Simulation of Singlet Oxygen Kinetics for Trace Organic Transformation in Wastewater Effluent

干旱地区的水资源因干旱和人口增长而紧张。 废水回收可以为这些地区提供额外的水源。 然而，在废水处理过程中未被去除的痕量污染物如药物可能会引起生态和/或人类健康问题。 该项目将提供有关阳光在破坏潜在有毒痕量污染物方面的作用的新信息，解决国家对可持续、低成本和节能的水处理技术的需求。 研究结果将为水资源紧张地区的废水回收处理系统设计提供信息。 该项目将利用亚利桑那大学的项目来加强STEM领域弱势学生的教育活动。 如果成功，该项目将提供关于如何从废水中去除潜在有害的药物和其他污染物的宝贵信息，以便在水安全受到威胁的地区安全地重新使用。涉及流出物有机物（EfOM）的太阳能驱动的过程产生有助于痕量有机污染物（TOrC）转化的活性氧物质（ROS）。 对于一个重要的TOrCs子集，与单线态氧的反应是处理过的废水中主要的自然反应途径。 目前还不可能提供该途径的物理准确表示或单线态氧间接光解转化TOrCs的动力学。 不确定性的领域包括：（i）单线态氧生成的量子效率对光波长的依赖性，（ii）EfOM中参与生成单线态氧的敏化剂的身份和浓度，（iii）许多TORC与单线态氧的反应速率常数，以及（iv）ROS生成的转化产物的毒性。 拟议的工作的主要目标是支持开发一个强大的和物理上准确的动力学模型，通过与单线态氧在处理后的废水中的反应，光驱动的降解TORCs。 拟议的研究将使用理论支持的方法来消除或最大限度地减少处理后废水中TOrC转化的单线态氧依赖性机制的光化学中的不确定性。 更具体地说，这项工作旨在揭示（i）在单线态氧途径中作为敏化剂的EfOM组分的浓度和特性，以及（ii）单线态氧的量子效率对光波长的依赖性。 研究结果将支持改进的动力学模型，是潜在的有用的反应器设计在先进的废水处理系统的发展。 下一代模型的基础上散装有机特征的EfOM和量子效率归一化溶解有机物浓度是必要的，以克服缺陷，在国家的最先进的动力学表示，必然是有条件的characters.This奖项反映了NSF的法定使命，并已被认为是值得的支持，通过评估使用基金会的智力价值和更广泛的影响审查标准。

Water resources in dry regions are stressed by drought and population growth. Wastewater reclamation can provide an additional source of water for these areas. However, trace contaminants such as pharmaceuticals that are not removed during wastewater treatment may pose ecological and/or human health concerns. This project will provide new information on the role of sunlight in destroying potentially toxic trace contaminants, addressing the national need for sustainable, low cost and energy efficient technologies for water treatment. Results will inform design of wastewater reclamation treatment systems in water-stressed areas. The project will take advantage of programs at the University of Arizona to augment educational activities among disadvantaged students in STEM areas. If successful, this project will provide valuable information on how to remove potentially harmful pharmaceutical and other contaminants from wastewater to allow its safe re-use in areas where water security is threatened. Solar-driven processes involving effluent organic matter (EfOM) generate reactive oxygen species (ROS) that contribute to transformations of trace organic contaminants (TOrCs). For an important subset of TOrCs, a reaction with singlet oxygen is the dominant natural reaction pathway in treated wastewater. It is not yet possible to provide a physically accurate representation of that pathway or the kinetics of indirect photolytic transformations of TOrCs by singlet oxygen. Areas of uncertainty include (i) the dependence of quantum efficiency for singlet oxygen generation on light wavelength, (ii) the identities and concentrations of sensitizers in EfOM that participate in generating singlet oxygen, (iii) reaction rate constants for many TOrCs with singlet oxygen, and (iv) the toxicities of ROS-generated transformation products. The primary objective of proposed work is to support the development of a robust and physically accurate kinetic model for the light-driven degradation of TORCs via reaction with singlet oxygen in treated wastewater. The proposed research will use mathematically-supported methods to eliminate or minimize uncertainties in the photochemistry of singlet-oxygen-dependent mechanisms for TOrC transformations in treated wastewater. More specifically, the work is designed to expose (i) the concentrations and characters of EfOM fractions that serve as sensitizers in the singlet oxygen pathway, and (ii) the dependence of quantum efficiency for singlet oxygen on light wavelength. Results will support development of improved kinetic models that are potentially useful for reactor design in advanced wastewater treatment systems. Next generation models based on bulk organic characteristics in EfOM and quantum efficiencies normalized to dissolved organic concentration are necessary to overcome deficiencies in state-of-the-art kinetic representations that are necessarily conditional in character.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.