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Related Concept Videos

Emission Spectra02:39

Emission Spectra

75.5K
When solids, liquids, or condensed gases are heated sufficiently, they radiate some of the excess energy as light. Photons produced in this manner have a range of energies, and thereby produce a continuous spectrum in which an unbroken series of wavelengths is present.
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Flame Photometry: Overview01:02

Flame Photometry: Overview

1.3K
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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Flame Photometry: Lab01:16

Flame Photometry: Lab

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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...
811
Atomic Emission Spectroscopy: Overview01:20

Atomic Emission Spectroscopy: Overview

3.4K
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...
3.4K
Atomic Emission Spectroscopy: Lab01:29

Atomic Emission Spectroscopy: Lab

538
AES is a powerful analytical technique, especially effective when used with plasma sources, producing abundant spectra in characteristic emission lines. The Inductively Coupled Plasma (ICP), in particular, yields superior quantitative analytical data due to its high stability, low noise, low background, and minimal interferences under optimal experimental conditions. However, newer air-operated microwave sources are emerging as promising alternatives that could be more cost-effective than...
538
Atomic Emission Spectroscopy: Instrumentation01:22

Atomic Emission Spectroscopy: Instrumentation

1.1K
The instrumentation of atomic emission spectrometry (AES) involves various components, including atomization devices that convert samples into gas-phase atoms and ions. There are two main types of atomization devices: continuous and discrete atomizers.  Continuous atomizers, like plasmas and flames, introduce samples in a constant stream, while discrete atomizers inject individual samples using syringes or autosamplers. The most common discrete atomizer is the electrothermal atomizer.
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Wind Tunnel Experiments to Study Chaparral Crown Fires
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Global Ensemble Fire Emission Product Version 1.0 (EnsemFire V1.0).

Yunyao Li1,2,3, Daniel Tong4,5, Ziheng Sun6

  • 1Department of Earth and Environmental Sciences, The University of Texas at Arlington, Arlington, TX, 76019, USA. yunyao.li@uta.edu.

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|December 18, 2025
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Summary

EnsemFire v1.0 is a new global fire emission dataset that reduces uncertainty in biomass burning estimates. This enhanced dataset improves air quality and climate model predictions.

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Area of Science:

  • Atmospheric Science
  • Environmental Science
  • Earth System Science

Background:

  • Biomass burning is a significant source of air pollutants and greenhouse gases.
  • Existing emission inventories show considerable inconsistencies, leading to large uncertainties in emission estimates.
  • Accurate fire emission data is crucial for atmospheric modeling, air quality forecasting, and climate research.

Purpose of the Study:

  • To present EnsemFire v1.0, a global ensemble fire emission dataset.
  • To reduce uncertainty in biomass burning emission estimates by integrating multiple inventories.
  • To evaluate the impact of EnsemFire on atmospheric model performance.

Main Methods:

  • Integrated seven global and regional biomass burning emission inventories into an ensemble dataset (EnsemFire v1.0).
  • Provided daily emissions at 0.1° × 0.1° spatial resolution for various pollutants, greenhouse gases, and fire radiative power.
  • Utilized the Unified Forecast System (UFS) model to assess EnsemFire's impact on simulation bias and aerosol optical depth prediction.

Main Results:

  • EnsemFire v1.0 integrates multiple datasets, revealing significant inconsistencies among them.
  • The ensemble approach effectively reduces uncertainty in biomass burning emission estimates.
  • Using EnsemFire as input to the UFS model reduced simulation bias and improved aerosol optical depth prediction compared to the default emission input.

Conclusions:

  • EnsemFire v1.0 provides a more robust and less uncertain estimate of biomass burning emissions.
  • The dataset serves as a valuable resource for atmospheric modeling, air quality forecasting, and climate research.
  • EnsemFire improves the performance of atmospheric models in predicting key environmental variables.