Abstract. In the frame of the EMEP/ACTRIS/COLOSSAL campaign in Milan during winter 2018, equivalent black carbon measurements using the Aethalometer 31 (AE31), the Aethalometer 33 (AE33), and the Multi-Angle Absorption Photometer (MAAP) were carried out together with levoglucosan analyses on 12-h resolved PM_2.5 samples collected in parallel. From AE31 and AE33 data, the loading-corrected aerosol attenuation coefficients (b_ATN) were calculated at 7 wavelengths (λs, where λ = 370, 470, 520, 590, 660, 880, 950 nm). Aerosol absorption coefficient at 637 nm (b_{abs_MAAP}) was determined by MAAP measurements. Furthermore, b_abs was also measured at 4 wavelengths (405, 532, 635, 780 nm) on the 12-h resolved PM_2.5 samples by a polar photometer (PP_UniMI). After comparing PP_UniMI and MAAP results, we exploited PP_UniMI data to evaluate the filter multiple-scattering enhancement parameter at different wavelengths for AE31 and AE33. We obtained instrument- and wavelength-dependent multiple-scattering parameters by linear regression of the Aethalometer b_ATN against the b_abs measured by PP_UniMI. We found significant filter material, and hence instrumental, dependence of the multiple-scattering enhancement parameter with the difference up to 30 % between the AE31 and the AE33 tapes. The wavelength dependence and day/night variations were small – the difference between the smallest and largest value was up to 6 %. Data from the different instruments were used as input to the so-called “Aethalometer model” for optical source apportionment and instrument-dependence of the results was investigated. Inconsistencies among the source apportionment were found fixing the AE31 and AE33 multiple-scattering enhancement parameters to their usual values. Opposite, optimised multiple-scattering enhancement parameters led to 5 % agreement among the approaches. Also, the component-apportionment “MWAA model” was applied to the dataset. It resulted less sensitive to the instrument and the number of wavelengths, whereas significant differences in the determination of the absorption Ångström exponent for brown carbon were found (up to 22 %).

中文翻译：

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确定2017-2018年冬季在米兰举行的EMEP / ACTRIS / COLOSSAL运动中的风速计多重散射增强参数及其对源分配的影响

摘要。在2018年冬季在米兰举行的EMEP / ACTRIS / COLOSSAL活动的框架中，一起使用Aethalometer 31（AE31），Aethalometer 33（AE33）和多角度吸收光度计（MAAP）进行了等效的黑碳测量用左旋葡聚糖分析平行采集的12小时分离的PM _2.5样品。根据AE31和AE33数据，在7个波长（λs，其中λ= 370、470、520、590、660、880、950 nm ）处计算出经过载荷校正的气溶胶衰减系数（b _ATN）。通过MAAP测量确定637 nm处的气溶胶吸收系数（b _{abs_MAAP}）。此外，还在12小时分辨PM _2.5上的4个波长（405、532、635、780 nm）处测量了b _abs通过极谱仪（PP_UniMI）进行采样。在比较PP_UniMI和MAAP结果之后，我们利用PP_UniMI数据评估了AE31和AE33在不同波长下的滤光片多散射增强参数。我们通过将湿度计b _ATN相对于b _abs进行线性回归获得了与仪器和波长相关的多重散射参数由PP_UniMI测量。我们发现大量的过滤材料，并因此对多重散射增强参数的依赖，在AE31和AE33磁带之间的差异高达30％。波长依赖性和日夜变化很小-最小值和最大值之间的差异最大为6％。来自不同仪器的数据被用作所谓的“测风计模型”的输入，用于光源分配，并研究了仪器对结果的依赖性。发现源分配之间存在不一致，将AE31和AE33多重散射增强参数固定为它们的通常值。相反，优化的多散射增强参数导致这些方法之间的一致性为5％。此外，将组件比例“ MWAA模型”应用于数据集。