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In a flame photometer, when a solution like potassium chloride is aspirated into the flame, the solvent evaporates, leaving behind dehydrated salt. This salt dissociates into free gaseous atoms in their ground state. Some of these atoms absorb energy from the flame, leading to their excitation. The excited atoms return to the ground state, emitting photons at characteristic wavelengths. Because only electronic transitions are involved, the resulting emission lines are very narrow. The intensity...
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Flame photometry, also known as flame emission spectrometry, is a technique used for the qualitative and quantitative analysis of elements present in a sample using a flame as the source of excitation energy. The concept of flame photometry was realized in the early 1860s by Kirchhoff and Bunsen, who discovered that specific elements emit characteristic radiation when excited in flames. The first instrument developed for this purpose was used to measure sodium (Na) in plant ash using a Bunsen...
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Precipitation Gravimetry01:03

Precipitation Gravimetry

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Updated: Jun 10, 2026

Measuring the Structure, Composition, and Change of Underwater Environments with Large-area Imaging
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CO(2) lidar backscatter profiles over Hawaii during fall 1988.

M J Post, R E Cupp

    Applied Optics
    |August 21, 2010
    PubMed
    Summary
    This summary is machine-generated.

    This study analyzed Doppler lidar data, revealing lower aerosol and cloud backscatter than typical for the continental U.S. Episodic enhancements from cirrus and dust were observed, with implications for satellite wind profiling sensors.

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    Published on: October 21, 2016

    Area of Science:

    • Atmospheric Science
    • Remote Sensing
    • Lidar Technology

    Background:

    • Doppler lidar measurements provide crucial data on atmospheric aerosols and clouds.
    • Understanding backscatter variations is essential for accurate atmospheric profiling.
    • Previous analyses were limited by biases due to data dropouts.

    Purpose of the Study:

    • To analyze aerosol and cloud backscatter data using a novel technique to reduce dropout-related biases.
    • To characterize typical backscatter cross sections and identify episodic events.
    • To discuss the implications of these findings for the Laser Atmospheric Wind Sounder (LAWS) satellite sensor.

    Main Methods:

    • Utilized 24-day Doppler lidar data collected in fall 1988 at a 10.59-microm wavelength.
    • Applied a new data analysis technique to mitigate biases caused by data dropouts.
    • Quantified backscatter cross sections and identified contributing aerosol types.

    Main Results:

    • Observed significantly lower typical backscatter cross sections compared to continental U.S. averages.
    • Documented episodic backscatter enhancements attributed to cirrus clouds and mineral dust.
    • The new technique successfully reduced biases in the backscatter data.

    Conclusions:

    • The study provides valuable insights into aerosol and cloud backscatter characteristics.
    • Findings highlight the importance of accounting for data dropouts in lidar analysis.
    • The results have direct implications for the design and capabilities of future satellite-based wind profiling systems like LAWS.