Retrieval of Aerosol Components Using Multi-Wavelength Mie-Raman Lidar and Comparison with Ground Aerosol Sampling
Retrieval of Aerosol Components Using Multi-Wavelength Mie-Raman Lidar and Comparison with Ground Aerosol Sampling
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DOI：
10.3390/rs10060937
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发表时间：
2018-06
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影响因子：
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通讯作者：
Y. Hara;T. Nishizawa;N. Sugimoto;K. Osada;K. Yumimoto;I. Uno;R. Kudo;H. Ishimoto
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文献类型：
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作者：
Y. Hara;T. Nishizawa;N. Sugimoto;K. Osada;K. Yumimoto;I. Uno;R. Kudo;H. Ishimoto
我们验证了一种使用多波长米拉曼激光雷达（MMRL）观测的算法，通过原位气溶胶测量反演四种气溶胶成分（黑碳（BC）、海盐（SS）、空气污染（AP）和矿物粉尘（DS）），并确定了日本西部地区福冈市气溶胶成分的季节变化。 PM2.5、PM10 以及 BC 和 SS 成分的质量浓度均来自现场测量。 MMRL 提供 355 和 532 nm 处的气溶胶消光系数 (α)、粒子线性去偏比 (δ)、反向散射系数 (β) 和激光雷达比 (S)，以及 1064 nm 处的衰减反向散射系数 (βatt)。我们使用 MMRL 的 1α532 + 1β532 + 1βatt、1064 + 1δ532 数据检索了四种气溶胶成分（BC、SS、AP 和 DS）在 532 nm 处的消光系数的垂直分布。假定每种气溶胶成分具有规定的尺寸分布、颗粒形状和折射率，使用理论计算的转换因子将在 532 nm 处检索到的四种气溶胶成分的消光系数转换为质量浓度。 MMRL 和原位测量证实，除了水溶性气溶胶的吸湿生长之外，气溶胶光学特性的季节性变化还受到各种气溶胶成分的内部/外部混合的影响。与使用纯 BC 模型进行原位观察相比，MMRL 高估了 BC 质量浓度。通过引入BC和水溶性物质的内部混合物模型（核心-灰壳（CGS）模型），这种高估现象大大减少。这一结果表明，考虑BC和水溶性物质的内部混合物对于评估该区域的BC质量浓度至关重要。即使我们应用 CGS 模型，在夏季也发现了对 BC 质量浓度的系统高估。基于原位和MMRL测量的观测事实表明，AP被错误分类为CGS颗粒是由于激光雷达分析中的数值模型低估了相对湿度（RH），以及反演中假设的AP和CGS光学模型与实际大气中气溶胶特性的不匹配。激光雷达观测的SS随时间变化与现场测量基本一致；然而，我们发现沙尘事件期间的 SS 存在一些高估。这种 SS 高估的原因主要是由于将内部混合 DS 错误分类为 SS，这意味着考虑 DS 和水溶性物质之间的内部混合可以得到更好的估计。尽管激光雷达得出的 PM2.5 和 PM10 在沙尘事件中被高估，但 PM2.5 和 PM10 的时间变化总体上与现场测量表现出良好的一致性。
We verified an algorithm using multi-wavelength Mie-Raman lidar (MMRL) observations to retrieve four aerosol components (black carbon (BC), sea salt (SS), air pollution (AP), and mineral dust (DS)) with in-situ aerosol measurements, and determined the seasonal variation of aerosol components in Fukuoka, in the western region of Japan. PM2.5, PM10, and mass concentrations of BC and SS components are derived from in-situ measurements. MMRL provides the aerosol extinction coefficient (α), particle linear depolarization ratio (δ), backscatter coefficient (β), and lidar ratio (S) at 355 and 532 nm, and the attenuated backscatter coefficient (βatt) at 1064 nm. We retrieved vertical distributions of extinction coefficients at 532 nm for four aerosol components (BC, SS, AP, and DS) using 1α532 + 1β532 + 1βatt,1064 + 1δ532 data of MMRL. The retrieved extinction coefficients of the four aerosol components at 532 nm were converted to mass concentrations using the theoretical computed conversion factor assuming the prescribed size distribution, particle shape, and refractive index for each aerosol component. MMRL and in-situ measurements confirmed that seasonal variation of aerosol optical properties was affected by internal/external mixing of various aerosol components, in addition to hygroscopic growth of water-soluble aerosols. MMRL overestimates BC mass concentration compared to in-situ observation using the pure BC model. This overestimation was reduced drastically by introducing the internal mixture model of BC and water-soluble substances (Core-Gray Shell (CGS) model). This result suggests that considering the internal mixture of BC and water-soluble substances is essential for evaluating BC mass concentration in this area. Systematic overestimation of BC mass concentration was found during summer, even when we applied the CGS model. The observational facts based on in-situ and MMRL measurements suggested that misclassification of AP as CGS particles was due to underestimation of relative humidity (RH) by the numerical model in lidar analysis, as well as mismatching of the optical models of AP and CGS assumed in the retrieval with aerosol properties in the actual atmosphere. The time variation of lidar-derived SS was generally consistent with in-situ measurement; however, we found some overestimation of SS during dust events. The cause of this SS overestimation is mainly due to misclassifying internally mixing DS as SS, implying that to consider internal mixing between DS and water-soluble substances leads to better estimation. The time-variations of PM2.5 and PM10 generally showed good agreement with in-situ measurement although lidar-derived PM2.5 and PM10 overestimated in dust events.