State Key Laboratory of Organic Geochemistry, Guangdong Key Laboratory of Environmental Protection and Resources Utilization, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou, China; College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing, China.
Longhua Center for Disease Control and Prevention of Shenzhen, Shenzhen 518109, China.
J Environ Sci (China). 2025 Feb;148:46-56. doi: 10.1016/j.jes.2023.07.001. Epub 2023 Jul 7.
Thermodynamic modeling is still the most widely used method to characterize aerosol acidity, a critical physicochemical property of atmospheric aerosols. However, it remains unclear whether gas-aerosol partitioning should be incorporated when thermodynamic models are employed to estimate the acidity of coarse particles. In this work, field measurements were conducted at a coastal city in northern China across three seasons, and covered wide ranges of temperature, relative humidity and NH concentrations. We examined the performance of different modes of ISORROPIA-II (a widely used aerosol thermodynamic model) in estimating aerosol acidity of coarse and fine particles. The M0 mode, which incorporates gas-phase data and runs the model in the forward mode, provided reasonable estimation of aerosol acidity for coarse and fine particles. Compared to M0, the M1 mode, which runs the model in the forward mode but does not include gas-phase data, may capture the general trend of aerosol acidity but underestimates pH for both coarse and fine particles; M2, which runs the model in the reverse mode, results in large errors in estimated aerosol pH for both coarse and fine particles and should not be used for aerosol acidity calculations. However, M1 significantly underestimates liquid water contents for both fine and coarse particles, while M2 provides reliable estimation of liquid water contents. In summary, our work highlights the importance of incorporating gas-aerosol partitioning when estimating coarse particle acidity, and thus may help improve our understanding of acidity of coarse particles.
热力学模型仍然是表征气溶胶酸度的最广泛使用的方法，气溶胶酸度是大气气溶胶的一个关键物理化学性质。然而，当使用热力学模型来估计粗颗粒的酸度时，是否应该纳入气-粒分配，这一点仍不清楚。在这项工作中，我们在中国北方的一个沿海城市进行了跨三个季节的现场测量，涵盖了广泛的温度、相对湿度和 NH 浓度范围。我们研究了不同模式的 ISORROPIA-II（一种广泛使用的气溶胶热力学模型）在估计粗颗粒和细颗粒气溶胶酸度方面的性能。M0 模式，纳入气相数据并以正向模式运行模型，为粗颗粒和细颗粒提供了气溶胶酸度的合理估计。与 M0 相比，M1 模式以正向模式运行但不包括气相数据，可能捕捉到气溶胶酸度的总体趋势，但低估了粗颗粒和细颗粒的 pH 值；以逆向模式运行的 M2 模式导致粗颗粒和细颗粒的估计气溶胶 pH 值产生较大误差，不应用于气溶胶酸度计算。然而，M1 模式显著低估了细颗粒和粗颗粒的液态水含量，而 M2 模式则提供了可靠的液态水含量估计。总之，我们的工作强调了在估计粗颗粒酸度时纳入气-粒分配的重要性，从而有助于提高我们对粗颗粒酸度的理解。
