INTRODUCTION:

Greenhouse gas flows on the earth's surface give an involved picture in space and time and its measurements are not directly via satellite observations. Concentration measurements can be used as inverse models that illustrate atmospheric transport.^1,2. Early estimates disclose that the intended level of measurement accuracy is unusually high^2,3. The major disadvantage of passive sounders in the infrared spectral region is related to their atmospheric weighting functions which favor the middle and the upper troposphere rather than the lower troposphere where the sources and sinks reside.^4,5

In the previous works, the evolution of active LIDAR sensors operating in the SWIR is now underway (MERLIN), with plans for a joint launch in 2020 by the German Aerospace Center and the French National Center for Space Studies.^6,7,8,9

To measure methane (CH4) from space, there are detection instruments to enhance spatial resolution, allow 24-hour data collection and reduce the effects of backscatter and cloud contamination. Several geostationary satellites have also been suggested to ensure continuous, high resolution surveillance of areas of interest (e.g. O and G basins) and continental coverage at hourly intervals⁶

In the studies concerning traces of atmospheric gases and highly concentrated atmospheric compounds for air quality control, including the use of LIDAR remote sensing.^10-13.

A measurement uncertainty is added as for the detection of greenhouse gases such as water vapor (H2O), methane (CH4) or carbon dioxide (CO2) in the mid-infrared spectral region.^13-14

During this work, some signals resulting from the LIDAR are analyzed and interpreted, this step is considered both important and accurate. Then, our simulation study is based on a digital program developed in FORTRAN language as well as the internationally approved HITRAN database.

In this present study, a LIDAR signal is analyzed to detect certain greenhouse gases; H₂O CH₄ and CO₂.

MATERIAL AND METHODS:

Experimental installation for the process registration of signal:

The process of recording a signal mainly depends on the laser beams, they are sent to the sample to study them. They are received by sensors, whose signal is amplified and recorded. Figure 2 shows the most important parts of the experimental structure.

Galtier et al. 2018¹³ carried out the experimental study of the OSAS-LIDAR methodology, designed to verify the methodology proposed for the recovery of methane concentrations.

For this purpose, the emitting part is a fs Ti: Sapphire laser pumped OPO emitting in the NIR with a pulse repetition frequency of 1 kHz. (See figure 1)

The spectral switch between the active channel P0;1(λ) at 1665.5nm and the reference channel P0;2(λ) at 1660 nm is done with an acousto-optic programmable dispersive filter.¹³ We have produced laser pulses with energy of 30 μJ and a spectral width of 2nm.

During the emission, we carried out the amplitude modulation of the laser, and we see the simplicity of the configuration of the LIDAR receiver.

The light collected with a Newtonian telescope by the following dimensions: focal length of 450mm and a primary mirror diameter of 115mm. The NIR detector is formed by an APD based on InGaAs mounted at the focal point of the telescope.

The range of view of 0.44 mrad is dependent on the detector diameter of 200μm.

The signal acquisition system is a 12-bit digitizing oscilloscope.¹³

Figure 1: Simplified experimental structure for recording a LIDAL signal ¹³

OSAS LIDAR Technique:

According to Galtier et al. 2018, in the OSAS-methodology, the power spectral density (PSD) of a broadband light source is set to be similar with the TG-gas absorption spectrum.^13,15

The OSAS principle is configured in Fig. 2 when the methane is proposed in its 2_υ3 absorption interval.

The active channel P0; 1 (λ), which interferes with the absorption lines of the Q section, follows light absorption along the optical path, while the reference channel P0; 2 (λ) pursues lower light extinction.

Therefore, by the absorption of light, the detection of the two different signals, S1 and S2, is carried out.¹³

Figure 2: OSAS principle applied to the 2 υ3 methane gas absorption band ¹³

In order to be able to know the chemical elements that absorbed the laser beams that were sent during the LIDAR experiment, a digital program was implemented.

This program is written in FORTRAN language, it mainly depends on the partial spectral data. First, we are looking for a molecular spectral data for the elements expected to be in the medium.

