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关于印度半岛中南部气溶胶主要类型的分类和子类划分:MODIS-OMI 算法。

On the classification and sub-classification of aerosol key types over south central peninsular India: MODIS-OMI algorithm.

机构信息

Department of Physics, CMR Institute of Technology, Bangalore 560 037, India.

出版信息

Sci Total Environ. 2014 Jan 15;468-469:1086-92. doi: 10.1016/j.scitotenv.2013.09.038. Epub 2013 Oct 4.

Abstract

Long-term (8 years), simultaneous data on aerosol optical properties from MODIS and OMI satellite sensors are analyzed to study their temporal characteristics and to infer on the major aerosol types present over the study location, Bangalore situated in south central peninsular India. Investigations are carried out on Aerosol Optical Depths (AODs), Angstrom exponent (α) and Aerosol Index (AI) for the purpose. Aerosol parameters exhibited significant seasonal variations: AODs peaking during monsoon, α during post-monsoon and AI during summer. Seasonal air mass back trajectories are computed to infer on the transport component over the study region. By assigning proper thresholds (depending on the nature of the location and transport pathways) on AOD and α values, aerosols are discriminated into their major types viz., marine influenced, desert dust, urban/industrialized and mixed types. Further sub-categorization of the aerosols has been done on an annual scale taking into account of their absorptance information in terms of the OMI-AI values. Mixed type aerosols contributed the most during all the seasons. Next to mixed type aerosols, marine influenced aerosols dominated during winter, desert dust during monsoon and summer, urban/industrialized aerosols during post-monsoon. Considering the urban nature of the study location, urban/industrialized/carbonaceous type aerosols have been significantly underestimated in these methodologies. Finally, discussion has been made on the consistency of the results obtained from the methodologies (i) based on AODs and α; (ii) based on AODs, α and AI.

摘要

利用 MODIS 和 OMI 卫星传感器的长期(8 年)气溶胶光学特性的同步数据,分析其时间特征,并推断研究地点班加罗尔(位于印度中南部半岛)存在的主要气溶胶类型。为此进行了气溶胶光学深度(AOD)、Angstrom 指数(α)和气溶胶指数(AI)的研究。气溶胶参数表现出明显的季节性变化:AOD 在季风期间达到峰值,α 在季风后期间达到峰值,AI 在夏季期间达到峰值。计算季节性大气质量后轨迹,以推断研究区域的传输分量。通过在 AOD 和α值上分配适当的阈值(取决于位置和传输路径的性质),将气溶胶分为其主要类型,即海洋影响、沙漠尘埃、城市/工业化和混合类型。进一步根据 OMI-AI 值的吸收信息,在年度尺度上对气溶胶进行了细分。在所有季节中,混合类型气溶胶的贡献最大。其次是混合类型气溶胶,海洋影响型气溶胶在冬季占主导地位,沙漠尘埃在季风和夏季占主导地位,城市/工业化气溶胶在季风后占主导地位。考虑到研究地点的城市性质,这些方法显著低估了城市/工业化/含碳气溶胶。最后,讨论了基于 AOD 和α的方法(i)和基于 AOD、α和 AI 的方法(ii)获得的结果的一致性。

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