Center for Atmospheric Particle Studies , Carnegie Mellon University , Pittsburgh , Pennsylvania 15213 , United States.
Mechanical Engineering , Carnegie Mellon University , Pittsburgh , Pennsylvania 15213 , United States.
Environ Sci Technol. 2020 Jan 21;54(2):714-725. doi: 10.1021/acs.est.9b06531. Epub 2020 Jan 3.
Mobile sampling studies have revealed enhanced levels of secondary organic aerosol (SOA) in source-rich urban environments. While these enhancements can be from rapidly reacting vehicular emissions, it was recently hypothesized that nontraditional emissions (volatile chemical products and upstream emissions) are emerging as important sources of urban SOA. We tested this hypothesis by using gas and aerosol mass spectrometry coupled with an oxidation flow reactor (OFR) to characterize pollution levels and SOA potentials in environments influenced by traditional emissions (vehicular, biogenic), and nontraditional emissions (e.g., paint fumes). We used two SOA models to assess contributions of vehicular and biogenic emissions to our observed SOA. The largest gap between observed and modeled SOA potential occurs in the morning-time urban street canyon environment, for which our model can only explain half of our observation. Contributions from VCP emissions (e.g., personal care products) are highest in this environment, suggesting that VCPs are an important missing source of precursors that would close the gap between modeled and observed SOA potential. Targeted OFR oxidation of nontraditional emissions shows that these emissions have SOA potentials that are similar, if not larger, compared to vehicular emissions. Laboratory experiments reveal large differences in SOA potentials of VCPs, implying the need for further characterization of these nontraditional emissions.
移动采样研究表明,在富含污染源的城市环境中,二次有机气溶胶(SOA)的含量有所增加。虽然这些增加可能来自快速反应的车辆排放,但最近有人假设,非传统排放(挥发性化学产品和上游排放)正在成为城市 SOA 的重要来源。我们通过使用气相和气溶胶质谱仪以及氧化流动反应器(OFR)来测试这一假设,以表征受传统排放(车辆、生物源)和非传统排放(例如油漆烟雾)影响的环境中的污染水平和 SOA 潜力。我们使用了两个 SOA 模型来评估车辆和生物源排放对我们观察到的 SOA 的贡献。在早晨的城市街道峡谷环境中,观察到的和模型预测的 SOA 潜力之间的差距最大,我们的模型只能解释我们观察到的一半。在这种环境中,VCP 排放(例如个人护理产品)的贡献最高,这表明 VCP 是前体的一个重要缺失来源,这将缩小模型预测和观察到的 SOA 潜力之间的差距。针对非传统排放的 OFR 靶向氧化表明,这些排放的 SOA 潜力与车辆排放相似,如果不是更大的话。实验室实验揭示了 VCP 的 SOA 潜力存在很大差异,这意味着需要进一步对这些非传统排放进行特征描述。