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Investigating the quality of modeled aerosol profiles based on combined lidar and sunphotometer data

机译:基于组合激光雷达和太阳光度计数据研究模拟气溶胶剖面的质量

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摘要

In this study we present an evaluation of the Comprehensive Air Quality Model with extensions (CAMx) for Thessaloniki using radiometric and lidar data. The aerosol mass concentration profiles of CAMx are compared against the PM2.5 and PM2. 5−10 concentration profiles retrieved by the Lidar-Radiometer Inversion Code (LIRIC). The CAMx model and the LIRIC algorithm results were compared in terms of mean mass concentration profiles, center of mass and integrated mass concentration in the boundary layer and the free troposphere. The mean mass concentration comparison resulted in profiles within the same order of magnitude and similar vertical structure for the PM2. 5 particles. The mean centers of mass values are also close, with a mean bias of 0.57 km. On the opposite side, there are larger differences for the PM2. 5−10 mode, both in the boundary layer and in the free troposphere. In order to grasp the reasons behind the discrepancies, we investigate the effect of aerosol sources that are not properly included in the model's emission inventory and in the boundary conditions such as the wildfires and the desert dust component. The identification of the cases that are affected by wildfires is performed using wind backward trajectories from the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model in conjunction with satellite fire pixel data from MODerate-resolution Imaging Spectroradiometer (MODIS) Terra and Aqua global monthly fire location product MCD14ML. By removing those cases the correlation coefficient improves from 0.69 to 0.87 for the PM2. 5 integrated mass in the boundary layer and from 0.72 to 0.89 in the free troposphere. The PM2.5 center of mass fractional bias also decreases to 0.38 km. Concerning the analysis of the desert dust component, the simulations from the Dust Regional Atmospheric Model (BSC-DREAM8b) were deployed. When only the Saharan dust cases are taken into account, BSC-DREAM8b generally outperforms CAMx when compared with LIRIC, achieving a correlation of 0.91 and a mean bias of −29.1 % for the integrated mass in the free troposphere and a correlation of 0.57 for the center of mass. CAMx, on the other hand, underestimates the integrated mass in the free troposphere. Consequently, the accuracy of CAMx is limited concerning the transported Saharan dust cases. We conclude that the performance of CAMx appears to be best for the PM2.5 particles, both in the boundary layer and in the free troposphere. Sources of particles not properly taken into account by the model are confirmed to negatively affect its performance, especially for the PM2. 5−10 particles.
机译:在这项研究中,我们使用辐射和激光雷达数据对塞萨洛尼基的综合空气质量模型进行了扩展(CAMx)评估。将CAMx的气溶胶质量浓度曲线与PM2.5和PM2进行比较。激光雷达辐射计反码(LIRIC)检索的5-10浓度曲线。比较了CAMx模型和LIRIC算法的结果,包括边界层和对流层中的平均质量浓度分布图,质心和积分质量浓度。平均质量浓度比较导致PM2的分布在相同数量级和相似的垂直结构内。 5个颗粒。平均质心值也很接近,平均偏差为0.57 km。相反,PM2的差异更大。在边界层和自由对流层均处于5-10模式。为了掌握差异背后的原因,我们调查了未适当纳入模型排放清单和边界条件(例如野火和沙漠尘埃成分)的气溶胶源的影响。使用混合单粒子拉格朗日综合轨迹(HYSPLIT)模型中的后风轨迹,结合现代分辨率成像光谱仪(MODIS)的Terra和Aqua全球月度火灾,确定受野火影响的病例定位产品MCD14ML。通过消除这些情况,PM2的相关系数从0.69提高到0.87。边界层的积分质量为5,自由对流层的积分质量为0.72至0.89。 PM2.5质心分数偏差也降低到0.38 km。关于沙漠尘埃成分的分析,采用了“尘埃区域大气模型”(BSC-DREAM8b)的模拟。如果仅考虑撒哈拉尘埃的情况,则与LIRIC相比,BSC-DREAM8b的性能通常优于CAMx,自由对流层积分质量的相关系数为0.91,平均偏差为-29.1%,而对流层的相关系数为0.57。重心。另一方面,CAMx低估了自由对流层中的积分质量。因此,对于运输的撒哈拉尘埃案件,CAMx的准确性受到限制。我们得出结论,无论在边界层还是在对流层中,CAMx的性能似乎都是对PM2.5颗粒最好的。确认模型未适当考虑的颗粒来源会对其性能产生负面影响,尤其是对于PM2。 5-10个粒子。

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