As an important part of the ecological environment, degraded coastal soils urgently require efficient and eco-friendly soil amendment. Biochar and wood vinegar have been proved to be effective soil amendments, and acid-modified biochar has great potential in ameliorating the degraded coastal saline–alkali soil. However, the effects of individual or combined application of biochar (BC), acid-modified biochar (ABC), and wood vinegar (WV) on coastal saline–alkali soil are unknown. Hence, biochar, wood vinegar, and acid-modified biochar were prepared by pyrolysis of poplar wood. The properties of biochar were characterized, and soil incubation experiments were conducted. The results showed that ABC decreased the soil alkalinity by acid-base neutralization and improved the soil fertility by increasing the nutrients (C, N, P). ABC provided a more suitable environment and changed the abundance and diversity of soil microorganisms. ABC increased the relative contents of specific families (e.g., Pseudomonadaceae and Sphingomonadaceae), which had strong ecological linkages in the C, N, and P cycles and organic matter degradation. The results indicated that WV had little effect on coastal saline–alkali soil, whereas individual and combined application of biochar (especially ABC) showed an efficient remediation effect. Our preliminary study demonstrated that the ABC could be a suitable solution for ameliorating degraded coastal saline–alkali soils.

The continued increase in greenhouse gas emissions as a result of unprecedented eutrophication has resulted in a rising trend of red tides in the sea, which may be responsible for ecological degradation in the surrounding environment. Studies rarely investigate the accurate concentration of seawater eutrophication substances in offshore aquaculture areas, which may lead to the exacerbated pollution of inshore aquaculture. We examined whether offshore seawater quality monitoring can be effectively performed through unmanned aerial vehicles’ (UAVs) airborne hyperspectral remote sensing technique at Jiaozhou Bay, a water body associated with eutrophication. We used the UAV airborne hyperspectral imager to detect and measure typical marine aquaculture areas in Jiaozhou Bay and selected the key parameters of seawater quality, chlorophyll-a (Chl-a) concentrations, and total suspended matter (TSM) concentrations as indicators of seawater eutrophication. The hyperspectral inversion model of the Jiaozhou Bay seawater (JZBZ) was established with the optimal sensitive band of parameters. Results showed that in comparison with the traditional inversion model, the inversion R² of the Chl-a was 0.712, the RPD was 3.72, and the inversion R² of the TSM concentration was 0.756 while the RPD was 5.83. We found that this model is more suitable for the retrieval of water color parameters in Jiaozhou Bay. Additionally, by actual measurement, it can be seen that the concentration ranges of Chl-a in the observation area are 0.380–1.74 mg/m³, and the concentration range of TSM is 12.6–131 mg/L. The results of this study indicate that the Jiaozhou Bay Water Quality Translation Model (JZBM), based on the UAV airborne hyperspectral imager, performs well in the inversion of the concentration of chlorophyll and suspended particulate matter in offshore water, which advances our understanding with a new method to assess the degree of eutrophication in coastal waters.

A polarized micropulse lidar (P-MPL) employing a pulsed laser at 532 nm was developed by the Institute of Oceanographic Instrumentation, Qilu University of Technology (Shandong Academy of Sciences). The optomechanical structure, technical parameters, detection principle, overlap factor calculation method, and inversion methods of the atmospheric boundary layer (ABL) depth and depolarization ratio (DR) were introduced. Continuous observations using the P-MPL were carried out at Xi’an Meteorological Bureau, and the observation data were analyzed. In this study, we gleaned much information on aerosols and clouds, including the temporal and spatial variation of aerosols and clouds, aerosol extinction coefficient, DR, and the structure of ABL were obtained by the P-MPL. The variation of aerosols and clouds before and after a short rainfall was analyzed by combining time-height-indication (THI) of range corrected signal (RCS) and DR was obtained by the P-MPL with profiles of potential temperature (PT) and relative humidity (RH) detected by GTS1 Digital Radiosonde. Then, the characteristics of tropopause cirrus cloud were discussed using the data of DR, PT, and RH. Finally, a haze process from January 1st to January 5th was studied by using aerosol extinction coefficients obtained by the P-MPL, PT, and RH profiles measured by GTS1 Digital Radiosonde and the time-varying of PM_2.5 and PM₁₀ observed by ambient air quality monitor. The source of the haze was simulated by using the NOAA HYSPLIT Trajectory Model.

Laser-induced breakdown spectroscopy (LIBS) offers a tantalizing glimpse into real-time, on-the-spot aerosol analysis. Yet, the reliance on traditional lasers, with their limitations in energy and frequency, hampers optimal sample handling, dissociation, and excitation. To address those challenges, we propose a novel tactic: utilize a high repetition-rate (rep.-rate) laser with low pulse energy in combination with the two-dimensional correlation (2D-corr.) technique for sea-salt aerosols analyses. By examining the emission patterns from both the laser pulse train and individual pulses, we recognize distinctive analyte-specific rep.-rate responses, which allowed spectral reconstruction of analytes, avoiding background interferences. This discovery enabled the rep.-rate modulation for a 2D-corr. spectroscopy workflow. Consequently, we successfully differentiated between particle-related and air-species-related spectral components, obviating expensive spectrometers or intensified image detectors. For instance, the Na I at 589 nm stemming from aerosols exhibited an entirely different correlation contribution compared to O I at 777 nm, resulting in reconstructed clean aerosol-spectra without spectral peaks originated from air species. This 2D-corr. aerosol LIBS approach shows promising analytical potential streamlining aerosol particle analysis.

Lidar has been used for many years to study the optical properties of aerosols, but estimating the boundary values requires solving the lidar elastic scattering equation, which remains a challenge. The boundary values are often determined by fitting to uniform regions of the atmosphere. This method typically excludes low signal-to-noise ratio (SNR) signals because it classifies them as non-uniform, reducing the effective detection range of the lidar. On the other hand, directly fitting low SNR signals to estimate the boundary values can introduce significant errors. The method is based on maximizing the lidar detection distance and determines the boundary value using a new estimation algorithm with the averaging of multiple fitted results in the low SNR region to reduce the impact of noise. Simulations demonstrate that the new method reduces the relative error in the boundary value estimation by approximately 5% and improves the accuracy of the extinction coefficient profile inversion compared with the method of directly fitting all-sample signals. Field comparison experiments with forward-scattering sensors further verify that the algorithm improves the retrieval accuracy by 17.3% under extremely low signal-to-noise ratio (SNR) conditions, while performing comparably to the traditional method in high SNR homogeneous atmospheres. Additionally, based on the scanned lidar signals, the algorithm can provide detailed information on the spatial distribution of sea fog and offer valuable insights for an in-depth understanding of the physical evolution of sea fog.

With the wide application of lidar in the future, the problem of crosstalk between lidars will become more serious. True random coding photon counting lidar with high anti-crosstalk ability will play an important role in solving this problem. In this paper, based on the working principle of Gm-APD, the detection probability theoretical model of true random coding photon counting lidar is built, and the impact of jitter on detection probability is considered for the first time. The influence of mean echo photon number, mean pulse count density, sequence length and pulse width on detection probability is analyzed. Monte Carlo simulation and experimental results are highly consistent with the theoretical model, which proves the correctness of the detection probability theoretical model. This theoretical model provides an effective means to evaluate the system performance.