AGS-PRF: Constraining and Modeling the Contribution of Organic Nitrate to Fine Mode Particulate Matter

AGS-PRF：有机硝酸盐对精细模式颗粒物的贡献进行约束和建模

• 批准号: 2005593
• 负责人: Jessica Haskell
• 金额: $ 19万
• 依托单位: Haskins, Jessica Danielle
• 依托单位国家: 美国
• 项目类别: Fellowship Award
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-07-01 至 2022-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2005593&HistoricalAwards=false
• 关键词: AGS; PRF; Constraining; Modeling; Contribution

Organic nitrate is a major contributor to fine particular matter (PM2.5) that affects Earth’s radiative balance, visibility, and environmental and human health. Atmospheric formation pathways of this particulate organic nitrate are ill-defined, however. In the current project, data collected during past field campaigns will be synthesized and analyzed to determine particulate organic and inorganic nitrate concentrations in PM2.5. This data will be used to constrain formation mechanisms in current atmospheric chemistry models which will help guide future research, improve predictive modeling of PM2.5, and inform nitrogen budget models.Data obtained with High-Resolution Time of Flight Aerosol Mass Spectrometers (HR-ToF-AMS) during 15 US field campaigns between 2009 and 2016 will be exploited for particulate organic and total nitrate. To test and validate mechanisms of organic and inorganic nitrate formation, temporally and spatially matched 3-D atmospheric chemistry transport (GEOS-Chem) model simulations will be performed and compared with observed concentrations. The new dataset will be made publicly available for use by other groups to guide future studies and help constrain regional and global models beyond the GEOS-Chem community. The PI will perform this work as a Postdoctoral Research Fellow at the Massachusetts Institute of Technology while engaging diverse undergraduate students in research.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.

有机硝酸盐是影响地球辐射平衡、能见度以及环境和人类健康的细颗粒物质 (PM2.5) 的主要贡献者，但在当前项目中，数据尚不清楚这种颗粒有机硝酸盐的形成途径。过去实地活动中收集的数据将被综合和分析，以部分确定 PM2.5 中的有机和无机硝酸盐浓度。这些数据将用于限制当前大气化学模型中的形成机制，这将有助于指导未来的研究，提高预测能力。 PM2.5 建模，并为氮收支模型提供信息。2009 年至 2016 年期间 15 次美国实地活动中使用高分辨率飞行时间气溶胶质谱仪 (HR-ToF-AMS) 获得的数据将用于颗粒有机物和总硝酸盐的分析。为了测试和验证有机和无机硝酸盐形成的机制，将进行时间和空间匹配的 3D 大气化学传输 (GEOS-Chem) 模型模拟，并与新的数据集将公开供其他团体使用，以指导未来的研究并帮助限制 GEOS-Chem 社区之外的区域和全球模型。 PI 将作为麻省理工学院的博士后研究员执行这项工作。技术，同时让不同的本科生参与研究。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。