Estimating fine particulate matter component concentrations and size distributions using satellite-retrieved fractional aerosol optical depth: Part 1 - Method development
Estimating fine particulate matter component concentrations and size distributions using satellite-retrieved fractional aerosol optical depth: Part 1 - Method development
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DOI：
10.3155/1047-3289.57.11.1351
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发表时间：
2007-11-01
影响因子：
2.7
通讯作者：
Kahn, Ralph
中科院分区：
文献类型：
--
作者：
Liu, Yang;Koutrakis, Petros;Kahn, Ralph
我们开发了一种方法，使用总柱气溶胶光学厚度（AOD）和不同的气溶胶类型的分数AOD值，来自多角度成像光谱辐射计（MISR）气溶胶数据，估计地面浓度的细颗粒物（PM2.5）质量和其主要成分在美国东部和西部。与以往将气柱气溶胶光学厚度与地面PM2.5联系起来的研究相比，该方法将各种MISR气溶胶组分作为单独的预测变量。因此，可以估计不同颗粒物类型对PM2.5浓度的贡献。当AOD大于0.15时，MISR能够以约4%的不确定性水平区分灰尘和非灰尘颗粒，并且以约20%的不确定性水平区分光吸收颗粒和非光吸收颗粒。进一步的分析表明，MISR Version 17气溶胶微物理特性具有良好的灵敏度和内部一致性之间的不同的混合物类。在美国东部，单个分数AOD的反演不确定性范围在5%和11%之间，而在西部，非尘埃气溶胶组分的反演不确定性范围在11%和31%之间。这些结果提供了信心，分数AOD模型与其固有的灵活性，可以更准确地预测PM2.5及其成分的浓度。
We develop a method that uses both the total column aerosol optical depth (AOD) and the fractional AOD values for different aerosol types, derived from Multiangle Imaging SpectroRadiometer (MISR) aerosol data, to estimate ground-level concentrations of fine particulate matter (PM2.5) mass and its major constituents in eastern and western United States. Compared with previous research on linking column AOD with ground-level PM2.5, this method treats various MISR aerosol components as individual predictor variables. Therefore, the contributions of different particle types to PM2.5 concentrations can be estimated. When AOD is greater than 0.15, MISR is able to distinguish dust from non-dust particles with an uncertainty level of approximately 4%, and light-absorbing from non-light-absorbing particles with an uncertainty level of approximately 20%. Further analysis shows that MISR Version 17 aerosol microphysical properties have good sensitivity and internal consistency among different mixture classes. The retrieval uncertainty of individual fractional AODs ranges between 5 and 11% in the eastern United States, and between 11 and 31% in the west for non-dust aerosol components. These results provide confidence that the fractional AOD models with their inherent flexibility can make more accurate predictions of the concentrations of PM2.5 and its constituents.