Division of Environment and Sustainability, The Hong Kong University of Science and Technology, Kowloon, Hong Kong SAR 999077, China.
Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Kowloon, Hong Kong SAR 999077, China.
Environ Sci Technol. 2023 May 23;57(20):7764-7776. doi: 10.1021/acs.est.2c09252. Epub 2023 May 8.
Oxygenated organic molecules (OOMs) are critical intermediates linking volatile organic compound oxidation and secondary organic aerosol (SOA) formation. Yet, the understanding of OOM components, formation mechanism, and impacts are still limited, especially for urbanized regions with a cocktail of anthropogenic emissions. Herein, ambient measurements of OOMs were conducted at a regional background site in South China in 2018. The molecular characteristics of OOMs revealed dominant nitrogen-containing products, and the influences of different factors on OOM composition and oxidation state were elucidated. Positive matrix factorization analysis resolved the complex OOM species to factors featured with fingerprint species from different oxidation pathways. A new method was developed to identify the key functional groups of OOMs, which successfully classified the majority species into carbonyls (8%), hydroperoxides (7%), nitrates (17%), peroxyl nitrates (10%), dinitrates (13%), aromatic ring-retaining species (6%), and terpenes (7%). The volatility estimation of OOMs was improved based on their identified functional groups and was used to simulate the aerosol growth process contributed by the condensation of those low-volatile OOMs. The results demonstrate the predominant role of OOMs in contributing sub-100 nm particle growth and SOA formation and highlight the importance of dinitrates and anthropogenic products from multistep oxidation.
含氧有机分子(OOMs)是挥发性有机化合物氧化和二次有机气溶胶(SOA)形成的关键中间体。然而,对于含有多种人为排放物的城市化地区,人们对 OOM 成分、形成机制和影响的理解仍然有限。本文于 2018 年在中国南方的一个区域背景站点进行了 OOM 的环境测量。OOM 的分子特征揭示了占主导地位的含氮产物,并阐明了不同因素对 OOM 组成和氧化态的影响。正定矩阵因子分析将复杂的 OOM 物种解析为具有来自不同氧化途径的特征指纹物质的因子。开发了一种新的方法来识别 OOM 的关键官能团,该方法成功地将大多数物种分为羰基(8%)、过氧化物(7%)、硝酸盐(17%)、过氧硝酸盐(10%)、二硝酸盐(13%)、保留芳环的物质(6%)和萜烯(7%)。基于鉴定出的官能团,改进了 OOM 的挥发性估计,并用于模拟那些低挥发性 OOM 凝结对气溶胶增长过程的贡献。结果表明,OOM 在贡献亚 100nm 颗粒生长和 SOA 形成方面起着主要作用,并强调了二硝酸盐和多步氧化产生的人为产物的重要性。