收稿：2018-04-18，
录用：2018-5-23，
纸质出版：2019-05
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大气气溶胶成分的复杂变化导致其在气候变化评估中具有很高的不确定性。气溶胶成分遥感利用遥感观测的气溶胶光学—微物理参数，定量估计整层大气气溶胶主要成分含量，具有实时快速、空间覆盖、保持气溶胶自然状态等特点。本文介绍了近年来气溶胶成分遥感在理论基础和观测研究方面的进展情况。首先，在简要回顾反演算法发展的基础上，以目前较先进的成分遥感分类模型(包括黑碳、棕色碳、沙尘、非吸光有机物、细粒子无机盐、海盐和水)为例，详细分析了气溶胶成分遥感反演的思路。据此提出了基于气溶胶综合光学—微物理特性(包括光学吸收/散射、粒径尺度、形状等敏感性特征参数)的气溶胶成分遥感识别方法。之后，结合气溶胶混合方式，讨论了复折射指数计算方法及其对成分反演的影响，并给出了利用同步化学采样观测验证气溶胶成分遥感的一些结果示例。最后，结合观测手段拓展、成分模型优化、反演精度提升、应用能力推广等4个方向，展望了大气气溶胶成分遥感的发展趋势，及其在全球气候变化评估等领域的应用。
Complex and drastic variations of atmospheric aerosol components lead to high uncertainties in climate change assessment. The remote sensing of aerosol composition is the technology often used in aerosol optical and microphysical parametric analysis. These parameters
which are derived from remote sensing measurements
can quantitatively estimate the aerosol components of the entire atmosphere. Remote sensing offers the advantages of real-time and fast detection
spatial coverage
and maintenance of natural aerosol status. This paper presents a comprehensive review of theories
observations
models
and algorithms for aerosol composition remote sensing. First
in the area of algorithm development
we analyze the main ideas and methods for establishing aerosol composition models. In particular
an advanced remote sensing categorization model
which includes black carbon
brown carbon
mineral dust
light-scattering organic matter
inorganic salts
sea salt
and water
is presented in detail. The methods are identified or distinguished according to components (i.e.
sensitivity parameters
including light absorption
size distribution
particulate shape
etc.). Second
for the calculation of the refractive index
some of the typical methods suitable for different aerosol mixing states are compared
and then their impacts on composition retrieval are determined. Third
some examples of remotely sensed aerosol components are given
and a preliminary validation of the retrievals is conducted by using synchronized chemical measurements. Finally
the development tendencies of the remote sensing of atmospheric aerosol composition are summarized from the perspectives of observation capability enhancement
optimization of the categorization model
improvements in retrieval accuracy
extension of application abilities
and identification of utilization prospects in global climate change assessment.
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