Wind fields provide direct power for exchanging energy and matter in the atmosphere. All-fiber coherent Doppler lidar is a powerful tool for detecting boundary-layer wind fields. According to the characteristics of the lidar echo signal, an adaptive noise-reduction peak retrieval (ANRPR) algorithm is proposed in this study. Firstly, the power spectrum data are divided into several continuous range gates according to the time series. Then, the adaptive iterative reweighted penalized least-squares (airPLS) method is used to reduce the background noise. Secondly, the continuity between spectra is enhanced by 2D Gaussian low-pass filtering. Finally, an adaptive peak-retrieval algorithm is employed to extract the Doppler shift, facilitating the synthesis of a spatial atmospheric 3D wind field through the vector synthesis method. When comparing data from different heights of the meteorological gradient tower, both the horizontal wind-speed correlation and the horizontal wind-direction correlation exceed 0.90. Experimental results show that the proposed algorithm has better robustness and a longer detection distance than the traditional algorithm.

This paper examines the effects of temperature and humidity on the absorption spectrum and concentration of nitrous oxide (${\mathrm{N}}_2\mathrm{O}$) using a compact, portable open optical-path gas detection sensor system. We obtained the absorption coefficient and widened the linear function of the ${\mathrm{N}}_2\mathrm{O}$ absorption spectrum related to temperature by theoretical analysis and the high-resolution transmission molecular absorption database (HITRAN). Afterward, we conducted real-time monitoring of ${\mathrm{N}}_2\mathrm{O}$ in both campus and laboratory environments using lasers for a duration of 32 h and 6 h, respectively, and the results were compared and analyzed with the theoretical derivation. The results show that the concentration of ${\mathrm{N}}_2\mathrm{O}$ increased with increasing environmental temperature but decreased with increasing humidity. Furthermore, the variations in temperature and humidity significantly affected the peak values of the second-harmonic (2f) and first-harmonic (1f) signals. Finally, the temperature ${\mathrm{N}}_2\mathrm{O}$ concentration and humidity ${\mathrm{N}}_2\mathrm{O}$ curves were calibrated separately, and temperature changes were positively correlated with the ${\mathrm{N}}_2\mathrm{O}$ concentration, while humidity changes were negatively correlated with the ${\mathrm{N}}_2\mathrm{O}$ concentration. The experimental results indicate that the concentration of ${\mathrm{N}}_2\mathrm{O}$ and its absorption spectra are influenced by humidity and temperature, which has a significant reference value in the absorption and measurement of ${\mathrm{N}}_2\mathrm{O}$ in practical applications.

Wind parameters play a vital role in studying atmospheric dynamics and climate change. In this study, a vehicle-mounted coherent wind measurement Lidar (CWML) with a wavelength of 1.55 µm is demonstrated based on a four-beam vertical azimuth display (VAD) scanning mode, and a method to estimate wind vector from power spectrum is proposed. The feasibility of the application of wind profile Lidar in vehicles is verified by calibration tests, comparison experiments, and continuous observation experiments, successively. The effective detection height of Lidar can reach 3 km. In contrasting experiments, the correlation coefficients of the magnitude and direction of horizontal wind speed measured by vehicle-mounted Lidar and fixed Lidar are 0.94 and 0.91, respectively. The experimental results reveal that the accuracies of wind speed and direction measurements with the vehicle-mounted CWML are better than 0.58 m/s and 4.20°, respectively. Furthermore, to understand the role of the wind field in the process of energy and material transport further, a proton-transfer reaction time-of-flight mass spectrometer (PTR-TOF-MS) is utilized to measure the concentration of volatile organic compounds (VOCs). Relevant experimental results indicate that the local meteorological conditions, including wind speed and humidity, influence the VOC concentrations.