: We estimated fine-mode black carbon (BC) concentrations at the surface using AERONET data from five AERONET sites in Korea, representing urban, rural, and background. We first obtained the columnar BC concentrations by separating the refractive index (RI) for fine-mode aerosols from AERONET data and minimizing the difference between separated RIs and calculated RIs using a mixing rule that can represent a real aerosol mixture (Maxwell Garnett for water-insoluble components and volume average for water-soluble components). Next, we acquired the surface BC concentrations by establishing a multiple linear regression (MLR) between in-situ BC concentrations from co-located or adjacent measurement sites, and columnar BC concentrations, by linearly adding meteorological parameters, month, and land-use type as the independent variables. The columnar BC concentrations estimated from AERONET data using a mixing rule well reproduced site-specific monthly variations of the in-situ measurement data, such as increases due to heating and/or biomass burning and long-range transport associated with prevailing westerlies in the spring and winter, and decreases due to wet scavenging in the summer. The MLR model exhibited a better correlation between measured and predicted BC concentrations than those based on columnar concentrations only, with a correlation coefficient of 0.64. The performance of our MLR model for BC was comparable to that reported in previous studies on the relationship between aerosol optical depth and particulate matter concentration in Korea. This study suggests that the MLR model with properly selected parameters is useful for estimating the surface BC concentration from AERONET data during the daytime, at sites where BC monitoring is not available.

中文翻译：

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根据韩国航空网站点的长期测量估算黑碳的表面浓度

： 我们使用来自韩国五个AERONET站点的AERONET数据（代表城市，农村和背景）估算了表面的精细模式黑碳（BC）浓度。我们首先通过从AERONET数据中分离出精细模式气溶胶的折射率（RI），并使用可以代表真实气溶胶混合物的混合规则（将Maxis Garnett用于水-不溶成分和水溶性成分的体积平均值）。接下来，我们通过线性添加气象参数，月份和土地利用类型，通过在位于同一地点或相邻测量点的原地BC浓度与柱状BC浓度之间建立多元线性回归（MLR），获得了表面BC浓度。作为自变量。使用混合规则从AERONET数据估算的柱状BC浓度很好地再现了现场测量数据的特定于位置的每月变化，例如由于加热和/或燃烧生物质以及与春季盛行的西风相关的长距离运输而增加冬季，由于夏季湿清除而减少。与仅基于柱状浓度的BCR浓度相比，MLR模型显示出测得的BC浓度与预测的BC浓度之间具有更好的相关性，相关系数为0.64。我们针对BC的MLR模型的性能可与之前有关韩国气溶胶光学深度与颗粒物浓度之间关系的研究报告相媲美。