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Atomic Emission Spectroscopy: Overview01:20

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Atomic emission spectroscopy (AES) is an analytical technique used to determine the elemental composition of a sample by analyzing the light emitted from excited atoms. In AES, atoms in a sample are excited to higher energy levels by thermal energy from high-temperature sources, such as plasma, arcs, or sparks. When these excited atoms return to lower energy states, they emit light at specific wavelengths characteristic of each element. The resulting atomic emission spectrum, which consists of...
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Inductively Coupled Plasma Atomic Emission Spectroscopy: Instrumentation01:26

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Inductively coupled plasma (ICP) is the common plasma source used in atomic emission spectroscopy (AES), a technique that detects and analyzes various elements in a sample. This method is often called inductively coupled plasma atomic emission spectroscopy (ICP-AES).
There are three main types of inductively coupled plasma atomic emission spectroscopy  (ICP-AES) instruments: sequential, simultaneous multichannel, and Fourier transform instruments, with the latter being less commonly used....
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Measurement of Aerosols Optical Thickness of the Atmosphere using the GLOBE Handheld Sun Photometer
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使用空间时空长短期内存卷积自编码器重建气溶光学深度.

Lu Liang1, Jacob Daniels2, Michael Biancardi3

  • 1Department of Geography and the Environment, University of North Texas, Denton, TX, 76203, USA. lu.liang@unt.edu.

Scientific data
|November 30, 2023
PubMed
概括
此摘要是机器生成的。

这项研究使用卫星数据和人工智能为德克萨斯州创建了一个无间隙,长期的气溶光学深度 (AOD) 数据集. 这种改进的AOD数据有助于气候和空气质量研究.

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科学领域:

  • 大气科学 大气科学
  • 遥感 遥感 遥感 遥感
  • 数据科学数据科学数据科学

背景情况:

  • 气溶光学深度 (AOD) 对气候,空气质量和健康评估至关重要.
  • 卫星AOD数据提供了广泛的覆盖范围,但由于各种因素而存在数据缺口.
  • 现有的AOD数据集缺乏全面分析所需的长期连续性.

研究的目的:

  • 为德克萨斯州 (2010-2022) 开发一个无间隙的,长期的卫星衍生的AOD数据集.
  • 使用先进的深度学习技术重建丢失的AOD数据.
  • 为环境和公共卫生研究提供可靠的AOD资源.

主要方法:

  • 使用中等分辨率成像光谱辐射仪 (MODIS) 多角度实现大气校正 (MAIAC) 产品.
  • 采用时空长短期记忆 (LSTM) 卷积自编码器进行数据重建.
  • 将重建的数据与独立测试和地面AERONET数据集进行验证.

主要成果:

  • 与测试数据相比,在AOD重建中实现了高精度,RMSE为0.017和R2为0.941.
  • 证明了与地面AERONET数据 (RMSE 0.052-0.067) 的满意一致.
  • 创建了一个全面的数据集,可用于每日,月度,季度和年度决议.

结论:

  • 开发的LSTM自编码器有效地重建了缺失的卫星AOD数据.
  • 无间隙的德克萨斯州AOD数据集为大气和健康研究提供了宝贵的资源.
  • 这项工作增强了卫星AOD数据对科学研究和决策的有用性.