This program, in addition to the spectral intensity equation, also it depends on the Beer Lambert absorption equation. The program is outlined in Figure 3.

Figure 3: The program illustration

Program Performance:

According to this program, we guarantee exact calculations. The carbon dioxide spectrum was calculated in the range of 6150 and 6500 cm^-1 through the implementation of spectral data using the HITRAN method¹⁶.

Based on a comparison between the simulated results and those of Anselmo et al. 2016, we notice an illustrated confrontation in the same spectral field. (See figures 4 and 5)

We notice after the comparison also that there is a good symmetry between the emission spectrum of methane with the absorption spectrum of methane calculated by our program (See figures 2 and 6).

Figure 4: CO2 absorption spectrum ¹⁷

Figure 5: Absorption spectrum for the carbon dioxide (the present study)

Figure 6: Absorption spectrum for the Methane (the present study)

RESULTS AND DISCUSSION:

Program implementation and signal interpretation:

The experimental signal of LIDAR we will be studied is presented in the figure 7.

Figure 7: Experimental Sample of LIDAR signal ¹⁸

The necessary data were prepared by relying on the HITRAN rule¹⁶, we obtain the absorption spectra according to each element expected to be present in the medium (CH4, N2, CO2, H2O…)

For CH4 methane, via a comparison, the theoretical signal of the absorption spectrum of methane. According to the experimental spectrum, we find that there is no absorption of this signal.

Therefore, the studied sample doesn't contain methane gas at all and its rate of presence is completely neglected. Figure 8 shows the methane signal is calculated theoretically.

Figure 8: Methane signal within the experimental spectrum range (present study)

Regarding nitrogen oxide, its absorption field is not included in this specific area of the experimental spectrum, and therefore we cannot speak of the percentage of its absorption in this sample.

As for carbon dioxide gas, by comparison between the theoretical spectrum calculated and shown in Figure 9 and the experimental spectrum, it is clear that this gas is present with the studied sample.

Figure 9: Carbon dioxide signal within the experimental spectrum range (present study)

Concerning water vapor, it is through the calculated theoretical absorption signal that its presence is clear, especially in the last part of the experimental signal. (See figure 10)

Figure 10: water vapor signal within the experimental spectrum range (present study)

In order to control the ratio of the presence of both carbon dioxide and water vapor with the studied sample, we need a digital calibration process, with mixing 1 mole of both elements gives the comparison shown in Figure 11 of their absorption spectrum.

Figure 11: 1 mole absorption signal for water vapor and carbon dioxide (present study)

For the absorption ratios between the theoretical and experimental spectrum, we need 1.45 mole of water vapor versus 1 mole of carbon dioxide.

CONCLUSION:

Global warming is considered one of the most dangerous natural phenomena that generally threaten living organisms. It is also considered one of the most important priority research topics at the present time.

Global warming is the gradual increase in the temperature of the layers of the atmosphere surrounding the Earth.

Due to an increase in greenhouse gas emissions, which play an important role in heating the earth's surface to be viable.

The absence of the greenhouse effect results in an increase in the Earth's temperature that can reach 15°C to 19°C below zero and these gases absorb part of the infrared reflected from the Earth's surface to maintain its temperature at its normal level.

During this work, we were able to detect some of these greenhouse gases by using the LIDAR technology. As it was based on the recorded signal, and by relying on a digital program prepared in the Fortran language. In addition, the spectral data, we obtained the presence of water vapor and carbon dioxide clearly in the studied sample.

ACKNOWLEDGEMENT:

The authors like to thank the General Direction of research and development technologies/Ministry of Higher Education and Research Sciences DGRSDT/MERS (Algeria) for their financial support.

CONFLICT OF INTEREST:

The authors declare no conflict of interest.

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Received on 23.02.2021 Modified on 19.03.2021

Asian Journal of Research in Chemistry. 2021; 14(4):292-296.

DOI: 10.52711/0974-4150.2021.00050