿路卫生区运行。所有实验系统都将完全自动化，采用传感器中介的控制策略。基于性能的计算模型将在第一年开发，并在随后几年进一步完善，以开发一种有用的设计工具，一旦这些技术实施，就可供业界使用。一名或多名研究生将在这个项目上得到资助，并将在其博士学位课程期间在校园内和汉普顿路卫生区工作。行业合作伙伴将担任研究生(S)的联合顾问。该项目将展示公用事业和大学的研究伙伴关系，作为国家模式。侧流处理氨氮废水的发展很快，使用亚硝酸盐抑制来防止完全的氨氧化，以及厌氧氨氧化(Anammox)来去除氮。然而，对于氨浓度低一个数量级以上、流量大得多的主流处理方法，还没有出现类似的发展。在主流实施传感器介导的部分氨氧化、亚硝酸盐抑制(NOB OUT-SELECT)和厌氧氨氧化有独特的挑战，将通过这个项目来解决。PIS还将涉及反硝化厌氧甲烷氧化，一种新的微生物新陈代谢，以及厌氧硫化物氧化。该团队将评估传感器中介的控制策略对组成这些系统的微生物群落的结构和功能的影响。反过来，这将促进我们在机械水平上更广泛地理解传感器中介的废水处理控制策略。由于在下一代治疗系统中推进传感器中介控制策略的使用方面的合作努力，研究团队更有可能得到一个传统上对先进自动化持谨慎态度的行业的“认可”。

1438560LoveGOALI: Developing Sensor-Mediated Control Strategies that Allow Innovative Treatment of Nitrogen in WastewaterThis proposal brings together Hampton Roads Sanitation District and the University of Michigan to develop a sensor-mediated control strategy for achieving efficient nitrogen removal from next generation mainstream wastewater systems, and to demonstrate that strategy through pilot-scale systems. The nitrogen removal technologies being considered are novel and undeveloped for mainstream implementation, but hold great promise by significantly reducing the energy, carbon and land footprint of treatment processes that meet stringent nutrient regulations for a significant percentage of the U.S. wastewater flow. To fully understand how sensor-mediated control strategies confer sustained performance and resiliency to microbiological communities that comprise these treatment systems, a strong university partnership is needed. In the bioreactors being evaluated, University of Michigan will be responsible for performing molecular microbiological analyses to evaluate the impact of sensor-mediated control strategies on the composition and metabolic function of the microbial consortia. Experimental lab-scale systems will be operated at University of Michigan while existing pilot-scale systems will be operated at both University of Michigan and Hampton Roads Sanitation District. All experimental systems will be fully automated with sensor-mediated control strategies. Performance-based computational models will be developed during the first year and further refined in subsequent years to develop a useful design tool for the industry to use once these technologies are implemented. One or more graduate students will be funded on this project and will work both on-campus and at Hampton Roads Sanitation District over the course of their Ph.D. degree program. The industrial co-PI will serve as co-advisor to the graduate student(s). This project will demonstrate a utility-university research partnership that will serve as a national model.There has been rapid development of sidestream treatment of ammonia-ladened wastewaters that use nitrite repression to prevent complete ammonia oxidation, and anaerobic ammonia oxidation (anammox) to remove N. However, comparable development for mainstream treatment where the ammonia concentrations are more than an order of magnitude lower and flows are vastly larger has not occurred. There are unique challenges to implementing sensor-mediated partial ammonia oxidation, nitrite repression (NOB out-selection) and anammox at the mainstream that will be addressed through this project. The PIs will also address denitrifying anaerobic methane oxidation, a new microbial metabolism, as well as anaerobic sulfide oxidation. The team will evaluate the impact that sensor-mediated control strategies have on the structure and function of microbial communities that comprise these systems. This, in turn, will advance our broader understanding of sensor-mediated control strategies for wastewater treatment at a mechanistic level. Due to the collaborative effort in advancing use of sensor-mediated control strategies with next-generation treatment systems, the research team is more likely to get "buy-in" from an industry that has traditionally been wary of advanced automation.