Engineered Biofiltration Processes for Microcystin Removal in Drinking Water: A Structured Enzyme-Kinetic Modeling Approach

去除饮用水中微囊藻毒素的工程生物过滤工艺：结构化酶动力学建模方法

• 批准号: 1806066
• 负责人: Chenyang Jiang
• 金额: $ 32.47万
• 依托单位: University of California-Irvine
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-09-15 至 2022-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1806066&HistoricalAwards=false
• 关键词: Engineered; Biofiltration; Processes; Microcystin; Removal

Harmful algal blooms are caused by the growth of algae that produce a toxin known as microcystin. Microcystin is linked to liver cancer and is difficult to treat using conventional drinking water treatment practices. This project investigates biological filtration ("biofiltration") to remove microcystin during drinking water treatment. Biofiltration relies on natural communities of bacteria in sand filters to degrade microcystin. This research focuses on establishing a stable biofiltration treatment system under the highly variable environment of a drinking water treatment plant. The project will develop models to predict biofiltration treatment behavior with the goal of making biofiltration an effective treatment process to protect the Nation's drinking water supply. The educational program will train students in cross-disciplinary science and engineering to improve the scientific literature and the technological skills of the Nation.The goal of this project is to develop a predictive understanding of the environmental and operational factors governing microbial community dynamics and microcystin biodegradation in biofiltration systems. The specific objectives are to: 1) quantify and compare the steady-state growth characteristics of suspended and immobilized microcystin-degrading bacterial consortia (MC-DBC) in engineered reactors; 2) define environmental and hydraulic conditions that enhance the activity and stability of the aqueous and biofilm MC-DBC in these reactor systems; and 3) investigate and compare the microbial community structure and function within each MC-DBC to gain a holistic understanding of the microbial community interactions within MC-DBC. This research will combine culture based and genetic microbiological investigations with numerical simulations of fate and transport to optimize management of algal toxin removal in biofiltration systems. The effects of various nutrient conditions on the growth and degradation kinetics of MC-DBC will directly inform biostimulation practices to improve biodegradation kinetics during harmful algal bloom periods. Integration of experimental observations with the development of a mechanistic numerical model will highlight the relative importance of enzyme induction kinetics, enzyme dilution, or enzyme regulation to biofiltration efficiency. The numerical model simulations will advance our ability to design biofiltration systems by assessing the feasibility and treatment capability of algal toxin removal over a wide range of operating conditions.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

有害的藻华是由藻类生长引起的，藻类会产生一种称为微囊藻毒素的毒素。微囊藻毒素与肝癌有关，并且很难使用传统的饮用水处理方法进行治疗。该项目研究生物过滤（“生物过滤”），以在饮用水处理过程中去除微囊藻毒素。生物过滤依靠砂滤器中的天然细菌群落来降解微囊藻毒素。本研究的重点是在饮用水处理厂的高度变化的环境下建立稳定的生物过滤处理系统。该项目将开发模型来预测生物过滤处理行为，目标是使生物过滤成为保护国家饮用水供应的有效处理过程。该教育计划将培训学生跨学科科学和工程，以提高科学文献和国家的技术技能。该项目的目标是对生物过滤系统中控制微生物群落动态和微囊藻毒素生物降解的环境和操作因素进行预测性了解。具体目标是：1）量化和比较工程反应器中悬浮和固定微囊藻毒素降解细菌群落（MC-DBC）的稳态生长特性； 2) 确定环境和水力条件，以增强这些反应器系统中水和生物膜 MC-DBC 的活性和稳定性； 3) 研究并比较每个 MC-DBC 内的微生物群落结构和功能，以全面了解 MC-DBC 内微生物群落的相互作用。这项研究将把基于培养和遗传的微生物学研究与命运和运输的数值模拟相结合，以优化生物过滤系统中藻类毒素去除的管理。各种营养条件对 MC-DBC 生长和降解动力学的影响将直接为生物刺激实践提供信息，以改善有害藻华期间的生物降解动力学。将实验观察与机械数值模型的开发相结合将突出酶诱导动力学、酶稀释或酶调节对生物过滤效率的相对重要性。数值模型模拟将通过评估在广泛的操作条件下去除藻类毒素的可行性和处理能力来提高我们设计生物过滤系统的能力。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

Can cyanotoxins penetrate human skin during water recreation to cause negative health effects?

• DOI: 10.1016/j.hal.2020.101872
• 发表时间: 2020-09-01
• 期刊: HARMFUL ALGAE
• 影响因子: 6.6
• 作者: Nielsen，Marisa Chattman;Jiang，Sunny C.
• 通讯作者: Jiang，Sunny C.

Modeled and measured SARS-CoV-2 virus in septic tank systems for wastewater surveillance

对化粪池系统中的 SARS-CoV-2 病毒进行建模和测量，用于废水监测

• DOI: 10.2166/wh.2023.128
• 发表时间: 2023
• 期刊: Journal of Water and Health
• 影响因子: 2.3
• 作者: Li, Dong;Quon, Hunter;Ervin, Jared;Jiang, Sunny;Rosso, Diego;Van De Werfhorst, Laurie C.;Steets, Brandon;Holden, Patricia A.
• 通讯作者: Holden, Patricia A.