Development of low-energy bio-wheel technology for wastewater treatment and reuse

市政和工业废水处理厂通常采用好氧生物工艺来降解有机污染物、营养物质和其他污染物，以减轻水污染和/或废水的再利用。这些过程需要能源密集型曝气，仅曝气就占总能耗的60%。随着能源成本的飙升和可持续发展的需求日益增长，许多污水处理厂面临着在满足更严格的污水排放限制的同时降低能耗的挑战。为了应对这些挑战并实现巨大的市场机遇，H2O Innovation, Inc.最近开发了Bio-Wheel技术，作为中小型废水处理设施的节能替代方案。有限的应用表明，与实践中常用的细泡曝气相比，该新技术可将能耗降低约30%。其他潜在的好处包括占地面积小，操作方便，出水质量更好。然而，Bio-Wheel技术仍处于早期发展阶段。需要进一步的研究来比较其与传统工艺的可靠性能，了解系统中发生的基本机制，并为进一步改进Bio-Wheel设计和运行优化提供建议。该项目将用于量化氧气向水中的传质速率，检查具有代表性的Bio-Wheel配置对工艺性能的关键因素的影响，并评估动态微生物行为与操作条件的关系。

Municipal and industrial wastewater treatment plants commonly employ aerobic biological processes to degrade organic contaminants, nutrients and other contaminants in order to mitigate water pollution and/or reuse wastewater. These processes require energy-intensive aeration, which alone accounts for up to 60% of total energy consumption. As the energy cost is soaring and the demand for sustainability development is growing, many wastewater treatment plants are facing the challenges to reduce the energy consumption while meeting the more strict effluent discharge limits. In response to these challenges and realizing huge market opportunities, H2O Innovation, Inc. has recently developed Bio-Wheel technology as an energy-efficient alternative for small- to medium-scale wastewater treatment facilities. Limited applications showed that this new technology could reduce the energy consumption by ~30% as compared to the fine bubble aeration commonly being used in practice. Other potential benefits include small foot print, easy operation and better effluent quality. Nevertheless, the Bio-Wheel technology is still in early stage of development. Further research is needed to compare its reliable performance side-by-side with conventional processes, to understand fundamental mechanisms occurring in the systems, and provide the recommendations for further improvement in Bio-Wheel design and operation optimization. This project will be directed to quantify the oxygen mass transfer rates into water, examine the effects of key factors on process performance for representative Bio-Wheel configurations, and assess the relationship of dynamic microbial behaviours with operating conditions.