Recently, atmospheric ozone pollution has demonstrated an aggravating tendency in China. To date, most research about atmospheric ozone has been confined near the surface, and an understanding of the vertical ozone structure is limited. During the 2016 G20 conference, strict emission control measures were implemented in Hangzhou, a megacity in the Yangtze River Delta, and its surrounding regions. Here, we monitored the vertical profiles of ozone concentration and aerosol extinction coefficients in the lower troposphere using an ozone lidar, in addition to the vertical column densities (VCDs) of ozone and its precursors in the troposphere through satellite-based remote sensing. The ozone concentrations reached a peak near the top of the boundary layer. During the control period, the aerosol extinction coefficients in the lower lidar layer decreased significantly; however, the ozone concentration fluctuated frequently with two pollution episodes and one clean episode. The sensitivity of ozone production was mostly within VOC-limited or transition regimes, but entered a NOx-limited regime due to a substantial decline of NOx during the clean episode. Temporary measures took no immediate effect on ozone pollution in the boundary layer; instead, meteorological conditions like air mass sources and solar radiation intensities dominated the variations in the ozone concentration.

To investigate the evolution of the nocturnal boundary layer (NBL) and its impacts on the vertical distributions of pollutant particulates, a combination of in situ observations from a large tethered balloon, remote sensing instruments (aerosol lidar and Doppler wind lidar) and an atmospheric environment-monitoring vehicle were utilized. The observation site was approximately 100 km southwest of Beijing, the capital of China. Results show that a considerable proportion of pollutant particulates were still suspended in the residual layer (RL) (e.g., the nitrate concentration reached 30 μg m⁻³) after sunset. The NBL height calculated by the aerosol lidar was closer to the top of the RL before midnight because of the pollutants stored aloft in the RL and the shallow surface inversion layer; after midnight, the NBL height was more consistent with the top of the surface inversion layer. As the convective mixing layer gradually became established after sunrise the following day, the pollutants stored in the nocturnal RL of the preceding night were entrained downward into the mixing layer. The early morning PM_2.5 concentration near 700 m in the RL on 20 December decreased by 83% compared with the concentration at 13:34 on 20 December at the same height. The nitrate concentration also decreased significantly in the RL, and the mixing down of nitrate from the RL could contribute about 37% to the nitrate in the mixing layer. Turbulence activities still existed in the RL with the bulk Richardson number (Rb) below the threshold value. The corresponding increase in PM_2.5 was likely to be correlated with the weak turbulence in the RL in the early morning.

Differential absorption lidar is an advanced tool for investigating tropospheric ozone transport and development. High-quality differential absorption lidar data are the basis for studying the temporal and spatial evolution of ozone pollution. We assessed the quality of the ozone data generated via differential absorption lidar. By correcting the ozone lidar profile in real-time with an atmospheric correction term and comparing the lidar data to ozone data collected using an unmanned aerial vehicle (UAV), we quantified the statistical error of the ozone lidar data in the vertical direction and determined that the data from the two instruments were generally in agreement. To verify the reliability of the ozone lidar system and the atmospheric correction algorithm, we conducted a long-term comparison experiment using data from the Canton Tower. Over the two months, the UAV and lidar data were consistent with one another, which confirmed the viability of the ozone lidar optomechanical structure and the atmospheric correction algorithm, both in real-time and over a given time duration. In addition, we also quantified the relationship between statistical error and signal-to-noise ratio. When the SNR is less than 10, the corresponding statistical error is about 40%. The statistical error was less than 15% when the signal-to-noise ratio was greater than 20, and the statistical error was mostly less than 8% when the signal-to-noise ratio was greater than 40. In general, the statistical error of the differential absorption lidar data was inversely proportional to the signal-to-noise ratio of each echo signal.

The range-resolved differential absorption lidar is a high-precision device to measure the concentration of carbon dioxide. This paper provides a system-wide theoretical analysis method for the performance analysis and parameter optimization of the lidar system using the given parameter range. The scattered echo signal, signal-to-noise ratio, and detection sensitivity were simulated by setting assumed parameters with the HITRAN 2020 database and the US 1976 standard atmosphere model to analyze the detection distance and concentration resolution of the lidar system. The effects of the laser energy, repetition frequency, and photodetector noise were also discussed. The wavelength selection near the absorption line is critical because it controls the height region of the highest sensitivity and the demands on frequency stability. Recommendations for the selection of absorption lines are provided in this paper. A quantitative analysis of each error source provided reasonable error ranges.

In order to investigate the variations of cloud and aerosol vertical profiles over the Tibetan Plateau (TP) in winter, we performed ground-based lidar observations in Lhasa, a city on the TP, from November 2021 to January 2022. The profiles of extinction coefficient, depolarization ratio, and signal-to-noise ratio (SNR) were retrieved using the atmospheric echo signals collected by the lidar. Clouds were identified by the range-correction echo signals and classified into water clouds, mixed clouds, horizontally oriented ice crystal clouds (HOICC), and ice clouds by the depolarization ratio and the hourly temperature from the European Centre for Medium-Range Weather Forecasts Reanalysis version 5 (ERA5). The clouds mainly appeared at a height of 3~5 km from 14:00–22:00 Beijing Time throughout the field campaign. The height and frequency (~30%) for cloud appearance were significantly lower than that reported in previous studies in summer. The cloud categories were dominated by mixed clouds and ice clouds during the observation period. The proportions of ice clouds gradually increased with increasing heights. After eliminating profiles influenced by clouds, the aerosol extinction coefficient and depolarization ratio were obtained, and the atmospheric boundary layer height (ABLH) was calculated. The aerosol extinction coefficient decreased with increasing height in the ABLH, and there were no obvious changes for the aerosol extinction coefficient above the ABL. The aerosol extinction coefficients near the Earth’s surface presented two peaks, appearing in the morning and evening, respectively. The high aerosols at the surface in the morning continually spread upward for 4–5 h and finally reached an altitude of 1 km with the development of ABLH. In addition, the depolarization ratio of aerosols decreased slowly with increasing altitudes. There was no obvious diurnal variation for depolarization ratios, indicating partly that the source of aerosols did not change significantly. These results are beneficial in understanding the evolution of cloud and aerosol vertical profiles over the TP.