首页> 外文期刊>Journal of Geophysical Research, D. Atmospheres: JGR >Prediction of cloud condensation nucleus number concentration using measurements of aerosol size distributions and composition and light scattering enhancement due to humidity
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Prediction of cloud condensation nucleus number concentration using measurements of aerosol size distributions and composition and light scattering enhancement due to humidity

机译:通过测量气溶胶尺寸分布和组成以及湿度导致的光散射增强来预测云凝结核数浓度

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摘要

A cloud condensation nucleus (CCN) closure experiment is carried out using data from the Chebogue Point, Nova Scotia, ground site during the International Consortium for Atmospheric Research on Transport and Transformation (ICARTT) field experiment in 2004. The number concentration of CCN at five supersaturations (~0.07% to ~0.5%) is predicted from measurements of aerosol size distribution, composition, and hygroscopic growth and is compared to measured CCN concentrations. It is shown that CCN can be predicted quite reliably using measured size distributions, a simple aerosol model to derive the solute-to-water mole ratio, and the diameter growth factor g(RH) or the optical growth factor f(RH). The mean error ranges from an overestimate in CCN of ≤5% at high supersaturation to a factor of 2.4 at low supersaturation with regression coefficients r 2 of 0.90 and 0.53, respectively. The poor agreement at low supersaturation is primarily a result of high flow rates in the CCN counter that prevented small particles from growing to detectable sizes. Precise knowledge of the temperature gradient, and flow rates of the instrument, is essential to establish the correct supersaturation, particularly at low supersaturation, where errors translate into a large percentage of the activated number. There may also be some contribution from simplified composition assumptions, e.g., neglecting variability with size and/or mixing state. The mostly oxygenated organic aerosol could be modeled as insoluble, within the above uncertainties, from the point of view of hygroscopicity and activation. The generality of these conclusions will have to be tested at other locations.
机译:在2004年国际运输与转化大气研究联合会(ICARTT)野外实验期间,使用来自新斯科舍省Chebogue Point地面站点的数据进行了云凝结核(CCN)封闭实验。CCN数浓度为5通过测量气溶胶的大小分布,组成和吸湿性增长可预测过饱和度(〜0.07%至〜0.5%),并将其与CCN浓度进行比较。结果表明,使用测得的尺寸分布,简单的气溶胶模型来推导溶质与水的摩尔比以及直径增长因子g(RH)或光学增长因子f(RH)可以非常可靠地预测CCN。平均误差的范围从高过饱和度时CCN的高估≤5%到低过饱和度时的系数2.4分别具有0.90和0.53的回归系数。低过饱和度时的不良一致性主要是由于CCN计数器中的高流速导致小颗粒无法生长到可检测的尺寸。准确了解仪器的温度梯度和流速对于建立正确的过饱和度至关重要,特别是在过饱和度较低的情况下(误差会转化为激活数的很大百分比)。简化的组成假设也可能有一些贡献,例如,忽略大小和/或混合状态的可变性。从吸湿性和活化性的角度来看,在上述不确定性范围内,大部分被氧化的有机气溶胶可以被建模为不溶的。这些结论的普遍性必须在其他地方进行检验。

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