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Raman Lidar for the Measurement of Temperature, Water Vapor, and Aerosol in Beijing in the Winter of 2014

  • Tan, Min (University of Science and Technology of China) ;
  • Shang, Zhen (University of Science and Technology of China) ;
  • Xie, Chenbo (Key Laboratory of Atmospheric Optics, Anhui Institute of Optics and Fine Mechanics, Chinese Academy of Sciences) ;
  • Ma, Hui (University of Science and Technology of China) ;
  • Deng, Qian (University of Science and Technology of China) ;
  • Tian, Xiaomin (University of Science and Technology of China) ;
  • Zhuang, Peng (University of Science and Technology of China) ;
  • Zhang, Zhanye (University of Science and Technology of China) ;
  • Wang, Yingjian (Key Laboratory of Atmospheric Optics, Anhui Institute of Optics and Fine Mechanics, Chinese Academy of Sciences)
  • Received : 2017.09.26
  • Accepted : 2018.01.23
  • Published : 2018.02.25

Abstract

To measure atmospheric temperature, water vapor, and aerosol simultaneously, an efficient multi-function Raman lidar using an ultraviolet-wavelength laser has been developed. A high-performance spectroscopic box that utilizes multicavity interference filters, mounted sequentially at small angles of incidence, is used to separate the lidar return signals at different wavelengths, and to extract the signals with high efficiency. The external experiments are carried out for simultaneous detection of atmospheric temperature, water vapor, and aerosol extinction coefficient in Beijing, under clear and hazy weather conditions. The vertical profiles of temperature, water vapor, and aerosol extinction coefficient are analyzed. The results show that for an integration time of 5 min and laser energy of 200 mJ, the mean deviation between measurements obtained by lidar and radiosonde is small, and the overall trend is similar. The statistical temperature error for nighttime is below 1 K up to a height of 6.2 km under clear weather conditions, and up to a height of 2.5 km under slightly hazy weather conditions, with 5 min of observation time. An effective range for simultaneous detection of temperature and water vapor of up to 10 km is achieved. The temperature-inversion layer is found in the low troposphere. Continuous observations verify the reliability of Raman lidar to achieve real-time measurement of atmospheric parameters in the troposphere.

Keywords

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FIG. 1. Schematic diagram and photograph of the developed TWAR lidar.

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FIG. 2. Lidar and radiosonde temperature profiles measured at Yanqi Lake (40.41°N, 116.68°E) on (a) 8 November 2014 and (b) 13 November 2014. Error profiles show the statistical temperature uncertainty.

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FIG. 3. Consecutive temperature profiles measured with TWAR lidar.

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FIG. 4. (a) Profiles of water-vapor mixing ratio, measured with lidar (circles) and radiosondes launched at night (black curves) on 28 July 2014. 900 s of lidar data were integrated, beginning at the radiosonde’s launch. Lidar signals were moothed with a gliding average of 150 m. (b) Difference between lidar and local radiosonde measurements. (c) Relative error profile.

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FIG. 5. Profiles of water-vapor mixing ratio, measured with lidar (black urves) and radiosonde (black dashs) for 9 and 10 November 2014.

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FIG. 6. Continuous observation of water-vapor mixing ratio measured by lidar, between 11 November and 13 November.

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FIG. 7. Profiles of range-corrected signal, aerosol extinction, water vapor mixing ratio and temperature taken at 19:30 and 20:00 on 28 July 2014.

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FIG. 8. Profiles for aerosol backscattering coefficient and total aerosol relative error taken at 02:00 on 11 November 2014.

