Quantitative analysis of open-path FTIR spectra by using artificial neural networks

Susana Briz; Esteban García-Cuesta; Isabel Fernández-Gómez; Antonio J. de Castro

doi:10.1117/12.689956

12 October 2006 Quantitative analysis of open-path FTIR spectra by using artificial neural networks

Susana Briz, Esteban García-Cuesta, Isabel Fernández-Gómez, Antonio J. de Castro

Proceedings Volume 6362, Remote Sensing of Clouds and the Atmosphere XI; 63621F (2006) https://doi.org/10.1117/12.689956
Event: SPIE Remote Sensing, 2006, Stockholm, Sweden

Abstract

Quantitative analysis of absorbance spectra to retrieve gas concentrations in open-path FTIR air monitoring is not always a straightforward task. Most of commercial software use classical-least-squared algorithms to retrieve the unknown concentrations. These codes usually work in real time and give appropriate results. However, sometimes these codes fail when the background reference spectrum presents absorption lines of the gas to be monitorized. This effect is frequent in some applications. Line-by-line approaches give satisfactory results because these codes solve the problem associated to the reference spectrum generating a synthetic reference background. The main drawback is that these algorithms do not work in real time, and need a skilled operator. In this work, we propose the use of artificial neural networks to analyze absorbance spectra in real time to retrieve the unknown concentrations in a simultaneous way. In addition, capabilities of the method to solve spectral overlapping will be studied. In this sense, simultaneous analysis of four atmospheric gases (CO₂, CO, H₂O and N₂O) will be included in this first version. The effectiveness of the method will be evaluated from the experimental point of view. Experimental open-path FTIR spectra (0.5 cm^-1 of spectral resolution) will be analyzed with the proposed method, as well as with CLS and LBL codes for comparison purposes. Moreover, in these experiments CO concentration has been measured by using standard extractive equipment and can be compared with the values provided by our method. Finally, some indications will be pointed to extend the method to other gases and spectral regions.

Citation Download Citation

Susana Briz, Esteban García-Cuesta, Isabel Fernández-Gómez, and Antonio J. de Castro "Quantitative analysis of open-path FTIR spectra by using artificial neural networks", Proc. SPIE 6362, Remote Sensing of Clouds and the Atmosphere XI, 63621F (12 October 2006); https://doi.org/10.1117/12.689956

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KEYWORDS

Carbon monoxide

Gases

FT-IR spectroscopy

Absorption

Testing and analysis

Absorbance

Artificial neural networks

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