Cloud water composition during HCCT-2010: Scavenging efficiencies, solute concentrations, and droplet size dependence of inorganic ions and dissolved organic carbon
Cloud water composition during HCCT-2010: Scavenging efficiencies, solute concentrations, and droplet size dependence of inorganic ions and dissolved organic carbon
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DOI：
10.5194/acp-16-3185-2016
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发表时间：
2015-09
影响因子：
6.3
通讯作者：
D. Pinxteren;K. Fomba;S. Mertes;K. Müller;G. Spindler;Johannes Schneider;Taehyoung Lee;J. Collett-J.-Coll
中科院分区：
文献类型：
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作者：
D. Pinxteren;K. Fomba;S. Mertes;K. Müller;G. Spindler;Johannes Schneider;Taehyoung Lee;J. Collett-J.-Coll
抽象的。2010年9月/10月在Mt. Schmucke在德国的一个农村，森林地区在拉格朗日型山顶云图林根2010年（HCCT-2010）云实验。除了大量收集器外，还应用了三级和五级收集器，并分析了样品中的无机离子（SO 42 −、NO3−、NH 4+、Cl−、Na+、Mg 2+、Ca 2+、K+）、H2 O2（aq）、S（IV）和溶解有机碳（DOC）。氨、硝酸盐和硫酸盐的活动体积加权平均浓度分别为191、142和39 µmol L−1，次要离子在4和27 µmol L−1之间，H2 O2（aq）为5.4 µmol L−1，S（IV）为1.9 µmol L−1，DOC为3.9 mgC L−1。这些浓度与最近欧洲类似地点的云水数据相比很好。在质量基础上，有机物质（DOC × 1.8）占总溶质浓度的20- 40%（事件平均值），并发现对云水酸度有不可忽视的影响。主要离子的相对标准偏差为溶质浓度的60- 66%和云水负荷（CWLs）的52- 80%。类似的变化的溶质浓度和CWLs一起的后向轨迹分析和主成分分析的结果，表明在传入的空气质量（即空气质量的历史），而不是云的液态水含量（LWC）的浓度，是主要因素控制散装溶质浓度的云研究。液滴有效半径被认为是一个更好的预测云水总离子含量（TIC）比LWC，即使没有一个单一的解释变量可以完全描述TIC（或溶质浓度）的变化，在一个简单的函数关系，由于所涉及的复杂过程。总体浓度通常与逆流虚拟撞击器（CVI）采样并由气溶胶质谱仪（AMS）分析的残留颗粒浓度的同位测量值在2倍内一致，偏差主要是由系统差异和方法限制（如残留颗粒采样期间溶解气体的脱气）造成的。当仅使用云内数据作为事件平均值计算时，气溶胶组分对SO 42-、NO3-、NH 4+和DOC的清除效率（SE）分别为0.56-0.94、0.79-0.99、0.71-98和0.67-0.92。在许多情况下，使用逆风站点的数据估计的SE有很大的不同，揭示了气相吸收（挥发性成分）和质量损失的影响。Schmucke可能是由于物理过程，如树木和/或夹带液滴清除。水滴大小分辨的主要离子SO 42-、NO3-和NH 4+的云水浓度揭示了两个主要的分布：浓度随着水滴大小的增加而降低，以及“U”形。相比之下，典型的粗颗粒模式的次要离子的配置文件往往随着液滴尺寸的增加而增加，突出了一个物种的颗粒浓度尺寸分布的大小分辨的溶质浓度模式的发展的重要性。液滴大小类别之间的浓度差异通常是
Abstract. Cloud water samples were taken in September/October 2010 at Mt. Schmucke in a rural, forested area in Germany during the Lagrange-type Hill Cap Cloud Thuringia 2010 (HCCT-2010) cloud experiment. Besides bulk collectors, a three-stage and a five-stage collector were applied and samples were analysed for inorganic ions (SO42−,NO3−, NH4+, Cl−, Na+, Mg2+, Ca2+, K+), H2O2 (aq), S(IV), and dissolved organic carbon (DOC). Campaign volume-weighted mean concentrations were 191, 142, and 39 µmol L−1 for ammonium, nitrate, and sulfate respectively, between 4 and 27 µmol L−1 for minor ions, 5.4 µmol L−1 for H2O2 (aq), 1.9 µmol L−1 for S(IV), and 3.9 mgC L−1 for DOC. The concentrations compare well to more recent European cloud water data from similar sites. On a mass basis, organic material (as DOC × 1.8) contributed 20–40 % (event means) to total solute concentrations and was found to have non-negligible impact on cloud water acidity. Relative standard deviations of major ions were 60–66 % for solute concentrations and 52–80 % for cloud water loadings (CWLs). The similar variability of solute concentrations and CWLs together with the results of back-trajectory analysis and principal component analysis, suggests that concentrations in incoming air masses (i.e. air mass history), rather than cloud liquid water content (LWC), were the main factor controlling bulk solute concentrations for the cloud studied. Droplet effective radius was found to be a somewhat better predictor for cloud water total ionic content (TIC) than LWC, even though no single explanatory variable can fully describe TIC (or solute concentration) variations in a simple functional relation due to the complex processes involved. Bulk concentrations typically agreed within a factor of 2 with co-located measurements of residual particle concentrations sampled by a counterflow virtual impactor (CVI) and analysed by an aerosol mass spectrometer (AMS), with the deviations being mainly caused by systematic differences and limitations of the approaches (such as outgassing of dissolved gases during residual particle sampling). Scavenging efficiencies (SEs) of aerosol constituents were 0.56–0.94, 0.79–0.99, 0.71–98, and 0.67–0.92 for SO42−, NO3−, NH4+, and DOC respectively when calculated as event means with in-cloud data only. SEs estimated using data from an upwind site were substantially different in many cases, revealing the impact of gas-phase uptake (for volatile constituents) and mass losses across Mt. Schmucke likely due to physical processes such as droplet scavenging by trees and/or entrainment. Drop size-resolved cloud water concentrations of major ions SO42−, NO3−, and NH4+ revealed two main profiles: decreasing concentrations with increasing droplet size and “U” shapes. In contrast, profiles of typical coarse particle mode minor ions were often increasing with increasing drop size, highlighting the importance of a species' particle concentration size distribution for the development of size-resolved solute concentration patterns. Concentration differences between droplet size classes were typically