Unraveling Nitrate Photochemistry in the Environment

在化学系环境化学科学项目的支持下，加州大学戴维斯分校的Cort Anastasio博士、Ted Hullar博士和Davide Donadio博士及其团队将研究表面和有机分子对硝酸盐光化学的影响。氮氧化物(NOx)是化石燃料燃烧过程中排放的，在烟雾的产生中发挥着重要作用。在烟雾形成过程中，NOx被转化为硝酸盐，而硝酸盐传统上被认为是一种不起反应的最终产物。然而，过去20年的研究表明，环境中的一些硝酸盐--例如在表面上或在某些含碳分子存在的情况下--可以吸收阳光，迅速转化为氮氧化物。如果情况属实，这将导致最初的NOx排放产生比预期更多的雾霾。加州大学戴维斯分校的合作团队将在计划的研究中解决这一差异。该项目还包括对本科生和研究生的培训，以及为中学生提供有关环境化学的播客和概况介绍。该项目将通过计算化学模拟与实验室实验测量相结合的方式，研究表面和有机分子存在下的硝酸盐光化学。模拟将利用(光)激发三重态的从头算分子动力学来揭示溶液中硝酸盐光化学的分子路径和自由能面。这将使硝酸盐量子产率的预测成为可能，并将以公布的测量结果为基准。然后，这种方法将被应用于预测各种与环境相关的表面上的量子产率，这些量子产率将与计算的硝酸盐吸收光谱相结合，以估计硝酸盐的光解速率。同时，硝酸盐在相同表面上的光解速率将在实验室中使用新开发的技术来测量，以研究单色照明的固态光化学。与过去的大多数研究不同，这些测量还将使用表面的化学辐射测量来更好地量化光子通量。然后，通过结合建模和实验结果，该团队的目标是确定表面上更快的硝酸盐光解在多大程度上是由于光吸收的增加和/或光化学效率的提高。利用计算和实验方法，这个项目还将评估有机分子如何影响溶液中的硝酸盐光解，并探索潜在的机制。这个奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

With support from the Environmental Chemical Sciences Program in the Division of Chemistry, Drs. Cort Anastasio, Ted Hullar, and Davide Donadio from the University of California at Davis and their teams will study the influence of surfaces and organic molecules on nitrate photochemistry. Nitrogen oxides (NOx), which are emitted during combustion of fossil fuels, play major roles in the production of smog. During smog formation, NOx is converted to nitrate, which traditionally was thought to be an unreactive final product. However, research over the past 20 years suggests that some nitrate in the environment – such as on surfaces or in the presence of certain carbon-containing molecules – can absorb sunlight to very quickly reform NOx. If true, this would lead to more smog than expected from the initial NOx emissions. The collaborative UC-Davis team will address this discrepancy in the projected studies. This project also includes the training of undergraduate and graduate students as well as contributions to podcasts and fact sheets about environmental chemistry for middle and high school students.This project will study nitrate photochemistry on surfaces and in the presence of organic molecules by combining computational chemical modeling with experimental measurements in the laboratory. The modeling will leverage ab initio molecular dynamics of the (photo)excited triplet state to unravel the molecular pathways and free energy surface of nitrate photochemistry in solution. This will allow predictions of nitrate quantum yields, which will be benchmarked against published measurements. This approach will then be applied to predict quantum yields on a variety of environmentally relevant surfaces, which will be integrated with computed nitrate absorption spectra to estimate nitrate photolysis rates. Simultaneously, rates of nitrate photolysis on the same surfaces will be measured in the laboratory using newly developed techniques to study solid-state photochemistry with monochromatic illumination. Unlike most past studies, the measurements will also employ chemical actinometry on the surface to better quantify photon fluxes. Then by combining the modeling and experimental results, the team aims to establish the extent to which faster nitrate photolysis on surfaces is due to an increase in light absorption and/or an increase in photochemical efficiency. Using computational and experimental approaches, this project will also assess how organic molecules impact nitrate photolysis in solution and explore the underlying mechanisms.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.