Pathway Generation and Byproduct Estimation for Chemical Oxidation Processes in Water Treatment

水处理中化学氧化过程的路径生成和副产物估算

• 批准号: 0607332
• 负责人: Paul Westerhoff
• 金额: --
• 依托单位: Arizona State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-07-15 至 2009-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0607332&HistoricalAwards=false
• 关键词: Pathway; Generation; Byproduct; Estimation; Chemical

0607332CrittendenThis project will develop a heuristic model to predict the degradation products and the toxicities of these products resulting from the oxidation of organic molecules by advanced oxidation processes (AOPs). These processes have promise to destroy many emerging organic contaminants in water and are being considered in potable water treatment, wastewater treatment, site remediation, and industrial applications. AOPs are mechanistically complex. This fact, combined with the diversity of structures of contaminants, makes it difficult to study the degradation pathways of potential contaminants and the fate of intermediates and byproducts. The modeling approach to be used will be based on an algorithm to solve reactions as systems of ordinary differential equations using graph theory. Quantum theory, linear free energy relationships, and QSARs will be used to estimate reaction rate constants. The model will help researchers and regulators better understand the potential efficacy, toxicity, and risks associated with a given AOP when specific compounds are present in a water supply. The project is a "high risk, high reward" effort because of the breath of the task and complexity of the reactions to be modeled and because it has a potentially large payoff that will promote pollution prevention and sustainability. The end-user community for the model could be large.

0607332Crittenden该项目将开发一个启发式模型来预测高级氧化过程（AOP）氧化有机分子产生的降解产物和这些产物的毒性。这些过程有希望破坏水中许多新出现的有机污染物，并正在考虑在饮用水处理，废水处理，现场修复和工业应用。AOP在机械上是复杂的。这一事实，再加上污染物结构的多样性，使得研究潜在污染物的降解途径以及中间体和副产物的命运变得困难。将使用的建模方法将基于一种算法，该算法使用图论将反应作为常微分方程组求解。量子理论，线性自由能关系，和QSAR将用于估计反应速率常数。该模型将帮助研究人员和监管机构更好地了解特定化合物存在于供水中时与给定AOP相关的潜在功效，毒性和风险。该项目是一项“高风险、高回报”的工作，因为任务的气息和要模拟的反应的复杂性，还因为它具有促进污染预防和可持续性的潜在巨大回报。该模型的最终用户群体可能很大。