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生物气溶胶是暖温浸没模式冰核粒子的主要来源,并导致冰核粒子可预测性存在不确定性。

Bioaerosols are the dominant source of warm-temperature immersion-mode INPs and drive uncertainties in INP predictability.

作者信息

Cornwell Gavin C, McCluskey Christina S, Hill Thomas C J, Levin Ezra T, Rothfuss Nicholas E, Tai Sheng-Lun, Petters Markus D, DeMott Paul J, Kreidenweis Sonia, Prather Kimberly A, Burrows Susannah M

机构信息

Atmospheric Science and Global Change Division, Pacific Northwest National Laboratory, Richland, WA 99352, USA.

Department of Chemistry and Biochemistry, University of California, San Diego, La Jolla, CA 92093, USA.

出版信息

Sci Adv. 2023 Sep 15;9(37):eadg3715. doi: 10.1126/sciadv.adg3715.

Abstract

Ice-nucleating particles (INPs) are rare atmospheric aerosols that initiate primary ice formation, but accurately simulating their concentrations and variability in large-scale climate models remains a challenge. Doing so requires both simulating major particle sources and parameterizing their ice nucleation (IN) efficiency. Validating and improving model predictions of INP concentrations requires measuring their concentrations delineated by particle type. We present a method to speciate INP concentrations into contributions from dust, sea spray aerosol (SSA), and bioaerosol. Field campaign data from Bodega Bay, California, showed that bioaerosols were the primary source of INPs between -12° and -20°C, while dust was a minor source and SSA had little impact. We found that recent parameterizations for dust and SSA accurately predicted ambient INP concentrations. However, the model did not skillfully simulate bioaerosol INPs, suggesting a need for further research to identify major factors controlling their emissions and INP efficiency for improved representation in models.

摘要

冰核粒子(INPs)是引发初次结冰的罕见大气气溶胶,但在大规模气候模型中准确模拟它们的浓度和变异性仍然是一项挑战。要做到这一点,既需要模拟主要的粒子源,又需要对它们的冰核形成(IN)效率进行参数化。验证和改进INP浓度的模型预测需要测量按粒子类型划分的浓度。我们提出了一种将INP浓度按尘埃、海喷雾气溶胶(SSA)和生物气溶胶的贡献进行分类的方法。来自加利福尼亚州博德加湾的实地考察数据表明,生物气溶胶是-12°至-20°C之间INPs的主要来源,而尘埃是次要来源,SSA影响很小。我们发现,最近对尘埃和SSA的参数化准确地预测了环境INP浓度。然而,该模型未能巧妙地模拟生物气溶胶INPs,这表明需要进一步研究以确定控制其排放和INP效率的主要因素,以便在模型中得到更好的体现。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4ea9/10881078/b7cbae46b2cf/sciadv.adg3715-f1.jpg

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