To evaluate the potential of Raman lidar observations for measuring precipitable water vapor (PWV), PWV variations and distribution characteristics were investigated in Xi'an (34.233 • N, 108.911 • E), and its comparisons with meteorological parameters were also analysed. Comparisons of lidar PWV with radiosonde PWV verified the ability and accuracy of using Raman lidars for PWV measurements. The diurnal and monthly variation trends in PWV in different layers are first discussed via the statistical analysis of lidar data from November 2013 to July 2016; different proportions of PWV were found in different layers, and the PWV in each layer presented a slight diurnal change trend and consistent seasonal variation, which was relatively rich in summer, less so in spring and autumn, and relatively deficient in winter. Furthermore, correlation analyses between lidar PWV and meteorological parameters are explored. Water vapor pressure and surface temperature revealed the same inter-seasonal oscillation of PWV, with a correlation coefficient of~0.90. However, incomplete synchronization was found between PWV and relative humidity and precipitation parameters. Higher humidity appeared in the late summer and the beginning of autumn of each year, which was also the case for precipitation and precipitation efficiency. In addition, atmospheric water vapor density profiles and the obtained PWV by Raman lidar are discussed employing a rainfall case, and a comprehensive analysis with meteorological parameters is undertaken. The intensifying characteristics of vertical change in water vapor and the accumulation of PWV in the lower troposphere can be captured by lidar before the onset of rainfall. In contrast to the obvious diurnal change trend, such meteorological parameters as relative humidity, water vapor pressure, and dew-point temperature difference are accompanied with stable trends with a change rate of close to 0 in the rainfall processes; they also show high correlated variations with lidar PWV. Thus, with the advantage of lidar detection, investigation of water vapor profiles and PWV by Raman lidar, and the comprehensive correlation analyses with synchronic meteorological parameters can prove to be good indications of rainfall.
All-day atmospheric water vapor content measurements determined by Raman lidar and a sunphotometer were combined to investigate the all-day variation characteristics in the water vapor distribution in Xi'an, China (34.233 • N, 108.911 • E). To enhance the daytime lidar performance, the wavelet threshold de-noising method is used to filter out the strong solar background light, and effective denoised results are demonstrated with the following optimization: wavelet sym6, the improved threshold function, and the improved threshold selection. The denoised system signal-to-noise ratio (SNR) for the water vapor daytime measurement is validated, with an enhancement of~3.4 times up to a height of 3 km compared to that of the original signal. The time series of the atmospheric water vapor mixing ratio profiles and the obtained precipitable water vapor (PWV) measured by Raman lidar are used to reveal the temporal and spatial variations in water vapor, and the comparisons with the total column water vapor content (TCWV) measured by a sunphotometer validate the daytime variation trend of the water vapor. All-day continuous observations clearly present a consistent variation trend in the water vapor between the sunphotometer and Raman lidar measurements. The correlation analysis between TCWV and PWV at the layers below 850 hPa and below 700 hPa yields a good positive correlation coefficient (>0.75), indicating that PWV determination in the bottom layer by Raman lidar can directly reflect the variations in the total water vapor content. Moreover, different diurnal variation trends in water vapor are also observed, that is, a downward trend from the afternoon to the night, or a tendency of being high in the morning and afternoon and low at noon, demonstrating the high temporal-spatial variation characteristics of water vapor and close correlation with weather changes. The results reflected and validated that the diurnal variation in water vapor is complicated and can be an indicator of the weather to a certain extent.
Current drugs do not provide an absolute cure or modify the course of asthma. Hyssopus cuspidatus Boriss extract (SXCF) has been used as Uyghur medicine for several years to treat bronchial asthma. However, very limited research has been conducted on the therapeutic mechanisms of SXCF. Disruptions in the metabolic network of lipid mediators (LMs) are closely linked to the development of asthma. Here, we explored the therapeutic mechanism of SXCF in asthma based on the metabolic network of LMs, aiming to contribute to the understanding of SXCF in asthma treatment at the molecular level. The UHPLC-MRM strategy was used for the quantitative detection of LMs in the lung tissue and in the peripheral circulatory system (serum). ELISA was used to detect IgE in serum and cytokines in BALF. The lung tissue sections were stained with H&E to observe the infiltration of inflammatory cells, and behavioural changes in mice were observed and recorded throughout the animal experiment. In contrast to the asthma group, the opposite result was observed in the SXCF groups, where the perturbed LMs metabolic network was partly restored in a dose-dependent manner with a significant elevation of anti-inflammatory metabolites, while pro-inflammatory lipids were decreased. As significant downregulation of IgE and pro-inflammatory cytokines was observed, IgE and cytokines analysis also supported the anti-inflammatory effects of SXCF. It was also noticed that SXCF treatment reduced the number of coughs and decreased the inflammatory cell infiltration around the bronchus in mice. These results suggested that SXCF has a significant ameliorative effect on ovalbumin (OVA)-induced asthma. The modulation of LMs is a possible underlying mechanism of the SXCF effects.
Water is the only atmospheric parameter with three-phase states. The study on distribution and variation in three-phase water is of great scientific significance for understanding cloud microphysics, cloud precipitation physics, and water circulation, especially in the fields of artificial weather process. In the Raman lidar detection technology of three-phase water, it is necessary to solve the problem of high-spectral spectroscopic technique to ensure fine extraction of the echo signal and the detection with high signal-to-noise ratio (SNR). Considering the Raman spectrum characteristics of three-phase water, the influences of filter parameters in the Raman channels on the overlapping characteristics are theoretical simulated and discussed in detail, and the SNR is investigated as well. Regarding the fact that optimal solution can be obtained for neither overlapping nor SNR at the same time, an evaluation function method based on the multi-objective programming problem is proposed to analyze the optimal filter parameters. The results show that the minimum overlapping value and the higher system SNR can be obtained when the central wavelength and bandwidth of the filters are determined to be 397.9 nm and 3.1 nm, 403 nm and 5 nm, 407.6 nm and 0.6 nm in solid water, liquid water and water vapor channel, respectively, and thus the optimal design can be realized for synchronous detection Raman spectroscopic system for three-phase water. Further simulation results show that effective detection can reach above 3.6 km in the daytime and over 4 km on sunny days under a system factor of 1800 J·mm·min for three-phase water Raman measurement in the daytime. Furthermore, the obtained overlapping values are applied to accurate retrieval theory for three-phase water profiles. The simulated profiles of atmospheric water vapor, liquid water and ice water indicate that the water vapor, liquid water and solid water content can be increased synchronously in the cloud layer, and their content, distribution characteristics and the corresponding error are also discussed. The above results validate the feasibility of highspectral spectroscopic technique for detecting the synchronous atmospheric three-phase water, and will provide technical and theoretical support for synchronous retrieval of three-phase water by Raman lidar.
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