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Introducing a Novel Absorbing Aerosol Index Retrieval Algorithm

In a study published in Remote Sensing, researchers introduced a novel absorbing aerosol index (AAI) retrieval algorithm based on an environmental trace gases monitoring instrument (EMI). EMI AAI algorithm could efficiently detect large aerosol events to reconstruct the spatial variability of ultraviolet-absorbing aerosols.

emi, aerosol

Study: Successful Derivation of Absorbing Aerosol Index from the Environmental Trace Gases Monitoring Instrument (EMI). Image Credit: Alexander_Magnum/Shutterstock.com

Effect of Aerosols on the Earth's Environment

Aerosols are tiny solid particles or liquid droplets suspended in the air. They can be anthropogenic and natural. Common examples are mist, dust and volcanic ash.

The impact of aerosols on Earth's climate is complicated. Aerosols directly impact the Earth's radiative balance by scattering and absorbing incoming solar and infrared light. However, they indirectly alter the optical characteristics and longevity of clouds.

Remote sensing from space has produced substantial, long-term records of aerosol data for research on aerosols' climate and health implications.

Absorbing Aerosol Index

The absorbing aerosol index (AAI) is widely used to give crucial data on the movement of tropospheric aerosols from anthropogenic sources such as industrial pollution and biomass burning and natural sources such as volcanic ash and desert dust.

All these aerosols can cause global and regional air pollution. Various satellite missions expanded our understanding of aerosol absorption by giving backscattered radiation observations, which were used to calculate the absorbing aerosol index.

AAI is a valuable parameter derived from spaceborne radiances. Since it is not sensitive to any surface type, it can be retrieved across land and water. However, AAI is very sensitive to UV-absorbing aerosols such as mineral dust, smoke, and volcanic ash.

Most aerosol optical characteristics are currently retrieved from space using methods that first conduct cloud screening. Therefore, AAI retrieval is useful since it can be used in cloudy settings.

Environmental Trace Gases Monitoring Instrument (EMI)

The environmental trace gases monitoring instrument is a GaoFen5 satellite-borne hyperspectral spectrometer that can recover trace gases. The EMI also offers independent world coverage AAI data, confirming that AAI is appropriate for monitoring and detecting aerosol absorption.

Retrieving Absorbing Aerosol Index from the Environmental Trace Gases Monitoring Instrument (EMI)

The objective of this study is to evaluate EMI AAI utilizing TROPOspheric monitoring instrument (TROPOMI) level 2 datasets comprising AAI and aerosol optical depth (AOD).

Researchers compared the AAI from TROPOMI with the monthly average EMI AAI for dust and smoke particles in August and October 2019. The spatial dispersion of aerosol EMI satellite data was validated using AOD from the aerosol robotic network and TROPOMI, and the effectiveness of EMI was verified by examining wildfires in Australia in November 2019.

This study employed the AAI technique under cloudy conditions. The AAI was calculated using EMI radiance measurements and geometries using the SCIATRAN radiative transfer model.

Since EMI irradiance calibration errors influenced some initial AAI values, the algorithm was corrected for across-track variability. In addition, the correction factors were derived using background values to mitigate radiometric inaccuracies.

Significant Findings of the Study

The proposed EMI instrument's AAI retrieval technique can track significant absorbing aerosol occurrences. The technique was built on reflectance, determined by observations of Earth radiance and sun irradiance at 380 and 340 nm (UV2 band).

EMI AAI results were initially verified using TROPOMI AAI data. Equal distributions of absorbing aerosols were found when comparing the monthly mean EMI to the TROPOMI AAI. The difference in mean AAI values between EMI and TROPOMI was less than 24%.

The investigation revealed that the monthly mean AAI in the primary polluted locations followed a unique seasonal cycle, with lower values in the fall and higher values in the summer season.

Researchers examined the EMI and TROPOMI AAI products using a single measurement taken over the Sahara Desert to further verify the accuracy of the EMI AAI retrievals. The geographic distribution AAI obtained by EMI and TROPOMI AOD appeared uniform.

This study also investigated an extreme wildfire event that transported substantial amounts of black carbon from Australia to the Pacific Ocean from November 8 to November 16, 2019. Comparisons of smoke plumes demonstrated that EMI and TROPOMI had the same geographic fluctuations and distributions.

AAI in clouds was retrieved using simple cloud optical parameter assumptions. In addition, EMI AAI auxiliary information did not include ozone absorption effects on AAI. Despite these limitations, the study proved that EMI is a promising technique for characterizing aerosols.

Reference

Tang, F., Wang, W., Si, F., Zhou, H., Luo, Y., & Qian, Y. (2022). Successful Derivation of Absorbing Aerosol Index from the Environmental Trace Gases Monitoring Instrument (EMI). Remote Sensing. https://www.mdpi.com/2072-4292/14/16/4105/htm

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Owais Ali

Written by

Owais Ali

NEBOSH certified Mechanical Engineer with 3 years of experience as a technical writer and editor. Owais is interested in occupational health and safety, computer hardware, industrial and mobile robotics. During his academic career, Owais worked on several research projects regarding mobile robots, notably the Autonomous Fire Fighting Mobile Robot. The designed mobile robot could navigate, detect and extinguish fire autonomously. Arduino Uno was used as the microcontroller to control the flame sensors' input and output of the flame extinguisher. Apart from his professional life, Owais is an avid book reader and a huge computer technology enthusiast and likes to keep himself updated regarding developments in the computer industry.

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