19 research outputs found

    European contribution to the study of ROS: A summary of the findings and prospects for the future from the COST action BM1203 (EU-ROS).

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    The European Cooperation in Science and Technology (COST) provides an ideal framework to establish multi-disciplinary research networks. COST Action BM1203 (EU-ROS) represents a consortium of researchers from different disciplines who are dedicated to providing new insights and tools for better understanding redox biology and medicine and, in the long run, to finding new therapeutic strategies to target dysregulated redox processes in various diseases. This report highlights the major achievements of EU-ROS as well as research updates and new perspectives arising from its members. The EU-ROS consortium comprised more than 140 active members who worked together for four years on the topics briefly described below. The formation of reactive oxygen and nitrogen species (RONS) is an established hallmark of our aerobic environment and metabolism but RONS also act as messengers via redox regulation of essential cellular processes. The fact that many diseases have been found to be associated with oxidative stress established the theory of oxidative stress as a trigger of diseases that can be corrected by antioxidant therapy. However, while experimental studies support this thesis, clinical studies still generate controversial results, due to complex pathophysiology of oxidative stress in humans. For future improvement of antioxidant therapy and better understanding of redox-associated disease progression detailed knowledge on the sources and targets of RONS formation and discrimination of their detrimental or beneficial roles is required. In order to advance this important area of biology and medicine, highly synergistic approaches combining a variety of diverse and contrasting disciplines are needed.The EU-ROS consortium (COST Action BM1203) was supported by the European Cooperation in Science and Technology (COST). The present overview represents the final Action dissemination summarizing the major achievements of COST Action BM1203 (EU-ROS) as well as research news and personal views of its members. Some authors were also supported by COST Actions BM1005 (ENOG) and BM1307 (PROTEOSTASIS), as well as funding from the European Commission FP7 and H2020 programmes, and several national funding agencies

    Confidence and Error Analyses of the Radiosonde and Ka-Wavelength Cloud Radar for Detecting the Cloud Vertical Structure

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    A macro-vertical structure is closely related to weather evolution and the energy budget balance of the atmospheric system of the Earth. In this study, radiosonde data were used to identify a cloud vertical structure (CVS) using the adjusted relative humidity threshold method. To evaluate the reliability and stability of this method, the results obtained based on the spatiotemporal matching criteria established in this study were compared with Ka-band millimetre-wave cloud radar (MMCR) observation data. This comparison showed that both devices exhibit high consistency in low-level cloud detection. With the increase in the cloud height, the frequency of the cloud appearance detection by the radiosonde became higher than that by the MMCR. In spring, the results of the CVS detection by the two devices were in good agreement. Specifically, the determination coefficients of the modified degrees of freedom (adjusted R-square) of the cloud base height (CBH) and cloud top height (CTH) detected by the two devices were 0.934 and 0.879, respectively. The horizontal drift of the radiosonde was the smallest in summer, and the adj. R-square values of the CBH and CTH were 0.814 and 0.852, respectively. The CVS observation results by the radiosonde and the MMCR were significantly different in autumn (the adj. R-Square values of the CBH and CTH were 0.715 and 0.629, respectively). In winter, the adj. R-Square values of the CBH and CTH observed by the radiosonde and the MMCR were 0.958 and 0.710, respectively. The statistics and analysis of the results of the distribution characteristics of the CVSs using radiosonde data from 2019 to 2021 from Xi’an showed that the average CTH and CBH were at 7–10 km and 3–5 km, respectively. The frequencies of the cloud absence, rainfall, and two- and three-layer clouds were the highest in the winter (34.36%), autumn (12.99%), and summer, respectively

    Aerosol Microphysical Particle Parameter Inversion and Error Analysis Based on Remote Sensing Data

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    The use of Raman and high-spectral lidars enables measurements of a stratospheric aerosol extinction profile independent of backscatter, and a multi-wavelength (MW) lidar can obtain additional information that can aid in retrieving the microphysical characteristics of the sampled aerosol. The inversion method for retrieving aerosol particle size distributions and microphysical particle parameters from MW lidar data was studied. An inversion algorithm for retrieving aerosol particle size distributions based on the regularization method was established. Based on the inversion of regularization, the inversion method was optimized by choosing the base function closest to the aerosol distribution. The logarithmic normal distribution function was selected over the triangle function as the base function for the inversion. The averaging procedure was carried out for three main types of aerosol. The 1% averaging result near the minimum of the discrepancy gave the best estimate of the particle parameters. The accuracy and stabilization of the optimized algorithm for microphysical parameters were tested by scores of aerosol size distributions. The systematic effects and random errors impacting the inversion were also considered, and the algorithm was tested by the data, showing 10% systematic error and 15% random error. At the same time, the reliability of the proposed algorithm was also verified by using the aerosol particle size distribution data of the aircraft. The inversion results showed that the algorithm was reliable in retrieving the aerosol particle size distributions at vertical heights using lidar data

    Polarization Measurements and Evaluation Based on Multidimensional Polarization Indices Applied in Analyzing Atmospheric Particulates

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    Online identification and characterization of suspended aerosols can provide a scientific basis for understanding aerosol transformations, quantitatively evaluating the impacts on air quality, public health, and the source apportionment of different atmospheric particulate matters. In this study, we confirm the validity of our developed high-throughput multi-angle polarized scattering vector detection of aerosols and multidimensional polarization scattering index systems. By observation of the mean values, variance, and Wilk’s Lambda of multidimensional polarization indices for different aerosol types, the polarization index shows unique characterization abilities for aerosol properties, and the optimal combination of polarization indices can always be found for a specific aerosol category with a high resolution and discrimination. Clearly, the multidimensional polarization indices of individual aerosols are more suitable for online and real-time aerosol identification and even help to explain the in situ microphysical characteristics of aerosols or evaluate the dynamic evolution of aerosols

    Raman Lidar for Synchronous Water Vapor, Liquid Water and Ice Water Profilings

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    Water is the only atmospheric parameter with three-phase state. An ultraviolet Raman lidar was developed for synchronous measurements for water vapor, liquid water and ice water in Xi’an University of Technology, Xi’an, China (34.233°N, 108.911°E). An accurate retrieval method on the basis of interference degree is proposed for synchronous three-phase water mixing ratio profiles. Preliminary measurements are carried out in the Laser Radar Center of Remote Sensing of Atmosphere (LRCRSA). Several representative examples are obtained and validated the performance of Raman system. Combined with atmospheric temperature profiles, the synchronous water vapor, liquid water and ice water profiling are retrieved and revealed the variation characteristics in three-phase water. The effective detection can reach up to a height of 5 km under cloudy weather, and synchronized growth in water vapor and liquid water content was obtained in cloud layers. Continuous observations are also made under haze weather condition, and the temporal and spatial evolution trend of three-phase water in clouds at 2 km altitude are successfully realized
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