*通讯联系人 e-mail: dengxinhua@xaut.edu.cn

Research of Solar-Blind Ultraviolet Raman Lidar for Water Vapor Measurement Technology
SHI Dong-chen, HUA Deng-xin*, LEI Ning, GAO Fei, WANG Li, YAN Qing, ZHOU Yi
School of Mechanical and Precision Instrument Engineering, Xi’an University of Technology, Xi’an 710048, China
Abstract

Raman Lidar can detect water vapor mixing ratio by atmospheric water vapor vibration Raman scattering echo signal associated with the water vapor concentration. However, vibration Raman scattering spectra would drown in the sun background light due to the weak Raman scattering echo signal, therefore the measured time is usually at night. All radiation below 300nm known at solar-blind ultraviolet band is absorbed by the ozone layer in the stratosphere. The shorter the wavelength is, the stronger the energy is. To realize the detection of atmospheric water vapor at daytime and night time, a Raman Lidar is developed at a solar-blind ultraviolet band. The system consists of the laser, telescope, photoelectric acquisition and signal processing part. Briefly, the forth harmonic output (ultraviolet 266 nm) of an externally triggered, 10 Hz repetition rate, Nd∶YAG laser is employed as the transmitter. The bore sight assembly uses a turning prism controlled by a New Focus actuator. With 400 mm diameter, 0.5 m rad field of view, a telescope forms the main part of the receiving optics. To obtain signals with fine separation and high efficient extraction, three dichroic mirrors separate out the detection channels by reflecting light with longer wavelengths while transmitting light with shorter wavelengths, a combination of narrow bandwidth (FWHM=1 nm) interference filters is employed to filter the backscattered signal. The rejection rate of the Mie-Rayleigh scattering signals reaches to 10-7. Before reaching the photomultiplier tube (PMT) in each channel, a plano-convex lens is employed to focus the backscattered signal on the front face of the PMT. The backscattered radiation is collected and analyzed at four wavelengths of interest, 266.0 nm for the elastic scattering, 277.6, 283.6 and 294.5 nm for the Raman scattering of O2, N2 and H2O molecules, respectively. The four PMTs output signals are then input into a multi-channel digitizer to record the backscattered signal, which is used to retrieve the water vapor profile. We use the standard atmospheric scattering models and aerosol extinction coefficients, set system of the sampling interval to 80 ns, cumulative average pulse number to 36 000, the signal-to-noise ratios of atmospheric water vapor measurement are simulated. The simulation results show that there exists influence on ozone absorbing mainly at the Solar-blind Ultraviolet Raman Lidar detection range. The signal to noise ratio simulation results show that the measurement height of the designed Solar-blind Ultraviolet Raman Lidar system can be up to 3.5 km during the daytime measurement. The optimal parameters of Lidar system are obtained based on the detailed analysis and the discussion of the SNR of echo signals. It is concluded that this new solar-blind ultraviolet band Raman Lidar system has the advantage of measuring the water vapor in the daytime without the influence of solar background radiation.

Keyword: Raman lidar; Solar-blind; Atmosphere water vapor; Ozone absorption

1 日盲紫外域拉曼激光雷达探测原理

$P(z, λk)=P0(λ0)cτ2Aη(λk)Ok(z)z2×βk(z, λk)Tk(z, λk)+Eb(λ)βk(z, λk)=Nk(z)·dσ266k(π)dΩ, k=N2, O2, H2O(1)$

$Tk(z, λk)=Tk1(z, λk)TkO3(z, λk)Tk1(z, λk)=exp[-∫0z[α(z, λ0)+α(z, λk)]dz]TkO3(z, λk)=exp[-∫0z[NO3(z)σ(z, λ0)+NO3(z)σ(z, λk)]dz](2)$

$Tk1$(z)为不考虑臭氧对日盲紫外域波段吸收时的大气透过率衰减项, $TkO3$(z)为臭氧对日盲紫外域波段的大气透过率吸收衰减项, α (z, λ )为消光系数, $NO3$(z)为大气中臭氧的浓度, σ (z, λ )为臭氧对日盲紫外域波长的吸收截面[10]。 氮气通道大气透过率曲线如图1所示, 如图可知, 随探测高度的增加, 臭氧吸收项加速了未考虑臭氧吸收时大气透过率的衰减, 该衰减加速程度如图1中虚线部分所示, 相比不考虑臭氧项时的大气透过率, 臭氧的吸收引起的大气透过率的衰减在3 500 m处可达到百分之90, 相应的拉曼激光雷达回波信号强度随高度增加被加速削弱。 因此该日盲紫外域拉曼激光雷达系统进行大气水汽反演时需加入臭氧吸收项。

 Figure Option 图1 氮气通道大气透过率曲线Fig.1 Curves of the N2 channel atmospheric transmissivity

