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用于研究大气新粒子形成机制的实验-理论混合方法

Experiment-theory hybrid method for studying the formation mechanism of atmospheric new particle formation.

作者信息

Liu Yi-Rong, Jiang Shuai, Huang Teng, Zhang Fan

机构信息

School of Information Science and Technology, University of Science and Technology of China, Hefei, Anhui, 230026, China.

Laboratory of Atmospheric Physico-Chemistry, Anhui Institute of Optics & Fine Mechanics, Chinese Academy of Sciences, Hefei, Anhui, 230031, China.

出版信息

Phys Chem Chem Phys. 2022 Nov 23;24(45):27908-27914. doi: 10.1039/d2cp03551k.

Abstract

Atmospheric aerosols have a significant influence on climate change through their effect on the cloud lifetime and the radiative balance of the Earth's atmosphere. Despite its importance, the mechanism of aerosol nucleation is still poorly understood. Based on the low-energy structure of cluster molecules, quantum chemical (QC) computations can help us to directly calculate the formation mechanism of atmospheric clusters and formation rates at the molecular level. However, deciphering the formation mechanism of pre-nucleated clusters, especially those close to the critical size (∼1.7 nm), remains extremely challenging because many millions of configuration spaces might need to be explored to find the low-energy structure. We present a new idea that establishes a comprehensive experimental and computational hybrid calculation protocol to integrate experimental data, isomer distributions, hydrogen bond interactions, and interaction sites for exploring the configuration spaces and clarifying the nucleation mechanism of acid-base clusters, whose maximum size can exceed 1.7 nm. This protocol can effectively and accurately explore the configuration space of complex large nucleation clusters on the potential energy surface (PES). The consistency of the cluster concentration and the formation rate between the experiment and the measurement is much better than that of the previous studies and proves its accuracy. In addition, we found that malic acid (MA) can enhance sulfuric acid-dimethylamine (SA-DMA)-based particle formation rates in the atmospheric boundary layer, for example, in Shanghai and Beijing in the summer, with an enhancement of up to 700- and 135-fold, respectively. The enhancement in atmospheric particle formation by MA is critical for new particle formation in the boundary layer with relatively low SA and DMA concentrations and at high temperature. This model greatly improves our understanding of the complex aerosol nucleation mechanism of large-scale multicomponent cluster molecules.

摘要

大气气溶胶通过对云寿命和地球大气辐射平衡的影响,对气候变化具有重大影响。尽管其重要性,但气溶胶成核机制仍知之甚少。基于团簇分子的低能结构,量子化学(QC)计算可以帮助我们在分子水平上直接计算大气团簇的形成机制和形成速率。然而,解读预成核团簇的形成机制,尤其是那些接近临界尺寸(约1.7纳米)的团簇,仍然极具挑战性,因为可能需要探索数百万个构型空间才能找到低能结构。我们提出了一种新的思路,即建立一个综合的实验和计算混合计算协议,以整合实验数据、异构体分布、氢键相互作用和相互作用位点,从而探索构型空间并阐明酸碱团簇的成核机制,其最大尺寸可超过1.7纳米。该协议可以有效且准确地探索势能面(PES)上复杂大尺寸成核团簇的构型空间。实验与测量之间团簇浓度和形成速率的一致性比以往研究要好得多,证明了其准确性。此外,我们发现苹果酸(MA)可以提高大气边界层中基于硫酸 - 二甲胺(SA - DMA)的颗粒形成速率,例如在夏季的上海和北京,分别提高了700倍和135倍。MA对大气颗粒形成的增强作用对于边界层中SA和DMA浓度相对较低且温度较高时的新颗粒形成至关重要。该模型极大地增进了我们对大规模多组分团簇分子复杂气溶胶成核机制的理解。

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