首页> 外文期刊>Atmospheric Chemistry and Physics Discussions >The size-resolved cloud condensation nuclei (CCN) activity and its prediction based on aerosol hygroscopicity and composition in the Pearl Delta River (PRD) region during wintertime 2014
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The size-resolved cloud condensation nuclei (CCN) activity and its prediction based on aerosol hygroscopicity and composition in the Pearl Delta River (PRD) region during wintertime 2014

机译:基于冬季冬季冬季河流(PRD)区气溶胶吸湿性及组成的尺寸分辨云凝结核(CCN)活性及其预测

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A hygroscopic tandem differential mobility analyzer (HTDMA), a scanning mobility cloud condensation nuclei (CCN) analyzer (SMCA), and an Aerodyne high-resolution time-of-flight aerosol mass spectrometer (HR-ToF-AMS) were used to, respectively, measure the hygroscopicity, condensation nuclei activation, and chemical composition of aerosol particles at the Panyu site in the Pearl River Delta region during wintertime 2014. The distribution of the size-resolved CCN at four supersaturations (SSs of 0.1%, 0.2%, 0.4%, and 0.7%) and the aerosol particle size distribution were obtained by the SMCA. The hygroscopicity parameter κ (κCCN, κHTDMA, and κAMS) was, respectively, calculated based upon the SMCA, HTDMA, and AMS measurements. The results showed that the κHTDMA value was slightly smaller than the κCCN one at all diameters and for particles larger than 100nm, and the κAMS value was significantly smaller than the others (κCCN and κHTDMA), which could be attributed to the underestimated hygroscopicity of the organics (κorg). The activation ratio (AR) calculated from the growth factor – probability density function (Gf-PDF) without surface tension correction was found to be lower than that from the CCN measurements, due most likely to the uncorrected surface tension (σs∕a) that did not consider the surfactant effects of the organic compounds. We demonstrated that better agreement between the calculated and measured ARs could be obtained by adjusting σs∕a. Various schemes were proposed to predict the CCN number concentration (NCCN) based on the HTDMA and AMS measurements. In general, the predicted NCCN agreed reasonably well with the corresponding measured ones using different schemes. For the HTDMA measurements, the NCCN value predicted from the real-time AR measurements was slightly smaller (~6.8%) than that from the activation diameter (D50) method due to the assumed internal mixing in the D50 prediction. The NCCN values predicted from bulk chemical composition of PM1 were higher (~11.5%) than those from size-resolved composition measured by the AMS because a significant fraction of PM1 was composed of inorganic matter. The NCCN values calculated from AMS measurement were underpredicted at 0.1% and 0.2% supersaturations, which could be due to underestimation of κorg and overestimation of σs∕a. For SS values of 0.4% and 0.7%, slight overpredicted NCCN values were found because of the internal mixing assumption. Our results highlight the need for accurately evaluating the effects of organics on both the hygroscopic parameter κ and the surface tension σ in order to accurately predict CCN activity.
机译:分别为A吸湿串联微分迁移率分析仪(HTDMA),凝结核(CCN)分析仪(SMCA)和重航空器高分辨率时间飞行气溶胶质谱仪(HR-TOF-AMS)被用来扫描移动性云, ,测量吸湿性,凝结核激活,和2014年冬季的大小分辨CCN在四个过饱和(0.1%SSS,0.2%,0.4分布期间在珠江三角洲番禺站点气溶胶粒子的化学组成%,和0.7%)和气溶胶颗粒大小分布是由SMCA获得。吸湿性参数κ(κCCN,κHTDMA和κAMS)为分别计算基于SMCA,HTDMA,和AMS的测量。结果表明,该κHTDMA值比在所有直径的κCCN一个和超过100nm的较大颗粒稍小,并且κAMS值比其他人(κCCN和κHTDMA),其可以归因于的所述低估吸湿性显著较小有机物(κorg)。从生长因子计算的激活比(AR) - 概率密度函数(GF-PDF)而没有表面张力校正被发现是比从CCN测量下,由于极有可能未校正的表面张力强度(σs/ A),该没有考虑有机化合物的表面活性剂的效果。我们证明了计算和测量AR间更好的一致性可以通过调整强度σs/ A获得。提出了各种方案来预测基于所述HTDMA和AMS测量CCN数浓度(NCCN)。一般来说,所述预测NCCN同意合理地使用不同的方案的相应测量的。对于HTDMA测量,从所述实时测量AR预测NCCN值呈微比从激活直径小(〜6.8%)(D50)的方法,由于假定在D50预测内部混合。从PM1的散装化学成分的预测值NCCN较高(〜11.5%)比由粒度分辨组合物由AMS测量,因为PM1的显著馏分组成的无机物质。从AMS测量中计算出的值NCCN在0.1%和0.2%的过饱和,这可能是由于κorg的低估和高估强度σs/一个被underpredicted。对于0.4%和0.7%SS值,发现由于内部混合假设的轻微overpredicted NCCN值。我们的结果突出了精确地评估在吸湿性参数κ,表面张力σ两者的有机物的影响以精确地预测CCN活性的需要。

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