地基MAX-DOAS系统获取大气水汽垂直柱浓度方法研究

doi:10.3964/j.issn.1000-0593(2024)08-2395-06

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Abstract Water vapor is a key component of the atmospheric water cycle, influencing global cloud distribution and precipitation frequency. As precipitation significantly impacts climate and the environment, rapidly acquiring atmospheric water vapor concentration is critical in environmental climate research. The multi-axis differential optical absorption spectroscopy (MAX-DOAS) technique is a remote sensing method that enables fast and accurate measurement of trace gas concentrations in the atmosphere. Due to its stability, real-time online measurement, and multi-component and non-contact measurement advantages, this technique has become a promising new method for measuring atmospheric water vapor column concentration. Considering the narrow absorption band range of water vapor and the saturation absorption effect at high concentrations, this paper develops a MAX-DOAS water vapor vertical distribution detection system. It conducts an inversion algorithm study to retrieve the vertical column water vapor concentration accurately. The water vapor vertical column concentration was obtained at the study site in Huaibei. During the inversion process, the solar spectra collected in the zenith direction are chosen as the reference spectra. Using the Differential Optical Absorption Spectroscopy (DOAS) algorithm, the differential slant column densities (dSCD) of water vapor at different elevation angles are obtained. Finally, water vapor's vertical column density (VCD) is extracted. The air mass factor (AMF) was obtained through geometric approximation. To minimize the interference from other gases, we analyzed the inversion errors for different spectral bands before the experiment and determined the optimal inversion band to be 433~452 nm. Continuous observations were conducted in the Huaibei region from February 24, 2023, to April 2, 2023. The experimental results indicate that during the monitoring period, the water vapor concentration in the Huabei region exhibited a V-shaped diurnal distribution pattern, with higher concentrations in the morning and evening and lower concentrations around noon. A correlation analysis was performed between water vapor's observed vertical column density (VCD) and the daily reanalysis data from the European Centre for Medium-Range Weather Forecasts (ECMWF)ERA5. The results showed a good consistency between the two datasets (R=0.95). Furthermore, an analysis of the relationship between wind speed, wind direction, and H₂O VCD distribution during the monitoring period revealed that when the wind direction was around 60° and the wind speed was less than 5 m·s^-1, there was an increasing trend in H₂O VCD. During the pollution stage, low wind speeds and higher water vapor concentrations were commonly observed features. The study demonstrated that the ground-based MAX-DOAS system effectively monitored water vapor vertical column concentration in the blue light band, providing an effective technical means for inverting atmospheric water vapor vertical column concentration.

Key words：MAX-DOAS; Water vapor; Vertical column concentration; Optimal retrieval wavelength; Huaibei region

Received: 2023-05-29 Accepted: 2023-10-17

ZTFLH:

X831

Corresponding Authors: LI Su-wen, MOU Fu-sheng E-mail: swli@chnu.edu.cn；moufusheng@163.com

Cite this article:

ZHOU Chuang,ZHANG Qi-jin,LI Su-wen, et al. Investigation of a Ground-Based MAX-DOAS System for Retrieving Vertical Column Density of Atmospheric Water Vapor[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(08): 2395-2400.

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https://www.gpxygpfx.com/EN/10.3964/j.issn.1000-0593(2024)08-2395-06 OR https://www.gpxygpfx.com/EN/Y2024/V44/I08/2395

[1] Wagner T, Andreae M O, Beirle S, et al. Atmospheric Measurement Techniques, 2013, 6(1): 131.
[2] Mieruch S, Schröder M, Nol S, et al. Journal of Geophysical Research: Atmospheres, 2014, 119(22): 12489.
[3] ZHANG Gong, XU Jian-min, HUANG Yi-fen, et al(张弓, 许健民, 黄意玢). Journal of Applied Meteorological Science(应用气象学报), 2003, 14(4): 385.
[4] LIU Jin, SI Fu-qi, ZHOU Hai-jin, et al(刘进, 司福祺, 周海金, 等). Acta Optica Sinica(光学学报), 2013, 33(8): 16.
[5] Borger C, Beirle S, Dörner S, et al. Atmospheric Measurement Techniques, 2020, 13(5): 2751.
[6] Chan K L, Valks P, Slijkhuis S, et al. Atmospheric Measurement Techniques, 2020, 13(8): 4169.
[7] Ehret G, Kiemle C, Renger W, et al. Applied Optics, 1993, 32(24): 4534.
[8] REN Hong-mei, LI Ang, HU Zhao-kun, et al(任红梅, 李昂, 胡肇焜, 等). Acta Physica Sinica(物理学报), 2020, 69(20): 255.
[9] ZHANG Qi-jin, GUO Ying-ying, LI Su-wen, et al(张琦锦，郭映映，李素文, 等). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2023, 43(3): 984.
[10] Platt U, Stutz J. Differential Optical Absorption Spectroscopy, Physics of Earth and Space Environments. Springer, Berlin, Heidelberg, 2008.
[11] Zhang Q J, Mou F S, Li S W, et al. Spectrochimica Acta Part A, 2023, 286：121959.
[12] GUO Ying-ying, QI He-xiang, LI Su-wen, et al(郭映映, 齐贺香, 李素文, 等). Journal of Atmospheric and Environmental Optics(大气与环境光学学报), 2021, 16(2): 107.
[13] Zhang Q J, Mou F S, Luo J, et al. Atmospheric Pollution Research, 2023, 14：101732.
[14] Lampel J, Pöhler D, Tschritter J, et al. Atmospheric Measurement Techniques, 2015, 8(10): 4329.
[15] Rothman L S, Gordon I E, Barber R J, et al. Journal of Quantitative Spectroscopy and Radiative Transfer, 2010, 111(15): 2139.
[16] Wagner T, Beirle S, Deutschmann T. Atmospheric Measurement Techniques, 2009, 2(1): 113.
[17] Vandaele A C, Hermans C, Simon P C , et al. Journal of Quantitative Spectroscopy and Radiative Transfer, 1998, 59(3-5): 171.
[18] Serdyuchenko A, Gorshelev V, Weber M, et al. Atmospheric Measurement Techniques, 2014, 7(2): 625.
[19] Thalman R, Volkamer R. Physical Chemistry Chemical Physics, 2013, 15(37): 15371.