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

本项目将开发一个启发式模型来预测由高级氧化过程（AOPs）氧化有机分子产生的降解产物和这些产物的毒性。这些工艺有望消除水中许多新出现的有机污染物，并被考虑用于饮用水处理、废水处理、场地修复和工业应用。aop在机制上是复杂的。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。所使用的建模方法将基于一种算法，利用图论将反应求解为常微分方程组。量子理论，线性自由能关系和qsar将用于估计反应速率常数。当供水系统中存在特定化合物时，该模型将帮助研究人员和监管机构更好地了解与特定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”的努力，因为这项任务的艰险和要模拟的反应的复杂性，还因为它有潜在的巨大回报，将促进污染预防和可持续发展。该模型的最终用户群体可能很大。

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.