Unraveling Nitrate Photochemistry in the Environment

在化学系环境化学科学项目的支持下，来自加州大学戴维斯分校的Cort Anastasio，Ted Hullar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），在化石燃料燃烧过程中排放，在烟雾的产生中起着重要作用。 在烟雾形成过程中，NOx转化为硝酸盐，传统上认为硝酸盐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--例如表面上或某些含碳分子存在的硝酸盐--可以吸收阳光，迅速改革NOx。 如果这是真的，这将导致更多的烟雾比预期的初始氮氧化物排放。加州大学戴维斯分校的合作团队将在预计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，以及为初中和高中生提供有关环境化学的播客和情况说明书。该项目将通过将计算化学建模与实验室实验测量相结合，研究表面上和有机分子存在下的硝酸盐光化学。该模型将利用（光）激发三重态的从头算分子动力学来解开硝酸盐光化学在溶液中的分子途径和自由能表面。 这将允许硝酸盐量子产率的预测，这将是对已公布的测量基准。 然后，这种方法将被应用于预测各种环境相关表面上的量子产率，这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，将在实验室中使用新开发的技术测量相同表面上的硝酸盐光解速率，以研究单色照明的固态光化学。 与过去的大多数研究不同，测量还将在表面上使用化学光化测量法，以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硝酸盐光解速度加快的程度是由于光吸收的增加和/或光化学效率的增加。 利用计算和实验方法，该项目还将评估有机分子如何影响硝酸盐在溶液中的光解，并探索潜在的机制。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值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.