Prediction of Organic-Vapor Wall Deposition Using a Qualitative Structure Activity Relationship and its Application to the Secondary Organic Aerosol (SOA) Model

使用定性构效关系预测有机气壁沉积及其在二次有机气溶胶 (SOA) 模型中的应用

• 批准号: 1923651
• 负责人: Myoseon Jang
• 金额: $ 58.21万
• 依托单位: University of Florida
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-08-01 至 2023-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1923651&HistoricalAwards=false
• 关键词: Prediction; Organic; Vapor; Wall; Deposition

Environmental chambers are frequently used to investigate atmospheric chemistry in a controlled setting. This research is focused on developing a model to predict the interactions of gases and particles with the walls of an environmental chamber, and to predict what effects these interactions might have on the results of a study. For example, the wall effects in an environmental chamber often result in the underestimation of the formation of small particles in the chamber, an error that can be carried through to air-quality and climate models. This project is expected to ultimately improve the predictive capability for the formation of SOA in the atmosphere and improve the estimates of both the direct and indirect effects of SOA on human health and climate. The three objectives of the proposal are to: (1) Predict the gas-wall process partitioning constant of various semivolatile organic compounds (SVOCs) and their deposition rate constants using a Quantitative Structure Activity Relation (QSAR) approach; (2) Integrate the gas-wall process model parameters with the model that predicts secondary organic aerosol (SOA) formation; and (3) Evaluate the potential for SOA formation produced via multiphase reactions of various hydrocarbons using the amended model including the bias due to the gas-wall process. A model that uses an explicit gas mechanism to predict SOA formation from multiphase reactions, will be amended and applied to investigate the impact of gas-wall processes on the formation of SOA.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.

环境舱经常用于在受控环境中研究大气化学。 这项研究的重点是开发一个模型来预测气体和颗粒与环境室壁的相互作用，并预测这些相互作用可能对研究结果产生的影响。 例如，环境室中的壁效应往往导致对室内小颗粒形成的低估，这种错误可能会影响到空气质量和气候模型。预计该项目最终将提高对大气中SOA形成的预测能力，并改善SOA对人类健康和气候的直接和间接影响的估计。本研究的主要目的是：（1）用定量构效关系（QSAR）方法预测各种半挥发性有机物（SVOCs）的气壁过程分配常数及其沉积速率常数：（2）将气壁过程模型参数与二次有机气溶胶（SOA）生成预测模型相结合;以及（3）使用包括由于气壁过程引起的偏差的修正模型来评估通过各种烃的多相反应产生SOA形成的可能性。一个模型，使用明确的气体机制，预测SOA的形成从多相反应，将被修改和应用于调查的影响，气体壁的过程中形成的SOA.This奖项反映了NSF的法定使命，并已被认为是值得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的支持。

项目成果

Characterization of Atmospheric Processes of Brevetoxins in Sea Spray Aerosols from Red Tide Events

赤潮事件海浪气溶胶中短尾藻毒素的大气过程特征

• DOI: 10.1021/acs.est.1c05740
• 发表时间: 2022
• 期刊: Environmental Science & Technology
• 影响因子: 11.4
• 作者: Sem, Karen;Jang, Myoseon;Pierce, Richard;Blum, Patricia;Yu, Zechen
• 通讯作者: Yu, Zechen

Suppression of the phenolic SOA formation in the presence of electrolytic inorganic seed

存在电解无机种子时抑制酚类 SOA 的形成

• DOI: 10.1016/j.scitotenv.2022.158082
• 发表时间: 2022
• 期刊: Science of The Total Environment
• 影响因子: 9.8
• 作者: Choi, Jiwon;Jang, Myoseon
• 通讯作者: Jang, Myoseon

Simulating the Impact of Long-Range-Transported Asian Mineral Dust on the Formation of Sulfate and Nitrate during the KORUS-AQ Campaign

• DOI: 10.1021/acsearthspacechem.0c00074
• 发表时间: 2020-06
• 作者: Zechen Yu;M. Jang;Soontae Kim;C. Bae;Bonyoung Koo;R. Beardsley;Jinsoo Park;L. Chang;H. Lee-H.-Le

CAMx-UNIPAR Simulation of SOA Mass Formed from Multiphase Reactions of Hydrocarbons under the Central Valley Urban Atmospheres of California

• 发表时间: 2023
• 作者: Yu-Jin Jo;M. Jang;Sanghee Han;Azad Madhu;Bonyoung Koo;Yiqin Jia;Zechen Yu;Soontae Kim;Jinsoo Park

Prediction of secondary organic aerosol from the multiphase reaction of gasoline vapor by using volatility–reactivity base lumping

使用挥发性反应基集总预测汽油蒸气多相反应产生的二次有机气溶胶

• DOI: 10.5194/acp-22-625-2022
• 发表时间: 2022
• 期刊: Atmospheric Chemistry and Physics
• 影响因子: 6.3
• 作者: Han, Sanghee;Jang, Myoseon
• 通讯作者: Jang, Myoseon