CAREER: Uncertainty Analysis and Modeling of the Biodegradation of Synthetic Organic Compounds in Activated Sludge Biotreatment Systems

职业：活性污泥生物处理系统中合成有机化合物生物降解的不确定性分析和建模

• 批准号: 0348161
• 负责人: Benjamin Magbanua
• 金额: --
• 依托单位: Mississippi State University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2004
• 资助国家: 美国
• 起止时间: 2004-04-15 至 2011-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0348161&HistoricalAwards=false
• 关键词: CAREER; Uncertainty; Analysis; Modeling; Biodegradation

0348161 Magbanua Intellectual merit. The activated sludge (AS) process was originally developed for the removal of oxygen demanding material and suspended solids, and later applied also to nutrient removal, from wastewater. More recently, effluent limits have been placed on specific chemicals of industrial and environmental significance, referred to as priority pollutants. Biotreatment has been designated the best available treatment technology, against which alternative treatment options are measured, for priority pollutants that are potentially biodegradable synthetic organic chemicals (SOCs). Consequently, the development of approaches to accurately predict SOC degradation in activated sludge systems has become a major research focus in environmental engineering. The current modeling approach combines traditional microbial growth kinetics with reactor engineering principles to derive a deterministic model of SOC degradation. Experience has shown, however, that bio kinetic parameters derived from laboratory experiments are poor predictors of SOC removal performance, even in controlled laboratory reactors. Therefore, a modeling approach that accounts for process uncertainties would be more appropriate. The PI further suggests that an understanding of the sources of uncertainty in wastewater bio treatment would facilitate the design of more efficient and reliable bioprocesses for priority pollutant removal. The PI hypothesizes that uncertainty in wastewater bio treatment, and the disparity between field performance and laboratory-derived kinetics, arises principally from the concentration and activity of the competent biomass, the diversity of the microbial community, and the size distribution of the microbial flocs.Broader Impacts. Priority pollutants have been identified as imminent threats to public health and the environment. Strict limits have consequently been established for effluent concentrations of priority pollutant. The kinetics of SOC removal are poorly understood, however, so engineers tend to use very conservative safety factors and grossly over design treatment systems to ensure that SOC removal goals are met. A better understanding of the uncertainties related to SOC bio treatment, and models incorporating uncertainty, would permit more realistic assessment of uncertainty risk, and facilitate the development of design and operational strategies that minimize such risk. In addition to the usual scientific channels, The PI plans to disseminate these models and other project results through an interactive web site, which will be promoted to practitioners through professional associations. The PI is also committed to enhancing science and engineering education at all levels, particularly by providing opportunities for research. Mississippi is a state in which research expenditures have traditionally lagged the rest of the country, so availability of research experiences at the undergraduate and secondary levels has been severely limited. The PI is committed to providing such opportunities, particularly to persons from groups traditionally underrepresented in science and engineering.

0348161马格巴努阿智力成绩。活性污泥（AS）工艺最初是为了去除需氧物质和悬浮固体而开发的，后来也应用于从废水中去除营养物。最近，对具有工业和环境重要性的特定化学品（称为优先污染物）规定了废水限制。生物处理已被指定为现有的最佳处理技术，可据此衡量替代处理方案，用于处理可能生物降解的合成有机化学品的优先污染物。 因此，活性污泥系统中SOC降解的准确预测方法的发展已成为环境工程领域的一个主要研究热点。目前的建模方法结合了传统的微生物生长动力学与反应器工程原理，得出一个确定性的SOC降解模型。然而，经验表明，即使在受控的实验室反应器中，来自实验室实验的生物动力学参数也不能很好地预测SOC去除性能。因此，考虑过程不确定性的建模方法将更合适。PI进一步建议，对废水生物处理中不确定性来源的理解将有助于设计更有效和可靠的生物工艺，以优先去除污染物。 PI假设废水生物处理的不确定性以及现场性能和实验室动力学之间的差异主要来自主管生物质的浓度和活性、微生物群落的多样性以及微生物絮体的大小分布。重点污染物已被确定为对公众健康和环境的紧迫威胁。 因此，对优先污染物的流出物浓度规定了严格的限制。然而，人们对SOC去除的动力学知之甚少，因此工程师倾向于使用非常保守的安全系数和过度设计处理系统，以确保达到SOC去除目标。更好地了解SOC生物处理相关的不确定性，以及包含不确定性的模型，将允许更现实的不确定性风险评估，并促进设计和操作策略的发展，最大限度地减少这种风险。除了通常的科学渠道外，PI计划通过一个互动网站传播这些模型和其他项目成果，并通过专业协会向从业人员推广。PI还致力于加强各级科学和工程教育，特别是通过提供研究机会。 密西西比是一个研究支出传统上落后于全国其他地区的州，因此本科和中学阶段的研究经验的可用性受到严重限制。PI致力于提供这样的机会，特别是从传统上在科学和工程代表性不足的群体的人。