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Journal of Geology & Geophysics

Journal of Geology & Geophysics
Open Access

ISSN: 2381-8719

Perspective - (2022)Volume 11, Issue 10

Technology and Applications of CO2 Remote Sensing

Desheng Liu*
 
*Correspondence: Desheng Liu, Department of Geography & Statistics, The Ohio State University, Ohio, USA, Email:

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Description

A key volatile of the Earth system, carbon dioxide (CO2) is regularly transferred between the hydrosphere, atmosphere, and solid Earth (mantle and crust). The relevant CO2 degassing mechanisms from the solid earth (i.e., geological CO2). 600 Metric tons of CO2 yr-1 is a conservative estimate of the total flux of lithospheric CO2 degassing. Volcanic (magmatic) CO2 and non-volcanic CO2 are two types of geological CO2. Magmatic CO2 is mainly released through volcanic and geothermal sites, where it can either be visible and easy to see due to the concurrent emission of condensing water vapour, or it can beinvisible and hard to see. Non-volcanic CO2 is produced by a variety of processes, such as metamorphism, carbonate hydrolysis, or deep burial mechanical disintegration of carbonates. It is released through mud volcanoes, sedimentary volcanism, faults and fractures, seeps, geysers, or mountain ranges. CO2 emissions from various sources may mix. While Lake Nyos in Cameroon is categorized as a non-volcanic CO2 emitter, co-emitted Helium points to a magmatic CO2 source beneath the lake.

Some molecules, such as CO2, absorb or emit photons of a particular wavelength when light interacts with them. Changes in the optical depth at that wavelength are a direct result of this interaction. This interaction is investigated using the physical analytical technique known as optical spectroscopy. By detecting changes in optical depth, optical remote sensing (hence referred to as RS) is a type of spectroscopy that is applied to a target that is far away from the analyzing device and can be used to estimate the amount of gas present.

Due to interference from other gases, particularly water vapour, not all of the discrete regions of the near and mid infrared optical spectrum where CO2 significantly absorbs are usable for remote sensing of CO2. Prior to developing a remote sensing platform, system analysis is essential to determining the best absorption band and the ideal absorption line within the band in order to improve Signal-to-Noise Ratio (SNR) and sensitivity (precision). A compromise between the best spectroscopic characteristics, the technology at hand, and spectroscopic factors such minimal parasitic absorption by other gas species or temperature dependency of absorption strength must often be made when selecting an absorption line.

The majority of RS methods produce absolute molecule number densities of some kind, either range resolved volume number densities (m3) or route averaged number densities (path densities for horizontal paths, column densities for vertical paths, in cm2 or m2). Number densities are frequently converted to mixing ratios for simpler comparison with ambient concentrations (in ppm.m for path averaging, ppm for range resolving techniques). Knowing the (dry) air number density is necessary for this since it affects the measurement path's air pressure, temperature, and humidity profiles. By simultaneously detecting air oxygen and connecting the CO2 concentration to the oxygen concentration, it is simple and easy to eliminate this dependence.

Aerial coverage to find new vents or diffuse degassing, which opens the door to studying related earth phenomena like volcanic flank degassing, are just a few of the significant advantages of remote sensing of CO2. Remote sensing offers a safer measuring distance and a faster measurement than traditional in-situ approaches, enabling simple time-lapse observations. For instance, changes in a volcano's degassing strength over a period of months that would have gone unreported otherwise could be found, and the source mechanism responsible could be looked into.

The ground-based differential absorption lidar and the groundbased solar open-path Fourier transform spectroscopy are the most accurate (sensitive) remote sensing devices. Optical remote sensing often gives a lower measurement precision than traditional in situ techniques and may suffer significantly from ambient noise sources, such as aerosols.

All six applications, such as study on the carbon cycle and warning and forecasting of volcanic eruptions, may benefit even though pure CO2 remote sensing is of limited utility for Earth science investigations that need multi-gas data (e.g. CO2 and SO2).

There are currently very few turnkey systems for remote sensing that are also commercially available. Additionally, these remote sensing packages are typically far more expensive than in-situ sensors. Open-path Fourier transform spectroscopy-based commercial systems stand out because they may offer exceptional measurement precisions, multi-gas detection, and high measurement repetition rates.

Although optical remote sensing has several drawbacks, it can be viewed as an addition to traditional gas measuring techniques rather than a complete replacement for them in the near future.

Satellite-borne remote sensing platforms that measure near surface CO2 concentrations are very appealing to Earth scientists because they offer free preprocessed data, a broad geographic reach, aerial coverage, and relatively high measurement repetition rates of the order of days and possibly hours in the future, despite the fact that their spatial resolution does not fit all reviewed Earth science problems. Currently available satellitebased remote sensing technologies, such the Orbiting Carbon Observatory (OCO-2), have measurement precisions and spatial resolution suitable for a variety of Earth science topics connected to CO2 degassing with significant user potential.

Author Info

Desheng Liu*
 
Department of Geography & Statistics, The Ohio State University, Ohio, USA
 

Citation: Liu D (2022) Technology and Applications of CO2 Remote Sensing. J Geol Geophys. 11:1057.

Received: 29-Nov-2022, Manuscript No. JGG-22-21113; Editor assigned: 01-Dec-2022, Pre QC No. JGG-22-21113 (PQ); Reviewed: 15-Dec-2022, QC No. JGG-22-21113; Revised: 22-Dec-2022, Manuscript No. JGG-22-21113 (R); Published: 29-Dec-2022 , DOI: 10.35248/2381-8719.22.11.1057

Copyright: © 2022 Liu D. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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