TABLE 1. Technical data

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References

  1. A. Behrendt, T. Nakamura, M. Onishi, R. Baumgart, and T. Tsuda, "Combined Raman lidar for the measurement of atmospheric temperature, water vapor, particle extinction coefficient, and particle backscatter coefficient," Appl. Opt. 41, 7657-7666 (2002). https://doi.org/10.1364/AO.41.007657
  2. H. Bardouki, H. Liakakou, C. Economou, J. Sciare, J. Smolík, V. Zdimal, K. Eleftheriadis, M. Lazaridis, C. Dye, and N. Mihalopoulos, "Chemical composition of size-resolved atmospheric aerosols in the eastern Mediterranean during summer and winter," Atmos. Environ. 37, 195-208 (2003). https://doi.org/10.1016/S1352-2310(02)00859-2
  3. V. Ramanathan and Y. Feng, "Air pollution, greenhouse gases and climate change: Global and regional perspectives," Atmos. Environ. 43, 37-50 (2009). https://doi.org/10.1016/j.atmosenv.2008.09.063
  4. R. G. Harrison, "Aerosol-induced correlation between visibility and atmospheric electricity," J. Aerosol Sci. 52, 121-126 (2012). https://doi.org/10.1016/j.jaerosci.2012.04.011
  5. D. Y. H. Pui, S. Chen, and Z. Zuo, "$PM_{2.5}$ in China: Measurements, sources, visibility and health effects, and mitigation," Particuology 13, 1-26 (2014). https://doi.org/10.1016/j.partic.2013.11.001
  6. S. Xiao, Q. Y. Wang, J. J. Cao, R. Huang, W. D. Chen, Y. M. Han, H. M. Xu, S. X. Liu, Y. Q. Zhou, P. Wang, J. Q. Zhang, and C. L. Zhan, "Long-term trends in visibility and impacts of aerosol composition on visibility impairment in Baoji, China," Atmos. Res. 149, 88-95 (2014). https://doi.org/10.1016/j.atmosres.2014.06.006
  7. O. G, "Pulmonary effects of inhaled ultrafine particles," Int. Arch. Occup. Environ. Health 74, 1-8 (2001).
  8. Z. Chen, J. Zhang, T. Zhang, W. Liu, and J. Liu, "Haze observations by simultaneous lidar and WPS in Beijing before and during APEC, 2014," Sci. China Chem. 58, 1385-1392 (2015). https://doi.org/10.1007/s11426-015-5467-x
  9. W. Zifa, L. I. Jie, W. Zhe, Y. Wenyi, T. Xiao, G. E. Baozhu, Y. A. N. Pinzhong, Z. H. U. Lili, C. Xueshun, C. Huansheng, W. Wei, L. I. Jianjun, L. I. U. Bing, W. Xiaoyan, W. Wei, Z. Yilin, L. U. Ning, and S. U. Debin, "Modeling study of regional severe hazes over mid-eastern China in January 2013 and its implications on pollution prevention and control," Sci. China Earth Sci. 57, 3-13 (2014). https://doi.org/10.1007/s11430-013-4793-0
  10. M. Radlach, A. Behrendt, and V. Wulfmeyer, "Scanning rotational Raman lidar at 355 nm for the measurement of tropospheric temperature fields Scanning rotational Raman lidar at 355 nm for the measurement of tropospheric temperature fields," Atmos. Chem. Phys. 8, 159-169 (2008). https://doi.org/10.5194/acp-8-159-2008
  11. E. Hammann, A. Behrendt, F. Le Mounier, and V. Wulfmeyer, "Temperature profiling of the atmospheric boundary layer with rotational Raman lidar during the HD (CP) 2," Atmos. Chem. Phys. 15, 2867-2881 (2015). https://doi.org/10.5194/acp-15-2867-2015
  12. L. Yunlei, L. Hua, C. Yubao, and G. Yuchun, "Aerosol detection experiment with 532nm lidar based on Fernald method," Electron. Des. Engimeering 22, 88-90 (2014).
  13. W. Zhanshan, L. Yunting, L. Qian, W. Lihua, and L. Baoxian, "Analysis on a Dust Pollution Event in Beijing in May, 2017 Based on the Observation of an Atmospheric Supersite," Environ. Monit. China 33, 28-34 (2017).
  14. W. Wei, Y. Nan, S. Yaolong, Z. Zhen, C. Linjun, C. Wenxuan, C. Baobin, F. Qiang, and L. Jianjun, "Application of Mobile Lidar in Analying Regional Pollutants Transportation During a Haze Episode over Beijing-Tianjin-Hebei Aera," Environ. Monit. China 33, 7-13 (2017).
  15. D. Chuanyao, Y. Liping, W. Mian, M. Jingjin, L. Dong, Z. Chunbo, M. Lei, and W. Lu, "Comprehensive detection of fog and haze process," Meteorol. Mon. 41, 1525-1530 (2015).
  16. Y. Chen, J.-L. An, J. Lin, Y.-L. Sun, X.-Q. Wang, Z.-F. Wang, and J. Duan, "Observation of nocturnal low-level wind shear and particulate matter in urban Beijing using a Doppler wind lidar," Atmos. Ocean. Sci. Lett. 10, 411-417 (2017). https://doi.org/10.1080/16742834.2017.1368349
  17. Z. Tiemin, W. Jihong, W. Linmao, C. Xueming, W. Jianqing, Z. Xu, and P. Hongyan, "Observations of sodium layer over Beijing and Haikou in july 2012," Chin. J. Sp. Sci 37, 424-431 (2017).
  18. S. Zhaobin, L. Xiaonong, W. Zhanshan, L. Ziming, Z. Xiujuan, and H. Cong, "Scavenging effect of rime and east wind on $PM_{2.5}$ under air heavy pollution in Beijing," Environ. Sci. 37, 4-10 (2016).
  19. D. N. Whiteman, S. H. Melfi, and R. A. Ferrare, "Raman lidar system for the measurement of water vapor and aerosols in the Earth's atmosphere," Appl. Opt. 31, 3068-3082 (1992). https://doi.org/10.1364/AO.31.003068
  20. C. Weitkamp, Lidar: Range-Resolved Optical Remote Sensing of the Atmosphere (Springer Science & Business, 2006), Vol. 102.
  21. A. Behrendt and T. Nakamura, "Calculation of the calibration constant of polarization lidar and its dependency on atmospheric temperature," Opt. Express 6, 6587-6595 (2002).
  22. C. T. W. D. L. Bo, C. K. W. Z. G. Yuan, and L. Z. Jun, "A new method for determining aerosol baekscatter coefficient boundary value in the lower troposphere," Acta Opt. Sin. 6, 3 (2010).
  23. Z. Tao, D. Wu, D. Liu, S. Hu, M. Nie, and B. Shi, "Estimation of aerosol backscatter coefficient error in lidar data processing," Zhongguo Jiguang (Chinese J. Lasers) 38, 1214001-1214005 (2011).