$WH2O≈0.207P(z, λH2O)P(z, λN2)Δτ(λN2, λH2O, z)ΔτO3(λN2, λH2O, z)Δτ(λN2, λH2O, z)=exp[∫0z[α(z, λH2O)-α(z, λN2)]]dzΔτO3(λN2, λH2O, z)=exp[∫0zNO3[σ(z, λH2O)-σ(z, λN2)]]dz(3)$

$NO3(z)=1σ(λN2, z)-σ(λO2, z)dlnPO2(z)PN2(z)dz-α(λN2, z)-α(λO2, z)σ(λN2, z)-σ(λO2, z)(4)$

2 日盲紫外域水汽探测拉曼激光雷达系统结构设计

 Figure Option 图2 大气水汽探测拉曼激光雷达系统原理图Fig.2 Schematic of the Water Detection Raman lidar system

 Figure Option 图3 二向色镜和干涉滤光片的透射特性曲线Fig.3 Transmittance curves of DMs and IFs

3 日盲紫外域拉曼激光雷达水汽探测系统信噪比仿真与分析
3.1 日盲紫外域拉曼激光雷达水汽探测系统信噪比仿真

$SNRi(T, z)=ni(z)Nni(z)+ne(z)+2(ns+nI)(5)$

 Figure Option 图4 (a)白天各探测通道拉曼回波信号强度分布; (b)白天拉曼探测系统仿真信噪比Fig.4 (a) Intensity distributions of Raman scattering echo signals in the daytime; (b) Simulation Simulated signal to noise ratio for Water Vapor Measurement in the daytime

3.2 日盲紫外域拉曼激光雷达水汽探测系统信噪比分析

3.2.1 臭氧等气体对系统信噪比的影响

$Tkh(z, λk)=exp[-∫0z[Nh(z)σ(λ0, z)+Nh(z)σ(λkh, z)]dz] h=O3, SO2, NO2(6)$

$Tk(z, λk)=Tk1(z, λk)TkO3(z, λk)TkSO2(z, λk)TkNO2(z, λk)(7)$

 Figure Option 图5 (a)美国标准大气下的臭氧浓度; (b)SNRMie-Raylie含臭氧与不含臭氧的仿真结果对比Fig.5 (a) US Stand Model Concentration of ozone molecule; (b) The comparison of simulation results with and without ozone

3.2.2 太阳背景噪声对系统信噪比的影响

$Eb(λ)=KSb(λ)ArΔλπ4θ2(8)$

 Figure Option 图6 白天测量时太阳背景噪声对水汽通道信噪比的影响Fig.6 The impact of the sun background noise on the SNR of the water vapor channel in the daylight measurement

3.2.3 系统参数选取的优化

$λ(θ)=λk1-sin2(θ)n2(9)$

4 结 论

The authors have declared that no competing interests exist.

 [1] Sica R, Haefle A. Applied Optics, 2016, 55: 763. [本文引用:1] [2] CHEN Sheng-zhe, ZHANG Yin-chao, CHEN Si-ying, et al(陈胜哲, 张寅超, 陈思颖, 等). Transactions of Beijing Institute of Technology(北京理工大学学报), 2014, 34(6): 617. [本文引用:1] [3] WANG Hong-wei, HUA Deng-xin, WANG Yu-feng, et al(王红伟, 华灯鑫, 王玉峰, 等). Acta Physica Sinica(物理学报), 2013, 62(12): 120701. [本文引用:1] [4] Hua Dengxin, Takao Kobayashi. Japanese Journal of Applied Physics, 2005, 44: 1287. [本文引用:1] [5] WANG Min, HU Shun-xing, FANG Xin(王敏, 胡顺星, 方欣). Infrared and Laser Engineering(红外与激光工程), 2008, 37: 156. [本文引用:1] [6] Leblanc T, McDermid I S, Walsh T D. Atmos. Meas. Tech. , 2012, 5: 30. [本文引用:1] [7] Uesugi T, Tsuda T, Yabuki M, et al. Agu. Fall. Meeting, 2014, 23: 2. [本文引用:1] [8] LIU Yu-li, XIE Chen-bo, SHANG Zhen, et al. Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2016, 36(6): 1978. [本文引用:1] [9] Mao Jiand ong, Hua Dengxin, Wang Yufeng, et al. Optics Communications, 2009, 282: 3113. [本文引用:1] [10] WANG Shao-lin(汪少林). Ph. D. Dissertation (Anhui: University of Chinese Academy of Sciences) (安徽: 中国科学院研究生院), 2010. [本文引用:1] [11] HU Shun-xing, ZHAO Pei-tao, WANG Shao-lin, et al(胡顺星, 赵培涛, 汪少林, 等). Journal of Atmospheric and Environmental Optics(大气与环境光学学报), 2009, 4(6): 401. [本文引用:2] [12] ASTMG173—03 2003, 15297. [本文引用:2] [13] SHENG Pei-xuan, MAO Jie-tai(盛裴轩, 毛节泰). Atmospheric Physics. Beijing: Peking University Press(北京: 北京大学出版社), 2003. 7. [本文引用:1]